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Today

Today. Chapter 4 extensions 4.6 - 4.8 Chapter 5. 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

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Today

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  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. 1 ( ) é ù - e N 1 ( ) å - e 1 = I p ê ú i ë û 1 = i 1 ù é r N å r = M c ú ê i û ë = i 1 value of all varieties produced The VL model in writing • U = F1-δ Mδ • cj = pj-ε Iε-1 E • total spending on M-products in stead of δY is now E = δY + μ npx

  4. Supply side • mark-up pricing in core model was p = βW/ρwith normalizationβ= ρ -> p = W • now becomes p = Iµ W(1-µ) • zero profit condition px = Iµ 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 x1 = demand in region 1 + demand in region 2 + extra production melted away • α (ε -1)/β = (E1 p1 -εI1ε-1+ E2 p1 -εT 1-εI1ε-1) leads to • W1 = (1- β)/α)1/ε(1-µ) I1-µ/1-µ (E1I1ε-1 + E2 T1-εI2ε-1)1/ε (1-µ) • W2 = (1- β)/α)1/ε(1-µ) I2-µ/1-µ (E2I2ε-1 + E1 T1-εI1ε-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 indexandcan 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. The VL model with DRS in the food sector T=1.5 W1/W2 region 2 B B stable equilibrium region 1 share of M-workers in region 1

  9. The VL model with DRS in the food sector T=1.3 W1/W2 region 1 B B unstable equilibrium region 2 share of M-workers in region 1

  10. The VL model with DRS in the food sector T=1.1 W1/W2 region 2 B B stable equilibrium region 1 share of M-workers in region 1

  11. The VL model with DRS in the food sector Fig 4.10 The bell-shaped cirve 1 λ1 0,5 0 T Unstable equilibria Stable equilibria VL model: with lowering T from dispersion to agglomeration to dispersion

  12. Fig 4.3 The Tomahawk diagram 1 λ1 0,5 0 T 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) ηs (intersector migration) and ηr (interregional migration) • Only the model with ηr =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 r1/r2 • 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 (xri /xni ) / ( xr /xn) >1 • Specialization: • region is specialized in some industries (xri /xr ) / ( xin /xn) > 1 • (xri /xr ) / ( xin /xn) also know as the location coeffcient • is the same : (xri /xni ) / ( xr /xn) = (xri /xr ) / ( xni /xn) 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 -> Eir / Ein ≠ Eis / Ein • concentration is relative not absolute

  18. No concentration, no agglomeration

  19. Concentration, no agglomeration

  20. No concentration, agglomeration

  21. concentration, agglomeration

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

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

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

  25. <1 Below national average > 1 Above national average Concentration manufacturing (Eir / Er)/( Ein / En )

  26. Absolute size manufacturing Eir

  27. < 1 Below national average > 1Above national average Concentration bussiness services (Eir / Er)/( Ein / En )

  28. Absolute size bussiness services Eir

  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

  31. EU 1995-2001

  32. EU 1995-2001

  33. 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 • mpj = ∑ i ≠ j ( Ni /dij)

  39. Five hypotheses to be tested • The home market effect: large home market leads to net exporters • Large market potential raises local factor prices • Large market potential induces factor inflows (Chapter 9) • Shock sensitivity • 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 • Xgnr = κgnr + κ1SHAREgnr + κ2IDIODEMgnr + END + errgnr • SHARE = share of output goodgin industynfor countryr • IDIODEM = difference between demand gn in r and demand gn in other countries • END = endowments for gn + (neo-classical theory) • if κ2 >1 home market effect (geographical economics) • IDIODEM no geographical content (no distance) • Test on Japanese regions

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

  43. 2) Spatial wage structure • 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)

  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 (Wit /Wct ) = k0 + k1 ln(tit ) + k2 ln(tfit ) + errit(5.2) (k1and k2negative) remember Wr = ( Σs Ys Trs1-εIsε-1 )1/ε

  45. 2) Spatial wage structure:market potential • Log (Wj) = κ0 + κ1 log(ΣkYk e-κ2 Dij) + erri (5.4) Table 5.3 EU regions 1992-2000 remember Wr = ( Σs Ys Trs1-εIsε-1 )1/ε

  46. 2) Spatial wage structure:real market potential • Hanson (1996) • Log (Wj) = κ0 + ε-1log(ΣkYk ε+(1- ε)/δHk(1-δ)(ε-1)/δ Wk(ε-1)/δ T(1-ε)Djk) + errj (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. Significant, but δ very high

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