Railroads, Specialization, and Population Growth in Chile
Andrés Forero
1
Francisco Gallego2
Felipe González
3
Matı́as Tapia2
1 PUC-Chile
2 PUC-Chile
3 UC
and EH Clio Lab
Berkeley
August 2014
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
1/1
Motivation
• Transportation technologies have been emphasized to be one of the
main causes behind the persistent decrease in transportation costs
(Hummels, 2007). Hence, understanding the causal impact
transportation technologies have on the economy is important.
However, the presence of endogeneity makes this task difficult.
• Railroads were a big shock to transportation costs between regions
and can help us to identify the causal effect of transport costs on
development and on outcomes such as population growth,
urbanization and specialization.
• As the reduction in transport costs is channeled through market
mechanisms, relative prices should play a crucial role in the
magnitude of the effects of railroads construction.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
2/1
Related Literature
1
Transportation technologies and the economy:
• Michaels (2008, Restat): Labor market consequences of increased trade
•
•
•
•
due to the interstate highway system.
Atack, Bateman and Margo (2010): Railroad impact on population
density and urbanization.
Banerjee, Duflo and Qian (2012): Access to transportation networks
and regional economic growth in China over a twenty-year period.
Faber (2012): Tests the “home market effect” in Krugman (1980)
using China’s Highway system as natural experiment.
Donaldson (forth., AER): Impact of access to transportation networks
in India on regional trade and income.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
3/1
Related Literature
• Donaldson and Hornbeck (2012): Impact of access to transportation
networks in the US on degree of market access, land value, and
production at the regional levels.
• Fajgelbaum and Redding (2014): Impact of expansion of railroads in
Argentina in 1870-1914 on trade patterns and interaction with
geography and other investments.
• Berlinski, Galiani and Jaitman (2011): “Impact of Railways: Expansion
on Spatial Population Patterns”: Impact of expansion and contraction
of railways in Argentina on spatial patterns of population and creation
of new cities and villages.
• Atack and Margo (2009) and Atack et al. (2008): effects of railways
on agriculture land expansion and on the emergence of the
manufacturing sector in the US over the 19th century.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
4/1
Related Literature
2
Transportation technologies in economic history:
• Fogel (1964), Fishlow (1965): Railroads as the main cause of economic
growth in the United States?
• North (1958, JEH): Decrease in water transportation costs and
economic development between 1750 and 1913.
• Kujovich (1970): The refrigerator car changed the relationship between
railroads and the industry.
• Rua (2011): The container as transportation technology, its adoption
and its impact on international trade.
3
Railroads in Latin American economy:
• Miller (1976): Impact on economic development in Perú 1890-1930.
• Coatsworth (1979, JEH): Social savings in Mexico in the 19th century.
• Ramı́rez (2001): No impact on Colombian economy, and social savings.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
5/1
Related Literature
• Summerhill (2005, JEH): Social savings in Brazil until 1913.
• Herranz-Loncán (2011): Growth acccounting in Argentina, Brazil,
Mexico and Uruguay.
• Zegarra (2011): Features of the railway in Perú, e.g. transport costs
and travel times.
• Berlinski, Galiani and Jaitman (2011): “Impact of Railways: Expansion
on Spatial Population Patterns”: Impact of expansion and contraction
of railways in Argentina on spatial patterns of population and creation
of new cities and villages.
• Fajgelbaum and Redding (2014): Impact of expansion of railroads in
Argentina in 1870-1914 on trade patterns and interaction with
geography and other investments.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
6/1
Our Paper
• We look at Latin America and construct a panel dataset of Chilean
departments spanning a sixty-year period of railroad construction
(1860-1920).
• Our paper estimates the causal impact railroads have on population
patterns and urbanization. In this sense, we are more related to the
literature on impacts and mechanisms.
• We suggest a novel mechanism for small open economies in which the
impact of railroads on population and specialization patterns depends
on the relevant relative prices –the real exchange rate– at the time of
construction of railroads. Related to Atack et al. (2008) and
Fajgelbaum and Redding (2014). Key difference: small open economy.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
7/1
Preview of Strategy and Results
• We estimate the causal effect railroads have on urban population
using two different sources of exogenous variation in an instrumental
variables framework:
Straight lines (Banerjee et al. 2012).
2 Theoretical construction.
1
• Our empirical strategy complements the existing literature and is
particularly appealing for a panel dataset
• We find that a 1% increase in availability of railways causes an
average increase of about 12-15% increase in total, rural, and urban
population. We do not find that an increase average railroads
increase on patterns of specialization.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
8/1
Preview of Strategy and Results
• However, we find that when the relative price of tradables to
non-tradables is high, railways construction does affect specialization
through a subsitution of agriculture for manufacturing employment
and, therefore, a decrease in urbanization.
