Download A Shadow Economy Model of Ethnic Conflict

A Shadow Economy Model of Ethnic
Conflict
Joseph J. St. Marie Ph.D
The University of Southern Mississippi
[email protected]
Samuel S. Stanton, Jr.
Grove City College
[email protected]
Shahdad Nagshspour Ph.D
The University of Southern Mississippi
[email protected]
A Shadow Economy Model of Ethnic Conflict
Introduction
In American cinema one of the most celebrated characters is Francis Ford Coppola’s
Vito Corleone. Known as the “Godfather” Vito oversees a mafia family with vast
nefarious dealings. On the other hand he also operates a legal enterprise, the “Genco”
olive oil company, importers of fine Sicilian olive oil. Don Vito takes part in the shadow
economy through the legal Genco import firm which most probably evades taxes, follows
its own employment procedures and is a front for the ‘families’ more nefarious illegal
activities such as gambling, smuggling, prostitution. Firmly embedded in the shadow
economy the Godfathers economic activities are difficult to measure. Perhaps even
more important are how his shadow economy activities affect the community in general,
do people voice their disgust or to they leave the community or “family”
The purpose of this paper is to examine the role the shadow economy has in the
initiation of ethnic conflict behavior. More specifically our goal is to see how one part of
the shadow economy—the legal portion--affects the propensity for minority groups to
initiate violence aimed at the economic and political institutions of the state. To this end
we examine the shadow economy by decomposing its constituent parts to gauge their
effects on the magnitude of ethic conflict behavior.
In this study we attempt to synthesize the shadow economy literature of economics with
the ethnic conflict behavior literature of political science in an attempt to generate a
political economy theory of ethnic conflict initiation. We proceed with this study in
several sections. First we examine the literatures, then, pulling from each discipline we
form a political economy theory of ethnic conflict behavior in our second section. In the
third section we outline our hypotheses for this study. In a fourth section we describe
our data and specify our models while in the fifth section we present our findings. Finally
we present our conclusions to this study.
Literature Review
The Shadow Economy
Each economy harbors an element seldom discussed save by economists and then only
in selected circles—the shadow economy. Shadow activities are activities that are
underground, covert or illegal. Governments have an interest in determining the size of
the shadow economy. First, governments need to provide accurate estimates of the size
of the economy and second to determine what activities lie outside the states regulatory
structure in order to bring these activities into the regulatory structure and derive
revenue.
While measuring the shadow economy is important, the definition of the shadow
economy is not uniform within the economic literature. Common definitions revolve
around economic activity that is not officially calculated in the GNP while Smith (1994)
defines it as, ”market-based production of goods and services, whether legal or illegal
that escapes detection in the official estimates.” Dell’Anno (2003 and Feige (1989)
provide a broad definition that accounts for,” those economic activities and the income
derived from that circumvent or otherwise government regulation, taxation or
observation.” German economist Friedrich Schneider (2005), who has done extensive
research on shadow economies worldwide, provides a definition we utilize in the main
with some revision, “The shadow economy includes unreported income from the
production of legal goods and services, either from monetary or barter transactions—and
so includes all economic activities that would generally be taxable were they reported to
the state (tax) authorities.” Our revision is that the illegal shadow economy is important
in the increase in the magnitude of the overall shadow economy and is a driving factor
when ethnic conflict behavior is present. Thus, while we do not measure the illegal
shadow economy in this work we note its importance for out theoretical basis. Table 1
details the various non-observable economic activities that comprise the shadow
economy.
From Schneider (2005, p. 5)
This taxonomy of underground, shadow economic activities comprise two axes, the
horizontal noting monetary and non-monetary transactions while the vertical axis
denotes legal and illegal activities. For our purposes this taxonomy fits well into
scenarios of ethnic conflict behavior and rebellion where the power of the state to control
disorder is at stake. To be sure, the capacity of the state to resist ethnic demands is
implicit in its capacity to regulate its economy.
The capacity of the state to harness its economy through various regulatory, law
enforcement or tax mechanisms can be seen in how successful the state controls legal
or illegal transactions.
Causes of the shadow economy
The economics literature considers the shadow economy primarily as a result of various
factors but in particular:
1. Increasing tax burdens, either direct (sales, value-added-tax, Income, real estate,
etc) or through increased social security contributions (increased withholding or
surcharges).
2. An increase in the number and intensity of regulations in the official economy,
especially in the labor markets.
3. Reductions in work hours either through layoffs or work slowdowns (reduced
working hours), early retirements and growing unemployment both in the private
and public sectors.
4. Decline in the loyalty of the populace toward the government and its regulations
or a decrease in the ability of the government to control the population and its
economic activities.
The influence of various types of taxation denotes how rising tax rates increase the
prevalence and size of shadow economies. Loayza (1996) in a study of 14 Latin
American nation’s finds that primary determinants of the shadow economy to be the tax
burden, labor market restrictions and the strength and efficiency of government
institutions. These findings indicate that the greater the tax burden the greater the
incentive to resort to the non-observable economy for labor as well as barter for heavily
taxed goods. Thus, major determinates of the shadow economy will be the overall tax
burden which when increasing tends to increase the size of the shadow economy as well
s the incentive to avoid “official” work. As seen in the above table this type activity
encompasses monetary transactions such as tax evasion or tax avoidance.
The intensity of the regulatory environment also affects the shadow economy. Johnson,
Kaufmann and Zoido-Lobaton (1998) demonstrate how labor market regulations for both
citizens and foreigners affect the incentive structure to avoid engagement in shadow
economy activities. Furthermore, the number of laws, regulations and license
requirements has been found to limit the choices for those individual seeking to
participate in the economy. De Soto (1989) argues this point by asserting that increased
regulation leads to increased entry costs in the official economy thus entrepreneurs favor
the unofficial economy where entry is easier. While technically illegal, these shadow
entrepreneurs fill a void created by an excessive regulatory state.
Increased labor regulation reduces official employment by creating incentives for firms
to hire shadow workers while cutting the hours of “official’ workers. Workers who have
had their work hours cut are provided with incentives to engage in shadow activities thus
increasing the overall size of the non-observable economy. Hunt (1999) agues that
Volkswagen workers who were limited in the hours they worked—against their wishes—
provided the labor for a home reconstruction and renovation boom. This sort of activity
is a type of tax evasion based upon barter of good and services or neighbor help which
in each instance result in lost tax revenue and an increase in the shadow economy.
Effects of the shadow economy on the state is also of interest to our study. Reduced
revenues can lead to either decreased public expenditures or a higher overall tax burden
to offset the loss. In the former case decreased public spending can lead to loss of
citizen loyalty, especially for minority groups who may rely upon income transfers or
government developmental aid. Sudden drops in spending can test the loyalty of even
majority groups. To be sure, once a public service is provided restricting or
discontinuing the service is difficult. While reducing public spending per-person may be
regime type dependent any reduction without an accompanying increase in replacement
benefits (tangible or intangible) or security will meet resentment in most societies. This is
especially important in developing nations.
