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includes two lags of shocks, GDP growth, and tax revenues. F (e)is the smooth transition function14 that allows the interaction with the continuum of states in the World Uncertainty Index for particular countries.15 Our dataset covers six South Asia economies from 1990 to 2019. We rely on World Bank WDI and IMF GFS data for the main variables. The usual multiplier measures the effect of a $1 change in expenditure on the level of GDP, so we multiply the coefficients from the estimated equation by the average ratio of GDP to government expenditure or its components. Regarding the empirical strategy for the identification of exogenous expenditure shocks, we follow the well-known Blanchard and Perotti (2002) methodology that imposes the following timing assumptions: (1) government expenditure changes are allowed to contemporaneously affect economic activity and (2) it takes the government at least one period to respond to developments in the state of the economy. Originally, this approach was applied to advanced economies with quarterly data. Due to limited data availability, we implement it here with annual data. Stronger assumptions are needed for the results to be valid in this case (Beetsma et al. (2014)). But it can be argued that the approach is justified because lags in implementing fiscal policies are longer in developing countries (Diop and Ben Abdallah (2009)).
References Abiad, A., D. Furceri, and P. Topalova. 2016. “The Macroeconomic Effects of Public Investment: Evidence from Advanced Economies.” Journal of Macroeconomics, 50 (C): 224–240. Agnello, L., D. Furceri, and R. M. Sousa. 2013. “How Best to Measure Discretionary Fiscal Policy? Assessing its Impact on Private Spending.” Economic Modelling, 34 (August): 15-24. Aizenman, J., and Y. Jinjarak. 2012. “Income Inequality, Tax Base and Sovereign Spreads.” NBER Working Paper 18176, National Bureau of Economic Research, Cambridge, MA. 14 Equals 0 in our benchmark case. 15 We use country-level smoothed version of the uncertainty index, as suggested by the authors. Missing values for Bhutan are proxied by India’s data, given their strong economic ties. 114
