Development Economics
ECON 4915
Lecture 12
Andreas Kotsadam
Outline
• Long run effects of the slave trade (Nunn and
Wantchekon 2009).
• Recap, recap, and recap.
Nunn and Wantchekon (2009)
• Research question: Did the slave trade cause a
persistent culture of mistrust?
 Interesting? Yes, long run effects of slavery. Culture
and development. The origins of trust. Test the causal
mechanisms behind the results in Nunn (2008).
Original? Yes, their causal channel has not been
credibly tested before.
 Feasible? Yes, by collecting innovative data and using
IV.
Why would slave trade affect trust
today?
• Early in the slave trade, slaves were primarily
captured through state organized raids and
warfare.
• By the end of the trade individuals - even friends
and family members - began to turn on one
another, kidnapping, tricking, and selling each
other into slavery.
• This environment, where everyone had to
constantly be on guard against being sold or
tricked into slavery by those around them,
generates a culture of mistrust.
Table 1 from wp version
But why do we find these effects
today?
• Using ‘rules-of-thumb’ can be an optimal strategy
in environments where information acquisition is
either costly or imperfect.
• These rules-of-thumb evolve according to which
norms yield the highest payoff.
• ”Our view is that in areas more exposed to the
slave trade, rules-of-thumb or beliefs based on
the mistrust of others would have been more
beneficial relative to norms of trust and therefore
would have become more prevalent over time.”
Cultural transmission
• For the explanation to work the culture must
be transmitted over time or cultural change
and social learning must occur slowly.
• Note that these aspects are not tested in the
paper and in that sense cultural transmission
is still a black box.
Data: Afrobarometer contains
questions on trust. Table 2 from wp
Data: Ethnicity level slave exports.
• The country-level estimates are constructed
by combining data on the total number of
slaves shipped from all ports and regions of
Africa with data on the ethnic origins of slaves
shipped from Africa.
• The individual samples are originally from a
variety of historical records, such as slave
runaway notices, plantation inventories,
marriage records, death records, etc.
Data: Ethnicity level slave exports.
• The ethnic groups in the historic documents
are matched to a common classification
scheme and linked to the map provided by
Murdock (1959).
Estimation
OLS:
i, individuals
e, ethnic groups,
d, districts,
c, countries.
Basic results (1)
Basic results (2)
How do we know it is causal?
• ”The negative correlation between slave
exports and trust … is consistent with our
hypothesis that the slave trade engendered a
culture of mistrust.”
• “However, the correlation could also be
explained by omitted variables that are
correlated with selection into the slave trade
and with subsequent trust.”
Example of problem
• Less trusting groups may have been more
likely to be taken during the slave trade and
they continue to be less trusting today for
other reasons.
3 solutions
• Controll for many things at the ethnicity level.
• Use selection on observables to say something
about possible selection on unobservables.
• Use IV
Controls
• Try to capture colonial rule and initial
conditions by controlling for:
Disease environment (following AJR),
precolonial population density, historical
location of railways, and missionary stations.
IV
• We need an instrument that is correlated with
slave exports, but uncorrelated with any
characteristics of the ethnic groups that may
affect trust today.
• Historic distance of each ethnic group from
the coast is used as an instrument for the
number of slaves taken during the slave trade.
Validity
• The critical issue is whether an ethnic group’s
historic distance from the coast is correlated
with factors other than the slave trade that
may affect how trusting the ethnic group is
today.
• What is the most obvious problem?
Validity
• Controlling for current distance to the coast,
identification will be driven by the effect of
the slave trade on the trust of individuals that
live in a location different from their
ancestors.
• These may be different types of people, but
they show that, if anything, are more trusting.
Results
• The first stage shows that the instrument is
relevant and that slave exports is primarily
explained by historic distance rather than
current distance from the coast.
• The second stage estimates show similar
magnitudes as OLS.
• Hence, OLS is likely not biased.
Falsification tests
• “As is generally the case with instruments, it is
possible that despite our second stage
controls, our instrument still does not satisfy
the necessary exclusion restriction. For this
reason, we also perform a number of
falsification exercises to assess the validity of
our identification strategy.”
Falsification tests
• If the assumption is satisfied, then we should
not observe a similar positive relationship
between distance from the coast and trust in
the parts of the world where the slave trade
did not occur.
• They find no relationship between distance
from the coast and trust outside of Africa.
• Or in African countries not affected by the
slave trade.
Mechanisms
• Are people less trusting today via the
evolution of vertically transmitted norms?
• Or because the slave trade damaged the
institutions so that people are less trusty due
to e.g. weak rule of law?
Test
• They create a measure quantifies the number of slaves
that were taken from the geographic location where
the individual is living today.
• If the slave trade affects trust through internal factors,
then mistrust should be correlated with the extent to
which their ancestors were heavily impacted by the
slave trade.
• If the slave trade affects trust through its deterioration
of domestic institutions, then mistrust should be
correlated with whether the external environment that
the individual is living in today was heavily impacted by
the slave trade.
Result
• Both factors are significant but the magnitude
of the internal channel is approximately twice
the magnitude of the external channel.
External validity
• “it is important to keep in mind that all of the
results in the paper apply only to the 17 subSahara African countries included in our
sample. The effects of the slave trade for the
countries not included in our analysis may be
different from the effects we estimate here.”
• What about other shocks? Slave trade in
Norway. What about the mechanisms?
Recap
• Email me if you want something specific
covered during next lecture.
Rural credit markets
• You should have some thoughts about:
 Why the poor often cannot borrow on the formal
market.
Why the poor pay so much interest on their loans, if
they are able to borrow.
The role of institutions.
