In an analysis connecting labor market earnings to college major choices, we find statistically significant relationships between changes in wages by occupation and subsequent changes in college majors completed in related fields of college study between 1982 and 2012. College majors (defined at a detailed level) are most strongly related to wages observed three years earlier, when students were college freshmen. The responses to wages vary depending on the extent to which there is a strong mapping of majors into particular occupations. We also find that women, blacks, Hispanics, and students with low test scores are less likely to respond to wage changes. These findings have implications for policy interventions designed to align students' major choices with labor market demand.
Acknowledgement:We thank
Despite their widespread use, there is little academic evidence on whether applicant selection instruments can improve teacher hiring. We examine the relationship between two screening instruments used by Spokane Public Schools to select classroom teachers and three teacher outcomes: value added, absences, and attrition. We observe all applicants to the district (not only those who are hired), allowing us to estimate sample selection-corrected models using random tally errors and variation in the level of competition across job postings as instruments. Ratings on the screening instruments significantly predict value added in math and teacher attrition, but not absences—an increase of one standard deviation in screening scores is associated with an increase of about 0.06 standard deviations of student math achievement, and a decrease in teacher attrition of 3 percentage points. Hence the use of selection instruments appears to be a key means of improving the quality of the teacher workforce.
Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many-analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size.Statistical significance varied across replications, and for one of the studies the effect's sign varied as well. The standard deviation of estimates across replications was 3-4 times the mean reported standard error.
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