A robust estimator for performance modelling

In recent economics literature, Malmquist productivity growth index (Fare et al.) is often used as a measure of total factor productivity. In finding the factors affecting the productivity growth, a two-step approach is often employed where the Malmquist index is computed in the first step and regressed on a set of explanatory variables in the second step. The two-step approach is also frequently used to study factors affecting technical efficiencies. Recent literature in efficiency and productivity studies criticized this twostep approach, arguing that bootstrapping should be used to correct the bias and solve the serial correlation problem which otherwise jeopardizes the validity of econometric procedure. Unfortunately, the bootstrapping method is computationally demanding and may be less appealing to applied researchers. In finding factors affecting firm performance, in many cases variables used in the regression model are likely to be endogenous. For example, investment may be affected by firm performance. Without addressing the endogeneity, analysis may result in inconsistent results. As an additional problem in modeling firm performance, we find that static models are routinely used both in efficiency and productivity studies and in financial studies. However, we notice that firm performance has its specific dynamics.