IDEAS home Printed from https://ideas.repec.org/f/c/pga362.html
   My authors  Follow this author

Jiti GAO

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Jiti Gao & Bin Peng & Yayi Yan, 2024. "Robust Inference for High Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 9/24, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Kaicheng Chen, 2025. "Inference in High-Dimensional Panel Models: Two-Way Dependence and Unobserved Heterogeneity," Papers 2504.18772, arXiv.org.

  2. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2024. "Robust Estimation and Inference for High-Dimensional Panel Data Models," Papers 2405.07420, arXiv.org, revised Feb 2025.

    Cited by:

    1. Haowen Bao & Yongmiao Hong & Yuying Sun & Shouyang Wang, 2024. "Sparse Interval-valued Time Series Modeling with Machine Learning," Papers 2411.09452, arXiv.org.

  3. Jiti Gao & Bin Peng & Yayi Yan, 2023. "Time-Varying Vector Error-Correction Models: Estimation and Inference," Papers 2305.17829, arXiv.org.

    Cited by:

    1. Panovska, Irina & Zhang, Licheng, 2024. "Jobless recoveries and time variation in labor markets," Journal of Macroeconomics, Elsevier, vol. 81(C).

  4. Heather M. Anderson & Jiti Gao & Guido Turnip & Farshid Vahid & Wei Wei, 2022. "Estimating the Effect of an EU-ETS Type Scheme in Australia Using a Synthetic Treatment Approach," Monash Econometrics and Business Statistics Working Papers 12/22, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Pan, Xian & Yu, Lihong, 2024. "Do China's pilot emissions trading schemes lead to domestic carbon leakage? Perspective from the firm relocation," Energy Economics, Elsevier, vol. 132(C).
    2. Jiaxin Zhong & Jianjun Zhang & Meichen Fu, 2024. "Does the Carbon Emissions Trading Pilot Policy Have a Demonstrated Impact on Advancing Low-Carbon Technology? Evidence from a Case Study in Beijing, China," Land, MDPI, vol. 13(8), pages 1-14, August.
    3. Tol, Richard S.J., 2023. "The fiscal implications of stringent climate policy," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 495-504.

  5. Jiti Gao & Bin Peng & Yayi Yan, 2022. "Higher-order Expansions and Inference for Panel Data Models," Papers 2205.00577, arXiv.org, revised Jun 2023.

    Cited by:

    1. Guohua Feng & Jiti Gao & Fei Liu & Bin Peng, 2024. "Estimation and Inference for Three-Dimensional Panel Data Models," Papers 2404.08365, arXiv.org, revised Sep 2024.
    2. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Cambridge Working Papers in Economics 2239, Faculty of Economics, University of Cambridge.

  6. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2429, Faculty of Economics, University of Cambridge.
    2. Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2467, Faculty of Economics, University of Cambridge.

  7. Difang Huang & Jiti Gao & Tatsushi Oka, 2022. "Semiparametric Single-Index Estimation for Average Treatment Effects," Papers 2206.08503, arXiv.org, revised Jan 2025.

    Cited by:

    1. Hui Liu & Jia Zhu & Huijie Cheng, 2024. "Enterprise digital transformation’s impact on stock liquidity: A corporate governance perspective," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-28, March.

  8. Xuan Liang & Jiti Gao & Xiaodong Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," Monash Econometrics and Business Statistics Working Papers 5/21, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Hong, Han & Ju, Gaosheng & Li, Qi & Yan, Karen X., 2024. "Varying-coefficient spatial dynamic panel data models with fixed effects: Theory and application," Journal of Econometrics, Elsevier, vol. 245(1).
    2. Wongsa-art, Pipat & Kim, Namhyun & Xia, Yingcun & Moscone, Francesco, 2024. "Varying coefficient panel data models and methods under correlated error components: Application to disparities in mental health services in England," Regional Science and Urban Economics, Elsevier, vol. 106(C).
    3. Yan-Yong Zhao & Ling-Ling Ge & Yuan Liu, 2025. "Estimation of panel data partially linear time-varying coefficient models with cross-sectional spatial autoregressive errors," Statistical Papers, Springer, vol. 66(1), pages 1-37, January.
    4. Bogui Li & Jianbao Chen & Hao Chen, 2024. "Estimation of fixed effects semiparametric single-index panel model with spatio-temporal correlated errors," Statistical Papers, Springer, vol. 65(8), pages 4915-4953, October.
    5. Shosei Sakaguchi & Hayato Tagawa, 2024. "Identification and Inference for Synthetic Control Methods with Spillover Effects: Estimating the Economic Cost of the Sudan Split," Papers 2408.00291, arXiv.org, revised Oct 2024.
    6. Lingling Tian & Yunan Su & Chuanhua Wei, 2024. "Tests for time-varying coefficient spatial autoregressive panel data model with fixed effects," Statistical Papers, Springer, vol. 65(9), pages 5481-5501, December.

  9. Bo Zhang & Jiti Gao & Guangming Pan, 2020. "Estimation and Testing for High-Dimensional Near Unit Root Time Series," Monash Econometrics and Business Statistics Working Papers 12/20, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.

  10. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Yayi Yan & Jiti Gao & Bin Peng, 2021. "Asymptotics for Time-Varying Vector MA(∞) Processes," Monash Econometrics and Business Statistics Working Papers 22/21, Monash University, Department of Econometrics and Business Statistics.

  11. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    2. Olatunji A. Shobande & Simplice A. Asongu, 2021. "Financial Development, Human Capital Development and Climate Change in East and Southern Africa," Research Africa Network Working Papers 21/042, Research Africa Network (RAN).

  12. Chaohua Dong & Jiti Gao & Oliver Linton & Bin peng, 2020. "On Time Trend of COVID-19: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 22/20, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.

  13. Jiti Gao & Bin peng & Russell Smyth, 2020. "On Income and Price Elasticities for Energy Demand: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 28/20, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Le, Ha Chi & Bhattacharya, Mita & Smyth, Russell & Zhang, Xibin, 2024. "Does economic growth cause energy intensity of well-being in the very long run? Semi-parametric evidence for selected OECD countries," Energy Economics, Elsevier, vol. 139(C).
    2. Furió, Dolores & Moreno-del-Castillo, Javier, 2024. "Dynamic demand response to electricity prices: Evidence from the Spanish retail market," Utilities Policy, Elsevier, vol. 88(C).
    3. Brantley Liddle, 2022. "What Is the Temporal Path of the GDP Elasticity of Energy Consumption in OECD Countries? An Assessment of Previous Findings and New Evidence," Energies, MDPI, vol. 15(10), pages 1-12, May.
    4. Dr. Christian Lutz & Dr. Marc Ingo Wolter, 2021. "Wege zur Klimaneutralität bis 2045 – Politische Handlungsfelder," GWS Discussion Paper Series 21-4, GWS - Institute of Economic Structures Research.
    5. Eshagh Mansourkiaee & Hussein Moghaddam, 2022. "Econometric Analysis of Residential Sector Gas Demand Elasticities in Gas Exporting Countries," Energy and Environment Research, Canadian Center of Science and Education, vol. 11(2), pages 1-1, December.
    6. Liddle, Brantley & Parker, Steven & Hasanov, Fakhri, 2023. "Why has the OECD long-run GDP elasticity of economy-wide electricity demand declined? Because the electrification of energy services has saturated," Energy Economics, Elsevier, vol. 125(C).
    7. Liddle, Brantley & Hasanov, Fakhri J. & Parker, Steven, 2022. "Your mileage may vary: Have road-fuel demand elasticities changed over time in middle-income countries?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 38-53.
    8. Liddle, Brantley, 2023. "Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying," Energy Economics, Elsevier, vol. 124(C).
    9. Anna Bohdan & Sabina Klosa & Urszula Romaniuk, 2023. "Fluctuations of Natural Gas Prices for Households in the 2017–2022 Period—Polish Case Study," Energies, MDPI, vol. 16(4), pages 1-19, February.
    10. Mohamad Husam Helmi & Abdurrahman Nazif Çatık & Çağla Bucak & Esra Ballı & Coşkun Akdeniz, 2024. "Time-Varying Income and Price Elasticities of Oil Demand in OECD Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 14(6), pages 303-311, November.
    11. Wang, Banban & Wei, Jie & Tan, Xiujie & Su, Bin, 2021. "The sectorally heterogeneous and time-varying price elasticities of energy demand in China," Energy Economics, Elsevier, vol. 102(C).
    12. Kettani, Maryème & Sanin, Maria Eugenia, 2024. "Energy consumption and energy poverty in Morocco," Energy Policy, Elsevier, vol. 185(C).
    13. Liddle, Brantley & Parker, Steven, 2022. "One more for the road: Reconsidering whether OECD gasoline income and price elasticities have changed over time," Energy Economics, Elsevier, vol. 114(C).
    14. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.

  14. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.

    Cited by:

    1. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.

  15. Cheng, T. & Gao, J. & Linton, O., 2019. "Nonparametric Predictive Regressions for Stock Return Prediction," Cambridge Working Papers in Economics 1932, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    2. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.

  16. Gong, Xiaodong & Gao, Jiti & Liang, Xuan, 2019. "Inter-City Spillover and Intra-City Agglomeration Effects among Local Labour Markets in China," IZA Discussion Papers 12329, Institute of Labor Economics (IZA).

    Cited by:

    1. Meng‐Ting Chen & Jiakai Zhang, 2024. "Political hierarchy spillovers: Evidence from China," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 329-348, January.
    2. Sobieralski, Joseph B., 2021. "Transportation infrastructure and employment: Are all investments created equal?," Research in Transportation Economics, Elsevier, vol. 88(C).

  17. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    2. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    3. Max Cytrynbaum, 2020. "Blocked Clusterwise Regression," Papers 2001.11130, arXiv.org.

  18. Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global Temperatures and Greenhouse Gases: A Common Features Approach," Monash Econometrics and Business Statistics Working Papers 23/19, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    2. Gadea Rivas, María Dolores & Gonzalo, Jesús & Ramos, Andrey, 2023. "Trends in temperature data: micro-foundations of their nature," UC3M Working papers. Economics 39045, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Chen, Liang & Dolado, Juan José & Gonzalo, Jesús & Ramos Ramirez, Andrey David, 2023. "Heterogeneous Predictive Association of CO2 with Global Warming," UC3M Working papers. Economics 36451, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    5. Anderson, Heather M. & Gao, Jiti & Turnip, Guido & Vahid, Farshid & Wei, Wei, 2023. "Estimating the effect of an EU-ETS type scheme in Australia using a synthetic treatment approach," Energy Economics, Elsevier, vol. 125(C).
    6. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.

  19. Bo Zhang & Jiti Gao & Guangming Pan, 2019. "A Near Unit Root Test for High-Dimensional Nonstationary Time Series," Monash Econometrics and Business Statistics Working Papers 10/19, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2019. "Spiked Eigenvalues of High-Dimensional Separable Sample Covariance Matrices," Monash Econometrics and Business Statistics Working Papers 31/19, Monash University, Department of Econometrics and Business Statistics.

  20. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2019. "Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone," Monash Econometrics and Business Statistics Working Papers 28/19, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Masako Ikegami & Zijian Wang, 2024. "Does energy technology R&D save energy in OECD countries?," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-22, April.
    2. Stefan Schiman-Vukan, 2019. "Langfristige Perspektiven der öffentlichen Finanzen in Österreich," WIFO Studies, WIFO, number 62243, October.
    3. Posso, Alberto & Zhang, Quanda, 2023. "Social R&D: Does academic freedom contribute to improved societal outcomes?," Information Economics and Policy, Elsevier, vol. 63(C).
    4. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    5. Le, Ha Chi & Bhattacharya, Mita & Smyth, Russell & Zhang, Xibin, 2024. "Does economic growth cause energy intensity of well-being in the very long run? Semi-parametric evidence for selected OECD countries," Energy Economics, Elsevier, vol. 139(C).
    6. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Quantile Random-Coefficient Regression with Interactive Fixed Effects: Heterogeneous Group-Level Policy Evaluation," Papers 2208.03632, arXiv.org, revised Nov 2024.
    7. Elisabet Rodriguez Llorian & Janelle Mann, 2022. "Exploring the technology–healthcare expenditure nexus: a panel error correction approach," Empirical Economics, Springer, vol. 62(6), pages 3061-3086, June.
    8. Liddle, Brantley & Hasanov, Fakhri J. & Parker, Steven, 2022. "Your mileage may vary: Have road-fuel demand elasticities changed over time in middle-income countries?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 38-53.
    9. Jiti Gao & Bin peng & Russell Smyth, 2020. "On Income and Price Elasticities for Energy Demand: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 28/20, Monash University, Department of Econometrics and Business Statistics.
    10. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Hailemariam, Abebe & Ivanovski, Kris & Dzhumashev, Ratbek, 2022. "Does R&D investment in renewable energy technologies reduce greenhouse gas emissions?," Applied Energy, Elsevier, vol. 327(C).
    12. Sefa Awaworyi Churchill & Bin Peng & Russell Smyth & Quanda Zhang, 2022. "R&D intensity and income inequality in the G7: 1870–2016," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 263-282, July.
    13. Liddle, Brantley & Parker, Steven, 2022. "One more for the road: Reconsidering whether OECD gasoline income and price elasticities have changed over time," Energy Economics, Elsevier, vol. 114(C).

  21. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Papers 1903.07948, arXiv.org.

    Cited by:

    1. Guohua Feng & Jiti Gao & Fei Liu & Bin Peng, 2024. "Estimation and Inference for Three-Dimensional Panel Data Models," Papers 2404.08365, arXiv.org, revised Sep 2024.
    2. Beyer,Robert Carl Michael & Wacker,Konstantin M., 2022. "Good Enough for Outstanding Growth : The Experience of Bangladesh in Comparative Perspective," Policy Research Working Paper Series 10150, The World Bank.
    3. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    4. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2025. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Working Papers 202526, University of Macau, Faculty of Business Administration.
    5. African Department International Monetary Fund & Western Africa Region World Bank, 2024. "Enhancing Sustainable and Inclusive Growth in the Central African Economic and Monetary Community," World Bank Publications - Reports 38438, The World Bank Group.
    6. Julia Varlamova & Ekaterina Kadochnikova, 2023. "Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models," Mathematics, MDPI, vol. 11(16), pages 1-31, August.
    7. Alexandra Horobet & Lucian Belascu & Magdalena Radulescu & Daniel Balsalobre-Lorente & Cosmin-Alin Botoroga & Cristina-Carmencita Negreanu, 2024. "Exploring the Nexus between Greenhouse Emissions, Environmental Degradation and Green Energy in Europe: A Critique of the Environmental Kuznets Curve," Energies, MDPI, vol. 17(20), pages 1-29, October.

  22. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    2. Gregory Connor & Robert A Korajczyk, 2024. "Semi-Strong Factors in Asset Returns," Journal of Financial Econometrics, Oxford University Press, vol. 22(1), pages 70-93.
    3. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2019. "Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone," Monash Econometrics and Business Statistics Working Papers 28/19, Monash University, Department of Econometrics and Business Statistics.

  23. Dong, C. & Gao, J. & Linton, O., 2018. "High Dimensional Semiparametric Moment Restriction Models," Cambridge Working Papers in Economics 1881, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    2. Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "Chaohua Dong, Jiti Gao and Oliver Linton’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 707-708, July.
    3. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    4. Pu, Dan & Fang, Kuangnan & Lan, Wei & Yu, Jihai & Zhang, Qingzhao, 2024. "Multivariate spatiotemporal models with low rank coefficient matrix," Journal of Econometrics, Elsevier, vol. 246(1).
    5. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    6. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    7. Liyuan Cui & Guanhao Feng & Yongmiao Hong, 2024. "Regularized Gmm For Time‐Varying Models With Applications To Asset Pricing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(2), pages 851-883, May.

  24. Tingting Cheng & Jiti Gao & Oliver Linton, 2018. "Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction," CeMMAP working papers CWP03/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Forecasting benchmarks of long-term stock returns via machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 221-240, February.

  25. Tingting Cheng & Jiti Gao & Yayi Yan, 2018. "Regime switching panel data models with interative fixed effects," Monash Econometrics and Business Statistics Working Papers 21/18, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Gobillon, Laurent & Magnac, Thierry & Roux, Sébastien, 2022. "Lifecycle Wages and Human Capital Investments: Selection and Missing Data," CEPR Discussion Papers 16999, C.E.P.R. Discussion Papers.
    2. Liu, Hao, 2019. "The communication and European Regional economic growth: The interactive fixed effects approach," Economic Modelling, Elsevier, vol. 83(C), pages 299-311.
    3. Cheng, Tingting & Xing, Shuo & Yao, Wenying, 2022. "An examination of herding behaviour of the Chinese mutual funds: A time-varying perspective," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    4. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.

  26. Jiti Gao & Oliver Linton & Bin Peng, 2018. "Inference on a semiparametric model with global power law and local nonparametric trends," CeMMAP working papers CWP05/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Chaohua Dong & Jiti Gao & Oliver Linton & Bin peng, 2020. "On Time Trend of COVID-19: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 22/20, Monash University, Department of Econometrics and Business Statistics.
    2. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    3. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.

  27. Shujie Ma & Oliver Linton & Jiti Gao, 2018. "Estimation in semiparametric quantile factor models," CeMMAP working papers CWP07/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Katal, Ali & Mortezazadeh, Mohammad & Wang, Liangzhu (Leon), 2019. "Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations," Applied Energy, Elsevier, vol. 250(C), pages 1402-1417.
    2. Canfield, Martha & Norton, Sam & Downs, Johnny & PMM Wijlaars, Linda & Gilchrist, Gail, 2023. "Risk factors for involvement in care proceedings for mothers receiving treatment for substance use: A cohort study using linked and administrative data in South London," Children and Youth Services Review, Elsevier, vol. 155(C).

  28. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Isabel Casas & Jiti Gao & Shangyu Xie, 2018. "Modelling Time-Varying Income Elasticities of Health Care Expenditure for the OECD," CREATES Research Papers 2018-29, Department of Economics and Business Economics, Aarhus University.
    2. Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2019. "Spiked Eigenvalues of High-Dimensional Separable Sample Covariance Matrices," Monash Econometrics and Business Statistics Working Papers 31/19, Monash University, Department of Econometrics and Business Statistics.

  29. Degui Li & Peter C.B. Phillips & Jiti Gao, 2017. "Kernel-Based Inference In Time-Varying Coefficient Cointegrating Regression," Cowles Foundation Discussion Papers 2109, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Ying Wang & Peter C. B. Phillips, 2024. "Limit Theory of Local Polynomial Estimation in Functional Coefficient Regression," Cowles Foundation Discussion Papers 2398, Cowles Foundation for Research in Economics, Yale University.
    2. Haiqi Li Author-Name-First: Haiqi & Jing Zhang & Chaowen Zheng, 2023. "Estimating and Testing for Functional Coefficient Quantile Cointegrating Regression," Economics Discussion Papers em-dp2023-07, Department of Economics, University of Reading.
    3. Polbin, Andrey & Skrobotov, Anton, 2022. "On decrease in oil price elasticity of GDP and investment in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 5-24.
    4. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    5. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.

  30. Shujie Ma & Oliver Linton & Jiti Gao, 2017. "Estimation and inference in semiparametric quantile factor models," Monash Econometrics and Business Statistics Working Papers 8/17, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Paper 2023/9, Norges Bank.
    2. Chen, Liang & Dolado, Juan J & Gonzalo, Jesus & Pan, Haozi, 2023. "Estimation of Characteristics-based Quantile Factor Models," CEPR Discussion Papers 18115, C.E.P.R. Discussion Papers.
    3. Yang, Shuquan & Ling, Nengxiang, 2023. "Robust projected principal component analysis for large-dimensional semiparametric factor modeling," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    4. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    5. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    6. Dong, Ruipeng & Li, Daoji & Zheng, Zemin, 2021. "Parallel integrative learning for large-scale multi-response regression with incomplete outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    7. Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," The Warwick Economics Research Paper Series (TWERPS) 1230, University of Warwick, Department of Economics.
    8. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Quantile Random-Coefficient Regression with Interactive Fixed Effects: Heterogeneous Group-Level Policy Evaluation," Papers 2208.03632, arXiv.org, revised Nov 2024.
    9. Wei, Jie & Chen, Hui, 2020. "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, vol. 191(C).
    10. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org, revised Nov 2024.
    11. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    12. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    13. Zhu, Zhoufan & Zhang, Ningning & Zhu, Ke, 2024. "Big portfolio selection by graph-based conditional moments method," Journal of Empirical Finance, Elsevier, vol. 78(C).
    14. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    15. Jozef Barunik & Matej Nevrla, 2022. "Common Idiosyncratic Quantile Risk," Papers 2208.14267, arXiv.org, revised Nov 2024.

  31. Nithi Sopitpongstorn & Param Silvapulle & Jiti Gao, 2017. "Local logit regression for recovery rate," Monash Econometrics and Business Statistics Working Papers 19/17, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Sopitpongstorn, Nithi & Silvapulle, Param & Gao, Jiti & Fenech, Jean-Pierre, 2021. "Local logit regression for loan recovery rate," Journal of Banking & Finance, Elsevier, vol. 126(C).
    2. Michal Pavlicko & Jaroslav Mazanec, 2022. "Minimalistic Logit Model as an Effective Tool for Predicting the Risk of Financial Distress in the Visegrad Group," Mathematics, MDPI, vol. 10(8), pages 1-22, April.

  32. Bing Jiang & Yanrong Yang & Jiti Gao & Cheng Hsiao, 2017. "Recursive estimation in large panel data models: Theory and practice," Monash Econometrics and Business Statistics Working Papers 5/17, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Chen, Qiang & Yan, Guanpeng, 2023. "On the two algorithms for estimating interactive fixed effects models in Bai (2009)," Economics Letters, Elsevier, vol. 233(C).
    2. Guowei Cui & Milda Norkuté & Vasilis Sarafidis & Takashi Yamagata, 2020. "Two-Stage Instrumental Variable Estimation of Linear Panel Data Models with Interactive Effects," ISER Discussion Paper 1101, Institute of Social and Economic Research, The University of Osaka.
    3. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    4. Gobillon, Laurent & Magnac, Thierry & Roux, Sébastien, 2022. "Lifecycle Wages and Human Capital Investments: Selection and Missing Data," CEPR Discussion Papers 16999, C.E.P.R. Discussion Papers.
    5. Cheng Hsiao & Qiankun Zhou, 2024. "Panel treatment effects measurement: Factor or linear projection modelling?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1332-1358, November.
    6. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    7. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Quantile Random-Coefficient Regression with Interactive Fixed Effects: Heterogeneous Group-Level Policy Evaluation," Papers 2208.03632, arXiv.org, revised Nov 2024.
    8. Sakiru Adebola Solarin & Mufutau Opeyemi Bello, 2024. "Modelling labour productivity and the role of research intensity in 129 years: evidence from a new dynamic instrumental variable estimation approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(3), pages 2619-2646, June.
    9. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    10. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    11. Jiti Gao & Bin Peng & Yayi Yan, 2022. "Nonparametric Estimation and Testing for Time-Varying VAR Models," Monash Econometrics and Business Statistics Working Papers 3/22, Monash University, Department of Econometrics and Business Statistics.
    12. Yu, Haijing & Shen, Shaowei & Han, Lei & Ouyang, Jian, 2024. "Spatiotemporal heterogeneities in the impact of the digital economy on carbon emission transfers in China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    13. Guohua Feng & Jiti Gao & Bin Peng, 2021. "Productivity Convergence in Manufacturing: A Hierarchical Panel Data Approach," Monash Econometrics and Business Statistics Working Papers 16/21, Monash University, Department of Econometrics and Business Statistics.
    14. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    15. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    16. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Monash Econometrics and Business Statistics Working Papers 6/19, Monash University, Department of Econometrics and Business Statistics.
    17. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    18. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    19. Stauskas, Ovidijus & De Vos, Ignace, 2024. "Handling Distinct Correlated Effects with CCE," MPRA Paper 120194, University Library of Munich, Germany.
    20. Guohua Feng & Jiti Gao & Bin Peng, 2022. "Multi-Level Panel Data Models: Estimation and Empirical Analysis," Monash Econometrics and Business Statistics Working Papers 4/22, Monash University, Department of Econometrics and Business Statistics.
    21. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.

  33. Degui Li & Peter CB Phillips & Jiti Gao, 2017. "Kernel-based inference in time-varying coefficient models with multiple integrated regressors," Monash Econometrics and Business Statistics Working Papers 11/17, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Yicong Lin & Hanno Reuvers, 2019. "Efficient Estimation by Fully Modified GLS with an Application to the Environmental Kuznets Curve," Papers 1908.02552, arXiv.org, revised Aug 2020.

  34. Tingting Cheng & Jiti Gao & Peter CB Phillips, 2017. "Bayesian estimation based on summary statistics: Double asymptotics and practice," Monash Econometrics and Business Statistics Working Papers 4/17, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. M Hashem Pesaran & Ron P Smith, 2017. "Posterior Means and Precisions of the Coefficients in Linear Models with Highly Collinear Regressors," BCAM Working Papers 1707, Birkbeck Centre for Applied Macroeconomics.
    2. Pesaran, M. Hashem & Smith, Ron P., 2019. "A Bayesian analysis of linear regression models with highly collinear regressors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 1-21.
    3. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Specification tests based on MCMC output," Journal of Econometrics, Elsevier, vol. 207(1), pages 237-260.

  35. Chaohua Dong & Jiti Gao & Bin Peng, 2016. "Another Look at Single-Index Models Based on Series Estimation," Monash Econometrics and Business Statistics Working Papers 19/16, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.

  36. Guohua Feng & Jiti Gao & Xiaohui Zhang, 2016. "Estimation of Technical Change and Price Elasticities: A Categorical Time-varying Coefficient Approach," Monash Econometrics and Business Statistics Working Papers 2/16, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Guanxiufeng Lan & Sumin Li, 2024. "Measurement and analysis of the distortion of factor prices in China," PLOS ONE, Public Library of Science, vol. 19(7), pages 1-24, July.

  37. Fengping Tian & Jiti Gao & Ke Yang, 2016. "A Quantile Regression Approach to Panel Data Analysis of Health Care Expenditure in OECD Countries," Monash Econometrics and Business Statistics Working Papers 20/16, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Linhong Chen & Yue Zhuo & Zhiming Xu & Xiaocang Xu & Xin Gao, 2019. "Is Carbon Dioxide (CO 2 ) Emission an Important Factor Affecting Healthcare Expenditure? Evidence from China, 2005–2016," IJERPH, MDPI, vol. 16(20), pages 1-14, October.
    2. Xiaocang Xu & Zhiming Xu & Linhong Chen & Chang Li, 2019. "How Does Industrial Waste Gas Emission Affect Health Care Expenditure in Different Regions of China: An Application of Bayesian Quantile Regression," IJERPH, MDPI, vol. 16(15), pages 1-12, August.
    3. Anne Mason & Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Martin Chalkley & Raphael Wittenberg & Jose-Luis Fernandez, 2019. "Drivers of health care expenditure: Final report," Working Papers 169cherp, Centre for Health Economics, University of York.
    4. Mujaheed Shaikh & Afschin Gandjour, 2019. "Pharmaceutical expenditure and gross domestic product: Evidence of simultaneous effects using a two‐step instrumental variables strategy," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 101-122, January.

  38. Michael Creel & Jiti Gao & Han Hong & Dennis Kristensen, 2016. "Bayesian Indirect Inference and the ABC of GMM," Monash Econometrics and Business Statistics Working Papers 1/16, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
    2. Valerio Scalone, 2018. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working papers 688, Banque de France.

