Download The determinants of railway development in Latin America before

The determinants of railway development in Latin
America before 1914
Vincent Bignon*
Rui Esteves†
Alfonso Herranz-Loncán‡
Abstract
Railways were one of the main growth engines of Latin American economies during the
first globalization boom. This paper analyses which were the main determinants of
differences in railway development among Latin American countries, i.e. which factors
made some destinations more attractive than others for foreign investors. It tries to
ascertain if differences in railway expansion were mainly the consequence of
fundamental geographical characteristics or if institutional factors and financial
rationing dynamics had also a significant effect on each country’s degree of railway
development. The results of the analysis provide evidence in favour of a significant
impact of political instability and financial rationing on the pace of railway expansion in
each country. This might be taken as evidence that the first globalization constituted a
lost opportunity for some Latin American economies, which could not take advantage
of all their economic potential.
Very preliminary, please do not quote
*
Banque de France; email: [email protected]
Brasenose College, Oxford; email: [email protected]
‡
University of Barcelona; email: [email protected]
We thank Rodrigo Rivero and César Yáñez for sharing with us unpublished population data.
†
1
1. Introduction
Railways were one of the main growth engines of Latin American economies
during the first globalization boom. Their potential capacity to transform the economies
they served was probably much more important in that region than in the Western
European countries, where the railway technology had actually been developed, for two
reasons. Firstly, due to the almost total absence of transport infrastructure and the
scarcity of waterways in the region by the mid-nineteenth century, railways constituted
the only available way to connect most of the territory of those countries with the
international markets. Secondly, during the first globalization wave, Latin American
economies’ expansion was mainly based on natural resources exports and, therefore, the
growth potential of the region crucially depended on the spread of a good transport
system throughout the largest possible portion of the territory. As a consequence, in
those countries that built extensive railway networks during the first globalization,
export expansion and, therefore, GDP growth was closely linked to railway
development. This direct link allowed Summerhill (2006: 297) to suggest that it “(…)
seems unlikely that any other technological or institutional innovation was more
important in the transition to economic growth in Latin America before 1930”.
The crucial role of Latin American railways before 1914 has been confirmed, for
some countries, by the social saving literature. In Argentina (Summerhill, 2000;
Herranz-Loncán, 2011), Mexico (Coatsworth, 1979) and Brazil (Summerhill, 2003),
because of the lack of cheap transport alternatives, the railways provided social savings
amounting on average of ca. one quarter of total GDP by 1910-13. Social savings were
much lower in Uruguay (Herranz-Loncán, forthcoming), because the geography of this
country provided it with exceptional natural transport advantages, which made the
railways less indispensable. But, apart from this case, it seems that those Latin
American countries that built extensive railway networks before 1914 obtained huge
direct benefits from railway transport.
However, despite the high potential growth impact of the railways, in many
Latin American countries, railway development was sluggish and the final network
mileage was disappointingly low. Actually, apart from Mexico, Cuba, and the Southern
Cone countries (Chile, Argentina and Uruguay), no integrated national railway network
was constructed in Latin America and, in many countries, railways consisted just of a
few isolated lines running from some production areas to the ports. As a consequence,
the new infrastructure seems to have exerted a minor role in several Latin American
economies during the first globalization boom. For instance, in the case of Colombia,
the estimates of the social savings of railway freight transport in the late 1920s are just 3
to 8 percent of GDP (Ramírez, 2001), i.e. not higher than estimates for industrialized
economies in the late 19th century.
This paper looks into the potential reasons that may explain differences in
railway development among Latin American countries during the first globalization.
More specifically, given that most Latin American railway investment was financed by
foreign private capital, it aims at analyzing which factors made some destinations more
attractive than others for foreign investors. In this regard, decisions on the allocation of
investment might have responded to the profitability prospects of each line, which
depended in turn on the potential international demand of the specific natural resources
of each area, the potential sources of internal transport demand (such as population
2
density), or ruggedness and its effect on construction costs. However, they may also
have been influenced by the perceived degree of institutional instability of each country,
as well as by the existence of some kind of rationing of some countries by the financial
markets. The latter, in turn, might have had an informational origin (if, for instance, a
country was poorly included in the networks of international financial intermediaries),
or could be linked to other factors, such as previous defaults, or the financial
intermediary that dominated each country’s relationship with the international capital
markets (Clemens and Williamson, 2004; Haber, 1997; Marichal, 1989).