A higher tax burden either in developed or developing nations signifies an attempt by
the government to increase its power or control over the population on one hand while
also deriving revenue on the other hand. Clearly state capacity is tied to its ability to
finance its endeavors and the ability to increase taxes to an optimum level creates this
ability. State capacity to exert its control over society is especially important in
developing countries, yet in segmented societies over-control may prod ethnic minorities
to seek autonomy or to rebel. For developed nations an increase in the tax burden leads
to a larger shadow economy as incentives for productive “official” employment is
lessened.
In both instances the logic of the Laffer Curve (Laffer 1979) is evident. In a developing
nation increased taxes beyond the optimum will lead to a decreased official sector and
increased shadow economy. As taxes rise an incentive to exit the official sector is
created. Theoretically when taxes reach one hundred percent of income employment in
the official economy would be nil while employment in the shadow economy would be
full. Alienated groups will resort to shadow economy activity especially if—as is the case
in many developing countries—they are economically disadvantaged vis-à-vis the
dominant group. This may also have political repercussions for state capacity and for
ethnic conflict behavior. In developed countries the political repercussions of an
increased tax burden will primarily be felt through the polls. In either instance an
increased tax burden has implications for the shadow economy, the official economy and
political implications.
The above discussion of the shadow economy revolves around those activities that are
legal, involving either monetary transactions or non-monetary transactions through tax
evasion or tax avoidance. However, many activities of the shadow economy are based
upon illegal monetary or non-monetary transactions. Monetary transactions might
include the trade of stolen goods, manufacture and distribution of illegal drugs, small
scale specialized manufacturing, prostitution, gambling smuggling, all types of fraud and
in general all non-violent felonious activity. Non-monetary illegal transactions include
barter for drugs, stolen goods, drug production for barter or personal use as well as theft
for ones personal use. These are they types of activities that make the shadow
economy difficult to measure especially if it is well established and relatively dependent
upon illegal activities. While not explicitly noted in the literature the implication is that
legal activities may eventually turn into illegal activities should the tax or regulatory
burden of the state increase to a significant level. This is especially true of in
underdeveloped economies where rule of law, judicial independence, onerous regulatory
regimes and corruption are present. In order to investigate the effects of the shadow
economy on ethnic conflict behavior we decompose the factors that lead to and
comprise the shadow economy. Once we specify these factors we test them to
determine their effects on the presence and magnitude of ethic conflict behavior.
Ethnic Conflict
Calling a conflict an ethnic conflict can cover a wide-range of behaviors and factors. We
define an ethnic conflict behavior as a conflict between communal groups that identify
themselves in terms of their ethnicity rather than class, geographic location, etc. In the
following discussion we develop the understanding of ethnicity, and ethnic conflict
behavior that will be used throughout the remainder of this study.
The terms minority and ethnic are used interchangeable for the purpose of this work.
Minority refers to being part of a group that is outnumbered in a civil society. Minority
groups in pluralistic governments often run the risk of being detrimentally affected by
state policy or by natural situations to the extent that conflict behavior is deemed a useful
or necessary step. Gurr (1985) and Saideman, Lanoue, Campenni and Stanton (2002)
use these terms in interchangeably, since most minority groups in the world today are
minorities based open ethnicity. The politicization of ethnicity and other identities that
has engendered new levels of conflict in the world since the 1980s are based in part on
grievances over inequality and past wrongs that linger. Also, groups within one state
looking at the activity of other groups similarly situated in other states have noticed a
success rate in conflict behavior that might make conflict behavior worthy of repeating in
their own state (Gurr 2000, xiv). Thus, ethnic conflict behavior is a protest or rebellion in
which at least one party to the dispute is an ethnic group. It is overshadowed by
concerns for international conflict and often masked by those conflicts.
Given the broad view of ethnicity that has been developed in the social sciences, we can
come to understand ethnic conflict behavior in many different ways. The ProtestantCatholic conflict in Northern Ireland is just as much an ethnic conflict behavior as the
Tamil-Sinhala conflict in Sri Lanka. The black versus white conflicts in the U.S. and
South Africa are ethnic conflict behaviors, as is the sectarian conflict between Shias and
Sunnis in Pakistan. Ashutosh Varshney explains the categories of ethnic conflict
behavior as being religious, racial, linguistic, or sectarian (2003). This categorization is
based on the idea that group identity; real or imagined is the basis of conflict behavior.
A theory of ethnic conflict behavior must also be rooted in an understanding that conflict
behavior is a security issue. Security for a group is threatened by lack of access to
resources, lack of economic opportunity or legal disenfranchisement. Access can be
lacking due to political actions of the state, social action by other groups, or general lack
of resources in the society. The problem is that actions taken to make a group more
secure, makes other groups feel less secure thereby causing a spiraling effect. A
dilemma is created by this spiral of security seeking, as all groups are left worse off than
they would be if no group sought to increase its own security (Jervis, 1978). The
spiraling of the security dilemma can be greatly enhanced by competition for scarce
resources, be they economic or political. Competition between groups or between a
group and a state for access and usage rights of resources can be exacerbated by
migration, self determination issues, social cleavages and class mobility, and the
repression of groups by the government.
Finally, before addressing the individual theories, we address the important concern
about any theory of collective action, namely the assumption of groups acting as rational
unitary actors. We choose to accept two primary arguments for the case of individuals
banding together in cooperative action. One, individuals will join collective action when
they believe that group action will benefit them more than they will lose personally by
joining the effort (Finkel and Muller, 1998), particularly where success is contingent on
group treatment (Horowitz, 1985). Two, Lichbach (1994) offers persuasive arguments
that collective action problems are regularly solved and we must move beyond them to
address important questions
Olzak (1992) offers an ecological theory of ethnic conflict behavior. The basis of this
theory is that competition between groups causes conflict. James (2002) refers to
competition as the moral equivalent of war. Competition is bred into societies from
childhood. It becomes a deeply embedded structure of human understanding and
affects the thinking and actions of individuals. When we translate this into the group
setting we see the same effect as between sports teams engaged in competition. The
struggle becomes “us vs. them”, a primal struggle for glory, reputation & prestige.
Competition between groups is in many instances is a healthy thing for the development
of a normal state as well as a productive and innovative economy. However if the
competition is biased in favor of one group or set of groups, and another group or set of
groups is intentionally or unintentionally disadvantaged, there is an increased likelihood
of conflict. The price of failure in this type of competition is the dissolution or extinction
of the group. The socio-economic changes that occur during unequal competition might
serve to increase the rate of conflict. This idea is closely related to the stratified look at
ethnic conflict behavior in Horowitz (1985). Where ethnic groups are ranked, there is a
greater likelihood of conflict than in systems where ethnic groups are not ranked.
