Charles A. Fleischman

Job-Hopping in Silicon Valley: Some Evidence Concerning the Micro-Foundations of a High Technology Cluster

Observers of Silicon Valleys computer cluster report that employees move rapidly between competing firms, but evidence supporting this claim is scarce. Job-hopping is important in computer clusters because it facilitates the reallocation of talent and resources toward firms with superior innovations. Using new data on labor mobility, we find higher rates of job-hopping for college-educated men in Silicon Valleys computer industry than in computer clusters located out of the state. Mobility rates in other California computer clusters are similar to Silicon Valleys, suggesting some role for features of California law that make noncompete agreements unenforceable. Consistent with our model of innovation, mobility rates outside computer industries are no higher in California than elsewhere.

THE CAUSES OF BUSINESS CYCLES AND THE CYCLICALITY OF REAL WAGES

A models ability to explain procyclical movements in real wages has become an important benchmark by which macroeconomists judge business cycle theories. Because Keynesian models with sticky nominal wages predict countercyclical real wages, they have been criticized and dismissed in favor of Real Business Cycle models or New Keynesian models based on price stickiness or countercyclical markups. The bulk of the evidence for procyclical real wages, however, comes from studies using panel data that estimate the unconditional, contemporaneous correlation between real wages and the unemployment rate. These studies constrain real wage cyclicality to be the same irrespective of the source of the business cycle fluctuations. This paper relaxes this constraint and estimates a structural VAR identified by long-run restrictions on the responses of hours and output to labor supply, technology, oil price, and aggregate demand shocks. It finds that real wages are procyclical in response to technology shocks and oil price shocks, but are countercyclical in response to labor supply shocks and aggregate demand shocks. The procyclicality of real wages during the periods covered by the panel data sets may be explained by the importance of the productivity slowdown and the 1970s oil price shocks. The results highlight the limitations of using the unconditional, contemporaneous correlation between real wages and business cycle indicators to sort out competing theories of the business cycle, and cast strong doubt on the appropriateness of the rejection of sticky wage models.

From Many Series, One Cycle: Improved Estimates of the Business Cycle from a Multivariate Unobserved Components Model

We construct new estimates of potential output and the output gap using a multivariate approach that allows for an explicit role for measurement errors in the decomposition of real output. Because we include data on hours, output, employment, and the labor force, we are able to decompose our estimate of potential output into separate trends in labor productivity, labor-force participation, weekly hours, and the NAIRU. We find that labor-market variables—especially the unemployment rate—are the most informative individual indicators of the state of the business cycle. Conditional on including these measures, inflation is also very informative. Among measures of output, we find that although they add little to the identification for the cycle, the income-side measures of output are about as informative as the traditional product-side measures about the level of structural productivity and potential output. We also find that the output gap resulting from the recent financial crisis was very large, reaching -7 percent of output in the second half of 2009.

The Endogeneity of Employment Adjustment Costs: The Tradeoff Between Efficiency and Flexibility

This paper models a firms choice of employment adjustment costs as one component of its choice of production process. In making a one-time choice of production process, firms tradeoff increased flexibility--the reduced cost of changing levels of production--against the diminished efficiency of producing a given level of output. The model predicts that firms facing greater volatility in expected employment choose production processes that entail relatively low costs of adjusting employment. Using estimates of adjustment costs and employment volatility for four-digit manufacturing industries, the paper finds empirical support for the model: Among four-digit industries facing similar choices of production process, those with more volatile employment tend to have lower costs of adjusting employment. Moreover, the paper finds that interindustry heterogeneity in the amplitude of deterministic seasonal fluctuations in employment is more important than the variance of stochastic employment fluctuations in explaining the choice of adjustment costs.

The GMM Parameter Normalization Puzzle

A feature of GMM estimation--the use of a consistent estimate of the optimal weighting matrix rather than the joint estimation of the model parameters and the weighting matrix--can lead to the sensitivity of GMM estimation to the choice of parameter normalization. In many applications, including Euler equation estimation, a model parameter multiplies the equation error in some, but not all, normalizations. But, conventional GMM estimators that either hold the estimate of the weighting matrix fixed or allow some limited iteration on the weighting matrix fail to account for the dependence of the weighting matrix on the parameter vector implied by the multiplication of the error by the parameter. In finite samples, GMM effectively minimizes the square of the parameter times the objective function that obtains from an alternative normalization where no parameter multiplies the equation error, resulting in estimates that are smaller (in absolute value) than those from the alternative normalization. Of course, normalization is irrelevant asymptotically.