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Dukpa Kim

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Dukpa Kim, 2014. "Common breaks in time trends for large panel data with a factor structure," Econometrics Journal, Royal Economic Society, vol. 17(3), pages 301-337, October.

    Mentioned in:

    1. Common breaks in time trends for large panel data with a factor structure (Econometrics J 2014) in ReplicationWiki ()

Working papers

  1. Dukpa Kim & Tatsushi Oka & Francisco Estrada & Pierre Perron, 2018. "Inference Related to Common Breaks in a Multivariate System with Joined Segmented Trends with Applications to Global and Hemispheric Temperatures," Papers 1805.09937, arXiv.org.

    Cited by:

    1. Ar'anzazu de Juan & Pilar Poncela & Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2022. "Economic activity and climate change," Papers 2206.03187, arXiv.org, revised Jun 2022.
    2. Carrion-i-Silvestre, Josep Lluís & Kim, Dukpa, 2021. "Statistical tests of a simple energy balance equation in a synthetic model of cotrending and cointegration," Journal of Econometrics, Elsevier, vol. 224(1), pages 22-38.
    3. 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.
    4. Grant R. McDermott, 2021. "Skeptic priors and climate consensus," Climatic Change, Springer, vol. 166(1), pages 1-23, May.
    5. Tatsushi Oka & Pierre Perron, 2018. "Testing for common breaks in a multiple equations system," Monash Econometrics and Business Statistics Working Papers 3/18, Monash University, Department of Econometrics and Business Statistics.
    6. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    7. 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.
    8. Francisco Estrada & Luis Filipe Martins & Pierre Perron, 2017. "Characterizing and attributing the warming trend in sea and land surface temperatures," Boston University - Department of Economics - Working Papers Series WP2017-009, Boston University - Department of Economics.

  2. In Choi & Dukpa Kim & Yun Jung Kim & Noh-Sun Kwark, 2016. "A Multilevel Factor Model: Identification, Asymptotic Theory and Applications," Working Papers 1609, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).

    Cited by:

    1. Shi Yafeng & Ai Chunrong & Yanlong Shi & Ying Tingting & Xu Qunfang, 2023. "Large covariance estimation using a factor model with common and group‐specific factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2217-2248, December.
    2. Sung Hoon Choi & Donggyu Kim, 2023. "Large Global Volatility Matrix Analysis Based on Observation Structural Information," Papers 2305.01464, arXiv.org, revised Feb 2024.
    3. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
    4. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    5. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
    6. Venetis, Ioannis & Ladas, Avgoustinos, 2022. "Co-movement and global factors in sovereign bond yields," MPRA Paper 115801, University Library of Munich, Germany.
    7. Sung Hoon Choi & Donggyu Kim, 2022. "Large Volatility Matrix Analysis Using Global and National Factor Models," Papers 2208.12323, arXiv.org, revised Dec 2022.
    8. Carlos Vladimir Rodríguez-Caballero & Massimiliano Caporin, 2018. "A multilevel factor approach for the analysis of CDS commonality and risk contribution," CREATES Research Papers 2018-33, Department of Economics and Business Economics, Aarhus University.
    9. Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
    10. Carlos Vladimir Rodríguez-Caballero, 2016. "Panel Data with Cross-Sectional Dependence Characterized by a Multi-Level Factor Structure," CREATES Research Papers 2016-31, Department of Economics and Business Economics, Aarhus University.
    11. Camacho, Maximo & Lopez-Buenache, German, 2023. "Factor models for large and incomplete data sets with unknown group structure," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1205-1220.
    12. In Choi & Rui Lin & Yongcheol Shin, 2020. "Canonical Correlation-based Model Selection for the Multilevel Factors," Working Papers 2008, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    13. Kapetanios, George & Serlenga, Laura & Shin, Yongcheol, 2021. "Estimation and inference for multi-dimensional heterogeneous panel datasets with hierarchical multi-factor error structure," Journal of Econometrics, Elsevier, vol. 220(2), pages 504-531.
    14. 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.
    15. Choi, Sung Hoon & Kim, Donggyu, 2023. "Large volatility matrix analysis using global and national factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1917-1933.
    16. Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
    17. Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053r, Institute of Social and Economic Research, Osaka University, revised Mar 2020.
    18. Ergemen, Yunus Emre, 2022. "Forecasting inflation rates with multi-level international dependence," Economics Letters, Elsevier, vol. 214(C).
    19. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    20. Rodríguez-Caballero, Carlos Vladimir, 2022. "Energy consumption and GDP: a panel data analysis with multi-level cross-sectional dependence," Econometrics and Statistics, Elsevier, vol. 23(C), pages 128-146.
    21. Wang, Zongrun & Zhou, Ling & Mi, Yunlong & Shi, Yong, 2022. "Measuring dynamic pandemic-related policy effects: A time-varying parameter multi-level dynamic factor model approach," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    22. Shiwen Liu & Zhen Zhang & Junhua Yang & Wei Hu, 2022. "Exploring Increasing Urban Resident Electricity Consumption: The Spatial Spillover Effect of Resident Income," Energies, MDPI, vol. 15(12), pages 1-17, June.