Ranking is based on socio-economic standing and also according to access to the
political system (Szayna 2000).
While competition might be diminished between parallel groups, their relationships are
much more difficult to predict. While there is less generalized position, there is greater
mistrust and misperception and a lesser probability for collaboration. The voluntary
nature of the unranked system’s creation makes it less cohesive and more regionally
defined. This lessens the likelihood for ethnic conflict behavior, but does little to dampen
competition. Conflict has proven to be a more likely result of acute competition where
ethnic groups are more evenly dispersed throughout the state. Where groups are
dispersed throughout the state and where they are highly concentrated on the local level
the likelihood that ethnic competition will lead to ethnic conflict behavior is increased.
Competition may be so ingrained that it cannot be rooted out of the behavioral patterns
of people. As James (2002) pointed out, our ancestors bred it into us, and “thousands of
years of peace won’t breed it out of us,” (2002, 146). Competition for resources and
position become fuel for a greater dilemma of mankind. Any gain made by another
group will elicit a response from at least one other group in the society, thus decreasing
stability and increasing the likelihood of the security dilemma.
Snyder and Jervis (1999) explain that security dilemmas can be causes of intrastate
conflict by making either one or both sides to the conflict less secure because of the
actions taken by either side to make themselves more secure. The security dilemma
can affect the way in which collective security measures can be taken to intervene and
shorten the duration of the conflict or alleviate the conflict. The security dilemma can
lead to predatory behavior on the part of elites in the differing ethnic groups in society.
This point is reflected in Uvin (1999), where he discusses the predatory behavior of the
ruling elite in Rwanda.
Woodward (1999) argues that the security dilemma does cause intrastate conflict under
certain structural conditions. The three main structures that drive security dilemmas and
breed conflicts are; lack of national majority, anarchy, and deprivation (Woodward 1999,
85). Under such a structure, political leaders become predatory and are likely to use the
security dilemma to spark civil conflict. The use of community identification and the
social ramifications of identity can be quite profitable to the leadership of ethnic groups.
Posen (1993) argues that the collapse of governments makes the security dilemma
more acute. Posen (1993) applied the security dilemma theory to ethnic conflict study,
applying the theory as a means of understanding ethnic conflict behavior in situations of
collapsing regimes, or what he terms “emerging anarchy”, (1993, 27). Posen assumes
that in a situation of regime collapse, security is the first concern of all groups located in
the state, hence the security dilemma is a grave concern. What makes one side more
secure makes another side feel less secure and feel that it is necessary to increase its
strength, which in turn makes the original group less secure. In the end, the actions that
made the first group secure have made it less secure and the reaction of other groups to
the first group will only lead to a response from the original group which will make them
less secure. The ethnic security dilemma, then, is the result of one group trying to take
control of the state and causing all groups to be less secure. This is because the ethnic
competition within a state is for the control of the government or state and, where ethnic
politics are primary; it is essentially a contest for domination. Given these theoretical
insights we might expect state actions, in particular those leading to an increased
shadow economy to lead to ethnic conflict behavior.
Synthesis
In this section we construct a political economy model of ethnic conflict behavior.
Drawing on the economic literature we attempt to capture the essence of the shadow
economy with its dual effects on the economy and political spheres. We integrate the
ethnic conflict behavior literature into our construct to provide a model of ethnic conflict
behavior that based upon both the political and economic aspects inherent in the
shadow economy. We believe that the economic process that lead to or create the
conditions for ethnic conflict behavior are not analytically distinct from those political or
social process that lead to or foster ethnic conflict behavior. Therefore, we attempt to
fuse the two into a unified model. This model seeks to explain how elements of the
shadow economy impacts decisions on ethnic conflict behavior. Rather than measure
the overall size of the shadow economy we present a more fine grained analysis by
analyzing the elements of the shadow economy to determine their effects on ethnic
conflict behavior. We use the term shadow economy to denote the whole of the various
factors that encompass the notion of the shadow economy to avoid confusion. In later
sections we refer to particular factors and their effects.
Shadow Economy Theory of Ethnic Conflict
In this section we attempt to develop a theory of ethnic conflict behavior based on the
role the shadow economy plays in the overall political systems and the political/social
effects an increasing shadow economy may play.
We begin with the assumption that many minorities are under some sort of economic or
political disenfranchisement. While this situation may not always be the case, we
believe that most minorities as such feel economic pressures or political pressures from
the majority. In general we tend to assume for illustrative purposes that minorities, given
their inferior numbers are essentially in a security dilemma. The security dilemma may
be latent or acute. Clearly those with a prolonged or acute security dilemma will seek to
enhance their security by initiating a spiraling into conflict. On the other hand those with
a lessened dilemma may not resort to enhancing their security if they perceive equality
in the societal, political and economic spheres, while remaining in a latent security
dilemma situation. As with all security dilemmas the situation is fluid and a latent
dilemma may change as was the case in Sri Lanka.
For minority ethnic groups in general—we exclude minority groups who hold political
power as the Alawites in Syria—state action in the economic realm can have serious
consequences especially if it tends to exclude workers from high income employment,
long-term or public sector employment or raises the overall tax burden beyond the level
to sufficiently cover ones taxes. The literature points to the shadow economy as an
alternative to the “official’ economy. Moreover, while the shadow economy may be an
option for the ethnic majority it may be in the form of the legal shadow economy while
minority groups may be more inclined to actively engage in illegal shadow economic
activities.
We base part of our theoretical framework on the work of Albert Hirschman. Hirschman
(1970) in Exit, Voice and Loyalty, presents a theory based upon organizational behavior.
We see the state, and groups within the state, behaving in much the same manner as
Hirschman predicts individuals would in a firm. For Hirschman the behavioral options for
individuals in the firm are divided into three aspects. One may “voice” decent by
complaining about a deteriorating condition in the firm or if the individual sees no
increases in conditions they may exercise the option of “exit” thereby leaving the firm.
Related to but in a separate category is the notion of Loyalty. Loyalty is a predictor of
the likelihood of an individual using the “voice” or ‘exit” option. Graphically we could see
the relationship between the three concepts as a spectrum called loyalty. On the low
end or far right side we would place exit while on the opposite end with high loyalty we
would place voice.
