Friday, 30 May 2014

What do we know about immigration?

by Christian Dustmann and Ian Preston

Centre for Research and Analysis of Migration (CReAM) at University College London.

In the current heightened political climate, consideration of the factors which determine immigration policy should be based on the best available evidence. We at the Centre for Research and Analysis of Migration have composed a briefing, intended to promote discussion that is informed and not alarmist, low key and not polemical. In that note we point out the challenges for researchers in measuring the social and economic consequences of immigration, backed up with detail and references to appropriate academic study in the respective field.

Restrictive immigration policies are a curtailment of individual freedom of movement that causes real harm both to individuals already in the receiving country and to potential immigrants. Families are prevented from being together, innovative and productive economic relationships are prevented from happening, fleeing persecution is made more difficult. To justify this requires strong reasons and reasons that are rooted in evidence rather than anecdote.

Advocates of tighter immigration control believe that reasons can be found in negative consequences for receiving countries.  For instance, wages may be depressed by inflows of labour; changes in the character of receiving neighbourhoods may cause cultural dislocation; pressure on public spending can worsen the state of public finances; pressure on public services may lead to deterioration in the quality of services to local populations.  All of these could, if true, be reasons for caution in immigration policy but it is not obvious that any of them are true. Immigration could be economically invigorating, promoting innovation and raising wages; local cultures could be enriched by the diversity that comes with immigration; taxes paid by young and productive immigrants could ease pressures on the public exchequer; staff born abroad could be essential to delivery of public services.

Whether or not any of these issues should be what determines immigration policy, it is surely true that discussion should be driven by something more substantial than hearsay and hunches. Measurement of the effects of immigration on receiving countries is challenging, fraught as it is within the need to separate genuinely causal from merely coincidental relationships and there is a great deal still to be understood. Nonetheless, we find the progress made by academic researchers in better understanding the phenomenon of immigration and in opening up new avenues of research to be encouraging. New scholars choosing migration studies as the topic of their academic career and new data sources paired with new methodology have provided new insights into phenomena that were previously not well understood. For instance, research is making progress in understanding the impact immigration has on innovation and entrepreneurship, on opportunities which immigration opens up for native-born individuals and in assessing the effects immigration has on the labour market and the economy of receiving countries, not just through employment and wage adjustments, but also through new trade opportunities and technological advances. In the briefing we try to summarise the best available research on some of the most critical impacts.

There are still many open questions that need addressing and the balance of evidence can always shift as research progresses, but there seems to us little basis in existing research to fear the consequences of or to feel the need to apologise for supporting a relatively open and progressive immigration policy.

Wednesday, 12 March 2014

Reply to the Report ‘An Assessment of the Fiscal Effects of Immigration to the UK’ by Migration Watch

by Christian Dustmann and Tommaso Frattini

Centre for Research and Analysis of Migration (CReAM) at University College London.

Migration Watch (MW) has released for publication on Thursday 13 March 2014 a report entitled ‘An Assessment of the Fiscal Effects of Immigration to the UK’.

In this report MW claims that our research paper on ‘The Fiscal Effects of Immigration to the UK’ [http://www.cream-migration.org/publ_uploads/CDP_22_13.pdf], released on November 5 2013, has some flaws that invalidate our main results, namely that EEA immigrants who came to the UK since 2000 have contributed over the last 11 substantially more in revenues than they received in state expenditures. This contrasts with the UK-born, who over the same period contributed substantially less than they received.

MW states that our main results – that EEA immigrants who came to the UK since 2000 have contributed over the last 11 years substantially more in revenues than they have received in state expenditures – is ‘simply wrong’ because it relies on the assumptions that that (page 7, point xi (a) of their report):

(1) [Migrant] employees earn the same as the UK-born population; (2) Self-employed migrants contribute far more than those employed; (3) Migrants own the same investments, property and other assets as the UK-born and long-term residents from the day they arrive in the UK. 

Their first claim is simply incorrect. At no point do we make assumption (1). We rather allocate earnings (and the ensuing tax receipts) according to the figures on earnings for immigrants and natives that we obtain from the UK Labour Force Survey (LFS). 

Further, their second claim is also incorrect. At no point do we make assumption (2). In fact, in the absence of information on self-employed earnings, we allocate tax payments of the self-employed according to the shares of income tax payments computed for employees. This may rather lead to an underestimate of the income taxes paid by immigrants, as relatively more immigrants are self-employed. 

Finally, we have responded to the third point in an earlier reply from November (ignored in the piece by MW), where we compute an extreme scenario where recent immigrants pay no corporate taxes and business rates whatsoever, and allocate these taxes to long term residents only. We still find that recent EU immigrant make a positive contribution, while the net contribution of natives remains negative.

