Instrumental variables are widely used in applied econometrics to achieve identification and carry out estimation and inference in models that contain endogenous explanatory variables. In most applications, the function of interest (e.g., an Engel curve or demand function) is assumed to be known up to finitely many parameters (e.g., a linear model), and instrumental variables are used identify and estimate these parameters. However, linear and other finite-dimensional parametric models make strong assumptions about the population being modeled that are rarely if ever justified by economic theory or other a priori reasoning and can lead to seriously erroneous conclusions if they are incorrect. This paper explores what can be learned when the function of interest is identified through an instrumental variable but is not assumed to be known up to finitely many parameters. The paper explains the differences between parametric and nonparametric estimators that are important for applied research, describes an easily implemented nonparametric instrumental variables estimator, and presents empirical examples in which nonparametric methods lead to substantive conclusions that are quite different from those obtained using standard, parametric estimators.

We find that over six hundred auditors with fewer than 100 SEC clients exit the market following SOX. Compared to the non-exiting auditors, the exiting auditors are lower quality, where quality is gauged by: (1) avoidance of AICPA peer reviews and failure to comply with PCAOB rules, and (2) severity of the peer review and inspection reports. In addition, clients of exiting auditors receive higher quality auditing from successor auditors, as captured by a greater likelihood of receiving going concern opinions. Our results suggest that the PCAOB inspections improve audit quality by incentivizing low quality auditors to exit the market.

Economic evaluations of alternative electric generating technologies typically rely on comparisons between their expected “levelized cost” per MWh supplied. I demonstrate that this metric is inappropriate for comparing intermittent generating technologies like wind and solar with dispatchable generating technologies like nuclear, gas combined cycle, and coal. It overvalues intermittent generating technologies compared to dispatchable base load generating technologies. It also likely overvalues wind generating technologies compared to solar generating technologies. Integrating differences in production profiles, the associated variations in wholesale market prices of electricity, and life-cycle costs associated with different generating technologies is necessary to provide meaningful comparisons between them.

We explore whether government ownership affects the cost of debt using a sample of fully and partially privatized companies. On average across firms, a one-percentage-point decrease in government ownership is associated with an increase in the credit spread, used as a proxy for the cost of debt, by three-quarters of a basis point. However, fully privatized companies exhibit lower credit spreads than partially privatized firms, indicating the cost of a lengthy privatization process. Empirical evidence suggests that these findings result from decreasing government guarantees, firm performance improvements, ownership uncertainty, and bondholder-shareholder conflicts. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

We present a revealed preference methodology for empirically analysing collective consumption behaviour. First, we introduce an integer programming (IP) methodology for testing data consistency with collective consumption models that account for publicly as well as privately consumed goods. This IP methodology can include information on “assignable quantities” for private goods. Next, we show that the IP methodology allows for recovering the personalized (Lindahl) prices for the public goods and the personalized quantities for the private goods. In turn, this implies recovery of the sharing rule (i.e. personalized income share levels). An empirical application demonstrates the practical usefulness of the methodology.

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