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Yongok Choi

Personal Details

First Name:Yongok
Middle Name:
Last Name:Choi
Suffix:
RePEc Short-ID:pch1839
[This author has chosen not to make the email address public]
Terminal Degree: Department of Economics; Indiana University (from RePEc Genealogy)

Affiliation

Economics
Chung-Ang University

Seoul, South Korea
http://econ.cau.ac.kr/
RePEc:edi:eccaukr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," Working Papers 2401, Department of Economics, University of Missouri.
  2. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2019. "Forecasting Regional Long-Run Energy Demand: A Functional Coefficient Panel Approach," Working Papers 1915, Department of Economics, University of Missouri.
  3. Choi, Yongok, 2016. "Longevity Risk in Korea," KDI Focus 69, Korea Development Institute (KDI).
  4. Choi, Yongok, 2015. "A Study on Measuring and Managing Longevity Risk," KDI Policy Studies 2015-18(K), Korea Development Institute (KDI).
  5. Yoosoon Chang & Yongok Choi & Chang Sik Kim & Joon Y. Park & J. Isaac Miller, 2013. "Disentangling Temporal Patterns in Elasticities: A Functional Coefficient Panel Analysis of Electricity Demand," Working Papers 1320, Department of Economics, University of Missouri.

Articles

  1. Yongok Choi & Giacomo Rondina & Todd B. Walker, 2023. "Information Aggregation Bias and Samuelson's Dictum," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(5), pages 1119-1145, August.
  2. Chang, Yoosoon & Choi, Yongok & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y., 2021. "Forecasting regional long-run energy demand: A functional coefficient panel approach," Energy Economics, Elsevier, vol. 96(C).
  3. Yongok Choi, 2020. "Impact of Longevity Risks on the Korean Government: Proposing a New Mortality Forecasting Model," Korean Economic Review, Korean Economic Association, vol. 36, pages 201-225.
  4. Chang, Yoosoon & Choi, Yongok & Park, Joon Y., 2017. "A new approach to model regime switching," Journal of Econometrics, Elsevier, vol. 196(1), pages 127-143.
  5. Chang, Yoosoon & Choi, Yongok & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y., 2016. "Disentangling temporal patterns in elasticities: A functional coefficient panel analysis of electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 232-243.
  6. Yoosoon Chang & Yongok Choi & Hwagyun Kim & Joon Y. Park, 2016. "Evaluating factor pricing models using high‐frequency panels," Quantitative Economics, Econometric Society, vol. 7(3), pages 889-933, November.
  7. Choi, Yongok & Jacewitz, Stefan & Park, Joon Y., 2016. "A reexamination of stock return predictability," Journal of Econometrics, Elsevier, vol. 192(1), pages 168-189.

Chapters

  1. Dohyung Kim & Taesuk Lee & Yongok Choi, 2021. "Fiscal implications of the 2015 government employees pension reform in Korea," Chapters, in: Robert L. Clark & YoungWook Lee & Andrew Mason (ed.), Fiscal Accountability and Population Aging, chapter 8, pages 155-181, Edward Elgar Publishing.
  2. Yongok Choi, 2021. "Enhancing accountability of Korea’s government funds system through consolidated management of surplus money in budget-type funds," Chapters, in: Robert L. Clark & YoungWook Lee & Andrew Mason (ed.), Fiscal Accountability and Population Aging, chapter 4, pages 73-92, Edward Elgar Publishing.

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. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2019. "Forecasting Regional Long-Run Energy Demand: A Functional Coefficient Panel Approach," Working Papers 1915, Department of Economics, University of Missouri.

