Datação, Conologia e Dinâmica de Ciclos Fiscais Brasileiros em Alta-Dimensão
DOI:
https://doi.org/10.55532/1806-8944.2023.209Palavras-chave:
Ciclos Fiscais, Datação, Cronologia, Sincronização de ciclos, Modelo Dinâmico Fatorial com Mudança de RegimeResumo
O estudo propõe a datação dos ciclos fiscais brasileiros. Foram datados os ciclos de Arrecadação Bruta de Despesas Primárias do Governo Central. O estudo também analisa a dinâmica de sincronização dos ciclos fiscais e os ciclos econômicos e eleitorais. A datação multivariada torna claro que a duração da fase de expansões das despesas estava, no período de estudo, em crescimento. O modelo multivariado também mostra que as recessões de arrecadação estão ampliando sua duração. Os resultados mostram que existe sincronização entre o ciclo de despesas e o ciclo econômico, bem como com o ciclo eleitoral, nesses casos, com sincronização maior do que com o ciclo de arrecadação. O ciclo de arrecadação apresentou sincronização com o ciclo econômico, contudo sem haver sincronismo com o ciclo eleitoral.
Referências
Araújo, E., Carpena, L. and Cunha, A. B.: 2008, Brazilian business cycles and growth from 1850 to 2000, Estudos
Econômicos (são paulo) 38(3), 557–581.
Backus, D. K. and Kehoe, P. J.: 1992, International evidence on the historical properties of business cycles, The
American Economic Review pp. 864–888.
Bańbura, M. and Modugno, M.: 2014, Maximum likelihood estimation of factor models on datasets with arbitrary
pattern of missing data, Journal of Applied Econometrics 29(1), 133–160.
Baxter, M. and King, R. G.: 1999, Measuring business cycles: approximate band-pass filters for economic time
series, Review of economics and statistics 81(4), 575–593.
Beveridge, S. and Nelson, C. R.: 1981, A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’, Journal of
Monetary economics 7(2), 151–174.
Boschan, C. and Ebanks, W.: 1978, The phase-average trend: A new way of measuring growth, in 1978, Proceedings of the Business and Economic Statistics Section.
Bry, G. and Boschan, C.: 1971, Interpretation and analysis of time-series scatters, The American Statistician
25(2), 29–33.
Burns, A. F. and Mitchell, W. C.: 1947, Measuring business cycles.
Burns, A. F., Mitchell, W. C. et al.: 1946, Measuring business cycles, Nber Books .
Céspedes, B. J., Chauvet, M. and Lima, E. C.: 2006, Forecasting brazilian output and its turning points in the
presence of breaks: a comparison of linear and nonlinear models, Estudos Econômicos (São Paulo) 36(1), 5–46.
Chari, V. V., Kehoe, P. J. and McGrattan, E. R.: 2007, Business cycle accounting, Econometrica 75(3), 781–836.
Chauvet, M.: 1998, An econometric characterization of business cycle dynamics with factor structure and regime
switching, International economic review pp. 969–996.
Chauvet, M.: 2002, The brazilian business and growth cycles, Revista Brasileira de Economia 56(1), 75–106.
Chauvet, M. and Hamilton, J. D.: 2006, Dating business cycle turning points, Contributions to Economic Analysis
276, 1–54.
Chauvet, M. and Piger, J.: 2008, A comparison of the real-time performance of business cycle dating methods,
Journal of Business & Economic Statistics 26(1), 42–49.
Chauvet, M. and Popli, G.: 2003, Maturing capitalism and stabilization: International evidence, Journal of
Business and Economics 1(12), 5–22.
Chauvet, M. and Potter, S.: 2001, Recent changes in the us business cycle, The Manchester School 69(5), 481–508.
Chauvet, M. and Potter, S.: 2002, Predicting a recession: evidence from the yield curve in the presence of
structural breaks, Economics Letters 77(2), 245–253.
Chauvet, M. and Potter, S.: 2005, Forecasting recessions using the yield curve, Journal of Forecasting 24(2), 77–
103.
Chauvet, M. and Su, Y.: 2014, Nonstationarities and markov switching models, Recent Advances in Estimating
Nonlinear Models, Springer, pp. 123–146.
Chauvet, M. and Tierney, H. L.: 2009, Real time changes in monetary policy, Working Paper .
Chauvet, M., William, B. and Danilo, L. L.: 2016, Real-time nowcasting of nominal gdp with structural breaks,
Journal of Econometrics pp. 312–324.