  39. Tingting Cheng & Jiti Gao & Xibin Zhang, 2015. "Bayesian Bandwidth Estimation In Nonparametric Time-Varying Coefficient Models," Monash Econometrics and Business Statistics Working Papers 3/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Lafourcade, Pierre & Gerali, Andrea & Brůha, Jan & Bursian, Dirk & Buss, Ginters & Corbo, Vesna & Haavio, Markus & Håkanson, Christina & Hlédik, Tibor & Kátay, Gábor & Kulikov, Dmitry & Lozej, Matija , 2016. "Labour market modelling in the light of the financial crisis," Occasional Paper Series 175, European Central Bank.
    2. Jan Bruha & Jiri Polansky, 2015. "Empirical Analysis of Labor Markets over Business Cycles: An International Comparison," Working Papers 2015/15, Czech National Bank, Research and Statistics Department.

  40. Biqing Cai & Chaohua Dong & Jiti Gao, 2015. "Orthogonal Series Estimation in Nonlinear Cointegrating Models with Endogeneity," Monash Econometrics and Business Statistics Working Papers 18/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.

  41. Guangming Pan & Jiti Gao & Yanrong Yang & Meihui Guo, 2015. "Cross-sectional Independence Test for a Class of Parametric Panel Data Models," Monash Econometrics and Business Statistics Working Papers 17/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Dogan, Eyup & Altinoz, Buket & Madaleno, Mara & Taskin, Dilvin, 2020. "The impact of renewable energy consumption to economic growth: A replication and extension of Inglesi-Lotz (2016)," Energy Economics, Elsevier, vol. 90(C).

  42. Guohua Feng & Jiti Gao & Bin Peng & Xiaohui Zhang, 2015. "A Varying-Coefficient Panel Data Model with Fixed Effects: Theory and an Application to U.S. Commercial Banks," Monash Econometrics and Business Statistics Working Papers 9/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Estimation of Varying Coefficient Models with Measurement Error," STICERD - Econometrics Paper Series 607, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. Phillips, Peter C.B. & Wang, Ying, 2022. "Functional coefficient panel modeling with communal smoothing covariates," Journal of Econometrics, Elsevier, vol. 227(2), pages 371-407.
    3. Chen, Qian & Zha, Donglan & Wang, Lijun & Yang, Guanglei, 2022. "The direct CO2 rebound effect in households: Evidence from China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    4. Price, Sarah & Zhang, Xiaohui & Spencer, Anne, 2020. "Measuring the impact of national guidelines: What methods can be used to uncover time-varying effects for healthcare evaluations?," Social Science & Medicine, Elsevier, vol. 258(C).
    5. Cheng, Ming-Yen & Wang, Shouxia & Xia, Lucy & Zhang, Xibin, 2024. "Testing specification of distribution in stochastic frontier analysis," Journal of Econometrics, Elsevier, vol. 239(2).
    6. Dong, Jichang & Yin, Lijun & Liu, Xiaoting & Hu, Meiting & Li, Xiuting & Liu, Lei, 2020. "Impact of internet finance on the performance of commercial banks in China," International Review of Financial Analysis, Elsevier, vol. 72(C).
    7. Emawtee Bissoondoyal‐Bheenick & Robert Brooks & Hung Xuan Do, 2023. "Risk Analysis of Pension Fund Investment Choices," Abacus, Accounting Foundation, University of Sydney, vol. 59(3), pages 872-898, September.
    8. Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro, 2021. "Visualization, Identification, and stimation in the Linear Panel Event-Study Design," Working Papers 21-44, Federal Reserve Bank of Philadelphia.
    9. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    10. Feng, Guohua & McLaren, Keith R. & Yang, Ou & Zhang, Xiaohui & Zhao, Xueyan, 2021. "The impact of environmental policy stringency on industrial productivity growth: A semi-parametric study of OECD countries," Energy Economics, Elsevier, vol. 100(C).
    11. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    12. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Yan-Yong Zhao & Ling-Ling Ge & Yuan Liu, 2025. "Estimation of panel data partially linear time-varying coefficient models with cross-sectional spatial autoregressive errors," Statistical Papers, Springer, vol. 66(1), pages 1-37, January.
    14. Heather Anderson & Jiti Gao & Farshid Vahid & Wei Wei & Yang Yang, 2023. "Does Climate Sensitivity Differ Across Regions?," Monash Econometrics and Business Statistics Working Papers 7/23, Monash University, Department of Econometrics and Business Statistics.
    15. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    16. Arteaga-Molina, Luis A. & Rodríguez-Poo, Juan M., 2019. "Empirical likelihood based inference for a categorical varying-coefficient panel data model with fixed effects," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 110-124.
    17. Hua Liu & Youquan Pei & Qunfang Xu, 2020. "Estimation for varying coefficient panel data model with cross-sectional dependence," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(3), pages 377-410, April.
    18. Lixiong Yang & Chingnun Lee & I‐Po Chen, 2021. "Threshold model with a time‐varying threshold based on Fourier approximation," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 406-430, July.
    19. Hao, Xiaoli & Deng, Feng, 2019. "The marginal and double threshold effects of regional innovation on energy consumption structure: Evidence from resource-based regions in China," Energy Policy, Elsevier, vol. 131(C), pages 144-154.
    20. Ji Wu & Shirong Zhao, 2024. "Returns to scale in cost, revenue, and profit for European banks: New results from nonparametric local linear methods," The Financial Review, Eastern Finance Association, vol. 59(2), pages 487-517, May.

  43. Jiti Gao & Bin Peng & Zhao Ren & Xiaohui Zhang, 2015. "Variable Selection for a Categorical Varying-Coefficient Model with Identifications for Determinants of Body Mass Index," Monash Econometrics and Business Statistics Working Papers 21/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Fatemeh Tajik & Mingzheng Wang & Xiaohui Zhang & Jie Han, 2020. "Evaluation of the impact of body mass index on venous thromboembolism risk factors," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-17, July.

  44. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    2. Pei, Youquan & Huang, Tao & You, Jinhong, 2018. "Nonparametric fixed effects model for panel data with locally stationary regressors," Journal of Econometrics, Elsevier, vol. 202(2), pages 286-305.
    3. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.

  45. Biqing Cai & Jiti Gao & Dag Tjostheim, 2015. "A New Class of Bivariate Threshold Cointegration Models," Monash Econometrics and Business Statistics Working Papers 1/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Bravo, Francesco & Li, Degui & Tjøstheim, Dag, 2021. "Robust nonlinear regression estimation in null recurrent time series," Journal of Econometrics, Elsevier, vol. 224(2), pages 416-438.
    2. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, vol. 3(2), pages 1-24, April.
    3. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    4. She, Rui & Ling, Shiqing, 2020. "Inference in heavy-tailed vector error correction models," Journal of Econometrics, Elsevier, vol. 214(2), pages 433-450.
    5. James A. Duffy & Sophocles Mavroeidis & Sam Wycherley, 2022. "Cointegration with Occasionally Binding Constraints," Papers 2211.09604, arXiv.org, revised Feb 2025.

  46. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection in Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 14/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Sreevani, & Murthy, C.A., 2016. "On bandwidth selection using minimal spanning tree for kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 102(C), pages 67-84.
    2. Tingting Cheng & Jiti Gao & Oliver Linton, 2017. "Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction," Monash Econometrics and Business Statistics Working Papers 13/17, Monash University, Department of Econometrics and Business Statistics.

  47. Jiti Gao & Xiao Han & Guangming Pan & Yanrong Yang, 2014. "High Dimensional Correlation Matrices: CLT and Its Applications," Monash Econometrics and Business Statistics Working Papers 26/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Guangming Pan & Jiti Gao & Yanrong Yang & Meihui Guo, 2015. "Cross-sectional Independence Test for a Class of Parametric Panel Data Models," Monash Econometrics and Business Statistics Working Papers 17/15, Monash University, Department of Econometrics and Business Statistics.

  48. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.

    Cited by:

    1. Phillips, Peter C.B. & Wang, Ying, 2022. "Functional coefficient panel modeling with communal smoothing covariates," Journal of Econometrics, Elsevier, vol. 227(2), pages 371-407.
    2. Russell Davidson & Victoria Zinde‐Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
    3. Jun Wang & Dianpeng Wang & Yubin Tian, 2022. "Multidimensional specification test based on non-stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 348-372, June.
    4. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.
    5. Tu, Yundong & Liang, Han-Ying & Wang, Qiying, 2022. "Nonparametric inference for quantile cointegrations with stationary covariates," Journal of Econometrics, Elsevier, vol. 230(2), pages 453-482.

  49. Chaohua Dong & Jiti Gao, 2014. "Specification Testing in Structural Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 2/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Biqing Cai & Chaohua Dong & Jiti Gao, 2015. "Orthogonal Series Estimation in Nonlinear Cointegrating Models with Endogeneity," Monash Econometrics and Business Statistics Working Papers 18/15, Monash University, Department of Econometrics and Business Statistics.
    2. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.
    3. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    4. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.

  50. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2014. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 8/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2023. "Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models," Monash Econometrics and Business Statistics Working Papers 2/23, Monash University, Department of Econometrics and Business Statistics.
    2. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    3. Jun Wang & Dianpeng Wang & Yubin Tian, 2022. "Multidimensional specification test based on non-stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 348-372, June.
    4. Peng, Zhen & Dong, Chaohua, 2022. "Augmented cointegrating linear models with possibly strongly correlated stationary and nonstationary regressors," Finance Research Letters, Elsevier, vol. 47(PB).
    5. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.
    6. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Papers 2111.02023, arXiv.org.
    7. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, vol. 3(2), pages 1-24, April.
    8. Tu, Yundong & Liang, Han-Ying & Wang, Qiying, 2022. "Nonparametric inference for quantile cointegrations with stationary covariates," Journal of Econometrics, Elsevier, vol. 230(2), pages 453-482.
    9. James A. Duffy & Sophocles Mavroeidis & Sam Wycherley, 2022. "Cointegration with Occasionally Binding Constraints," Papers 2211.09604, arXiv.org, revised Feb 2025.
    10. Shan Dai & Ngai Hang Chan, 2023. "Testing of Constant Parameters for Semi‐Parametric Functional Coefficient Models with Integrated Covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 474-486, September.
    11. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.

  51. Jiti Gao & Han Hong, 2014. "A Computational Implementation of GMM," Monash Econometrics and Business Statistics Working Papers 24/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
    2. Cheng, Tingting & Gao, Jiti & Phillips, Peter C.B., 2018. "A frequentist approach to Bayesian asymptotics," Journal of Econometrics, Elsevier, vol. 206(2), pages 359-378.
    3. Michael Creel & Jiti Gao & Han Hong & Dennis Kristensen, 2016. "Bayesian Indirect Inference and the ABC of GMM," Monash Econometrics and Business Statistics Working Papers 1/16, Monash University, Department of Econometrics and Business Statistics.
    4. Tingting Cheng & Jiti Gao & Peter CB Phillips, 2016. "A Frequency Approach to Bayesian Asymptotics," Monash Econometrics and Business Statistics Working Papers 5/16, Monash University, Department of Econometrics and Business Statistics.
    5. Tingting Cheng & Jiti Gao & Peter CB Phillips, 2017. "Bayesian estimation based on summary statistics: Double asymptotics and practice," Monash Econometrics and Business Statistics Working Papers 4/17, Monash University, Department of Econometrics and Business Statistics.

  52. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 27/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Sreevani, & Murthy, C.A., 2016. "On bandwidth selection using minimal spanning tree for kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 102(C), pages 67-84.
    2. Tingting Cheng & Jiti Gao & Oliver Linton, 2017. "Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction," Monash Econometrics and Business Statistics Working Papers 13/17, Monash University, Department of Econometrics and Business Statistics.

  53. Bin Peng & Chaohua Dong & Jiti Gao, 2014. "Semiparametric Single-Index Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 9/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2023. "Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models," Monash Econometrics and Business Statistics Working Papers 2/23, Monash University, Department of Econometrics and Business Statistics.
    3. Shujie Ma & Oliver Linton & Jiti Gao, 2017. "Estimation and inference in semiparametric quantile factor models," Monash Econometrics and Business Statistics Working Papers 8/17, Monash University, Department of Econometrics and Business Statistics.
    4. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    5. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    6. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    7. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    8. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    9. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    10. Bing Jiang & Yanrong Yang & Jiti Gao & Cheng Hsiao, 2017. "Recursive estimation in large panel data models: Theory and practice," Monash Econometrics and Business Statistics Working Papers 5/17, Monash University, Department of Econometrics and Business Statistics.
    11. Pei, Youquan & Huang, Tao & You, Jinhong, 2018. "Nonparametric fixed effects model for panel data with locally stationary regressors," Journal of Econometrics, Elsevier, vol. 202(2), pages 286-305.
    12. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    13. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    14. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    15. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    16. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.
    17. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    18. Lin, Yingqian & Tu, Yundong, 2020. "Sieve extremum estimation of a semiparametric transformation model," Economics Letters, Elsevier, vol. 189(C).
    19. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    20. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    21. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    22. Lin, Yingqian & Tu, Yundong, 2024. "Functional coefficient cointegration models with Box–Cox transformation," Economics Letters, Elsevier, vol. 234(C).
    23. Ma, Yingying & Guo, Shaojun & Wang, Hansheng, 2023. "Sparse spatio-temporal autoregressions by profiling and bagging," Journal of Econometrics, Elsevier, vol. 232(1), pages 132-147.
    24. Shan Dai & Ngai Hang Chan, 2023. "Testing of Constant Parameters for Semi‐Parametric Functional Coefficient Models with Integrated Covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 474-486, September.

  54. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.

  55. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression with Non- and Semi-Parametric Cointegration," Monash Econometrics and Business Statistics Working Papers 16/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Guohua Feng & Jiti Gao & Xiaohui Zhang, 2016. "Estimation of Technical Change and Price Elasticities: A Categorical Time-varying Coefficient Approach," Monash Econometrics and Business Statistics Working Papers 2/16, Monash University, Department of Econometrics and Business Statistics.
    2. Li, Haiqi & Zhang, Jing & Zheng, Chaowen, 2025. "Functional-coefficient quantile cointegrating regression with stationary covariates," Statistics & Probability Letters, Elsevier, vol. 219(C).
    3. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    4. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    5. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, vol. 3(2), pages 1-24, April.
    6. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    7. Chaohua Dong & Jiti Gao, 2014. "Specification Testing in Structural Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 2/14, Monash University, Department of Econometrics and Business Statistics.
    8. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  56. Degui Li & Peter C.B. Phillips & Jiti Gao, 2013. "Uniform Consistency of Nonstationary Kernel-Weighted Sample Covariances for Nonparametric Regression," Cowles Foundation Discussion Papers 1929, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    3. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2023. "Estimation of the variance function in structural break autoregressive models with non‐stationary and explosive segments," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 181-205, March.
    4. Degui Li & Peter C.B. Phillips & Jiti Gao, 2017. "Kernel-Based Inference In Time-Varying Coefficient Cointegrating Regression," Cowles Foundation Discussion Papers 2109, Cowles Foundation for Research in Economics, Yale University.
    5. Bu, Ruijun & Kim, Jihyun & Wang, Bin, 2023. "Uniform and Lp convergences for nonparametric continuous time regressions with semiparametric applications," Journal of Econometrics, Elsevier, vol. 235(2), pages 1934-1954.
    6. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    7. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.
    8. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
    9. Yayi Yan & Jiti Gao & Bin Peng, 2021. "Asymptotics for Time-Varying Vector MA(∞) Processes," Monash Econometrics and Business Statistics Working Papers 22/21, Monash University, Department of Econometrics and Business Statistics.

  57. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression," Cowles Foundation Discussion Papers 1911, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Cizek, Pavel & Koo, Chao, 2017. "Jump-Preserving Varying-Coefficient Models for Nonlinear Time Series," Other publications TiSEM c849e96f-3ad1-461e-96c6-f, Tilburg University, School of Economics and Management.
    2. Guohua Feng & Jiti Gao & Xiaohui Zhang, 2016. "Estimation of Technical Change and Price Elasticities: A Categorical Time-varying Coefficient Approach," Monash Econometrics and Business Statistics Working Papers 2/16, Monash University, Department of Econometrics and Business Statistics.
    3. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    4. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    5. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    6. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, vol. 3(2), pages 1-24, April.
    7. Chaohua Dong & Jiti Gao, 2014. "Specification Testing in Structural Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 2/14, Monash University, Department of Econometrics and Business Statistics.
    8. Jiti Gao & Bin Peng & Zhao Ren & Xiaohui Zhang, 2015. "Variable Selection for a Categorical Varying-Coefficient Model with Identifications for Determinants of Body Mass Index," Monash Econometrics and Business Statistics Working Papers 21/15, Monash University, Department of Econometrics and Business Statistics.
    9. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  58. Peter C.B. Phillips & Degui Li & Jiti Gao, 2013. "Estimating Smooth Structural Change in Cointegration Models," Cowles Foundation Discussion Papers 1910, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Arčabić, Vladimir & Gelo, Tomislav & Sonora, Robert J. & Šimurina, Jurica, 2021. "Cointegration of electricity consumption and GDP in the presence of smooth structural changes," Energy Economics, Elsevier, vol. 97(C).
    3. Kapetanios, George & Millard, Stephen & Petrova, Katerina & Price, Simon, 2019. "Time-varying cointegration and the UK great ratios," Bank of England working papers 789, Bank of England.
    4. Isabel Casas & Eva Ferreira & Susan Orbe, 2017. "Time-varying coefficient estimation in SURE models. Application to portfolio management," CREATES Research Papers 2017-33, Department of Economics and Business Economics, Aarhus University.
    5. Isabel Casas & Jiti Gao & Shangyu Xie, 2018. "Modelling Time-Varying Income Elasticities of Health Care Expenditure for the OECD," CREATES Research Papers 2018-29, Department of Economics and Business Economics, Aarhus University.
    6. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    7. Gao, Jiti & Peng, Bin & Wu, Wei Biao & Yan, Yayi, 2024. "Time-varying multivariate causal processes," Journal of Econometrics, Elsevier, vol. 240(1).
    8. Haiqi Li Author-Name-First: Haiqi & Jing Zhang & Chaowen Zheng, 2023. "Estimating and Testing for Functional Coefficient Quantile Cointegrating Regression," Economics Discussion Papers em-dp2023-07, Department of Economics, University of Reading.
    9. Peter C. B. Phillips, 2022. "Asymptotics of Polynomial Time Trend Estimation and Hypothesis Testing under Rank Deficiency," Cowles Foundation Discussion Papers 2332, Cowles Foundation for Research in Economics, Yale University.
    10. Liu, Yanbo & Phillips, Peter C. B. & Yu, Jun, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Economics and Statistics Working Papers 1-2022, Singapore Management University, School of Economics.
    11. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    12. Harris, A.R. & Rogers, Michelle Marinich & Miller, Carol J. & McElmurry, Shawn P. & Wang, Caisheng, 2015. "Residential emissions reductions through variable timing of electricity consumption," Applied Energy, Elsevier, vol. 158(C), pages 484-489.
    13. Zhishui Hu & Ioannis Kasparis & Qiying Wang, 2020. "Locally trimmed least squares: conventional inference in possibly nonstationary models," Papers 2006.12595, arXiv.org.
    14. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    15. Peng, Zhen & Dong, Chaohua, 2022. "Augmented cointegrating linear models with possibly strongly correlated stationary and nonstationary regressors," Finance Research Letters, Elsevier, vol. 47(PB).
    16. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    17. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
    18. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2023. "Estimation of the variance function in structural break autoregressive models with non‐stationary and explosive segments," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 181-205, March.
    19. Kapetanios, George & Millard, Stephen & Petrova, Katerina & Price, Simon, 2020. "Time-varying cointegration with an application to the UK Great Ratios," Economics Letters, Elsevier, vol. 193(C).
    20. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2019. "Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone," Monash Econometrics and Business Statistics Working Papers 28/19, Monash University, Department of Econometrics and Business Statistics.
    21. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    22. Degui Li & Peter C.B. Phillips & Jiti Gao, 2017. "Kernel-Based Inference In Time-Varying Coefficient Cointegrating Regression," Cowles Foundation Discussion Papers 2109, Cowles Foundation for Research in Economics, Yale University.
    23. Tingting Cheng & Jiti Gao & Oliver Linton, 2017. "Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction," Monash Econometrics and Business Statistics Working Papers 13/17, Monash University, Department of Econometrics and Business Statistics.
    24. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    25. Degui Li & Peter C. B. Phillips & Jiti Gao, 2013. "Uniform Consistency of Nonstationary Kernel-Weighted Sample Covariances for Nonparametric Regression," Monash Econometrics and Business Statistics Working Papers 27/13, Monash University, Department of Econometrics and Business Statistics.
    26. Polbin, Andrey & Skrobotov, Anton, 2022. "On decrease in oil price elasticity of GDP and investment in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 5-24.
    27. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    28. Yu, Deshui & Chen, Li & Li, Luyang, 2023. "Time-varying predictability of the long horizon equity premium based on semiparametric regressions," Economics Letters, Elsevier, vol. 224(C).
    29. Ayman Mnasri & Zouhair Mrabet & Mouyad Alsamara, 2023. "A new quadratic asymmetric error correction model: does size matter?," Empirical Economics, Springer, vol. 65(1), pages 33-64, July.
    30. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    31. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    32. Tu, Yundong & Liang, Han-Ying & Wang, Qiying, 2022. "Nonparametric inference for quantile cointegrations with stationary covariates," Journal of Econometrics, Elsevier, vol. 230(2), pages 453-482.
    33. Li, Li & Tu, Yundong, 2022. "The varying spillover of U.S. systemic risk: A functional-coefficient cointegration approach," Economics Letters, Elsevier, vol. 212(C).
    34. Kunpeng Li & Degui Li & Zhongwen Liang & Cheng Hsiao, 2017. "Estimation of semi-varying coefficient models with nonstationary regressors," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 354-369, March.
    35. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.
    36. Shan Dai & Ngai Hang Chan, 2023. "Testing of Constant Parameters for Semi‐Parametric Functional Coefficient Models with Integrated Covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 474-486, September.
    37. Qiying Wang & Peter C. B. Phillips & Ying Wang, 2023. "New asymptotics applied to functional coefficient regression and climate sensitivity analysis," Cowles Foundation Discussion Papers 2365, Cowles Foundation for Research in Economics, Yale University.
    38. Yayi Yan & Jiti Gao & Bin Peng, 2021. "Asymptotics for Time-Varying Vector MA(∞) Processes," Monash Econometrics and Business Statistics Working Papers 22/21, Monash University, Department of Econometrics and Business Statistics.

  59. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2013. "Nonparametric Estimation and Parametric Calibration of Time-Varying Coefficient Realized Volatility Models," Monash Econometrics and Business Statistics Working Papers 21/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Fengler, Matthias R. & Mammen, Enno & Vogt, Michael, 2013. "Additive modeling of realized variance: tests for parametric specifications and structural breaks," Economics Working Paper Series 1332, University of St. Gallen, School of Economics and Political Science.
    2. Fengler, M.R. & Mammen, E. & Vogt, M., 2015. "Specification and structural break tests for additive models with applications to realized variance data," Journal of Econometrics, Elsevier, vol. 188(1), pages 196-218.
    3. Yudong Wang & Zhiyuan Pan & Chongfeng Wu, 2017. "Time‐Varying Parameter Realized Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 566-580, August.

  60. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.
    3. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  61. Jiti Gao & Shin Kanaya & Degui Li & Dag Tjøstheim, 2013. "Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series," CREATES Research Papers 2013-29, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    2. Federico M Bandi & Valentina Corradi & Daniel Wilhelm, 2016. "Possibly Nonstationary Cross-Validation," CeMMAP working papers CWP11/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Biqing Cai & Chaohua Dong & Jiti Gao, 2015. "Orthogonal Series Estimation in Nonlinear Cointegrating Models with Endogeneity," Monash Econometrics and Business Statistics Working Papers 18/15, Monash University, Department of Econometrics and Business Statistics.
    4. Yuliana Linke & Igor Borisov & Pavel Ruzankin & Vladimir Kutsenko & Elena Yarovaya & Svetlana Shalnova, 2024. "Multivariate Universal Local Linear Kernel Estimators in Nonparametric Regression: Uniform Consistency," Mathematics, MDPI, vol. 12(12), pages 1-23, June.
    5. Bravo, Francesco & Li, Degui & Tjøstheim, Dag, 2021. "Robust nonlinear regression estimation in null recurrent time series," Journal of Econometrics, Elsevier, vol. 224(2), pages 416-438.
    6. Kim, Jihyun & Park, Joon Y., 2017. "Asymptotics for recurrent diffusions with application to high frequency regression," Journal of Econometrics, Elsevier, vol. 196(1), pages 37-54.
    7. Bu, Ruijun & Kim, Jihyun & Wang, Bin, 2023. "Uniform and Lp convergences for nonparametric continuous time regressions with semiparametric applications," Journal of Econometrics, Elsevier, vol. 235(2), pages 1934-1954.
    8. Shin Kanaya, 2015. "Uniform Convergence Rates of Kernel-Based Nonparametric Estimators for Continuous Time Diffusion Processes: A Damping Function Approach," CREATES Research Papers 2015-50, Department of Economics and Business Economics, Aarhus University.
    9. Degui Li & Peter C. B. Phillips & Jiti Gao, 2013. "Uniform Consistency of Nonstationary Kernel-Weighted Sample Covariances for Nonparametric Regression," Monash Econometrics and Business Statistics Working Papers 27/13, Monash University, Department of Econometrics and Business Statistics.
    10. Li, Degui & Li, Runze, 2016. "Local composite quantile regression smoothing for Harris recurrent Markov processes," Journal of Econometrics, Elsevier, vol. 194(1), pages 44-56.
    11. Ruijun Bu & Jihyun Kim & Bin Wang, 2020. "Uniform and Lp Convergences of Nonparametric Estimation for Diffusion Models," Working Papers 202021, University of Liverpool, Department of Economics.
    12. Degui Li & Dag Tjøstheim & Jiti Gao, 2012. "Nonlinear Regression with Harris Recurrent Markov Chains," Monash Econometrics and Business Statistics Working Papers 14/12, Monash University, Department of Econometrics and Business Statistics.
    13. Yayi Yan & Jiti Gao & Bin Peng, 2021. "Asymptotics for Time-Varying Vector MA(∞) Processes," Monash Econometrics and Business Statistics Working Papers 22/21, Monash University, Department of Econometrics and Business Statistics.
    14. James A. Duffy, 2015. "Uniform Convergence Rates over Maximal Domains in Structural Nonparametric Cointegrating Regression," Economics Papers 2015-W03, Economics Group, Nuffield College, University of Oxford.

  62. Nam H Kim & Patrick W Saart & Jiti Gao, 2013. "Semi-parametric Analysis of Shape-Invariant Engel Curves with Control Function Approach," Monash Econometrics and Business Statistics Working Papers 10/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Mélanie BIRKE & Sébastien VAN BELLEGEM & Ingrid VAN KEILEGOM, 2017. "Semi-parametric estimation in a single-index model with endogenous variables," LIDAM Reprints CORE 2898, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.

  63. Jiti Gao & Peter M. Robinson, 2013. "Inference on Nonstationary Time Series with Moving Mean," Monash Econometrics and Business Statistics Working Papers 15/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.

  64. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    2. Peter Pütz & Thomas Kneib, 2016. "A Penalized Spline Estimator for Fixed Effects Panel Data Models," SOEPpapers on Multidisciplinary Panel Data Research 827, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. Badi H. Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: a Bayesian Semiparametric Model With Random Coefficients for a Panel of OECD Countries," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 217-253, Emerald Group Publishing Limited.
    4. Peter Pütz & Thomas Kneib, 2018. "A penalized spline estimator for fixed effects panel data models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 145-166, April.

