Essays on the Macroeconometrics of Uncertainty

This dissertation is a collection of three essays in Applied Macroeconomics, where I analyze the role of volatility in the economy, as well as the different macroeconomic effects of time varying policy. In order to do that, I estimate three different models that incorporate novel features that allow me to isolate those effects. The models are estimated using recently developed Bayesian techniques (Hamiltonian Monte Carlo) that allow me to consider non linearities and interesting economic features that could not have been considered in the past. In the first essay, I estimate the evolution of fiscal multipliers in the postwar era, using a time varying parameter vector autorregressive model that includes stochastic volatility. First, I find that there is significant evidence that the multiplier has changed over time, once we control for changes in volatility, but that there is no empirical support to claim that the fiscal multiplier is bigger during a recession even if we consider different components of government spending, as some recent literature has suggested. Second, I show that not accounting for stochastic volatility in the model can seriously affect both the size and the uncertainty around the fiscal multiplier. Finally, I show that government spending was extremely ineffective during the Great Recession of 2008, but taxes and transfer payments played an important role to stabilize the economy. In the second essay, I consider the contribution of changes in the conduct of Monetary Policy to the so-called "Great Moderation" (that is, the reduction of the volatility of several macroeconomic variables after 1985). I argue that a better monetary policy conduct can be responsible for the Great Moderation and the stabilization of the economy after the high inflation episodes of the 1970s, contrary to the findings of other authors. The estimation is based on a model that incorporates time varying responses of monetary policy to changes in inflation and output, and that, as a novelty, estimates the relationship between those responses and the volatility of those variables. There are two main findings. First, I show that there is evidence of a change in the conduct of monetary policy during the sample period. Second, using counterfactual exercises, I find that after Paul Volcker is appointed as Chairman of the Federal Reserve, the economy would have been more volatile if the conduct of monetary policy would not have changed. Moreover, the economy would have exhibit less uncertainty in the Pre-Volcker period if the policy conducted afterwards would have been in place. In the last essay, I propose a framework and a model-consistent estimation approach for the analysis of the dynamic consequences of changes in volatility. The proposed model is a Vector Autoregression in which time-varying volatility has a first-order impact on the observable variables. The volatility process is estimated within the model, and therefore, the proposed estimation approach does not rely on proxy measures of aggregate uncertainty as it has been generally done in the literature extant. Estimates of the proposed model using data from the United States show important quantitative and qualitative departures from estimates incorporating non-model-consistent measures of volatility. In particular, an increase in overall volatility similar to the one experienced during the Great Recession is predicted to have a strong negative and persistent impact on key macroeconomic indicators, including output, investment and the unemployment rate, and to worsen financial conditions. Moreover, a decomposition of the estimated volatility time series shows that fiscal volatility shocks are associated with important deflationary pressures, have a strong crowding out effect on investment and increase the cost of borrowing. Finally, the estimated model predicts that volatility has an asymmetric effect on the economy so that only rare shocks matter.