Are international migrants happier after their move?

Why do people migrate? While there may be many motivations, it is very clear that migrants find much better material well-being in their new location. But they have to live away from their roots and traditions, and it is not clear their subjective well-being is better in the new location. Actually establishing this is very difficult, because migrants self-select themselves into migration. To do this properly, one would need a randomized experiment.

Steven Stillman, John Gibson, David McKenzie and Halahingano Rohorua have found this experiment with a migration lottery for Tongans interested in moving to New Zealand. The authors were able to interview both successful, unsuccessful and ineligible households one and four years after the lottery. They confirm that material well-being increases, but the matter of satisfaction is much more difficult to parse. Mental health is better, happiness lower. Interestingly, the study finds contradicting results when comparing recollection of welfare and static assessments. Despite this great dataset, we now only know better that we do not know.

On measuring income standards

How do you measure living standards? The usual way is to look at income, because it is the easiest to find. But of course, this only pertains to market income and does not include other potential forms of income, such as informal income, income in goods, and imputed income from home production. All these can be important for poor households, and a better way may be to look at consumption, especially if you want to look at a proxy for permanent income rather than a temporary measure like income.

Mike Brewer and Cormac O'Dea do this for the United Kingdom. They show that the correlation between income and consumption is actually quite low, and defining poverty with income measures can be quite misleading, and they suggest this is due to underreporting of income while consumption expenditures are rather accurate, at least for the poor. This implies that if one looks at consumption expenditures to identify the poor, one should not focus so much on retirees. Indeed, they enjoy substantial housing services, need to sustain fewer people and can draw on the sale of assets. Absent a measure of consumption, using income plus imputed income from housing services does a good job, though.

On the difficulty of calculating the cost of living

Quality of life indexes are popular in the press. But they are not that easy to compute. While one can easily measure how much one has to work for, say, a loaf of bread, quality of life needs to consider a broader basket of goods. Now, you need to define that basket, which may be very different across locations (and across time if the horizon is long enough). It becomes even more difficult if some of the goods are location specific, such as housing.

John Winters points out that housing rents and house values are typically used for this kind of exercise. But house values can be very misleading, as most of the price of a house contains future services and their price, not current ones. Rents, in contrast, only contain the value of current services. An additional problem is that depending on the location the rental and sale markets may be very segregated and thick. Indeed, rentals are typically small and of lower quality. Winters compares rents and house values for US metropolitan areas and finds that they correlate well, but house values exhibit wide dispersion, making them indeed less reliable. He recommends using only rents, even if few rents are available and may not be necessarily representative of the housing stock and market.

Children in out-of-home care and adult criminality

It always saddens me when children are born into bad families. In extreme cases, society's responses is to put them into foster care or into institutions, in the hope that they will have a better shot at good adult outcomes. While there are some prominent counter-examples, the norm is that they still face significant hurdles. One measure of this is how frequently they end up being convicted of a crime.

Matthew Lindquist and Torsten Santavirta look at Sweden and children sent to foster or residential care. The latter seems seems to increase the likelihood of criminality in later years, as does placing boys in foster care after 13. Girls seems largely unaffected by this, except for residential care. Of course, this could all be selection bias, as the worst cases cannot be put in foster care. But in this study, much of the case record is knwon to the econometrician, in particular whether placement is due to child or parent behavior.

On the difficulty of implementing right-to-work legislation

The chronically poor have a low labor-market attachment, to a large extend because of a lack of skills and experience. This is thus a vicious circle. One way to break this vicious circle is to offer them employment and hope this turns into a virtuous circle. This is what India implemented in 2005, a program that guarantees any rural adult 100 works days on public projects at minimum wage (thereby getting the richer people to self-select out). Does the theory work out in practice?

