Dalibor Stevanovic

Factor-Augmented VARMA Models With Macroeconomic Applications

We study the relationship between vector autoregressive moving-average (VARMA) and factor representations of a vector stochastic process. We observe that, in general, vector time series and factors cannot both follow finite-order VAR models. Instead, a VAR factor dynamics induces a VARMA process, while a VAR process entails VARMA factors. We propose to combine factor and VARMA modeling by using factor-augmented VARMA (FAVARMA) models. This approach is applied to forecasting key macroeconomic aggregates using large U.S. and Canadian monthly panels. The results show that FAVARMA models yield substantial improvements over standard factor models, including precise representations of the effect and transmission of monetary policy.

An Empirical Study of Credit Shock Transmission in a Small Open Economy

In this paper, we identify and estimate the dynamic effects of foreign (US) and national (Canadian) credit shocks in a small open economy. We use standard credit spreads as proxies to the external finance premium. Our first result suggests that the US and Canadian credit spreads contain substantial forecasting power for several measures of the Canadian real economic activity, especially during the recent financial crisis and its aftermath. Secondly, an adverse US credit shock generates a significant and persistent economic slowdown in Canada: the national external finance premium rises immediately while interest rates, credit aggregates, output and employment indicators decline. Variance decomposition reveals that credit shocks have a sizeable effect on real activity measures, leading indicators and credit spreads. Yet, the unexpected shocks in domestic credit spreads are not able to generate any significant dynamic response of the real activity once we control for the US credit market conditions.

Common time variation of parameters in reduced-form macroeconomic models

Abstract Standard time varying parameter (TVP) models usually assume independent stochastic processes. In this paper, I show that the number of underlying sources of parameters’ time variation is likely to be small, and provide empirical evidence for factor structure amongst TVPs of popular macroeconomic models. In order to test for the presence of low dimension sources of time variation in parameters and estimate their magnitudes, I develop the factor time varying parameter (Factor-TVP) framework and apply it to [Primiceri, G.E. (2005), “Time Varying Structural Vector Autoregressions and Monetary Policy,” The Review of Economic Studies, 72, 821–852] monetary TVP-VAR model. I find that one factor explains most of the variability in VAR coefficients, while the stochastic volatility parameters vary independently. The inclusion of post-“Great Recession” data causes an important change within VAR coefficients and the procedure suggests two factors. The roots of variability in the VAR parameters are likely to have derived from the financial markets and the real sector. The TVP factors have predictive power for a large number of output, investment, and employment series, as well as for the term structure of interest rates.

Dynamic Effects of Credit Shocks in a Data-Rich Environment

ABSTRACT We examine the dynamic effects of credit shocks using a large dataset of U.S. economic and financial indicators in a structural factor model. An identified credit shock resulting in an unanticipated increase in credit spreads causes a large and persistent downturn in indicators of real economic activity, labor market conditions, expectations of future economic conditions, a gradual decline in aggregate price indices, and a decrease in short- and longer-term riskless interest rates. Our identification procedure allows us to perform counterfactual experiments which suggest that credit spread shocks have largely contributed to the deterioration in economic conditions during the Great Recession. Recursive estimation of the model reveals relevant instabilities since 2007 and provides further evidence that monetary policy has partly offset the effects of credit shocks on economic activity. Supplementary materials for this article are available online.

The Macroeconomic Effects of Shocks to Large Banks’ Capital

We propose a simple approach to quantifying the macroeconomic effects of shocks to large banks’ leverage. We first estimate a standard dynamic model of leverage targeting at the bank level and use it to derive an aggregate measure of the economic capital buffer of large US bank holding corporations. We then evaluate the response of key macro variables to a shock to this aggregate bank capital buffer using standard monetary VAR models. We find that shocks to the capital of large US banks explain a substantial share of the variance of credit to firms and real activity.