Labor Market Power, Self-Employment, and Development

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Francesco Amodio shows that self-employment opportunities shape the market power of employers in low-income countries, with implications for industrial development.

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Francesco Amodio shows that self-employment opportunities shape the market power of employers in low-income countries, with implications for industrial development.

Image courtesy of interviewee. December 21, 2023

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This video video discusses a research paper by authors Pamela Medina and Monica Malaco, which investigates labor market power and its impact on employment characteristics in low-income countries, particularly focusing on Peru. The authors analyze how the limited number of employers and high self-employment rates affect wage employment and overall labor market dynamics.

Key points include:

1. In low-income countries, labor markets differ significantly from those in high-income countries, characterized by high self-employment rates and concentration of formal employment within a few medium and large firms.
2. The research highlights that historical patterns in countries that became high-income show a correlation between wage employment growth and sustained economic growth.
3. Self-employment is often seen as a necessary solution against unemployment, but this high prevalence can also hinder policy effectiveness aimed at increasing wage employment.
4. The authors explore monopsony power (market power of employers) in labor markets, noting that while it may be high due to few firms, the prevalence of self-employment can act as a buffer, affecting the dynamics of labor supply and demand.
5. The study utilizes data from various sources, including firm surveys and household surveys, to understand local labor market conditions and measure the extent of monopsony power.
6. Their findings reveal that labor market power is significant, with workers earning only 70 cents for every dollar they produce on average. However, self-employment can moderate the negative effects of monopsony on wages.
7. The paper also examines the potential impact of policies to improve employment outcomes and how labor market power influences the effectiveness of such policies.

Overall, the authors argue that monopsony power is a crucial factor in understanding labor market issues in both low- and high-income countries, affecting wage levels, employment types, and the outcomes of policy interventions aimed at economic improvement.

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X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

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So in this paper with, Pamela Medina,

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who's at University of Toronto

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and, Monica Malaco,

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who's at University of Southern California.

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What we did was to ask ourselves whether labor market power,

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meaning the extent to which employers compete

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for workers in labor market, whether that can explain some

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of these features of labor markets in poor countries,

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and also why when we try to change those features

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with policies, we only get, limited effects.

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If we look at labor markets in, in poor countries

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and compare them to labor markets in high income

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countries, they look very different.

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Um, because on the one hand,

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because of a number of barriers,

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it is harder in low income countries for firms to grow,

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even if even for the most productive ones.

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And so you have a few, a relatively small number

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of medium and large firms.

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And this means that also that employment, wage employment

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and formal wage employment, in particularly,

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is concentrated in the hands of a few employers.

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Another key feature is

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that you have very high self-employment rates.

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Uh, this self-employment is typically informal,

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and this, it's very prevalent even within the

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manufacturing sector.

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Of course, we don't see much self-employment in say,

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you know, oil or steel manufacturing,

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but we do see a lot of it in garment

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or furniture making or food processing.

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And the other thing that is peculiar is that workers switch

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between, you know, being, working for a wage

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and being self-employed at the high rates from one state

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to the other continuously at rates that are two

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to three times higher than what we observe in,

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in high income countries.

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So I mean, the thing is why, why we care about this.

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We care, because essentially,

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if we look back historically at the experience of countries

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that are now high income, the expansion of wage

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and employment of salary jobs, that was a big correlate

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of sustained economic growth.

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And so this is why governments around the world have tried

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to implement different policies to expand wage employment

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and therefore decrease the, the, the, the,

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the self-employment rates in these countries.

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So there is a, a literature of course,

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on self-employment in, in low

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and middle income countries documenting these facts

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that I just mentioned, meaning it's high prevalence.

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And it's, some papers essentially emphasize

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how you can think about it as a, a subsistence subsistence

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of employment and some sort of sub, you know, a,

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a substitute for what will be

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unemployment in high income countries.

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So in places where there's no welfare

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and unemployment benefits, then workers will lose their job.

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They do subsistence self-employment to,

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to make end ends meet.

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Um, there is a literature also

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that emphasize more macro literature that has,

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has emphasized the role of self-employment for job search

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and work and labor market dynamics.

