Nondemocratic regimes and trade
liberalization: An empirical study of electoral
regimes and monarchies∗
Bianca Oehl, ETH Zurich
Abstract
Nondemocracies participate at an increasing rate in world trade.
However, there is significant variation in the levels of trade liberalization. Instead of relying on unidimensional democracy measures to
explain this, the present paper applies a qualitative distinction between two subtypes of nondemocratic regimes, namely monarchies
and electoral regimes. The research question is: Do different kinds
of nondemocratic regimes display different behavior regarding international trade and trade regulations? The present paper argues that it
is important to distinguish between electoral regimes and monarchies
because their institutions of power generation and retention vary and
that these different institution influence trade openness. Additionally,
trade openness in general is expected to depend on factor endowment.
Thus, factor endowment will serve as the second main explanatory
variable. A panel data analysis covering the time period from 1972 to
2005 is applied to test if differences depending on the regime type exist. Two measures of trade openness (de facto and de jure) are used to
test for the two dimensions of trade liberalization. The results show
that electoral regimes and monarchies behave significantly different
with respect to trade openness.
Keywords: rational choice institutionalism, trade openness, trade
liberalization, authoritarian regimes, nondemocracies, autocracy
∗
Paper presented at the ECPR Graduate Conference 4th - 6th July 2012 in Bremen
1 INTRODUCTION
1
1
Introduction
‘(D)emocracy is a rather marginal phenomenon both historically and
geographically’
(Voigt 2003, p. 146)
Most people nowadays still live in nondemocratic countries; likewise, the majority of countries are also nondemocratic (Freedom House 2011).1 Recently,
interest in studying these regimes beyond their democratization prospects
increased and consequently resulted in more policy-oriented studies. An interesting subject for policy analysis in nondemocracies is trade policy; although many nondemocracies are developing countries, they participate at
an increasing rate in world trade but trade volumes vary a lot among these
regimes. Additionally, from 1978 to 1999, the variance of international trade
regulations within the group of non-OECD countries (which are mainly nondemocratic) increased (Martin and Schneider 2007, p. 460).2 How can we
explain this divergence among nondemocratic countries?
Previous attempts to explain the degree of trade openness conditional on
regime type referred to the level of democracy or democratization (for a review see Milner and Mukherjee 2009), or they have mainly been treated as
a uniform counterpart to democracies. Unidimensional measures like Polity
IV Index (Marshall, Gurr, and Jaggers 2010) cannot distinguish between
qualitative characteristics of nondemocracies. For example, Chile under the
military dictatorship of General Augusto Pinochet (1973-1989) with its liberal economic policy has the Polity scores -7 and -6.3 For the same time
period, the communist Soviet Union has an average score of -7 as well. Obviously, these two regimes had relatively little in common regarding their
economic policies. The basic contribution of this paper is to show that qual1
The term ‘nondemocracy’ or ‘nondemocratic’ is used to avoid misunderstandings: It
covers all forms of regimes that are not clearly ‘democratic’, e.g. do not fulfill the minimum
requirements of free and fair elections. Thus, this definition comprises also hybrid regimes.
Other terms as ‘dictatorship’ are often used in the literature to refer to specific subtypes,
for example ‘autocracy’ in contrast to ‘totalitarian regime’.
2
In contrast, regulation levels for OECD countries (which are mainly democratic)
became more equal during the same time (Martin and Schneider 2007, p. 460).
3
The Polity IV Index ranges from -10 (fully autocratic) to +10 (fully democratic).
2 TRADE: FROM POLITICAL SCIENCE TO ECONOMICS
2
itative differences among nondemocratic regimes matter for trade openness.
Such differentiations were previously used to explain quality of governance
(Charron and Lapuente 2011), economic growth (Wright 2008a) and foreign
aid effectiveness (Wright 2008b) in nondemocracies.
When speaking of trade openness I will from now on distinguish between
two components: legal regulations of trade (policy output) and actual trade
volumes (policy outcome). These two aspects are examined by using different
dependent variables in the empirical part. Thus, the research question is:
Do different kinds of nondemocratic regimes display different behavior regarding international trade volumes and trade regulations?
The argument put forward is that they do because institutions shape outcomes and the institutions of power generation and retention of power vary
between nondemocratic regimes.
The structure of the paper is as follows. A brief review of literature on trade
policy making in nondemocracies and trade liberalization is given in the next
part. Then the hypothesis are derived based on an analysis of the interaction of the economic and political sphere in nondemocracies. Additionally,
I explain why the model allows only to make statements on monarchies and
electoral regimes. Subsequently, the methodical approach is discussed including operationalization of the central variables. Results are presented for
the two different dependent variables followed by concluding remarks.
2
Trade: From Political Science to Economics
In general, there has been little research on trade liberalization in nondemocracies. Therefore, the literature review covers two fields of research: First,
the few contributions studying the relationship between nondemocracies and
trade is presented and second, a brief overview on classical trade theory is
given.