MW’s main criticism is based on a fundamental misapprehension of what we are doing. MW’s main argument builds on a serious misinterpretation of the way we estimate income tax contributions and NIC payments of immigrants. MW claims that we assume that migrant employees earn the same as the UK-born population, and that self-employed migrants contribute more than those who are in salaried employment. But at no point do we make any of these assumptions, nor is there anything in our paper that suggests that in any way. It is therefore puzzling to us why their piece attacks our work so violently, based on a complete misapprehension of what we are doing. 

More precisely, data in the UK LFS does not collect information on self-employment earnings. Despite this shortcoming, the LFS is the best available data source for our purposes, as it contains consistent wage data and information on country of birth over a long time period. It is well known that the Annual Survey of Hours and Earnings (ASHE) that MW suggests as a more reliable data source (point 36, page 23) does not contain information on the earnings of self-employed either, and, more importantly, does not have any information on country of birth, which is obviously crucial for analysis on the fiscal impact of immigration.

Thus, in the absence of information on earnings of the self-employed, we use the LFS to construct the share of income tax and National Insurance contributions payments made by native and immigrant employees based on their reported earnings. We then use these shares to allocate the total amount of income tax and NIC revenues to immigrants and natives, including that paid by the self-employed. This strategy does not require making either assumption (1) or (2) above, as MW claims we do. Further, since self-employment is more common among recent EEA immigrants than among natives, this choice may lead to an underestimate of total EEA immigrant tax payments, exactly the opposite to what they claim.

MW also criticises the way we have allocated corporate tax payments. We assume that company ownership (i.e. share ownership) is similarly distributed between the native and immigrant population, and we clearly state this assumption in our paper (page 13). MW’s criticism is not new, and we have already responded to it in an earlier reply [http://www.cream-migration.org/commentsarticle.php?blog=2]. In the same reply, we also respond to a related criticism, which MW raises again, about the way we allocate business rate revenues, based on the share of self-employed in each population group. MW – and other commentators before – argued that this may be incorrect because business rates are primarily paid by large businesses.

As an example, MW says that Sainsburys pays £400 million a year in business rates (no source is given). But as we explained in our earlier response, ‘the allocation of corporate taxation and business rates raises complicated questions of incidence. The fact that businesses write the cheques does not mean that the burdens do not fall ultimately on people. Whether those people are customers, shareholders, property owners or whoever, depends upon how economic decisions and, as a consequence, prices respond to taxation and is not a straightforward question.’ Coming back to MW’s example, the burden of business rates may be borne by consumers in terms of higher prices or local property owners in terms of lower rents, and so on.

In our previous reply, we have also computed the total fiscal contribution of recent EEA immigrants under the extreme (and clearly implausible) assumption that recent immigrants do not pay any corporate taxes or business rates, and we have allocated these taxes to long term residents. Even in this case, which represents an extreme lower bound on the tax payments of recent immigrants, we still find that EEA immigrants made a substantial overall positive net fiscal contribution, while the contribution of natives remains negative. It is disappointing that MW ignores this reply in their piece.

To summarise, MW’s main criticism is based on a stark misapprehension of our methodology. The report is written in a derogatory language seemingly attempting to undermine our reputation with suggestions that we do not adequately describe our methodology or comment on all our results. We are in fact very open about our methodology - which has been acknowledged even by earlier critics of our work (including Prof M. Stone, cited approvingly in their report, who comments that ‘we set out our assumptions with commendable clarity’ [page 3 here: http://www.civitas.org.uk/pdf/assumptionsandwizardry.pdf]).

Their strongly worded criticism is all the more surprising as the MW report is based on a substantial amount of guesswork, does not provide clear indication of how their figures are computed, and is at times sloppy or simply wrong. For example, the authors must have misread section 2.2.3 of our paper and/or earlier research of ours (Dustmann, 1997; and Dustmann, Fasani and Speciale 2013), as this research never claims that the level of consumption for migrants may be 20% lower than that of the indigenous population. Also, there seem to be calculation mistakes in some of the figures in their tables.

We welcome constructive criticism of our work, and we have engaged responsively and transparently with outside researchers who have raised criticisms since we believe that only an open and fact-based debate can do justice to a subject as sensitive as immigration. 

MW chose to circulate their critique to the media earlier this week without sending it to us so we have not had the chance to point out errors to them as we would have been able if they believed in conducting debate similarly openly. Although the report cites some of the reports that are critical of our work, MW has chosen to ignore detailed replies already made, notwithstanding the fact that they are easily available on the CReAM webpage [http://www.cream-migration.org/comments.php], were brought to their attention at the time, and already respond to some of their criticisms.

Wednesday, 29 January 2014

There are no “Schoolboy Errors” in our report

by Christian Dustmann and Tommaso Frattini

Centre for Research of Analysis and Migration (CReAM) at University College London

On January 2nd, Civitas published two reports on our paper The Fiscal Effect of Immigration on the UK on their website, and added a press-release entitled “Schoolboy errors in UCL report claiming fiscal benefit to immigration”. Reading the two reports carefully, it is puzzling what has led Civitas to this headline, and to some of the statements made in the press release.

