Abstract
Firms located in communities in which people are, on average, more trusting enjoy some benefits in terms of the power of CEO contracts. We present two pieces of empirical evidence to support this claim: (1) higher average trust in a county is associated with “flatter” executive contracts and (2) when an exogenous shock occurs (such as a scandal involving an important social institution), both trust and contracting move in similar directions. We obtain the first result in a panel specification and the second in a “difference-in-difference” specification that uses the revelation of sex scandals involving the Catholic Church across different U.S. localities.
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Notes
A “flat” contract is a contract that has low power; in other words, a “flat” contract is less sensitive to measures of performance and closer to a “flat” salary.
The difference-in-differences approach is typical in disciplines such as accounting, economics, or finance. See, among others, Angrist and Krueger (1999) for a description of the difference-in-differences approach. They indicate that the approach “is well-suited to estimating the effect of sharp changes in the economic environment or changes in government policy. The [difference-in-differences] method has been used in hundreds of studies in economics, especially in the last two decades, but the basic idea has a long history” (p. 1296).
In economics, an incomplete contract is one that cannot specify what is to be done in every possible contingency (e.g., Grossman and Hart 1986; Hart 1995; Hart and Moore 1990). The remaining ambiguities have to be resolved through renegotiation or through the intervention of a third party (e.g., a court). This resolution may impose an additional cost on the different parties.
When moral hazard is applied to executive employment, it is often referred to as the agency problem (Jensen 1986).
This prediction does not necessarily imply that trust is an optimal form of contracting in the sense that it may be sub-optimal for the principal to incur costs to build trust. Rather, we hypothesize that organizations endowed with trust may be able to capitalize on this advantage.
We conducted a search of the newspapers for the first mention of the scandal in different counties. We identified a few cases that may have indeed been revealed at a later date. In these cases, we used the date when the scandal was first reported.
More technical information on the survey can be found at http://www3.norc.org/GSS+Website. The General Social Survey (GSS) is a project of the independent research organization NORC at the University of Chicago, with principal funding from the National Science Foundation. We acknowledge that NORC at the University of Chicago, and all parties associated with the General Social Survey (including the principal investigators), offer the data and documentation “as is” with no warranty and assume no legal liability or responsibility for the completeness, accuracy, or usefulness of the data, or fitness for a particular purpose. Some of the data used in this analysis are derived from Sensitive Data Files of the GSS, obtained under special contractual arrangements designed to protect the anonymity of respondents. These data are not available from the authors. Persons interested in obtaining GSS Sensitive Data Files should contact the GSS at GSS@NORC.org.
This sample starts in 1992 because compensation-related variables are only available from 1992 onwards from the Execucomp database. It stops in 2010 to offer a balance period around the shock (i.e., we use nine years before the scandal to nine years after the scandal) from the period covered in the main sample (1998–2005).
Both Delta and Vega are computed utilizing the Execucomp Database. We thank Lalitha Naveen for making these data available to us.
However, we note that ordinary least squares (OLSs) estimations (such as the one used in Table 3 Panel A) yield the Best Linear Unbiased Estimators (BLUE), while hierarchical models only yield the Best Linear Unbiased Predictors (BLUP).
Note that the main effects of Post and Treat are absorbed by the time- and county-fixed effects, respectively.
Note that the main effects of Post and Treat are absorbed by the time- and firm-fixed effects, respectively.
Untabulated results from an OLS estimation are similar.
We identify 2037 CEO turnover events from Execucomp over the 1993–2010 period. When we impose the further constraint that departing CEOs join another firm in the Execucomp universe, we are left with 107 events.
Conversely, Al-Najjar and Casadesus-Masanell (2002) indicate that the presence of these beliefs is a necessary condition to work under incomplete contracts and that there is a monotonic relationship between the principal’s ability to hold these beliefs and their expected profit.
Although exploring the antecedent of trust can be a very interesting topic, it is beyond the scope of this study.
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Acknowledgements
We thank Ying-Chi Huang, Shuo Li, Yuan Zhao, and the workshop participants at INSEAD, the University of Amsterdam, the University of Melbourne, the University of New South Wales, the University of Queensland, WHU, and the 2015 CAPANA Conference (Shanghai) for their valuable comments. We gratefully acknowledge financial support from the School of Accountancy Research Center (SOAR) at Singapore Management University and from Georgetown University. The project was initiated when both authors were at INSEAD.