Chernozhukov, V., Hansen, C. and Spindler, M.: 2015, Post-selection and post-regularization inference in linear
models with many controls and instruments, American Economic Review 105(5), 486–90.
Christiano, L. J. and Fitzgerald, T. J.: 2003, The band pass filter, international economic review 44(2), 435–465.
Cole, H. L. and Ohanian, L. E.: 2004, New deal policies and the persistence of the great depression: A general
equilibrium analysis, Journal of political Economy 112(4), 779–816.
Cribari-Neto, F.: 1993, The cyclical component in brazilian gdp, Brazilian Review of Econometrics 13(1), 1–22.
Doz, C., Giannone, D. and Reichlin, L.: 2012, A quasi–maximum likelihood approach for large, approximate
dynamic factor models, Review of economics and statistics 94(4), 1014–1024.
Ellery-Jr, R. and Gomes, V.: 2005, Ciclo de negócios no brasil durante o século xx–uma comparaçao com a
evidência internacional, Revista Economia 6(1), 45–66.
Ellery Jr, R., Gomes, V. and Sachsida, A.: 2002, Business cycle fluctuations in brazil, Revista Brasileira de
Economia 56(2), 269–308.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2000, The generalized dynamic-factor model: Identification and
estimation, Review of Economics and statistics 82(4), 540–554.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2001, Coincident and leading indicators for the euro area, The
Economic Journal 111(471), C62–C85.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2004, The generalized dynamic factor model consistency and
rates, Journal of Econometrics 119(2), 231–255.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2005, The generalized dynamic factor model: one-sided estimation and forecasting, Journal of the American Statistical Association 100(471), 830–840.
Forni, M. and Lippi, M.: 2001, The generalized dynamic factor model: representation theory, Econometric theory
17(6), 1113–1141.
Friedman, M. and Schwartz, A. J.: 1965, Money and business cycles, The state of monetary economics, NBER,
pp. 32–78.
Hamilton, J. D.: 1989, A new approach to the economic analysis of nonstationary time series and the business
cycle, Econometrica: Journal of the Econometric Society pp. 357–384.
Hampel, F. R.: 1971, A general qualitative definition of robustness, The Annals of Mathematical Statistics
pp. 1887–1896.
Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J. and Stahel, W. A.: 2011, Robust statistics: the approach based
on influence functions, Vol. 196, John Wiley & Sons.
Harding, D. and Pagan, A.: 2002, Dissecting the cycle: a methodological investigation, Journal of monetary
economics 49(2), 365–381.
Harding, D. and Pagan, A.: 2003, A comparison of two business cycle dating methods, Journal of Economic
Dynamics and Control 27(9), 1681–1690.
Harding, D. and Pagan, A.: 2006, Synchronization of cycles, Journal of Econometrics 132(1), 59–79.
Haywood, E.: 1973, The deviation cycle: a new index of the australian business cycle 1950–1973, Australian
Economic Review 6(4), 31–39.
Hodrick, R. J. and Prescott, E. C.: 1997, Postwar us business cycles: an empirical investigation, Journal of
Money, credit, and Banking pp. 1–16.
Jungbacker, B. M. J. P., Koopman, S.-J. et al.: 2008, Likelihood-based analysis for dynamic factor models,
Working Paper .
Kaldor, N.: 1961, Capital accumulation and economic growth, The theory of capital, Springer, pp. 177–222.
Kalecki, M.: 1937, A theory of the business cycle, The Review of Economic Studies 4(2), 77–97.
Kalecki, M.: 1968, Trend and business cycles reconsidered, The Economic Journal 78(310), 263–276.
Kanczuk, F.: 2002, Juros reais e ciclos reais brasileiros, Revista Brasileira de Economia 56(2), 249–267.
Keynes, J. M.: 1940, On a method of statistical business-cycle research. a comment, The Economic Journal
pp. 154–156.
Kim, C.-J.: 1994, Dynamic linear models with markov-switching, Journal of Econometrics 60(1-2), 1–22.
Kim, C.-J. and Nelson, C. R.: 1999, Has the us economy become more stable? a bayesian approach based on a
markov-switching model of the business cycle, Review of Economics and Statistics 81(4), 608–616.
Kim, C.-J., Piger, J. and Startz, R.: 2008, Estimation of markov regime-switching regression models with endogenous switching, Journal of Econometrics 143(2), 263–273.
