Alexander Chudik

Federal Reserve Bank of Dallas · Research

This paper provides estimates of COVID-19 transmission rates and explains their evolution for selected European countries since the start of the pandemic taking account of changes in voluntary and government mandated social distancing, incentives to comply, vaccination and the emergence of new variants. Evidence based on panel data modeling indicat...

This article introduces the idea of self-instrumenting endogenous regressors in settings when the correlation between these regressors and the errors can be derived and used to bias-correct the moment conditions. The resulting bias-corrected moment conditions are less likely to be subject to the weak instrument problem and can be used on their own...

This paper develops a threshold-augmented dynamic multi-country model (TGVAR) to quantify the macroeconomic effects of the Covid-19 pandemic. We show that there exist threshold effects in the relationship between output growth and excess global volatility at individual country levels in a significant majority of advanced economies and several emerg...

This paper uses a threshold-augmented Global VAR model to quantify the macroeconomic effects of countries’ discretionary fiscal actions in response to the Covid-19 pandemic and its fallout. Our results are threefold: (1) fiscal policy is playing a key role in mitigating the effects of the pandemic; (2) all else equal, countries that implemented lar...

This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of time-varying parameters, including the use of rolling windows and exponential down-weighting. However, these studies start with a given model specificat...

This paper proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions (IRFs) in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is observed at a lower frequency (as a temporally aggregated or sequentially sampled variable), (iii) the data generating process (DGP) is given by a...

The growth of globalization in recent decades has increased the importance of external factors as drivers of the business cycle in many countries. Globalization affects countries not just at the macro level but at the level of states and metro areas as well. This paper isolates the relative importance of global, national and region‐specific shocks...

This paper considers a modification of the standard Susceptible-Infected-Recovered (SIR) model of epidemic that allows for different degrees of compulsory as well as voluntary social distancing. It is shown that the fraction of population that self-isolates varies with the perceived probability of contracting the disease. Implications of social dis...

Using quarterly data for 42 products over the period 1990‐2015, we find that there has been a large and growing dispersion of purchasing power across U.S. cities since 1990 and the dispersion varies widely across products. We also find that total factor productivity (TFP) shock precedes or predicts the rise in regional inequality of purchasing powe...

This paper considers a modification of the standard Susceptible-Infected-Recovered (SIR) model of epidemic that allows for different degrees of compulsory as well as voluntary social distancing. It is shown that the fraction of population that self-isolates varies with the perceived probability of contracting the disease. Implications of social dis...

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...

This paper extends the mean group (MG) estimator for random coefficient panel data models by allowing the underlying individual estimators to be weakly cross correlated. This can arise, for example, in panels with spatially correlated errors. We establish that the MG estimator is asymptotically correctly centered, and its asymptotic covariance matr...

This paper provides an alternative approach to penalized regression for model selection in the context of high-dimensional linear regressions where the number of covariates is large, often much larger than the number of available observations. We consider the statistical significance of individual covariates one at a time, while taking full account...

This paper studies the relationship between public debt expansion and economic growth and investigates whether the debt-growth relation varies with the level of indebtedness.We contribute theoretically by developing tests for threshold effects in the context of dynamic heterogeneous panel data models with cross-sectionally dependent errors. In the...

This paper considers estimation and inference in linear panel regression models with lagged dependent variables and/or other weakly exogenous regressors when N (the cross‐section dimension) is large relative to T (the time series dimension). It allows for fixed and time effects (FE‐TE) and derives a general formula for the bias of the FE‐TE estimat...

Forecasts of global growth have historically been imprecise, punctuated by periods of optimism and pessimism. Inaccuracy in forecasting partly reflects quantifiable risks to the global outlook as well as economic uncertainty.

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T) and...

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised regression has become the de facto benchmark technique...

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised regression has become the de facto benchmark technique...

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised regression has become the de facto benchmark technique...

This paper studies the long-run impact of public debt expansion on economic growth and investigates whether the debt-growth relation varies with the level of indebtedness. Our contribution is both theoretical and empirical. On the theoretical side, we develop tests for threshold effects in the context of dynamic heterogeneous panel data models with...

This paper studies the long-run impact of public debt expansion on economic growth and investigates whether the debt-growth relation varies with the level of indebtedness. Our contribution is both theoretical and empirical. On the theoretical side, we develop tests for threshold effects in the context of dynamic heterogeneous panel data models with...

The Global Vector Autoregressive (GVAR) approach has proven to be a very useful approach to analyse interactions in the global macroeconomy and other data networks where both the cross-section and the time dimensions are large. This paper surveys the latest developments in the GVAR modelling, examining both the theoretical foundations of the approa...

This paper extends the Common Correlated Effects (CCE) approach developed by Pesaran (2006) to heterogeneous panel data models with lagged dependent variable and/or weakly ex-ogenous regressors. We show that the CCE mean group estimator continues to be valid but the following two conditions must be satisfied to deal with the dynamics: a sufficient...

This paper studies the influence of aggregating across space when (i) testing the PPP theory or more generally pair-wise cointegration and (ii) evaluating the PPP puzzle. Our contribution is threefold: we show that aggregating foreign data and applying an ADF test may lead to erroneously reject the PPP hypothesis. We then show, on the basis of theo...

This paper uncovers the response pattern to global shocks of euro area countries' real effective exchange rates before and after the start of Economic and Monetary Union (EMU), a largely open ended question when the euro was created. We apply to that end a newly developed methodology based on high dimensional VAR theory. This approach features a do...

This paper provides an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with weakly exogenous regressors. The paper begins with a review of the concepts of weak and strong cross-sectional...

This article considers a simple stock-flow matching model with fully informed market participants. Unlike in the standard matching literature, prices are assumed to be set ex-ante. When sellers pre-commit themselves to sell their products at an advertised price, the unique equilibrium is characterized by price dispersion due to the idiosyncratic ma...

The global financial turmoil has led to an unprecedented current account adjustment in central and eastern Europe. This article investigates this issue by revisiting two approaches. The first is the current account literature based on panel econometric techniques. This article adds to the literature by showing that, although there is a large degree...

The curse of dimensionality refers to the difficulty of including all relevant variables in empirical applications due to the lack of sufficient degrees of freedom. A common solution to alleviate the problem in the context of open economy models is to aggregate foreign variables by constructing trade-weighted cross-sectional averages. This paper pr...

The global financial crisis has led to a revival of the empirical literature on current account imbalances. This paper contributes to that literature by investigating the importance of evaluating model and parameter uncertainty prior to reaching any rm conclusion. We explore three alternative econometric strategies: examining all models, selecting...

The paper analyses the transmission of liquidity shocks and risk shocks to global financial markets. Using a Global VAR methodology, the findings reveal fundamental differences in the transmission strength and pattern between the 2007-08 financial crisis and the 2010-11 sovereign debt crisis. Unlike in the former crisis, emerging market economies h...