Download The Effect of Inequality, Democracy, and Economic

The E¤ect of Inequality, Democracy, and Economic Development on
Institutions: A Dynamic Panel Study
Nadezhda V. Baryshnikova and Maria Monica Wihardja
University of Adelaide and University of Indonesia
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We study how inequality, democracy, and economic development a¤ects government
stability, investment pro…le, the level of corruption, and bureaucratic quality using a
dynamic panel data across 58 countries from 1998 to 2006, controlling for population size,
natural resource endowment, and con‡icts/tension. Savoia, Easaw and McKay (2010)
argue that inequality is detrimental to institutional variables because inequality directly
advances rent-seeking behaviors of political and economic elites that perpetuates the
unequal distribution and political power. Meanwhile, inequality works indirectly through
democracy since voting rights are granted to poorer citizens who demand redistribution.
Using the Arellano-Bond (1991) 2-step GMM estimator with a heteroskedastic-consistent
error correction by Windmeijer (2005) to control for endogeneity biases, we …nd that
inequality has a negative e¤ect on investment pro…le but a less negative e¤ect in a more
democratic country. The direct e¤ect of polity, a measure of democracy, on investment
pro…le is mixed. There is a strong evidence that the level of development has a positive
e¤ect on government stability and investment pro…le, which supports the theory of vicious
cycle (Myrdal, 1944). Moreover, natural resource endowment has a negative e¤ect on
investment pro…le, which suggests the phenomenon of a resource curse. These e¤ects
are either non-robust or insigni…cant on the level of corruption and bureaucratic quality.
Policy interventions on enhancing investment climate and ensuring political stability on
the one hand, and increasing the level of development and reducing inequality, on the
other hand, are therefore crucial in breaking the vicious cycle.
Keywords: endogenous institutions, inequality, democracy, dynamic panel.
Address for correspondance: Nadezhda Baryshinkova, School of Economics, University of Adelaide,
Adelaide, SA 5005; Email: [email protected]; Phone: +61 8 8303 4821; Fax: +61
8 8223 1460
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or Maria Monica Wihardja, Department of Economics, University of Indonesia, Indonesia. Email:
[email protected]. Phone; +62-81-21220313. Fax: +62-21-5365-4607.
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1. Introduction
Using a dynamic panel data, we look at cross-country evidence of how inequality, democracy, and GDP per capita may a¤ect qualities of institutions - government stability, investment pro…le, corruption, and bureaucratic quality - using an empirical model suggested
by Savoia, Easaw, and McKay (2010), controlling for natural resource endowments, population, and military in politics/ethnic tension/religious tension/internal con‡icts/external
con‡icts. Savoia, et al. (2010) asserts that inequality a¤ects quality of economic institutions (de…ned as a set of rules constraining incentives) directly through the persistent
rent-seeking policies and indirectly through democracy. In areas with high inequalities,
the rent-seeking behaviors of political and economic elites perpetuate the unequal distribution of wealth and political power. Democracy indirectly a¤ects economic institutions
through voting rights granted to poorer citizens demanding redistribution. In other
words, democracy promotes greater participation of the voters that serves as a whistle blowers to poor-quality institution, while inequality works in the opposite direction
namely greater inequality translate into weaker economic and political power of the poor
and therefore their voices for better institutions are not heard of. The possibility of
resource curse in which natural resource abundance results in more rent-seeking behavior
and hence lower institutional qualities is also studied in our paper. Moreover, this paper
will study how the level of development, proxied by GDP per capita, a¤ects institutional
quality. A number of studies show that a good institution delivers economic prosperity, including IMF (2005) and Kau¤man and Kray (2010). But, what actually shapes
institutions remains a question. Institution is often misunderstood to be an exogenous
factor that a¤ects economic performance and other factors with little thoughts given to
the endogeneity issues on the formation of institutions. The theory of endogenous institution contends that institution is endogenously determined and not exogenously given,
by showing factors that a¤ect the quality of institution. This theory may help us understand why some countries are "trapped" as a low middle-income countries with poor
institutions.
The de…nition of institution is broad and multiple. Plott (1979) equate the sum of
preference, institutions, and physical possibilities to outcomes. Schotter (1981) de…nes
institutions as the alternative equilibrium standards of behavior or conventions of behavior
that evolve from a given game described by its rule. Schotter contends that institutions
are about the properties of the equilibrium of games and not properties of the game’s
description. They are about what the agents do with the rules of the game, not what
the rules are. Reformulating Plott’s equation, Ostrom (1986) equates the sum of rules,
physical laws, behavioral laws, and model of a decision maker to outcomes. The most wellknown de…nition of institution probably comes from North (1990) that de…ne institution
as rules of the game consisting of formal rules, informal constraints, and enforcement.
Similarly, Savoia et al (2010) de…nes institutions as a set of rules to constrain incentives,
and the absence of these rules will generate undesired outcomes. More recently, an
economic historian, Greif (2006), sees institution as a system that consists of rules, beliefs,
norms, implied behaviors, players/organization, in equilibrium.
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We will de…ne institution as that of Schotter (1981) and Greif (2006): it is a system in
equilibrium. This allows us to study the strategic behaviors of individuals given the incentive and informational structures of the societies. However, Ostrom’s equation agrees in
substance with Schotter’s and Greif’s de…nition of institution. Ostrom’s second equation
(1986) emphasizes two things: what we want to study is how rules change the incentive
structure leading to a change in outcomes, and these rules change the incentive structure
given that physical and behavioral laws are invariant. In practice, we will use some
governance indicators as proxies to institutional qualities.