    Cited by:

    1. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," CAMA Working Papers 2024-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Xin Ma & Yubin Cai & Hong Yuan & Yanqiao Deng, 2023. "Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States," Sustainability, MDPI, vol. 15(9), pages 1-26, April.
    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. Wang, You & Gong, Xu, 2022. "Analyzing the difference evolution of provincial energy consumption in China using the functional data analysis method," Energy Economics, Elsevier, vol. 105(C).
    5. Liddle, Brantley, 2023. "Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying," Energy Economics, Elsevier, vol. 124(C).
    6. Grzegorz Ślusarz & Dariusz Twaróg & Barbara Gołębiewska & Marek Cierpiał-Wolan & Jarosław Gołębiewski & Philipp Plutecki, 2023. "The Role of Biogas Potential in Building the Energy Independence of the Three Seas Initiative Countries," Energies, MDPI, vol. 16(3), pages 1-23, January.
    7. Miller, J. Isaac & Nam, Kyungsik, 2022. "Modeling peak electricity demand: A semiparametric approach using weather-driven cross-temperature response functions," Energy Economics, Elsevier, vol. 114(C).
    8. Rao, Congjun & Zhang, Yue & Wen, Jianghui & Xiao, Xinping & Goh, Mark, 2023. "Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model," Energy, Elsevier, vol. 263(PC).
    9. Zhao, Jing & Miller, J. Isaac & Binfield, Julian & Thompson, Wyatt, 2022. "Modeling and Forecasting Agricultural Commodity Support in the Developing Countries," Commissioned Papers 321785, International Agricultural Trade Research Consortium.

  2. Choi, Yongok, 2015. "A Study on Measuring and Managing Longevity Risk," KDI Policy Studies 2015-18(K), Korea Development Institute (KDI).

    Cited by:

    1. Yongok Choi, 2020. "Impact of Longevity Risks on the Korean Government: Proposing a New Mortality Forecasting Model," Korean Economic Review, Korean Economic Association, vol. 36, pages 201-225.
    2. Choi, Yongok, 2016. "Longevity Risk in Korea," KDI Focus 69, Korea Development Institute (KDI).

  3. Yoosoon Chang & Yongok Choi & Chang Sik Kim & Joon Y. Park & J. Isaac Miller, 2013. "Disentangling Temporal Patterns in Elasticities: A Functional Coefficient Panel Analysis of Electricity Demand," Working Papers 1320, Department of Economics, University of Missouri.

    Cited by:

    1. Ha-Hyun Jo & Minwoo Jang & Jaehyeok Kim, 2020. "How Population Age Distribution Affects Future Electricity Demand in Korea: Applying Population Polynomial Function," Energies, MDPI, vol. 13(20), pages 1-17, October.
    2. Fakhri J. Hasanov & Lester C. Hunt & Ceyhun I. Mikayilov, 2016. "Modeling and Forecasting Electricity Demand in Azerbaijan Using Cointegration Techniques," Energies, MDPI, vol. 9(12), pages 1-31, December.
    3. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    4. 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.
    5. Yongok Choi, 2020. "Impact of Longevity Risks on the Korean Government: Proposing a New Mortality Forecasting Model," Korean Economic Review, Korean Economic Association, vol. 36, pages 201-225.
    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. Kyungsik Nam & Sungro Lee & Hocheol Jeon, 2020. "Nonlinearity between CO 2 Emission and Economic Development: Evidence from a Functional Coefficient Panel Approach," Sustainability, MDPI, vol. 12(24), pages 1-10, December.
    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. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
    10. 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.
    11. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Carlo A. Bollino & Ceyhun Mahmudlu, 2017. "Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach," Energies, MDPI, vol. 10(11), pages 1-12, November.
    12. Miller, J. Isaac & Nam, Kyungsik, 2022. "Modeling peak electricity demand: A semiparametric approach using weather-driven cross-temperature response functions," Energy Economics, Elsevier, vol. 114(C).
    13. Meangbua, Onicha & Dhakal, Shobhakar & Kuwornu, John K.M., 2019. "Factors influencing energy requirements and CO2 emissions of households in Thailand: A panel data analysis," Energy Policy, Elsevier, vol. 129(C), pages 521-531.
    14. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand," Working Papers 1409, Department of Economics, University of Missouri.
    15. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2019. "Forecasting Regional Long-Run Energy Demand: A Functional Coefficient Panel Approach," Working Papers 1915, Department of Economics, University of Missouri.
    16. 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).
    17. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    18. Julián Pérez-García & Julián Moral-Carcedo, 2017. "Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis," Energies, MDPI, vol. 10(3), pages 1-20, March.
    19. 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.
    20. Mohammad Nure Alam, 2021. "Accessing the Effect of Renewables on the Wholesale Power Market," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 341-360.
    21. Jeyhun Mikayilov & Fred Joutz & Fakhri Hasanov, 2019. "Gasoline Demand in Saudi Arabia: Are the Price and Income Elasticities Constant?," Discussion Papers ks--2019-dp81, King Abdullah Petroleum Studies and Research Center.