Puja Dutta, Rinku Murgai, Martin Ravallion and Dominique van de Walle report that it worked, sort of. The poorest families do indeed use the scheme most, but here remains unmet demand, thus the state was not able to fulfill its work guarantee. In fact, this rationing was most prevalent in the poorest Indian states, where the guarantee is the most needed, and where the resulting public works would also be of the highest benefit. And while the scheme seems to motivate more rural women to participate in the labor market, the rationing still privileges men. All in all, the program seems to roughly target the right people, although there is substantial scope for improvement. But we still need to wait for more data to see whether it works to alleviate chronic poverty.

Why the young demand more social insurance than older generations

Take up rates for various social insurance schemes generally increase from generation to generation, even when their is no change to the rules. That must be either because new generations are more feeble and, say, tend to become more frequently or earlier handicapped, or that they have a higher demand for social insurance benefits, say, because they are feeling more entitled (one can have different interpretations).

Martin Ljunge build a model where younger generations are influenced by what older generations did in the following way: Deciding whether to apply for benefits depends on a "psychic cost" that depends on the take up rate of the previous cohort. The model is the estimated using individual data from the sick leave program in Sweden (I think, this is never explicitly mentioned). It is found that, indeed, having parents taking advantage of social benefits lowers the cost on one doing so oneself. This effect makes up half of the long term increase in the take up rate.

How much does race contribute to poverty in South Africa?

It is no one's surprise that blacks in South Africa are poor, less educated and less healthy than whites, given the still rather recent struggles through apartheid. But the country has also gone through a remarkable reversal of fortunes, with blacks now running the country and leading some formidable efforts to raise the blacks from chronic poverty. In some ways, these efforts are much more substantial than those that have been made in the US, where blacks are still a minority and yet have remained in poverty with little progress for decades. It is therefore of interest to understand how things have improved in South Africa, and whether the damage from apartheid has been overcome.

Carlos Gradín focuses on poverty and deprivation, both of which still show considerable gaps between blacks and whites, and comes to the conclusion that they are mostly explained by education and "family background" (parents' occupation and education). This all points to the fact that education is the big policy option, but it will take considerable time to reduce the gap.

These results are obtained by estimating a reduced-form equation for blacks and then letting them assume the characteristics of whites. Unfortunately, this procedure does not allow to determine whether there is still some discrimination against blacks, which would have been of particular interest in this context.

Religion as an insurance mechanism against aggregate shocks

I have never been fond of the claims that the world is better with religion. The principal claim is that religion gives hope for people in dire circumstances, and thus in Economic terms increases their utility despite having hit the budget constraint. But one could also argue that these people are being mislead, as religion provides them with subjective probabilities that are far off the objective ones, all the while making the budget constraint even tighter because of the tithe and other material donations.

Olga Popova studies whether this effect of religion on happiness not only applies to individual circumstances, but also for aggregate shocks. Looking at the transition countries, which each suffered through substantial falls in GDP after the collapse of the Soviet rule, more religious people suffered, in terms of happiness, less than others from the large economic reforms. Of course, it is easy to understand that for most, they were happier than circumstances would indicate because it was rather obvious that things would eventually improve, likely a lot. The question is why religious would believe this more? Because they are easily indoctrinated, and it is certainly true that there was a lot of excessive pro-market rhetoric at the time. Non-religious people were probably more among the skeptics. And they were also more likely to be among those who benefited from the previous regime, which definitely oppressed religion. Unfortunately, this study does not take (previous) party affiliation into account, which is likely very (negatively) correlated with religiosity. Too bad.

Is this what Republicans are really about?

Europeans have struggled for some time to understand the philosophy of the US Republican party, and especially how it manages to get such popular support in the electorate. On the surface, indeed, it all appears to be a platform that favors the rich at the expense of the more numerous poor, the latter having been indoctrinated for many years that governments are bad and, at the extreme, robber barons are better than a benevolent government. The consequence is a drive to increase inequalities in income and wealth.