The answers to these questions are highly relevant to get a better understanding
of the reasons of the differential growth record of Latin American countries in a crucial
period of their economic development. As has been indicated, in many cases, a
sufficient endowment of transport infrastructure was an absolutely essential condition to
take advantage of the opportunities open by the international markets during the first
globalization. If the absence of railways was mainly the consequence of fundamental
geographical hindrances (such as bad relief, or the scarcity of valuable natural
resources), insufficient transport infrastructure would just be another dimension of some
countries’ bad luck in the commodity lottery of the late 19th century (Díaz Alejandro,
1984). If, by contrast, institutional factors and financial rationing dynamics had an
effect on the degree of railway development in each country, this might be taken as
evidence that the first globalization constituted a lost opportunity for some Latin
American economies and, more generally speaking, as an additional argument in favour
of the crucial role of institutions on long-term economic development.
We are not aware of any previous research on the factors explaining differences
in railway development among Latin American countries. The main antecedent of this
paper is Bogart (2009), which examines whether nationalizations reduced railway
mileage growth in a sample of 29 countries of all over the world between 1860 and
1912. In this paper, we take a similar approach, although with a different cross-section
and time sample, and considering a different potential set of determinants of railway
development.
The next section provides a very quick overview of the history of railway
expansion in Latin America before 1914; Section 3 presents an econometric model in
which we try to ascertain the influence of several factors on the dynamism of railway
construction in each economy; and finally Section 4 concludes.
2. Railway expansion in Latin America before 1914
By 1914 railways were present all over Latin America, although their
development had been highly unequal among countries. The first railway line in the
region was open in Cuba in 1837, only 12 years after the inauguration of the first British
railway. Cuba would not be joined by any other Latin American economy until the
1850s, when railway construction started slowly in Argentina, Brazil, Chile, Colombia,
Costa Rica, Mexico or Peru. By 1900, all countries of the region had some railways in
operation. Railway construction was especially intense in Argentina, Brazil and Mexico.
These countries accounted, since the late 1880s, for approximately 75 percent of the
whole Latin American railway mileage. However, in terms of railway density, they fell
behind some small Central American and Caribbean countries, as may be seen in Tables
3
1 and 2, due to their large surface area and the low settlement rates of some parts of
their territory.
Table 1. Railway mileage in Latin America (1890-1912) (km)
1890
1900
Argentina
9,254
16,767
Brazil
9,973
15,316
Mexico
9,718
13,585
Chile
2,747
4,354
Cuba
1,731
1,960
Peru
1,599
1,800
Uruguay
983
1,730
Bolivia
209
972
Colombia
358
644
Venezuela
454
858
Guatemala
186
640
Costa Rica
241
388
Ecuador
92
92
Paraguay
240
240
Puerto Rico
18
223
Nicaragua
143
225
El Salvador
87
116
Dominican R.
115
182
Honduras
96
96
Haiti
0
37
Panama
TOTAL
38,244
60,225
Source: See the Appendix.
Note: Panama is included within Colombia both in 1890 and in 1900.
1912
32,212
23,491
20,447
7,260
3,803
3,276
2,522
1,284
1,061
858
808
619
587
373
354
322
320
241
170
103
76
100,187
4
Table 2. Railway density in Latin America (1890-1912) (km per 100 km2)
1890
1900
1912
Puerto Rico
19.77
244.95
388.84
Cuba
151.90
171.99
333.72
Salvador
41.99
55.98
154.44
Uruguay
52.71
92.77
135.24
Costa Rica
46.53
74.90
119.50
Argentina
32.72
59.28
113.89
Chile
38.99
59.19
109.71
Mexico
49.31
68.93
103.74
Guatemala
17.10
58.83
74.28
Dominican R.