Kim, M.-J. and Yoo, J.-S.: 1995, New index of coincident indicators: A multivariate markov switching factor
model approach, Journal of Monetary Economics 36(3), 607–630.
Kuznets, S.: 1930, Equilibrium economics and business-cycle theory, The Quarterly Journal of Economics
44(3), 381–415.
Kydland, F. E. and Prescott, E. C.: 1982, Time to build and aggregate fluctuations, Econometrica: Journal of
the Econometric Society pp. 1345–1370.
Kydland, F. E. and Prescott, E. C.: 1990, The econometrics of the general equilibrium approach to business
cycles, Real Business Cycles pp. 219–236.
Kydland, F. E. and Prescott, E. C.: 1996, The computational experiment: an econometric tool, Journal of
economic perspectives 10(1), 69–85.
Layton, A. P.: 1996, Dating and predicting phase changes in the us business cycle, International Journal of
Forecasting 12(3), 417–428.
Leiva-Leon, D.: 2014, Real vs. nominal cycles: a multistate markov-switching bi-factor approach, Studies in
Nonlinear Dynamics & Econometrics 18(5), 557–580.
Lucas, R.: 1972, Expectations and the neutrality of money, Journal of economic theory 4(2), 103–124.
Lucas, R. E.: 1973, Some international evidence on output-inflation tradeoffs, The American Economic Review
63(3), 326–334.
Mankiw, N. G.: 1989, Real business cycles: A new keynesian perspective, Journal of economic perspectives
3(3), 79–90.
Medeiros, M. C. and Mendes, E. F.: 2017, Adaptive lasso estimation for ardl models with garch innovations,
Econometric Reviews 36(6-9), 622–637.
Meller, B. and Metiu, N.: 2017, The synchronization of credit cycles, Journal of Banking & Finance 82, 98–111.
Mink, M., Jacobs, J. P. and de Haan, J.: 2011, Measuring coherence of output gaps with an application to the
euro area, Oxford Economic Papers 64(2), 217–236.
Mitchell, W. C.: 1927, Business cycles: the problem and its setting, Technical report.
Mitchell, W. C.: 1930, Business cycles: the problems and its setting Business cycles: The problem and its setting,
National Bureau of Economic Research, New York.
Neftici, S. N.: 1982, Optimal prediction of cyclical downturns, Journal of Economic Dynamics and Control
4, 225–241.
Pedersen, T. M.: 2001, The hodrick–prescott filter, the slutzky effect, and the distortionary effect of filters,
Journal of economic dynamics and control 25(8), 1081–1101.
Pereira, P. L. V. and Vieira, H. P.: 2013, A study of the brazilian business cycles (1900–2012), Brazilian Review
of Econometrics 33(2), 123–143.
Pollock, D.: 2000, Trend estimation and de-trending via rational square-wave filters, Journal of Econometrics
99(2), 317–334.
Pollock, D. S. G.: 2007, Wiener–kolmogorov filtering, frequency-selective filtering, and polynomial regression,
Econometric Theory 23(1), 71–88.
Prescott, E. C.: 1986, Theory ahead of business-cycle measurement, Carnegie-Rochester conference series on
public policy, Vol. 25, Elsevier, pp. 11–44.
Proietti, T. and Harvey, A.: 2000, A beveridge–nelson smoother, Economics Letters 67(2), 139–146.
Schumpeter, J.: 1927, The explanation of the business cycle, Economica (21), 286–311.
Schumpeter, J. A. and Fels, R.: 1939, Business cycles: a theoretical, historical, and statistical analysis of the
capitalist process, Vol. 2, McGraw-Hill New York.
Stock, J. H. and Watson, M.: 2011, Dynamic factor models, Oxford University Press.
Stock, J. H. and Watson, M. W.: 1999, Business cycle fluctuations in us macroeconomic time series, Handbook of
macroeconomics 1, 3–64.
Stock, J. H. and Watson, M. W.: 2002, Macroeconomic forecasting using diffusion indexes, Journal of Business
& Economic Statistics 20(2), 147–162.
Stock, J. H. and Watson, M. W.: 2014, Estimating turning points using large data sets, Journal of Econometrics
178, 368–381.
Tibshirani, R.: 1996, Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society:
Series B (Methodological) 58(1), 267–288.
Tinbergen, J.: 1939, Statistical testing of business-cycle theories: Business cycles in the United States of America,
1919-1932, Vol. 2, League of nations, Economic intelligence service.
