INTRODUCTION

When the overall homogeneity hypothesis is rejected by the panel data while the specification of a model appears proper, a simple way to take account of the unobserved heterogeneity across individuals and/or through time is to use the variable-intercept models (1.3.1) and (1.3.2). The basic assumption of such models is that, conditional on the observed explanatory variables, the effects of all omitted (or excluded) variables are driven by three types of variables: individual time-invariant, period individual-invariant, and individual time-varying variables. The individual time-invariant variables are variables that are the same for a given cross-sectional unit through time but that vary across cross-sectional units. Examples of these are attributes of individual firm management, ability, sex, and socioeconomic background variables. The period individual-invariant variables are variables that are the same for all cross-sectional units at a given point in time but that vary through time. Examples of these variable are prices, interest rates, and widespread optimism or pessimism. The individual time-varying variables are variables that vary across cross-sectional units at a given point in time and also exhibit variations through time. Examples of these variables are firm profits, sales, and capital stock.

The variable-intercept models assume that the effects of the numerous omitted individual time-varying variables are each individually unimportant but are collectively significant and possess the property of a random variable that is uncorrelated with (or independent of) all other included and excluded variables.