  3. Dukpa Kim & Yohei Yamamoto, 2013. "Time Instability of the U.S. Monetary System: Multiple Break Tests and Reduced Rank TVP VAR," Global COE Hi-Stat Discussion Paper Series gd12-279, Institute of Economic Research, Hitotsubashi University.

    Cited by:

    1. Eddie Gerba & Klemens Hauzenberger, 2013. "Estimating US Fiscal and Monetary Interactions in a Time Varying VAR," Studies in Economics 1303, School of Economics, University of Kent.

  4. Josep Lluís Carrion-i-Silvestre & Dukpa Kim & Pierre Perron, 2007. "GLS-based unit root tests with multiple structural breaks both under the null and the alternative hypotheses," Boston University - Department of Economics - Working Papers Series wp2008-019, Boston University - Department of Economics.

    Cited by:

    1. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," PSE Working Papers halshs-00564897, HAL.
    2. Alfred A. Haug & Ian P. King, 2011. "Empirical Evidence on Inflation and Unemployment in the Long Run," Working Papers 1109, University of Otago, Department of Economics, revised Aug 2011.
    3. Mohitosh Kejriwal & Pierre Perron, 2009. "A Sequential Procedure to Determine the Number of Breaks in Trend with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series wp2009-005, Boston University - Department of Economics.
    4. Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "Testing for unit roots in the presence of a possible break in trend and non-stationary volatility," Discussion Papers 09/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    5. Ghoshray, Atanu & Kejriwal, Mohitosh & Wohar, Mark E., 2011. "Breaking Trends and the Prebisch-Singer Hypothesis: A Further Investigation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120387, European Association of Agricultural Economists.
    6. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2010. "Unit root testing under a local break in trend," Discussion Papers 10/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    7. Paulo M.M. Rodrigues & A. M. Robert Taylor, 2009. "The Flexible Fourier Form and Local GLS De-trended Unit Root Tests," Working Papers w200919, Banco de Portugal, Economics and Research Department.
    8. jair Ojeda Joya, 2009. "Purchasing Power Parity and Breaking Trend Functions in the Real Exchange Rate," Borradores de Economia 5521, Banco de la Republica.
    9. Mohitosh Kejriwal & Claude Lopez, 2013. "Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 892-927, November.

  5. Dukpa Kim & Pierre Perron, 2006. "Assessing the Relative Power of Structural Break Tests Using a Framework Based on the Approximate Bahadur Slope," Boston University - Department of Economics - Working Papers Series WP2006-063, Boston University - Department of Economics.

    Cited by:

