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E/ESCWA/EDID/2017/Technical Paper.21
11 December 2017
ORIGINAL: ENGLISH
Economic and Social Commission for Western Asia (ESCWA)
Economic Justice in the Arab Region
By
Sama El-Hage Sleiman
Salim Araji
Ahmad Kamaly
Hala Tarabay
United Nations
Beirut, 2017
______________________
Note: This document has been reproduced in the form in which it was received, without formal editing. The opinions expressed are
those of the author and do not necessarily reflect the views of ESCWA.
.
elhagesleiman@un.org
17-00766
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Abstract
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I. Introduction & Motivation
Economic growth has been in the center of attention of policymakers for quite some time. It has been
considered an indicator of success of a regime to the extent that it has become an ultimate objective by itself.
This direction is dangerous since it diverges attention from the prime purpose of economic growth that is to
improve the welfare of the society. In this context, the concept of economic justice is very critical as it
refocuses the aim of economic system and economic policies toward people’s welfare. The core of justice is
dual: equal opportunities and fair distribution of benefits.
The concept of economic justice is very relevant to the Arab region. In fact, it can be argued that weak
economic justice contributed to the eruption of the Arab Spring in 2011 in Tunisia and Egypt. Prior to 2011,
both Egypt and Tunisia enjoyed high economic growth supported by upbeat fundamentals. These strong
fundamentals made both countries weather well the woes of the global financial crisis. International
agencies such as the World Bank (WB) and the International Monetary Fund (IMF) praised the conduct of
economic policies in Egypt and Tunisia signaling their positive economic growth. Still, some voices in both
countries alerted to the issue of inclusivity of growth. Despite this high growth, large segments of the
population did not witness significant improvement in their well-beings and some were made strictly worse
off. Notions such as “trickle-down effect” started to emerge responding to this serious phenomenon and
warning about it. The weak governance regarding voice and accountability in the Arab countries have
belittled this problem in the eyes of policymakers as they were contended with strong macroeconomic
performance and the vote of confidence echoed in various WB and IMF reports. Nevertheless, rampant
unemployment especially among the youth reaching 30% and 42% in 2011 in Egypt and Tunisia respectively,
stagnant poverty and rising inequality prior to 2011 made large segments of the population have serious
grievances (Achy, 2011; El-Khawas, 2012; Ghanem, 2014). These grievances were associated with the core
pillars of economic justice.
It is safe to argue that economic justice does not contradict economic efficiency. For example, a country
which suffers from economic injustice may suffer from widespread youth unemployment or a portion of
labor that are engaging in jobs below their qualifications and skills. In this case making the country more just
economically would raise output and growth and place the economy is a strictly better equilibrium (Pareto
optimal). In addition, poverty, a major problem in many Arab countries, could be drastically reduced by
improving economic justice. Economic justice would increase wages especially for the poor.
Economic justice does not reflect only on the economic front. Economic justice is associated with more
fundamental concepts such as fairness, equality in opportunities, and utilitarianism. These concepts are
particularly important for the region which is usually criticized on the ground of low justice and weak
governance. Improving economic justice then would not only lead to higher equilibrium but also this
equilibrium would be more just and more inclusive.
The 2030 Agenda is a transformative plan to push countries toward sustainable development. Given its three
dimensions: economic, social and environmental, the Agenda puts the welfare and the wellbeing of the
individual in the center of attention. Consequently, a high level of economic growth which does not take
into consideration economic justice dimension is not consistent with the 2030 Agenda; it leaves marginalized
segments of the population suffering from poverty and low level of human capital. This implies that
prioritizing economic justice is a key catalyst and impetus to achieve the Sustainable Development Goals
(SDGs).
This study attempts, for the first time, to gauge the level of economic justice in the Arab region. More
specifically, building on a conceptual framework defining the elements of economic justice, the study
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proceeds by adopting a statistical framework to construct a composite index of economic justice in the
region. After undergoing a series of robustness checks, this composite justice index is then compared to
other relevant indices such as Human Development Index, Global Competitiveness Index, and the Index of
Economic Freedom to understand better the complex relationships between economic justice from one side
and human development, competitiveness and freedom from the other side.
The paper is divided into five sections. The second section introduces the conceptual framework of the
economic justice index. Section three presents the statistical framework. Section four discusses the results
and compares the economic justice index to other relevant indices. The last section concludes and presents
policy implications and recommendations.
II. Conceptual Framework
2.1. Defining Justice
Justice as a concept has been a subject of discussion for many centuries, yet it has often been concerned
mostly with describing the “utopic” society and in creating a set of laws that would create one. For example,
the earliest recorded theory of justice was described by Plato in the Republic in classical Greece (circa 380
BC), in which justice is discussed and the character dialogue describes some characteristics of the perfectly
just society, a “utopia” in the literal sense. Further, Aristotle is regarded as the first author to distinguish
between justice and equity. This distinction was found in many other religions, for example Islamic law,
distinguished between “Adala” and “Insaf”. The former is justice and the latter is equity (Intini, 2015).
According to DESA (2006), there are three major areas of priorities when it comes to equity and equality.
These areas are the equality of rights, equality of opportunity and equity of living conditions for all
individuals. The three areas were interpreted by DESA as follows:
− Equality of rights: The concept implies the elimination of all forms of discrimination and respect for
the fundamental freedoms and civil and political rights of all individuals
− Equality of opportunities, points to stable social, economic, cultural and political conditions that
enable all individuals to fulfil their potential and contribute to the economy and to society. Policies
focusing on health, education and housing are traditionally seen as particularly important for
ensuring equality of opportunities
− Equity in living conditions for all individuals: This concept is understood to reflect a contextually
determined “acceptable” range of inequalities in income, wealth and other aspects of life in the
society.”
Recently, Amartya Sen (2011) attempted to explain justice in a comparative sense rather than the
transcendental, emphasizing the need for logical reasoning and subsequently allowing for pragmatic decision
making in policy. Sen’s essential goal was to allow for a more practical theory that is not involved with
searching for the “perfect” (transcendental) system of justice, which he proclaims a futile endeavor, but
instead would be relevant in policy work through comparative reasoning and assessment and seeing how a
policy would advance or hinder justice in a society. In the context of international politics, Sen says that due
to the vast cultural and historical differences it becomes less and less possible to agree on a single concept
for a “perfectly just” society that would conform to their limitations. When discussing the role of
international entities, such as the United Nations acting the role of arbitrators, Sen suggests that the cultural
distance allows for objectivity away from biases and parochial interests, yet a common core set of values
should be agreed upon to avoid any issues caused by cultural distance.
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2.2. Defining Economic Justice
According to UN-DESA, economic justice as part of social justice is defined as the “existence of opportunities
for meaningful work and employment and the dispensation of fair rewards for the productive activities of
individuals, is an aspect of social justice, and is treated as one integral concept in order to avoid to “legitimize
the dichotomization of the economic and social spheres” (DESA, p. 14). Further, the commitment of the
United Nations to promote peaceful and healthy relations among countries based on respect, equal rights
and self-determination of people was clear. Article 55 of chapter IX of the Charter of the United Nations,
presented clearly the UN’s attitude toward its commitment to promote the following:
a. higher standards of living, full employment, and conditions of economic and social progress and
development;
b. solutions of international economic, social, health, and related problems; and international cultural
and educational cooperation; and
c. universal respect for, and observance of, human rights and fundamental freedoms for all without
distinction as to race, sex, language, or religion.
Aside from the UN attempts of defining justice economic justice as a concept is considered recent. Adler and
Kelso (1958) defined economic justice as composed of complementary principles. First participatory justice
is defined as allowing individuals the right to participate with their own inputs (such as their own labor or
physical capital) including the right to own property. Next distributive justice is concerned with rewarding
each person according to his contribution of inputs measured by the value determined in the free market.
Adler and Kelso, considered that the exchange of goods depends on subjective opinions, and does not
depend on the value of the labor used to produce it (i.e. the “labor theory of value” advocated by Marx is
considered false). Macpherson, in his “The Rise and Fall of Economic Justice” (1985), describes how the
concept of economic justice only arose when production started dissociating from political and social
relations. Before this dissociation, one’s place in production had been based on his social class and status,
and the relations of production were entirely political. In practical terms, economic justice aims to allow
individuals the opportunities with which they can attain a decent and fulfilling life; therefore, economic
justice relies on the building of economic institutions that can maintain a set of moral principles.
2.3. Economic Justice in the regional context
According to Gallup polls “life satisfaction survey question,” almost 50 percent of the Arab populations are
not satisfied with their lives. Recently, the urge to create a justice index in the Arab world became pressing
and indispensable. Lately, the Arab region has been suffering from severe injustice in many countries in
conflict and heightened levels of economic downturns in vulnerable and stable countries.
The surge of injustice in the region, solicits us to question the available tools utilized to measure justice in
the past decades. History revealed that previous attempts in the region failed to measure among economic
agents the level of equality of opportunity agents, equity of living conditions and equality of rights in a precise
way. For example, countries such as Libya, Bahrain, and Tunisia made significant gains in their HDI scores
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between 2005 and 2010; however, the level of dissatisfaction and the feel of dishonor led to major
repercussions in Tunisia and Bahrain and a protracted civil war in Libya (ECRI, 2013).
Aside from the imposed humanitarian challenges, the Arab region needs to cope with socioeconomic
challenges such as high unemployment particularly among the youth, income discrepancies, geographic
inequalities, economic exclusion, lack of social benefits and infrastructures. Those challenges should be
addressed simultaneously, without overlooking the role of political uncertainty in affecting the economic
performances since political turbulence increases volatility in economic growth, reduces investments,
restricts tourism and reduces exports. Poor economic performance associated with corruption and weak
institutions raises many questions related to modality of economic distribution especially due to the
concentration of major dividends generated from economic activities in the hands of small segment of the
population.
In light of all the issues raised above, up to this point, the international community failed to set a well-defined
means of justice measurement leaving these issues floating in a vicious cycle. For example, if we link justice
to currently available indices, one can claim that indices such as the Human Development Index (HDI), World
Governance Indicators (WGIs), Multidimensional Poverty Index (MPI), and many others, measure different
aspects of justice in the region, while each one of these indices solely captures a specific area of potential
measurement. Further, such indices are based on different methodologies, theoretical background,
calculation, and most importantly, the core objective of the aforementioned indices is not Economic Justice.
2.4. Discussion of Indicators
The concept of Economic Justice is of normative nature, whose measurement depends on the philosophical
and empirical setting on which the index is based. The literature on this topic, at the macroeconomic level,
contains qualitative analyses but is still unexplored quantitatively. The Economic Justice Index is created to
quantify economic justice in Arab countries, from a policymaking perspective. In this context, economic
justice refers to the basic inputs that prevent the violation of a person’s, as well as a society’s, economic
rights that revolve around exchanging goods and services, entering contracts and earning a living. It is
inspired by several ideas the literature defined and were deemed to affect economic justice. The index
consists of five dimensions: Competitive environment, enabling environment for private sector, red tape and
regulations, financial sector and monetary policy.
The above dimensions, or pillars, are composed of smaller constituents, called indicators and summarized in
Table 1
. The rationale behind choosing the components of those dimensions is briefly introduced with
reference to the literature, in the next sub-sections.
2.4.1. Contract Enforcement:
Contract enforcement at a lower cost provided by the state is considered as an essential pillar for economic
development as it facilitates exchange between economic agents, hence increasing welfare. Douglas North
(North D. , 1990) argued that the development of contract enforcement lowers contract cost and increase
trade volume and profits among merchants. Therefore, as markets gets more complex, they require effective
and efficient contract enforcement away from personal and social alternatives to attain further development
and decrease uncertainty. This will provide an equal opportunity for economic agents to participate in
markets and incentivize new innovative firms to participate. In our analysis, we use the contract enforcement
indicator to measure the cost and efficiency of judicial systems in resolving commercial disputes.
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2.4.2. Perception of standard of living for entrepreneurs:
Usually entrepreneurs come up with innovative business ideas that create employment opportunities
(mainly in the formal sector) and increase productivity through the adoption of newer technologies.
Improving the entrepreneurial environment through strengthening institutions (such as rule of law), labor
market accessibility and flexibility, financial markets, and infrastructure accessibility, could increase domestic
and foreign direct investments and provide employment opportunity and diffusion of technology. To
measure the standard of living of entrepreneurs, we use Gallup Polls analytics to see whether the city or area
where an economic agent reside is a good place for entrepreneurs to form new businesses. Most definitions
of economic justice stress the role of opportunities in creating a dignified and productive life.
Entrepreneurship create economic opportunities for individuals as it advances human development through
increase employment opportunity and subsequently household welfare.
2.4.3. Getting credit:
Getting Credit promotes the equal rights of borrowers and lenders to secure a financial transaction and
mutually report credit information to a credit registry that archives all borrowing and lending transactions.
We use the Getting Credit indicator to measure two important aspects, the strength of the reporting system
and the effectiveness of collateral and bankruptcy laws to facilitate lending. The scope and accessibility of
information could reduce the coordination failure between borrowers and lenders and could exclude people
that are unlikely of being credit worthy, especially those who are bankrupt or in high level of debt compared
to their income (Finlay, 2010). The disclosure and accessibility of information could determine the likelihood
of an individual to get credit and the probability of default based on the information provided. At the same
time people will be aware of the variation in the price of capital (rate to borrowers versus rates to lenders).
The second aspect of the indicator measures if collaterals and bankruptcy laws protect the rights of both
parties and facilitate the lending transaction. Both aspects provide the opportunity for people to borrow and
lend with clear rights and obligations.
2.4.4. Starting a business:
According to the Ease of Doing Business index, “Starting a business” indicator measures the time, cost, and
the number of procedures to get a local limited liability company up and running. The indicator categorizes
all stages new business owners pass through to attain the requirements of starting a commercial or industrial
business. Since entrepreneurship creates economic opportunities for individuals therefore, the lower the
time, the number of steps and the cost to finish a given procedure the better the entrepreneurial
environment in a given country. According to Kritikos (2014), administrative and activation constraints for
new businesses has to be low to reduce additional cost Usually, companies in business-friendly countries are
registered in one day, especially in states having state of the art e-business/government services for standard
businesses.
2.4.5. Efficiency of the tax administration:
Tax authorities usually collect taxes, tariffs and customs to finance government’s expenditures, distributions
and investment spending. This indicator measures specifically the efficiency of tax administration through
tax collections of corporate taxes, income taxes (it excludes household with low income), and the practical
ability of the administration to limit illegal transactions such as illicit capital flow, tax evasion and tax
avoidance. According to Murphy and Nagel (2002) Government revenues collection and redistribution could
be considered as a crucial tool to practice economic justice by any political system. However, it is hard to
evaluate the optimality of a fiscal stance from a justice perspective ex ante. For example, justice theory could
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not judge if a tax cut without looking at empirical evidences of the impact on employment, investments and
most importantly the distribution of after tax income.
