going o the rails: the e ect of railroad abandonments on...

Going Off the Rails: The Effect of Railroad Abandonments on

Population and Industrial Decline ∗

Dustin Frye†

Vassar College

February 19, 2018

Abstract

The paper exploits the abandonment of American railroads over the twentieth century to studythe impact of reductions in transportation infrastructure on population and industrial growth. Usingnewly digitized spatial data on the location and timing of railroad abandonments, I find that com-munities with more severe reductions in railroads experienced declines in population, urbanization,and manufacturing. There is also suggestive evidence of declines in wholesale trade, retail trade,and agricultural property values. These declines persist despite investments in highway infrastruc-ture. These findings reaffirm the importance of transportation networks for economic development.Despite their long-run presence, the removal of railroads was able to upset the spatial distributionof economic activity, suggesting that continued investment and improvements in infrastructure areimportant for maintaining the growth benefits of transit infrastructure.

Keywords: Railroad Abandonment,

JEL Classification:

∗I would like to thank Jacob Sowder for excellent research assistance. All errors are my own.†Department of Economics, Vassar College, 124 Raymond Ave, Box 76, Poughkeepsie, NY 12604 (e-mail:

[email protected]; website: http://pages.vassar.edu/dustinfrye/ )

1 Introduction

The expansion of railroads transformed the landscape of trade and travel in the nineteenth and

early twentieth centuries, resulting in over 250,000 miles of track by 1916. Following this high-water

mark in railroad mileage, competition, changing economic conditions, and deregulation contributed

to the steady abandonment of railroad mileage. Despite being the leading method of shipping high

volume goods within the US, over 40 percent of railroad miles were abandoned during the 20th

century. These abandonments introduced a potentially substantial shock for rail reliant locations

and industries. This article exploits this substantial reduction in infrastructure and examines the

impact of railroad abandonment on population and the economic conditions in five industries:

agriculture, manufacturing, retail trade, services, and wholesale trade.

Railroads were a key contributor to the spatial arrangement of both population and industry

throughout the nineteenth and early twentieth centuries (Atack, et al., 2010; Atack, Haines, &

Margo, 2008; Atack & Margo, 2012). The abandonment of rail lines provide a setting to understand

the fragility of these spatial equilibria to negative shocks in infrastructure and market access.

Additionally, abandonments were more severe in less populated, rural counties, potentially removing

a valuable channel of access to larger outside markets. This reduction in market access directly

affects traded sectors and a decline in those sectors could have negative spillover effects to the rest

of the local economy. Taken together, these effects would likely exacerbate regional differences in

economic growth between urban and rural areas.

Using county-level data from the Censuses of Agriculture and Population from 1910 to 1990 and

the County Business Patterns from 1947 to 1994, the empirical specifications use newly digitized

locations and dates of railroad abandonments to estimate the effect of increased abandonments

on county-level outcomes. To address the endogeneity regarding selection into abandonment, this

paper exploits techniques in graph theory to measure railway network importance. This technique

establishes the most unnecessary segments for travel and therefore the most likely segments of

railroad for abandonment, which I use to instrument for actual abandoned segments.

Preliminary estimates indicate railroad abandonment led to a consistent pattern of decline

in population and industry after accounting for differences in population trends, geography, and

access to alternative forms of transit infrastructure. A county experiencing the average level of

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abandonment saw population fall by 4.71 percent. This same county also experienced industrial

decline. The declines were most severe and consistent in manufacturing, which experienced a 4.67

percent reduction in the number of manufacturing firms and an 8.37 percent decline in the value

added of manufactured goods. Abandonments led to slightly weaker declines in retail trade, services,

wholesale trade, and agricultural property values. These declines are more severe in places with

fewer miles of substitutable highway infrastructure, suggesting that a reduction in market access is

partially responsible for the declines.