Voice
Exit
Loyalty
In practice an Hirschman (p. 70) notes that there are two principle determinates of when
one resorts to voice or exit. The first is the extent to which the person is willing to trade
off the certainty of exit against the uncertainties of an improvement in the deteriorating
organization. Second, is the person’s assessment of their ability to influence the
organization. These calculi drive the voice/exit determination. Implicit in Hirschman’s
model is the important assumption that the firm or organization is in decline. Thus,
perceived or actual decline is an impetus for the person to begin making the voice/exit
calculus depending on the loyalty. Clearly exit/voice and loyalty are complex
interrelationships. As noted by Boroff and Lewin (1997) the imprecision of loyalty by
defining it as a tradeoff between exit and voice produces a tautology as, “The likelihood
of using voice depends on one’s loyalty which is the trade-off between using voice or
exiting…….we conceptualize loyalty as the degree to which a person identifies with an
organization…….loyalty, a much broader construct, measures one’s attitudes toward the
entire organization.” This fuzziness of this concept was not been lost on scholars as
loyalty has been defined as “giving public an private support to the organization or
practicing good citizenship as noted by Boroff and Lewin (1997, 53) we tend to argue for
purposes of this study that loyalty is good citizenship and acceptance of the current
political and economic institutions.
By applying this schema to ethnic minorities under conditions of the security dilemma,
we can show how the shadow economy in a country increases and how this increase
may be fueled by state actions. Moreover, we theorize, but do no test the notion, that in
extreme cases where exit is actively being sought, that the shadow economy ratio of
legal/illegal activities increases significantly in favor of the illegal. In political terms the
individual in the minority group has the choice of voicing his opinion through the political
process for redress of ethnic group grievances or through exiting the political system as
a whole. Exit in this case may-mean emigration or exit may be seen as a continuum
from being apolitical to engaging in ethnic conflict behavior. We assert that if the
individual does not leave the country but decides to exit they will exit through nonpeaceful means—ethnic conflict behavior. Therefore for our purposes political exit is
tantamount to the least violent form of ethnic conflict behavior. The underlying theme on
the continuum of voice and exit is as Hirschman notes, loyalty, and in this case it is
loyalty to the state. Some form of loyalty will lead individuals to voice their
dissatisfaction with a declining system either meekly or aggressively. While others
having less loyalty will seek the exit option as they have little loyalty. Exit may be less
physical than emotional and political. Political exit would have greater impact on ethnic
conflict behavior than physical exit would have.
Our theory regarding the shadow economy and its effects on ethnic conflict behavior
revolves around the concept of an increasing shadow economy creating the conditions
where ethnic conflict behavior becomes more likely. In sum, we theorize: that an
increase in the factors comprising the shadow economy increases the likelihood and
magnitude of ethnic conflict behavior. The basic logic of our argument follows the figure
below.
Stylized Model of an Increasing Shadow Economy
Percent of GDP as Shadow Economy
100%
Adapted from: Enste 2002.
The above diagram demonstrates how an increasingly large public sector or more
demands by the state on resources such as higher taxes or more onerous regulations
will create incentives for individuals to defect to the shadow economy. As state revenue
drops as a result of an increase in the shadow economy, we assume that increased
taxation etc will cause even further increases in the shadow economy. Eventually, the
public sector will decline as defections to the shadow economy make revenue collection
impossible. If we look at this scenario on a linear continuum we can see how
consolidation of state power and economic development creates conditions of economic
prosperity. Economic prosperity leads to the expansion to the public sector, creates
"institutional sclerosis” to use Olson’s terminology, and eventually defections to the
shadow economy. Increasing defection and minority grievances leads to potential ethnic
security dilemmas. Furthermore an increase in the shadow economy for all ethnic
groups leads to the ethnic conflict behavior in disenfranchised minorities and a decline in
state authority followed by civil war and finally institutional change. Graphically we
superimpose this process on the shadow economy model as follows:
Consolidation of State Power/Decrease in Shadow Economy
Increasing Economic Prosperity
Expansion of Public Sector
Defections to Shadow Economy
Potential Ethnic Security Dilemma
Increase in the Shadow Economy
Rebellion & Ethnic conflict behavior
Decline of State Authority
Civil War
Institutional
Change
Clearly there are limitations to our analysis. First, is the direction of causality question—
does the shadow economy cause the ethnic conflict behavior or does the ethnic conflict
behavior cause the shadow economy. We believe that ethnic conflict behavior is indeed
a path dependent process and that while the process can be halted or redirected that
certain steps in general are necessary for ethnic conflict behavior or rebellion to occur.
At the same time the processes that create an increase in the shadow economy follow a
similar path and logic. We theorize that instead of attempting to determine the direction
of causality that conceptualizing the co-movement of both processes is analytically
useful for capturing the essence of the individual’s decision to either to use voice or to
exit the political system.
Second, we acknowledge that the shadow economy is a hybrid of the legal and the
illegal. The problem for this study is how the ratio of each component (legal/illegal) is
measured. Furthermore at what point in the increase in shadow economy and increase
in ethnic conflict behavior does the ratio move from majority legal to majority illegal. This
legal/illegal switch may indeed occur, yet the tracking and measurement of such
activities is difficult and beyond the scope of this first cut. To eliminate this theoretical
clutter we start with the assumption that the legal an illegal parts of the shadow economy
can not accurately be determined (see Schneider 2005 for more detail) thus we take the
shadow economy as a unified or unitary concept. However, we do illuminate the notion
of the shadow economy and its effects on ethnic conflict behavior and the magnitude of
such behavior by examining the constituent parts of the shadow economy. This
approach avoids the pitfalls of calculating the legal/illegal components of the shadow
economy while providing a more nuanced analysis. We believe that our preliminary
analysis provided below points to interesting findings and further directions for research.
Hypotheses
For this study we do not examine the size of the shadow economy directly but instead
take a fine granted look at those elements that comprise the shadow economy.
Theoretically we know the shadow economy is caused by increasing tax burdens, a
burdensome regulatory environment, work/wage related issued and overall decline in the
loyalty of the population. We disaggregate these elements of the shadow economy for
this work by testing the individual elements that contribute to the shadow economy.
Friedman et al. (2000) and Johnson et. all. (1998) find a correlation between the level of
fiscal burden and the level of unofficial economic activity. A high fiscal burden has been
found to drive legitimate business underground to avoid onerous taxation (Loayza,
1996). In a similar vein high barriers to trade are found to have the same effect as noted
by Dreher and Siemers (2005). Furthermore Dreher and Schneider (2006) find support
that tight credit markets, higher minimum wages and stricter administrative procedures
produce an expansion in the shadow economy. Conversely, and in line with out
argument they also find that better rule of law, governance, judicial independence,
impartial courts produce not only produce a smaller shadow economy but corruption as
well.