• We use a simple theoretical model to rationalize these results.
• We focus our analysis on departments in the south, whose economy is
mainly based on agriculture. This also allows us to use the distinction
between urban and rural population as a proxy
• We argue that the economy’s aggregate real exchange rate, which we
use as a proxy for the relevant relative price, is largely exogenous to
these departments, who are a small share of the total economy, as it
is largely driven by mining activities in the north
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
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EHSpecialization
Clio Lab, UC Berkeley )
August 2014
9/1
Railroad Construction
1
Mining and the first railway connecting Copiapó and Caldera.
• Importance of Copiapó as mining city (Chañarcillo 1832).
• Obsolescence of old technologies (carts and mules).
• These railways encouraged following constructions.
2
Connecting Valparaiso and Santiago.
• Obsolescence of public roads and public pressure.
• 187 kilometere railroad connecting the port and the capital.
Railroad Construction
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
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August 2014
10 / 1
Railroad Construction
3
Railroads everywhere.
• Santiago and Rancagua connected by a 52 kilometer line.
• Railways reached Concepción in 1970 with a 588 kilometers line.
• Pause due to the Pacific War.
• Railroads reached Arauco in 1894.
• Reached the region close to Puerto Montt in 1913.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
11 / 1
Figure: Railroad Construction
(a) 1854
(b) 1865
(c) 1875
(d) 1885
(e) 1895
(f) 1907
Figure: Railroad Construction until 1920
Transportation Costs
• Railroads brought a significant decrease in transportation costs
because:
Chile’s inability to transport goods through rivers.
2 Cold winter and flooding from rivers made transportation difficult.
3 Poor quality of roads.
4 Possibility of being victimized by bandits (Verniory, 2001).
1
• Before railroads freight between Valparaiso and Santiago was done
with forty ox carts, with capacity for fifty quintals, during a period of
6-12 days (costs $1–1.75). By railroad: 8 hours and cost $0.44-0.55.
• Passenger time decreased from 20 to 6 hours and costs from $10–20
to $2.5–5.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
15 / 1
Table: Composition of Exports and Imports
(Shares, Average 1844-1900)
Exports
Imports
Mining
Agriculture
Manufacturing
Others
71.1
21.6
1.4
5.9
4.7
8.8
82.8
3.4
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
16 / 1
Data Construction
• Two historical sources to document the railroad construction:
1
2
Historical censuses (1865, 1875, 1885, 1895, 1907, and 1920).
Railroad construction: Espinoza (1897), Thompson and Angerstein
(1997), Alliende (2006) and others.
• From these sources we constructed a panel dataset of 45 departments
at 6 different periods.
• However, we exclude 10 departments located in the North of the
country: just related to mining and different gauge.
• In sum, 13,586 kilometers of railroads were constructed, but we will
only use 8,681 kilometers constructed from Valparaı́so to the south.
• For comparison: 4,500 km. in Perú and 24,000 km. in Brazil in a
similar period.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
17 / 1
Table: Descriptive statistics for main variables
Summary Statistics for Variable:
Urban Population
Sample:
Population
Railways (in Km.)
All
North
Rest
All
North
Rest
All
North
Rest
11,570
(19,918)
16,122
(26,767)
21,772
(33,160)
24,587
(44,998)
28,384
(58,017)
37,131
(83,818)
8,609
(8,340)
13,066
(9,665)
15,276
(11,899)
13,316
(10,581)
8,478
(9,650)
8,221
(10,032)
12,416
(22,174)
16,995
(29,983)
23,628
(37,007)
27,807
(50,425)
34,072
(64,665)
45,891
(94,086)
40,427
(32,792)
46,133
(39,152)
53,634
(52,222)
56,618
(63,568)
66,470
(80,751)
76,399
(104,123)
26,984
(15,652)
27,473
(16,230)
28,107
(16,993)
25,500
(15,399)
28,459
(17,107)
24,791
(15,809)
44,268
(35,474)
51,464
(42,218)
60,927
(56,625)
65,509
(69,285)
77,331
(88,400)
91,144
(114,829)
13
(31)
32
(51)
35
(52)
50
(75)
62
(78)
108
(122)
27
(51)
56
(90)
65
(92)
68
(93)
90
(86)
177
(140)
9
(22)
25
(31)
27
(31)
44
(70)
54
(75)
89
(111)
23,157
(49,253)
11,161
(10,058)
26,618
(55,194)
56,614
(67,224)
26,886
(15,567)
65,107
(73,632)
50
(79)
80
(103)
41
(69)
Year:
1865
1875
1885
1895
1907
1920
Total
Basic Correlations
• We present correlations by estimating:
log udt = αd + λt + β log rdt + ε dt
(1)
• Where udt is the total amount of people living in urban areas in
department d at year t, rdt is kilometers of railroads constructed until
year t, and ε dt is a random shock.