23.37
36.98
48.97
Haiti
0.00
12.99
36.15
Brazil
11.98
18.39
27.60
Nicaragua
11.04
17.37
24.86
Paraguay
14.95
14.95
23.23
Peru
12.76
12.68
23.08
Ecuador
3.23
3.23
20.60
Honduras
8.62
8.62
15.26
Colombia
2.56
5.16
10.34
Panama
10.12
Bolivia
1.24
6.39
9.93
Venezuela
4.25
9.41
9.41
WEIGHTED AV.
18.90
29.90
50.44
Source: See the Appendix.
Note: Panama is included within Colombia both in 1890 and in 1900.
Tables 1 and 2 may be taken as preliminary evidence of the different role that
railways performed in the growth of each Latin American economy before 1914.
Whereas some countries could benefit from relatively dense networks since an early
date, in other cases the expansion of the new infrastructure was extremely slow, and
railway systems were scarcely integrated, consisting mainly of a series of isolated lines
that connected production areas with the main ports, and hardly affecting large shares of
the territory of their countries.
In Latin America, railway capital and entrepreneurial initiative came from three
different origins: governments, domestic capitalists and foreign firms. The first two
sources were relatively important at the beginning of the period, but gradually lost
prominence. As a result, by 1899 governments owned just 16 percent and domestic
capital 13 percent of the total Latin American railway mileage. Public capital was
especially important in some Central American economies and in Chile, although its
presence was also significant in the railway systems of Colombia, Brazil and Argentina.
In some countries (especially in Central America), public railways, which were largely
financed through foreign debt, were used as a substitute for foreign private capital when
no foreign direct investment was received. By contrast, in large economies such as
Argentina and Chile, they were, to some extent, complementary to private undertakings,
being sometimes built in poor and distant regions, as an instrument of political
integration and with very low profitability prospects. As for domestic private capital, it
was especially present in Cuba (where it owned 40% of the network in 1899, but had
5
controlled almost 100% until the 1880s), Puerto Rico, Brazil and Venezuela (with
percentages of 20 to 30% in 1899), and also, to a certain extent, in Chile, and was
highly connected with certain export activities, such as Cuban sugar, Brazilian coffee,
or Chilean copper mining (Sanz Fernández, 1998).
However, by far the largest share of Latin American railway capital came from
foreign private investment, which entered the region both in the form of new
construction initiatives and through the taking over of public and private domestic
firms. The process of privatization of pre-existing public firms was very relevant in
some countries, such as Peru, where foreign capital bought a large percentage of public
railways in 1890, and it was also important in Argentina and Mexico in the closing
years of the 19th century. The relevance of foreign capital increased since the 1880s,
specially after the Baring crisis led to the failure of several local initiatives, such that
foreign enterprise ended up controlling almost 75% of the railway mileage in 1899, and
an even higher percentage (80 to 90%) in the years immediately before 1914. Among
foreign investors, British capital was absolutely dominant during the late 19th century,
accounting for 70% of foreign railway firms’ mileage in 1899. However, since 1900,
the importance of US capital grew rapidly, and it was especially relevant in the US
closest area of influence i.e. Mexico, the Caribbean and Central America (Sanz
Fernández, 1998).
Public subsidies appear to have been a condition for foreign capital to be
invested in Latin America. They took different forms, such as guarantees of interest
(often at 7% of invested capital), or a fixed amount per mile (as in the cases of Mexico
and Honduras). Apparently, when subsidies were absent or were eliminated (such as in
Venezuela in 1892), foreign capital disappeared completely. Railway subsidies
constituted a huge burden on Latin American countries’ public budgets, and their size
(relative to each State’s financial capabilities) often forced governments to renegotiate
them, and to look for additional sources of foreign capital in the form of public debt.
Latin American railway history has usually associated railway construction
waves in each country with both periods of institutional stability and the growth of
exports of one or several products of increasing world demand. This might help to
explain that, in most countries, significant construction only started in the 1870s, when
post-independence political turmoil substantially diminished, while world trade was
expanding rapidly. In this regard, the two main exceptions to late construction were
Cuba and Chile, which were among the most institutionally stable countries during the
post-independence period. Cuba, which remained linked to the Spanish Empire until
1898, was in fact one of the first countries to build railways, starting in 1837, and in
Chile construction was very active since the early 1850s. In both cases, primary exports
(sugar in Cuba, saltpetre in Chile) were essential to foster construction.
