Time Series Issues in the Estimation of the Rational Addiction using Micro Data
- Presenter:
Chair: Susan Ettner; Discussant: Bill Crown Mon June 5, 2006 10:45-12:15 Room 226
Increased availability of micro panel data sets make time series econometric issues relevant in the estimation of RA models. In particular, the theoretical RA model possesses a saddlepoint equilibrium, meaning that the time series properties of the data are represented by a second order difference equation with one stable and one unstable root. The unstable root is expected to introduce nonstationarity problems akin to those found in the unit root macroeconometrics literature, and is also expected to dominate, and bias, the estimation of the coefficients of the RA equation as the time dimension of the data grows. In this paper we use Monte Carlo simulation methodology to illustrate the effects of the presence of an unstable root on the estimation of the coefficients of an RA model, and in particular on the estimated coefficients on lead and lag consumption. We show that as the time dimension of the data increases, the unstable root comes to dominate the estimation of RA-type models, to the point where the RA form can be decisively rejected even when it is the true data generating process. We also show that the larger the unstable root, the smaller the length of the time series required for the unstable root to come to dominate the estimation. Conclusions: The earlier applied RA literature paid little attention to time series issues, probably because the lack of individual level panel data sets made those issues moot. As, increasingly, micro panel data becomes available, researchers will need to take account of the implications of the dynamic structure of the RA model for its estimation, and in particular for the likelihood of significant bias to the estimated coefficients.