2.4.6. Financial Sector
The recent financial crisis led to one of the worst economic recessions in decades taking many by surprise.
History revealed that scholars failed neither to deliver an early warning of the financial crisis nor anticipated
the severity of the tailgating recession ex ante. This reduced the trust in financial markets and people’s
believe that authorities are capable to resolve the financial crisis. The exposed financial fragility lead to major
injustice as it impacted major economic and social outcomes such as unemployment, poverty, inequality and
the overall welfare of economic agents. These unjust consequences brought us to pioneer an index that
measures the financial sector performance. To anticipate the financial rigidity in the Arab countries we
propose indicators such as the banking system, financial freedom, reliability of financial institutions, banks
assets to gdp, private credit to gdp and number of commercial banks.
The banking system:
The banking system is a financial institution that acts as an intermediary entity between borrowers
and lenders. The banking system indicator by Bertelsman Transformation Index(BTI) measures if
banks are complying with international regulations (such as maintain a minimum requirement of
capital relative to the risk exposure) and if capital markets are open to domestic and foreign capital
with sufficient resilience to cope with sudden capital flow reversals. Previously, we presented in our
“Getting Credit Indicator” the importance of information disclosure by borrowers. Now, assessing
the banking system provides an assessment of bank’s compliance and resilience. Both indicators
could provide a holistic picture of financial markets efficiency.
Financial Freedom:
Financial freedom requires financial institutions to be independent from government control. It is
evident that state ownership of banks have an ambiguous impact on economic and financial
development (Porta, Lopezde-Silanes, & Shleifer, 2002). Financial freedom away from state
intervention enhances competition and increase access to credit markets. In a free market
environment, financial channeling is market based where governments do not control credit
allocation to sectors. In this setting banks are free to provide or extend credit, accept deposits and/or
provide any financial services to individuals and companies. Further, financial freedom entitles banks
to conduct international transactions with no control on financial capital flow. We use this indicator
to measures the level of government intervention in the financial sector. It also measures the
development of financial and capital markets, government influence on the allocation of credit and
openness to foreign competition. The deep financialization
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of economic activity increasingly
connects people’s life to financial markets. Therefore, financial freedom could reduce negative
externalities resulting from state interventions and restrictions and increase efficiency.
Reliance on Financial Institutions:
The reliance on financial institutions indicator measures the ratio of bank deposits to broad money
(m2). According to WDI, Bank deposits is total value of demand deposits, time deposits and saving
deposits at commercial banks and other financial institutions. M2 is the sum of deposits in
commercial (M0), plus transferable deposits and electronic currency (M1), plus time and savings
deposits, foreign currency transferable deposits, certificates of deposit, and securities repurchase
agreements. Bank deposits measure the size and depth of the financial sector while m2 captures the
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Financialization is the process by which financial institutions, markets, etc., increase in size and influence.
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degree of monetization. Therefore, the ratio of bank deposits to m2 measures to what extent people
trust financial institutions as depositary institutions compared to longer term investments (such as
savings accounts, time deposits and mutual funds).
Bank assets to GDP and Private credit by banks to GDP:
The World Bank measures bank assets as claims on domestic real nonfinancial sector which includes
central, state and local governments, nonfinancial public enterprises and private sector. In other
words, bank assets is a comprehensive measure of the size of credit to private sector, credit to
government as well as bank assets other than credit. Bank assets to GDP measures the financial
depth of the economy through weighing the size of financial markets to total output. According to
King and Levine (1993) financial depth in a given country has a statistical correlation with economic
growth and also linked to poverty reduction. As part of banks assets, private credit by banks to GDP
refers to all financial resources issued to the private sector by deposit money banks. A higher value
of the private credit by banks signals to the strength of the economy as it measures the performance
of the private sector and its capability to develop.
Number of commercial bank branches:
In our analysis, we use the number of commercial bank per 100,000 adults as a proxy of financial
services accessibility. Bringing financial services coverage to all regions is an eminent challenge
especially in rural areas in developing countries. According to CGAP (2009) more financial outreach
is better for borrowers and lenders and allows banks to be more responsive to people’s requests to
facilitate small business and development especially in rural areas.
2.4.7. Dealing with Construction Permits:
Our index, uses “Dealing with Construction Permits” as an indicator to measure the required number of
procedures used by the majority of businesses to legally build a warehouse or any commercial facility, the
time recorded in a calendar year to complete each procedure, and the cost recorded as a percentage of the
warehouse value associated with each procedure. The more time, cost and red tapes to finalize a
construction permit, the more the associated opportunity cost for business owners and employees especially
in growing economies with high competition. In monetary terms, applied efficient regulations could save
billions of dollars to business owners. Diniz and Ramalho (2015) estimated the cost of red tapes in 90
countries to be around $180 billion in 2012. Since the private sector employs 9 out of every 10 jobs (in formal
and informal sectors) around the globe, any delays in setting up a new business could delay employment
opportunities as well.
2.4.8. Regulatory Quality:
Market regulations are crucial in shaping the welfare of economies. It profiles the relationship between
governments, people and businesses. The Regulatory Quality Indicator that we use captures the prevalence
of unfriendly market policies. As an economic governance indicator, regulatory quality measures the ability
of governments to formulate and implement sound policies and regulations that promote private sector
development. According to the world governance indicators (WGI), Regulatory quality assess major
regulatory practices in the private sector such as unfair competition, taxation and tariffs policies, monopoly
and unti-trust laws, trade barriers, price controls, investment and financial freedom and other regulatory
burdens. A higher score of Regulatory Quality hints to the ability of the state to create a conducive regulatory
environment for private sector development.
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2.4.9. Market-Based competition:
Economic justice cannot be achieved in inefficient markets. Market-based competition prohibits exclusionary
behavior and promotes efficient markets. Non-competitive market structures produce wealth inequality. The
goods and services can be of lower quality, narrower variety and higher prices. Additionally, restraints on
competition can benefit certain groups over others, or over society’s welfare as a whole, as these special
interest groups lobby for their own advantage. Removing competition from the market causes concentration
of economic powers to the detriment of society. Market-based competition prevents inefficient allocation
and economic deadweight loss to both consumers and producers. The gain from using the scarce resources
of the economy competitively, promotes individuals’ welfare and equal treatment (Stucke, 2013). The index
accounts for the market-based competition component as a numerical value scaled from 1 to 10. The highest
score, 10, refers to markets that host rules promoting competition; while the lowest score 1 signifies the
absence of competition in most segments of the economy.
2.4.10. Anti-monopoly policy:
The behavior of non-competitive entities can be extortionary and diminishing to economic justice, thus it
must be regulated. Oligopolies and monopolies lead to inefficient resource allocation and are one of the very
few exceptions where governments absolutely have to intervene (Ver Eecke, 2013). As these firms pursue
their self-interest and maximize their profits, they tend to keep output below its socially efficient level and
harm both buyers and sellers. They harm the former by increasing the prices of goods and services and the
latter by limiting their ability to enter and participate in the market (Hahnel, 2005; Harris & Jorde, 1984).
Among many reasons, monopolies form due to innovation and learning or due to natural barriers of entry
(North D. , 1994; Stucke, 2013). In the first case, the right to benefit from one’s innovation may lead to the
formation of market exclusion as other market participants lag behind in acquiring new technologies. In the
second case, the naturally high fixed cost of the sector prevents market competition. This is when anti-
monopoly policies and regulation become indispensable for economic justice (Ver Eecke, 2013). The anti-
monopoly policy component is also a numerical value scaled from 1 to 10; 10 being the presence of the most
active anti-monopoly policies, while 1 being the absence of political measures to prevent monopolistic
behavior.
2.4.11. Administered Prices:
Administered prices are prices set internally by firms or by regulatory bodies and do not respond to short-
term variations in supply and demand (OECD, 1993), thus they do not reflect the economically just prices.
Pursuing self-interest in competitive markets will produce efficient production levels and remove the need
for administering prices. Competition diminishes bargaining power between consumers and producers and
creates fairer outcomes (Ver Eecke, 2013). When regulatory bodies or firms set the price below equilibrium,
the quantity demanded will increase above equilibrium quantity, while supply will not. Conversely, when
prices are set above equilibrium level consumers will become reluctant to buy the products, while suppliers
will overproduce them, potentially diverting resources from more efficient lines of production (Morton,
2001). Administered prices would result in deadweight loss and efficiency problems, thus diminishing
economic fairness, as suppliers and consumers do not share the full potential of the exchange equally.
Administered prices is a numerical variable scaled from 1 to 4. The smaller the portion of administered prices,
the closer the score to 4.
2.4.12. Monetary policy:
Economic justice requires that an economic agent’s long-term financial capital does not devalue as a
consequence of monetary instability. Four components of the Economic Justice Index attempt to capture this
concept: monetary freedom, independence of central banks, anti-inflation and foreign exchange policy, and
inflation standard deviation over 5 years. As measures of currency stability and price freedom, these
components translate the importance of storing the value of economic agents’ accumulated financial capital.
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As they face varying levels of inflation, monetary policy guarantees their right to exchange goods and services
with reliable mediums of exchange.
The ideal model of a central bank requires it to be independent from the government, targeting a nominal
anchor and stabilizing macroeconomic fluctuations. Economic cycles showed that central banks are exposed
to a trade-off between an economy’s operating capacity and a moderate rate of inflation. As a consequence,
the monetary authority in accordance with the fiscal authority should cooperate to ensure that adequate
levels of inflation and economic capacity are harmonized to attain economic justice. This necessitates that
central banks retain their operational independence (Balls, Howat, & Stansbury, 2016). While there is no
consensus on a specific monetary policy that will make the economy more just, there is wide support for low
inflation levels and central bank independence (Index of Economic Freedom, 2017).
Monetary freedom is measure by a numerical scale from 0 to 100; 100 being the highest freedom level.
Independence of central banks varies on a scale between 0 and 4; 0 reflects no independence, while 4 reflect
strong independence. Anti-inflation and foreign exchange policy are measured on a scale between 1 and 10;
10 being the most persistent and appropriate policies, respectively. Finally, Inflation standard deviation over
5 years is a rate measured by the consumer price index.
2.4.13 External Sector:
Economic justice requires complete financial and goods markets; barriers to trade and to capital flows should
be lessened and eliminated to achieve global market completeness. Foreign trade risk should be addressed
with the purpose of integrating markets into one global market and to achieve equal treatment (Hockett,
2005) . This component includes two main sources of risk. The first one is positioned in the goods and services
market and includes discriminatory tariffs and excessive protection. The second one references the financial
markets and entails contagion risk, capital control risk, current account convertibility and capital account –
as a measure of the ease of execution of financial transactions. The remaining element of foreign trade risk,
trade embargo risk, can be applied to both markets. Foreign trade risk is measure on a scale from 0 to 4, with
0 being the lowest risk level, and 4 the highest.
The principles of the World Trade Organization state that countries should not discriminate among their
trading partners and should discourage protectionism. Free international trade benefits producers and
consumers. Through comparative advantage, trade liberalization improves productivity by increasing
investment in technology, raising aggregate productivity and reallocating resources to the most efficient
sectors. Moreover, knowledge spills over across borders, as firms learn by exporting and importing goods.
Open trade is also linked to less corruption, more ease of doing business and financial deepening (WTO,
Making Trade an Engine of Growth for All , 2017). As for consumers, the competition policy doctrine,
inherently present in free trade principles, consists of admitting the largest number of competitors to local
markets from the broadest range of sources. This minimizes the risk of a single or a cluster of firms
dominating the market and offers a wide variety to consumers for low prices. This channel is in particular
beneficial to lower-income households – and courtiers -, thus creating more fairness in the economy (WTO,
Making Trade an Engine of Growth for All , 2017; UNCTAD, 2008).
The imposition of trade barriers, such as tariffs is associated with negative consequences. For example, while
the tariffed industry may gain more local market share and host more jobs in the country imposing the tariff,
research show that that this gain is offset by the jobs lost in the retail sector. Second, consumer surplus
shrinks as consumers shift to an alternative source and pay higher prices to buy the same product that may
also not be produced domestically. Finally, other industries may be harmed as the tariffed country retaliates
(Hufbauer & Lowry, 2012). Capital controls also have destabilizing effects on the economy. Difficulties in
bringing capital in, and taking capital out of a country discourages individuals from investing and distort
resource allocation and economic stability. A restrictive business environment with weak current account
12
convertibility and capital account –as measured by this index- would drive investors away, reducing present
and future growth potential and employment opportunities. As for contagion risk, governments hold the
right to take prudential measures to mitigate the negative effects of financial crisis, and its resilience against
worldwide shocks protects depositors and investors against financial markets’ instability (WTO, Trading into
the Future, 2001).
Table 1 – Retained Indicators
Pillar Indicator source
Competitive Environment
Market-based competition BTI
Administered prices IPD
Anti-monopoly policy BTI
Enabling Environment for
Private Sector
Contract enforcing (DTF) Ease of Doing Business - WB
Perception of standard of living for entrepreneurs Gallup
Likelihood of violent demonstrations Global Peace Index
Getting credit (DTF) Ease of Doing Business - WB
Foreign trade risk EIU Operational Risk Model
Red Tape & Regulations
Dealing with construction permits (DTF) Ease of Doing Business - WB
Index of Regulatory Quality WGI
Starting a business (DTF) Ease of Doing Business - WB
Trading across borders (DTF) Ease of Doing Business - WB
Efficiency of the tax administration IPD
Financial Sector
Banking system BTI
Financial freedom Heritage - Index of Economic Freedom
Reliance on financial institutions (Deposit rate=Deposit/M2) WDI
Banks' assets to GDP GFDD
Private credit by banks to GDP GFDD
Frequency of bank branches GFDD
Monetary Policy
Independence of Central Banks IPD
Anti-inflation/forex policy BTI
Monetary freedom Heritage - Index of Economic Freedom
Inflation standard deviation over 5-years WDI
2.4.14. Trading Across Borders:
Economic justice involves the procedure that shapes trade. Trade occurs justly when the process underlying
it is timely and uncostly. Trading across border measures the cost and time to import and export goods and
services and includes three components: domestic transport, border compliance and documentary
compliance (Trading Across Borders Methodology, 2017). This indicator thus concerned with procedural
justice, which is looks at the governance mechanism through which the transaction is made. A low score
reflects an economy that lacks a large private sector cross-border trade.
2.4.15. Likelihood of Violent Demonstrations:
Violent demonstrations reflect a collective feeling of dissatisfaction that is primarily a consequence of
government mismanagement, lack of trust and perceived injustice. The escalation in these demonstrations
is linked to the incapacity of the government to handle the protesters and to communicate with them. Social
unrest is a form of systemic risk, whose effects ripples onto several arenas such as the economy. More violent
demonstrations are associated with poorer business environments and weaker well-being measures (Global
13
Peace Index, 2015). In addition to the direct costs incurred such as losses to property, infrastructure and
human lives - which further deepen economic injustice- these demonstrations reflect the poor quality of
institutions that are unable to resolve economic injustice. All of these factors reflect an unsound business
environment and an unjust economic system (Renn, Jovanovic, & Schrö, 2011; Global Peace Index, 2015).