The link between railway development and export expansion was extremely
strong in the region, as may be seen in Figure 1. The close association between railway
density and export density is an obvious sign of the mutual causation between both
variables. Railway development allowed the exploitation of natural resources in the
inner areas of each country and the subsequent export expansion, whereas export
growth increased both state resources and the profitability prospects of private
investment. In this context, this work aims at ascertaining if this virtuous circle between
railway and export development (and therefore economic growth) was hindered in some
6
countries by factors not directly related to the economic potential of each economy,
such as political instability or some sort of financial rationing. In order to do this, in the
next section we analyse the determinants of railway density growth across the Latin
American countries in the half century before World War One.
Figure 1. Railway density and exports density in Latin American economies in
1913.
6
R² = 0,7873
5
ARG
Log railway density
MEX
CUB
SLV
URY
CRI
CHL
GTM
4
DOM
BRA
PER
NIC
ECU HND
PAR
3
COL
BOL
VEN
2
1
2
3
4
Log exports value / surface area (pounds per sq. km)
5
6
Source: See the Appendix.
3. The model
In this section we analyse the determinants of railway development in Latin
American countries through the estimation of a panel data model of railway mileage
expansion. The analysis is based on a rational expectations model of investment in Latin
American railways, which assumes that there was an ideal size for each country’s
railway network given a vector of geographic, economic, political and financial
variables. More specifically,
ܻ௧∗ = ߚ଴ + ߚଵ ܺ௧ + ߳௧
(1)
where Yt* is the ideal railway density (in logs) and Xt a vector of covariates. In this
context, the (public or private) investors would catch up each period with the desired
network size. In other words, the growth rate of railway density would be a fraction of
the gap between its ideal level and the density of the inherited network:
∗
ܻ௧ − ܻ௧ିଵ = ߜ(ܻ௧ିଵ
− ܻ௧ିଵ )
(2)
Replacing (2) in (1), we obtain the equation to estimate:
7
ܻ௧ − ܻ௧ିଵ = ߜߚ଴ − ߜܻ௧ିଵ + ߜߚଵ ܺ௧ିଵ + ߜ߳௧
(3)
Since we are interested in the coefficients of equation (1) (i.e. the relationships
between the covariates and the desired network density level), we may recover them as
β1=(δβ1)/δ.
Regarding the covariates, here we consider a number of economic, political and
financial variables. Among the former, we include population density and several
indicators of economic dynamism (exports pc, terms of trade and GDP per capita),
which are intended to approach the evolution of the profitability prospects of
investment.1 In addition, we also include the effective distance to the European
economies, under the assumption that cheaper access to the core markets would have
increased the latent demand for transportation in Latin America, to take advantage of
the easier access to international trade. Finally, railway density in the neighbouring
countries would account for possible “contagion effects” among countries, as well as
the possibility that incentives to build new lines increased with the availability of other
lines to connect with; and the square lagged dependent variable would account for the
possibility that railway network growth slowed down as the saturation point was closer.
As for the potential influence of political and institutional variables, we include
the incidence of wars, as well as the share of railways that were publicly owned in each
year. We consider the first one as representative for the degree of institutional
instability. This might have been a deterrent to railway investment, both directly (i.e.
through the lower friendliness of the business environment) and indirectly (because of
the difficulty to reach consensus on taxes and therefore to finance public subsidies to
private railway capital). In order to account for this double link, we also consider the
effect of government revenue per capita.2 As for the share of public railways, Bogart
(2009) observes, for a different sample of economies, that the fraction of miles
nationalised in each country between 1860 and 1912 had a negative effect on mileage
growth. This might be related to private investors fear that the government would
expropriate their investments, and also to the possibility that governments limited
network expansion after nationalisations, in order to increase its own profits from stateowned railways. However, the share of public railways might also be an indicator of the
State’s relative fiscal capacity (which might stimulate foreign capital imports),
especially in those cases in which public railways were the result of direct State’s
investment, rather than nationalisations.
