Estimation Techniques for Macro Diffusion Models

In this chapter, the authors review estimation techniques for macro diffusion models. The chapter begins by discussing estimation of single equation models under the assumption of time invariant parameters. The authors then forcus on recent models in which the diffusion parameters are allowed to vary over time. Stationary and non-stationary processes are discussed. Simultaneous equation estimation issues follow-the application of full information maximum likelihood and three stage least squares in the context of lienar as well as non-linear models are reviewed. Issues in estimating diffusion models in a multinational environment, data constraints, and the use of non-nested hypothesis tests for model comparisons are then discussed. previous research addressing estimation in the presence of little or no data is also reviewed. This chapter concludes with normative guidleines and suggestions for future research.