Although wide variation in teacher effectiveness is well established, much less is known about differences in teacher improvement over time. We document that average returns to teaching experience mask large variation across individual teachers, and across groups of teachers working in different schools. We examine the role of school context in explaining these differences using a measure of the professional environment constructed from teachers’ responses to state-wide surveys. Our analyses show that teachers working in more supportive professional environments improve their effectiveness more over time than teachers working in less supportive contexts. On average, teachers working in schools at the 75th percentile of professional environment ratings improved 20% more than teachers in schools at the 25th percentile after five years.
Attracting and retaining effective teachers in high-poverty, urban schools remains a critical challenge. Some scholars interpret high turnover rates at these schools as evidence that teachers prefer to work with wealthier, whiter groups of students. Others argue that teachers are leaving behind the poor working conditions that tend to prevail in these schools. We interviewed 95 teachers and administrators in six high-poverty, urban schools in order to understand teachers’ views about their work with students and how school context influences their experience. We found that most teachers chose their schools, and stayed, because of their students. However, when schools failed to provide instructional supports, an orderly environment and extra assistance for students, teachers expressed frustration and their intentions to leave.
In this paper, we develop bias formulas for front-door estimates and front-door/back- door hybrid estimates of average treatment effects under general patterns of measured and unmeasured confounding. These bias formulas allow for sensitivity analysis, and also allow for comparisons of the bias resulting from standard back-door covariate ad- justments (also known as direct adjustment and standardization). We also present these bias comparisons in two special cases: linear structural equation models and nonrandomized program evaluations with one-sided noncompliance. These compar- isons demonstrate that there are broad classes of applications for which the front-door or hybrid adjustments will be preferred to the back-door adjustments. We illustrate this point with an application to the National JTPA (Job Training Partnership Act) Study, showing that by using information on enrollment in addition to pre-treatment covariates, the front-door approach provides estimates that are closer to the experi- mental benchmark than the back-door approach.
In a one-shot Prisoners’ dilemma experiment, female participants are highly sensitive
to the social frame. Male participants are not. Additional evidence suggests that the operative gender difference is in beliefs, not preferences.
The recent housing bust precipitated a wave of mortgage defaults, with over seven percent of the owner-occupied housing stock experiencing a foreclosure. This paper presents a model that shows how foreclosures can exacerbate a housing bust and delay the housing market's recovery. By raising the ratio of sellers to buyers, by making buyers more selective, and by changing the composition of houses that sell, foreclosures freeze up the market for retail (non-foreclosure) sales and reduce both price and volume. Because negative equity is necessary for default, these general equilibrium effects on prices can create price-default spirals that amplify an initial shock. To assess the magnitude of these channels, the model is calibrated to simulate the downturn. The amplification channel is significant. The model successfully explains aggregate and retail price declines, the foreclosure share of volume, and the number of foreclosures both nationwide and across MSAs. While the model can explain variation in sales across MSAs, it cannot account for the aggregate level of the volume decline, suggesting that other forces have reduced sales nationwide. The quantitative analysis implies that from 2007 to 2011 foreclosures exacerbated aggregate price declines by approximately 50 percent and declines in the prices of retail homes by approximately 30 percent.
Why are contracts incomplete? Transaction costs and bounded rationality cannot be a total explanation since states of the world are often describable, foreseeable, and yet are not mentioned in a contract. Asymmetric information theories also have limitations. We offer an explanation based on “contracts as reference points”. Including a contingency of the form, “The buyer will require a good in event E”, has a benefit and a cost. The benefit is that if E occurs there is less to argue about; the cost is that the additional reference point provided by the outcome in E can hinder (re)negotiation in states outside E. We show that if parties agree about a reasonable division of surplus, an incomplete contract can be strictly superior to a contingent contract.
We present new evidence on the relationship between employee productivity and job tenure using data from the teacher labor market. Econometric challenges require identifying assumptions to model the within-teacher returns to experience with teacher fixed effects. We describe the bias introduced by violations of two common assumptions, and we propose a third approach with a different and empirically-testable assumption. Consistent with past research, we find that teachers experience rapid productivity growth early in their careers. However, we find suggestive evidence of returns to experience later in the career, indicating that teachers continue to build human capital beyond these first years.
Using the Rosenbaum (2002, 2009) approach to observational studies, we show how qualitative information can be incorporated into quantitative analyses to improve causal inference in three ways. First, we can ameliorate the effects of difficult-to-measure outcomes by including qualitative information on outcomes within matched sets, sometimes reducing p-values. Second, additional information across matched sets enables the construction of qualitative confidence intervals on effect size. Third, qualitative information on unmeasured confounders within matched sets reduces the conservativeness of Rosenbaum-style sensitivity analysis. This approach accommodates small to medium sample sizes in a nonparametric framework, and therefore may be particularly useful for analyses of the effects of institutions in a given set of countries or subnational units. We illustrate these methods by examining the effect of using plurality rules in transitional presidential elections on opposition harassment in 1990s sub-Saharan Africa.