  65. Jiti Gao & Maxwell King, 2012. "An Improved Nonparametric Unit-Root Test," Monash Econometrics and Business Statistics Working Papers 16/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Christian Gouriéroux & Joann Jasiak, 2016. "Robust Analysis of the Martingale Hypothesis," Working Papers 2016-18, Center for Research in Economics and Statistics.
    2. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.

  66. Jiti Gao & Dag Tjøstheim & Jiying Yin, 2012. "Model Specification between Parametric and Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 18/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jun Wang & Dianpeng Wang & Yubin Tian, 2022. "Multidimensional specification test based on non-stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 348-372, June.
    2. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    3. Sepideh Mosaferi & Mark S. Kaiser, 2021. "Nonparametric Cointegrating Regression Functions with Endogeneity and Semi-Long Memory," Papers 2111.00972, arXiv.org, revised Jan 2025.
    4. Qiying Wang & Peter C. B. Phillips & Ying Wang, 2023. "New asymptotics applied to functional coefficient regression and climate sensitivity analysis," Cowles Foundation Discussion Papers 2365, Cowles Foundation for Research in Economics, Yale University.

  67. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.

    Cited by:

    1. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    2. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  68. Chaohua Dong & Jiti Gao, 2012. "Solving Replication Problems in Complete Market by Orthogonal Series Expansion," Monash Econometrics and Business Statistics Working Papers 7/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Shawkat Hammoudeh & Michael McAleer, 2012. "Risk Management and Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2012-08, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Retrieving the implicit risk neutral density of WTI options with a semi-nonparametric approach," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    3. Chaohua Dong & Jiti Gao, 2013. "Orthogonal Expansion of Levy Process Functionals: Theory and Practice," Monash Econometrics and Business Statistics Working Papers 3/13, Monash University, Department of Econometrics and Business Statistics.
    4. Lin, Shin-Hung & Huang, Hung-Hsi & Li, Sheng-Han, 2015. "Option pricing under truncated Gram–Charlier expansion," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 77-97.

  69. Chaohua Dong & Jiti Gao, 2012. "Specification Testing Driven by Orthogonal Series in Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 20/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jun Wang & Dianpeng Wang & Yubin Tian, 2022. "Multidimensional specification test based on non-stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 348-372, June.
    2. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.
    3. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  70. G. Pan & J. Gao & Y. Yang & M. Guo, 2012. "Independence Test for High Dimensional Random Vectors," Monash Econometrics and Business Statistics Working Papers 1/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Hyodo, Masashi & Nishiyama, Takahiro & Pavlenko, Tatjana, 2020. "Testing for independence of high-dimensional variables: ρV-coefficient based approach," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    2. Joel Bun & Jean-Philippe Bouchaud & Marc Potters, 2016. "Cleaning large correlation matrices: tools from random matrix theory," Papers 1610.08104, arXiv.org.
    3. Feng, Long & Zhang, Xiaoxu & Liu, Binghui, 2020. "Multivariate tests of independence and their application in correlation analysis between financial markets," Journal of Multivariate Analysis, Elsevier, vol. 179(C).
    4. Bodnar, Taras & Dette, Holger & Parolya, Nestor, 2019. "Testing for independence of large dimensional vectors," MPRA Paper 97997, University Library of Munich, Germany, revised May 2019.

  71. Chaohua Dong & Jiti Gao, 2012. "Expansion of Lévy Process Functionals and Its Application in Statistical Estimation," Monash Econometrics and Business Statistics Working Papers 2/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.

  72. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  73. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    2. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    3. George Athanasopoulos & Minfeng Deng & Gang Li & Haiyan Song, 2013. "Domestic and outbound tourism demand in Australia: a System-of-Equations Approach," Monash Econometrics and Business Statistics Working Papers 6/13, Monash University, Department of Econometrics and Business Statistics.
    4. Chaohua Dong & Jiti Gao, 2012. "Expansion of Lévy Process Functionals and Its Application in Statistical Estimation," Monash Econometrics and Business Statistics Working Papers 2/12, Monash University, Department of Econometrics and Business Statistics.
    5. Chaohua Dong & Jiti Gao, 2013. "Orthogonal Expansion of Levy Process Functionals: Theory and Practice," Monash Econometrics and Business Statistics Working Papers 3/13, Monash University, Department of Econometrics and Business Statistics.

  74. Jiti Gao & Dag Tjøstheim & Jiying Yin, 2011. "Estimation in threshold autoregressive models with a stationary and a unit root regime," Monash Econometrics and Business Statistics Working Papers 21/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jiti Gao & Maxwell King, 2012. "An Improved Nonparametric Unit-Root Test," Monash Econometrics and Business Statistics Working Papers 16/12, Monash University, Department of Econometrics and Business Statistics.
    2. Duan Lianjie, 2023. "Export Cutoff Productivity, Uncertainty and Duration of Waiting for Exporting," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 17(1), pages 1-19, January.
    3. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.
    4. Jiti Gao & Degui Li & Dag Tjøstheim, 2011. "Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series," Monash Econometrics and Business Statistics Working Papers 13/11, Monash University, Department of Econometrics and Business Statistics.
    5. Lihua Feng & Gaoyuan Luo, 2014. "Application of a nonlinear model in landfall number forecasting for tropical cyclones in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(3), pages 1475-1482, September.
    6. Anna Bykhovskaya & James A. Duffy, 2022. "The Local to Unity Dynamic Tobit Model," Papers 2210.02599, arXiv.org, revised May 2024.
    7. Bravo, Francesco & Li, Degui & Tjøstheim, Dag, 2021. "Robust nonlinear regression estimation in null recurrent time series," Journal of Econometrics, Elsevier, vol. 224(2), pages 416-438.
    8. Yang, Yaxing & Ling, Shiqing, 2017. "Self-weighted LAD-based inference for heavy-tailed threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 197(2), pages 368-381.
    9. Thouraya Boujelbène Dammak & Kamel Helali, 2016. "A Nonlinear Approach to Tunisian Inflation Rate," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(61), pages 147-164, September.
    10. Bykhovskaya, Anna & Duffy, James A., 2024. "The local to unity dynamic Tobit model," Journal of Econometrics, Elsevier, vol. 241(2).
    11. Li, Degui & Li, Runze, 2016. "Local composite quantile regression smoothing for Harris recurrent Markov processes," Journal of Econometrics, Elsevier, vol. 194(1), pages 44-56.
    12. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    13. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, vol. 3(2), pages 1-24, April.
    14. Joseph Ngatchou-Wandji & Madan L. Puri & Michel Harel & Echarif Elharfaoui, 2019. "Testing nonstationary and absolutely regular nonlinear time series models," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 557-593, October.
    15. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    16. George Athanasopoulos & Minfeng Deng & Gang Li & Haiyan Song, 2013. "Domestic and outbound tourism demand in Australia: a System-of-Equations Approach," Monash Econometrics and Business Statistics Working Papers 6/13, Monash University, Department of Econometrics and Business Statistics.
    17. Yaxing Yang & Shiqing Ling, 2018. "A Note On The Lse Of Three-Regime Tar Model With An Infinite Variance," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-13, June.
    18. Francesco Giordano & Marcella Niglio & Cosimo Damiano Vitale, 2017. "Unit Root Testing in Presence of a Double Threshold Process," Methodology and Computing in Applied Probability, Springer, vol. 19(2), pages 539-556, June.
    19. James A. Duffy & Sophocles Mavroeidis & Sam Wycherley, 2022. "Cointegration with Occasionally Binding Constraints," Papers 2211.09604, arXiv.org, revised Feb 2025.
    20. Victor V. Konev & Sergey E. Vorobeychikov, 2022. "Fixed accuracy estimation of parameters in a threshold autoregressive model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 685-711, August.

  75. Jiti Gao & Maxwell King, 2011. "A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors," Monash Econometrics and Business Statistics Working Papers 20/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.

  76. Jia Chen & Jiti Gao & Degui Li, 2011. "Estimation in Partially Linear Single-Index Panel Data Models with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 14/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jun Zhang, 2021. "Estimation and variable selection for partial linear single-index distortion measurement errors models," Statistical Papers, Springer, vol. 62(2), pages 887-913, April.
    2. Huang, Lei & Jiang, Hui & Wang, Huixia, 2019. "A novel partial-linear single-index model for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 110-122.
    3. Xie, Chuanlong & Zhu, Lixing, 2019. "A goodness-of-fit test for variable-adjusted models," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 27-48.
    4. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
    5. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    6. Bang-Qiang He & Xing-Jian Hong & Guo-Liang Fan, 2020. "Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects," Statistical Papers, Springer, vol. 61(6), pages 2351-2381, December.
    7. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    8. Suigen Yang & Xiujuan Yang & Xuefei Wang, 2024. "Estimation and Simultaneous Confidence Bands for Fixed-Effects Panel Data Partially Linear Models," Mathematics, MDPI, vol. 12(23), pages 1-18, November.
    9. Hu, Xuemei, 2017. "Semi-parametric inference for semi-varying coefficient panel data model with individual effects," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 262-281.
    10. Mengqi Zhang & Boping Tian, 2023. "Profile Maximum Likelihood Estimation of Single-Index Spatial Dynamic Panel Data Model," Mathematics, MDPI, vol. 11(13), pages 1-16, July.
    11. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    12. Shakhawat Hossain & Le An Lac, 2021. "Optimal shrinkage estimations in partially linear single-index models for binary longitudinal data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 811-835, December.
    13. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    14. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    15. Yan-Yong Zhao & Ling-Ling Ge & Yuan Liu, 2025. "Estimation of panel data partially linear time-varying coefficient models with cross-sectional spatial autoregressive errors," Statistical Papers, Springer, vol. 66(1), pages 1-37, January.
    16. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    17. Jia Chen & Degui Li & Yingcun Xia, 2015. "New Semiparametric Estimation Procedure for Functional Coefficient Longitudinal Data Models," Discussion Papers 15/17, Department of Economics, University of York.
    18. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    19. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    20. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    21. Chen, Jia & Li, Degui & Xia, Yingcun, 2019. "Estimation of a rank-reduced functional-coefficient panel data model with serial correlation," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 456-479.
    22. Arteaga-Molina, Luis A. & Rodríguez-Poo, Juan M., 2019. "Empirical likelihood based inference for a categorical varying-coefficient panel data model with fixed effects," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 110-124.
    23. Jia Chen & Degui Li & Hua Liang & Suojin Wang, 2014. "Semiparametric GEE Analysis in Partially Linear Single-Index Models for Longitudinal Data," Discussion Papers 14/26, Department of Economics, University of York.
    24. Peter Pütz & Thomas Kneib, 2018. "A penalized spline estimator for fixed effects panel data models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 145-166, April.
    25. Ma, Shujie & Liang, Hua & Tsai, Chih-Ling, 2014. "Partially linear single index models for repeated measurements," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 354-375.
    26. Xuemei Hu & Weiming Yang, 2019. "Semi-parametric small area inference in generalized semi-varying coefficient mixed effects models," Statistical Papers, Springer, vol. 60(4), pages 1039-1058, August.
    27. Bogui Li & Jianbao Chen & Shuangshuang Li, 2023. "Estimation of Fixed Effects Partially Linear Varying Coefficient Panel Data Regression Model with Nonseparable Space-Time Filters," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    28. Yingli Pan & Wen Cai & Zhan Liu, 2022. "Inference for non-probability samples under high-dimensional covariate-adjusted superpopulation model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 955-979, October.
    29. Hu Yang & Ning Li & Jing Yang, 2020. "A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates," Statistical Papers, Springer, vol. 61(5), pages 1911-1937, October.
    30. Huilan Liu & Hu Yang & Changgen Peng, 2019. "Weighted composite quantile regression for single index model with missing covariates at random," Computational Statistics, Springer, vol. 34(4), pages 1711-1740, December.

  77. Jiti Gao & Peter C. B. Phillips, 2010. "Semiparametric Estimation in Time Series of Simultaneous Equations," Cowles Foundation Discussion Papers 1769, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Dursun Aydın & Ersin Yılmaz, 2021. "Semiparametric modeling of the right-censored time-series based on different censorship solution techniques," Empirical Economics, Springer, vol. 61(4), pages 2143-2172, October.
    2. Chaohua Dong & Jiti Gao, 2011. "Expansion of Brownian Motion Functionals and Its Application in Econometric Estimation," Monash Econometrics and Business Statistics Working Papers 19/11, Monash University, Department of Econometrics and Business Statistics.

  78. Degui Li & Jia Chen & Jiti Gao, 2010. "Nonparametric Time-Varying Coefficient Panel Data Models with Fixed Effects," School of Economics and Public Policy Working Papers 2010-08, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. António Afonso & Michael G. Arghyrou & María Dolores Gadea & Alexandros Kontonikas, 2017. ""Whatever it takes" to resolve the European sovereign debt crisis? Bond pricing regime switches and monetary policy effects," Working Papers REM 2017/02, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. Tingting Cheng & Jiti Gao & Xibin Zhang, 2015. "Bayesian Bandwidth Estimation In Nonparametric Time-Varying Coefficient Models," Monash Econometrics and Business Statistics Working Papers 3/15, Monash University, Department of Econometrics and Business Statistics.
    3. Phillips, Peter C.B. & Wang, Ying, 2022. "Functional coefficient panel modeling with communal smoothing covariates," Journal of Econometrics, Elsevier, vol. 227(2), pages 371-407.
    4. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    5. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    6. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    7. Jean-Louis Combes & Rasmané Ouedraogo, 2014. "Does Pro-cyclical Aid Lead to Pro-cyclical Fiscal Policy? An Empirical Analysis for Sub-Saharan Africa," CERDI Working papers halshs-01084600, HAL.
    8. Dufrénot Gilles & Ginn William & Pourroy Marc & Sullivan Adam, 2025. "Does State Dependence Matter in Relation to Oil Price Shocks on Global Economic Conditions?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(2), pages 247-264.
    9. Aktham Maghyereh & Hussein Abdoh, 2024. "Oil price uncertainly and sovereign credit risk in GCC countries: fresh evidence," International Economics and Economic Policy, Springer, vol. 21(2), pages 457-482, May.
    10. Awaworyi Churchill, Sefa & Inekwe, John & Smyth, Russell & Zhang, Xibin, 2019. "R&D intensity and carbon emissions in the G7: 1870–2014," Energy Economics, Elsevier, vol. 80(C), pages 30-37.
    11. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    12. Elkhan Richard Sadik-Zada & Wilhelm Loewenstein, 2020. "Drivers of CO 2 -Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses," Energies, MDPI, vol. 13(15), pages 1-24, August.
    13. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
    14. Lee, Jungyoon & Robinson, Peter, 2015. "Panel nonparametric regression with fixed effects," LSE Research Online Documents on Economics 61431, London School of Economics and Political Science, LSE Library.
    15. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    16. Wei, Honglei & Zhang, Hongfan & Jiang, Hui & Huang, Lei, 2022. "On the semi-varying coefficient dynamic panel data model with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    17. Lin, Cunjie & Zhou, Yong, 2016. "Semiparametric varying-coefficient model with right-censored and length-biased data," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 119-144.
    18. Ivanovski, Kris & Hailemariam, Abebe, 2022. "Time-varying geopolitical risk and oil prices," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 206-221.
    19. Bang-Qiang He & Xing-Jian Hong & Guo-Liang Fan, 2020. "Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects," Statistical Papers, Springer, vol. 61(6), pages 2351-2381, December.
    20. Ben Cheikh, Nidhaleddine & Ben Zaied, Younes & Mahmoud, Faisal, 2025. "Energy transition, institutional quality, and financial development in Africa," Research in International Business and Finance, Elsevier, vol. 74(C).
    21. Arghyrou, Michael G & Gadea, Mar a Dolores, 2019. "Private bank deposits and macro/fiscal risk in the euro-area," Cardiff Economics Working Papers E2019/6, Cardiff University, Cardiff Business School, Economics Section.
    22. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    23. Le, Ha Chi & Bhattacharya, Mita & Smyth, Russell & Zhang, Xibin, 2024. "Does economic growth cause energy intensity of well-being in the very long run? Semi-parametric evidence for selected OECD countries," Energy Economics, Elsevier, vol. 139(C).
    24. Ren, Xiaohang & Tong, Ziwei & Sun, Xianming & Yan, Cheng, 2022. "Dynamic impacts of energy consumption on economic growth in China: Evidence from a non-parametric panel data model," Energy Economics, Elsevier, vol. 107(C).
    25. Ghazouani, Tarek, 2024. "Investigating the dynamic link between globalization and carbon emissions in BRICS nations: Insights from a non-parametric perspective," International Economics, Elsevier, vol. 180(C).
    26. Pei, Youquan & Huang, Tao & You, Jinhong, 2018. "Nonparametric fixed effects model for panel data with locally stationary regressors," Journal of Econometrics, Elsevier, vol. 202(2), pages 286-305.
    27. Jia Chen, 2019. "Estimating latent group structure in time-varying coefficient panel data models," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 223-240.
    28. Selahattin Güriş & Sevcan Çağlayan, 2023. "Co2 Emisyonlarını Etkileyen Faktörlerin Zamanla Değişen Katsayılı Parametrik Olmayan Panel Veri Modelleri ile Analizi," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(39), pages 76-88, December.
    29. Sanying Feng & Tiejun Tong & Sung Nok Chiu, 2023. "Statistical Inference for Partially Linear Varying Coefficient Spatial Autoregressive Panel Data Model," Mathematics, MDPI, vol. 11(22), pages 1-19, November.
    30. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    31. Li, Han & O’Hare, Colin & Zhang, Xibin, 2015. "A semiparametric panel approach to mortality modeling," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 264-270.
    32. Li, Kunming & Fang, Liting & He, Lerong, 2019. "How population and energy price affect China's environmental pollution?," Energy Policy, Elsevier, vol. 129(C), pages 386-396.
    33. Huazhen Lin & Hyokyoung G. Hong & Baoying Yang & Wei Liu & Yong Zhang & Gang-Zhi Fan & Yi Li, 2019. "Nonparametric Time-Varying Coefficient Models for Panel Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 548-566, December.
    34. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    35. G. Arghyrou, Michael & Gadea, Maria-Dolores & Kontonikas, Alexandros, 2024. "Private bank deposits and macro/fiscal risk in the euro-area," Journal of International Money and Finance, Elsevier, vol. 140(C).
    36. Sun, Xianming & Xiao, Shiyi & Ren, Xiaohang & Xu, Bing, 2023. "Time-varying impact of information and communication technology on carbon emissions," Energy Economics, Elsevier, vol. 118(C).
    37. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    38. Ghazouani, Tarek, 2022. "Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    39. Qu, Lianqiang & Song, Xinyuan & Sun, Liuquan, 2018. "Identification of local sparsity and variable selection for varying coefficient additive hazards models," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 119-135.
    40. Garriga, Ana Carolina & Rodriguez, Cesar M., 2020. "More effective than we thought: Central bank independence and inflation in developing countries," Economic Modelling, Elsevier, vol. 85(C), pages 87-105.
    41. Chenlin Zhang & Huazhen Lin & Li Liu & Jin Liu & Yi Li, 2023. "Functional data analysis with covariate‐dependent mean and covariance structures," Biometrics, The International Biometric Society, vol. 79(3), pages 2232-2245, September.
    42. Lee, Yoon-Jin, 2014. "Testing a linear dynamic panel data model against nonlinear alternatives," Journal of Econometrics, Elsevier, vol. 178(P1), pages 146-166.
    43. Yao, Yao & Ivanovski, Kris & Inekwe, John & Smyth, Russell, 2020. "Human capital and CO2 emissions in the long run," Energy Economics, Elsevier, vol. 91(C).
    44. Elkhan Richard Sadik-Zada, 2021. "An Ode to ODA against all Odds? A Novel Game-Theoretical and Empirical Reappraisal of the Terrorism-Aid Nexus," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 49(2), pages 221-240, June.
    45. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2013. "Nonparametric Estimation and Parametric Calibration of Time-Varying Coefficient Realized Volatility Models," Monash Econometrics and Business Statistics Working Papers 21/13, Monash University, Department of Econometrics and Business Statistics.
    46. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    47. Tarek Ghazouani, 2024. "Is the Relationship Between Clean/Non-clean Energy Consumption and Economic Growth Time-Varying? Non-parametric Evidence for MENA Region," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(4), pages 19964-19988, December.
    48. Tiwari, Aviral Kumar & Eapen, Leena Mary & Nair, Sthanu R, 2021. "Electricity consumption and economic growth at the state and sectoral level in India: Evidence using heterogeneous panel data methods," Energy Economics, Elsevier, vol. 94(C).
    49. Feng, Sanying & He, Wenqi & Li, Feng, 2020. "Model detection and estimation for varying coefficient panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    50. Yonghui Zhang & Liangjun Su & Peter C.B. Phillips, 2011. "Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects," Cowles Foundation Discussion Papers 1832, Cowles Foundation for Research in Economics, Yale University.
    51. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    52. Abebe Hailemariam & Tutsirai Sakutukwa & Ratbek Dzhumashev, 2021. "Long-term determinants of income inequality: evidence from panel data over 1870–2016," Empirical Economics, Springer, vol. 61(4), pages 1935-1958, October.
    53. Ben Cheikh, Nidhaleddine & Ben Zaied, Younes & Nguyen, Duc Khuong, 2023. "Understanding energy poverty drivers in Europe," Energy Policy, Elsevier, vol. 183(C).
    54. Chen, Jia & Li, Degui & Xia, Yingcun, 2019. "Estimation of a rank-reduced functional-coefficient panel data model with serial correlation," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 456-479.
    55. Badi H. Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: a Bayesian Semiparametric Model With Random Coefficients for a Panel of OECD Countries," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 217-253, Emerald Group Publishing Limited.
    56. Cepni, Oguzhan & Emirmahmutoglu, Furkan & Guney, Ibrahim Ethem & Yilmaz, Muhammed Hasan, 2023. "Do the carry trades respond to geopolitical risks? Evidence from BRICS countries," Economic Systems, Elsevier, vol. 47(2).
    57. Elkhan Richard Sadik‐Zada, 2021. "Natural resources, technological progress, and economic modernization," Review of Development Economics, Wiley Blackwell, vol. 25(1), pages 381-404, February.
    58. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
    59. Junrong Liu & Robin C. Sickles & E. G. Tsionas, 2017. "Bayesian Treatments for Panel Data Stochastic Frontier Models with Time Varying Heterogeneity," Econometrics, MDPI, vol. 5(3), pages 1-21, July.
    60. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    61. Wan-Jiun Chen, 2022. "Toward Sustainability: Dynamics of Total Carbon Dioxide Emissions, Aggregate Income, Non-Renewable Energy, and Renewable Power," Sustainability, MDPI, vol. 14(5), pages 1-27, February.
    62. Bampinas, Georgios & Mavropoulos, Georgios, 2024. "Asymmetric effects between economic development and fertility: What do 140 years of data tell us?," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).
    63. Dirk Broeders & Marleen de Jonge & David Rijsbergen, 2024. "The European Carbon Bond Premium," Working Papers 798, DNB.
    64. Annegues, Ana Claudia & Rodrigues de Oliveira, Victor & Souza, Wallace Patrick Santos de Farias, 2017. "Thoughts on the inequality of opportunities: new evidence," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    65. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    66. Dogan, Ergun & Zhang, Xibin, 2023. "A nonparametric panel data model for examining the contribution of tourism to economic growth," Economic Modelling, Elsevier, vol. 128(C).
    67. Sefa Awaworyi Churchill & Bin Peng & Russell Smyth & Quanda Zhang, 2022. "R&D intensity and income inequality in the G7: 1870–2016," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 263-282, July.
    68. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    69. Hua Liu & Youquan Pei & Qunfang Xu, 2020. "Estimation for varying coefficient panel data model with cross-sectional dependence," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(3), pages 377-410, April.
    70. Timothy Neal, 2018. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15A, School of Economics, The University of New South Wales.
    71. Yu Bai & Massimiliano Marcellino & George Kapetanios, 2023. "Mean Group Instrumental Variable Estimation of Time-Varying Large Heterogeneous Panels with Endogenous Regressors," Monash Econometrics and Business Statistics Working Papers 13/23, Monash University, Department of Econometrics and Business Statistics.
    72. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The effect of structural oil shocks on bank systemic risk in the GCC countries," Energy Economics, Elsevier, vol. 103(C).
    73. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2018. "Nonparametric Estimation and Forecasting for Time-Varying Coefficient Realized Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 88-100, January.
    74. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    75. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    76. Lee, Jungyoon & Robinson, Peter M., 2015. "Panel nonparametric regression with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 346-362.
    77. Anagnostopoulou, Seraina C. & Tsekrekos, Andrianos E. & Voulgaris, Georgios, 2021. "Accounting conservatism and corporate social responsibility," The British Accounting Review, Elsevier, vol. 53(4).
    78. Wenhao Song & Chunhui Ye & Yuheng Liu & Weisong Cheng, 2021. "Do China’s Urban–Environmental Quality and Economic Growth Conform to the Environmental Kuznets Curve?," IJERPH, MDPI, vol. 18(24), pages 1-15, December.
    79. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.

  79. Jiti Gao & Peter C. B. Phillips, 2010. "Semiparametric Estimation in Simultaneous Equations of Time Series Models," School of Economics and Public Policy Working Papers 2010-26, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Dursun Aydın & Ersin Yılmaz, 2021. "Semiparametric modeling of the right-censored time-series based on different censorship solution techniques," Empirical Economics, Springer, vol. 61(4), pages 2143-2172, October.
    2. Chaohua Dong & Jiti Gao, 2011. "Expansion of Brownian Motion Functionals and Its Application in Econometric Estimation," Monash Econometrics and Business Statistics Working Papers 19/11, Monash University, Department of Econometrics and Business Statistics.