Despite the large literature devoted to understanding the benefits of expanding transportation

infrastructure, very little is known about the potential effects of removing infrastructure. In Ghana,

the neglect of colonial railroads did not alter the spatial equilibrium that developed following

construction (Jedwab & Moradi, 2016). The authors propose that the lack of developed cities

created a stronger environment for railroads to create persistent local returns to scale, thereby

creating a suitable environment for a persistent spatial equilibrium to develop around railroads. The

relative level of development, fluidity of capital and labor markets, and availability of alternative

locations in the United States likely explains the difference in persistence across settings. During a

similar period to the US, Britain instituted a series of cutbacks to rail financing, an event commonly

referred to as the ‘Beeching Axe’. These cuts reduced mileage by over 41 percent and there is still

uncertainty to how these reductions impacted rural Britain (Loft, 2013).

More broadly this paper contributes to our understanding of the conditions under which per-

sistent historic spatial equilibriums can change. There is a large literature documenting the im-

portance of increasing returns to scale in promoting persistent effects brought about by historical

shocks (Ahlfeldt et al., 2015; Bleakley & Lin, 2012; Bosker et al., 2007, 2008; Kline & Moretti, 2014;

Michaels & Rauch, 2016; Redding, Sturm, & Wolff, 2011). My preliminary findings suggest that

transit infrastructure and market access are important components for maintaining agglomeration

due to increasing returns to scale and after removing infrastructure or decreasing access to mar-

kets, the channels promoting agglomeration can be undermined. My setting is similar to the case

of German reunification, where Redding & Sturm (2008) find evidence that reunifying Germany

altered market access and reversed the persistent differences in population growth across regions in

former West Germany. My paper highlights a similar reversal brought about by the abandonment

of infrastructure.

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This paper also relates to the broader literature on the employment effects of transportation

infrastructure.1 The American railroad literature has primarily focused on the era of railroad

expansion or the more recent period post-deregulation. Early American railways promoted changes

in agriculture, property values, manufacturing, banking, trade, and structural change (Atack &

Margo, 2012; Atack et al., 2010; Atack, Jaremski & Rousseau, 2014; Donaldson & Hornbeck, 2016;

Fogel 1964; Fajgelbaum & Redding, 2014). More recent work has focused on price discrimination

and pricing behavior following deregulation (Busse & Keohane, 2007; Ellig, 2002; Hughes, 2011).

This paper bridges the gap between those two eras. It also overlaps with the period of interstate

highway expansion. Interstate expansion led to increases and changes in the locations of employ-

ment, both overall and by sector (Chandra & Thompson, 2000; Duranton, Morrow, & Turner 2014;

Duranton & Turner 2012; Frye, 2017; Michaels, 2008). I find that the abandonment of railway net-

works has a similar, although inverse, effect. Additionally, I find that the negative affects of railroad

abandonment are more severe in the absence of highways, suggesting that railroad abandonment

and highway expansion offset through a similar mechanism.

Railways were of similar importance to historic development outside of the American setting.

Jedwab & Moradi (2016) document persistent benefits for colonial railways in Africa. Indian railway

expansion produced substantial benefits to trade, income, and welfare (Donaldson, 2010). In Ger-

many, railroad development promoted manufacturing, industrialization, and economic integration

(Gutberlet, 2014; Walker, 2015). My paper speaks to how these industrial developments continue

to evolve as the railway ages and alternative forms of transportation develop.

The paper proceeds as follows. Section 2 provides a brief overview of railroad history and the

process of railway abandonments. Section 3 discusses the data. Section 4 introduces the empirical

strategy and addresses the endogeneity concerns. Section 5 presents the major findings, and Section

7 concludes.

1For a recent survey of this literature see Redding & Turner (2015).

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2 Historical Background

2.1 Railroad Expansion and Decline

Railroad expansion dates back to the early 1800s, but the first major wave followed the federal gov-

ernment’s opening of land grant subsidies in 1850. This era of construction was largely decentralized

and the network was mostly constructed by entrepreneurial investors (White, 2011). Following the

Civil War, the federal government became increasingly involved in developing a transcontinental

railroad. Through the Pacific Railway Act of 1862 it reinstated land grant subsidies and instituted

a system of loans that varied based on construction costs. In the land grant process, railroad

companies were given blocks of public land along the proposed routes. This policy incentivized

speculation and building ahead of demand as railway companies competed to secure land rights.

