Railroads, Reallocation, and the Rise of American Manufacturing. Richard Hornbeck, Martin Rotemberg. NBER Working Paper No. 26594, December 2019. https://www.nber.org/papers/w26594
Program: We examine impacts of market integration on the development of American manufacturing, as railroads expanded through the latter half of the 19th century. Using new county-by-industry data from the Census of Manufactures, we estimate substantial impacts on manufacturing productivity from relative increases in county market access as railroads expanded. In particular, the railroads increased economic activity in marginally productive counties. Allowing for the presence of factor misallocation generates much larger aggregate economic gains from the railroads than previous estimates. Our estimates highlight how broadly-used infrastructure or technologies can have much larger economic impacts when there are inefficiencies in the economy.
VI Interpretation
We estimate that the railroads substantially increased the scale of the United States’ economy: increasing the production and use of materials, spurring increased capital investment,
and encouraging population growth. The economic consequences of this expansion are substantially greater than previously considered because, in most counties, the value marginal
products of materials, capital, and labor were greater than their marginal costs. We do not
estimate that railroads reduced these market distortions, whether due to firm markups or
input frictions, but the railroads generated substantial economic gains by encouraging the
expansion of an economy with market distortions.
We calculate that aggregate productivity would have been 25% lower in 1890 in the
absence of the railroads, through declines in reallocative efficiency alone. We assume that
technical efficiency would have been unchanged in the counterfactuals, but this decline in
reallocative efficiency is equivalent to a 25% decline in technical efficiency (or total factor
productivity, TFP). It is challenging to estimate aggregate TFP growth, with the proper
price deflators, but estimates suggest that annual TFP growth was approximately 0.37%
from 1855 to 1890 and 1.24% from 1890 to 1927 (Abramovitz and David, 1973). That is,
the railroads effectively contributed 31 years worth of technological innovation, by driving
increases in reallocative efficiency.79
The railroads’ 25% impact on productivity was worth 25% of GDP in 1890, or $3 billion
in 1890 dollars. As a comparison, the estimated cost of the railroad network in 1890 was $8
billion (Adams, 1895). We estimate that the railroads generated an annual private return
of 3.5% in 1890,80 which increases to an annual social return of 7.5% – 8.3% once including
estimates from Fogel (1964) or Donaldson and Hornbeck (2016) and increases to 43% when
also including our estimated impact on productivity.81 These estimates imply that the
railroad sector was capturing roughly 8% of its social return in 1890.
Our estimated increases in productivity do not include the direct benefits of the railroads
from decreasing resources spent on transportation. To see this, consider that we would mechanically estimate no impact on productivity from the railroads if there were no differences
between value marginal product and marginal cost, whereas the economy would still benefit
through decreases in transportation costs. In our model, those decreases in transportation
costs are capitalized into higher land values.
Donaldson and Hornbeck (2016) estimate that agricultural land values would have fallen
by 60% without the railroad network, which, multiplying by an interest rate, generates
annual economic losses equal to 3.2% of GDP. The total loss of all agricultural land would
only generate annual economic losses equal to 5.35% of GDP, so an analysis of agricultural
land values could never find larger economic impacts.82
The crucial difference in our approaches is that Donaldson and Hornbeck (2016) assume
an efficient economy, in which value marginal product is equal to marginal cost, such that all
output value is paid to factors. By contrast, our estimated increases in reallocative efficiency
reflect the creation of output value that is not paid to factors. In both of our analyses, the
railroads increase the scale of the US economy, but because we allow for the marginal value
of product to exceed marginal costs, this increase in economic activity generates surplus
or “profit” that is reflected in aggregate productivity growth rather than increases in land
values. Further, our estimated impacts on productivity do not include any economic gains
reflected in increased factor payments, and so our estimated impact on productivity is in
addition to impacts on land value.
A general implication for measuring economic incidence is that factor payments do not
include all economic gains when there are market distortions. More inelastically supplied
factors will bear more economic incidence, but there are additional economic gains that are
not captured by factor payments. We show that these additional economic gains can be
substantively large, particularly when new infrastructure investment or new technologies are
broadly used and encourage broad expansion of economic activity.
