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Immigration, wages, and employment under informal labor markets

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Abstract

This paper studies the labor market impacts of the Venezuelan immigration in Colombia. Exploiting spatial variation in exposure, I find a negative effect on native wages driven by the informal sector (where immigrants are concentrated) and a reduction in native employment in the formal sector (where the minimum wage binds for many workers). To explain this, I build a model in which a firm substitutes formal for informal labor in response to lower informal wages. Consistent with the model’s predictions, I document that the decrease in formal employment is driven by small firms that use both labor types in production and by workers earning the minimum wage.

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Data availability

The main datasets used in this paper are publicly available on the official webpage of DANE. They can be downloaded in their https://microdatos.dane.gov.co/index.php/catalog/central/about repository.

Notes

  1. The supply of migrants is measured as working-age Venezuelans over working-age natives.

  2. The trade-off between wages and employment in the face of migration shocks goes back to Grossman (1982).

  3. In addition, to alleviate concerns with the exclusion restriction, I further show that trade shocks arising from the Venezuelan crisis are not particularly relevant in the post-treatment period, as most trade adjustments happened before the arrival of migrants.

  4. Throughout this paper, wages can refer to labor income as they contain both the labor income of self-employed and wages of employees.

  5. In fact, Caruso et al. (2021) find the most negative wage elasticity (\(-\)7.6%) relative to the existing migration literature cited by Dustmann et al. (2016). In Appendix G, I show that the difference between the wage estimates of this paper and that one is driven by the sample period they analyze (until 2017) and the empirical specification they choose (panel data regression). This motivates, in part, the analysis performed in this paper.

  6. Edo (2020) finds for the Algerian inflow in France that a one pp increase of repatriates lowered native wages by between 1.3 and 2%.

  7. The event study design is motivated by the fact that the static coefficient in most previous studies comes from a panel IV regression that may be interpreted as a weighted average of treatment effects. The issue is that these weights may even be negative, for instance, because the timing of treatment varies across groups or because the treatment is continuous (De Chaisemartin and d’Haultfoeuille 2020; Goodman-Bacon 2021). Moreover, this specification needs the PTA, among other assumptions, to yield consistent estimates. Caruso et al. (2021) provide evidence of the lack of correlation between migration rates in 1973 and 2005 with present outcomes, yet the authors do not analyze pre-treatment data before the immigration shock. In that sense, Morales-Zurita et al. (2020) use recent pre-treatment data to find null correlations between past settlements and migration flows between 2013 and 2015, but they do not study if their instrument predicts economic outcomes during the same years. Finally, Lebow (2024) studies pre-trends for different outcomes between 2013 and 2015 to find significant differences in unemployment and labor force participation rates before the immigration shock. Therefore, these studies need to account for possible differences in pre-trends.

  8. For instance, Morales-Zurita et al. (2020), Caruso et al. (2021), and Lebow (2024) include in their post-treatment period the years before 2015. But these years of low immigration rates coincide with the massive drop in cross-border trade with Venezuela (as shown later in Appendix Figure F.1), resulting in a source of bias in their estimates.

  9. It also helps to distinguish the possible effects of the change in the legal status of Venezuelans during the post-treatment years.

  10. In July 2018, the salient president of Colombia, Juan Manuel Santos, unexpectedly announced the creation of a special permit to work for all Venezuelans registered in the Administrative Record of Venezuelan Migrants (RAMV, by its acronym in Spanish).

  11. The PEP was initially valid for 90 days and could be renewed for up to 2 years.

  12. In Ecuador, Olivieri et al. (2021) find that providing work permits to Venezuelan workers would increase their average earnings.

  13. Moreover, I include 2011 and 2012 in the analysis for additional pre-treatment periods, assuming all survey respondents were Colombian.

  14. Nearly 443,000 individual records were gathered from April 6 to June 8 in 2018 at different points in all the territory. It was an optional and go-to-the-registration-point kind of survey for undocumented Venezuelans.