Articles

  1. Chang, Yoosoon & Choi, Yongok & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y., 2021. "Forecasting regional long-run energy demand: A functional coefficient panel approach," Energy Economics, Elsevier, vol. 96(C).
    See citations under working paper version above.
  2. Chang, Yoosoon & Choi, Yongok & Park, Joon Y., 2017. "A new approach to model regime switching," Journal of Econometrics, Elsevier, vol. 196(1), pages 127-143.

    Cited by:

    1. Yoosoon Chang & Ana Maria Herrera & Elena Pesavento, 2023. "Oil Prices Uncertainty, Endogenous Regime Switching, and Inflation Anchoring," CAEPR Working Papers 2023-002 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Binh Thai Pham & Hector Sala, 2023. "Fiscal deficits and the socioeconomic consequences of rebalancing: Insights from a TVP‐VAR with stochastic volatility," Australian Economic Papers, Wiley Blackwell, vol. 62(2), pages 214-235, June.
    3. Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2021. "Multimodality In Macrofinancial Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 861-886, May.
    4. Cho, Dooyeon & Han, Heejoon & Lee, Na Kyeong, 2019. "Carry trades and endogenous regime switches in exchange rate volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 255-268.
    5. Andrei Sirchenko, 2019. "A regime-switching model for the federal funds rate target," UvA-Econometrics Working Papers 19-01, Universiteit van Amsterdam, Dept. of Econometrics.
    6. Stéphane Lhuissier, 2019. "Bayesian Inference for Markov-switching Skewed Autoregressive Models," Working papers 726, Banque de France.
    7. Chang, Yoosoon & Kwak, Boreum & Qiu, Shi, 2021. "U.S. monetary and fiscal policy regime changes and their interactions," IWH Discussion Papers 12/2021, Halle Institute for Economic Research (IWH).
    8. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
    9. Heejoon Han & Na Kyeong Lee, 2018. "Modeling the Dynamics between Stock Price and Dividend: An Endogenous Regime Switching Approach," Korean Economic Review, Korean Economic Association, vol. 34, pages 213-235.
    10. Fédéric Holm-Hadulla & Kirstin Hubrich, 2017. "Macroeconomic Implications of Oil Price Fluctuations : A Regime-Switching Framework for the Euro Area," Finance and Economics Discussion Series 2017-063, Board of Governors of the Federal Reserve System (U.S.).
    11. Julien Albertini & Stéphane Moyen, 2020. "A General and Efficient Method for Solving Regime-Switching DSGE Models," Working Papers 2035, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    12. Ruijun Bu & Jie Cheng & Fredj Jawadi, 2022. "A latent‐factor‐driven endogenous regime‐switching non‐Gaussian model: Evidence from simulation and application," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3881-3896, October.
    13. Chang, Yoosoon & Maih, Junior & Tan, Fei, 2021. "Origins of monetary policy shifts: A New approach to regime switching in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    14. Chaojun Li & Yan Liu, 2020. "Asymptotic Properties of the Maximum Likelihood Estimator in Regime-Switching Models with Time-Varying Transition Probabilities," Papers 2010.04930, arXiv.org, revised Dec 2021.
    15. Nguyen Bao Anh & Yiqiang Q. Zhao, 2021. "Half Century of Gold Price: Regime-Switching and Forecasting Framework," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 1-18, May.
    16. Andrei A. Sirchenko, 2017. "An endogenous regime-switching model of ordered choice with an application to federal funds rate target," 2017 Papers psi424, Job Market Papers.
