Native-migrant labour substitution by industry and wage effects: evidence from the UK

ABSTRACT

Unlike previous studies, we estimate the native-migrant substitution elasticity (NME) differentiated by sector. To do so, we employ a straightforward estimation strategy that consists of adding slope-shifters to the reduced form of the labour demand equation to allow for sectoral differentiation and adjusting the restrictions on the efficiency parameters consequently. Our study contributes to the literature in three ways. First, this is the first example that estimates NME differentiated by industry. Second, previous studies assessed the effect of the past migration on wages. In contrast, we assess the impact of potential restrictions to unskilled EU labour in the UK and this can useful to design future immigration policies in the country. Third, our results contribute to understand the dynamics between migration and the domestic labour market in the UK and provide a lesson for other developed economies.

KEYWORDS:

• Immigration
• industry
• wage
• Brexit

JEL CLASSIFICATION:

• F22
• J31
• L52

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ NME indicates how close natives and migrants are in the production process: when there are no differences, they are perfect substitutes and wage differentials are zero.

² New Member States: Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, and Slovenia (Migration Advisory Committee 2018b).

³ In this study, the parameters of technical efficiency of working experience and education are assumed to be time invariant. This assumption has been made in similar studies that analysed the UK case (Manacorda, Manning, and Wadsworth 2012). Moreover, in our study we consider a short and recent period and it is reasonable to assume that there were no huge changes of working experience-education technical efficiency. Thus, the additional terms D2_t and D2_et were included to control for the trend in output and education supply.

⁴ Clustering at education, working experience, and sector level controls for serial correlation only over time and it produces smaller standard errors than the employed clustering.

⁵ Apart from UK and ROI, the Common Travel Area includes the Channel Islands and the Island of Man.

⁶ The EEA includes the EU member states, the European Free Trade Association States (EFTA) and Switzerland. The EFTA includes Iceland, Liechtenstein, and Norway (European Economic Area 2018).

⁷ Where the survey weights were employed, we used the cross-sectional adult main weights wave_indinui_xw in the dataset to calculate the average wages and a number of workers at the cell level. (University of Essex 2017).

⁸ In the UK labour market, immigrant workers from EEA countries, as regulated in the Citizen’s Rights Directive (Directive 2004/38/EC) have the right to the free movement; thus they are not subject to the UK immigration policy, while those from the rest of the world are ‘managed migration’ which are subject to constraints of holding a valid worker permit and entry visa (UK Government 2018b).

⁹ Most of the wage gap is due to the workers located in London. Once we recalculate it without London, the wage differential is 0.94. Second, the wage differential in favour of migrant workers in highly skilled occupations is not limited to UK. For instance, in Switzerland, a country heavily reliant on the Finance & Insurance sector, the wage gap is in favour of the native workers at the aggregate level, but the opposite is true as we move up the managerial hierarchy (Federla Statistical Office 2018).

¹⁰ The sensitivity analysis of the education elasticity does not show the results of 2 Education Groups model (Secondary & College) because this specification has more parameters than observations in the 2SLS.

¹¹ Under the existing Tier 2 scheme, i. e. the labour VISA that is currently applied to non-EEA migrants, were extended to all migrants, 83% of the current EEA employees would not be eligible (Office for Budget Responsability 2018).

¹² The industries most distant from the plotted line are characterized by a substantial presence of the public employment (Public Administration, Education, and Health) where wages can be sticky (Afonso and Gomes 2014).

Additional information

Funding

This work was supported by the Department of Agriculture, Environment and Rural Affairs Northern Ireland [E-I 2017-18 17/2/S1].