The additional economic gains, from decreasing resources spent on transportation, could
instead be measured directly by calculating the decreases in transportation costs using the
railroads instead of the waterways. This is precisely the social savings calculation in Fogel
(1964), which implies that our estimated impact on productivity is in addition to Fogel’s
estimate of 2.7% of GDP.
In considering why Fogel’s estimates do not include our estimated economic gains, we
highlight the importance of resource misallocation in welfare analysis more generally. Fogel
(1964) proposes a social savings calculation to bound the economic gains from the railroads.
Fogel focuses on the transportation sector, and looks to calculate the additional cost from
using waterways to transport goods instead of the railroads. This calculation is closely
related to aggregate productivity in the transportation sector, measured as revenue minus
costs: for transporting the same quantity of goods (fixing revenue), calculating the increase
in costs without the railroads.83
David (1969) critiques Fogel’s calculations on several grounds, but much of this critique
is essentially calling attention to Fogel’s implicit assumption that value marginal product is
equal to marginal cost.84 This assumption is required for the increase in transportation costs
without the railroads to equal the value lost from decreased production in non-transportation
sectors. David (1969) proposes that this assumption would be violated by increasing returns
to scale, and Fogel (1979) responds by disputing the empirical magnitude of increasing
returns to scale.85 Fogel (1979) also makes this assumption more explicit: that in nontransportation sectors, firms’ value marginal product is equal to their marginal cost.
Our analysis relaxes this assumption, and estimates the economic consequences from
a broader range of market distortions, which restates the above critique by David (1969).
Rather than appealing to increasing returns to scale, we allow for a wide variety of distortions that can drive a wedge between the social benefit and private cost of firms expanding
production (e.g., firm markups, credit constraints, taxes and regulation, imperfect property
rights).86 The railroads decrease transportation costs, effectively subsidizing the expansion
of economic activities throughout the economy that have a positive social return (i.e., whose
value marginal product exceeds their marginal cost).
Fogel (1964, 1979) emphasizes that assuming an inelastic demand for transportation
provides an upper bound estimate on the railroads’ impacts, for the social savings calculation,
but the opposite is true in the presence of market distortions. A greater elasticity of demand
for transportation magnifies the economic impacts of the railroads by yielding greater changes
in activities whose value marginal product exceeds marginal cost across other sectors in the
economy. Fogel does not consider the indirect losses in other sectors due to reductions in
transported goods, because he aims to calculate the costs of maintaining the same levels of
transportation, but it is precisely because transportation would fall that there are such large
indirect losses in other sectors.87
More generally, there is an analogous need to consider resource misallocation in partial
equilibrium welfare analysis. Harberger (1964) lays the foundation for much welfare analysis
in economics, using the example of calculating the economic cost of a tax, making a powerful
assumption that there are no other distortions in the economy. This assumption means that
it is not necessary to consider how a marginal tax affects other activities, which reflect
only small welfare “triangles,” and the welfare effects of the tax are largely captured by the
demand curve for the taxed activity.88 Harberger (1964) makes this assumption clear, and
notes that it probably has the effect of understating the true cost of a tax, but this assumption
is often overlooked in applications due to its substantial analytical convenience.89 In Fogel’s
application, when analyzing the impacts of a higher transportation cost (similar to a higher
tax), the demand curve for transported goods is used to capture the welfare effects, and the
mistake is to not consider impacts from resulting changes in other activities.
Our estimated impacts of the railroads are a reminder that indirect effects on other
economic activities can generate substantial economic benefits, which are missed in partial
equilibrium welfare analysis. When there is resource misallocation, such as due to firm
markups or capital constraints, and other activities are under-provided then there are firstorder welfare gains from their encouragement. Only in a special case, when there are no
market distortions and other economic activities are efficient, can we invoke the envelope
theorem and consider only the direct economic effects
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