Nondemocracies and trade liberalization Some recent contributions,
which analyze trade liberalization in nondemocratic regimes, are the following. Hausken, Plümper, and Schneider (2002) developed a formal model
2 TRADE: FROM POLITICAL SCIENCE TO ECONOMICS
3
aiming to explain liberalization for autocracies in general with changes and
struggles on the politics level. A rather inductive approach is used by Richter
(2010), who examines the trade liberalization in four Arab countries. His conclusion is that trade liberalization occurred after severe financial problems of
the country leading to an opening as a condition for IMF assistance.
Classical works in the field of autocracy research, such as Tullock (1987) and
Wintrobe (1998), cannot contribute to the discussion of the effects of different kinds of nondemocratic regimes on economic policies as they do not
make the connection between the two topics. Nevertheless, they provide us
with more general insights: By trading with foreign countries, private businesses distance themselves from the influence of domestic control and thus
can create independent power bases (ibid.). This is postulated to foster a
challenge to the incumbent. Wintrobe (ibid., p. 72) argued that the effect
can be ambiguous; The ‘clash of civilization’ (Huntington 1996), which is a
synonym for perceived differences between cultures, can lead to an increase
in nationalism and thus generate support for a nondemocratic regime. In
addition, trade generates higher returns to the state, either directly through
tariffs or indirectly through increased tax revenues, due to possible income
growth. With the additional income for the state, the budgetary possibilities
for repression or redistribution to the supporters of the regime increase (Wintrobe 1998, p. 73). The well known Selectorate theory by Bueno de Mesquita
et al. (2002) that is often applied to explain policy making in nondemocracies
only makes assumption based on the size - and not the composition - of the
system supporting elite and is therefor not applicable to the present research
question. 4
Trade theory However, none of these findings help to create a more general framework on the influence of the type of nondemocratic regime on trade
liberalization. Therefore, I will reach back to classical trade theory. Some
core questions in trade theory are:
1. What are the gains from trade?
2. Who – or which group – gains?
4
Bueno de Mesquita et al. (2003, p. 72) explicitly distance themselves from making
the connection between regime classification and the Selectorate theory.
2 TRADE: FROM POLITICAL SCIENCE TO ECONOMICS
4
3. How much is traded?
The first question on the gains of trade is answered with the Ricardian comparative advantage, the Heckscher-Ohlin theorem on different factor endowments and economies of scale (Krugman and Obstfeld 2009). The argument
of the Ricardian comparative advantage is that even though some countries
have a an absolute advantage in producing all kinds of goods due to different technology levels, countries with a lower level will produce the goods for
which they have a comparative advantage and thus still can benefit from free
trade. The Heckscher-Ohlin (HO) theorem assumes that under free trade,
countries will consequently specialize production according to their factor endowment, making use of their abundant factor. These two theorems together
with economies of scale imply that international trade results in gains.
However, not all domestic groups (e.g. in a model with just two factors - as it
is assumed here - this would be labor- and capital-owners) are going to benefit
equally and some might even face a loss in returns because of the move from
autarky to free trade; prices change and so do factor returns. Especially
in nondemocracies, which often tend to be kleptocratic, the elites or the
dictator himself will try to skim off these gains. For democracies this might
be a different case; With social security systems a lot of redistribution is going
on that can actually make all societal groups benefit from the gains of trade.
Stolper and Samuelson (1941) finally provided an answer to the question who
gains. Under the assumption of a world with just two production factors,
‘(i)nternational trade necessarily lowers the real wage of the scarce factor’,
while simultaneously increasing the return to the abundant factor (ibid.,
p. 66). This is so because domestic production factors compete with foreign
production factors under free trade. Based on this theorem, preferences of
different factor owners can be derived. This is done in the next section.
The volume of trade – how much is traded – is often used as a proxy for the
trade openness of a country. In contrast to the first two questions, there is
less agreement as to an answer for the third one, instead, there are several
competing approaches. Milner (1999) addressed this question with an extensive review. She came to the conclusion that economists take a different
approach than political scientists: For the latter, protection is the norm and
so explanations try to explain the rush to free trade. The former puzzle
over why countries protect certain industries given that free trade would be
3 TRADE LIBERALIZATION IN NONDEMOCRACIES
5
the better alternative. In the end, this paper tries to provide an (empirical)
answer to this question for different types of nondemocracies.
3
Trade Liberalization in Nondemocracies
To explain trade liberalization in nondemocracies, the theoretical framework
builds on several established approaches. For the economic sphere this is
classical trade theory and for the political sphere it is rational choice institutionalism. The trade theorems have already been introduced in the
literature review and thus only the central propositions are recapitulated.
After a brief summary of rational choice institutionalism, different types of
nondemocracies are presented and I discuss for which of them we can formulate hypothesis based on the previously introduced theories. followed by the
actual derivation.
Economic sphere Economic trade theory provides us with means to formulate expectations on preferences of different groups for or against trade
liberalization. Relying on the argument of the Ricardian comparative advantage and the Heckscher-Ohlin theorem, I assume that there are aggregate
gains from trade. Considering the Stolper-Samuelson theorem, I expect that
these gains affect groups with varying factor endowments in different ways.
