Does the flow of financing respond to changes in productive opportunities even for the world's poor? We answer this question by examining the response of private bank financing to a shock to the rural road network in India, which brought road access to hitherto unconnected villagers. http://iems.ust.hk/roads

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Roads and Loans
Sumit Agarwal, Abhiroop Mukherjee and S. Lakshmi Naaraayanan
March 7, 2018
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Roadmap
1 Overview
2 Background and Data
3 Main Results
4 Distributional Effects
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Motivation: Finance and Productivity Changes
When productive opportunities improve, financing should flow to
those who see gains
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Motivation: Finance and Productivity Changes
When productive opportunities improve, financing should flow to
those who see gains
But does private, profit-motivated financing really respond to
productivity changes?
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Motivation: Finance and Productivity Changes
When productive opportunities improve, financing should flow to
those who see gains
But does private, profit-motivated financing really respond to
productivity changes?
not just for the large corporations or households in countries with
developed financial markets –
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Motivation: Finance and Productivity Changes
When productive opportunities improve, financing should flow to
those who see gains
But does private, profit-motivated financing really respond to
productivity changes?
not just for the large corporations or households in countries with
developed financial markets –
but also in the day-to-day lives of the world’s poor?
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Motivation: Finance and Productivity Changes
We shed new light on this issue by focusing on a large rural
road-building initiative in India
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New Roads Everywhere
In many parts of the world, infrastructure projects are thought to be
key to unlocking productivity increases
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New Roads Everywhere
In many parts of the world, infrastructure projects are thought to be
key to unlocking productivity increases
e.g., Storeygard(2014), Aggarwal (2015), Donaldson(2016),
Shamdasani (2016), Asher and Novosad (2017)
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New Roads Everywhere
In many parts of the world, infrastructure projects are thought to be
key to unlocking productivity increases
e.g., Storeygard(2014), Aggarwal (2015), Donaldson(2016),
Shamdasani (2016), Asher and Novosad (2017)
Roads are particularly topical
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New Roads Everywhere
In many parts of the world, infrastructure projects are thought to be
key to unlocking productivity increases
e.g., Storeygard(2014), Aggarwal (2015), Donaldson(2016),
Shamdasani (2016), Asher and Novosad (2017)
Roads are particularly topical
Tremendous growth in roads in Asia, Africa, South America, and
Eastern Europe in the past 20 years alone
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New Roads Everywhere
In many parts of the world, infrastructure projects are thought to be
key to unlocking productivity increases
e.g., Storeygard(2014), Aggarwal (2015), Donaldson(2016),
Shamdasani (2016), Asher and Novosad (2017)
Roads are particularly topical
Tremendous growth in roads in Asia, Africa, South America, and
Eastern Europe in the past 20 years alone
China’s trillion dollar ‘Belt and Road Initiative’ – “the biggest
investment project in history”
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New Roads Everywhere
In many parts of the world, infrastructure projects are thought to be
key to unlocking productivity increases
e.g., Storeygard(2014), Aggarwal (2015), Donaldson(2016),
Shamdasani (2016), Asher and Novosad (2017)
Roads are particularly topical
Tremendous growth in roads in Asia, Africa, South America, and
Eastern Europe in the past 20 years alone
China’s trillion dollar ‘Belt and Road Initiative’ – “the biggest
investment project in history”
India built 1.96 million kilometers of rural roads between 2000-2016
connecting 100s of millions
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Roads to Growth?
How are roads meant to create productive opportunities for people
connected?
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Roads to Growth?
How are roads meant to create productive opportunities for people
connected?
opening or expansion of small businesses, like village grocery shops
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Roads to Growth?
How are roads meant to create productive opportunities for people
connected?
opening or expansion of small businesses, like village grocery shops
allowing surplus agricultural laborers to commute to nearby towns to
access more productive jobs
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Roads to Growth?
How are roads meant to create productive opportunities for people
connected?
opening or expansion of small businesses, like village grocery shops
allowing surplus agricultural laborers to commute to nearby towns to
access more productive jobs
changing crop patterns from subsistence cereal farming to more
profitable market-based crops
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Roads to Growth?
Many of these channels, however, require availability of financing
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Roads to Growth?
Many of these channels, however, require availability of financing
Typically assumed that such financing to households will automatically
follow once roads are built
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Roads to Growth?
Many of these channels, however, require availability of financing
Typically assumed that such financing to households will automatically
follow once roads are built
But many rural economies suffer from chronic problems of financing
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Roads to Growth?
Many of these channels, however, require availability of financing
Typically assumed that such financing to households will automatically
follow once roads are built
But many rural economies suffer from chronic problems of financing
Formal finance is largely absent in many parts of the world
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Roads to Growth?
Many of these channels, however, require availability of financing
