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Antonio F Galvao

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Ferreira, Francisco H. G. & Firpo, Sergio & Galvao, Antonio F., 2017. "Estimation and Inference for Actual and Counterfactual Growth Incidence Curves," IZA Discussion Papers 10473, Institute of Labor Economics (IZA).

    Mentioned in:

    1. Estimation and Inference for Actual and Counterfactual Growth Incidence Curves
      by maximorossi in NEP-LTV blog on 2017-03-22 00:55:01

Working papers

  1. Montes Rojas Gabriel & Alejo Javier & Galvao Antonio & Martínez-Iriarte Julián, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Asociación Argentina de Economía Política: Working Papers 4674, Asociación Argentina de Economía Política.

    Cited by:

    1. Martínez-Iriarte, Julián & Montes-Rojas, Gabriel & Sun, Yixiao, 2024. "Unconditional effects of general policy interventions," Journal of Econometrics, Elsevier, vol. 238(2).

  2. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.

    Cited by:

    1. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    2. Li Tao & Lingnan Tai & Manling Qian & Maozai Tian, 2023. "A New Instrumental-Type Estimator for Quantile Regression Models," Mathematics, MDPI, vol. 11(15), pages 1-26, August.

  3. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2021. "A first-stage representation for instrumental variables quantile regression," Papers 2102.01212, arXiv.org, revised Feb 2022.

    Cited by:

    1. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.

  4. Luciano De Castro & Antonio F. Galvao & Gabriel Montes Rojas & José Olmo, 2020. "Portfolio Selection in Quantile Decision Models," Working Papers 11, Red Nacional de Investigadores en Economía (RedNIE).

    Cited by:

    1. Balter, Anne G. & Chau, Ki Wai & Schweizer, Nikolaus, 2024. "Comparative risk aversion vs. threshold choice in the Omega ratio," Omega, Elsevier, vol. 123(C).

  5. Sergio Firpo & Antonio F. Galvao & Thomas Parker, 2019. "Uniform inference for value functions," Papers 1911.10215, arXiv.org, revised Oct 2022.

    Cited by:

    1. Sungwon Lee, 2021. "Partial Identification and Inference for Conditional Distributions of Treatment Effects," Papers 2108.00723, arXiv.org, revised Nov 2023.

  6. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.

    Cited by:

    1. 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.
    2. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    3. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    4. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    5. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    6. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    7. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    8. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    9. Li Tao & Lingnan Tai & Manling Qian & Maozai Tian, 2023. "A New Instrumental-Type Estimator for Quantile Regression Models," Mathematics, MDPI, vol. 11(15), pages 1-26, August.
    10. Bahram Adrangi & Arjun Chatrath & Madhuparna Kolay & Kambiz Raffiee, 2021. "Dynamic Responses of Standard and Poor’s Regional Bank Index to the U.S. Fear Index, VIX," JRFM, MDPI, vol. 14(3), pages 1-18, March.
    11. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    12. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    13. Sabeeh Ullah, 2023. "Impact of COVID-19 Pandemic on Financial Markets: a Global Perspective," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 982-1003, June.
    14. Sunil K. Mohanty & Stein Frydenberg & Petter Osmundsen & Sjur Westgaard & Christian Skjøld, 2023. "Risk factors in stock returns of U.S. oil and gas companies: evidence from quantile regression analysis," Review of Quantitative Finance and Accounting, Springer, vol. 60(2), pages 715-746, February.
    15. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    16. Bahram Adrangi & Arjun Chatrath & Kambiz Raffiee, 2023. "S&P 500 volatility, volatility regimes, and economic uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1362-1387, October.
    17. Xiaorui Liu & Wen Guo & Yuyu Chen & Qiang Feng & Xiutian Zheng, 2024. "Energy-saving effect of financial development and its dynamic heterogeneity: Empirical evidence from the dynamic panel quantile model," Energy & Environment, , vol. 35(6), pages 3065-3086, September.
    18. Martina Pons & Blaise Melly, 2022. "Stata commands to estimate quantile regression with panel and grouped data," Swiss Stata Conference 2022 05, Stata Users Group.
    19. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    20. Cepoi, Cosmin-Octavian, 2020. "Asymmetric dependence between stock market returns and news during COVID-19 financial turmoil," Finance Research Letters, Elsevier, vol. 36(C).

  7. Ferreira, Francisco H. G. & Firpo, Sergio & Galvao, Antonio F., 2017. "Estimation and Inference for Actual and Counterfactual Growth Incidence Curves," IZA Discussion Papers 10473, Institute of Labor Economics (IZA).

    Cited by:

    1. David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
    2. Kim, Ju Hyun & Park, Byoung G., 2018. "Weak convergence of local quantile treatment effect processes," Economics Letters, Elsevier, vol. 162(C), pages 49-52.

  8. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.

    Cited by:

    1. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    2. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," AMSE Working Papers 1920, Aix-Marseille School of Economics, France.
    3. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    4. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    5. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Nov 2024.
    6. Fusejima, Koki, 2024. "Identification of multi-valued treatment effects with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    7. Di Liu, 2024. "Instrumental-variables quantile regression," French Stata Users' Group Meetings 2024 07, Stata Users Group.
    8. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.
    9. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Di Liu, 2024. "Instrumental variables quantile regression," Chinese Stata Conference 2023 07, Stata Users Group.
    11. Javier Alejo & Gabriel Montes-Rojas, 2021. "Quantile Regression under Limited Dependent Variable," Papers 2112.06822, arXiv.org.
    12. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    13. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
    14. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    15. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    16. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    17. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    18. de Castro, Luciano I. & Galvao, Antonio F. & Nunes, Daniel da Siva, 0. "Dynamic economics with quantile preferences," Theoretical Economics, Econometric Society.
    19. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.

  9. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.

    Cited by:

    1. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    2. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," AMSE Working Papers 1920, Aix-Marseille School of Economics, France.
    3. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    4. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    5. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Nov 2024.
    6. Fusejima, Koki, 2024. "Identification of multi-valued treatment effects with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    7. Di Liu, 2024. "Instrumental-variables quantile regression," French Stata Users' Group Meetings 2024 07, Stata Users Group.
    8. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.
    9. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Di Liu, 2024. "Instrumental variables quantile regression," Chinese Stata Conference 2023 07, Stata Users Group.
    11. Javier Alejo & Gabriel Montes-Rojas, 2021. "Quantile Regression under Limited Dependent Variable," Papers 2112.06822, arXiv.org.
    12. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    13. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
    14. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    15. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    16. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    17. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    18. de Castro, Luciano I. & Galvao, Antonio F. & Nunes, Daniel da Siva, 0. "Dynamic economics with quantile preferences," Theoretical Economics, Econometric Society.
    19. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.

  10. Javier Alejo & Antonio Galvao & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2015. "Tests for Normality in Linear Panel Data Models," CEDLAS, Working Papers 0178, CEDLAS, Universidad Nacional de La Plata.

    Cited by:

    1. Michael L. Polemis, 2020. "A note on the estimation of competition-productivity nexus: a panel quantile approach," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(4), pages 663-676, December.
    2. Ahmet Hamdi Yanık & Ahmet İncekara, 2024. "Relationship Between Household Consumption and Disaggregated Wealth Components in OECD Countries: Panel Data Analysis for the Period 2010-2017," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 11(2), pages 370-382, July.
    3. Daniel Santabárbara & Marta Suárez-Varela, 2022. "Carbon pricing and inflation volatility," Working Papers 2231, Banco de España.
    4. Emmanuel Mensah & Christopher Boachie, 2023. "Analysis of the determinants of corporate governance quality: evidence from sub-Saharan Africa," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 20(4), pages 431-450, December.
    5. Seifelyazal Mostafa & Salah Eldin Ashraf & ElSherif Marwa, 2023. "The Impact of Financial Inclusion on Economic Development," International Journal of Economics and Financial Issues, Econjournals, vol. 13(2), pages 93-101, March.
    6. Noman Arshed & Rukhsana Kalim, 2021. "Modelling demand and supply of Islamic banking deposits," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2813-2831, April.
    7. Sisay Demissew Beyene & Mohammed Seid Ali & Belayneh Taye & Yihenew Wubu Endalew, 2024. "Questioning the democracy–growth debate in countries of the East African region: a political economy perspective," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 26(3), pages 1059-1081, December.
    8. Jose Fernando Vilcarromero Arbulu & Jorge Luis Castilla Raimundo & Pedro Bernabe Venegas Rodriguez & Nivardo Alonzo Santillan Zapata & Jimmy Alberth Deza Quispe, 2021. "Financial Factors and Their Relative Importance Analysis in Peruvian Gold Mining Companies¡¯ Stock Price," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(2), pages 251-262, April.
    9. Tehmina Zahid & Noman Arshed & Mubbasher Munir & Kamran Hameed, 2021. "Role of energy consumption preferences on human development: a study of SAARC region," Economic Change and Restructuring, Springer, vol. 54(1), pages 121-144, February.

  11. Heitor Almeida & Murillo Campello & Antonio F. Galvao Jr., 2010. "Measurement Errors in Investment Equations," NBER Working Papers 15951, National Bureau of Economic Research, Inc.

    Cited by:

    1. Niclas Andrén & Håkan Jankensgård, 2020. "Disappearing investment‐cash flow sensitivities: Earnings have not become a worse proxy for cash flow," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 47(5-6), pages 760-785, May.
    2. René Belderbos & Boris Lokshin & Bert Sadowski, 2015. "The returns to foreign R&D," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 46(4), pages 491-504, May.
    3. Michael Machokoto, 2021. "Do financial constraints really matter? A case of understudied African firms," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4670-4705, July.
    4. Bose, Udichibarna & MacDonald, Ronald & Tsoukas, Serafeim, 2015. "Education and the local equity bias around the world," SIRE Discussion Papers 2015-76, Scottish Institute for Research in Economics (SIRE).
    5. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
    6. Pierluigi Balduzzi & Emanuele Brancati & Fabio Schiantarelli, 2013. "Financial Markets, Banks' Cost of Funding, and Firms' Decisions: Lessons from Two Crises," Boston College Working Papers in Economics 824, Boston College Department of Economics, revised 12 Aug 2016.
    7. de Andrés, Pablo & de la Fuente, Gabriel & Velasco, Pilar, 2016. "Are real options a missing piece in the diversification-value puzzle?," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 261-271.
    8. Firth, Michael & Malatesta, Paul H. & Xin, Qingquan & Xu, Liping, 2012. "Corporate investment, government control, and financing channels: Evidence from China's Listed Companies," Journal of Corporate Finance, Elsevier, vol. 18(3), pages 433-450.
    9. Aissata Boubacar Moumouni, 2020. "Investment Sensitivity to Inter-enterprises Payment Deadlines," Working Papers hal-02889436, HAL.
    10. Z. Jun Lin & Shengqiang Liu & Fangcheng Sun, 2017. "The Impact of Financing Constraints and Agency Costs on Corporate R&D Investment: Evidence from China," International Review of Finance, International Review of Finance Ltd., vol. 17(1), pages 3-42, March.
    11. Bo Becker & Marcus Jacob & Martin Jacob, 2011. "Payout Taxes and the Allocation of Investment," NBER Working Papers 17481, National Bureau of Economic Research, Inc.
    12. Chien, Chih-Chung & Chen, Shikuan & Chang, Ming-Jen, 2023. "Financial constraints on credit ratings and cash-flow sensitivity," International Review of Financial Analysis, Elsevier, vol. 88(C).
    13. Jacob, Marcus & Jacob, Martin, 2013. "Taxation and the cash flow sensitivity of dividends," Economics Letters, Elsevier, vol. 118(1), pages 186-188.
    14. Alhassan, Abdulrahman & Naka, Atsuyuki, 2020. "Corporate future investments and stock liquidity: Evidence from emerging markets," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 69-83.
    15. Wagner, Wolf & Gong, Di, 2016. "Systemic risk-taking at banks: Evidence from the pricing of syndicated loans," CEPR Discussion Papers 11150, C.E.P.R. Discussion Papers.
    16. Javier Alejo & Antonio Galvao & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2015. "Tests for Normality in Linear Panel Data Models," CEDLAS, Working Papers 0178, CEDLAS, Universidad Nacional de La Plata.
    17. Ricky W. Scott, 2014. "Institutional Investors, Stock Repurchases and Information Asymmetry," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 5(4), pages 39-51, October.
    18. Chalak, Karim & Kim, Daniel, 2020. "Measurement error in multiple equations: Tobin’s q and corporate investment, saving, and debt," Journal of Econometrics, Elsevier, vol. 214(2), pages 413-432.
    19. Galvao, Antonio F. & Montes-Rojas, Gabriel & Sosa-Escudero, Walter & Wang, Liang, 2013. "Tests for skewness and kurtosis in the one-way error component model," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 35-52.
    20. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
    21. Almeida, Heitor & Campello, Murillo & Weisbach, Michael S., 2011. "Corporate financial and investment policies when future financing is not frictionless," Journal of Corporate Finance, Elsevier, vol. 17(3), pages 675-693, June.
    22. Behr, Patrick & Norden, Lars & Noth, Felix, 2013. "Financial constraints of private firms and bank lending behavior," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3472-3485.
    23. Masanori Orihara, 2016. "Corporate tax asymmetries and R&D: Evidence from a tax reform for business groups in Japan," Discussion papers ron273, Policy Research Institute, Ministry of Finance Japan.
    24. Ding, David K. & Ferreira, Christo & Wongchoti, Udomsak, 2016. "Does it pay to be different? Relative CSR and its impact on firm value," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 86-98.
    25. Sheng-Kai Chang & Yi-Yi Chen & Hung-Jen Wang, 2012. "A Bayesian estimator for stochastic frontier models with errors in variables," Journal of Productivity Analysis, Springer, vol. 38(1), pages 1-9, August.
    26. Ogura, Yoshiaki, 2017. "Investment Distortion by Collateral Requirement: Evidence from Japanese SMEs," HIT-REFINED Working Paper Series 73, Institute of Economic Research, Hitotsubashi University.
    27. Borisova, Ginka & Brown, James R., 2013. "R&D sensitivity to asset sale proceeds: New evidence on financing constraints and intangible investment," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 159-173.
    28. Claessens, Stijn & Yafeh, Yishay & Ueda, Kenichi, 2010. "Financial Frictions, Investment, and Institutions," CEPR Discussion Papers 8170, C.E.P.R. Discussion Papers.
    29. Galvao, Antonio F. & Wang, Liang, 2015. "Efficient minimum distance estimator for quantile regression fixed effects panel data," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 1-26.
    30. Fuente, Gabriel de la & Velasco, Pilar, 2020. "Capital structure and corporate diversification: Is debt a panacea for the diversification discount?," Journal of Banking & Finance, Elsevier, vol. 111(C).
    31. Machokoto, Michael & Areneke, Geofry, 2021. "Is the cash flow sensitivity of cash asymmetric? African evidence," Finance Research Letters, Elsevier, vol. 38(C).
    32. Ljungqvist, Alexander & Asker, John & Farre-Mensa, Joan, 2010. "Does the Stock Market Harm Investment Incentives?," CEPR Discussion Papers 7857, C.E.P.R. Discussion Papers.
    33. Bruno Ćorić & Vladimir Šimić, 2021. "Economic disasters and aggregate investment," Empirical Economics, Springer, vol. 61(6), pages 3087-3124, December.
    34. Milan Hladík & Michal Černý & Jaromír Antoch, 2020. "EIV regression with bounded errors in data: total ‘least squares’ with Chebyshev norm," Statistical Papers, Springer, vol. 61(1), pages 279-301, February.
    35. Chen, Hong-Yi & Lee, Alice C. & Lee, Cheng-Few, 2015. "Alternative errors-in-variables models and their applications in finance research," The Quarterly Review of Economics and Finance, Elsevier, vol. 58(C), pages 213-227.
    36. Badertscher, Brad & Shroff, Nemit & White, Hal D., 2013. "Externalities of public firm presence: Evidence from private firms' investment decisions," Journal of Financial Economics, Elsevier, vol. 109(3), pages 682-706.
    37. Liao, Shushu, 2021. "The effect of credit shocks in the context of labor market frictions," Journal of Banking & Finance, Elsevier, vol. 125(C).
    38. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers 34/15, Institute for Fiscal Studies.
    39. Farman Ali & Muhammad Ullah & Syed Tauseef Ali & Zhen Yang & Imran Ali, 2022. "Board Diversity and Corporate Investment Decisions: Evidence from China," SAGE Open, , vol. 12(2), pages 21582440221, June.
    40. Brown, James R. & Martinsson, Gustav & Petersen, Bruce C., 2015. "Do Financing Constraints Matter for R&D?," Working Paper Series in Economics and Institutions of Innovation 394, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    41. Hachmi Ben Ameur & Fredj Jawadi & Abdoulkarim Idi Cheffou & Wael Louhichi, 2018. "Measurement errors in stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 287-306, March.
    42. Kim, Kirak, 2020. "Inventory, fixed capital, and the cross-section of corporate investment," Journal of Corporate Finance, Elsevier, vol. 60(C).
    43. Aissata Boubacar Moumouni, 2020. "Investment Sensitivity to Inter-enterprises Payment Deadlines," AMSE Working Papers 1938, Aix-Marseille School of Economics, France.
    44. Jeon, Heung-Jae & Jung, Sumi, 2024. "Generalist vs. Specialist CEOs: R&D Investment Sensitivity to Stock Price," Finance Research Letters, Elsevier, vol. 62(PA).
    45. Timothy Erickson & Toni M. Whited, 2012. "Treating Measurement Error in Tobin's q," The Review of Financial Studies, Society for Financial Studies, vol. 25(4), pages 1286-1329.
    46. Muñoz, Francisco, 2013. "Liquidity and firm investment: Evidence for Latin America," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 18-29.
    47. Spaliara, Marina-Eliza & Tsoukas, Serafeim, 2017. "Corporate failures and the denomination of corporate bonds: Evidence from emerging Asian economies over two financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 84-97.
    48. Chacko Jacob & Jijo Lukose P.J., 2019. "Institutional ownership and the investment-cash flow sensitivity Evidence from India," Working papers 329, Indian Institute of Management Kozhikode.
    49. Emmanuel Adu‐Ameyaw & Albert Danso & Moshfique Uddin & Samuel Acheampong, 2024. "Investment‐cash flow sensitivity: Evidence from investment in identifiable intangible and tangible assets activities," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1179-1204, April.
    50. Bernal, Oscar & Gnabo, Jean-Yves & Guilmin, Grégory, 2016. "Economic policy uncertainty and risk spillovers in the Eurozone," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 24-45.
    51. Pindado, Julio & Requejo, Ignacio & de la Torre, Chabela, 2011. "Family control and investment–cash flow sensitivity: Empirical evidence from the Euro zone," Journal of Corporate Finance, Elsevier, vol. 17(5), pages 1389-1409.
    52. Antonio F. Galvao & Gabriel Montes–Rojas & Jose Olmo & Suyong Song, 2018. "On solving endogeneity with invalid instruments: an application to investment equations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 689-716, June.
    53. Kwanglim Seo & Jungtae Soh & Amit Sharma, 2018. "Do financial constraints affect the sensitivity of investment to cash flow? New evidence from franchised restaurant firms," Tourism Economics, , vol. 24(6), pages 645-661, September.
    54. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    55. Ding, David K. & Ferreira, Christo & Wongchoti, Udomsak, 2019. "The geography of CSR," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 265-288.
    56. Brown, James R. & Floros, Ioannis V., 2012. "Access to private equity and real firm activity: Evidence from PIPEs," Journal of Corporate Finance, Elsevier, vol. 18(1), pages 151-165.
    57. Grullon, Gustavo & Hund, John & Weston, James P., 2018. "Concentrating on q and cash flow," Journal of Financial Intermediation, Elsevier, vol. 33(C), pages 1-15.

  12. Arbex, Marcelo & Galvao, Antonio F. & Gomes, Fábio Augusto Reis, 2010. "Heterogeneity in the Returns to Education and Informal Activities," Insper Working Papers wpe_216, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Olivier Bargain & Prudence Kwenda, 2013. "The Informal Sector Wage Gap: New Evidence using Quantile Estimations on Panel Data," Working Papers halshs-00967324, HAL.
    2. Italo Lopez Garcia, 2015. "Human Capital and Labor Informality in Chile A Life-Cycle Approach," Working Papers WR-1087, RAND Corporation.
    3. Tareq Sadeq, 2014. "Formal-Informal Gap in Return to Schooling and Penalty to Education-Occupation Mismatch a Comparative Study for Egypt, Jordan, and Palestine," Working Papers 894, Economic Research Forum, revised Dec 2014.
    4. Daeheon Choi & Chune Young Chung & Ha Truong, 2019. "Return on Education in Two Major Vietnamese Cities," Sustainability, MDPI, vol. 11(18), pages 1-30, September.

  13. Tommaso Gabrieli & Antonio F. Galvao, Jr. & Antonio F. Galvao, Jr., 2010. "Who Benefits from Reducing the Cost of Formality? Quantile Regression Discontinuity Analysis," Real Estate & Planning Working Papers rep-wp2010-11, Henley Business School, University of Reading.

    Cited by:

    1. Basu, Arnab K. & Chau, Nancy H. & Siddique, Zahra, 2011. "Tax Evasion, Minimum Wage Non-Compliance and Informality," IZA Discussion Papers 6228, Institute of Labor Economics (IZA).

  14. Galvao Jr, A. F. & Montes-Rojas, G. & Park, S. Y., 2009. "Quantile autoregressive distributed lag model with an application to house price returns," Working Papers 09/04, Department of Economics, City University London.

    Cited by:

    1. Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
    2. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    3. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    5. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    6. Haroon Mumtaz & Paolo Surico, 2015. "The Transmission Mechanism In Good And Bad Times," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1237-1260, November.
    7. Gabriel Montes-Rojas & Zacharias Psaradakis & Martín Sola, 2024. "On Regime Separation in Markov-Switching Quantile Regressions," Department of Economics Working Papers 2024_05, Universidad Torcuato Di Tella.
    8. Nicholas Apergis, 2022. "Evaluating tail risks for the U.S. economic policy uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3971-3989, October.
    9. Marques, André M. & Lima, Gilberto Tadeu, 2022. "Testing for Granger causality in quantiles between the wage share in income and productive capacity utilization," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 290-312.
    10. Nicholas Apergis, 2023. "Forecasting energy prices: Quantile‐based risk models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 17-33, January.
    11. Xu, Qifa & Niu, Xufeng & Jiang, Cuixia & Huang, Xue, 2015. "The Phillips curve in the US: A nonlinear quantile regression approach," Economic Modelling, Elsevier, vol. 49(C), pages 186-197.
    12. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    13. Tae-Hwan Kim & Dong Jin Lee & Paul Mizen, 2020. "Impulse Response Analysis in Conditional Quantile Models and an Application to Monetary Policy," Working papers 2020rwp-164, Yonsei University, Yonsei Economics Research Institute.
    14. Lee, Chien-Chiang & Lee, Cheng-Feng & Lee, Chi-Chuan, 2014. "Asymmetric dynamics in REIT prices: Further evidence based on quantile regression analysis," Economic Modelling, Elsevier, vol. 42(C), pages 29-37.
    15. Linas Jurksas & Arvydas Paskevicius, 2017. "The Relationship Between Macroeconomy And Asset Prices: Long Run Causality Evidence From Lithuania," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 8(1).
    16. Debdatta Pal & Subrata K. Mitra, 2017. "Diesel and soybean price relationship in the USA: evidence from a quantile autoregressive distributed lag model," Empirical Economics, Springer, vol. 52(4), pages 1609-1626, June.
    17. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2016. "Crude oil and stock markets: Causal relationships in tails?," Energy Economics, Elsevier, vol. 59(C), pages 58-69.
    18. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
    19. Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
    20. Emmanuel Uche & Lionel Effiom, 2021. "Oil price, exchange rate and stock price in Nigeria: Fresh insights based on quantile ARDL model," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2021(1), pages 59-79.
    21. Guodong Li & Yang Li & Chih-Ling Tsai, 2015. "Quantile Correlations and Quantile Autoregressive Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 246-261, March.
    22. Yuyan Wang & Akhgar Ghassabian & Bo Gu & Yelena Afanasyeva & Yiwei Li & Leonardo Trasande & Mengling Liu, 2023. "Semiparametric distributed lag quantile regression for modeling time‐dependent exposure mixtures," Biometrics, The International Biometric Society, vol. 79(3), pages 2619-2632, September.
    23. Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & Francisco Marcos Rodrigues Figueiredo, 2015. "Local Unit Root and Inflationary Inertia in Brazil," Working Papers Series 406, Central Bank of Brazil, Research Department.
    24. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    25. Debdatta PAL & Subrata Kumar MITRA, 2015. "Impact of price realization on India's tea export: Evidence from Quantile Autoregressive Distributed Lag Model," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(9), pages 422-428.
    26. Zhu, Hui-Ming & Li, ZhaoLai & You, WanHai & Zeng, Zhaofa, 2015. "Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 142-153.
    27. Robert Wojciechowski, 2024. "A Structural Approach to Growth-at-Risk," Papers 2410.04431, arXiv.org.
    28. Montes-Rojas, Gabriel, 2017. "Reduced form vector directional quantiles," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 20-30.
    29. Martins, Luis F., 2021. "The US debt–growth nexus along the business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    30. Janda, Karel & Kravec, Peter, 2022. "VECM Modelling of the Price Dynamics for Fuels, Agricultural Commodities and Biofuels," EconStor Preprints 259404, ZBW - Leibniz Information Centre for Economics.

  15. Baer, Werner & Fialho Galvao, Antonio, Jr., 2005. "Tax Burden, Government Expenditures and Income Distribution in Brazil," Working Papers 05-0129, University of Illinois at Urbana-Champaign, College of Business.

    Cited by:

    1. John Kwaku Amoh, 2019. "An Estimation of the Taxable Capacity, Tax Effort and Tax Burden of an Emerging Economy: Evidence from Ghana," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 12-21.

Articles

  1. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2024. "Bootstrap Inference for Panel Data Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 628-639, April.
    See citations under working paper version above.
  2. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    See citations under working paper version above.
  3. Firpo, Sergio & Galvao, Antonio F. & Parker, Thomas, 2023. "Uniform inference for value functions," Journal of Econometrics, Elsevier, vol. 235(2), pages 1680-1699.
    See citations under working paper version above.
  4. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.

    Cited by:

    1. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.

  5. Luciano Castro & Antonio F. Galvao, 2022. "Static and dynamic quantile preferences," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(2), pages 747-779, April.

    Cited by:

    1. Marinacci Massimo & Principi Giulio & Stanca Lorenzo, 2023. "Recursive Preferences and Ambiguity Attitudes," Working papers 082, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    2. Thomas J. Sargent & John Stachurski, 2024. "Dynamic Programming: Finite States," Papers 2401.10473, arXiv.org.
    3. Massimo Marinacci & Giulio Principi & Lorenzo Stanca, 2023. "Recursive Preferences and Ambiguity Attitudes," Carlo Alberto Notebooks 695 JEL Classification: C, Collegio Carlo Alberto.
    4. de Castro, Luciano & Galvao, Antonio F. & Muchon, Andre, 2023. "Numerical Solution of Dynamic Quantile Models," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
    5. Rabah Amir & Bernard Cornet & M. Ali Khan & David Levine & Edward C. Prescott, 2022. "Special Issue in honor of Nicholas C. Yannelis – Part II," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(2), pages 377-385, April.
    6. Massimo Marinacci & Giulio Principi & Lorenzo Stanca, 2023. "Recursive Preferences and Ambiguity Attitudes," Papers 2304.06830, arXiv.org, revised Jul 2024.

  6. de Castro, Luciano & Galvao, Antonio F. & Noussair, Charles N. & Qiao, Liang, 2022. "Do people maximize quantiles?," Games and Economic Behavior, Elsevier, vol. 132(C), pages 22-40.

