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Mr. Raphael A Espinoza
In this paper, we estimate the aggregate and sectoral fiscal multipliers of EU Structural Investment (ESI) Funds and of public investment at the EU level. We complement these results with a specific application to the case of Slovenia. We first analyze aggregate data and find large and significant multipliers and strong crowding-in of private investment. Our main findings show that positive shocks to ESI Funds are followed by an increase in output that ranges from 1.2 percent on impact, to 1.8 percent after 1 year, and by an increase in private investment between 0.7 and 0.8 percent of GDP. We address country heterogeneity by dividing countries according to key characteristics that have been known to affect multipliers. In particular, we find higher multipliers in a group of CEE countries that are important recipients of European funds and are characterized by fixed exchange rate regimes and sound public investment governance (e.g. Croatia and Slovenia). We also complement the aggregate analysis by estimating the effect of different types of public investment and the effect of public investment on different sectors of the economy.
Mr. Raphael A Espinoza

estimating the effect of different types of public investment and the effect of public investment on different sectors of the economy. JEL Classification Numbers: E62; H30 Keywords: fiscal multiplier; European Structural Investment funds; private investment; Slovenia Author’s E-Mail Address: ldurand@imf.org ; respinoza@imf.org Contents Abstract I. Introduction II. Literature Review III. Fiscal Multipliers: An IV approach IV. Aggregate Multipliers V. Sectoral Multipliers A. Crowding-in of Investment B. Effect on Gross Value Added (Sectoral

Sophia Chen, Mr. Lev Ratnovski, and Pi-Han Tsai

secretaries Tables Table 1. Summary statistics Table 2. Appointments of party secretaries and provincial economic conditions Table 3. Full sample results Table 4. Early and late subsamples results Table 5. Weighted results Table 6. Sectoral multipliers References

Vincent Belinga and Mr. Constant A Lonkeng Ngouana

-slack (extended sample through 2012Q4) A1. GDP Cumulative and Peak Multipliers with Alternative Measures of Inflation in the Taylor Rule A2. GDP Cumulative and Peak Multipliers with Different Values of the Smoothing Parameter, γ A3. Cumulative and Peak Sectoral Multipliers (surprise federal government spending) Figures 1. The Fed Funds Rate and the Likelihood of Being in the Accommodative State 2. Predictability of Innovations from the Cholesky Decomposition 3. IRFs of Federal Government Spending and Output to Federal Government Spending Shocks 4. IRFs of

Sophia Chen, Mr. Lev Ratnovski, and Pi-Han Tsai

output sums up to aggregate output, the effects on all sectors also sum up to the aggregate multiplier. For this reason, we refer to β G and β CR as sectoral contributions to the aggregate multipliers (“sectoral multipliers”). The results for sectoral multipliers are shown in Table 6 . Panel A reports the results for the entire sample. Panel B reports the results for the 2010-2015 period. We report the results for construction (columns 1-2), manufacturing (columns 3-4), and services excluding financials (columns 5-6). As before, we report the OLS estimates first

Sophia Chen, Mr. Lev Ratnovski, and Pi-Han Tsai
We jointly estimate credit and fiscal multipliers in China. We use the tenure of the provincial party secretary, interacted with the type of stimulus used in other provinces, to obtain separate instruments for provincial credit and government expenditure. We estimate a fiscal multiplier of 0.8 and a credit multiplier of 0.2 in 2001-2015. The multipliers have changed over time. The fiscal multiplier has increased from 0.75 in 2001-2008 to 1.4 in 2010-2015. The credit multiplier has declined from 0.17 to zero over the same periods. Our results suggest that reducing credit growth in China is unlikely to disrupt output growth, whereas fiscal policy may be effective in supporting macroeconomic adjustment.
Mr. Raphael A Espinoza

-specific macroeconomic and financial characteristics play in shaping the response of economies to fiscal policy. Examples include Auerbach and Gorodnichenko (2012) , who study sectoral multipliers using government spending disaggregated between military and non-military spending, Ilzetzki, Mendoza and Vegh (2013) , who highlight that the level of economic development, the exchange rate regime, trade openness and public debt, all influence the macroeconomic response to fiscal shocks, and Espinoza, Gamboa-Arbelaez and Sy (2020) , who emphasize that leverage and financial constraints