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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. [ABSTRACT FROM AUTHOR]

David Hendry has made major contributions to many areas of economic forecasting. He has developed a taxonomy of forecast errors and a theory of unpredictability that have yielded valuable insights into the nature of forecasting. He has also provided new perspectives on many existing forecast techniques, including mean square forecast errors, add factors, leading indicators, pooling of forecasts, and multi-step estimation. In addition, David has developed new forecast tools, such as forecast encompassing; and he has improved existing ones, such as nowcasting and robustification to breaks. This interview for the International Journal of Forecasting explores David Hendry's research on forecasting. [ABSTRACT FROM AUTHOR]

Government debt and forecasts thereof attracted considerable attention during the recent financial crisis. The current paper analyzes potential biases in different U.S. government agencies' one-year-ahead forecasts of U.S. gross federal debt over 1984--2012. Standard tests typically fail to detect biases in these forecasts. However, impulse indicator saturation (IIS) detects economically large and highly significant time-varying biases, particularly at turning points in the business cycle. These biases do not appear to be politically related. IIS defines a generic procedure for examining forecast properties; it explains why standard tests fail to detect bias; and it provides a mechanism for potentially improving forecasts. [ABSTRACT FROM AUTHOR]

Stekler and Symington (2016) construct indexes that quantify the Federal Open Market Committee's views about the U.S. economy, as expressed in the minutes of the FOMC's meetings. These indexes provide insights on the FOMC's deliberations, especially at the onset of the Great Recession. The current paper complements Stekler and Symington's analysis by showing that their indexes reveal relatively minor bias in the FOMC's views when the indexes are reinterpreted as forecasts. Additionally, these indexes provide a proximate mechanism for inferring the Fed staff's Greenbook forecasts of the U.S. real GDP growth rate, years before the Greenbook's public release. [ABSTRACT FROM AUTHOR]

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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 discussion on model averaging and the pooling of forecasts. [ABSTRACT FROM AUTHOR]

This paper assesses the empirical merits of PcGets and Autometrics— two recent algorithms for computer-automated model selection—using them to improve upon Kamin and Ericsson's (1993) model of Argentine broad money demand. The selected model is an economically sensible and statistically satisfactory error correction model, in which cointegration between money, inflation, the interest rate, and exchange rate depreciation depends on the inclusion of a "ratchet" variable that captures irreversible effects of inflation. Short-run dynamics differ markedly from the long run. Algorithmically based model selection complements opportunities for the researcher to contribute value added in the empirical analysis. [ABSTRACT FROM AUTHOR]

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 of model selection, noting that general-to-specific modeling is the practical embodiment of reduction. This paper then summarizes fifty-seven articles key to the development of general-to-specific modeling. [ABSTRACT FROM AUTHOR]

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 housing and mortgage markets; economic forecasting and policy analysis; the history of econometric thought; and the use of computers for live empirical and Monte Carlo econometrics. [ABSTRACT FROM AUTHOR]

This paper presents a biographical retrospective of J. Denis Sargan and his contributions in both applied and theoretical econometrics. This retrospective includes a complete bibliography of his works, as well as a list of PhD theses he supervised. The recent discovery of two of his unpublished works is discussed in detail, as is the influence Sargan's research has had on current econometric research. This working paper can be found at the United States Federal Reserve Board's International Finance Discussion Papers. You can access it by going to http://www.federalreserve.gov/pubs/ifdp/.

This paper serves as an introduction to forecast uncertainty in empirical economic modeling. The author defines forecast uncertainty and examines various measures of forecast uncertainty. Also, some sources and consequences of forecast uncertainty are analyzed. These issues are illustrated with the use of sample models with regards to the United States trade balance, United Kingdom inflation and real national income, and the U.S./U.K. exchange rate. This working paper can be found at the United States Federal Reserve Board's International Finance Discussion Papers. You can access it by going to http://www.federalreserve.gov/pubs/ifdp/.

This paper examines predictable uncertainty in economic forecasting and provides an introduction to predictable forecast uncertainty in empirical economic modeling. The study categorizes the sources of both predictable and unpredictable forecast uncertainty. Several analytical models, including static and dynamic models, illustrate the key features of predictable forecast uncertainty. Empirical models of the United States trade account, United Kingdom (U.K.) inflation, and U.K. real national income are used to help clarify the issues involved in this study. This working paper can be found at the United States Federal Reserve Board's International Finance Discussion Papers. You can access it by going to http://www.federalreserve.gov/pubs/ifdp/.

This paper examines output growth and inflation in the long run. Cross-country regressions explaining output growth frequently obtain a negative effect from inflation but that result is not robust due to the selection of countries in the sample, temporal aggregation, and omission of important variables in levels. This study shows some suggestions of these misspecifications. More specifically, for most G-7 countries, annual time series of inflation and the log levels of output are co-integrated. This rejects the existence of a long-run relation between output growth and inflation. This working paper can be found at the United States Federal Reserve Board's International Finance Discussion Papers. You can access it by going to http://www.federalreserve.gov/pubs/ifdp/.