Tinbergen, J.: 1940a, Econometric business cycle research, The Review of Economic Studies 7(2), 73–90.
Tinbergen, J.: 1940b, On a method of statistical business-cycle research. a reply, The Economic Journal pp. 141–
154.
Val, P. R. d. C. and Ferreira, P. C.: 2001, Modelos de ciclos reais de negócios aplicados à economia brasileira,
Technical report.
Zou, H.: 2006, The adaptive lasso and its oracle properties, Journal of the American statistical association
101(476), 1418–1429.
Econômicos (são paulo) 38(3), 557–581.
Backus, D. K. and Kehoe, P. J.: 1992, International evidence on the historical properties of business cycles, The
American Economic Review pp. 864–888.
Bańbura, M. and Modugno, M.: 2014, Maximum likelihood estimation of factor models on datasets with arbitrary
pattern of missing data, Journal of Applied Econometrics 29(1), 133–160.
Baxter, M. and King, R. G.: 1999, Measuring business cycles: approximate band-pass filters for economic time
series, Review of economics and statistics 81(4), 575–593.
Beveridge, S. and Nelson, C. R.: 1981, A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’, Journal of
Monetary economics 7(2), 151–174.
Boschan, C. and Ebanks, W.: 1978, The phase-average trend: A new way of measuring growth, in 1978, Proceedings of the Business and Economic Statistics Section.
Bry, G. and Boschan, C.: 1971, Interpretation and analysis of time-series scatters, The American Statistician
25(2), 29–33.
Burns, A. F. and Mitchell, W. C.: 1947, Measuring business cycles.
Burns, A. F., Mitchell, W. C. et al.: 1946, Measuring business cycles, Nber Books .
Céspedes, B. J., Chauvet, M. and Lima, E. C.: 2006, Forecasting brazilian output and its turning points in the
presence of breaks: a comparison of linear and nonlinear models, Estudos Econômicos (São Paulo) 36(1), 5–46.
Chari, V. V., Kehoe, P. J. and McGrattan, E. R.: 2007, Business cycle accounting, Econometrica 75(3), 781–836.
Chauvet, M.: 1998, An econometric characterization of business cycle dynamics with factor structure and regime
switching, International economic review pp. 969–996.
Chauvet, M.: 2002, The brazilian business and growth cycles, Revista Brasileira de Economia 56(1), 75–106.
Chauvet, M. and Hamilton, J. D.: 2006, Dating business cycle turning points, Contributions to Economic Analysis
276, 1–54.
Chauvet, M. and Piger, J.: 2008, A comparison of the real-time performance of business cycle dating methods,
Journal of Business & Economic Statistics 26(1), 42–49.
Chauvet, M. and Popli, G.: 2003, Maturing capitalism and stabilization: International evidence, Journal of
Business and Economics 1(12), 5–22.
Chauvet, M. and Potter, S.: 2001, Recent changes in the us business cycle, The Manchester School 69(5), 481–508.
Chauvet, M. and Potter, S.: 2002, Predicting a recession: evidence from the yield curve in the presence of
structural breaks, Economics Letters 77(2), 245–253.
Chauvet, M. and Potter, S.: 2005, Forecasting recessions using the yield curve, Journal of Forecasting 24(2), 77–
103.
Chauvet, M. and Su, Y.: 2014, Nonstationarities and markov switching models, Recent Advances in Estimating
Nonlinear Models, Springer, pp. 123–146.
Chauvet, M. and Tierney, H. L.: 2009, Real time changes in monetary policy, Working Paper .
Chauvet, M., William, B. and Danilo, L. L.: 2016, Real-time nowcasting of nominal gdp with structural breaks,
Journal of Econometrics pp. 312–324.
Chernozhukov, V., Hansen, C. and Spindler, M.: 2015, Post-selection and post-regularization inference in linear
models with many controls and instruments, American Economic Review 105(5), 486–90.
Christiano, L. J. and Fitzgerald, T. J.: 2003, The band pass filter, international economic review 44(2), 435–465.
Cole, H. L. and Ohanian, L. E.: 2004, New deal policies and the persistence of the great depression: A general
equilibrium analysis, Journal of political Economy 112(4), 779–816.
Cribari-Neto, F.: 1993, The cyclical component in brazilian gdp, Brazilian Review of Econometrics 13(1), 1–22.
Doz, C., Giannone, D. and Reichlin, L.: 2012, A quasi–maximum likelihood approach for large, approximate
dynamic factor models, Review of economics and statistics 94(4), 1014–1024.
