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The effects of agglomeration on wages: evidence from the micro-level

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  • Bernard Fingleton

    (Department of Economics, University of Strathclyde)

  • Simonetta Longhi

    (Institute for Social and Economic Research (ISER), University of Essex.)

Abstract

This paper estimates individual wage equations in order to test two rival non-nested theories of economic agglomeration, namely New Economic Geography (NEG), as represented by the NEG wage equation and urban economic (UE) theory , in which wages relate to employment density. The paper makes an original contribution by evidently being the first empirical paper to examine the issue of agglomeration processes associated with contemporary theory working with micro-level data, highlighting the role of gender and other individual-level characteristics. For male respondents, there is no significant evidence that wage levels are an outcome of the mechanisms suggested by NEG or UE theory, but this is not the case for female respondents. We speculate on the reasons for the gender difference.

Suggested Citation

  • Bernard Fingleton & Simonetta Longhi, 2011. "The effects of agglomeration on wages: evidence from the micro-level," Working Papers 1124, University of Strathclyde Business School, Department of Economics.
    • Handle: RePEc:str:wpaper:1124
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    2. Guo, Yunxia & Yu, Mengyao & Xu, Mingchen & Tang, Ying & Huang, Jingran & Liu, Jia & Hao, Yu, 2023. "Productivity gains from green finance: A holistic and regional examination from China," Energy Economics, Elsevier, vol. 127(PA).
    3. Ana Maria Bonomi Barufi, 2014. "Regional labor markets in Brazil: the role of skills and agglomeration economies," Working Papers, Department of Economics 2014_18, University of São Paulo (FEA-USP).
    4. Fingleton, Bernard & Szumilo, Nikodem, 2019. "Simulating the impact of transport infrastructure investment on wages: A dynamic spatial panel model approach," Regional Science and Urban Economics, Elsevier, vol. 75(C), pages 148-164.
    5. Long Thanh Giang & Cuong Viet Nguyen & Tuyen Quang Tran & Vu Thieu, 2017. "Does Firm Agglomeration Matter to Labor and Education of Local Children? Evidence in Vietnam," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 10(4), pages 1015-1041, December.
    6. Barufi, Ana Maria, 2014. "Agglomeration Economies in the Brazilian Formal Labor Market," TD NEREUS 3-2014, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
    7. Qing Guo & Siyu Chen & Xiangquan Zeng, 2024. "Digital finance, Bargaining Power and Gender Wage Gap," Papers 2405.15486, arXiv.org.
    8. Juan Soto & Dusan Paredes, 2016. "Cities, Wages, And The Urban Hierarchy," Journal of Regional Science, Wiley Blackwell, vol. 56(4), pages 596-614, September.
    9. Hamann, Silke & Niebuhr, Annekatrin & Peters, Jan Cornelius, 2016. "Benefits of dense labour markets: Evidence from transitions to employment in Germany," Economics Working Papers 2016-07, Christian-Albrechts-University of Kiel, Department of Economics.
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    11. Carlos Carreira & Luís Lopes, 2020. "How are the potential gains from economic activity transmitted to the labour factor: more employment or more wages? Evidence from the Portuguese context," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(2), pages 319-348, April.
    12. Li, Yan & Chen, Zhenhua, 2023. "Does transportation infrastructure accelerate factor outflow from shrinking cities? An evidence from China," Transport Policy, Elsevier, vol. 134(C), pages 180-190.
    13. Bruna, Fernando, 2024. "Market Potential, panel data, and aggregate fluctuations: All that glitters is not gold," MPRA Paper 121949, University Library of Munich, Germany.
    14. Jiamin Liu & Xiaoyu Ma & Wenli Jia & Sisi Zhang, 2022. "Can New-Type Urbanization Construction Narrow the Urban–Rural Income Gap? Evidence from China," Sustainability, MDPI, vol. 14(22), pages 1-25, November.
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    More about this item

    Keywords

    urban economics; new economic geography; household panel data.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D1 - Microeconomics - - Household Behavior
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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