New Economist

Skilled migration boosts innovation

A recent paper by McGill University's Jennifer Hunt to an NBER labour studies programme conference asks whether the increase in foreign-born college graduates has contributed to innovation in the United States. Her paper, How Much Does Immigration Boost Innovation? (PDF), finds that it does:

In this paper I have demonstrated the important boost to innovation per capita provided by skilled immigration to the United States in 1950-2000. A calculation of the effect of immigration in the 1990-2000 period puts the magnitudes of the effects in context.

The 1990-2000 increase from 2.2% to 3.5% in the share of the population composed of immigrant college graduates increased patenting by at least 81:3 = 10:4%, and perhaps by as much as 18%. The increase in the share of post-college immigrants from 0.9% to 1.6% increased patenting by at least 10.5% and perhaps by as much as 24%. The increase from 0.30% to 0.55% in the share of workers who are immigrant scientists and engineers increased patenting by at least 13% but probably by less than 23%.

While I find evidence for the crowding-out of natives in the short run, in the long run there is evidence for the reverse: that skilled natives are attracted to states or occupations with skilled immigrants. The results hint that skilled immigrants innovate more than their native counterparts, especially if they are scientists or engineers. If correct, the result could reflect higher education of immigrants within skill categories, or positive selection of immigrants in terms of ability to innovate. However, the effect of natives is not as well identified econometrically as the effect of immigrants.

These findings suggest there are clear merits in adopting policies to both attract foreign students and to retain them once they have completed their studies (as the UK and Australia, among others, currently do).

How rural villages have gained from China's great migration

Inter-county migration in China - mostly rural migrants moving to urban areas - increased four-fold during the 1990s, from just over 20 million in 1990 to 79 million by 2000. With what effect?

Co-authors Alan de Brauw from the International Food Policy Research Institute and Michigan State University's John Giles examine the impacts this great tide of migration has had on China's rural villages. Their paper, Migrant Labor Markets and the Welfare of Rural Households in the Developing World: Evidence from China (PDF), finds that rural out-migration has boosted per capita consumption and reduced inequality:

We find that increased migration from rural villages leads to signicant increases in consumption per capita, and that this effect is stronger for poorer households within villages. Household income per capita and non-durable consumption per capita both increase with out-migration, and increase more for poorer households.

Villages with the fastest growth in out-migration have seen the largest reductions in village poverty headcount and the strongest growth in average consumption levels. Out-migration has also reduced inequality - "expanded migration is associated with decreasing inequality within villages", as poorer households "supply more labor to productive activities and experience more rapid income growth".

There are mixed effects on rural investment - new earnings from urban jobs have largely been spent on better homes and durable goods:

A second important finding relates to the impact of migration on investment in rural areas. Increases in migration from rural China are associated with increased accumulation of housing wealth and consumer durables, but we do not find evidence of a significant relationship between migration and investment in productive assets.

While none of these findings are particularly unexepected, they help unpack China's economic story. And they show that it is not just international migration that brings benefits.

Why people emigrate

Semi-regular blogging service resumes this week with a few posts on migration - still a very topical issue on both sides of the Atlantic.

The first paper I'd like to highlight is by the University of Chicago's Jeffrey Grogger, and UCSD's Gordon H. Hanson. Their recent NBER Working Paper No. 13821, Income Maximization and the Selection and Sorting of International Migrants, seeks to explain to what extent selection and sorting account for international migration flows using data on emigrant stocks by schooling level and source country in OECD destinations. As the authors conclude, a simple model can explain a lot:

Two dominant features of international labor movements are positive selection of individuals into migration and positive sorting of migrants across destinations. We show that a simple model of income maximization can account for both phenomena.

The more educated are more likely to emigrate; and more-educated migrants are more likely to settle in destination countries with higher rewards to skill. As the authors explain:

In our selection regression, we find that migrants for a source-destination pair are more educated relative to non-migrants, the larger is the skill-related difference in earnings between the destination country and the source. That is, positive selectivity is stronger where the reward to skill in the destination is relatively large. This result obtains for wage differences expressed in levels, but not in logs.

...Positive sorting is a general prediction of income maximization. In our sorting regression, the relative stock of more-educated migrants in a destination is increasing in the level earnings difference between high and low-skilled workers. This correlation is stronger when wage differences are adjusted for taxes, implying that migrants weigh post-tax earnings when choosing a destination. The U.S. and Canada enjoy relatively large post-tax skill-related wage differences, which largely account for their ability to attract more educated migrants relative to other OECD countries.

Other factors are also at work:

Our analysis also shows that language, history, and policy affect migration. English-speaking destinations draw higher-skilled immigrants than other destinations, whereas former colonial powers draw lower-skilled immigrants from their former colonies than from other source countries. Destinations with liberal refugee and asylum policies draw relatively low-skilled immigrants, all else equal.

An ungated version of the paper is available here or here.

Should we kill the king?

Are autocratic leaders an impediment to democratisation? An intriguing question, which some economists have recently sought to answer.

