Empirical Evidence on Growth: A Closer Look on Cross-Country Regressions

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Empirical Evidence on GrowthA Closer Look on
Cross-Country Regressions

• Presentation by
• Dejan Jasnic and Philipp Wahlen
• 24. November 2008

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Regression Analysis

• Characteristics of relationship between dependent
  variable and independent variables y f(x)
• ? strength, direction, type
• Simple linear regressions
• y a bx
• Multivariate regressions
• y ? ?1x1 ?2x2 ?nxn

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Regression Analysis scatter plot

• What does it tell us about strength, direction
  and type of the relationship?

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Regression Analysis growth regressions

• Multivariate regressions y ? ?1x1 ?2x2
  ?nxn
• Complexity
• What is the right model? Right variables?
• More major shortcomings
• parameter heterogeneity, outliers, measurement
  error, endogenity
• assumption that economic growth operates
  according to universal laws across countries
  through the time

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Cross-Country Regressions

• RecallBy regressing annual growth
  on political and economic indicators across
  countries researchers attempt to find generally
  valid driving forces of economic growth.
• What might be problematic with this approach?

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Basic problems

• Levine and Zervos (2001) identify the following
  problems
• Statistical entries are sometimes inconsistently
  or inaccurately measured
• Construction of proxies that measure policy
  actions is difficult
• Sala-i-Martin (1997) gives example of human
  capital how to measure it?
• Regression analysis presupposes that observations
  are drawn from a distinct population
• Growth is often averaged over 30 years
  including business cycles, policy changes and
  political disturbances which makes
  interpretation of coefficients conceptually
  difficult
• Cross-country regressions do not address causal
  issues per se.
• Relationships might be discontinuous or non-linear

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Further problems

• Also McCartney (2006) brings forward fundamental
  critique
• Cross-country regressions (averaging growth
  rates) typically do not consider structural
  breaks
• Growth patterns in development countries are
  discontinuous, periods of fast growth are
  succeeded by those of slow growth. Growth
  accelerations are common (see also Hausmann et
  al. 2005).
• Interactions between policy measures cannot be
  feasibly incorporated into econometric
  cross-country models
• Simple cross country regressions do not account
  for so-called hysteresis effects
• Temporary economic shocks that have a permanent
  impact on economic growth threshold effects
  virtuous and vicious circles
• Static regressions do not consider dynamic
  effects
• Does a policy have impact during one or a few
  business cycles only or on long term growth?

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Two problems to focus on

• All considered papers name at least one of these
  two difficulties and make suggestions how to deal
  with them
• Growth theories are not explicit about what
  variables should be in a growth regression
• Take A, the level of technology in many
  growth models)
• Many empirical economists are tempted to try
  around with indicators without a theoretical
  backup
• Most variables are significant in some
  combinations and insignificant in others
• The problem is mentioned by Sala-i-Martin (1997),
  McCartney (2006), Brunetti (1997), and Levine and
  Zervos (2001)
• Government policy is probably endogenous and not
  random
• Governments adopt certain policies, because they
  are optimizing over policies in some objective
  function. Then the estimated coefficients will be
  biased.
• The problem is mentioned by Rodrik (2005) and
  Brunetti (1997)

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Regressors and robustness of results (1)

• Two papers, Levine and Zervos (2001) and
  Sala-i-Martin (1997) are specifically concerned
  with the issue
• Levine and Zervos cite papers by Levine and
  Renelt (1992) and Levine and Zervos (1993) that
  have used Extreme Bounds Analysis (EBA) to
  identify reliable determinants of growth

regressor of interest
growth rate ß1I ß2M ß3Z
set of fixed regressors
3 out of 7 possible regressors
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Regressors and robustness of results (2)

• Both cited papers take 1960-1989 average growth
  in a cross-section of over 100 countries as
  regressand
• EBA checks, whether a variable is positive and
  significant in all regression variants then it
  is called robust
• Hardly any relationship is found to be robust in
  this approach

regressor of interest
growth rate ß1I ß2M ß3Z
set of fixed regressors
3 out of 7 possible regressors
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Regressors and robustness of results (3)

