Railways and Market Integration in British India

January 2007Comments Welcome

Tahir Andrabiand

Michael KuehlweinPomona College

Main Questions:

Did India have an integrated market between 1860-1920?

How much did railways contribute to market integration?

Standard Story: Hurd (1975)

Figure 2: Standard Deviation of the Log Wheat Price and the Number of Districts with Railways (out of 159 districts)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

1861

1864

1867

1870

1873

1876

1879

1882

1885

1888

1891

1894

1897

1900

1903

1906

1909

1912

1915

1918

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Standard Deviation

Railways

Big Picture

Scale and Scope

Colonialism and the British Did the British Unite India? Benign Neglect, Famine, Victorian Holocaust

GIPR ghat loco Y43, SS class 4-6-0ST in 1863. Scan provided by John Lacey.

http://www.irfca.org/

Big Picture, contd.

Market Integration

PPP

How wide is the border?

Literature (contd.) US: Atack and Passel (1994) Russia: Metzer (1974) India: Hurd (1975), Whitcomb and

Hurd (1983), Indian Famine Commission of 1901, McAlpin (1974), Latham and Neal (1983), Collins (1999)

Results mixed for India. Methodologically, somewhat mixed

Preview of the Results

Did India have an integrated market between 1860-1920? YES!

How much did railways contribute to market integration? NOT A WHOLE LOT!

INDIAN RAILWAY DETAILS

First trains: 1853 in Bombay, 1854 in Calcutta Miles of track:

1860: 838 1870: 4,771 1880: 9,162 1890: 16,401 1900: 24,751 1910: 32,099

By 1873, the largest 20 cities had railroads and were linked to each other

DATA Annual retail wheat price data by district

between 1860 and 1920 Collected fortnightly at district headquarter

114 districts with data in 1861 162 districts with data by 1920 Two samples:

114 districts with complete data from 1861-1920

147 districts with complete data from 1873-1913

DATA (contd.)

Years districts got railways from 1947 History of Indian Railways

Population data from Indian Census of 1872

Distance measures from maps

TIME SERIES TESTS

Market integration implies stable long-run relationship in relative wheat prices and mean reversion in deviations from that long-run relationship

Market segmentation: permanent relative price changes

TIME SERIES TESTS (Contd.) Simple test: unit root in relative wheat prices (1) qi,t = i + iqi,t-1 + i,t qi,t: log price of district i at time t minus

mean log price across districts at time t i: district specific constant i,t: error term with different variance and

serial correlation across districts

Null: unit root so i=0

TIME SERIES TESTS (Contd.)

Panel unit root tests have higher power Levin-Lin: common β in alternative to

null Im-Pesaran-Shin: β can vary across

districts

Table Levin-Lin Panel Unit Root Tests

Sample t-star p-value p ^ Approximate half-life (years)

Price Level Test1861-1920 (114 districts) -37.544 0.000 0.506 1.019Inflation Rate Test1862-1920 (114 districts) -98.358 0.000 -0.133 *Price Level Test1874-1913 (149 districts) -28.417 0.000 0.544 1.140Inflation Rate Test1875-1913 (149 districts) -77.352 0.000 -0.103 *

Notes: The price level is the deviation of the log price from the mean log price each year. The inflation rate is the deviation of the difference in log prices (current minus lagged) from the mean difference in log prices each year.

Market Integration Results

Markets were integrated

Short half life

ESTIMATING RAILWAYS’ CONTRIBUTION

Our method: measuring their impact on absolute (log) price differentials (APDs) between district pairs

114 districts: 6,441 district pairs a year

147 districts: up to 10,731 district pairs a year

ESTIMATING RAILWAYS’ CONTRIBUTION TO MARKET INTEGRATION

econometric specification:

(2) APDj,k,t = α + β1 BothRailj,k,t +Σβj,kDj,k + µj,k,t

BothRail j,k,t: dummy variable = 1 when districts j and k have railways in year t

D j,k: fixed effects dummy variable for each district pair

Table 1 Summary Statistics of Variables

Sample 1: 114 Districts

Years 1861-1920 No Missing Price

Variable Obs. Mean St. Dev. Minimum Maximum Absolute Price Differential 386,460 0.262 0.248 0 2.427

Log Distance 386,460 6.147 0.751 2.024 8.178 One Princely State 386,460 0.052 0.221 0 1

Both Big Cities 386,460 0.072 0.259 0 1 Both on Ganges 386,460 0.021 0.144 0 1 Both on Coast 386,460 0.009 0.090 0 1