John Roemer offers a glimpse into the American ideology for inequality. He says that "American philosophy" sees inequality as ethical, as it gives everyone what nature endows him with. That seems like a very fatalist argument (as in some religions) that ignores that redistribution is about the ex-post insurance of where someone is born. having the luck to be born in a good family and in a good country ought to be taxed to some degree to benefit the unlucky. A second argument is the old trickle-down one: if the most talented can keep all the fruits of their labor, they will work more (never mind decreasing marginal utility of consumption and how redistribution can improve global well-being). The third argument is that the government is good at nothing, and should thus be largely absent.

All these arguments are largely shared in the United States, and especially among Republicans. In fact, the latter are now going much farther in reversing redistribution than ever before. Just see how they they are vehemently opposed to any risk sharing through public health insurance, how they limit school funding and public goods in general. In fact, I am starting to wonder whether the hidden goal is to create a new underclass that would be in some ways reminiscent of the old slavery days. That would be consistent with the opposition to minimum wages, with the large prison population, and with keeping the poor uneducated. That would also be coherent with the Republicans willingness to increase the payroll tax (a flat tax applicable to everyone) while calling for a reduction in the income tax (a progressive tax). I hope I am wrong, though.

Marx and Solow

For all the justified criticism one can have about the work of Karl Marx and the economic system that resulted from it, old Karl was onto something. The Industrial Revolution saw the rise of a new class, the capitalist, that generates a smaller share of its income from manual work and instead uses its brain and capital. That is in terms of welfare a positive evolution, were it for the fact that workers hardly had it better compared to their previous agricultural life and thus did not get a share of the new riches. What especially irked Karl Marx was the lot of the workers could not improve, either because they were not getting a larger share of income, or because there was no path to become capitalists themselves in large numbers, something later termed as a lack of social capilarity.

Jørgen Heibø Modasli finds some of these features in a model inspired by the Solow growth model, augmented by incomplete markets that require that one cannot borrow to become a capitalist entrepreneur and that the entrepreneur can only work for himself. This introduces a non-convexity and quickly a two-class system emerges, with workers not having any reason to save much as they have no chance to become capitalists. Also, the class division persists over time, even when credit and capital markets improve.

Yet, this is not entirely convincing. Indeed, economies with less incomplete markets, say, the United States, should see less inequalities, and inequalities should have declined over time as markets developed. This is hardly what we can see in the United States, where access to credit is widespread, yet income inequalities are high and growing, and social capilarity is largely absent.

The Internet makes you happy

We have previous established that the Internet, contrarily to conventional wisdom, makes people more social. Does this also mean that people with Internet access are happier? Of course, one should take into account that those without Internet, at least nowadays, are likely to face hardships like low income and education.

Thierry Pénard, Raphaël Suire and Nicolas Poussing do such an analysis for Luxembourg and find indeed that Internet users are happier, especially among those with lower incomes. This is also true when taking into account the intensity of Internet use. This implies that making the Internet accessible to lower socio-economic classes can improve welfare, possibly significantly. Of course, one has to take with a grain of salt studies of happiness based on surveys that ask for subjective self-evaluations. That grain of salt may be bigger when one considers who small Luxembourg is. The approach then becomes similar to the randomized experiments in the development literature where results for a small set of villages are difficult to apply to other contexts. Yet, Luxembourg is surprisingly diverse, so maybe these results are generalizable. Readers, you can now safely that you are now happier from being on the Internet and reading this.

Fiscal policy as insurance

The goal of fiscal policy is at the macroeconomic level to steer the economy towards efficiency and, depending on the country, to smooth somewhat economic fluctuations. It has long been debated whether this is desirable or possible at all, given the large delays in implementing public expenses. But changes to tax policies are quicker to put in place and implement. At the microeconomic level, the focus is more on the long term, again try to attain better efficiency as well to optimize some definition of fairness across economic agents, however this may be defined in the respective countries. These micro and macro aspects have largely been regarded as separate. This does need to be so.