This led to massive expansion in the railroad network. Between 1860 and 1880, over 100,000 miles

of railroad track were constructed (Fishlow, 1965; Fishlow, 2000). Growth slowed in the 1890s and

shifted to the Midwest where agricultural traffic boosted profits. By the turn of the century total

railroad mileage exceeded 190,000 miles and railroads continued as the primary mode of trans-

portation. Railroad mileage peaked in 1916 with over 250,000 miles of track. Despite the sustained

expansion in mileage, the number of railroad companies actually fell over time as regulation and

financial panics contributed to the consolidation of the industry.

In 1887, Congress passed the Interstate Commerce Act and created the Interstate Commerce

Commission (ICC), which established early railroad regulations targeting rates and discrimination

(Stone & Landry, 2012). The Transportation Act of 1920 expanded the regulatory arm of the ICC

to cover entry, exit, rates, and service. This act formalized the process of railroad abandonment.

Prior to 1930, the abandonment of rail lines was overwhelmingly driven by the exhaustion of natural

resources (Weissman, 1958). By the early 1930s, the primary cause shifted to non-rail competition

and insufficient traffic (Weissman, 1958).

2.2 Railroad Legislation and Abandonments

The Transportation Act of 1920 required railroad companies to apply for abandonment. The

ICC weighed the potential losses by railroad companies against the losses to the shippers and

communities from the loss of the line (GAO, 1976). A key consideration for the Commission

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was the availability of alternative forms of transit. Between 1920 and 1963, over 90 percent of

abandonment applications were approved, partly because railroad companies only submitted cases

with a high probability of success (Due, 1978). From 1920 to 1972, the ICC approved an average

of 1,023 miles per year of abandonments, totaling over 53,000 miles. Despite these abandonments,

railroad companies, especially those in the Northeast, were still facing financial hardship due to

increased competition from highways and air travel and ICC regulation.

Congress introduced several measures during the 1970s to alleviate the financial burdens of rail

companies, including relaxing abandonment regulations. Passenger travel had steadily declined

and in 1970 Congress created Amtrak to alleviate the burden of passenger travel. In the mid-1970s

Congress passed the 3R Act of 1973 and the 4R Act of 1976 aimed to accelerate the abandonment

process.2 Deregulation of railroads started with the Staggers Rail Act of 1980 and was expanded

with the Northeast Rail Service Act of 1981. These acts reduced the role of the ICC and allow

carriers to abandon lines more freely. The early 1980s saw a sharp increase in the number of

abandonment applications and total mileage of abandonment. By 1987, over 88,000 miles of track

had been abandoned, roughly 35 percent of the 1916 peak mileage.

3 Data Construction and Description

3.1 Data Construction

Historic county-level data are drawn from the Census of Population and the County Business

Patterns (Haines, 2010). The main variables of interest are population, population in urban areas,

and economic indicators across five industries: agriculture, manufacturing, retail trade, services,

and wholesale trade. The industrial variables include the number of establishments, employment,

payrolls, and measures of the value of output, including sales and value added in the case of

manufacturing. Table 1 provides summary statistics for the full sample of each outcome. The

number of observations vary across outcomes as the availability depends on the data collection and

suppression to maintain confidentiality. Table 2 lists the source document, year of interest, and

2The formal names for the two acts are the Regional Rail Reorganization Act of 1973 and the Railroad Revital-ization and Regulatory Reform Act fo 1976. For a survey of their legal features see Due (1978).

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the number of observations available.3 The empirical analysis focuses on an unbalanced panel of

counties, from 1910 to 1990, for which data is available across multiple years. The final sample is

restricted to exclude counties that did not have railroads in 1916, counties in Alaska and Hawaii,

and counties that had substantive county border changes between 1920 and 1990.4

Figure 1 maps the national system of railways at near peak mileage in 1916 (Atack, 2016).

Railroad abandonment information comes from a series of maps and tables created by Waldo Nielsen

(1992). The maps and tables include information about each railroad abandonment prior to 1992

including the start and end points for each abandoned segment and a date range of abandonment. I

digitized these maps and used contemporary and historic maps to match the start and end points of

each segment. I then isolated the segments from the original Atack 1916 map that were eventually

abandoned. I cross-referenced Nielsen’s date and location information with published railroad

maps that span the period. Figure 2 maps the full railroad network split by eventual abandonment

status in 1987. Figure 3 maps only the set of abandoned railroad segments. In general, the spatial

distribution of abandonments is consistent with overbuilding in the midwest and northeast, but

every state experienced some degree of abandonment.

