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Self-employment and mental health

Abstract

This paper analyzes the role of mental health in self-employment decisions. We find evidence of a relationship between psychological distress and self-employment for men that depends on type of self-employment and severity of psychological distress. Specifically, there is suggestive evidence of a causal link from moderate psychological distress to self-employment in an unincorporated business as a main job for men. Additionally, we find evidence that long term mental illness can significantly increase the probability of self-employment in an unincorporated business for both men and women. Our results suggest that individual difficulty in wage-and-salary employment is the likely mechanism for this connection.

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Fig. 1

Notes

  1. https://www.entrepreneur.com/article/321463

  2. While we follow Levine & Rubinstein (2017) in interpreting unincorporated self-employment as reflecting a poor fit with wage-and-salary labor, there is the possibility that individuals may seek self-employment for some specific benefit. Our data do not allow for any more detailed evaluation of motivation for self-employment. This suggests some care is needed in interpretation of the results that follow.

  3. The PSID does have a high proportion of African American households, as the panel oversampled low income households from urban areas and the rural south.

  4. Data from year 2001 is used for lagged mental health variables.

  5. We do exclude respondent householders who are neither head, nor spouse, nor long term co-habitor, since there is no employment data for those who are not head/spouse/long term co-habitor.

  6. We combined married and single people because a Chow test indicates that the coefficients for single individuals are not jointly statistically significantly different from those for married individuals (F = 1.14, p = 0.3256).

  7. Within the PSID sample, who is the respondent can be correlated with who is descendant from an original PSID household and the original PSID sample focused on male respondents. This implies that the respondent householder is not entirely random. To address this concern, we analyze if couple households with the wife as a respondent are similar to couple households with the husband as a respondent in terms of basic characteristics: age, education, net worth, home ownership, financial distress, number of children, race, ethnicity, health status indicators. The differences in the health status indicator variables are not statistically significant. The differences in the other characteristic variables are statistically significant, but the actual values of the differences are small for all variables except race and net worth.

  8. An incorporated business is a legal entity that is recognized as a person under the law. An unincorporated business is a privately owned business in which the owners have unlimited liability as the business is not legally registered as a company. Since unincorporated businesses are essentially extensions of their owners, these organizations have a finite life—each unincorporated business can only last as long as the owners live. While an unincorporated owner may be able to share business assets, (s)he is generally unable to sell his/her interest in the business because the business is legally an extension of him/herself. Additionally, unincorporated business owners must report their share of the business income and losses on their personal returns. In contrast, an incorporated business is independent and not tied to the life of any person. As a result, an incorporated business, theoretically, could last forever. Since an incorporated business is legally independent, an owner’s interest in the business can be transferred without affecting the business itself. Incorporated businesses must pay taxes on any income it earns. Then, if it distributes any income to its owners, the owners must pay tax on any cash they receive. (Source—http://info.legalzoom.com/difference-between-incorporated-unincorporated-businesses-24040.html)

  9. Only 0.4% of the male sample and 0.2% of the female sample include respondents with wage-and-salary as a main job and incorporated business as a secondary job. Thus, these respondents are included in this category.

  10. The PSID asks about up to four jobs where job 1 is the current or last main job and jobs 2–4 are current or past other jobs. However, we only include in the analysis jobs that the person had not left in the last two years. So, all of the jobs can be described as “current” meaning the job was held since the last wave.

  11. Note that 0.4% of unique males were unemployed in all waves, 1.5% of unique males were OLF in all waves, 0.4% of unique females were unemployed in all waves, and 3.0% of unique females were OLF in all waves. While these figures are non-trivial, these individuals are dropped in the fixed effects model specifications so do not influence our results.

  12. In addition to the K-6 related questions, the PSID also asks whether the respondent has EVER been diagnosed with any emotional, nervous, or psychiatric problems by a doctor. This question is asked in every wave beginning in 2001. We do not utilize this variable in our primary analysis as there are drawbacks to the diagnosis question. The timing is not specific and because the question requires a doctor visit, it captures socioeconomic status and health care preferences along with mental health status. Furthermore, the self-reports of lifetime diagnosis in the PSID survey are often inconsistent longitudinally as “individuals alter their reports to make past states consistent with current states” (Aneshensel et al., 1987).

  13. As a robustness check, we estimate a model that utilizes both a K-6 score continuous variable and a K-6 score squared continuous variable and find results consistent with our main specification.

  14. The PSID does have a high proportion of African American households as the panel oversampled low income households from urban areas and the rural south.

  15. Note that within our fixed effects specification, the number of biological children variable will capture the effect of having a baby on both employment decisions and psychological distress.

  16. If consumer debt equals 0 and household income equals 0, then the financial distress variable is set to 0. If consumer debt is greater than household income, then the financial distress variable is set to 1. Approximately six percent of the sample had more debt than income. For the sample with more debt than income, the median financial distress indicator value was 1.8 with a maximum value of over 100,000. To minimize the effect of these outlier ratios, we truncated this variable at 1.