The likelihood of violent demonstrations is scaled from 1 to 5, with 5 being the highest level of threat.
III. Statistical Framework
While developing the conceptual framework, the main components of Economic Justice (EJ) were identified.
Available information for the Arab world is collected to form a complete dataset relevant to EJ. A
considerable amount of data was available from reliable national and international sources (
Table 2 – list of
sources
, p.14). the data is used to build the EJ composite index. Practical guidelines have been developed by
research centers, international agencies and consultancy firms to provide some international standards in
the field of composite indicators.
The diagram in Figure 1 represents the adopted procedural framework. It represents an adapted version
from the original framework found in the auditing report (Saisana & Philippas, 2013) of the Gender Inequality
Index, produced by the Joint Research Center
2
(JRC) of the European Commission.
3.1. The Dataset
The data harvesting resulted in a large number of indicators that fit under the dimensions of EJ. A total of
110 indicators, relevant to the concept of Economic Justice, were collected, from 17 renowned sources.
However, none provided data for all 22 Arab countries. A list of indicators, their definition and source is
presented in the annexes (ANNEX 1 – Originally Considered Indicators).
However, those numerous indicators suggest a necessary reduction in the dimension of the database, so data
can be used efficiently. In other words, this suggests coming up with a composite indicator for EJ, that
summarizes the information provided by the indicators in a statistically significant way.
2
JRC audited famous indices such as: Global Innovation Index – Johnson Cornell University, INSEAD and WIPO, Gender
Equality Index – European Institute for Gender Equality, EU Regional Human Development Index – Directorate General
Regional and Urban Policy of the European Commission, Europe 2020 Regional Index – Directorate General Regional
and Urban Policy of the European Commission, Index for Risk Management (INFORM) – 17 partners of International
agencies listed here , Sustainable Society Index – Sustainable Society Foundation, Global Talent Competitiveness Index
– INSEAD, Rule of Law Index – World Justice Project, etc.
14
Figure 1 – Framework
This process guarantees an objective procedure for developing a robust EJ Index and is applied across the
predefined conceptual dimensions of EJ.
3.1.1. Soundness of Sources
“In terms of data availability, a 'constant awareness of the sources and
interpretation of data' is required (McGranahan, 1972, p. 3)”
(Booysen, 2002)
A significant time spent on revising the methodologies used by the data sources verified the soundness
of the measurement, the scale interpretation and their temporal comparability
3
. When the underlying
measurement methodology is judged sound
4
for this study, an indicator is qualified for inclusion in the
database. In addition, the reported figures with their interpretation were revised meticulously.
For some sources, the process involves going back to the raw data and recompile
5
them. In other sources,
some years had to be rescaled to align the figures from year to year and make them comparable. Some
sources were contacted for methodology verification, or data correction.
Table 2 – list of sources
3
Temporal comparability is considered if a dynamic index is to be developed
4
Clear and consistent methodologies, without logical fallacies.
5
That was mainly the case with the Institutional Profile Database (IPD), to insure comparability through time. IPD
changed the formulation of questions, the number of sub-variables and scales, repeatedly, over time. So indicators
that can be steadily measured through time were chosen.
Step 1. Conceptual Consistency
Concept definition
Compatibility with
existing literature
of Economic
Justice (EJ) and
justification of EJ's
definition
Enhance the
definition to fit the
regional context of
the EJ index
Discuss the added
value of the index
_______________
Discussion of EJ
components
Logical assessment
and choice of
indicators
Step 2. Data Check
Soundness of sources Verifiy
methodologies of data sources to
assert what the indicators are
measuring exactly
____________________________
Data Coverage Indicators
inclusion based on availability
requirements, mainly country
coverage and specified time
window
____________________________
Data Preparation At the
indicators level, ensure
comparablity between countries
Ensure indicators' direction is
consistent with the concept of EJ
(The higher the better)
Specify data considerations to
deal with missingness, outliers,
correlation significance and
imputations.
Step 3. Statistical Coherence
Multivariate
Analysis Assess
the dimensions of
EJ (splitting or re-
group via PCA
assessment)
_______________
Model Selection
External
Robustness:
simulate and test
diferent weighting
schemes
Internal
Robustness: assess
potential
redundancy of
information and
coherence of
correlations
between
indicators,
categories and EJ
index.
Step 4. Qualitative Assessment
Internal coherence
assessment via
brownbag
seminars within
ESCWA
_______________
External
assessment,
auditing by JRC
15
Directly Accessed Source
Directly Accessed Source
BTI
IFAD
Doing Business
-
WB
IPD
EIU Operational Risk Model
OECD
Enterprise Surveys
-
WB
Open Budget Index
Gallup
UNCTAD
GFDD
WDI
Global Integrity Report
WEF
-
Global Competitiveness Index
Global Peace Index
WGI
Heritage
-
Index of Economic Freedom
3.1.2. Data Coverage
Originally, the data was collected over a window of 14 years (2000 to 2014).
Some countries have scarce data across indicators, while some indicators have scarce data across
countries. To optimize the number of observations per country, a number of ‘poor’ indicators
6
were
identified and then exclude. Since the intended index is static, the temporal window is reduced to 2012-
2014, from which only latest observations were considered.
3.1.3. Data Preparation
At this stage, and prior to any analysis, the raw data has to be prepared and harmonized to be part of
the EJ scores, coherently.
Correlation Significance
As specified in the framework, pairwise correlations are analyzed at the pillar level. This analysis shows
whether indicators have their highest positive significant correlation within the conceptual pillar they
have been assigned to. A correlation matrix is run at the pillar level, and significant correlations are
reported. The test statistics is
,
where is the correlation coefficient, and is the number of cases (sample size). This statistic follows a
t-distribution with
degrees of freedom. At a 5% significance level, the critical value is
.
Accordingly, within each pillar:
1. Perfectly collinear
7
indicators are flagged.
2. Indicators that do not correlate significantly with any indictor in the pillar
are flagged.
3. Indicators that correlate negatively to all other indicators are flagged.
4. Indicators that do not correlate with any indicator within the same pillar, but
correlate with indicators in another pillar are flagged.
5. Indicators that have higher
8
correlations in another pillar are flagged.
6. Indicators that correlate positively to some indicators and negatively to
others within the same pillar are flagged.
As a general guideline, for each indicator, the highest correlation coefficient should be within the same
pillar (Athanasoglou, Weziak-Bialowolska, & Saisana, 2014). Assigned treatments are presented in
Table
3
. Flags 1, 2 and 3 are treated by reassessing directions and/or dropping indicators. Flags 4 and 5 will be
6
in terms of data availability
7
correlation coefficient = 1
8
Higher correlation, positive and statistically significant
16
treated by moving indicators to better pillars if they fit conceptually, else by dropping them. Flag 6 will
be treated during the multivariate analysis.
Imputation
There are several methods one can employ to deal with missing data. The most popular methods are:
Listwise or Casewise Deletion, Pairwise Deletion, Mean Substitution, Median Substitution, Expert
Opinion Adjustment, Imputation by Regression, Hot Deck Imputation, Expectation Maximization (EM)
Algorithm, Raw Maximum Likelihood or Full Information Maximum Likelihood (FIML) Method, and finally
the Multiple Imputations approach. For the current static approach, a simple imputation method for
missing values
9
is employed. If the country has historical data on the missing indicator, then the historic
value would imputed. Otherwise, the median of the indicator will be imputed, and that for Gulf and non-
Gulf countries separately. In other words, if a missing value is that of a Gulf country the median of the
Gulf-countries subgroup is imputed, else the imputed value will be the median of the non-gulf countries
subgroup.
Table 3 – Flags and treatments for correlation inspection
Flag Solution Correlation
Inspection
1
Collinear
indicators
Merge pillars and delete duplicate
indicators
Treatment in Part 1
2
No Significant correlations with any other
indicator within the same pillar
Drop
Treatment in Part 1
3
Negative Correlations
with all indicators
If direction of scale is wrong, correct it;
else, drop indicator.
Treatment in Part 1
4
No Correlation with any indicator within the
same pillar, but correlates within the pillar
If the correlations fit our conceptual
frame, move to another pillar; else, drop
Treatment in Part 2
5
Correlates with indicators in the same pillar,
but correlates higher with indicators in other
pillars
If the correlations with another pillar fit
our conceptual frame, move to the
other pillar; else, keep
Treatment in Part 2
6
Correlates positively to some indicators and
negatively to others (Mixed +/- Correlations)
Wait for
PCA
check
Treatment in
Multivariate Analysis
3.1.4. Multivariate Analysis
The rationale behind building a composite indicator is to condense all retained indicators into one score:
the index. Since multiple variables are being considered, dealing with the data gives rise to a multivariate
analysis. One aspect of this analysis is already used in course of inspecting correlations of the indicators.
In the literature, dimension reduction methods have been in existence for more than a century. Karl
Pearson was the first to introduce the idea. After his famous memoire on regression lines, he made a
clear distinction between a regression line and a best-fit-line. This linear dimension reduction proposition
aimed at “representing a system of points in […] highly dimensioned space by the best-fitting straight
line or plane” (Pearson, 1901).
9
Percentage of missingness in final dataset is 1.92%
17
Figure 2 – Taxonomy of dimensionality reduction techniques. Source: (Maaten, Postma, & Herik, 2009)
Shortly after, Charles Spearman published his seminal paper on factor analysis (Spearman, 1904). Today,
different methods are spread across statistics, computer science and engineering literature aiming at
embedding big datasets in lower dimensional “best-fits”, that are either linear or non-linear. Reviews by
Carreira-Perpiñán (1997), Fodor (2002), Mateen et al. (2009), Burges (2010), Arunasakthi and
KamatchiPriya (2014), and Sorzano et al. (2014) have exhibited a spectrum of methods (Figure 2) dealing
with dimension reduction from both linear and non-linear perspectives. Linear methods include
Canonical Correlation Analysis, Principal Component Analysis (PCA), Factor Analysis (FA), Linear
Discriminant Analysis, and Projection Pursuit, while non-linear methods include probabilistic PCA
(Lawrence, 2005)
and machine learning, among others
10
.
For the purpose of this study, a confirmatory PCA is employed to verify that the conception of pillars is
statistically coherent. A pillar is confirmed to be satisfactory if indicators load on only one factor, and all
loadings have positive signs. The final objective of this section is to have the indicators loading on one
main factor per pillar. Confirmatory PCA results are summarized in
Table 4
.
Table 4 – Confirmatory PCA
Name of Pillar Components Indicators Rho
Competitive Environment
1 3 0.6135
Enabling Environment for Private Sector
1 5 0.684
Red Tape & Regulations
1 5 0.6111
Financial Sector
1 6 0.7414
Monetary Policy
1 4 0.6998
3.2. Computing the Index
This index is a powerful tool to monitor the evolution of Arab countries in EJ. A desired feature of this
measurement is to be an objective index. So far, all maneuvers of data were objective. Subjectivity, however,
10
Non Linear Methods: probabilistic PCA, Kernel PCA, multi-dimensional scaling, independent component analysis,
cluster analysis, Isomap, Maximum Variance Unfolding, diffusion maps, Locally Linear Embedding, Laplacian Eigenmaps,
Hessian LLE, Local Tangent Space Analysis, Sammon mapping, multilayer autoencoders, Locally Linear Coordination,
manifold charting, decision trees, random forests, Support Vector Machine, artificial neural networks, etc.
18
is introduced at different stages of building indices. For example, it can be present in the preliminary selection
of indicators (although justified conceptually) or simply present in the choice of computational methods.
“Subjectivity is introduced in composite indicators through the choices made to
compute them. To remove this subjectivity,” one may adopt “the principle of multi-
modelling (Saisana and Saltelli, 2011). This means that instead of relying on a single
model, a set of potential indices are computed in order to select the one that best
measures” the desired concept. “This is the one that is most robust. An Index is said
to be robust when changing assumptions do not significantly affect its ability to
measure the concept of interest.”
(European Institute for Gender Equality, 2013)
For building the EJ Index, a selection of methods is employed. All of them share the same principle of
dimension reduction where the EJ index is the essence of the 5 pillars and their relevant indicators (see:
Table 5
below).
Table 5 – the EJ composition
Economic Justice
Competitive Environment
Market-based competition
Administered prices
Anti-monopoly policy
Enabling Environment for Private Sector
Contract enforcing (DTF)
Perception of standard of living for entrepreneurs
Likelihood of violent demonstrations
Getting credit (DTF)
Foreign trade risk
Red Tape & Regulations
Dealing with construction permits (DTF)
Index of Regulatory Quality
Starting a business (DTF)
Trading across borders (DTF)
Efficiency of the tax administration
Financial Sector
Banking system
Financial freedom
Reliance on financial institutions (Deposit rate=Deposit/M2)
Banks' assets to GDP
Private credit by banks to GDP
Frequency of bank branches
Monetary Policy
Independence of Central Banks
Anti-inflation/forex policy
Monetary freedom
Inflation standard deviation over 5-years
At first, scores are computed at the pillar level by aggregating the scores of indicators within each pillar. For
example, the score of a country on Competitive Environment will be a summary of its scores on each of the
three indicators: ‘market-based competition’, ‘Administered Prices’, ‘Anti-monopoly policy’. Each indicator
is assigned a weight, depending on the model used, as explained below.
19
Similarly, the pillars’ scores are aggregated to form the final EJ score. Each pillar is assigned a weight. The
different methods assign different weights to the retained indicators, consequently they will produce
different scores for the same country.
It should be clear to the reader that assigning weights, whether for indicators or for pillars, would necessarily
affect the final scores and might very well affect the ranking. Since the choice of weights is controversial, one
should study the effect of different methods producing different weights, and analyze the robustness of the
ranking.
3.2.1. Models based on Simple and Weighted Averages
A simple set of models is a linear combination of indicators
that form the score
, for pillar j and
country c. The latter scores are weighted and summed to form the EJ score.
The model is written as follows:
(A)
(B)
Where
and
. If the weights are equal, the model is called a simple average
model, otherwise it is a weighted average.
Since indicators’ direction is positively correlated to the concept of economic justice, the higher the
obtained scores, the better the EJ situation is.
3.2.2. Models based Factor Analysis
This family of models will be applied at the indicators level only.
In this section, three variants of dimension reduction methods for latent variables are considered: Principal
factor (PF), Iterated principal factor (IPF), and Principal component (PCF). The three methods are readily
available in STATA.
“ pf specifies that the principal-factor method be used to analyze the correlation
matrix. The factor loadings, sometimes called the factor patterns, are computed
using the squared multiple correlations as estimates of the communality. pf is
the default.
pcf specifies that the principal-component factor method be used to analyze the
correlation matrix. The communalities are assumed to be 1.
ipf specifies that the iterated principal-factor method be used to analyze the
correlation matrix. This re-estimates the communalities iteratively.”
