Transport investment: urban form, trade and growth Vernon Henderson Brown University July 2012 Lectures at EIEF, Rome
Motivation • World Bank: about 20% of lending to transport infrastructure (more than social lending) • Huge investments: China: $200b (2007) in infrastructure investments per year. Much in cities • Within cities • Shapes cities for decades/centuries to come (LA vs. NY; Shanghai vs. Beijing) • Little known about impacts in developing countries • Mayors/planners : (1) Optimal configurations: transit, radial and ring highways? (2) How much to spend?: fundamental law of congestion (3) Sprawl/compactness and environmental footprint (3) Impact of specific types of investments? • city shape • urban growth
Motivation • Across cities/districts • Who grows / has higher income: on vs. left off the network • Issue of general equilibrium effects • Hinterland development (penetration roads, partial equilibrium) • Overall network and effect on trade costs and total welfare • Can be general equilibrium • Optimal spending • Positive analysis of impacts: perhaps benefits? • Effect on comparative advantage – More transport: produce heavier stuff
Past literature • Limited – Early location theory and network literature – 1980-1990’s literature on the effect of public investment on growth • No identification • NEG theory gives a framework • Empirical literature we look at is all from last 5 years. Starts with Baum-Snow (2007) focused on identification of causal effects – Smaller picture?
Outline 1– Across cities districts • Effect on inter-city/district trade, prices, and either growth or income – Places that have better access have better outcomes in a later cross- section • Income levels up but not growth rates ( Banerjee, Duflo, Qian 2012 ) • Trade flows up (usual NEG virtuous circle); shift to heavy stuff ( Duranton and Turner 2012) • Inference tough: effect of placing a transport ray & then instrument with historical lines – Modern lines follow historical; historical built with an eye to trade and linking places with a competitive advantage • Look before and after transport construction • Price gaps narrow (export vs. import point), exports rise, real incomes rise (Donaldson 2010) • But who got treated (not random) • Other exogenous change in transport costs – Effect on income levels of oil price rise in places near versus distant from coastal markets places (Storeygard 2012)
Outline 2– Within cities • Effect of transport investments within cities – Urban form and decentralization • “Sprawl” and spatial reorganization of production – Baum-Snow (QJE, 2007); Baum-Snow, Brandt, Henderson, Turner & Zhang (2012) • More efficient commuting and within city movement of goods – Gains in welfare, growth » Duranton and Turner, RES 2012 • Inferences reasonable – No random assignment: try for pseudo-randomization – Growing (or not growing) cities (good vs. bad unobservables) receive investments • Instruments: historical lines/plans built between cities for national defense or even trade, but with no intent to improve modern intra-city efficiency or facilitate decentralization (suburbanization)
Inter-city/district trade: Income effects • “On the road…..” Banerjee, Duflo, Qian NBER, 2012 – If “quasi-randomly assigned better access, do you have better long run outcomes?” • Rails connecting traditional major cities and treaty ports in late 19 th and early 20 th century (but then later roads, also (maintained) canals & rivers) – Look 1986-2006 for a sub-set of counties – Look at places near and further from straight lines connecting these nodes, to assess impact of future rail (and road) construction – Exclude nodes. Each county’s distance to line, segment city, later rail, river, coast, border » Not just trade, but public service delivery » Benefits differential between places limited by factor mobility (vs. Donaldson)
Treaty ports: Shanghai, Ningbo, Fuzhou, Guangzhou Neat instrument
Interpretation • (Not) mode (rail) specific? Vs. reduced form? – 2-3 modes (?); one instrument: distance to straight line + δ + ε ln(dist to mode for county ) = ln(area )+ ln(dist hist line ) j i a b 0 0 ij i p i = + + λ + ln(GDP pc ) ln(area )+ ln(dist hist line ) a b c X e 1 1 1 1 i ij i p i ≈ ˆ ˆ mode effect on ln(GDP pc ) / j b b i 1 0 • Approximation since not use same controls • Same instrument for several modes, vs. just rail effect?
