Learning Why More Learning Takes Place in Some Classrooms Than Others

Abstract. The relatively poor average performance of German students on the recent PISA international evaluations of 15- and 16-year-olds' literary skills (2000) and mathematical skills (2003) and the wide variation in performance, with low-income students scoring particularly poorly, have led to calls for reforms of the German educational system. Understanding why students in some classrooms learn more than do those in other classrooms is an important first step in considering alternative reform strategies. Possible explanations include differences in teacher quality, class sizes and peer groups, and also differences among the types of secondary schools that parents select for their children. This paper illustrates a set of techniques that are useful in examining the roles these factors play in predicting why, net of family background and prior achievement, the average achievement of children in some classrooms is much higher than that of children in other classrooms. We illustrate the use of these techniques with a dataset from Bogotá, Colombia, that has two attractive properties. First, some teachers teach multiple classes of students. Second, students are enrolled in schools in two sectors (public and private). Application of the techniques described in this paper could shed light on the reasons why the average academic achievement of German students attending some schools is much higher than that of German students attending other schools.     

Aggregate implications of indivisible labor, incomplete markets, and labor market frictions

We study the impact of tax and transfer programs on steady-state allocations in a model with search frictions, an operative labor supply margin, and incomplete markets. In a benchmark model that has indivisible labor and incomplete markets but no trading frictions we show that the aggregate effects of taxes are identical to those in the economy with employment lotteries, though individual employment and asset dynamics can be different. The effect of frictions on the response of aggregate hours to a permanent tax change is highly nonlinear. There is considerable scope for substitution between “voluntary” and “frictional” nonemployment in some situations.     

Regulator performance,regulatory environment and outcomes: An examination of insurance regulator career incentives on state insurance markets

In this paper we test whether the past or future labor market choices of insurance commissioners provide incentives for regulators in states with price regulation to either favor or oppose the industry by allowing prices that differ significantly from what would otherwise be the competitive market outcome. Using biographical data on insurance regulators, economic and state specific market structure and regulatory variables, and state premium and loss data on the personal automobile insurance market, we find no evidence consumers in prior approval states paid significantly different “unit prices” for insurance than consumers in states that allow competitive market forces to determine equilibrium prices during the time period 1985–2002. We do, however, find evidence regulators who obtained the position of insurance commissioner by popular election and those who seek higher elective office following their tenure as insurance commissioner allow higher overall “unit prices” relative to competitive market states. The “unit price” of insurance in regulated states is not statistically different from the competitive market outcome for regulators that make lateral moves back into state government and it is mildly higher for regulators who enter the insurance industry following their tenure. Finally, we find some evidence regulators who describe themselves as consumer advocates are successful reducing the price of insurance in favor of consumers in regulated markets. Overall the results are consistent with the existence of asymmetric information in the regulatory process that agents use to enhance their career aspirations.     

Investor recognition and stock returns

It is well established that investment fundamentals, such as earnings and cash flows, can explain only a small proportion of the variation in stock returns. We find that investor recognition of a firm’s stock can explain relatively more of the variation in stock returns. Consistent with Merton’s (J Finance 42(3):483–510, 1987) theoretical analysis, we show that (i) contemporaneous stock returns are positively related to changes in investor recognition, (ii) future stock returns are negatively related to changes in investor recognition, (iii) the above relations are stronger for stocks with greater idiosyncratic risk and (iv) corporate investment and financing activities are both positively related to changes in investor recognition. Our research suggests that investors and managers who are concerned with firm valuation should consider investor recognition in addition to accounting information and related investment fundamentals.     

Evidence on Simulation Inference for Near Unit-Root Processes with Implications for Term Structure Estimation

The high persistence of interest rates has important implicationsfor the preferred method used to estimate term structure models.We study the finite-sample properties of two standard dynamicsimulation methods—efficient method of moments (EMM) andindirect inference—when they are applied to an first orderautoregressive (AR[1]) process with Gaussian innovations. Whensimulated data are as persistent as interest rates, the finite-sampleproperties of EMM differ both from their asymptotic propertiesand from the finite-sample properties of indirect inferenceand maximum likelihood. EMM produces larger confidence boundsthan indirect inference and maximum likelihood, yet is muchless likely to contain the true parameter value. This is primarilybecause the population variance of the data plays a much largerrole in the EMM conditions than in the moment conditions foreither indirect inference or maximum likelihood. These resultssuggest that, under Gaussian assumptions, indirect inference(if practical) is preferable to EMM when working with persistentdata such as interest rates. EMM's emphasis on the populationvariance strongly enforces stationarity on the underlying process,so this same reasoning suggests that EMM may be preferable insettings where stability and stationarity are important anddifficult to impose.     

Nonlinear models for strongly dependent processes with financial applications

This paper is motivated by recent evidence that many univariate economic and financial time series have both nonlinear and long memory characteristics. Hence, this paper considers a general nonlinear, smooth transition regime autoregression which is embedded within a strongly dependent, long memory process. A time domain MLE$MLE$ with simultaneous estimation of the long memory, linear AR$AR$ and nonlinear parameters is shown to have desirable asymptotic properties. The Bayesian and Hannan–Quinn information criteria are shown to provide consistent model selection procedures. The paper also considers an alternative two step estimator where the original time series is fractionally filtered from an initial semi-parametric estimate of the long memory parameter. Simulation evidence indicates that the time domain MLE$MLE$ is generally superior to the two step estimator. The paper also includes some applications of the methodology and estimation of a fractionally integrated, nonlinear autoregressive-ESTAR$ESTAR$ model to forward premium and real exchange rates.