Knowledge that Transforms

In their comment, Subhash C. Ray and Evangelia Desli (1997) (hereafter RD) point out that the specification of the decomposition of the Malmquist productivity index used by Fare et al. (1994) (hereafter FGNZ) is not unique, and propose and compute an alternative specification of that decomposition. We will discuss additional decompositions at the end of this note, but proceed here by comparing the RD decomposition with FGNZ based on both conceptual and computational grounds. RD provide a discussion of the overall Malmquist productivity index, including the important issue of when this index is equivalent to the traditional notion of total factor productivity (TFP) -namely under the condition that the technology be consistent with constant returns to scale (CRS). As they point out, this will yield a measure of TFP even if the true underlying technology is not CRS, for example. Both RD and FGNZ use the CRS technology to compute overall Malmquist productivity. One of the key issues raised is the role of the underlying scale properties of the benchmark technologies used to define and compute both productivity and its components. In particular, two reference technologies are employed in both RD and FGNZ: what we refer to as CRS and variable returns to scale (VRS) technologies.' By construction, these technologies are nested: the CRS technology contains the VRS technology, as in Figure 1 in RD. This nestedness provides the logical basis for our decomposition. At a very intuitive level, we would argue that these two benchmarks can be used to provide bounds on the underlying true-but unknown-technology.2 Intuitively we see the VRS technology providing a type of convex inner approximation, whereas the CRS technology provides a type of convex outer approximation. Thus these two technologies provide alternative benchmarks; they do not require that the data satisfy either CRS or VRS. Another possible intuitive interpretation is that the CRS captures a (perhaps hypothetical) long run and the VRS approximates the short run. As a technology, the CRS technology has some very useful features; for example, it captures the notion of maximal

Economic agents rarely write optimally complete contracts in the Arrow-Debreu sense. Few regard this as puzzling, since contractual completeness of this kind is often technically infeasible. Our concern here is with the question of why contracts so often leave the contracting parties' obligations incompletely specified; that is, of why they contain "gaps".

This paper develops a computable general equilibrium model in which endogenous agency costs can potentially alter business-cycle dynamics. A principal conclusion is that the agency-cost model replicates the empirical fact that output growth displays positive autocorrelation at short horizons. This hump-shaped output behavior arises because households delay their investment decisions until agency costs are at their lowest--a point in time several periods after the initial shock.

In this paper I try to move away from the Extreme Bounds method of identifying robust empirical relations in the economic growth literature. Instead of analyzing the extreme bounds of the estimates of the coefficient of a particular variable, I analyze the entire distribution. My claim in this paper is that, if we do this, the picture emerging from the empirical growth literature is not the pessimistic Nothing is Robust that we get with the extreme bound analysis. Instead, we find that a substantial number of variables can be found to be strongly related to growth.

The authors investigate the productivity effects of innovative employment practices using data from a sample of thirty-six homogeneous steel production lines owned by seventeen companies. The productivity regressions demonstrate that lines using a set of innovative work practices, which include incentive pay, teams, flexible job assignments, employment security, and training, achieve substantially higher levels of productivity than do lines with the more traditional approach, which includes narrow job definitions, strict work rules, and hourly pay with close supervision. Their results are consistent with recent theoretical models which stress the importance of complementarities among work practices.