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
19 / 1
Table: OLS Regression
Dependent variable is:
Log Urban Pop
Log railways
Department Fixed Effects
Year Fixed Effects
Observations
R2
Log Rural Pop
Share of Urban Pop
Log Total Pop
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
0.241***
(0.028)
(0.076)
Yes
Yes
0.098***
(0.032)
(0.154)
Yes
No
0.118***
(0.023)
(0.055)
Yes
Yes
0.091***
(0.030)
(0.120)
Yes
No
0.017***
(0.004)
(0.012)
Yes
Yes
0.005
(0.005)
(0.021)
Yes
No
0.157***
(0.025)
(0.063)
Yes
Yes
0.080***
(0.026)
(0.121)
Yes
No
208
0.850
208
0.893
207
0.889
207
0.895
208
0.901
208
0.918
210
0.849
210
0.866
Table: First Stages
Dependent variable: Log Railways
(1)
Log Predicted Railways
(2)
(3)
0.389***
(0.042)
0.575***
(0.086)
0.223***
(0.050)
Yes
Yes
Yes
Yes
Yes
Yes
210
0.881
210
0.842
210
0.904
0.736***
(0.071)
Log Straight Lines
Department Fixed Effects
Year Fixed Effects
Observations
R2
Table: IV Results
Dependent variable is:
Log Urban Pop
Log Rural Pop
Share of Urban Pop
Log Total Pop
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
Predicted Railways
0.131***
(0.042)
Straight Lines
0.158***
(0.045)
Both
0.149***
(0.040)
Predicted Railways
0.129***
(0.037)
Straight Lines
0.140***
(0.044)
Both
0.137***
(0.036)
Predicted Railways
-0.002
(0.006)
Straight Lines
0.008
(0.006)
Both
0.005
(0.005)
Predicted Railways
0.105***
(0.037)
Straight Lines
0.131***
(0.038)
Both
0.122***
(0.034)
Sargan Test (p-value)
Kleibergen-Paap Test (p-value)
0.00
0.00
0.51
0.00
0.00
0.00
0.81
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.43
0.00
Department Fixed Effects
Year Fixed Effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
208
35
82.82
208
35
100.5
208
35
168.9
207
35
82.78
207
35
100.2
207
35
169.0
208
35
82.82
208
35
100.5
208
35
168.9
210
35
84.50
210
35
106.3
210
35
175.5
IV
Log Railways
Observations
Number of id
F-test first Stage
Economic Mechanisms
• What are the economic mechanisms linking a reduction in transport
costs and an increase in population?
• We now present the main ideas of a simple model that highlights
some mechanisms and also provides a new test related with the
relevance of the real exchange rate.
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23 / 1
Theoretical model
• The impact of railroads goes mainly through a reduction in
transportation costs
• This reduces trade barriers, and allows regions to specialize in the
goods in which they have a comparative advantage
• Labor mobility plays a crucial role, as workers move across regions
and sectors to arbitrage real wage differences
• Given that most regions in our analysis have a comparative advantage
on agriculture, the allocation of labor between tradable and
non-tradable sectors will play a role in the relative growth of urban
and rural population
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
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August 2014
24 / 1
Theoretical model
• The overall impact of access to the railroad on a given a region will
depend on its specific impact on trade costs with the world economy
and the rest of the country (which might vary across regions) and
relevant prices
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
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August 2014
25 / 1
Related theoretical literature
• City development:
• Desmet & Rossi-Hansberg (AER, 2014)
• Rossi-Hansberg and Wright (RES, 2007)
• Regional development and transportation costs:
• Fajgelbaum and Redding (NBER WP, 2014)
• Adamopoulos (IER, 2011)
• Vanderbroucke (IER, 2008)
• Herrendorf, Schmitz, and Teixeira (IER, 2012)
• Caselli and Coleman (JPE, 2001)
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
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August 2014
26 / 1
Related theoretical literature
• Railroads and trade:
• Donaldson (AER, forthcoming)
• Donaldson and Hornbeck (NBER WP, 2013)
• Haines, and Margo (NBER WP, 2006)
• Perez Cervantes (WP, 2013)
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Model setup
• Consider a country with N agents and M different regions.
• Each region is endowed with L units of land .