Eduardo Engel, Christopher Neilson and Rodrigo Valdés look at the particular fiscal policy of Chile. This country is characterized, like many emerging economies, by wild fluctuations in economic activity. In this case this is triggered by changes in commodity prices, in particular for copper. The most important implication is that government revenue varies wildly (a macroeconomic impact) between 1 and 8% of GDP, which changes Chile's ability to redistributes across heterogeneous households (a microeconomic impact). Adhering to a balanced budget rule would have a dramatic effect, in terms of aggregate welfare it would be like renouncing to half of the copper revenue. The reason is that households' incomes is also correlated with copper revenue, and a countercyclical policy is then optimal. And to be the most effective, the poorest households are helped in hard times, both because they have the highest marginal utility from consumption and because they have the highest propensity to consume.

Chile has been pursuing so far something that is close to a balanced budget rule: expenses are related to a permanent income measure of income. This means expenses are relatively constant, except for the last years, where expenses grew significantly despite a reduction in copper prices. This appears to have worked well, in particular because the poor have been the target of this largesse, not the rich. That was stimulus spending done right. This paper shows how this can be done even better.

Energy spending and household poverty

There is broad agreement that energy, especially polluting energy, is too cheap, calling for higher energy taxes. The problem is that such taxes are believed to be highly regressive, as poor households spend a larger share of their income on energy for transportation, heating and cooling. Of course, this could be alleviated by an appropriate redistribution of the proceeds, but to do this properly one first needs to understand well the energy spending of poor households.

Tooraj Jamasb and Helena Meier do this for the United Kingdom. There, households that spend more than 10% of their income on energy are considered "fuel poor" and deemed as having difficulties heating their home. I have always been suspicious of such definitions, as one may choose to spend more to heat at higher temperatures, for example, without being considered at risk. But this definition may indeed capture a good portion of the households of interest. While Jamasb and Meier find the usual conclusions (fuel poor households are poor, have children or are retired, spend more time at home), they also put high hope in smart meters. By showing current energy consumption, they hope that these meters will trigger behavioral changes and in particular help so far ill-informed households manage better the available energy and look for energy efficiency. As so often, good information goes a long way in managing scarcity.

Transfers to mothers may hurt children

It is conventional wisdom in policy circles that if you want a policy intervention to benefit children, transfers have to be paid out explicitly to the mother. The understanding is that mothers care more about their children than men, and thus are more likely to use the funds for them, directly or indirectly. There is really not reason to this backfire, but as two recent papers show, it can, in fact.

Matthias Doepke and Michèle Tertilt build a series of non-cooperative bargaining models of the household and show that things can go wrong with targeted transfers or women empowerment in general. Indeed, for transfers to have an impact on the intra-household allocation of public goods, there needs to be some kind on friction. The specifics of this friction have a large impact. For example, if women are hard-wired to prefer spending on children, then transfers targeted to them may lead to over-spending on children and under-spending on other public goods that also benefit children (say, shelter), reducing child welfare. Or: if the difference between men and women is in the market wage, women will naturally tends to more time intensive activities in the household, such as child rearing. Empowering women leads them to spend less time at home, hurting the children. If empowerment implies that women have access to more private goods (such as bars or entertainment), they will focus less on public goods that also benefit children. While these examples seem a bit convoluted, they highlight that things are not so simple.

Olivier Bargain and Olivier Donni show in another series of models with altruistic parents that targeted transfers may not work as well as targeted price subsidies. They demonstrate that price subsidies have an income effect and a substitution effect, something we teach undergraduates. But they reinterpret the substitution effect as a "targeting effect." Naturally, transfers only lead to an income effect. Thus subsidies are better at improving children welfare, but they are more expensive as they apply to everyone. So it all depends on elasticities, and depending on the situation, transfers or price subsidies could be preferred.

The impact of poor climate

We often cannot choose where we live, especially as academics, and have to bite the bullet when we end up in places where the climate is less than favorable. You sometimes wonder why humans willingly decided to settle in numbers in uninviting places. And it matters, as people not like poor climate, but that may be compensate by other factors, like having a job. Still, climate matters for satisfaction.

