are there urbanization economies in a post-socialist city? evidence from ukrainian firm-level data...
TRANSCRIPT
Are There Urbanization Economies in a Post-Socialist City?
Evidence from Ukrainian Firm-Level Data
Volodymyr Vakhitov
Saint PetersburgOctober 11, 2012
2
Outline
• Motivation
• Data description
• Model and Estimation Issues
• Preliminary results
3
Agglomeration in the Nutshell
?
Common labor pool?
Relationships between managers and/or owners?
Common market?
4
Motivation: Objective
• Agglomeration economies:External (to the firm) economies of scale
• Localization:Internal to the industry Internal to the location
• Urbanization:External to the industry Internal to the location
5
Motivation: Urbanization Economies
• Urbanization economies: external to the firm and the industry as a
whole, internal to the location
• Jacobs (1969): spillovers matter!InnovationsKnowledge sharing Borrowing and developing new product[Schumpeterian] churning
6
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”?
7
Motivation: Post-Socialist City
• Land “price” and previous allocation
• “Lock-in effect” within city boundaries
• Ownership issues
• Outdated capital stock
8
Outline
• Motivation
• Data description
• Model and Estimation Issues
• Preliminary results
9
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
10
Data Description
Ownership:
• “Official” data (State Property Fund and FDI statements)
• Panel (2001-2005), collected by SPF
• Firm level only
11
Data: Sample Composition
Year Urban firms, Nonzero Output, K, L Manufacturing Sample*
Small Big Total
2001 111,587 14,736 126,323 21,346 19,385
2002 123,085 14,334 137,419 22,762 20,682
2003 130,668 14,008 144,676 23,194 21,016
2004 135,810 14,644 150,454 23,759 21,594
2005 139,857 15,333 155,190 24,148 21,823
2006 143,287 15,543 158,830 24,668 21,861
2007 148,511 15,985 164,496 24,138 21,496
Total 932,805 104,583 1,037,388 164,015 147,857
12
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
13
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 HHIShare of imports in the inputsUse of products from other sectors produced in the
same city (!!!)
14
Outline
• Motivation
• Data description
• Model and Estimation Issues
• Preliminary results
15
mjtjttmjjtjtjtjty IEX lnlnlnαln 1
Model
• TFP Model (Rosenthal and Strange, 2004):
• Econometric Specification (Henderson, 2003):
Kk
Tij
Iij
Gijjkj
jjj
dddxxsA
XfAgY
),,(),(
)()(
16
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
17
Outline
• Motivation
• Data description
• Model and Estimation Issues
• Preliminary results
18
Production Function Results Size-based
ln (Employment) 0.479***
ln(Capital) 0.058***
ln(Materials) 0.461***
… …Observations 151,775
Number of clusters 41898
R-squared overall 0.85
19
Basic specification (XT-FE) Size Diversity
ln(Local employment) 0.040
(0.022)
ln(# firms) 0.059*
(0.028)
ln(average employment) 0.014
(0.027)
“Anti-diversity index” -0.026
(0.020)
Multi-plant 0.115*** 0.115*** 0.112***
(0.029) (0.029) (0.030)
Firms 41,898 41,898 41,240
obs 151,775 151,775 147,857
Overall R2 0.85 0.85 0.85
20
Olley-Pakes Two Stage (TFP) Size Diversity
ln(Local empl) 0.043*
(0.019)
ln(# firms) 0.044*
(0.022)
ln(Average empl) 0.041
(0.025)
“Anti-diversity index” -0.051**
(0.018)
Multi-plant firm 0.005 0.005 0.001
(0.028) (0.028) (0.028)
Firms 25,906 25,906 25,541
obs 110,613 110,613 107,737
Overall R2 0.30 0.30 0.30
21
“Urban depreciation”
• Ratio:Current value of all fixed assets in the city
toHistorical value of all fixed assets in the city
• Predicted effect: the higher, the better
22
“Urban depreciation” Size OP (1 stage) Diversity
Local employment 0.104*** 0.418***
(0.038) (0.550)
# firms 0.003***
(0.001)
“Anti-diversity index” -0.004
(0.023)
Urban depreciation 0.080*** 0.085*** 0.620 0.111***
(0.038) (0.037) (0.060) (0.038)
Industry* Year f.e. yes yes yes yes
City f.e. yes yes yes yes
firms 42,026 41,898 26,909 41,240
obs 150,311 151,775 73,870 147,857
Overal 0.63 0.85 - 0.85
23
Ownership variables
• PO: privately owned
• DO: private, majority domestic
• FO: private, majority state
• PO = FO + DO
24
Ownership variables
State Domestic Foreign Total
2001 1,072 19,342 636 21,050
2002 994 20,753 695 22,442
2003 930 21,209 767 22,906
2004 883 21,734 837 23,454
2005 872 22,073 910 23,855
Total 4,751 105,111 3,845 113,707
25
Ownership results Size Diversity
ln(Local employment) 0.032
(0.023)
Primarily domestic 0.169*** 0.169*** 0.174***
(0.021) (0.021) (0.021)
Primarily foreign 0.285*** 0.285*** 0.292***
(0.028) (0.028) (0.028)
ln(# firms) 0.026
(0.030)
ln(average employment) 0.038
(0.028)
"Anti-diversity index" -0.068**
(0.021)
Multi-plant firm 0.068** 0.069** 0.067**
(0.025) (0.025) (0.025)
27
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.