    1. Andersen, Torben G. & Varneskov, Rasmus T., 2022. "Testing for parameter instability and structural change in persistent predictive regressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 361-386.
    2. Alessandro Casini & Pierre Perron, 2018. "Generalized Laplace Inference in Multiple Change-Points Models," Papers 1803.10871, arXiv.org, revised Jan 2021.
    3. Pierre Perron & Yohei Yamamoto, 2022. "Structural change tests under heteroskedasticity: Joint estimation versus two‐steps methods," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 389-411, May.
    4. Luis Filipe Martins & Pierre Perron, 2014. "Improved Tests for Forecast Comparisons in the Presence of Instabilities," Boston University - Department of Economics - Working Papers Series 2014-003, Boston University - Department of Economics.
    5. Seong Yeon Chang & Pierre Perron, 2013. "A Comparison of Alternative Methods to Construct Confidence Intervals for the Estimate of a Break Date in Linear Regression Models," Boston University - Department of Economics - Working Papers Series wp2015-010, Boston University - Department of Economics, revised 11 Oct 2015.
    6. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    7. Alessandro Casini & Pierre Perron, 2021. "Prewhitened Long-Run Variance Estimation Robust to Nonstationarity," Papers 2103.02235, arXiv.org, revised Dec 2021.
    8. Otilia Boldea & Alastair R. Hall, 2013. "Testing structural stability in macroeconometric models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 9, pages 206-228, Edward Elgar Publishing.
    9. Reese, Simon & Li, Yushu, 2013. "Testing for Structural Breaks in the Presence of Data Perturbations: Impacts and Wavelet Based Improvements," Working Papers 2013:36, Lund University, Department of Economics.
    10. Pierre Perron & Yohei Yamamoto, 2018. "Testing for Changes in Forecasting Performance," Boston University - Department of Economics - Working Papers Series WP2019-03, Boston University - Department of Economics, revised Dec 2018.
    11. Shahbaz, Muhammad & Ahmed, Khalid & Tiwari, Aviral Kumar & Jiao, Zhilun, 2019. "Resource Curse Hypothesis and Role of Oil Prices in USA," MPRA Paper 96633, University Library of Munich, Germany, revised 14 Oct 2019.
    12. Pierre Perron & Yohei Yamamoto, 2008. "On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests," Boston University - Department of Economics - Working Papers Series wp2008-006, Boston University - Department of Economics.
    13. Alessandro Casini, 2021. "Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models," Papers 2103.02981, arXiv.org.
    14. Zeng-Hua Lu, 2020. "Bahadur intercept with applications to one-sided testing," Statistical Papers, Springer, vol. 61(2), pages 645-658, April.
    15. Kurozumi Eiji, 2015. "Testing for Multiple Structural Changes with Non-Homogeneous Regressors," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 1-35, January.
    16. Tatsushi Oka & Pierre Perron, 2018. "Testing for common breaks in a multiple equations system," Monash Econometrics and Business Statistics Working Papers 3/18, Monash University, Department of Econometrics and Business Statistics.
    17. YAMAMOTO, Yohei & 山本, 庸平 & TANAKA, Shinya & 田中, 晋也, 2013. "Testing for Factor Loading Structural Change under Common Breaks," Discussion Papers 2013-17, Graduate School of Economics, Hitotsubashi University.
    18. Federico Belotti & Alessandro Casini & Leopoldo Catania & Stefano Grassi & Pierre Perron, 2023. "Simultaneous bandwidths determination for DK-HAC estimators and long-run variance estimation in nonparametric settings," Econometric Reviews, Taylor & Francis Journals, vol. 42(3), pages 281-306, February.
    19. Alessandro Casini & Pierre Perron, 2020. "Continuous Record Laplace-based Inference about the Break Date in Structural Change Models," Boston University - Department of Economics - Working Papers Series WP2020-014, Boston University - Department of Economics.
    20. Casini, Alessandro, 2023. "Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstationary models," Journal of Econometrics, Elsevier, vol. 235(2), pages 372-392.
    21. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    22. Zameer, Hashim & Yasmeen, Humaira & Zafar, Muhammad Wasif & Waheed, Abdul & Sinha, Avik, 2020. "Analyzing the association between Innovation, Economic Growth, and Environment: Divulging the Importance of FDI and Trade Openness in India," MPRA Paper 101323, University Library of Munich, Germany, revised 2020.
    23. Alessandro Casini & Taosong Deng & Pierre Perron, 2021. "Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference," Papers 2103.01604, arXiv.org, revised Nov 2021.

Articles

  1. Han, Chirok & Kim, Dukpa, 2020. "Testing for the null of block zero restrictions in common factor models," Economics Letters, Elsevier, vol. 188(C).

    Cited by:

    1. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.