STATA Multivariate Statistics
Reference manual, Release 12
20
The analysis starts at the pillar level and the first factor is retained to compute the scores per country, across
pillars. The country score according to the first factor is a linear combination of the indicators included in the
analysis, and therefore can be interpreted as the index score for each country. The coefficients employed in
this linear combination are the loadings generated throughout each method (PF loadings, IPF loadings, and
PCF loadings).
To describe briefly what factor analysis does, consider a standardized data matrix of dimension .
Each column of denotes observations of a given variable. In this sample denotes the countries and
denotes the variables in each pillar. A principal component analysis means that each observed variable is
explained by a set of common factors,. The principal components are by construction an orthonormal
linear transformation of . Notationally,
′
where
• is a matrix of factor loadings. Each row of gives the weights assigned by each variable to
the factors. So the correlation of variables and factors is given by these loadings.
• is a matrix of scoring coefficients. Column of denotes the weights assigned by -th factor
to variables. Therefore, the first factor score of country “” is given by
where
is the first
column of matrix .
Singular value decomposition of a data matrix X gives the following:
′
′
where is a left singular vectors; is a right singular vectors. is diagonal matrix of eigen values and each
column of is the corresponding eigen vector of the data covariance matrix . Both and are
orthonormal. The factor, thus computed, is also othonormal i.e.
. Note, the above implies
Denoting the data correlation matrix, as , the total variation in data is given by
= [Eigen Value Decomposition]
Trace()= trace(VDV') = trace(DVV') = trace(D)
Thus the i
th
principal component explains
proportion of total variance.
Principal factor analysis differs from principal component analysis in that
where is normal error term.
Similar to Simple and Weighted Average models, the higher the score, the better the economic justice
situation.
3.2.3. Scores, Bounds and Benchmarks
Once the coefficients are determined, the standardized values of the indicators are loaded with the
coefficients and aggregated. The same scheme is applied for the minimum and maximum values of each
indicator, to bound the index. The bounds are used in the min-max formula to rescale the EJ Index from 0 to
100, where zero and 100 are the lowest and the highest hypothetical values possible, respectively.
21
In addition, data was collected for OECD countries, and the same computation procedures were applied to
get the OECD average score. This figure will be used as a benchmark, other than the theoretical maximum.
3.3. Model Selection
3.3.1. Sources of uncertainty
Different experts could have different views about the importance of each indicator, and each pillar, with
respect to the others. In addition, they will be concerned about the way pillars are amassed, as each method
will yield different results. The arguable points are the sources of uncertainly that should be considered for
robustness tests (as discussed in the following section).
The different models and the different sources of uncertainty, suggested in
Table 6
, show that there is no
ONE correct way of producing the index scores when building a composite indicator.
One identity of a good index is robustness. Robustness check is a way to measure the confidence of the
formulated index scores and ranks.
For robustness check, two levels are considered: external and internal robustness.
To assess the robustness of an index, all possible combination of uncertain options should be tested, and the
best model is to be chosen. If all models give the same ranks, then whichever model is chosen is a good
model, and the results will be robust; results are not sensitive to changes in the sources of uncertainty.
However, in practice models produce different ranks for countries, so the best model is the one that
minimizes the distance between those ranks, and that is among all tested models. This is called external
robustness.
Table 6 – Sources of Uncertainty
Source of uncertainty
Options to
study
Importance of Indicators
Simple average, where all indicators have the
same positive weights, adding up to 1.
Weighted average, where indicators have
random positive weights (beta) whose sum is
always equal to 1.
Correlation based dimension
reduction methods
such as PCA, FA, etc. weights are associated to
the degree of correlation between the variables.
Importance of Pillars
The weight associated to each
pillar
determines
its importance to the index. A range of positive
weights (alpha) will be applied, including equal
weights, whose sum is always equal to 1.
In addition to the external robustness as compared to other models, the best model should be coherent and
should possess internal robustness as well. This is reflected in the internal correlations as will be shown
below.
A robust model that is complex to build, thus to analyze, is not beneficial for practitioners and policy makers.
The simpler the robust model the better it is.
3.3.2. External Robustness (uncertainty)
For the five pillars of the EJ Index, external robustness is tested by comparing the results of a range of
weighted average models, including the 3 factor models and the simple average.
22
The models were simulated according to a range of positive weights described in section 3.3.1 (Sources of
uncertainty), satisfying the constraints
and
. Weights must be positive, as
indicators’ direction was designed to be the higher the score, the more just the economic situation is. This
means that an indicator’s weights should not drag the overall score down, when the indicator gets higher.
To limit the number of possible weights combinations, a jump of 0.1 was adopted. The number of simulated
models by pillar, is presented in the table below:
Table 7 – Simulated Models Summary
Pillar (j)
Number of
indicators
Number of possible weights combinations (M
j
)
Competitive Environment
3
3
6
weighted average models + 1 simple average + 3 Factor models
Enabling Environment for Private Sector
5
125
weighted average models + 1 simple average + 3 Factor models
Red Tape &
Regulations
5
125
weighted average models + 1 simple average + 3 Factor models
Financial Sector
6
126
weighted average models + 1 simple average + 3 Factor models
Monetary Policy
4
84
weighted average models + 1 simple average + 3 Factor models
Total
models
516
simulated models
3.3.2.1. Indicators Aggregation Uncertainty
A first assessment of the models aggregates the indicators within each pillar. The assessment consists of
taking the difference of ranks between each model and all other models, then plot the distribution. Best
models must show the highest peaks at zero, meaning that the ranks do not vary between ‘r’ and other
models, except rarely. Soon picking the model based on visual selection becomes subjective. The need of a
more objective measure arises.
A second assessment is to compute the standardized Euclidian differences (Ed) for all models, then select the
model with the smallest Ed.
For each of the 5 pillars, we have simulated ‘Mj’ models. In total, we have
models. In
the j
th
pillar, the Ed for model ‘m’ is the square root of the sum of squared differences of ranks (r) between
that model and all the other models, across all countries ‘c’ (c=1,…,17). And that is for all ‘r’. Its expression is
presented in the following formula :
(1)
A summary of the Euclidian Differences for the best three models, by pillar, can be found in Table 12, ANNEX
2 – Euclidian Differences. Each pillar showed a different preference of models; 2 pillars showed that Weighted
Averages minimize the Euclidian difference, 2 showed that simple average models are more robust and finally
only 1 method showed that the PCF model is the best choice. Overall, the choice should fall between the
weighted average models and the simple average models. However, uncertainty has an unexplored source
yet which makes the robustness analysis incomplete. The aggregation at the pillar level certainly affects the
final ranking.
Boxplots of the best models are presented in ANNEX 3 – Boxplots of best 3 models per pillar (p.56), to
compare the dispersion between the scores of the best models and the dispersion of their ranks. As expected,
and for each pillar, the best three models show identical boxplots for ranks, while they show differences and
outliers for raw scores.
23
3.3.2.2. Pillars Aggregation Uncertainty
Best models are selected not only considering indicators’ weights uncertainty, but also the importance of the
weights by pillar as a constituent of the overall index. A similar simulation is conducted, where pillars’ scores
are positively weighted under the constraint that weights must add up to one.
Euclidian distances are computed for each set of weights, in comparison to the other sets, across countries.
Models of the same type are aggregated with a range of weights, assigned to each of the 5 pillars. For each
set of models, WA, SA and PCF, 126 aggregated models were generated, to sum up to 378 simulated models.
As noticed in Table 13, ANNEX 2 – Euclidian Differences. the top 2 models have the same minimum Euclidian
Distance, and they are both an aggregation of the Weighted Average model, with slightly different weights.
While the worse fit models were three different cases, each derived from a set of models: A PCF model, then
a Simple Average model, then a weighted average model. The three models provided the most unlikely
ranking of countries. The two best models provide the same ranking for countries. The choice between the
best two models is bound by the ease of interpretation to the users. So, the model that assigns equal weights
to all pillars is considered as it is more intuitive for analysis. Accordingly, the final scheme of the robust index
is presented in the table below.
Table 8 – Final model with robust coefficients
Economic Justice
Competitive Environment
Market-based competition .4
.2
Administered prices .3
Anti-monopoly policy .3
Enabling Environment for
Private Sector
Contract enforcing (DTF) .2
Perception of standard of living for entrepreneurs .2
.2
Likelihood of violent demonstrations .1
Getting credit (DTF) .2
Foreign trade risk .3
Red Tape & Regulations
Dealing with construction permits (DTF) .2
Starting a business (DTF) .2
.2
Trading across borders (DTF) .3
Efficiency of the tax administration .2
Index of Regulatory Quality 284b .1
Financial Sector
Banking system .3
Financial freedom .2
.2
Reliance on financial institutions (Deposit rate=Deposit/M2) .1
Banks' assets to GDP .1
Private credit by banks to GDP .2
Frequency of bank branches .1
Monetary Policy
Independence of Central Banks .2
.2
Anti-inflation/forex policy .3
Monetary freedom .2
Inflation standard deviation over 5-years .3
24
3.3.3. Internal Robustness (correlations)
For the internal robustness verification, the correlation matrix is presented between the EJ Index and its
pillars, hoping for significant positive correlations across the matrix, and hoping that the highest correlations
of the indicators are within their conceptual pillars (see ANNEX 4 – Correlation Matrix, p.60).
All pillars of EJ are significantly correlated with the Index, with a confidence level beyond 95%, as shown in
Table 9.
Table 9 – Correlation between the EJ Index and its categories
Competitive
Environment
Enabling
Environment
for Private
Sector
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Aggregate
EJ Index
Pearson Correlation 0.893
0.881
0.846
0.895
0.879
Bootstrap
Bias -0.00005
-0.0186
0.000733
0.005792
-0.00989
Std. Error 0.037
0.078
0.055
0.035
0.072
95%
CI
Lower
0.805
0.654
0.722
0.818
0.689
Upper
0.955
0.956
0.937
0.956
0.966
As for internal consistency, the correlation matrix in ANNEX 4 – Correlation Matrix shows the significant
coherence of the index, where all indicators are positively correlated to the EJ Index and to its pillars, and
they are correlated the most to their own pillar.
IV. EJ Index Results
4.1. Heat Map and figures
Figure 3 – Heat Map of the EJ Index
The index ranks countries between 0-100, with 100 being the highest attainable value. Scaling countries
based on our EJ index shows that six countries scored below 50 points while 11 countries scored above it
(see: Table
10
). The heat map in Figure 3 depicts the performance of the Arab countries in terms of Economic
Justice, where the lighter the color the less just the economic situation is. Accordingly, Syria has scored the
lowest preceded by Sudan while the United Arab Emirates (UAE) scored the highest. Based on the dimensions
utilized to build up the index, the low scores for Syria and Sudan are not surprising. The conflict in Syria wiped
25
out decades of development and limited the ability of existing institution for forward improvement. Political
instability reduced the ability of the state to have an enabling environment for private sectors to exist, shrank
the newly expanded banking sector and limited the governments capability to reduce inflation and formulate
policy that could advance private sector development.
It is worth noting that the quality of Economic Justice in most Arab countries is lower than most developed
countries in the world, however, some Arab states experienced major improvements. For example, in the
Financial Sector pillar, Lebanon (80), Bahrain (75) and Jordan (68), perform better than the average of OECD
countries (66). While in the “Red Tape and Regulation” pillar, the United Arab Emirates (81) performed
beyond the OECD average (82), and in the “Competitive Environment” pillar, Bahrain (71) scored as good as
the OECD average. Nevertheless, the highest scoring Arab country in the overall EJ index (UAE) scored below
the OECD average with a difference of 5%.
For all pillars, the Arab mean and median split the data with consistent similarity, except for the “Monetary
Policy” pillar, where some countries fall between the mean and the median. Countries such as Iraq, Oman ,
Qatar and KSA, score below the median, so they score less than 50% of the present countries. In addition,
they score above the mean, which indicates a left skewed distribution where the mean got affected with low
scores, significantly distant from the average.
Table 10 – EJ Index scores by pillar
weights
0.2 0.2 0.2 0.2 0.2
Country Competitive
Environment
Enabling
Environment for
Private Sector
Red Tape &
Regulations
Financial
Sector
Monetary
Policy EJ %
Algeria 26 50 62 32 65 49%
Bahrain 71 55 74 75 77 70%
Egypt 45 45 68 46 68 55%
Iraq 36 43 42 24 74 45%
Jordan 53 49 71 68 84 65%
Kuwait 51 57 58 61 78 62%
Lebanon 61 55 64 80 77 67%
Libya 34 43 47 30 60 44%
Mauritania 20 48 56 39 69 48%
Morocco 50 57 77 64 81 67%
Oman 43 60 73 58 75 63%
Qatar 59 65 74 58 75 67%
Saudi Arabia 43 67 74 50 70 62%
Sudan 31 31 53 26 41 37%
Syria 15 23 51 28 37 32%
Tunisia 47 55 73 50 76 61%
UAE 70 64 87 58 81 72%
OECD Average 71 77 82 66 86 77%
Arab Average
44
51
65
50
70
57
Arab Median
45
55
68
50
75
62
CV
36%
23%
19%
35%
19%
21%
A detailed presentation of radars, by country is presented in ANNEX 5 – Results by country.
26
4.2. Results by Pillars and Groups of Countries
As mentioned earlier, the EJ index is computed based on the five sub-indices, relevant to each of the five
pillars of Economic Justice: Competitive Environment, Enabling Environment for Private Sector, Red Tape &
Regulations, Financial Sector, Monetary Policy. In terms of comparative variation of the EJ index, some pillars
show more dispersion in scores while others were more concentrated. For example, the “Competitive
Environment” and “Financial Sector” dimensions show the most disparity among Arab states, with
coefficients of variation of 36% and 35% respectively (see:
Table 10
). In addition, the differences between the
Arab averages and the OECD averages were around 16 percentage points for all pillars except for Competitive
Environment and Enabling Environment for Private Sector, where the magnitude of differences increased to
27 and 26 percentage points respectively.
Below, we explain the obtained results by each dimension with reference to the countries in the EJ index.
4.2.1. Competitive Environment Pillar
The Competitive Environment dimension measures the efficiency of the private sector through measuring
the economic participative power, monopolistic power, privileges and exclusiveness to specific economic
agents, informal sector and price controls. Economic justice in the Arab world requires the march toward
more efficient policies that enhance market-based competition, healthier strategies for administered prices
to better target the vulnerable and poor, and more efficient anti-monopoly policies. there is a positive
relationship between the “Competitive Environment” pillar and the EJ Index, with a significant correlation
coefficient of 0.893 (see:
Table 9
, p.24). Qatar, the UAE and Bahrain, all high-income countries with high levels
of economic justice, have competitiveness levels comparable to the OECD average of 71%. On the other end
of the spectrum, Syria and Mauritania, both lower middle-income countries with below average levels of
economic justice, demonstrate a very low level of competitiveness at 15% and 20% respectively. Some high-
income level are Saudi Arabia and Oman are expected to perform better in the Competitive Environment
pillar. These two countries have relatively high levels of economic justice yet fall short on the competitive
environment front; this affirms that the areas where Saudi Arabia and Oman need to exert some effort are
in fostering a competitive environment as their scores in the other pillars, especially Red Tape and
Regulations, are close to the OECD average.