The first piece [http://www.civitas.org.uk/pdf/assumptionsandwizardry.pdf] is by Prof. Mervyn Stone, an emeritus statistics professor at UCL.

Prof. Stone thought that the report is an ambitious and largely scholarly study, in which crucial assumptions (about how to share expenditures and revenue between immigrants and natives) are set out with commendable clarity – and are therefore open to a degree of critical comment…. He then raises some econometric/statistical criticisms of our analysis. However, the main and most important part of the report does not contain any econometrics, as Prof. Stone admits (“Econometric modelling was not invoked for the estimation of fiscal effects”). His piece has therefore not much to say at all about the main part of our paper, which relates to the fiscal effects of immigration.

The emphasis of his piece is rather on the estimation of probability models to determine whether immigrants from different groups are more or less likely than natives to receive state benefits/tax credits or live in social housing. Overall, all of these comments are quite minor and indeed “text-book” like, and we cannot detect any hint to a fundamental flaw in the way we have conducted our analysis. As with any analysis of data, the analyst has to make some assumptions, which is what we have done here as well, and which - as Prof. Stone admits – we “set out with commendable clarity”. None of the assumptions Prof. Stone mentions in his piece would in our view change the main conclusions that we draw from this part of our analysis, as we illustrate in our brief appendix below.

The second piece [http://www.civitas.org.uk/pdf/RespondingtotheFiscalEffects.pdf], by Nigel Williams, focuses in turn on the fiscal contribution analysis. His emphasis is on the government data we use and the assumptions needed for conducting analysis. Some of these comments are indeed well taken – and we are very clear in our report about the difficulties in conducting such analysis, based on the data that is available. In fact, we devote an entire section (section 2) to discussion of issues involved. However, overall, it is very unlikely that any other, equally reasonable, assumptions would change the general conclusions of our report. In fact, most of the points raised by Mr Williams will lead to a more positive, rather than more negative, conclusion on the net contribution of immigrants.

For instance, Nigel Williams argues that the cost of interest on public sector debt should accrue only to natives, and not to immigrants, since it is natives who accumulated the debt. This means that – if anything - we are over-estimating the fiscal cost of immigration. Similarly, he argues that ”apportioning the cost of immigration and citizenship police services (as we do in our main scenario)  entirely to immigrants is debatable.” We agree, but nevertheless we chose this option in our analysis because it provides a “worst case scenario” from the immigrants’ point of view. Assigning the cost of interest on public sector debt only to natives, as suggested by Mr Williams, would decrease the estimated fiscal cost of immigrants and correspondingly increase the fiscal cost of natives.

Therefore, again, we appreciate the comments by this author and the interest he took in our study. Although we agree on a number of issues brought up, we also do not believe that any of the points raised would change our main conclusions.

Thus, we were surprised by the mismatch between the content of the reports and the aggressively condescending tone of Civitas’ press release [http://www.civitas.org.uk/press/PRimmigration.html].

In this context, we would like to raise two points.

First, in the two reports there seems to be the suggestion that we should better not have done any analysis at all, as the data is not “perfect” and there is some remaining uncertainty in our findings. We totally disagree with this view. No analysis based on data will ever lead to results that are absolutely free of “uncertainty”, and no data is ever “perfect”. We have followed good academic practice and set out clearly the assumptions we have made in this piece, as has been acknowledged by Prof. Stone. We have (in earlier replies to comments [http://www.cream-migration.org/commentsarticle.php?blog=2]) computed some extreme scenarios and we have shown that even that would not have changed our main conclusions. Thus, different assumptions may lead to slightly higher or slightly lower net contributions of immigrants, but they will not change the general conclusions of the study – namely that EEA immigrants who arrived after 1999 have made a substantial net fiscal contribution to the UK. We believe that – in a climate where anecdotal evidence rather than well researched data work dominate the public and policy debate – this is an important piece of information that the public ought to know.

Second, both pieces mention the 2003 report on the likely inflow of immigrants from the A8 countries to the UK [http://www.ucl.ac.uk/~uctpb21/reports/HomeOffice25_03.pdf] that Christian Dustmann co-authored. This report has nothing to do with our latest piece, but their criticism is eagerly taken up by Civitas director David Green to insult us and our reputation. Christian Dustmann and Ian Preston have responded to the ill-informed criticisms of that report in a separate piece [http://www.cream-migration.org/commentsarticle.php?blog=1].

In conclusion, we welcome constructive comments on our analysis. We are pleased that our report is so thoroughly publicly scrutinised, and we believe that this interchange will help improve the way we inform the public debate on this important and sensitive issue. However, we reject the offensive tones used by Civitas’ press release, and we believe that if accusing someone of "schoolboy errors", as done by Civitas’ director David Green, you ought to be able to point to more actual errors.

Appendix
Mervyn Stone, “Plain Assumptions and Unexplained Wizardy Called in Aid of “The Fiscal Effects of Immigration to the UK”

The piece has two parts.