There are two interesting properties of institution namely endogeneity, which is reiterated by Myrdal’s reinforcing cycle of Negro oppression and White prejudice (1944)
and North’s address on endogenously determined incentive structures in slow-growth
economies (1990), and indeterminacy. In what he calls "the theory of the vicious cycle," Myrdal argues that white prejudice and discrimination keep the Negro oppressed
and more oppressions in turn exacerbate white prejudice. Moreover, he argues that the
original change of either white prejudice or Negro oppression could set a di¤erent future
trajectory that spirals either upward or downward. North (1990) wrote, "What makes
for e¢ cient markets? If poor countries are poor because they are the victims of an institutional structure that prevents growth, is that institutional structure imposed from
without or is it endogenously determined or is it some combination of both?" (p.134-135).
Endogeneity means that not only does institution a¤ect welfare but also welfare a¤ects
institutions through, among others, behavioral and physical law. This latter hypothesis is
also what we study in this paper namely how the level of development proxied by GDP per
capita a¤ects institutional qualities. Being hungry and is unable to eat because a poor
individual could not a¤ord buying food would a¤ect this individual’s preferences between
rice and the right to vote. Educated and uneducated citizens will have di¤erent capacities
in participating in a democratic system. There are a lot more examples to these. A
more rigorous analytical framework of how welfare could a¤ect preferences, choices, and
implied behaviors of individuals is called a set-dependent choice framework. Suppose a
household has a choice of saving some income for future higher education of the children,
spending some income on better education of the children now, or saving some income for
food in times of crises. Given that the head of the household cares about the future of the
children but also cares about having enough money for food in times of crises, he might
choose to spend some income on better education for the children now. Now, suppose the
same household has a choice of spending some income on better education of the children
now or saving some income for food in times of crises. In this latter case, the household
does not perceive any opportunity for their children to attend higher education and hence,
saving some income for future higher education is not in their choice set. Given only the
two choices, He might choose not to send their children to school at all. It might seem
inconsistent with what he chooses in the prior case, but a set-dependent choice framework
agrees that people’s choice and preference depend on the choice set. This story tells us
that how the “almost poor” and the “very poor” people may react very di¤erently to a
government poverty program because their choice sets are not completely identical.
In regards to inequality and democracy, we may as well argue that institution may
evolve with inequality and democracy, just as it does with welfare. Political and economic
institutions that are captured by a few political and economic elites while leaving the rest
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of the society poor may perpetuate unequal distribution of wealth, which in turn, giving
more de facto power to the elites to capture those institutions in the next period, and so
on, regardless of the de jure political regime (Acemoglu, 2008; Acemoglu and Robinson,
2008). This evolution is socially unstable in the long term and may result in a revolution,
such as what happens in Tunisia, Egypt, Libya, Bahrain, Yemen, and Syria in beginning
of 2011, where people revolted against decades of dictatorship regimes, ignited by some
worsening socio-economic conditions.
Indeterminacy in the context of institutions means that there is no unique outcome that
comes out from a certain incentive structure. Indeterminacy arises because of multiplicity
of equilibria - the same set of rules, payo¤s, and players may result in multiple outcomes
of implied behaviors by the players. This also means that two di¤erent institutions can
arrive at the same outcome without necessarily having the same institutional trajectory.
This is why studying institutions must involve both deductive and inductive methods
done iteratively. A lot of times, it will involve also historical analysis. Indeterminacy
of institutions make traditional social science di¢ cult because neither deductive nor inductive analysis alone is su¢ cient to explain the complexity of institutions (Greif, 2006).
Moreover, institutions are context-speci…c and there is no "one-size-…ts-all" remedy to
improve an institution.
Future works in this direction may focus on individual country-level panel studies across
states, districts, municipalities, and provinces.
2. Literature Review
The study of endogenous institution goes back to Myrdal (1944) and more recently
North (1990). More recent literatures link together more explicitly political democracy,
distribution of wealths, and economic welfare, which intertwine resulting in persistency
of institutions. Acemoglu (2008) discusses the reasons of why a dysfunctional institution
continues to persist, and relates to the theory of endogenous institutions. He argues
that distributions of resources and initial political institutions a¤ect the de facto and
de jure political power respectively that a¤ects the economic institutions and political
institutions of the next period. Economic institutions and political institutions further
a¤ect the economic growth and the distributions of resources in the period after next.
This framework illustrates the evolution between distribution of resources and institutions.
Acemoglu and Robinson (2008) show an equilibrium that is called captured democracy.
The de facto investment on political power by the elites is high enough that the economic
institution is captured by the elites despite democratic political institution. Savoia, et
al. (2010) argue that inequality a¤ects quality of economic institutions (de…ned as a set
of rules constraining incentives) directly through the persistent rent-seeking policies and
indirectly through democracy. In areas with high inequalities, the rent-seeking behaviors
of political and economic elites perpetuate the unequal distribution of wealth and political
power. Democracy indirectly a¤ects economic institutions through voting rights that are
granted to poorer citizens demanding redistribution.
Resource-curse phenomenon has been studied by a series of literature. Leite and Weidmann (2002) study the extent to which natural resource abundance, trade openness, rule
of law, and political instability a¤ect corruption, and hence economic growth. By using a
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Two-stage Least Squares, they show that natural resource abundance increases opportunities for rent-seeking behavior, while trade openness, rule of law, and political stability
reduces corruption. In the growth regression, they …nd that natural resource abundance
tends to reduce long-run growth rate and long-term growth is negatively a¤ected by the
level of corruption. Busse and Groning (2011) analyze the impact of natural resource
abundance on governance indicators using a dynamic GMM panel estimator introduced
by Blundell and Bond (1998). They show that natural resource abundance leads to an
increase in corruption, but not for other governance indicators. In this paper, we will
study using the same econometric model and control variables as that of Busse and Groning (2011), adding inequality, democracy, and tension/con‡ict as extra control variables.
Acemoglu, Johnson, and Robinson (2002) shows a reversal of fortune that weigh against
a view linking economic development to geographic factors. Instead, they show that
reversal took place through institutional reversal resulting from European colonialism.
