Even more zeros

There’s more experimental-like evidence that immigrants have little or no negative effect on native employment opportunities, if you need it.

In 1962, 900,000 pied-noirs repatriated to France after fleeing Algeria following their loss in the country’s war of independence. These repatriates settled in the warmer departments of France with climates more similar to their former home country. And as evidence that this was an exogenous shock to the labor force, they tended to settle in those departments with the higher unemployment and lower wages.

This exogenous shock to the French labor force that increased the number of workers by 1.7% was studied by Jennifer Hunt in her 1992 paper. She found a small but significantly negative effects on native unemployment six years after the mass repatriation. However, she found no effect on native participation rates. Her data on wages is a bit of a mess, but with what she had she found at most a small negative effect ((She worries that given her data limitations, she’s not able to properly control for the fact that the repatriates happened to have chosen to migrate to departments that were having bad economic outcomes unrelated to the mass migration. Interestingly, the migrants didn’t seem to have an effect on internal migration patterns, i.e. their presence didn’t discourage the native French from migrating to departments heavily populated by the new immigrants.))

Another crumbling empire provides us with another immigration experiment: the returnados from Angola and Mozambique in the mid-1970s increased Portugal’s work force by 10%. In a study design similar to Card’s Mariel paper, Carrington and Delima find the Europe-wide recession of those years swamps out any effect the the immigrants might have had.

Substitutability as default?

I’m jumping ahead of my own narrative, but why does it seem ingrained in people (including economists) that immigrants must be competing with native workers? Why is complementarity so much more unlikely in people’s priors?

We don’t have this bias when it comes to new technologies. In fact, we have the opposite bias. Despite the popularity of the phrase “creative destruction”, quality ladder models are much less common than expanding variety models of growth. Anyone who suggests there may be a negative externality of R&D in competitive industries gets jumped all over.

Can’t immigration be seen as a type of innovation? Immigrants bring more with them than their L.

А русских евреев принять на нашу работу?

Нет! ((Thanks Google Translate!))

An easy criticism of “experimental” data, like that from the Mariel boatlift, is it only applies to the particular situation under which the experiment was run. Immigrants may have had no effect on employment outcomes in the very special circumstances of Miami in the early 1980’s, but in other places and times immigration would have an effect. Card, himself, says that one of the reasons the Mariels had no effect on the Miami labor market was because the city had had ample experience in the preceding decades absorbing Hispanic and, in particular, Cuban immigrants. Maybe Miami is just an extremely efficient melting pot.

The only way around this criticism of experiments is to do as laboratory scientists do, replicate them. Of course, in the economic study of immigration, this is not something that can be done in the lab. Economists studying immigration can not run their own experiments; they can not produce their own data. They have to wait for nature run experiments for them. Lucky for economists, nature provided such an experiment in the collapse of the Soviet Union.

Between 1990 and 1994, Israel’s population grew by 12% due to immigration. Most of these immigrants were Jews from the becoming-former Soviet Union. Like the Mariel boatlift, this mass migration was almost entirely due to circumstances in the sending country and at least at first, it was largely unanticipated by the native population. The instability in the Soviet Union at that time encouraged many people to leave. Israel was chosen as the destination country simply because of shared religion and open immigration policies.

When something external to the system causes a change to that system, like these particular mass migrations, economists call it an “exogenous shock”. Laboratory scientists use random assignments into control and treatment groups, for example, as their exogenous shock. The great thing about exogenous shocks is that they remove the mystery from what causes what. If conditions in the system under study do not affect the timing or magnitude of the shock, then any changes to the system that come after the shock must be due to the shock itself. Because unlike laboratory scientists they can not induce exogenous shocks to the systems they study, the challenge for economists is to look for data that was generated from exogenous shocks or to use various, and sometimes complicated, techniques to analyze data in a way that makes it look like it was generated by exogenous shocks.