In part one (“The Cream fiscal effect calculation”), Prof. Stone discusses our fiscal effect calculations. It remains unclear to us what the point of this section is – Stone’s report simply repeats our calculations and lists numbers in slightly different ways in his first two tables.

Part two (“The econometrics that Cream calls on to estimate putative ‘probability gaps’) refers to Table 3 in our paper where we fit linear probability models  to investigate the probability of welfare receipt of different immigrant populations, as compared to native born individuals. The main observations of Prof. Stone refer to two issues, the fit of our estimated model, and the model specification.
  1. The fit of the model, as measured by the coefficient of determination (R2). R2 is a statistics that measures how much of the variation in the outcome variable that is explained by the independent variables is included in the model. It is a useful statistic if we would want to use our model for predictions. However, our analysis is aimed at estimating the difference in the probability of welfare receipt between two groups of individuals, immigrants and natives. In the simplest case (if we were interested in the unconditional difference, and the data was for one cross section only), this difference in probabilities would simply be the difference in the mean of the share of immigrants and the share of natives who receive welfare. No statistical measure of fit is needed to understand this difference, obviously. Further, this difference in the proportion of immigrants and natives’ welfare receipt would be estimated more precisely the more data points are available, as this adds information, and would thus reduce sampling error and increase statistical significance (see his point (iii) (a) on page 13). When we condition on observables, what matters is not R2 per se, but how different characteristics may affect benefit take-up and whether these characteristics are correlated with immigrant status.
  2. The specification of the model. (i) Choice of estimator: We estimate a simple linear probability model, which is easy to interpret. The method essentially fits cell probabilities (see above example), especially when all regressors are binary and mutually orthogonal (in which case probit models and LPM produce exactly the same cell probabilities). When we condition on observables, there may be some extrapolation because of functional form assumptions. However, re-estimating our specification using a probit estimator results in very similar conclusions (we are happy to provide the estimates). (ii) Specification: Our data covers many periods (quarters), and we are interested in a summary measure of the differences in welfare receipt between immigrants and natives. The specification we have chosen conditions on a set of time dummies (to allow for variation in welfare receipt over time that affects immigrants and natives alike), but does not allow for interactions between quarters and immigrant status in addition. As Prof Stone points out himself, our coefficient estimate is therefore interpretable as the weighted combination of the differences between welfare receipt between immigrants and natives across all quarters, which is precisely the coefficient we wish to estimate, as it has a meaningful and simple interpretation in this context. It is therefore a representation of the “weighted averaged” difference in welfare receipt between immigrants and natives over all quarters observed, conditioning on fluctuations in welfare receipt over time that affect immigrants and natives alike. We do agree however that the formulation “… difference in the probability of receiving benefits or living in social housing between immigrants and natives observed at the same moment in time” is imprecise, as Prof Stone points out – what we should have said is “…the weighted averaged difference across quarters in the probability of receiving benefits or living in social housing between immigrants and natives, conditioning on fluctuations in welfare receipt over time that affect immigrants and natives alike.” Thanks for pointing this out to us. (iii) Conditional models: To capture differences between immigrants and natives in demographic characteristics, we condition on gender and a quadratic in age. Again, this is a standard procedure. Of course, it implies an assumption about functional form – which we believe is not implausible but at the same time simple and transparent. One could relax functional form assumptions by including a full set of dummy variables for age, and interact them with gender dummies, or use matching type estimators. Using such estimators, results show an even larger difference in welfare and transfer receipt between immigrants and natives than reported in our Table 3. For instance the gap resulting from a fully interacted model specification is  -0.125 for immigrants arriving since 2000, compared to the estimates of  our more restricted specification reported in the Table, which gives an estimate of -0.084.
  3. Robust standard errors: This is standard jargon in econometrics for the Huber and White estimator of the variance (see White, 1980 and MacKinnon and White, 1985), an estimator that corrects for the heteroscedasticity  implied by the linear probability model. It is a textbook-like correction to make when calculating standard errors in this context (see e.g. Wooldridge (2001), page 454).

References
MacKinnon, J. G., and H. White (1985), “Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties.” Journal of Econometrics, 29, 305–325.

White, H. (1980), “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct
Test for Heteroskedasticity,” Econometrica, 48, 817–838.

Wooldridge, J.M. (2001), “Econometric Analysis of Cross Section and Panel Data”, 1st edition, MIT Press.

