Informal employment from migration shocks
Timm Gries and
Working Papers from Faculty of Economics and Statistics, Universität Innsbruck
We propose a new approach to detect and quantify informal employment resulting from irregular migration shocks. Focusing on a largely informal sector, agriculture, and on the exogenous variation from the Arab Spring wave on southern Italian coasts, we use machine-learning techniques to document abnormal increases in reported (vs. predicted) labor productivity on vineyards hit by the shock. Misreporting is largely heterogeneous across farms depending e.g. on size and grape quality. The shock resulted in a 6% increase in informal employment, equivalent to one undeclared worker for every three farms on average and 23,000 workers in total over 2011-2012. Misreporting causes significant increases in farm profits through lower labor costs, while having no impact on grape sales, prices, or wages of formal workers.
Keywords: Informal employment; Migration shocks; Farm labor; Machine learning (search for similar items in EconPapers)
JEL-codes: C53 F22 J43 J46 J61 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big, nep-cmp, nep-dev, nep-iue, nep-lab, nep-mig and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:inn:wpaper:2023-09
Access Statistics for this paper
More papers in Working Papers from Faculty of Economics and Statistics, Universität Innsbruck Contact information at EDIRC.
Bibliographic data for series maintained by Janette Walde ().