They argue that Europeans were more likely to introduce good institutions in previously
poor regions, encouraging investment and allowing industrialization to take place.
There is little empirical study that has been done on the e¤ect of both inequality and
democracy on institutions. Keefer and Knack (2000) estimate how land and income
inequality a¤ect property rights security, controlling for regime type. However, they
conduct the estimation using OLS that fails to deliver unbiased and consistent estimates
because of the possible endogeneity of institutions. Other papers focus on one of the
variables, either democracy or inequality alone (Savoia et al., 2010). Our paper will
contribute to the literature by analyzing the e¤ects of democracy and inequality on various
institutional indicators controlling for endogeneity biases.
Societal participation, social pressure, and accesses to information to voters are studied
in a number of literatures. Von Luebke (2009) discusses the importance of local leadership and societal pressures in shaping local governance. He argues that variations in local
governance are better explained by local leadership than it is by societal pressure. The
importance of participation level in curbing corruption is ingeniously captured by Serra
(2008), who conducts an experimental study on bribery games that show that combining
bottom-up and top-down monitoring on corruption the is most e¤ective way, even if the
institution is weak. Trust-based, informal institutions may also help to attenuate institutional constraints (Della -Giusta, 2008). Providing access of information to voters, thus
avoiding a narrow ‡ow of information going to only speci…c interest groups, is necessary
(Economic Review, RIETI, 2009).
Ivanyna and Shah (2010) argue that four widely used indicators including the World
Bank’s Worldwide Governance Indicators and Overseas Development Institute’s Word
Governance Assessments are lacking citizen-based evaluations. This paper provides a
framework for governance quality measurement across countries and over- time based on
citizens’evaluations.
In terms of policy implication, Myrdal (1944) wrote, "a rational policy will never work
by changing only one factor" (p.77). This is particularly true in the case of an endogenous system. In order for the system to work well, existing institutions and socioeconomic
conditions must reinforce each other. Moreover, Greif (2006) writes that,"...rather than
focusing only on helping countries specify rules, it will have to seek to change organizations, beliefs, and intertransactional linkages" (p.403). Central government must be
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able to provide legal rules to ensure participation of citizens in regulating local policies,
and must be able to empower the citizens to raise their voices and demand for change
(Hirschman, 1970). In other words, policies on institutions must be context-speci…c and
multi-dimensional.
3. Data
3.1. Dependent Variables
We use the following dependent variables as proxies for institutional indicators.3
1. Government Stability assesses both of the government ability to carry out its declared program(s) and its ability to stay in o¢ ce. It consists of three subcomponents namely government unity, legislative strength, and popular support. Source:
International Country Risk Guide.
2. Investment Pro…le assesses factors a¤ecting the risk to investment that are not
covered by other political, economic and …nancial risk components. It consists of
three subcomponents namely contract viability/expropriation, pro…ts repatriation,
payment delays. Source: International Country Risk Guide.
3. Corruption assesses corruption within the political system. Source: International
Country Risk Guide.
4. Bureaucracy Quality assesses the ability to govern without drastic changes in policy
or interruptions in government autonomous from political pressures and to have an
established mechanism for recruitment and training. Source: International Country
Risk Guide.
3.2. Independent Variables
The following variables are used as independent and control variables.4
1. Gini Coe¢ cient is used as a measure of inequality. Since the cross-country Gini
Coe¢ cients provided by the UNU-WIDER’s WIID2C use di¤erent methods and
survey data, we include dummy variables controlling for these methods in all our
equations. The method categories are consumption, income, expenditure, earnings,
and tax and income. The survey data categories are household survey, panel data,
tax-record data, international organizations. When there are multiple entries for
some country-year data, we pick the one that is most consistent with the rest of the
data. Source: UNU-WIDER, WIID2C.
2. Polity Index is used as a proxy for democracy. Source: Polity IV.
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A higher score on these variables indicates a better institutional indicator.
For Variable 7-11, a higher score indicates a better control variable. For example, a country with a
higher score on military politics means less military intervention in politics is observed in this country.
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3. Log of GDP per capita is used as a welfare measure Source: World Development
Indicator Database and CIA World Factbook.
4. Endowment is GDP share of natural resource exports. Natural resources include
mineral fuels (SITC section 3), ores and metal (27), metalliferous ores (28), and
nonferrous metals (68). We compute Endowment using the following equation:
Endowment = RES
M ES
where RES is resource exports as a share of total merchandise exports, M ES is
merchandise exports as a share of GDP. These, in turn, are computed
as
RES = (F E + OE)=100
M ES = M E=GDP
where F E is Fuel Exports (as % of merchandise exports), OE is Ores and metal
exports (as % of merchandise exports), M E is Merchandise export (in current US$),
GDP is GDP (in current US$), taken from the World Development Indicator Database. Source: World Development Indicator Database.
5. Mineral Depletion is the product of unit resource and the physical quantities of
minerals and energy extracted. It refers to bauxite, copper, iron, lead, nickel, phosphate, tin, zinc, gold, and silvers as well as crude oil, natural gas, and coal. It is
expressed as a percentage share of Gross National Income (GNI). Source: World
Development Indicator Database.
6. Log of Population is used to control for population size. Source: World Development
Indicator Database.
7. Internal Con‡ict assesses political violence in the country and its actual or potential
impact on governance. It consists of three subcomponents namely civil war/coup
threat, terrorism/ political violence, civil disorder. Source: International Country
Risk Guide.
8. External Con‡ict assesses both the risk to the incumbent government from foreign
actions, ranging from non-violent external pressure (diplomatic pressures, withholding of aid, trade restrictions, territorial disputes, sanctions, etc.) to violent external
pressure (cross-border con‡icts to all-out war). It consists of three subcomponents:
war, cross-border con‡ict, foreign pressures. Source: International Country Risk
Guide.