What can be done to improve the situation.
Why is credit important?
• Credit is needed for efficient production as
well as smoothing out consumption.
 Production requires investments.
 Income streams often fluctuate.
There are two basic (and related) problems
• Moral hazard: Lenders cannot monitor the
actions of the borrowers.
• Adverse selection: Lenders cannot distinguish
between borrowers with different
characteristics.
These problems are severe for formal
lenders
• They don´t have personal knowledge
regarding the clients.
• They cannot monitor how the loans are used.
• Limited liability implies that borrowers take to
much risk or default voluntarily.
• Collaterals may solve this problem, but this is
infeasible for the poorest.
Characteristics of rural credit markets
• Information problems (also for informal
lenders) leading to:
• High interest rates.
• Segmentation.
• Interlinkage.
• Interest rate variation.
• Rationing.
• Exclusivity.
Lender’s risk hypothesis for informal
lending
Assume perfect competition.
Let L= Loan amount,
r= Lender’s opportunity cost,
p= Fraction of loans repaid, and
i= Interest rate.
The expected profit of the lender is
therefore:
p(1  i)L  (1  r )L
Setting expected profits equal to zero and solving for the interest rate
gives:
1 r
i
1
p
Main lesson of the model
• Hence, even under competition informal sector
interest rates are very sensitive to the default risk.
• But is it true?
True with an important twist
• Looking at data it is obvious that defaults are quite
rare in rural credit markets.
• So, this mechanism of potential default is largely
circumvented but this is costly.
• This cost is basically what drives the observed high
interest rates.
• And since some of these costs are fixed, small loans
demand a higher interest rate.
Information assymetries and rationing
• Information assymetries may cause credit
rationing as lenders are not able to fully
observe if a borrower is of high or low risk.
• Too high interest rates may drive away the low
risk type of borrowers.
• It may therefore be optimal to have a lower
interest rate and a higher probability of
receiving the money back.
Now we know the theory behind:
•
Why interest rates are high.
•
Why there is credit rationing.
•
It all has to do with information asymmetries
in the following way:
Adverse selection and moral hazard
• Adverse selection: If banks raise interest rates
the project mix will become riskier.
• Moral hazard: If interest rates increase,
borrowers themselves choose more risky
projects and/or put in less effort to repay.
Policies
• A nice (but not so simple) solution would be
to build up good institutions and eliminate
poverty.
• In the meantime, we have covered:
Government intervention to expand credit (Burgess
and Pande 2005).
 Microfinance (Banarjee and Duflo 2010).
Typical exam question
• 2a) Give some arguments for and against the
idea that a state led expansion of rural banks
should reduce poverty (2 points).
• 2b) If we are interested in the effects of rural
banks on poverty, why is it a bad idea to draw
conclusions by simply comparing poverty in
areas that have banks to poverty in areas that
do not have banks? (1 point)
Typical exam question
• 2c) Burgess and Pande (2005) instead use a policy
rule in India between 1977 and 1990 that forced
banks who wanted to open in a location that
already had banks to open banks in four areas
that had no banks. In particular, they exploit the
trend reversals between 1977 and 1990 and
between 1990 and 2000 (relative to the 19611977 trend) in the relationship between a state's
initial financial development and rural branch
expansion as instruments for branch openings in
rural unbanked locations. What arguments are
provided for using these instruments? (4 points)
Typical exam question
• 2d) What are their conclusion and how can it
be criticized? (3 points)
Their conclusion
• “We provide robust evidence that opening
branches in rural unbanked locations in India
was associated with reduction in rural
poverty.”
Critical questions
• Have they really showed that rural banks
matter or just that this policy had effects?
• Does it matter that the bank openings were
not randomly assigned?
• Is the result generalizable to other contexts?
• Do we know why the reform had an effect?
• What about the long term effects?
• Was it cost effective?
Typical exam question
• 3a) Banarjee and Duflo (2010) define
microcredit as innovations that lower the
administrative cost of making small loans.
Describe these innovations and discuss their
advantages and disadvantages (5 points).
Some innovations and mechanisms
•
•
•
•
•
Dynamic incentives.
Group liability.
Repayment frequency and social interactions.
Simplified collection technology.
Temptation and self-control.
Dynamic incentives.
• Default implies a lost opportunity of larger
loans in the future.
• Theoretically, dynamic incentives cannot work
alone…
• … and competition may undermine them.
Group liability.
• Default by one member hurts the other
members.
• This should make clients invest in screening
and monitoring.
• But the drawback may be too little risk-taking.
• Empirical evidence suggests joint liability is
not the driving factor.
Repayment frequency and social
interactions.
• Weekly repayment is the typical time period.
• Evidence suggest that longer time periods are
better for investment…
• …but worse for default.
• Compatible with a social capital story, which
actually recieves empirical support.
Simplified collection technology.
• The costs of collecting the loans are very low.
• Loan officers are able to collect payments
from many people each day and it becomes
very easy.
Temptation and self-control.
• What if borrowers have self control problems?
Wouldn’t easy credit make this worse?
• It actually seems to be the other way around:
microcredit helps people commit to a savings
plan.
• But is it the best way to achieve commitment?
Insurance
• The problem of risk.
• Why doesn’t insurance markets work well?
• What can be done?
To reduce risk, smoothing of
consumption is necessary
• How smooth consumption?
• One way is via credit.
• We have already seen that this is not very
easy.
• Another way is via self-insurance.
Typical exam question
• 4b) If we have data on individuals in a village
and we observe that the change in
consumption perfectly follows the change in
village income and is completely unrelated to
changes in income at the household level. Is
this evidence of perfect insurance? (3 points)