  2. Kim, Dukpa & Oka, Tatsushi & Estrada, Francisco & Perron, Pierre, 2020. "Inference related to common breaks in a multivariate system with joined segmented trends with applications to global and hemispheric temperatures," Journal of Econometrics, Elsevier, vol. 214(1), pages 130-152.
    See citations under working paper version above.
  3. Josep Lluís Carrion-i-Silvestre & Dukpa Kim, 2019. "Quasi-likelihood ratio tests for cointegration, cobreaking, and cotrending," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 881-898, September.

    Cited by:

    1. Carrion-i-Silvestre, Josep Lluís & Kim, Dukpa, 2021. "Statistical tests of a simple energy balance equation in a synthetic model of cotrending and cointegration," Journal of Econometrics, Elsevier, vol. 224(1), pages 22-38.
    2. Skrobotov, Anton, 2021. "Structural breaks in cointegration models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 117-141.
    3. María Dolores Gadea Rivas & Jesús Gonzalo, 2022. "A tale of three cities: climate heterogeneity," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 475-511, May.
    4. Gadea Rivas, Marta Dolores & Gonzalo, Jesús, 2022. "Climate change heterogeneity: a new quantitative approach," UC3M Working papers. Economics 35442, Universidad Carlos III de Madrid. Departamento de Economía.

  4. In Choi & Dukpa Kim & Yun Jung Kim & Noh‐Sun Kwark, 2018. "A multilevel factor model: Identification, asymptotic theory and applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 355-377, April.
    See citations under working paper version above.
  5. Kim Dukpa & Kim Yunjung & Bak Yuhyeon, 2017. "Multi-level factor analysis of bond risk premia," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-19, December.

    Cited by:

    1. Venetis, Ioannis & Ladas, Avgoustinos, 2022. "Co-movement and global factors in sovereign bond yields," MPRA Paper 115801, University Library of Munich, Germany.

  6. Dukpa Kim & Tatsushi Oka, 2014. "Divorce Law Reforms And Divorce Rates In The Usa: An Interactive Fixed‐Effects Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 231-245, March.

    Cited by:

    1. Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP52/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Yi‐Ting Chen, 2020. "A distributional synthetic control method for policy evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 505-525, August.
    3. Gobillon, Laurent & Magnac, Thierry, 2013. "Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls," TSE Working Papers 13-419, Toulouse School of Economics (TSE).
    4. Hyungsik Roger Roger Moon & Martin Weidner, 2014. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers 35/14, Institute for Fiscal Studies.
    5. Xiang, Jingjie & Li, Li, 2022. "Monetary policy uncertainty, debt financing cost and real economic activities: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1025-1044.
    6. Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," University of California at San Diego, Economics Working Paper Series qt90m9d66s, Department of Economics, UC San Diego.
    7. Susan Athey & Mohsen Bayati & Nikolay Doudchenko & Guido Imbens & Khashayar Khosravi, 2017. "Matrix Completion Methods for Causal Panel Data Models," Papers 1710.10251, arXiv.org, revised Apr 2022.
    8. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    9. Edith Aguirre, 2019. "Do changes in divorce legislation have an impact on divorce rates? The case of unilateral divorce in Mexico," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 28(1), pages 1-24, December.
    10. Hyungsik Roger Moon & Martin Weidner, 2013. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers CWP49/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
    12. Harouna Sedgo & Luc-Désiré Omgba, 2021. "Corruption and distortion of public expenditures: Evidence from Africa," Working Papers hal-04159761, HAL.
    13. Iv'an Fern'andez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-Rank Approximations of Nonseparable Panel Models," Papers 2010.12439, arXiv.org, revised Mar 2021.
    14. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Papers 2208.03632, arXiv.org, revised Apr 2023.
    15. Matteo Picchio, 2021. "Microchip bags and waste sorting," Working Papers 449, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    16. Peter Backus & Thien Nguyen, 2021. "The Effect of the Sex Buyer Law on the Market for Sex, Sexual Health and Sexual Violence," Economics Discussion Paper Series 2106, Economics, The University of Manchester.
    17. Shi, Wei & Lee, Lung-fei, 2018. "A spatial panel data model with time varying endogenous weights matrices and common factors," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 6-34.
    18. Totty, Evan, 2015. "The Effect of Minimum Wages on Employment: A Factor Model Approach," Institute for Research on Labor and Employment, Working Paper Series qt2b26n60q, Institute of Industrial Relations, UC Berkeley.
    19. Ryan Rafaty & Geoffroy Dolphin & Felix Pretis, 2020. "Carbon pricing and the elasticity of CO2 emissions," Working Papers EPRG2035, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    20. Chigavazira, Abraham & Fisher, Hayley & Robinson, Tim & Zhu, Anna, 2019. "The Consequences of Extending Equitable Property Division Divorce Laws to Cohabitants," Working Papers 2019-02, University of Sydney, School of Economics.
    21. Gagliardi, Luisa, 2019. "The impact of foreign technological innovation on domestic employment via the industry mix," Research Policy, Elsevier, vol. 48(6), pages 1523-1533.
    22. Rafaty, Ryan & Dolphin, Geoffroy & Pretis, Felix, 2021. "Carbon Pricing and the Elasticity of CO2 Emissions," RFF Working Paper Series 21-33, Resources for the Future.
    23. Wei Shi & Lung-fei Lee, 2018. "The effects of gun control on crimes: a spatial interactive fixed effects approach," Empirical Economics, Springer, vol. 55(1), pages 233-263, August.
    24. Mohitosh Kejriwal & Xiaoxiao Li & Linh Nguyen & Evan Totty, 2024. "The efficacy of ability proxies for estimating the returns to schooling: A factor model‐based evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 3-21, January.
    25. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019. "Inference on average treatment effects in aggregate panel data settings," CeMMAP working papers CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Shen, Danqing, 2018. "Marriage, Divorce and Sorting: A Reassessment of Unilateral Divorce Laws," MPRA Paper 92848, University Library of Munich, Germany.
    28. Shinya Fukui, 2020. "The effect of deregulation of the "Act concerning the Industry Restriction"," Discussion Papers 2002, Graduate School of Economics, Kobe University.
    29. Xu Lin & Lizi Wu, 2021. "Interdependence among mental health care providers: evidence from a spatial dynamic panel data model with interactive fixed effects," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(1), pages 131-165, August.
    30. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018. "A $t$-test for synthetic controls," Papers 1812.10820, arXiv.org, revised Jan 2024.
    31. Feng, Qu, 2020. "Common factors and common breaks in panels: An empirical investigation," Economics Letters, Elsevier, vol. 187(C).
    32. Xingyu Li & Yan Shen & Qiankun Zhou, 2022. "Confidence Intervals of Treatment Effects in Panel Data Models with Interactive Fixed Effects," Papers 2202.12078, arXiv.org.
    33. Bai, Jushan & Liao, Yuan, 2017. "Inferences in panel data with interactive effects using large covariance matrices," Journal of Econometrics, Elsevier, vol. 200(1), pages 59-78.

  7. Jinhee Lee & Dukpa Kim, 2014. "Forecasting Korean Macroeconomic Variables with Autoregressions and Vector Autoregressions (in Korean)," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 20(4), pages 114-150, December.

    Cited by:

    1. Kim, Jung-Wook & Kim, Jinkyeong, 2023. "Regulatory Sentiment and Economic Performance," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 45(1), pages 69-86.

  8. Kim, Dukpa, 2014. "Maximum likelihood estimation for vector autoregressions with multivariate stochastic volatility," Economics Letters, Elsevier, vol. 123(3), pages 282-286.

    Cited by:

    1. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    2. Moura, Guilherme V. & Noriller, Mateus R., 2019. "Maximum likelihood estimation of a TVP-VAR," Economics Letters, Elsevier, vol. 174(C), pages 78-83.
    3. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    4. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    6. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).

  9. Dukpa Kim, 2014. "Common breaks in time trends for large panel data with a factor structure," Econometrics Journal, Royal Economic Society, vol. 17(3), pages 301-337, October.

    Cited by:

    1. Oualid Bada & Alois Kneip & Dominik Liebl & Tim Mensinger & James Gualtieri & Robin C. Sickles, 2021. "A Wavelet Method for Panel Models with Jump Discontinuities in the Parameters," Papers 2109.10950, arXiv.org.
    2. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    3. Badi H. Baltagi & Chihwa Kao & Long Liu, 2015. "Estimation and Identification of Change Points in Panel Models with Nonstationary or Stationary Regressors and Error Term," Center for Policy Research Working Papers 178, Center for Policy Research, Maxwell School, Syracuse University.
    4. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    5. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    6. Eunju Hwang & Dong Wan Shin, 2017. "Stationary bootstrapping for common mean change detection in cross-sectionally dependent panels," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(6), pages 767-787, November.
    7. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    8. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    9. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    10. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    11. Barbora Peštová & Michal Pešta, 2017. "Change Point Estimation in Panel Data without Boundary Issue," Risks, MDPI, vol. 5(1), pages 1-22, January.

