1. Today Chapter 4 extensions 4.6 - 4.8 Chapter 5

2. Krugman & Venables (1995-1996) intermediate inputs labor mobile between sectors but not between regions firms use M-products (µ) and M-labor (1-µ) also known as the Vertical Linkages (VL) model base model of Chapter 3 is usually named the CP model (Core-Periphery)

3. The VL model in writing U = F 1-δ M δ c j = p j -ε I ε- 1 E total spending on M-products in stead of δY is now E = δY + μ npx   1 1          N i i cM                1 1 1 1 N i i pI value of all varieties produced

4. Supply side mark-up pricing in core model was p = βW/ρ with normalization β = ρ -> p = W now becomes p = I µ W (1-µ) zero profit condition px = I µ W (1-µ) ( α + βx) x = α(ε-1)/β = αε Food sector: –CRS: F(1-λ) = 1-λ –DRS: F'(1-λ) >0 ; F''(1-λ) < 0 Consumer income = (M) wage income + output food sector: Y = Wλ + F(1-λ)

5. Intersector mobility price index is the same for F workers and M- workers for mobility between sectors only the nominal wage matters dλ/λ = η [W - F'(1-λ) ] ( 4.14) same as in core model: equal demand and supply leads to

6. Regional wages in VL model Supply x 1 = demand in region 1 + demand in region 2 + extra production melted away α (ε -1)/β = (E 1 p 1 -ε I 1 ε-1 + E 2 p 1 -ε T 1-ε I 1 ε-1 ) leads to W 1 = (1- β)/α) 1/ε(1-µ) I 1 -µ/1-µ (E 1 I 1 ε-1 + E 2 T 1-ε I 2 ε-1 ) 1/ε (1-µ) W 2 = (1- β)/α) 1/ε(1-µ) I 2 -µ/1-µ (E 2 I 2 ε-1 + E 1 T 1-ε I 1 ε-1 ) 1/ε (1-µ) simplifies to core model when µ = 0 main differences: –E in stead of Y –Extra term I -µ/1-µ : supplier access effect : closer to suppliers lowers price index and can give higher nominal wages.

7. The four forces in the LV model extent of competition effect: a higher λ lowers the price index of all other products (-) market size or home market effect: a higher λ increases the market (+) (new) access supplier effect: a higher λ increases nominal wages (+) (new) marginal productivity effect in food sector (-) –only with DRS: a higher λ increases food wages

8. region 2 region 1 share of M-workers in region 1 W 1 /W 2 T=1.5 B stable equilibrium B The VL model with DRS in the food sector

9. region 1 region 2 share of M-workers in region 1 W 1 /W 2 T=1.3 B unstable equilibrium B The VL model with DRS in the food sector

10. region 2 region 1 share of M-workers in region 1 W 1 /W 2 T=1.1 B stable equilibrium B The VL model with DRS in the food sector

11. T 0 1 0,5 λ1λ1 Fig 4.10 The bell-shaped cirve Unstable equilibria Stable equilibria The VL model with DRS in the food sector VL model: with lowering T from dispersion to agglomeration to dispersion

12. T 0 1 0,5 λ1λ1 Fig 4.3 The Tomahawk diagram Unstable equilibria Stable equilibria CP model: no (increasing) spreading force when T becomes low Next chapter: Helpman(1998) also gets a bell-shaped curve by introducing the housing market as a spreading force

13. The generalized model Puga (1999) not discussed here in detail CP model plus µ (intermediate production) η s (intersector migration) and η r (interregional migration) Only the model with η r =0 (no interregional migration) gives the bell-shape curve

14. The Footloose Entrepreneur (FE) model two labor production factors in stead of one: skilled/unskilled ; human capital/labour ; R&D/production; headquarters/plants Skilled labor is mobile, unskilled labor immobile In production function: –α: skilled labor as fixed costs –β: unskilled labor as variable costs makes the model solvable because the mobile skilled labor demand is not a function of x equation (4.25) for skilled labor wage rate r 1 /r 2 discussion on the FE model will come back later

15. Chapter 5 Agglomeration, the home market effect and spatial wages

16. Terminology ( confusing! ) Concentration: –industry is concentrated in some regions ( x ri /x ni ) / ( x r /x n ) >1 Specialization: –region is specialized in some industries ( x ri /x r ) / ( x in /x n ) > 1 –( x ri /x r ) / ( x in /x n ) also know as the location coeffcient is the same : ( x ri /x ni ) / ( x r /x n ) = ( x ri /x r ) / ( x ni /x n ) Concentration=Specialization The distinction between concentration and specialization is not relevant for one spatial level. It is only done to be consistent with trade theory terminology: –specialization=concentration at the country level Agglomeration: –concentration of more than one industry

17. Wrong terminology: There is more car production in Germany than in The Netherlands or: concentration -> E ir / E in ≠ E is / E in concentration is relative not absolute

18. No concentration, no agglomeration

19. Concentration, no agglomeration

20. No concentration, agglomeration

21. concentration, agglomeration

22. Country A Country B a. Neither specialization, concentration nor agglomeration Industry 1 Industry 2 b. Specialization (=country concentration), no agglomeration

