Abstract
The spatial distribution of self-employment in India: evidence from semiparametric geoadditive models, Regional Studies. The entrepreneurship literature has rarely considered spatial location as a micro-determinant of occupational choice. It has also ignored self-employment in developing countries. Using Bayesian semiparametric geoadditive techniques, this paper models spatial location as a micro-determinant of self-employment choice in India. The empirical results suggest the presence of spatial occupational neighbourhoods and a clear north–south divide in self-employment when the entire sample is considered; however, spatial variation in the non-agriculture sector disappears to a large extent when individual factors that influence self-employment choice are explicitly controlled. The results further suggest non-linear effects of age, education and wealth on self-employment.
| Original language | English |
|---|---|
| Pages (from-to) | 300-322 |
| Number of pages | 23 |
| Journal | Regional Studies |
| Volume | 49 |
| Issue number | 2 |
| Early online date | 24 Apr 2013 |
| DOIs | |
| Publication status | Published - 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
Keywords
- Bayesian semiparametric methods
- developing countries
- entrepreneurship
- geoadditive models
- self-employment
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