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Luiz Renato Regis de Oliveira Lima

Citations

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

Working papers

  1. Erik Figueiredo & Luiz Renato Lima & Gianluca Orefice, 2016. "Third Country Effect of Migration: the Trade-Migration Nexus Revisited," Working Papers 2016-22, CEPII research center.

    Cited by:

    1. Bulawayo, Maio & Mudenda, Dale & Ndulo, Manenga & Simwanza, Charles, 2020. "Does Immigration Stimulate Non-Traditional Exports? Evidence from Zambia," African Journal of Economic Review, African Journal of Economic Review, vol. 8(3), November.

  2. Gianluca Orefice & Luiz Lima & Erik Figueiredo, 2014. "Migration and Regional Trade Agreement: a (new) Gravity Estimation," Working Papers 2014-13, CEPII research center.

    Cited by:

    1. Beverelli, Cosimo & Orefice, Gianluca, 2019. "Migration deflection: The role of Preferential Trade Agreements," Regional Science and Urban Economics, Elsevier, vol. 79(C).
    2. Maria Santana-Gallego & Jordi Paniagua, 2022. "Tourism and migration: Identifying the channels with gravity models," Tourism Economics, , vol. 28(2), pages 394-417, March.
    3. Figueiredo, Erik & Lima, Luiz Renato & Loures, Alexandre & Oliveira, Celina, 2014. "Uma Análise para o Efeito-Fronteira no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(4), October.
    4. Erik Figueiredo & Luiz Renato Lima, 2020. "Do economic integration agreements affect trade predictability? A group effect analysis," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 637-664, May.
    5. Cosimo Beverelli, 2022. "Pull factors for migration: The impact of migrant integration policies," Economics and Politics, Wiley Blackwell, vol. 34(1), pages 171-191, March.

  3. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    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. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    4. Erik Figueiredo & Luiz Renato Lima & Gianluca Orefice, 2016. "Migration and Regional Trade Agreements: A (New) Gravity Estimation," Review of International Economics, Wiley Blackwell, vol. 24(1), pages 99-125, February.
    5. Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
    6. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    7. Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.
    8. Todd Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Working Papers 2307, University of Strathclyde Business School, Department of Economics.
    9. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    10. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
    11. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
    12. Wagner Piazza Gaglianone & Waldyr Dutra Areosa, 2016. "Financial Conditions Indicators for Brazil," Working Papers Series 435, Central Bank of Brazil, Research Department.
    13. Christina Anderl & Guglielmo Maria Caporale, 2023. "Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts," Manchester School, University of Manchester, vol. 91(3), pages 171-232, June.
    14. 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.
    15. Korobilis, Dimitris, 2015. "Quantile forecasts of inflation under model uncertainty," MPRA Paper 64341, University Library of Munich, Germany.
    16. Fernando Eguren-Martin & Andrej Sokol, 2022. "Attention to the Tail(s): Global Financial Conditions and Exchange Rate Risks," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(3), pages 487-519, September.
    17. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    18. Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
    19. Luiz Renato Lima & Lucas Lúcio Godeiro, 2023. "Equity‐premium prediction: Attention is all you need," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 105-122, January.
    20. Ramsey, A., 2018. "Conditional Distributions of Crop Yields: A Bayesian Approach for Characterizing Technological Change," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277253, International Association of Agricultural Economists.
    21. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    22. Iddrisu, Abdul-Aziz & Alagidede, Imhotep Paul, 2020. "Monetary policy and food inflation in South Africa: A quantile regression analysis," Food Policy, Elsevier, vol. 91(C).
    23. Laurent Ferrara & Joseph Yapi, 2020. "Measuring exchange rate risks during periods of uncertainty," CAMA Working Papers 2020-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
    25. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    26. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    27. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2024. "A Quantile Nelson-Siegel model," Papers 2401.09874, arXiv.org.
    28. Dimitris Korobilis & Maximilian Schröder, 2023. "Probabilistic Quantile Factor Analysis," Working Papers No 05/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    29. González-Ordiano, Jorge Ángel & Mühlpfordt, Tillmann & Braun, Eric & Liu, Jianlei & Çakmak, Hüseyin & Kühnapfel, Uwe & Düpmeier, Clemens & Waczowicz, Simon & Faulwasser, Timm & Mikut, Ralf & Hagenmeye, 2021. "Probabilistic forecasts of the distribution grid state using data-driven forecasts and probabilistic power flow," Applied Energy, Elsevier, vol. 302(C).
    30. James Mitchell & Saeed Zaman, 2023. "The Distributional Predictive Content of Measures of Inflation Expectations," Working Papers 23-31, Federal Reserve Bank of Cleveland.

  4. Wagner P. Gaglianone & Luiz Renato Lima & Oliver Linton, 2008. "Evaluating Value-at-Risk Models via Quantile Regressions," Working Papers Series 161, Central Bank of Brazil, Research Department.

    Cited by:

    1. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    2. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    3. Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
    4. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    5. Zongwu Cai & Haiqiang Chen & Xiaosai Liao, 2020. "A New Robust Inference for Predictive Quantile Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202002, University of Kansas, Department of Economics, revised Feb 2020.
    6. Steven Kou & Xianhua Peng, 2014. "On the Measurement of Economic Tail Risk," Papers 1401.4787, arXiv.org, revised Aug 2015.
    7. So Yeon Chun & Alexander Shapiro & Stan Uryasev, 2012. "Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics," Operations Research, INFORMS, vol. 60(4), pages 739-756, August.
    8. Wilson Calmon & Eduardo Ferioli & Davi Lettieri & Johann Soares & Adrian Pizzinga, 2021. "An Extensive Comparison of Some Well‐Established Value at Risk Methods," International Statistical Review, International Statistical Institute, vol. 89(1), pages 148-166, April.
    9. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2015. "Systemic risk and asymmetric responses in the financial industry," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 471-485.
    10. Jenq-Tzong Shiau & Jia-Wei Lin, 2016. "Clustering Quantile Regression-Based Drought Trends in Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1053-1069, February.
    11. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    12. Jenq-Tzong Shiau & Ting-Ju Chen, 2015. "Quantile Regression-Based Probabilistic Estimation Scheme for Daily and Annual Suspended Sediment Loads," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2805-2818, June.
    13. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    14. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    15. Tjeerd de Vries, 2021. "A Tale of Two Tails: A Model-free Approach to Estimating Disaster Risk Premia and Testing Asset Pricing Models," Papers 2105.08208, arXiv.org, revised Oct 2023.
    16. Sebastian Bayer & Timo Dimitriadis, 2018. "Regression Based Expected Shortfall Backtesting," Papers 1801.04112, arXiv.org, revised Sep 2019.
    17. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    18. Emese Lazar & Ning Zhang, 2017. "Model Risk of Expected Shortfall," ICMA Centre Discussion Papers in Finance icma-dp2017-10, Henley Business School, University of Reading.
    19. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    20. Zhu, Xuening & Wang, Weining & Wang, Hansheng & Härdle, Wolfgang Karl, 2019. "Network quantile autoregression," Journal of Econometrics, Elsevier, vol. 212(1), pages 345-358.
    21. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    22. Bonga-Bonga, Lumengo & Manguzvane, Mathias Mandla, 2018. "Assessing the extent of contagion of sovereign credit risk among BRICS countries," MPRA Paper 89200, University Library of Munich, Germany.
    23. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    24. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    25. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
    26. Wang, Jying-Nan & Du, Jiangze & Hsu, Yuan-Teng, 2018. "Measuring long-term tail risk: Evaluating the performance of the square-root-of-time rule," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 120-138.
    27. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    28. Ophélie Couperier & Jérémy Leymarie, 2020. "Backtesting Expected Shortfall via Multi-Quantile Regression," Working Papers halshs-01909375, HAL.
    29. Wagner Piazza Gaglianone & Luiz Renato Lima, 2012. "Constructing Density Forecasts from Quantile Regressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1589-1607, December.
    30. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    31. David Kohns & Tibor Szendrei, 2020. "Horseshoe Prior Bayesian Quantile Regression," Papers 2006.07655, arXiv.org, revised Mar 2021.
    32. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    33. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
    34. Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2012. "The Risk Map: A New Tool for Validating Risk Models," Working Papers halshs-00746273, HAL.
    35. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    36. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    37. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    38. Bruno Ferreira Frascaroli & Wellington Charles Lacerda Nobrega, 2019. "Inflation Targeting and Inflation Risk in Latin America," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(11), pages 2389-2408, September.
    39. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.
    40. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    41. Karmakar, Madhusudan & Paul, Samit, 2019. "Intraday portfolio risk management using VaR and CVaR:A CGARCH-EVT-Copula approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 699-709.
    42. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying – the case of multivariate GARCH models," Economics Working Paper Series 1517, University of St. Gallen, School of Economics and Political Science.
    43. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
    44. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    45. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jun 2023.
    46. 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.
    47. Taylor, James W., 2022. "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, vol. 140(C).
    48. Hayette Gatfaoui, 2017. "Equity market information and credit risk signaling: A quantile cointegrating regression approach," Post-Print hal-01745285, HAL.
    49. Pradhan, Ashis Kumar & Tiwari, Aviral Kumar, 2021. "Estimating the market risk of clean energy technologies companies using the expected shortfall approach," Renewable Energy, Elsevier, vol. 177(C), pages 95-100.
    50. Daniel Mariño Ustacara & Luis Fernando Melo Velandia, 2016. "Regresión Cuantílica Dinámica para la Medición del Valor en Riesgo: una Aplicación a Datos Colombianos," Borradores de Economia 939, Banco de la Republica de Colombia.
    51. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    52. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
    53. Aramonte, Sirio & Giudice Rodriguez, Marius del & Wu, Jason, 2013. "Dynamic factor Value-at-Risk for large heteroskedastic portfolios," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4299-4309.
    54. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    55. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    56. Katherine Uylangco & Siqiwen Li, 2016. "An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 699-718, November.
    57. Chao Wang & Qian Chen & Richard Gerlach, 2017. "Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution," Papers 1707.03715, arXiv.org.
    58. Iqbal, Javed, 2017. "Does gold hedge stock market, inflation and exchange rate risks? An econometric investigation," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 1-17.
    59. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    60. Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
    61. Filippo Curti & Marco Migueis, 2016. "Predicting Operational Loss Exposure Using Past Losses," Finance and Economics Discussion Series 2016-2, Board of Governors of the Federal Reserve System (U.S.).
    62. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    63. Argyropoulos, Christos & Panopoulou, Ekaterini, 2019. "Backtesting VaR and ES under the magnifying glass," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 22-37.
    64. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
    65. Storti, Giuseppe & Wang, Chao, 2022. "A multivariate semi-parametric portfolio risk optimization and forecasting framework," MPRA Paper 115266, University Library of Munich, Germany.
    66. Chao Wang & Richard Gerlach & Qian Chen, 2018. "A Semi-parametric Realized Joint Value-at-Risk and Expected Shortfall Regression Framework," Papers 1807.02422, arXiv.org, revised Jan 2021.
    67. Lúcio Godeiro, Lucas, 2012. "Estimando o VaR (Value-at-Risk) de carteiras via modelos da família GARCH e via Simulação de Monte Carlo [Estimating the VaR (Value-at-Risk) of portfolios via GARCH family models and via Monte Carl," MPRA Paper 45146, University Library of Munich, Germany.
    68. Gerlach, Richard & Abeywardana, Sachin, 2016. "Variational Bayes for assessment of dynamic quantile forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1385-1402.
    69. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    70. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    71. Timo Dimitriadis & Sebastian Bayer, 2017. "A Joint Quantile and Expected Shortfall Regression Framework," Papers 1704.02213, arXiv.org, revised Aug 2017.
    72. Armstrong, Christopher S. & Blouin, Jennifer L. & Jagolinzer, Alan D. & Larcker, David F., 2015. "Corporate governance, incentives, and tax avoidance," Journal of Accounting and Economics, Elsevier, vol. 60(1), pages 1-17.
    73. Chan Jennifer So Kuen & Nitithumbundit Thanakorn & Peiris Shelton & Ng Kok-Haur, 2019. "Efficient estimation of financial risk by regressing the quantiles of parametric distributions: An application to CARR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-22, April.
    74. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    75. Rubia, Antonio & Sanchis-Marco, Lidia, 2013. "On downside risk predictability through liquidity and trading activity: A dynamic quantile approach," International Journal of Forecasting, Elsevier, vol. 29(1), pages 202-219.
    76. Giessing, Alexander & He, Xuming, 2019. "On the predictive risk in misspecified quantile regression," Journal of Econometrics, Elsevier, vol. 213(1), pages 235-260.
    77. Richard Gerlach & Chao Wang, 2016. "Bayesian Semi-parametric Realized-CARE Models for Tail Risk Forecasting Incorporating Realized Measures," Papers 1612.08488, arXiv.org.
    78. Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.
    79. Richard Gerlach & Chao Wang, 2018. "Semi-parametric Dynamic Asymmetric Laplace Models for Tail Risk Forecasting, Incorporating Realized Measures," Papers 1805.08653, arXiv.org.
    80. Cai, Zongwu & Chen, Haiqiang & Liao, Xiaosai, 2023. "A new robust inference for predictive quantile regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 227-250.