David Maddison and Katrin Rehdanz document using the world values survey that poor climate has a significant impact on life satisfaction. The latter is defined by self-reported survey results, thus to be taken with a rock of salt, and poor climate is defined by a measure akin to a standard deviation from a comfortable temperature, 65F or 18C. How significant the impact is cannot be evaluated without seeing some statistics about the climate measure, but let us believe the authors for a moment. This means that, ceteribus paribus, people in Central America and some parts of Africa should be the happiest. Of course, all other things are not equal. And there may be others things that correlate with temperature variations that also have an impact of happiness. For example, long nights in the winter have a strong impact on depressions in Nordic countries.

Maddison and Rehdanz then proceed to look at the consequences of a climate change scenario which provides country specific temperature changes. From this exercise, they find that Europe will gain in satisfaction, the US will be unaffected and Africa will suffer tremendously. While this is an interesting first shot at the question, I am not quite sure I am willing to run with it. In particular because the initial elasticities may be tainted by correlates that do not vary with climate change (for example, length of night is not expect to change), and because climate change will have other important consequences, for example about the availability of fresh water. But at least, this paper gets us thinking about these issues, and it highlights that those who would suffer the most are those that have the least to do with the origin of climate change.

How big are welfare stigma?

There is some literature that has tried to establish how large the stigma of participating in welfare programs are. Indeed, the fact that not all those that can obtain welfare benefits actually take them is an indication that feel bad about it, as long as they are aware of the relevant programs.Just how bad do people feel about this? The problem is that another factor comes in: time costs. Getting welfare benefits typically takes time: getting to the welfare office, waiting, filling forms and getting interviewed. This implies that the econometrician has a hard time figuring out the psychological costs of welfare participation. Indeed, time and psychological costs have very different policy implications. Time costs have a good reason: to select against welfare cheaters who are more likely to be discouraged by lost time. Psychological costs, however, are lower for the cheater. Also, discovering that the latter costs are high for the intended recipients is detrimental to the success of a program.

Colleen Flaherty Manchester and Kevin Mumford build a model of labor supply with an additive, one-time cost to welfare program participation in the utility function. Using structural estimation, they infer what the time cost as well as the psychological cost are, using the example of food stamps and WIC (healthy food checks for small children and pregnant mothers-to-be) in the US. They conclude that time costs amount to 0.5 hours a week for food stamps and 3 hours a week for WIC. The psychological costs are larger, about 3 hours for each program, but incurred only in the first week of participation, by assumption.

I am a big fan of structural estimation because it gives us the right quantitative framework for policy experiments. But the inferences in this case seem rather heroic to me. Indeed, there is no direct observation of the time cost. It is inferred from estimating a labor supply equation on a population where many do not work, for reasons beyond observables, and for them virtual wages are inferred. And the psychological cost amounts to a residual, and accordingly is estimated with a very large standard error. With all these caveats, I am surprised that there is no data that would measure the actual time lost through participation in those programs. This would considerably tighten estimates.

It is difficult to measure poverty

Measuring poverty is very difficult. First, it is a relative concept and requires the definition of a standard or threshold. Second, as people are usually not normally distributed, any single measure misses some aspect of the distribution. Third, the item whose distribution is measured may not be the appropriate one to represent poverty. Most of the time this is income, but temporary low income is very different from permanent low income, and in both cases, purchasing power may differ dramatically on location, social policies and period. All these difficulties have lead to a plethora of poverty measures. In fact, if you look at the program of any economic inequality conference, there will be plenty of papers on new measures by authors hopeful that their names will stick to a new index or coefficient.

Walter Bossert, Satya Chakravarty and Conchita d'Ambrosio come up with a new measure that emphasizes the persistence of poverty. They are very careful in making their measure following three axioms: the measure corresponds to static poverty in the one period-case, a measure is worse is poverty spells are longer ans spells out of poverty are shorter, and two decomposability axioms too complex to describe here.