Thursday, 16 January 2014

How Early Estimates for Migration Flows after EU Enlargement in 2004 are Misinterpreted

by Christian Dustmann and Ian Preston

Department of Economics and Centre for Research of Analysis and Migration (CReAM) at University College London

Introduction and Summary

It has become part of recent conventional political wisdom that immigration to the UK from the eight countries acceding to the EU in May 2004 (A8 countries) was dramatically underestimated.  Certain characterisations of the extent of this underestimation are very large.  For example, then Conservative shadow minister,  Lord Howell of Guildford, described predictions in 2005 as being "Laughably, ... out by about 2,200%” [http://www.publications.parliament.uk/pa/ld200506/ldhansrd/vo051220/text/51220-20.htm] whereas then Liberal Democrat spokesman, Chris Huhne, claimed in 2008 that the "breathtaking" scale of the misprediction was 1,373% [http://www.publications.parliament.uk/pa/cm200708/cmhansrd/cm080424/debtext/80424-0016.htm]. More recently, Jack Straw, Foreign Secretary at the time of accession, has said that “The predictions were completely catastrophic. I mean they were wrong by a factor of 10,” and offered a number for annual net migration of “something like 130,000” [http://www.bbc.co.uk/programmes/b03phwk5].  Outside of party politics, a recent report by Civitas [http://www.civitas.org.uk/press/PRimmigration.html], for example, draws attention to the supposedly large deviation between forecast and outcome to cast doubt on other research.

By contrast, one of the authors of this note has claimed that the figures were “not very far off” [http://www.bbc.co.uk/news/uk-politics-21682810].  The discrepancy between such a judgment and some of the comments above may seem difficult to understand but becomes more intelligible if attention is paid to what the predictions were for and the policy regime to which they were meant to apply.  Poor understanding of the predictions and their policy context is unhelpful to a balanced debate on associated issues and this brief historical note is intended to clarify their basis.

There are three types of error. The first two are elementary definitional errors:
  • Some have confused annual figures with those which are cumulative over 9/10 years.
  • Some have confused gross numbers (i.e. those coming to the UK) with net numbers (i.e. the difference between those coming to the UK and those leaving the UK for elsewhere). 

The third type of error is to ignore the difference between the context to which the predictions were supposed to apply and the reality of the context in which actual post-accession flows occurred. The Home Office commissioned a report with forecasts for the case in which other EU member states, and particularly Germany, would also, like the UK, permit labour migration from the A8 countries.  In the event, all other EU member states except Ireland and Sweden put controls on labour migration in place.  No forecasts were commissioned or calculated for such a case.  Nonetheless the report recognises the importance of the issue and offers some speculative observations pointing out that migration to the UK would be substantially higher if other EU countries put controls in place.

Below we explain in more detail the common misinterpretations of the projections which together explain the extent to which the under-prediction is frequently exaggerated.

The 2003 Report and Subsequent Migration

The numbers usually quoted originate in a report [http://www.ucl.ac.uk/~uctpb21/reports/HomeOffice25_03.pdf] written at the Centre for Research and Analysis of Migration (CReAM) [http://www.cream-migration.org].  The report contained predictions for net migration inflows from A8 accession countries to both the UK and Germany under a variety of scenarios.  In particular, two scenarios presented for the UK gave predicted net inflows of 5,000 and 13,000 per year, averaged over a ten year period. The assumption underlying the central cases discussed was that other large countries in the EU (in particular Germany) would also open up their labour markets to A8 immigrants in May 2004. The report emphasised the weaknesses inherent in any attempt to predict immigration from A8 countries in the absence of historical migrations from these countries upon which predictions could be based. The forecasts were based on historic migration flows from other countries and the resulting numbers described as needing to be treated with “great caution” since the assumption of similarity between flows from these countries and A8 countries was highly unreliable.

Estimates from the Office of National Statistics suggest that the actual net inflow over the nine years from 2004-2012 was 423,000 (Office of National Statistics: “Migration Statistics Quarterly Report”, November 2013). This corresponds to an actual outturn of about 50,000 per year. Comparison between the 2001 Census and 2011 suggests that the rate of arrival may have been substantially higher (although such a comparison also covers year prior to the 2004 enlargement) [http://www.ons.gov.uk/ons/guide-method/method-quality/specific/population-and-migration/population-statistics-research-unit--psru-/methods-used-to-revise-the-national-population-estimates-for-mid-2002-to-mid-2010.pdf].

Errors in Comparison

The following are the most common errors in drawing comparisons involving these and other figures.

Firstly, there are errors in interpreting what the forecasts were for. Some commentators seem not to distinguish between a predicted annual rate of inflow averaged over ten years and inflows for particular years or, worse, the cumulated flow of immigrants over many years.  This can lead to particularly lurid comparisons.

Secondly, another error is to fail to distinguish between net and gross migration flows. Gross migration is the total number of individuals entering the country. Net migration is the difference between the number entering and the number leaving. Return migration by earlier immigrants can mean that the numbers differ substantially. The numbers in the report referred to net migration flows.  In the case of migration from A8 countries, gross migration between 2004 and 2011 has been estimated as 713,000 (Office of National Statistics: “Migration Statistics Quarterly Report”, November 2013), or about 80,000 individuals per year, a number higher by about two thirds than net migration.  Again, failing to make this distinction tends to an exaggeration of the underprediction.