  5. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2008. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 668, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Issler, João Victor & Soares, Ana Flávia, 2019. "Central Bank credibility and inflation expectations: a microfounded forecasting approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 812, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    3. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2009. "Do Composite Procedures Really Improve the Accuracy of Outlook Forecasts?," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53052, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    4. Atak, Alev & Linton, Oliver B. & Xiao, Zhijie, 2010. "A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom," MPRA Paper 22079, University Library of Munich, Germany.
    5. Emerson Fernandes Marçal & Eli Hadad Junior, 2016. "Is It Possible to Beat the Random Walk Model in Exchange Rate Forecasting? More Evidence for Brazilian Case," Brazilian Review of Finance, Brazilian Society of Finance, vol. 14(1), pages 65-88.
    6. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    7. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    8. Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
    9. Conrad, Christian, 2017. "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168200, Verein für Socialpolitik / German Economic Association.
    10. Marcelo C. Medeiros & Eduardo F. Mendes, 2012. "Estimating High-Dimensional Time Series Models," CREATES Research Papers 2012-37, Department of Economics and Business Economics, Aarhus University.
    11. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
    12. Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011. "Forecast combination through dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237, April.
    13. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    14. Constantin Rudolf Salomo Bürgi, 2023. "How to deal with missing observations in surveys of professional forecasters," Journal of Applied Economics, Taylor & Francis Journals, vol. 26(1), pages 2185975-218, December.
    15. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    16. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
    17. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
    18. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-19, August.
    19. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    20. Mont'Alverne Duarte, Angelo & Gaglianone, Wagner Piazza & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor, 2021. "Commodity prices and global economic activity: A derived-demand approach," Energy Economics, Elsevier, vol. 96(C).
    21. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.
    22. Francisco J. Díaz-Borrego & María del Mar Miras-Rodríguez & Bernabé Escobar-Pérez, 2019. "Looking for Accurate Forecasting of Copper TC/RC Benchmark Levels," Complexity, Hindawi, vol. 2019, pages 1-16, April.
    23. Medeiros, Marcelo C. & Mendes, Eduardo F., 2016. "ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 191(1), pages 255-271.
    24. Christian Brownlees & Vladislav Morozov, 2022. "Unit Averaging for Heterogeneous Panels," Papers 2210.14205, arXiv.org, revised Nov 2022.
    25. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    26. Marcus Alexander & Matthew Harding & Carlos Lamarche, 2011. "Quantifying the impact of economic crises on infant mortality in advanced economies," Applied Economics, Taylor & Francis Journals, vol. 43(24), pages 3313-3323.

  6. Xiao, Zhijie & Lima, Luiz Renato Regis de Oliveira, 2006. "Testing covariance stationarity," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 632, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    2. Aviral Kumar Tiwari & Aruna Kumar Dash & Subhendu Dutta, 2015. "Testing the mean reversion in prices of agricultural commodities in India," Economics Bulletin, AccessEcon, vol. 35(3), pages 1928-1940.
    3. George Kapetanios, 2007. "Testing for Strict Stationarity," Working Papers 602, Queen Mary University of London, School of Economics and Finance.
    4. Kapetanios, George, 2009. "Testing for strict stationarity in financial variables," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2346-2362, December.
    5. James E Payne & Junsoo Lee, 2024. "Global perspective on the permanent or transitory nature of shocks to tourist arrivals: Evidence from new unit root tests with structural breaks and factors," Tourism Economics, , vol. 30(1), pages 67-103, February.

  7. Luiz Renato Lima & Breno Pinheiro Néri, 2006. "Comparing Value-at-Risk Methodologies," Computing in Economics and Finance 2006 1, Society for Computational Economics.

    Cited by:

    1. Allen, D.E. & McAleer, M.J. & Amram, R., 2011. "Volatility Spillovers from the Chinese Stock Market to Economic Neighbours," Econometric Institute Research Papers EI 2011-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. David E. Allen & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2012. "Volatility Spillovers from the US to Australia and China across the GFC," Documentos de Trabajo del ICAE 2012-30, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    4. Aymen BEN REJEB & Ousama BEN SALHA & Jaleleddine BEN REJEB, 2012. "Value-at-Risk Analysis for the Tunisian Currency Market: A Comparative Study," International Journal of Economics and Financial Issues, Econjournals, vol. 2(2), pages 110-125.
    5. A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.
    6. Xiao, Zhijie & Lima, Luiz Renato Regis de Oliveira, 2006. "Testing covariance stationarity," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 632, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    7. David E. Allen & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2014. "Volatility Spillovers from Australia's Major Trading Partners across the GFC," Tinbergen Institute Discussion Papers 14-106/III, Tinbergen Institute.
    8. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra & Gaglianone, Wagner Piazza, 2006. "Debt ceiling and fiscal sustainability in Brazil: a quantile autoregression approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 631, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