Under the assumption that there are only two factors, which are labor and
capital, the preferences of factor-owners are as follows. In a capital(labor)abundant country capital(labor)-owners favor opening up the economy for
free trade and oppose a closed economy setting. Hence, in a capital(labor)abundant country, labor(capital)-owners favor the closed economy and oppose
free trade.
Political sphere An instrument to analyze the relationship between policy
outcomes and output or characteristics of the polity is the rational choice institutionalism. Weingast defines rational choice institutionalism as the study
of ‘how institutions constrain the sequences of interaction among the actors, the choices available to particular actors, the structure of information
and hence beliefs of the actors, and the payoffs to individuals and groups’
(Weingast 2003, p. 661). Institutions are accordingly assumed to be ‘the
3 TRADE LIBERALIZATION IN NONDEMOCRACIES
6
Figure 1: Types of nondemocracies (Hadenius and Teorell 2007)
humanly devised constraints that structure political, economic and social
interaction.’ (North 1991, p. 97). They can be either formal or informal
(Williamson 2009): Formal institutions are shaped and enforced by governments and other administrative bodies. ‘In contrast, informal institutions are
private constraints stemming from norms, culture, and customs that emerge
spontaneously’ (ibid., p. 372).
Institutions of nondemocratic regimes are mainly informal in their characteristics; Formal institutions, such as the constitution, laws and so on, are often
of no relevance for de facto governance. The most important nondemocratic
informal institution is the constraint of the nondemocratic government by the
regime supporting elite; The government in nondemocracies has to provide
a sufficient amount of private goods to satisfy the elite in order to maintain
their support. These goods can also be policies that yield payoffs for the
elite. With respect to payoffs, economic policies like trade liberalization are
central. This is so because I assume that in nondemocracies gains from trade
are not equally distributed among the whole society and instead can serve
as a mean of income generation for the elites. However, only under certain
conditions does the elite actually profit from free trade. At this point, the
prepositions of the economic trade theory play a role; preferences depend on
the respective factor endowment. To examine this point closer, the next section deals with regime characteristics and building on that, the hypotheses
building.
Regime Classification and Scoping of the Model The economic theorems make predictions for capital- and labor-owners only. Thus, we can
only test the framework for nondemocratic regimes where either of the two
3 TRADE LIBERALIZATION IN NONDEMOCRACIES
7
constitutes the regime supporting elite. Therefore, this paragraph introduces
the comprehensive regime classification of nondemocracies by Hadenius and
Teorell (2007), see Figure 1. They distinguish among regimes regarding their
‘modes of maintaining power’ (ibid., p. 146): Hereditary succession or lineage
(monarchy), the actual or threatened use of military force (military regime)
and popular election (electoral regime) and theocracy, the rule of an religious
elite.
The elites of military regimes, the army, are out of the range of the economic model: They are indeed labor owners but do not compete on the
labor market. By definition, as members of the military elite, they are military personnel and can not be treated in the way the average worker is as
their wage is not determined on the market. Therefore, the model does not
capture their incentives. Likewise is the case for theocracy.
For monarchies and electoral regimes, the elites, which are either the aristocracy or party members, can be associated with the two economic groups.
This is further discussed in the following paragraphs. Additionally, monarchies are the most durable nondemocracies and electoral regimes the most
common ones in country-years (ibid.).
Monarchies A monarchy is a regime type where the power passes by hereditary succession typically from the incumbent to the oldest male descendant
in a stratified society that has at least one upper class like the nobility.
The nobility traditionally belongs to the group of capital owners, specifically
land and therefore they control very often also natural resources of a country:
Historically, the privileges of the nobility grounds in military earnings and
advantages, which then led to real property holding, either as a reward from
the monarch or by conquest (Reinhard 2003). A look at the modern world
shows that elites in current monarchies, like Saudi Arabia, understood it very
well to transfer their ‘old’ capital (land, natural resources) into ‘new’ capital such as commercial interests, stocks and other capital investments (Sabri
2001). Therefore, they should support trade liberalization only if ‘their’ factor
(capital) is going to benefit.
In order to avoid being overthrown by rivaling members of the line of succession, the monarch relies on support from inside the nobility. The argument
that he needs to control the armed forces is neither wrong nor inconsistent
3 TRADE LIBERALIZATION IN NONDEMOCRACIES
8
with this statement as the military elite in monarchies is typically part of the
nobility as well. Taking into account the properties of the Stolper-Samuelson
theorem, the following expectation can be stated:
Hypothesis 1 The more capital abundant a monarchy is, the more open is
its economy.
Electoral Regimes An electoral regime is a nondemocracy where a party
rules that came into power through elections. In contrast to monarchies,
electoral regimes are mostly based on a principle of egalitarianism; they
are non-exclusionary - or at least pretend to be so. Nobody is favored by
birthright5 or anything similar; Seniority in rank is derived from the party
alone, for example by executing a given office. In theory, anybody could
become an active party member. In fact, parties in electoral regimes are not
comparable to parties in democracies: Party leaders are not actually elected
during party congresses but rather as a result of internal power politics.