This paper examines constructive data mining with regards to modeling consumers' expenditures in Venezuela. The study identifies four negative senses of data mining and demonstrates how Hoover and Perez's (1999) study and approach to constructive data mining counter each of the senses identified. To analyze the benefits of constructive data mining a data mining algorithm similar to the Hoover and Perez study is applied to a dataset for Venezuelan consumer expenditure. This analysis demonstrates that such methods of data mining can be successful empirically, even on very short samples. This working paper can be found at the United States Federal Reserve Board's International Finance Discussion Papers. You can access it by going to http://www.federalreserve.gov/pubs/ifdp/.

This paper presents distributions of error correction tests for cointegration. The authors offer cumulative distribution functions, densities, and finite sample critical values for the single-equation error correction statistic for testing cointegration. They conduct Monte Carlo simulations and emphasize simple dependencies of the statistic's quantities on the number of variables in the error correction model, the choice of deterministic components, and the estimation sample size. This working paper is available at the US Federal Reserve Board. You can access this site by going to www.federalreserve.gov/pubs/workingpapers.htm.

This paper proposes a framework design and post evaluation analysis for economic forecasts. This framework is illustrated by re-examining mean square forecast errors from dynamic models and nonlinearity biases of US external trade. Previous studies examined properties of nonlinearity bias and the possible nonmonotonicity and nonexistence of mean square forecast errors separate from other aspects of the forcasting process. This resulted in inefficient forecasting. This working paper can be found at the US Federal Reserve Board's International Finance Discussion Papers. You can access this by going to

This paper overviews the econometric concepts of exogeneity, cointegration, causality and invariance conditions for reliable economic policy analysis based on econometric models. The authors focus on the weak, strong, and super exogeneity that are discussed in general. These concepts are applied to the econometric models in the policy analysis when the variables are cointegrated. A small money demand for the United Kingdom illustrates the main analytical points. In addition, this paper summarizes the other articles on exogeneity, cointegration, and economic policy analysis. This working paper can be found at the US Federal Reserve Board's International Finance Discussion Papers. You can access this by going to

This paper reviews the economic theory of money demand and defines and describes the data series. The authors emphasize the connection of empirical modeling, econometric methodology, and conceptual issues when evaluating econometric models over additional observations. The authors extend the models to include two decades of new data and clarify the concept of parameter reliability. Lengthening the sample expands the number of alternative measures of both credit derestrictions and opportunity cost of holding money. This working paper can be found at the US Federal Reserve Board's International Finance Discussion Papers. You can access this by going to

The central banks of Canada, Sweden, and Norway are all part of a Monetary Conditions Index (MCI) for the purpose of conducting monetary policy. An MCI is calculated as the weighted sum of changes in a short-term interest rate and the exchange rate relative to values in a baseline year, in addition to focusing on economic activity and inflation. This paper obtains analytical and empirical assets of MCIs in an attempt to ascertain their usefulness in monetary policy. This working paper can be found at the US Federal Reserve Board's International Finance Discussion Papers. You can access this by going to

This paper develops a constant, data-coherent, error correction model for broad money demand (M3) in Greece. By giving a better understanding of the effects of monetary policy in Greece, this model contributes to portfolio consequences of financial innovation in general. The broad monetary aggregate M3 was targeted until recently, and current monetary policies still use such aggregates as guidelines. The estimated model is remarkably stable, in spite of large fluctuations in the inflation rate, introduction to new financial instruments, and the liberalization of the financial system. The dynamics of money demand are important with price and income flexibilities being small in the short run. This working paper can be found at the US Federal Reserve Board's International Finance Discussion Papers. You can access this by going to

We introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) ination forecasts produced by the staff of the Board of Governors of the Federal Reserve System. In contrast to the eight Greenbook forecasts a year the staff produces for Federal Open Market Committee (FOMC) meetings, our dataset has roughly weekly forecasts. We use these new data to study whether the staff forecasts efficiently and whether efficiency, or lack thereof, is time-varying. Prespecified regressions of forecast errors on forecast revisions show that the staff's GDP forecast errors correlate with its GDP forecast revisions, particularly for forecasts made more than two weeks from the start of a FOMC meeting, implying GDP forecasts exhibit time-varying inefficiency between FOMC meetings. We find some weaker evidence for inefficient ination forecasts. [ABSTRACT FROM AUTHOR]

I show that the probability that the Board of Governors of the Federal Reserve System staff's forecasts (the "Greenbooks") overpredicted quarterly real gross domestic product (GDP) growth depends on both the forecast horizon and also whether the forecasted quarter was above or below trend real GDP growth. For forecasted quarters that grew below trend, Greenbooks were much more likely to overpredict real GDP growth, with one-quarter ahead forecasts overpredicting real GDP growth more than 75% of the time, and this rate of overprediction was higher for further ahead forecasts. For forecasted quarters that grew above trend, Greenbooks were slightly more likely to underpredict real GDP growth, with one-quarter ahead forecasts underpredicting growth about 60% of the time. Unconditionally, on average, Greenbooks overpredicted real GDP growth. [ABSTRACT FROM AUTHOR]