9. Military in Politics assesses military involvement in politics. Source: International
Country Risk Guide.
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10. Religious Tension assesses various religious tension from the domination of society
and/or governance by a single religious group that seeks to replace civil law by
religious law and to exclude other religion from the political and/or social process;
the desire of a single religious group to dominate governance; the suppression of
religious freedom; the desire of a religious group to express its own identity, separate
from the country as a whole. Source: International Country Risk Guide.
11. Ethnic tension assesses the degree of tension within a country attributable to racial,
nationality, or language divisions. Source: International Country Risk Guide.
The summary statistics of the dependent and independent variables as well as control
variables are given in Table 1.
4. Model
We test a version of the model proposed by Savoia et al. (2010) that asserts that
inequality a¤ects quality of economic institutions directly through the persistent rentseeking policies and indirectly through democracy.
yit =
i+
t + 1 yit 1 +
1 giniit +
2 polityit +
3 giniit
polityit +
4 lgdpit +
xit + wit +"it
where:
yit is one of the governance indicators (government stability, investment pro…le, corruption, and bureaucratic quality)
i is a country …xed-e¤ect
t is a time-speci…c e¤ect, which include changes in the governance variables over time
xit is a set of control variables (population, endowment or mineral depletion, internal/external con‡icts, military in politics, religious tension, ethnic tension)
wit is a set of method and survey dummies for Gini (see the Data section above)
"it are the errors
We take all variables to be endogenous except for population size (and endowment/mineral
depletion, for a robustness check), and take the …rst di¤erence and use past levels lagged
two periods of more as instruments for the endogenous variables (e.g. y(t-1)-y(t-2) is
instrumented with y(t-3), y(t-4), etc., and x(t)-x(t-1) is instrumented with x(t-2), x(t-3),
etc.). We use the Arellano-Bond (1991) 2-step GMM estimator, with a heteroskedasticconsistent error correction by Windmeijer (2005). Sargan test of overidentifying restrictions is used to check the appropriateness of the instruments. The Arellano-Bond test is
used to test second-order serial correlation. To avoid over…tting the endogenous variables,
we reduce the number of instruments to be below the number of countries. For some
of the variables, we add the second lag of the dependent variable to avoid second-order
serial correlation.
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5. Results
Table 2-21 show the regression coe¢ cients and their signi…cance. The coe¢ cients in
these tables are robust and pass the Sargan and Arellano-Bond tests (with the Sargan
and Arellano-Bond p-values being greater than 0.05). The main results suggest that the
level of development (proxied by GDP per capita) has a positive e¤ect on government
stability and investment pro…le and this is consistent throughout di¤erent control variables namely internal and external con‡icts/ military in politics/ religious tension/ ethnic
tension (Table 2 to Table 11). These are robust throughout regressions with endowment
or mineral depletion. This con…rms our hypothesis on endogenous institutions. However,
this result somehow contradicts the Kau¤man and Kraay’s (2010) empirical study that
suggests that the level of income negatively a¤ects governance. While this paper suggests
the existence of "vicious" and "virtuous" cycles, Kau¤man and Kraay’s result suggests
the absence of those cycles.
Inequality has a negative e¤ect on investment pro…le, but it has a less negative e¤ect in
more democratic countries in both regressions with endowment (in this case, with military in politics, Table 7) and mineral depletion (in this case, with ethnic tension, religious
tension, and internal con‡icts, Table 8-10). This con…rms the hypothesis proposed by
Savoia et al. (2010) that inequality may exacerbate the rent-seeking behaviors of political
and economic elites and perpetuate unequal distribution of wealth and political power.
Rent-seeking behaviors are certainly harmful to investment climate, including pro…t repatriation. However, this negative e¤ect is smaller if a democratic political regime can
guarantee people’s representation, who may serve as whistle blowers to a bad government
and demand for a more equal distribution.
Endowment has a negative e¤ect on the investment pro…le throughout di¤erent control
variables namely internal and external con‡icts/ military in politics/ religious tension/
ethnic tension, which suggests a "resource curse" phenomenon (Table 7-11). This result is
consistent with Busse and Groning (2011) and Leite and Weidmann (2002), although our
…nding shows no signi…cant e¤ect on corruption but on investment pro…le. As argued
in both papers, natural resource abundance increases the opportunities of rent-seeking
behaviors, including obtaining concessions to mining areas or permits to exploit forest
areas whose issuances are controlled by a few political elites in the government. The
existence of such costly rent-seeking behaviors is damaging to contract viability, pro…t
repatriation, and other elements of investment pro…le.
Moreover, fewer internal con‡icts improve government stability (Table 5). More military involvements in politics means better investment pro…le (Table 7). This may be
surprising but one may perceive military involvement in politics as a way to secure and
protect certain business interests.
The e¤ects of polity and gini on corruption are both positive when religious tension is
included (Table 14). The positive e¤ect of gini on corruption (more unequal society means
less corruption) is surprising, but this result is not very robust since the signi…cance goes
away in the robustness check regression with mineral depletion. Moreover, less religious
tension means less corruption (Table 14).
In the robustness check regression with mineral depletion, there are some evidence that
polity has an e¤ect on investment pro…le, although this e¤ect is mixed being positive
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in some regressions and negative in others (Table 8-10). This may not be surprising
since there are many anomalies with respect to the e¤ect of autocracy - for example,
Singapore has thrived under an authoritarian political regime, and so has China, while
autocracy in some of the Middle East and other Northern African countries may be
blamed for poor socio-economic conditions. Moreover, as mentioned earlier, in a captured
democracy, a democratic political institution may coexist with an economic institution
that is captured by elites. Hence, the direct e¤ect of democracy on institutional indicators
is ambiguous.