  80. Jia Chen & Jiti Gao & Degui Li, 2010. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," School of Economics and Public Policy Working Papers 2010-10, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Tingting Cheng & Jiti Gao & Xibin Zhang, 2015. "Bayesian Bandwidth Estimation In Nonparametric Time-Varying Coefficient Models," Monash Econometrics and Business Statistics Working Papers 3/15, Monash University, Department of Econometrics and Business Statistics.
    2. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Series estimation for single-index models under constraints," Monash Econometrics and Business Statistics Working Papers 5/18, Monash University, Department of Econometrics and Business Statistics.
    3. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    4. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    5. Deshui Yu & Yayi Yan, 2023. "Joint dynamics of stock returns and cash flows: A time‐varying present‐value framework," Financial Management, Financial Management Association International, vol. 52(3), pages 513-541, September.
    6. Isabel Casas & Jiti Gao & Shangyu Xie, 2018. "Modelling Time-Varying Income Elasticities of Health Care Expenditure for the OECD," CREATES Research Papers 2018-29, Department of Economics and Business Economics, Aarhus University.
    7. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    8. Guohua Feng & Jiti Gao & Xiaohui Zhang, 2016. "Estimation of Technical Change and Price Elasticities: A Categorical Time-varying Coefficient Approach," Monash Econometrics and Business Statistics Working Papers 2/16, Monash University, Department of Econometrics and Business Statistics.
    9. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
    10. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    11. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    12. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    13. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    14. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    15. Bing Jiang & Yanrong Yang & Jiti Gao & Cheng Hsiao, 2017. "Recursive estimation in large panel data models: Theory and practice," Monash Econometrics and Business Statistics Working Papers 5/17, Monash University, Department of Econometrics and Business Statistics.
    16. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    17. Awaworyi Churchill, Sefa & Baako, Kingsley Tetteh & Mintah, Kwabena & Zhang, Quanda, 2021. "Transport infrastructure and house prices in the long run," Transport Policy, Elsevier, vol. 112(C), pages 1-12.
    18. Ghazouani, Tarek, 2024. "Investigating the dynamic link between globalization and carbon emissions in BRICS nations: Insights from a non-parametric perspective," International Economics, Elsevier, vol. 180(C).
    19. Pei, Youquan & Huang, Tao & You, Jinhong, 2018. "Nonparametric fixed effects model for panel data with locally stationary regressors," Journal of Econometrics, Elsevier, vol. 202(2), pages 286-305.
    20. Jia Chen, 2019. "Estimating latent group structure in time-varying coefficient panel data models," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 223-240.
    21. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Quantile Random-Coefficient Regression with Interactive Fixed Effects: Heterogeneous Group-Level Policy Evaluation," Papers 2208.03632, arXiv.org, revised Nov 2024.
    22. Silvapulle, Param & Smyth, Russell & Zhang, Xibin & Fenech, Jean-Pierre, 2017. "Nonparametric panel data model for crude oil and stock market prices in net oil importing countries," Energy Economics, Elsevier, vol. 67(C), pages 255-267.
    23. KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2014. "Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model," Research Paper Series 347, Quantitative Finance Research Centre, University of Technology, Sydney.
    24. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    25. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    26. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    27. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    28. Zongwu Cai & Ying Fang & Qiuhua Xu, 2020. "Testing Capital Asset Pricing Models using Functional-Coefficient Panel Data Models with Cross-Sectional Dependence," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202009, University of Kansas, Department of Economics, revised Jul 2020.
    29. Jiti Gao & Bin Peng & Yayi Yan, 2021. "Parameter Stability Testing for Multivariate Dynamic Time-Varying Models," Monash Econometrics and Business Statistics Working Papers 11/21, Monash University, Department of Econometrics and Business Statistics.
    30. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2025. "Panel Data Estimation and Inference: Homogeneity versus Heterogeneity," Papers 2502.03019, arXiv.org.
    31. Yu, Deshui & Chen, Li, 2024. "Local predictability of stock returns and cash flows," Journal of Empirical Finance, Elsevier, vol. 77(C).
    32. Bhattacharya, Mita & Inekwe, John & Yan, Eric, 2021. "Dynamics of energy poverty: Evidence from nonparametric estimates across the ASEAN+6 region," Energy Economics, Elsevier, vol. 103(C).
    33. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    34. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    35. Jiti Gao & Bin Peng & Yayi Yan, 2023. "Higher-order Expansions and Inference for Panel Data Models," Monash Econometrics and Business Statistics Working Papers 14/23, Monash University, Department of Econometrics and Business Statistics.
    36. Wongsa-art, Pipat & Kim, Namhyun & Xia, Yingcun & Moscone, Francesco, 2024. "Varying coefficient panel data models and methods under correlated error components: Application to disparities in mental health services in England," Regional Science and Urban Economics, Elsevier, vol. 106(C).
    37. Ghazouani, Tarek, 2022. "Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    38. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2019. "Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone," Monash Econometrics and Business Statistics Working Papers 28/19, Monash University, Department of Econometrics and Business Statistics.
    39. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    40. Yan-Yong Zhao & Ling-Ling Ge & Yuan Liu, 2025. "Estimation of panel data partially linear time-varying coefficient models with cross-sectional spatial autoregressive errors," Statistical Papers, Springer, vol. 66(1), pages 1-37, January.
    41. Lee, Yoon-Jin, 2014. "Testing a linear dynamic panel data model against nonlinear alternatives," Journal of Econometrics, Elsevier, vol. 178(P1), pages 146-166.
    42. Yao, Yao & Ivanovski, Kris & Inekwe, John & Smyth, Russell, 2020. "Human capital and CO2 emissions in the long run," Energy Economics, Elsevier, vol. 91(C).
    43. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    44. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    45. Yonghui Zhang & Liangjun Su & Peter C.B. Phillips, 2011. "Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects," Cowles Foundation Discussion Papers 1832, Cowles Foundation for Research in Economics, Yale University.
    46. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    47. Badi H. Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: a Bayesian Semiparametric Model With Random Coefficients for a Panel of OECD Countries," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 217-253, Emerald Group Publishing Limited.
    48. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    49. Arteaga-Molina, Luis A. & Rodríguez-Poo, Juan M., 2019. "Empirical likelihood based inference for a categorical varying-coefficient panel data model with fixed effects," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 110-124.
    50. Ma, Shujie & Liang, Hua & Tsai, Chih-Ling, 2014. "Partially linear single index models for repeated measurements," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 354-375.
    51. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    52. Cai, Zongwu & Fang, Ying & Xu, Qiuhua, 2022. "Testing capital asset pricing models using functional-coefficient panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 227(1), pages 114-133.
    53. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    54. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    55. Archer Gong Zhang & Jiahua Chen, 2023. "Optimal Estimation under a Semiparametric Density Ratio Model," Papers 2309.09103, arXiv.org.
    56. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.
    57. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
    58. Ma, Yingying & Guo, Shaojun & Wang, Hansheng, 2023. "Sparse spatio-temporal autoregressions by profiling and bagging," Journal of Econometrics, Elsevier, vol. 232(1), pages 132-147.
    59. Jiti Gao & Bin Peng & Zhao Ren & Xiaohui Zhang, 2015. "Variable Selection for a Categorical Varying-Coefficient Model with Identifications for Determinants of Body Mass Index," Monash Econometrics and Business Statistics Working Papers 21/15, Monash University, Department of Econometrics and Business Statistics.
    60. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

  81. Jia Chen & Jiti Gao & Degui Li, 2010. "Estimation in Semiparametric Time Series Regression," School of Economics and Public Policy Working Papers 2010-27, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    2. Justin Dang & Aman Ullah, 2021. "Machine Learning Based Semiparametric Time Series Conditional Variance: Estimation and Forecasting," Working Papers 202204, University of California at Riverside, Department of Economics, revised Jan 2022.
    3. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    4. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    5. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    6. George Athanasopoulos & Minfeng Deng & Gang Li & Haiyan Song, 2013. "Domestic and outbound tourism demand in Australia: a System-of-Equations Approach," Monash Econometrics and Business Statistics Working Papers 6/13, Monash University, Department of Econometrics and Business Statistics.

  82. Jia Chen & Jiti Gao & Degui Li, 2010. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," School of Economics and Public Policy Working Papers 2010-09, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Huang, Lei & Jiang, Hui & Wang, Huixia, 2019. "A novel partial-linear single-index model for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 110-122.
    2. Kutlu, Levent & Sickles, Robin & Tsionas, Mike G., 2019. "Heterogeneous Decision-Making and Market Power," Working Papers 19-008, Rice University, Department of Economics.
    3. Suigen Yang & Xiujuan Yang & Xuefei Wang, 2024. "Estimation and Simultaneous Confidence Bands for Fixed-Effects Panel Data Partially Linear Models," Mathematics, MDPI, vol. 12(23), pages 1-18, November.
    4. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    5. Xiaohui Yuan & Xuefei Xiang & Xinran Zhang, 2023. "Bayesian composite quantile regression for the single-index model," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-17, May.
    6. Yang, Suigen & Xue, Liugen & Li, Gaorong, 2014. "Simultaneous confidence band for single-index random effects models with longitudinal data," Statistics & Probability Letters, Elsevier, vol. 85(C), pages 6-14.
    7. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    8. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    9. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    10. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    11. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    12. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    13. Jia Chen & Degui Li & Hua Liang & Suojin Wang, 2014. "Semiparametric GEE Analysis in Partially Linear Single-Index Models for Longitudinal Data," Discussion Papers 14/26, Department of Economics, University of York.

  83. Jiti Gao & Irene Gijbels, 2009. "Bandwidth Selection in Nonparametric Kernel Testing," School of Economics and Public Policy Working Papers 2009-01, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2011. "Testing functional inequalities," CeMMAP working papers CWP12/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Delsol, Laurent & Ferraty, Frédéric & Vieu, Philippe, 2011. "Structural test in regression on functional variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 422-447, March.
    3. Bagkavos, Dimitrios & Patil, Prakash N. & Wood, Andrew T.A., 2023. "Nonparametric goodness-of-fit testing for a continuous multivariate parametric model," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    4. Gijbels, Irène & Omelka, Marek & Veraverbeke, Noël, 2021. "Omnibus test for covariate effects in conditional copula models," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    5. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    6. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    7. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
    8. Jiti Gao & Maxwell King, 2011. "A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors," Monash Econometrics and Business Statistics Working Papers 20/11, Monash University, Department of Econometrics and Business Statistics.
    9. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2021. "Optimal Minimax Rates of Specification Testing with Data-driven Bandwidth," KIER Working Papers 1053, Kyoto University, Institute of Economic Research.
    10. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    11. Jácome, M.A. & López-de-Ullibarri, I., 2016. "Bandwidth selection for the presmoothed logrank test," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 151-157.
    12. Politis, D N, 2009. "Higher-Order Accurate, Positive Semi-definite Estimation of Large-Sample Covariance and Spectral Density Matrices," University of California at San Diego, Economics Working Paper Series qt66w826hz, Department of Economics, UC San Diego.
    13. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2025. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Working Papers 202526, University of Macau, Faculty of Business Administration.
    14. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    15. Xu, Ke-Li, 2013. "Powerful tests for structural changes in volatility," Journal of Econometrics, Elsevier, vol. 173(1), pages 126-142.
    16. Bravo, Francesco & Chu, Ba M. & Jacho-Chávez, David T., 2017. "Generalized empirical likelihood M testing for semiparametric models with time series data," Econometrics and Statistics, Elsevier, vol. 4(C), pages 18-30.
    17. Kim, Min Seong & Sun, Yixiao & Yang, Jingjing, 2016. "A Fixed-bandwidth View of the Pre-asymptotic Inference for Kernel Smoothing with Time Series Data," University of California at San Diego, Economics Working Paper Series qt2240n3n5, Department of Economics, UC San Diego.
    18. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    19. Rahvar, Sepehr & Reihani, Erfan S. & Golestani, Amirhossein N. & Hamounian, Abolfazl & Aghaei, Fatemeh & Sahimi, Muhammad & Manshour, Pouya & Paluš, Milan & Feudel, Ulrike & Freund, Jan A. & Lehnertz,, 2024. "Characterizing time-resolved stochasticity in non-stationary time series," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    20. Taoufik Bouezmarni & Jeroen V.K. Rombouts & Abderrahim Taamouti, 2011. "Nonparametric Copula-Based Test for Conditional Independence with Applications to Granger Causality," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 275-287, October.
    21. Stefan Sperlich, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 419-427, September.
    22. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    23. Sun, Zhihua & Ye, Xue & Sun, Liuquan, 2015. "Consistent test of error-in-variables partially linear model with auxiliary variables," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 118-131.
    24. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers 1740, Cowles Foundation for Research in Economics, Yale University.
    25. Liang, Zhongwen & Li, Qi, 2012. "Functional coefficient regression models with time trend," Journal of Econometrics, Elsevier, vol. 170(1), pages 15-31.
    26. Weijia Jia & Weixing Song, 2018. "Goodness-of-fit tests in linear EV regression with replications," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(4), pages 395-421, May.
    27. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.
    28. Masayuki Hirukawa & Mari Sakudo, 2016. "Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels," Econometrics, MDPI, vol. 4(2), pages 1-27, June.
    29. Laurent Delsol, 2013. "No effect tests in regression on functional variable and some applications to spectrometric studies," Computational Statistics, Springer, vol. 28(4), pages 1775-1811, August.
    30. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    31. Sun, Yixiao, 2013. "Let's Fix It: Fixed-b Asymptotics versus Small-b Asymptotics in Heteroscedasticity and Autocorrelation Robust Inference," University of California at San Diego, Economics Working Paper Series qt8x8307rz, Department of Economics, UC San Diego.
    32. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    33. J. M. Krief, 2009. "Two Stage Semi Parametric Quantile Regression," Departmental Working Papers 2009-05, Department of Economics, Louisiana State University.
    34. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    35. Bagkavos, Dimitrios & Patil, Prakash N., 2023. "Goodness-of-fit testing for normal mixture densities," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
    36. George Athanasopoulos & Minfeng Deng & Gang Li & Haiyan Song, 2013. "Domestic and outbound tourism demand in Australia: a System-of-Equations Approach," Monash Econometrics and Business Statistics Working Papers 6/13, Monash University, Department of Econometrics and Business Statistics.
    37. Sun, Shuang & Song, Zening & Song, Xiaojun, 2025. "Unified specification tests in partially linear time series models," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
    38. Bagkavos, D. & Patil, P.N., 2017. "A new test of independence for bivariate observations," Journal of Multivariate Analysis, Elsevier, vol. 160(C), pages 117-133.
    39. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    40. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    41. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.
    42. Zu, Yang & Boswijk, H. Peter, 2017. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 53-75.
    43. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.
    44. Pablo Martínez-Camblor & Jacobo Uña-Álvarez, 2013. "Studying the bandwidth in $$k$$ -sample smooth tests," Computational Statistics, Springer, vol. 28(2), pages 875-892, April.
    45. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Coverage Error Optimal Confidence Intervals for Local Polynomial Regression," Papers 1808.01398, arXiv.org, revised Jul 2021.
    46. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.
    47. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    48. Zu, Yang, 2015. "Nonparametric specification tests for stochastic volatility models based on volatility density," Journal of Econometrics, Elsevier, vol. 187(1), pages 323-344.
    49. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.
    50. Tang, Shijie & Chen, Lisha & Tsui, Kam-Wah & Doksum, Kjell, 2014. "Nonparametric variable selection and classification: The CATCH algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 158-175.
    51. Jacobo Uña-Álvarez, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 414-418, September.
    52. Zu, Y., 2015. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Working Papers 15/02, Department of Economics, City University London.

  84. Jia Chen & Jiti Gao & Degui Li, 2009. "Semiparametric Regression Estimation in Null Recurrent Nonlinear Time Series," School of Economics and Public Policy Working Papers 2009-02, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Jiti Gao & Maxwell King, 2011. "A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors," Monash Econometrics and Business Statistics Working Papers 20/11, Monash University, Department of Econometrics and Business Statistics.
    2. Jiti Gao & Degui Li & Dag Tjøstheim, 2011. "Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series," Monash Econometrics and Business Statistics Working Papers 13/11, Monash University, Department of Econometrics and Business Statistics.
    3. Jiti Gao & Dag Tjøstheim & Jiying Yin, 2011. "Estimation in threshold autoregressive models with a stationary and a unit root regime," Monash Econometrics and Business Statistics Working Papers 21/11, Monash University, Department of Econometrics and Business Statistics.
    4. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    5. Toshio Honda, 2011. "Nonparametric LAD Cointegrating Regression," Global COE Hi-Stat Discussion Paper Series gd11-207, Institute of Economic Research, Hitotsubashi University.

  85. Jia Chen & Jiti Gao & Degui Li, 2009. "A New Diagnostic Test for Cross-Section Independence in Nonparametric Panel Data Model," School of Economics and Public Policy Working Papers 2009-16, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
    2. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    3. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
    4. Lee, Jungyoon & Robinson, Peter, 2015. "Panel nonparametric regression with fixed effects," LSE Research Online Documents on Economics 61431, London School of Economics and Political Science, LSE Library.
    5. Liu, Xiangling, 2019. "The income elasticity of housing demand in New South Wales, Australia," Regional Science and Urban Economics, Elsevier, vol. 75(C), pages 70-84.
    6. G. Pan & J. Gao & Y. Yang & M. Guo, 2012. "Independence Test for High Dimensional Random Vectors," Monash Econometrics and Business Statistics Working Papers 1/12, Monash University, Department of Econometrics and Business Statistics.
    7. Gao, Jiti & Pan, Guangming & Yang, Yanrong, 2012. "Testing Independence for a Large Number of High–Dimensional Random Vectors," MPRA Paper 45073, University Library of Munich, Germany, revised 15 Mar 2013.
    8. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.

  86. Jiti Gao & Qiying Wang & Jiying Yin, 2009. "Specification Testing in Nonlinear Time Series with Long-Range Dependence," School of Economics and Public Policy Working Papers 2009-04, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Phillips, Peter C.B. & Wang, Ying, 2022. "Functional coefficient panel modeling with communal smoothing covariates," Journal of Econometrics, Elsevier, vol. 227(2), pages 371-407.
    2. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    3. Jun Wang & Dianpeng Wang & Yubin Tian, 2022. "Multidimensional specification test based on non-stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 348-372, June.
    4. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2025. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Working Papers 202526, University of Macau, Faculty of Business Administration.
    5. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.
    6. Chaohua Dong & Jiti Gao, 2012. "Specification Testing Driven by Orthogonal Series in Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 20/12, Monash University, Department of Econometrics and Business Statistics.
    7. Chaohua Dong & Jiti Gao, 2014. "Specification Testing in Structural Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 2/14, Monash University, Department of Econometrics and Business Statistics.
    8. Xu Guo & Wangli Xu & Lixing Zhu, 2015. "Model checking for parametric regressions with response missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(2), pages 229-259, April.

  87. Jiti Gao & Maxwell King & Zudi Lu & Dag Tjøstheim, 2009. "Nonparametric Specification Testing for Nonlinear Time Series with Nonstationarity," School of Economics and Public Policy Working Papers 2009-03, University of Adelaide, School of Economics and Public Policy.

    Cited by:

    1. Jiti Gao & Maxwell King, 2012. "An Improved Nonparametric Unit-Root Test," Monash Econometrics and Business Statistics Working Papers 16/12, Monash University, Department of Econometrics and Business Statistics.
    2. Phillips, Peter C.B. & Wang, Ying, 2022. "Functional coefficient panel modeling with communal smoothing covariates," Journal of Econometrics, Elsevier, vol. 227(2), pages 371-407.
    3. Russell Davidson & Victoria Zinde‐Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
    4. Malikov, Emir & Sun, Yiguo, 2017. "Semiparametric estimation and testing of smooth coefficient spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 199(1), pages 12-34.
    5. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
    6. Jiti Gao & Maxwell King, 2011. "A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors," Monash Econometrics and Business Statistics Working Papers 20/11, Monash University, Department of Econometrics and Business Statistics.
    7. Jiti Gao & Degui Li & Dag Tjøstheim, 2011. "Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series," Monash Econometrics and Business Statistics Working Papers 13/11, Monash University, Department of Econometrics and Business Statistics.
    8. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    9. Auld, T., 2022. "Betting and financial markets are cointegrated on election night," Cambridge Working Papers in Economics 2263, Faculty of Economics, University of Cambridge.
    10. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    11. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2025. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Working Papers 202526, University of Macau, Faculty of Business Administration.
    12. Chen, Haiqiang & Fang, Ying & Li, Yingxing, 2013. "Estimation and inference for varying-coeffcient models with nonstationary regressors using penalized splines," SFB 649 Discussion Papers 2013-033, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    14. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    15. Yu-ting Bai & Xiao-yi Wang & Qian Sun & Xue-bo Jin & Xiao-kai Wang & Ting-li Su & Jian-lei Kong, 2019. "Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network," IJERPH, MDPI, vol. 16(20), pages 1-15, October.
    16. Jiti Gao & Dag Tjøstheim & Jiying Yin, 2011. "Estimation in threshold autoregressive models with a stationary and a unit root regime," Monash Econometrics and Business Statistics Working Papers 21/11, Monash University, Department of Econometrics and Business Statistics.
    17. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    18. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    19. Sepideh Mosaferi & Mark S. Kaiser, 2021. "Nonparametric Cointegrating Regression Functions with Endogeneity and Semi-Long Memory," Papers 2111.00972, arXiv.org, revised Jan 2025.
    20. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    21. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.
    22. Vasiliki Christou & Konstantinos Fokianos, 2014. "Quasi-Likelihood Inference For Negative Binomial Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 55-78, January.
    23. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    24. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    25. Chaohua Dong & Jiti Gao, 2012. "Specification Testing Driven by Orthogonal Series in Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 20/12, Monash University, Department of Econometrics and Business Statistics.
    26. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    27. Tu, Yundong & Liang, Han-Ying & Wang, Qiying, 2022. "Nonparametric inference for quantile cointegrations with stationary covariates," Journal of Econometrics, Elsevier, vol. 230(2), pages 453-482.
    28. Gan, Li & Hsiao, Cheng & Xu, Shu, 2014. "Model specification test with correlated but not cointegrated variables," Journal of Econometrics, Elsevier, vol. 178(P1), pages 80-85.
    29. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.
    30. Lin, Zhongjian & Li, Qi & Sun, Yiguo, 2014. "A consistent nonparametric test of parametric regression functional form in fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 167-179.

  88. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    3. Jiti Gao & Maxwell King, 2012. "An Improved Nonparametric Unit-Root Test," Monash Econometrics and Business Statistics Working Papers 16/12, Monash University, Department of Econometrics and Business Statistics.
    4. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression with Non- and Semi-Parametric Cointegration," Monash Econometrics and Business Statistics Working Papers 16/13, Monash University, Department of Econometrics and Business Statistics.
    5. Huang, Lei & Jiang, Hui & Wang, Huixia, 2019. "A novel partial-linear single-index model for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 110-122.
    6. Wang, Jianqiang C. & Holan, Scott H., 2012. "Bayesian multi-regime smooth transition regression with ordered categorical variables," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4165-4179.
    7. Guohua Feng & Jiti Gao & Fei Liu & Bin Peng, 2024. "Estimation and Inference for Three-Dimensional Panel Data Models," Papers 2404.08365, arXiv.org, revised Sep 2024.
    8. Malikov, Emir & Zhao, Shunan & Kumbhakar, Subal C., 2020. "Estimation of Firm-Level Productivity in the Presence of Exports: Evidence from China's Manufacturing," MPRA Paper 98077, University Library of Munich, Germany.
    9. Patrick W. Saart & Jiti Gao & David E. Allen, 2015. "Semiparametric Autoregressive Conditional Duration Model: Theory and Practice," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 849-881, December.
    10. Michael Wegener & Göran Kauermann, 2017. "Forecasting in nonlinear univariate time series using penalized splines," Statistical Papers, Springer, vol. 58(3), pages 557-576, September.
    11. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    12. Elliott Robert J. & Siu Tak Kuen & Lau John W., 2018. "A hidden Markov regime-switching smooth transition model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-21, September.
    13. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    14. Guohua Feng & Jiti Gao & Xiaohui Zhang, 2016. "Estimation of Technical Change and Price Elasticities: A Categorical Time-varying Coefficient Approach," Monash Econometrics and Business Statistics Working Papers 2/16, Monash University, Department of Econometrics and Business Statistics.
    15. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    16. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    17. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    18. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    19. Daniel J. Henderson & Christopher F. Parmeter & Liangjun Su, 2017. "M-Estimation of a Nonparametric Threshold Regression Model," Working Papers 2017-15, University of Miami, Department of Economics.
    20. Jiti Gao & Bin Peng & Yayi Yan, 2023. "A Localised Neural network with Dependent Data: Estimation and Inference," Monash Econometrics and Business Statistics Working Papers 15/23, Monash University, Department of Econometrics and Business Statistics.
    21. Biqing Cai & Chaohua Dong & Jiti Gao, 2015. "Orthogonal Series Estimation in Nonlinear Cointegrating Models with Endogeneity," Monash Econometrics and Business Statistics Working Papers 18/15, Monash University, Department of Econometrics and Business Statistics.
    22. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
    23. Jiti Gao & Maxwell King, 2011. "A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors," Monash Econometrics and Business Statistics Working Papers 20/11, Monash University, Department of Econometrics and Business Statistics.
    24. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    25. Jiti Gao & Degui Li & Dag Tjøstheim, 2011. "Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series," Monash Econometrics and Business Statistics Working Papers 13/11, Monash University, Department of Econometrics and Business Statistics.
    26. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    27. Gao, Jiti & Casas, Isabel, 2008. "Specification testing in discretized diffusion models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 131-140, November.
    28. Dursun Aydın & Ersin Yılmaz, 2021. "Semiparametric modeling of the right-censored time-series based on different censorship solution techniques," Empirical Economics, Springer, vol. 61(4), pages 2143-2172, October.
    29. Chen, Xiaohong & Huang, Zhuo & Yi, Yanping, 2021. "Efficient estimation of multivariate semi-nonparametric GARCH filtered copula models," Journal of Econometrics, Elsevier, vol. 222(1), pages 484-501.
    30. Xiaohong Chen & Wei Biao Wu & Yanping Yi, 2009. "Efficient Estimation of Copula-based Semiparametric Markov Models," Cowles Foundation Discussion Papers 1691, Cowles Foundation for Research in Economics, Yale University, revised Mar 2009.
    31. Feng, Guohua & McLaren, Keith R. & Yang, Ou & Zhang, Xiaohui & Zhao, Xueyan, 2021. "The impact of environmental policy stringency on industrial productivity growth: A semi-parametric study of OECD countries," Energy Economics, Elsevier, vol. 100(C).
    32. Chad Brown, 2024. "Inference in Partially Linear Models under Dependent Data with Deep Neural Networks," Papers 2410.22574, arXiv.org.
    33. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    34. Tae-Hwy Lee & Yundong Tu & Aman Ullah, 2014. "Forecasting Equity Premium: Global Historical Average versus Local Historical Average and Constraints," Working Papers 201405, University of California at Riverside, Department of Economics.
    35. Polonik, Wolfgang & Yao, Qiwei, 2008. "Testing for multivariate volatility functions using minimum volume sets and inverse regression," Journal of Econometrics, Elsevier, vol. 147(1), pages 151-162, November.
    36. Kim, Namhyun & W. Saart, Patrick, 2021. "Estimation in partially linear semiparametric models with parametric and/or nonparametric endogeneity," Cardiff Economics Working Papers E2021/9, Cardiff University, Cardiff Business School, Economics Section.
    37. Chad Brown, 2024. "Statistical Properties of Deep Neural Networks with Dependent Data," Papers 2410.11113, arXiv.org, revised Jan 2025.
    38. Gao, Jiti & McAleer, Michael & Allen, David E., 2008. "Econometric modelling in finance and risk management: An overview," Journal of Econometrics, Elsevier, vol. 147(1), pages 1-4, November.
    39. Maria Mohr & Natalie Neumeyer, 2021. "Nonparametric volatility change detection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 529-548, June.
    40. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    41. Anna Bykhovskaya & James A. Duffy, 2022. "The Local to Unity Dynamic Tobit Model," Papers 2210.02599, arXiv.org, revised May 2024.
    42. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    43. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    44. Zongwu Cai & Zhijie Xiao, 2010. "Semiparametric Quantile Regression Estimation in Dynamic Models with Partially Varying Coefficients," Boston College Working Papers in Economics 761, Boston College Department of Economics.
    45. Jia Chen & Jiti Gao & Degui Li, 2010. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," School of Economics and Public Policy Working Papers 2010-09, University of Adelaide, School of Economics and Public Policy.
    46. Qiu, Jia & Li, Degao & You, Jinhong, 2015. "SCAD-penalized regression for varying-coefficient models with autoregressive errors," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 100-118.
    47. Raushan Kumar, 2017. "Price Discovery in Some Primary Commodity Markets in India," Economics Bulletin, AccessEcon, vol. 37(3), pages 1817-1829.
    48. Xiaohong Chen & . . & Yixiao Sun, 2012. "Sieve inference on semi-nonparametric time series models," CeMMAP working papers 06/12, Institute for Fiscal Studies.
    49. Jiti Gao & Dag Tjøstheim & Jiying Yin, 2011. "Estimation in threshold autoregressive models with a stationary and a unit root regime," Monash Econometrics and Business Statistics Working Papers 21/11, Monash University, Department of Econometrics and Business Statistics.
    50. Bontempi, Gianluca & Ben Taieb, Souhaib, 2011. "Conditionally dependent strategies for multiple-step-ahead prediction in local learning," International Journal of Forecasting, Elsevier, vol. 27(3), pages 689-699, July.
    51. Yan Li & Liangjun Su & Yuewu Xu, 2014. "A Combined Approach to the Inference of Conditional Factor Models," Working Papers 10-2014, Singapore Management University, School of Economics.
    52. Martins-Filho, Carlos & Yao, Feng & Torero, Maximo, 2018. "Nonparametric Estimation Of Conditional Value-At-Risk And Expected Shortfall Based On Extreme Value Theory," Econometric Theory, Cambridge University Press, vol. 34(1), pages 23-67, February.
    53. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    54. Jiti Gao & Fei Liu & Bin Peng & Yanrong Yang, 2024. "Localized Neural Network Modelling of Time Series: A Case Study on US Monetary Policy," Monash Econometrics and Business Statistics Working Papers 14/24, Monash University, Department of Econometrics and Business Statistics.
    55. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    56. Francesco Bravo & Ba M. Chu & David T. Jacho-Chávez, 2017. "Semiparametric estimation of moment condition models with weakly dependent data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(1), pages 108-136, January.
    57. Degui Li & Jia Chen & Zhengyan Lin, 2009. "Variable selection in partially time-varying coefficient models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(5), pages 553-566.
    58. Jia Chen & Jiti Gao & Degui Li, 2011. "Estimation in Partially Linear Single-Index Panel Data Models with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 14/11, Monash University, Department of Econometrics and Business Statistics.
    59. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    60. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    61. Xiaohong Chen & Zhipeng Liao & Yixiao Sun, 2012. "Sieve Inference on Semi-nonparametric Time Series Models," Cowles Foundation Discussion Papers 1849, Cowles Foundation for Research in Economics, Yale University.
    62. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    63. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2013. "Nonparametric Estimation and Parametric Calibration of Time-Varying Coefficient Realized Volatility Models," Monash Econometrics and Business Statistics Working Papers 21/13, Monash University, Department of Econometrics and Business Statistics.
    64. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.
    65. Chen, Xiaohong & Liao, Zhipeng & Sun, Yixiao, 2014. "Sieve inference on possibly misspecified semi-nonparametric time series models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 639-658.
    66. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    67. Bykhovskaya, Anna & Duffy, James A., 2024. "The local to unity dynamic Tobit model," Journal of Econometrics, Elsevier, vol. 241(2).
    68. Phillips, Peter C.B., 2009. "Local Limit Theory And Spurious Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1466-1497, December.
    69. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    70. Neumeyer, Natalie & Omelka, Marek & Hudecová, Šárka, 2019. "A copula approach for dependence modeling in multivariate nonparametric time series," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 139-162.
    71. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    72. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    73. Xiaohong Chen & Zhuo Huang & Yanping Yi, 2019. "Efficient Estimation of Multivariate Semi-nonparametric GARCH Filtered Copula Models," Cowles Foundation Discussion Papers 2215, Cowles Foundation for Research in Economics, Yale University.
    74. Peng, Rong & Lu, Zudi, 2024. "Semiparametric Averaging of Nonlinear Marginal Logistic Regressions and Forecasting for Time Series Classification," Econometrics and Statistics, Elsevier, vol. 31(C), pages 19-37.
    75. Tae Kim & Zhi-Ming Luo & Chiho Kim, 2011. "The central limit theorem for degenerate variable -statistics under dependence," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 683-699.
    76. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    77. Jirak, Moritz, 2012. "Change-point analysis in increasing dimension," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 136-159.
    78. Christian Gourieroux & Hung T. Nguyen & Songsak Sriboonchitta, 2017. "Nonparametric estimation of a scalar diffusion model from discrete time data: a survey," Annals of Operations Research, Springer, vol. 256(2), pages 203-219, September.
    79. S. Yaser Samadi & Tharindu P. De Alwis, 2023. "Fourier Methods for Sufficient Dimension Reduction in Time Series," Papers 2312.02110, arXiv.org.
    80. Chaohua Dong & Jiti Gao, 2012. "Specification Testing Driven by Orthogonal Series in Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 20/12, Monash University, Department of Econometrics and Business Statistics.
    81. Arteaga-Molina, Luis A. & Rodríguez-Poo, Juan M., 2019. "Empirical likelihood based inference for a categorical varying-coefficient panel data model with fixed effects," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 110-124.
    82. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    83. Jia Chen & Degui Li & Hua Liang & Suojin Wang, 2014. "Semiparametric GEE Analysis in Partially Linear Single-Index Models for Longitudinal Data," Discussion Papers 14/26, Department of Economics, University of York.
    84. Chaohua Dong & Jiti Gao, 2012. "Expansion of Lévy Process Functionals and Its Application in Statistical Estimation," Monash Econometrics and Business Statistics Working Papers 2/12, Monash University, Department of Econometrics and Business Statistics.
    85. Wang, Xiaoguang & Lu, Dawei & Song, Lixin, 2013. "Statistical inference for partially linear stochastic models with heteroscedastic errors," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 150-160.
    86. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    87. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection in Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 14/14, Monash University, Department of Econometrics and Business Statistics.
    88. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression," Cowles Foundation Discussion Papers 1911, Cowles Foundation for Research in Economics, Yale University.
    89. Chen, Jia & Li, Degui & Zhang, Lixin, 2010. "Robust estimation in a nonlinear cointegration model," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 706-717, March.
    90. Zhenyu Jiang & Nengxiang Ling & Zudi Lu & Dag Tj⊘stheim & Qiang Zhang, 2020. "On bandwidth choice for spatial data density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 817-840, July.
    91. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.
    92. Pipat Wongsaart & Jiti Gao, 2011. "Nonparametric Kernel Testing in Semiparametric Autoregressive Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 18/11, Monash University, Department of Econometrics and Business Statistics.
    93. Chaohua Dong & Jiti Gao, 2013. "Orthogonal Expansion of Levy Process Functionals: Theory and Practice," Monash Econometrics and Business Statistics Working Papers 3/13, Monash University, Department of Econometrics and Business Statistics.
    94. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.
    95. Lee, Jungyoon & Robinson, Peter M., 2015. "Panel nonparametric regression with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 346-362.
    96. Toshio Honda, 2011. "Nonparametric LAD Cointegrating Regression," Global COE Hi-Stat Discussion Paper Series gd11-207, Institute of Economic Research, Hitotsubashi University.
    97. Degao Li & Guodong Li & Jinhong You, 2014. "Significant Variable Selection And Autoregressive Order Determination For Time-Series Partially Linear Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 478-490, August.
    98. Giovanni Ballarin, 2023. "Impulse Response Analysis of Structural Nonlinear Time Series Models," Papers 2305.19089, arXiv.org, revised Feb 2025.
    99. Jiti Gao, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 459-463, September.
    100. Chaohua Dong & Jiti Gao, 2011. "Expansion of Brownian Motion Functionals and Its Application in Econometric Estimation," Monash Econometrics and Business Statistics Working Papers 19/11, Monash University, Department of Econometrics and Business Statistics.