While parties in democracies are at least partially structured in a bottomtop fashion, in the case of nondemocratic electoral regimes only top-down
governance occurs. Obviously, the average party member is not crucial for
supporting the current regime. However, the mass can be important.
Party systems typically have a high integrative or mobilizing power which
is used in varying degrees.6 Every regime, including party regimes that are
strictly non-totalitarian, possesses some kind of ideology. Ideologies always
serve the purpose of ‘self-perpetuation’ (Rejai 1995, p. 13). Besides the ideologies Rejai (ibid.) identifies in his comparative analysis (namely nationalism,
fascism and Nazism, Marxism, Lenism, guerrilla communism, democracy,
feminism and environmentalism), one type of ideology seems to be especially
important today: Developmentalism. With developmentalism, I refer to the
compromise of the acceptance of a nondemocratic regime by the citizenry
in exchange for growth and wealth for the country, in short; development.
This concept has also many other names, for example, output or performance legitimacy (Lambach and Göbel 2010). Authors like Haggard (1990);
5
An exception are regimes which systematically suppress one or several ethnicity from
within the country. However, within the governing ethnicity there should be equality.
6
The most extreme case is probably the Gleichschaltung enforced by the Nazis, which
can also be described by the term totalitarianism in the Friedrich and Brzezinski (1956)
understanding.
3 TRADE LIBERALIZATION IN NONDEMOCRACIES
9
Przeworski and Limongi (1993) discuss the advantages dictatorships might
actually have compared to democracy when it comes to development. A
commonly accepted mean to achieve development is trade (UN Millennium
Project 2005). As many nondemocracies belong to the group of the least developed countries (LLDC) or less developed countries (LDC), this concept is
highly relevant for them.
A distinct difference to monarchies is that electoral regimes are mobilizing,
thus, rely on manifestations of loyalty and are less grounded in tradition:
A hint for that is the shorter durability. This mobilizing efforts aim at the
citizens which are labor owners. ‘(T)he same motivation that leads them
[the leaders] to bargain with the elites often induces autocrats to use the
party machine as a patronage system, whereby citizens receive rents from
the government.’ (Magaloni and Kricheli 2010) Lambach and Göbel (2010)
described this concept as responsivity and stated that clever nondemocratic
regimes use responsivity as a way to secure their rule. I expect that this
applies in particular to electoral regimes as the party structure supplies a
valuable function to the nondemocratic leader. To a certain extent, exogenous demands (here meaning independent of pure party interests) can be
expressed within the party framework. This is impossible in monarchies.
Although this could remind one of the incentives a democratic government
faces, the larger orientation towards the interest of the masses are solely
conditioned on a better fulfillment of the development bargain: acceptance of
a nondemocratic regime for development. This bargain is totally independent
of other factors which are typically connected with democratic regimes: free
and fair election, press freedom, freedom of speech and so on. From this
follows the second hypothesis:
Hypothesis 2 The more capital abundant an electoral regime is, the more
closed is its economy.
Monarchies and electoral regimes are thus expected to be opposite in their
influence on trade liberalization.
4 DATA AND METHODS
10
Figure 2: Distribution of Trade vol-
Figure 3: Distribution of Trade regu-
ume
lation
4
4.1
Data and Methods
Operationalization and Data Description
Trade Openness The dependent variable trade openness has two dimensions. The first dimension is de jure trade regulation, also described as output, and the second dimension is de facto trade meaning trade volumes, the
outcome. Trade volumes are operationalized as the share of imports and exports of GDP. Data is taken from the World Development Indicators (WDI)
dataset (World Bank 2011) because it also provides many control variables.
The variable capturing the share of trade of GDP is called (Trade) Volume.
For the first dimension, I rely on the Current and Capital Account Openness
(CACAO) dataset by Martin (2005). It comprises the years 1978 to 2005 and
consists of two indices, one for capital and one for trade, which is used here.
CACAO builds solely on de jure restrictions of trade which are collected as
dummy variables and then transformed into an index. These dummies cover
e.g. import surcharges, licensing duties for imports and exports, quotas,
maximum tariff > 100%, governmental foreign currency budget, state import
monopoly for certain goods, positive (negative) list of goods that are (not)
allowed to be imported, prohibition to export certain goods and multiple
currency exchange rate regimes. In the present analysis, the index is labeled
(Trade) Regulation. Figure 3 shows the distribution. Important to notice
here is that in the original data set high values mean high legal restrictions.
To simplify comprehension of results, the index is reversed; For both variables
4 DATA AND METHODS
11
higher values mean more trade openness.
A problem for both variables is missing data or bad data quality; When it
comes to data quantity and quality, nondemocracies are probably the most
ungrateful objects of research. It is to notice that the correlation between
the two measures with 0.19 (based on 991 shared observations) is very small.
This confirms that each of them measures something distinct.
