Forthcoming - Studies in Nonlinear Dynamics and Econometrics
In this paper, I investigate the impact of uncertainty shocks across countries in recessions by using a Smooth Transition Vector Auto Regression (STVAR) framework. I compare the responses of real variables in recessions as predicted by the STVAR model with the responses obtained from a linear SVAR model. The results emphasize asymmetries in two dimensions. First, using a sample of 8 countries, (U.S., U.K, France, Canada, Mexico, Chile, Argentina, and South Korea) I show that uncertainty shocks trigger deeper and more persistent effects on real variables in emerging countries in comparison to advanced countries during recessionary episodes. Second, I show that the linear SVAR model consistently underestimates the response of macroeconomic variables to uncertainty shocks when compared to the predictions of the recessionary regime of the STVAR model. Furthermore, using forecast error variance decomposition I show that innovations to aggregate macroeconomic uncertainty are more important towards explaining the unpredictability of real variables during recessions. The findings suggest upward surges in macroeconomic uncertainty as a driver of the excess volatility of real variables in emerging countries during recessions.
with Sylwia Nowak, International Monetary Fund
IMF Working Papers, Working Paper No. 16/228
Presented at - 4th "Continuing Education in Macroeconometrics" Workshop organized by the Reserve Bank of New Zealand, 2016
Macroeconomic forecasts are persistently too optimistic. This paper finds that common factors related to general uncertainty about U.S. macrofinancial prospects and global demand drive this overoptimism. These common factors matter most for advanced economies and G- 20 countries. The results suggest that an increase in uncertainty-driven overoptimism has dampening effects on next-year real GDP growth rates. This implies that incorporating the common structure governing forecast errors across countries can help improve subsequent forecasts.
Presented at - 4th Annual Conference - The Society for Economic Measurement - July 2017, CAFRAL conference on Financial system and Macroeconomy in Emerging Economies - Reserve Bank of India - December 2017
This paper explores the interaction of uncertainty shocks and financial frictions towards generating the excess volatility of real variables in emerging countries vis-à-vis advanced countries. I use an open economy DSGE model augmented with the financial accelerator mechanism and nominal rigidities with uncertainty evolving as the time-varying volatility of exogenous shocks. An uncertainty shock in the model triggers a precautionary response among agents and generates the simultaneous decline in GDP, investment and consumption in this open economy environment. Financial frictions interact with uncertainty to generate the amplified responses in emerging countries. Using this feature of the model I estimate key behavioral parameters that guide differences in business cycle characteristics across advanced and emerging countries using a sample of 8 countries (U.S., U.K., Canada, France, Mexico, Chile, Argentina and South Korea). The results from estimation suggest that borrowing costs for non-financial debt in emerging countries are 64-67% higher compared to advanced countries. While heightened uncertainty is common for both groups of countries in recessions, differences in financial development captured through financial frictions is key towards generating the amplified responses in emerging countries.
Perceived Uncertainty Shocks, Excess Optimism-Pessimism, and Learning in the Business Cycle
with Fabio Milani, University of California, Irvine
Presented at - 23rd International Conference Computing in Economics and Finance - July 2017
This paper studies the effects of uncertainty and waves of optimism and pessimism over the business cycle. We develop a behavioral New Keynesian macroeconomic model, in which we relax the assumption of rational expectations. Economic agents form expectations from a near-rational model with constant-gain learning. The conventional New Keynesian model is extended to allow for a potential impact of uncertainty shocks on the real economy and for shifts in sentiment, i.e. changes in aggregate optimism or pessimism in the formation of expectations that are unjustified based on current and past fundamentals. We estimate the structural model using Bayesian methods and exploiting a variety of subjective expectation series at different horizons from the Survey of Professional Forecasters. The results shed light on the overall importance of behavioral forces over the business cycles and on the relative contribution of first-moment, sentiment, shocks versus second-moment, perceived uncertainty, shocks.