    Cited by:

    1. Luciano De Castro & Antonio F. Galvao & Gabriel Montes Rojas & José Olmo, 2020. "Portfolio Selection in Quantile Decision Models," Working Papers 11, Red Nacional de Investigadores en Economía (RedNIE).
    2. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    3. de Castro, Luciano & Galvao, Antonio F. & Muchon, Andre, 2023. "Numerical Solution of Dynamic Quantile Models," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).

  7. Luciano de Castro & Antonio F. Galvao & Gabriel Montes-Rojas & Jose Olmo, 2022. "Portfolio selection in quantile decision models," Annals of Finance, Springer, vol. 18(2), pages 133-181, June.
    See citations under working paper version above.
  8. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.

    Cited by:

    1. Inuwa, Nasiru & Adamu, Sagir & Hamza, Yusuf & Sani, Mohammed Bello, 2023. "Does dichotomy between resource dependence and resource abundance matters for resource curse hypothesis? New evidence from quantiles via moments," Resources Policy, Elsevier, vol. 81(C).
    2. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    3. Khan, Yasir & Hassan, Taimoor & Guiqin, Huang & Nabi, Ghulam, 2023. "Analyzing the impact of natural resources and rule of law on sustainable environment: A proposed policy framework for BRICS economies," Resources Policy, Elsevier, vol. 86(PA).
    4. Christis Katsouris, 2023. "Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models," Papers 2311.08218, arXiv.org, revised Apr 2024.
    5. Dianliang Deng & Mashfiqul Huq Chowdhury, 2022. "Quantile Regression Approach for Analyzing Similarity of Gene Expressions under Multiple Biological Conditions," Stats, MDPI, vol. 5(3), pages 1-23, July.
    6. Jayeeta Bhattacharya, 2020. "Quantile regression with generated dependent variable and covariates," Papers 2012.13614, arXiv.org.

  9. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    See citations under working paper version above.
  10. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).

    Cited by:

    1. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).

  11. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.

    Cited by:

    1. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    2. Daan Opschoor & Dick van Dijk & Philip Hans Franses, 2021. "Heterogeneity in Manufacturing Growth Risk," Tinbergen Institute Discussion Papers 21-036/III, Tinbergen Institute.
    3. Andreas Hagemann, 2023. "Inference on quantile processes with a finite number of clusters," Papers 2301.04687, arXiv.org, revised Jun 2023.

  12. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
    See citations under working paper version above.
  13. Luciano de Castro & Antonio F. Galvao, 2019. "Dynamic Quantile Models of Rational Behavior," Econometrica, Econometric Society, vol. 87(6), pages 1893-1939, November.

    Cited by:

    1. Gabriel Montes-Rojas & Luciano de Castro & Antonio F. Galvao & Jeong Yeol Kim & José Olmo, 2021. "Experiments On Portfolio Selection: A Comparison Between Quantile Preferences And Expected Utility Decision Models," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2021-68, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    2. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    3. de Castro, Luciano & Galvao, Antonio F. & Noussair, Charles N. & Qiao, Liang, 2022. "Do people maximize quantiles?," Games and Economic Behavior, Elsevier, vol. 132(C), pages 22-40.
    4. Le-Yu Chen & Ekaterina Oparina & Nattavudh Powdthavee & Sorawoot Srisuma, 2019. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Papers 1902.07696, arXiv.org, revised Jun 2022.
    5. Hirbod Assa & Peng Liu, 2024. "Factor risk measures," Papers 2404.08475, arXiv.org.
    6. Xue Dong He & Zhaoli Jiang & Steven Kou, 2020. "Portfolio Selection under Median and Quantile Maximization," Papers 2008.10257, arXiv.org, revised Mar 2021.
    7. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    8. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.
    9. Long, Yan & Sethuraman, Jay & Xue, Jingyi, 2021. "Equal-quantile rules in resource allocation with uncertain needs," Journal of Economic Theory, Elsevier, vol. 197(C).
    10. Luciano De Castro & Antonio F. Galvao & Gabriel Montes Rojas & José Olmo, 2020. "Portfolio Selection in Quantile Decision Models," Working Papers 11, Red Nacional de Investigadores en Economía (RedNIE).
    11. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    12. Thomas J. Sargent & John Stachurski, 2024. "Dynamic Programming: Finite States," Papers 2401.10473, arXiv.org.
    13. Xue Dong He & Zhaoli Jiang, 2020. "Optimal Payoff under the Generalized Dual Theory of Choice," Papers 2012.00345, arXiv.org.
    14. Striani, Fabrizio, 2023. "Life-cycle consumption and life insurance: Empirical evidence from Italian Survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    15. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    16. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    17. de Castro, Luciano & Galvao, Antonio F. & Muchon, Andre, 2023. "Numerical Solution of Dynamic Quantile Models," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
    18. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    19. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    20. Luciano Castro & Antonio F. Galvao, 2022. "Static and dynamic quantile preferences," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(2), pages 747-779, April.
    21. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.

  14. Antonio F. Galvao & Alexandre Poirier, 2019. "Quantile Regression Random Effects," Annals of Economics and Statistics, GENES, issue 134, pages 109-148.

    Cited by:

    1. Paulo M.M. Rodrigues & Matei Demetrescu, 2022. "Cross-Sectional Error Dependence in Panel Quantile Regressions," Working Papers w202213, Banco de Portugal, Economics and Research Department.
    2. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    4. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021. "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, vol. 60(1), pages 227-259, January.
    5. Schorr, A. & Lips, M., 2018. "Influence of milk yield on profitability a quantile regression analysis," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277000, International Association of Agricultural Economists.
    6. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.
    7. Martina Pons & Blaise Melly, 2022. "Stata commands to estimate quantile regression with panel and grouped data," Swiss Stata Conference 2022 05, Stata Users Group.

  15. Murillo Campello & Antonio F. Galvao & Ted Juhl, 2019. "Testing for Slope Heterogeneity Bias in Panel Data Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 749-760, October.

    Cited by:

    1. Musarat Abbas & Ling Yang & Michael L. Lahr, 2024. "Globalization’s effects on South Asia’s carbon emissions, 1996–2019: a multidimensional panel data perspective via FGLS," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-19, December.
    2. Zhang, Chunhong & Khan, Irfan & Dagar, Vishal & Saeed, Asif & Zafar, Muhammad Wasif, 2022. "Environmental impact of information and communication technology: Unveiling the role of education in developing countries," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    3. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    4. Cai, Zongwu & Juhl, Ted, 2023. "The distribution of rolling regression estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1447-1463.
    5. Feng Wang & Seemab Gillani & Rabia Nazir & Asif Razzaq, 2024. "Environmental regulations, fiscal decentralization, and health outcomes," Energy & Environment, , vol. 35(6), pages 3038-3064, September.
    6. Umer Shahzad & Magdalena Radulescu & Syed Rahim & Cem Isik & Zahid Yousaf & Stefan Alexandru Ionescu, 2021. "Do Environment-Related Policy Instruments and Technologies Facilitate Renewable Energy Generation? Exploring the Contextual Evidence from Developed Economies," Energies, MDPI, vol. 14(3), pages 1-25, January.
    7. Deng, Wei & Akram, Rabia & Mirza, Nawazish, 2022. "Economic performance and natural resources: Evaluating the role of economic risk," Resources Policy, Elsevier, vol. 78(C).
    8. Yoonseok Lee & Donggyu Sul, 2022. "Trimmed Mean Group Estimation," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, volume 43, pages 177-202, Emerald Group Publishing Limited.
    9. Wang, Chen & Xia, Mengli & Wang, Piao & Xu, Junjie, 2022. "Renewable energy output, energy efficiency and cleaner energy: Evidence from non-parametric approach for emerging seven economies," Renewable Energy, Elsevier, vol. 198(C), pages 91-99.
    10. Kumar, Virender & Dua, Pami, 2024. "What explains foreign portfolio investment inflows to BRICS countries?," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 32-46.
    11. Zeeshan Khan & Ramez Abubakr Badeeb & Kishwar Nawaz, 2022. "Natural resources and economic performance: Evaluating the role of political risk and renewable energy consumption," Post-Print hal-03858132, HAL.
    12. Wang, Fei & Liu, Xiaoyan, 2023. "Resources extraction and geopolitical risk: A novel perspective of World's biggest economies," Resources Policy, Elsevier, vol. 85(PA).
    13. Li, Ying & Tariq, Muhammad & Khan, Saleem & Rjoub, Husam & Azhar, Aisha, 2022. "Natural resources rents, capital formation and economic performance: Evaluating the role of globalization," Resources Policy, Elsevier, vol. 78(C).
    14. Ferdi Akpilic & Caglayan Aslan, 2024. "The impact of real exchange rate uncertainty on exports by technology classification in emerging economies," International Economics and Economic Policy, Springer, vol. 21(4), pages 907-931, October.
    15. Su, Chi-Wei & Sun, Tiezhu & Ahmad, Shabbir & Mirza, Nawazish, 2021. "Does institutional quality and remittances inflow crowd-in private investment to avoid Dutch Disease? A case for emerging seven (E7) economies," Resources Policy, Elsevier, vol. 72(C).
    16. Wen, Jun & Mughal, Nafeesa & Kashif, Maryam & Jain, Vipin & Ramos Meza, Carlos Samuel & Cong, Phan The, 2022. "Volatility in natural resources prices and economic performance: Evidence from BRICS economies," Resources Policy, Elsevier, vol. 75(C).
    17. Arpita Patnaik & Joanna Venator & Matthew Wiswall & Basit Zafar, 2020. "The Role of Heterogeneous Risk Preferences, Discount Rates, and Earnings Expectations in College Major Choice," NBER Working Papers 26785, National Bureau of Economic Research, Inc.
    18. Khan, Yasir & Liu, Fang & Hassan, Taimoor, 2023. "Natural resources and sustainable development: Evaluating the role of remittances and energy resources efficiency," Resources Policy, Elsevier, vol. 80(C).
    19. Liu, Qiang & Sun, Hongyu & Luo, Haiming, 2022. "Resource-richness, technological innovation, and sustainable development: Evidence from emerging economies," Resources Policy, Elsevier, vol. 79(C).
    20. Liu, Xiaojing & Yang, Jie & Bilan, Yuriy & Shahzad, Umer, 2023. "Resources curse hypothesis and COP26 target: Mineral and oil resources economies COVID-19 perspective," Resources Policy, Elsevier, vol. 83(C).
    21. Liang, Jinhao & Razzaq, Asif & Sharif, Arshian & Irfan, Muhammad, 2022. "Revisiting economic and non-economic indicators of natural resources: Analysis of developed economies," Resources Policy, Elsevier, vol. 77(C).
    22. Arif, Asma & Minh Vu, Hieu & Cong, Ma & Hon Wei, Leow & Islam, Md. Monirul & Niedbała, Gniewko, 2022. "Natural resources commodity prices volatility and economic performance: Evaluating the role of green finance," Resources Policy, Elsevier, vol. 76(C).
    23. Fareeha Adil & Rabia Nazir, 2023. "Firms Financial Inclusion and Export Performance: Evidence from Manufacturing Sector Firms in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 62(3), pages 409-430.
    24. Pourya Valizadeh & Bart L. Fischer & Henry L. Bryant, 2024. "SNAP enrollment cycles: New insights from heterogeneous panel models with cross‐sectional dependence," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 354-381, January.
    25. Zongwu Cai & Ted Juhl, 2020. "The Distribution Of Rolling Regression Estimators," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202218, University of Kansas, Department of Economics, revised Dec 2022.
    26. Hordofa, Tolassa Temesgen & Liying, Song & Mughal, Nafeesa & Arif, Asma & Minh Vu, Hieu & Kaur, Prabjot, 2022. "Natural resources rents and economic performance: Post-COVID-19 era for G7 countries," Resources Policy, Elsevier, vol. 75(C).
    27. Huang, Tianwei & Yang, Lei & Liu, Yufei & Liu, Haibing, 2023. "Dutch disease revisited: China's provincial data perspective with the role of green finance and technology peak," Resources Policy, Elsevier, vol. 83(C).
    28. Wang, Zhe & Chen, Huangxin & Teng, Yin-Pei, 2023. "Role of greener energies, high tech-industries and financial expansion for ecological footprints: Implications from sustainable development perspective," Renewable Energy, Elsevier, vol. 202(C), pages 1424-1435.
    29. Gu, Xiao & Shen, Xi & Zhong, Xiangming & Wu, Tong & Rahim, Syed, 2023. "Natural resources and undesired productions of environmental outputs as green growth: EKC in the perspective of green finance and green growth in the G7 region," Resources Policy, Elsevier, vol. 82(C).
    30. Zhu, Jia & Zhou, Pengfei & Shen, Yang, 2024. "Exploring the individual and combined effect of natural resource rents, fin-tech, and renewable energy on sustainable development: New insights from SSA countries," Resources Policy, Elsevier, vol. 91(C).
    31. Huo, Qixin & Huang, Yuchen & Khan, Salahuddin & Mallek, Sabrine & Wolanin, Elżbieta, 2023. "Employment generation via natural resources: A novel perspective of Dutch disease in the employment market," Resources Policy, Elsevier, vol. 85(PB).
    32. Wang, Tianyang & Umar, Muhammad & Li, Menggang & Shan, Shan, 2023. "Green finance and clean taxes are the ways to curb carbon emissions: An OECD experience," Energy Economics, Elsevier, vol. 124(C).
    33. Xu, Jiaqi & Zhao, Jingfeng & She, Shengxiang & Liu, Wen, 2022. "Green growth, natural resources and sustainable development: Evidence from BRICS economies," Resources Policy, Elsevier, vol. 79(C).
    34. Li, Menghan & Zhang, Kaiyue & Alamri, Ahmad Mohammed & Ageli, Mohammed Moosa & Khan, Numan, 2023. "Resource curse hypothesis and sustainable development: Evaluating the role of renewable energy and R&D," Resources Policy, Elsevier, vol. 81(C).
    35. Hagenhoff, Tim & Lustenhouwer, Joep, 2023. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    36. Wang, Zhongbao & Razzaq, Asif, 2022. "Natural resources, energy efficiency transition and sustainable development: Evidence from BRICS economies," Resources Policy, Elsevier, vol. 79(C).
    37. Winkelmann Rainer, 2024. "Neglected Heterogeneity, Simpson’s Paradox, and the Anatomy of Least Squares," Journal of Econometric Methods, De Gruyter, vol. 13(1), pages 131-144, January.
    38. Li, Xuelin & Yang, Lin, 2023. "Natural resources, remittances and carbon emissions: A Dutch Disease perspective with remittances for South Asia," Resources Policy, Elsevier, vol. 85(PB).
    39. Khan, Arshad Ahmad & Luo, Jianchao & Safi, Adnan & Khan, Sufyan Ullah & Ali, Muhammad Abu Sufyan, 2022. "What determines volatility in natural resources? Evaluating the role of political risk index," Resources Policy, Elsevier, vol. 75(C).
    40. Zhou, Rong & Su, Kaihua & Zheng, Li, 2022. "Natural resources led growth and the role of financial development: Evidence from Next-11 economies," Resources Policy, Elsevier, vol. 79(C).
    41. Zhou, Haonan & Li, Dongxin & Mustafa, Faisal & Altuntaş, Mehmet, 2022. "Natural resources volatility and South Asian economies: Evaluating the role of COVID-19," Resources Policy, Elsevier, vol. 75(C).
    42. Gao, Chunjiao & Chen, Hongxi, 2023. "Electricity from renewable energy resources: Sustainable energy transition and emissions for developed economies," Utilities Policy, Elsevier, vol. 82(C).
    43. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    44. Tong, Jun & Wang, Kai, 2024. "Exploring the role of higher education attainment in shaping the nexus of mineral resources dependency, business freedom, and globalization in South Asia," Resources Policy, Elsevier, vol. 91(C).
    45. Aamir Javed & Bilal Haider Subhani & Asif Javed & Agnese Rapposelli, 2024. "Accessing the efficacy of green growth, energy efficiency, and green innovation for environmental performance in top manufacturing nations in the framework of sustainable development," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(6), pages 5829-5863, December.
    46. Ding, Yuanyi, 2023. "Does natural resources cause sustainable financial development or resources curse? Evidence from group of seven economies," Resources Policy, Elsevier, vol. 81(C).
    47. Sun, Yanpeng & Chang, Hsuling & Vasbieva, Dinara G. & Andlib, Zubaria, 2022. "Economic performance, investment in energy resources, foreign trade, and natural resources volatility nexus: Evidence from China's provincial data," Resources Policy, Elsevier, vol. 78(C).
    48. Lin, Renzao & Wang, Zhe & Gao, Chunjiao, 2023. "Re-examining resources taxes and sustainable financial expansion: An empirical evidence of novel panel methods for China's provincial data," Resources Policy, Elsevier, vol. 80(C).
    49. Wu, Zihao & Gao, Jun & Xu, Hui & Shi, Guanqun & Zaidan, Amal Mousa & Ageli, Mohammed Moosa, 2023. "Visualizing symmetric and asymmetric settings in MMQR for natural resources extraction and economic performance: A COVID-19 perspective," Resources Policy, Elsevier, vol. 85(PB).
    50. Ramzan, Muhammad & Abbasi, Kashif Raza & Salman, Asma & Dagar, Vishal & Alvarado, Rafael & Kagzi, Muneza, 2023. "Towards the dream of go green: An empirical importance of green innovation and financial depth for environmental neutrality in world's top 10 greenest economies," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    51. Ma, Qiang & Mentel, Grzegorz & Zhao, Xin & Salahodjaev, Raufhon & Kuldasheva, Zebo, 2022. "Natural resources tax volatility and economic performance: Evaluating the role of digital economy," Resources Policy, Elsevier, vol. 75(C).
    52. Liu, Qiang & Zhao, Zhongwei & Liu, Yiran & He, Yao, 2022. "Natural resources commodity prices volatility, economic performance and environment: Evaluating the role of oil rents," Resources Policy, Elsevier, vol. 76(C).
    53. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).