Regime Type
For the operationalization of the independent variable,
nondemocratic regime type, data on the classification of regimes is available
from Hadenius and Teorell (2007) for the years 1972 to 2005 for 191 countries
(including democracies). The advantage of this data set is that it clearly
distinguishes between democracies and nondemocracies in a dichotomous way
and then differentiates between types of nondemocracies in more qualitative
terms. For the first step, the authors combined the Polity and Freedom
House scores of a country and rescaled it. The new scale ranges from 0 (least
democratic) to 10 (most democratic). The threshold for nondemocracies is
set at 7.5. Only those regimes which survived for more than two years are
analyzed. The reason is that short-lived regimes were probably unable to
rule and might bias our results. As discussed in the previous section, only
monarchies and electoral regimes are analyzed.7
Figures 4 and 5 display the average value of each trade measurement for the
year of the earliest observation and 2005 by regime type. All regimes by both
measures became more open on average.
Factor Endowment The hyptheses state a conditional relationship between regime type and factor endowment. This best translated into an empirical model by using interaction terms. Aiken and West (1991) recommend
the use of weighted effects analysis with interaction terms. Therefore, we need
to determine if a country i (i = 1, ..., I) is labor L or capital K abundant.
Thus, we compare its capital-labor ratio Ki /Li to the weighted capital-labor
ratios KI /LI of all other countries in the world. It has to be weighted, as
only those countries who participate in international trade are relevant for
situation of country i on the world market for a given year (subscript t is
7
The models have been estimated using the subtypes of electoral regime as well.
However, there were no significant differences for the results.
4 DATA AND METHODS
12
Figure 4: Average values of trade vol-
Figure 5: Average values of trade reg-
ume
ulation
omitted for means of readability).8 The weight is the respective trade share
of country i, T radei , of the world trade, T radeI .
I
1 X T radei Ki
KI
=
∗
LI
I i=1 T radeI Li

 Ki <
If for country i holds that Li
 Ki >
Li
KI
,
LI
KI
,
LI
then it is labor abundant.
then it is capital abundant.
Data for the trade weight stems from Barbieri, Keshk, and Pollins (2008).
They provide data on total exports and imports for 174 countries. The sum
of exports and imports for country i is used as a proxy for T radei . The world
trade for a given year is estimated by summing up the values for all countries
as described above.
Unlike for democracy or trade openness, no established data set(s) or measurements exist for the capital-labor ratio or its components. However,
a common approach to estimate capital stocks is the perpetual inventory
method, which is also used by Shirotori, Tumurchudur, and Cadot (2010),
whose data will be used for the analysis. They rely on data from Heston,
Summers, and Aten (2011) to estimate stock sizes for 137 countries from
1962 to 2007 as
Kt−1 = (1 − δ)Kit + Iit
8
Realistically considered, we are not going to be able to compute KI /LI based on all
countries of the world but on a relevant share.
4 DATA AND METHODS
13
I being the investment and δ the depreciation rate (Shirotori, Tumurchudur,
and Cadot 2010). Additionally, they do the same with education data from
Barro and Lee (2010) which allows for testing of the influence of human
capital Human Capital.
The operationalization of factor endowment (Factor Endowment) is thus the
difference between a countries ratio of physical capital per worker and the
weighted yearly average of all countries.
Control Variables Besides the factors discussed above, there is a wide
range of other issues that might influence trade openness and therefore is
discussed and tested in research. For sources and descriptive statistics of all
discussed variables see Table 1. Two factors that are commonly stated as
influential on economic policy in general are (economic) crises (Haggard and
Kaufman 1995) and the influence of the international economic regimes such
as the Bretton Woods institutions. Martin (2005) also highlights the interdependence between crises and trade regulations. However, he also points out
that most empirical tests of crises as a causal factor (including his own) only
marginally confirm this argument (ibid., Chapter 5). Nevertheless, the models
will test for crises by the inflation rate (Inflation) as a proxy. Alternatively,
GDP growth can also reflect economic crises (GDP Growth). As it is their
raison d’être, the Bretton Woods institutions seek to influence the economic
policies of their loan recipients. Pevehouse, Nordstrom, and Warnke (2004)
provide data for the membership in all international organizations (updated
until 2005 on the website).
The dependence on natural resources can alter the structure of an economy.
Such commodities are generally traded on the world market. We should,
therefore, expect countries that are more dependent on natural resources,
which is measured by the share of natural resources trading on overall trade
(Resources), to score higher (meaning more open) on all scales of trade openness. Another factor which is likely to influence trade openness is the size of
an economy per se: Smaller economies should trade more as their domestic
market is small and they can efficiently specialize only on a small amount
of goods. This can be easily tested by the total GDP (GDP ). However, not
just size but also wealth might influence trade openness as rich societies could
have demands the domestic market can not provide for. Hence, the GDP per
4 DATA AND METHODS
14
capita (GDP per capita) will also be tested.
4.2
Model Determination and Preliminary Diagnostics
The available data has a time-series cross-section (TSCS) structure which
allows following trends across time and countries.
The interaction term with Endowment account for the conditionality expressed in the hypotheses. The regime type monarchy is the reference group.
For trade volume, a Hausman test indicates that with 99% confidence the
choice should indeed be FE. A Woolridge test reveals that there is serial
correlation. Therefore, a lagged dependent variable (LDV) is included. Additionally, the standard errors (SE) have to be adjusted accordingly.
