Abiad, A., D. Furceri., Topalova, P., 2016. “The Macroeconomic Effects of Public Investment: Evidence from Advanced Economies.” Journal of Macroeconomics, 50: pp. 224–240.
Auerbach, A., Gorodnichenko, Y., (2012), “Measuring the Output Responses to Fiscal Policy,” American Economic Journal: Economic Policy 4(2): pp. 1–27.
Auerbach, A., Gorodnichenko, Y., (2013), “Fiscal Multipliers in Recession and Expansion,” In Fiscal Policy After the Financial Crisis, edited by Alberto Alesian and Francesco Giavazzi, pp. 63–98. University of Chicago Press.
Barrell, R., D. Holland, and I. Hurst, 2012, “Fiscal Consolidation: Part 2. Fiscal Multipliers and Fiscal Consolidations,” OECD Economics Department Working Paper No. 933 (Paris: Organisation for Economic Co-operation and Development).
Blanchard, O. and R. Perotti, “An empirical characterization of the dynamic effects of changes in government spending and taxes on output,” the Quarterly Journal of economics 117 (2002), pp. 1329–1368.
Blanchard, O., and D. Leigh, 2013, “Growth Forecast Errors and Fiscal Multipliers,” American Economic Review, Vol. 103, No. 3, pp. 117–20.
Boeckx, J, M. Dossche, A. Galesi, B. Hofmann, G. Peersman, 2019, “Do SVAR with sign restrictions not identify unconventional monetary policy shocks?,” BIS Working Papers No 788.
Born, B. F. Juessen, G.J. Mueller, 2013, “Exchange Rate Regimes and Fiscal Multipliers,” Journal of Economic Dynamics and Control, Vol. 37, No. 2, pp. 446–65.
Budescu, D.V. (1993) Dominance Analysis: A New Approach to the Problem of Relative Importance of Predictors in Multiple Regression. Psychological Bulletin, 114, 542–551.
Cole, H. L., and L.E. Ohanian, 2004, “New Deal Policies and the Persistence of the Great Depression: A General Equilibrium Analysis,” Journal of Political Economy, Vol. 112, No. 4, pp. 779–816.
Dabla-Norris, E., Brumby, J., Kyobe, A., Mills, Z., and Chris Papageorgiou, 2011, “Investing in Public Investment: An Index of Public Investment Efficiency,” IMF Working Paper 11/37.
Dolls, M., C. Fuest, and A. Peichl, 2012. “Automatic Stabilizers and Economic Crisis: US vs. Europe,” Journal of Public Economics, Vol. 96, pp. 279–94.
Furceri, D., B. Li, 2017, “The Macroeconomic (and Distributional) Effects of Public Investment in Developing Economies.” International Monetary Fund Working Paper, No. 17–217.
Ilzetzki E., E. G. Mendoza, and C. A. Vegh, 2013, “How Big (Small?) Are Fiscal Multipliers?” Journal of Monetary Economics, Vol. 60, pp. 239–54.
Ilzetzki, E., C. M. Reinhart, and K. S. Rogoff, 2017, “Exchange Arrangements Entering the 21st Century: Which Anchor Will Hold?” NBER Working Paper No. 23134.
Izquierdo, A., R. Lama, J. P. Medina, J. Puig, D. Riera-Crichton, C. Vegh, and G. Vuletin, “Is the Public Investment Multiplier Higher in Developing Countries? An Empirical Exploration,” IMF Working Paper (forthcoming).
Jordà, Ò., (2005), “Estimation and Inference of Impulse Responses by Local Projections,” American Economic Review 95(1): pp. 161–182.
Kirchner, M., J. Cimadomo, and S. Hauptmeier, 2010, “Transmission Of Government Spending Shocks In The Euro Area: Time Variation and Driving Forces,” ECB Working Paper Series 1219 (Frankfurt: European Central Bank).
Koh, W. C., (2017), “Fiscal multipliers: new evidence from a large panel of countries,” Oxford Economic Papers, Vol. 69 (3), pp. 569–590,
Kraay, A. (2012). How large is the government spending multiplier? Evidence from World Bank lending. The Quarterly Journal of Economics, 127(2), pp. 829–887.
Kraay, A. (2014). Government spending multipliers in developing countries: evidence from lending by official creditors. American Economic Journal: Macroeconomics, 6(4), pp. 170–208.
Leeper, E. M., Richter, A. W., Walker, T. B., 2012. Quantitative effects of fiscal foresight. American Economic Journal: Economic Policy, 4 (2), pp.115–144.
Miyamoto, Wataru, Thuy Lan Nguyen, and Viacheslav Sheremirov. “The effects of government spending on real exchange rates: Evidence from military spending panel data.” Journal of International Economics 116 (2019): pp. 144–157.
Ramey, V. A. and M. D. Shapiro, “Costly capital reallocation and the effects of government spending,” in Carnegie-Rochester Conference Series on Public Policy, Vol. 48 (Elsevier, 1998), pp. 145–194.
Ramey, V. A., Zubairy, V. (2018), “Government Spending Multipliers in Good Times and in Bad: Evidence from U.S. Historical Data,” Journal of Political Economy, 126:2, pp. 850–901.