  8. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra & Gaglianone, Wagner Piazza, 2006. "Debt ceiling and fiscal sustainability in Brazil: a quantile autoregression approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 631, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    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. Mário Jorge Mendonça & Cláudio H. dos Santos, 2008. "Revisitando a Função de Reação Fiscal no Brasil Pós-Real: Uma Abordagem de Mudanças de Regime," Discussion Papers 1337, Instituto de Pesquisa Econômica Aplicada - IPEA.
    3. María del Carmen Ramos-Herrera & Simón Sosvilla-Rivero, 2020. "Fiscal Sustainability in Aging Societies: Evidence from Euro Area Countries," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    4. Tilak Abeysinghe & Ananda Jayawickrama, 2013. "A segmented trend model to assess fiscal sustainability: The US experience 1929–2009," Empirical Economics, Springer, vol. 44(3), pages 1129-1141, June.
    5. Mário Jorge Cardoso de Mendonça & Cláudio Hamilton Matos dos Santos, 2008. "Revisitando a Função de Reação Fiscal no Brasil Pós-Real: Uma Abordagem de Mudanças de Regime," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807171729460, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    6. Boengiu, Tudor & Morar Triandafil, Cristina & Morar Triandafil, Adrian, 2011. "Debt Ceiling and External Debt Sustainability in Romania: A Quantile Autoregression Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 15-29, December.
    7. Abderrahim Chibi & Sidi Mohamed Chekouri & Mohamed Benbouziane, 2019. "The dynamics of fiscal policy in Algeria: sustainability and structural change," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-27, December.
    8. 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.
    9. Chang, Chun-Ping & Lee, Chien-Chiang & Hsieh, Meng-Chi, 2015. "Does globalization promote real output? Evidence from quantile cointegration regression," Economic Modelling, Elsevier, vol. 44(C), pages 25-36.
    10. Johann Bröthaler & Michael Getzner & Gottfried Haber, 2015. "Sustainability of local government debt: a case study of Austrian municipalities," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 521-546, August.
    11. Abel Cadenillas & Ricardo Huamán-Aguilar, 2016. "Explicit formula for the optimal government debt ceiling," Annals of Operations Research, Springer, vol. 247(2), pages 415-449, December.
    12. 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.
    13. 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.
    14. Ricardo Ramalhete Moreira, 2017. "Pro-cyclical fiscal policy in Brazil: long- and short-term relationships using cointegration and error correction model (2005-2015)," International Journal of Economic Policy in Emerging Economies, Inderscience Enterprises Ltd, vol. 10(2), pages 171-184.
    15. Lee, Chien-Chiang & Zeng, Jhih-Hong, 2011. "Revisiting the relationship between spot and futures oil prices: Evidence from quantile cointegrating regression," Energy Economics, Elsevier, vol. 33(5), pages 924-935, September.
    16. Lin, Wen-Yuan & Tsai, I-Chun, 2019. "Black swan events in China's stock markets: Intraday price behaviors on days of volatility," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 395-411.
    17. 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.
    18. Sidi Mohammed Chekouri & Abderrahim Chibi & Mohamed Benbouziane, 2024. "Public debt dynamics and fiscal sustainability in selected North African countries: new evidence from recurrent explosive behavior tests and quantile unit root analysis," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-27, April.

  9. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra, 2005. "The asymmetric behavior of the U.S. public debt," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 593, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    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. Aloisio Araujo & Mário R. Páscoa & Juan Pablo Torres-Martínez, 2006. "Bubbles, Collateral and Monetary Equilibrium," Levine's Working Paper Archive 122247000000001055, David K. Levine.
    3. Bonomo, Marco Antônio Cesar & Terra, Maria Cristina T., 2005. "Special interests and political business cycles," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 597, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    4. Monteiro, Paulo Klinger, 2009. "First-price auction symmetric equilibria with a general distribution," Games and Economic Behavior, Elsevier, vol. 65(1), pages 256-269, January.
    5. Boengiu, Tudor & Morar Triandafil, Cristina & Morar Triandafil, Adrian, 2011. "Debt Ceiling and External Debt Sustainability in Romania: A Quantile Autoregression Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 15-29, December.
    6. Cysne, Rubens Penha, 2006. "Income inequality in a job-search model with heterogeneous discount factors: (revised version, forthcoming 2006, Revista Economia)," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 611, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    7. Renato G. Flôres & Maria Paula Fontoura & Rogério Guerra Santos, 2007. "Foreign Direct Investment Spillovers in Portugal: Additional Lessons from a Country Study," The European Journal of Development Research, Taylor and Francis Journals, vol. 19(3), pages 372-390.
    8. Cysne, Rubens Penha, 2006. "An intra-household approach to the welfare costs of inflation (Revised Version, Forthcoming 2006, Estudos Econômicos)," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 612, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    9. 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.
    10. Flôres Junior, Renato Galvão & Watanuki, Masakazu, 2006. "Integration options for mercosul - an investigation Uusing the AMIDA Model," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 610, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    11. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra & Gaglianone, Wagner Piazza, 2006. "Debt ceiling and fiscal sustainability in Brazil: a quantile autoregression approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 631, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

  10. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra & Gaglianone, Wagner Piazza, 2005. "Limite de endividamento e sustentabilidade fiscal no Brasil: uma abordagem via modelo quantílico auto-regressivo (QAR)," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 602, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Aloisio Araujo & Mário R. Páscoa & Juan Pablo Torres-Martínez, 2006. "Bubbles, Collateral and Monetary Equilibrium," Levine's Working Paper Archive 122247000000001055, David K. Levine.
    2. Monteiro, Paulo Klinger, 2009. "First-price auction symmetric equilibria with a general distribution," Games and Economic Behavior, Elsevier, vol. 65(1), pages 256-269, January.
    3. Cysne, Rubens Penha, 2006. "Income inequality in a job-search model with heterogeneous discount factors: (revised version, forthcoming 2006, Revista Economia)," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 611, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    4. Renato G. Flôres & Maria Paula Fontoura & Rogério Guerra Santos, 2007. "Foreign Direct Investment Spillovers in Portugal: Additional Lessons from a Country Study," The European Journal of Development Research, Taylor and Francis Journals, vol. 19(3), pages 372-390.
    5. Cysne, Rubens Penha, 2006. "An intra-household approach to the welfare costs of inflation (Revised Version, Forthcoming 2006, Estudos Econômicos)," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 612, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    6. Cavalcanti, Ricardo de Oliveira & Wallace, Neil, 2006. "New models of old(?) payment questions," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 619, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    7. Flôres Junior, Renato Galvão, 2006. "Dois ensaios sobre diversidade cultural e o comércio de serviços," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 622, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    8. Flôres Junior, Renato Galvão, 2006. "The diversity of diversity: further methodological considerations on the use of the concept in cultural economics," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 626, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    9. Flôres Junior, Renato Galvão & Watanuki, Masakazu, 2006. "Integration options for mercosul - an investigation Uusing the AMIDA Model," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 610, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