The measure they propose is a weighted sum of per period poverty measures, where weight are proportional to the current poverty spell. Using the European Community Household Panel, they find that their measure does not change rankings much whether poverty spell weights are used or not. But I bet they would change quite a bit for the US.

Making Sen's capacity approach functional

Amartya Sen has provided an important framework that helps define the basic needs that human should be able to get. His capabilities and functionings approach has been very helpful in establishing how to measure human rights, and especially economic and social rights can be achieved. There is a large literature that helps to channel policy given current rights achievements.

Martin Binder and Alex Coad point out that all elements in Sen's approach (the capabilities) could in fact be endogenous to each other, in other words, one component could be a precondition to the other. For example, some functioning could depend on particular resources, or the reverse, or some functionings could be resources for others. one's health may depend on income, but income may also depend on health. This is rather important when one should decide what policy one should concentrate on. But it is not obvious how to establish such a hierarchy. To do this, they apply a panel vector autoregression to the British Household Survey Panel. Thus allows to extract the relevant leads and lags.

Clearly, income is a resources for many functionings, but "being happy" is also a resource for income, especially for males, and for other functionings like "being healthy," "being nourished" and "moving about freely." Mobility is also a resource for higher material well-being. Thus, ensuring people a happy can help ensuring other dimensions of welfare are more easily achieved.

Borrowing constraints and (seasonal) famines

Imagine that local food crops have very strong and predictable seasonal fluctuations. The obvious way to smooth consumption and avoid famines before new crops is to store food. Suppose now that this is for some reason not possible. Then, you should trade food with another region that has countercyclical crops, or at least storable crops. What if even that is not possible? Then it should be seasonal migration that should bring people where there is food. And what if that does not happen? You have the rural northwestern districts of Bangladesh.

Shyamal Chowdhury, Ahmed Mushfiq Mobarak and Gharad Bryan performed there a randomized intervention by giving a monetary incentive for seasonal migration. While this would obviously improve outcomes, they varied the conditions for the payout to see what would work best: cash or credit, mandating group or individual migration, changing group size, imposing destinations, etc. For once a randomized intervention study tackles the efficiency of the intervention, a welcome change.

While seasonal migration in the control group was 13%, it was 40% in the intervention group, a significant difference, and much more efficient than just informing about wage opportunities elsewhere, which only triggers a 2% increase in migration. The fact that these payments have such a large effect highlights that the true problem is the liquidity constraint these people are facing.

That said, all this depends on the size of this cash payout. With a very large payout, it would not be surprising to see a large response. The financial incentive corresponded to US$11.50, or about 4 days worth of wages in the destination regions. That does not seem very high, and one could hope that with the normal improvement of conditions over time, this problem should be relatively easy to overcome.

How much to save for retirement

The conventional wisdom is that one should live in retirement with an income of about 70-80% of pre-retirement income. It is less than 100% because the tax rate is lower, because Medicare takes care of some expenses, and because employment related expenses disappear. But these 70-80% are really a rule of thumb that should clearly be differentiated in various ways.

John Karl Scholtz and Ananth Seshadri do this using life cycle models. The easy parts: if you previously had a particularly high income, a lower share can do easily, in part because taxes drop much more. Same if you had many children as they are, hopefully, out of the house by retirement. The more complex part: one should draw a life-cycle model where the goal is to equalize the discounted expected marginal utility of consumption across time, where health, incomes and lifetimes all are uncertain.

Scholtz and Seshadri find replacement rates that differ widely, with a median of 68% (or 57% considering the five highest years of income) and range of 47% to 90%, depending on the household category. For example, married couples need a higher replacement rate because of the higher expected lifetime of the survivor compared to a single person. Also, changes in taxation rates are very important for determining the marginal utility of consumption, especially if tax rates will be increasing instead of decreasing like in recent years. Finally, shocks to earnings are very persistent, thus whether they happen at the start or the end of a career can change dramatically the replacement rate.