Annex I. Impacts of Fiscal Spending Shocks on Private Consumption and Investment
Annex II. Impacts of Fiscal Spending Shocks on Private Consumption and Investment in LICs During Booms
Annex III. Output Effects of Fiscal Spending Shocks Under Floating Exchange Rate Regimes in LICs
Annex IV. Possible Determinants of the Size of Fiscal Multiplier
We are grateful for helpful comments and suggestions from Vitor Gaspar, Nikolay Gueorguiev, Celine Allard, Sandesh Dhungana, Giovanni Melina, Kenji Moriyama, Chris Papageorgiou, Marcos Poplawski Ribeiro, Hoda Selim, and participants of IMF’s Fiscal Affairs Department seminar. The authors are grateful to Paulomi Mehta for her research assistance, and Sofia Cerna Rubinstein and Julie Vaselopulos for editorial assistance.
IMF (2017) finds that fiscal multipliers in sub-Saharan Africa tend to be smaller than those typically identified in AEs or EMs.
In this paper, fiscal multipliers and output effects of government spending shocks are used interchangeably. In general, fiscal multipliers are defined as the ratio of a change in output to a discretionary change in government spending. For this purpose, this paper—following the methodologies widely used in the literature—identifies government spending shocks as forecast errors of government spending and estimate their impacts on output. Thus, in an attempt to describe the exercise more accurately, this paper predominantly uses the term “the output effects of government spending shocks”.
According to Keynesian models, trade linkages reduce the effectiveness of fiscal policy. Ilzetzki et al., (2013) support this conventional view. They find that on average fiscal multipliers are smaller in economics with more open economies. In contrast, Cacciatore and Traum (2019) show that fiscal multipliers can be larger in economies more open to trade in a simple two-country, two-good model. Koh (2017) finds that fiscal multipliers are not necessarily smaller in countries that are relatively open to trade by using panel data analysis of 120 countries over the period 2006–2014.
Shen et al., (2018) provides a conceptual framework to analyze the fiscal policy effects in LICs by developing a New Keynesian small open economy model.
Kraay (2014)’s finding on countries with flexible exchange rate regimes differs from other analyses (e.g., Born et al., (2013) and Ilzetzki et al., (2013)). They find that fiscal multipliers are higher under fixed exchange rate regimes (consistent with the prediction of the Mundell-Fleming model with capital mobility).
Economic agents receive signals about future changes in fiscal spending policy before they actually take place, which may affect their decisions. This is known as the fiscal foresight problem. Also, fiscal policy is likely to be a response to the current state of economy even if the policy is unanticipated. The forecast error approach reduces the probability that the fiscal policy shock contains information about the current business cycle since most of the information about the business cycle in year t would be contained in the forecast (published in October), not in the forecast errors.
It is important to keep in mind the caveat associated with the shock identification. As Jordà’s (2005) local projection does not impose structure on the impulse response functions, this method is more robust to mis-specification than standard VAR models, if the shocks are well-identified. However, the challenge to identify fiscal policy shocks in a satisfactory manner remains.
We use the actual GDP as denominator for both actual and forecast series.
Estimated fiscal multipliers in AEs are somewhat lower than those in the literature. This may reflect differences in shock identification methods and specification of empirical models.
This is broadly consistent with the previous empirical studies finding larger fiscal multipliers in AEs than those in developing countries.
It is important to note that an overlap of the confidence interval by itself does not imply that the differences are statistically insignificant. For example, Boeckx et al. (2019) show that the difference between the impulse responses are statistically significant though the confidence intervals overlap. To check whether the differences of output effects between LICs and AEs (EMs) are statistically significant, we nest the estimation for AEs and LICs within the single model and calculate the differences between output responses and the confidence bands of the differences. The differences are statistically significant at 5 percent level for AEs and LICs after t=2, while the differences for AEs and LICs are not statistically significant at any horizon.
Instead of using the output gap, we identify the state of the economy using GDP growth as the output gap is unobservable and subject to substantial and frequent revisions, and thus estimates of output gaps are typically surrounded by great uncertainty. However, as noted below, similar results are obtained when we use the estimated output gap as the business cycle indicator.
We split the sample into economies with fixed and flexible exchange rate regimes as in Ilzetzki et al., (2011). That is, based on the de facto exchange rate arrangement classification of Ilzetzki et al., (2017), who define fixed exchange rate regimes as no separate legal tender, hard pegs, crawling pegs, or de facto/pre announced horizontal bands or crawling bands that are narrower than or equal +/-2 percent.
In contrast, as noted above, Kraay (2014) finds that fiscal multipliers are higher in countries with flexible exchange rate regimes.
As the capital inflow is small in many LICs, this channel may be limited.
See Footnote 5 above for details.
Botero et al., (2004) also mention that they would have a measurement error problem because some employment is informal, especially in developing countries.
IMF (2014) points out that the fiscal stabilizer is more effective in AEs than in EMs and LICs, reflecting the characteristics of these developing countries such as less potent fiscal instruments and lower priorities of stabilization.
The threshold is a median for the business cycle indicator and the institutional quality indicator. When k = exchange rate regime,
The results of these robustness checks are available upon request.