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I think the, the important thing is, is to also,

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to emphasize how, self-employment is, is sometimes seen

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as a, as a buffer for workers when they're hit by, by shocks

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of, of different nature.

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So we kind of accommodate for this view of self-employment

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as buffer, against, in this case the, the,

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the market power of employers.

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But then on the other hand, we, as I'm gonna say later,

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self-employment turns out also to be a barrier

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for the effectiveness of policies that try

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to expand which employment.

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Um, so there's also then a literature on, on,

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that has been quite separate from this one thus far on,

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on the market power of employers

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or monopsony power in the labor market,

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which has been exploding over the last, few years,

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with studies mostly focusing on high income countries.

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Uh, and we have much less evidence of, of the extent of,

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monopsony power, meaning lack of competition among employers

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in, in lower income countries or poor countries.

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So I have done some work in Columbia, for instance.

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Uh, there are some work in India,

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there's been some other works in India.

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Um, but essentially what we're bringing

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to the table here is a little bit connecting these two,

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these two literatures in the sense that we think that

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on the one hand,

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because you have few employers, you may think market,

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the market power of employers is particularly high

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in low income countries.

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But on the other hand, because you have lots

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of self-employment, you can think about those as a source

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of, of untapped labor, essentially,

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which can be leveraged by firms.

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And that will be, in particular, that will be very elastic

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to, to the wage that the, the, the firms pay.

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So that will kind of contract, the, the, the effect

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that monopsony would, the negative effect

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of monopsony on wages.

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Peru is a country that, especially in between,

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in the first decade of the 21st century,

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has experienced terrific growth.

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Uh, we're talking about, GDP per capita was

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around $2,000 in the 2000,

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and it went up to $5,000 in in 2010.

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Uh, in 2000, just to give you another number, in 2008,

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it was the country that grew the most in the world

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with the 9.8%, growth.

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So we are looking precisely at this time

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period in our study.

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And what is interesting is that as, as I said, it's typical

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to other low and middle countries.

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Despite this, big increase in GDP per capita,

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we keep observing those features in the labor market,

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meaning persistently, high self-employment rates,

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concentration of jobs among a few,

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few large manufacturing firms.

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So we were kind of trying to understand how come that the,

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the, you know, despite this growth, we, these,

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these features of the labor markets are persistent in a way

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after this period of spectacular growth.

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Uh, there has been now in the most recent past a period

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of huge political instability, which is very worrisome

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because it may undermine all the

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progress that has been made.

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Uh, I mean, Peru was a country with like, in, in

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that period I was mentioning

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before inflation was also particularly low,

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and that that of course was changed in light

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of global inflation surge,

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but also this political instability.

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Another thing that is important to mention is

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that Peru stands out in the world in terms

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of low union unionization rates

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and low collective bargaining, coverage.

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So we, if we look at data from the International Labor

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Organization, Peru is consistently at the bottom in terms

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of, among all the countries we have data for in terms

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of unionization rates and, and,

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and collective bargaining coverage.

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For the purpose of, of this paper,

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basically we bring together data on, on firms and workers.

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So, the data on firms, they belong to this,

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annual economic survey, which is a survey of

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firms across all sectors.

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We're gonna be looking specifically at manufacturing,

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but what's key is that for medium and large firms, so medium

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and large firms, meaning firms with sales

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above a given threshold, they're, they're, it's,

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they're required to fill in this survey.

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So you can really think about it at a census as a census of,

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of medium and large firms.

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So that's where the data on firms comes about.

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And then the data on workers, instead, we get them from,

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a household survey,

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which is representative also at the local level.

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I mean, this is, from method,

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a methodological point is important because

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whenever you want to think about issues of market power

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and high self deployment rates

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and so on, a lot of the action

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that we are interested in takes place in,

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in local liberal markets that are not, extremely rural,

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and also not the main capitals or,

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or the, you know, cities of like billion inhabitants.

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So it's important to be able to get snap the right snapshot

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of this kind of mid urbanized counties essentially.

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And so it's important to have enough coverage of those,

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as well, which you can do using household service.

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And with this data, essentially what we do is

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to first document the fact that the average county

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or local labor market exhibits high levels of concentration

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of wage jobs and high self-employment rates.