    17. Paul Ho & Thomas A. Lubik & Christian Matthes, 2020. "How To Go Viral: A COVID-19 Model with Endogenously Time-Varying Parameters," Working Paper 20-10, Federal Reserve Bank of Richmond.
    18. Yoosoon Chang & Fei Tan & Xin Wei, 2018. "State Space Models with Endogenous Regime Switching," CAEPR Working Papers 2018-012, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    19. 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.
    20. Yoosoon Chang & Boreum Kwak, 2017. "U.S. Monetary-Fiscal Regime Changes in the Presence of Endogenous Feedback in Policy Rules," CAEPR Working Papers 2017-016, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    21. Zhentao Shi & Huanhuan Zheng, 2018. "Structural Estimation of Behavioral Heterogeneity," Papers 1802.03735, arXiv.org, revised Jun 2018.
    22. Zhicheng Li & Haipeng Xing & Xinyun Chen, 2019. "A multifactor regime-switching model for inter-trade durations in the limit order market," Papers 1912.00764, arXiv.org.
    23. Yoosoon Chang & Junior Maih & Fei Tan, 2018. "State Space Models with Endogenous Regime Switching," Working Papers No 9/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    24. Suah, Jing Lian, 2020. "Veiled Expectations: The Heterogeneous Impact of Exchange Rate Shocks at the Sectoral-Level," MPRA Paper 109086, University Library of Munich, Germany.
    25. Focardi, Sergio M. & Fabozzi, Frank J. & Mazza, Davide, 2019. "Modeling local trends with regime shifting models with time-varying probabilities," International Review of Financial Analysis, Elsevier, vol. 66(C).
    26. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    27. Javier Hidalgo & Heejun Lee & Heejun Lee & Jungyoon Lee & Myung Hwan Seo, 2021. "Minimax Risk in Estimating Kink Threshold and Testing," STICERD - Econometrics Paper Series 622, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    28. Lhuissier, Stéphane, 2022. "Financial conditions and macroeconomic downside risks in the euro area," European Economic Review, Elsevier, vol. 143(C).
    29. Jeong, Minsoo, 2022. "Modelling persistent stationary processes in continuous time," Economic Modelling, Elsevier, vol. 109(C).
    30. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
    31. Hao, Shiming, 2021. "True structure change, spurious treatment effect? A novel approach to disentangle treatment effects from structure changes," MPRA Paper 108679, University Library of Munich, Germany.
    32. Gilbert Mbara, 2017. "Business Cycle Dating after the Great Moderation: A Consistent Two – Stage Maximum Likelihood Method," Working Papers 2017-13, Faculty of Economic Sciences, University of Warsaw.
    33. Javier Hidalgo & Heejun Lee & Jungyoon Lee & Myung Hwan Seo, 2022. "Minimax Risk in Estimating Kink Threshold and Testing Continuity," Papers 2203.00349, arXiv.org.
    34. 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).
    35. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    36. Mika Meitz & Pentti Saikkonen, 2017. "Testing for observation-dependent regime switching in mixture autoregressive models," Papers 1711.03959, arXiv.org.
    37. Kirstin Hubrich & Daniel F. Waggoner, 2022. "The Transmission of Financial Shocks and Leverage of Financial Institutions: An Endogenous Regime-Switching Framework," FRB Atlanta Working Paper 2022-5, Federal Reserve Bank of Atlanta.
    38. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
    39. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    40. Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.