For the FE model, a modified Wald test confirmed the existence of heteroscedasticity. There are two ways to handle the problem of heteroscedasticity and autocorrelation in FE models: Either clustered or Discroll-Kraay
standard errors (Hoechle 2007). The latter, additionally controls for crosssectional dependence, meaning that errors are not just correlated with errors from earlier observation of the same country but also across countries.
Theoretical justification for assuming cross-sectional dependence is given
by Simmons and Elkins (2004). Unfortunately, the unbalanced panel structure makes it impossible to apply a Pasaran cross-sectional dependence test,
though, as unpleasant as it is, this only leaves one to estimate both ways
and check if they deliver consistent results. Time effects are significant and
also have to be included in the model. The econometric model looks as follows (here it is displayed for Volume but it looks essentially the same for
Regulation):
volumeit = β0 + β1 endowmentit + β2 electoralit
+ β3 electoral ∗ endowmentit + β4 controlsit + ui + vt + wit
(1)
As the dependent variable Trade regulation has an ordinal scale, a linear
regression model would produce inconsistent estimators. Therefore, I apply the BUC estimator for fixed effects ordered logit model proposed by
Baetschmann, Staub, and Winkelmann (2011). It artificially increases observations by multiplying existing ones with the possible number of cut-off
-46.98
11.52
1688
1549
1497
1484
1499
1489
1688
1688
1297
1688
Electoral
*Endowment
Resources
Inflation
GDP per capita
GDP growth
GDP
IMF
GATT/WTO
Loans
Human capital
2.8
0.3
0.49
2.93e+09
6.81
138.14
491.11
6.08
16.03
33.47
43.74
Std. Dev.
43.01
41.93
1.48
1.48
0.41
0.17
0
0
0
-41.8
0.12
-31.9
0.12
0
-91.41
-91.41
Min
6.61
6.61
0
0
0
11.18
1
1
2.88e+10
106.28
1910
13611.63
49.33
116.54
125.78
204.75
Max
428.46
423.57
7
7
1
Total natural resources rents
(% of GDP)
Annual GDP deflator in percent
Gross domestic product in thousand
constant 2000 US$ per capita
Annual growth of GDP in percent
Gross domestic product $
in billion constant 2000 US
Dummy for membership
Dummy for membership
IBRD loans and IDA
credits in current US$
Measurement of human capital
stock as average years of schooling.
Dummy differentiating between
electoral regime and monarchy
Proxy for the capital-labor ratio:
Difference between mean physical
capital per worker weighted yearly
by {tshare} for all countries.
Conditional effect of Endowment
Measures
Trade openness measured by exports
plus imports as share of GDP
Trade openness index (see p.11)
hum cap
IMF
GATT, WTO
DT.DOD.MWBG.CD
NY.GDP.MKTP.KD.ZG
NY.GDP.MKTP.KD
NY.GDP.DEFL.KD.ZG
NY.GDP.PCAP.KD
NY.GDP.TOTL.RT.ZS
-
-
Name in source
NE.TRD.GNFS.ZS
trade
mul, onep, mon
Table 1: Descriptive statistics
Trade volume, Inflation, GDP per capita, GDP growth and GDP are taken from World Bank (2011). Trade regulation is taken from
Martin (2005). Electoral regime is taken from Hadenius and Teorell (2007). Endowment and human capital are taken
from Shirotori, Tumurchudur, and Cadot (2010). IMF and GATT/WTO are taken from Pevehouse, Nordstrom, and Warnke (ibid.).
4.68
0.9
0.57
1.30e+09
3.72
49.31
58.39
3.07
-47.98
1688
Endowment
Mean
76.21
75.79
2.07
2.04
0.79
Obs
1476
1379
999
924
1688
Variable
Trade volume
LDV volume
Trade regulation
LDV regulation
Electoral regime
4 DATA AND METHODS
15
5 RESULTS
16
points and sets these cut-off points at all possible values and then estimate
conditional likelihood estimators. Like for Volume, time effects and an LDV
will be included, as serial correlation is highly likely for Regulation as well.
5
5.1
Results
De facto Trade
All results and interpretations in this section for the analysis with the dependent variable trade volume are displayed in Table 2. The model is tested with
two different specifications; In both cases, a fixed-effects model is estimated,
first, with clustered standard errors (CSE) and, second, with Discroll-Kray
standard errors (DKSE). In Model (1) and (2) the baseline model which includes only the key dependent variables is estimated and in Model (3) to (6)
covariates were also integrated.
Most important is that independent of the standard errors used, the results
remain stable regarding significance. The regime variable Electoral is positive and significant which means that electoral regimes are more open than
monarchies. The coefficient for Endowment is insignificant.
The interaction term Electoral*Endowment captures the conditional effect
of the capital-labor ratio for electoral regimes. Brambor, Clark, and Golder
(2006) summarized three points that should be considered when using interaction terms: The inclusion of all factors that constitute the interaction term,
the fact that these constitutive terms are not unconditional effects, and that
standard errors have to be estimated correctly. Thus, the displayed t statistics are not qualified for assertions on the significance of interaction terms.
