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Urban versus Rural Firms

Is there a Spatial Heterogeneity of Labour Demand

Bibliographic Data

ID4138856
AuthorsJean-Pierre Huiban (INRA ESR Dijon, BP87999 Dijon Cedex, France, corresponding author), Cecile Detang-Dessendre (0000-0002-4386-8710, INRA ESR Dijon, BP87999 Dijon Cedex, France, corresponding author), Francis Aubert (0000-0001-8298-3423, INRA ESR Dijon, BP87999 Dijon Cedex, France, corresponding author)
Year2004
Volume36
Issue11
Pages2033-2045
Publication date2004-11-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning A Economy and Space (JOURNAL)
Journal identifiersISSN: 0308-518X • E-ISSN: 1472-3409
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1068/a36207
OpenAlexW2049977652
LanguageEN
Citations received2
References cited12

This paper analyses the spatial heterogeneity of labour demand. Our main assumption is that for each location there is a combination of factors which is the most efficient, given the endowment of the location in terms of technology access and the relative cost of factors. We estimate our model using a panel of more than 1000 industrial firms over a six-year period. The contribution of skilled labour is emphasised in the firms located in urban areas, unskilled labour in rural firms, and capital in periurban units. The functional distribution of jobs also plays a discriminating role: direct production and similar functions seem to be more concentrated in periurban and rural areas, whereas tertiary functions are clearly assigned to urban units. We then make conclusions as to the existence of different technical paths of growth, with high productivity growth and a dramatic decline of demand for unskilled labour in urban areas, and the maintenance of a labour-intensive method of production in rural areas

Econometrics · Economic geography · Economic growth · Economics · Endowment · Geography · Labour economics · Microeconomics · Panel data · Productivity · Rural area · Supply and demand · Regional Economic and Spatial Analysis · Regional Economics and Spatial Analysis · Spatial and Panel Data Analysis

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Unique citing works2
Citations per year0,11
Citation span2008 - 2011 (4)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 2

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