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Uh, and we also document, you know, consistent with the,

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with the evidence that we know from other places

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that there are these high rates of transitions, from

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and into wage employment and self-employment.

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Um, and then the other thing is, which is critical, we,

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we want to estimate the extent of monopsony power,

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the extent of market power of employers,

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which is notoriously very difficult to do

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because, what you would wanna do is to try

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to understand the extent to which employers are able to

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suppress wages below what they would be in the presence

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of perfectly competitive labor markets.

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And so what you these ends up, b in terms

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of measurement, what you really wanna get at is the slope

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of the, supply corps that labor supply corps

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that the firm faces.

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So essentially what you need is a labor demand shifter

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to make that, that, that that measurement.

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And so what we do is to exploit the, the fact that in Peru,

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at the time we're looking at it was this rural

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electrification program that was implemented that was,

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meant to increase, access

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and more stable access even to electricity,

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even in the rural parts

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of the country. And so there are, we have

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Variation across counties in when electricity

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or stable electricity comes to town, essentially.

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And we can combine this variation with,

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differences across firms within the same industry

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in the extent to which they need electricity,

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meaning they faced constraints in

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electricity access to begin with.

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And so the idea is that when electricity comes to town,

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the firms that were the, that were the most needy

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of electricity to begin with,

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they experienced a bigger boost to productivity and

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therefore labor demand.

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And so that works as a, as a firm level labor demand shock,

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which is what you need to measure labor market power.

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And what we find essentially is

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that a labor market power is, is high on average, meaning

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that workers receive about 70 cents

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for every dollar they generate.

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Um, but then interestingly, I mean,

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labor market power goes up with the extent of concentration

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as you would expect in the classical league option model.

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But that, that is less the case in places where,

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where self-employment is more prevalent.

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Precisely speaking to the, to the fact

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that if you have this source of un top labor

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that you can leverage that kind

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of keeps market power in check somehow with this facts,

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what we do is to inform a generally a criminal model

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where we think about Peru as a collection

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of local labor markets.

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In each one of them, we're gonna see,

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we're gonna have some medium

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and large firms that hire workers

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and some self-employed workers.

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They these two producing these two categories

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of producers producing different varieties of the same good.

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And then the workers are gonna be deciding whether

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to pursue self-employment or to be working for a wage.

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And the firms, they're gonna decide whether to,

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be in business and how much worker, how many workers

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to hire essentially.

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Uh, and so what happens is that, so, so this means

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that the entry of firms is gonna be endogenous in,

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in this model, and it's gonna depend on, on the productivity

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of the market, the on average fixed costs and,

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and the skills of the workers that,

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that are available in a particular local labor market.

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And so what is key about the model is

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that you have these oli sy source

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of market power on the one hand,

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because you have a finite number of firms

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that strategically interact when hiring workers.

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And on the labor supply side, you have this mechanism

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of workers sorting between wage work

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and self-employment according to their, you know,

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in a classical ROY setting, meaning according to their,

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based on their comparative advantage and posted wages.

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So essentially what happens in the model is that,

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let's say you, you set up policies in order to, in,

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in promote firm entry.

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So you're gonna have more firms operating labor demand is

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gonna, is gonna grow, more workers are gonna shift from

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being self-employed to be wage employed.

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But then this also means

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that those are sticking to self-employment.

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They're gonna become increasingly inelastic

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to changes in the wage.

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And that's gonna limit somehow the, the scope for expansion

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for the, for the wage employment sector

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because the, the mono,

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because of this source of increase of decreased elasticity,

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But also power actually is not gonna go down as much

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as it would in the absence of this,

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of these worker sorting mechanism.

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Uh, and we can use this model then

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to do two different things.

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We can, we can ask ourselves, okay, how much,

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market labor, market power can explain of,

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of labor market outcomes in Peru.

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So we can say, okay, let's pretend now

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that there's no longer oligo ops, meaning

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that workers no longer

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strategically interact when hiring workers.

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And we can look at what the impact this would have in a,

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you know, in our estimated, within our estimated model

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on the share of workers

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that are wage employed versus self-employed

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or wages and so on and so forth.