  89. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007.

    Cited by:

    1. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.

  90. Casas, Isabel & Gao, Jiti, 2006. "Econometric estimation in long-range dependent volatility models: Theory and practice," MPRA Paper 11981, University Library of Munich, Germany, revised Aug 2007.

    Cited by:

    1. Ugur, Mehmet & Vivarelli, Marco, 2020. "Innovation, firm survival and productivity: The state of the art," Greenwich Papers in Political Economy 28308, University of Greenwich, Greenwich Political Economy Research Centre.
    2. Mehmet Ugur & Marco Vivarelli, 2020. "Technology, industrial dynamics and productivity: a critical survey," DISCE - Working Papers del Dipartimento di Politica Economica dipe0011, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    3. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Estimation of Long Memory in Integrated Variance," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 785-814, October.
    4. Ugur, Mehmet & Trushin, Eshref & Solomon, Edna, 2016. "Inverted-U relationship between R&D intensity and survival: evidence on scale and complementarity effects in UK data," Greenwich Papers in Political Economy 15510, University of Greenwich, Greenwich Political Economy Research Centre.
    5. Sung Ik Kim, 2022. "ARMA–GARCH model with fractional generalized hyperbolic innovations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    6. Henghsiu Tsai & Heiko Rachinger & Edward M.H. Lin, 2015. "Inference of Seasonal Long-memory Time Series with Measurement Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 137-154, March.
    7. Xu, Weijun & Sun, Qi & Xiao, Weilin, 2012. "A new energy model to capture the behavior of energy price processes," Economic Modelling, Elsevier, vol. 29(5), pages 1585-1591.
    8. Ugur, Mehment & Vivarelli, Marco, 2020. "The role of innovation in industrial dynamics and productivity growth: a survey of the literature," GLO Discussion Paper Series 648, Global Labor Organization (GLO).
    9. Lavancier, Frédéric & Philippe, Anne & Surgailis, Donatas, 2010. "A two-sample test for comparison of long memory parameters," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2118-2136, October.
    10. Zhibiao Zhao & Yiyun Zhang & Runze Li, 2014. "Non-Parametric Estimation Under Strong Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 4-15, January.
    11. Alexandra Chronopoulou & Frederi Viens, 2012. "Estimation and pricing under long-memory stochastic volatility," Annals of Finance, Springer, vol. 8(2), pages 379-403, May.
    12. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
    13. Li, Hongjun & Li, Qi & Liu, Ruixuan, 2016. "Consistent model specification tests based on k-nearest-neighbor estimation method," Journal of Econometrics, Elsevier, vol. 194(1), pages 187-202.
    14. Sun, Qi & Xu, Weijun & Xiao, Weilin, 2013. "An empirical estimation for mean-reverting coal prices with long memory," Economic Modelling, Elsevier, vol. 33(C), pages 174-181.

  91. Gao, Jiti & Casas, Isabel, 2006. "Specification testing in discretized diffusion models: Theory and practice," MPRA Paper 11980, University Library of Munich, Germany, revised Aug 2007.

    Cited by:

    1. Tianshun Yan & Changlin Mei, 2017. "A test for a parametric form of the volatility in second-order diffusion models," Computational Statistics, Springer, vol. 32(4), pages 1583-1596, December.
    2. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    3. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
    4. Jun Wang & Dianpeng Wang & Yubin Tian, 2022. "Multidimensional specification test based on non-stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 348-372, June.
    5. Álvarez-Liébana, J. & López-Pérez, A. & González-Manteiga, W. & Febrero-Bande, M., 2025. "A goodness-of-fit test for functional time series with applications to Ornstein-Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
    6. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    7. Zhang, Shulin & Song, Peter X.-K. & Shi, Daimin & Zhou, Qian M., 2012. "Information ratio test for model misspecification on parametric structures in stochastic diffusion models," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3975-3987.
    8. Monsalve-Cobis, Abelardo & González-Manteiga, Wenceslao & Febrero-Bande, Manuel, 2011. "Goodness-of-fit test for interest rate models: An approach based on empirical processes," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3073-3092, December.
    9. A. López-Pérez & M. Febrero-Bande & W. González-Manteiga, 2025. "Estimation and specification test for diffusion models with stochastic volatility," Statistical Papers, Springer, vol. 66(2), pages 1-36, February.

  92. Dong, Chaohua & Gao, Jiti & Tong, Howell, 2006. "Semiparametric penalty function method in partially linear model selection," MPRA Paper 11975, University Library of Munich, Germany, revised Aug 2006.

    Cited by:

    1. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.

  93. Gao, Jiti & McAleer, Michael & Allen, Dave, 2006. "Econometric modelling in finance and risk management: An overview," MPRA Paper 11978, University Library of Munich, Germany, revised Nov 2007.

    Cited by:

    1. Arnaud Dufays & Jeroen V. K. Rombouts, 2019. "Sparse Change-point HAR Models for Realized Variance," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 857-880, September.

  94. Chen, Song Xi & Gao, Jiti & Tang, Chenghong, 2005. "A test for model specification of diffusion processes," MPRA Paper 11976, University Library of Munich, Germany, revised Feb 2007.

    Cited by:

    1. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    2. Xu, Ke-Li, 2009. "Empirical likelihood-based inference for nonparametric recurrent diffusions," Journal of Econometrics, Elsevier, vol. 153(1), pages 65-82, November.
    3. Choi, Hwan-sik & Jeong, Minsoo & Park, Joon Y., 2014. "An asymptotic analysis of likelihood-based diffusion model selection using high frequency data," Journal of Econometrics, Elsevier, vol. 178(P3), pages 539-557.
    4. Gao, Jiti & Casas, Isabel, 2008. "Specification testing in discretized diffusion models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 131-140, November.
    5. Chen, Bin & Hong, Yongmiao, 2011. "Generalized spectral testing for multivariate continuous-time models," Journal of Econometrics, Elsevier, vol. 164(2), pages 268-293, October.
    6. Kristensen, Dennis, 2011. "Semi-nonparametric estimation and misspecification testing of diffusion models," Journal of Econometrics, Elsevier, vol. 164(2), pages 382-403, October.
    7. Zou, Tao & Chen, Song Xi, 2014. "Enhancing Estimation for Interest Rate Diffusion Models with Bond Prices," MPRA Paper 67073, University Library of Munich, Germany, revised Apr 2015.
    8. Song, Zhaogang, 2011. "A martingale approach for testing diffusion models based on infinitesimal operator," Journal of Econometrics, Elsevier, vol. 162(2), pages 189-212, June.
    9. Vance Martin & Yoshihiko Nishiyama & John Stachurski, 2011. "A Goodness Of Fit Test For Ergodic Markov Processes," KIER Working Papers 787, Kyoto University, Institute of Economic Research.
    10. Fan, Jianqing & Fan, Yingying & Jiang, Jiancheng, 2007. "Dynamic Integration of Time- and State-Domain Methods for Volatility Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 618-631, June.
    11. Monsalve-Cobis, Abelardo & González-Manteiga, Wenceslao & Febrero-Bande, Manuel, 2011. "Goodness-of-fit test for interest rate models: An approach based on empirical processes," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3073-3092, December.
    12. Lin, Liang-Ching & Lee, Sangyeol & Guo, Meihui, 2013. "Goodness-of-fit test for stochastic volatility models," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 473-498.
    13. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    14. Jianqing Fan & Yingying Fan & Jinchi Lv, 0. "Aggregation of Nonparametric Estimators for Volatility Matrix," Journal of Financial Econometrics, Oxford University Press, vol. 5(3), pages 321-357.
    15. Song Chen & Ingrid Van Keilegom, 2009. "Rejoinder on: A review on empirical likelihood methods for regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(3), pages 468-474, November.

  95. Arapis, Manuel & Gao, Jiti, 2004. "Empirical comparisons in short-term interest rate models using nonparametric methods," MPRA Paper 11974, University Library of Munich, Germany, revised 23 Dec 2005.

    Cited by:

    1. Nikolay Gospodinov & Masayuki Hirukawa, 2008. "Nonparametric Estimation of Scalar Diffusion Processes of Interest Rates Using Asymmetric Kernels," Working Papers 08011, Concordia University, Department of Economics, revised Dec 2008.
    2. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    3. Casas, Isabel & Gao, Jiti, 2008. "Econometric estimation in long-range dependent volatility models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 72-83, November.
    4. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    5. Xin Wang, 2017. "Online Kernel estimation of stationary stochastic diffusion models," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1089-1103, July.
    6. Gutiérrez, R. & Gutiérrez-Sánchez, R. & Nafidi, A., 2009. "The trend of the total stock of the private car-petrol in Spain: Stochastic modelling using a new gamma diffusion process," Applied Energy, Elsevier, vol. 86(1), pages 18-24, January.
    7. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
    8. Gao, Jiti & Casas, Isabel, 2008. "Specification testing in discretized diffusion models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 131-140, November.
    9. Álvarez-Liébana, J. & López-Pérez, A. & González-Manteiga, W. & Febrero-Bande, M., 2025. "A goodness-of-fit test for functional time series with applications to Ornstein-Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
    10. Muhammad Hanif, 2011. "Reweighted Nadaraya-Watson estimator of scalar diffusion models by using asymmetric kernels," Far East Journal of Psychology and Business, Far East Research Centre, vol. 4(5), pages 53-69, July.
    11. Peroni Chiara, 2009. "A Non-Parametric Investigation of Risk Premia," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(4), pages 1-52, September.
    12. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    13. Zhang, Shulin & Song, Peter X.-K. & Shi, Daimin & Zhou, Qian M., 2012. "Information ratio test for model misspecification on parametric structures in stochastic diffusion models," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3975-3987.
    14. Seungmoon Choi, 2011. "Closed-Form Likelihood Expansions for Multivariate Time-Inhomogeneous Diffusions," School of Economics and Public Policy Working Papers 2011-26, University of Adelaide, School of Economics and Public Policy.
    15. Yedidya Rabinovitz, 2017. "A new S.D.E. and instantaneous mean reversion rate formula (presented via a numerical empirical model comparison)," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(02n03), pages 1-22, June.
    16. Charlotte Christiansen, 2008. "Mean Reversion in US and International Short Rates," CREATES Research Papers 2008-47, Department of Economics and Business Economics, Aarhus University.
    17. Al-Zoubi, Haitham A., 2019. "Bond and option prices with permanent shocks," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 272-290.
    18. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    19. Somvang PHIMMAVONG & Ian FERGUSON & Barbara OZARSKA, 2010. "Economy-Wide Impact of Forest Plantation Development in Laos Using a Dynamic General Equilibrium Approach," EcoMod2010 259600131, EcoMod.
    20. Monsalve-Cobis, Abelardo & González-Manteiga, Wenceslao & Febrero-Bande, Manuel, 2011. "Goodness-of-fit test for interest rate models: An approach based on empirical processes," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3073-3092, December.
    21. Li, Minqiang, 2010. "A damped diffusion framework for financial modeling and closed-form maximum likelihood estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 132-157, February.
    22. A. López-Pérez & M. Febrero-Bande & W. González-Manteiga, 2025. "Estimation and specification test for diffusion models with stochastic volatility," Statistical Papers, Springer, vol. 66(2), pages 1-36, February.
    23. Ye, Xu-Guo & Lin, Jin-Guan & Zhao, Yan-Yong & Hao, Hong-Xia, 2015. "Two-step estimation of the volatility functions in diffusion models with empirical applications," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 135-159.
    24. Yamamura, Mariko & Shoji, Isao, 2010. "A nonparametric method of multi-step ahead forecasting in diffusion processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2408-2415.
    25. Al-Zoubi, Haitham A., 2009. "Short-term spot rate models with nonparametric deterministic drift," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 731-747, August.
    26. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    27. Gospodinov, Nikolay & Hirukawa, Masayuki, 2012. "Nonparametric estimation of scalar diffusion models of interest rates using asymmetric kernels," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 595-609.
    28. Gao, Jiti & Gijbels, Irene, 2005. "Bandwidth selection for nonparametric kernel testing," MPRA Paper 11982, University Library of Munich, Germany, revised Jun 2007.

  96. Jiti Gao & Maxwell King, 2004. "Model Specification Testing in Nonparametric and Semiparametric Time Series Econometric Models," Econometric Society 2004 North American Winter Meetings 225, Econometric Society.

    Cited by:

    1. Fernandes, Marcelo, 2001. "Nonparametric entropy-based tests of independence between stochastic processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 413, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Semiparametric spatial regression: theory and practice," MPRA Paper 11991, University Library of Munich, Germany, revised Oct 2006.
    3. Amaro de Matos, Joao & Fernandes, Marcelo, 2007. "Testing the Markov property with high frequency data," Journal of Econometrics, Elsevier, vol. 141(1), pages 44-64, November.
    4. Juan Carlos Escanciano, 2006. "Joint Diagnostic Tests for Conditional Mean and Variance Specifications," Faculty Working Papers 02/06, School of Economics and Business Administration, University of Navarra.

  97. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.

    Cited by:

    1. El Ghouch, Anouar & Genton, Marc G. & Bouezmarni , Taoufik, 2012. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," LIDAM Discussion Papers ISBA 2012001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  98. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Estimation in semiparametric spatial regression," MPRA Paper 11971, University Library of Munich, Germany.

    Cited by:

    1. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    2. Tang Qingguo, 2013. "B-spline estimation for semiparametric varying-coefficient partially linear regression with spatial data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 361-378, June.
    3. Tang Qingguo & Cheng Longsheng, 2010. "B-spline estimation for spatial data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 197-217.
    4. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    5. Kunpeng Li & Degui Li & Zhongwen Liang & Cheng Hsiao, 2017. "Estimation of semi-varying coefficient models with nonstationary regressors," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 354-369, March.

  99. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Semiparametric spatial regression: theory and practice," MPRA Paper 11991, University Library of Munich, Germany, revised Oct 2006.

    Cited by:

    1. Saeed Alaei & Ali Makhdoumi & Azarakhsh Malekian & Saša Pekeč, 2022. "Revenue-Sharing Allocation Strategies for Two-Sided Media Platforms: Pro-Rata vs. User-Centric," Management Science, INFORMS, vol. 68(12), pages 8699-8721, December.
    2. Yiwei Chen & Vivek F. Farias, 2018. "Robust Dynamic Pricing with Strategic Customers," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1119-1142, November.
    3. Ruomeng Cui & Hyoduk Shin, 2018. "Sharing Aggregate Inventory Information with Customers: Strategic Cross-Selling and Shortage Reduction," Management Science, INFORMS, vol. 64(1), pages 381-400, January.
    4. Maxime C. Cohen & Ruben Lobel & Georgia Perakis, 2016. "The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption," Management Science, INFORMS, vol. 62(5), pages 1235-1258, May.
    5. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Estimation in semiparametric spatial regression," MPRA Paper 11979, University Library of Munich, Germany, revised Jul 2005.
    6. Ken Moon & Kostas Bimpikis & Haim Mendelson, 2018. "Randomized Markdowns and Online Monitoring," Management Science, INFORMS, vol. 64(3), pages 1271-1290, March.
    7. Mehmet Altin, 2017. "A taxonomy of hotel revenue management implementation strategies," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(3), pages 246-264, June.
    8. Rajib L. Saha & Sumanta Singha & Subodha Kumar, 2021. "Does Congestion Always Hurt? Managing Discount Under Congestion in a Game-Theoretic Setting," Information Systems Research, INFORMS, vol. 32(4), pages 1347-1367, December.
    9. Mohammad Vardi & Ali Salmasnia & Ali Ghorbanian & Hadi Mokhtari, 2016. "A bi-objective airline revenue management problem with possible cancellation," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 8(1), pages 20-37.
    10. Henry Lam & Clementine Mottet, 2017. "Tail Analysis Without Parametric Models: A Worst-Case Perspective," Operations Research, INFORMS, vol. 65(6), pages 1696-1711, December.

  100. Gao, Jiti & Tong, Howell, 2002. "Nonparametric and semiparametric regression model selection," MPRA Paper 11987, University Library of Munich, Germany, revised Feb 2004.

    Cited by:

    1. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    2. Dong, Chaohua & Gao, Jiti & Tong, Howell, 2006. "Semiparametric penalty function method in partially linear model selection," MPRA Paper 11975, University Library of Munich, Germany, revised Aug 2006.

  101. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.

    Cited by:

    1. Zhangong Zhou & Linjun Tang, 2019. "Testing for parametric component of partially linear models with missing covariates," Statistical Papers, Springer, vol. 60(3), pages 747-760, June.
    2. You, Jinhong & Zhou, Xian, 2005. "The law of iterated logarithm of estimators for partially linear panel data models," Statistics & Probability Letters, Elsevier, vol. 75(4), pages 267-279, December.
    3. Gao, Jiti & Tong, Howell & Wolff, Rodney, 2002. "Model Specification Tests in Nonparametric Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 324-359, November.
    4. Xin Geng & Carlos Martins-Filho & Feng Yao, 2018. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 18-05, Department of Economics, West Virginia University.
    5. Pateiro-López, Beatriz & González-Manteiga, Wenceslao, 2006. "Multivariate partially linear models," Statistics & Probability Letters, Elsevier, vol. 76(14), pages 1543-1549, August.
    6. Xuejun Ma & Yue Du & Jingli Wang, 2022. "Model detection and variable selection for mode varying coefficient model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 321-341, June.
    7. Jiti Gao & Peter C. B. Phillips, 2010. "Semiparametric Estimation in Time Series of Simultaneous Equations," Cowles Foundation Discussion Papers 1769, Cowles Foundation for Research in Economics, Yale University.
    8. Du, Pang & Cheng, Guang & Liang, Hua, 2012. "Semiparametric regression models with additive nonparametric components and high dimensional parametric components," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2006-2017.
    9. Jianhong Shi & Fanrong Zhao, 2018. "Statistical inference for heteroscedastic semi-varying coefficient EV models under restricted condition," Statistical Papers, Springer, vol. 59(2), pages 487-511, June.
    10. Bianco, Ana M. & Boente, Graciela & González-Manteiga, Wenceslao & Pérez-González, Ana, 2015. "Robust inference in partially linear models with missing responses," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 88-98.
    11. Kim, Kun Ho & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function," IRTG 1792 Discussion Papers 2020-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. B. Ettinger & S. Perotto & L. M. Sangalli, 2016. "Spatial regression models over two-dimensional manifolds," Biometrika, Biometrika Trust, vol. 103(1), pages 71-88.
    13. Boente, Graciela & Salibian-Barrera, Matías & Vena, Pablo, 2020. "Robust estimation for semi-functional linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    14. Yunlu Jiang, 2015. "Robust estimation in partially linear regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2497-2508, November.
    15. Zhou, Jianjun & Chen, Min, 2012. "Spline estimators for semi-functional linear model," Statistics & Probability Letters, Elsevier, vol. 82(3), pages 505-513.
    16. Patrick W. Saart & Jiti Gao & David E. Allen, 2015. "Semiparametric Autoregressive Conditional Duration Model: Theory and Practice," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 849-881, December.
    17. Shang, Suoping & Zou, Changliang & Wang, Zhaojun, 2012. "Local Walsh-average regression for semiparametric varying-coefficient models," Statistics & Probability Letters, Elsevier, vol. 82(10), pages 1815-1822.
    18. M. Arashi & Mahdi Roozbeh, 2019. "Some improved estimation strategies in high-dimensional semiparametric regression models with application to riboflavin production data," Statistical Papers, Springer, vol. 60(3), pages 667-686, June.
    19. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    20. Guozhi Hu & Weihu Cheng & Jie Zeng, 2023. "Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data," Mathematics, MDPI, vol. 11(3), pages 1-21, February.
    21. Zhang, Jun & Lin, Bingqing & Zhou, Yan, 2021. "Kernel density estimation for partial linear multivariate responses models," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    22. Hsiao-Hsian Gao & Li-Shan Huang, 2016. "Sample size planning for testing significance of curves," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(11), pages 2019-2028, August.
    23. A. Delaigle & P. Hall & J. R. Wishart, 2014. "New approaches to nonparametric and semiparametric regression for univariate and multivariate group testing data," Biometrika, Biometrika Trust, vol. 101(3), pages 567-585.
    24. Raúl Sergio González Treviño, 2003. "Dividends and the Agency Cost of Free Cash Flows," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 1-18, May.
    25. Yang, Lijian & Park, Byeong U. & Xue, Lan & Härdle, Wolfgang Karl, 2005. "Estimation and testing for varying coefficients in additive models with marginal integration," SFB 649 Discussion Papers 2005-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    26. Dette, Holger & Marchlewski, Mareen, 2007. "A test for the parametric form of the variance function in apartial linear regression model," Technical Reports 2007,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    27. Jean‐Pierre Florens & Jan Johannes & Sébastien Van Bellegem, 2012. "Instrumental regression in partially linear models," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 304-324, June.
    28. Raheem, S.M. Enayetur & Ahmed, S. Ejaz & Doksum, Kjell A., 2012. "Absolute penalty and shrinkage estimation in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 874-891.
    29. Xiaochao Xia, 2021. "Model averaging prediction for nonparametric varying-coefficient models with B-spline smoothing," Statistical Papers, Springer, vol. 62(6), pages 2885-2905, December.
    30. Robinson, Peter M. & Thawornkaiwong, Supachoke, 2012. "Statistical inference on regression with spatial dependence," Journal of Econometrics, Elsevier, vol. 167(2), pages 521-542.
    31. Ana M. Bianco & Graciela Boente & Wenceslao González-Manteiga & Ana Pérez-González, 2019. "Plug-in marginal estimation under a general regression model with missing responses and covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 106-146, March.
    32. Daniel Becker & Alois Kneip & Valentin Patilea, 2021. "Semiparametric inference for partially linear regressions with Box-Cox transformation," Papers 2106.10723, arXiv.org.
    33. Sigve Hovda, 2014. "Using pseudometrics in kernel density estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 669-696, December.
    34. Boente, Graciela & Rodriguez, Daniela, 2010. "Robust inference in generalized partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2942-2966, December.
    35. Yixin Fang & Heng Lian & Hua Liang, 2018. "A generalized partially linear framework for variance functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1147-1175, October.
    36. You, Jinhong & Chen, Gemai, 2006. "Estimation of a semiparametric varying-coefficient partially linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 324-341, February.
    37. Hongwei Shi & Weichao Yang & Bowen Sun & Xu Guo, 2025. "Tests for high-dimensional partially linear regression models," Statistical Papers, Springer, vol. 66(3), pages 1-23, April.
    38. Sang, Peijun & Lockhart, Richard A. & Cao, Jiguo, 2018. "Sparse estimation for functional semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 105-118.
    39. Huang, Zhensheng & Zhang, Riquan, 2009. "Empirical likelihood for nonparametric parts in semiparametric varying-coefficient partially linear models," Statistics & Probability Letters, Elsevier, vol. 79(16), pages 1798-1808, August.
    40. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.
    41. Shuping Jiang & Lan Xue, 2015. "Globally consistent model selection in semi-parametric additive coefficient models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(4), pages 532-551, December.
    42. Ma, Xin & Deng, Yanqiao & Ma, Minda, 2024. "A novel kernel ridge grey system model with generalized Morlet wavelet and its application in forecasting natural gas production and consumption," Energy, Elsevier, vol. 287(C).
    43. You, Jinhong & Zhou, Xian, 2006. "Statistical inference in a panel data semiparametric regression model with serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 844-873, April.
    44. Gao, jiti & Anh, vo & Heyde, christopher, 1999. "Statistical estimation of nonstationaryGaussian processes with long-range dependence and intermittency," MPRA Paper 11972, University Library of Munich, Germany, revised 23 Oct 2001.
    45. Härdle, Wolfgang & Liang, Hua & Sommerfeld, Volker, 1997. "Bootstrap approximations in a partially linear regression model," SFB 373 Discussion Papers 1997,102, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    46. Boente, Graciela & Vahnovan, Alejandra, 2017. "Robust estimators in semi-functional partial linear regression models," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 59-84.
    47. Bogomolov, Marina & Davidov, Ori, 2019. "Order restricted univariate and multivariate inference with adjustment for covariates in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 20-27.
    48. Feng Yao & Junsen Zhang, 2015. "Efficient kernel-based semiparametric IV estimation with an application to resolving a puzzle on the estimates of the return to schooling," Empirical Economics, Springer, vol. 48(1), pages 253-281, February.
    49. Lian, Heng & Liang, Hua, 2016. "Separation of linear and index covariates in partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 56-70.
    50. Guo-Liang Fan & Han-Ying Liang & Jiang-Feng Wang, 2013. "Empirical likelihood for heteroscedastic partially linear errors-in-variables model with α-mixing errors," Statistical Papers, Springer, vol. 54(1), pages 85-112, February.
    51. Yang, Hu & Li, Tingting, 2010. "Empirical likelihood for semiparametric varying coefficient partially linear models with longitudinal data," Statistics & Probability Letters, Elsevier, vol. 80(2), pages 111-121, January.
    52. Kim, Namhyun & W. Saart, Patrick, 2021. "Estimation in partially linear semiparametric models with parametric and/or nonparametric endogeneity," Cardiff Economics Working Papers E2021/9, Cardiff University, Cardiff Business School, Economics Section.
    53. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    54. Roozbeh, Mahdi, 2016. "Robust ridge estimator in restricted semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 127-144.
    55. Przystalski, Marcin, 2014. "Estimation of the covariance matrix in multivariate partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 380-385.
    56. Cui, Xia & Lu, Ying & Peng, Heng, 2017. "Estimation of partially linear regression models under the partial consistency property," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 103-121.
    57. Xiuli Wang & Gaorong Li & Lu Lin, 2011. "Empirical likelihood inference for semi-parametric varying-coefficient partially linear EV models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(2), pages 171-185, March.
    58. Lan, Wei & Ding, Yue & Fang, Zheng & Fang, Kuangnan, 2016. "Testing covariates in high dimension linear regression with latent factors," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 25-37.
    59. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2012. "Inference on treatment effects after selection amongst high-dimensional controls," CeMMAP working papers CWP10/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    60. Marcelo M. Taddeo & Pedro A. Morettin, 2023. "Bayesian P-Splines Applied to Semiparametric Models with Errors Following a Scale Mixture of Normals," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 1331-1355, August.
    61. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    62. Wei Lan & Ronghua Luo & Chih-Ling Tsai & Hansheng Wang & Yunhong Yang, 2015. "Testing the Diagonality of a Large Covariance Matrix in a Regression Setting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 76-86, January.
    63. Mou, Xichen & Wang, Dewei, 2024. "Additive partially linear model for pooled biomonitoring data," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
    64. Radhey S. Singh & Lichun Wang, 2012. "A Note on Estimation in Seemingly Unrelated Semi-Parametric Regression Models," Journal of Quantitative Economics, The Indian Econometric Society, vol. 10(1), pages 56-69, January.
    65. Liang, Hua, 2006. "Estimation in partially linear models and numerical comparisons," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 675-687, February.
    66. You, Jinhong & Chen, Gemai & Zhou, Yong, 2007. "Statistical inference of partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 98(8), pages 1539-1557, September.
    67. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    68. Xiaohong Chen & . . & Yixiao Sun, 2012. "Sieve inference on semi-nonparametric time series models," CeMMAP working papers 06/12, Institute for Fiscal Studies.
    69. Han Shang, 2014. "Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density," Computational Statistics, Springer, vol. 29(3), pages 829-848, June.
    70. Wong, Heung & Liu, Feng & Chen, Min & Ip, Wai Cheung, 2009. "Empirical likelihood based diagnostics for heteroscedasticity in partial linear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3466-3477, July.
    71. Feng Li & Lu Lin & Yuxia Su, 2013. "Variable selection and parameter estimation for partially linear models via Dantzig selector," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(2), pages 225-238, February.
    72. You, Jinhong & Chen, Gemai, 2006. "Wild bootstrap estimation in partially linear models with heteroscedasticity," Statistics & Probability Letters, Elsevier, vol. 76(4), pages 340-348, February.
    73. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    74. Lu Lin & Lili Liu & Xia Cui & Kangning Wang, 2021. "A generalized semiparametric regression and its efficient estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 1-24, March.
    75. Wang, Zhaoliang & Xue, Liugen & Liu, Juanfang, 2019. "Checking nonparametric component for partially nonlinear model with missing response," Statistics & Probability Letters, Elsevier, vol. 149(C), pages 1-8.
    76. Helmut Wasserbacher & Martin Spindler, 2024. "Credit Ratings: Heterogeneous Effect on Capital Structure," Papers 2406.18936, arXiv.org.
    77. Laurini, Márcio Poletti & de Carvalho Andrade, Eduardo, 2012. "New evidence on the role of cognitive skill in economic development," Economics Letters, Elsevier, vol. 117(1), pages 123-126.
    78. Martins-Filho, Carlos & Yao, Feng, 2012. "Kernel-based estimation of semiparametric regression in triangular systems," Economics Letters, Elsevier, vol. 115(1), pages 24-27.
    79. Duran, Esra Akdeniz & Härdle, Wolfgang Karl & Osipenko, Maria, 2011. "Difference based ridge and Liu type estimators in semiparametric regression models," SFB 649 Discussion Papers 2011-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    80. Lai, Peng & Wang, Qihua, 2014. "Semiparametric efficient estimation for partially linear single-index models with responses missing at random," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 33-50.
    81. Cai, Xizhen & Zhu, Yeying & Huang, Yuan & Ghosh, Debashis, 2022. "High-dimensional causal mediation analysis based on partial linear structural equation models," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    82. Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric Identification and Estimation of Nonclassical Errors-in-Variables Models Without Additional Information," Boston College Working Papers in Economics 676, Boston College Department of Economics.
    83. Gao, Jiti & Tong, Howell, 2002. "Nonparametric and semiparametric regression model selection," MPRA Paper 11987, University Library of Munich, Germany, revised Feb 2004.
    84. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    85. Manzan, Sebastiano & Zerom, Dawit, 2005. "Kernel estimation of a partially linear additive model," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 313-322, May.
    86. Hardle, Wolfgang & Linton, Oliver & Wang, Qihua, 2003. "Semiparametric regression analysis under imputation for missing response data," LSE Research Online Documents on Economics 2206, London School of Economics and Political Science, LSE Library.
    87. Song, Lixin & Zhao, Yue & Wang, Xiaoguang, 2010. "Sieve least squares estimation for partially nonlinear models," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1271-1283, September.
    88. Zhang, Chunming & Li, Jialiang & Meng, Jingci, 2008. "On Stein's lemma, dependent covariates and functional monotonicity in multi-dimensional modeling," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2285-2303, November.
    89. You, Jinhong & Chen, Gemai, 2005. "Testing heteroscedasticity in partially linear regression models," Statistics & Probability Letters, Elsevier, vol. 73(1), pages 61-70, June.
    90. Zhang, Jun & Feng, Zhenghui & Peng, Heng, 2018. "Estimation and hypothesis test for partial linear multiplicative models," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 87-103.
    91. Xue-Jun Ma & Jing-Xiao Zhang, 2016. "A new variable selection approach for varying coefficient models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 59-72, January.
    92. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    93. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Estimation in semiparametric spatial regression," MPRA Paper 11979, University Library of Munich, Germany, revised Jul 2005.
    94. Boente, Graciela & Martínez, Alejandra Mercedes, 2023. "A robust spline approach in partially linear additive models," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    95. Lin, Lu & Zhu, Lixing & Gai, Yujie, 2016. "Inference for biased models: A quasi-instrumental variable approach," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 22-36.
    96. Xiaohong Chen & Zhipeng Liao & Yixiao Sun, 2012. "Sieve Inference on Semi-nonparametric Time Series Models," Cowles Foundation Discussion Papers 1849, Cowles Foundation for Research in Economics, Yale University.
    97. Silvia Novo & Germán Aneiros & Philippe Vieu, 2025. "Semi-functional partial linear regression with measurement error: an approach based on kNN estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 34(1), pages 235-261, March.
    98. Wang, Xiaoguang & Shi, Xinyong, 2014. "Robust estimation for survival partially linear single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 140-152.
    99. Aifen Feng & Xiaogai Chang & Jingya Fan & Zhengfen Jin, 2023. "Application of LADMM and As-LADMM for a High-Dimensional Partially Linear Model," Mathematics, MDPI, vol. 11(19), pages 1-14, October.
    100. Wang, Qihua & Sun, Zhihua, 2007. "Estimation in partially linear models with missing responses at random," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1470-1493, August.
    101. Yuejin Zhou & Yebin Cheng & Wenlin Dai & Tiejun Tong, 2018. "Optimal difference-based estimation for partially linear models," Computational Statistics, Springer, vol. 33(2), pages 863-885, June.
    102. Li, Jinfang, 2020. "The momentum and reversal effects of investor sentiment on stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    103. Chen, Xiaohong & Liao, Zhipeng & Sun, Yixiao, 2014. "Sieve inference on possibly misspecified semi-nonparametric time series models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 639-658.
    104. Zhu, Xuehu & Wang, Tao & Zhao, Junlong & Zhu, Lixing, 2017. "Inference for biased transformation models," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 105-120.
    105. Wang, Xiuli & Zhao, Shengli & Wang, Mingqiu, 2017. "Restricted profile estimation for partially linear models with large-dimensional covariates," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 71-76.
    106. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    107. Haotian Chen & Xibin Zhang, 2014. "Bayesian Estimation for Partially Linear Models with an Application to Household Gasoline Consumption," Monash Econometrics and Business Statistics Working Papers 28/14, Monash University, Department of Econometrics and Business Statistics.
    108. Liang, Han-Ying & Fan, Guo-Liang, 2009. "Berry-Esseen type bounds of estimators in a semiparametric model with linear process errors," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 1-15, January.
    109. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
    110. Germán Aneiros & Nengxiang Ling & Philippe Vieu, 2015. "Error variance estimation in semi-functional partially linear regression models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(3), pages 316-330, September.
    111. Samuele Centorrino & Jean-Pierre Florens, 2014. "Nonparametric Instrumental Variable Estimation of Binary Response Models," Department of Economics Working Papers 14-07, Stony Brook University, Department of Economics.
    112. Chao, Shih-Kang & Härdle, Wolfgang Karl & Wang, Weining, 2012. "Quantile regression in risk calibration," SFB 649 Discussion Papers 2012-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    113. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    114. Bianco, Ana M. & Spano, Paula M., 2017. "Robust estimation in partially linear errors-in-variables models," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 46-64.
    115. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    116. Lam, Clifford & Fan, Jianqing, 2008. "Profile-kernel likelihood inference with diverging number of parameters," LSE Research Online Documents on Economics 31548, London School of Economics and Political Science, LSE Library.
    117. Yangxin Huang & Tao Lu, 2017. "Bayesian inference on partially linear mixed-effects joint models for longitudinal data with multiple features," Computational Statistics, Springer, vol. 32(1), pages 179-196, March.
    118. Hadi Emami & Omid Khademnoe, 2025. "Shrinkage and pretest Liu estimators in semiparametric linear measurement error models," Statistical Papers, Springer, vol. 66(2), pages 1-35, February.
    119. Dong, Chaohua & Gao, Jiti & Tong, Howell, 2006. "Semiparametric penalty function method in partially linear model selection," MPRA Paper 11975, University Library of Munich, Germany, revised Aug 2006.
    120. Liang, Hua & Härdle, Wolfgang & Carroll, Raymond J., 1997. "Large sample theory in a semiparametric partially linear errors-in-variables models," SFB 373 Discussion Papers 1997,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    121. Boente, Graciela & Cao, Ricardo & González Manteiga, Wenceslao & Rodriguez, Daniela, 2013. "Testing in generalized partially linear models: A robust approach," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 203-212.
    122. Germán Aneiros-Pérez & Philippe Vieu, 2011. "Automatic estimation procedure in partial linear model with functional data," Statistical Papers, Springer, vol. 52(4), pages 751-771, November.
    123. George Athanasopoulos & Minfeng Deng & Gang Li & Haiyan Song, 2013. "Domestic and outbound tourism demand in Australia: a System-of-Equations Approach," Monash Econometrics and Business Statistics Working Papers 6/13, Monash University, Department of Econometrics and Business Statistics.
    124. Sun, Shuang & Song, Zening & Song, Xiaojun, 2025. "Unified specification tests in partially linear time series models," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
    125. Zhang, Yuanqing & Sun, Yanqing, 2015. "Estimation of partially specified dynamic spatial panel data models with fixed-effects," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 37-46.
    126. Haiyan Su & Linlin Chen, 2024. "Empirical-Likelihood-Based Inference for Partially Linear Models," Mathematics, MDPI, vol. 12(1), pages 1-12, January.
    127. You, Jinhong & Zhou, Xian & Zhu, Li-Xing, 2009. "Inference on a regression model with noised variables and serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1182-1197, July.
    128. Moral-Arce, Ignacio & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 2011. "Low dimensional semiparametric estimation in a censored regression model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 118-129, January.
    129. Ana Bianco & Graciela Boente & Wenceslao González-Manteiga & Ana Pérez-González, 2011. "Asymptotic behavior of robust estimators in partially linear models with missing responses: the effect of estimating the missing probability on the simplified marginal estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 524-548, November.
    130. Aneiros-Pérez, Germán & Vieu, Philippe, 2006. "Semi-functional partial linear regression," Statistics & Probability Letters, Elsevier, vol. 76(11), pages 1102-1110, June.
    131. Nengxiang Ling & Germán Aneiros & Philippe Vieu, 2020. "kNN estimation in functional partial linear modeling," Statistical Papers, Springer, vol. 61(1), pages 423-444, February.
    132. Zhang, Jun & Zhou, Yan & Lin, Bingqing & Yu, Yao, 2017. "Estimation and hypothesis test on partial linear models with additive distortion measurement errors," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 114-128.
    133. Wang, Xiaoguang & Lu, Dawei & Song, Lixin, 2013. "Statistical inference for partially linear stochastic models with heteroscedastic errors," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 150-160.
    134. Lu, Xuewen, 2009. "Empirical likelihood for heteroscedastic partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 387-396, March.
    135. Huang, Zhensheng & Zhou, Zhangong & Jiang, Rong & Qian, Weimin & Zhang, Riquan, 2010. "Empirical likelihood based inference for semiparametric varying coefficient partially linear models with error-prone linear covariates," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 497-504, March.
    136. Jun Zhang & Zhenghui Feng & Peirong Xu & Hua Liang, 2017. "Generalized varying coefficient partially linear measurement errors models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 97-120, February.
    137. Aifen Feng & Xiaogai Chang & Youlin Shang & Jingya Fan, 2022. "Application of the ADMM Algorithm for a High-Dimensional Partially Linear Model," Mathematics, MDPI, vol. 10(24), pages 1-13, December.
    138. M. Christopher Auld, 2002. "Disentangling the effects of morbidity and life expectancy on labor market outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 11(6), pages 471-483, September.
    139. Wang, Dewei & Kulasekera, K.B., 2012. "Parametric component detection and variable selection in varying-coefficient partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 117-129.
    140. Qinqin Hu & Lu Lin, 2018. "Conditional feature screening for mean and variance functions in models with multiple-index structure," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(4), pages 357-393, May.
    141. Zhang, Yaowu & Zhu, Liping & Ma, Yanyuan, 2017. "Efficient dimension reduction for multivariate response data," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 187-199.
    142. Hilafu, Haileab & Wu, Wenbo, 2017. "Partial projective resampling method for dimension reduction: With applications to partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 1-14.
    143. Roozbeh, Mahdi, 2015. "Shrinkage ridge estimators in semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 56-74.
    144. Jun Zhang & Zhenghui Feng & Peirong Xu, 2015. "Estimating the conditional single-index error distribution with a partial linear mean regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 61-83, March.
    145. You, Jinhong & Zhou, Xian & Zhou, Yong, 2010. "Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1079-1101, May.
    146. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.
    147. Aneiros-Perez, G. & Vilar-Fernandez, J.M., 2008. "Local polynomial estimation in partial linear regression models under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2757-2777, January.
    148. Ying Lu & Jiang Du & Zhimeng Sun, 2014. "Functional partially linear quantile regression model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 317-332, February.
    149. Germán Aneiros & Philippe Vieu, 2015. "Partial linear modelling with multi-functional covariates," Computational Statistics, Springer, vol. 30(3), pages 647-671, September.
    150. Su, Liangjun & Jin, Sainan, 2010. "Profile quasi-maximum likelihood estimation of partially linear spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 157(1), pages 18-33, July.
    151. Hu Yang & Ning Li & Jing Yang, 2020. "A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates," Statistical Papers, Springer, vol. 61(5), pages 1911-1937, October.
    152. Huang, Zhensheng, 2012. "Empirical likelihood for the parametric part in partially linear errors-in-function models," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 63-66.
    153. Liu, Jialuo & Chu, Tingjin & Zhu, Jun & Wang, Haonan, 2021. "Semiparametric method and theory for continuously indexed spatio-temporal processes," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    154. Ferraccioli, Federico & Sangalli, Laura M. & Finos, Livio, 2022. "Some first inferential tools for spatial regression with differential regularization," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    155. Moral, Ignacio & Rodriguez-Poo, Juan M., 2004. "An efficient marginal integration estimator of a semiparametric additive modelling," Statistics & Probability Letters, Elsevier, vol. 69(4), pages 451-463, October.
    156. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    157. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," LSE Research Online Documents on Economics 28868, London School of Economics and Political Science, LSE Library.
    158. Q. Shao, 2009. "Seasonality analysis of time series in partial linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(7), pages 827-837.
    159. Huang, Zhensheng & Pang, Zhen & Hu, Tao, 2013. "Testing structural change in partially linear single-index models with error-prone linear covariates," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 121-133.
    160. Boente, Graciela & Rodriguez, Daniela, 2008. "Robust bandwidth selection in semiparametric partly linear regression models: Monte Carlo study and influential analysis," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2808-2828, January.
    161. Amini, Morteza & Roozbeh, Mahdi, 2015. "Optimal partial ridge estimation in restricted semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 26-40.
    162. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
    163. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    164. Zhou, Xing-cai & Lin, Jin-guan, 2013. "Asymptotic properties of wavelet estimators in semiparametric regression models under dependent errors," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 251-270.
    165. Germán Aneiros-Pérez & Philippe Vieu, 2013. "Testing linearity in semi-parametric functional data analysis," Computational Statistics, Springer, vol. 28(2), pages 413-434, April.
    166. Roozbeh, M. & Arashi, M., 2013. "Feasible ridge estimator in partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 35-44.
    167. Graciela Boente & Daniela Rodriguez & Pablo Vena, 2020. "Robust estimators in a generalized partly linear regression model under monotony constraints," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 50-89, March.
    168. Jun Zhang & Yao Yu & Li-Xing Zhu & Hua Liang, 2013. "Partial linear single index models with distortion measurement errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(2), pages 237-267, April.
    169. Heng Lian, 2020. "Asymptotics of the Non‐parametric Function for B‐splines‐based Estimation in Partially Linear Models," International Statistical Review, International Statistical Institute, vol. 88(1), pages 142-154, April.
    170. Xin Lu & Brent A. Johnson, 2015. "Direct estimation of the mean outcome on treatment when treatment assignment and discontinuation compete," Biometrika, Biometrika Trust, vol. 102(4), pages 797-807.

  102. Gao, jiti & Anh, vo & Heyde, christopher, 1999. "Statistical estimation of nonstationaryGaussian processes with long-range dependence and intermittency," MPRA Paper 11972, University Library of Munich, Germany, revised 23 Oct 2001.

    Cited by:

    1. Leonenko, N.N. & Sakhno, L.M., 2006. "On the Whittle estimators for some classes of continuous-parameter random processes and fields," Statistics & Probability Letters, Elsevier, vol. 76(8), pages 781-795, April.
    2. Casas, Isabel & Gao, Jiti, 2008. "Econometric estimation in long-range dependent volatility models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 72-83, November.
    3. Anh, V.V. & Leonenko, N.N. & Sakhno, L.M., 2007. "Statistical inference using higher-order information," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 706-742, April.
    4. Gao, Jiti, 2002. "Modeling long-range dependent Gaussian processes with application in continuous-time financial models," MPRA Paper 11973, University Library of Munich, Germany, revised 18 Sep 2003.
    5. Casas, Isabel, 2008. "Estimation of stochastic volatility with LRD," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 335-340.

  103. Gao, Jiti, 1994. "Asymptotic theory for partly linear models," MPRA Paper 40452, University Library of Munich, Germany, revised 02 Dec 1994.

    Cited by:

    1. You, Jinhong & Zhou, Xian, 2006. "Statistical inference in a panel data semiparametric regression model with serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 844-873, April.
    2. Zhensheng Huang, 2012. "Empirical likelihood for varying-coefficient single-index model with right-censored data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(1), pages 55-71, January.
    3. Wong, Heung & Liu, Feng & Chen, Min & Ip, Wai Cheung, 2009. "Empirical likelihood based diagnostics for heteroscedasticity in partial linear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3466-3477, July.
    4. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    5. Huang, Tzee-Ming & Chen, Hung, 2008. "Estimating the parametric component of nonlinear partial spline model," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1665-1680, September.
    6. Aneiros-Perez, G. & Vilar-Fernandez, J.M., 2008. "Local polynomial estimation in partial linear regression models under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2757-2777, January.
    7. Q. Shao, 2009. "Seasonality analysis of time series in partial linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(7), pages 827-837.
    8. Xiaohui Liu & Zhizhong Wang & Xuemei Hu, 2011. "Testing heteroscedasticity in partially linear models with missing covariates," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 321-337.

Articles

  1. Jiti Gao & Bin Peng & Yayi Yan, 2024. "Higher-Order Expansions and Inference for Panel Data Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(548), pages 2760-2771, October.
    See citations under working paper version above.
  2. Jiti Gao & Bin Peng & Yayi Yan, 2024. "Estimation, Inference, and Empirical Analysis for Time-Varying VAR Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(1), pages 310-321, January.

    Cited by:

    1. Fahad Abdelaziz Almohaimeed & Khaled Ahmed Abouelnour, 2025. "The Role of Food Processing in Sustaining Food Security Indicators in the Kingdom of Saudi Arabia," Economies, MDPI, vol. 13(3), pages 1-25, March.

  3. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).

    Cited by:

    1. Fatimah A. Almulhim & Mohammed B. Alamari & Salim Bouzebda & Zoulikha Kaid & Ali Laksaci, 2025. "Robust Estimation of L 1 -Modal Regression Under Functional Single-Index Models for Practical Applications," Mathematics, MDPI, vol. 13(4), pages 1-20, February.

  4. Cheng, Tingting & Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2024. "GMM estimation for high-dimensional panel data models," Journal of Econometrics, Elsevier, vol. 244(1).
    See citations under working paper version above.
  5. Gao, Jiti & Liu, Fei & Peng, Bin & Yan, Yayi, 2023. "Binary response models for heterogeneous panel data with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 1654-1679.
    See citations under working paper version above.
  6. He, Yi & Jaidee, Sombut & Gao, Jiti, 2023. "Most powerful test against a sequence of high dimensional local alternatives," Journal of Econometrics, Elsevier, vol. 234(1), pages 151-177.

    Cited by:

    1. Beyhum, Jad & Striaukas, Jonas, 2024. "Testing for sparse idiosyncratic components in factor-augmented regression models," Journal of Econometrics, Elsevier, vol. 244(1).

  7. Anderson, Heather M. & Gao, Jiti & Turnip, Guido & Vahid, Farshid & Wei, Wei, 2023. "Estimating the effect of an EU-ETS type scheme in Australia using a synthetic treatment approach," Energy Economics, Elsevier, vol. 125(C).
    See citations under working paper version above.
  8. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    See citations under working paper version above.
  9. Chen, Li & Gao, Jiti & Vahid, Farshid, 2022. "Global temperatures and greenhouse gases: A common features approach," Journal of Econometrics, Elsevier, vol. 230(2), pages 240-254.
    See citations under working paper version above.
  10. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    See citations under working paper version above.
  11. Xuan Liang & Jiti Gao & Xiaodong Gong, 2022. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1784-1802, October.
    See citations under working paper version above.
  12. Chaohua Dong & Jiti Gao & Bin Peng, 2021. "Varying-Coefficient Panel Data Models With Nonstationarity and Partially Observed Factor Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 700-711, July.