Ellery-Jr, R. and Gomes, V.: 2005, Ciclo de negócios no brasil durante o século xx–uma comparaçao com a
evidência internacional, Revista Economia 6(1), 45–66.
Ellery Jr, R., Gomes, V. and Sachsida, A.: 2002, Business cycle fluctuations in brazil, Revista Brasileira de
Economia 56(2), 269–308.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2000, The generalized dynamic-factor model: Identification and
estimation, Review of Economics and statistics 82(4), 540–554.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2001, Coincident and leading indicators for the euro area, The
Economic Journal 111(471), C62–C85.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2004, The generalized dynamic factor model consistency and
rates, Journal of Econometrics 119(2), 231–255.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.: 2005, The generalized dynamic factor model: one-sided estimation and forecasting, Journal of the American Statistical Association 100(471), 830–840.
Forni, M. and Lippi, M.: 2001, The generalized dynamic factor model: representation theory, Econometric theory
17(6), 1113–1141.
Friedman, M. and Schwartz, A. J.: 1965, Money and business cycles, The state of monetary economics, NBER,
pp. 32–78.
Hamilton, J. D.: 1989, A new approach to the economic analysis of nonstationary time series and the business
cycle, Econometrica: Journal of the Econometric Society pp. 357–384.
Hampel, F. R.: 1971, A general qualitative definition of robustness, The Annals of Mathematical Statistics
pp. 1887–1896.
Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J. and Stahel, W. A.: 2011, Robust statistics: the approach based
on influence functions, Vol. 196, John Wiley & Sons.
Harding, D. and Pagan, A.: 2002, Dissecting the cycle: a methodological investigation, Journal of monetary
economics 49(2), 365–381.
Harding, D. and Pagan, A.: 2003, A comparison of two business cycle dating methods, Journal of Economic
Dynamics and Control 27(9), 1681–1690.
Harding, D. and Pagan, A.: 2006, Synchronization of cycles, Journal of Econometrics 132(1), 59–79.
Haywood, E.: 1973, The deviation cycle: a new index of the australian business cycle 1950–1973, Australian
Economic Review 6(4), 31–39.
Hodrick, R. J. and Prescott, E. C.: 1997, Postwar us business cycles: an empirical investigation, Journal of
Money, credit, and Banking pp. 1–16.
Jungbacker, B. M. J. P., Koopman, S.-J. et al.: 2008, Likelihood-based analysis for dynamic factor models,
Working Paper .
Kaldor, N.: 1961, Capital accumulation and economic growth, The theory of capital, Springer, pp. 177–222.
Kalecki, M.: 1937, A theory of the business cycle, The Review of Economic Studies 4(2), 77–97.
Kalecki, M.: 1968, Trend and business cycles reconsidered, The Economic Journal 78(310), 263–276.
Kanczuk, F.: 2002, Juros reais e ciclos reais brasileiros, Revista Brasileira de Economia 56(2), 249–267.
Keynes, J. M.: 1940, On a method of statistical business-cycle research. a comment, The Economic Journal
pp. 154–156.
Kim, C.-J.: 1994, Dynamic linear models with markov-switching, Journal of Econometrics 60(1-2), 1–22.
Kim, C.-J. and Nelson, C. R.: 1999, Has the us economy become more stable? a bayesian approach based on a
markov-switching model of the business cycle, Review of Economics and Statistics 81(4), 608–616.
Kim, C.-J., Piger, J. and Startz, R.: 2008, Estimation of markov regime-switching regression models with endogenous switching, Journal of Econometrics 143(2), 263–273.
Kim, M.-J. and Yoo, J.-S.: 1995, New index of coincident indicators: A multivariate markov switching factor
model approach, Journal of Monetary Economics 36(3), 607–630.
Kuznets, S.: 1930, Equilibrium economics and business-cycle theory, The Quarterly Journal of Economics
44(3), 381–415.
Kydland, F. E. and Prescott, E. C.: 1982, Time to build and aggregate fluctuations, Econometrica: Journal of
the Econometric Society pp. 1345–1370.
Kydland, F. E. and Prescott, E. C.: 1990, The econometrics of the general equilibrium approach to business
cycles, Real Business Cycles pp. 219–236.
Kydland, F. E. and Prescott, E. C.: 1996, The computational experiment: an econometric tool, Journal of
economic perspectives 10(1), 69–85.