Finally, we take into account several potential determinants of financial
rationing, such as the number of defaults in the previous years. According to both
historical and contemporary evidence, the corporate sector suffers a big penalty from
default in terms of lack of access to external finance (Bergquist, 1978; Arteta and Hale,
2008). In addition, some defaults might have been related to the use of public money to
subsidize unprofitable railways or even unscrupulous foreign railway promoters, which
1
Investment potential profitability would also be affected by other essentially time-invariant variables,
such as construction costs (largely dependent on geography, especially ruggedness), or the presence of
alternative cheap transport means (e.g. waterways). We assume these to be accounted for by country fixed
effects in the regression.
2
According to Flandreau and Zumer (2004), the main determinant of lending to countries was their
ability to repay the debt, which depended in turn on the debt burden per capita. However, data on the
volume of debt is very scarce, and in this paper we take the preliminary assumption that the ability to
repay the debt was determined by the level of government revenue per capita.
8
would be a deterrent for additional investment. As alternative financial variables, we
also include the level of spreads of the sovereign debt, and each country’s adherence to
the gold standard.
Lagged variables are dated 5 years before the dependent variable, in order to
account for the fact that railway construction took a long period to be completed since
the time of the investment decision.
Table 3 lists the results of the estimation of the model for the whole railway
system, and Table 4 presents the same results when the dependent variable is limited to
the growth of private railways. The first three columns in each table refer to the baseline
model, which only considers the potential economic determinants of railway
investment. Each of those columns considers a different indicator of each country’s
economic dynamism. Two of them (terms of trade and GDP pc) are only available for a
reduced number of countries. Therefore, the results are not totally comparable, since
they refer to different samples. Estimates are OLS with country fixed effects, and
standard errors are robust to the presence of serial correlation.
9
Table 3. The determinants of railway expansion in Latin American countries (1870-1913)
(1)
(2)
(3)
(4)
Constant
-0.886
-1.245
-5.072*** -1.433**
(0.665)
(1.225)
(0.955)
(0.697)
Log railway density (t-5)
-0.708*** -0.558*** -0.952*** -0.761***
(0.081)
(0.132)
(0.114)
(0.096)
Sq. log railway density (t-5)
-0.037
-0.026
-0.094***
-0.042*
(0.027)
(0.033)
(0.025)
(0.023)
Log pop. density (t-5)
0.789**
0.587
1.173***
0.949***
(0.353)
(0.466)
(0.280)
(0.337)
Log exports p.c. (t-5)
0.00001
-0.025
(0.046)
(0.045)
Terms of trade (t-5)
0.224
(0.183)
Log GDP pc (t-5)
0.713***
(0.149)
Log eff. distance (t-5)
-0.123
-0.171
-0.271**
-0.022
(0.171)
(0.115)
(0.117)
(0.166)
Log neighbouring countries’ rw density (t-5)
0.009
-0.008
0.184
-0.055
(0.114)
(0.151)
(0.133)
(0.119)
No. of years with war (t-5 to t-9)
-0.050**
(0.020)
Share of public railways (t-5)
0.002
(0.002)
Log government revenues pc (t-5)
No. of defaults (t-5 to t-9)
(5)
0.108
(0.542)
-0.855***
(0.088)
-0.071***
(0.018)
1.263***
(0.254)
-0.049
(0.040)
(6)
-1.239*
(0.679)
-0.752***
(0.095)
-0.042*
(0.023)
0.963***
(0.337)
-0.049
(0.046)
(7)
-0.219
(0.365)
-0.835***
(0.093)
-0.047***
(0.016)
0.844***
(0.250)
-0.048
(0.030)
(8)
-0.701
(0.488)
-0.797***
(0.118)
-0.028
(0.025)
0.931***
(0.350)
-0.046
(0.031)
(9)
-0.137
(0.340)
-0.883***
(0.088)
-0.050***
(0.015)
0.871***
(0.245)
-0.033
(0.032)
-0.099
(0.121)
0.047
(0.093)
-0.037**
(0.017)
0.0002
(0.002)
0.294***
(0.046)
-0.093
(0.166)
-0.026
(0.120)
-0.046**
(0.020)
0.002
(0.002)
-0.306***
(0.111)
0.053
(0.083)
-0.063***
(0.014)
-0.001
(0.002)
-0.140
(0.136)
0.035
(0.136)
-0.070***
(0.018)
0.003
(0.002)
-0.314***
(0.111)
0.038
(0.085)
-0.057***
(0.013)
-0.003
(0.002)
-0.033*
(0.019)
-0.023
(0.021)
Spread (t-5)
-0.0001***
-0.0001**
(0.00004)
(0.00004)
Years in gold standard between t-5 and t-9
-0.030
-0.049***
(0.026)
(0.018)
Time trend
0.021**
0.015
0.008
0.026***
0.012*
0.021**
0.019***
0.017**
0.023***
(0.009)
(0.010)
(0.008)
(0.008)
(0.007)
(0.009)
(0.005)
(0.008)
(0.006)
Country fixed effects
YES
YES
YES
YES
YES
YES
YES
YES
YES
N
469
348
226
389
347
389
238
269
238
Nº countries included
18
8
9
18
18
18
7
8
7
Adj. R2
0.576
0.558
0.775
0.664
0.706
0.674
0.798
0.780
0.816
Notes: i) Dependent variable: growth in log railway density between t-5 and t; ii) standard errors in brackets. *** Significant at the 1% level; ** Significant at the 5% level; * Significant at the
10% level.