  16. Francisco H.G. Ferreira & Sergio Firpo & Antonio F. Galvao, 2019. "Actual and counterfactual growth incidence and delta Lorenz curves: Estimation and inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 385-402, April.

    Cited by:

    1. Edwin Fourrier-Nicolai & Michel Lubrano, 2020. "Bayesian Inference for Distributional Changes: The Effect of Western TV on Wage Inequality and Female Participation in Former East Germany," Working Papers halshs-02909932, HAL.
    2. Zachary Parolin & Janet Gornick, 2021. "Pathways toward Inclusive Income Growth: A Comparative Decomposition of National Growth Profiles," LIS Working papers 802, LIS Cross-National Data Center in Luxembourg.
    3. Laurent Piet & M Benoit & V Chatellier & K. Hervé Dakpo & N Delame & Yann Desjeux & P Dupraz & M Gillot & Philippe Jeanneaux & C Laroche-Dupraz & A Ridier & E Samson & P Veysset & P Avril & C Beaudoui, 2020. "Hétérogénéité, déterminants et trajectoires du revenu des agriculteurs français," Working Papers hal-02877320, HAL.
    4. Parolin, Zachary & Gornick, Janet C., 2021. "Pathways toward Inclusive Income Growth: A Comparative Decomposition of National Growth Profiles," SocArXiv rsxz6, Center for Open Science.
    5. Laurent Piet & Vincent Chatellier & Nathalie Delame & Yann Desjeux & Philippe Jeanneaux & Catherine Laroche-Dupraz & Aude Ridier & Patrick Veysset, 2021. "Hétérogénéité, déterminants et soutien du revenu des agriculteurs français," Post-Print hal-03405184, HAL.

  17. Antonio F Galvao & Ted Juhl & Gabriel Montes-Rojas & Jose Olmo, 2018. "Testing Slope Homogeneity in Quantile Regression Panel Data with an Application to the Cross-Section of Stock Returns," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 211-243.

    Cited by:

    1. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    2. Chuliá, Helena & Koser, Christoph & Uribe, Jorge M., 2021. "Analyzing the Nonlinear Pricing of Liquidity Risk according to the Market State," Finance Research Letters, Elsevier, vol. 38(C).
    3. Daan Opschoor & Dick van Dijk & Philip Hans Franses, 2021. "Heterogeneity in Manufacturing Growth Risk," Tinbergen Institute Discussion Papers 21-036/III, Tinbergen Institute.

  18. Antonio F. Galvao & Gabriel Montes–Rojas & Jose Olmo & Suyong Song, 2018. "On solving endogeneity with invalid instruments: an application to investment equations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 689-716, June.

    Cited by:

    1. Ali Al-Sharadqah & Majid Mojirsheibani & William Pouliot, 2020. "On the performance of weighted bootstrapped kernel deconvolution density estimators," Statistical Papers, Springer, vol. 61(4), pages 1773-1798, August.

  19. Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.

    Cited by:

    1. Wagner, Helga & Frühwirth-Schnatter, Sylvia & Jacobi, Liana, 2023. "Factor-augmented Bayesian treatment effects models for panel outcomes," Econometrics and Statistics, Elsevier, vol. 28(C), pages 63-80.
    2. Gabriel Montes-Rojas & Vera Chiodi, 2021. "MENTORING AS A DOSE TREATMENT: FREQUENCY MATTERS: Evidence from a French mentoring program," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2021-65, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    3. Ai, Chunrong & Linton, Oliver & Zhang, Zheng, 2022. "Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models," Journal of Econometrics, Elsevier, vol. 228(1), pages 39-61.

  20. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.

    Cited by:

    1. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Childhood Intervention," IZA Discussion Papers 13101, Institute of Labor Economics (IZA).
    2. Wei Fang & Zhenyu Yang & Zhen Liu & Assem Abu Hatab, 2023. "Green recovery of cropland carrying capacity in developed regions: empirical evidence from Guangdong, China," Economic Change and Restructuring, Springer, vol. 56(4), pages 2405-2436, August.
    3. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Child Intervention," CEPR Discussion Papers 14721, C.E.P.R. Discussion Papers.
    4. Andrew Chesher, 2017. "Understanding the effect of measurement error on quantile regressions," CeMMAP working papers CWP19/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2021. "A Nonparametric Test for Testing Heterogeneity in Conditional Quantile Treatment Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202117, University of Kansas, Department of Economics, revised Aug 2021.
    6. Brantly Callaway & Tong Li & Irina Murtazashvili, 2021. "Distributional Effects with Two-Sided Measurement Error: An Application to Intergenerational Income Mobility," Papers 2107.09235, arXiv.org, revised Jun 2024.
    7. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    8. Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2020. "Inferences for Partially Conditional Quantile Treatment Effect Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202005, University of Kansas, Department of Economics, revised Feb 2020.
    9. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.

  21. Galvao, Antonio F. & Montes-Rojas, Gabriel & Song, Suyong, 2017. "Endogeneity bias modeling using observables," Economics Letters, Elsevier, vol. 152(C), pages 41-45.

    Cited by:

    1. Hoedoafia, Mabel Akosua, 2020. "On the Link between Trade Liberalization and Firm Productivity: Panel Data Evidence from Private Firms in Ghana," MPRA Paper 99568, University Library of Munich, Germany.
    2. Antonio F. Galvao & Gabriel Montes–Rojas & Jose Olmo & Suyong Song, 2018. "On solving endogeneity with invalid instruments: an application to investment equations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 689-716, June.

  22. Bera Anil K. & Galvao Antonio F. & Montes-Rojas Gabriel V. & Park Sung Y., 2016. "Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 79-101, January.

    Cited by:

    1. Bernstein, David H. & Parmeter, Christopher F. & Tsionas, Mike G., 2023. "On the performance of the United States nuclear power sector: A Bayesian approach," Energy Economics, Elsevier, vol. 125(C).
    2. Javier Alejo & Antonio F. Galvao & Julian Martinez-Iriarte & Gabriel Montes-Rojas, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Papers 2301.07241, arXiv.org, revised Dec 2023.
    3. Bajgiran, Amirsaman H. & Mardikoraem, Mahsa & Soofi, Ehsan S., 2021. "Maximum entropy distributions with quantile information," European Journal of Operational Research, Elsevier, vol. 290(1), pages 196-209.
    4. Huang, Huafang & Cheng, Xianfu & Wei, Liangli & Liu, Dongping & Deng, Minmin, 2024. "Are natural resources a driving force for financial development or a curse for the economy? Policy insight from Next-11 countries," Resources Policy, Elsevier, vol. 88(C).
    5. Volkan Han & Oguz Ocal & Alper Aslan, 2023. "A revisit to the relationship between globalization and income inequality: are levels of development really paramount?," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 973-990, February.
    6. Yuxiao Jiang & Xinyu Han & Ning Qiu & Mengbing Du & Liang Zhao, 2023. "Identifying Urban–Rural Disparities and Associated Factors in the Prevalence of Disabilities in Tianjin, China," Land, MDPI, vol. 12(8), pages 1-20, July.
    7. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    8. Ellen Thio & MeiXuen Tan & Liang Li & Muhammad Salman & Xingle Long & Huaping Sun & Bangzhu Zhu, 2022. "The estimation of influencing factors for carbon emissions based on EKC hypothesis and STIRPAT model: Evidence from top 10 countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 11226-11259, September.
    9. Ren, Xiaohang & Lu, Zudi & Cheng, Cheng & Shi, Yukun & Shen, Jian, 2019. "On dynamic linkages of the state natural gas markets in the USA: Evidence from an empirical spatio-temporal network quantile analysis," Energy Economics, Elsevier, vol. 80(C), pages 234-252.
    10. Zhilun Jiao & Ningning Yu & Xiaofan Wu, 2024. "Disentangling the Intelligentization–Carbon Emission Nexus within China’s Logistics Sector: An Econometric Approach," Energies, MDPI, vol. 17(16), pages 1-21, August.
    11. Hyung-Gun Kim & Kwong-Chin Hung & Sung Park, 2015. "Determinants of Housing Prices in Hong Kong: A Box-Cox Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(2), pages 270-287, February.
    12. Cheng Cheng & Xiaohang Ren & Zhen Wang & Yukun Shi, 2018. "The Impacts of Non-Fossil Energy, Economic Growth, Energy Consumption, and Oil Price on Carbon Intensity: Evidence from a Panel Quantile Regression Analysis of EU 28," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
    13. Alfredo Cartone & Paolo Postiglione, 2016. "Modelli spaziali di regressione quantilica per l?analisi della convergenza economica regionale," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 28-48.
    14. Davidmac O. Ekeocha & Jonathan E. Ogbuabor & Oliver E. Ogbonna & Anthony Orji, 2023. "Economic policy uncertainty, governance institutions and economic performance in Africa: are there regional differences?," Economic Change and Restructuring, Springer, vol. 56(3), pages 1367-1431, June.
    15. Chen, Hongrui, 2023. "Energy innovations, natural resource abundance, urbanization, and environmental sustainability in the post-covid era. Does environmental regulation matter?," Resources Policy, Elsevier, vol. 85(PB).
    16. Gyamfi, Bright Akwasi & Bein, Murad A. & Udemba, Edmund Ntom & Bekun, Festus Victor, 2021. "Investigating the pollution haven hypothesis in oil and non-oil sub-Saharan Africa countries: Evidence from quantile regression technique," Resources Policy, Elsevier, vol. 73(C).
    17. Melike E. Bildirici & Rui Alexandre Castanho & Fazıl Kayıkçı & Sema Yılmaz Genç, 2022. "ICT, Energy Intensity, and CO 2 Emission Nexus," Energies, MDPI, vol. 15(13), pages 1-15, June.
    18. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).