    Cited by:

    1. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    2. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    3. Jiti Gao & Bin Peng & Yayi Yan, 2022. "Nonparametric Estimation and Testing for Time-Varying VAR Models," Monash Econometrics and Business Statistics Working Papers 3/22, Monash University, Department of Econometrics and Business Statistics.
    4. Jia Chen Author-Name-First: Jia & Yongcheol Shin & Chaowen Zheng, 2023. "Dynamic Quantile Panel Data Models with Interactive Effects," Economics Discussion Papers em-dp2023-06, Department of Economics, University of Reading.
    5. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Cambridge Working Papers in Economics 2239, Faculty of Economics, University of Cambridge.
    6. Wongsa-art, Pipat & Kim, Namhyun & Xia, Yingcun & Moscone, Francesco, 2024. "Varying coefficient panel data models and methods under correlated error components: Application to disparities in mental health services in England," Regional Science and Urban Economics, Elsevier, vol. 106(C).
    7. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2019. "Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone," Monash Econometrics and Business Statistics Working Papers 28/19, Monash University, Department of Econometrics and Business Statistics.
    8. Guohua Feng & Jiti Gao & Bin Peng, 2022. "Multi-Level Panel Data Models: Estimation and Empirical Analysis," Monash Econometrics and Business Statistics Working Papers 4/22, Monash University, Department of Econometrics and Business Statistics.
    9. Heather Anderson & Jiti Gao & Farshid Vahid & Wei Wei & Yang Yang, 2023. "Does Climate Sensitivity Differ Across Regions?," Monash Econometrics and Business Statistics Working Papers 7/23, Monash University, Department of Econometrics and Business Statistics.

  13. Sopitpongstorn, Nithi & Silvapulle, Param & Gao, Jiti & Fenech, Jean-Pierre, 2021. "Local logit regression for loan recovery rate," Journal of Banking & Finance, Elsevier, vol. 126(C).

    Cited by:

    1. Nazemi, Abdolreza & Fabozzi, Frank J., 2024. "Interpretable machine learning for creditor recovery rates," Journal of Banking & Finance, Elsevier, vol. 164(C).
    2. Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2022. "Corporate Loan Recovery Rates under Downturn Conditions in a Developing Economy: Evidence from Zimbabwe," Risks, MDPI, vol. 10(10), pages 1-24, October.
    3. Marc Gürtler & Marvin Zöllner, 2023. "Heterogeneities among credit risk parameter distributions: the modality defines the best estimation method," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 251-287, March.
    4. Tobias Börger & Kolobe Mmonwa & Danny Campbell, 2024. "Hazardous human–wildlife encounters, risk attitudes, and the value of shark nets for coastal recreation," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 925-945, March.
    5. Kellner, Ralf & Nagl, Maximilian & Rösch, Daniel, 2022. "Opening the black box – Quantile neural networks for loss given default prediction," Journal of Banking & Finance, Elsevier, vol. 134(C).

  14. Gao, Jiti & Peng, Bin & Smyth, Russell, 2021. "On income and price elasticities for energy demand: A panel data study," Energy Economics, Elsevier, vol. 96(C).
    See citations under working paper version above.
  15. Yan Meng & Jiti Gao & Xibin Zhang & Xueyan Zhao, 2021. "A panel data model of length of stay in hospitals for hip replacements," Econometric Reviews, Taylor & Francis Journals, vol. 40(7), pages 688-707, August.

    Cited by:

    1. Wongsa-art, Pipat & Kim, Namhyun & Xia, Yingcun & Moscone, Francesco, 2024. "Varying coefficient panel data models and methods under correlated error components: Application to disparities in mental health services in England," Regional Science and Urban Economics, Elsevier, vol. 106(C).

  16. Ma, Shujie & Linton, Oliver & Gao, Jiti, 2021. "Estimation and inference in semiparametric quantile factor models," Journal of Econometrics, Elsevier, vol. 222(1), pages 295-323.
    See citations under working paper version above.
  17. Isabel Casas & Jiti Gao & Bin Peng & Shangyu Xie, 2021. "Time‐varying income elasticities of healthcare expenditure for the OECD and Eurozone," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 328-345, April.
    See citations under working paper version above.
  18. Jiang, Bin & Yang, Yanrong & Gao, Jiti & Hsiao, Cheng, 2021. "Recursive estimation in large panel data models: Theory and practice," Journal of Econometrics, Elsevier, vol. 224(2), pages 439-465.
    See citations under working paper version above.
  19. Li, Degui & Phillips, Peter C.B. & Gao, Jiti, 2020. "Kernel-based Inference in Time-Varying Coefficient Cointegrating Regression," Journal of Econometrics, Elsevier, vol. 215(2), pages 607-632.
    See citations under working paper version above.
  20. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    See citations under working paper version above.
  21. Chaohua Dong & Jiti Gao, 2019. "Expansion and estimation of Lévy process functionals in nonlinear and nonstationary time series regression," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 125-150, February.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2023. "Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models," Monash Econometrics and Business Statistics Working Papers 2/23, Monash University, Department of Econometrics and Business Statistics.
    3. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Papers 2111.02023, arXiv.org.
    4. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.

  22. Tingting Cheng & Jiti Gao & Xibin Zhang, 2019. "Bayesian Bandwidth Estimation in Nonparametric Time-Varying Coefficient Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 1-12, January.
    See citations under working paper version above.
  23. Chaohua Dong & Jiti Gao & Bin Peng, 2019. "Estimation in a semiparametric panel data model with nonstationarity," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 961-977, September.

    Cited by:

    1. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    2. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.

  24. Cheng, Tingting & Gao, Jiti & Yan, Yayi, 2019. "Regime switching panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 177(C), pages 47-51.
    See citations under working paper version above.
  25. Fengping Tian & Jiti Gao & Ke Yang, 2018. "A quantile regression approach to panel data analysis of health‐care expenditure in Organisation for Economic Co‐operation and Development countries," Health Economics, John Wiley & Sons, Ltd., vol. 27(12), pages 1921-1944, December.

    Cited by:

    1. Tahir Abbas, 2025. "Impact of Government Health Expenditure on Economic Growth: A Comparative Study of Selected Countries," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(3), pages 196-208, March.
    2. Hartwig, Jochen, 2020. "Not Evidence for Baumol’s Cost Disease. A Reply to Atanda and Reed (International Journal for Re-Views in Empirical Economics, 2020)," International Journal for Re-Views in Empirical Economics (IREE), ZBW - Leibniz Information Centre for Economics, vol. 4, pages 1-4.
    3. Cristian Barra & Nazzareno Ruggiero, 2023. "Institutional quality and public spending in Europe: A quantile regression approach," Economics and Politics, Wiley Blackwell, vol. 35(3), pages 949-1019, November.
    4. Kaan Celebi & Jochen Hartwig & Anna Pauliina Sandqvist, 2024. "Baumol's Cost Disease in Acute vs. Long-term Care - Do the Differences Loom Large?," Chemnitz Economic Papers 062, Department of Economics, Chemnitz University of Technology.

  26. Guohua Feng & Jiti Gao & Xiaohui Zhang, 2018. "Estimation of technical change and price elasticities: a categorical time–varying coefficient approach," Journal of Productivity Analysis, Springer, vol. 50(3), pages 117-138, December.
    See citations under working paper version above.
  27. Dong, Chaohua & Gao, Jiti, 2018. "Specification Testing Driven By Orthogonal Series For Nonlinear Cointegration With Endogeneity," Econometric Theory, Cambridge University Press, vol. 34(4), pages 754-789, August.

    Cited by:

    1. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2023. "Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models," Monash Econometrics and Business Statistics Working Papers 2/23, Monash University, Department of Econometrics and Business Statistics.
    2. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    3. Jun Wang & Dianpeng Wang & Yubin Tian, 2022. "Multidimensional specification test based on non-stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 348-372, June.
    4. Li, Haiqi & Zhang, Jing & Zheng, Chaowen, 2025. "Functional-coefficient quantile cointegrating regression with stationary covariates," Statistics & Probability Letters, Elsevier, vol. 219(C).
    5. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    6. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    7. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Papers 2111.02023, arXiv.org.
    8. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    9. Shan Dai & Ngai Hang Chan, 2023. "Testing of Constant Parameters for Semi‐Parametric Functional Coefficient Models with Integrated Covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 474-486, September.
    10. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.

  28. Cheng, Tingting & Gao, Jiti & Phillips, Peter C.B., 2018. "A frequentist approach to Bayesian asymptotics," Journal of Econometrics, Elsevier, vol. 206(2), pages 359-378.

    Cited by:

    1. Doğan, Osman & Taşpınar, Süleyman & Bera, Anil K., 2021. "A Bayesian robust chi-squared test for testing simple hypotheses," Journal of Econometrics, Elsevier, vol. 222(2), pages 933-958.

  29. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2018. "Nonparametric Estimation and Forecasting for Time-Varying Coefficient Realized Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 88-100, January.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Cizek, Pavel & Koo, Chao, 2017. "Jump-Preserving Varying-Coefficient Models for Nonlinear Time Series," Other publications TiSEM c849e96f-3ad1-461e-96c6-f, Tilburg University, School of Economics and Management.
    3. Deshui Yu & Yayi Yan, 2023. "Joint dynamics of stock returns and cash flows: A time‐varying present‐value framework," Financial Management, Financial Management Association International, vol. 52(3), pages 513-541, September.
    4. Jozef Barunik & Lukas Vacha, 2023. "The Dynamic Persistence of Economic Shocks," Papers 2306.01511, arXiv.org, revised Jun 2025.
    5. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    6. Niklas Kroner, 2025. "How Markets Process Macro News: The Importance of Investor Attention," Finance and Economics Discussion Series 2025-022, Board of Governors of the Federal Reserve System (U.S.).
    7. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    8. Wei Wei & Asger Lunde, 2023. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1647-1679.
    9. Ren, Boru & Lucey, Brian, 2023. "Herding in the Chinese renewable energy market: Evidence from a bootstrapping time-varying coefficient autoregressive model," Energy Economics, Elsevier, vol. 119(C).
    10. Ngai Hang Chan & Linhao Gao & Wilfredo Palma, 2022. "Simultaneous variable selection and structural identification for time‐varying coefficient models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 511-531, July.
    11. Yu, Deshui & Chen, Li, 2024. "Local predictability of stock returns and cash flows," Journal of Empirical Finance, Elsevier, vol. 77(C).
    12. Yu, Deshui & Chen, Li & Li, Luyang, 2023. "Nonparametric modeling for the time-varying persistence of inflation," Economics Letters, Elsevier, vol. 225(C).
    13. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    14. Hu, Nan & Yin, Xuebao & Yao, Yuhang, 2025. "A novel HAR-type realized volatility forecasting model using graph neural network," International Review of Financial Analysis, Elsevier, vol. 98(C).
    15. Qiao, Gaoxiu & Teng, Yuxin & Li, Weiping & Liu, Wenwen, 2019. "Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 133-151.
    16. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    17. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.
    18. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    19. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    20. Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
    21. Li Liu & Zhiyuan Pan & Yudong Wang, 2021. "What can we learn from the return predictability over the business cycle?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 108-131, January.
    22. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    23. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.

  30. Dong, Chaohua & Gao, Jiti & Tjøstheim, Dag & Yin, Jiying, 2017. "Specification testing for nonlinear multivariate cointegrating regressions," Journal of Econometrics, Elsevier, vol. 200(1), pages 104-117.
    See citations under working paper version above.
  31. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    See citations under working paper version above.
  32. Jiti Gao & Xiao Han & Guangming Pan & Yanrong Yang, 2017. "High dimensional correlation matrices: the central limit theorem and its applications," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 677-693, June.

    Cited by:

    1. Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024. "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, vol. 239(2).
    2. Chen, Jiaqi & Zhang, Yangchun & Li, Weiming & Tian, Boping, 2018. "A supplement on CLT for LSS under a large dimensional generalized spiked covariance model," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 57-65.
    3. He, Yi & Jaidee, Sombut & Gao, Jiti, 2023. "Most powerful test against a sequence of high dimensional local alternatives," Journal of Econometrics, Elsevier, vol. 234(1), pages 151-177.
    4. Xu, Kai & Cheng, Qing & He, Daojiang, 2025. "On summed nonparametric dependence measures in high dimensions, fixed or large samples," Computational Statistics & Data Analysis, Elsevier, vol. 205(C).
    5. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    6. Yang, Xinxin & Zheng, Xinghua & Chen, Jiaqi, 2021. "Testing high-dimensional covariance matrices under the elliptical distribution and beyond," Journal of Econometrics, Elsevier, vol. 221(2), pages 409-423.
    7. Dörnemann, Nina, 2023. "Likelihood ratio tests under model misspecification in high dimensions," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
    8. Li, Yanpeng, 2025. "Large sample correlation matrices with unbounded spectrum," Journal of Multivariate Analysis, Elsevier, vol. 205(C).

  33. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.
    See citations under working paper version above.
  34. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    See citations under working paper version above.
  35. Gao, Jiti & Robinson, Peter M., 2016. "Inference On Nonstationary Time Series With Moving Mean," Econometric Theory, Cambridge University Press, vol. 32(2), pages 431-457, April.
    See citations under working paper version above.
  36. Li, Degui & Phillips, Peter C. B. & Gao, Jiti, 2016. "Uniform Consistency Of Nonstationary Kernel-Weighted Sample Covariances For Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 32(3), pages 655-685, June.
    See citations under working paper version above.
  37. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.

    Cited by:

    1. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    2. Shiqing Ling & Michael McAleer & Howell Tong, 2015. "Frontiers in Time Series and Financial Econometrics: An Overview," Tinbergen Institute Discussion Papers 15-026/III, Tinbergen Institute.
    3. Ling, S. & McAleer, M.J. & Tong, H., 2015. "Frontiers in Time Series and Financial Econometrics," Econometric Institute Research Papers EI 2015-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    5. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    6. N. Balakrishna & Hira L. Koul, 2017. "Varying kernel marginal density estimator for a positive time series," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(3), pages 531-552, July.
    7. Hira L. Koul & Indeewara Perera & Narayana Balakrishna, 2023. "A class of Minimum Distance Estimators in Markovian Multiplicative Error Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 87-115, May.
    8. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    9. Guo, Bin & Li, Shuo, 2018. "Diagnostic checking of Markov multiplicative error models," Economics Letters, Elsevier, vol. 170(C), pages 139-142.

  38. Gao, Jiti & Kanaya, Shin & Li, Degui & Tjøstheim, Dag, 2015. "Uniform Consistency For Nonparametric Estimators In Null Recurrent Time Series," Econometric Theory, Cambridge University Press, vol. 31(5), pages 911-952, October.
    See citations under working paper version above.
  39. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2015. "Specification testing in nonstationary time series models," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 117-136, February.
    See citations under working paper version above.
  40. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    See citations under working paper version above.
  41. Patrick W. Saart & Jiti Gao & David E. Allen, 2015. "Semiparametric Autoregressive Conditional Duration Model: Theory and Practice," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 849-881, December.

    Cited by:

    1. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    2. Pooi AH-HIN & Ng KOK-HAUR & Soo HUEI-CHING, 2016. "Modelling and Forecasting with Financial Duration Data Using Non-linear Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 79-92.
    3. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    4. Gavin Ooft & Philip Hans Franses & Sailesh Bhaghoe, 2023. "Autoregressive conditional durations: An application to the Surinamese dollar versus the US dollar exchange rate," Review of Development Economics, Wiley Blackwell, vol. 27(4), pages 2618-2637, November.
    5. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.

  42. Guangming Pan & Jiti Gao & Yanrong Yang, 2014. "Testing Independence Among a Large Number of High-Dimensional Random Vectors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 600-612, June.

    Cited by:

    1. Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024. "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, vol. 239(2).
    2. Merlevède, F. & Peligrad, M., 2016. "On the empirical spectral distribution for matrices with long memory and independent rows," Stochastic Processes and their Applications, Elsevier, vol. 126(9), pages 2734-2760.
    3. Loubaton, Philippe & Rosuel, Alexis & Vallet, Pascal, 2023. "On the asymptotic distribution of the maximum sample spectral coherence of Gaussian time series in the high dimensional regime," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
    4. He, Yi & Jaidee, Sombut & Gao, Jiti, 2023. "Most powerful test against a sequence of high dimensional local alternatives," Journal of Econometrics, Elsevier, vol. 234(1), pages 151-177.
    5. Jiti Gao & Xiao Han & Guangming Pan & Yanrong Yang, 2017. "High dimensional correlation matrices: the central limit theorem and its applications," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 677-693, June.
    6. Bo Zhang & Guangming Pan & Jiti Gao, 2016. "CLT for Largest Eigenvalues and Unit Root Tests for High-Dimensional Nonstationary Time Series," Monash Econometrics and Business Statistics Working Papers 11/16, Monash University, Department of Econometrics and Business Statistics.
    7. Yi He & Sombut Jaidee & Jiti Gao, 2020. "Most Powerful Test against High Dimensional Free Alternatives," Monash Econometrics and Business Statistics Working Papers 13/20, Monash University, Department of Econometrics and Business Statistics.
    8. Bo Zhang & Jiti Gao & Guangming Pan, 2020. "Estimation and Testing for High-Dimensional Near Unit Root Time Series," Monash Econometrics and Business Statistics Working Papers 12/20, Monash University, Department of Econometrics and Business Statistics.
    9. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.
    10. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
    11. Bo Zhang & Jiti Gao & Guangming Pan, 2019. "A Near Unit Root Test for High-Dimensional Nonstationary Time Series," Monash Econometrics and Business Statistics Working Papers 10/19, Monash University, Department of Econometrics and Business Statistics.
    12. Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2019. "Spiked Eigenvalues of High-Dimensional Separable Sample Covariance Matrices," Monash Econometrics and Business Statistics Working Papers 31/19, Monash University, Department of Econometrics and Business Statistics.

  43. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression with Non- and Semi-Parametric Cointegration," Monash Econometrics and Business Statistics Working Papers 16/13, Monash University, Department of Econometrics and Business Statistics.
    3. Qiu, Guo & Xu, Wangtu (Ato) & Li, Ling, 2018. "Key factors to annual investment in public transportation sector: The case of China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 1-19.
    4. Wang, Qiying & Wu, Dongsheng & Zhu, Ke, 2018. "Model checks for nonlinear cointegrating regression," Journal of Econometrics, Elsevier, vol. 207(2), pages 261-284.
    5. Biqing Cai & Chaohua Dong & Jiti Gao, 2015. "Orthogonal Series Estimation in Nonlinear Cointegrating Models with Endogeneity," Monash Econometrics and Business Statistics Working Papers 18/15, Monash University, Department of Econometrics and Business Statistics.
    6. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    7. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    8. Qiying Wang & Peter C. B. Phillips, 2022. "A General Limit Theory for Nonlinear Functionals of Nonstationary Time Series," Cowles Foundation Discussion Papers 2337, Cowles Foundation for Research in Economics, Yale University.
    9. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    10. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    11. Chaohua Dong & Jiti Gao & Dag Tjostheim & Jiying Yin, 2016. "Specification Testing for Nonlinear Multivariate Cointegrating Regressions," Monash Econometrics and Business Statistics Working Papers 14/16, Monash University, Department of Econometrics and Business Statistics.
    12. Jiti Gao & Han Hong, 2014. "Nonparametric Regression Approach to Bayesian Estimation," Monash Econometrics and Business Statistics Working Papers 25/14, Monash University, Department of Econometrics and Business Statistics.
    13. Degui Li & Peter C.B. Phillips & Jiti Gao, 2017. "Kernel-Based Inference In Time-Varying Coefficient Cointegrating Regression," Cowles Foundation Discussion Papers 2109, Cowles Foundation for Research in Economics, Yale University.
    14. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    15. Degui Li & Peter C. B. Phillips & Jiti Gao, 2013. "Uniform Consistency of Nonstationary Kernel-Weighted Sample Covariances for Nonparametric Regression," Monash Econometrics and Business Statistics Working Papers 27/13, Monash University, Department of Econometrics and Business Statistics.
    16. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.
    17. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    18. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    19. Jiti Gao & Peter C.B. Phillips, 2013. "Functional Coefficient Nonstationary Regression," Cowles Foundation Discussion Papers 1911, Cowles Foundation for Research in Economics, Yale University.
    20. Noureddine Kouaissah & Sergio Ortobelli Lozza & Ikram Jebabli, 2022. "Portfolio Selection Using Multivariate Semiparametric Estimators and a Copula PCA-Based Approach," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 833-859, October.
    21. Chaohua Dong & Jiti Gao, 2014. "Specification Testing in Structural Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 2/14, Monash University, Department of Econometrics and Business Statistics.
    22. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.
    23. Zhishui Hu & Peter C.B. Phillips & Qiying Wang, 2019. "Nonlinear Cointegrating Power Function Regression with Endogeneity," Cowles Foundation Discussion Papers 2211, Cowles Foundation for Research in Economics, Yale University.
    24. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  44. Gao, Jiti & Tjøstheim, Dag & Yin, Jiying, 2013. "Estimation in threshold autoregressive models with a stationary and a unit root regime," Journal of Econometrics, Elsevier, vol. 172(1), pages 1-13.
    See citations under working paper version above.
  45. Dong, Chaohua & Gao, Jiti, 2013. "Solving replication problems in a complete market by orthogonal series expansion," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 306-317.
    See citations under working paper version above.
  46. Jia Chen & Jiti Gao & Degui Li, 2013. "Estimation in Partially Linear Single-Index Panel Data Models With Fixed Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 315-330, July.
    See citations under working paper version above.
  47. Jia Chen & Jiti Gao & Degui Li, 2013. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 928-955, November.
    See citations under working paper version above.
  48. Chen, Jia & Gao, Jiti & Li, Degui, 2012. "A New Diagnostic Test For Cross-Section Uncorrelatedness In Nonparametric Panel Data Models," Econometric Theory, Cambridge University Press, vol. 28(5), pages 1144-1163, October.

    Cited by:

    1. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    2. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    3. Guohua Feng & Jiti Gao & Fei Liu & Bin Peng, 2024. "Estimation and Inference for Three-Dimensional Panel Data Models," Papers 2404.08365, arXiv.org, revised Sep 2024.
    4. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    5. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    6. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    7. Lee, Jungyoon & Robinson, Peter, 2015. "Panel nonparametric regression with fixed effects," LSE Research Online Documents on Economics 61431, London School of Economics and Political Science, LSE Library.
    8. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    9. Jiti Gao & Guangming Pan & Yanrong Yang & Bo Zhang, 2019. "Estimation of Cross-Sectional Dependence in Large Panels," Papers 1904.06843, arXiv.org.
    10. Hyunseok Jung & Xiaodong Liu, 2023. "Testing for Peer Effects without Specifying the Network Structure," Papers 2306.09806, arXiv.org, revised Jul 2024.
    11. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    12. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    13. Jiti Gao & Guangming Pan & Yanrong Yang, 2016. "CEstimation of Structural Breaks in Large Panels with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 12/16, Monash University, Department of Econometrics and Business Statistics.
    14. Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2024. "Estimation and Inference for a Class of Generalized Hierarchical Models," Monash Econometrics and Business Statistics Working Papers 7/24, Monash University, Department of Econometrics and Business Statistics.
    15. G. Pan & J. Gao & Y. Yang & M. Guo, 2012. "Independence Test for High Dimensional Random Vectors," Monash Econometrics and Business Statistics Working Papers 1/12, Monash University, Department of Econometrics and Business Statistics.
    16. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Cambridge Working Papers in Economics 2239, Faculty of Economics, University of Cambridge.
    17. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    18. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    19. Gao, Jiti & Pan, Guangming & Yang, Yanrong, 2012. "Testing Independence for a Large Number of High–Dimensional Random Vectors," MPRA Paper 45073, University Library of Munich, Germany, revised 15 Mar 2013.
    20. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    21. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    22. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
    23. Arteaga-Molina, Luis A. & Rodríguez-Poo, Juan M., 2019. "Empirical likelihood based inference for a categorical varying-coefficient panel data model with fixed effects," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 110-124.
    24. Lee, Jungyoon & Robinson, Peter M., 2015. "Panel nonparametric regression with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 346-362.
    25. Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2023. "Estimation of Semiparametric Multi-Index Models Using Deep Neural Networks," Monash Econometrics and Business Statistics Working Papers 21/23, Monash University, Department of Econometrics and Business Statistics.
    26. Guangming Pan & Jiti Gao & Yanrong Yang & Meihui Guo, 2015. "Cross-sectional Independence Test for a Class of Parametric Panel Data Models," Monash Econometrics and Business Statistics Working Papers 17/15, Monash University, Department of Econometrics and Business Statistics.
    27. Jiti Gao & Guangming Pan & Yanrong Yang & Bo Zhang, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Monash Econometrics and Business Statistics Working Papers 9/19, Monash University, Department of Econometrics and Business Statistics.

  49. Chen, Jia & Gao, Jiti & Li, Degui, 2012. "Semiparametric trending panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 171(1), pages 71-85.
    See citations under working paper version above.
  50. Degui Li & Jia Chen & Jiti Gao, 2011. "Non‐parametric time‐varying coefficient panel data models with fixed effects," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 387-408, October.
    See citations under working paper version above.
  51. Xi Chen, Song & Gao, Jiti, 2011. "Simultaneous Specification Testing Of Mean And Variance Structures In Nonlinear Time Series Regression," Econometric Theory, Cambridge University Press, vol. 27(4), pages 792-843, August.

    Cited by:

    1. Perera, Indeewara & Silvapulle, Mervyn J., 2023. "Bootstrap specification tests for dynamic conditional distribution models," Journal of Econometrics, Elsevier, vol. 235(2), pages 949-971.
    2. Álvarez-Liébana, J. & López-Pérez, A. & González-Manteiga, W. & Febrero-Bande, M., 2025. "A goodness-of-fit test for functional time series with applications to Ornstein-Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
    3. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    4. Okorie, David Iheke, 2025. "A gentle reminder: Should returns be interpreted as log differences?," International Review of Financial Analysis, Elsevier, vol. 97(C).

  52. Gao, Jiti & Wang, Qiying & Yin, Jiying, 2011. "Specification Testing In Nonlinear Time Series With Long-Range Dependence," Econometric Theory, Cambridge University Press, vol. 27(2), pages 260-284, April.
    See citations under working paper version above.
  53. Zhengyan Lin & Degui Li & Jiti Gao, 2009. "Local Linear M‐estimation in non‐parametric spatial regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 286-314, May.

    Cited by:

    1. Tang Qingguo, 2015. "Robust estimation for spatial semiparametric varying coefficient partially linear regression," Statistical Papers, Springer, vol. 56(4), pages 1137-1161, November.
    2. Tang Qingguo, 2013. "B-spline estimation for semiparametric varying-coefficient partially linear regression with spatial data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 361-378, June.
    3. Kuangyu Wen & Ximing Wu & David J. Leatham, 2021. "Spatially Smoothed Kernel Densities with Application to Crop Yield Distributions," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 349-366, September.
    4. Chen, Jia & Li, Degui & Zhang, Lixin, 2010. "Robust estimation in a nonlinear cointegration model," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 706-717, March.
    5. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    6. Hongxia Wang & Jinde Wang & Bo Huang, 2012. "Prediction for spatio-temporal models with autoregression in errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 217-244.

  54. Gao, Jiti & King, Maxwell & Lu, Zudi & Tjøstheim, Dag, 2009. "Nonparametric Specification Testing For Nonlinear Time Series With Nonstationarity," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1869-1892, December.
    See citations under working paper version above.
  55. Allen, David E. & Gao, Jiti & McAleer, Michael, 2009. "Modelling and managing financial risk: An overview," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2521-2524.

