We are delighted to announce Ben Brindle as one of our #DataImpactFellows for 2019.
Ben Brindle is in the first year of his economics PhD at the University of Brighton’s Business School. His research, which is funded by the ESRC’s South Coast DTP, examines how the labour market responds to immigration-induced supply shocks; through either technology mix changes, where firms alter their production techniques or output mix changes, where firms that use the abundant labour type intensively grow in size. To do this, he uses the Quarterly Labour Force Survey and the Annual Respondent’s Database.
Ben’s research examines how immigration has impacted the UK labour market since 1998. Given that the current immigration debate, both in the UK and beyond, is characterised by misinformation, Ben’s hope is that he can provide clarity as to how the labour market responds to immigration-induced supply shocks. This, however, requires that his results – and those produced by other researchers – are heard by policy makers and, crucially, the general public. Ben’s aim is to bridge this divide by engaging with these groups.
Ben holds an MSc in Social Research Methods from the University of Southampton, an interdisciplinary masters that equipped him with an in-depth knowledge of both the myriad research methodologies at his disposal, and an understanding of when their usage is most appropriate. Prior to this, Ben completed a BSc in Business Management with Economics at the University of Brighton, where he was the best performing final year on the Business Management pathway.
Alongside Ben’s studies he teach seminars in a variety of economics modules at the University of Brighton, where he focuses on the role that economic theory, and economic data, can play in producing new knowledge and insights that leads to positive change in our daily lives. He is also a co-editor of the South Coast DTP academic blog, and has previously written for the Business and Daily Registers and Letters sections of The Times.
Ben’s research
Over the past two decades, immigration to the UK has reached unprecedented levels, rising from 48,000 in 1997 to 283,000 in 2018 (although peaking at 332,000 in 2015), while wage growth has stagnated since the financial crisis. Indeed, according to the IFS median annual wages were £760 (or 3.2%) lower in 2017 than they were in 2008.
As a result, many UK-born individuals – or natives – have voiced concerns that the two phenomena are related, with these concerns driving both the public’s strong opposition to immigration, and the consistent identification of the topic as one of the most salient issues facing the UK. This opposition and perceived importance has, in turn, led to large shifts in the political landscape, including:
- the Conservative Party pledge to reduce net migration to “the tens of thousands”;
- the rise of the UK Independence Party earlier in the decade;
- the decision to leave the European Union in 2016;
- and, crucially, the preference to have “greater control” over immigration following the UK’s exit from the bloc.
In light of these far-reaching social and economic changes, my PhD investigates how the UK labour market has adjusted to labour supply shocks induced by immigration between 1998 and 2018. To do this I conduct three pieces of original research.
My first paper employs the empirical strategy first utilised by Dustmann et al. (2013) in order to ascertain how immigration has impacted wages at different points along the wage distribution. In the paper, I will extend the original study – which found that immigration depresses wages in the lower part of the wage distribution but raises wages in the upper part – in two ways. First, I will produce separate results for individuals working in tradable and nontradable sectors, with less adverse effects anticipated in the former sector owing to the other adjustments than can take place (outlined below). Second, using statistics produced by Goodwin and Health (2016) in their analysis of the drivers behind the UK’s decision to leave the European Union, I will identify whether the wages of those individuals who are probabilistically likely to have voted “Remain” were affected by immigration differently to the wages of those individuals who are probabilistically likely to have voted “Leave”.
In light of the fact that the majority of UK literature fails to find any evidence that immigration adversely impacts natives’ wages, my second paper identifies whether the labour market instead absorbs arriving immigrants through other means; notably through changes in the technology mix, where firms increase the intensity with which they use the labour type (skilled or unskilled) made abundant by immigration in production, or through changes in the output mix, where industries that use the abundant labour type intensively increase their scale of production. The latter mechanism only occurs in those industries which produce output that can be traded (manufacturing, for example).
Both mechanisms offset any negative wage impacts as they increase the demand for labour and thus reduce the effective increase in labour supply caused by immigration. While there is little evidence that output mix changes occur, evidence which indicates that immigration induces technology mix changes has been found in Israel, Germany, Spain, and the US. To date no study has examined whether these alternative adjustment mechanisms occur in the UK.
Given the tendency of workplace technology (such as computers, for example) to complement skilled labour but substitute for their unskilled counterparts, my third paper builds upon the second paper and asks whether immigrant inflows that increase the ratio of unskilled to skilled labour lead to a fall in the capital intensity of production. If the skill mix does in fact influence firms’ use of technology, as is indicated by the results obtained by Lewis (2011) and Lafortune et al. (2015) for the US, this would not only provide insight as to how immigrant supply shocks are absorbed by labour markets, but also as to the extent to which new technology is adopted by firms, and the speed at which this adoption takes place. Further, it may also shed light on the impact that immigration has on productivity and, in turn, potential solutions to the UK’s productivity puzzle.
The empirical approach is broadly similar for each of my three papers; the aim is to obtain the missing counterfactual – the change in the labour market outcome that would have ensued had no immigration taken place – and compare this to the change in the labour market outcome that was observed in reality. To do this I will use the spatial correlation approach, a technique which exploits the geographical variation in immigrant concentrations by dividing the labour market into regions and regressing the change in a regional labour market outcome against the immigration-induced supply shock in the respective region.
One issue concerns causality: as immigrants are free to choose where they settle, they may be attracted to those regions enjoying positive economic shocks, thus positively biasing the results. Therefore, I am required to use as a proxy for immigration something related to inflows of immigrants but unrelated to current economic shocks. Given the tendency of immigrants to move into enclaves established by earlier immigrant cohorts of the same origin or ethnicity, an obvious choice are immigrant concentrations from some point prior to the period of study. The data for my instrument, as well as the characteristics of the labour market more broadly, comes from the Quarterly Labour Force Survey, while my capital intensity figures are sourced from the Annual Respondent’s Database X.
Ben’s plans
With the financial support provided by the UK Data Service Data Impact Fellows Programme, I plan to both attend and speak at academic conferences related to migration (domestic and international) as well as other research events, such as the ESRC’s Festival of Social Science.
Further, given the importance of communicating my research to policy makers, journalists, and the general public, I would also like to undertake media and public engagement training. Finally, I intend to communicate my research findings using the platform provided by the UK Data Service Data Impact Blog.
Follow Ben on Twitter: @bmbrindle