We are interested in the marginal effects of the capital-labor ratio. Hence,
the following outline of the marginal effects plus the respective variance and
the corrected t test based on Model (5) with CSE is more informative:
5 RESULTS
17
(1)
Volume
30.50**
(2.69)
(2)
Volume
30.50***
(4.06)
(3)
Volume
36.16**
(2.92)
(4)
Volume
36.16***
(4.32)
(5)
Volume
38.72**
(2.97)
(6)
Volume
38.72***
(4.55)
-0.00893
(-0.16)
-0.00893
(-0.31)
-0.0409
(-1.00)
-0.0409
(-1.07)
-0.0477
(-1.09)
-0.0477
(-1.22)
0.329*
(2.33)
0.329***
(3.68)
0.401**
(2.65)
0.401***
(3.95)
0.423**
(2.68)
0.423***
(4.10)
0.768***
(20.81)
0.768***
(29.19)
0.756***
(19.76)
0.756***
(29.34)
0.751***
(18.99)
0.751***
(29.79)
Resources
0.315***
(3.42)
0.315**
(3.27)
0.327***
(3.51)
0.327***
(3.47)
Inflation
0.00245*
(2.61)
0.00245*
(2.36)
0.00243*
(2.57)
0.00243*
(2.33)
GDP per capita
-0.544*
(-2.31)
-0.544**
(-2.89)
-0.540*
(-2.09)
-0.540**
(-2.97)
GDP Growth
-0.0194
(-0.21)
-0.0194
(-0.25)
-0.0257
(-0.27)
-0.0257
(-0.33)
0.00646***
(4.18)
0.00646***
(6.17)
0.00757***
(4.03)
0.00757***
(6.70)
0.928
(1.00)
0.928
(1.36)
0.849
(0.91)
0.849
(1.19)
IMF
2.853
(0.57)
2.853*
(1.99)
GATT/WTO
2.732*
(2.43)
2.732*
(2.45)
-3.228
(-0.39)
0.693
1340
-2.478
(-0.57)
Electoral Regime
Factor Endowment
Electoral * Endowment
L.Volume
GDP
Human Capital
Constant
R2
N
8.054
(1.69)
0.677
1378
14.76***
(5.36)
1378
1.470
(0.27)
0.691
1340
3.322
(0.73)
1340
t statistics in parentheses, * p < .05, ** p < .01, *** p < .001
Yearly dummies were estimated for all models but are not displayed.
Table 2: Regression results for Trade volume
1340
5 RESULTS
δvolumeit
δendowmentit
σ2
δvolumeit
δendowmentit
18
= β2 + β3 electoralit = −0.0477 + 0.423electoralit
= var(β2 ) + electoralit 2 var(β3 ) + 2 electoralit cov(β2 β3 )
= 0.02064424
Based on this variances the t statistics for the conditional effect of endowment
for electoral regimes has a value of 2.612. Obviously, the t test for the
conditional effect of Endowment for monarchies equals the results from the
table for the coefficient of Endowment and is therefore not repeated. Using
the DKSE of Model (6), we get the following variances and t value of 3.905.
Hence, the interaction is significant independent of the SE used.
δvolume
δendowment
σ2
δvolume
δendowment
= β2 + β3 electoral = −0.0477 + 0.423electoral
= var(β2 ) + electoral2 var(β3 ) + 2 electoral cov(β2 β3 )
= 0.00923708
Thus, the marginal effect of endowment is only significant for electoral regimes.
Figure 6 provides a graphical presentation of the situation based on Model
(5): The more capital abundant an electoral regime is, the more it trades
with the rest of the world. The Volume of monarchies is independent of
Endowment.
The covariates - when significant - behave as expected. Dependence on natural resources is significantly associated with higher trade volumes: A percentage point increase in the trade share of natural resources is paralleled by half
a percentage point increase of the trade share. This result is straightforward
as it can be expected that lots of natural resources are traded outside the
own country. The inflation rate is significant as well, although, the effect is
rather small: An increase by one percent of inflation is associated with less
than one-tenth of a percent increase in the trade volume. A similar small
5 RESULTS
19
Figure 6: Marginal effects of Electoral regime depending on Endowment
coefficient describes the relationship with GDP. That bigger economies trade
more is unexpected.
The influence of IMF and GATT/WTO memberships is also comparably
small, although, at least the latter is significant across model specifications.
The comparison of Model (3) and (5) - or (4) and (6) respectively - yields that
the explanatory power of membership in these IGO is rather small compared
to the influence of regime type.
5.2
De jure Trade Regulations
Table 3 contains the results for Trade regulation. The interpretation of results
has to be rather cautious due to the used estimator. The displayed point
estimators are log odds of having a trade regulation level greater or equal a
certain level of Regulation, rather than less than that level (Baetschmann,
Staub, and Winkelmann 2011, p. 19).
