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Would you Value a few More Hours of work? Underemployment and Subjective Well-Being Across Chilean Workers

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Abstract

Underemployment has gained attention in recent years because of its effects on health and well-being (life satisfaction), it is a widespread phenomenon in the labor force that affects not only workers, but also households, companies and governments. This paper explores the relationship between underemployment and subjective well-being for a representative sample of Chilean workers using an ordered probit model. Also, by using different underemployment definitions and a latent class ordered probit model we analyze the observed and unobserved heterogeneity in this relationship. Finally, we assess the monetary valuation of well-being costs by estimating the amount of money that a worker is willing to accept in order to bear the potential negative effects of underemployment on well-being. Our results find a negative relationship between underemployment and subjective well-being, as the average worker is willing to accept an increase of CLP$64,009 (roughly 30.5% of the minimum wage) in her/his monthly wage for being underemployed. If we take into account the observed and unobserved heterogeneity, our results identify a group that is not sensitive to underemployment, while others are willing to accept an increase of CLP$146,622 in her/his monthly wage for being underemployed. Our work highlights the importance of well-being in the workplace and has implications for labor flexibility legislation and the empowerment of workers. Heterogeneous responses to underemployment imply that one-size-fits-all policies to regulate working hours might not suffice.

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Notes

  1. The large reduction in the sample is due to the fact that we dropped 129,792 non-workers respondents, 3,881 individuals with an age less than 18 or more than 65, 55,098 individuals that do not report SWB, wage or underemployment, and 152 individuals with no information in other variables used in the estimations.

  2. As we can see in Fig. 1, these four categories (now grouped in category 1) represent only 6% of total responses. This collapse might lead to missing information and less efficient estimators (Greene and Hensher 2010). However, as indicated by Murad et al. (2003) this is a common practice to obtain better asymptotic approximation in maximum likelihood estimation.

  3. This variable is important to capture our WTA value, yet it is important to address its potential endogeneity. Therefore, we test our regressions with and without it in order to check the consistency of our model, as can be seen in Table 7.

  4. Argentina, Brazil, Colombia, Ecuador, Peru and Uruguay.

  5. It is common to include the logarithm of income in the subjective well-being research, as in Palomino and Sarrias (2019), this allows us to introduce heterogeneity in the WTA value, implying that richer individuals should have higher compensations, as their marginal utility of income is lower.

  6. We do not develop the complete explanation of the OPM since is standard in the literature, see Palomino and Sarrias (2019) for more details.

  7. We also tried a specification of all the following estimations with linear income instead of its logarithm. Although the magnitude of the estimates change, the confidence intervals for the WTA values suggest that the difference between both specifications is not statistically significant.

  8. In order to avoid convergence issues of the models in the search of maximum likelihood estimate, we re-scaled some of the variables in all estimations, as in Palomino and Sarrias (2019). This can be seen in the variable names in Fig. 2, and Tables 5, 6 and 7.

  9. For reasons of clarity, the marginal effects of the quadratic term of age and the administrative regions were excluded from the graphs, but they are included in the estimation.

  10. We can also use these results to interpret some examples of the average partial effects. For instance, if the worker is underemployed the probability of being completely satisfied with life decreases by 1.0 percentage points. Similarly, if the worker has a couple the probability of being completely satisfied with life increases by 6.4 percentage points.

  11. The third quartile includes the largest share of the sample, as most workers are hired for exactly 45 hours per week in formal full-time jobs.

  12. To compute the WTA for the different groups of individuals we interact UND with the categorical variables representing the observed heterogeneity dimensions. In non-linear models like the OPM, we follow Ai and Norton (2003), Norton et al. (2004), and Karaca-Mandic et al. (2012) to compute the correct marginal effects of the interaction terms. However, our focus is on the marginal effect of each category in order to compute the WTAs.

  13. As a reference, the Chilean minimum wage in 2013 was CLP$210,000 (USD$404)

  14. Note that any single class can be set as baseline.

  15. It is important to note that only the coefficients associated to class 2 are shown. They should be interpreted in relation to class 1, because the first class coefficients have been normalized to zero.

  16. Such as easy contract terminations, lack of severance pay, unilateral working hours adjustments and random schedule assignments.

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Authors and Affiliations

  1. Universidad Tecnológica de Bolívar, Cartagena, Colombia

    Gabriel Rodríguez-Puello

  2. Universidad Católica del Norte, Antofagasta, Chile

    Ariel Arcos

  3. GSSI, Gran Sasso Science Institute, L’Aquila, Italy

    Benjamin Jara

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  1. Gabriel Rodríguez-Puello
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  2. Ariel Arcos
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  3. Benjamin Jara
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Correspondence to Gabriel Rodríguez-Puello.

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Appendix: Additional Tables and Figures

Appendix: Additional Tables and Figures

Table 6 Ordered Probit Model: SWB - Marginal Effects Pr(SWB = 1,2,3,4,5,6,7)
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Table 7 Ordered Probit Model: SWB - Marginal Effects Pr(SWB = 7) with and without wage
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Fig. 6
figure 6

WTA for underemployment by Working day type. WTA and 99%, 95% and 90% confidence intervals for underemployment. Standard errors were computed using delta method. USD WTA values in parentheses. WTA converted to USD using observed conversion rate from 30/Dic/2013, $523.76 CLP/USD. Source: Own elaboration using CASEN 2013

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Rodríguez-Puello, G., Arcos, A. & Jara, B. Would you Value a few More Hours of work? Underemployment and Subjective Well-Being Across Chilean Workers. Applied Research Quality Life 17, 885–912 (2022). https://doi.org/10.1007/s11482-021-09941-7

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