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Working Paper
exuber: Recursive Right-Tailed Unit Root Testing with R
http://fedora:8080/fcrepo/rest/objects/authors/; Martinez-Garcia, Enrique; Pavlidis, Efthymios (2020-05-12)
This paper introduces the R package exuber for testing and date-stamping periods of mildly explosive dynamics (exuberance) in time series. The package computes test statistics for the supremum ADF test (SADF) of Phillips, Wu and Yu (2011), the generalized SADF (GSADF) of Phillips, Shi and Yu (2015a,b), and the panel GSADF proposed by Pavlidis, Yusupova, Paya, Peel, Martínez-García, Mack and Grossman (2016); generates finite-sample critical values based on Monte Carlo and bootstrap methods; and implements the corresponding date-stamping procedures. The recursive least-squares algorithm that ...
Globalization Institute Working Papers , Paper 383

Working Paper
Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels
Smith, Ron P.; Chudik, Alexander; Pesaran, M. Hashem (2021-05-27)
This paper, using the Bewley (1979) transformation of the autoregressive distributed lag model, proposes a pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics, in the same setting as the widely used Pooled Mean Group (PMG) estimator. The Bewley transform enables us to obtain an analytical closed form expression for the PB, which is not available when using the maximum likelihood approach. This lets us establish asymptotic normality of PB as n,T→∞ jointly, allowing for applications with n and T large and of the same order of ...
Globalization Institute Working Papers , Paper 409

Working Paper
Visualization, Identification, and stimation in the Linear Panel Event-Study Design
Freyaldenhoven, Simon; Hansen, Christian; Shapiro, Jesse; Perez Perez, Jorge (2021-12-20)
Linear panel models, and the “event-study plots” that often accompany them, are popular tools for learning about policy effects. We discuss the construction of event-study plots and suggest ways to make them more informative. We examine the economic content of different possible identifying assumptions. We explore the performance of the corresponding estimators in simulations, highlighting that a given estimator can perform well or poorly depending on the economic environment. An accompanying Stata package, xtevent, facilitates adoption of our suggestions.
Working Papers , Paper 21-44

Working Paper
Incarceration, Earnings, and Race
Gordon, Grey; Jones, John Bailey; Neelakantan, Urvi; Athreya, Kartik B. (2021-07-02)
Working Paper , Paper 21-11`

Report
Identifying inflation's grease and sand effects in the labor market
Schweitzer, Mark E.; Groshen, Erica L. (1997-10-01)
Inflation has been accused of causing distortionary prices and wage fluctuations (sand) as well as lauded for facilitating adjustments to shocks when wages are rigid downwards (grease). This paper investigates whether these two effects can be distinguished from each other in a labor market by the following identification strategy: inflation-induced deviations among employer's mean wage-changes represent unintended intramarket distortions (sand), while inflation-induced, inter-occupational wage-changes reflect intended alignments with intermarket forces (grease). Using a unique 40-year panel ...
Staff Reports , Paper 31

Working Paper
Challenging Demographic Representativeness at State Borders: Implications for Policy Research
Kay, Benjamin S.; Khatiwoda, Albina (2025-03-07)
This study examines the demographic characteristics of U.S. state border counties, comparing them with those of nonborder counties. The demographic representativeness of border counties is essential for the interpretation of the results in state border-county difference-in-difference analyses, used in state policy evaluations. Our findings reveal that border counties generally have higher proportions of White, older, and disabled populations. We also see occasional instances of wide demographic differences across state boundaries. These differences potentially undermine the external validity ...
Finance and Economics Discussion Series , Paper 2025-018

Working Paper
Mean Group Distributed Lag Estimation of Impulse Response Functions in Large Panels
Chudik, Alexander; Choi, Chi-Young (2024-05-08)
This paper develops Mean Group Distributed Lag (MGDL) estimation of impulse responses of common shocks in large panels with one or two cross-section dimensions. We derive sufficient conditions for asymptotic normality, and document satisfactory small sample performance using Monte Carlo experiments. Three empirical illustrations showcase the usefulness of MGDL estimators: crude oil price pass-through to U.S. city- and product-level retail prices; retail price effects of U.S. monetary policy shocks; and house price effects of U.S. monetary policy shocks.
Globalization Institute Working Papers , Paper 423

Working Paper
Can Italy Grow Out of Its NPL Overhang? A Panel Threshold Analysis
Raissi, Mehdi; Weber, Anke; Mohaddes, Kamiar (2017-03-01)
This paper examines whether a tipping point exists for real GDP growth in Italy above which the ratio of non-performing loans (NPLs) to total loans falls significantly. Estimating a heterogeneous dynamic panel-threshold model with data on 17 Italian regions over the period 1997-2014, we provide evidence for the presence of growth-threshold effects on the NPL ratio in Italy. More specifically, we find that real GDP growth above 1.2 percent, if sustained for a number of years, is associated with a significant decline in the NPLs ratio. Achieving such growth rates requires decisively tackling ...
Globalization Institute Working Papers , Paper 309

Report
A Simple Diagnostic for Time-Series and Panel-Data Regressions
Crump, Richard K.; Gospodinov, Nikolay; Lopez Gaffney, Ignacio (2024-10-01)
We introduce a new regression diagnostic, tailored to time-series and panel-data regressions, which characterizes the sensitivity of the OLS estimate to distinct time-series variation at different frequencies. The diagnostic is built on the novel result that the eigenvectors of a random walk asymptotically orthogonalize a wide variety of time-series processes. Our diagnostic is based on leave-one-out OLS estimation on transformed variables using these eigenvectors. We illustrate how our diagnostic allows applied researchers to scrutinize regression results and probe for underlying fragility ...
Staff Reports , Paper 1132

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