  23. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. 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.
    3. Lee, Chien-Chiang & Yuan, Zihao & Ho, Shan-Ju, 2022. "How does export diversification affect income inequality? International evidence," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 410-421.
    4. Fattouh, Bassam & Pisicoli, Beniamino & Scaramozzino, Pasquale, 2024. "Debt and financial fragility: Italian non-financial companies after the pandemic," Economic Modelling, Elsevier, vol. 131(C).
    5. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    6. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    7. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    8. Edmond Berisha & Ram Sewak Dubey & Orkideh Gharehgozli, 2022. "Inflation and income inequality: Does the level of income inequality matter?," Papers 2202.05743, arXiv.org.
    9. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    10. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    11. Xiao Huang, 2023. "Composite Quantile Factor Model," Papers 2308.02450, arXiv.org, revised Nov 2024.
    12. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    13. Hang, Yin & Xue, Wenjun, 2020. "The asymmetric effects of monetary policy on the business cycle: Evidence from the panel smoothed quantile regression model," Economics Letters, Elsevier, vol. 195(C).
    14. Alexander Blasberg & Rüdiger Kiesel & Luca Taschini, 2022. "Carbon Default Swap - Disentangling the Exposure to Carbon Risk through CDS," CESifo Working Paper Series 10016, CESifo.
    15. Mohammad Arshad Rahman & Angela Vossmeyer, 2019. "Estimation and Applications of Quantile Regression for Binary Longitudinal Data," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B, volume 40, pages 157-191, Emerald Group Publishing Limited.
    16. Spyridon Boikos & Theodore Panagiotidis & Georgios Voucharas, 2021. "Financial Development, Reforms and Growth," Bank of Lithuania Working Paper Series 98, Bank of Lithuania.
    17. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    18. Galina Besstremyannaya & Sergei Golovan, 2023. "Measuring heterogeneity in hospital productivity: a quantile regression approach," Journal of Productivity Analysis, Springer, vol. 59(1), pages 15-43, February.
    19. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    20. Marcelo Fernandes & Emmanuel Guerre & Eduardo Horta, 2021. "Smoothing Quantile Regressions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 338-357, January.
    21. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    22. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    23. Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jan 2023.
    24. Bonaccolto-Töpfer, Marina & Castagnetti, Carolina & Prümer, Stephanie, 2022. "Understanding the public-private sector wage gap in Germany: New evidence from a Fixed Effects quantile Approach∗," Economic Modelling, Elsevier, vol. 116(C).
    25. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    26. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
    27. Chen, Liang & Ramos Ramirez, Andrey David, 2013. "Revisiting Granger Causality of CO2 on Global Warming: a Quantile Factor Approach," DES - Working Papers. Statistics and Econometrics. WS 35531, Universidad Carlos III de Madrid. Departamento de Estadística.
    28. Lee, Chien-Chiang & Yuan, Zihao & Lee, Chi-Chuan & Chang, Yu-Fang, 2022. "The impact of renewable energy technology innovation on energy poverty: Does climate risk matter?," Energy Economics, Elsevier, vol. 116(C).
    29. Castagnetti, Carolina & Giorgetti, Maria Letizia, 2019. "Understanding the gender wage-gap differential between the public and private sectors in Italy: A quantile approach," Economic Modelling, Elsevier, vol. 78(C), pages 240-261.
    30. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    31. Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.
    32. Besstremyannaya, Galina & Golovan, Sergei, 2021. "Measuring heterogeneity with fixed effect quantile regression: Long panels and short panels," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 70-82.
    33. Dogan, Eyup & Altinoz, Buket & Tzeremes, Panayiotis, 2020. "The analysis of ‘Financial Resource Curse’ hypothesis for developed countries: Evidence from asymmetric effects with quantile regression," Resources Policy, Elsevier, vol. 68(C).
    34. Daan Opschoor & Dick van Dijk & Philip Hans Franses, 2021. "Heterogeneity in Manufacturing Growth Risk," Tinbergen Institute Discussion Papers 21-036/III, Tinbergen Institute.
    35. 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.
    36. Jung-In Yeon & Jeong-Dong Lee & Chulwoo Baek, 2021. "A tale of two technological capabilities: economic growth revisited from a technological capability transition perspective," The Journal of Technology Transfer, Springer, vol. 46(3), pages 574-605, June.
    37. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased Inference for Dynamic Nonlinear Panels with Multi-dimensional Heterogeneities," Papers 2305.03134, arXiv.org, revised Nov 2024.
    38. Bargain, Olivier & Etienne, Audrey & Melly, Blaise, 2021. "Informal pay gaps in good and bad times: Evidence from Russia," Journal of Comparative Economics, Elsevier, vol. 49(3), pages 693-714.
    39. 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.
    40. Kean Ming Tan & Lan Wang & Wen‐Xin Zhou, 2022. "High‐dimensional quantile regression: Convolution smoothing and concave regularization," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 205-233, February.
    41. Carolina Castagnetti & Luisa Rosti & Marina Toepfer, 2019. "The Public-Private Sector Wage Differential Across Gender in Italy: a New Quantile-Based Decomposition Approach," DEM Working Papers Series 172, University of Pavia, Department of Economics and Management.
    42. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    43. 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.
    44. Hongqi Chen & Ji Hyung Lee, 2024. "Predictive Quantile Regression with High-Dimensional Predictors: The Variable Screening Approach," Papers 2410.15097, arXiv.org.
    45. Machado, José A.F. & Santos Silva, J.M.C., 2019. "Quantiles via moments," Journal of Econometrics, Elsevier, vol. 213(1), pages 145-173.
    46. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    47. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    48. Battagliola, Maria Laura & Sørensen, Helle & Tolver, Anders & Staicu, Ana-Maria, 2022. "A bias-adjusted estimator in quantile regression for clustered data," Econometrics and Statistics, Elsevier, vol. 23(C), pages 165-186.
    49. Panayiotis Tzeremes, 2022. "The Asymmetric Effects of Regional House Prices in the UK: New Evidence from Panel Quantile Regression Framework," Studies in Microeconomics, , vol. 10(1), pages 7-22, June.
    50. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    51. Lee, Chien-Chiang & Yuan, Zihao & Lee, Chi-Chuan, 2023. "A nonlinear analysis of the impacts of information and communication technologies on environmental quality: A global perspective," Energy Economics, Elsevier, vol. 128(C).
    52. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    53. Jorge Eduardo Camusso & Ana Inés Navarro, 2021. "Asymmetries in aggregate income risk over the business cycle: evidence from administrative data of Argentina," Asociación Argentina de Economía Política: Working Papers 4447, Asociación Argentina de Economía Política.
    54. Peng, Liuhua & Qu, Long & Nettleton, Dan, 2021. "Variable importance assessments and backward variable selection for multi-sample problems," Journal of Multivariate Analysis, Elsevier, vol. 186(C).

  24. Bera, Anil K. & Galvao, Antonio F. & Wang, Liang & Xiao, Zhijie, 2016. "A New Characterization Of The Normal Distribution And Test For Normality," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1216-1252, October.

    Cited by:

    1. Dong, Kangyin & Dong, Xiucheng & Ren, Xiaohang, 2020. "Can expanding natural gas infrastructure mitigate CO2 emissions? Analysis of heterogeneous and mediation effects for China," Energy Economics, Elsevier, vol. 90(C).
    2. Steffen Betsch & Bruno Ebner, 2020. "Testing normality via a distributional fixed point property in the Stein characterization," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 105-138, March.
    3. Panagiotis Palaios & Evangelia Papapetrou, 2022. "Oil prices, labour market adjustment and dynamic quantile connectedness analysis: evidence from Greece during the crisis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 11(1), pages 1-21, December.
    4. Sarantis Lolos & Panagiotis Palaios & Evangelia Papapetrou, 2023. "Tourism-led growth asymmetries in Greece: evidence from quantile regression analysis," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 22(1), pages 125-148, January.
    5. L. Ndwandwe & J. S. Allison & L. Santana & I. J. H. Visagie, 2023. "Testing for the Pareto type I distribution: a comparative study," METRON, Springer;Sapienza Università di Roma, vol. 81(2), pages 215-256, August.
    6. Marcel, Bräutigam & Marie, Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," ESSEC Working Papers WP1807, ESSEC Research Center, ESSEC Business School.
    7. Tauchmann, Harald, 2019. "Fixed-effects estimation of the linear discrete-time hazard model: An adjusted first-differences estimator," FAU Discussion Papers in Economics 09/2019, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    8. Ron Mittelhammer & George Judge & Miguel Henry, 2022. "An Entropy-Based Approach for Nonparametrically Testing Simple Probability Distribution Hypotheses," Econometrics, MDPI, vol. 10(1), pages 1-19, January.
    9. Gabriel Montes Rojas & Andrés Sebastián Mena, 2020. "Density estimation using bootstrap quantile variance and quantile-mean covariance," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2020-50, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    10. Ya. Yu. Nikitin, 2018. "Local exact Bahadur efficiencies of two scale-free tests of normality based on a recent characterization," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(6), pages 609-618, August.
    11. Marcel Bräutigam & Marie Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," Working Papers hal-02296832, HAL.

  25. Javier Alejo & Anil Bera & Antonio Galvao & Gabriel Montes-Rojas & Zhijie Xiao, 2016. "Tests for normality based on the quantile-mean covariance," Stata Journal, StataCorp LP, vol. 16(4), pages 1039-1057, December.

    Cited by:

    1. Tauchmann, Harald, 2019. "Fixed-effects estimation of the linear discrete-time hazard model: An adjusted first-differences estimator," FAU Discussion Papers in Economics 09/2019, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    2. Gabriel Montes Rojas & Andrés Sebastián Mena, 2020. "Density estimation using bootstrap quantile variance and quantile-mean covariance," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2020-50, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).

  26. Javier Alejo & Antonio Galvao & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2015. "Tests for normality in linear panel-data models," Stata Journal, StataCorp LP, vol. 15(3), pages 822-832, September.
    See citations under working paper version above.
  27. Galvao, Antonio F. & Wang, Liang, 2015. "Efficient minimum distance estimator for quantile regression fixed effects panel data," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 1-26.

    Cited by:

    1. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    2. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    3. Fattouh, Bassam & Pisicoli, Beniamino & Scaramozzino, Pasquale, 2024. "Debt and financial fragility: Italian non-financial companies after the pandemic," Economic Modelling, Elsevier, vol. 131(C).
    4. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    5. Edmond Berisha & Ram Sewak Dubey & Orkideh Gharehgozli, 2022. "Inflation and income inequality: Does the level of income inequality matter?," Papers 2202.05743, arXiv.org.
    6. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    7. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    8. Zhang, Yue-Jun & Peng, Hua-Rong & Liu, Zhao & Tan, Weiping, 2015. "Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach," Energy Policy, Elsevier, vol. 87(C), pages 303-313.
    9. Alexander Blasberg & Rüdiger Kiesel & Luca Taschini, 2022. "Carbon Default Swap - Disentangling the Exposure to Carbon Risk through CDS," CESifo Working Paper Series 10016, CESifo.
    10. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    11. Samiul Haque, 2022. "US federal farm payments and farm size: Quantile estimation on panel data," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 139-154, February.
    12. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    13. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    14. Philip Kostov & Julie Le Gallo, 2018. "What role for human capital in the growth process: new evidence from endogenous latent factor panel quantile regressions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(5), pages 501-527, November.
    15. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    16. Xiaowen Dai & Libin Jin, 2021. "Minimum distance quantile regression for spatial autoregressive panel data models with fixed effects," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-13, December.
    17. Antonio F. Galvao & Gabriel Montes-Rojas, 2015. "On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study," Econometrics, MDPI, vol. 3(3), pages 1-13, September.
    18. Xiao, Zhijie & Xu, Lan, 2019. "What do mean impacts miss? Distributional effects of corporate diversification," Journal of Econometrics, Elsevier, vol. 213(1), pages 92-120.
    19. Li Tao & Lingnan Tai & Manling Qian & Maozai Tian, 2023. "A New Instrumental-Type Estimator for Quantile Regression Models," Mathematics, MDPI, vol. 11(15), pages 1-26, August.
    20. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    21. Gaglianone, Wagner Piazza & Issler, João Victor, 2019. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 813, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    22. Daan Opschoor & Dick van Dijk & Philip Hans Franses, 2021. "Heterogeneity in Manufacturing Growth Risk," Tinbergen Institute Discussion Papers 21-036/III, Tinbergen Institute.
    23. Fukui, Hideki, 2019. "How do slot restrictions affect airfares? New evidence from the US airline industry," Economics of Transportation, Elsevier, vol. 17(C), pages 51-71.
    24. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    25. Machado, José A.F. & Santos Silva, J.M.C., 2019. "Quantiles via moments," Journal of Econometrics, Elsevier, vol. 213(1), pages 145-173.
    26. Martina Pons & Blaise Melly, 2022. "Stata commands to estimate quantile regression with panel and grouped data," Swiss Stata Conference 2022 05, Stata Users Group.
    27. Lahiri, Bidisha & Daramola, Richard, 2023. "Effects of credit and labor constraints on microenterprises and the unintended impact of changes in household endowments: Use of threshold estimation to detect heterogeneity," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 21-38.
    28. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
    29. Battagliola, Maria Laura & Sørensen, Helle & Tolver, Anders & Staicu, Ana-Maria, 2022. "A bias-adjusted estimator in quantile regression for clustered data," Econometrics and Statistics, Elsevier, vol. 23(C), pages 165-186.
    30. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    31. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    32. Jorge Eduardo Camusso & Ana Inés Navarro, 2021. "Asymmetries in aggregate income risk over the business cycle: evidence from administrative data of Argentina," Asociación Argentina de Economía Política: Working Papers 4447, Asociación Argentina de Economía Política.

  28. Antonio F. Galvao & Liang Wang, 2015. "Uniformly Semiparametric Efficient Estimation of Treatment Effects With a Continuous Treatment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1528-1542, December.

