Kenneth F. Wallis

Seasonal Adjustment and Relations between Variables

Abstract This article studies the effect of official seasonal adjustment procedures on the relations between variables. By considering time-invariant linear filters, and in particular a linear approximation to the Census Method II adjustment program, the effect of adjusting one or both of the variables in a distributed lag relation is examined, and the distortions which can arise are described. Applying the actual (nonlinear) adjustment procedure to artificial data indicates that at least for the particular x-series used, the results of the linear filter analysis provide a good guide to the behavior of estimates obtained from data adjusted by the official method.

Advances in Economics and Econometrics: Theory and Applications

This 1997 book is the third of three volumes containing papers presented at the Seventh World Congress of the Econometric Society. The papers summarize and interpret key recent developments and discuss current and future directions in a wide range of topics in economics and econometrics. They cover both theory and applications. Authored by leading specialists in their fields, these volumes provide a unique survey of progress in the discipline.

Density forecasting: a survey

A density forecast of the realization of a random variable at some future time is an estimate of the probability distribution of the possible future values of that variable. This article presents a selective survey of applications of density forecasting in macroeconomics and finance, and discusses some issues concerning the production, presentation and evaluation of density forecasts.

Multiple Time Series Analysis and the Final Form of Econometric Models

Univariate autoregressive moving average models for the endogenous variables of a dynamic simultaneous equations system can be interpreted as a form of solution of that system. This paper considers the interrelationships between the various representations of the system, and develops joint estimation and model selection procedures for the multiple time series model which arises as a multivariate representation of the individual autoregressive moving average models. A test of the restriction of common autoregressive parameters is incorporated. Two empirical examples are presented, the first concerned with a model of the hog cycle and the second with a model of the United States economy previously considered by Zellner and Palm.

Combining Density and Interval Forecasts: A Modest Proposal

The finite mixture distribution is proposed as an appropriate statistical model for a combined density forecast. Its implications for measures of uncertainty and disagreement, and for combining interval forecasts, are described. Related proposals in the literature and applications to the U.S. Survey of Professional Forecasters are discussed.

Uncertainty and Disagreement in Economic Prediction: The Bank of England Survey of External Forecasters*

This article introduces a new source of survey data, namely the Bank of England Survey of External Forecasters. The survey collects point and density forecasts of inflation and GDP growth, and hence offers the opportunity of constructing direct measures of uncertainty. We present a simple statistical framework in which to define and interrelate measures of uncertainty and disagreement. The resulting measures are compared with other direct measures of uncertainty, nationally and internationally. A significant, sustained reduction in inflation uncertainty followed the 1997 granting of operational independence to the Bank of England to pursue a monetary policy of inflation targeting.

An Assessment of Bank of England and National Institute Inflation Forecast Uncertainties

This article evaluates the density forecasts of inflation published by the Bank of England and the National Institute of Economic and Social Research. It extends the analysis of the Bank of England’s fan charts in an earlier article by considering data up to 2003, quarter 4, and by correcting some technical details in the light of information published on the Bank’s website in Summer 2003. National Institute forecasts are also considered, although there are fewer comparable observations. Both groups’ central point forecasts are found to be unbiased, but their density forecasts substantially overstated forecast uncertainty.

Combining forecasts - forty years later

This article is dedicated to the memory of Clive Granger, a founding editor of this journal. Its title echoes the title of his invited review article in a special issue of the Journal of Forecasting in 1989. That issue marked the twentieth anniversary of the publication of his article with John Bates, which is widely regarded as the seminal article in the field of forecast combination. This article returns to two of the topics in ‘Combining forecasts – twenty years later’ that are of much current interest, namely the impact of forecasters’ different information sets on the original point forecast combination result, and properties of different methods of combining density forecasts. A parallel result to his inefficiency-of-mean-forecasts result for point forecasts is seen to apply to density forecasts, where logarithmic combination is shown to have some advantage over linear combination.

Models of the UK Economy: A Fourth Review by the ESRC Macroeconomic Modelling Bureau.

This book contains comparative analyses of seven models in all: those of the five groups currently receiving support from the Economic Social Research Council--Cambridge Growth Project, City University Business School, Liverpool University Research Group in Macroeconomics, London Business School, and National Institute of Economic and Social Research--as well as the Treasury and the Bank of England.

Unobserved-Components Models for Seasonal Adjustment Filters

Time series models are presented for which the seasonal component estimates delivered by linear least squares signal extraction closely approximate those of the standard option of the widely-used Cencus X-11 program. Earlier work is extended by consideration of a broader class of models and by examination of asymmetric filters in addition to the symmetric filter implicit in the adjustment of historical data. Various criteria that guide the specification of unobserved-component models are discussed, and a new preferred model is presented. Other models generate filters that approximate X-11 rather well, explaining the wide acceptance of the X-11 method.