We include an element on the informal market based upon the Transparency
International, Corruption Perception Index, while not a “true” shadow economy measure
the TI index does accurately measure the level of corruption in a country. Theoretically
we assume that corruption can be both a compliment and substitute for the shadow
economy. Choi and Thum (2004) and Dreher, Kostsogiannis and McCorriston (2005a)
find that corruption can be a substitute for the shadow economy. In particular lowincome contries corruption and the shadow economy seem to be complimentary in
nature as noted by Hendrix et. al. (1999) and Johnson et. al. (1997).
To summarize, the shadow economy is present in all economies and is affected by
various factors such as regulation and property rights. Owing to the difficulty in
accurately measuring the shadow economy we utilize those factors that comprise the
shadow economy in this analysis. To determine the effects we model these factors
independently to determine their effects upon ethnic conflict as measured by protest and
rebellion. Given the above we develop the following hypotheses relating to our study.
We also recognize that scholarship in recent years (Hegre, et al 2001, Marshall and Gurr
2004) has focused on transitional periods in democratizing states as a better fit for
causation of ethnic conflict. We consider this, but feel that a better means of testing the
relationship of democratization and ethnic conflict is to look at economic freedom that is
assumed to accompany or precede democratization processes.
H1: As the size of the shadow economy increases, as represented by its constituent
parts, so does the magnitude of ethnic protest or ethnic rebellion.
H1a: As economic freedom increases the level of ethnic conflict will increase.
H1b: As tariffs increase ethnic conflict will increase.
H1c: As tax rates and government expenditures increase ethnic conflict will
increase.
H1d: As government intervention in the economy increases ethnic conflict will
increase.
H1e: As inflation increases ethnic conflict will increase.
H1f: As discrimination against foreign investment increases ethnic conflict will
increase.
H1g: As government regulation of banking increases ethnic conflict will increase.
H1h: As government control of wages and prices increases ethnic conflict will
increase.
H1i: As restrictions on private property increase ethnic conflict will increase.
Hj1: As government regulation of new businesses increases ethnic conflict will
increase.
H1k: As the scope of the informal market increases ethnic conflict will increase.
Data, Models, and Findings
Testing our hypotheses requires the use of data from multiple sources. We examined
several sources of data and merged data to form a unique dataset. Our dataset
examines 115 countries. These 115 countries all have at least one ethnic minority group
that is politically active. While our preference would be to conduct a cross-sectional
time-series analysis of ethnic conflict in these 115 countries, data issues kept this from
being possible. We do however examine each of these countries in 6 years (19952000). This makes our unit of analysis a country-year. This provides us with 690 for our
dataset.
The dependent concept in our study is ethnic conflict. Ethnic conflict takes on two
distinct forms. One is protest behavior, behavior designed to influence government to
change policy or make new policy. The second is rebellion, a hostile militarized attempt
to change the government (Saideman, Lanoue, Campenni and Stanton 2002).
Therefore we employ two variables—rebellion and protest—taken from the Minorities at
Risk (MAR) data.1 Rebellion and Protest are group specific for each country in each
year of the MAR data. We took an average of the level of rebellion and the level of
protest in each country in each of the six years in our data. The following tables (Table 1
and Table 2) show the frequency distribution for each of these dependent variables.
Table 1 indicates the level of measurement of protest is ordinal. The median response
is found in the category of symbolic opposition, the modal category of demonstration
isless than 10K. This indicates more countries experienced a demonstration of at less
than 10,000 people as their average level of protest in a given year than experienced
any other single form of protest in a given year between 1995 and 2000.
1
The MAR is archived at: www.cidcm.umd.edu/inscr/mar.html access to this data is provided by a
downloadable program (MARGene) located at: www.cidcm.umd.edu/inscr/mar/margene.htm.
Table 1: Average Level of Protest
Response
None
Reported
Verbal
Opposition
Symbolic
Opposition
Demonstration
Less than 10K
Demonstration
Less than
100K
Demonstration
More than
100K
Totals
Missing
Totals
Frequency
Percent
Valid Percent
Cumulative
Percent
157
22.8
23.1
23.1
84
12.2
12.4
35.4
175
25.4
25.7
61.2
190
27.5
27.9
89.1
55
8.0
8.1
97.2
19
2.8
2.8
100.0
680
10
690
98.6
1.4
100.0
100.0
Frequency
Percent
Valid Percent
Cumulative
Percent
422
61.2
62.3
62.3
60
8.7
8.9
71.2
32
4.6
4.7
75.9
37
5.4
5.5
81.4
46
6.7
6.8
88.2
19
2.8
2.8
91.0
29
4.2
4.3
95.3
32
4.6
4.7
100.0
677
13
690
98.1
1.9
100.0
100.0
Table 2: Average Level of Protest
Response
None
Reported
Political
Banditry
Campaigns of
Terrorism
Local
Rebellion
Small-scale
Guerilla
Activity
Intermediate
Guerilla
Activity
Large-scale
Guerrilla
Activity
Protracted
Civil War
Totals
Missing
Totals
Table 2 shows the modal case to be, none reported. The median value for rebellion is
also, none reported. Ethnic rebellion is a rare event. In most countries, in most years
ethnic rebellion simply does not occur.
To test eleven specific hypotheses about the relationship of the shadow economy and
ethnic conflict we took data from a dataset compiled by researchers at the Heritage
Foundation. The data is found in the 2006 Index of Economic Freedom.2 Chapter five
(Beach and Miles 2006) explains in great detail the variables in this dataset and the
sources from which they are derived.3 Table 3 shows each of the independent variables
and its corresponding median value (each of these variables is ordinal in measure).
Table 3: Independent Variables
Variable
Valid
Economic Freedom
623
Trade Policy
623
Fiscal Burden of
623
Government on Citizens
Government Intervention
623
in Economy
Monetary Policy
623
Foreign Investment and
623
Capital Flow
Banking and Finance
623
Wage and Price Control
623
Property Rights
623
Regulation of New
621
Business
Informal Market
623
Median
3
4
4
3
4
3
3
3
3
4
4
Economic Freedom is a measure of the overall economic freedom of a country, it is
based on data collected on over 160 countries since 1995. Scores range from total
economic freedom (1), characterized by a free market with little government involvement
and regulation, to repressed (4), characterized by a highly government controlled and
centralized market. While the other ten independent variables are part of the theoretical
development of this variable, we found no significant covariation between this variable
and the other ten variables. We also found no significant autocorrelation between this
variable and the other ten independent variables. The median value is 3 (mostly unfree).
Trade Policy refers to tariffs a country levies against imports and exports. This data was
collected by Beach and Miles (2006) from the World Bank where available. When World
Bank data was not available the data was derived from a country’s average tariff rates or
from revenue raised from tariffs. The values are weighted by average imports from a
country’s trading partners. The values range from 1 (very low) a tariff rate of less than or
equal to 2.5 % to 5 (very high) a tariff rate of over 20 %. The median score (4)
represents average tariff rates between 15% to 17.5%
2
The 2006 Index of Economic Freedom is archived at:
www.heritage.org/research/features/index/downloads.cfm.