4.2.2. Enabling Environment for Private Sector Pillar
This pillar measures areas related to contract enforcing, perception of entrepreneurs’ standard of living,
likelihood of violent demonstrations, getting credit, and foreign trade risk. The linear association between
this pillar and EJ Index is strong and positive (0.881, see:
Table 9
, p.24).
It is not surprising to see that Syria would has a score of 23%, placing it at the bottom of the ranking. Syria
suffered from an international embargo for more than a decade and a low level of banking sector
development, which limited credit accessibility, especially that most lending facilities were limited to
government owned entities. Recently, political instability reduced the private sector’s ability to survive and
impacted the overall institutional framework. What is surprising is that all Arab states, especially high income
level countries, scored well below the OECD average (see:
Table 10
); at a maximum of 67%, Saudi Arabia was
the most privileged, with a 10 percentage points difference from the OECD average (77).
4.2.3. Red Tape & Regulations Pillar
Red Tape and lengthy bureaucratic procedures inhibit the presence of an enabling business climate and
reduce economic participation. Aside from other constraints, Red Tape usually increases the cost of
transactions to both the private and public sectors, where small and medium enterprises entrepreneurs
share the highest cost. This pillar appraises how costly and lengthy procedures to start any business could
cost economic agents billions of dollars annually in many Arab countries. The red tape scores reveal that
27
Libya (47%), Sudan (53%) and Syria (51%) have the lowest performance scores while the best performance
score was recorded for the UAE at 87%, outperforming the OECD average (82). Below the OECD average,
Morocco scores 77%, and Bahrain, Qatar and KSA at 74% each. The strong performance in the GCC nations
was due to the recent reform initiatives to improve the public administrative infrastructure especially in the
UAE and Bahrain (such as the E-government and sponsorship requirements to start a business among others).
Overall, the GCC countries enjoy a more efficient economic regulatory framework, especially when it comes
to starting a business. Mauritania and Algeria score well on this pillar relative to other pillars. However their
score is dragged down by the first pillar “Competitive Environment” principally as well as by the 2
nd
and 4
th
pillars “Enabling Environment for Private Sector” and “Financial Sector”, respectively.
4.2.4. Financial Sector Pillar
Financial sector policies are considered integral to economic growth. Looking at the outcomes of the Financial
Sector pillar, a positive relationship between this pillar and EJ Index is predominant, with a correlation
coefficient of 0.895 (see:
Table 9
above). On the one hand, Lebanon (80), Bahrain (75) and Jordan (68)
outperformed the OECD average (66). This good performance is attributed to the availability of financial
services, access to credit, financial freedom and financial sector credibility facing all the political and
economic shocks especially in Lebanon and Bahrain. On the other hand, Iraq (24) performed the worst with
followed by Sudan (26), Syria (28) and Libya (30).
4.2.5. Monetary Policy Pillar
Assigned targets of monetary policy include inflation, economic growth and employment. Having well
defined targets for monetary authority should enhance macroeconomic stability, improve business climate
and increase citizen’s purchasing power. Any exchange rate geographical map shows that Arab countries
have either a pegged or a crawling peg regime. Targeting exchange rate limits the role of central banks to act
as stabilizers in the presence of aggregate shocks. However, anecdotal evidence revealed that due to
recurrent geopolitical and economic instability in most Arab states, a pegged regime serves economic
stability better, helping keeping prices at manageable levels. Countries such as Jordan, UAE, Iraq, Tunisia,
Lebanon, Kuwait and Qatar obtain a high score in this pillar. None of the countries meet OECD levels at 86%,
but Jordan (84%), Morocco (81%) and the UAE (81%) are not far behind, while countries such as Sudan (41%)
and Syria (37%), experienced a relatively low score due to their political instability. For example, looking at
Syria, the currency lost huge percentage of its value due to double digits inflation since the start of the conflict
in 2011. Further, Sudan experienced major socioeconomic conditions and the secession of South Sudan. Iraq
(74), Mauritania (69) Algeria (65) and Libya (60), all score high in this pillar relative to other pillars. Their
overall EJ index score is dragged down due to their lack of competitiveness and their financial system fragility,
mainly.
4.3. Overview of related indices
Many indices have tackled tangent components of EJ described in this paper. Indices such as the World
Governance Indicators (WGI’s), the Human Development Index (HDI), Global Competitiveness Index (GCI),
and others (
Table 11
), are linked to a certain extent to economic justice. Nonetheless, each one of these
indices solely captures a specific area of potential measurement. Further, such indices are based on different
methodologies, theoretical background, calculation, and most importantly, the core objective of the
aforementioned indices is not economic justice.
28
Table 11 – Available Indices Related to Justice
Index Dimensions
Number of
Arab Countries
Covered
Issuer(s)
Worldwide Governance
Indicator
Governance 22 /22 World Bank
Human Development Index Health, Education,
Standard of Living
21 /22 UNDP
Global Competitiveness Index Institutions, infrastructure, stable
macroeconomic framework,
health and primary education, higher
education and training, efficient goods
markets, efficient labor markets,
developed financial markets,
technologies, market size (domestic
and international), production
processes, innovation
14/22 World Economic Forum
The Index of Economic
Freedom
Rule of Law (property rights,
government integrity, judicial
effectiveness)
Government Size (government
spending, tax burden, fiscal health)
Regulatory Efficiency (business
freedom, labor freedom, monetary
freedom)
Open Markets (trade freedom,
investment freedom, financial freedom)
16/22 The Heritage Foundation
4.4. Association between EJ Index and other Indices
In this section, we attempt to provide an analytical comparison between the EJ index and other indices. This
comparison should reveal the added value of the EJ index in capturing dimensions unique to economic
justice, uncovered by other indices. This comparison is based on a simple rational saying that if two indices
measure the same phenomenon, they should have a strong linear association. This means that scores should
be more or less aligned at the bisector line. Unlike the plots between EJ and its own pillars, it is expected in
this section that countries deviate from the bisector, thus fall more frequently in the 2
nd
(top left) or 4
th
(bottom right) quadrants. On the other hand, a sound and just economic situation is expected to affect
positively the scores of other indices measuring economic freedom, human development, global
competitiveness and governance. Consequently, it is expected of the first quadrant (top right) to be
populated with countries performing well in economic justice.
29
Figure 4 – Plot of the Index of Economic Freedom versus Economic Justice Index
4.4.1. The Index of Economic Freedom (IEF)
The fundamental principles that underlie this index are non-discrimination, empowerment of the individual
and open competition, as described by the Heritage Foundation, the developers of IEF. The main economic
freedoms measured are based on the rule of law, the size of the government, regulatory efficiency and
market openness. With a score ranging from 0 to 100, the countries in this study show high discrepancy
among each other, with scores ranging from as low as 35 to as high as 75. As expected, Figure 4 shows a
strong positive relationship between the two indices. Most countries cluster in the first quadrant, with high
income countries surrounding the OECD average as seen with the GCI. Libya and Sudan score low on both
EFI and EJ Index. Algeria and Mauritania seem to score low on the economic justice index relative to their
index of economic freedom. Mainly, this discrepancy stems from high fiscal freedom recorded under the EFI,
which pulled-up the two countries’ scores on EFI. Syria and Iraq are not included in the analysis due to data
unavailability.
4.4.2. Human Development Index (HDI)
The human development index is a measure of life expectancy, education and per capita income and was
devised with the purpose of shifting focus from GDP to people-centered indicators of development. As
structured by the UNDP, the scale of HDI varies from 0 to 1, and the higher the score, the higher the level of
human development. The relationship between HDI and EJ is horizontal with a cluster of high income level
countries in the 1
st
quadrant scoring close to the OECD average of 0.88. This clustering becomes less obvious
for upper-middle and lower-middle income level countries, as Algeria, Libya, Iraq, Mauritania, Syria and
Sudan are scattered in 2
nd
quadrant of the graph in Figure 5. Specifically, Sudan and Mauritania fall on the
boarders of the 3
rd
and 2
nd
quadrants, where the former scored the lowest HDI score at 0.47. Algeria shows
a higher HDI level for its below average EJ score. This can be attributed to higher years of schooling and life
expectancy, but stagnant income levels, which do not have an immediate or large impact on economic
justice, especially with the prevalent political environment. . Finally, Syria, Iraq and Libya’s HDI scores are
high mainly due to good standing in terms of life expectancy at birth for Syria (which may have been
BHR
KWT
OMN
QAT
SAU
ARE
DZA
JOR
LBN
LBY
EGY
MRT
MAR
SDN
TUN
OECD
20 30 40 50 60 70 80
The Index for Economic Freedom
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
30
computed for periods before the war), and high gross national income per capita for Iraq and Libya.
Figure 5 – Plot of Human Development Index versus Economic Justice Index
4.4.3. Global Competitiveness Index (GCI)
With a score from 1-7, 7 being the best, GCI ranks countries according to their set of institutions, policies and
other factors that determine an economy’s level of productivity and competitiveness, as designed by the
World Economic Forum. The Arab countries’ score range between 3 and 6. The graph plotting the GCI versus
the EJ index in Figure 6 shows that most countries are clustered in the first quadrant, especially high-income
countries. Notably, 4 out of 6 GCC countries score above the OECD average on the GCI, but are still lagging
behind on the EJ Index, especially in terms of enabling of the private sector. Lebanon and Egypt suffer
significant setbacks in macroeconomic policy stability and infrastructure provision, thus keeping their score
in the fourth quadrant, below the corresponding expected GCI levels. Sudan and Iraq were excluded from
the analysis due to data unavailability.
BHR
KWT
OMN
QAT
SAU
ARE
DZA
IRQ
JOR
LBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
0 .5 1
Human Development Index
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
31
Figure 6 – Plot of Global Competitiveness Index versus Economic Justice Index
4.4.4. World Governance Indicators (WGI)
World governance indicators measure government effectiveness, regulatory quality, control for corruption,
rule of law, political stability and absence of violence, and voice and accountability. The scores are developed
by the World Bank and range from -2.5 to +2.5 . In general, Arab countries score poorly on the WGI, in effect
the MENA region lags behind other economies, such as that of Europe, North America and Latin America.
(Kamaly & El-Said, 2017). Needless to say, the economic justice index is multidimensional and goes beyond
any of these standalone indices. For instance, “rule of law” under WGI can be compared to “Enabling
Environment for Private Sector” under EJ index with reference to quality of contracts and likelihood of violent
demonstrations; while “Regulatory efficiency” can be linked to “Red Tape & Regulations”. Generally,
countries under analysis are very dispersed in these dimensions. The recorded irregularities reflect strong
weaknesses which states can focus on for their pursuit of economic justice.
Regulatory quality and government effectiveness indicators show approximately the same results (see Figure
7). First, all the countries lag behind the OECD average on the EJ axis, while on the “Government
Effectiveness” axis Tunisia is an exception, where it surpassed the OECD average; some of the high income
level countries such as Oman, Qatar and Bahrain came close to the OECD average.
BHR
KWT
OMN
QAT
SAU
ARE
DZA
JOR
LBN
LBY
EGY
MRT
MAR
SYR
TUN
OECD
1 2 3 4 5 6 7
Global Competitiveness Index
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
32
Figure 7 – Plot of Economic Justice Index versus WGI: Regulatory Quality and Government Effectiveness
Second, these graphs do not show a strong positive trend, nor do they show a pattern related to income
levels. The main irregularities are captured by the data points of Egypt, Saudi Arabia, Kuwait, Morocco and
Lebanon. These countries are an interesting combination of lower middle income, upper middle income and
high income countries.
Control for corruption and rule of law are also consistent with the previous analysis (see: Figure 8). However,
for the control for corruption, we observe Saudi Arabia joining its high income level peers in the first quadrant
and Tunisia falling to the 4
th
. As for the rule of law, we see Kuwait joining its peers in the first quadrant.
Control for corruption is the only measure under which Saudi Arabia performs well in the WGI.
BHR
KWT
OMN
QAT
SAU
ARE
DZA
IRQ
JOR
LBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
-2.5 -1.5 -.5 0 .5 1.5 2.5
WGI - Regulatory Quality
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
BHR
KWT
OMN QAT
SAU ARE
DZA
IRQ
JOR
LBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
-2.5 -1.5 -.5 0 .5 1.5 2.5
WGI - Government Effectiveness
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
33
Figure 8 – Plot of Economic Justice Index versus WGI: Control for Corruption and Rule of Law
Its relatively high EJ Index scores under “Enabling Environment for Private Sector” and “Red Tape &
Regulations” pillars can be attributed to perception of standard of living for entrepreneurs, foreign trade risk,
and trading across borders (see: ANNEX 6 – Dataset : Indicators, Pillars, EJ Index, p.64). Lebanon and Morocco
show resilience in the EJ Index due to their high scores in the three pillars: “Red Tape & Regulations”,
“Financial Sector” and “Monetary Policy”. Egypt does perform relatively well on these scores, but to a lesser
extent than Lebanon and Morocco.
Political stability and the absence of violence indicator is very scattered and does not follow a specific trend,
nor income level patterns. Figure 9 shows that 7 out of 17 countries fall in the 4
th
quadrant, three of which
are high income level countries including Bahrain and the UAE went below the bisector line.
BHR
KWT
OMNQAT
SAU
ARE
DZA
IRQ
JOR
LBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
-2.5 -1.5 -.5 0 .5 1.5 2.5
WGI - Control for Corruption
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
BHR
KWT
OMNQAT
SAU
ARE
DZA
IRQ
JOR
LBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
-2.5 -1.5 -.5 0 .5 1.5 2.5
WGI - Rule of Law
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
34
Figure 9 – Plot of Economic Justice Index versus WGI: Political Stability & Absence of Violence
Voice and accountability shows an even odder trend, with 11 countries falling in the 4
th
quadrant, leaving the
OECD data point alone in the 1
st
quadrant and showing an alarming gap (see: Figure 10). These indicators do
not show a positive nor a negative correlation. The ability of some countries to maintain fair levels of
economic justice in the absence of political stability and accountability proves again the multidimensionality
of this index. It is important to note that data on Syria cannot be taken with as precision as the other countries
due to the ongoing Syrian civil war.
Figure 10 – Plot of Economic Justice Index versus WGI: Voice & Accountability
4.4.5. Gender Inequality Index (GII)
GII measures gender disparities in reproductive health, empowerment and economic status on a 0-1 scale.
