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Author:Pesaran, M. Hashem 

Working Paper
A multi-country approach to forecasting output growth using PMIs

This paper derives new theoretical results for forecasting with Global VAR (GVAR) models. It is shown that the presence of a strong unobserved common factor can lead to an undetermined GVAR model. To solve this problem, we propose augmenting the GVAR with additional proxy equations for the strong factors and establish conditions under which forecasts from the augmented GVAR model (AugGVAR) uniformly converge in probability (as the panel dimensions N,T? ? such that N/T?? for some 0
Globalization Institute Working Papers , Paper 213

Working Paper
Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels

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

Early Mandated Social Distancing Does Best to Control COVID–19 Spread

Voluntary social distancing and a lack of compliance with mandated polices have led to unnecessarily high infection rates and death tolls in a number of countries.
Dallas Fed Economics

Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks

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 breaks, including the use of rolling windows and exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection, which is complicated by time variations in the effects of signal variables. In this study we investigate whether or not we should use weighted observations at the variable selection stage in the presence of ...
Globalization Institute Working Papers , Paper 394

Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks

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 breaks, including the use of rolling windows or exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection. It is clear that, in the absence of breaks, researchers should weigh the observations equally at both the variable selection and forecasting stages. In this study, we investigate whether or not we should use ...
Globalization Institute Working Papers , Paper 394

Working Paper
An Augmented Anderson-Hsiao Estimator for Dynamic Short-T Panels

This paper 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 or in conjunction with other available moment conditions to obtain more efficient estimators. This approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. This paper focuses on the latter, and ...
Globalization Institute Working Papers , Paper 327

Working Paper
Aggregation in large dynamic panels

This paper investigates the problem of aggregation in the case of large linear dynamic panels, where each micro unit is potentially related to all other micro units, and where micro innovations are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate function is derived and used (i) to establish conditions under which Granger's (1980) conjecture regarding the long memory properties of aggregate variables from "a very large scale dynamic, econometric model" holds, and (ii) to show which distributional features of micro parameters can be identified from ...
Globalization Institute Working Papers , Paper 101

Working Paper
Large panel data models with cross-sectional dependence: a survey

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 dependence, and discusses the exponent of cross-sectional dependence that characterizes the different degrees of cross-sectional dependence. It considers a number of alternative estimators for static and dynamic panel data models, distinguishing ...
Globalization Institute Working Papers , Paper 153

Working Paper
Identifying Global and National Output and Fiscal Policy Shocks Using a GVAR

The paper contributes to the growing Global VAR (GVAR) literature by showing how global and national shocks can be identified within a GVAR framework. The usefulness of the proposed approach is illustrated in an application to the analysis of the interactions between public debt and real output growth in a multi-country setting, and the results are compared to those obtained from standard single-country VAR analysis. We find that on average (across countries) global shocks explain about one-third of the long-horizon forecast error variance of output growth, and about one-fifth of the long-run ...
Globalization Institute Working Papers , Paper 351

Working Paper
An Augmented Anderson-Hsiao Estimator for Dynamic Short-T Panels

This paper 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 and/or augmented with other available moment conditions (if any) to obtain more efficient estimators. This approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. This paper focuses on the latter, ...
Globalization Institute Working Papers , Paper 327

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