C.W.J.Granger – Time Series And Spectral Methods In Econometrics

This chapter discusses two alternative approaches to the analysis of economic data, which is time series and the classical econometric approaches. The time series approach is based on experience from many fields, but that of the econometrician has been viewed as applicable only to economic data that have displayed a great deal of simultaneous or contemporaneous interrelationships. Some influences from the time series domain penetrated that of the classical econometrician, such as how to deal with trends and seasonal components, Durbin–Watson statistics, and first-order serial correlation, but there was little influence in the other direction. In the past 10 years, this state of affairs has changed dramatically, with time series ideas becoming more mainstream and the procedures developed by econometricians being considered more carefully by the time series analysts. The building of large-scale models, worries about efficient estimation, the growing popularity of rational expectations theory and the consequent interest in optimum forecasts, and the discussion of causality testing have greatly helped in bringing the two approaches together, with benefits to both sides. The chapter briefly discusses the question of differencing of data, as an illustration of the alternative approaches taken in the past. It also discusses some applications of time series methods to economic data.