Tone at the Bottom: Measuring Corporate Misconduct Risk from the Text of Employee Reviews

Management Science ◽

10.1287/mnsc.2021.4211 ◽

2021 ◽

Author(s):

Dennis W. Campbell ◽

Ruidi Shang

Keyword(s):

Statistical Methods ◽

Firm Size ◽

Press Coverage ◽

Organizational Cultures ◽

Inside Information ◽

Corporate Misconduct ◽

Out Of Sample ◽

Industry Risk

This paper examines whether information extracted via text-based statistical methods applied to employee reviews left on the website Glassdoor.com can be used to develop indicators of corporate misconduct risk. We argue that inside information on the incidence of misconduct as well as the control environments and broader organizational cultures that contribute to its occurrence are likely to be widespread among employees and to be reflected in the text of these reviews. Our results show that information extracted from such text can be used to develop measures with useful properties for measuring misconduct risk. Specifically, the measures we develop clearly discriminate between high- and low-misconduct-risk firms and improve out-of-sample predictions of realized misconduct risk above and beyond other readily observable characteristics, such as Glassdoor firm ratings, firm size, performance, industry risk, violation history, and press coverage. We provide further evidence on the efficacy of our text-based measures of misconduct risk by showing that they are associated with future employee whistleblower complaints even after controlling for these same observable characteristics. This paper was accepted by Brian Bushee, accounting.

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Pengaruh Profitabilitas, Struktur Aktiva, Resiko Bisnis, dan Ukuran Perusahaan Terhadap Struktur Modal

Jurnal Kajian Manajemen Bisnis ◽

10.24036/jkmb.10838000 ◽

2017 ◽

Vol 6 (2) ◽

Author(s):

Rahmiati Rahmiati ◽

Halkadri Fitra ◽

Fastri Prisma Grizmaldy

Keyword(s):

Capital Structure ◽

Statistical Methods ◽

Firm Size ◽

Sampling Method ◽

Stock Exchange ◽

Business Risk ◽

Multiple Regressions ◽

Mining Companies ◽

Insignificant Effect ◽

Research Populations

The purpose of this research is to examine the effect of profitability, asset structure, business risk, and firm size to capital structure. The research populations are 44 mining companies which listed In Indonesian Stock Exchange (IDX) with 11 research samples around 2011-2015. This research used purposive sampling method. The statistical methods used in this research are multiple regressions. The result shows that insignificant effect of profitability, business risk, and firm size to capital structure and positive significant effect of asset structure to capital structure. Keywords: Profitability, Asset Structure, Business Risk, Firm size, Capital Structure

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Comparing Random Forest with Logistic Regression for Predicting Class-Imbalanced Civil War Onset Data

Political Analysis ◽

10.1093/pan/mpv024 ◽

2016 ◽

Vol 24 (1) ◽

pp. 87-103 ◽

Cited By ~ 77

Author(s):

David Muchlinski ◽

David Siroky ◽

Jingrui He ◽

Matthew Kocher

Keyword(s):

Logistic Regression ◽

Civil War ◽

Statistical Methods ◽

Random Forests ◽

Binary Data ◽

Rare Events ◽

Rare Event ◽

Sample Data ◽

Out Of Sample ◽

Civil War Onset

The most commonly used statistical models of civil war onset fail to correctly predict most occurrences of this rare event in out-of-sample data. Statistical methods for the analysis of binary data, such as logistic regression, even in their rare event and regularized forms, perform poorly at prediction. We compare the performance of Random Forests with three versions of logistic regression (classic logistic regression, Firth rare events logistic regression, andL1-regularized logistic regression), and find that the algorithmic approach provides significantly more accurate predictions of civil war onset in out-of-sample data than any of the logistic regression models. The article discusses these results and the ways in which algorithmic statistical methods like Random Forests can be useful to more accurately predict rare events in conflict data.

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Statistics and parallaxes

International Astronomical Union Colloquium ◽

10.1017/s0252921100073875 ◽

1978 ◽

Vol 48 ◽

pp. 7-29

Author(s):

T. E. Lutz

Keyword(s):

Experimental Design ◽

Statistical Methods ◽

Review Paper ◽

Systematic Errors ◽

Past Experience ◽

Random Errors ◽

Trigonometric Parallaxes ◽

Systematic And Random Errors

This review paper deals with the use of statistical methods to evaluate systematic and random errors associated with trigonometric parallaxes. First, systematic errors which arise when using trigonometric parallaxes to calibrate luminosity systems are discussed. Next, determination of the external errors of parallax measurement are reviewed. Observatory corrections are discussed. Schilt’s point, that as the causes of these systematic differences between observatories are not known the computed corrections can not be applied appropriately, is emphasized. However, modern parallax work is sufficiently accurate that it is necessary to determine observatory corrections if full use is to be made of the potential precision of the data. To this end, it is suggested that a prior experimental design is required. Past experience has shown that accidental overlap of observing programs will not suffice to determine observatory corrections which are meaningful.

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