    Cited by:

    1. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    2. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    3. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    5. Christopher Harshaw & Fredrik Savje & Yitan Wang, 2022. "A Design-Based Riesz Representation Framework for Randomized Experiments," Papers 2210.08698, arXiv.org, revised Oct 2022.
    6. Javier Alejo & Antonio F. Galvao & Julian Martinez-Iriarte & Gabriel Montes-Rojas, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Papers 2301.07241, arXiv.org, revised Dec 2023.
    7. Jiang, Qingshan & Xu, Li & Huang, Can, 2022. "Covariates distributions balancing for continuous treatment," Economics Letters, Elsevier, vol. 217(C).
    8. Brantly Callaway & Weige Huang, 2020. "Distributional Effects of a Continuous Treatment with an Application on Intergenerational Mobility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 808-842, August.
    9. Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
    10. Ferreira,Francisco H. G. & Firpo,Sergio & Galvao,Antonio F., 2017. "Estimation and inference for actual and counterfactual growth incidence curves," Policy Research Working Paper Series 7933, The World Bank.
    11. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    12. Brantly Callaway & Andrew Goodman-Bacon & Pedro H. C. Sant'Anna, 2021. "Difference-in-Differences with a Continuous Treatment," Papers 2107.02637, arXiv.org, revised Jan 2024.
    13. Brantly Callaway & Tong Li & Irina Murtazashvili, 2021. "Distributional Effects with Two-Sided Measurement Error: An Application to Intergenerational Income Mobility," Papers 2107.09235, arXiv.org, revised Jun 2024.
    14. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2018. "A Unified Framework for Efficient Estimation of General Treatment Models," Papers 1808.04936, arXiv.org, revised Aug 2018.
    15. Gabriel Montes-Rojas & Vera Chiodi, 2021. "MENTORING AS A DOSE TREATMENT: FREQUENCY MATTERS: Evidence from a French mentoring program," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2021-65, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    16. Wei Huang & Oliver Linton & Zheng Zhang, 2022. "A Unified Framework for Specification Tests of Continuous Treatment Effect Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1817-1830, October.
    17. Yu-Chin Hsu & Martin Huber & Ying-Ying Lee & Chu-An Liu, 2021. "Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data," Papers 2106.04237, arXiv.org, revised Aug 2022.
    18. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Hsu, Yu-Chin & Huber, Martin & Lee, Ying-Ying & Pipoz, Layal, 2018. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," FSES Working Papers 495, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    20. Myeonggyun Lee & Andrea B. Troxel & Mengling Liu, 2024. "Partial-linear single-index transformation models with censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(4), pages 701-720, October.
    21. Huang, Ming-Yueh & Chan, Kwun Chuen Gary, 2018. "Joint sufficient dimension reduction for estimating continuous treatment effect functions," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 48-62.
    22. Brantly Callaway & Weige Huang, 2018. "Intergenerational Income Mobility: Counterfactual Distributions with a Continuous Treatment," DETU Working Papers 1801, Department of Economics, Temple University.
    23. Ai, Chunrong & Linton, Oliver & Zhang, Zheng, 2022. "Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models," Journal of Econometrics, Elsevier, vol. 228(1), pages 39-61.
    24. Yukitoshi Matsushita & Taisuke Otsu & Keisuke Takahata, 2022. "Estimating density ratio of marginals to joint: Applications to causal inference," STICERD - Econometrics Paper Series 619, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    25. Jie Zhu & Blanca Gallego, 2021. "Continuous Treatment Recommendation with Deep Survival Dose Response Function," Papers 2108.10453, arXiv.org, revised Sep 2023.
    26. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    27. Edward H. Kennedy & Zongming Ma & Matthew D. McHugh & Dylan S. Small, 2017. "Non-parametric methods for doubly robust estimation of continuous treatment effects," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(4), pages 1229-1245, September.
    28. Nenci, Silvia & Vurchio, Davide, 2023. "Modeling country-sectoral spillovers in generalized propensity score matching: An empirical test on trade data," Economic Modelling, Elsevier, vol. 124(C).
    29. Xiaoyun Wei & Chuanmin Zhao, 2024. "Does Chinese Environmental Policy Affect Income Inequality? Evidence from the Central Environmental Protection Inspection," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 32(3), pages 130-161, May.

  29. Antonio F. Galvao & Gabriel Montes-Rojas, 2015. "On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study," Econometrics, MDPI, vol. 3(3), pages 1-13, September.

    Cited by:

    1. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    2. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    3. Yoshihiko Norimasa & Kazuki Ueda & Tomohiro Watanabe, 2021. "Emerging Economies' Vulnerability to Changes in Capital Flows: The Role of Global and Local Factors," Bank of Japan Working Paper Series 21-E-5, Bank of Japan.
    4. Samiul Haque, 2022. "US federal farm payments and farm size: Quantile estimation on panel data," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 139-154, February.
    5. Claudiu Tiberiu Albulescu & Camélia Turcu, 2022. "Productivity, financial performance, and corporate governance: evidence from Romanian R&D firms," Post-Print hal-03810531, HAL.
    6. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    7. Mr. Tobias Adrian & Federico Grinberg & Nellie Liang & Sheheryar Malik, 2018. "The Term Structure of Growth-at-Risk," IMF Working Papers 2018/180, International Monetary Fund.
    8. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    9. Xiaowen Dai & Shidan Huang & Libin Jin & Maozai Tian, 2023. "Wild Bootstrap-Based Bias Correction for Spatial Quantile Panel Data Models with Varying Coefficients," Mathematics, MDPI, vol. 11(9), pages 1-16, April.
    10. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
    11. Battagliola, Maria Laura & Sørensen, Helle & Tolver, Anders & Staicu, Ana-Maria, 2022. "A bias-adjusted estimator in quantile regression for clustered data," Econometrics and Statistics, Elsevier, vol. 23(C), pages 165-186.
    12. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data: a comment on the Canay (2011) fixed effects estimator," Working Papers w0249, Center for Economic and Financial Research (CEFIR).
    13. Gareth W. Peters, 2018. "General Quantile Time Series Regressions for Applications in Population Demographics," Risks, MDPI, vol. 6(3), pages 1-47, September.
    14. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    15. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data: a comment on the Canay (2011) fixed effects estimator," Working Papers w0249, New Economic School (NES).

  30. Galvao, Antonio F. & Montes-Rojas, Gabriel, 2015. "On the equivalence of instrumental variables estimators for linear models," Economics Letters, Elsevier, vol. 134(C), pages 13-15.

    Cited by:

    1. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    2. Almeida, Carlo Alano Soares de & Fernandes, Kaio César & Oliveira, Denison Murilo de & Rocha, Leonardo Andrade & Silva, Napiê Galvê Araújo, 2020. "Growth and heterogeneity of human capital: effects of the expansion of higher education on the income increase in Brazilian municipalities," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    3. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.

  31. Bera Anil K. & Galvao Antonio F. & Wang Liang, 2014. "On Testing the Equality of Mean and Quantile Effects," Journal of Econometric Methods, De Gruyter, vol. 3(1), pages 47-62, January.

    Cited by:

    1. Gabriel Montes-Rojas & Lucas Siga & Ram Mainali, 2017. "Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 245-255, September.
    2. Karsten Schweikert, 2019. "Asymmetric price transmission in the US and German fuel markets: a quantile autoregression approach," Empirical Economics, Springer, vol. 56(3), pages 1071-1095, March.
    3. Gabriel Montes Rojas & Andrés Sebastián Mena, 2020. "Density estimation using bootstrap quantile variance and quantile-mean covariance," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2020-50, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    4. Kuck, Konstantin & Maderitsch, Robert & Schweikert, Karsten, 2015. "Asymmetric over- and undershooting of major exchange rates: Evidence from quantile regressions," Economics Letters, Elsevier, vol. 126(C), pages 114-118.

  32. Antonio F. Galvao & Kengo Kato, 2014. "Estimation and Inference for Linear Panel Data Models Under Misspecification When Both n and T are Large," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 285-309, April.

    Cited by:

    1. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    2. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Springer, vol. 68(3), pages 283-304, September.
    3. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    4. Juodis, Artūras & Karabiyik, Hande & Westerlund, Joakim, 2021. "On the robustness of the pooled CCE estimator," Journal of Econometrics, Elsevier, vol. 220(2), pages 325-348.
    5. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    6. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    7. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    8. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    9. Ulrike Unterhofer & Conny Wunsch, 2022. "Macroeconomic Effects of Active Labour Market Policies: A Novel Instrumental Variables Approach," Papers 2211.12437, arXiv.org.
    10. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    11. Ignace De Vos & Gerdie Everaert, 2024. "GLS Estimation of Local Projections: Trading Robustness for Efficiency," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1095, Ghent University, Faculty of Economics and Business Administration.
    12. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    13. 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.
    14. Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, vol. 4(1), pages 1-14, December.
    15. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    16. De Vos, Ignace & Stauskas, Ovidijus, 2024. "Cross-section bootstrap for CCE regressions," Journal of Econometrics, Elsevier, vol. 240(1).
    17. De Vos, Ignace & Stauskas, Ovidijus, 2021. "Bootstrap Improved Inference for Factor-Augmented Regressions with CCE," Working Papers 2021:16, Lund University, Department of Economics.

  33. Montes-Rojas, Gabriel & Galvao, Antonio F., 2014. "Bayesian endogeneity bias modeling," Economics Letters, Elsevier, vol. 122(1), pages 36-39.

    Cited by:

    1. Just, David R. & Jiao, Jie, 2024. "Using Multiple Methods to Improve Validity," 2024 Annual Meeting, July 28-30, New Orleans, LA 345097, Agricultural and Applied Economics Association.
    2. Galvao, Antonio F. & Montes-Rojas, Gabriel & Song, Suyong, 2017. "Endogeneity bias modeling using observables," Economics Letters, Elsevier, vol. 152(C), pages 41-45.
    3. Paulo Chahuara, 2020. "Análisis Empírico de la Relación entre Competencia e Inversión en el Servicio de Telefonía Móvil Peruano," Documentos de Trabajo 42, OSIPTEL.
    4. Maynou, Laia & Saez, Marc & López-Casasnovas, Guillem, 2024. "Association of income and wealth with self-reported health status: analysis of European countries during the financial crisis," LSE Research Online Documents on Economics 124212, London School of Economics and Political Science, LSE Library.
    5. Byaro, Mwoya & Msafiri, Derick, 2021. "The uncertainty of natural gas consumption in Tanzania to support economic development. Evidence from Bayesian estimates," African Journal of Economic Review, African Journal of Economic Review, vol. 9(4), September.
    6. Mukhoti, Sujay & Guhathakurta, Kousik, 2015. "Product market performance and capital structure: A Hierarchical Bayesian semi-parametric panel regression model," MPRA Paper 62517, University Library of Munich, Germany.

  34. Antonio Galvao & Kengo Kato & Gabriel Montes-Rojas & Jose Olmo, 2014. "Testing linearity against threshold effects: uniform inference in quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 413-439, April.

    Cited by:

    1. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
    2. Liwen Zhang & Huixia Judy Wang & Zhongyi Zhu, 2017. "Composite change point estimation for bent line quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 145-168, February.
    3. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    4. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series," Cambridge Working Papers in Economics 1452, Faculty of Economics, University of Cambridge.
    5. Christoph Rothe & Dominik Wied, 2013. "Misspecification Testing in a Class of Conditional Distributional Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 314-324, March.
    6. Junho Lee & Ying Sun & Huixia Judy Wang, 2021. "Spatial cluster detection with threshold quantile regression," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    7. Christis Katsouris, 2023. "Estimation and Inference in Threshold Predictive Regression Models with Locally Explosive Regressors," Papers 2305.00860, arXiv.org, revised May 2023.
    8. Sokbae (Simon) Lee & Hyunmin Park & Myung Hwan Seo & Youngki Shin, 2014. "A contribution to the Reinhart and Rogoff debate: not 90 percent but maybe 30 percent," CeMMAP working papers CWP39/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Martins, Luis F., 2021. "The US debt–growth nexus along the business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

  35. Antonio F. Galvao JR. & Gabriel Montes-Rojas & Sung Y. Park, 2013. "Quantile Autoregressive Distributed Lag Model with an Application to House Price Returns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 307-321, April.
    See citations under working paper version above.
  36. Antonio F. Galvao & Carlos Lamarche & Luiz Renato Lima, 2013. "Estimation of Censored Quantile Regression for Panel Data With Fixed Effects," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 1075-1089, September.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    3. 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.
    4. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    5. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    6. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    7. Choi, Jin-young & Lee, Myoung-jae, 2019. "Twins are more different than commonly believed, but made less different by compensating behaviors," Economics & Human Biology, Elsevier, vol. 35(C), pages 18-31.
    8. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    9. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021. "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, vol. 60(1), pages 227-259, January.
    10. Junlong Feng, 2019. "Regularized Quantile Regression with Interactive Fixed Effects," Papers 1911.00166, arXiv.org, revised Mar 2021.
    11. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    12. Ayala, Diana & Nedeljkovic, Milan & Saborowski, Christian, 2016. "What slice of the pie? The corporate bond market boom in emerging economies," BOFIT Discussion Papers 8/2016, Bank of Finland Institute for Emerging Economies (BOFIT).
    13. Harrison Fell & Daniel T. Kaffine, 2014. "A one-two punch: Joint effects of natural gas abundance and renewables on coal-fired power plants," Working Papers 2014-10, Colorado School of Mines, Division of Economics and Business.
    14. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    15. De Silva, Dakshina G. & Kosmopoulou, Georgia & Lamarche, Carlos, 2017. "Subcontracting and the survival of plants in the road construction industry: A panel quantile regression analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 137(C), pages 113-131.
    16. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    17. Matthew Harding & Carlos Lamarche, 2017. "Penalized Quantile Regression with Semiparametric Correlated Effects: An Application with Heterogeneous Preferences," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 342-358, March.
    18. Matthew Harding & Carlos Lamarche, 2018. "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment," Papers 1808.03364, arXiv.org.
    19. Fell, Harrison & Kaffine, Daniel T., 2014. "A one-two punch: Joint eects of natural gas abundance and renewables on coal-red power plants," CEnREP Working Papers 340063, North Carolina State University, Department of Agricultural and Resource Economics.
    20. Diana Ayala & Milan Nedeljkovic & Christian Saborowski, 2017. "What Slice of the Pie? The Corporate Bond Market Boom in Emerging Economies," CESifo Working Paper Series 6376, CESifo.
    21. Zongwu Cai & Meng Shi & Yue Zhao & Wuqing Wu, 2020. "Testing Financial Hierarchy Based on A PDQ-CRE Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202011, University of Kansas, Department of Economics, revised Jul 2020.
    22. Antonio F. Galvao & Gabriel Montes-Rojas, 2015. "On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study," Econometrics, MDPI, vol. 3(3), pages 1-13, September.
    23. Galvao, Antonio F. & Wang, Liang, 2015. "Efficient minimum distance estimator for quantile regression fixed effects panel data," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 1-26.
    24. Xiao, Zhijie & Xu, Lan, 2019. "What do mean impacts miss? Distributional effects of corporate diversification," Journal of Econometrics, Elsevier, vol. 213(1), pages 92-120.
    25. Li Tao & Lingnan Tai & Manling Qian & Maozai Tian, 2023. "A New Instrumental-Type Estimator for Quantile Regression Models," Mathematics, MDPI, vol. 11(15), pages 1-26, August.
    26. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    27. Harrison Fell & Daniel T. Kaffine, 2018. "The Fall of Coal: Joint Impacts of Fuel Prices and Renewables on Generation and Emissions," American Economic Journal: Economic Policy, American Economic Association, vol. 10(2), pages 90-116, May.
    28. Alexander Silbersdorff & Julia Lynch & Stephan Klasen & Thomas Kneib, 2017. "Reconsidering the Income-Illness Relationship Using Distributional Regression: An Application to Germany," SOEPpapers on Multidisciplinary Panel Data Research 931, DIW Berlin, The German Socio-Economic Panel (SOEP).
    29. Yuzhu Tian & Er’qian Li & Maozai Tian, 2016. "Bayesian joint quantile regression for mixed effects models with censoring and errors in covariates," Computational Statistics, Springer, vol. 31(3), pages 1031-1057, September.
    30. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.
    31. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    32. Ali Aghamohammadi, 2018. "Bayesian analysis of dynamic panel data by penalized quantile regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 91-108, March.
    33. Yuzhu Tian & Manlai Tang & Maozai Tian, 2018. "Joint modeling for mixed-effects quantile regression of longitudinal data with detection limits and covariates measured with error, with application to AIDS studies," Computational Statistics, Springer, vol. 33(4), pages 1563-1587, December.
    34. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.