  10. Kim, Dukpa, 2011. "Estimating a common deterministic time trend break in large panels with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 164(2), pages 310-330, October.

    Cited by:

    1. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    2. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    3. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    4. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    5. Tatsushi Oka & Pierre Perron, 2018. "Testing for common breaks in a multiple equations system," Monash Econometrics and Business Statistics Working Papers 3/18, Monash University, Department of Econometrics and Business Statistics.
    6. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    7. Ryo Okui & Wendun Wang, 2018. "Heterogeneous structural breaks in panel data models," Papers 1801.04672, arXiv.org, revised Nov 2018.
    8. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    9. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    10. Chang, Seong Yeon, 2021. "Estimation of a level shift in panel data with fractionally integrated errors," Economics Letters, Elsevier, vol. 206(C).
    11. Feng, Qu, 2020. "Common factors and common breaks in panels: An empirical investigation," Economics Letters, Elsevier, vol. 187(C).

  11. Kim, Dukpa, 2010. "Improved And Extended End-Of-Sample Instability Tests Using A Feasible Quasi-Generalized Least Squares Procedure," Econometric Theory, Cambridge University Press, vol. 26(4), pages 994-1031, August.

    Cited by:

    1. Skrobotov, Anton, 2021. "Structural breaks in cointegration models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 117-141.
    2. KUROZUMI, Eiji & 黒住, 英司, 2017. "Confidence Sets for the Date of a Mean Shift at the End of a Sample," Discussion Papers 2017-06, Graduate School of Economics, Hitotsubashi University.
    3. Eiji Kurozumi, 2018. "Confidence Sets for the Date of a Structural Change at the End of a Sample," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 850-862, November.

  12. Kim, Dukpa & Perron, Pierre, 2009. "Assessing the relative power of structural break tests using a framework based on the approximate Bahadur slope," Journal of Econometrics, Elsevier, vol. 149(1), pages 26-51, April.
    See citations under working paper version above.
  13. Kim, Dukpa & Perron, Pierre, 2009. "Unit root tests allowing for a break in the trend function at an unknown time under both the null and alternative hypotheses," Journal of Econometrics, Elsevier, vol. 148(1), pages 1-13, January.