  15. A recent paper by Lebow (2022) summarizes the differences in the wage effects of immigration in Colombian studies.

  16. By construction, \(\beta _{2015}=0\) and all coefficients \(\beta _t \in T=\{2011,...,2019\}\) measure the effect relative to 2015.

  17. In the Appendix F, I show that results are almost identical if I use a denominator from the GEIH survey in 2015 (see Figures F.3a and F.3b).

  18. Moreover, the survey weights were built using the 2005 census, and its reference frame was not updated until the 2018 census, creating additional uncertainty when constructing migration shares using the survey.

  19. The use of a time-invariant treatment variable is particularly attractive in settings in which the intensity of the treatment increases proportionally across regions over time, i.e., in which the measure of exposure for different years differs only in scale. As shown in Fig. 2b, this is the case in my setting.

  20. Regression weights are typically used to estimate population average partial effects. However, Solon et al. (2015) state that this is not straightforward, bringing up arguments for using or not using the weights. In any case, when using regression weights, I find more negative estimates for native wages and more positive ones for employment (see Appendix Figure F.6a), and also results by the formal and informal sectors hold (see Appendix Figure F.7a).

  21. Jaeger (2007) and Borjas (2001) have pointed out that immigrants tend to settle in areas that offer the best economic opportunities for the skills they provide.

  22. The data for the outcomes is available to 24 departments, not to all 33 in the country. The missing nine departments, mostly located in the Amazonia and Orinoquia regions, only account for 2.8% of Colombia’s total population, according to the 2018 census.

  23. As a robustness check, I develop the test proposed in Goldsmith-Pinkham et al. (2020) to calculate the weights of the distance instrument, namely the Rotemberg weights, of the overall coefficient. I decompose the instrument into 15 shares arising from the different origin cities of migrants in Venezuela to determine which of them gets more weight in the overall estimate. This exercise yields that Maracaibo and San Cristóbal concentrate 0.7 of the weights, which sum up to 1. In fact, those cities are closer to the border with Colombia; hence, effectively, the instrument compares cities closer to the border with those further away. To name some characteristics of these migrants, Maracaibo is an industrial city focusing on oil extraction, while San Cristóbal relies more on the service and commerce sector.

  24. For employment, the pre-trends are insignificant only for the distance instrument.

  25. The first step to evaluate the exogeneity of the two instruments and possible heterogeneous effects is to perform a Hansen J test for over-identifying restrictions. In this case, I use both instruments in the first-stage regression 5 to find that the null hypothesis of the instruments being exogenous is not rejected.

  26. In practice, for instrumenting the interaction of year dummies with the immigration shock of Eq. 1, I interact the instruments with year dummies.

  27. Recently, Lee et al. (2022) argue for a higher F-statistic in the first stage, exactly a value of around 104.7. In this case, the distance instrument’s F-statistic is 287.1, and the past settlements instrument’s F-statistic is 33.7.

  28. Instruments predict a higher pre-treatment coefficient in 2011, which does not seem to be a big problem since trends have been relatively stable after 2011. A joint F-test for coefficients from 2012 to 2014 yields a p-value between 0.24 and 0.27, depending on the instrument.

  29. The construction of the wage, or labor income, variable is shown in Appendix I. Importantly, it covers all types of labor income, including self-employed earnings.

  30. I do not combine both instruments in the first stage as the distance instrument captures all the predictive power of the past settlements instrument.

  31. Appendix Figure E.1b shows that when using \(\Delta M_{dt}\) as the explanatory variable, instead of the fixed \(\Delta M_{d,2018}\) from the census, the results of native employment are similar but with wider confidence intervals in 2017.

  32. For firms, formality is defined based on the payment of direct taxes. For workers, formality is defined based on the contribution to the health or pension system. The EMICRON survey only covers owners of firms with less than 10 workers.

  33. In this model, I abstract from the extensive margin followed by Ulyssea (2018) to take into account only the labor choices of a given formal firm (the intensive margin). This means the model does not account for the firm’s decision to register in the tax records (become a formal firm), as the goal is to model informality through the worker side and analyze changes of a representative firm.

  34. Fines for hiring workers informally may go up to 500 minimum wages and are enforced by the Ministry of Labor in Colombia.