  37. Antonio F. Galvao & Gabriel Montes-Rojas & Jose Olmo, 2013. "A panel data test for poverty traps," Applied Economics, Taylor & Francis Journals, vol. 45(14), pages 1943-1952, May.

    Cited by:

    1. Golub, A. & Potashnikov, V., 2022. "Theoretical analysis of development traps: On the example of Russia," Journal of the New Economic Association, New Economic Association, vol. 54(2), pages 56-74.

  38. Galvao, Antonio F. & Montes-Rojas, Gabriel & Sosa-Escudero, Walter & Wang, Liang, 2013. "Tests for skewness and kurtosis in the one-way error component model," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 35-52.

    Cited by:

    1. Guido M. Kuersteiner & Ingmar R. Prucha & Ying Zeng, 2021. "Efficient Peer Effects Estimators with Group Effects," Papers 2105.04330, arXiv.org, revised Apr 2022.
    2. Dilawar Khan & Nihal Ahmed & Bahtiyar Mehmed & Ihtisham ul Haq, 2021. "Assessing the Impact of Policy Measures in Reducing the COVID-19 Pandemic: A Case Study of South Asia," Sustainability, MDPI, vol. 13(20), pages 1-12, October.
    3. Chirwa, Themba G. & Odhiambo, Nicholas M., 2017. "Public debt and economic growth nexus in the Euro area: A dynamic panel ARDL approach," Working Papers 23477, University of South Africa, Department of Economics.
    4. Dong, Kangyin & Dong, Xiucheng & Ren, Xiaohang, 2020. "Can expanding natural gas infrastructure mitigate CO2 emissions? Analysis of heterogeneous and mediation effects for China," Energy Economics, Elsevier, vol. 90(C).
    5. Javier Alejo & Antonio Galvao & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2015. "Tests for Normality in Linear Panel Data Models," CEDLAS, Working Papers 0178, CEDLAS, Universidad Nacional de La Plata.
    6. Seemab Ahmad & Dilawar Khan & Róbert Magda, 2022. "Assessing the Influence of Financial Inclusion on Environmental Degradation in the ASEAN Region through the Panel PMG-ARDL Approach," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    7. Elena Kopnova & Lilia Rodionova, 2017. "An Analysis of the Economic Determinants of Food Security in North Africa," HSE Working papers WP BRP 166/EC/2017, National Research University Higher School of Economics.
    8. Soberón, Alexandra & Stute, Winfried, 2017. "Assessing skewness, kurtosis and normality in linear mixed models," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 123-140.
    9. Marco Baudino, 2020. "Environmental Engel curves in Italy: A spatial econometric investigation," Papers in Regional Science, Wiley Blackwell, vol. 99(4), pages 999-1018, August.
    10. Jose Fernando Vilcarromero Arbulu & Jorge Luis Castilla Raimundo & Pedro Bernabe Venegas Rodriguez & Nivardo Alonzo Santillan Zapata & Jimmy Alberth Deza Quispe, 2021. "Financial Factors and Their Relative Importance Analysis in Peruvian Gold Mining Companies¡¯ Stock Price," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(2), pages 251-262, April.
    11. Itemgenova, Aigerim & Sikveland, Marius, 2020. "The determinants of the price-earnings ratio in the Norwegian aquaculture industry," Journal of Commodity Markets, Elsevier, vol. 17(C).

  39. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.

    Cited by:

    1. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    2. Paulo M.M. Rodrigues & Matei Demetrescu, 2022. "Cross-Sectional Error Dependence in Panel Quantile Regressions," Working Papers w202213, Banco de Portugal, Economics and Research Department.
    3. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Paolo Frumento & Matteo Bottai & Iv'an Fern'andez-Val, 2020. "Parametric Modeling of Quantile Regression Coefficient Functions with Longitudinal Data," Papers 2006.00160, arXiv.org.
    6. João Santos Silva, 2019. "Quantile regression: Basics and recent advances," London Stata Conference 2019 27, Stata Users Group.
    7. Jorge E. Galán, 2020. "The benefits are at the tail: uncovering the impact of macroprudential policy on growth-at-risk," Working Papers 2007, Banco de España.
    8. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    9. Roger Koenker, 2017. "Quantile regression 40 years on," CeMMAP working papers CWP36/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    11. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    12. Younes Ben Zaied & Béchir Ben Lahouel, 2021. "Does environmental CSR performance matter for corporate financial performance? Evidence from panel quantile regression," Economics Bulletin, AccessEcon, vol. 41(3), pages 938-951.
    13. Liang Chen & Juan Jose Dolado & Jesus Gonzalo & Haozi Pan, 2023. "Estimation of Characteristics-based Quantile Factor Models," Papers 2304.13206, arXiv.org.
    14. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    15. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    18. Sanjay B. Singh & Talal H. Alsabhan & Reem Alshagri, 2024. "Evaluating the Policy Implications of Renewable Portfolio Standards on Grid Reliability in the United States: An Instrumental Variable Quantile Analysis," Energies, MDPI, vol. 17(23), pages 1-22, December.
    19. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    20. Hatice Jenkins & Ezuldeen Alshareef & Amer Mohamad, 2023. "The impact of corruption on commercial banks' credit risk: Evidence from a panel quantile regression," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1364-1375, April.
    21. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    22. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Financial Stability Review, Banco de España, issue Autumn.
    23. Tu D. Q. Le & Dat T. Nguyen, 2020. "Capital Structure and Bank Profitability in Vietnam: A Quantile Regression Approach," JRFM, MDPI, vol. 13(8), pages 1-17, August.
    24. Eugénie Joltreau, 2022. "Extended Producer Responsibility, Packaging Waste Reduction and Eco-design," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(3), pages 527-578, November.
    25. Xiao Huang, 2023. "Composite Quantile Factor Model," Papers 2308.02450, arXiv.org, revised Nov 2024.
    26. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    27. Hang, Yin & Xue, Wenjun, 2020. "The asymmetric effects of monetary policy on the business cycle: Evidence from the panel smoothed quantile regression model," Economics Letters, Elsevier, vol. 195(C).
    28. Alexander Blasberg & Rüdiger Kiesel & Luca Taschini, 2022. "Carbon Default Swap - Disentangling the Exposure to Carbon Risk through CDS," CESifo Working Paper Series 10016, CESifo.
    29. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    30. Nadezhda V. Baryshnikova & Ngoc T. A. Pham, 2019. "Natural Disasters and Mental Health: A Quantile approach," School of Economics and Public Policy Working Papers 2019-03, University of Adelaide, School of Economics and Public Policy.
    31. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    32. Martina Pons, 2022. "The impact of air pollution on birthweight: evidence from grouped quantile regression," Empirical Economics, Springer, vol. 62(1), pages 279-296, January.
    33. Junlong Feng, 2019. "Regularized Quantile Regression with Interactive Fixed Effects," Papers 1911.00166, arXiv.org, revised Mar 2021.
    34. Galina Besstremyannaya & Sergei Golovan, 2023. "Measuring heterogeneity in hospital productivity: a quantile regression approach," Journal of Productivity Analysis, Springer, vol. 59(1), pages 15-43, February.
    35. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.
    36. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    37. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    38. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    39. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
    40. Samiul Haque, 2022. "US federal farm payments and farm size: Quantile estimation on panel data," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 139-154, February.
    41. Jiang, Hai & Zhang, Jinyi & Sun, Chen, 2020. "How does capital buffer affect bank risk-taking? New evidence from China using quantile regression," China Economic Review, Elsevier, vol. 60(C).
    42. Simons, Andrew M., 2016. "What is the optimal locus of control for social assistance programs? Evidence from the productive safety net programme in Ethiopia," ESSP working papers 86, International Food Policy Research Institute (IFPRI).
    43. Crescenzi, Riccardo & Giua, Mara, 2016. "The EU cohesion policy in context: does a bottom-up approach work in all regions?," LSE Research Online Documents on Economics 66946, London School of Economics and Political Science, LSE Library.
    44. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    45. Ivan Fernandez-Val & Martin Weidner, 2014. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 32/14, Institute for Fiscal Studies.
    46. Mr. Gaston Gelos & Lucyna Gornicka & Mr. Robin Koepke & Ms. Ratna Sahay & Ms. Silvia Sgherri, 2019. "Capital Flows at Risk: Taming the Ebbs and Flows," IMF Working Papers 2019/279, International Monetary Fund.
    47. Schorr, A. & Lips, M., 2018. "Influence of milk yield on profitability a quantile regression analysis," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277000, International Association of Agricultural Economists.
    48. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    49. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    50. Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jan 2023.
    51. Matthew Harding & Carlos Lamarche, 2017. "Penalized Quantile Regression with Semiparametric Correlated Effects: An Application with Heterogeneous Preferences," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 342-358, March.
    52. Bargain, Olivier B. & Etienne, Audrey & Melly, Blaise, 2018. "Public Sector Wage Gaps over the Long-Run: Evidence from Panel Administrative Data," IZA Discussion Papers 11924, Institute of Labor Economics (IZA).
    53. Pauline Givord & Milena Suarez, 2020. "Excellence for all ? Heterogeneity in high-schools' value-added," SciencePo Working papers Main hal-03389176, HAL.
    54. Matthew Harding & Carlos Lamarche, 2018. "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment," Papers 1808.03364, arXiv.org.
    55. Andres Sagner, 2020. "High Dimensional Quantile Factor Analysis," Working Papers Central Bank of Chile 886, Central Bank of Chile.
    56. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    57. Vu, Dung Anh & Van Nguyen, Thinh & Nhu, Quang Minh & Tran, Tuyen Quang, 2024. "Does increased digital transformation promote a firm's financial performance? New insights from the quantile approach," Finance Research Letters, Elsevier, vol. 64(C).
    58. Xiaowen Dai & Libin Jin, 2021. "Minimum distance quantile regression for spatial autoregressive panel data models with fixed effects," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-13, December.
    59. Xue, Wenjun & Zhang, Liwen, 2019. "Revisiting the asymmetric effects of bank credit on the business cycle: A panel quantile regression approach," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    60. Antonio F. Galvao & Gabriel Montes-Rojas, 2015. "On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study," Econometrics, MDPI, vol. 3(3), pages 1-13, September.
    61. Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2018. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP38/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    62. Galvao, Antonio F. & Wang, Liang, 2015. "Efficient minimum distance estimator for quantile regression fixed effects panel data," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 1-26.
    63. Xiao, Zhijie & Xu, Lan, 2019. "What do mean impacts miss? Distributional effects of corporate diversification," Journal of Econometrics, Elsevier, vol. 213(1), pages 92-120.
    64. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
    65. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    66. Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.
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    74. Jung-In Yeon & Jeong-Dong Lee & Chulwoo Baek, 2021. "A tale of two technological capabilities: economic growth revisited from a technological capability transition perspective," The Journal of Technology Transfer, Springer, vol. 46(3), pages 574-605, June.
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    87. Paul Contoyannis & Jinhu Li, 2017. "The dynamics of adolescent depression: an instrumental variable quantile regression with fixed effects approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 907-922, June.
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    4. Mensi, Walid & Hammoudeh, Shawkat & Tiwari, Aviral Kumar & Al-Yahyaee, Khamis Hamed, 2020. "Impact of Islamic banking development and major macroeconomic variables on economic growth for Islamic countries: Evidence from panel smooth transition models," Economic Systems, Elsevier, vol. 44(1).
    5. Galina Besstremyannaya, 2014. "The adverse effects of value-based purchasing in health care: dynamic quantile regression with endogeneity," Discussion Papers 14-006, Stanford Institute for Economic Policy Research.
    6. Heather D Gibson & Georgia Pavlou, 2017. "Exporting and performance:evidence from Greek firms," Economic Bulletin, Bank of Greece, issue 45, pages 7-30, July.
    7. Dong-Hyeon Kim & Joyce Hsieh & Shu-Chin Lin, 2021. "Financial liberalization, political institutions, and income inequality," Empirical Economics, Springer, vol. 60(3), pages 1245-1281, March.
    8. Khurshid Djalilov & Christopher A. Hartwell, 2023. "The spirit is willing, but the institutions are weak: disclosure of corporate social responsibility and the financial sector in transition," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 385-427, June.
    9. Marwa Elsherif, 2024. "Nexus between Blue Economy, Renewable Energy and Environmental Sustainability in the MENA Region: Evidence from Panel Threshold Regression," International Journal of Energy Economics and Policy, Econjournals, vol. 14(4), pages 169-185, July.
    10. Marco Letta & Pierluigi Montalbano & Richard S.J. Tol, 2017. "Temperature shocks, growth and poverty thresholds: evidence from rural Tanzania," Working Paper Series 2117, Department of Economics, University of Sussex Business School.
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    12. Nguyen Van Bon, 2021. "Does FDI inflow crowd in private investment? Empirical evidence for the Southeast region of Vietnam from the panel quantile regression approach," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ECONOMICS AND BUSINESS ADMINISTRATION, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 11(2), pages 127-136.
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    43. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2014. "Revisiting Growth Empirics Based on IV Panel Quantile Regression," Working papers 2014rwp-72, Yonsei University, Yonsei Economics Research Institute.
    44. Jiahong Guo & Zhongqi Yu & Zihao Ma & Duanyang Xu & Shixiong Cao, 2022. "What factors have driven urbanization in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6508-6526, May.
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    60. Méndez Ortega, Carles, & Teruel, Mercedes, 2018. "To acquire or not to acquire: Mergers and Acquisitions in the Software Industry," Working Papers 2072/307043, Universitat Rovira i Virgili, Department of Economics.
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  41. Antonio F. Galvao Jr. & Gabriel Montes‐Rojas & Jose Olmo, 2011. "Threshold quantile autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 253-267, May.