3
See fn2.
Fiscal Burden of Government on Citizens is based on three factors. One is rate of
individual income tax. The second is the rate of corporate taxation. The third factor is
change in government expenditures from the previous year. The purpose of this
variable is to examine how much burden the government creates on the population by
removal of financial resources from the private sector. This allows a determination to be
made on whether government spending exceeds the financial resources extracted from
society. The values range from 1 very low fiscal burden (characterized by less than10%
individual tax rates, 15% corporate tax rates and decrease of at least 4% in government
expenditures from the previous year) to very high fiscal burden (tax rates exceeding 50%
for individuals and 35% for corporations and increased expenditure of at least 3% from
the previous year). The median value (4) represents tax rates of 40-45% for individuals,
30-33% for corporations, and a moderate 1-2% increase in government expenditures.
Government Intervention in the economy measures the amount of Gross Domestic
Product (GDP) that is consumed by the state. This measure compliments the Fiscal
Burden measure. This measure accounts for difference between government
consumption and government production, but does not include transfer payments made
by the state to individuals. The values range from very low (5% or less government
consumption) to very high (government consumption greater than 40%). The median
value (3) represents a moderate government intervention rate of 10-20% GDP
consumption. This measure is also suitable for noting the strength of the state, as a
state that consumes more of the GDP will have greater capacity for strong state
behavior.
Monetary Policy is a measure of inflation. Inflation distorts pricing, confiscates wealth,
raises the cost of doing business and undermines a free society (Beach and Miles
2006). While there is no one monetary theory that is universally subscribed to today,
there is general agreement that zero inflation is the goal of monetary policy. The scores
range from 1 (very low), inflation less than 3%, to 5 (very high), inflation greater than
20%. The median value (4) represents high inflation rates of 12-20%.
Foreign Investment and capital flow scrutinizes the amount of restriction on foreign
investment in a country in a given year. Factors such as legality of foreign land
ownership, foreign ownership of businesses, repatriation of earnings, and restrictions on
capital transactions are analyzed to create this measure. The range is 1 (very low),
where there is very little difference in regulation between foreign and domestic
investments and ownerships, to 5 (very high), where foreign investments are
discouraged by restrictive policies on ownership and investment. The median value (3)
represents a moderate amount of barriers to foreign investment where foreign
investment is encouraged but may not receive equal treatment with domestic investment
in all sectors of the economy.
Banking and Finance refers to a measure of how banking is restricted by the
government. The measure ranges from very low (prudent regulation and government
has minor overall role) to very high (government highly involved in banking regulation
and most banks owned by the state). The median value is 3, meaning that the
government has substantial involvement in regulation and ownership of financial
institutions.
Wage and Price Control measures how much the market or how much the government
controls wages and prices in a society. A low value of 1 represent the market setting the
prices of goods and the wages workers earn with little influence from a government
created minimum wage. A high value of 5 represents complete control of prices and
wages by the state. The median value of 3 represents government control of some
pricing through ownership or subsidies and/or government-set wages apply to a large
portion of the workforce.
Property Rights measures the ability for individuals to accumulate property in a country.
The values range from 1 (very high), meaning individuals are guaranteed the right to
acquire private property by the state and the legal system enforces contracts, to 5 (very
low) meaning that the state has outlawed private property or that the country is
experiencing such chaos that there is no possibility of protecting private property rights.
The median value is 3 (moderate) meaning that private property rights exist, but the
legal system is inefficient in protecting these rights and that state corruption exists and
expropriation of the property by the state is possible.
Regulation of New Business measures the level of state interference in the creation and
development of new businesses. Particularly this measure seeks to see if regulations
are evenly applied across the board regardless of who might create or operate a
business. Values range from 1 (very low regulation), where regulations are evenly
applied and not much of a burden on new business, to 5 (very high) where state
ownership of business and industry impede creation of new business and where
corruption and misapplication of the regulations is widespread. The median value for
this variable is 4 representing high levels of complication in opening and managing new
businesses, haphazard application of existing rules (where they are even published) and
high levels of corruption creating undue burden on owners.
The final independent variable is measures Informal Market activity. Informal markets
are not necessarily illegal and often are very beneficial to societies. They allow people
to trade goods and services outside the normal restrictions of a government controlled
marketplace (such as a craftsmen trading services rather than individually purchasing
said services from one another). This variable measures the extent of this informal
market and ranges from 1 (very low) where the free-market economy makes informal
markets rather unnecessary to 5 (very high) where the informal market is larger than the
measurable formal economy of the society. The median value is 4 (high) meaning that
substantial levels of informal marketing of labor, intellectual property, and consumer
goods/services does exist, but does not outperform the existing formal market.
Literature on ethnic conflict suggests that other causal factors matter. To control, in a
general manner, for these other factors we borrow four variables from the MAR data.4
The first is group spatial concentration, measuring how concentrated groups are in a
state in a given year. Spatial concentration of groups has shown itself to be an
important factor in ethnic rebellion. The second is the index of average cultural
differentials between groups in a state, which looks at how much cultural difference
exists between ethnic minority groups and the majority population. The third is an index
of economic differentials, which measures whether ethnic minority groups are
economically advantaged or disadvantaged (and to what extent) compared with the
majority population. The final variable used is an index of average political differentials
measuring the extent of political advantage or disadvantage of ethnic minority groups in
comparison to the majority population.
4
See fn 1.
Finally, to ensure that fixed and random effects are controlled for in our model, we
include dummy variables for each year in the dataset and a dummy for whether or not
the country in question is part of the global north or global south. Wald testing of
correlation preempted us from including a dummy for each individual country. But, we
believe that it is important to consider whether or not a country is considered to be part
of the industrialized, developed global north, or part of the under-industrialized,
developing global south. Countries in the global south have different circumstances of
economic and political importance than do countries in the global north. 91 of the 115
countries in our dataset are found in the global south (with six cases for each country in
the data set, this represents 79.1% of all cases in our data).5
We do not have sufficient time intervals in the data to consider creating a time-series
model. This left us the option of a straight snap-shot test or a panel study. Because we
have a continuous time line, we chose the former and included dummies for each year to
account for random effects that might occur in the data due to covering six years.
The models are maximum likelihood estimators for ordinal data (ordered logistical
regressions). We ran one model for protest and one model for rebellion. To determine
the best specification of the models using the variables incorporated in our dataset, we
employed Wald testing to ensure that inclusions of variables did not produce coefficients
simultaneously equal to zero, and used differences in BIC’ (Bayesian Information
Criterion (prime)) to determine the best fit of variables in the model. The BIC’ for the
model containing all the variables was smaller than the BIC’ for any of the models with
one or more variables removed, indicating that the full model is the best fit.
