Proxy (statistics)

About: Proxy (statistics) is a research topic. Over the lifetime, 5257 publications have been published within this topic receiving 94504 citations. The topic is also known as: proxy variable & proxy measurement.

Ownership studies: The data source does matter

Abstract: We examine the fit between the ownership data provided by four surrogate databases and the data collected from proxy statements. We discover an unambiguous pecking order among the surrogates relative to the benchmark ownership statistics of corporate proxy statements. Corporate Text is first, followed in descending order by Compact Disclosure, Value Line, and Spectrum. Further tests show that reporting discrepancies in the Value Line and Spectrum databases could affect economic inferences drawn from regressions using their ownership data. A field guide describing each data source's reporting conventions, formats, and strate? gies for data aggregation may be downloaded from the Journal of Financial and Quantitative Analysis' web site (http.V/weber.u.washington.edu/~jfqa/hola7andeapdx.pdf).

Causal Inference and Omitted Variable Bias in Financial Aid Research: Assessing Solutions.

Abstract: This article highlights the problem of omitted variable bias in research on the causal effect of financial aid on college‑going. I first describe the problem of self‑selection and the resulting bias from omitted variables. I then assess and explore the strengths and weaknesses of random assignment, multivariate regression, proxy variables, fixed effects, difference‑in‑differences, regression discontinuity, and instrumental variables techniques in addressing the problem. I focus on the intuition, assumptions, and applications of each method in the context of the same research question, providing practical guidance for researchers interested in implementing these approaches.

The Market Portfolio May Be Mean/Variance Efficient After All

Abstract: Numerous studies have examined the mean/variance efficiency of various market proxies by employing sample parameters and have concluded that these proxies are inefficient. These findings cast doubt about the capital asset pricing model (CAPM), one of the cornerstones of modern finance. This study adopts a reverse-engineering approach: given a particular market proxy, we find the minimal variations in sample parameters required to ensure that the proxy is mean/variance efficient. Surprisingly, slight variations in parameters, well within estimation error bounds, suffice to make the proxy efficient. Thus, many conventional market proxies could be perfectly consistent with the CAPM and useful for estimating expected returns. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

The Impact of Uncertainty Shocks under Measurement Error: A Proxy SVAR Approach

Abstract: A growing literature considers the impact of uncertainty using SVAR models that include proxies for uncertainty shocks as endogenous variables. In this paper, we consider the impact of measurement error in these proxies on the estimated impulse responses. We show via a Monte Carlo experiment that measurement error can result in attenuation bias in impulse responses. In contrast, the proxy SVAR that uses the uncertainty shock proxy as an instrument does not suffer from this bias. Applying this latter method to the Bloom (2009) data set results in impulse responses to uncertainty shocks that are larger in magnitude and more persistent than those obtained from a recursive SVAR.