Typically assumed that such financing to households will automatically
follow once roads are built
But many rural economies suffer from chronic problems of financing
Formal finance is largely absent in many parts of the world
Informal money lenders charge usurious interest rates, tying down
laborers to dismal conditions
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Roads and Finance
Central question today in finance for emerging markets
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Roads and Finance
Central question today in finance for emerging markets
Will traditional private sector financing respond to changing productive
opportunities created by these mega infrastructure projects?
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Roads and Finance
Central question today in finance for emerging markets
Will traditional private sector financing respond to changing productive
opportunities created by these mega infrastructure projects?
Outside of very limited microfinance wings, private banks typically do
not lend to rural households, ticket sizes are small
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Roads and Finance
Central question today in finance for emerging markets
Will traditional private sector financing respond to changing productive
opportunities created by these mega infrastructure projects?
Outside of very limited microfinance wings, private banks typically do
not lend to rural households, ticket sizes are small
But massive market sizes and growth rates of the rural sector in
emerging economies has piqued interest recently
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Roads and Finance
Why do we care?
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Roads and Finance
Why do we care?
If private financing does NOT respond:
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Roads and Finance
Why do we care?
If private financing does NOT respond:
governments will have to provide financing to rural households on top
of financing roads
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Roads and Finance
Why do we care?
If private financing does NOT respond:
governments will have to provide financing to rural households on top
of financing roads
If private financing DOES respond:
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Roads and Finance
Why do we care?
If private financing does NOT respond:
governments will have to provide financing to rural households on top
of financing roads
If private financing DOES respond:
room for private sector financing can mean less fiscal pressure, easier
path to benefits percolating down
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Roads and Finance
Why do we care?
If private financing does NOT respond:
governments will have to provide financing to rural households on top
of financing roads
If private financing DOES respond:
room for private sector financing can mean less fiscal pressure, easier
path to benefits percolating down
Relates to literature on the role of financing in development
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Roads and Finance
Why do we care?
If private financing does NOT respond:
governments will have to provide financing to rural households on top
of financing roads
If private financing DOES respond:
room for private sector financing can mean less fiscal pressure, easier
path to benefits percolating down
Relates to literature on the role of financing in development
King and Levine (1993), Black and Strahan (2002), Burgess and Pande
(2004), Levine (2005), Beck, Demirguc-Kunt and Peria (2007),
Demirguc-Kunt and Levine (2008), Beck (2012), Demirguc-Kunt,
Feyen, and Levine (2013)
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Roads and Finance
Distributional Effects
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Roads and Finance
Distributional Effects
If private financing does respond, who does it benefit more?
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Roads and Finance
Distributional Effects
If private financing does respond, who does it benefit more?
Richer villagers who had access to finance before roads, and might be
in a better position to exploit new opportunities?
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Roads and Finance
Distributional Effects
If private financing does respond, who does it benefit more?
Richer villagers who had access to finance before roads, and might be
in a better position to exploit new opportunities?
Or the poor – people who were excluded from formal finance, but can
now find a way in?
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Roads and Finance
Distributional Effects
If private financing does respond, who does it benefit more?
Richer villagers who had access to finance before roads, and might be
in a better position to exploit new opportunities?
Or the poor – people who were excluded from formal finance, but can
now find a way in?
Will roads increase – or reduce – inequality?
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Main Challenge
Difficult to accurately identify the impact of new infrastructure
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Main Challenge
Difficult to accurately identify the impact of new infrastructure
Hard to identify an appropriate counterfactual or comparison group
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Main Challenge
Difficult to accurately identify the impact of new infrastructure
Hard to identify an appropriate counterfactual or comparison group
What would have happened if roads were not built where they got
built?
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Main Challenge
Difficult to accurately identify the impact of new infrastructure
Hard to identify an appropriate counterfactual or comparison group
What would have happened if roads were not built where they got
built?
We can observe what happens before and after new infrastructure is
constructed in ‘treated’ areas
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Main Challenge
Difficult to accurately identify the impact of new infrastructure
Hard to identify an appropriate counterfactual or comparison group
What would have happened if roads were not built where they got
built?
We can observe what happens before and after new infrastructure is
constructed in ‘treated’ areas
But incorrect to attribute the change exclusively to roads – maybe
policy is to help a region: roads and financing are both a result of that
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Main Challenge