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    1. Antonio Afonso & Florence Huart & João Tovar Jalles & Piotr Stanek, 2018. "Assessing the sustainability of external imbalances in the European Union," Post-Print hal-01914597, HAL.
    2. Shahbaz, Muhammad & Hoang, Thi Hong Van & Mahalik, Mantu Kumar & Roubaud, David, 2017. "Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis," Energy Economics, Elsevier, vol. 63(C), pages 199-212.
    3. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    4. Ramesh Chandra Das, 2021. "Does Minimum Support Price Have Long-Run Associations and Short-Run Interplays with Yield Rates and Quantities of Outputs? A Study on Food and Non-food Grains in India," Review of Market Integration, India Development Foundation, vol. 13(1), pages 42-65, April.
    5. Wang, Zhaohua & Asghar, Muhammad Mansoor & Zaidi, Syed Anees Haider & Nawaz, Kishwar & Wang, Bo & Zhao, Wehui & Xu, Fengxing, 2020. "The dynamic relationship between economic growth and life expectancy: Contradictory role of energy consumption and financial development in Pakistan," Structural Change and Economic Dynamics, Elsevier, vol. 53(C), pages 257-266.
    6. Zheng, Jingling & Li, Zeyun & Ghardallou, Wafa & Wei, Xuecheng, 2023. "Natural resources and economic performance: Understanding the volatilities caused by financial, political and economic risk in the context of China," Resources Policy, Elsevier, vol. 84(C).
    7. Huang, Haiping & Huang, Baolian & Sun, Aijun, 2023. "How do mineral resources influence eco-sustainability in China? Dynamic role of renewable energy and green finance," Resources Policy, Elsevier, vol. 85(PA).
    8. Jung, Alexander & Carcel Villanova, Hector, 2020. "The empirical properties of euro area M3, 1980-2017," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 37-49.
    9. Shahbaz, Muhammad & Mateev, Miroslav & Abosedra, Salaheddin & Nasir, Muhammad Ali & Jiao, Zhilun, 2019. "Determinants of FDI in France: Role of Transport Infrastructure, Education, Financial Development and Energy Consumption," MPRA Paper 96371, University Library of Munich, Germany, revised 05 Oct 2019.
    10. Esteve García, Vicente & Navarro Ibáñez, Manuel & Prats Albentosa, María Asuncíon, 2017. "The present value model of U.S. stock prices revisited: Long-run evidence with structural breaks, 1871-2012," Economics Discussion Papers 2017-93, Kiel Institute for the World Economy (IfW Kiel).
    11. Pan, Guochen & Chang, Hsu-Ling & Su, Chi-Wei, 2012. "Regional differences in development of life insurance markets in China," Emerging Markets Review, Elsevier, vol. 13(4), pages 548-558.
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    13. Jiao, Zhilun & Sharma, Rajesh & Kautish, Pradeep & Hussain, Hafezali Iqbal, 2021. "Unveiling the asymmetric impact of exports, oil prices, technological innovations, and income inequality on carbon emissions in India," Resources Policy, Elsevier, vol. 74(C).
    14. Xin, Yongrong & Ajaz, Tahseen & Shahzad, Mohsin & Luo, Jia, 2023. "How productive capacities influence trade-adjusted resources consumption in China: Testing resource-based EKC," Resources Policy, Elsevier, vol. 81(C).
    15. Brittle, Shane, 2009. "Ricardian Equivalence and the Efficacy of Fiscal Policy in Australia," Economics Working Papers wp09-10, School of Economics, University of Wollongong, NSW, Australia.
    16. Li, Wei & Cao, Ning & Xiang, Zejia, 2023. "Drivers of renewable energy transition: The role of ICT, human development, financialization, and R&D investment in China," Renewable Energy, Elsevier, vol. 206(C), pages 441-450.
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    18. Imran Khan & Faheem Ur Rehman & Paula Pypłacz & Muhammad Asif Khan & Agnieszka Wiśniewska & Katarzyna Liczmańska-Kopcewicz, 2021. "A Dynamic Linkage between Financial Development, Energy Consumption and Economic Growth: Evidence from an Asymmetric and Nonlinear ARDL Model," Energies, MDPI, vol. 14(16), pages 1-15, August.
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    3. Alfred A. Haug & Ian P. King, 2011. "Empirical Evidence on Inflation and Unemployment in the Long Run," Working Papers 1109, University of Otago, Department of Economics, revised Aug 2011.
    4. Benos, Nikos & Stavrakoudis, Athanassios, 2020. "Okun's Law: Copula-based Evidence from G7 Countries," MPRA Paper 103318, University Library of Munich, Germany.
    5. Mariam Camarero & Josep Lluís Carrion-i-Silvestre & Cecilio Tamarit, 2013. "Global imbalances and the Intertemporal External Budget Constraint: A multicointegration approach," Working Papers 1303, Department of Applied Economics II, Universidad de Valencia.
    6. Yan Qian & Zijun Wang, 2021. "A model selection approach to jointly testing for structural breaks and cointegration with application to the Eurocurrency interest rates market," Empirical Economics, Springer, vol. 61(2), pages 799-825, August.
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    9. Omri, Anis, 2014. "An international literature survey on energy-economic growth nexus: Evidence from country-specific studies," MPRA Paper 82452, University Library of Munich, Germany, revised 30 Jun 2014.
    10. Hervé Ott, 2014. "Extent and possible causes of intrayear agricultural commodity price volatility," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 225-252, March.
    11. Esteve García, Vicente & Navarro Ibáñez, Manuel & Prats Albentosa, María Asuncíon, 2017. "The present value model of U.S. stock prices revisited: Long-run evidence with structural breaks, 1871-2012," Economics Discussion Papers 2017-93, Kiel Institute for the World Economy (IfW Kiel).
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    14. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
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