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Are There Urbanization Economies in a Post-Socialist City? Evidence from Ukrainian Firm-Level Data. Volodymyr Vakhitov Saint Petersburg October 11, 2012. Outline. Motivation Data description Model and Estimation Issues Preliminary results. Agglomeration in the Nutshell.
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Are There Urbanization Economies in a Post-Socialist City? Evidence from Ukrainian Firm-Level Data Volodymyr Vakhitov Saint Petersburg October 11, 2012
Outline • Motivation • Data description • Model and Estimation Issues • Preliminary results
Agglomeration in the Nutshell Common labor pool? Relationships between managers and/or owners? ? Common market?
Motivation: Objective • Agglomeration economies: • External (to the firm) economies ofscale • Localization: • Internal to the industry • Internal to the location • Urbanization: • External to the industry • Internal to the location
Motivation: Urbanization Economies • Urbanization economies: • external to the firm and the industry as a whole, internal to the location • Jacobs (1969): spillovers matter! • Innovations • Knowledge sharing • Borrowing and developing new product • [Schumpeterian] churning
Motivation: Important Issues • How to measure (Research Policy, 2009)? • Size (employment, # of plants) • Diversity (similarity and concentration indices) • Are measures comparable (robustness)? • Cluster boundaries (aggregation): • What is “the same location”? • What is “the same industry”?
Motivation: Post-Socialist City • Land “price” and previous allocation • “Lock-in effect” within city boundaries • Ownership issues • Outdated capital stock
Outline • Motivation • Data description • Model and Estimation Issues • Preliminary results
Data Description Registry: • “Official” data (National Statistics Office) • Panel (2001-2007), submitted by firms • Firm level (plant level on the way) • Excludes budgetary sector and banks
Data Description Ownership: • “Official” data (State Property Fund and FDI statements) • Panel (2001-2005), collected by SPF • Firm level only
Data Description: Raw Variables • Territory and industry codes • Output, employment, capital, materials • Ownership (private: domestic / foreign) • Output assortment • Innovation activity • FDI • Purchases from other sectors • Exports and imports
Data Description: Constructed Variables • Size: • Other employment in the city • ln(empl) = ln(# firm) + ln(empl/# firms) (Henderson, 2003) • Diversity: • Market: employment or firm count based HHI • Internal: output composition HHI • Share of imports in the inputs • Use of products from other sectors produced in the same city (!!!)
Outline • Motivation • Data description • Model and Estimation Issues • Preliminary results
Model • TFP Model (Rosenthal and Strange, 2004): • Econometric Specification (Henderson, 2003):
Estimation issues • One-stage and two-stage estimation • Restricted to manufacturing in cities • Area and industry-year fixed effects • Robust estimation • 2-stage: TFP by Olley-Pakes, then regress on agglomeration variables + controls
Outline • Motivation • Data description • Model and Estimation Issues • Preliminary results
“Urban depreciation” • Ratio: • Current value of all fixed assets in the city to • Historical value of all fixed assets in the city • Predicted effect: the higher, the better
Ownership variables • PO: privately owned • DO: private, majority domestic • FO: private, majority state • PO = FO + DO
Conclusions and implications • Urbanization economies seem to be present • More pronounced for firm counts based measures, than labor based • Urban capital depreciation matters • Ownership effect: foreign – private domestic – state.
Volodymyr Vakhitov Kyiv School of Economics : vakhitov@kse.org.ua