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Working Paper
Estimating the Missing Intercept
Matthes, Christian; Nagasaka, Naoya; Schwartzman, Felipe (2025-10-03)
Cross-sectional data have proven to be increasingly useful for macroeconomic research. However, their use often leads to the 'missing intercept' problem in which aggregate general equilibrium effects and policy responses are absorbed into fixed effects. We present a statistical approach to jointly estimate aggregate and idiosyncratic effects within a panel framework, leveraging identification strategies coming from both cross-sectional or time-series settings. We then apply our methodology to study government spending multipliers (Nakamura and Steinsson, 2014) and wealth effects from stock ...
Working Paper , Paper 25-12

Working Paper
Estimating Impulse Response Functions When the Shock Series Is Observed
Choi, Chi-Young; Chudik, Alexander (2019-03-04)
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.
Globalization Institute Working Papers , Paper 353

Working Paper
What Do Sectoral Dynamics Tell Us About the Origins of Business Cycles?
Matthes, Christian; Schwartzman, Felipe (2019-03-29)
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, ...
Working Paper , Paper 19-9

Working Paper
Virtue or Mirage? Complexity in Exchange Rate Prediction
Kılıç, Rehim (2025-09-25)
This paper investigates whether the “virtue of complexity” (VoC), documented in equity return prediction, extends to exchange rate forecasting. Using nonlinear Ridge regressions with Random Fourier Features (Ridge–RFF), we compare the predictive performance of complex models against linear regression and the robust random walk benchmark. Forecasts are constructed across three sets of economic fundamentals—traditional monetary, expanded monetary and non-monetary, and Taylor-rule predictors—with nominal complexity varied through rolling training windows of 12, 60, and 120 months. Our ...
Finance and Economics Discussion Series , Paper 2025-089

Working Paper
Linear and nonlinear econometric models against machine learning models: realized volatility prediction
Kılıç, Rehim (2025-08-08)
This paper fills an important gap in the volatility forecasting literature by comparing a broad suite of machine learning (ML) methods with both linear and nonlinear econometric models using high-frequency realized volatility (RV) data for the S&P 500. We evaluate ARFIMA, HAR, regime-switching HAR models (THAR, STHAR, MSHAR), and ML methods including Extreme Gradient Boosting, deep feed-forward neural networks, and recurrent networks (BRNN, LSTM, LSTM-A, GRU). Using rolling forecasts from 2006 onward, we find that regime-switching models—particularly THAR and STHAR—consistently outperform ...
Finance and Economics Discussion Series , Paper 2025-061

Working Paper
Can We Take the “Stress” Out of Stress Testing? Applications of Generalized Structural Equation Modeling to Consumer Finance
Canals-Cerda, Jose J. (2021-01-29)
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 Papers , Paper 21-01

Working Paper
Fast Locations and Slowing Labor Mobility
Coate, Patrick; Mangum, Kyle (2019-12-02)
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 Papers , Paper 19-49

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