Douglas O. Staiger

This paper develops asymptotic distribution theory for instrumental variable regression when the partial correlation between the instruments and a single included endogenous variable is weak, here modeled as local to zero. Asymptotic representations are provided for various instrumental variable statistics, including the two-stage least squares (TSLS) and limited information maximum- likelihood (LIML) estimators and their t-statistics. The asymptotic distributions are found to provide good approximations to sampling distributions with just 20 observations per instrument. Even in large samples, TSLS can be badly biased, but LIML is, in many cases, approximately median unbiased. The theory suggests concrete quantitative guidelines for applied work. These guidelines help to interpret Angrist and Krueger's (1991) estimates of the returns to education: whereas TSLS estimates with many instruments approach the OLS estimate of 6%, the more reliable LIML and TSLS estimates with fewer instruments fall between 8% and 10%, with a typical confidence interval of (6%, 14%).

We used a random-assignment experiment in Los Angeles Unified School District to evaluate various non-experimental methods for estimating teacher effects on student test scores. Having estimated teacher effects during a pre-experimental period, we used these estimates to predict student achievement following random assignment of teachers to classrooms. While all of the teacher effect estimates we considered were significant predictors of student achievement under random assignment, those that controlled for prior student test scores yielded unbiased predictions and those that further controlled for mean classroom characteristics yielded the best prediction accuracy. In both the experimental and non-experimental data, we found that teacher effects faded out by roughly 50 percent per year in the two years following teacher assignment.

This paper examines the precision of conventional estimates of the NAIRU and the role of the NAIRU and unemployment in forecasting inflation. The authors find that, although there is a clear empirical Phillips relation, the NAIRU is imprecisely estimated, forecasts of inflation are insensitive to the NAIRU, and there are other leading indicators of inflation that are at least as good as unemployment. This suggests deemphasizing the NAIRU in public discourse about monetary policy and instead drawing on a richer variety of leading indicators of inflation.

In recent years, most states have constructed elaborate accountability systems using school-level test scores. However, because the median elementary school contains only 69 children per grade level, such measures are quite imprecise. We evaluate the implications for school accountability systems. For instance, rewards or sanctions for schools with scores at either extreme primarily affect small schools and provide weak incentives to large ones. Nevertheless, we conclude that accountability systems may be worthwhile. Even in states with aggressive financial incentives, the marginal reward to schools for raising student performance is a small fraction of the potential labor market value for students.

Registered nurse (RN) employment has increased during the current recession, and we may soon see an end to the decade-long nurse shortage. This would give hospitals welcome relief and an opportunity to strengthen the nurse workforce by addressing issues associated with an increasingly older and foreign-born workforce. The recent increase in employment is also improving projections of the future supply of RNs, yet large shortages are still expected in the next decade. Until nursing education capacity is increased, future imbalances in the nurse labor market will be unavoidable.