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Working Paper
Dynamic Econometrics in Action: A Biography of David F. Hendry
David Hendry has made–and continues to make–pivotal contributions to the econometrics of empirical economic modeling, economic forecasting, econometrics software, substantive empirical economic model design, and economic policy. This paper reviews his contributions by topic, emphasizing the overlaps between different strands in his research and the importance of real-world problems in motivating that research.
Working Paper
Exact and approximate multi-period mean-square forecast errors for dynamic econometric models
Both future disturbances and estimated coefficients contribute to the uncertainty in model-based ex ante forecasts, but only the first source is usually taken into account when calculating confidence intervals for practical applications. Schmidt (1974) and Baillie (1979) provide an easily computable second-order approximation to the mean-square forecast error (MSFE) for linear dynamic systems which recognizes both sources of uncertainty. To assess the accuracy of their approximation, and thus its usefulness, we compare it with three sets of estimates of the exact MSFE for the univariate AR(l) ...
Working Paper
An econometric analysis of UK money demand in MONETARY TRENDS IN THE UNITED STATES AND THE UNITED KINGDOM by Milton Friedman and Anna J. Schwartz
This paper evaluates an empirical model of UK money demand developed by Friedman and Schwartz in Monetary Trends... .Testing reveals mis-specification and hence the potential for an improved model. Using recursive procedures on their annual data, we obtain a better-fitting, constant, dynamic error-correction (cointegration) model. Results on exogeneity and encompassing imply that our money-demand model is interpretable as a model of money but not of prices since its constancy holds only conditional on contemporaneous prices.
Working Paper
The fragility of sensitivity analysis: an encompassing perspective
Robustness and fragility in Leamer's sense are defined with respect to a particular coefficient over a class of models. This paper shows that inclusion of the data generation process in that class of models is neither necessary nor sufficient for robustness. This result holds even if the properly specified model has well-determined, statistically significant coefficients. The encompassing principle explains how this result can occur. Encompassing also provides a link to a more common-sense notion of robustness, which is still a desirable property empirically; and encompassing clarifies recent ...
Working Paper
General-to-specific modeling: an overview and selected bibliography
This paper discusses the econometric methodology of general-to-specific modeling, in which the modeler simplifies an initially general model that adequately characterizes the empirical evidence within his or her theoretical framework. Central aspects of this approach include the theory of reduction, dynamic specification, model selection procedures, model selection criteria, model comparison, encompassing, computer automation, and empirical implementation. This paper thus reviews the theory of reduction, summarizes the approach of general-to-specific modeling, and discusses the econometrics ...
Working Paper
Predictable uncertainty in economic forecasting
This paper provides an introduction to predictable forecast uncertainty in empirical economic modelling. The sources of both predictable and unpredictable forecast uncertainty are categorized. Key features of predictable forecast uncertainty are illustrated by several analytical models, including static and dynamic models, and single-equation and multiple-equation models. Empirical models of the U.S. trade account, U.K. inflation, and U.K. real national income help clarify the issues involved.
Working Paper
The ET interview: professor David F. Hendry
This interview for Econometric Theory explores David Hendry's research. Issues discussed include estimation and inference for nonstationary time series; econometric methodology; strategies, concepts, and criteria for empirical modeling; the general-to-specific approach, as implemented in the computer packages PcGive and PcGets; computer-automated model selection procedures; David's textbook Dynamic Econometrics; Monte Carlo techniques (PcNaive); evaluation of these developments in simulation studies and in empirical investigations of consumer expenditure, money demand, inflation, and the ...
Discussion Paper
Milton Friedman and Data Adjustment
When empirically modelling the U.S. demand for money, Milton Friedman more than doubled the observed initial stock of money to account for a "changing degree of financial sophistication" in the United States relative to the United Kingdom. This note discusses effects of this adjustment on Friedman's empirical models. His data adjustment dramatically reduced apparent movements in the velocity of circulation of money, and it adversely affected the constancy and fit of his estimated money demand models.
Working Paper
The power of cointegration tests
A cointegration test statistic based upon estimation of an error correction model can be approximately normally distributed when no cointegration is present. By contrast, the equivalent Dickey-Fuller statistic applied to residuals from a static relationship has a non-standard asymptotic distribution. When cointegration exists, the error-correction test generally is more powerful than the Dickey-Fuller test. These differences arise because the latter imposes a possibly invalid common factor restriction. The issue is general and has ramifications for system-based cointegration tests. Monte ...
Working Paper
Cointegration, seasonality, encompassing, and the demand for money in the United Kingdom
Virtually all previous narrow money demand studies for the United Kingdom have used seasonally adjusted data for money, prices, and expenditure. This paper develops a constant, data-coherent M1 demand equation for the United Kingdom with seasonally unadjusted data. For that model, we address issues of cointegration, error correction, generalto-specific modeling, dynamic specification, model evaluation and testing, parameter constancy, and exogeneity. We also establish theoretical and empirical relationships between seasonally adjusted and unadjusted data, and so between models using those ...