Other coe¢ cients are either insigni…cant, non-robust, or both. From these results, we
…nd that only investment pro…les are most responsive to changes in inequality, polity,
GDP per capita and endowment although government stability is better with a higher
level of development. We contend that other institutional variables are more dependent
on other factors excluded in our regression speci…cations. For example, corruption and
bureaucratic quality may depend more on personal integrity rather than economic incentives such as higher payments. From the results, we can argue that reinforcing factors
behind the vicious cycles between low welfare and low institutional qualities may not be
corruption nor bad bureaucracy but lower investment pro…le and government instability.
One may ask why some of the lagged dependent variables are not signi…cant. Only the
lagged two periods variable on government stability is signi…cant while only lagged one
period variable on corruption is signi…cant. Meanwhile, both lagged one and two periods
variables on investment pro…les and bureaucratic quality are signi…cant. We argue that
some institutional indicators are more "persistent" than others while others are more
prone to abrupt shocks. It makes sense that bureaucracy and investment pro…les are
institutional qualities that cannot change very rapidly, while government stability and
corruption in the government are more random in a sense that one big political con‡ict
or one big corruption case in one year can make government stability and corruption
indicator to rise rapidly, etc.. In other words, lagged dependent variables only a¤ect
"structural" parts of institutions, such as bureaucracy and investment pro…le, but they
do not a¤ect parts of institutions that are more abrupt to changes, such as government
stability and corruption.
We try the same data on di¤erent years namely 1984-1997 using the same empirical
model, and surprisingly, we …nd no signi…cant coe¢ cient. We argue that there are a lot
of structural changes on these years on some of our sample countries, including the fall of
the Soviet Union. Further researches on this is encouraged.
6. Conclusion
We study how inequality, democracy, GDP per capita a¤ect institutional variables
controlling for endowment, population, and military involvement in politics/ethnic tension/religious tension/internal con‡ict/external con‡ict. We test the hypothesis proposed
by Savoia et al.(2010) that inequality a¤ects quality of economic institutions de…ned as
a set of rules constraining incentives directly through the persistent rent-seeking policies
and indirectly through democracy. Based on the theory of endogenous institutions that
contests that not only do institutions a¤ect economic performance but also the level of
development a¤ects institutional variables, we test whether GDP per capita as a proxy
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to the level of development a¤ects institutional variables. Based on many studies on
resource curse, we also test whether after controlling for inequality and democracy, we
still …nd an evidence on resource curse. To control for endogeneity biases because of the
two-way relationship between institutions and economic development, we use the ArellanoBond (1991) 2-step GMM estimator, with a heteroskedastic-consistent error correction by
Windmeijer (2005).
We …nd that among the four institutional variables that we use as the dependent variables namely government stability, investment pro…le, corruption, and bureaucratic quality, only government stability and investment pro…le depend on inequality, democracy,
GDP per capita, and endowment. We argue that this is because corruption and bureaucratic quality may depend more on other factors excluded from the regression such
as personal integrity. We …nd a strong evidence that GDP per capita has a positive
e¤ect on government stability and investment pro…le. We also …nd that inequality has
a negative e¤ect on investment pro…le, but a less negative e¤ect in a more democratic
country. Our result also shows a strong evidence of a negative e¤ect of endowment on
investment pro…le, suggesting the resource-curse phenomenon. The e¤ect of democracy
on investment pro…le is ambiguous and insigni…cant on the rest of institutional variables.
This is not surprising since there are many anomalies with respect to the impact of a more
democratic political regime. In some countries, autocracy has been proven to be able
to build a well-functioning market and support economic growths, including in Singapore
and China.
All these results suggest that reinforcing factors behind the vicious cycles between low
welfare and low institutional qualities are not so much corruption nor bad bureaucracy
but lower investment pro…le and government instability. However, this is not to say
that corruption and bureaucratic quality do not a¤ect economic performance. Hence,
policy interventions on enhancing investment climate and ensuring political stability on
the one hand, and increasing the level of development and reducing inequality on the other
hand, are crucial in breaking the vicious cycle between low welfare and low institutional
qualities.
We also …nd that lagged one- and two-periods institutional variables are signi…cant
only for "structural" types of institutions, like investment pro…le and bureaucracy. These
structural types of institutions are more persistent than corruption and government stability, which are prone to abrupt changes in a particular year.
There are rooms to try di¤erent regression speci…cations and models. Moreover, this
model can be used to measure these e¤ects at the regional or local level.
Acknowledgements
Special thanks to the seminar participants at Monash University. This paper is based
on a working paper started during a visiting fellowship with the Indonesia Project, ArndtCorden Division of Economics, Australian National University, in February 2011.
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14
8. Appendix
Table 1
Summary Statistics.
Va ria b le s
G ove rn m e nt S ta b ility
Inve stm e nt P ro …le
C o rru p tio n
B u re a u c ra tic Q u a lity
G in i
P o lity
G D P p e r C a p ita
E n d ow m e nt
M in e ra l D e p le tio n
P o p u la tio n
M ilita ry in P o litic s
E th n ic te n sio n
R e lig io u s te n sio n
Inte rn a l C o n ‡ic t
E x te rn a l C o n ‡ic t
G in i* P o lity
N o te s:
(a ) To ta l nu m b e r o f c o u ntrie s is 5 8
(b ) Ye a rs 1 9 9 8 -2 0 0 6
m ean
sd
m in
m ax
8:964406
9:07933
3:193045
2:661166
38:84978
7:62419
12155:76
0:0448842
:1607567
5:27e + 07
4:596479
4:339719
5:248942
9:733456
10:50019
288:6345
1:360339
2:314032
1:277403
1:057693
11:13341
4:200239
13467
0:0607713
:5221184
1:61e + 08
1:456775
1:180652
:9086055
1:78258
1:254021
167:7911
5:04
3
1
1
21
7
253:2448
0:0004981
0
836000
:5
1
1
:42
5:17
355:6
12
12
6
4
63:3
10
72249:91
:3720273
4:83
1:29e + 09
6
6
6
12
12
569:7
15
Table 2
Government Stability with Military in Politics.
