Os Gastos Tributários Contribuem para o Aumento da Produtividade Total dos Fatores no Brasil?
Keywords:
Gastos Tributários; Política Fiscal; Produtividade Total dos Fatores (PTF); VAR Bayesiano; Avaliação de Políticas PúblicasAbstract
The effectiveness of tax expenditures as a public policy instrument is a central issue in both Brazil and the global context, given their expansion and the significant indirect costs imposed on public budgets. Despite their relevance, further debate is needed in Brazil, where tax expenditures have exceeded the combined budgets of Health and Education since 2006 and have grown at a faster rate since 1996, without clear evidence of returns. This study aims to evaluate the dynamic effects of tax expenditures on total factor productivity in Brazil. To this end, a Bayesian Vector Autoregression (BVAR) model was employed, using deflated, per capita, and log-transformed variables, suitable for short macroeconomic time series. Holding other factors constant, an increase in tax expenditures leads to a reduction of 0.006331 in total factor productivity. These findings highlight the need for periodic and robust evaluations of such policies to ensure their effectiveness and to promote sustainable economic growth
References
AUTOREGRESSION, Bayesian Vector. Improving Economic Forecasting With Bayesian Vector Autoregression. Modelling Economic Series: Readings in Econometric Methodology, p. 214, 1990.
BEER, Sebastian; et al. How to Evaluate Tax Expenditures. International Monetary Fund, 2022. (IMF Working Paper, WP/22/65). Disponível em: https://www.imf.org/en/Publications/Fiscal-Affairs-Department-How-To-Notes/Issues/2022/11/How-to-Evaluate-Tax-Expenditures-525166. Acesso em: 20 out. 2025.
CHRISTIANO, Lawrence J. Searching for a Break in GNP. Journal of Business & Economic Statistics, v. 10, n. 3, p. 237-250, 1992.
Corcelli, C. (2021). GASTOS TRIBUTÁRIOS E CRESCIMENTO ECONÔMICO NO BRASIL ENTRE 2004 A 2015: UMA AVALIAÇÃO EMPÍRICA. CADERNOS DE FINANÇAS PÚBLICAS, 20(3). Disponível em: https://doi.org/10.55532/1806-8944.2020.100. Acesso em: 20 out. 2025.
DEVARAJAN, Shantayanan; et al. The composition of public expenditure and economic growth. Journal of Monetary Economics, v. 37, n. 2, p. 313–344, 1996. Disponível em: https://doi.org/10.1016/S0304-3932(96)90039-2. Acesso em: 20 out. 2025.
DICKEY, D. A. e FULLER, W.A. Distribution of the estimators for autoregressive time series with unit root. Journal of the American Statistical Association, v. 74, n. 336, p. 427-431, 1979.
______. Likelihood ratio statistics for auto-regressive time series with unit root. Econometrica, v. 49, nº 4, 1981.
DOAN, Thomas; LITTERMAN, Robert; SIMS, Christopher. Forecasting and conditional projection using realistic prior distributions. Econometric reviews, v. 3, n. 1, p. 1-100, 1984.
ELLIOT, G., ROTHENBERG, T. J. e STOCK, J. H. Efficient tests for an autoregressive unit root. Econometrica, v. 64, n. 4, p. 813-836, 1996.
ENDERS, W. Applied econometric time series. Fourth Edition. Wiley series in probability and mathematical statistics, Nova York, 4ª ed., 2015.
HOLDEN, Ken. Vector auto regression modeling and forecasting. Journal of Forecasting, v. 14, n. 3, p. 159-166, 1995.
KOOP, Gary; PESARAN, M. Hashem; POTTER, Simon M. Impulse response analysis in nonlinear multivariate models. Journal of econometrics, v. 74, n. 1, p. 119-147, 1996.
LANNE, M; SAIKKONEN, P; LÜTKEPOHL, H. Comparison of unit root tests for time series with level shifts. Journal of Time Series Analysis, 23, p. 667-685, 2002.
______. Test procedures for unit roots in time series with level shifts at unknown time. Oxford Bulletin of Economics and Statistics, v. 65, p. 91-115, 2003.
LUTKEPOHL, H. Introduction to multiple time series analysis. Berlin: Springer, 1991.
LITTERMAN, Robert B. Bayesian procedure for forecasting with vector autoregressions. Massachusetts Institute of Technology, 1980. Disponível em: https://www.scirp.org/reference/referencespapers?referenceid=2912401. Acesso em 20 out. 2025.
MA, Guangrong; et al. Do tax incentives foster productivity in China? Firm-level evidence. Economic Modelling, v. 126, 106289, 2023.
NG, S. e PERRON, P. Lag length selection and the construction of unit root tests with good size and power. Econometrica, v. 69, n. 6, p. 1519-1554, 2001.
OLIVEIRA, J. L. M. B. de; et al. GASTOS TRIBUTÁRIOS EM TRAJETÓRIA: ANÁLISE DAS POLÍTICAS DE RENÚNCIA FISCAL DA UNIÃO (1996-2023). Boletim de Conjuntura (BOCA), Boa Vista, v. 18, n. 52, p. 802–831, 2024. DOI: 10.5281/zenodo.11238703.
PERRON, P. The great crash, the oil price shock, and the unit root hypothesis. Econometrica, v. 57, n. 6. p. 1361-1401, 1989.
__________ Further evidence on breaking trend functions in macroeconomic variables. Journal of Econometrics, v. 80, n. 2, p. 355-385, 1997.
PESARAN, H. Hashem; SHIN, Y. Generalized impulse response analysis in linear multivariate models. Economics Letters, v. 58, n. 1, p. 17-29, 1998.
PHILLIPS, P. C. B. e PERRON, P. Testing for unit root in time series regression. Biometrika, v. 75, n. 2, p. 335-346, 1988.
SAID, S. e DICKEY, D. A. Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, v. 71, p. 599-607, 1984.
SAIKKONEN, Pentti; LÜTKEPOHL, Helmut. Testing for a unit root in a time series with a level shift at unknown time. Econometric theory, v. 18, n. 2, p. 313-348, 2002.
SPENCER, David E. Developing a Bayesian vector autoregression forecasting model. International Journal of Forecasting, v. 9, n. 3, p. 407-421, 1993.
SIMS, Christopher A. Macroeconomics and reality. Econometrica: journal of the Econometric Society, p. 1-48, 1980.
VOGELSANG, Timothy J.; PERRON, Pierre. Additional tests for a unit root allowing for a break in the trend function at an unknown time. International economic review, p. 1073-1100, 1998.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 CADERNOS DE FINANÇAS PÚBLICAS
This work is licensed under a Creative Commons Attribution 4.0 International License.
The articles can be copied, since quoted the source.
