Estimating the local employment impacts of immigration: A dynamic spatial panel model
| Autor: | Gwilym Pryce, Bernard Fingleton, Dan Olner |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
media_common.quotation_subject
05 social sciences Immigration 0211 other engineering and technologies 021107 urban & regional planning 02 engineering and technology Environmental Science (miscellaneous) Base (topology) Urban Studies 0502 economics and business Economics Economic geography 050207 economics media_common |
| Zdroj: | Urban Studies. 57:2646-2662 |
| ISSN: | 1360-063X 0042-0980 |
| Popis: | This 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. |
| Databáze: | OpenAIRE |
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