Government Stability
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment
Mineral Depletion
Military in Politics
Constant
Endowment
-0.051 [-0.123]
-0.486*** [-0.109]
0.166 [-0.782]
0.07 [-0.093]
-0.007 [-0.01]
3.129*** [-1.002]
1.305 [-6.796]
1.088 [-9.682]
Mineral Depletion
-0.029 [-0.134]
-0.507*** [-0.096]
-0.176 [-0.838]
0.036 [-0.098]
-0.005 [-0.011]
3.543** [-1.397]
1.681 [-6.165]
0.567 [-0.464]
-38.362 [-114.577]
-0.203 [-0.453]
0.365 [-0.331]
-43.365 [-110.466]
Observations
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
359.3
320.1
Sargan p-value
0.295
0.388
AB 2 p-values
0.129
0.131
Notes:
(a)*** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
(c) Standard errors in brackets
16
Table 3
Government Stability with Ethnic Tension.
Government Stability
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Ethnic Tension
Constant
Endowment
-0.051 [-0.169]
-0.486*** [-0.126]
0.006 [-0.808]
0.03 [-0.076]
0.001 [-0.011]
3.147* [-1.616]
1.761 [-10.044]
5.308 [-9.132]
0.184 [-1.012]
-47.569 [-176.069]
Mineral Depletion
0.011 [-0.145]
-0.493*** [-0.097]
-0.028 [-1.213]
0.037 [-0.085]
-0.004 [-0.012]
2.835** [-1.245]
0.397 [-7.201]
0.081 [-0.677]
0.188 [-0.94]
-17.516 [-126.372]
Observations
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
171.5
483.7
Sargan p-value
0.349
0.327
AB 2 p-values
0.153
0.137
Notes:
(a)*** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
17
Table 4
Government Stability with Religious Tension.
Government Stability
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Religions Tension
Constant
Endowment
-0.064 [-0.104]
-0.463*** [-0.089]
-0.642 [-0.686]
0.043 [-0.066]
-0.009 [-0.009]
3.411*** [-1.29]
-0.879 [-7.321]
-4.98 [-8.568]
-0.533 [-0.557]
-1.313 [-125.408]
Mineral Depletion
-0.034 [-0.145]
-0.487***[-0.105]
0.091 [-1.244]
0.045 [-0.081]
-0.006 [-0.011]
3.223** [-1.407]
-1.065 [-7.075]
0.286 [-0.675]
-0.165 [-0.567]4
4.529 [-121.155]
Observations
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
215.6
221.2
Sargan p-value
0.351
0.34
AB 2 p-values
0.116
0.17
Notes:
(a)*** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
18
Table 5
Government Stability with Internal Con‡ict.
Government Stability
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Internal Con‡icts
Constant
Endowment
-0.08 [-0.139]
-0.407*** [-0.09]
-0.22 [-0.571]
-0.012 [-0.08]
0.006 [-0.008]
3.456*** [-1.093]
7.165 [-8.005]
0.583 [-7.136]
0.227** [-0.111]
-139.439 [-135.528]
Mineral Depletion
-0.004 [-0.135]
-0.414*** [-0.096]
-0.053 [-0.867]
-0.004 [-0.09]
0.002 [-0.01]
2.947** [-1.383]
3.626 [-7.574]
0.339 [-0.824]
0.201* [-0.12]
-73.139 [-128.91]
Observations
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
570
575.5
Sargan p-value
0.196
0.307
AB 2 p-values
0.144
0.147
Notes:
(a)*** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
19
Table 6
Government Stability with External Con‡ict.
Government Stability
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
External Con‡icts
Constant
Endowment
-0.046 [-0.139]
-0.448*** [-0.095]
0.168 [-0.573]
-0.01 [-0.065]
-0.003 [-0.009]
3.007** [-1.323]
4.438 [-7.03]
1.744 [-9.446]
0.168 [-0.21]
-92.83 [-122.535]
Mineral Depletion
-0.002 [-0.125]
-0.490*** [-0.1]
-0.102 [-0.97]
0.033 [-0.067]
-0.002 [-0.007]
2.980*** [-1.148]
4.312 [-6.342]
0.369 [-0.738]
0.184 [-0.143]
-88.179 [-111.98]
Observations
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
220.3
914.2
Sargan p-value
0.444
0.61
AB 2 p-values
0.141
0.144
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
20
Table 7
Investment Provile with Military in Politicst.
Investment Pro…le
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/Mineral Depletion
Military in Politics
Constant
Endowment
0.326*** [-0.116]
-0.213** [-0.087]
-1.008 [-0.629]
-0.139** [0.058]
0.018** [-0.008]
1.533*** [-0.597]
1.058 [-6.145]
-13.131*** [-3.473]
-0.404* [-0.221]
-11.679 [-106.757]
Mineral Depletion
0.417 ***[-0.112]
-0.125 [-0.115]
-1.176 [0.982]
-0.169** [-0.08]
0.02 [-0.013]
2.147** [-0.95]
3.215 [-7.332]
0.071 [-0.394]
-0.134 [-0.268]
-54.923 [-126.124]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
335.7
335.8
Sargan p-value
0.149
0.114
AB 2 p-values
0.95
0.565
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
21
Table 8
Investment Provile with Ethnic Tension.