  17. We obtain the unemployment rate data from the Bureau of Labor Statistics (BLS) website.

  18. If the respondent race observation was missing, we used the national average for the gender of the respondent. The BLS only provides unemployment rate data for four ethnic groups: Caucasian, African American, Asian, and Latino/Hispanic. For the other race group, we utilize the Asian unemployment rate.

  19. Only 0.4% of the male sample and 0.2% of the female sample include respondents with wage-and-salary as a main job and incorporated business as a secondary job. Thus, these respondents are included in this category.

  20. Our identification strategy includes lagged employment, similar to the Case et al. (2005) approach which also utilizes the reasoning of Granger causality to overcome similar identification challenges.

  21. It is unlikely that current employment affects previous mental health measures. Further, our fixed effects model addresses the concern that both mental health and self-employment could have been influenced by longstanding situations.

  22. We test for multicollinearity in our models. In all of the models, the variance inflation factor (VIF) is always below 2.83.

  23. A less robust push-pull effect also could be identified by the relative magnitudes of the coefficient of the effect of mental distress on unincorporated business ownership and the coefficient of the effect of mental distress on incorporated business ownership. If mental distress “pushes” individuals into entrepreneurship, the unincorporated business ownership coefficient would be larger than the incorporated business ownership coefficient. If mental distress “pulls” individuals into entrepreneurship, the incorporated business ownership coefficient would be larger than the unincorporated business ownership coefficient.

  24. Given that the identified respondent for a household can change between PSID waves, the fixed effects model also would drop households with respondent changes between waves. We did conduct analysis comparing couple households that change who is the respondent with couple households who do not change. There are only changes in respondents in 23% of the person-year observations. If the couple respondent is different than in the last wave, the couple is significantly younger on average than if the couple respondent is the same. Correspondingly, this couple household has less wealth, is less likely to be a homeowner, and is healthier on average.

  25. The fixed effects sample size is significantly smaller but notably, those in the fixed effects sample and the full sample have similar distributions of K-6 scores. The fixed effects sample does differ from the full sample in expected ways. For example, those in the fixed effects sample are less likely to be wage-and-salary employees and more likely to have been self-employed, and they are less likely to have health insurance (which is more common with wage-and-salary employment).

  26. These measures capture mental health conditions that are removed by our fixed effects models.

  27. https://www.nimh.nih.gov/health/topics/men-and-mental-health/

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Acknowledgements

We would like to thank John Cawley, Janet Currie, Angus Deaton, David Bradford, and seminar participants at Cornell University, Duke University, Princeton University, and the University of Georgia.

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Correspondence to Vicki L. Bogan.

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Appendices

Appendix

A. Description of variables used in primary analysis

Employment variables

  • Employment Status Unordered Categorical Variable (six categories): Each respondent is asked about up to four jobs where job 1 is the current or last main job and jobs 2-4 are current or past other jobs. For this variable, we only include in the analysis jobs that the person has not left in the last two years. Thus, all of the jobs can be described as "current" meaning the job was held since the last wave. For each job, they are asked whether this job involves being self-employed or employed by someone else. If they respond that they are self-employed, then they are asked if that is an unincorporated business or a corporation. From these three questions, we categorize each head and spouse as one of the following: (1) wage-and-salary employment only, (2) wage-and-salary employment with an unincorporated business as a secondary job, (3) main job is self-employment in an unincorporated business, (4) is self-employed in an incorporated business, (5) unemployed, or (6) out of the labor force. Note that only 0.4% of the male sample and 0.2% of the female sample include respondents with wage-and-salary as a main job and incorporated business as a secondary job. Thus, both respondents with an incorporated business as a main job and respondents with an incorporated business as a secondary job are included in one category.

Mental health variables

  • Moderate Psychological Distress Dummy Variable (lagged one wave)—The respondent is asked a series of 6 questions about their current feelings. The questions ask the respondent to rate the following feelings on a scale of 0 (=none of the time) to 4 (=all of the time): whether he/she has felt sad, nervous, restless, hopeless, worthless, and that everything was an effort in the last 30 days. These question responses are summed to create the K-6 non-specific psychological distress score. If the K-6 score is between 5 and 12 (inclusive) this variable is given a value of 1 and is set to 0 otherwise.

  • High Psychological Distress Dummy Variable (lagged one wave)—The respondent is asked a series of 6 questions about their current feelings. The questions ask the respondent to rate the following feelings on a scale of 0 (=none of the time) to 4 (=all of the time): whether he/she has felt sad, nervous, restless, hopeless, worthless, and that everything was an effort in the last 30 days. These question responses are summed to create the K-6 non-specific psychological distress score. If the K-6 score is higher than 12 this variable is given a value of 1 and is set to 0 otherwise.