A year ago a JPE article by Harvard's Ben Olken on corruption in Indonesia attracted attention for its innovative appproach. The American magazine has a profile of him by Michael Moynihan, Graft Paper, discussing this and other research, including a paper co-written with Northwestern's Ben Jones, Hit or Miss? The Effect of Assassinations on Institutions and War (PDF). Moynihan summarises it thus:

Olken and Jones looked at the effects of political assassination, using a strict empirical methodology that takes into account economic conditions at the time of the killing and what Olken calls a “novel data set” of assas­sination attempts, successful and unsuccessful, between 1875 and 2004.

Olken and Jones discovered that a country was “more likely to see democratization follow­ing the assassination of an autocratic leader,” but found no substantial “effect following assassinations—or assassination attempts—on democratic leaders.” They concluded that “on average, successful assassinations of autocrats produce sustained moves toward democracy.” The researchers also found that assassinations have no effect on the inauguration of wars, a result that “suggests that World War I might have begun regardless of whether or not the attempt on the life of Archduke Franz Ferdinand in 1914 had succeeded or failed.”

The whole article is worth a read - as are Olken's other papers.

Winning American Idol: try to be last

If you are appearing on American Idol or the X-Factor, try to be one of the last to sing. That's the conclusion from a new paper presented at a University of Westminster seminar today. Lionel Page and Katie Page look at an important topic - the evaluation of a sequential order of performances. Their paper, Biases in sequential performance evaluation, a field study on the Idol series (PDF), drew on a large dataset based on the ranking of contestants in live pop Idol shows in 8 countries (Australia, Brazil, Canada, Germany, India, Netherlands, UK, USA). That's 1,522 performances from over 165 shows. They found two main biases which influenced overall sequential performance ratings:

Our results suggest that the two mechanisms, memory and direct comparison, both play a role in the order bias. With respect to memory it appears that both primacy and recency effects are implicated when sequentially evaluating performance. Irrespective of ability, contestants who perform first are more likely to be positively evaluated than those who come in second and third positions, which provides evidence of a primacy effect. Contestants who perform in the later serial positions (particularly last position) have the largest advantage with respect to positive evaluations, implying a strong recency effect.p>

...The second bias we demonstrate is a direct comparison effect with the previous contestant. Specifically, one's performance evaluation is influenced by the evaluation of the previous contestant. If you perform after a weak contestant there is a bias such that you are more likely to be evaluated poorly than if you perform after a strong contestant. Therefore, we find evidence for an assimilation effect with respect to sequential judgments.

...Overall, we show that these two effects both operate and are important explanatory mechanisms in the evaluation of sequential performance.

Something to ponder when you go speed dating, or get a call to say you've been shortlisted for a job interview and are asked what slot you'd like.

UPDATE:

WSJ's Matt Phillips has obviously read my post, writing about the paper at the Journal's real Time Economics blog: Last Shall Be First in Idol Economics

The mixed benefits of remittances

Recent years have seen international agencies like the World Bank and IMF extol the econmic benefits of remittances. Sending money to the folks back home boosts the incomes of developing countries and helps to offset losses fom the 'brain drain'. What's not to like?

Well, we wouldn't be economists if we weren't looking for unintended consequences. And sure enough, David Grigorian and Tigran Melkonyan have found some. Their recent IMF working paper Microeconomic Implications of Remittances in an Overlapping Generations Model with Altruism and Self-Interest studies the impact of remittances on Armenian households:

We demonstrate that when the migrant and the relative(s) cooperate to maximize the joint utility of the household, this leads to higher level of remittances as well as investment and hours worked by the relative(s). We use data from Armenia to test our predictions regarding implications of remittances flows on behavior of receiving households.

Consistent with our predictions, remittance-receiving households work fewer hours and spend less on the education of their children. While saving more, these households are not leveraging their savings to borrow from the banking system to expand their business activities. This evidence suggests that the benefits of remittances might be overstated and emphasizes the importance of measuring their impact in a general- rather than a partial-equilibrium context.

So remittances lead to households working fewer hours: "The coefficient is negative and significant and its magnitude is rather large." More surprising is the apparent negative effect on education. The authors conjecture:

The impact of remittances on education spending (column 3, Table 3) is perhaps the most controversial of our findings. The negative (and significant) coefficient here could be indicative of two things. First, it is possible that members of remittance-receiving households are likely to later migrate themselves and, therefore, not value the local education as much. Second, because their consumption patterns might be under scrutiny by the remitter, the receiving households may adjust their consumption pattern to look more conservative and be
centered around necessities (such as food and public services/utilities, and presumably not education and other types of spending that could be considered unnecessary from theremitter’s point of view). To the extent that remittances represent a large share of the receiving family’s income, for the same level of disposable income, this tendency to “simplify” the spending pattern could in fact lead to lower spending on education (in nominal terms) out of total income.

Families with remittances do accumulate more savings. While the costs of migration on households have a negative effect, it is "not large enough ..to offset the accumulation of savings due to remittances."

I would be interested to see if similar remittance effects are to found in other countries with high levels of emigration.