My primary measure of abandonment intensity is the share of 1916 railroad lines that were

abandoned in a county. I use the date information from Nielsen and additional railroad maps to

measure the abandonment intensity at different points in time. Nielsen’s date information is limited

to six date ranges between 1939 and 1987.5 I create both a discrete and smoothed abandonment

measure. The discrete measure only attributes track as abandoned in the final year of the date

range. The smoothed measure assumes abandonment occurred linearly over the date range.6 My

preferred specification uses the discrete measure as it is likely to underestimate the true effect of

railroad abandonment by understating the degree of abandonment that actually occurred.7

Table 1 shows the average level of abandonment across the entire period and the average level of

abandonment in 1987. By the end of the sample period, the average county in the sample lost about

3In future drafts I will add some analysis to understand the characteristics of these omitted counties, and how, ifat all, they might impact the main findings.

4The empirical models control for 1920 population, so counties without population measures in 1920 are alsoexcluded from the analysis.

5The dates are before 1939, 1940 - 1944, 1945 - 1959, 1960 - 1971, 1972 - 1984, and 1984 - 1987. I am currentlyin the process of collecting more refined segment abandonment information from ICC annual reports.

6For the period prior to 1939, I assume abandonments started in 1920.7When I compare the smoothed model to the discrete model the OLS estimates are consistent with this assumption.

6

33 percent of it’s railroad mileage, with some counties not losing any and others abandoning the

railroad completely. Figure 4 maps these final abandonment shares. Abandonments are spatially

distributed with some clustering in western New York, the upper midwest, and western Colorado.

The baseline Atack 1916 railroad file contains information about the operation dates of each rail

line. Figure 5 plots the distribution of the first known operation dates for the set of abandoned

lines and the full sample of rail lines. The distribution of abandoned lines is consistent with the

distribution of overall rail lines.

Table 3 reports summary statistics for each outcome in the first period I observe the outcome,

split by the mean fraction of abandonment. Counties with higher eventual shares of abandonment

were more economic developed in the early periods. High abandonment counties were smaller in

population, less urbanized, and were less developed across all industry measures.

3.2 Trends Relative to Abandonment

Figures 6 through 11 plot each outcome of interest relative to the date of each counties first

abandonment. Each plot shows the mean residual of the outcome variable after de-trending by

state and year. Across the outcomes, the figures show a striking relationship relative to the date

of the first abandonment. Importantly, prior to abandonment the outcomes are either steady or

increasing. From Figure 6, both population and the percent of the population living in urban areas

show a sharp decline following abandonment. A similar trend develops across the manufacturing

outcomes in Figure 7, the services outcomes in Figure 8, the wholesale trade outcomes in Figure

9, and the retail trade outcomes in Figure 10. The agricultural outcomes in Figure 11 appear

to be the exception, with the downward trend in the amount of acreage under cultivation and

average property value per acre starting several years in advance of railroad abandonment. These

provide some suggestive evidence that railroad abandonments negatively impacted communities in

the decades after abandonment.

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4 Empirical Framework

4.1 Baseline Specification

To estimate the effect of railroad abandonment on population and industry outcomes, I exploit

variation in the severity of railroad abandonment across locations and over time. Outcome Y in

county c and year t is regressed on the fraction of railroad that was abandoned at time t, a vector

of geographic and demographic controls, X, state-by-year effects, and county fixed-effects:

Yct = βRRAbandShrct + δst + γc +X ′ρct + εct (1)

The specifications control for several time invariant geographic characteristics and baseline pre-

abandonment measures. These time invariant controls are interacted with year-dummy variables to

flexibly control for these covariates over time. The identifying assumption is that, if not for railroad

abandonment, counties with abandoned rail would have changed similarly to non-abandoned coun-

ties in the same state and year and with similar geographic and pre-abandonment characteristics.