The wider the gap between men and women, the greater the loss to human development, and the higher
BHR
KWT
OMN
QAT
SAU
ARE
DZA
IRQ
JOR
LBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
-2.5 -1.5 -.5 0 .5 1.5 2.5
WGI - Political Stability and Absence of Violence
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
BHR
KWT
OMN
QAT
SAU
ARE
DZA
IRQ
JORLBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
-2.5 -1.5 -.5 0 .5 1.5 2.5
WGI - Voice and Accountability
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
35
the score. For consistency purposes, the graph plotting GII versus EJ employs the flipped values of the GII,
where the higher the score the less the inequality (see: Figure 11). This index is produces by UNDP as a part
of the Human Development Report. Mostly, countries with lower gender gaps score higher on the economic
justice index. The exceptions include Libya and Algeria, which score relatively high on keeping the gender gap
narrow and still score low on the economic justice index due to the lack proper competition-fostering
policies, as well as robust financial institutions. Qatar and Egypt are also exceptions that score high on
economic justice, yet suffer on the gender inequality front. The labor force participation rate of females is
significantly underrepresented in both Qatar and Egypt. Additionally, the latter suffers from high maternal
mortality ratios.
Figure 11 – Plot of Gender Inequality Index versus Economic Justice Index
4.4.6. Youth Employment
The indicator is retrieved from the World Development Indicators database, by the World Bank. The figures
are based on ILO estimates of the percentage of youth unemployment. For consistency purposes, the
indicator was reversed to get the percentage of youth employment instead. The graph in Figure 12 is
coherent with the higher the better concept. Most countries (11 out of 17) lie in the first quadrant, suggesting
that a country with a good economic justice standing is expected to have high levels of youth employment.
In this quadrant, four Arab countries’ youth employment outshines that of the OECD (83.06%), all of which
are high-income level countries: Qatar (98.82%), Bahrain (94.86%), United Arab Emirates (88.51%) and
Kuwait (85.54). Seven countries fall under the second quadrant: Syria, Sudan, Mauritania, Iraq, Libya and
Algeria, and they represent a sample of middle-income countries that are facing conflicts and political unrest.
BHR
KWT
OMN
QAT
SAU
ARE
DZA
IRQ
JOR LBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
0 .5 1
Gender Inequality Index
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
36
Figure 12 – Plot of Youth Employment versus Economic Justice Index
BHR
KWT
OMN
QAT
SAU
ARE
DZA
IRQ
JORLBN
LBY
EGY
MRT
MAR
SDN
SYR
TUN
OECD
0 10 20 30 40 50 60 70 80 90 100
% Youth Employment
20 30 40 50 60 70 80
Economic Justice Index
Higher Quadrant High Income Countries
Upper Middle Income Countries Lower Middle Income Countries
OECD average
37
V. Conclusion and Recommendations
The eruption of Arab Spring in 2011 has revealed that reaching high level of economic growth is not a
panacea. It was a surprise and an eye-opener that the outbreak of demands for change happened in
Tunisia and Egypt, two countries which have witnessed significant economic growth and stability prior
to 2011. Indeed, according to Gallop polls, almost 50 percent of the Arab populations are not satisfied
with their lives. Policymakers in the region should not only content with basic macroeconomic indicators
which cannot capture the level of equality of opportunity, equity of living conditions and equality of
rights. These concepts are particularly important for the region which is usually criticized on the ground
of low justice and weak governance. If Arab countries are serious about achieving the 2030 Agenda, they
should regard economic growth not as an aim in itself but rather a tool to improve all citizens’ wellbeing.
In this context, the concept of economic justice is very critical as it refocuses the compass of economic
system and economic policies toward people’s welfare.
This paper attempts to draw the attention of the policymakers in the region to the centrality of economic
justice in their march toward inclusive growth and sustainable development. This study aims, for the
first time, to gauge the level of economic justice in the Arab region by building a conceptual framework
defining the elements of economic justice, from a policymaking perspective. It then proceeds by adopting
a carefully designed statistical framework to construct a composite index of economic justice for the
Arab region. After undergoing a series of robustness checks, this composite justice index is then
compared to other relevant indices such as Human Development Index, Global Competitiveness Index,
and the Index of Economic Freedom to understand better the complex relationships between economic
justice from one side and human development, competitiveness and freedom from the other side.
Besides its originality in creating an index for economic justice in the Arab region, the study reveals a
number of interesting results. First, on average, economic justice is trailing behind more advanced
countries (OECD) with a big margin (20% difference). The pillars which are lagging the most are the
competitive environment and enabling environment for the private sector (27% and 26% difference
respectively); whereas the pillars which are lagging the least are financial sector and monetary policy
(16% difference each). Second, despite the mediocre average of the Arab countries in terms of economic
justice, the index points to the significant discrepancies among them. For example, UAE is behind the
OECD average of 77% by only 5%; whereas Syria and Sudan are trailing OECD average by a staggering
difference of 45% and 40% respectively. Third, while the economic index of each Arab country falls below
the average of OECD countries, a few countries have surpassed the OECD average in certain pillars: UAE
in red tape and regulation pillar and Bahrain, Jordan and Lebanon in the financial sector pillar. Fourth,
comparing the economic justice index with other global indices show that there is evidence of positive
association between the economic justice index from one side and index of global freedom, human
development index, global competitiveness index and youth employment from the other side; whereas
governance indicators and gender inequality index have shown ambiguous relationship with the
economic justice index. This result is expected since while our constructed economic justice index is
related in general to some aspects of development and competitiveness and freedom; however, it carries
additional information pertaining to the society’s economic rights that revolve around exchanging goods
and services, entering contracts and earning a living.
Finally, the policy implications of this index are numerous. Among the most important are the follwoing:
First, it presents an evidence-based assessment of the stance of economic justice in the region with its
corresponding pillars. This by itself is a groundbreaking analysis which puts in the forefront, for the first
time, the performance of Arab countries in terms of economic justice and benchmarking it against more
advanced countries. Second, it helps identifying the pillars for each Arab country that need further
attention to improve the stance of economic justice which is critical to render development and growth
38
more inclusive and fair to all the society’s segments. Third, this index could be used as input to a
multiplicity of qualitative and quantitative analyses to understand better the challenges facing the Arab
region and to design more rightful policies to eliminate injustice and grievances plaguing the Arab region
and hampering its development. In order, to make use fully of this index, further research will be aimed
to render the index dynamic and to expand it to include more countries.
39
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43
ANNEX 1 – Originally Considered Indicators
Indicators Definition Source
Market-based competition To what level have the fundamentals of market-based competition developed? BTI
Administered prices Share of administered prices IPD
Ease of market entry
It is the simple average of two variables: importance, in practice, of barriers to entry for new competitors in
markets for goods and services (excluding the financial sector and beyond the narrow constraints of the market)
(1) related to administration (red tape etc.), (2) related to the practices of already established competitors
IPD
Intensity of local competition In your country, how intense is competition in the local markets?
WEF - Global
Competitiveness
Index
Extent of market dominance In your country, how would you characterize corporate activity?
WEF - Global
Competitiveness
Index
Percent of firms competing against
unregistered or informal firms Does this establishment compete against unregistered or informal firms?
Enterprise Surveys -
WB
Percent of firms identifying practices
of competitors in the informal sector
as a major constraint
Using the response options on the card; To what degree are Practices of Competitors in the Informal Sector an
obstacle to the current operations of this establishment?
Enterprise Surveys -
WB
Effectiveness of anti-monopoly policy In your country, to what extent does anti-monopoly policy promote competition?
WEF - Global
Competitiveness
Index
Competition regulation
arrangements Efficiency of competition regulation in the market sector (excluding the financial sector)
IPD
Anti-monopoly policy To what extent do safeguards exist to prevent the development of economic monopolies and cartels, and to
what extent are they enforced?
BTI
Protecting Minority Investors (DTF)
It measures the strength of minority shareholder protections against misuse of corporate assets by directors for
their personal gain as well as shareholder rights, governance safeguards and corporate transparency
requirements that reduce the risk of abuse.
The DTF measure illustrates the distance of an economy to the “frontier”, which represents the best
performance observed on each Doing Business topic across all economies and years included since 2005. An
economy’s distance to frontier is indicated on a scale from 0 to 100, where 0 represents the lowest performance
and 100 the frontier.
Ease of Doing
Business - WB
44
Government respect for contracts It is the simple average of two variables: In the past 3 years, has the State withdrawn from contracts without
paying the corresponding compensation (1) vis-à-vis national stakeholders? (2) vis-à-vis foreign stakeholders?
IPD
Information on the quality of goods
and services (International
Standards)
Implementation of a system of norms and standards as part of an international system (e.g. ISO, Codex etc.)
IPD
Investment freedom
constructs the freedom of investment by deducing investment restrictions over 7 categories:
-1-National treatment of foreign investment
-2-Foreign investment code
-3-Restrictions on land ownership
-4-Sectoral investment restrictions
-5-Expropriation of investments without fair compensation
-6-Foreign exchange controls
-7-Capital controls
Heritage - Index of
Economic Freedom
Ratio of FDI inflows to GNI, (per
capita, current $US)
FDI flows consist of the net sales of shares and loans (including non-cash acquisitions made against equipment,
manufacturing rights, etc.) to the parent company plus the parent firm´s share of the affiliate´s reinvested
earnings plus total net intra-company loans (short- and long-term) provided by the parent company. For
branches, FDI flows consist of the increase in reinvested earnings plus the net increase in funds received from the
foreign direct investor.
FDI flows with a negative sign (reverse flows) indicate that at least one of the components in the above definition
is negative and not offset by positive amounts of the remaining components.
GNI per capita based on purchasing power parity (PPP). PPP GNI is gross national income (GNI) converted to
international dollars using purchasing power parity rates. An international dollar has the same purchasing power
over GNI as a U.S. dollar has in the United States. GNI is the sum of value added by all resident producers plus
any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income
(compensation of employees and property income) from abroad. Data are in current international dollars based
on the 2011 ICP round.
UNCTAD
Public support for innovation
It is the simple average of three variables: (1) Efficiency of technology transfer mechanisms and skills from
foreign to domestic stakeholders. Efficiency of public support in moving upmarket and acquiring technologies (2)
in SMEs, (3) in large companies
IPD
Public-private cooperation
it is the simple average of three variables: (1) Degree of cooperation between the public and private sectors? (2)
Degree of involvement by the State's highest authorities in the cooperation between public and private
stakeholders? (3) Does this cooperation allow account to be taken of the interests of key economic and social
stakeholders in the country?
IPD
Support for businesses considering
the public interest
Is support (subsidies, trade protection, financial facilities etc.) granted to local and foreign companies conditional
on the achievement of objectives serving the general interest?
IPD
45
Investment climate for rural
businesses
It is composed of 3 variables: (1) Environment for private sector development in rural areas, (2) Market
liberalization in rural areas, (3) Procedures for registering small rural business
IFAD
Effectiveness of insolvency law Is insolvency legislation efficient? IPD
Restructuring procedures (in case of
insolvency) Efficiency of restructuring procedures in the event of insolvency IPD
Resolving Insolvency (DTF)
Resolving Insolvency indicator studies the time, cost and outcome of insolvency proceedings involving domestic
entities. In addition, this year it introduces a new measure, the strength of insolvency framework index,
evaluating the adequacy and integrity of the legal framework applicable to liquidation and reorganization
proceedings. The data for the resolving insolvency indicators are derived from questionnaire responses by local
insolvency practitioners and verified through a study of laws and regulations as well as public information on
bankruptcy systems. The ranking of economies on the ease of resolving insolvency is determined by sorting their
distance to frontier scores for resolving insolvency.
Ease of Doing
Business - WB
Procedures for land tenure
formalization and registration Are there any current procedures for land tenure formalization and registration?
IPD
Land tenure insecurity
It is the simple average of three variables: (1) Importance of land issues as a political and media concern. Share of
the population with no formally recognized land tenure rights (2) in urban and peri-urban areas, (3) in rural areas
IPD
Contract enforcing (DTF)
This indicator measures the time and cost for resolving a commercial dispute through a local first-instance court.
In addition, this year it introduces a new measure, the quality of judicial processes index, evaluating whether
each economy has adopted a series of good practices that promote quality and efficiency in the court system.
The ranking of economies on the ease of enforcing contracts is determined by sorting their distance to frontier
scores for enforcing contracts.
Ease of Doing
Business - WB
Transparency of government
policymaking
In your country, how easy is it for businesses to obtain information about changes in government policies and
regulations affecting their activities?
WEF - Global
Competitiveness
Index
Perception of standard of living for
entrepreneurs
Is the city or area where you live a good place or not a good place to live for entrepreneurs forming new
businesses?
Gallup
Corruption Within Businesses Is corruption widespread within businesses located in this country, or not? Gallup
Efficiency of legal framework in
settling disputes In your country, how efficient is the legal framework for private businesses in settling disputes?
WEF - Global
Competitiveness
Index
Efficiency of legal framework in
challenging regulations
In your country, how easy is it for private businesses to challenge government actions and/or regulations through
the legal system?
WEF - Global
Competitiveness
Index
46
Transparency of government
policymaking to businesses
In your country, how easy is it for businesses to obtain information about changes in government policies and
regulations affecting their activities?
WEF - Global
Competitiveness
Index
Likelihood of violent demonstrations Assessment of the likelihood of violent demonstrations, based on the question, “Are violent demonstrations or
violent civil/labor unrest likely to pose a threat to property or the conduct of business over the next two years?”
Global Peace Index
Business Impact of rules on FDI In your country, how restrictive are rules and regulations on foreign direct investment (FDI)?
WEF - Global
Competitiveness
Index
Dealing with construction permits
(DTF)
This indicator records all procedures required for a business in the construction industry to build a warehouse
along with the time and cost to complete each procedure. In addition, this year Doing Business introduces a new
measure, the building quality control index, evaluating the quality of building regulations, the strength of quality
control and safety mechanisms, liability and insurance regimes, and professional certification requirements.
Ease of Doing
Business - WB
Number of days to obtain an
operating license
Approximately how many days did it take to obtain this operating license from the day of the application to the
day it was granted?
Enterprise Surveys -
WB
Business licensing and regulations
Are business licenses available to all citizens? It is composed of four variables: (1) In law, anyone may apply for a
business license. (2) In practice, citizens can obtain any necessary business license (i.e. for a small import
business) within a reasonable time period.(3) In practice, citizens can obtain any necessary business license (i.e.
for a small import business) within a reasonable time period.(4) In practice, citizens can obtain any necessary
business license (i.e. for a small import business) at a reasonable cost.
Q2- Are there transparent business regulatory requirements for basic health, environmental, and safety
standards? (A) In law, basic business regulatory requirements for meeting public health standards are
transparent and publicly available. (B) In law, basic business regulatory requirements for meeting public
environmental standards are transparent and publicly available. (C) In law, basic business regulatory
requirements for meeting public safety standards are transparent and publicly available.
Q3- Does government effectively enforce basic health, environmental, and safety standards on businesses? (A) In
practice, business inspections by government officials to ensure public health standards are being met and are
carried out in a uniform and even-handed manner. (B) In practice, business inspections by government officials to
ensure public environmental standards are being met are carried out in a uniform and even-handed manner. (C)
In practice, business inspections by government officials to ensure public safety standards are being met are
carried out in a uniform and even-handed manner.