  11. Andrei G. Simonassi & Luiz Renato Lima, 2005. "Dinâmica Não-Linear E Sustentabilidade Da Dívida Pública Brasileira," Anais do XXXIII Encontro Nacional de Economia [Proceedings of the 33rd Brazilian Economics Meeting] 051, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

    Cited by:

    1. Campos, Eduardo Lima & Cysne, Rubens Penha, 2017. "A time-varying fiscal reaction function for Brazil," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 795, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Araújo, Fabio & Issler, João Victor & Fernandes, Marcelo, 2005. "Estimating the stochastic discount factor without a utility function," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 583, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    3. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra & Gaglianone, Wagner Piazza, 2006. "Debt ceiling and fiscal sustainability in Brazil: a quantile autoregression approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 631, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

  12. Luiz Renato Lima & Zhijie Xiao, 2004. "Testing Unit Root Based on Partially Adaptive Estimation," Econometric Society 2004 Latin American Meetings 63, Econometric Society.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    2. Flôres Junior, Renato Galvão, 2004. "On the use (fulness) of CGE modelling in trade negotiations and policy," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 564, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    3. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.

  13. Xiao, Zhijie & Lima, Luiz Renato Regis de Oliveira, 2004. "Purchasing power parity and the unit root tests: a robust analysis," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 552, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Flôres Junior, Renato Galvão, 2004. "On the use (fulness) of CGE modelling in trade negotiations and policy," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 564, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Aloisio Araujo & Luciano I. de Castro Filho, 2004. "Pure Strategy Equilibria of Multidimensional and Non-Monotonic Auctions," Econometric Society 2004 Latin American Meetings 300, Econometric Society.
    3. Athayde, Gustavo M. de & Flôres Junior, Renato Galvão, 2004. "Do higher moments really matter in portfolio choice?," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 574, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    4. Horowitz, Andrew W. & Flôres Junior, Renato Galvão, 2004. "Beyond indifferent players: on the existence of prisoners dilemmas in games with amicable and adversarial preferences," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 576, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

  14. Lima, Luiz Renato Regis de Oliveira & Xiao, Zhijie, 2004. "Do shocks permanently change output? : Local persistency in economic time series," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 529, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Flôres Junior, Renato Galvão, 2004. "On the use (fulness) of CGE modelling in trade negotiations and policy," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 564, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

  15. Kim, Soyoung & Lima, Luiz Renato Regis de Oliveira, 2004. "A new perspective on the PPP hypothesis," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 530, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Flôres Junior, Renato Galvão, 2004. "On the use (fulness) of CGE modelling in trade negotiations and policy," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 564, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Mauro S. Ferreira, 2007. "Capturing asymmetry in real exchange rate with quantile autoregression," Textos para Discussão Cedeplar-UFMG td306, Cedeplar, Universidade Federal de Minas Gerais.

  16. Lima, Luiz Renato Regis de Oliveira & Xiao, Zhijie, 2004. "Robustness of stationary tests under long-memory alternatives," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 541, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Flôres Junior, Renato Galvão, 2004. "On the use (fulness) of CGE modelling in trade negotiations and policy," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 564, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Francis Ahking, 2010. "Non-parametric tests of real exchange rates in the post-Bretton Woods era," Empirical Economics, Springer, vol. 39(2), pages 439-456, October.
    3. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.

  17. Issler, João Victor & Lima, Luiz Renato Regis de Oliveira, 1997. "Public debt sustainability and endogenous seignorage in Brazil: time-series evidence from 1947-92," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 306, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Amir Kia, 2005. "Sustainability of the Fiscal Process in Developing Countries- Egypt, Iran and Turkey: A Multicointegration Approach – revised version: Fiscal Sustainability in Emerging Countries: Evidence from Iran a," Carleton Economic Papers 05-08, Carleton University, Department of Economics, revised Nov 2008.
    2. Ohana, Eduardo Felipe, 1997. "The Brazilian 1994 stabilization plan: an analytical view," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 307, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

Articles

  1. Figueiredo, Erik & Lima, Luiz Renato & Orefice, Gianluca, 2020. "Migration, trade and spillover effects," Journal of Comparative Economics, Elsevier, vol. 48(2), pages 405-421.

    Cited by:

    1. Anthony Edo & Lionel Ragot & Hillel Rapoport & Sulin Sardoschau & Andreas Steinmayr & Arthur Sweetman, 2020. "An introduction to the economics of immigration in OECD countries," PSE-Ecole d'économie de Paris (Postprint) hal-03134977, HAL.

  2. Erik Figueiredo & Luiz Renato Lima, 2020. "Do economic integration agreements affect trade predictability? A group effect analysis," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 637-664, May.

    Cited by:

    1. Zhijie Guan & Yue Zhang & Ip Ping Sheong Jim Kwee Fat, 2021. "Trade Relations Between Mauritius and China: A Gravity Model Approach," SAGE Open, , vol. 11(4), pages 21582440211, November.

  3. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.

    Cited by:

    1. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    2. Laurent Ferrara & Matteo Mogliani & Jean-Guillaume Sahuc, 2020. "High-frequency monitoring of growth-at-risk," CAMA Working Papers 2020-97, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    4. Algieri, Bernardina & Iania, Leonardo & Leccadito, Arturo & Meloni, Giulia, 2023. "Message in a Bottle: Forecasting wine prices," LIDAM Discussion Papers LFIN 2023004, Université catholique de Louvain, Louvain Finance (LFIN).
    5. Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022. "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN 2022003, Université catholique de Louvain, Louvain Finance (LFIN).
    6. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Monitoring daily unemployment at risk"," IREA Working Papers 202211, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.

  4. Luiz Renato Lima & Fanning Meng, 2017. "Out‐of‐Sample Return Predictability: A Quantile Combination Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 877-895, June.

    Cited by:

    1. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2020. "Can systemic risk measures predict economic shocks? Evidence from China," China Economic Review, Elsevier, vol. 64(C).
    2. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
    3. Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).
    4. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    6. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    7. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    8. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
    9. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    10. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    11. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    12. Philippe Goulet Coulombe & Maximilian Goebel, 2023. "Maximally Machine-Learnable Portfolios," Papers 2306.05568, arXiv.org, revised Apr 2024.
    13. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    14. Philippe Goulet Coulombe & Maximilian Gobel, 2023. "Maximally Machine-Learnable Portfolios," Working Papers 23-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Apr 2023.
    15. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    16. De Gooijer Jan G. & Zerom Dawit, 2020. "Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.