The bottom panel of Table 1 lists the key covariates of interest. Controlling for initial railroad

mileage flexibly accounts for the degree of initial overbuilding and speculation that occurred prior

to abandonment. Controlling for distance from county centroid to the closest MSA helps account

for potential differences in the probability of abandonment at different distances from major cities.

County areas differ substantially by region, with the southwest having larger counties on average.

Controlling for county area helps account for differential trends in population and industrial move-

ment to larger counties, which often had less abandonment. County centroid latitude and longitude

controls allow for spatial patterns in economic changes that may be correlated with abandonment.

The model controls for three types of highway infrastructure, two time-invariant measures of major

highway mileage and time varying county level measures of interstate highway mileage. These con-

trols are potentially endogenous as highways are often used as a form of stimulus for lagging areas

(Frye, 2017; Jaworski & Kitchens 2017). Particularly in the case of interstate highways, regions

that were more negatively affected by abandoned lines might be more likely to receive or be near

an interstate in the future. The substitution between railroads and highways was a fundamental

part of the abandonment of railroads that it is a useful control despite the potential endogeneity

8

concerns. In Section 6, I show the results without the interstate highway control. Finally, control-

ling for population in 1920 allows for the impact of pre-treatment population levels to vary over

time.8

4.2 Endogeneity Concerns and Network Centrality

Measuring differences between counties with abandoned and non-abandoned segments of rail will

likely result in biased estimates because segments of track selected for abandonment are likely

correlated with unobserved time varying characteristics that are correlated with both demographic

changes and industry growth. Railroad companies were selecting their segments based on both

current and expected future profitability. The motives for their selection and the willingness of

the ICC to grant an abandonment permit create an endogeneity problem that the controls cannot

account for.

To address this issue I use an application from graph theory to predict a set of underutilized seg-

ments of the railroad that would be ideal candidates for abandonment. Once I have this pseudo-set

of abandonment locations, I can calculate a predicted share of abandonment to use as an instru-

mental variable. To identify underutilized segments, I calculate the edge betweenness centrality for

the 1916 railroad network similar to Frye (2017). The process converts the 1916 railway network

into a mathematical network of nodes and edges and weights each edge by distance. Nodes occur at

the intersection of each two edges or at the endpoint of an edge. I use Brandes’s (2008) algorithm

to calculate the betweenness centrality of each edge. The betweenness centrality value indicates

the number of times that particular edge was used when traveling using the shortest path between

every two pairs of nodes in the network. Higher betweenness centrality values are travel more

frequently. I identify the lowest 25 percent of betweenness centrality values as the set of segments

that will be abandoned.9 Figure 10 plots the set of predicted abandonments.

Once I have a set of candidates for abandonment I assume that segments were abandoned

according to their betweenness centrality value, so the lowest centrality value would be abandoned

first. I rank the centrality values, and “abandon” an equal percentage of mileage each year between

8I have altered the year and number of population controls and the results are extremely stable.9The 25 percent cutoff is arbitrary, however it matches closely in mileage to the actual eventual mileage that was

abandoned. In future drafts I plan on testing the sensitivity to this threshold.

9

1939 and 1990.10 This gives me a predicted amount of mileage each year that varies by county. I

then use this to calculate a predicted share of abandonment, which I use to instrument for actual

abandonment shares.

Figure 12 plots the flow of abandonments and predicted flow of abandonments over time. The

predicted flow of abandonments is consistently higher because it is a mechanically smoothed process

from 1939 to 1990, whereas actual abandonments move variably with the legislative eras. The figure

illustrates the sharp increase in abandonments after deregulation in 1980. Table 3 illustrates the

fraction of the instances where the predicted shares are below the actual shares, are equal to the

actual shares, and are less than the actual shares in each year. Consistent with Figure 12, the

predicted shares are consistently higher in early periods, but the IV generates predicted values

that are both above and below the actual values in each period. Figure 13 shows the actual and

predicted distributions of both the distance abandoned and the share abandoned. The distributions

of both measures are very similar.

4.3 Defending Network Centrality

The validity of the instrument hinges on the degree that edge betweenness centrality of the railroad

network is orthogonal to changes in population and industry over the twentieth century. One source

of variation in railroad centrality is driven by the connectedness of the graph. By controlling for the

number of railroad intersections in the county, I account for the number of available shortest paths

originating in the county, junctions where shortest paths could change direction in the county, and

potential growth that could occur around the intersections.