Global Integrity
Report
47
Registering property (DTF)
This indicator records the full sequence of procedures necessary for a business (the buyer) to purchase a
property from another business (the seller) and to transfer the property title to the buyer’s name so that the
buyer can use the property for expanding its business, use the property as collateral in taking new loans or, if
necessary, sell the property to another business. It also measures the time and cost to complete each of these
procedures.
In addition, this year Doing Business adds a new measure to the set of registering property indicators, an index of
the quality of the land administration system in each economy. The quality of land administration index has four
dimensions: reliability of infrastructure, transparency of information, geographic coverage and land dispute
resolution.
Ease of Doing
Business - WB
Index of Regulatory Quality Reflects perceptions of the ability of the government to formulate and implement sound policies and regulations
that permit and promote private sector development.
WGI
Getting credit (DTF) Getting Credit explores two sets of issues—the strength of credit reporting systems AND the effectiveness of
collateral and bankruptcy laws in facilitating lending.
Ease of Doing
Business - WB
Labor regulations as a major
business constraint To what degree are Labor Regulations an obstacle to the current operations of firms? Enterprise Surveys -
WB
Burden of government regulation In your country, how burdensome is it for companies to comply with public administration’s requirements (e.g.,
permits, regulations, reporting)?
WEF - Global
Competitiveness
Index
Number of procedures to start a
business Number of procedures to start a business
WEF - Global
Competitiveness
Index
Tax policy risk
Tax policy risk is the average of: 1- stable regime (Is the tax regime clear and predictable?) Consider: - all forms of
taxation and taxes at the federal state and municipal level if relevant. - imposition, or likely imposition, of taxes in
case of fiscal emergency caused by excessive deficits, natural disasters or political conflicts. - cases where taxes
are imposed for a defined period of time (for example, one year) for specific defined reasons and then
maintained indefinitely. - frequent changes in administration which result in sharp swings in tax policy. 2-
discriminatory taxes (What is the risk that corporations will face discriminatory taxes?) : Are domestic firms in
effect taxed at lower rates than foreign firms? Does government use taxes to protect domestic industries or to
favor specific local corporations?
level of corporate taxation (Is the corporate tax rate low or is the prevailing rate of corporate tax actually paid
low?) If foreign and national firms face different tax regimes, consider each separately with final score an average
of the two regimes.
retroactive taxation (What is the risk from retroactive taxation?) Consider the severity of the fiscal constraint,
the government's record, and recent statements by planners regarding tax policy.
EIU Operational Risk
Model
48
Percentage of firms identifying
business licensing and permits as a
major constraint
Percentage of establishments that consider business licensing and permits to be the Biggest Obstacle
Enterprise Surveys -
WB
Electrical connection waiting time Delay in obtaining an electrical connection (upon application) Enterprise Surveys -
WB
Transparency of economic policy
(fiscal, budgetary, monetary,
exchange rate, etc)
It is the simple average of two variables: Is State economic policy (e.g. budgetary policy, fiscal policy etc.) (1)
communicated? (2) publicly debated?
IPD
Customs waiting time - exports
Average number of days to clear direct exports through customs.
Question: In fiscal year [….], when this establishment exported goods directly, how many days did it take on
average from the time this establishment’s goods arrived at their main point of exit (e.g., port, airport) until the
time these goods cleared customs?
Enterprise Surveys -
WB
Customs waiting time - imports Average number of days to clear imports from customs Enterprise Surveys -
WB
Percentage of firms identifying
customs and trade regulations as a
major constraint
Percent of firms identifying customs and trade regulations as a major constraint
Enterprise Surveys -
WB
Issuance of import licenses Difficulty in obtaining import licenses (entry barriers, corruption, red tape etc.) IPD
Foreign trade risk
It is the average of the following:
1. Trade embargo risk (What is the risk that the country will be subject to a trade embargo sponsored either by a
major international organization, a significant trading partner, or one or more of the G-8 countries?) If such an
embargo is already in place, score as high-risk.
2. Capital account (Can investors move money in and out of the country with ease for financial transactions
(capital account)?)
3. Financial crisis (What is the risk that a financial crisis could curtail access to foreign exchange for direct
investors?) Consider risk of contagion effects from peers and neighboring countries, as well as prevailing
domestic conditions
4. Capital controls risk (What is the risk that capital controls would be applied or, if already in place, tightened in
time of economic or financial crisis?)
5. Current account convertibility (Can investors make payments for goods and services and access foreign
exchange without restriction? (current-account convertibility)
6. Discriminatory tariffs (What is the risk of discriminatory tariffs?)
7. Excessive protection (What is the risk of excessive protection (tariff and non-tariff) in current period?)
EIU Operational Risk
Model
49
Availability of financial services In your country, to what extent does the financial sector provide the products and services that meet the needs
of businesses?
WEF - Global
Competitiveness
Index
Ease of starting a business It is the simple average of two variables: (1) Ease of starting a business governed by local law?, (2) Ease of setting
up a subsidiary of a foreign firm?
IPD
Ease of access to loans In your country, how easy is it to obtain a bank loan with only a good business plan and no collateral?
WEF - Global
Competitiveness
Index
Proportion of investments financed
by banks
Proportion of investments financed by banks (%)
Estimated proportion of purchases of fixed assets that was financed from bank loans.
Over fiscal year, please estimate the proportion of this establishment’s total purchase of fixed assets that was
financed from each of the following sources:
-Internal funds or retained earnings
-Owners’ contribution or issued new equity shares
-Borrowed from banks: private and state-owned
-Borrowed from non-bank financial institutions
-Purchases on credit from suppliers and advances from customers
-Other, moneylenders, friends, relatives, bonds, etc
Enterprise Surveys -
WB
Proportion of working capital
financed by banks
Proportion of the working capital that was financed by bank loans.
Over fiscal year , please estimate the proportion of this establishment’s working capital that was financed from
each of the following sources:
-Internal funds or retained earnings
-Borrowed from banks: private and state-owned
-Borrowed from non-bank financial institutions which include microfinance institutions, credit cooperatives,
credit unions, or finance companies
-Purchases on credit from suppliers and advances from customers
-Other, moneylenders, friends, relatives, etc.
Enterprise Surveys -
WB
Percentage of firms identifying
access to finance as a major
constraint
Percent of firms identify access/cost of finance as a "major" or "very severe" obstacle
Using the response options on the card; To what degree is Access to Finance an obstacle to the current
operations of this establishment?
Enterprise Surveys -
WB
50
Starting a business (DTF)
This indicator records all procedures officially required, or commonly done in practice, for an entrepreneur to
start up and formally operate an industrial or commercial business, as well as the time and cost to complete
these procedures and the paid-in minimum capital requirement. These procedures include obtaining all
necessary licenses and permits and completing any required notifications, verifications or inscriptions for the
company and employees with relevant authorities.
Ease of Doing
Business - WB
Trading across borders (DTF)
This indicator records the time and cost associated with the logistical process of exporting and importing goods.
Under the new methodology introduced this year, Doing Business measures the time and cost (excluding tariffs)
associated with three sets of procedures—documentary compliance, border compliance and domestic
transport—within the overall process of exporting or importing a shipment of goods
Ease of Doing
Business - WB
Efficiency of the tax administration
It is the simple average of four variables: Efficiency of the tax administration in relation to the collection of (1)
corporation tax in non-exempt economic sectors, (2) income tax of households with formal income (excluding
measures exempting low-income households), (3) tax across the whole of the national territory (excluding
statutory scheme exempting parts of the territory for specific reasons), (4) Practical ability of the administration
to limit tax evasion.
IPD
Soundness of banks In your country, how do you assess the soundness of banks?
WEF - Global
Competitiveness
Index
Micro-lending It is the simple average of two variables: (1) Significance of informal microfinance (tontines etc.), (2) Significance
of institutional microfinance (supported by NGOs, banks etc.)
IPD
Transparency of listed companies Transparency of information on listed companies IPD
Strengthening of banking and
financial supervision
It is the simple average of two variables: (1) Efficiency of the banking supervisory authority, (2) Efficiency of the
insurance market supervisory authority
IPD
Banking system To what extent have a solid banking system and a functioning capital market been established? BTI
Accounting information on banks It is the simple average of two variables: (1) Implementation of a standardized accounting system, (2)
Implementation of accounts certification for banks
IPD
Financial freedom
Financial freedom is an indicator of banking efficiency as well as a measure of independence from government
control and interference in the financial sector. State ownership of banks and other financial institutions such as
insurers and capital markets reduces competition and generally lowers the level of access to credit.
The Index scores an economy’s financial freedom by looking at five broad areas:
1-The extent of government regulation of financial services,
2-The degree of state intervention in banks and other financial firms through direct and indirect ownership,
Heritage - Index of
Economic Freedom
51
3-Government influence on the allocation of credit,
4-The extent of financial and capital market development, and
5-Openness to foreign competition.
Reliance on financial institutions
(Deposit rate=Deposit/M2)
Money and quasi money comprise the sum of currency outside banks, demand deposits other than those of the
central government, and the time, savings, and foreign currency deposits of resident sectors other than the
central government. This definition of money supply is frequently called M2; it corresponds to lines 34 and 35 in
the International Monetary Fund's (IMF) International Financial Statistics (IFS).
GDP (current LCU): GDP at purchaser's prices is the sum of gross value added by all resident producers in the
economy plus any product taxes and minus any subsidies not included in the value of the products. It is
calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of
natural resources. Data are in current local currency.
WDI
Life Insurance Premium to GDP Ratio of life insurance premium volume to GDP. Premium volume is the insurer's direct premiums earned (if
Property/Casualty) or received (if Life/Health) during the previous calendar year.
GFDD
Non-life Insurance Premium to GDP Ratio of nonlife insurance premium volume to GDP. Premium volume is the insurer's direct premiums earned (if
Property/Casualty) or received (if Life/Health) during the previous calendar year.
GFDD
Pension fund assets to GDP Ratio of assets of pension funds to GDP. A pension fund is any plan, fund, or scheme that provides retirement
income.
GFDD
Nonbank financial institutions’ assets
to GDP
Total assets held by financial institutions that do not accept transferable deposits but that perform financial
intermediation by accepting other types of deposits or by issuing securities or other liabilities that are close
substitutes for deposits as a share of GDP. It covers institutions such as saving and mortgage loan institutions,
post-office savings institution, building and loan associations, finance companies that accept deposits or deposit
substitutes, development banks, and offshore banking institutions. Assets include claims on domestic real
nonfinancial sector such as central-, state- and local government, nonfinancial public enterprises and private
sector.
GFDD
Mutual fund assets to GDP Ratio of assets of mutual funds to GDP. A mutual fund is a type of managed collective investment scheme that
pools money from many investors to purchase securities.
GFDD
Banks Concentration
Assets of five largest banks as a share of total commercial banking assets. Total assets include total earning
assets, cash and due from banks, foreclosed real estate, fixed assets, goodwill, other intangibles, current tax
assets, deferred tax, discontinued operations and other assets.
GFDD
Banks Competition A measure of deviation from perfect competition in the banking market (deviation of the H-statistic from 1).
The H-statistic measures the elasticity of banks revenues relative to input prices. Under perfect competition, an
GFDD
52
increase in input prices raises both marginal costs and total revenues by the same amount, and hence the H-
statistic equals 1. Under a monopoly, an increase in input prices results in a rise in marginal costs, a fall in output,
and a decline in revenues, leading to an H-statistic less than or equal to 0. When H-statistic is between 0 and 1,
the system operates under monopolistic competition. However, it is possible for H-stat to be greater than 1 in
some oligopolistic markets.
Bank overhead costs to total assets
Operating expenses of a bank as a share of the value of all assets held. Total assets include total earning assets,
cash and due from banks, foreclosed real estate, fixed assets, goodwill, other intangibles, current tax assets,
deferred tax assets, discontinued operations and other assets.
GFDD
Stock market turnover Total value of shares traded during the period divided by the average market capitalization for the period. GFDD
Capital adequacy The capital adequacy of deposit takers. It is a ratio of total regulatory capital to its assets held, weighted
according to risk of those assets.
GFDD
Bank nonperforming loans to gross
loans
Ratio of defaulting loans (payments of interest and principal past due by 90 days or more) to total gross loans
(total value of loan portfolio). The loan amount recorded as nonperforming includes the gross value of the loan
as recorded on the balance sheet, not just the amount that is overdue.
GFDD
Liquid assets to deposits and short-
term funding
The ratio= the value of liquid assets (easily converted to cash)/(total deposits + short-term funding).
This ratio gives an idea about the prudential measures taken by the regulator/banks to cover banks liability to
customers
Liquid assets include cash and due from banks, trading securities and at fair value through income, loans and
advances to banks, reverse repos and cash collaterals. Deposits and short-term funding includes total customer
deposits (current, savings and term) and short-term borrowing (money market instruments, CDs and other
deposits).
Consequently a very high ratio would mean that there is no adequate investments and opportunities. Too much
liquidity means the economic cycle is idle.
GFDD
Enabling conditions for rural
financial services development
It is composed of 4 variables: A-Government's policy on rural financial services
B-provision of rural financial services
C-Legal framework for the promotion and regulation of rural finance
D-Inspection and supervision of rural financial services providers
IFAD
Confidence in financial institutions In this country, do you have confidence in each of the following, or not? How about financial institutions or
banks?
Gallup
Interest rate spread (lending rate -
deposit rate)
Interest rate spread (lending rate minus deposit rate, %). Interest rate spread is the interest rate charged by
banks on loans to private sector customers minus the interest rate paid by commercial or similar banks for
demand, time, or savings deposits. The terms and conditions attached to these rates differ by country, however,
limiting their comparability.
WDI
53
Banks' assets to GDP
Total assets held by deposit money banks as a share of GDP. Assets include claims on domestic real nonfinancial
sector which includes central, state and local governments, nonfinancial public enterprises and private sector.
Deposit money banks comprise commercial banks and other financial institutions that accept transferable
deposits, such as demand deposits.
GFDD
Wastefulness of government
spending In your country, how efficiently does the government spend public revenue?
WEF - Global
Competitiveness
Index
Quality of budgetary and financial
management
Quality of budgetary and financial management assesses the extent to which there is a comprehensive and
credible budget linked to policy priorities, effective financial management systems, and timely and accurate
accounting and fiscal reporting, including timely and audited public accounts.
WDI
Generic subsidies (fuel sector) IEA estimates of fossil fuel consumption subsidies (billion USD) OECD
Central government debt, total (% of
GDP)
Debt is the entire stock of direct government fixed-term contractual obligations to others outstanding on a
particular date. It includes domestic and foreign liabilities such as currency and money deposits, securities other
than shares, and loans. It is the gross amount of government liabilities reduced by the amount of equity and
financial derivatives held by the government. Because debt is a stock rather than a flow, it is measured as of a
given date, usually the last day of the fiscal year.
