The Geography of Urban Development: Evidence from German Division and Reunification

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1 The Geography of Urban Development: Evidene from German Division and Reunifiation Preliminary Work in Progress Stephen Redding London Shool of Eonomis & CEPR Daniel Sturm University of Munih & CEPR Motivation What determines the spatial distribution of eonomi ativity? What is the role of institutions and poliies? Fous on ities Small spatial sale Comparable data over long periods of time Theories of ity development Natural advantage Inreasing returns to sale Independent stohasti proess Exploit German division and reunifiation as a natural experiment 2

2 Outline of Talk 1. German division and reunifiation as a natural experiment 2. Empirial hypotheses 3. Theoretial model 4. Empirial strategy and identifiation 5. Data and desriptive statistis 6. Empirial results 7. Conlusions 3 German Division and Reunifiation as a Natural Experiment Pre WW II Germany Single market-based eonomy Common poliies and institutions Integrated goods and fator markets Cold-war Nation divided into four parts (West, East, Polish and Russian) Market-based and entrally planned eonomies Very different poliies and institutions Post-1961, sealed border between East & West Germany with goods and fator market disintegration German Reunifiation 1990 onwards Transition to a single market-based eonomy in East & West Germany Re-integration of goods and fator markets in East & West Germany 4

3 German Reih and Post - WW II Division 5 Empirial Hypotheses Hypothesis 1 (City Systems) Within a market-based eonomy with integrated goods and fator markets, there is a ity system within whih ity populations o-move Aross sealed borders between different eonomi systems, the ity system disintegrates so that ity populations no longer o-move Hypothesis 2 (Geographial Disadvantage) Within a market-based eonomy, the imposition of a sealed border has a detrimental effet on the development of ities proximate to the border Within a entrally planned eonomy, the impat of a sealed border on proximate ities will depend on entralized eonomi poliy 6

4 Example : West and East Berlin Ln Pop W Berlin ln Pop E Berlin Ln Pop W Berlin ln Pop E Berlin Ln Pop W Berlin.95.9 ln Pop E Berlin Ln Pop W Berlin.7.65 ln Pop E Berlin year Figure 1A: Former German Reih Ln Pop W Berlin ln Pop E Berlin year Figure 1B: Cold-war Ln Pop W Berlin ln Pop E Berlin year Figure 1C: Post Reunifiation Figure 1: Log Population of West and East Berlin (Resaled) 7 Theoretial Model (Henderson 1974, Helpman 1998, Hanson 1998, Fujita et al. 1999) Consumer Behaviour U = M ( ) µ H 1 C ( C ) µ P M 1 σ 1/(1 σ ) 1/(1 σ ) [ n ( p T ) ] = [ SA ] = i i i i Trade osts P H 1 E H Produer Behaviour [ F x ] a l = + σ p = a w σ 1 x = F( σ 1) 8

5 Theoretial Model (Henderson 1974, Helpman 1998, Hanson 1998, Fujita et al. 1999) Equilibrium Wages a 1 w 1 x i w il i P i M 1 T i 1 1 x MA 1 w = ξ a 1/ [ MA ] σ Change in market aess Change in population Fator Mobility 1 1 SA / 1 w i = = 1 i i M ( ) µ H 1 ( ) µ M ( ) µ H P P P ( P ) µ 1/a MA 1 / L H 1 w SA i / 1 1/a i MA i 1 / L i H i 1 9 Theoretial Preditions Hypothesis 1 (City Systems) Positive orrelation between the population growth of neighboring ities within a single market-based eonomy Aross a sealed border between a market-based and entrally planned eonomies, there need to be no suh orrelation Hypothesis 2 (Geographial Disadvantage) With trade osts, ities lose to an exogenously imposed sealed border will experiene redued market and supplier aess relative to those ities further from the border Within a market-based eonomy, this redution in market and supplier aess will redue their equilibrium size relative to ities further from the border 10

6 Data City Sample In 2000, there were 210 ities within the area of pre WW II Germany (1937 boundaries) with a population greater than 50,000 We onsider all ities whih are among the largest 210 ities within the area of pre WW II Germany in any year of our sample ( ) Dropping border ities (eg E & W Berlin) leaves 290 ities Variables Population Industrial struture pre-1939 (Agriulture, Industry and Servies) Time Period (80 5 year intervals) Pre WW II Germany : 1919, 1925, 1933, 1939 Post-war Period : 1950, 1960 Cold-War : 1970, 1975, 1980, 1984, 1988 Reunifiation : 1992, 1996, Empirial Strategy West Germany Border East Germany (1) Analyze differential hange in o-movements between Cities and treatment partners aross the border Cities and ontrol partners within the same zone City. (2) Analyze hange in relative growth performane within a ountry Border zone. Control Partner Non-border zone Treatment Partner. Treatment Distane 120 km Control Distane 125 km 75 km 75 km 12

7 Desriptive Statistis : Area & 1939 Population Table 1A : Desriptives Geog Area Total Pop 1939 (all Total Pop City Sample Median City Pop t-test for Mean City St Dev City Differene Number of ities (1000 km^2) settlements, 1000s) 1939 (1000s) 1939 (1000s) Pop 1939 (1000s) Pop 1939 (1000s) in Means (p-value) German Reih ,787 68,400 26, W Germany ,289 39,340 18, W Germany 75km E-W Border , W Germany Non E-W Border , E Germany ,173 15,160 5, E Germany 75km New Border , E Germany 75km E-W Border , E Germany Non New Border , West Berlin , East Berlin , Part of Poland 25-2, ,560 Part of Russia Notes: Definition of German Reih based on 1937 boundaries. Sample of West and East German ities exludes Berlin and other Border Cities 13 Border Cities : Examples East Germany, 75km Border, 1939 City Pop Ind Share Serv Share Altenburg Gotha Jena Magdeburg Plauen West Germany, 75km Border, 1939 City Pop Ind Share Serv Share Bamberg Bayreuth Braunshweig Kiel Wuerzburg