The mass migration from the Soviet Union to Israel, then, was an exogenous shock to the Israel labor force. However, the occupations chosen by Russian immigrants once they entered Israel are not exogenous. Because Rachel Friedberg wanted to study the effect of the mass migration on wages within occupations — her question was “Did Russian immigrants entering an occupation cause wages in that occupation to decline?” — she was worried about the non-random choice of occupation. Specifically, she was worried that the immigrants had chosen occupations that were experiencing above average growth in wages. In this case, if immigrants were depressing wages by increasing labor supply and so competing with natives for jobs, the raw correlation would show no effect of immigration. In the raw correlation the bad effects of immigrants on wages would be cancelled out by the fact that immigrants were disproportionately choosing occupations with higher wage growth. In a hypothetical world without immigrants, then, native wages would have been higher.

To test to see if Russian migrants were choosing occupations with higher wage growth and so creating an artificial zero correlation between immigration and Israeli native wages, she came up with a clever way to see what would have happened if those immigrants did not get to chose their occupations in Israel. What she did was to assign each immigrant to the occupation they had back in Russia. She reasoned that because of training and skills accumulated over the career, immigrants would prefer to have occupations in Israel that were similar to their old ones in Russia. Because some occupations get paid more than others, that the old occupation is similar to the new one means the old occupation is correlated with immigrant wages in Israel. The old occupations, however, do not depend on the growth in wages in Israeli occupations. So assigning the immigrant to their old occupation instead of their chosen one essentially removes the problem of occupation choice that was screwing up the raw correlation in the previous paragraph. Getting rid of the choice problem means we can see the real effect of immigration on wages.

The results are surprising. The immigrants that choose occupations different from their old occupations actually had lower wages than if they had stayed in their old occupation. Maybe “choose” is the wrong word here. It may be that immigrants, with their poor language skills or lacking social networks or because of discrimination, were forced into occupations with lower wages. In fact, when you control for this downward mobility of immigrants, the actual correlation between immigration and native wages is positive! Occupations that saw a disproportionate amount of immigration had higher wage growth in the period of the study.

This potentially throws the simple model of the affect of immigration on native employment opportunities on its head. Not only can we not confirm its implications, but its implications seem to be backwards. How is it possible that immigrants could increase wages of native workers!?

¿Los cubanos del Mariel toman nuestros trabajos?


David Card’s famous paper studied the impact of the sudden arrival of 120,000 refugees to Miami in 1980. He estimates that the total labor supply in Miami suddenly increased by 7% and the Cuban work force increased by 20%.

Because labor is one undifferentiated mass doing the same tasks, with the same skills, creating the same nondescript widget with a fixed number of machines, this increase in supply induces a decrease in wages and an increase in unemployment among native-born workers. At least this is the mental model most observers at the time carried around in their heads: people conjectured that unemployment spiked to 7.1% in the summer of 1980 because of the arrival of the refugees. It was presumed that the influx of workers created other systematic problems. For example, the boatlift was said to be partially to blame for riots in black neighborhoods that killed 13 people. Also crime, and specifically the homicide rate, spiked in 1980. The Mariel’s themselves participated in a number of crimes; they were responsible for about 10% of homicides. But presumably through their bad affects on the labor market, they caused higher crime rates even among the native population.

To a certain group of economists, to which Card is a high priest, the most important question to ask of correlations like the one found between unemployment and the Mariel boatlift is the following: is there some third factor that is correlated with bad market outcomes that is also, but independently, correlated with the influx of Cubans? Because the stories being told at the time suggested the boatlift caused bad labor opportunities for native-born Americans and then other social ills, this question is particularly important. If a third factor explains the worsening labor conditions in Miami around the time of the boatlift, then that would be the cause of so many social ills and not the boatlift itself. The obvious candidate for this third factor is the deepening national and international recession in 1980 ((The recession that year was later dated by the NBER to have started in January 1980, several months before the boatlift. Its also interesting to note that a primary reason for the boatlift was a bad economy in Cuba.)).

By comparing Miami’s experience with other similar cities that were not affected by the boatlift but were affected by the general economic slowdown, Card was able to show that wages and unemployment in Miami were not affected by the boatlift. He, in effect, subtracted out the effects of the recession on the Miami labor market and got zero. This suggests that the real culprit in Miami in 1980 was the recession. The boatlift just happened to have happened at the same time the economy was contracting.