The dummy for Electoral regime is insignificant in all models. After controlling for the set of covariates, Endowment and the interaction term are
significant. For monarchies, being more capital abundant has a positive influ-
5 RESULTS
20
(1)
Regulation
-0.835
(-0.12)
(2)
Regulation
-3.266
(-0.44)
(3)
Regulation
-3.461
(-0.48)
Factor Endowment
0.151
(1.80)
0.201*
(2.12)
0.199*
(2.08)
Electoral Regime * Factor Endowment
-0.172
(-1.94)
-0.207*
(-2.17)
-0.205*
(-2.23)
2.024***
(7.88)
2.072***
(7.75)
2.074***
(8.03)
Resources
0.00757
(0.22)
0.00709
(0.21)
Inflation
0.000116
(1.30)
0.000117
(1.28)
GDP per capita
-0.724
(-1.14)
-0.711
(-1.10)
GDP Growth
0.00727
(0.39)
0.00707
(0.40)
GDP
0.00875
(1.32)
0.00867
(1.28)
Human Capital
0.0256
(0.04)
0.0136
(0.02)
1755
-0.0752
(-0.06)
1755
Electoral Regime
LDV
Gatt/WTO
N
1853
t statistics in parentheses, * p < .05, ** p < .01, *** p < .001
Yearly dummies were estimated for all models but are not displayed.
Variable IMF was dropped because of multicollinearity.
Table 3: Regression results for Trade regulation
6 DISCUSSION AND CONCLUDING REMARKS
21
ence on the likelihood of having higher values of Regulation. The coefficient
of the interaction term is negative, this means that with higher values of
Endowment the likelihood to have higher values of Regulation decrease. Interestingly, the two last mentioned coefficients have a nearly equal magnitude
but opposite signs. Thus, it could be the case, that the effects cancel out
perfectly for electoral regimes which would leave us with Endowment being
only relevant for monarchies.
6
Discussion and concluding remarks
The paper aims at explaining differences in trade openness of nondemocracies
with the respective nondemocratic regime type, monarchy or electoral regime.
The theoretical framework was tested with two different dependent variables:
The first one accounted for trade volumes and the second one for legal trade
regulations. The empirical results present a challenging puzzle. For the
trade volume measure, they indicate that the outcome for monarchies is
independent of the factor endowment and that monarchies are more closed
compared to electoral regimes. In contrast, the trade volume in electoral
regimes depends positively on the endowment. Whether a country is capital
or labor abundant compared to the rest of the (trading) world does not play
a role (see Figure 6). Thus, the more capital abundant an electoral regime
is, the more it trades with the rest of the world. These results yield no
support for the stated hypothesis. In fact, the empirical relationship for
electoral regimes is exactly opposite and significant. Hence, with regard to
trade volumes, all hypotheses have to be rejected.
For the trade regulations index, factor endowment seems only to matter for
monarchies; The more capital abundant a monarchy is the more likely it is to
have high values on the trade regulation index meaning that is is more open.
At best, this relationship is reversed and only weakly existing for electoral
regimes. Thus, the link for monarchies reflects the stated relationship of
hypothesis 1 and to some extent also for hypothesis 2. Summarizing this,
evidence for the expected influence of nondemocratic regime type can only
be found for legal trade regulations but not for actual trade volumes.
A possible explanation for these findings could be that trade volumes do not
only depend on actions taken by the nondemocratic government but also on
6 DISCUSSION AND CONCLUDING REMARKS
22
the willingness and motivation of potential trading partners to actually trade
with a nondemocracy and, thus, is outside the influence of the nondemocratic
government (Mansfield, Milner, and Rosendorff 2000). Additionally, changes
in trade regulations might be more visible to the elites who have to be satisfied
than changes in trade volumes.
Many possibilities to enhance this model are given. The theory itself should
be revised, as it only seems to be applicable to part of the reality even for
electoral regimes and monarchies. To enhance the theoretical model in order
to cover other nondemocratic regime types like military regimes is certainly
what should come next. For example, one could argue that military and
clerical elites acquire capital due to their leading position within a regime
and therefore should behave like monarchies. Another way to develop this
theoretical framework further would be to figuratively open the black box
of inputs and to analyze which nondemocratic regimes prefer which tools to
regulate (or not) their foreign trade. Especially as tariffs can generate direct
income for the state, in contrast to non-tariff-barriers to trade such as quotas
and standards, the incentives for a government to implement one or the
other could be quite interesting under a political economy perspective. For
example, the state can maximize its revenues from trade either through tariffs
or through taxes on the, due to free trade, increased, income. Countries with
little infrastructure can more easily collect tariffs than taxes. The theory can
of course also be extended by a differentiating of assumptions. A possible way
to do this would be by distinguishing between high- and low-skilled workers
instead of assuming one homogenous labor force.
Furthermore, it would be interesting to test if these relationships are stable
with other methodical approaches. For example, instead of trade share of
GDP, one could use the predicted and actual share of a countries trade of
world trade by a gravitation model. Of course, one could and should try to
gather data from more countries as the sample used here might be biased
due to the availability and provision of data by the nondemocracies. Last
but not least, the theory clearly could improve on the part of policy making
within nondemocracies. In general, that is a major research gap that has to
be filled in order to understand actions of nondemocratic regimes. However,
the results make clear that there is more to say about nondemocracies than
statements based on their missing degree of democracy.
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