Table 4 displays the results of our models. This display does not include the control
variables for each time period included in the data (none of these were statistically
significant at the .05 level or higher). Since the models are MLE models, the coefficients
do not equal the amount of change caused in the dependent variable by a one unit
change in the independent variable. Instead they represent a value that can be placed
in a standardization formula to explain how much likelihood there is of an increase in the
value of the dependent variable if the value of the independent variable increases. After
discussing the actual results of the models, we will turn to a discussion of the real effect
of the independent variables that are statistically significant on the dependent variables.
The LR Chi-square for the protest model is 112.643 and is statistically significant at the
.001 level. We are safe to infer from this model to the population of countries in the
world. Given the normal distribution of the LR Chi-square we can use the Cragg and
Uhler R-square to explain variance in the dependent variable explained by the inclusion
of the independent variables in the model. The Cragg and Uhler R-square for protest is
.182, which means we can explain 18.2% of the variance in the dependent variable with
this model.
5
We do not include a variable to measure GDP or GDP Per Capita in the model. The literature would
indicate the usefulness of such a variable, however, there were numerous indicators of collinearity with
Economic Freedom, Fiscal Burden, and Foreign Investment. It was more important to discover the impact
of these variables on ethnic conflict than to maintain a measure of state economic health. We also believed
theoretically that Government Intervention and the Political Differentials measurements satisfy the need to
measure the strength of the state.
The LR Chi-square for the rebellion model is 125.395 and this is significant at the .001
level. We are safe to infer to the general population findings from this sample model.
The Cragg and Uhler R-square for this model is .206. The inclusion of the independent
variables explains 20.6% of the variance in rebellion in this model.
Table 4. Results of Ordered Logistic Model for Protest and Rebellion
Variable
Protest
Rebellion
Economic Freedom
-.739**
-.410
.260
.311
Trade Policy
.379**
.257*
.100
.119
Fiscal Burden of
.181
.123
Government on Citizens
.124
.141
Government Intervention
.179*
-.033
in Economy
.089
.102
Monetary Policy
.102
.001
.070
.081
Foreign Investment and
-.086
-.038
Capital Flow
.147
.168
Banking and Finance
.138
.433**
.131
.155
Wage and Price Control
-.229
.746**
.145
.179
Property Rights
-.575**
-.431*
.162
.183
Regulation of New
.093
.017
Business
.133
.165
Informal Market
.252*
.345**
.110
.126
Group Spatial
.089
.201
Concentration
.089
.108
Cultural Differentials
.232*
-.340**
.097
.117
Economic Differentials
.203**
.137*
.058
.065
Political Differentials
-.006
.118
.072
.081
Global North/South
-.080
.285
.231
.302
Italicized numbers in each cell are the std. error. * p > .05, ** p> .01 for protest N=588
For rebellion N=586
The findings for protest indicate that economic freedom, trade policy, government
intervention in the economy, property rights, the informal market, cultural differentials,
and economic differentials are statistically significant. The positive or negative directions
of the coefficient for each of these shows support for the hypotheses offered, except
property rights. The direction of the coefficient for property rights shows that as private
property rights increase the amount of protest will also increase. The negative
coefficient for economic freedom represents support for our finding, because in our data
economic freedom is greatest the lower the value and conflict is greater in magnitude at
the high end of the scale. Our findings show more freedom leads to more conflict. This
may clash with findings in recent literature arguing that higher conflict is associated with
transitional periods from autocracy to democracy (in consideration of democracy being
associated with more economic freedom).6
In terms of the substance of these findings, we turn to the use of post-estimation
evaluation of standardized coefficients.7 Table 5 shows how much a one standard
deviation increase in the standardized value of the statistically significant independent
variables will change the value of protest based on full XY standardization of the logit
coefficient. Table 6 shows the same information for rebellion.
Table 5: Effect of One Standard Deviation Increase on Protest
Variable
Change in Protest
Economic Freedom
-.815
Trade Policy
1.20
Government Intervention in Economy
1.02
Property Rights
-1.08
Informal Market
1.31
Cultural Differentials
.91
Economic Differentials
1.75
This indicates that as economic freedom increases (which represents a decrease in
economic freedom given our coding of the variable) protest will increase by .815. This
makes some substantive sense even though protest is measured on an ordinal scale.
What it shows is an approximately one unit increase in protest when economic freedom
increases. The finding regarding property rights is counter to our hypotheses, but if
greater right to property is associated with more economic freedom, then this finding is
consistent with the finding regarding economic freedom. The finding regarding informal
markets is most promising. A standard deviation increase in informal market share will
cause an approximately one unit increase in the magnitude of protest.
In regard to rebellion we find trade policy, banking and finance regulation, wage and
price controls, property rights, informal market, cultural differentials and economic
differentials to be statistically significant. As found in the protest model, property rights
have a negative relationship with rebellion. As restrictions on private property rights
decrease rebellion is actually shown to increase in this model. This is less surprising
given the findings regarding economic freedom in the protest model. As seen in Table 6,
for each standard deviation increase in the value of property rights, rebellion will actually
decrease approximately one level.
Overall we find statistically significant support for three of our hypotheses when
measuring ethnic conflict as protest and support for four of our hypotheses when
measuring ethnic conflict as rebellion. We also find statistically significant rejection of
our two hypotheses when using protest to measure ethnic conflict and one hypothesis
6
Discussions of the U-shaped conflict curve in relation to autocracy and democracy can be found in Hegre,
et al (2001), Zakaria (2003), Mansfeld and Snyder (2004), Marshall and Gurr (2004).
7
Post-estimation evaluations were performed using the SPOST commands created by J. Scott Long and
Jeremy Freese for use with STATA. These commands can be downloaded into stata directly using that
program’s net search function, or you can find them archived at: www.indiana.edu/~jslsoc/stata.
when using rebellion to measure ethnic conflict. Table 7 summarizes our findings in
relation to the hypotheses.
Table 6: Effect of One Standard Deviation Increase on Rebellion
Variable
Change in Rebellion
Trade Policy
1.20
Banking and Finance
.99
Wage and Price Controls
.85
Property Rights
-1.07
Informal Market
1.30
Cultural Differentials
-.91
Economic Differentials
1.75
Further we find no statistical significance for political differentials when considering
conflict as protest or rebellion and a negative relationship between cultural differentials
and conflict behavior measured as rebellion. Also, we find no relationship between
whether a state is part of the global south and conflict behavior—which would indicate
that conflict behavior does not respect the differences of circumstances faced by states
that are in the global south as compared to states in the global north. In the conclusion
section we will turn to discussing the implications of these findings.
