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100			_aFingleton, Bernard _956917
245			_aEstimating the local employment impacts of immigration: _bdynamic spatial panel model/
260			_bSage, _c2020.
300			_aVol 57, Issue 13, 2020 ( 2646–2662 p.).
520			_aThis paper highlights a number of important gaps in the UK evidence base on the employment impacts of immigration, namely: (1) the lack of research on the local impacts of immigration – existing studies only estimate the impact for the country as a whole; (2) the absence of long-term estimates – research has focused on relatively short time spans – there are no estimates of the impact over several decades, for example; (3) the tendency to ignore spatial dependence of employment which can bias the results and distort inference – there are no robust spatial econometric estimates we are aware of. We aim to address these shortcomings by creating a unique data set of linked Census geographies spanning five Censuses since 1971. These yield a large enough sample to estimate the local impacts of immigration using a novel spatial panel model which controls for endogenous selection effects arising from migrants being attracted to high-employment areas. We illustrate our approach with an application to London and find that no migrant group has a statistically significant long-term negative effect on employment. EU migrants, however, are found to have a significant positive impact, which may have important implications for the Brexit debate. Our approach opens up a new avenue of inquiry into subnational variations in the impacts of immigration on employment.
700			_aOlner, Daniel _956918
700			_aPryce, Gwilym _953957
773	0		_08843 _916581 _dLondon Sage Publications Ltd. 1964 _tUrban studies _x0042-0980
856			_uhttps://doi.org/10.1177/0042098019887916
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