  5. Erik Figueiredo & Luiz Renato Lima & Gianluca Orefice, 2016. "Migration and Regional Trade Agreements: A (New) Gravity Estimation," Review of International Economics, Wiley Blackwell, vol. 24(1), pages 99-125, February.
    See citations under working paper version above.
  6. Erik Figueiredo & Luiz Lima & Georg Schaur, 2016. "The effect of the Euro on the bilateral trade distribution," Empirical Economics, Springer, vol. 50(1), pages 17-29, February.

    Cited by:

    1. Giovanni Cerulli & Silvia Nenci & Luca Salvatici & Antonio Zinilli, 2022. "Currency Unions and Global Value Chains: The Impact of the Euro on the Italian Value Added Exports," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 8(2), pages 373-407, July.
    2. Douglas L. Campbell & Aleksandr Chentsov, 2021. "Breaking Badly: The Currency Union Effect on Trade," Working Papers w0281, New Economic School (NES).
    3. Campbell, Douglas L. & Chentsov, Aleksandr, 2023. "Breaking badly: The currency union effect on trade," Journal of International Money and Finance, Elsevier, vol. 136(C).
    4. Brandon J. Sheridan & Rishav Bista & Erik Figueiredo, 2020. "Growth takeoffs and trade margins: a quantile regression approach," Empirical Economics, Springer, vol. 59(1), pages 275-294, July.
    5. Erik Figueiredo & Luiz Renato Lima, 2020. "Do economic integration agreements affect trade predictability? A group effect analysis," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 637-664, May.
    6. Andrew K. Rose, 2017. "Why do Estimates of the EMU Effect on Trade Vary so Much?," Open Economies Review, Springer, vol. 28(1), pages 1-18, February.
    7. Figueiredo, Erik & Lima, Luiz Renato & Orefice, Gianluca, 2020. "Migration, trade and spillover effects," Journal of Comparative Economics, Elsevier, vol. 48(2), pages 405-421.
    8. Dong Phong Nguyen & Xuan Vinh Vo, 2017. "Determinants of bilateral trade: evidence from ASEAN+3," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 31(2), pages 115-122, November.

  7. Clark, Don P. & Lima, Luiz Renato & Sawyer, W. Charles, 2016. "Stages of diversification in Africa," Economics Letters, Elsevier, vol. 144(C), pages 68-70.

    Cited by:

    1. Macatangay, Rafael Emmanuel “Manny”, 2016. "Optimal local content requirement policies for extractive industries," Resources Policy, Elsevier, vol. 50(C), pages 244-252.
    2. Matallah, Siham, 2022. "Economic diversification and governance challenges in MENA oil exporters: A comparative analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).

  8. Lima, Luiz Renato & Mesquita, Shirley & Wanamaker, Marianne, 2015. "Child labor and the wealth paradox: The role of altruistic parents," Economics Letters, Elsevier, vol. 130(C), pages 80-82.

    Cited by:

    1. Huamaní-Huapaya, Edson Raúl, 2019. "Persistencia Intergeneracional del Trabajo Infantil y Adolescente en Perú [Intergenerational Persistence of Child Labor in Peru]," MPRA Paper 101247, University Library of Munich, Germany.
    2. Figueiredo, Erik & Lima, Luiz Renato, 2022. "Unintended consequences of trade integration on child labor," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 523-541.
    3. Victor Champonnois & Olivier Chanel, 2016. "How useful are (Censored) Quantile Regressions for Contingent Valuation?," Working Papers 2016.12, FAERE - French Association of Environmental and Resource Economists.
    4. Basu, Arnab K. & Dimova, Ralitza, 2020. "Household Behavioral Preferences and the Child Labor-Education Trade-off: Framed Field Experimental Evidence from Ethiopia," IZA Discussion Papers 13011, Institute of Labor Economics (IZA).
    5. Bang, James & Mitra, Aniruddha & Abbas, Faisal, 2023. "Remittances and Child Labor in Pakistan: A Tale of Complementarities," GLO Discussion Paper Series 1285, Global Labor Organization (GLO).
    6. Julián Arteaga Vallejo, 2016. "Land, Child Labor, and Schooling: Longitudinal evidence from Colombia and Mexico," Documentos CEDE 14977, Universidad de los Andes, Facultad de Economía, CEDE.
    7. Oryoie, Ali Reza & Alwang, Jeffrey & Tideman, Nicolaus, 2017. "Child Labor and Household Land Holding: Theory and Empirical Evidence from Zimbabwe," World Development, Elsevier, vol. 100(C), pages 45-58.
    8. Basu, Arnab K. & Dimova, Ralitza, 2021. "Household Preferences and Child Labor in Rural Ethiopia," IZA Discussion Papers 14062, Institute of Labor Economics (IZA).

  9. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    See citations under working paper version above.
  10. 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. 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. 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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    11. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    12. 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.
    13. 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.
    14. 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.
    15. Bresson, Georges & Lacroix, Guy & Arshad Rahman, Mohammad, 2020. "Bayesian Panel Quantile Regression for Binary Outcomes with Correlated Random Effects: An Application on Crime Recidivism in Canada," IZA Discussion Papers 12928, Institute of Labor Economics (IZA).
    16. Harding, Matthew & Lamarche, Carlos, 2013. "Penalized Quantile Regression with Semiparametric Correlated Effects: Applications with Heterogeneous Preferences," IZA Discussion Papers 7741, Institute of Labor Economics (IZA).
    17. 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.
    18. Carlos Lamarche & Thomas Parker, 2022. "Wild Bootstrap Inference For Penalized Quantile Regression For Longitudinal Data," Working Papers 22003 Classification-C15,, University of Waterloo, Department of Economics.
    19. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    20. 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.
    21. Junlong Feng, 2019. "Regularized Quantile Regression with Interactive Fixed Effects," Papers 1911.00166, arXiv.org, revised Mar 2021.
    22. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    23. 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).
    24. 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.
    25. 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.
    26. 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.
    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.
    28. 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.
    29. 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.
    30. 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).
    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.

