Measuring the macroeconomic impact of uncertainty
AuthorTran, Trung Duc
Document TypePhD thesis
Access StatusOpen Access
© 2019 Dr. Trung Duc Tran
This dissertation provides three chapters that study uncertainty and its macroeconomics effects by using large data sets and combining both empirical and theoretical evidence. In the first chapter, we develop uncertainty indices for the United States and Australia based on freely accessible, real time Google Trends data. Our Google Trends Uncertainty (GTU) indices are found to be positively correlated to a variety of alternative proxies for uncertainty available for these two countries. VAR investigations document an economically and statistically significant contribution to unemployment dynamics by GTU shocks in the United States. In contrast, the contribution of GTU shocks to unemployment dynamics in Australia is found to be much milder and substantially lower than that of monetary policy shocks. The second chapter estimates the impact of uncertainty shocks in a disaggregate model featuring state-level economic activity and uncertainty proxies. Uncertainty is measured using Google search data. The disaggregate model is shown to capture important spillover effects which a model focusing only on aggregate data would overlook. The impact of national uncertainty shocks is heterogeneous, and on average is quantitatively less relevant as state-level uncertainty shocks in explaining the unemployment dynamics at the state level. The importance of national uncertainty shocks is found to be related to the state-specific industry compositions and fiscal deficits. The last chapter shows how unexpected changes in uncertainty about the commodity market affects real economic activity in a small commodity-exporting country. Using Australia as a case study, I first propose a novel commodity uncertainty index that is measured by the conditional volatility of the unpredictable component of commodity prices. I find that Australia has experienced more uncertainty in the commodity market recently. Second, a VAR model is estimated to examine the respective effect of commodity uncertainty shocks. The VAR evidence shows that commodity uncertainty shocks lower output, consumption, investment and net exports. In contrast, hours worked do not fall. Last, I interpret these VAR results in a non-linear multi-sector DSGE model of the Australian economy by estimating key parameters in the DSGE model to match its responses to the VAR responses. Uncertainty shocks in the DSGE model trigger a precautionary response and cause a decline in output, consumption, and investment. By contrast, hours worked do not fall, a finding that could be explained by the sectoral allocation effect.
Keywordsuncertainty shocks; VAR analysis; GVAR analysis; DSGE analysis; Google trends uncertainty indices; commodity uncertainty index
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- Economics - Theses