Railways and the Raj: The Economic Impact of Transportation Infrastructure Dave Donaldson...
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Transcript of Railways and the Raj: The Economic Impact of Transportation Infrastructure Dave Donaldson...
Railways and the Raj: The Economic Impact of
Transportation Infrastructure
Dave Donaldson
Research Questions
• What is the effect on economic outcomes of opening up to external (ie. international) trade?
• What is the effect on economic outcomes of enabling internal (ie. inter-regional) trade?
• What are the economic gains from improving transportation infrastructure?
• Why economic change underpins these effects?
Motivation
• Our understanding of the effects of openness to trade is still incomplete:– External trade: usually all of country liberalises trade
at same time, so finding counterfactuals is difficult– Internal trade: virtually unexplored, for lack of data
• Transportation infrastructure is a dominant important policy issue in LDCs (eg WDR 1994), yet evidence base is lacking– very hard to evaluate, due to endogenous placement
This paper
• Collect new dataset on prices, wages, production (agricultural), and trade at the district-level (N=~300) in India, from 1870-1925
• Use features of colonial construction of railways (1850-1900) in India as a set of ‘natural experiments’ in openness– Military motive (responding to domestic and foreign aggression)– Famine-prevention motive
• Study impact of railways on agricultural output• Interpret this impact in context of a simple trade model
– Predicts specialisation in comparative advantage crops
• Use data on internal and external trade flows to examine this mechanism
• Where data permits, examine other possible mechanisms (capital and labour reallocations, technological change)
Why Colonial India?
• This region and period of history offer a number of institutional and methodological advantages:– Railway system was dramatic shock (in most of India
at this time, road and river transport was poor/non-existent)
– Railway line placement motives were non-economic in many instances
– Availability of unique internal trade data• Allows external trade to be studied using within-country
variation• Allows internal trade to be studied
Related Literature
• Effect of openness, using natural experiment approach:– Bernhofen-Brown (JPE ‘03, AER ‘04) use Japan’s
1851 (forced) openness to test comparative advantage mechanisms behind opening
– Michaels (2006) uses US Interstate highway expansion to study effect of openness on skill premium
• Quantifying the gains from railways:– Fogel (1967) on USA: uses ‘social savings’ technique,
ignores endogenous placement– Hurd (1998) on India: same method; finds large effect
(9% of GDP in 1900)
This presentation
– Background:• Railways• Economic environment
– Elements of a simple theoretical framework for thinking about these issues
– Data– Empirical method
• Identification strategy for estimating effect of railways
• What economic mechanisms underpin this effect?
Background: Railways
• Principal public investment in colonial India (over half of government spending)
• Mixtures of pure public and public-private provision, but Indian Government always determined route selection
• 95% of current lines built in 1853-1930
• 1870-1920 was highest growth period
Background: Economic Environment (1)
• Structure of economy in 1870:– Agriculture: 68% of GDP, (73% of labour)– Small-scale manuf. and services: 26%, (26%) – Large-scale manufacturing: 0.5%, (0.2%)
• Structure of economy in 1930:– Agriculture: 59%, (75%)– Small-scale manuf. and services: 34%, (23%)– Large-scale manufacturing: 4%, (2%)
Background: Economic Environment (2)
• Effect of railways on transport costs:– Standard estimates suggest that the pure
freight costs of railways were 5-10 times lower than on alternative method (bullock carts)
– However, this ignores other savings:• Bullocks/roads seasonal (bullocks need
food/water, roads unpassable for
Data (1870-1930)• Agricultural production (annual, ~300 districts/native
states):– Yields, by crop (~15 crops)– Land area allocations, by crop– Capital stocks (livestock, carts)– Irrigated areas, by crop
• Prices and wages (annual, ~200 districts/native states)– Prices: by ~30 commodities– Wages: by ~5 occupations (skilled and unskilled)
• Trade (annual, ~70 trade blocks):– Internal trade: full block-to-block matrix of trade flows (but intra-
block diagonals empty)– External trade: trade by port, by foreign country– All in physical units, by commodity (~100 goods), by mode of
transportation (rail, river, coast)
Limitations of the Data
• Agricultural Yields:– Subject of much controversy among econ historians– Created by multiplying normal yields (factual) by subjective
‘conditioning factor’– But largely corroborated by quinquennial crop-cutting surveys
(and no obvious signs that this is not just classical ME)
• Trade data:– External trade flows by block not collected
• have to make assumptions of constant port consumption, and no port transformation
– Roads data very limited in coverage – Lack of unit values may obscure quality-differentiation within
observed commodity classifications
The second stage• Run regressions of form:
dtdtdttddt XRy
y = real agricultural output
R = shortest distance from (population-weighted geographic) centre of district to railway
X= other controls
d = district
t = year
• Can then think of modifying how R is included, to allow for heterogeneous treatment – Distance to port (and which port)
– Distance to internal cities, or other markets
The first stage
dtdtdttddt XZR
•Run regressions of form:
•Where Z is a variable that predicts R, but has no direct effect on y
General IV set-up (1)
• Railways are lines designed to connect two points, A and B
• For any points (A,B), and the observed railway between them, can ask:– What is the effect of the railway on A or B?– What is the effect of the railway on intervening point C?
A
C
B
RAdt ~=0 RBdt ~=0
RCdt = d
d
General IV set-up (2)
• Challenge is to find A-B pairs, such that:– (1) the decision to put a railway between A and B had
nothing to do with unobservable characteristics of C– (2) there is nothing unobservably different about
locations C along the line from A-B
• It is very unlikely that A or B can be used in the analysis, for fear that exclusion restriction violated there– So ideally want 2 or more IVs, with very different
types of A-B pairs
Instrumental Variables (Option 1): Famine-prevention in 1880
• 1880 Famine Commission recommended a number of railways to be built
• This was idiosyncratic feature of that Commission: earlier and later Famine Commissions did not recommend any railways
• Translation into instrument– A: locations of abnormally low rainfall in 1877-78– B: nearest point to A that is on an 1879 railway line – Control for rainfall variation (at C) throughout period
Instrumental Variables (Option 2) – Military Transportation
• Macpherson (1955) estimates that over half of track placement decisions were militarily-driven
• British government was motivated by internal control, and external border defence (esp. Afghanistan border)
• Translation to IV:– A: sites of suspected military action, not already on a
railway at time t– B: nearest military cantonment (base) to A, or nearest
point on existing railways to A
What mechanisms drive the result?
• Obtain a 2SLS estimate , but what is driving this change?– Specialisation?– Specialisation according to comparative advantage?– Capital accumulation:
• returns to capital higher?• railways affected banks’ ability to monitor borrowers?
– Labour supplied to agriculture changes?• Higher wage draws in labour from other sectors?• Railways enable migration?
– Land used in agriculture increases?• Extension of land cultivation margin (deforestation etc.)?• More double-cropping?
– Technological progress?• Returns to innovation higher (size of market larger)?• Technology transfer on the railways?