Table 7: Summary of Findings in Relation to Hypotheses
Hypothesis
Protest
Rebellion
Economic Freedom
Significant support found
No statistically significant
for hypothesis
finding
Tariffs
Significant support found
Significant support found
for hypothesis
for hypothesis
Tax Rates and Govt.
No statistically significant
No statistically significant
Expenditures
finding
finding
Government Intervention
Significant support found
No statistically significant
in Economy
for hypothesis
finding
Inflation/Monetary Policy
No statistically significant
No statistically significant
finding
finding
Foreign Investment
No statistically significant
No statistically significant
finding
finding
Banking Regulation
No statistically significant
Significant support found
finding
for hypothesis
Wage and Price Control
No statistically significant
Significant support found
finding
for hypothesis
Private Property
Significant finding in
Significant finding in
opposite direction of
opposite direction of
hypothesis
hypothesis
Regulation of New
No statistically significant
No statistically significant
Business
finding
finding
Informal Market
Significant support found
Significant support found
for hypothesis
for hypothesis
Conclusions
There are two major areas we address in our conclusions. One is mechanical limitations
and issues in our study. The second is what the findings tell us about the relationship of
shadow economies and ethnic conflict.
Our modeling suffers from two general limitations. One limitation of our model is the
inability to do a time-series analysis that could show significantly different or similar
results and account in a much better fashion than we managed for random effects. The
data simply did not exist for enough countries and years for us to complete a time-series
analysis at this time. This does give us direction for future research, as scholars should
increase the time frame of the factors in our models and determine if the effect of
shadow economy on ethnic conflict is simply a current phenomenon or has traceable
roots dating back at least to the Cold War era.
The second modeling limitation is the inability to build a single complex measure for
shadow economy. We attempted this in a earlier project with less than stellar results.
Other scholarship has created a measure of shadow economy as a percentage of
overall GNP (Schneider 2005), but this measure is available currently only for certain
years restricting its use to panel studies.
This study creates a shadow economy model of ethnic conflict behavior by decomposing
and measuring the factors that contribute to the shadow economy. Our primary findings
indicate that there is considerable support for the proposition that elements of the
shadow economy do in fact affect the presence and magnitude of protest and rebellion.
Taken as a whole our results explain 18% of variation in protest and 20% of variation in
rebellion. This finding is consistent with previous research stressing the importance of
economics in ethnic conflict behavior.
Our results also indicate that common motivators exist for protest and rebellion, namely
tariff rates, while informal markets have opposite effect. Tariff policy can have an overall
effect on a nation by decreasing exports, the accumulation of foreign currency reserves
and restrict business development. Especially important in developing countries are
sectors like agriculture and textiles that employ many and are adversely affected by
tariffs. Clearly unemployment and loss of income can lead to protest and rebellion in the
affected population. Considering many ethnic groups and especially ethnic minorities
are in general economically disadvantaged trade policy would affect create a
disproportional hardship.
The informal market was found to have a significant effect on the magnitude of rebellion.
We conclude that an increased informal market indicates an underlying weakness of the
entire economy based upon corruption and shadow economy activities. The net effect
for minorities is decreased income, decreased economic opportunities and the possible
movement into the illegal portion of the shadow economy—the drug or arms trade. Such
a lack of governance and attending economic problems will spawn movements seeking
more minority autonomy or even exit from the political system.
One finding that does not conform to our theoretical construct is that of private property.
Private property was found to be significant but in the opposite direction of our theory.
To reiterate we hypothesized that as restrictions on private property increase so does
ethnic conflict. Our results indicate that the increase in restrictions on private property
decreased ethnic conflict. One explanation for this finding is that while restrictions
increase, people and especially ethnic minority’s move to those areas of the shadow
economy we are unable to measure. These include monetary transaction such as tax
avoidance, tax evasion, unreported income and non-monetary transactions such as
barter for services, do-it-yourself work that are difficult at best to accurately measure. In
sum, restrictions on private property will crate a hoarding effect congruent with the
formation of the shadow economy. A second explanation is linked to our finding
regarding economic freedom, where there is more economic freedom there is more
conflict, part of economic freedom may be loosening of private property restrictions.
Although testing in our data showed no covariation or autocorrelation between economic
freedom and private property rights.
The models did not produce statistically significant findings for four variables, monetary
policy (inflation), foreign investment, regulation of new businesses and fiscal burden of
government. Monetary policy or inflation may not be significant as a move to the
shadow economy increasingly consumes the formal market, thus becoming impossible
to measure. For example, uncontrollable inflation will drive people to informal means of
barter or markets. Foreign direct investment is a factor that has long lead times—the
time needed to build the factory or extract minerals—thus may not be affected by short
term fluctuations. Surprisingly regulation of new business provided no significant
relationship in the direction of our hypotheses. One possibility is that entrepreneurs
simply do not start legitimate businesses or do not start a business at all. We believe
that onerous regulation will force business underground into the shadow economy that
again is difficult to measure. Tax rates and fiscal burden also have a different
relationship than was hypothesized. Again we believe that an opposite relationship is an
indication of a move to the shadow economy. As noted in the literature review each of
these variables is a primary factor in the creation and expansion of the shadow
economy. We believe that each of these four variables may not be significant in our
model since they are not only indicators of the presence and increase in the shadow
economy but more importantly that they may be future indicators of ethnic conflict. Due
to data limitations we do not test for lagged effects, thus we are not able to fully exploit
these factors in our analysis.
We find mixed results for three variables—Economic Freedom, banking regulation and
wage and price controls. Economic freedom is significant for protest but not for
rebellion. We believe that the significance for protest is predicted by theory. As
economic freedom decreases the level of protest will also increase. This is both logical
and evident in many case studies. Conversely for rebellion economic freedom is not
significant. We believe that once the tipping point is reached for rebellion to begin that
decreasing the already dismal economic environment may indeed be irrelevant for the
initiation of a rebellion. Furthermore we also believe that banking regulation and wage
and price controls to reflect that same relationships as the economic freedom variable
One direction for further research is a decomposition of the factors that contribute to the
shadow economy to determine specific policies and their effect on the overall shadow
economy and potential protest/rebellion. A second avenue would be an examination of
thresholds. Clearly ethnic conflict is a rare multi-factor occurrence. An examination of
the various factors and how they contribute to building and ultimately to actual ethnic
conflict is in order. While multiple thresholds are part of the equation, we believe our
present research is a stating point in disentangling the economic factors leading to
ethnic conflict. Research on the shadow economy also touches on factors that may lead
to terrorism and insurgency, thus providing an avenue for future research.
To conclude, our research finds interesting relationships between the shadow economy
and ethnic conflict. We feel this first cut at an important element of the overall ethnic
conflict/civil war research program contributes to the literature and study of conflict
processes by highlighting a frequently ignored dynamic of internal conflict.
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