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Working Paper
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 ...
Working Paper
A Flexible Finite-Horizon Identification of Technology Shocks
Recent empirical studies using in finite horizon long-run restrictions question the validity of the technology-driven real business cycle hypothesis. These results have met with their own controversy, stemming from their sensitivity to changes in model specification and the general poor performance of long-run restrictions in Monte Carlo experiments. We propose an alternative identification that maximizes the contribution of technology shocks to the forecast-error variance of labor productivity at a long, but finite horizon. In small samples, our identification outperforms its in finite ...
Working Paper
Can We Take the “Stress” Out of Stress Testing? Applications of Generalized Structural Equation Modeling to Consumer Finance
Financial firms, and banks in particular, rely heavily on complex suites of interrelated statistical models in their risk management and business reporting infrastructures. Statistical model infrastructures are often developed using a piecemeal approach to model building, in which different components are developed and validated separately. This type of modeling framework has significant limitations at each stage of the model management life cycle, from development and documentation to validation, production, and redevelopment. We propose an empirical framework, spurred by recent developments ...
Working Paper
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, ...
Working Paper
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 ...
Working Paper
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 ...
Working Paper
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 ...
Working Paper
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 ...
Journal Article
Tracking U.S. GDP in Real Time
Measuring the current state of the U.S. economy in real time is an important but challenging task for monetary policymakers. The most comprehensive measure of the state of the economy?real gross domestic product?is available at a relatively low frequency (quarterly) and with a significant delay (one month). To obtain more timely assessments of the state of the economy, the Federal Reserve Bank of Kansas City has developed a GDP tracking model that combines new econometric methods with two conventional approaches to estimating GDP. {{p}} Taeyoung Doh and Jaeheung Bae review the Kansas City Fed ...
Working Paper
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 ...