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Productivity, Factor Accumulation and Social Networks: Theory and Evidence

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  • P. Dorian Owen
  • R. Quentin Grafton
  • Tom Kompas

Abstract

The paper analyses how barriers to communication across social groups affect economy-wide productivity and factor accumulation. Using a dynamic model of an economy that includes a reproducible capital stock (physical or human) and effective labour, social barriers to communication are shown to have a negative effect on total factor productivity (TFP), per capita consumption and the accumulation of reproducible capital. Propositions from the model are tested using cross-country data from over a 100 countries. The results obtained from OLS and instrumental variables estimation, and with an exhaustive set of robustness tests, support the hypothesis that social barriers to communication, as measured by linguistic diversity, reduce TFP. Some evidence is also found to support the idea that the effects of social barriers to communication may be mitigated by improvements in mass communications. In addition, changes in the stocks of human and physical capital are found to be negatively related to social barriers to communication, after controlling for the initial levels of income and human or physical capital. The theory and empirical results together help explain the persistence of cross-country differences in TFP and provide insights as to how economies may initiate productivity 'catch up'.

Suggested Citation

  • P. Dorian Owen & R. Quentin Grafton & Tom Kompas, 2004. "Productivity, Factor Accumulation and Social Networks: Theory and Evidence," Econometric Society 2004 Australasian Meetings 224, Econometric Society.
  • Handle: RePEc:ecm:ausm04:224
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    2. Kaasa, Anneli, 2016. "Culture, religion and productivity: Evidence from European regions," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 12(1), pages 1-18.
    3. Anneli Kaasa, 2016. "Culture, religion and productivity: Evidence from European regions," Business and Economic Horizons (BEH), Prague Development Center, vol. 12(1), pages 11-28, April.
    4. Jingfeng Yuan & Wen Yi & Mengyi Miao & Lei Zhang, 2018. "Evaluating the Impacts of Health, Social Network and Capital on Craft Efficiency and Productivity: A Case Study of Construction Workers in China," IJERPH, MDPI, vol. 15(2), pages 1-25, February.
    5. Anneli Kaasa, 2018. "Intangible factors and productivity: Evidence from Europe at the regional level," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(2), pages 300-325, April.

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    More about this item

    Keywords

    productivity; social networks; economic growth;
    All these keywords.

    JEL classification:

    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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