Another exam entry.
Jensen, N. and Wantchekon, L. (2004), “Resource Wealth and
Political Regimes in Africa,” Comparative
Political Studies 37(7): 816-841.
Question 1: What is the central hypothesis of the article?
How strong is the theoretical justification for that hypothesis? Explain.
Jensen and Wantchekon are testing four hypotheses, all based
on the relationship between natural resource endowment and regime type and
action. First, they examine the relationship between natural resource endowment
and likelihood of authoritarian regime type. Second, they test the relationship
between natural resource endowment and government spending. Next, they consider
the relationship between natural resource endowment and quality of governance.
Finally, they examine the likelihood that greater natural resource endowment
leads to a breakdown in democracy in the 1990s. They limit their analysis to
Africa, which justifies the 1990s as a critical break point. This approach is
justified because while their first three hypotheses are all well-supported in
the literature, the prior literature was based on a specific, narrow group of
states – oil-rich OPEC states. Thus, the variance in type of natural resource endowment throughout Africa allows for
more robust testing of the hypotheses. Specifically, qualitative research
supports their argument by showing three paths for resource-rich states to
develop authoritarian regimes.
Question 2: What dependent variables are used and how are
they measured? Are these valid and reliable measures? Why or why not?
Each hypothesis uses different dependent variables (as is
appropriate). For the first hypothesis, Jensen and Wantchekon operationalize
democracy through the standard derivation of Polity III scores, and then adding
10 to eliminate negative values. For government spending, they use government
spending expressed as a percentage of GDP. For governance, they use six
aggregate measures of governance developed by the World Bank. For the final
hypothesis, they use democracy measures again as with the first hypothesis, but
use a later derivative of the Polity dataset (Polity 98). These variables have
internal validity throughout: using Polity scores is a standard measure of
regime type, and the manipulation they employ renders the data amenable to
regression analysis without eliminating any meaning; and using government
spending to measure government spending is, well, intuitive. The most
interesting variable is the governance measures, which they justify by
reference to the literature developing it. Presumably the aggregate data used
to generate the measures are internally valid; however, since they are only
World Bank working papers, and not subject to formal peer review, I would not
object to someone questioning the validity of these measures. For the same
reasons, I would regard all of these measures as reliable, since they can
presumably be reconstructed; but would not complain if someone else reached a
different conclusion, particularly if the World Bank measures had inter-coder
issues.
Question 3: What are the primary independent variables and
how are they measured? Are these valid and reliable measures? Why or why not?
Jensen and Wantchekon use a constructed variable for their
tested independent variable. This variable was assigned an ordinal value based
on the percentage of merchandise exports derived from fuel, minerals, and
metals. I am concerned about the internal validity of this measure, as it
excludes exports based on renewable natural resources such as agricultural
products and timber. Jensen and Wantchekon do not justify this exclusion; as it
could reduce the values of many cases’ independent variables, the exclusion
could lead to Type I error. Because the measure is invalid, its reliability is
irrelevant; however, I note in passing that the data is easily recoverable, and
the way that they reduce the granularity of the data to allow them to fill in
missing data is actually pretty ingenious.
For control variables, they rely exclusively on control
variables found in the data sets they use for their panel data, to insure
internal validity (since all the data therefore comes from the same source).
Log GDP per capita eliminates GDP fluctuations caused by population shifts, and
is therefore externally valid, and GDP growth controls for democratization
driven by economic growth – the “rising tide lifts all boats” hypothesis. Both
measures are easily reconstructed either from existing data sources or by
minimal mathematical manipulation, and thus are reliable.
Question 4: Are there any unnecessary control variables in
the analyses? What are they and why are they unnecessary?
For their final hypothesis, Jensen and Wantchekon are
replicating a test done in 1994 by Bratton and Van de Walle, and thus must use
their control variables. So even though they find that none of Bratton and Van
de Walle’s control variables significantly account for democratic
sustainability between 1994 and 1998, their inclusion is necessary to make it a
valid replication. The use of colonial dummies baffles me. It clearly matters,
as it is strongly significant at even a higher correlation coefficient than the
test IV, but Jensen and Wantchekon say that it “had little effect on our
dependence on political regimes.” This statement seems either to be saying
something different than its facial content, or to contradict the data
altogether. While I can’t say this variable was unnecessary, I would say that without a better explanation than
what was offered, that the paper should have been unpublishable.
Question 5: Does the study not control for something that
should be controlled for? What is it and why should it be controlled for?
Because African politics can frequently be driven by ethnic
divisions, I would like to see that variable accounted for somehow. In
particular, I question whether differential resource endowment for different
ethnic groups could be driving authoritarian regimes, or whether it merely
heightens existing autocratic tendencies that are driven by ethnic divisions.