Investment Pro…le
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/Mineral Depletion
Ethnic Tension
Constant
Endowment
0.262** [-0.108]
-0.242** [-0.112]
-0.887 [-0.704]
-0.092 [-0.074]
0.015 [-0.01]
1.971***[-0.501]
5.766 [-4.599]
-10.724*** [-4.068]
-0.291 [-0.324]
-95.242 [-79.556]
Mineral Depletion
0.254** [-0.119]
-0.229** [-0.099]
-1.260** [-0.612]
-0.146** [-0.062]
0.020** [-0.009]
2.657*** [-0.644]
6.968 [-5.844]
-0.39 [-0.435]
-0.393 [-0.312]
-117.793 [-100.61]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
115.9
211.8
Sargan p-value
0.248
0.286
AB 2 p-values
0.813
0.908
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
22
Table 9
Investment Provile with Religious Tension.
Investment Pro…le
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/Mineral Depletion
Religious Tension
Constant
Endowment
0.386*** [ -0.118]
-0.215** [0.096]
-0.95 [-0.68]
-0.086 [-0.079]
0.015 [0.011]
1.684*** [-0.46]
2.682 [-4.378]
-9.059*** [-3.496]
-0.103 [-0.299]
-43.456 [-76.433]
Mineral Depletion
0.346*** [-0.122]
-0.128 [-0.106]
0.021** [-0.009]
-0.149** [-0.061]
0.021** [-0.009]
2.283** [-0.913]
3.326[-6.32]
-0.168 [-0.381]
-0.159 [-0.261]
-55.716 [-109.263]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
241
345.2
Sargan p-value
0.157
0.225
AB 2 p-values
0.937
0.678
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
23
Table 10
Investment Provile with Internal Con‡ict.
Investment Pro…le
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/Mineral Depletion
Internal Con‡ict
Constant
Endowment
0.307** [-0.15]
-0.260*** [-0.093]
-0.931 [-0.607]
-0.09 [-0.072]
0.012* [-0.007]
1.903*** [-0.516]
-1.058 [-5.798]
-10.406*** [-3.31]
-0.168* [-0.093]
19.066 [-99.878]
Mineral Depletion
0.328** [-0.14]
-0.206** [-0.098]
-1.435* [-0.737]
-0.180*** [-0.067]
0.023** [-0.009]
2.414** [-0.956]
0.923 [-6.225]
-0.291 [-0.447]
-0.082 [-0.11]
-15.828 [-107.043]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
249.2
347.2
Sargan p-value
0.102
0.229
AB 2 p-values
0.979
0.851
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
24
Table 11
Investment Provile with External Con‡ict.
Investment Pro…le
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/Mineral Depletion
External Con‡ict
Constant
Endowment
0.372*** [-0.1]
-0.203*** [-0.069]
-0.62 [-0.715]
-0.061 [-0.082]
0.007 [-0.01]
1.478*** [-0.472]
0.498 [-5.439]
-10.774*** [-3.79]
-0.072 [-0.162]
-6.641 [-95.602]
Mineral Depletion
0.403*** [-0.145]
-0.1 [-0.094]
-1.334 [-1.388]
-0.151 [-0.094]
0.014 [-0.014]
2.058* [-1.052]
0.792 [-7.38]
-0.036 [-0.54]
-0.126 [0.262]
-11.084 [-126.864]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
356.7
274.5
Sargan p-value
0.204
0.189
AB 2 p-values
0.803
0.374
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
25
Table 12
Corruption with Military in Politics.
Corruption
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Military in Politics
Constant
Endowment
0.523*** [-0.099]
-0.062 [-0.133]
0.35 [-0.51]
0.085 [-0.088]
-0.004 [-0.01]
-0.14 [-0.402]
1.67 [-3.424]
-1.808 [-3.903]
0.076 [-0.218]
-29.617 [-58.281]
Mineral Depletion
0.421*** [-0.111]
-0.068 [-0.118]
0.584 [-0.419]
0.110* [-0.062]
-0.007 [-0.007]
-0.624 [-0.56]
-0.012 [-3.748]
-0.075 [-0.298]
0.072 [-0.154]
0.656 [-64.49]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
280.7
179.1
Sargan p-value
0.46
0.118
AB 2 p-value
0.961
0.839
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
26
Table 13
Corruption with Ethnic Tension.
Corruption
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Ethnic Tension
Constant
Endowment
0.640*** [-0.115]
-0.033 [-0.144]
0.216 [-0.363]
0.049 [-0.052]
-0.002 [-0.007]
0.014 [-0.33]
-0.686 [-3.642]
-3.367 [-2.969]
0.206 [-0.273]
8.675 [-61.464]
Mineral Depletion
0.508*** [-0.172]
-0.051 [-0.145]
0.365 [-0.461]
0.063 [-0.069]
0.003 [-0.009]
-0.219 [-0.368]
-0.246 [-3.638]
-0.151 [-0.276]
0.231 [-0.315]
2.581 [-61.577]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
366.7
233.9
Sargan p-value
0.197
0.165
AB 2 p-value
0.825
0.923
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
27
Table 14
Corruption with Religions Tension.
Corruption
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Religious Tension
Constant
Endowment
0.553*** [-0.114]
-0.036 [-0.141]
0.524* [-0.316]
0.067* [-0.039]
-0.005 [-0.005]
-0.231 [-0.348]
-0.669 [-3.049]
-1.606 [-3.741]
0.565*** [-0.21]
6.441 [-51.12]
Mineral Depletion
0.299* [-0.18]
-0.04 [-0.115]
0.302 [-0.335]
0.046 [-0.043]
0 [-0.005]
-0.493 [-0.392]
0.969 [-3.674]
-0.112 [-0.246]
0.605*** [-0.203]
-16.33 [-60.285]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
223.6
252.1
Sargan p-value
0.497
0.331
AB 2 p-value
0.807
0.823
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
28
Table 15
Corruption with Internal Con‡ict.