Growth diagnostics: the dangers of agnosticism

Why does income grow faster in some countries than others? A common empirical approach in recent growth analysis has been to adopt an 'agnostic' approach and let the data do the talking (i.e. weak priors). But a new paper by Antonio Ciccone from Barcelona's ICREA-Universitat Pompeu Fabra, and ECB economist Marek Jarocinski, question this approach. In their new ECB working paper no. 852, Determinants of economic growth: will data tell? (PDF), they show that small differences in the comparative income data can have a substantial effect on the outcomes:

As many potential explanatory variables have been suggested, these agnostic empirical approaches inevitably need to start out with a long list of variables. We show that, as a result, the growth determinants emerging from these approaches turn out to be sensitive to seemingly minor variations in international income estimates across datasets. This is because strong conclusions are drawn from small differences in the R2 of different growth regressions. Small changes in the relative fit of different models—due to Penn World Table income data revisions or methodological differences between the PWT and the World Bank income data for example—can therefore lead to substantial changes regarding growth determinants.

Their analysis clearly shows that agnostic growth regressions can be sensitive even to small data revisions. They suggest that "the available income data may be too imperfect for agnostic empirical analysis". So what to do? Stronger (and fewer) priors:

At the same time, we find that the sensitivity of growth determinants to income differences across data revisions and datasets falls considerably when priors regarding potential growth determinants become stronger. That is, the data appears good enough to differentiate among a limited number of hypotheses. Empirical models of the typical size in the literature, for example, tend to point to the same growth determinants using different versions of the PWT or the World Bank income data.

Researchers who want to continue giving equal a priori weight to all potential growth determinants in the literature, should consider shrinkage priors, explicitly incorporating priors about measurement error in the income data, or implementing Zellner’s (2002) adjustment for data quality.

Growth theory: Solow or Lucas?

I've just come across a new OECD economic working paper on growth theory: Solow or Lucas? Testing growth models using panel data from OECD countries. Authors Jens Arnold, Andrea Bassanini and Stefano Scarpetta test whether the growth experience of a sample of OECD countries over the past three decades is more consistent with the human-capital augmented Solow model of exogenous growth, or with an endogenous growth model à la Uzawa-Lucas with constant returns to scale to “broad” (human and physical) capital. Here's their methodology:

We exploit the different non-linear restrictions implied by these two models to discriminate between them. Using pooled cross-country time-series data, we specify our growth regression by imposing cross-country homogeneity restrictions only on  long-run  coefficients, while  letting  the  speed  of  convergence  and  short  term  dynamics  to  vary  across  countries.

Their conclusions?

The results suggest a strong effect of human capital accumulation: the estimated long-run effect on output of one additional year of education (about 6-9%) is also within the range of the estimates obtained in microeconomic analyses of the private returns  to  schooling. Our estimated speed of convergence is too fast to be compatible with the augmented Solow model, while is consistent with the Uzawa-Lucas model with constant returns to scale. This main finding is robust to several robustness tests. 

How useful is Okun's Law?

Edward S. Knotek asks an interesting question in the latest Kansas City Fed's Economic Review: How Useful is Okun's Law? (PDF)

From the beginning of 2003 through the first quarter of 2006, real gross domestic product in the United States grew at an average annual rate of 3.4 percent. As expected, unemployment during the period fell. Over the course of the next year, average growth slowed to less than half its earlier rate--but unemployment continued to drift downward. This situation presented a puzzle for policymakers and economists, who expected the unemployment rate to increase as the economy slowed.

Typically, growth slowdowns coincide with rising unemployment. This negative correlation between GDP growth and unemployment has been named “Okun’s law.” Part of the enduring appeal of Okun’s law is its simplicity, since it involves two important macroeconomic variables. Additionally, the relationship appears to enjoy empirical support. In reality, though, Okun’s law is a statistical relationship rather than a structural feature of the economy. As with any statistical relationship, it may be subject to revisions in an ever-changing macro economy.

Knotek considers the usefulness of Okun’s law for policymakers and economists. The evidence suggests that Okun’s relationship between changes in the unemployment rate and output growth has varied considerably over time and over the business cycle. Nevertheless, Okun’s relationship can still be useful as a forecasting tool--provided that one takes its instability into account.

Do economic sanctions deter?

Harvard doctoral graduate Ioana M. Petrescu has studied a much-discussed but little-studied subject: do economic sanctions actually work? Her recent paper, Rethinking Economic Sanction Success: Sanctions as Deterrents (PDF), finds that they do appear to deter future disputes:

Economic sanctions are one of the most common foreign policy tools. Despite their widespread use, there is little empirical evidence and much debate about how sanctions affect countries’ behavior. In this study, I investigate whether sanctions affect future military behavior.

I look at the effects of sanctioning a country involved in a militarized dispute on the probability that the sanctioned country or any other country involved in the dispute will be involved in a militarized dispute in the future. I also look at the effects of the sanction on the probability that countries similar to the ones in the sanctioned dispute will participate in another dispute in the future. I use the Correlates of War data on militarized interstate disputes and Hufbauer et al.’s data on economic sanctions.

I find that countries involved in a dispute and countries similar to the ones involved in the dispute are less likely to participate in another dispute in the future if one of the countries involved in the original dispute was sanctioned.