Finally, a different sort of error is to fail to appreciate the difference between the policy context of the estimates in the report and that of the final outcomes.  The report was prepared in early 2003 and its forecasts assume that labour markets of other European countries would also be open: as noted, migration flows to these other European countries were discussed in the report, and estimates for one of them, specifically Germany, also calculated.  The report draws attention to possible sensitivity to adoption of transitional arrangements restricting access to labour markets in those other countries. The estimated average net yearly inflows to Germany (geographically and, arguably, culturally closer to the A8 countries than the UK) under various scenarios were between 20,000 and 210,000.  In the event that Germany should impose a transitional arrangement closing its labour market, the report suggested that up to a third of these might come to the UK instead (and others to other closer countries) – although this was a speculative observation rather than an estimate, this is compatible with an additional flow diverted from Germany alone of anywhere between 7,000 and 70,000.  In fact, not only did Germany impose the longest legally possible transitional restrictions but the UK was alone with Sweden and Ireland in allowing immediate access.  Allowing for diverted migration flows not only from Germany but also from other countries which closed their labour markets, the range of possible inflows suggested in the report comes to encompass values of the order of magnitude that actually arose.  Institutional arrangements under which A8 migrants have equal access to the labour markets of all EU partners have in fact held only since 2011.

Conclusion

The frequent suggestion that the forecasts were misleading by orders of magnitude is not supported by close reading of the report, which is explicit on

  • providing numbers on average annual net inflows covering a period of ten years, rather than cumulated (gross) inflows of immigrants over several years
  • providing numbers applicable to a policy regime in which other large EU countries open their labour markets alongside the UK – a regime that did not materialise 

The range of tentative suggestions the report provides on possible annual net migration inflows if Germany – the largest potential immigration country for A8 immigrants – should not allow for free movement of labour includes numbers comparable with the actual annual net immigration from A8 countries based on ONS figures for the period 2004 to 2012.

References:

Dustmann, C., Casanova, M., Fertig, M., Preston, I. and Schmidt, C.M. (2003) The impact of EU enlargement on migration flows. (Home Office Online Report 25/03 ).

Office of National Statistics: “Migration Statistics Quarterly Report”, November 2013

Tuesday, 26 November 2013

Further Response to Comments on “The Fiscal Impact of Immigration on the UK”

by Christian Dustmann and Tommaso Frattini

Centre for Research and Analysis of Migration (CReAM) at University College London

Our paper “The Fiscal Impact of Immigration on the UK” [http://www.cream-migration.org/publ_uploads/CDP_22_13.pdf] has continued to be the object of lively debate.  We intend here to address certain criticisms and explore further issues. In particular, among the points that have been raised, there has been criticism of the way we deal with the allocation of corporate tax revenues and of business rates. We have responded to these criticisms before [http://creamcomments.blogspot.co.uk/2013/11/nothing-is-hidden-in-our-report-on.html]. 

In a recent piece [http://strongerinnumbers.com/komposersitelocal/CReAMresponse1.pdf], Michael O’Connor argues again that our way of allocating corporate tax revenues between UK natives and different immigrant groups would over-estimate the likely payments of recent immigrants for two reasons:
  1. “As it treats even a recent immigrant as having the same investment in UK companies as soon as they arrive as a lifelong resident does”.
  2. As “the same fiscal contribution will be attributed to any partner accompanying the migrating worker and also to any child they might have”, so that the “fiscal contribution [of immigrants] through corporate taxes will be deemed to increase with every new migrant and new child born”.
We welcome all suggestions for improving our estimates, and indeed we acknowledge that point 1 deserves consideration. However, point 2 incorrectly overstates his case, as we allocate revenues of corporation taxes (and of capital gains tax) – after taking out the share which is paid by overseas shareholders – on a per capita basis among the adult (18+) population only (we explain this in Table A2 [http://www.cream-migration.org/publ_uploads/CDP_22_13.pdf]). Therefore it is not the case that the estimated amount of corporation taxes paid by immigrants is “deemed to increase with every new child born”.

As regards point 1, we believe that in the absence of better approximations, a per capita allocation among the adult population is a reasonable criterion. However, we could also take the comment to its extreme consequence, and assume that immigrants arrived since 2000 do not contribute at all to corporate and capital gains tax revenues in any year. This is obviously an extreme assumption, and one which will considerably under-estimate the tax payments of immigrants. Nevertheless, it will clearly establish a lowest bound estimate for the tax contributions immigrants make. We show what effect this would have below.

In a previous comment [http://strongerinnumbers.com/cream3.html], Michael O’Connor also suggests that our imputation of business rates revenues based on share of self-employment might misleadingly over-estimate the tax payments of recent immigrants. We have already responded to that criticism, which we think is unfounded [http://creamcomments.blogspot.co.uk/2013/11/nothing-is-hidden-in-our-report-on.html]. Here we should reiterate that allocating business rates according to self-employment shares – as we do – does not mean that we are assuming that only the self-employed pay them. It just means that we believe a reasonable proxy for the distribution of business rates revenues might be the self-employment density among immigrants and natives. 