  11. Wagner Piazza Gaglianone & Luiz Renato Lima, 2012. "Constructing Density Forecasts from Quantile Regressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1589-1607, December.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    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. Mihail Yanchev, 2023. "Uncertainty - Definition and Classification for the Task of Economic Forecasting," Bulgarian Economic Papers bep-2023-03, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, revised Mar 2023.
    4. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    5. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    6. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    7. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Working Papers 22-25, Federal Reserve Bank of Cleveland.
    8. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    9. James Mitchell & Aubrey Poon & Dan Zhu, 2022. "Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics," Working Papers 22-12R, Federal Reserve Bank of Cleveland, revised 11 Apr 2023.
    10. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.
    11. Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.
    12. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    13. Francisco Covas & Ben Rump & Egon Zakrajšek, 2013. "Stress-testing U.S. bank holding companies: a dynamic panel quantile regression approach," Finance and Economics Discussion Series 2013-55, Board of Governors of the Federal Reserve System (U.S.).
    14. Todd Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Working Papers 2307, University of Strathclyde Business School, Department of Economics.
    15. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    16. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
    17. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    18. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
    19. Wagner Piazza Gaglianone & Waldyr Dutra Areosa, 2016. "Financial Conditions Indicators for Brazil," Working Papers Series 435, Central Bank of Brazil, Research Department.
    20. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    21. 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.
    22. Korobilis, Dimitris, 2015. "Quantile forecasts of inflation under model uncertainty," MPRA Paper 64341, University Library of Munich, Germany.
    23. Fernando Eguren-Martin & Andrej Sokol, 2022. "Attention to the Tail(s): Global Financial Conditions and Exchange Rate Risks," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(3), pages 487-519, September.
    24. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    25. Milan Szabo, 2020. "Growth-at-Risk: Bayesian Approach," Working Papers 2020/3, Czech National Bank.
    26. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    27. Ramsey, A., 2018. "Conditional Distributions of Crop Yields: A Bayesian Approach for Characterizing Technological Change," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277253, International Association of Agricultural Economists.
    28. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    29. Iddrisu, Abdul-Aziz & Alagidede, Imhotep Paul, 2020. "Monetary policy and food inflation in South Africa: A quantile regression analysis," Food Policy, Elsevier, vol. 91(C).
    30. Laurent Ferrara & Joseph Yapi, 2020. "Measuring exchange rate risks during periods of uncertainty," CAMA Working Papers 2020-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    31. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
    32. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    33. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2024. "A Quantile Nelson-Siegel model," Papers 2401.09874, arXiv.org.
    34. Dimitris Korobilis & Maximilian Schröder, 2023. "Probabilistic Quantile Factor Analysis," Working Papers No 05/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    35. González-Ordiano, Jorge Ángel & Mühlpfordt, Tillmann & Braun, Eric & Liu, Jianlei & Çakmak, Hüseyin & Kühnapfel, Uwe & Düpmeier, Clemens & Waczowicz, Simon & Faulwasser, Timm & Mikut, Ralf & Hagenmeye, 2021. "Probabilistic forecasts of the distribution grid state using data-driven forecasts and probabilistic power flow," Applied Energy, Elsevier, vol. 302(C).
    36. Yuzhi Cai & Guodong Li, 2018. "A novel approach to modelling the distribution of financial returns," Working Papers 2018-22, Swansea University, School of Management.
    37. James Mitchell & Saeed Zaman, 2023. "The Distributional Predictive Content of Measures of Inflation Expectations," Working Papers 23-31, Federal Reserve Bank of Cleveland.

  12. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
    See citations under working paper version above.
  13. Lima Luiz Renato & Xiao Zhijie, 2010. "Testing Unit Root Based on Partially Adaptive Estimation," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-34, June.
    See citations under working paper version above.
  14. Kim, Soyoung & Lima, Luiz Renato, 2010. "Local persistence and the PPP hypothesis," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 555-569, April.

    Cited by:

    1. Meher Manzur, 2018. "Exchange rate economics is always and everywhere controversial," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 216-232, January.
    2. Brissimis, Sophocles & Migiakis, Petros, 2010. "Inflation persistence and the rationality of inflation expectations," MPRA Paper 29052, University Library of Munich, Germany.
    3. Baharumshah & Siew-Voon Soon & Wohar, 2015. "Parity reversion in the Asian real exchange rates: new evidence from the local-persistent model," Applied Economics, Taylor & Francis Journals, vol. 47(59), pages 6395-6408, December.
    4. Erik Alencar de Figueiredo & André de Mattos Marques, 2013. "Testing absolute PPP hypothesis for twenty countries through the skeleton from a SETAR model- some new evidence," Série Textos para Discussão (Working Papers) 16, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    5. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Hamzah, Nor Aishah, 2013. "Parity reversion in real interest rate in the Asian countries: Further evidence based on local-persistent model," Economic Modelling, Elsevier, vol. 35(C), pages 634-642.
    6. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Boršič, Darja, 2013. "Real interest parity in Central and Eastern European countries: Evidence on integration into EU and the US markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 163-180.
    7. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    8. Njindan Iyke, Bernard, 2015. "Real Exchange Rates Persistence in the West African Monetary Zone: A Revisit of the PPP Puzzle," MPRA Paper 67282, University Library of Munich, Germany.
    9. Luke Lin & Chun I. Lee, 2016. "Central Bank Intervention, Exchange Rate Regime and the Purchasing Power Parity," The World Economy, Wiley Blackwell, vol. 39(8), pages 1256-1274, August.
    10. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Lau, Evan, 2017. "Fiscal sustainability in an emerging market economy: When does public debt turn bad?," Journal of Policy Modeling, Elsevier, vol. 39(1), pages 99-113.

  15. Lima, Luiz Renato & Notini, Hilton Hostalácio & Reis Gomes, Fábio Augusto, 2010. "Empirical Evidence on Convergence Across Brazilian States," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 64(2), June.

    Cited by:

    1. Mello, Marcelo, 2010. "Stochastic Convergence Across Brazilian States," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    2. Christiano M. Penna & Fabricio Linhares, 2011. "Convergênciae Formação de Clubes no Brasil sob aHipótese de Heterogeneidade no DesenvolvimentoTecnológico," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 87, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    3. Penna, Christiano Modesto & Linhares, Fabricio Carneiro, 2013. "Há controvérsia entre análises de beta e sigma-convergência no Brasil?," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.