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And so what we see is that labor market power,

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eliminating labor market power would increase the share

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of workers who have a, who are wage employed

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by 11 percentage points.

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So from 60 to 71%

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and wages importantly would go up by around 30%.

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And also earnings from self-employment would go up by 27%.

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And this is interesting because there are several mechanisms

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behind these changes, which is not just the fact

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that now without a league oping, the wages are equal to

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what they will be in the presence of perfect competition.

13:04.055 --> 13:05.615
There are other mechanisms that place,

13:05.615 --> 13:07.975
there is a misallocation element to this

13:07.975 --> 13:10.935
because workers are gonna reallocate disproportionately more

13:10.935 --> 13:11.975
to the most productive firms.

13:12.595 --> 13:13.975
Uh, there's a selection element

13:13.975 --> 13:15.815
because workers who are sticking

13:15.835 --> 13:18.335
to self-employment on average are gonna be more positively

13:18.575 --> 13:21.015
selected and that pushes their earnings up generally

13:21.015 --> 13:23.335
equilibrium, effect in the sense that,

13:23.575 --> 13:25.295
earnings are gonna go up, which in turn increases

13:25.295 --> 13:26.615
demand and so on and so forth.

13:27.155 --> 13:30.175
Um, so the other exercise that we do then is,

13:30.505 --> 13:33.735
which is perhaps the most interesting, is

13:34.505 --> 13:38.755
let's think about policy, in within the estimated model

13:38.935 --> 13:42.115
and within the model as is, so within labor market power

13:42.175 --> 13:44.675
and within the model without labor market power.

13:45.015 --> 13:46.675
So thinking about the difference in difference,

13:46.675 --> 13:48.275
meaning the same policies,

13:48.375 --> 13:50.635
how much more effective would it would be

13:51.215 --> 13:52.835
if labor market power was not there?

13:53.375 --> 13:55.635
And what we find, so we, we use different policy,

13:55.855 --> 13:58.715
we use actually, actually implemented policies

13:58.715 --> 14:01.355
that have been evaluated in reduced forms in the literature

14:02.195 --> 14:05.195
policies that target for firm registration to lower first

14:05.375 --> 14:09.555
for fixed costs, policies that improve market access and

14:09.555 --> 14:10.875
therefore increase firm productivity

14:11.215 --> 14:13.915
or policies that aim at, training workers.

14:14.695 --> 14:18.475
Uh, we use the existing policy experiments essentially to,

14:19.215 --> 14:20.555
to inform the, the size

14:20.555 --> 14:22.515
of the policy shock within the model.

14:23.095 --> 14:24.915
And then we look at their effects in the,

14:24.915 --> 14:27.115
in the model without labor market power in the model

14:27.115 --> 14:28.155
with labor market power.

14:28.155 --> 14:31.275
And what we find is that these policies, if it,

14:31.285 --> 14:33.475
would be way more effective in the absence

14:33.475 --> 14:34.475
of labor market power.

14:34.475 --> 14:36.795
So we're talking about, for instance, policy

14:36.795 --> 14:38.275
that would increase productivity,

14:38.445 --> 14:40.075
would increase labor income,

14:40.495 --> 14:43.955
but 64% more if labor market power was

14:43.975 --> 14:45.035
not, was not an issue.

14:45.265 --> 14:47.915
What this work shows is that,

14:48.025 --> 14:50.835
monopsony power is not just something we should worry

14:50.835 --> 14:53.765
About about and we increasingly worry about in high income

14:54.045 --> 14:57.285
countries, but it is a feature also of, of poor countries.

14:57.545 --> 15:01.045
And it is important both in explaining some of the facts

15:01.115 --> 15:03.885
that we, some of the things that we see in terms

15:03.885 --> 15:05.325
of concentration away jobs

15:05.385 --> 15:07.125
and high self deployment rates and so on.

15:07.425 --> 15:10.445
But also in explaining why when we try to change things

15:10.445 --> 15:13.645
with policy, we don't get much of the intended effects

15:13.985 --> 15:18.245
and these policies only go, this far in trying

15:18.245 --> 15:21.205
to fit to expand which employment and promote ferment entry

15:21.465 --> 15:22.045
and so on.

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