Immigration benefits us all – now the IMF gets in on the act

Only a short time after the Foged & Peri paper (summarised here) found that an “influx” of immigrants to Denmark benefited the both high-skilled and low-skilled workers in the local population, the IMF has examined whether or not those results apply to other advanced economies.

And, guess what? They do! Unsurprisingly.

In order to do so, the study uses a fairly nifty approach to accounting for potential reverse causation between migration and GDP per capita (since migrants might prefer moving to countries with higher GDP per capita in the first place). The study uses a “gravity model” to instrument for the share of migrants in a country, including various “push” factors (such as growth in the origin country, demographic variables etc.) and other controls, proving once again that describing something as “gobbledygook” just because you don’t understand it isn’t a particularly sensible thing to do.

The paper’s main findings are threefold. First, a 1% point increase in the proportion of population made up by migrants actually increases GDP per capita by 2%. Interestingly, this benefit arises via an increase in labour productivity, rather than an increase in the proportion of the population that is of working age.

For example, high-skilled immigrants can increase productivity through innovation and positive spillovers on native wages, while low-skilled workers can increase productivity by enabling native workers to re-train and move into more complex occupations (exactly as was found by Foged & Peri). An alternative mechanism cited by the IMF study suggests that the presence of low-skilled female immigrants increases the provision of household and child-care service, thereby increasing the labour supply of high-skilled native women. This result is robust to controlling for technology, trade openness, demographics, and country development.

Second, these benefits arise from both low-skilled and high-skilled migrants. As above, both skill-types affect GDP per capita through increasing labour productivity, rather than via increasing the proportion of the population that is of working age. However, the effect does appear to be more statistically significant for migration by low-skilled workers than it is for high-skilled migrants.

The study suggests that this difference could reflect differences in the impact of high-skilled migrants across different countries, but this seems unlikely to be sufficient to render the impact insignificant. More likely is the second reason posited by the study – namely, that high-skilled migrants initially might have to obtain jobs for which they are over-qualified, thereby meaning that their impact on the incentives of high-skilled native workers to retrain etc. is limited at first.

Third, the benefits to native workers arise across the entire income distribution. Both low-skilled and high-skilled immigration increase the GDP per capita of those in the bottom 90% of the income distribution by roughly the same amount, while high-skilled immigration increases the GDP per capita of those in the top 10% of the income distribution by roughly twice as much as does low-skilled immigration.

However, the study does not really examine the distribution within the bottom 90% particularly closely – the study just looks at the estimated impact of immigration on the Gini coefficient to conclude that the distribution within the bottom 90% would not be changed significantly. The study should, instead, have looked at, say, the impact of immigration on each decile or quintile of the income distribution separately so as to give a more complete picture of the impact of immigration across the income distribution.

The paper (and particularly the blog post linked to above) ends by getting somewhat more political. In particular the study suggests that there is a need for improvement in terms of providing support for native workers that want to re-train, find a new job etc. However, these policy suggestions are made without taking into account the fact that some countries do already have plentiful such schemes in place, to the extent that increasing the provision of such schemes in those countries might not be efficient. Of course, that’s not to say that some countries would benefit from increasing the provision of such schemes.

Grammar Schools: Sam Freedman really should know better

Over the past few days there as been quite a bit written about whether or not selective schools (i.e. allocating children to schools at age 11 based on ability) are beneficial or not, either in terms of social mobility, educational outcomes or other areas. This stems from rumours that Theresa May is reviewing current ban on Grammar Schools.

A number of commentators have claimed that re-introducing academic selection at 11 years old is a bad idea. For example, Sam Freedman, an executive director of Teach First and someone who really should know better has claimed that selective education is bad for social mobility; societal integration; accuracy of assessing ability; and/or promoting parental choice of school.

However each of Freedman’s supposed criticisms are not supported by the evidence.

First, there is strong evidence to support the idea that grammar schools actually improve social mobility and countries with selective systems tend to be no less integrated than those without. In making his claim that grammar schools harm social mobility and lead to decreased integration, Freedman cites this webpage. However, the results displayed on that webpage rely solely on correlations and does not try to control for any other factor that might account for the apparent relationship between deprivation and performance. For example, the difference in wages between grammar and comprehensive educated people could simply reflect the fact that grammar schools select those who are more likely to obtain a better wage anyway and enable them to reach their full potential, whereas those students would be held back if they were forced to attend a comprehensive. It also does nothing to account for different demographics beyond an entirely arbitrary and undefined measure of “deprivation”.

Indeed, the webpage cited by Freedman seems to view social mobility as being achieved by “preventing the gifted from reaching their full potential” rather than “allowing everyone to reach their maximum”. However, there is a substantial weight of evidence that indicates that selective schools not only enable the most-skilled to achieve their full potential, but also substantially improved outcomes for the less-skilled. For example, Dale & Krueger states that “students who attended more selective colleges earned about the same as students of seemingly comparable ability who attended less selective  schools. Children from low-income families, however, earned more if they attended selective colleges.”