The allocation of corporate taxation and business rates raises complicated questions of incidence.  The fact that businesses write the cheques does not mean that the burdens do not fall ultimately on people. Whether those people are customers, shareholders, property owners or whoever, depends upon how economic decisions and, as a consequence, prices respond to taxation and is not a straightforward question. 

However, again, an extreme scenario would be one where immigrants who have arrived since 2000 do not pay any business rates.

We have re-estimated our models to obtain the net fiscal contribution of immigrants and natives for these extreme scenarios. Remember that corporate and capital gains tax amount to more than 9% of total government revenues, and business rates to more than 4% of total government revenues (see Table A2 in our paper [http://www.cream-migration.org/publ_uploads/CDP_22_13.pdf]), so we are assuming that more than 13% of total revenues are only attributable to natives and immigrants who were in the UK before 2000.

The next table compares our original results with the results that we obtain under these extreme assumptions.
Years 2001-2011
Original calculations in our paper
Natives

EEA

Non EEA

Recent EEA

Recent Non EEA
 Overall net fiscal contributions (million, 2011 GBP equivalent),  2001-2011
-624,120
8,978
-86,820
22,106
2,942
 Ratio of real revenues to real expenditures, 2001-2011
0.894
1.045
0.851
1.339
1.019
Assuming no corporation tax, capital gains tax, or business rates paid by recent immigrants
 Overall net fiscal contributions (million, 2011 GBP equivalent) , 2001-2011
-601,175
2,199
-96,772
13,422
-9,921
 Ratio of real revenues to real expenditures, 2001-2011
0.898
1.011
0.834
1.206
0.937

As the entries in the table clearly show, even under this scenario, recent EEA immigrants still make a substantial positive net fiscal contribution over the period 2001-2011. The numbers in the Table show that they would have paid 21% more in taxes than they received in transfers and benefits. Moreover, even though the net fiscal contribution of recent non-EEA immigrants is now negative (although less negative than that of natives, despite the fact that we allocate the revenues from corporate and capital gains tax and business rates to natives), the overall contributions of all immigrants who arrived since 2000 still remains  positive.1

More generally, and as we have already mentioned in our first response, we believe we have taken an approach that tends to understate overall immigrants’ fiscal contributions, for different reasons. In our calculations we always consider second generation immigrant children (i.e. the UK-born children of foreign-born parents) until age 15 as immigrants, but (due to a lack of information in the LFS that allows us to identify individuals born to immigrants once they have left the parental household) we consider them as natives when they are adults (we explain that and discuss the consequences of this assumption in section 2.1.1 in our paper).  In this way, we understate immigrant contributions from a dynamic angle. One can see this from two perspectives. Looking at it one way, we consider the cost of educating the children of immigrants, but we do not correspondingly consider the savings the UK makes by not bearing the cost of educating adult and highly educated migrants. Alternatively, looking at it in another way, we consider the cost of educating UK-born children of immigrants as a cost of immigration, but when these children grow up, work and pay taxes we allocate their revenues to the native population.

An alternative approach, that would perhaps get closer to capturing the dynamic fiscal effects of immigration, would be to not consider the costs of educating the UK-born children of immigrants. If we do so, the estimated net fiscal contributions of immigrants obviously increase, especially for those groups who have more children. In this case, and maintaining the extreme assumption of no corporate and capital gains tax and no business rates paid by recent immigrants, the ratio of revenues to expenditures would be 1.23 for recent EEA immigrants and 0.98 for recent non-EEA immigrants (while still 0.9 for natives). 

                                    
1 There was also a slight misunderstanding of our Table 1 in Michael O’Connor’s piece. To reconstruct the size of the total population from our Table 1, one should just sum over columns 1-2-3, and not over all columns, as columns 4 and 5 are just subsamples of columns 2 and 3, respectively. 

Thursday, 7 November 2013

Nothing is ‘hidden’ in our report on the fiscal effects of recent UK immigration


by Christian Dustmann, Tommaso Frattini


Two pieces on the Telegraph blog criticise our recent report on the fiscal impact of immigration to the UK [http://www.cream-migration.org/publ_uploads/CDP_22_13.pdf].

The first by Tim Wigmore [http://blogs.telegraph.co.uk/news/timwigmore/100244413/the-immigration-debate-everyone-ignores-the-inconvenient-facts/ ] suggests HhEHthat the press release summarising our report only highlights the positive effect of recent immigration to the public purse, while ‘hiding’ the fiscal cost represented by earlier non-European immigrants. He says that it is not ‘OK for a report to whitewash out inconvenient facts’.

In the report, we compute the fiscal net contribution for two immigrant populations: first, all those who arrived after 1999; and second, all those immigrants who lived in the UK between 1995 and 2011, whenever they arrived. In both cases, we distinguish between immigrants from the European Economic Area (EEA) and non-EEA immigrants. The press release focuses on the first population because recent debate has been about the fiscal impact of immigrants who arrived over the last decade, many of them from Eastern Europe [http://www.cream-migration.org/files/Press_release_fiscal_costs_benefits.pdf]. But the paper also reports results for all immigrants who reside in the UK in each year between 1995 and 2011.