10
Table 4. The determinants of private railway expansion in Latin American countries (1870-1913)
(1)
(2)
(3)
(4)
(5)
Constant
-0.937
-1.728*
-6.136*** -1.946**
-0.334
(0.825)
(1.017)
(0.949)
(0.793)
(0.733)
Log railway density (t-5)
-0.778*** -0.809*** -1.017*** -0.833*** -0.911***
(0.123)
(0.135)
(0.143)
(0.110)
(0.113)
Sq. log railway density (t-5)
-0.066**
-0.061**
-0.097**
-0.049** -0.081***
(0.028)
(0.028)
(0.038)
(0.022)
(0.021)
Log pop. density (t-5)
1.111***
1.171***
1.410***
1.390***
1.637***
(0.395)
(0.401)
(0.362)
(0.345)
(0.328)
Log exports p.c. (t-5)
-0.016
-0.065
-0.050
(0.056)
(0.048)
(0.047)
Terms of trade (t-5)
0.262
(0.171)
Log GDP pc (t-5)
0.890***
(0.186)
Log eff. distance (t-5)
-0.224
-0.308
-0.354
-0.247
-0.364*
(0.250)
(0.235)
(0.284)
(0.218)
(0.188)
Log neighbouring countries’ rw density (t-5)
0.010
-0.012
0.239
-0.137
-0.046
(0.106)
(0.118)
(0.157)
(0.120)
(0.126)
No. of years with war (t-5 to t-9)
-0.082*** -0.070***
(0.021)
(0.021)
Share of public railways (t-5)
0.010***
0.008***
(0.002)
(0.003)
Log government revenues pc (t-5)
0.234***
(0.060)
No. of defaults (t-5 to t-9)
(6)
-1.836**
(0.773)
-0.833***
(0.109)
-0.050**
(0.022)
1.415***
(0.353)
-0.073
(0.049)
(7)
-0.598
(0.525)
-0.887***
(0.121)
-0.058***
(0.018)
1.450***
(0.337)
-0.078*
(0.041)
(8)
-1.080**
(0.501)
-0.910***
(0.123)
-0.049**
(0.019)
1.485***
(0.338)
-0.058
(0.036)
(9)
-0.582
(0.453)
-0.938***
(0.118)
-0.061***
(0.016)
1.452***
(0.325)
-0.056
(0.043)
-0.292
(0.212)
-0.114
(0.125)
-0.080***
(0.021)
0.010***
(0.002)
-0.645***
(0.182)
-0.065
(0.126)
-0.105***
(0.018)
0.011***
(0.002)
-0.440***
(0.158)
-0.088
(0.139)
-0.104***
(0.017)
0.013***
(0.002)
-0.604***
(0.187)
-0.100
(0.133)
-0.098***
(0.015)
0.010***
(0.029)
-0.020
(0.023)
-0.011
(0.029)
Spread (t-5)
-0.0001**
-0.0001
(0.00004)
(0.00005)
Years in gold standard between t-5 and t-9
-0.053** -0.067***
(0.025)
(0.023)
Time trend
0.019*
0.020**
-0.0004
0.014*
0.015*
0.023***
0.015**
0.022***
0.024***
(0.010)
(0.010)
(0.012)
(0.007)
(0.009)
(0.009)
(0.007)
(0.008)
(0.008)
Country fixed effects
YES
YES
YES
YES
YES
YES
YES
YES
YES
N
378
301
213
359
328
365
238
269
238
Nº countries included
18
8
9
18
18
18
7
8
7
Adj. R2
0.546
0.587
0.703
0.671
0.673
0.673
0.743
0.781
0.765
Notes: i) Dependent variable: growth in log railway density between t-5 and t; ii) standard errors in brackets. *** Significant at the 1% level; ** Significant at the 5% level; * Significant at the
10% level.