Difficult to accurately identify the impact of new infrastructure
Hard to identify an appropriate counterfactual or comparison group
What would have happened if roads were not built where they got
built?
We can observe what happens before and after new infrastructure is
constructed in ‘treated’ areas
But incorrect to attribute the change exclusively to roads – maybe
policy is to help a region: roads and financing are both a result of that
Could be solved if we could find 2 identical villages, one that –
randomly – gets a road, the other does not
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How we progress
Exploit conditions surrounding India’s Pradhan Mantri Gram Sadak
Yojna (PMGSY)
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How we progress
Exploit conditions surrounding India’s Pradhan Mantri Gram Sadak
Yojna (PMGSY)
Objective was to provide all-weather road connectivity to hitherto
unconnected villages
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How we progress
Exploit conditions surrounding India’s Pradhan Mantri Gram Sadak
Yojna (PMGSY)
Objective was to provide all-weather road connectivity to hitherto
unconnected villages
Aggarwal (2015) and Shamdasani (2016)
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How we progress
Exploit conditions surrounding India’s Pradhan Mantri Gram Sadak
Yojna (PMGSY)
Objective was to provide all-weather road connectivity to hitherto
unconnected villages
Aggarwal (2015) and Shamdasani (2016)
Program explicitly prioritized building new roads to connect all
villages above explicit population thresholds
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How we progress
Exploit conditions surrounding India’s Pradhan Mantri Gram Sadak
Yojna (PMGSY)
Objective was to provide all-weather road connectivity to hitherto
unconnected villages
Aggarwal (2015) and Shamdasani (2016)
Program explicitly prioritized building new roads to connect all
villages above explicit population thresholds
E.g., villages with populations just above key round figures, 1000 and
500, were to be prioritized under the program.
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How we progress
Exploit conditions surrounding India’s Pradhan Mantri Gram Sadak
Yojna (PMGSY)
Objective was to provide all-weather road connectivity to hitherto
unconnected villages
Aggarwal (2015) and Shamdasani (2016)
Program explicitly prioritized building new roads to connect all
villages above explicit population thresholds
E.g., villages with populations just above key round figures, 1000 and
500, were to be prioritized under the program.
Assuming a village with populations just below the threshold, say
population 480, is very similar to one just above, say population 520 –
if one has a road and the other does not, this is almost random
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How we progress
Exploit conditions surrounding India’s Pradhan Mantri Gram Sadak
Yojna (PMGSY)
Objective was to provide all-weather road connectivity to hitherto
unconnected villages
Aggarwal (2015) and Shamdasani (2016)
Program explicitly prioritized building new roads to connect all
villages above explicit population thresholds
E.g., villages with populations just above key round figures, 1000 and
500, were to be prioritized under the program.
Assuming a village with populations just below the threshold, say
population 480, is very similar to one just above, say population 520 –
if one has a road and the other does not, this is almost random
Allows us to identify the effect of roads better
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Population-based Cutoffs for Road Building
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Summary Results
We find large financing responses to rural road connectivity
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Summary Results
We find large financing responses to rural road connectivity
In villages right above the population cutoff
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Summary Results
We find large financing responses to rural road connectivity
In villages right above the population cutoff
over 50% more villagers receive loans
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Summary Results
We find large financing responses to rural road connectivity
In villages right above the population cutoff
over 50% more villagers receive loans
average amount lent to them is 20-40% higher
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Summary Results
We find large financing responses to rural road connectivity
In villages right above the population cutoff
over 50% more villagers receive loans
average amount lent to them is 20-40% higher
Roads seem to disproportionately benefit
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Summary Results
We find large financing responses to rural road connectivity
In villages right above the population cutoff
over 50% more villagers receive loans
average amount lent to them is 20-40% higher
Roads seem to disproportionately benefit
villagers who lack collateralizable assets
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Summary Results
We find large financing responses to rural road connectivity
In villages right above the population cutoff
over 50% more villagers receive loans
average amount lent to them is 20-40% higher
Roads seem to disproportionately benefit
villagers who lack collateralizable assets
lower caste villagers with basic education
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Roadmap
1 Overview
2 Background and Data
3 Main Results
4 Distributional Effects
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Does being above the population cutoff really predict road
construction?
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Does being above the population cutoff really predict road
construction?
An average Ganjam village right above the population cutoff is
23-28% more likely to get a road than one right below
Even higher differences in our bank loan sample
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No evidence of population manipulation
Population figures from 2001 census – before PMGSY policy cutoffs
announced
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No differences in other village characteristics around cutoff
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Financing: Data
Proprietary loan-level dataset from one of India’s largest private
lenders
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Financing: Data
Proprietary loan-level dataset from one of India’s largest private
lenders
