We develop a novel methodology for the proxy variable identification of firm productivity in the presence of productivity-modifying learning and spillovers, which facilitates a unified internally consistent analysis of the spillover effects among firms. Contrary to the popular two-step empirical approach, ours does not postulate contradictory assumptions about firm productivity across the estimation steps. Instead, we explicitly accommodate cross-sectional dependence in productivity induced by spillovers, which facilitates identification of both the productivity and spillover effects simultaneously. We apply our model to study cross-firm spillovers in China's electric machinery manufacturing, with a particular focus on productivity effects of inbound FDI.
机构:
KIEP, Yeongi, South Korea
Korea Inst Int Econ Policy, Int Macroecon & Finance Dept, Yeongi, South KoreaKIEP, Yeongi, South Korea
Han, Wontae
Wang, Jian
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机构:
CUHK Shenzhen, Shenzhen, Peoples R China
SFI, Shenzhen, Peoples R China
Chinese Univ Hong Kong Shenzhen, Sch Management & Econ, Shenzhen, Peoples R China
Shenzhen Finance Inst, Shenzhen, Peoples R ChinaKIEP, Yeongi, South Korea
Wang, Jian
Wang, Xiao
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机构:
USTC, Hefei, Peoples R China
Univ Sci & Technol China, Sch Management, Int Inst Finance, Hefei, Peoples R ChinaKIEP, Yeongi, South Korea
机构:
Univ Sheffield, Dept Econ, Sheffield, S Yorkshire, England
Natl Univ Ireland, JE Cairnes Sch Business & Econ, Galway, IrelandUniv Sheffield, Dept Econ, Sheffield, S Yorkshire, England