11
The inherited railway density (Yt-1 in equation 3) is always significant and has
the right sign, and the lagged square of railway density also has always a negative
(albeit sometimes non-significant) effect on railway density growth, which would be
consistent with the gradual deceleration of railway construction as the saturation point is
approached. As for the coefficient of population density, it is always positive and
significant, except for column (2) of Table 3. By contrast, the economic dynamism
indicators are rarely significant. This might indicate that, broadly speaking, railways
tended to precede the expansion of the economy rather than the other way around,
which is consistent with the idea that the new transport infrastructure was a necessary
condition for the extensive exploitation of a large share of the region’s natural
resources. Finally, the reduction in the effective distance to the core markets also seems
to have stimulated Latin American railway investment throughout the first globalisation,
although its coefficient is not significant in many cases. By contrast, we find no sign of
a significant contagion effect across countries.
Columns 4 to 9 of each table incorporate the political and financial variables. To
make the exposition short, we only show the results of the regressions that include
exports per capita as the indicator of economic development. However, the outcomes of
the estimation using the other two variables are very similar. The results indicate that
political instability (approached through the incidence of internal or international wars)
was clearly detrimental to railway expansion. As has been indicated, this might reflect
both the direct effect of institutional stability and its indirect impact through the
difficulty to reach consensus on taxes and therefore to repay the debt and finance public
subsidies to private railway capital. In this regard, when government revenue per capita
is included in the regression it has a clearly positive and significant effect, and the
coefficient of the incidence of wars is reduced. As for the influence of the share of
public railways, whereas it seems to have been immaterial for the development of the
whole railway network, in Table 4 it appears to have been beneficial from the point of
view of the attraction of private investment. This result is not necessarily in
contradiction with Bogart (2009). Actually, it might be just the consequence of the
relative high importance of public railways in some countries of the region at the
beginning of the period under study, and its slow growth or its privatisation as time
went by. Therefore, this might not be reflecting the influence of nationalisations on
private decision making, but a change in the ownership structure of some railway
networks of the region.
Finally, columns 6 to 9 present the result of the estimation of the model with
some financial variables. The coefficient on the number of previous defaults is negative
but rarely significant. By contrast, evidence in favour of the influence of the spreads on
sovereign debt over railway investors’ decisions seems to be stronger. And, finally,
opposite to what might be expected, each country’s previous adherence to the gold
standard appears to have been negative from the viewpoint of railway expansion. In this
context, it seems that financial risk would be better captured by spreads, whereas the
negative sign of the adherence to gold might be interpreted in terms of the efforts made
by each country to belong to the “gold club”. For a not so rich country, these would
involve fiscal conservatism, in a context in which the growth of the network until its
“ideal” level was dependent on the presence of public subsidies.
12
4. Conclusions
This paper provides a very preliminary approach to the potential determinants of
railway expansion in Latin American countries. The results are necessarily provisional.
The rate of railway density growth seems to have had a non-linear relationship with
network mileage, slowing down as this approached its saturation point. In addition,
railway density growth was directly related with the demographic evolution of each
country, but does not seem to have reacted to changes in exports dynamism, which
would be consistent with railways being constructed ahead of demand.
