Fast Locations and Slowing Labor Mobility
Declining internal migration in the United States is driven by increasing home attach-ment in locations with initially high rates of population turnover. These ?fast? locations were the population growth destinations of the 20th century, where home attachments were low, but have increased as regional population growth has converged. Using a novel measure of attachment, this paper estimates a structural model of migration that distinguishes moving frictions from home utility. Simulations quantify candidate explanations of the decline. Rising home attachment accounts for most of the decline not ...
Piecewise-Linear Approximations and Filtering for DSGE Models with Occasionally Binding Constraints
We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with an occasionally binding constraint. The functional form of the decision rules allows us to derive a conditionally optimal particle filter (COPF) for the evaluation of the likelihood function that exploits the structure of the solution. We document the accuracy of the likelihood approximation and embed it into a particle Markov chain Monte Carlo algorithm to conduct Bayesian estimation. Compared with a standard bootstrap particle filter, the COPF significantly reduces ...
What Do Sectoral Dynamics Tell Us About the Origins of Business Cycles?
We use economic theory to rank the impact of structural shocks across sectors. This ranking helps us to identify the origins of U.S. business cycles. To do this, we introduce a Hierarchical Vector Auto-Regressive model, encompassing aggregate and sectoral variables. We find that shocks whose impact originate in the "demand" side (monetary, household, and government consumption) account for 43 percent more of the variance of U.S. GDP growth at business cycle frequencies than identified shocks originating in the "supply" side (technology and energy). Furthermore, corporate financial shocks, ...
Drifts, Volatilities, and Impulse Responses Over the Last Century
How much have the dynamics of U.S. time series and in particular the transmission of innovations to monetary policy instruments changed over the last century? The answers to these questions that this paper gives are "a lot" and "probably less than you think," respectively. We use vector autoregressions with time-varying parameters and stochastic volatility to tackle these questions. In our analysis we use variables that both influenced monetary policy and in turn were influenced by monetary policy itself, including bond market data (the difference between long-term and short-term nominal ...
Monetary Policy Spillovers, Capital Controls and Exchange Rate Flexibility, and the Financial Channel of Exchange Rates
We assess the empirical validity of the trilemma (or impossible trinity) in the 2000s for a large sample of advanced and emerging market economies. To do so, we estimate Taylor-rule type monetary policy reaction functions, relating the local policy rate to real-time forecasts of domestic fundamentals, global variables, as well as the base-country policy rate. In the regressions, we explore variations in the sensitivity of local to base-country policy rates across different degrees of exchange rate flexibility and capital controls. We find that the data are in general consistent with the ...
Evidence on the Production of Cognitive Achievement from Moving to Opportunity
This paper performs a subgroup analysis on the effect of receiving a Moving to Opportunity (MTO) housing voucher on test scores. I find evidence of heterogeneity by number of children in the household in Boston, gender in Chicago, and race/ethnicity in Los Angeles. To study the mechanisms driving voucher effect heterogeneity, I develop a generalized Rubin Causal Model and propose an estimator to identify transition-specific Local Average Treatment Effects (LATEs) of school and neighborhood quality. Although I cannot identify such LATEs with the MTO data, the analysis demonstrates that ...
Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks
Financial globalisation and spillovers have gained immense prominence over the last two decades. Yet, powerful cross-border financial spillover channels have not become a standard element of structural monetary models. Against this background, we hypothesise that New Keynesian DSGE models that do not feature powerful financial spillover channels confound the effects of domestic and foreign disturbances when confronted with the data. We derive predictions from this hypothesis and subject them to data on monetary policy shock estimates for 29 economies obtained from more than 280 monetary ...
Estimating Impulse Response Functions When the Shock Series Is Observed
We compare the finite sample performance of a variety of consistent approaches to estimating Impulse Response Functions (IRFs) in a linear setup when the shock of interest is observed. Although there is no uniformly superior approach, iterated approaches turn out to perform well in terms of root mean-squared error (RMSE) in diverse environments and sample sizes. For smaller sample sizes, parsimonious specifications are preferred over full specifications with all ?relevant? variables.
Dominant-Currency Pricing and the Global Output Spillovers from U.S. Dollar Appreciation
Different export-pricing currency paradigms have different implications for a host of issues that are critical for policymakers such as business cycle co-movement, optimal monetary policy, optimum currency areas and international monetary policy coordination. Unfortunately, the literature has not reached a consensus on which pricing paradigm best describes the data. Against this background, we test for the empirical relevance of dominant-currency pricing (DCP). Specifically, we first set up a structural three-country New Keynesian dynamic stochastic general equilibrium model which nests DCP, ...
BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R
This document introduces the R library BGVAR to estimate Bayesian global vector autoregressions (GVAR) with shrinkage priors and stochastic volatility. The Bayesian treatment of GVARs allows us to include large information sets by mitigating issues related to overfitting. This improves inference and often leads to better out-of-sample forecasts. Computational efficiency is achieved by using C++ to considerably speed up time-consuming functions. To maximize usability, the package includes numerous functions for carrying out structural inference and forecasting. These include generalized and ...