Corruption
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Internal Con‡ict
Constant
Endowment
0.510*** [-0.147]
-0.087 [-0.149]
0.696 [-0.469]
0.073 [-0.055]
-0.006 [-0.006]
-0.407 [-0.385]
-1.048 [-3.944]
2.227 [-4.117]
-0.08 [-0.061]
16.642 [-66.491]
Mineral Depletion
0.329* [-0.171]
-0.158 [-0.157]
-0.783 [-0.766]
0.083 [-0.097]
0.004 [-0.011]
-0.708 [-0.608]
0.012 [-4.16]
0.056 [-0.401]
-0.086 [-0.067]
1.466 [-70.949]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
294.5
204.6
Sargan p-value
0.434
0.343
AB 2 p-value
0.868
0.634
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
29
Table 16
Corruption with External Con‡ict.
Corruption
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
External Con‡ict
Constant
Endowment
0.599*** [-0.105]
-0.089 [-0.133]
0.279 [-0.596]
0.044 [-0.079]
-0.002 [-0.01]
-0.151 [-0.259]
0.159 [-4.4277]
-0.153 [-2.791]
0.073 [-0.095]
-3.936 [-73.888]
Mineral Depletion
0.410*** [-0.145]
-0.109 [-0.167]
0.633 [-0.446]
0.078 [-0.054]
-0.005[-0.007]
-0.437 [-0.491]
1.926 [-3.986]
-0.077 [-0.316]
0.109 [-0.102]
-33.119 [-66.91]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
404
163.1
Sargan p-value
0.175
0.144
AB 2 p-value
0.775
0.618
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
30
Table 17
Bureaucratic Quality with Military in Politics.
Bureaucratic Quality
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Military in Politics
Constant
Endowment
0.954*** [-0.129]
-0.817*** [-0.264]
0.005 [-0.024]
0 [-0.005]
0 [-0.001]
0.023 [-0.078]
0.035 [-0.71]
0.638 [-0.494]
0.007 [-0.043]
1.412 [-11.648]
Mineral Depletion
1.023*** [-0.142]
-0.841*** [-0.236]
0.003 [-0.034]
-0.001 [-0.002]
0 [-0.001]
-0.021 [-0.048]
-0.081 [-0.016]
-0.009 [-0.016]
0.001 [-0.008]
3.758 [-9.467]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
322.7
183.5
Sargan p-value
0.993
0.997
AB 2 p-values
0.511
0.64
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
31
Table 18
Bureaucratic Quality with Ethnic Tension.
Bureaucratic Quality
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Ethnic Tension
Constant
Endowment
0.945*** [-0.142]
-0.867*** [-0.266]
-0.037 [-0.051]
-0.003 [-0.007]
0 [-0.001]
0.023 [-0.064]
-0.114 [-1.089]
0.385 [-0.613]
0.069 [-0.059]
4.052 [-18.171]
Mineral Depletion
0.967*** [-0.219]
-0.831** [-0.326]
-0.028 [-0.052]
-0.002 [-0.007]
0 [-0.001]
-0.011 [-0.058]
-0.25 [-1.007]
-0.008 [-0.024]
0.08 [-0.055]
6.362 [-16.873]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
208.9
341.8
Sargan p-value
0.841
0.863
AB 2 p-values
0.469
0.625
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
32
Table 19
Bureaucratic Quality with Religious Tension.
Bureaucratic Quality
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Religious Tension
Constant
Endowment
0.909*** [-0.127]
-0.895*** [-0.254]
0.021 [-0.043]
0.001 [-0.005]
0 [-0.001]
0.034 [-0.058]
0.104 [-0.676]
0.36 [-0.425]
-0.013 [-0.043]
0.524 [-11.332]
Mineral Depletion
0.989*** [-0.141]
-0.882***[-0.267]
0 [-0.023]
-0.001 [-0.003]
0 [0]
-0.003 [-0.067]
0.017 [-0.902]
-0.003 [-0.018]
0.002 [-0.041]
2.061 [-15.332]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
131.8
317.8
Sargan p-value
0.999
0.998
AB 2 p-values
0.309
0.471
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
33
Table 20
Bureaucratic Quality with Internal Con‡ict.
Bureaucratic Quality
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
Internal Con‡ics
Constant
Endowment
0.994*** [-0.116]
-0.893*** [-0.164]
-0.032 [-0.049]
-0.002 [-0.004]
0 [-0.001]
0.042 [-0.056]
-0.057 [-0.806]
0.27 [-0.512]
0.006 [-0.009]
3.25 [-13.577]
Mineral Depletion
1.017*** [-0.141]
-0.899*** [-0.189]
-0.005 [-0.028]
0 [-0.004]
0 [0]
0.019 [-0.054]
0.263 [-0.754]
-0.003 [-0.027]
0.015 [-0.013]
-2.21 [-12.891]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
229.2
276.2
Sargan p-value
0.913
0.907
AB 2 p-values
0.377
0.41
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions
34
Table 21
Bureaucratic Quality with External Con‡ict.
Bureaucratic Quality
Lagged 1-yr
Lagged 2-yr
Polity
Gini
Gini*Polity
Log GDP per capita
Log of Population
Endowment/ Mineral Depletion
External Con‡ics
Constant
Endowment
0.956*** [-0.131]
-0.933** [-0.375]
-0.005 [-0.054]
-0.001 [-0.003]
0 [-0.001]
0.045 [-0.063]
0.355 [-0.597]
0.777 [-0.856]
0.015 [-0.018]
-3.831 [-9.681]
Mineral Depletion
1.016*** [-0.133]
-0.902*** [-0.308]
0.001 [-0.033]
0.001 [-0.004]
0 [-0.001]
0.006 [-0.077]
0.05 [-0.965]
-0.002 [-0.033]
1.322 [-15.878]
1.322 [-15.878]
Observation
267
267
Number of Countries
58
58
Number of Instruments
55
55
Chi2
190.7
285.7
Sargan p-value
0.978
0.961
AB 2 p-values
0.439
0.524
Notes:
(a) *** p=0.01, ** p=0.05, *p=0.1
(b) Time dummies and category dummies are included in all regressions