Many controls for access • Move from 25 th to 75 th percentile of distance to line: GDP pc drops by 19%
Evaluating magnitudes • Net general equilibrium effects? – Winners over losers • If factors mobile why see any GDP pc differences? – Simple model: labor, land, capital. Same returns to labor and capital if mobile • Then just differences in return to land [labor/land ratio down to equalize V MP of labor] • Want total GDP (per unit land)? – Goods composition (4 or more factors of production) • Low skill production off network?
“Roads and trade” Duranton, Morrow and Turner, 2011 • NEG virtuous circle model: reduced transport costs increase demand for different varieties everywhere City i produces one variety of each sector k • Value and weight of trade flows between 65 regions in USA for 2007 • “Propensity” to export related to in-city transport– kms of roads within city
Issues in estimation D • current highway distance. Other R ’s have kms of roads ij within city • For kms of roads within city , roads allocated to growing cities (China) or as make-work to poorly performing cities (USA) – Instrument with kms from 1947 plan, historical rails & exploration routes within city • Old routes: cheaper to build more roads in city (e.g. right-of-way, bed) • Built for inter-city trade, not movement within city (but looking at inter-city trade) • Between-city highway distances . Issue of highway placement: serve regions with comparative advantage in trade and with historical cultural links? – Instrument with historical rail distances (built for agriculture and natural resource extraction) • City i uses j ’s inputs historically and were provided better links historically and today
Trade flow equations
OLS: small insignificant effects. Actual roads over-allocated to non-exporters and poorly performing cities (make-work and rules)
“Railroads of the Raj” Donaldson 2010 • British colonial rails: military vs. extractive purposes – Incredible change in transport costs • India poor roads and no canal system • Cool things: conceptual framework and transport modeling • Conceptual framework: Usual NEG preferences, Eaton-Kortum (2002) Ricardian • comparative advantage model. Amount of output z from a unit of land of commodity k in region 0 is realization of draw Z θ k 0 , iid draws by , ,& A o k j k • In autarky produce things badly for consumption; with trade can focus just on what do well. As trade costs fall, buy more products from other places (as they are lowest cost producer).
Transport • Roads, rivers, coast, rails – Rivers not canals; silted and yearly variation in quality (flooding and water level drop) – Coast: steamships after 1840 for major ports • GIS network analysis of modes, used between region o and f, with nodes and arcs – Shortest path vs. lowest cost. α = α rail road Assume cost prop. to distance. Unit costs: 1. Solve for , α α α sea river , . For each vector , pick cost minimizing combo (network) of modes over different parts of route from to . o f α Then pic k to minimize sq residuals in price equation.
Some results • Look at salt prices with several types with unique origin and many destinations – Differential in destination prices fully reflect transport costs differentials from origins • Modal differences: rails, road, sea and river LCRED : Effective distance in railway units
Welfare • Section on trade flows– ignored here • Look at welfare . – Simple in model (only land in production) – Rents equal nominal ag. output per unit land • Local yields and national prices of grains (?) – Deflate by price index (prices for products) • includes transport cost based on prior estimates • Change in “rents” when rail introduced in a district; 235 districts from 1870-1935: – Change in output composition vs. price index
“Farther on down the road” Storeygard, 2012 • Sub-Saharan African coastal nations where primate city is a port – Idea is export agricultural products to port for export – But sold and serviced in local interior cities each serving an agricultural hinterland • Take road network as given – Ask what happens to city incomes if transport costs rise exogenously?
Road systems in Tanzania Dar es Salaam
Cost change: Elasticity of VTC per unit distance with respect to price of fuel =. 35
How measure income: Lights! • 287 cities over 17 years (92-07) • Cities are light blobs with census populations Henderson, Storeygard and Weil, AER 2012 • elasticity for low-middle income countries is just over 0.3 • LD and FE same
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