Same State 386,460 0.180 0.385 0 1 Both have Railways 386,460 0.555 0.497 0 1

Sample2 : 147 districts No missing price 1873-1913

Prices for all available consecutive years 1861-1920 Variable Obs Mean Std. Dev. Min Max Absolute Price Differential 617439 0.260 0.242 0 2.580

Log Distance 617439 6.194 0.728 1.949 8.178 One Princely State 617439 0.143 0.350 0 1

Both Big Cities 617439 0.061 0.240 0 1 Both on Ganges 617439 0.025 0.157 0 1 Both on Coast 617439 0.007 0.085 0 1

Same State 617439 0.136 0.343 0 1 Both have Railways 617439 0.535 0.499 0 1

Table 2Absolute Price Dispersion

with District Pair Fixed Effects

Sample 1 114 Districts

w/o time effects

BothRail -0.1680 (225.71)*** Observations 386460 R-squared 0.44 Sample 2 147 Districts

BothRail -0.1560 (263.48)*** Observations 617439 R-squared 0.43

Mean Absolute Log Price Differences: Wheat: 1861-1920

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0.1

0.2

0.3

0.4

0.5

0.6

With Railways

Without Railways

Table 2 Absolute Price Dispersion with District Pair Fixed Effects

Sample 1 114 Districts

w/o time effects

with year dummy

with quadratic trend

BothRail -0.1680 -0.0273 -0.0273 (225.71)*** (28.95)*** (27.74)*** Observations 386460 386460 386460 R-squared 0.44 0.53 0.50 Sample 2 147 Districts

BothRail -0.1560 -0.0283 -0.0281 (263.48)*** (37.94)*** (36.30)*** Observations 617439 617439 617439 R-squared 0.43 0.51 0.48

Robust t statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

Table 2Absolute Price Dispersion with District Pair Fixed Effects

Figure 5: Price Dispersion Before and After Railways

0

0.05

0.1

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0.25

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0.35

-20 -15 -10 -5 0 5 10 15 20

Years Before or After Railway Connection

Mean Absolute Price Dispersion

Table 5 Absolute Price Dispersion with District Pair Characteristics

Sample 1 Sample 1 Sample 2 Sample 2 With Year

Dummies With Quadratic Trend

With Year Dummy

With Quadratic Trend

BothRail -0.0388 -0.0386 -0.0446 -0.0443 (0.0009)**

* (0.0009)***

(0.0007)***

(0.0007)***

LnDistance 0.0852 0.0852 0.0829 0.0830 (0.0006)**

* (0.0006)***

(0.0004)***

(0.0004)***

BothLargeCity -0.0058 -0.0059 0.0045 0.0043 (0.0013)**

* (0.0013)***

(0.0011)***

(0.0011)***

BothonGanges -0.0399 -0.0399 -0.0595 -0.0592 (0.0016)**

* (0.0015)***

(0.0012)***

(0.0012)***

BothonCoast -0.0291 -0.0291 -0.0453 -0.0452 (0.0029)**

* (0.0030)***

(0.0025)***

(0.0025)***

Same State -0.0337 -0.0337 -0.0216 -0.0217 (0.0009)**

* (0.0009)***

(0.0008)***

(0.0008)***

OnePrincelyState

0.1750 0.1750 0.0338 0.0330

(0.0019)***

(0.0020)***

(0.0008)***

(0.0008)***

Observations 386460 386460 617439 617439 R-squared .30 .27 0.25 0.22 Robust standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

CONCLUSIONS Wheat markets were integrated in India

between 1860-1920 Significant price convergence during

this period Railways’ contribution to that

convergence appears to be relatively small: 10% Railways effect is comparable to being on

the Ganges or the coast

Potential Endogeneity Direction of bias ?

Economic

Military

Humanitarian Likely bias to reinforce small effect of

railways Can do some more work

Potential instrument

Further Work Rice Data Political boundaries matter too, so

perhaps institutional integration contributed significantly to economic integration

Other technological breakthroughs such as telegraphs may have been important

Standard Deviation of the Log Rice Price and the Number of Districts with Railways (out of 183 districts)

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0.35

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0.45

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Standard Deviation

Number of Railways

Mean Absolute Log Price Differences: Rice: 1861-1920

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0.1

0.2

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0.4

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0.6

1873

1875

1877

1879

1881

1883

1885

1887

1889

1891

1893

1895

1897

1899

1901

1903

1905

1907

1909

1911

1913

1915

1917

1919

With Railways

Without Railways