The aim of this chapter is to review some econometric terms and methods that are particularly useful for empirical macroeconomics. The technical level of the chapter assumes completion of an intermediate or good introductory course such as covered by, for example, Dougherty (2011) or Wooldridge (2011). Ideally, some knowledge of the linear regression model in matrix-vector notation would also be helpful, such as provided in Greene (2011). This chapter proceeds as follows. The starting point for the analysis of macroeconomic time series is univariate modelling, a classic case being Nelson and Plosser’s (1982) analysis of a number of macroeconomic time series to assess whether they were generated by unit root processes, a finding that would have implications not only for econometric analysis but, from a macroeconomic perspective, also for the persistence of shocks and the generation of the business cycle. There are two basic concepts that enable a better understanding of the framework of unit root tests, the first being that of a stochastic process and the second that of stationarity and non-stationarity, and these are outlined in sectio . Stationarity is a property related to the process generating the observable data of macroeconomic analysis, although one often finds a shorthand reference to the stationarity or non-stationarity of the data or of a particular time series.
You are not authenticated to view the full text of this chapter or article.
Get access to the full article by using one of the access options below.