On the other hand, we found strong evidence in favour of the influence of
institutional instability on railway expansion, both directly and through its effects on
each country’s fiscal position. Finally, the results of our analysis indicate that the
development of the different railway systems might have been affected by financial
rationing, and that railway density growth might have been hindered in those countries
with a highest spreads on sovereign debt. Given the importance of railways for the
economic development of Latin American countries during the first globalisation boom,
this might be taken as preliminary evidence that some of the economies of the region
could not fully benefit from the export boom due to the difficulty to access to
international capital markets for financing its basic infrastructure.
Appendix: data sources
Railway data
Yearly railway mileage has been taken from Mitchell (2003), except in the
following cases: Argentina (from Dirección General de Ferrocarriles, Estadística de los
ferrocarriles en explotación, 1892-1913); Chile before 1870 (own estimation from
Marín Vicuña, 1901, and Alliende Edwards, 1993); and Uruguay (own estimation from
the country’s statistical yearbooks). The length of public railways has been taken from
Sanz Fernández (1998); gaps between close or very similar observations have been
filled through interpolation.
Population and pcGDP
Population figures have been taken from recent research by Rivero (2011), who
has carried out a critical joint revision of the different available demographic datasets
for Latin America (mainly Maddison, 2003; Mitchell, 2003; and the MOxLAD and
ECLAC databases); in the case of Bolivia, we have used our own figures (see HerranzLoncán and Peres-Cajías, 2011). GDP per capita comes from Maddison (2003), except
in the case of Bolivia (our own data; see Herranz-Loncán and Peres-Cajías, 2011).
Effective distance to the core markets
We estimated effective distance following Clemens and Williamson (2004)’s
procedure, i.e. we coded this variable as the product of a measure of geographic
distance and an index of cost of shipping between each country and the main European
trading partners. For most countries, geographical distance has been taken as the prePanama canal distance between the main port of each country and London or Hamburg,
13
as listed in Philip (1914). For the majority of nations we have used the index of tramp
shipping freight charges from Isserlis (1938: 122), with base year 1869 = 100.
Exports, government revenues and exchange rates
Foreign trade statistics in local currency were were mainly obtained from
Mitchell (2003) with the following exceptions. Brazil from Motta et al. (1990); Chile
from Wagner et al. (2000); and Mexico from INEGI (2009) and El Colégio de Mexico
(1960). Total government revenue, in local currency units were obtained from
Accominotti et al. (2011) for the period 1880-1913. For the earlier period or countries
not covered in this database, information was gathered from the following sources.
Argentina from Cortes Conde (1989); Brazil from Motta et al. (1990) and several issues
of the Brazilian budget laws; Chile from Wagner et al. (2000) and the Sinópsis
Estadística (1918); Colombia from Mitchell (2003) and Kalmanovitz (2010); Mexico
from El Colégio de Mexico (1960), Wilkie (1967) and Mitchell (2003); Peru from
Mitchell (2003) and Tantaléan Arbulú (1983); and Uruguay from Millot and Bertino
(1996, 2005) and the Uruguayan Statistical Yearbooks. The majority of the exchange
rate (local currency units per pound sterling) data comes from the compilation by
Schneider et al. (1911) or Accominotti et al. (2011) with the following exceptions.
Argentina from Cortes Conde (1989); Brazil from Motta et al. (1990); Colombia from
Ocampo (1984) and the MOxLAD database at http://oxlad.qeh.ox.ac.uk/; Cuba from the
MOxLAD database.
Terms of trade
Given that the UK was by far the main trading partner of Latin American
countries throughout the period under analysis, for each country we have used the ratio
between a trade-weighted index of commodity export prices and an index of UK export
prices, as compiled by Christopher Blattman (see Blattman et al., 2007).
Defaults, spreads and adherence to gold standard
Defaults were coded from Esteves (2007b) and Suter (1990); spreads over
British consols use mostly four sources: Accominotti et al. (2011), Ferguson and
Schularick (2006), Esteves (2007b) and Clemens and Williamson (2004); and adherence
to gold standard has been taken from Accominotti et al. (2011), Meissner (2005) and
Esteves (2007a).
Wars
The number of internal and international wars that affected each country has
been compiled from the Correlates of War database (we have incorporated the
independence wars of Cuba and Puerto Rico).
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