  3. Chang, Yoosoon & Choi, Yongok & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y., 2016. "Disentangling temporal patterns in elasticities: A functional coefficient panel analysis of electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 232-243.
    See citations under working paper version above.
  4. Yoosoon Chang & Yongok Choi & Hwagyun Kim & Joon Y. Park, 2016. "Evaluating factor pricing models using high‐frequency panels," Quantitative Economics, Econometric Society, vol. 7(3), pages 889-933, November.

    Cited by:

    1. Zi-Yi Guo, 2017. "Order Flow and Exchange Rate Dynamics in Continuous Time: New Evidence from Martingale Regression," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 507-512.
    2. Guo, Zi-Yi, 2017. "Martingale Regressions for a Continuous Time Model of Exchange Rates," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12(2), pages 40-45.
    3. Jasman Tuyon & Zamri Ahmad, 2018. "Behavioural Asset Pricing Determinants in a Factor and Style Investing Framework," Capital Markets Review, Malaysian Finance Association, vol. 26(2), pages 32-52.
    4. Jasman Tuyon & Zamri Ahmad, 2021. "Dynamic risk attributes in Malaysia stock markets: Behavioural finance insights," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5793-5814, October.

  5. Choi, Yongok & Jacewitz, Stefan & Park, Joon Y., 2016. "A reexamination of stock return predictability," Journal of Econometrics, Elsevier, vol. 192(1), pages 168-189.

    Cited by:

    1. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility Regressions with Fat Tails," TSE Working Papers 20-1097, Toulouse School of Economics (TSE).
    2. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    3. Bingduo Yang & Xiaohui Liu & Liang Peng & Zongwu Cai, 2018. "Unified Tests for a Dynamic Predictive Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201808, University of Kansas, Department of Economics, revised Sep 2018.
    4. Xiaosai Liao & Xinjue Li & Qingliang Fan, 2024. "Robust Inference for Multiple Predictive Regressions with an Application on Bond Risk Premia," Papers 2401.01064, arXiv.org.
    5. Jihyun Kim & Nour Meddahi, 2020. "Volatility Regressions with Fat Tails," Post-Print hal-03142647, HAL.
    6. Rustam Ibragimov & Jihyun Kim & Anton Skrobotov, 2020. "New robust inference for predictive regressions," Papers 2006.01191, arXiv.org, revised Mar 2023.
    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. Zongwu Cai & Seong Yeon Chang, 2018. "A New Test In A Predictive Regression with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201811, University of Kansas, Department of Economics, revised Dec 2018.
    9. 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.
    10. Liu, Xiaohui & Yang, Bingduo & Cai, Zongwu & Peng, Liang, 2019. "A unified test for predictability of asset returns regardless of properties of predicting variables," Journal of Econometrics, Elsevier, vol. 208(1), pages 141-159.
    11. 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.
    12. Becker, Janis & Leschinski, Christian, 2018. "Directional Predictability of Daily Stock Returns," Hannover Economic Papers (HEP) dp-624, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Hong, Shaoxin & Zhang, Zhengyi & Cai, Zongwu, 2021. "Testing heteroskedasticity for predictive regressions with nonstationary regressors," Economics Letters, Elsevier, vol. 201(C).
    14. Cai, Zongwu & Chen, Haiqiang & Liao, Xiaosai, 2023. "A new robust inference for predictive quantile regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 227-250.
    15. Fan, Rui & Lee, Ji Hyung, 2019. "Predictive quantile regressions under persistence and conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 213(1), pages 261-280.

Chapters

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ENE: Energy Economics (3) 2013-11-16 2019-12-23 2024-01-22
  2. NEP-ECM: Econometrics (2) 2013-11-16 2024-01-22
  3. NEP-FOR: Forecasting (1) 2019-12-23
  4. NEP-ORE: Operations Research (1) 2019-12-23

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