Being Self-Employee in Urban and Rural Areas: Data Sources and Methodological Approaches

Alessandro Muolo () and Luca Salvati ()
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Alessandro Muolo: Gran Sasso Science Institute
Luca Salvati: Sapienza University of Rome

Chapter Chapter 11 in Urban-Rural Labour Markets, 2026, pp 159-171 from Springer

Abstract: Abstract The present chapter illustrates an empirical study using official statistics and micro-data derived from sampling surveys for the years 2010, 2015, and 2021, aimed at identifying the main elements characteristic of self-employment, with a specific focus on the causal role of living in a rural area. In this exercise, we analyzed in detail the phenomenon of self-employment in various European countries, trying to understand how different socioeconomic and contextual variables influence the probability of becoming self-employed. In particular, we examined the differences between urban and rural areas, the impact of digitalization and remote work, and the role of public policies. To address the issue of reverse causality and provide more precise estimates, we used an Instrumental Variables (IV) regression approach corroborated with traditional econometric controls. After a brief description of empirical data, we presented the statistical-econometric strategy adopted in the exercise and aimed at investigating if, on average, rural areas present a higher probability of self-employment compared with urban areas in the same country.

Keywords: Official statistics; micro-data; indicators; endogeneity; regression (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:conchp:978-3-032-17592-2_11

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DOI: 10.1007/978-3-032-17592-2_11

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