23. c. regional concentration, specialization, no agglomeration (??) d. Concentration and agglomeration, no specialization Country A Country B Industry 1 Industry 2 in terms of ch 3-4 this was called agglomeration here agglomeration is about more industries

24. e. Concentration, agglomeration and specialization Country A Country B Industry 1 Industry 2 d. Concentration and agglomeration, no specialization

25. Concentration manufacturing <1 Below national average > 1 Above national average (E ir / E r )/( E in / E n )

26. Absolute size manufacturing E ir

27. Concentration bussiness services < 1 Below national average > 1Above national average (E ir / E r )/( E in / E n )

28. Absolute size bussiness services E ir

29. Convergence Increase/decline of gdp/cap differences Barro & Sala-i-Martin and others: Global no;within EU yes,but Results for EU: –1980-1990 convergence –Later: divergence –Depends on level of region disaggregation

30. EU 1995-2001

34. 1980-2000: Increasing specialization

35. Moderate changes

36. G. Ellison & E. L. Gleaser (1997)/(1999) Concentration is the rule, not the exception Geography accounts for 20% of economic concentration Concentration itself does not imply the existence of spill-overs Natural advantages (first nature) may have similar effects -> no real support for GE

37. D. Black & J. Vernon Henderson (1999) ‘Spatial Evolution of Population and Industry in the United States’, American Economic Review Vol. 89, No. 2, May 1999, pp321-327 evolution US urban growth 1900-1990 Scale economies and agglomeration distribution remains remarkably stable big cities stay big little downward mobility more upward mobility

38. “Geography matters?” Market potential mp j = ∑ i ≠ j ( N i /d ij )

39. Five hypotheses to be tested 1.The home market effect: large home market leads to net exporters 2.Large market potential raises local factor prices 3.Large market potential induces factor inflows (Chapter 9) 4.Shock sensitivity 5.Reductions in trade costs induce agglomeration

40. 1. Home market effect an increase in a country's demand for cars will lead to a more than proportional increase of the production of cars if yes: support for new trade theory with transport costs and geographical economics if no: support for new trade theory without transport costs or neoclassical theory

41. Davis & Weinstein (1996-2003) Distinguish between trade theory and geographical economics Measuring the home-market effect X gnr = κ gnr + κ 1 SHARE gnr + κ 2 IDIODEM gnr + END + err gnr SHARE = share of output good g in industy n for country r IDIODEM = difference between demand gn in r and demand gn in other countries END = endowments for gn + (neo-classical theory) if κ 2 >1 home market effect (geographical economics) IDIODEM no geographical content (no distance) Test on Japanese regions

42. Table 5.1 Home market effect for Japanese regions IDIODEM 1.416 (0.025) 0.888 (0.070) SHARE 1.033 (0.007) -1.7441 (0.211) END included? No Yes # Observations 760 Source: Davis and Weinstein (1999); Standard errors between brackets, estimation method: Seemingly Unrelated Regressions Problems END is in fact endogenous according to GE theory Home market effect lack of labor supply elasticity -> higher wages in agglomerations yesno

43. Neoclassical trade theory: factor price equalization -> no spatial wage structure New trade theory: some varieties produced in country A and others in country B, no endogeous agglomeration towards A or B -> no spatial wage structure (unless A and B are different in size from the start) 2) Spatial wage structure

44. 2) Spatial wage structure: distance to centres Hanson (1998) study on Mexico Hypothesis 1: regional wages lower at higher distances from Mexico City and USA Hypothesis 2: trade liberalization has lead to a decline of regional wage differences finds strong support for H1 and weak support for H2 H1: (H2 with time dummy) ln (W it /W ct ) = k 0 + k 1 ln(t it ) + k 2 ln(tf it ) + err it (5.2) ( k 1 and k 2 negative) remember W r = ( Σ s Y s T rs 1-ε I s ε-1 ) 1/ε

45. 2) Spatial wage structure: market potential Log (W j ) = κ 0 + κ 1 log(Σ k Y k e -κ 2 Dij ) + err i (5.4) Table 5.3 EU regions 1992-2000 remember W r = ( Σ s Y s T rs 1-ε I s ε-1 ) 1/ε CoefficientStandard error k1k1 0.8980.020 k2k2 0.0130.001 R2R2 0.61

46. 2) Spatial wage structure: real market potential Hanson (1996) Log (W j ) = κ 0 + ε -1 log(Σ k Y k ε+(1- ε)/δ H k (1-δ)(ε-1)/δ W k (ε-1)/δ T (1-ε)Djk ) + err j (5.5) assumption: agriculture replaced by the housing market as a spreading force of non-tradables. If local demand increases due to agglomeration prices will go up -> additional spreading force

47. Structural wage equation: (5.5)1970-801980-90 δ 0.962 (0.015)0.956 (0.013) ε7.597 (1.250)6.562 (0.838) Log(T)1.970 (0.328)3.219 (0.416) Adjusted R 2 0.2560.347 Observations3075 ε/(ε-1)1.1521.180 ρ0.8680.847 Significant, but δ very high