loans made to villagers in the largely rural district of Ganjam in the
eastern state of Odisha
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Financing: Data
Proprietary loan-level dataset from one of India’s largest private
lenders
loans made to villagers in the largely rural district of Ganjam in the
eastern state of Odisha
Detailed information on loans made, purpose of loan, maturity,
repayment behavior, and borrower characteristics
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Financing: Data
Proprietary loan-level dataset from one of India’s largest private
lenders
loans made to villagers in the largely rural district of Ganjam in the
eastern state of Odisha
Detailed information on loans made, purpose of loan, maturity,
repayment behavior, and borrower characteristics
Supplemented by data from PMGSY and Census websites, carefully
hand-matched
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Bank presence in Ganjam
Sample villages within population range (+/-200) in very close proximity
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Data Summary
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Empirical Methodology
Compare various financing-related outcomes for villagers in above
cutoff villages, relative to below
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Empirical Methodology
Compare various financing-related outcomes for villagers in above
cutoff villages, relative to below
All villages were unconnected when the bank started operations in our
district
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Empirical Methodology
Compare various financing-related outcomes for villagers in above
cutoff villages, relative to below
All villages were unconnected when the bank started operations in our
district
Most of the above-cutoff ones received roads before the end of our
sample; most of the below-cutoff ones did not
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Empirical Methodology
Compare various financing-related outcomes for villagers in above
cutoff villages, relative to below
All villages were unconnected when the bank started operations in our
district
Most of the above-cutoff ones received roads before the end of our
sample; most of the below-cutoff ones did not
Key idea:
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75. 23/38
Empirical Methodology
Compare various financing-related outcomes for villagers in above
cutoff villages, relative to below
All villages were unconnected when the bank started operations in our
district
Most of the above-cutoff ones received roads before the end of our
sample; most of the below-cutoff ones did not
Key idea:
Villagers in above cutoff villages are very similar to those below
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Empirical Methodology
Compare various financing-related outcomes for villagers in above
cutoff villages, relative to below
All villages were unconnected when the bank started operations in our
district
Most of the above-cutoff ones received roads before the end of our
sample; most of the below-cutoff ones did not
Key idea:
Villagers in above cutoff villages are very similar to those below
EXCEPT that they are much more likely to have received a road in the
recent past
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77. 23/38
Empirical Methodology
Compare various financing-related outcomes for villagers in above
cutoff villages, relative to below
All villages were unconnected when the bank started operations in our
district
Most of the above-cutoff ones received roads before the end of our
sample; most of the below-cutoff ones did not
Key idea:
Villagers in above cutoff villages are very similar to those below
EXCEPT that they are much more likely to have received a road in the
recent past
Note that we will not exploit the exact timing of road construction, since
that is still likely endogenous
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Roadmap
1 Overview
2 Background and Data
3 Main Results
4 Distributional Effects
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Extensive Margin
Number of people who get loans substantially higher above population
cutoff
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Intensive Margin: Loan Amounts
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Intensive Margin: Loan Amounts
Loan amounts substantially higher as well
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Intensive Margin: Loan Amounts
Loan amounts substantially higher as well
loans made to villagers in above-cutoff villages about 20% higher
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Intensive Margin: Loan Amounts
Loan amounts substantially higher as well
loans made to villagers in above-cutoff villages about 20% higher
As a percentage of borrower income, magnitude of this difference close
to 40%
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Intensive Margin: Loan Amounts
Loan amounts substantially higher as well
loans made to villagers in above-cutoff villages about 20% higher
As a percentage of borrower income, magnitude of this difference close
to 40%
Note that since we have bank data, we can control for all borrower
characteristics that the bank cares about and collects information on
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Other Loan Characteristics
No substantial difference in other loan features:
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Other Loan Characteristics
No substantial difference in other loan features:
Maturity
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Other Loan Characteristics
No substantial difference in other loan features:
Maturity
Interest rates
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Other Loan Characteristics
No substantial difference in other loan features:
Maturity
Interest rates
Default behavior
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Other Loan Characteristics
No substantial difference in other loan features:
Maturity
Interest rates
Default behavior
Indicates loans not riskier or less profitable – consistent with
connectivity expanding profitable lending opportunities
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Loan Types
We can differentiate between types of loans made, based on use
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Loan Types
We can differentiate between types of loans made, based on use
Productive loans are crop loans, micro-enterprise loans for village
shops, or those that are meant for business expansion, asset
acquisition, and working capital needs
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 29 / 38