Low betweenness values are primarily driven by redundancies and under-traveled spurs in the

network. Redundancies are more likely in places with excessive overbuilding. One concern is that

these places experienced an unusual boom in construction due to some persistent process and

this process is correlated with changes after railroad abandonment. Given the history of railroad

expansion and subsidies, railroad expansion was largely motivated by land speculation and railroad

entrepreneurs were focused on short-term gains. The speculative motives of railroad entrepreneurs

in the late-nineteenth century is unlikely to directly affect population changes, except through the

channel of potentially redundant lines, which is a key source of the variation in the instrument.

10I have also adjusted the date range to begin in 1920 and the results are similar.

10

Additionally, the nature and structure of the US economy changed dramatically from the late-

nineteenth century to the mid-twentieth century. Late arriving rail line developers were interested

in income from shipping agricultural products. One concern is that rail line network betweenness

is simply measuring areas developed for the quality of their agricultural land. To address this

concern, I control for agricultural suitability.

5 Main Results

5.1 Population and Urbanization

Table 4 reports estimated declines in population and the percent of population living in urban

areas when estimating equation 1 and including the full set of controls. The table also reports first-

stage results and the mean and standard deviation of the treatment variable. The population and

urbanization results indicate that the abandonment of railroads led to a sharp decline in population

and urbanization. Results from the instrumental variable specification indicate that a one standard

deviation increase in railroad abandonment led to an 8.16 percent decline in population. These

population declines appear to target urban areas, with populations over 2500 people. Following a

similar one standard deviation increase in abandonment, the percent of the population living in

urban areas fell by 8.94 percentage points. Railroad abandonment is correlated with lower initial

levels of population, indicating that these population declines are most likely affecting small and

medium sized urban centers.

5.2 Industrial Growth

Table 5 reports changes to the manufacturing and wholesale traded sectors following abandonment.

Manufacturing experienced the sharpest declines in the number of establishments and manufactur-

ing value added. A one standard deviation increase in abandonment is associated with a 14.5

percent reduction in the value added of manufactured goods. Counties that lost all of their rail-

roads would be expected to lose over 65 percent of the value added of their manufactured goods

compared to a county that retained all of it’s rail lines. Changes in wholesale trade tell a similar

story in the magnitude of declines for both the number of establishments and the value of total

sales, although the later is not statistically distinguishable from zero. Taken together these results

11

suggest traded sectors faced sharp declines following the abandonment of railroads.

Estimated changes in the agricultural sector, given in Table 6, suggest that the number of

farms and acreage under cultivation were unaffected by railroad abandonment. However, the value

of farm property per acre fell by over 9 percent following a one standard deviation increase in

abandonments. The estimated effects of abandonment on the service sector suggest similar declines

to those in wholesale trade. Table 7 reports the estimated impact of abandonment for retail trade.

The results suggest potentially small declines in the number of firms, employment, and total payroll.

However, there are much larger declines in the value of total sales, where a one standard deviation

increase in abandonments led to a 13.6 percent decline.

6 Robustness

6.1 Excluding Interstate Highway Controls

Table 8 reproduces the OLS and IV results with the full set of covariates from Table 4. Columns 3

and 4 exclude interstate highway mileage from the set of covariates. As expected, the OLS estimates

become larger in magnitude, consistent with interstate mileage being positively associated with

growth. However, the IV estimates also become larger. Indicating that interstate highway mileage

is correlated with railroad centrality. Given that railroad locations have been used to instrument

for interstate highway connections, it is likely that the centrality of highways is correlated with the

centrality of railroads (Duranton, Morrow, & Turner, 2014; Duranton & Turner, 2012). Given this

correlation, controlling for interstate highway mileage seems important for the IV estimation.

7 Conclusion

The process of structural transformation, characterized by the transition of workers into increas-

ingly productive and skilled occupations, requires modern technology that can support the changes.