Layton, A. P.: 1996, Dating and predicting phase changes in the us business cycle, International Journal of
Forecasting 12(3), 417–428.
Leiva-Leon, D.: 2014, Real vs. nominal cycles: a multistate markov-switching bi-factor approach, Studies in
Nonlinear Dynamics & Econometrics 18(5), 557–580.
Lucas, R.: 1972, Expectations and the neutrality of money, Journal of economic theory 4(2), 103–124.
Lucas, R. E.: 1973, Some international evidence on output-inflation tradeoffs, The American Economic Review
63(3), 326–334.
Mankiw, N. G.: 1989, Real business cycles: A new keynesian perspective, Journal of economic perspectives
3(3), 79–90.
Medeiros, M. C. and Mendes, E. F.: 2017, Adaptive lasso estimation for ardl models with garch innovations,
Econometric Reviews 36(6-9), 622–637.
Meller, B. and Metiu, N.: 2017, The synchronization of credit cycles, Journal of Banking & Finance 82, 98–111.
Mink, M., Jacobs, J. P. and de Haan, J.: 2011, Measuring coherence of output gaps with an application to the
euro area, Oxford Economic Papers 64(2), 217–236.
Mitchell, W. C.: 1927, Business cycles: the problem and its setting, Technical report.
Mitchell, W. C.: 1930, Business cycles: the problems and its setting Business cycles: The problem and its setting,
National Bureau of Economic Research, New York.
Neftici, S. N.: 1982, Optimal prediction of cyclical downturns, Journal of Economic Dynamics and Control
4, 225–241.
Pedersen, T. M.: 2001, The hodrick–prescott filter, the slutzky effect, and the distortionary effect of filters,
Journal of economic dynamics and control 25(8), 1081–1101.
Pereira, P. L. V. and Vieira, H. P.: 2013, A study of the brazilian business cycles (1900–2012), Brazilian Review
of Econometrics 33(2), 123–143.
Pollock, D.: 2000, Trend estimation and de-trending via rational square-wave filters, Journal of Econometrics
99(2), 317–334.
Pollock, D. S. G.: 2007, Wiener–kolmogorov filtering, frequency-selective filtering, and polynomial regression,
Econometric Theory 23(1), 71–88.
Prescott, E. C.: 1986, Theory ahead of business-cycle measurement, Carnegie-Rochester conference series on
public policy, Vol. 25, Elsevier, pp. 11–44.
Proietti, T. and Harvey, A.: 2000, A beveridge–nelson smoother, Economics Letters 67(2), 139–146.
Schumpeter, J.: 1927, The explanation of the business cycle, Economica (21), 286–311.
Schumpeter, J. A. and Fels, R.: 1939, Business cycles: a theoretical, historical, and statistical analysis of the
capitalist process, Vol. 2, McGraw-Hill New York.
Stock, J. H. and Watson, M.: 2011, Dynamic factor models, Oxford University Press.
Stock, J. H. and Watson, M. W.: 1999, Business cycle fluctuations in us macroeconomic time series, Handbook of
macroeconomics 1, 3–64.
Stock, J. H. and Watson, M. W.: 2002, Macroeconomic forecasting using diffusion indexes, Journal of Business
& Economic Statistics 20(2), 147–162.
Stock, J. H. and Watson, M. W.: 2014, Estimating turning points using large data sets, Journal of Econometrics
178, 368–381.
Tibshirani, R.: 1996, Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society:
Series B (Methodological) 58(1), 267–288.
Tinbergen, J.: 1939, Statistical testing of business-cycle theories: Business cycles in the United States of America,
1919-1932, Vol. 2, League of nations, Economic intelligence service.
Tinbergen, J.: 1940a, Econometric business cycle research, The Review of Economic Studies 7(2), 73–90.
Tinbergen, J.: 1940b, On a method of statistical business-cycle research. a reply, The Economic Journal pp. 141–
154.
Val, P. R. d. C. and Ferreira, P. C.: 2001, Modelos de ciclos reais de negócios aplicados à economia brasileira,
Technical report.
Zou, H.: 2006, The adaptive lasso and its oracle properties, Journal of the American statistical association
101(476), 1418–1429.
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28-06-2023
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Maranhão, A. (2023). Datação, Conologia e Dinâmica de Ciclos Fiscais Brasileiros em Alta-Dimensão. CADERNOS DE FINANÇAS PÚBLICAS , 23(01). https://doi.org/10.55532/1806-8944.2023.209
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