8 Empirial Speifiation : Hypothesis 1 (City Systems) Baseline Speifiation For eah ity within 75km of the border, find the nearest treatment partner aross the border For eah ity within 75km of the border, find a ontrol partner in the border zone with a distane most similar to the treatment partner Analyze the differential hange in population growth orrelations between treatment and ontrol partners Consider progressively more general speifiations ln( Pop ln( Pop t t ) = + γ ) = α ln( Pop pt ) + β ( Bord ln( Pop pt )) ( Treat Bord ln( Pop pt )) + dt + ut α ln( Pop pt ) + β ( Bord ln( Pop pt )) + γ ( Treat Bord ln( Pop )) ρ ln( Pop + t 1) δ ln( Pop pt 1 ) t pt + d + u t 15 Baseline Results Table 2: Co-movements in City Populations and the East-West Border (1) (2) (3) (4) (5) (6) (7) (8) (9) ln(pop()) ln(pop()) ln(pop()) ln(pop()) ln(pop()) ln(pop()) ln(pop()) ln(pop()) ln(pop()) ln(pop(p)) 0.133** 0.234*** 0.156* ** 0.176** 0.126* 0.178** 0.160** (0.062) (0.076) (0.078) (0.097) (0.071) (0.072) (0.074) (0.071) (0.074) ln(pop(p))* Border 0.156* * 0.139* 0.148** (0.080) (0.138) (0.077) (0.078) (0.067) (0.080) (0.080) ln(pop(p)) * Treat * Border *** *** *** ** *** ** (0.126) (0.165) (0.120) (0.120) (0.133) (0.124) (0.124) ln(pop(,t-1) * (0.005) ln(pop(p,t-1)) (0.006) Observations Time period Full Full Pre-1990 Post-1970 Full Full Full Full Full Years Year Dummies Undivided ities & partners Zone-era Dummies Zone-year Dummies City fixed effets R-squared

9 Empirial Speifiation : Hypothesis 2 (Geographial Disadvantage) Baseline Speifiation Compare border to non-border zones Run for East and West Germany separately Consider progressively more general error struture t ( Popt ) + βbord + ( Treatt Bord ) + d t ut ln( Pop ) = ln γ + α 1 Robustness Alternative widths of the border zone Mathing 17 West German Border Zone : Non-Border Zone Table 3 : City Growth in West German Border Zone Relative to the Rest of West Germany (1) (2) (3) (4) (5) (6) (7) (8) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop(t-1)) *** *** *** *** *** *** *** *** (0.005) (0.006) (0.002) (0.004) (0.004) (0.003) (0.003) (0.023) 75km Border ** ** (0.009) (0.008) (0.004) (0.010) (0.006) (0.006) (0.008) Treat 75km Border ** * ** ** ** (0.013) (0.008) (0.010) (0.010) (0.013) Observations Cities Border Cities Time period Reih Cold-War Re-unifiation Pre-1990 Post-1970 Full Full Full Years Year Dummies Laender Dummies City Fixed Effets R-squared

10 East German Border Zone : Non-Border Zone Table 4 : City Growth in East German Border Zone Relative to the Rest of East Germany (1) (2) (3) (4) (5) (6) (7) (8) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop(t-1)) *** 0.020*** ** *** (0.010) (0.006) (0.008) (0.006) (0.004) (0.005) (0.005) (0.033) 75km Border ** 0.033*** * (0.019) (0.009) (0.010) (0.019) (0.011) (0.013) (0.014) Treat 75km Border 0.051** ** 0.038** 0.031* (0.020) (0.016) (0.016) (0.016) (0.017) Observations Cities Border Cities Time period Reih Cold-War Re-unifiation Pre-1990 Post-1970 Full Full Full Years Year Dummies Laender Dummies City Fixed Effets R-squared Robustness Table 5 : Robustness, City Growth in Border Zones relative to Non-Border Zones (1) (2) (3) (4) (5) (6) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop) ln(pop(t-1)) *** ** *** *** *** (0.028) (0.048) (0.028) (0.044) (0.008) (0.016) Border * ** (0.029) (0.046) Treat * Border ** ** 0.059** ** 0.079* (0.022) (0.021) (0.020) (0.023) (0.040) (0.045) Observations Border Width (km) Cities Border Cities Region West East West East West East Time period Pre-1990 Pre-1990 Pre-1990 Pre-1990 Pre-1990 Pre-1990 Years Year Dummies City Fixed Effets Mathing Longer Differenes R-squared

11 Future Diretions City employment struture Agriulture Industry Servies Fator market integration Migration data 21 Conlusions City systems Within a single market-based eonomy with integrated goods and fator markets, ity populations o-move Following the division between East and West Germany, this relationship breaks down Geographial Disadvantage Negative treatment effet of proximity to the East West border on ity development in market-based West Germany Positive treatment effet in entrally-planned East Germany Wider impliations City systems Eonomi integration and ity development Institutions and eonomi geography 22

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