• Land is equally owned by all agents, so per capita land holdings are
ML/N.
• There are 3 goods: agriculture (A), tradable manufactures (M ), and
services and non-tradable manufactures (S ).
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
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28 / 1
Model setup
• Agricultural and manufacturing goods can be traded between regions,
and also with an international market with exogenous prices, pA∗ and
∗ .
pM
• Trade between regions and with the rest of the world is subject to
iceberg costs related to the transportation technology: consuming one
unit of good M (S ) produced in region i at region j implies shipping
(1 + δij ) units at origin.
• Services are non-tradable, and must be produced and consumed
within each region.
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Model setup
• Within each region, there are 2 locations, rural and urban.
Agriculture is produced in the rural location, while manufacturing and
services are produced only in the urban location
• Each region is a small open economy
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Agents and preferences
• Agents live where they work, and derive utility from the consumption of the 3 goods.
• Agents supply their labor inelastically in the labor market, and can choose freely where
to locate.
• The problem for any given agent agent can be written as:
Max U = U (cA (r , l ), cM (r , l ), cS (r , l )) = [cA (r , l )α + cA (r , l )α + cA (r , l )α ]
1
C (r ,l )
w (r , l ) + R = pM (r , l )cM (r , l ) + pA (r , l )cA (r , l ) + ps (r , l )cs (r , l ) + q (r , l )
, where r is region and l is sector.
• Free mobility implies that::
U (r , l ) = Ufor all r , l
where U is an equilibrium object
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Technologies
• Goods are produced by perfectly competitive firms that face constant
returns to scale technologies on land and labor:
δA
yA,r = γAr LA
WA1−δA
δM
1−δM
WM
yM,r = γM LM
yS,r = ξ Lsδs Ws1−δs
, where γAr reflects the productivity of agricultural land in region L.
• We assume that δA > δM , δS (agriculture is more land intensive than
manufacturing or services)
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Technologies
• We also assume γAr > γM
• Firms maximize profits, taking as given final goods prices and factor
rental prices.
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Equilibrium properties
• If regions trade, they specialize in the tradable good in which they
have a comparative advantage
• Real wages are fully equalized across regions, so workers are
indifferent about where to live
• A (non-observable) RER exists for each region
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Propositions on the impact of railroads
• Proposition 1: Overall effect of access to railroads
Access to railroads for a given region, which reduces trade
costs, is akin to a productivity shock for firms, increasing the
demand for labor and real wages. New workers flow into the
region until equilibrium is restored
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Propositions on the impact of railroads
• Proposition 2: Compositional effects of access to railroads
The compositional effect of population changes depends on
relative prices at the time in which railroads arrive. If the price
of tradables is relatively high, relatively more workers will flow
into agriculture and live in rural areas
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Empirical implications
• (i) Access to railroads increases specialization in agriculture if the
nationwide relative price of tradables to non-tradables, as measured
by the nationwide RER, is high.
• (ii) The main mechanism to do that is a substitution between
agriculture and manufacturing production, in which crucially the
empirical measure of manufacturing has an important non-tradables
component
• (iii) Therefore, urbanization decreases when the relative price of
tradables to non-tradables is high, as workers move towards tradables,
in particular towards the one in which the economy has a competitive
advantage
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Real Exchange Rate “shocks”
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Table: Population effects: IV estimates with interaction effects
VARIABLES
Log railways
LogRailways ∗ LogRER
(1)