  35. In this case, I assume for simplicity that the number of consumers grows at the same rate as the workforce, that is, what Borjas (2013) defines as product market neutrality.

  36. A model proposed by Kleemans and Magruder (2018) distinguishes between types of skills for formal and informal workers. The main findings are that if migration is highly skilled, there is a crowd-out effect of existing formal low-skilled workers (with formal wages staying constant) and that migration (of any skill type) will (weakly) decrease wages in the informal sector.

  37. In the working paper version of this paper, I extend this theoretical framework with a general equilibrium model that includes capital responses and differential labor supply functions of migrants and natives. A strong substitutability between labor types also predicts a decrease in formal employment in this model.

  38. Results are unaltered if I use the past settlement instrument or control for trade with Venezuela.

  39. Because the results are aggregated, this effect is capturing possible spillover effects between the two sectors, that is, workers moving from formal to informal employment or the other way.

  40. Appendix Figure D.1 shows similar wage estimates using more frequent time windows (quarters instead of years). Also, pre-trends are not significant in this specification,

  41. Though, Dustmann et al. (2022) discuss that regional wages arising from cross-sectional data jointly measure the selection of workers and changes in the price of labor. Thus, there can be a compositional bias in the wage estimates.

  42. Dividing the sample by industry and sector increases the sampling error considerably, so I focus only on the largest industries.

  43. Regarding formal wages, coefficients are insignificant for both firm sizes.

  44. Informal employment significantly increases for smaller firms but not as much to counteract the formal employment decrease.

  45. In comparison to Turkey, Altindag et al. (2020) find that the large refugee shock of Syrians boosted firm creation in the country, especially for those with foreign partnerships.

  46. I measure the average number of workers who report working in a given firm size category with a specific question from the GEIH survey.

  47. Another mechanism to be analyzed is the effect on the creation of informal firms not registered in tax records.

  48. This assumption aligns with most of the literature; for a discussion of the wage effects of immigration allowing for demand shifts, see Borjas (2013).

  49. I use native wage change in 2018 and not overall wage change to remove possible compositional bias from immigrants’ lower wages. If, instead of the total change in employment, I include in the numerator the change in native employment, I would be estimating the labor supply elasticity.

  50. In Italy, Guriev et al. (2019) find an elasticity of labor demand in the informal market of around \(-\)1, meaning a more elastic demand in this sector and close to the long-run one when it is possible to adjust capital.

  51. The effect is so large because salaried informal employment is a small subset of employment, whereas the immigration shock is the share of overall employment.

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Acknowledgements

I am grateful to the editor, Shuaizhang Feng, and three anonymous referees for their insightful comments and suggestions. I am also grateful to Jan Stuhler for all the detailed comments, useful arguments, in-depth suggestions, and close guidance; to Luigi Minale for further remarks and discussions; and to Juanjo Dolado for the extensive revision of the manuscript. I thank Jesús Fernández-Huertas, Jorge Pérez Pérez, Lorenzo Aldeco, and Sarah Schneider-Strawcynski for the helpful feedback. In general, I am indebted to all the comments from participants in the UC3M Applied Reading Group, the Junior Economics of Migration Seminar, the Seminario de Economía Aplicada BANREP-UIS-UNAB, the 10th European Meeting of the Urban Economics Association, the 17th IZA Annual Migration Meeting, the Seminar Series of Banxico, the 14th Migration and Development Conference, and the Seminar at ZEW. I am also grateful for all the support from the DANE staff, especially from Geovanni Portilla. This paper was previously circulated as “Dynamics of Local Wages and Employment: Evidence from the Venezuelan Immigration in Colombia.” Replication files are available upon request. All errors are my own.

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The author gratefully acknowledges the financial support from the Ministry of Science and Innovation in Spain through research grant PDI2019-108144GB-I00.

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    Lukas Delgado-Prieto

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Delgado-Prieto, L. Immigration, wages, and employment under informal labor markets. J Popul Econ 37, 55 (2024). https://doi.org/10.1007/s00148-024-01028-5

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