Question 6: Using only Table 1 of the article, answer the
following:
a)
What is the likely substantive effect of each
independent variable on democracy in column 2, when moving the variable from
one value to another (using your choice of values)?
b)
Explain why and how the addition of dummy
variables for four colonial legacies changes the statistical results from
column 1 to column 2. Be as specific as possible in your answer.
a.
The relationships between the variables are
assumed to be unstandardized. Thus, I will speak in terms of actual values
instead of standard deviations. However, I will express the values of changes in terms of standard
errors. Thus, for example, for an increase in log GDP per capita of 3.141 (the
standard error), I would expect an increase in democracy score of 1.995 (the
correlation coefficient). A quick review of the log tables suggests that this
is a remarkably difficult achievement, since this would require a GDP growth of
23.127 percent. A log GDP per capita increase of 1 (still substantively
unbelievable for a single country to accomplish without an exogenous variable
not captured in the data), would result in an increase in democracy score of
.635 – or an 11.3% increase in democracy scores for the mean country, ceteris paribus. Wealth thus clearly
plays a tremendous role in the health and longevity of democratic institutions.
A more reasonable increase in log GDP per capita of .5 would increase democracy
scores by .318, a nearly 6% increase.
The same cannot be said for economic growth.
It appears that a 28-point increase in GDP growth rates only increases
democracy scores by .076. Increasing GDP growth rates by one point thus increases democracy scores by .003 – an increase of
less than 1/10 of one percent.
Looking at natural-resource dependence
changes the analysis, because unlike the two prior independent variables,
Jensen and Wantchekon have converted their measure of resource dependence to an
ordinal variable. This means that while we can still talk about the
relationship, we can’t give it the kind of mathematical precision that we could
before. We can assume with ordinal variables that a one-step change in
resource-dependence equals the standard deviation (instead of assuming, as we
did with the continuous IVs, that the standard error equaled the standard
deviation). Thus, a one-step increase in resource-dependence (which could be a
one-percent increase in the share of merchandise exports from the extraction
sector) should decrease democracy scores by .364 – or a 6.5% decrease from the
mean.
The remaining variables are dummies, and
thus are treated differently. It appears that the 1970s were more authoritarian
than the other twenty-five years of the study’s period. If a regime was
measured during the 1970s, it averaged a 15.8% decrease in democracy scores.
The 1980s were the same, but less so, with a 12.4% decrease in democracy scores
– but the p-value cautions us that this may be noise. This is probably because
of a tremendous increase in democratization in the 1990s. The remaining dummy
variables are based on the colonial heritage of the regimes studied. Because
there is no reference category, we can assume that these dummy variables do not
interact. In summary, being a former British colony would be expected to
increase democracy scores by 40.9% over the mean, or 2.305, while being any
other nation’s former colony would be expected to decrease democracy scores by
anywhere from 27.8% below the mean (-1.566) to 32.4% below the mean (-1.825).
b.
The addition of colonial heritage dummies
reduces correlation values for log GDP per capita, GDP growth, and resource
dependence, while increasing correlation coefficients for decade dummies. This
suggests that the philosophy of the “white man’s burden” actually had
relatively beneficial effects on a colonized population. Setting aside the
question of whether colonialism was an absolute benefit to colonized peoples,
it is clear that the British, who saw their institutions and systems as vital
to the governance of colonies, tended to create wealthier and more diverse
economies that had more robust democracies, while Continental colonizers, who
saw the colonies as resource-extraction outposts and nothing more, did not have
a lasting effect in creating institutions to provide just and secure government
to the colonized after their departure. Perhaps they thought they’d never
leave. It also is clear that the effect of colonialism diminishes over time, as
other variables come into play to drive democratization and stability.
Question
7: How would you go about either a) extending this study or b) challenging this
study with a separate research design? Discuss.
Frankly,
given that I’ve demonstrated that the paper should have never been published in
its current state, I object to being asked to extend or challenge a paper that
should be retracted. However, this is clearly a place for comparative
institutional design approaches. It seems clear to me that while resource
dependence may have a role to play in democratization, colonial heritage – and
thus, institutional design – has a far vaster role to play. It is thus vital to
test this by examining the institutional design factors that are the legacy of
colonialism, and to test Westminster-descended institutions against those of
other types. I would start with a fine-grained comparative approach – paired
case studies. I would use a successful Westminster democracy and a successful
Continental democracy, and a similar pair of authoritarian regimes. Once that
was done, and I had identified what I thought were the salient factors, then a
quantitative method could robustly test that model throughout Africa.
Controlling for resource dependence as Jensen and Wantchekon measure it would
allow me to directly test the different models.