Search results
1 – 10 of 195
We would like to thank the University of Washington Daniel J. Evans School of Public Affairs and the Haglund Kelley Horngren Jones & Wilder LLP law firm for financial support.
Christopher J. Sweeney, Richard A. Bernardi and Donald F. Arnold
This research examines the effect of auditors’ personal debt on their audit decision making. We developed two different background scenarios that vary the level of the auditor’s…
Abstract
This research examines the effect of auditors’ personal debt on their audit decision making. We developed two different background scenarios that vary the level of the auditor’s personal debt. While one scenario indicated that the partner lived a modest lifestyle and was relatively free of debt, the other indicated that the partner lived an expensive lifestyle and had considerable personal debt. Our data indicate that auditors receiving the higher personal indebtedness scenario were more likely to believe that the auditor in the case study would sign-off on the audit without doing any additional work. We also found that the propensity to believe that the auditor in the case study would sign-off on the audit without doing any additional work decreased as the participants’ rank within the firm increased. Our research documents that a partner’s level of indebtedness could influence the participant’s audit decisions.
Details
Keywords
The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and…
Abstract
The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and ideology of the FTC’s leaders, developments in the field of economics, and the tenor of the times. The over-riding current role is to provide well considered, unbiased economic advice regarding antitrust and consumer protection law enforcement cases to the legal staff and the Commission. The second role, which long ago was primary, is to provide reports on investigations of various industries to the public and public officials. This role was more recently called research or “policy R&D”. A third role is to advocate for competition and markets both domestically and internationally. As a practical matter, the provision of economic advice to the FTC and to the legal staff has required that the economists wear “two hats,” helping the legal staff investigate cases and provide evidence to support law enforcement cases while also providing advice to the legal bureaus and to the Commission on which cases to pursue (thus providing “a second set of eyes” to evaluate cases). There is sometimes a tension in those functions because building a case is not the same as evaluating a case. Economists and the Bureau of Economics have provided such services to the FTC for over 100 years proving that a sub-organization can survive while playing roles that sometimes conflict. Such a life is not, however, always easy or fun.
Details
Keywords
Strong versions of the Precautionary Principle (PP) require regulators to prohibit or impose technology controls on activities that pose uncertain risks of possibly significant…
Abstract
Strong versions of the Precautionary Principle (PP) require regulators to prohibit or impose technology controls on activities that pose uncertain risks of possibly significant environmental harm. This decision rule is conceptually unsound and would diminish social welfare. Uncertainty as such does not justify regulatory precaution. While they should reject PP, regulators should take appropriate account of societal aversion to risks of large harm and the value of obtaining additional information before allowing environmentally risky activities to proceed.
Roman Liesenfeld, Jean-François Richard and Jan Vogler
We propose a generic algorithm for numerically accurate likelihood evaluation of a broad class of spatial models characterized by a high-dimensional latent Gaussian process and…
Abstract
We propose a generic algorithm for numerically accurate likelihood evaluation of a broad class of spatial models characterized by a high-dimensional latent Gaussian process and non-Gaussian response variables. The class of models under consideration includes specifications for discrete choices, event counts and limited-dependent variables (truncation, censoring, and sample selection) among others. Our algorithm relies upon a novel implementation of efficient importance sampling (EIS) specifically designed to exploit typical sparsity of high-dimensional spatial precision (or covariance) matrices. It is numerically very accurate and computationally feasible even for very high-dimensional latent processes. Thus, maximum likelihood (ML) estimation of high-dimensional non-Gaussian spatial models, hitherto considered to be computationally prohibitive, becomes feasible. We illustrate our approach with ML estimation of a spatial probit for US presidential voting decisions and spatial count data models (Poisson and Negbin) for firm location choices.
Details