92. 29/38
Loan Types
We can differentiate between types of loans made, based on use
Productive loans are crop loans, micro-enterprise loans for village
shops, or those that are meant for business expansion, asset
acquisition, and working capital needs
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 29 / 38

93. 29/38
Loan Types
We can differentiate between types of loans made, based on use
Productive loans are crop loans, micro-enterprise loans for village
shops, or those that are meant for business expansion, asset
acquisition, and working capital needs
Non-productive loans are those meant for consumption needs, marriage
and festival expenses
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 29 / 38

94. 30/38
Loan Types
Difference comes entirely from productive loans
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 30 / 38

95. 30/38
Loan Types
Difference comes entirely from productive loans
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 30 / 38

96. 30/38
Loan Types
Difference comes entirely from productive loans
Within productive loans, crop and micro-enterprise loans account for
the largest differences
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 30 / 38

97. 30/38
Loan Types
Difference comes entirely from productive loans
Within productive loans, crop and micro-enterprise loans account for
the largest differences
Non-productive Loans are actually lower in above cut-off villages
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 30 / 38

98. 30/38
Loan Types
Difference comes entirely from productive loans
Within productive loans, crop and micro-enterprise loans account for
the largest differences
Non-productive Loans are actually lower in above cut-off villages
Consistent with reallocation from consumption-oriented to
production-orientation lending
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 30 / 38

99. 30/38
Loan Types
Difference comes entirely from productive loans
Within productive loans, crop and micro-enterprise loans account for
the largest differences
Non-productive Loans are actually lower in above cut-off villages
Consistent with reallocation from consumption-oriented to
production-orientation lending
Not consistent with wealth effects driving lending
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 30 / 38

100. 31/38
Demand or Supply?
Demand-side story
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 31 / 38

101. 31/38
Demand or Supply?
Demand-side story
Higher demand for bank loans in above-cutoff villages to utilize new
opportunities
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 31 / 38

102. 31/38
Demand or Supply?
Demand-side story
Higher demand for bank loans in above-cutoff villages to utilize new
opportunities
Supply-side story
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 31 / 38

103. 31/38
Demand or Supply?
Demand-side story
Higher demand for bank loans in above-cutoff villages to utilize new
opportunities
Supply-side story
Easier to provide and travel to monitor bank loans in above-cutoff
villages
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 31 / 38

104. 32/38
Demand or Supply?
Evidence mostly supports a demand-side story
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 32 / 38

105. 32/38
Demand or Supply?
Evidence mostly supports a demand-side story
Loan amounts are higher in above-cutoff villages, conditional on
borrower having been reached by bank
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 32 / 38

106. 32/38
Demand or Supply?
Evidence mostly supports a demand-side story
Loan amounts are higher in above-cutoff villages, conditional on
borrower having been reached by bank
Productive loans higher at the expense of non-productive loans
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 32 / 38

107. 32/38
Demand or Supply?
Evidence mostly supports a demand-side story
Loan amounts are higher in above-cutoff villages, conditional on
borrower having been reached by bank
Productive loans higher at the expense of non-productive loans
Bank operates on a nodal branch model – villagers come to the
branch to seek loans, bank officers typically do not travel to villages
to generate interest
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108. 33/38
A Placebo Test
Comparing similar villages across the population cutoff
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 33 / 38