  16. Issler, João Victor & Lima, Luiz Renato, 2009. "A panel data approach to economic forecasting: The bias-corrected average forecast," Journal of Econometrics, Elsevier, vol. 152(2), pages 153-164, October.
    See citations under working paper version above.
  17. Lima, Luiz Renato & Gaglianone, Wagner Piazza & Sampaio, Raquel M.B., 2008. "Debt ceiling and fiscal sustainability in Brazil: A quantile autoregression approach," Journal of Development Economics, Elsevier, vol. 86(2), pages 313-335, June.
    See citations under working paper version above.
  18. Luiz Lima & Jaime de Jesus Filho, 2008. "Further investigation of the uncertain trend in US GDP," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1207-1216.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.

  19. Lima, Luiz Renato & Néri, Breno Pinheiro, 2007. "Comparing Value-at-Risk Methodologies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.
    See citations under working paper version above.
  20. Lima, Luiz Renato & Xiao, Zhijie, 2007. "Do shocks last forever? Local persistency in economic time series," Journal of Macroeconomics, Elsevier, vol. 29(1), pages 103-122, March.

    Cited by:

    1. Brissimis, Sophocles & Migiakis, Petros, 2010. "Inflation persistence and the rationality of inflation expectations," MPRA Paper 29052, University Library of Munich, Germany.
    2. Baharumshah & Siew-Voon Soon & Wohar, 2015. "Parity reversion in the Asian real exchange rates: new evidence from the local-persistent model," Applied Economics, Taylor & Francis Journals, vol. 47(59), pages 6395-6408, December.
    3. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Hamzah, Nor Aishah, 2013. "Parity reversion in real interest rate in the Asian countries: Further evidence based on local-persistent model," Economic Modelling, Elsevier, vol. 35(C), pages 634-642.
    4. Kim, Soyoung & Lima, Luiz Renato, 2010. "Local persistence and the PPP hypothesis," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 555-569, April.
    5. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    6. Jozef Barunik & Lukas Vacha, 2023. "The Dynamic Persistence of Economic Shocks," Papers 2306.01511, arXiv.org.
    7. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Boršič, Darja, 2013. "Real interest parity in Central and Eastern European countries: Evidence on integration into EU and the US markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 163-180.
    8. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    9. Dimitris A. Georgoutsos & Petros Migiakis, 2010. "European sovereign bond spreads: monetary unification, market conditions and financial integration," Working Papers 115, Bank of Greece.

  21. Zhijie Xiao & Luiz Renato Lima, 2007. "Testing Covariance Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 643-667.
    See citations under working paper version above.
  22. Luiz Lima & Breno Neri, 2006. "Omitted Asymmetric Persistence and Conditional Heteroskedasticity," Economics Bulletin, AccessEcon, vol. 3(5), pages 1-6.

    Cited by:

    1. Schechtman, Ricardo & Gaglianone, Wagner Piazza, 2012. "Macro stress testing of credit risk focused on the tails," Journal of Financial Stability, Elsevier, vol. 8(3), pages 174-192.

  23. Issler, Joao Victor & Lima, Luiz Renato, 2000. "Public debt sustainability and endogenous seigniorage in Brazil: time-series evidence from 1947-1992," Journal of Development Economics, Elsevier, vol. 62(1), pages 131-147, June.

    Cited by:

    1. Campos, Eduardo Lima & Cysne, Rubens Penha, 2017. "A time-varying fiscal reaction function for Brazil," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 795, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Raí Da Silva Chicoli & Siegfried Bender, 2016. "Sustentabilidade Da Dívida Pública Brasileira: Uma Análise Sob Diversos Conceitos De Superávit Primário E Endividamento," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 068, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    3. Manoel Carlos de Castro Pires, 2006. "Uma Análise de Credibilidade na Política Fiscal Brasileira," Discussion Papers 1222, Instituto de Pesquisa Econômica Aplicada - IPEA.
    4. Valdeir Monteiro & Paulo Matos & Cristiano Silva, 2022. "Modeling Brazilian federal government fiscal reaction in the time-frequency domain," Economics Bulletin, AccessEcon, vol. 42(4), pages 1836-1847.
    5. Viviane Luporini, 2014. "Sustainability Of Brazilian Fiscalpolicy, Once Again: Corrective Policy Response Over Time," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 064, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    6. Eduardo de Sá Fortes Leitão Rodrigues, 2020. "Uncertainty And The Effectiveness Of Fiscal Policy In The United States And Brazil: Svar Approach," Working Papers REM 2020/0150, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    7. Faria, Joao Ricardo & McAdam, Peter & Viscolani, Bruno, 2021. "Monetary policy, neutrality and the environment," Working Paper Series 2573, European Central Bank.
    8. Luckas Sabioni Lopes & Marcelle Chauvet & João Eustáquio Lima, 2018. "The end of Brazilian big inflation: lessons to monetary policy from a standard New Keynesian model," Empirical Economics, Springer, vol. 55(4), pages 1475-1505, December.
    9. Raí da Silva Chicoli & Siegfried Bender, 2015. "Sustentabilidade da dívida publica brasileira: Uma análise sob diversos conceitos de superávit primário e endividamento," Working Papers, Department of Economics 2015_37, University of São Paulo (FEA-USP).
    10. Cysne, Rubens Penha & Campos, Eduardo Lima, 2019. "Sustainability of the Brazilian public pebt an analysis using multicointegration," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 805, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    11. Rocha, Fabiana, 2001. "Is There Any Rationale to the Brazilian Fiscal Policy?," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 55(3), July.
    12. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra & Gaglianone, Wagner Piazza, 2006. "Debt ceiling and fiscal sustainability in Brazil: a quantile autoregression approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 631, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    13. Trachanas, Emmanouil & Katrakilidis, Constantinos, 2013. "Fiscal deficits under financial pressure and insolvency: Evidence for Italy, Greece and Spain," Journal of Policy Modeling, Elsevier, vol. 35(5), pages 730-749.
    14. Eduardo de Sa Fortes Leitao Rodrigues, 2023. "Uncertainty and the effectiveness of fiscal policy in the United States and Brasil: SVAR Approach," Working Papers 2023.03, International Network for Economic Research - INFER.

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