This study investigates whether local gambling norms are associated with audit pricing. Using a religion-based measure of local social gambling norms, we find strong evidence that public firms located in U.S. counties with more liberal gambling norms exhibit higher levels of audit fees. This result is consistent with our view that, as an important external risk factor, clients’ local gambling norms influence audit pricing decisions. Our findings are robust to a battery of sensitivity tests, including non-religion based measures of liberal gambling norms and a natural experiment.
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We do not include these additional controls in the main analysis because they reduce the sample size significantly.
Akerlof (1980) proposes a utility-maximization model that incorporates social sanctions imposed by loss of reputation from breaking custom to rationalize why social customs costly to the individual persist over time.
The evidence is not unanimous. Callen et al. (2011) do not find a relation between religiosity and earnings management in a cross-country study.
Chen et al. (2014) state that “a number of features of innovation make it unappealing for rational managers and investors. These factors include the long-term nature of research projects, the high likelihood of failure, and large information asymmetry between insiders and outside investors.”
Due to data restrictions, most empirical studies do not distinguish between the two effects—increased auditor effort and increased risk premium—with the notable exception of Bell, Landsman, and Shackelford (2001).
Firms headquartered in localities with more liberal gambling norms are also more likely to employ a larger percentage of people with higher propensity to take speculative risks, which indirectly increase firms’ risk-taking.
To control for potential outliers, we winsorize the top and bottom 1% for all variables in the regression. The regression results are quantitatively similar (untabulated) without winsorization.
We control for this through year fixed-effects.
Since audit report lag is a count variable, we also estimated Poisson and Negative Binomial regressions. The results (untabulated) remain robust.
Because of the well-known biases in the coefficient estimates of a logistic regression that includes fixed-effects, we elected to estimate a linear probability model instead. Nevertheless, the results (untabulated) remain robust for a logistic regression without fixed-effects and for a logistic regression with year and industry fixed-effects.
We also controlled for Gompers, Ishii, and Metrick (2003)’s governance measure (G index), and the α1 coefficient remains positive and significant at less than the 1% level.
We also included Altman’s Z-SCORE (Altman 1968) financial distress measure to control for firms’ excessive risk-taking behavior. The results (untabulated) remain very similar.
Based on Liu et al. (2014), we also look at the time-series survey data from the Gallup Corporation regarding social attitudes toward alcohol and tobacco consumption. The survey data are subject to similar concerns as gaming consumption and casino visitations, and are also likely to be a less direct measure of social gambling norms. The untabulated results show mixed evidence when we replace the CP ratio with survey data. Thus, we suggest that readers exercise caution when using the survey data related to social attitudes toward alcohol and tobacco consumption to proxy for social gambling norms.
Since our system is just identified with one instrumental variable, we cannot implement a formal test for the validity of the instrument, which requires the system to be over-identified. In fact, the exclusion restriction cannot be tested directly (Wooldridge 2006). However, with more than one instrument, over-identification tests for exclusion restriction are possible under the assumption that one of the instruments is valid.
An alternative but equivalent difference-in-differences approach includes main effects (i.e., treatment variable and post-event variable, respectively) and an interaction term (i.e., treatment variable * post-event variable). Since our regression model (2) controls for firm and year fixed-effects, the LEG variable here is in fact equivalent to the interaction term in the alternative model. For treatment firms, LEG is switched off in the years before legalization and switched on in the years of and after legalization.
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We are thankful to the editor, Steven Dellaportas, and two anonymous reviewers of this journal for their helpful and constructive comments. We also wish to thank participants at the 2016 CAAA Annual Conference and 2017 Annual Hawaii International Conference on Arts & Humanities for their remarks.
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
Appendix A: Variable Definitions
Appendix A: Variable Definitions
Main Dependent Variable
LN_AUDIT_FEE is the natural logarithm of total audit service fees.
LN_CPRATIO is the natural logarithm of the ratio of Catholic residents to Protestant residents in the county where the firm is headquartered.
LN_ASSETS is the log value of total assets at the end of the fiscal year.
QUICK is current assets minus inventory, divided by current liabilities at the end of the fiscal year.
INV is the ratio of total inventory to total assets at the end of the fiscal year.
REC is the ratio of accounts receivable to total assets at the end of the fiscal year.
LEVERAGE is the book value ratio of liabilities to total assets at the end of the fiscal year.
MB is the ratio of the market value of equity to the book value of equity measured at the end of the fiscal year.
ROA is income before extraordinary items divided by the book value of total assets at the end of the fiscal year.
LOSS is an indicator variable that equals one if the company reports a loss, and zero otherwise.
LN_SEGMENT is the natural logarithm of the number of business segments.
FOREIGN is an indicator variable that equals one if the company has foreign assets, and zero otherwise.
INST is the percentage of the firm’s equity held by institutional investors at the end of the fiscal year.
ANA is the log value of one plus the number of analysts that issue earnings forecasts for a given firm during the fiscal year.
BIG is an indicator variable that equals one if the engagement auditor is a Big 4 or Big 5 auditor, and zero otherwise.
R_OFFICE_SIZE is the percentile rank of the number of clients a local auditor has for each county-year.
AUDIT_LAG is the number of days between the date of a company’s fiscal year- end and the signature date of the audit opinion.
LN_TENURE is the natural logarithm of auditor tenure.
SPECIALIST is an indicator variable that equals one if engagement auditor is a local industry specialist, and zero otherwise.
GOING_CONCERN is an indicator variable that equals one if a going-concern opinion is issued, and zero otherwise.
UNQUALIFIED is an indicator variable that equals one if an unqualified opinion without any additional language is issued, and zero otherwise.
AUDITOR_CHANGE is as an indicator variable that equals one if there is an auditor change, and zero otherwise.
REP is an indicator variable that equals one if a firm’s headquarter is in a county dominated by the Republican Party, and zero otherwise.
CSR is an index of corporate social responsibility (CSR) for each firm-year, based on CSR strengths and concerns reported by the KLD database.
RURAL is an indicator variable that equals one if a firm is headquartered in a rural area, and zero otherwise.
REL is the ratio of religious adherents to total population in the county in which the firm is headquartered.
LN_POP is the natural logarithm of the population in the county.
LN_AGE is the natural logarithm of the median age of people in the county.
MARRIED is the percentage of married people in the county.
LN_INCOME is the natural logarithm of the average income in the county.
MALE is the male-to-female ratio in the county.
MINORITY is the percentage of minorities in the county.
EDU is the percentage of people aged 25 years and older who have a bachelor’s, graduate, or professional degree.
LAWSUIT is an indicator variable that equals one if litigation is filed against the firm and its auditor during the year, and zero otherwise.
LEG is equal to one if the firm is headquartered in a state that passed commercial casino legislation, and zero otherwise.
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Callen, J.L., Fang, X. Local Gambling Norms and Audit Pricing. J Bus Ethics 164, 151–173 (2020). https://doi.org/10.1007/s10551-018-4079-8
- Social norms
- Audit pricing