As to Mr Wigmore’s criticism, we first note that if we had wanted to ‘hide’ numbers relating to all immigrants who resided in the UK between 1995 and 2011, we would not have put them in the report in the first place. We could easily have written a report that dealt exclusively with recent immigrants. And these numbers are not ‘hidden away’ in the report – in fact, they are not only shown in the Table 5 Mr Wigmore refers to, but also, and broken down by years, in Table 4a and in Figures 1a and 1b, which features on the BBC website [http://www.bbc.co.uk/news/uk-24813467] for everybody to see.

As for the findings for the non-EEA immigrants who resided in the UK between 1995 and 2011, the fact that their average contribution is negative just means that they are similar to the native British-born. This is as much a reflection of the fact that the exercise is being conducted for a period of overall budget deficit, when the average contribution must be negative, as it is of anything distinctive about their fiscal contribution. The fact on which we focused is the noteworthy one that a particular group of immigrants (EEA-immigrants) are net contributors even when there is an overall deficit.

Further, the deficit that we attribute to older non-EEA immigrants is likely to be significantly overstated because we are taking a very cautious approach. This group has large numbers of UK-born second generation children and the cost of educating them is counted as a cost associated with the ‘Immigrant’ group even though, for data reasons, we cannot include grown children’s tax payments as benefits to set against that. Thus, this contributes to understating immigrant contributions. 

The piece by Douglas Carswell MP [http://blogs.telegraph.co.uk/news/douglascarswellmp/100244371/why-the-experts-are-wrong-about-immigration/] raises a number of methodological points relating to our study and suggests that some points are intentionally not made clear. He then challenges some of our conclusions.

We first note that – precisely because we very clearly lay out how every single number is constructed, as is good academic practice – Mr Carswell is actually able to try to ‘deconstruct what the experts say’. Precisely because we do not want people to believe experts' opinions as if they were true by definition, we have clearly detailed how we have apportioned each item of government receipt and expenditure.

Our study uses the best data available to reach conclusions on the fiscal impact of recent immigration. But even those data are not perfect, and as in every such analysis, some assumptions have to be made when using them to compute the fiscal net contribution of population groups. 

As to the first point Mr Carswell raises, that we are misallocating business rates as we allocate their revenue based on self-employment shares: this method is well-established in the research literature predating our work; it is not an unreasonable criterion to use; and any other criterion would be more arbitrary. In any case, business rates account for about 4% of total revenues, so changes in the apportioning coefficient will certainly not ‘massively distort the balance sheet’ as Mr Carswell claims. 

As regards Mr Carswell’s other points: the allocation of company and capital taxes accounts for the fact that a substantial fraction of UK companies is owned by non-resident shareholders. After removing their estimated payments, we allocate the remaining revenues on a per capita basis to the resident population. We clearly explain the assumption that we are making in choosing our apportioning criterion. Again, we do not believe other assumptions are more justified or better grounded.

We use data from the UK Labour Force Survey (LFS) in our study. This is a large representative survey of the UK population, which provides the most comprehensive data available and over a long period of time. The DWP data to which Mr Carswell refers are not as complete (they start in 2002), and using them to study the welfare take-up of immigrants requires a number of (potentially questionable) assumptions, as the author of that report correctly points out, since immigrant status is not recorded. Moreover, the report to which Mr Carswell refers [http://www.strongerinnumbers.com/komposersitelocal/NonUKreportfinal.pdf] does not distinguish between different groups of immigrants, as we do. 

Further, Mr Carswell’s claim (in point 4) that we mix together all benefits in our analysis of the fiscal contribution is simply untrue. In fact, we know from the LFS who is receiving what type of benefit, and we use that information to allocate the cost of each benefit (as we detail in Table A1). 

Finally, on Mr Carswell’s point 5, although it may be true that different immigrant groups have different claiming patterns, this is not at all a concern for our analysis, as we are looking at broad groups of individuals, and we effectively consider average behaviour across national groups, within the groups we define (EEA and non-EEA). Thus, even if we would distinguish between immigrants from Poland, Estonia, etc. when assigning benefit receipts, by aggregating them up to larger groups, this distinction would be averaged away. Therefore, Mr Carswell’s claim that this aspect of our methodology ‘undermine(s) the claim that European Economic Area migrants contribute 34 percent more in taxes than they receive in benefits’ is simply incorrect.

Although both of these pieces base their critiques on the suggestion that there are things hidden in the report, the ease with which each has identified the facts which have interested them shows that our report is on the contrary unusually open about how its figures are arrived at. And contrary to the impression that might be given by these two pieces, we have at all points leaned towards conclusions that understate immigrants’ contributions. We disagree with some of the interpretations on which these critiques are based, but welcome any fair-minded discussion of the reasonableness of the procedures we adopt.