• The Levine and Renelt (1992) paper is criticized
  by Sala-i-Martin (1997) for employing a
  robustness test that coefficients cannot survive
• It is in the nature of statistical tests that
  they yield insignificant results every once in a
  while, even if the assessed coefficient is
  significant thus, when taking into account many
  regressions, one should use softer measures of
  robustness
• Sala-i-Martin
• Uses 63 variables collected from different papers
• Runs 30,856 regressions for each of 58 variables
  of concern of the type on the previous two
  slides
• Weights estimated coefficients using integrated
  likelihoods
• Constructs a distribution of the weighted
  coefficients and then ranks coefficients by the
  percentage of their cumulative density functions
  that concentrates in either the positive or the
  negative quadrant
• Furthermore, for every variable he records the
  percentage of regressions in which significance
  is recorded

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Regressors and robustness of results (4)
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Endogeneity of government behavior (1)

• Recall Government policies are probably
  endogenous and not random
• Governments adopt certain policies, because they
  are optimizing some objective function. Then the
  estimated coefficients will be biased.
• Rodrik (2005) shows how cross-country growth
  regressions might yield negative coefficients for
  policy measures, even if the country is better
  off with the policy
• Rodrik introduces the following simple model
• Growth is determined by
• g(s, ?, f) (1 ?(1-s))A fa(s)
  ? a(s)gt0, a(s)gt0
• Government behavior is given by maximization over
  s
• max u ?g(s, ?, f) p(s) p(s)gt0, p(s)lt0

government ability
market imperfection
policy tool
weight placed on growth
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Endogeneity of government behavior (2)

• Then, under the assumption- that governments
  differ in their weights for growth, or- or that
  the severity of market failures differs between
  the countries,the estimated coefficient should
  be negative
• Mathematical derivations can be studied in the
  paper
• Intuition
• Assuming that governments can create rents for
  themselves from a certain policy, they will adopt
  the policy to a farther extent than optimal for
  growth dg/ds lt 0 evaluated at this point
• Growth is decreasing in the market failure
  parameter optimal extent of policy
  implementation is growing in market failure
  parameter this leads to a seemingly negative
  effect of policy on growth in the model, dg/ds lt
  0
• Example Ownership of banks around the world (as
  in La Porta, Lopez-de-Silanes, and Shleifer, 2002)

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Endogeneity of government behavior (3)

• How to deal with the problem
• Rodrik sees no opportunities for field
  experiments, in which policies would be
  randomized over situations governments will not
  readily allow for such experiments
• Instrumental variables are hard to find in the
  context of cross-country regressions (Rodrik,
  Brunetti 1997)
• Furthermore, they are not able to identify the
  success of purposeful policy action, which we are
  most interested in (Rodrik)
• Finally, the common use of past values of
  variables as instruments bears the danger of
  autocorrelation (Brunetti)
• Rodrik demands that before regressing and testing
• a full theoretical model must be specified
• this should incorporate a likely channel through
  which policies might operate

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General outlooks

• Rodrik (2005) See previous slide in general
  very pessimistic about the sense of general
  cross-country regressions
• Just as well Levine and Zervos (2001) they call
  for better measures of policies and for closer
  investigation of interaction between policies and
  the interactions effect on growth thus they do
  not seem to completely discard the approach
• Sala-i-Martin (1997) acknowledges problems but
  recommends not to be too pessimistic quite a few
  indicators can be found as very robust under the
  right robustness test
• Brunetti (1997) claims that with the development
  of more advanced policy indicators, the
  predictions seem to become more robust
  furthermore, he calls for the identification of
  IV to deal with the endogeneity issue
• McCartney (2006), however, suggests to discard
  the cross-country regression approach as a whole,
  as it rests on the neo-classical assumption of
  mechanically equal growth processes over all
  countries

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Used Papers

• Ross Levine and Sara Zervos (2001) What We Have
  Learned About Policy and Growth from
  Cross-Country Regressions?
• Xavier Sala-i-Martin (1997) I Just Ran Four
  Million Regressions
• Dani Rodrik (2005) Why We Learn Nothing from
  Regressing Economic Growth on Policies
• Aymo Brunetti (1997) Political Variables in
  Cross-Country Growth Analysis
• Matthew Mc Cartney (2006) Can a Heterodox
  Economist Use Cross-country Growth Regressions?