    Cited by:

    1. Gao, Jiti & McAleer, Michael & Allen, David E., 2008. "Econometric modelling in finance and risk management: An overview," Journal of Econometrics, Elsevier, vol. 147(1), pages 1-4, November.
    2. Ledermann, Daniel & Alexander, Carol, 2012. "Further properties of random orthogonal matrix simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 83(C), pages 56-79.
    3. Xue, Jian & Ding, Jing & Zhao, Laijun & Zhu, Di & Li, Lei, 2022. "An option pricing model based on a renewable energy price index," Energy, Elsevier, vol. 239(PB).

  56. Jiti Gao & Yongmiao Hong, 2008. "Central limit theorems for generalized -statistics with applications in nonparametric specification," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(1), pages 61-76.

    Cited by:

    1. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    2. Tae Kim & Zhi-Ming Luo & Chiho Kim, 2011. "The central limit theorem for degenerate variable -statistics under dependence," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 683-699.
    3. Mammen, Enno & Van Keilegom, Ingrid & Yu, Kyusang, 2013. "Expansion for Moments of Regression Quantiles with Applications to Nonparametric Testing," LIDAM Discussion Papers ISBA 2013027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2012. "International market links and volatility transmission," Journal of Econometrics, Elsevier, vol. 170(1), pages 117-141.

  57. Gao, Jiti & Lu, Zudi & Tjøstheim, Dag, 2008. "Moment inequalities for spatial processes," Statistics & Probability Letters, Elsevier, vol. 78(6), pages 687-697, April.

    Cited by:

    1. Sophie Dabo-Niang & Zoulikha Kaid & Ali Laksaci, 2015. "Asymptotic properties of the kernel estimate of spatial conditional mode when the regressor is functional," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(2), pages 131-160, April.
    2. Sophie Dabo-Niang & Sidi Ould-Abdi & Ahmedoune Ould-Abdi & Aliou Diop, 2014. "Consistency of a nonparametric conditional mode estimator for random fields," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 1-39, March.
    3. Zhenyu Jiang & Nengxiang Ling & Zudi Lu & Dag Tj⊘stheim & Qiang Zhang, 2020. "On bandwidth choice for spatial data density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 817-840, July.

  58. Gao, Jiti & Casas, Isabel, 2008. "Specification testing in discretized diffusion models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 131-140, November.
    See citations under working paper version above.
  59. Gao, Jiti & Gijbels, Irène, 2008. "Bandwidth Selection in Nonparametric Kernel Testing," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1584-1594.
    See citations under working paper version above.
  60. Gao, Jiti & McAleer, Michael & Allen, David E., 2008. "Econometric modelling in finance and risk management: An overview," Journal of Econometrics, Elsevier, vol. 147(1), pages 1-4, November.
    See citations under working paper version above.
  61. Gao, Jiti & Gijbels, Irene & Van Bellegem, Sebastien, 2008. "Nonparametric simultaneous testing for structural breaks," Journal of Econometrics, Elsevier, vol. 143(1), pages 123-142, March.

    Cited by:

    1. Cizek, Pavel & Koo, Chao, 2017. "Jump-Preserving Varying-Coefficient Models for Nonlinear Time Series," Other publications TiSEM c849e96f-3ad1-461e-96c6-f, Tilburg University, School of Economics and Management.
    2. Daniel J. Henderson & Christopher F. Parmeter & Liangjun Su, 2017. "M-Estimation of a Nonparametric Threshold Regression Model," Working Papers 2017-15, University of Miami, Department of Economics.
    3. Anna Bykhovskaya & Peter C. B. Phillips, 2017. "Boundary Limit Theory for Functional Local to Unity Regression," Cowles Foundation Discussion Papers 2108, Cowles Foundation for Research in Economics, Yale University.
    4. Marie Hušková & Matúš Maciak, 2017. "Discontinuities in robust nonparametric regression with α-mixing dependence," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(2), pages 447-475, April.
    5. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    6. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.
    7. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    8. Porter, Jack & Yu, Ping, 2015. "Regression discontinuity designs with unknown discontinuity points: Testing and estimation," Journal of Econometrics, Elsevier, vol. 189(1), pages 132-147.

  62. Casas, Isabel & Gao, Jiti, 2008. "Econometric estimation in long-range dependent volatility models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 72-83, November.
    See citations under working paper version above.
  63. Chen, Song Xi & Gao, Jiti, 2007. "An adaptive empirical likelihood test for parametric time series regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 950-972, December.

    Cited by:

    1. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    2. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    3. Jiti Gao & Maxwell King, 2011. "A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors," Monash Econometrics and Business Statistics Working Papers 20/11, Monash University, Department of Econometrics and Business Statistics.
    4. Gao, Jiti & Casas, Isabel, 2008. "Specification testing in discretized diffusion models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 131-140, November.
    5. Gong, Yun & Peng, Liang & Qi, Yongcheng, 2010. "Smoothed jackknife empirical likelihood method for ROC curve," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1520-1531, July.
    6. Zhiyuan Pan & Xianchao Sun, 2014. "Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures," International Journal of Economics and Financial Issues, Econjournals, vol. 4(1), pages 107-121.
    7. Aït-Sahalia, Yacine & Fan, Jianqing & Peng, Heng, 2009. "Nonparametric Transition-Based Tests for Jump Diffusions," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1102-1116.
    8. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.
    9. Chen, Song Xi & Lei, Lihua & Tu, Yundong, 2014. "Functional Coefficient Moving Average Model with Applications to forecasting Chinese CPI," MPRA Paper 67074, University Library of Munich, Germany, revised 2015.
    10. Jia Chen & Jiti Gao & Degui Li & Zhengyan Lin, 2014. "Specification Testing in Nonstationary Time Series Models," Discussion Papers 14/19, Department of Economics, University of York.
    11. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    12. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    13. Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.
    14. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    15. Chen, Song Xi & Cui, Hengjian, 2007. "On the second-order properties of empirical likelihood with moment restrictions," Journal of Econometrics, Elsevier, vol. 141(2), pages 492-516, December.
    16. Chen, Song Xi & Xu, Zheng, 2014. "On implied volatility for options—Some reasons to smile and more to correct," Journal of Econometrics, Elsevier, vol. 179(1), pages 1-15.

  64. Manuel Arapis & Jiti Gao, 2006. "Empirical Comparisons in Short-Term Interest Rate Models Using Nonparametric Methods," Journal of Financial Econometrics, Oxford University Press, vol. 4(2), pages 310-345.
    See citations under working paper version above.
  65. Jiti Gao & Kim Hawthorne, 2006. "Semiparametric estimation and testing of the trend of temperature series," Econometrics Journal, Royal Economic Society, vol. 9(2), pages 332-355, July.

    Cited by:

    1. Tingting Cheng & Jiti Gao & Xibin Zhang, 2015. "Bayesian Bandwidth Estimation In Nonparametric Time-Varying Coefficient Models," Monash Econometrics and Business Statistics Working Papers 3/15, Monash University, Department of Econometrics and Business Statistics.
    2. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    3. Isabel Casas & Jiti Gao & Shangyu Xie, 2018. "Modelling Time-Varying Income Elasticities of Health Care Expenditure for the OECD," CREATES Research Papers 2018-29, Department of Economics and Business Economics, Aarhus University.
    4. Kyungsik Nam, 2021. "Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing," Econometrics, MDPI, vol. 9(1), pages 1-25, February.
    5. Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global temperatures and greenhouse gases - a common features approach," Working Papers 2019-07-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    6. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
    7. Elkhan Richard Sadik-Zada & Wilhelm Loewenstein, 2020. "Drivers of CO 2 -Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses," Energies, MDPI, vol. 13(15), pages 1-24, August.
    8. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
    9. Chang, Yoosoon & Kaufmann, Robert K. & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2020. "Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate," Journal of Econometrics, Elsevier, vol. 214(1), pages 274-294.
    10. Atak, Alev & Linton, Oliver B. & Xiao, Zhijie, 2010. "A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom," MPRA Paper 22079, University Library of Munich, Germany.
    11. Chen, Liang & Dolado, Juan José & Gonzalo, Jesús & Ramos Ramirez, Andrey David, 2023. "Heterogeneous Predictive Association of CO2 with Global Warming," UC3M Working papers. Economics 36451, Universidad Carlos III de Madrid. Departamento de Economía.
    12. Javier Hidalgo & Jungyoon Lee, 2014. "A Cusum Test of Common Trends in Large Heterogeneous Panels," STICERD - Econometrics Paper Series 576, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    13. Aleksey Kolokolov & Giulia Livieri & Davide Pirino, 2022. "Testing for Endogeneity of Irregular Sampling Schemes," CEIS Research Paper 547, Tor Vergata University, CEIS, revised 19 Dec 2022.
    14. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    15. Ngai Hang Chan & Linhao Gao & Wilfredo Palma, 2022. "Simultaneous variable selection and structural identification for time‐varying coefficient models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 511-531, July.
    16. Yu, Deshui & Chen, Li, 2024. "Local predictability of stock returns and cash flows," Journal of Empirical Finance, Elsevier, vol. 77(C).
    17. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
    18. Yu, Deshui & Chen, Li & Li, Luyang, 2023. "Nonparametric modeling for the time-varying persistence of inflation," Economics Letters, Elsevier, vol. 225(C).
    19. Erhua Zhang & Xiaojun Song & Jilin Wu, 2022. "A non‐parametric test for multi‐variate trend functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 856-871, November.
    20. Yonghui Zhang & Liangjun Su & Peter C.B. Phillips, 2011. "Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects," Cowles Foundation Discussion Papers 1832, Cowles Foundation for Research in Economics, Yale University.
    21. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    22. Badi H. Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: a Bayesian Semiparametric Model With Random Coefficients for a Panel of OECD Countries," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 217-253, Emerald Group Publishing Limited.
    23. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    24. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
    25. Annegues, Ana Claudia & Rodrigues de Oliveira, Victor & Souza, Wallace Patrick Santos de Farias, 2017. "Thoughts on the inequality of opportunities: new evidence," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    26. Wang, Xiaoguang & Lu, Dawei & Song, Lixin, 2013. "Statistical inference for partially linear stochastic models with heteroscedastic errors," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 150-160.
    27. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    28. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    29. Azad Haider & Muhammad Iftikhar ul Husnain & Wimal Rankaduwa & Farzana Shaheen, 2021. "Nexus between Nitrous Oxide Emissions and Agricultural Land Use in Agrarian Economy: An ARDL Bounds Testing Approach," Sustainability, MDPI, vol. 13(5), pages 1-19, March.

  66. Yao, Juan & Gao, Jiti & Alles, Lakshman, 2005. "Dynamic investigation into the predictability of Australian industrial stock returns: Using financial and economic information," Pacific-Basin Finance Journal, Elsevier, vol. 13(2), pages 225-245, March.

    Cited by:

    1. Wu, Qiongbing & Shamsuddin, Abul, 2014. "Investor attention, information diffusion and industry returns," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 30-43.
    2. Jurdi, Doureige J., 2022. "Predicting the Australian equity risk premium," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    3. Yiwen (Paul) Dou & David R. Gallagher & David Schneider & Terry S. Walter, 2012. "Out-of-sample stock return predictability in Australia," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 461-479, December.
    4. Philip Gray, 2008. "Economic significance of predictability in Australian equities," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 48(5), pages 783-805, December.
    5. Camilo Serrano & Martin Hoesli, 2012. "Fractional Cointegration Analysis of Securitized Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 44(3), pages 319-338, April.
    6. Watson, John & Wickramanayake, J., 2012. "The relationship between aggregate managed fund flows and share market returns in Australia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 451-472.
    7. Ramiah, Vikash & Cam, Marie-Anne & Calabro, Michael & Maher, David & Ghafouri, Shahab, 2010. "Changes in equity returns and volatility across different Australian industries following the recent terrorist attacks," Pacific-Basin Finance Journal, Elsevier, vol. 18(1), pages 64-76, January.

  67. Jiti Gao & Howell Tong, 2004. "Semiparametric non‐linear time series model selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(2), pages 321-336, May.

    Cited by:

    1. Philipp Ratz, 2022. "Nonparametric Value-at-Risk via Sieve Estimation," Papers 2205.07101, arXiv.org.
    2. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    3. Gao, Jiti & Tong, Howell, 2002. "Nonparametric and semiparametric regression model selection," MPRA Paper 11987, University Library of Munich, Germany, revised Feb 2004.
    4. Degui Li & Jia Chen & Zhengyan Lin, 2009. "Variable selection in partially time-varying coefficient models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(5), pages 553-566.
    5. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    6. Dong, Chaohua & Gao, Jiti & Tong, Howell, 2006. "Semiparametric penalty function method in partially linear model selection," MPRA Paper 11975, University Library of Munich, Germany, revised Aug 2006.
    7. Jansen, Dennis W. & Li, Qi & Wang, Zijun & Yang, Jian, 2008. "Fiscal policy and asset markets: A semiparametric analysis," Journal of Econometrics, Elsevier, vol. 147(1), pages 141-150, November.
    8. Chen, Xirong & Li, Degui & Li, Qi & Li, Zheng, 2019. "Nonparametric estimation of conditional quantile functions in the presence of irrelevant covariates," Journal of Econometrics, Elsevier, vol. 212(2), pages 433-450.
    9. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.

  68. Gao, Jiti & King, Maxwell, 2004. "Adaptive Testing In Continuous-Time Diffusion Models," Econometric Theory, Cambridge University Press, vol. 20(5), pages 844-882, October.

    Cited by:

    1. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007.
    2. Bagkavos, Dimitrios & Patil, Prakash N. & Wood, Andrew T.A., 2023. "Nonparametric goodness-of-fit testing for a continuous multivariate parametric model," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    3. Jiti Gao & Maxwell King, 2011. "A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors," Monash Econometrics and Business Statistics Working Papers 20/11, Monash University, Department of Econometrics and Business Statistics.
    4. Gao, Jiti & Casas, Isabel, 2008. "Specification testing in discretized diffusion models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 131-140, November.
    5. Chen, Bin & Hong, Yongmiao, 2011. "Generalized spectral testing for multivariate continuous-time models," Journal of Econometrics, Elsevier, vol. 164(2), pages 268-293, October.
    6. Álvarez-Liébana, J. & López-Pérez, A. & González-Manteiga, W. & Febrero-Bande, M., 2025. "A goodness-of-fit test for functional time series with applications to Ornstein-Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
    7. Zhao, Zhibiao, 2011. "Nonparametric model validations for hidden Markov models with applications in financial econometrics," Journal of Econometrics, Elsevier, vol. 162(2), pages 225-239, June.
    8. Patrick Saart & Jiti Gao, 2012. "Semiparametric Methods in Nonlinear Time Series Analysis: A Selective Review," Monash Econometrics and Business Statistics Working Papers 21/12, Monash University, Department of Econometrics and Business Statistics.
    9. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    10. Gao, Jiti & Lu, Zudi & Tjøstheim, Dag, 2008. "Moment inequalities for spatial processes," Statistics & Probability Letters, Elsevier, vol. 78(6), pages 687-697, April.
    11. Manuel Arapis & Jiti Gao, 2006. "Empirical Comparisons in Short-Term Interest Rate Models Using Nonparametric Methods," Journal of Financial Econometrics, Oxford University Press, vol. 4(2), pages 310-345.
    12. Kim, Seonjin & Zhao, Zhibiao, 2014. "Specification test for Markov models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 118-133.
    13. Péter Farkas, 2013. "Counting Process Generated by Boundary-crossing Events. Theory and Statistical Applications," CEU Working Papers 2013_4, Department of Economics, Central European University.
    14. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    15. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    16. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    17. Monsalve-Cobis, Abelardo & González-Manteiga, Wenceslao & Febrero-Bande, Manuel, 2011. "Goodness-of-fit test for interest rate models: An approach based on empirical processes," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3073-3092, December.
    18. A. López-Pérez & M. Febrero-Bande & W. González-Manteiga, 2025. "Estimation and specification test for diffusion models with stochastic volatility," Statistical Papers, Springer, vol. 66(2), pages 1-36, February.
    19. Zhao, Zhibiao, 2010. "Density estimation for nonlinear parametric models with conditional heteroscedasticity," Journal of Econometrics, Elsevier, vol. 155(1), pages 71-82, March.
    20. Jansen, Dennis W. & Li, Qi & Wang, Zijun & Yang, Jian, 2008. "Fiscal policy and asset markets: A semiparametric analysis," Journal of Econometrics, Elsevier, vol. 147(1), pages 141-150, November.
    21. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    22. Zu, Yang & Boswijk, H. Peter, 2017. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 53-75.
    23. Pipat Wongsaart & Jiti Gao, 2011. "Nonparametric Kernel Testing in Semiparametric Autoregressive Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 18/11, Monash University, Department of Econometrics and Business Statistics.
    24. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.
    25. Gao, Jiti & Gijbels, Irene & Van Bellegem, Sebastien, 2008. "Nonparametric simultaneous testing for structural breaks," Journal of Econometrics, Elsevier, vol. 143(1), pages 123-142, March.
    26. Zu, Yang, 2015. "Nonparametric specification tests for stochastic volatility models based on volatility density," Journal of Econometrics, Elsevier, vol. 187(1), pages 323-344.
    27. Zu, Y., 2015. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Working Papers 15/02, Department of Economics, City University London.

  69. Juan Yao & Jiti Gao, 2004. "Computer-Intensive Time-Varying Model Approach to the Systematic Risk of Australian Industrial Stock Returns," Australian Journal of Management, Australian School of Business, vol. 29(1), pages 121-145, June.

    Cited by:

    1. Francisco José López-Arceiz & Ana José Bellostas-Pérezgrueso & José Mariano Moneva, 2018. "Evaluation of the Cultural Environment’s Impact on the Performance of the Socially Responsible Investment Funds," Journal of Business Ethics, Springer, vol. 150(1), pages 259-278, June.
    2. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    3. Sascha Mergner & Jan Bulla, 2005. "Time-varying Beta Risk of Pan-European Industry Portfolios: A Comparison of Alternative Modeling Techniques," Finance 0510029, University Library of Munich, Germany.
    4. Hooy Chee-Wooi & Robert D. Brooks, 2015. "The Components of Systematic Risk and Their Determinants in The Malaysian Equity Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 11(2), pages 151-176.
    5. Sercan Demiralay & Erhan Kilincarslan, 2024. "Uncertainty Measures and Sector-Specific REITs in a Regime-Switching Environment," The Journal of Real Estate Finance and Economics, Springer, vol. 69(3), pages 545-584, October.
    6. Zhou, Jian, 2013. "Conditional market beta for REITs: A comparison of modeling techniques," Economic Modelling, Elsevier, vol. 30(C), pages 196-204.
    7. Bulla, Jan & Bulla, Ingo, 2006. "Stylized facts of financial time series and hidden semi-Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2192-2209, December.
    8. Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
    9. Holmes, Kathryn A. & Faff, Robert, 2008. "Estimating the performance attributes of Australian multi-sector managed funds within a dynamic Kalman filter framework," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 998-1011, December.
    10. Antonio Terceño & María Glòria Barberà-Mariné & Yanina Laumann, 2018. "Análisis de los coeficientes beta: evidencia en el mercado de activos chileno," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 21(3), pages 076-093, December.

  70. Gao, Jiti & Anh, Vo & Heyde, Chris, 2002. "Statistical estimation of nonstationary Gaussian processes with long-range dependence and intermittency," Stochastic Processes and their Applications, Elsevier, vol. 99(2), pages 295-321, June.
    See citations under working paper version above.
  71. Gao, Jiti & Tong, Howell & Wolff, Rodney, 2002. "Model Specification Tests in Nonparametric Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 324-359, November.

    Cited by:

    1. Chen, Song Xi & Gao, Jiti, 2007. "An adaptive empirical likelihood test for parametric time series regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 950-972, December.
    2. Pourkhanali, Armin & Tafakori, Laleh & Bee, Marco, 2023. "Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Dabo-Niang, Sophie & Francq, Christian & Zakoian, Jean-Michel, 2009. "Combining parametric and nonparametric approaches for more efficient time series prediction," MPRA Paper 16893, University Library of Munich, Germany.
    4. Sophie DABO-NIANG & Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Combining Nonparametric and Optimal Linear Time Series Predictions," Working Papers 2009-18, Center for Research in Economics and Statistics.
    5. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.
    6. Gao, Jiti & Tong, Howell, 2002. "Nonparametric and semiparametric regression model selection," MPRA Paper 11987, University Library of Munich, Germany, revised Feb 2004.
    7. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    8. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    9. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    10. Lin, Yingqian & Tu, Yundong, 2020. "Sieve extremum estimation of a semiparametric transformation model," Economics Letters, Elsevier, vol. 189(C).
    11. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    12. Chaohua Dong & Jiti Gao, 2012. "Specification Testing Driven by Orthogonal Series in Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 20/12, Monash University, Department of Econometrics and Business Statistics.
    13. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    14. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    15. Chaohua Dong & Jiti Gao, 2014. "Specification Testing in Structural Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 2/14, Monash University, Department of Econometrics and Business Statistics.
    16. Ivan Korolev, 2018. "A Consistent Heteroskedasticity Robust LM Type Specification Test for Semiparametric Models," Papers 1810.07620, arXiv.org, revised Nov 2019.
    17. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    18. Chaohua Dong & Jiti Gao & Dag Tjostheim, 2014. "Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 7/14, Monash University, Department of Econometrics and Business Statistics.

  72. Jiti Gao & Vo Anh & Chris Heyde & Quang Tieng, 2001. "Parameter Estimation of Stochastic Processes with Long‐range Dependence and Intermittency," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(5), pages 517-535, September.

    Cited by:

    1. Leonenko, N.N. & Sakhno, L.M., 2006. "On the Whittle estimators for some classes of continuous-parameter random processes and fields," Statistics & Probability Letters, Elsevier, vol. 76(8), pages 781-795, April.
    2. Casas, Isabel & Gao, Jiti, 2008. "Econometric estimation in long-range dependent volatility models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 72-83, November.
    3. Anh, V.V. & Leonenko, N.N. & Sakhno, L.M., 2007. "Statistical inference using higher-order information," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 706-742, April.
    4. Gao, jiti & Anh, vo & Heyde, christopher, 1999. "Statistical estimation of nonstationaryGaussian processes with long-range dependence and intermittency," MPRA Paper 11972, University Library of Munich, Germany, revised 23 Oct 2001.
    5. A. V. Ivanov & N. N. Leonenko & I. V. Orlovskyi, 2020. "On the Whittle estimator for linear random noise spectral density parameter in continuous-time nonlinear regression models," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 129-169, April.
    6. Gao, Jiti, 2002. "Modeling long-range dependent Gaussian processes with application in continuous-time financial models," MPRA Paper 11973, University Library of Munich, Germany, revised 18 Sep 2003.
    7. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.

  73. Gao, Jiti & Anh, Vo, 2000. "A central limit theorem for a random quadratic form of strictly stationary processes," Statistics & Probability Letters, Elsevier, vol. 49(1), pages 69-79, August.

    Cited by:

    1. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    2. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007.
    3. Gao, Jiti & Tong, Howell, 2002. "Nonparametric and semiparametric regression model selection," MPRA Paper 11987, University Library of Munich, Germany, revised Feb 2004.
    4. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.

  74. Jiti Gao & Hua Liang, 1997. "Statistical Inference in Single-Index and Partially Nonlinear Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 49(3), pages 493-517, September.

    Cited by:

    1. Gao, Jiti & Tong, Howell & Wolff, Rodney, 2002. "Model Specification Tests in Nonparametric Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 324-359, November.
    2. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    3. Qingming Zou & Zhongyi Zhu, 2014. "M-estimators for single-index model using B-spline," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 225-246, February.
    4. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    5. Xiaobing Zhao & Xian Zhou, 2020. "Partial sufficient dimension reduction on additive rates model for recurrent event data with high-dimensional covariates," Statistical Papers, Springer, vol. 61(2), pages 523-541, April.
    6. Francesco Bravo & Ba M. Chu & David T. Jacho-Chávez, 2017. "Semiparametric estimation of moment condition models with weakly dependent data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(1), pages 108-136, January.
    7. Huang, Tzee-Ming & Chen, Hung, 2008. "Estimating the parametric component of nonlinear partial spline model," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1665-1680, September.
    8. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    9. Sun, Shuang & Song, Zening & Song, Xiaojun, 2025. "Unified specification tests in partially linear time series models," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
    10. Liu, Jialuo & Chu, Tingjin & Zhu, Jun & Wang, Haonan, 2021. "Semiparametric method and theory for continuously indexed spatio-temporal processes," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    11. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    12. Strzalkowska-Kominiak, Ewa & Cao, Ricardo, 2013. "Maximum likelihood estimation for conditional distribution single-index models under censoring," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 74-98.

  75. Gao, Jiti, 1995. "The laws of the iterated logarithm of some estimates in partly linear models," Statistics & Probability Letters, Elsevier, vol. 25(2), pages 153-162, November.

    Cited by:

    1. You, Jinhong & Zhou, Xian, 2005. "The law of iterated logarithm of estimators for partially linear panel data models," Statistics & Probability Letters, Elsevier, vol. 75(4), pages 267-279, December.
    2. You, Jinhong & Chen, Gemai, 2006. "Estimation of a semiparametric varying-coefficient partially linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 324-341, February.
    3. You, Jinhong & Zhou, Xian, 2006. "Statistical inference in a panel data semiparametric regression model with serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 844-873, April.
    4. Jinhong You & Xian Zhou & Lixing Zhu & Bin Zhou, 2011. "Weighted denoised minimum distance estimation in a regression model with autocorrelated measurement errors," Statistical Papers, Springer, vol. 52(2), pages 263-286, May.
    5. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    6. Jinhong You & Xian Zhou, 2010. "Statistical inference on seemingly unrelated varying coefficient partially linear models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(2), pages 227-253, May.
    7. Silvia Novo & Germán Aneiros & Philippe Vieu, 2025. "Semi-functional partial linear regression with measurement error: an approach based on kNN estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 34(1), pages 235-261, March.
    8. Gemai Chen & Jinhong You, 2005. "An asymptotic theory for semiparametric generalized least squares estimation in partially linear regression models," Statistical Papers, Springer, vol. 46(2), pages 173-193, April.
    9. Germán Aneiros & Nengxiang Ling & Philippe Vieu, 2015. "Error variance estimation in semi-functional partially linear regression models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(3), pages 316-330, September.
    10. Hu, Jianhua & You, Jinhong & Zhou, Xian, 2017. "Improved estimation of fixed effects panel data partially linear models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 96-111.
    11. You, Jinhong & Zhou, Xian & Zhu, Li-Xing, 2009. "Inference on a regression model with noised variables and serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1182-1197, July.
    12. Aneiros-Pérez, Germán & Vieu, Philippe, 2006. "Semi-functional partial linear regression," Statistics & Probability Letters, Elsevier, vol. 76(11), pages 1102-1110, June.
    13. You, Jinhong & Zhou, Xian & Zhou, Yong, 2010. "Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1079-1101, May.
    14. Su, Liangjun & Jin, Sainan, 2010. "Profile quasi-maximum likelihood estimation of partially linear spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 157(1), pages 18-33, July.

  76. Gao, Jiti & Liang, Hua, 1995. "Asymptotic normality of pseudo-LS estimator for partly linear autoregression models," Statistics & Probability Letters, Elsevier, vol. 23(1), pages 27-34, April.

    Cited by:

    1. Cai, Zongwu & Fan, Jianqing, 2000. "Average Regression Surface for Dependent Data," Journal of Multivariate Analysis, Elsevier, vol. 75(1), pages 112-142, October.

Chapters

  1. Jiti Gao & Maxwell King, 2014. "Specification Testing in Parametric Trending Models with Unknown Errors," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 151-202, Emerald Group Publishing Limited.

    Cited by:

    1. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.

Books

    Sorry, no citations of books recorded.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.