As the US transitioned from a largely agrarian and small manufacturing economy to a more ad-

vanced manufacturing and service based economy it required transportation infrastructure that

could support changing industrial development. This modernization led to a transition in the over-

land transportation networks, shifting away from railroads towards highways and air travel. These

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changes resulted in the abandonment of over 88,000 miles of rail lines during the mid-twentieth

century. These abandonments changed the economic conditions in formerly connected areas, de-

creasing population, urbanization, and industrial growth across several industries.

These findings reaffirm the importance of transportation networks for economic development.

Despite their long-run presence, the removal of railroads was able to upset the spatial distribution

of economic activity, suggesting that continued investment and improvements in infrastructure are

important for maintaining the growth benefits of transit infrastructure.

13

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16

8 Figures

Figure 1: National Railroad Map

17

Figure 2: National Railroad Map by Abandonment Status

Figure 3: Abandoned Railroads

18

Figure 4: Share of Abandoned Railroad

Figure 5: Distribution of Dates of Operation for Rail Lines

0.0

5.1

.15

Dens

ity

1820 1840 1860 1880 1900 1920Date of Operation

Abandoned Lines

0.0

5.1

.15

Dens

ity

1820 1840 1860 1880 1900 1920Date of Operation

All Lines

19

Figure 6: Population

-150

00-1

0000

-500

00

5000

1000

0Po

pula

tion

-75 -50 -25 0 25 50Years Relative to First Abandonment

(a) Total Population

-2-1

01

2Pc

t. Po

p in

Urb

an A

reas


(b) Pct. Urban Population

20

Figure 7: Manufacturing

-40

-20

020

40M

anuf

actu

ring

Esta

blis

hmen

ts


(a) Establishments

-200

0-1

000

010

0020

00M

anuf

actu

ring

Empl

oym

ent


(b) Employment

-150

-100

-50

050

100

Man

ufac

turin

g Va

lue

Adde

d ('0

00s)


(c) Value Added

21

Figure 8: Services

-150

-100

-50

050

Serv

ice

Esta

blis

hmen

ts


(a) Establishments

-150

0-1

000

-500

050

0Se

rvic

e Em

ploy

men

t


(b) Employment

-60

-40

-20

020

Serv

ice

Payr

oll (

'000

s)


(c) Total Payroll

22

Figure 9: Wholesale Trade

-40

-20

020

40W

hole

sale

Est

ablis

hmen

ts


(a) Establishments

-100

0-5

000

500

Who

lesa

le E

mpl

oym

ent


(b) Employment

-600

-400

-200

020

040

0W

hole

sale

Sal

es ('

000s

)


(c) Total Sales

23

Figure 10: Retail Trade

-100

-50

050

100

Ret

ail S

tore

s


(a) Establishments

-100

0-5

000

500

Ret

ail E

mpl

oym

ent


(b) Employment

-150

-100

-50

050

Ret

ail S

ales

('00

0s)


(c) Total Sales

-20

-10

010

Ret

ail P

ayro

ll ('0

00s)


(d) Total Payroll

24

Figure 11: Agriculture

-200

-100

010

020

0N

umbe

r of F

arm

s


(a) Total Farms

-15

-10

-50

510

Acre

age

in F

arm

ing

('000

s)


(b) Total Acreage

-600

-400

-200

020

0To

tal F

arm

Val

ue P

er A

cre


(c) Farm Value Per Acre

25

Figure 12: Predicted Location of Abandoned Railroads

Figure 13: Railroad Abandonment vs. Predicted Railroad Abandonment Over Time

010

2030

40

1900 1920 1940 1960 1980 2000year

Pct. RR Abandoned Predicted Pct. RR Abandoned

26

Figure 14: Distribution of Railroad Abandonment and Predicted Abandonment

0.0

1.0

2.0

3.0

4D

ensi

ty

0 100 200 300 400RR Abandoned (km)

05

1015

Den

sity

0 .2 .4 .6 .8 1Pct. RR Abandoned

0.0

05.0

1.0

15.0

2.0

25D

ensi

ty

0 100 200 300 400 500Predicted RR Abandoned (km)

02

46

810

Den

sity

0 .2 .4 .6 .8 1Predicted Pct. RR Abandoned

27

9 Tables

28

going o the rails: the e ect of railroad abandonments on...

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