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Unit Roots and Causal Inference in Political Science Freeman, John R. Williams, John T. Houser, Daniel Kellstedt, Paul Uploaded 01-01-1995 Keywords Time series unit roots VAR FM-VAR Abstract In the 1980s political scientists were introduced to vector autoregression (Sims, 1980). In the years that followed, they used this method to evaluate competing theories (Goldstein and Freeman, 1990, 199l; Freeman and Alt, 1994; Williams, 1990) and to test the validity of the restrictions in their regression models (MacKuen, Erikson, and Stimson, 1992). In the process, important empirical anomalies came to light. At about this same time, econometricians identified and began to evaluate the problems which unit roots and cointegration produced in vector autoregression and related time series methods. These problems had to do with nothing less than the validity of Granger causality tests and other inferential tools which are the heart of the approach. This research was important because econometricians had discovered years before that many economic time series are first-order integrated (Nelson and Plosser, 1982). Studying the trend properties of economic time series therefore is considered essential in time series econometrics. Recently political scientists (Ostrom and Smith, 1993; Durr, 1993) have argued that certain political time series contain unit roots as well. Yet, to date, no political scientist has made any such demonstration, let alone explained what should be done to put our results on sounder footings if, in fact, our level VARs are faulty. This is the purpose of this paper. In it, we explain the problems which unit roots and cointegration produce in level VARs--why it is so important to take into account the trend properties of one's data. We then review several approaches to solving these problems. One of these approaches, Phillips's (1995) Fully Modified Vector Autoregression (FM-VAR) is singled out for closer study. The theoretical nature of FM-VAR is briefly explained and some practical difficulties in implementing the associated estimation techniques and hypothesis tests are discussed. Finally, the usefulness of FM-VAR is explored in several analyses which parallel the main uses of level VARs mentioned above. These are a stylized Monte Carlo analysis; a reanalysis of Freeman's (1983) study of arms races; a retest of the specifications of MacKuen, Erikson, and Stimson's (1992) model of approval; and a reexamination of the exogeneity-of-vote intentions anomaly in Freeman, Williams and Lin's (1989) study of British government spending.

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Recent Developments in Econometric Modelling: A Personal Viewpoint Maddala, G.S. Uploaded 07-17-1997 Keywords dynamic panel data models dynamic models with limited dependent variables unit roots cointegration VAR's Bayesian Abstract The quotation above (more than three thousand years ago) essentially summarizes my perception of what is going on in econometrics. Dynamic economic modelling is a comprehensive term. It covers everything except pure cross-section analysis. Hence, I have to narrow down the scope of my paper. I shall not cover duration models, event studies, count data and Markovian models. The areas covered are: dynamic panel data models, dynamic models with limited dependent variables, unit roots, cointegration, VAR’s and Bayesian approaches to all these problems. These are areas I am most familiar with. Also, the paper is not a survey of recent developments. Rather, it presents what I feel are important issues in these areas. Also, as far as possible, I shall relate the issues with those considered in the work on Political Methodology. I have a rather different attitude towards econometric methods which my own colleagues in the profession may not share. In my opinion, there is too much technique and not enough discussion of why we are doing what we are doing. I am often reminded of the admonition of the queen to Pollonius in Shakespeare’s Hamlet, “More matter, less art.”