    Cited by:

    1. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    2. Tang, Yanlin & Song, Xinyuan & Zhu, Zhongyi, 2015. "Threshold effect test in censored quantile regression," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 149-156.
    3. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    4. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
    5. Camille Aït-Youcef, 2019. "How index investment impacts commodities : A story about the financialization of agricultural commodities," Post-Print hal-03484371, HAL.
    6. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.
    7. Tae-Hwan Kim & Dong Jin Lee & Paul Mizen, 2020. "Impulse Response Analysis in Conditional Quantile Models and an Application to Monetary Policy," Working papers 2020rwp-164, Yonsei University, Yonsei Economics Research Institute.
    8. Galvao, Antonio F. & Montes-Rojas, Gabriel & Olmo, Jose, 2009. "Quantile Threshold Effects in the Dynamics of the Dollar/Pound Exchange Rate," The Journal of Economic Asymmetries, Elsevier, vol. 6(2), pages 69-82.
    9. Junho Lee & Ying Sun & Huixia Judy Wang, 2021. "Spatial cluster detection with threshold quantile regression," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    10. Christis Katsouris, 2023. "Estimation and Inference in Threshold Predictive Regression Models with Locally Explosive Regressors," Papers 2305.00860, arXiv.org, revised May 2023.
    11. Olivier Damette & Beum-Jo Park, 2015. "Tobin Tax and Volatility: A Threshold Quantile Autoregressive Regression Framework," Review of International Economics, Wiley Blackwell, vol. 23(5), pages 996-1022, November.
    12. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
    13. Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
    14. Chavas, Jean-Paul & Grainger, Corbett & Hudson, Nicholas, 2016. "How should economists model climate? Tipping points and nonlinear dynamics of carbon dioxide concentrations," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 56-65.
    15. Neil Foster-McGregor & Anders Isaksson & Florian Kaulich, 2013. "Importing, Productivity and Absorptive Capacity in Sub-Saharan African Manufacturing Firms," wiiw Working Papers 105, The Vienna Institute for International Economic Studies, wiiw.
    16. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    17. Montes-Rojas, Gabriel, 2017. "Reduced form vector directional quantiles," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 20-30.
    18. Martins, Luis F., 2021. "The US debt–growth nexus along the business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    19. Jean-Paul Chavas & Salvatore Falco, 2017. "Resilience, Weather and Dynamic Adjustments in Agroecosystems: The Case of Wheat Yield in England," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(2), pages 297-320, June.

  42. Heitor Almeida & Murillo Campello & Antonio F. Galvao, 2010. "Measurement Errors in Investment Equations," The Review of Financial Studies, Society for Financial Studies, vol. 23(9), pages 3279-3328.
    See citations under working paper version above.
  43. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.

    Cited by:

    1. Najia Saqib & Ivan A. Duran & Ilhan Ozturk, 2023. "Unraveling the Interrelationship of Digitalization, Renewable Energy, and Ecological Footprints within the EKC Framework: Empirical Insights from the United States," Sustainability, MDPI, vol. 15(13), pages 1-21, July.
    2. Jin Seo Cho & Tae-Hwan Kim & Yongcheol Shin, 2014. "Quantile Cointegration in the Autoregressive Distributed-Lag Modelling Framework," Working papers 2014rwp-69, Yonsei University, Yonsei Economics Research Institute.
    3. Francis Leni Anguyo & Rangan Gupta & Kevin Kotzé, 2017. "Inflation Dynamics in Uganda: A Quantile Regression Approach," Working Papers 201772, University of Pretoria, Department of Economics.
    4. Ben-Salha, Ousama & Mokni, Khaled, 2022. "Detrended cross-correlation analysis in quantiles between oil price and the US stock market," Energy, Elsevier, vol. 242(C).
    5. Awasthi, Kritika & Ahmad, Wasim & Rahman, Abdul & Phani, B.V., 2020. "When US sneezes, clichés spread: How do the commodity index funds react then?," Resources Policy, Elsevier, vol. 69(C).
    6. Hosseinkouchack, Mehdi & Wolters, Maik H., 2012. "Do large recessions reduce output permanently?," Economics Working Papers 2012-16, Christian-Albrechts-University of Kiel, Department of Economics.
    7. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    8. Fossati, Sebastian, 2011. "Covariate Unit Root Tests with Good Size and Power," Working Papers 2011-4, University of Alberta, Department of Economics.
    9. Gangopadhyay, Partha & Das, Narasingha & Alam, G.M. Monirul & Khan, Uzma & Haseeb, Mohammad & Hossain, Md. Emran, 2023. "Revisiting the carbon pollution-inhibiting policies in the USA using the quantile ARDL methodology: What roles can clean energy and globalization play?," Renewable Energy, Elsevier, vol. 204(C), pages 710-721.
    10. Fossati, Sebastian, 2011. "Unit Root Testing with Stationary Covariates and a Structural Break in the Trend Function," Working Papers 2011-10, University of Alberta, Department of Economics.
    11. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    12. Rehman, Mobeen Ur & Sensoy, Ahmet & Eraslan, Veysel & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Sensitivity of US equity returns to economic policy uncertainty and investor sentiments," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    13. Mohsen Bahmani-Oskooee & Tsangyao Chang & Tsung-Hsien Chen & Han-Wen Tzeng, 2017. "Revisiting purchasing power parity in Eastern European countries: quantile unit root tests," Empirical Economics, Springer, vol. 52(2), pages 463-483, March.
    14. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2022. "The COVID-19 black swan crisis: Reaction and recovery of various financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    15. Muhammad Shafiullah & Sajid M. Chaudhry & Muhammad Shahbaz & Juan C. Reboredo, 2021. "Quantile causality and dependence between crude oil and precious metal prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6264-6280, October.
    16. Tillmann, Peter & Wolters, Maik Hendrik, 2012. "The changing dynamics of US inflation persistence: A quantile regression approach," IMFS Working Paper Series 60, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    17. Akanksha Jalan & Roman Matkovskyy & Valerio Potì, 2022. "Shall the winning last? A study of recent bubbles and persistence," Post-Print hal-03603161, HAL.
    18. Seyi Saint Akadiri & Tomiwa Sunday Adebayo & Obioma Chinenyenwa Asuzu & Ijeoma Christina Onuogu & Izuchukwu Oji-Okoro, 2023. "Testing the role of economic complexity on the ecological footprint in China: a nonparametric causality-in-quantiles approach," Energy & Environment, , vol. 34(7), pages 2290-2316, November.
    19. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    20. Arshian Sharif & Subhan Ullah & Muhammad Shahbaz & Mantu Kumar Mahalik, 2021. "Sustainable tourism development and globalization: Recent insights from the United States," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(5), pages 957-973, September.
    21. Feng, Hao, 2023. "Testing for explosive bubbles in the presence of non-Gaussian conditions," Economics Letters, Elsevier, vol. 233(C).
    22. Goodness C. Aye & Tsangyao Chang & Wen-Yi Chen & Rangan Gupta & Mark Wohar, 2016. "Testing the Efficiency of the Art Market using Quantile-Based Unit Root Tests with Sharp and Smooth Breaks," Working Papers 201625, University of Pretoria, Department of Economics.
    23. Xiao, Jihong & Wang, Yudong & Wen, Danyan, 2023. "The predictive effect of risk aversion on oil returns under different market conditions," Energy Economics, Elsevier, vol. 126(C).
    24. Tae-Hwan Kim & Dong Jin Lee & Paul Mizen, 2020. "Impulse Response Analysis in Conditional Quantile Models and an Application to Monetary Policy," Working papers 2020rwp-164, Yonsei University, Yonsei Economics Research Institute.
    25. Lee, Chien-Chiang & Lee, Cheng-Feng & Lee, Chi-Chuan, 2014. "Asymmetric dynamics in REIT prices: Further evidence based on quantile regression analysis," Economic Modelling, Elsevier, vol. 42(C), pages 29-37.
    26. Lee, Chi-Chuan & Li, Yong-Yi, 2024. "Does environmental policy matter for renewable energy production and economic activity? Evidence from Granger causality in quantiles," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 225-237.
    27. Lee, Cheng-Feng & Hu, Te-Chung & Li, Ping-Cheng & Tsong, Ching-Chuan, 2013. "Asymmetric behavior of unemployment rates: Evidence from the quantile covariate unit root test," Japan and the World Economy, Elsevier, vol. 28(C), pages 72-84.
    28. Mighri, Zouheir & Ragoubi, Hanen & Sarwar, Suleman & Wang, Yihan, 2022. "Quantile Granger causality between US stock market indices and precious metal prices," Resources Policy, Elsevier, vol. 76(C).
    29. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2020. "Are unemployment rates in OECD countries stationary? Evidence from univariate and panel unit root tests," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    30. Lee, Chi-Chuan & Yu, Chin-Hsien & Zhang, Jian, 2023. "Heterogeneous dependence among cryptocurrency, green bonds, and sustainable equity: New insights from Granger-causality in quantiles analysis," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 99-109.
    31. Debdatta Pal & Subrata K. Mitra, 2017. "Diesel and soybean price relationship in the USA: evidence from a quantile autoregressive distributed lag model," Empirical Economics, Springer, vol. 52(4), pages 1609-1626, June.
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    Cited by:

    1. Lee, Chien-Chiang & Lee, Jun-De, 2009. "Income and CO2 emissions: Evidence from panel unit root and cointegration tests," Energy Policy, Elsevier, vol. 37(2), pages 413-423, February.
    2. Alan King & Carlyn Ramlogan-Dobson, 2016. "Is there club convergence in Latin America?," Empirical Economics, Springer, vol. 51(3), pages 1011-1031, November.
    3. Andrea Bonilla, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region's Integration Projects," Working Papers halshs-01069353, HAL.
    4. De Siano, Rita & D'Uva, Marcella, 2009. "Regional convergence in Italy: time series approaches," MPRA Paper 20397, University Library of Munich, Germany.
    5. Atanu Ghoshray & Faiza Khan, 2015. "New empirical evidence on income convergence," Empirical Economics, Springer, vol. 49(1), pages 343-361, August.
    6. Christos Kollias & Petros Messis, 2020. "Are future enlargement candidate countries converging with the EU?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(3), pages 453-473, August.
    7. Astrid Ayala & Juncal Cuñado & Luis Alb�riko Gil-Alana, 2012. "Real convergence in Latin America: a fractionally integrated approach," Applied Financial Economics, Taylor & Francis Journals, vol. 22(20), pages 1713-1717, October.
    8. Carlos Mendez & Felipe Santos-Marquez, 2022. "Economic and Social Disparities across Subnational Regions of South America: A Spatial Convergence Approach," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 64(4), pages 582-605, December.
    9. Martin Victor & Vazquez Guillermo, 2015. "Club convergence in Latin America," The B.E. Journal of Macroeconomics, De Gruyter, vol. 15(2), pages 791-820, July.
    10. Hakan SARIBAŞ, 2016. "Ana Akım Büyüme Modeli ve Yakınsama Hipotezlerinin Analizi: Panel Veri Yaklaşımı," Sosyoekonomi Journal, Sosyoekonomi Society, issue 24(30).
    11. Andrea Bonilla Bolanos, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region’s Integration Projects," Working Papers 1424, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    12. Burcu Ozcan, 2014. "Does Income Converge among EU Member Countries following the Post-War Period? Evidence from the PANKPSS Test," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-38, October.
    13. King, Alan & Ramlogan-Dobson, Carlyn, 2015. "Is Africa Actually Developing?," World Development, Elsevier, vol. 66(C), pages 598-613.
    14. Andrea Bonilla BOLAÑOS, 2017. "Are South American Countries Really Converging?: The Influence of the Region's Integration Projects," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 130-149, September.
    15. Zhao, Jun & Serieux, John, 2020. "Economic globalization and regional income convergence: Evidence from Latin America and the Caribbean," World Development Perspectives, Elsevier, vol. 17(C).

Chapters

  1. Anil K. Bera & Antonio F. Galvao Jr. & Gabriel V. Montes-Rojas & Sung Y. Park, 2014. "Which Quantile is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression," World Scientific Book Chapters, in: Kaddour Hadri & William Mikhail (ed.), Econometric Methods and Their Applications in Finance, Macro and Related Fields, chapter 7, pages 167-199, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. Friedson, Andrew I. & Kniesner, Thomas J., 2011. "Losers and Losers: Some Demographics of Medical Malpractice Tort Reforms," IZA Discussion Papers 5921, Institute of Labor Economics (IZA).

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