Another group of economists cares more about the mental model used to understand the Miami labor market. In the case of the Mariel boatlift, for them the most important question to ask is: what’s wrong with the simple mental model that its obvious implication — more workers leads to lower wages and higher native unemployment — broke down? Here’s a number of possibilities:

  • Workers are not an undifferentiated mass; they have different and complimentary tasks or they have different skills
  • Workers are not all producing the same good
  • The number and quality of machines is not fixed

To the degree that any of those three things are true, the implications of the simple model break down. If Cuban refugee workers have skills that are complimentary to native-born workers or if Cuban workers are making products that natives don’t make, then those two groups will not compete with each other in the labor market. Just like an increase in the number of dentists would not have an effect on the wages of construction workers, refugees with different skills from natives would not have an effect on native wages.

But even if workers are an undifferentiated mass, if the machines and production processes they use can be quickly installed or upgraded to accommodate new workers, then the refugee workers will increase the total amount produced by the Miami economy and they will not affect wages or employment of native workers.

Immigrants taking our jerbs?

I’m writing a “vulgarized” immigration paper (my Italian co-author’s adjective). One thing we academics like to do is pick on the idea that immigrants take the jobs of native-born Americans.

Watching Fox the last couple of weeks, it doesn’t seem like many folks take that point of view anymore. Conservatives talk about the “rule of law” and the deleterious effect of immigrants on the welfare state ((btw, why do conservatives think this is a bad thing?)), but not many were talking about the direct economic costs of immigration.

Do you know of example of politicians or otherwise high profile people taking the view that immigrants hurt native-born American job opportunities? Quotes would be awesome!

June 6, 1999

A week after my graduation from college, I ordered: The Virgin Queen by Christopher Hibbert, Measuring Customer Satisfaction by Bob Hayes, Unidimensional Scaling by McIver and Stocks for the Long Run by Jeremy J. Siegel.

I just started my first “real” job, at a customer survey company.

(meme inherited from McArdle)

Stated preferences

I just finished the first happiness tracking cycle and they‘ve sent me my Happiness Report. There’s some unsurprising things like I’m happier on the weekends and when I’m doing stuff I want to do. The surprises:

  • I’m happier when I’m interacting with more than one person
  • There’s no relationship between the quality of sleep and happiness, but there is a pretty strong relationship between the length of sleep and happiness
  • While my level of focus has no relationship to happiness, there’s a U-shaped relationship between how productive I’m being and happiness

I’m not sure how to explain that last one. Perhaps I mark middling productivity when I really want to get work done, or when some potential leisure activity is distracting me from my work. But this would suggest “focus” should have a similar relationship with happiness. I’m not sure what productivity is net of focus.

Here’s my happiness by activity:
My happiness by activity
A vast majority of the mass is in the middle groups: “home computer” and “working”. Also, most of these activities probably generate a level of happiness, but I suspect the causation works the other way on “listening to music”. This makes me think the real problem with happiness research in the context of economic analysis is not the revealed preference critique. This stuff might also get the outcomes and behaviors mixed.

Another thought: there may be a finance twist to happiness correlations. Controlling for the level, folks with more swings in utility generating behavior (call it “consumption”) will, on average, have higher marginal utility, i.e. they’ll be less happy on average. With standard arguments from finance, they would be willing to pay more for “investments” that have payoffs which are positively correlated with marginal utility like listening to music and having children.

UPDATE: Some potentially testable hypotheses (assuming happiness panel data exists): do people that have/ have more children have higher variance in happiness? Controlling for income, do people in richer societies have higher variance of happiness?

The computer thinks for us

Angus Deaton:

Structural estimation is useful, not only for the estimates (whose credibility is often undercut by the panoply of supporting assumptions that are required to obtain them), but for understanding the empirical predictions of the theory.

Do we do this with DSGEs? We try to replicate known patterns in the data, but I don’t think we use these models to find potential new patterns.

In one of my myriad of yet-unfinished papers I report things I call “simulated comparative statics”. I can’t solve the model, so I have the computer generate numerical derivatives. People don’t like ’em. Can I market them better? “Simulated theorems”? “Generated predictions”? “Computed hypotheses”?