1. The Institutions and Development Debate: Part I
Cause or effect?
Paul Dower
NES

2. Modern economic growth
Economic growth is a relatively recent phenomenon.
Maddison (2003):
World income per capita same in 500 and 1500 AD
In cumulative growth of 15% (0.04% p.a.)
Since then growth at 1.2% a year (doubles every 58 years)
Details of Maddison data

3. The Great Divergence
Source: Pritchett (1997)

4. Growth Theory in brief Factor accumulation (conditional convergence)
Differences in technology
Question: How is it that these differences come about?

5. Adam Smith’s answer
Differences in institutions can possibly explain income differences across countries because of differences in how they affect the growth process.

6. Source: Easterly and Levine (2003)

7. What is an Institution?
An integrated system of beliefs, norms, organizations and rules that generate a regularity of behavior
Man-made, non-technological features that influence economic outcomes by constraining behavior.
Grief (2006), North (1990)
Technology in its broad sense. This includes physical and human capital. Does not include social capital.

8. Coordinating Institutions
Rule: Drive on the right side of the road
Organization: Highway Patrol
Belief or Norm: Drivers will follow the rule.
Regularity of behavior: Drivers drive on the right side of the road.

9. Extractive Institutions
Rule: Police require at least $100 to dismiss minor offense charges.
Organization: Police, Courts
Belief or Norm: Police find bribes profitable and bribes are cheaper than facing the charges.
Regularity of behavior: Corruption

10. Productive Institutions
Rule: Secure property rights assure investors get return to investment.
Organization: Courts
Belief or Norm: Financial contract will be enforced.
Regularity of behavior: Investment in enterprise.

11. Institutions affect efficiency and productivity by influencing and coordinating:
consumption,
savings,
exchange,
investment,
production and
innovation.

12. Adam Smith’s answer
Geography can explain differences in the growth process through endowments that are more or less conducive to trade, technology and survival.

15. What do we mean by geography?
Disease, germs
Crop suitability
Temperature
Distance to major bodies of water

17. Source: Sachs et al. (1998)

18. How can geography affect the growth process?
Transportation costs
Mortality
Subsistence
Agricultural productivity

19. The Institutions and Development Debate
Weak view: Geography has an indirect effect through institutions.
(Easterly and Levine 2003), (Acemoglu et. al. 2001, 2002)
Alternative: The direct effect of geography dominates any indirect effects.
(Sachs 2002), (Sachs et al. 1998)
Strong view: Variation is due to differences in legal tradition.
(Djankov et. al) (Kuran 2003)
Alternative: Human capital is needed to establish good institutions.
(Glaeser et. al. 2004)

20. Major Data Sources Historical income: Maddison
Income inequality: UN WIDER
Institutional indices:
Polity IV
ICRG
Kauffman, Kraay and Zoido-Labaton (2002)
Freedom Index, Doing Business, Lex Mundi

21. Institutions Rule Indirectly
Acemoglu et al. (2002) argue that the level of development before colonization led to different incentives to set up productive or extractive institutions, which eventually led to a reversal in income for these ex-colonies.
Acemoglu et al. (2001) argue that extractive institutions were set up during the colonial period in places where colonists did not want to stay using settler mortality rates as a proxy for this desire.
Easterly and Levine (2003) show that tropics, germs, and crops matter for economic growth but primarily through the effect of good institutions on economic growth.
India, Mexico, Indonesia all richer than the US before industrialization.

22. Easterly and Levine (2003)
Replacing Mexico’s institutional index score with the US score removes the income gap.
“if Burundi’s endowments had been like those of Canada, it would have increased Burundi’s income per capita through institutions by a factor of 38.”
Actual difference is 107 times so only variation by a factor of 2.8 (107/38) is unexplained.
(In log terms, 78 percent of the log income difference between Canada and Burundi is explained.)

23. Reversal of Fortune?
Direct effects of geography can not explain the reversal of fortune (Acemoglu et. al. 2002)
Idea: Do urbanization rates in 1500 predict current differences in income?
For non-colonies, positive effect.
For ex-colonies, negative effect but not once we control for institutions.

24. Source: Acemoglu et al. (2002)

25. “Temperate Drift” Hypothesis
Tropics had an early advantage which shifted to more temperate zones with subsequent agricultural technological developments.
Empirical Evidence:
Divergence in income did not occur when these technologies were introduced.
Divergence was mainly due to industrialization.
The reversal in income does not appear to depend on geographical variables. Nor does industrialization depend on geographical variables.

26. Institutions don’t rule Sachs (2003), Sachs et al. (1998)
Strong correlations between geographical variables and income per capita.
Disease environment
Distance to international trade
High population density (especially when it is due to a rapid increase)
Malaria risk has a direct effect after controlling for institutions and indirect effects of geography on institutions.
Population increase is likely to take place in geographically disadvantaged regions.