109. 33/38
A Placebo Test
Comparing similar villages across the population cutoff
Difference: already had roads under a different program that had
nothing to do with population-based cutoffs
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 33 / 38

110. 33/38
A Placebo Test
Comparing similar villages across the population cutoff
Difference: already had roads under a different program that had
nothing to do with population-based cutoffs
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 33 / 38

111. 33/38
A Placebo Test
Comparing similar villages across the population cutoff
Difference: already had roads under a different program that had
nothing to do with population-based cutoffs
None of our results obtain, in spite of more statistical power in tests
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 33 / 38

112. 34/38
Roadmap
1 Overview
2 Background and Data
3 Main Results
4 Distributional Effects
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 34 / 38

113. 35/38
Who Benefits More?
Results stronger for
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 35 / 38

114. 35/38
Who Benefits More?
Results stronger for
Households that have low assets – especially those without significant
cultivable land ownership
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 35 / 38

115. 35/38
Who Benefits More?
Results stronger for
Households that have low assets – especially those without significant
cultivable land ownership
Lower caste villagers – SCs, STs and OBCs
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 35 / 38

116. 35/38
Who Benefits More?
Results stronger for
Households that have low assets – especially those without significant
cultivable land ownership
Lower caste villagers – SCs, STs and OBCs
Villagers with basic education
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 35 / 38

117. 35/38
Who Benefits More?
Results stronger for
Households that have low assets – especially those without significant
cultivable land ownership
Lower caste villagers – SCs, STs and OBCs
Villagers with basic education
No differential effect for women, or the young
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 35 / 38

118. 36/38
Who Benefits More?
Some possibilities why:
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 36 / 38

119. 36/38
Who Benefits More?
Some possibilities why:
Opportunities to work in higher paying jobs outside neighboring villages
might alleviate collateral constraints: income less dependent on local
crop yields, so less risky
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 36 / 38

120. 36/38
Who Benefits More?
Some possibilities why:
Opportunities to work in higher paying jobs outside neighboring villages
might alleviate collateral constraints: income less dependent on local
crop yields, so less risky
Or, opportunities to move into more profitable cash crops: given similar
riskiness of income, expected returns on lending higher
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 36 / 38

121. 37/38
Who Benefits More?
None of this is due to any government mandate or rule – this is a
private sector lender
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 37 / 38

122. 37/38
Who Benefits More?
None of this is due to any government mandate or rule – this is a
private sector lender
Giving access to financial markets to landless peasants and socially
under-priviledged castes – some of the poorest sections of village
society in India – has long been a focus of policy
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 37 / 38

123. 37/38
Who Benefits More?
None of this is due to any government mandate or rule – this is a
private sector lender
Giving access to financial markets to landless peasants and socially
under-priviledged castes – some of the poorest sections of village
society in India – has long been a focus of policy
Rules out connectivity driving our effects through increases in land
value
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 37 / 38

124. 37/38
Who Benefits More?
None of this is due to any government mandate or rule – this is a
private sector lender
Giving access to financial markets to landless peasants and socially
under-priviledged castes – some of the poorest sections of village
society in India – has long been a focus of policy
Rules out connectivity driving our effects through increases in land
value
Can geographic mobility beget socio-economic mobility in India?
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 37 / 38

125. 38/38
Conclusion
We find that private financing does indeed respond to changes in
productive opportunities resulting from road connectivity
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 38 / 38

126. 38/38
Conclusion
We find that private financing does indeed respond to changes in
productive opportunities resulting from road connectivity
In spite of private-sector rural banking being a relatively new
phenomenon
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 38 / 38

127. 38/38
Conclusion
We find that private financing does indeed respond to changes in
productive opportunities resulting from road connectivity
In spite of private-sector rural banking being a relatively new
phenomenon
Financing productivity increases might see a lot more interest among
private lenders going forward
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 38 / 38

128. 38/38
Conclusion
We find that private financing does indeed respond to changes in
productive opportunities resulting from road connectivity
In spite of private-sector rural banking being a relatively new
phenomenon
Financing productivity increases might see a lot more interest among
private lenders going forward
Lending related to connectivity can have distributional effects, but no
evidence to suggest that it worsened inequality
Agarwal, Mukherjee and Naaraayanan Roads and Loans March 7, 2018 38 / 38