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Working Paper
Growth-at-Risk is Investment-at-Risk
We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role.
Working Paper
Simultaneous Spatial Panel Data Models with Common Shocks
I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroskedasticity result in a large number of incidental parameters. I propose two estimation approaches, a quasi-maximum likelihood (QML) method and an iterative generalized principal components (IGPC) method. I develop full inferential theories for the estimation approaches and study the trade-off between the model specifications and their respective asymptotic properties. I further ...
Working Paper
Metro Business Cycles
We construct monthly economic activity indices for the 50 largest U.S. metropolitan statistical areas (MSAs) beginning in 1990. Each index is derived from a dynamic factor model based on twelve underlying variables capturing various aspects of metro area economic activity. To accommodate mixed-frequency data and differences in data-publication lags, we estimate the dynamic factor model using a maximum- likelihood approach that allows for arbitrary patterns of missing data. Our indices highlight important similarities and differences in business cycles across MSAs. While a number of MSAs ...
Working Paper
Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models
We develop a framework for measuring and monitoring business cycles in real time. Following a long tradition in macroeconometrics, inference is based on a variety of indicators of economic activity, treated as imperfect measures of an underlying index of business cycle conditions. We extend existing approaches by permitting for heterogenous lead-lag patterns of the various indicators along the business cycles. The framework is well suited for high-frequency monitoring of current economic conditions in real time - nowcasting - since inference can be conducted in presence of mixed frequency ...
Working Paper
International Stock Comovements with Endogenous Clusters
We examine international stock return comovements of country-industry portfolios. Our model allows comovements to be driven by a global and a cluster component, with the cluster membership endogenously determined. Results indicate that country-industry portfolios tend to cluster mainly within geographical areas that can include one or more countries. The cluster compositions substantially changed over time, with the emergence of clusters among European countries from the early 2000s. The cluster component was the main driver of country-industry portfolio returns for most of the sample, except ...
Working Paper
A Generalized Factor Model with Local Factors
I extend the theory on factor models by incorporating local factors into the model. Local factors only affect an unknown subset of the observed variables. This implies a continuum of eigenvalues of the covariance matrix, as is commonly observed in applications. I derive which factors are pervasive enough to be economically important and which factors are pervasive enough to be estimable using the common principal component estimator. I then introduce a new class of estimators to determine the number of those relevant factors. Unlike existing estimators, my estimators use not only the ...
Working Paper
International Stock Comovements with Endogenous Clusters
We use an endogenous cluster factor model to examine international stock return comovements of country-industry portfolios. Our model allows country-industry portfolio comovements to be driven by a global and a cluster component, with the cluster membership endogenously determined. Results indicate that country-industry portfolios tend to cluster mainly within geographical areas that can include one or more countries. The cluster component was the main driver of country-industry portfolio returns for most of the sample, except from mid-2000 to mid-2010s when the global component had a more ...
Working Paper
In-migration and Dilution of Community Social Capital
Consistent with predictions from the literature, we find that higher levels of in-migration dilute multiple dimensions of a community's level of social capital. The analysis employs a 2SLS methodology to account for potential endogeneity of migration.
Working Paper
House Price Growth Interdependencies and Comovement
This paper examines house price diffusion across metropolitan areas in the United States. We develop a generalization of the Hamilton and Owyang (2012) Markov-switching model, where we incorporate direct regional spillovers using a spatial weighting matrix. The Markov-switching framework allows consideration for house price movements that occur due to similar timing of downturns across MSAs. The inclusion of the spatial weighting matrix improves fit compared to a standard endogenous clustering model. We find seven clusters of MSAs that experience idiosyncratic recessions plus one distinct ...
Working Paper
A Global Trade Model for the Euro Area
We propose a model for analyzing euro area trade based on the interaction between macroeconomic and trade variables. First, we show that macroeconomic variables are necessary to generate accurate short-term trade forecasts; this result can be explained by the high correlation between trade and macroeconomic variables, with the latter being released in a more timely manner. Second, the model tracks well the dynamics of trade variables conditional on the path of macroeconomic variables during the great recession; this result makes our model a reliable tool for scenario analysis. Third, we ...