Similarly, Galindo-Rueda & Vignoles finds that “the most able pupils in the selective school system did do somewhat better than those of similar ability in mixed ability school systems. Thus the grammar system was advantageous for the most able pupils in the system, i.e. highly able students who managed to get into grammar schools.

In other words, selective schools incontrovertibly enable the highly-skilled to achieve their full potential as well as benefiting children from low-income families. This result is also supported by a study commissioned by the Sutton Trust – despite their avidly anti-selective school bias leading them to try to weasel their way out of the positive grammar school effect, the study finds that grammar schools tend to increase student performance by roughly two grades per subject taken at GCSE.

Second, Freedman’s claim that the 11-plus is poor at assessing ability does not stand up to scrutiny. Freedman claims that 70,000 students are wrongly classified by the 11-plus test – it is not clear if Freedman means 70,000 over the entire span of grammar schools’ existence, or 70,000 “mistakes” every year. If the former, then the proportion of mistakes made is clearly tiny as millions of people would have taken the 11-plus since it was first used. If the latter, then assuming that all 700,000 11 year olds take the 11-plus (not an unreasonable assumption) that gives a “failure rate” of just 10%. Clearly this is not very large. And those that suggest that even a single failure is unacceptable when it comes to a child’s education are being completely impractical since no educational system exists that can completely eradicate failures.

Finally, Freedman claims that grammar schools are “anti-choice”. However, this is clearly false – there is an obvious mechanism by which grammar schools promote choice of school. Specifically, the presence of an 11-plus test gets parents thinking about what will happen after the test, encourages them to research different schools and think about what school(s) would be best for their child. In other words, the 11-plus exam incentivises parental involvement in school choice, thereby promoting it.

Hence, Freedman is incorrect on every single point he mentions about selective schools. From someone that high up in Teach First, that is simply unforgivable.

(Not) Eating for two: Fasting and educational attainment

Recent news regarding the possibility of moving the dates on which core GCSE exams are held forward so as to avoid Ramadan has highlighted the impact that fasting and nutrition can have on exam results and educational attainment.

The impact of fasting / poor nutrition during exam periods and/or while growing up has been subject to numerous studies before – see, for example, Anderson et al. and  Glewwe & Miguel.

However, what has received less attention (at least until now) is the impact of a mother’s fasting during pregnancy on a child’s educational attainment. That is why a paper by Douglas Almond, Bhashkar Mazumder, and Reyn van Ewijk in the latest issue of The Economic Journal is rather interesting – it looks at precisely this issue.

Specifically, the paper looks at the impact of Ramadan falling during pregnancy (i.e. the impact of fasting during the gestation period) on the educational attainment of Pakistani and Bangladeshi children (i.e. those children most likely to be of Muslim decent and, hence, whose mothers are most likely to have fasted during Ramadan) at age seven compared to that of other groups of children and finds that there is a small, but significant, decrease in educational attainment of the Pakistani and Bangladeshi children. The authors use this result to suggest that “brief prenatal investments may be more cost effective than traditional educational intervention in improving academic performance.

On the whole, the paper is a good one, following a clearly set out method, and the results provide useful policy indications. However, that is not to say that the paper does not have some flaws.

First, the paper uses the educational attainment of children of Caribbean decent as the “control group” against which the educational attainment of Pakistani and Bangladeshi children is tested. The authors justify this on the grounds that Caribbean families are unlikely to fast during Ramadan, such that the control group is unaffected by Ramadan. Although this might seem reasonable from a statistical perspective (although I’d argue that it still introduces unacceptable biases into the analysis), from a policy perspective it is less desirable.

Specifically, the relevant control group to determine whether a policy would be worthwhile is “the average student” – the authors do not provide any evidence to indicate that Caribbean students represent the average attainment in the UK. Indeed, the paper actually suggests that Caribbean students’ educational attainment tends to be below the UK average. In other words, the effect that the paper finds is likely to be understated relative to the average student, such that the paper’s conclusions could be much stronger if the average educational attainment was used. (Although the paper conducts a “robustness check” using White British students as an alternative control group, this still fails to get at the effect compared to the average student.)

Second, the paper assumes a “standard” gestation period of xx days, but does not investigate the extent to which changing the length of this gestation period affects the results. It could be that a slight change in the length of the gestation period assumed by the authors would affect the effect they find, which is important given that the effect they find is relatively small (albeit statistically significant). Hence, the rigour of the paper could have been improved by including this sensitivity check.

Third, the authors fail to make sufficient inference from the results presented in the paper. In particular, the paper’s results indicate that the impact of fasting on educational attainment differs according to the stage during the gestation period at which the fasting occurred – the impact of gestational fasting on educational attainment is largest when it happens during the third and fourth month of gestation and is almost negligible when it occurs after the seventh month. In other words, the paper could have highlighted the importance of early nutritional interventions for policy during gestation, but failed to do so.

Nonetheless, despite these flaws, the paper is an interesting one, with some important policy implications.