Log Urban Pop
(2)
Log Rural Pop
(3)
Share of Urban Pop
(4)
Log Urban Pop
(5)
Log Rural Pop
(6)
Share of Urban Pop
(7)
Log Urban Pop
(8)
Log Rural Pop
(9)
Share of Urban Pop
(10)
Log Urban Pop
(11)
Share of Urban Pop
(12)
Log Urban Pop
0.156***
(0.039)
-0.039
(0.153)
0.132***
(0.035)
0.173*
(0.094)
0.006
(0.005)
-0.053**
(0.025)
0.120***
(0.033)
0.110
(0.121)
0.159***
(0.040)
0.136***
(0.035)
0.010
(0.006)
0.124***
(0.034)
0.002
(0.001)
-0.001
(0.001)
0.001***
(0.000)
-0.000
(0.001)
0.165***
(0.039)
0.090
(0.155)
0.002*
(0.001)
0.131***
(0.036)
0.144
(0.130)
-0.000
(0.001)
0.008
(0.005)
-0.014
(0.025)
0.001***
(0.000)
0.121***
(0.033)
0.129
(0.129)
0.000
(0.001)
LogRailways ∗ Trend
Sargan Test (p-value)
Kleibergen-Paap Test (p-value)
0.47
0.00
0.74
0.00
0.12
0.00
0.70
0.00
0.52
0.00
0.38
0.00
0.80
0.00
0.45
0.00
0.64
0.00
0.44
0.00
0.16
0.00
0.55
0.00
Department Fixed Effects
Year Fixed Effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
208
35
95.29
207
35
94.89
208
35
95.29
210
35
102.0
208
35
93.99
207
35
93.68
208
35
35.94
210
35
98.94
208
35
78.74
207
35
78.13
208
35
78.74
210
35
82.96
Observations
Number of id
F-test first Stage
Table: Specialization effects: IV estimates with interaction effects
(1)
Log Labor Force
(2)
Herfindahl Index
(3)
%LF in agriculture
(4)
%LF in non-agr primary
(5)
%LF in primary sectors
(6)
%LF in mfg
(7)
% LF in services
(8)
%LF in blue collar services
(9)
%LF in white collar services
0.119***
(0.036)
-0.000
(0.001)
0.008
(0.157)
-0.002
(0.005)
-0.000
(0.000)
0.035*
(0.018)
0.005
(0.006)
-0.000
(0.000)
0.067***
(0.026)
-0.003
(0.002)
0.000**
(0.000)
0.000
(0.009)
0.002
(0.005)
-0.000
(0.000)
0.068***
(0.025)
0.003
(0.004)
-0.000
(0.000)
-0.045**
(0.020)
-0.007*
(0.004)
0.000***
(0.000)
-0.004
(0.013)
-0.005
(0.004)
0.000**
(0.000)
0.011
(0.022)
-0.001
(0.002)
0.000*
(0.000)
-0.016
(0.016)
Sargan Test (p-value)
Kleibergen-Paap Test (p-value)
0.12
0.00
0.30
0.00
0.54
0.00
0.00
0.00
0.54
0.00
0.56
0.00
0.02
0.00
0.08
0.00
0.36
0.00
Department Fixed Effects
Year Fixed Effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
174
35
72.89
175
35
72.84
210
35
82.96
210
35
82.96
210
35
82.96
210
35
82.96
210
35
82.96
158
35
80.39
158
35
80.39
VARIABLES
Log Railways
LogRailways ∗ Trend
LogRailways ∗ LogRER
Observations
Number of id
F-test first Stage
Falsification Exercise
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
41 / 1
Table: Alternative explanations: IV estimates with interaction effects
(1)
%students in population
(2)
%teachers in LF
(3)
%public servants in population
(4)
%LF in transport
(5)
%LF in telegraphs
(6)
Log Foreigners
(7)
Log Nationals
(8)
%Foreigners in population
0.003
(0.002)
0.000
(0.000)
-0.002
(0.005)
-0.000
(0.000)
-0.000
(0.000)
-0.000
(0.000)
0.000
(0.001)
0.000
(0.000)
-0.004
(0.005)
-0.000
(0.000)
0.000***
(0.000)
-0.002
(0.001)
-0.000
(0.000)
0.000***
(0.000)
-0.000
(0.000)
0.099**
(0.046)
0.006***
(0.001)
0.039
(0.161)
0.125***
(0.033)
0.001
(0.001)
0.068
(0.108)
-0.001*
(0.001)
0.000***
(0.000)
-0.002
(0.002)
Sargan Test (p-value)
Kleibergen-Paap Test (p-value)
0.22
0.00
0.66
0.00
0.21
0.00
0.55
0.00
0.38
0.00
0.11
0.00
0.09
0.00
0.15
0.00
Department Fixed Effects
Year Fixed Effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
139
34
52.34
175
35
72.84
175
35
72.84
175
35
72.84
175
35
72.84
204
34
78.52
204
34
78.52
204
34
78.52
VARIABLES
Log railways
LogRailways ∗ Trend
LogRailways ∗ LogRER
Observations
Number of id
F-test first Stage
Conclusions and future research
• We document that access to railroads had a significant impact on
•
•
•
•
overall population on Chile’s southern departments
Specialization patterns, and effects on the rate of urbanization, can
only be seen when we take into account the relative price of tradables
and non-tradables
We find no evidence of a significant effect of railroads on human
capital accumulation, public goods (government services) or foreign
inmigration
These results are consistent with the predictions on migration and
location decisions of a regional trade model with interregional labor
mobility
An interesting venue to explore in the future deals with population
dynamics and the importance of the timing of access to railroads
Forero, Gallego, González, & Tapia ( PUC-Chile, PUC-Chile
Railroads
and
and
EHSpecialization
Clio Lab, UC Berkeley )
August 2014
43 / 1