27. A horse named malaria Effect on Income Malaria -1.43*** -.32*
Institutions
.53***
1.43**
Sachs
Rodrik et al.
*, **, *** means statistically different than zero at the 10%, 5%, and 1% level.
Source: Sachs (2002) and Rodrik et al. (2003)

28. A closer look at the evidence
Reverse causality (Albouy 2006)
Measurement (Woodruff 2006), (Glaeser et. al. 2004)
Persistence of institutions

29. Causality
Potential reverse causality from development to institutions.
Possible Solution: find instruments for institutions.
Requirement of instrument: (1) good predictor of institutions, but (2) doesn’t directly affect development, i.e. other than through its effect on institutions

30. Causal Structure of Development
Geography  Development   
Institutions

31. Causal + Econometric Structure of Development
Geography  Development   
Institutions
(not necessarily causal)
Instrumental Variable

32. Colonial Origins and Settler Mortality (Acemoglu et. al. 2001)
Settler mortality as an IV (and theory of differences in institutions)
High rates encourage the use of extractive institutions by the colonial settlers whereas low rates encourage the use of productive institutions.
If institutions persist through time, then settler mortality could predict an exogenous source of variation in current institutions.

33. Causal effect of colonial institutions
Effect on Income
Institutions
.41***
1.0***
1.1***
Latitude
.92
-.65
-1.2
Africa
-.90***
-.44
OLS
2SLS
*, **, *** means statistically different than zero at the 10%, 5%, and 1% level.
Model predicts Chile has seven times the income per capita of Nigeria given their differences in institutions.
Actual amount is 11 times.
Source: Acemoglu et. al (2001)

34. Checking the data -- Story of two data points (Singapore and Mali, SGP and MLI in diagram below)

35. Investigating the IV Albouy (2006)
Acemoglu et al. (2001) distribute 34 distinct mortality rates among 64 countries. Some mistakes on assigning mortality rates to countries.
They also mix high wartime deaths from disease of soldiers with low peacetime soldier death rates.
Data sometimes based on very small samples; larger samples available for the same country give different estimates.

36. Singapore and Hong Kong
Singapore is an influential observation with mortality of only 17.7.
Curtin (1989) says “the mean strength of this {military} force was too low to be significant.” He gives example of 83 men in Straits Settlement in 1863, with one death (from a heart attack).
Data are actually from Penang in Malaysia, more than 500 km from Singapore.
Historical literature on Singapore points to normal tropical mortality rates.
Alternative numbers on Hong Kong from a report by the Colonial Surgeon and from statistics on soldier mortality give much higher mortality in Hong Kong than Acemoglu et al. (2001).
Source: Easterly Lecture notes (2007)

37. Further considerations on data
“the remarkable nineteenth century success of European medicine in keeping soldiers alive in tropical conditions” (p. ix)
Is this mortality measure endogenous?
Disease rates throughout tropics dropped sharply during second half of 19th century
One speculation is that causation is from “desire for tropical empire”, which “may have been the principal incentive for research and discoveries in tropical hygiene” (p. x)
Source: Easterly Lecture Notes, 2007.

38. Institutions Rule
La Porta et al. (1999): French civil law does less to ensure the security of private property than the British common law, and consequently, citizens governed by French civil law will have weaker protection of their property.
Kuran (2003): Commercial crisis in the Islamic states in the Middle East mainly driven by a comparative disadvantage in legal rules.

39. Measurement Main measures of institutions: Risk of expropriation
Cost of doing business
Constraints on executive
Constitutional checks and balances such as judicial independence
Rules on representation such as electoral rules
The first three measures:
change over time
represent outcomes not rules
highly correlated with each other.
Ex. North Korea vs. South Korea

40. Measurement continued
Hard (objective) vs. soft (subjective) measures:
The drawback is soft often measure de facto institutions which matter for economic outcomes, whereas hard measures only capture de jure differences.
Ex. Under 4, Peru is the ideal state.
Broad vs. narrow measures
In general, the empirical evidence suggests soft and broad measures matter more for economic outcomes. But these measures are vague and hard to target with policies.

41. Human capital vs. formal institutions Glaeser et al. (2004)
Authors restrict notion of institutions to objectively measurable characteristics.
Implication 1: informal institutions are lumped into human capital.
Implication 2: indirect effect of geography on institutions becomes statistically weak.
Implication 3: effect of institutions disappears.
Implication 4: lagged values of education predict current institutions and not the other way around.
Measurement matters!

42. Concluding Remarks: What about institutional change?
Problem: Evidence requires institutional persistence AND no direct effect of settler mortality on development.
Malaria (Carstensen and Gundlach, 2005)
Why didn’t institutions change? Or did they?

43. Concluding Remarks: Unobserved institutional change makes the estimates difficult to interpret.
Historical accidents trigger change:
Ensminger (1992) studies the emergence of commercialism among Orma cattle herders in Kenya. She argues the conversion to Islam led to the adoption of social practices such as credit lending system and counting of cattle for alms that made market practices less costly. Greater market activity and the standardization of measures led to increased use of credit and individualization of herd ownership.
Colonial origins may be irrelevant:
Colonial traditions of commercial law in Benin, Madagascar and Malawi. Fafchamps (2004) shows that traders took preventative measures which they would not have to take if courts were effective.

44. Concluding Remarks: Directed Institutional Change
Given the apparent importance of institutions for explaining income differences, policies that initiate institutional change as a development tool are an intriguing possibility.
The open question is which institutions matter most and how to achieve desired effects if institutions primarily affect economic outcomes through informal means.