Back Matter

IX. References

  • Batini, N., L. Eyraud, L. Forni, and A. Weber, 2014, “Fiscal Multipliers: Size, Determinants, and Use in Macroeconomic Projects,” IMF Technical Notes and Manuals No. 14/4 (Washington: International Monetary Fund).

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  • Ilzetzki, E., 2011, “Fiscal Policy and Debt Dynamics in Developing Countries,” Policy Research Working Paper Series No. 5666 (Washington: The World Bank).

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  • Ilzetzki E., E. G. Mendoza, and C. A. Vegh, 2013, “How Big (Small?) Are Fiscal Multipliers?”, Journal of Monetary Economics, Vol. 60, pp. 23954.

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  • International Monetary Fund, 2008, World Economic Outlook, October 2008, Chapter 5, “Fiscal Policy as a Countercyclical Tool,” World Economic and Financial Surveys (Washington: International Monetary Fund).

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  • Mendonça, M. J. C., L. A. Medrano, and A. Sachsida, 2009, “Avaliando os efeitos da política fiscal no Brasil: resultados de um procedimento de identificação agnóstica,” Texto para Discussão IPEA, No. 1377.

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  • Mertens, R. and M. O. Ravn, 2012, “A Reconciliation of SVAR and Narrative Estimates of Tax Multipliers,” CEPR Discussion Paper No. 8973 (London: Center for Economic Policy Research).

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  • Oreng, M., 2012, “Estimando o impacto da política Fiscal no Brazil: 2004 a 2011,” mimeo.

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  • Peres, M. A., 2006, “Os efeitos dinâmicos da política fiscal sobre a atividade econômica: um estudo para o caso brasileiro,” Dissertação (Mestrado em Economia), Departamento de Economia, Universidade de Brasília.

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  • Ramey, V.A, and S. Zubairy, 2014, “Government Spending Multipliers in Good Times and in Bad: Evidence from U.S. Historical Data,” NBER Working Paper, No. 20719.

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1

The model includes one lag of all variables, as suggested by the Schwarz-Bayesian criterion.

2

The natural logarithm is taken of each variable prior to estimation, except the interest rate, which is left in levels (see the appendix for a more detailed description of the data). The VAR is estimated in levels and is stationary; it has a well-defined vector-moving-average representation and the impulse response functions are not explosive.

3

The minimum wage directly influences with social welfare spending, given that the minimum benefit is, by a constitutional requirement, linked to the minimum wage. Higher benefits are indirectly linked to the minimum wage, through its impact on average wages.

4

Bootstrapping involves the following steps: 1) estimate the model parameters and obtain the residuals; 2) resample (with replacement) from the estimated residuals and simulate the model using the parameters from 1; 3) re-estimate the model, saving the parameters; 4) repeat steps 2 and 3 a large number of times.

5

The lower spending multipliers in EMEs has been often attributed to relative expenditure inefficiencies and the difficulty of unwinding expenditure growth, both of which of potential relevance in Brazil.

6

Model estimates are based on central government quarterly fiscal data (see appendix for details), which is available from 1995 onwards. However, there is no information on public investment at quarterly frequency before 2006.

7

The pre-crisis subsample ends in 2007Q4.

8

The size of the output gap is not included in the framework; thus Figure 3 plots average multipliers over the cycle. Supply constraints in the post crisis period can, however, have contributed to lower multipliers. We do not expect such impact be significant, though, as revenue multipliers would also be lower, which does not seem to be the case.

Fiscal Multipliers for Brazil
Author: Mr. Troy D Matheson and Ms. Joana Pereira