  • Mental Health Diagnosis Dummy Variable—A dummy variable that is given a value of 1 if the individual has been told by a doctor that he/she has or had any emotional, nervous, or psychiatric problems and is set to 0 otherwise.

Demographic characteristic variables

  • Age Variable—The age in years of the individual.

  • African American Dummy Variable—A dummy variable that is given a value of 1 if the individual is African American and is set to 0 otherwise.

  • Hispanic Dummy Variable—A dummy variable that is given a value of 1 if the individual is Hispanic and is set to 0 otherwise.

  • Other Race Dummy Variable—A dummy variable that is given a value of 1 if the individual is not Caucasian, African American, or Hispanic, and is set to 0 otherwise.

  • Married Dummy Variable—A dummy variable that is given a value of 1 if the individual is married and is set to 0 otherwise.

  • Number of Children Variable—A variable indicating the number of children under the age of 18 currently in the household.

Socio-economic status variables

  • No High School Diploma—A dummy variable that is given a value of 1 if the individual reports that their completed years of education is less than 12, and is set to 0 if otherwise.

  • Some College—A dummy variable that is given a value of 1 if the individual reports that their completed years of education is greater than 12 and less than 16, and is set to 0 if otherwise.

  • College Graduate—A dummy variable that is given a value of 1 if the individual reports that their completed years of education is greater than 16, and is set to 0 if otherwise.

  • Log of Household Net Worth—The natural logarithm of the combined value of stock holdings, savings accounts, checking accounts, government bonds, T-bills, a valuable collection, bond funds, rights in a trust or estate, holdings in a farm or business, real estate other than the main home, and assets in IRA accounts, Keogh accounts, 401Ks or similar defined contribution pension plans, net of the value of debt from credit cards charges, student loans, medical or legal bills, or loans to relatives. It also includes main home and second home equity and the net value of vehicles. All dollar values are adjusted to 2017 US$ using the all-item CPI-U from the Bureau of Labor Statistics.)

  • Own Home (Primary Residence) Dummy Variable—A dummy variable that is given a value of 1 if the respondent owns or is buying a home and is set to 0 otherwise.

  • Financial Distress Indicator—The value of household consumer debt (Household consumer debt includes credit card charges, student loans, medical or legal bills, or loans from relatives but does NOT include any mortgage on a primary residence or vehicle loans.) divided by household income, \(\frac{\,{{\mbox{consumer debt}}}}{{{\mbox{household income}}}\,}\). The scale goes from 0 to 1 where 1 is distressed. Approximately six percent of the sample had more debt than income. For the sample with more debt than income, the median financial distress indicator value was 1.8 with a maximum value of over 100,000. To minimize the effect of these outlier ratios, we truncated values at 1.

Physical health-related variables

  • Number of Chronic Conditions Variable—A variable that counts the number of chronic conditions that a doctor has ever told them they had from the following list of possible conditions: high blood pressure or hypertension; diabetes or high blood sugar; cancer or a malignant tumor (excluding skin cancer); chronic lung disease such as bronchitis or emphysema; coronary heart disease, angina, congestive heart failure; or arthritis or rheumatism. This variable ranges between 0 and 6. This variable is recorded separately for the husband and wife in couple households.

  • Total Medical Expenditures Variable—A variable that sums together all out-of-pocket expenditures for health insurance premiums; nursing home or hospital care; doctor, outpatient surgery, or dental care; and prescriptions, in-home medical care, special facilities, or other services for any member of the household. (All dollar values are adjusted to 2017 US$ using the all-item CPI-U from the Bureau of Labor Statistics.)

  • Has Health Insurance Variable—A dummy variable that is given a value of 1 if the respondent was covered by health insurance for the full prior year, and 0 otherwise.

Other control variables

  • Year Dummy Variables—Dummy variables for years 2001, 2003, 2007, 2009, 2011, 2013, and 2015.

  • Unemployment Rate Variable—A continuous variable indicating the national unemployment rate specific for each individual’s race (white, African-American, Hispanic, and Asian=Other) and gender, and the interview year. Values ranged from 3.1 to 17.8.

B. Fixed effects sample descriptive statistics

Tables 1214.

Table 12 Control variable statistics—fixed effects sample
Table 13 Self-employment occupational categories—fixed effects sample
Table 14 Effects of psychological distress on employment decisions (main job)—no fixed effects

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Bogan, V.L., Fertig, A.R. & Just, D.R. Self-employment and mental health. Rev Econ Household 20, 855–886 (2022). https://doi.org/10.1007/s11150-021-09578-3

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JEL classification

  • J24
  • J23
  • I10

Keywords

  • Entrepreneurship
  • Self-employment
  • Occupational choice
  • Mental health