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Appendices
Appendix 1
Variable definitions
Variables | Definition |
|---|---|
Trust | Trust constructed from the GSS. The survey asks whether people can be trusted, to which respondents answer “can be trusted” (assigned a value of 3), “can’t be trusted” (assigned a value of 1) or “depends or don’t know” (assigned a value of 2). We then average across all respondents from one county to obtain a county-level measure of trust for each year. When the trust measure is not available for that year, we interpolate the value from the most recently available value |
Delta | Log of the dollar change in wealth associated with a 0.01 change in the standard deviation of the firm’s returns. Obtained from Coles et al. (2013) |
Vega | Log of the dollar change in wealth associated with a 1% change in the firm’s stock price. Obtained from Coles et al. (2013) |
PPE Growth | Change in PPE over lagged assets |
Tobin | Market value of equity plus the book value of assets minus the sum of the book value of common equity and deferred taxes, all divided by the book value of assets |
Firm Age | Log of firm age, where age is calculated as number of years since a firm first appeared in the CRSP |
Firm Size | Log of total assets |
Leverage | Short-term debt plus long-term debt, divided by total assets |
ROA | Operating income before depreciation expenses over lagged total assets |
Capex/AT | Capital expenditure over total assets |
%Catholic | Percentage of Catholic population at the county level. When the measure is not available in that year, we interpolate the value from the most recently available value |
% Female | Percentage of females in the county-level population. When the measure is not available in that year, we interpolate the value from the most recently available value |
Education | Percentage of population with at least a bachelor’s degree at the county level. When the measure is not available in that year, we interpolate the value from the most recently available value |
Income | Income per capita at the county level. When the measure is not available in that year, we interpolate the value from the most recently available value |
Ethnicity | Percentage of white population at the county level. When the measure is not available in that year, we interpolate the value from the most recently available value |
% Vote Democrats | Percentage of vote cast for Democratic president. When the measure is not available in that year, we interpolate the value from the most recently available value |
Post | Indicator equal to one for observations from 2002 onward and zero otherwise |
Treat | Indicator equal to one for firms located in counties affected by a scandal in the Catholic |
D(t = − 2) | Indicator equal to one if it is 2 years prior to the report of the Catholic church scandal and zero otherwise |
D(t = − 1) | Indicator equal to one if it is 1 year prior to the report of the Catholic church scandal and zero otherwise |
D(t = 0) | Indicator equal to one if it is the year during which the Catholic church scandal was reported and zero otherwise |
D(t = 1) | Indicator equal to one if it is 1 year after the report of the Catholic church scandal and zero otherwise |
D(t ≥ 2) | Indicator equal to one if it is two or more years after the report of the Catholic church scandal and zero otherwise |
Appendix 2
List of counties with scandals where Catholic Church scandals have been reported
State names | County names | First news report |
|---|---|---|
Alaska | Anchorage | 28Apr2002 |
Arizona | Maricopa | 07Jun2002 |
Arizona | Pima | 13Dec2001 |
California | Alameda | 11Apr2002 |
California | Los Angeles | 28Apr2002 |
California | Orange | 21Aug2001 |
California | Sacramento | 28Jan2002 |
California | San Bernardino | 13Feb2002 |
California | San Diego | 31Jan2002 |
California | Santa Barbara | 04Mar2002 |
California | Santa Clara | 27Mar2002 |
California | Sonoma | 15Mar2002 |
Colorado | Denver | 20Mar2002 |
Connecticut | Fairfield | 19Mar2002 |
Delaware | Newcastle | 07Apr2002 |
Florida | Palm beach | 11Feb2002 |
Illinois | Cook | 15Mar2002 |
Illinois | Will | 17Apr2002 |
Indiana | Marion | 20Mar2002 |
Kansas | Wyandotte | 18Jun2002 |
Kentucky | Kenton | 19Mar2002 |
Maryland | Baltimore | 26Jan2002 |
Massachusetts | Norfolk | 03Feb2002 |
Massachusetts | Suffolk | 08May2001 |
Massachusetts | Worcester | 31Aug2001 |
Michigan | Kent | 18May2002 |
Michigan | Wayne | 29Mar2002 |
Minnesota | Ramsey | 13Apr2002 |
Missouri | Jackson | 03Jul2002 |
Missouri | St. Louis | 03Jul2001 |
New Jersey | Camden | 12Apr2002 |
New York | Kings | 23May2002 |
New York | Monroe | 27Feb2002 |
New York | Nassau | 15Mar2002 |
New York | New York | 28Apr2002 |
New York | Orange | 21Aug2001 |
North Carolina | Wake | 25Apr2002 |
Ohio | Cuyahoga | 29Mar2002 |
Ohio | Hamilton | 18Mar2002 |
Oregon | Multnomah | 06Nov2001 |
Pennsylvania | Allegheny | 18Apr2002 |
Pennsylvania | Philadelphia | 05Feb2002 |
South Carolina | Charleston | 12Mar2002 |
Tennessee | Davidson | 18Mar2002 |
Tennessee | Shelby | 30Apr2002 |
Texas | Bexar | 23Apr2002 |
Texas | Dallas | 17Mar2002 |
Texas | Tarrant | 15Aug2002 |
Vermont | Chittenden | 12Apr2002 |
Washington | King | 10Apr2002 |
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Hilary, G., Huang, S. Trust and Contracting: Evidence from Church Sex Scandals. J Bus Ethics 182, 421–442 (2023). https://doi.org/10.1007/s10551-021-04996-w
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DOI: https://doi.org/10.1007/s10551-021-04996-w