WEF - Global
Competitiveness
Index
10 years average of (GDP Growth
Rate-Interest Rate)
It is the difference of the 10-year averages of GDP growth and real interest rate. Real interest rate is the lending
interest rate adjusted for inflation as measured by the GDP deflator. The terms and conditions attached to
lending rates differ by country, however, limiting their comparability. GDP growth is the annual percentage
growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2005
U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes
and minus any subsidies not included in the value of the products. It is calculated without making deductions for
depreciation of fabricated assets or for depletion and degradation of natural resources.
WDI
Ratio of short-term public debt to
total external debt
Short-term debt includes all debt having an original maturity of one year or less and interest in arrears on long-
term debt. Total external debt is debt owed to nonresidents repayable in currency, goods, or services. Total
external debt is the sum of public, publicly guaranteed, and private nonguaranteed long-term debt, use of IMF
credit, and short-term debt. This measures government commitment to long term liabilities
WDI
Ratio of short-term public debt to
total reserves
Short-term debt includes all debt having an original maturity of one year or less and interest in arrears on long-
term debt. Total reserves include gold.
It measures how much the government can commit to its short-term liabilities
WDI
54
Budget quality and transparency
It is the simple average of the numerical value of each of the responses to the 95 questions in the questionnaire
that assess the public availability of budget information. A country’s OBI score reflects the timeliness and
comprehensiveness of publicly available budget information in the eight key budget documents.
Open Budget Index
Budget Process Oversight &
Transparency
It consists of four questions: (1) Can the legislature provide input to the national budget? (2) Can citizens access
the national budgetary process? (3) In law, is there a separate legislative committee which provides oversight of
public funds? (4) Is the legislative committee overseeing the expenditure of public funds effective?
Global Integrity
Report
Reliability of government budget
it is the simple average of four variables: (1) Is the report produced by the IMF under Article IV published? (2)
Reliability of the State budget (completeness, credibility, performance etc.), (3) Reliability of basic economic and
financial statistics (e.g. national accounts, price indices, foreign trade, currency and credit etc.), (4) Reliability of
State-owned firms' accounts.
IPD
Private credit by banks to GDP Private credit by deposit money banks and other financial institutions to GDP. GFDD
Frequency of bank branches Number of commercial bank branches per 100,000 adults. GFDD
Fairness and Capacity of Taxes and
Customs
It consists of the following questions: In law, is there a national tax collection agency? Is the tax collection agency
effective? In practice, are tax laws enforced uniformly and without discrimination?
In law, is there a national customs and excise agency? Is the customs and excise agency effective? In practice, are
customs and excise laws enforced uniformly and without discrimination?
Global Integrity
Report
Macro-stability To what extent do the government’s fiscal and debt policies support macroeconomic stability? BTI
Tax administration as a major
business constraint Percent of firms identifying tax administration as a "major" or "very severe" obstacle
Enterprise Surveys -
WB
Tax rates as a major business
constraint Percent of firms identifying tax rates as a "major" or "very severe" obstacle Enterprise Surveys -
WB
Reliability of the State accounts Reliability of the State accounts (completeness, audit, budget review law etc.) IPD
Allocation and management of
public resources for rural
development
Composed of 4 variables:
A- Decentralization of administrative and fiscal authority
B- Budgetary allocation process against policy priorities (PRSP/relevant sector policies)
C- Release of budget for agricultural / rural development
D- Budget execution for agricultural and rural development
IFAD
Paying taxes (DTF) This topic addresses the taxes and mandatory contributions that a medium-size company must pay or withhold in
a given year, as well as measures the administrative burden in paying taxes
Ease of Doing
Business - WB
Independence of Central Banks Independence of the Central Bank IPD
55
Anti-inflation/forex policy To what extent do government and central bank pursue a consistent inflation policy and an appropriate foreign
exchange policy?
BTI
Monetary freedom
Monetary freedom combines a measure of price stability with an assessment of price controls. Both inflation and
price controls distort market activity. Price stability without microeconomic intervention is the ideal state for the
free market.
Heritage - Index of
Economic Freedom
Inflation standard deviation over 5-
years
We took the standard deviation of inflation, over 5 years, as measured by the consumer price index. inflation
reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and
services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally
used.
WDI
Trade liberalization it is the simple average of two variables: (1) Currency convertibility for current account transactions, (2) Is the
country a WTO member?
IPD
Prevalence of non-tariff barriers In your country, to what extent do non-tariff barriers (e.g. health and product standards, technical and labeling
requirements, etc.) limit the ability of imported goods to compete in the domestic market?
WEF - Global
Competitiveness
Index
Trade freedom
Trade freedom is a composite measure of the extent of tariff and non-tariff barriers that affect imports and
exports of goods and services. The trade freedom score is based on two inputs: (1) The trade-weighted average
tariff rate and (2)Non-tariff barriers (NTBs).
Heritage - Index of
Economic Freedom
56
ANNEX 2 – Euclidian Differences
Table 12 – Summary of top 3 Euclidian Differences
Competitive Environment Pillar - 3 indicators (j247 j248 j256)
Model Ed Method (Coefficients) Comments
m39 254.85 PCF Min Ed
m40 256.02 Simple Average (1/3,1/3,1/3) 1
st
after min Ed
m24 258.71 Weighted Average (.4,.3,.3) 2
nd
after min Ed
Enabling Environment for Private Sector Pillar - 5 indicators (j271 j273 j278 j298 j356)
Model Ed Method (Coefficients) Comments
m64 579.9699 Weighted Average (.2, .1, .2, .3, .2) Min Ed
m77 586.1912 Simple Average (.2,.2,.2,.2,.2) 1
st
after min Ed
m129 586.1912 PCF Same ranking as previous
Red Tape & Regulations Pillar - 5 indicators (j283 j288 j291 j344 j284b)
Model Ed Method (Coefficients) Comments
m77 660.56 Simple Average (.2,.2,.2,.2,.2) Min Ed
m129 669.09 PCF 1
st
after min Ed
m80 688.29 Weighted Average (.2, .2, .3, .2, .1) 2
nd
after min Ed
Financial Sector Pillar - 6 indicators (j296 j305 j310 j311 j312 j313)
Model Ed Method (Coefficients) Comments
m130 423.3759 Simple Average (1/6,1/6,1/6,1/6,1/6,1/6) Min Ed
m117 423.3759 Weighted Average (.3, .2, .1, .1, .2, .1) Same ranking as min Ed
m129 423.3759 PCF Same ranking as min Ed
Monetary Policy Pillar - 4 indicators (j303 j350 j351 j352)
Model Ed Method (Coefficients) Comments
m41 516.475 Weighted Average (.2,.3,.2,.3) Min Ed
m88 517.1911 Simple Average (.25,.25,.25,.25) 1
st
after min Ed
m36 520.9001 Weighted Average (.2,.2,.2,.4)
m87 526.6246 PCF 3
rd
after min Ed
Table 13 – Best aggregated models
Model Ed Model Specification Aggregation Coefficients
at the pillars level
Best Fit models
r202 1743.614
Combination of the best Weighted Average models:
‘Competitive Environment’ (.4,.3,.3)
‘Enabling Environment for Private Sector’ (.2,.2,.1,.2,.3)
‘Red Tape & Regulations’ (.2,.2,.3,.2,.1)
‘Financial Sector’ (.3,.2,.1,.1,.2,.1)
‘Monetary Policy’ (.2,.3,.2,.3)
0.2 0.2 0.2 0.2 0.2
r201 1743.614
Combination of the best Weighted Average models:
‘Competitive Environment’ (.4,.3,.3)
‘Enabling Environment for Private Sector’ (.2,.2,.1,.2,.3)
‘Red Tape & Regulations’ (.2,.2,.3,.2,.1)
‘Financial Sector’ (.3,.2,.1,.1,.2,.1)
‘Monetary Policy’ (.2,.3,.2,.3)
0.2 0.2 0.2 0.1 0.3
57
Worse Models
r181 3558.167
Combination of the best Weighted Average models:
‘Competitive Environment’ (.4,.3,.3)
‘Enabling Environment for Private Sector’ (.2,.2,.1,.2,.3)
‘Red Tape & Regulations’ (.2,.2,.3,.2,.1)
‘Financial Sector’ (.3,.2,.1,.1,.2,.1)
‘Monetary Policy’ (.2,.3,.2,.3)
0.1 0.6 0.1 0.1 0.1
r55 3641.185 Combination of the Simple Average models
0.1 0.6 0.1 0.1 0.1
r307 3641.185 Combination of PCF models, for the 5 pillars
0.1 0.6 0.1 0.1 0.1
Model Ed Model Specification Aggregation Coefficients
at the pillars level
58
ANNEX 3 – Boxplots of best 3 models per pillar
-2 -1 0 1 2
Boxplots of best 3 models
Competitive Environment
coefficients: .4, .3, .3 SA
f1_pcf
0 5 10 15 20
Boxplots of best 3 models - Ranks
Competitive Environment
coefficients: .4, .3, .3 SA
f1_pcf
-2 -1 0 1 2
Boxplots of best 3 models
Enabling Environment for Private Sector
coefficients: .2, .1, .2, .3, .2 SA
f1_pcf
0 5 10 15 20
Boxplots of best 3 models - Ranks
Enabling Environment for Private Sector
coefficients: .2, .1, .2, .3, .2 SA
f1_pcf
-2 -1 0 1 2
Boxplots of best 3 models
Red Tape & Regulations
coefficients: .2, .2, .3, .2, .1 SA
f1_pcf
0 5 10 15 20
Boxplots of best 3 models - Ranks
Red Tape & Regulations
coefficients: .2, .2, .3, .2, .1 SA
f1_pcf
59
-2 -1 0 1 2
Boxplots of best 3 models
Financial Sector
coefficients: .3, .2, .1, .1, .2, .1 SA
f1_pcf
0 5 10 15 20
Boxplots of best 3 models - Ranks
Financial Sector
coefficients: .3, .2, .1, .1, .2, .1 SA
f1_pcf
-3 -2 -1 0 1
Boxplots of best 3 models
Monetary Policy
coefficients: .2, .3, .2, .3 SA
f1_pcf
0 5 10 15 20
Boxplots of best 3 models - Ranks
Monetary Policy
coefficients: .2, .3, .2, .3 SA
f1_pcf
60
ANNEX 4 – Correlation Matrix
EJ Index
Score
Competitive
Environment
Enabling
Environment
for Private
Sector
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Market-based competition .884
**
.864
**
.839
**
.681
**
.771
**
.732
**
Administered prices .422 .656
**
.111 .275 .518
*
.304
Anti-monopoly policy .686
**
.753
**
.507
*
.628
**
.586
*
.556
*
Contract enforcing (DTF) .686
**
.422 .770
**
.494
*
.539
*
.770
**
Perception of standard of living for
entrepreneurs .718
**
.582
*
.911
**
.506
*
.430 .728
**
Likelihood of violent demonstrations .556
*
.437 .750
**
.468 .329 .465
Getting credit (DTF) .673
**
.499
*
.710
**
.785
**
.535
*
.440
Foreign trade risk .873
**
.732
**
.929
**
.689
**
.690
**
.793
**
Dealing with construction permits (DTF) .716
**
.567
*
.733
**
.684
**
.483
*
.689
**
Index of Regulatory Quality .571
*
.623
**
.362 .672
**
.472 .406
Starting a business (DTF) .757
**
.607
**
.628
**
.887
**
.723
**
.494
*
Trading across borders (DTF) .406 .247 .415 .763
**
.294 .095
Efficiency of the tax administration .904
**
.795
**
.795
**
.863
**
.802
**
.724
**
Banking system .880
**
.850
**
.685
**
.668
**
.927
**
.729
**
Financial freedom .817
**
.728
**
.612
**
.728
**
.913
**
.602
*
Reliance on financial institutions (Deposit
rate=Deposit/M2) .648
**
.605
*
.479 .442 .741
**
.562
*
Banks' assets to GDP .718
**
.699
**
.424 .569
*
.885
**
.562
*
Private credit by banks to GDP .810
**
.740
**
.543
*
.664
**
.922
**
.675
**
Frequency of bank branches .697
**
.610
**
.510
*
.465 .814
**
.638
**
Independence of Central Banks .542
*
.522
*
.355 .215 .513
*
.756
**
Anti-inflation/forex policy .896
**
.725
**
.859
**
.619
**
.758
**
.960
**
Monetary freedom .686
**
.567
*
.565
*
.572
*
.632
**
.669
**
Inflation standard deviation over 5-years .768
**
.574
*
.809
**
.525
*
.543
*
.914
**
61
ANNEX 5 – Results by country
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
United Arab Emirates
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Bahrain
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Qatar
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Lebanon
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Morocco
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Jordan
62
0
20
40
60
80
100
C6_1
C6_2
C6_4C6_5
C6_6
Oman
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Saudi Arabia
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Kuwait
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Tunisia
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Egypt
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Algeria
63
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Mauritania
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Iraq
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Libya
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Sudan
0
20
40
60
80
100
Competitive
Environment
Enabling
Environment
for Private…
Red Tape &
Regulations
Financial
Sector
Monetary
Policy
Syrian Arab Republic
64
ANNEX 6 – Dataset : Indicators, Pillars, EJ Index and Others
Table 14 - Raw Data
Raw data Indicator
Algeria
Bahrain
Egypt
Iraq
Jordan
Kuwait
Lebanon
Libya
Mauritania
Morocco
Oman
Qatar
Saudi
Arabia
Sudan
Syrian
Tunisia
UAE
OECD
Average -
Year 2014
Competitive
Environment
Market-based
competition
4 8 4 4 5 7 6 5 3 6 7 7 6 3 2 6 7 8.8
Administered prices
1 4 2 3 3 2 4 2 2 3 2 2 2 3 2 2 4 1.21
Anti-monopoly policy
4 5 7 3 6 5 5 3 2 4 3 7 4 3 2 5 6 9.2
Enabling
Environment
for Private
Sector
Contract enforcing
(DTF)
52.89 52.33 44.02 47.32 54.04 52.28 55.4 51.42 58.47 60.14 50.67 56.73 54.82 40.43 35.17 60.96 52.52 69.52
Perception of
standard of living for
entrepreneurs
0.61 0.65 0.47 0.65 0.52 0.6 0.67 0.61 0.61 0.64 0.65 0.77 0.81 0.42 0.19 0.64 0.77 1
Likelihood of violent
demonstrations
3 2 1 2 3 4 2 2.5 2 3 3 5 4 2 1 2 4 3.85
Getting credit (DTF)
43.75 43.75 56.25 18.75 25 43.75 50 12.5 25 50 56.25 43.75 68.75 25 25 50 56.25 71.97
Foreign trade risk
1.71 3.00 2.00 1.79 2.43 3.14 2.43 1.71 1.86 2.25 3.57 3.57 3.29 0.43 0.43 2.00 3.43 3.25
Red Tape &
Regulations
Dealing with
construction permits
(DTF)
63.81 84.26 61.71 68.85 65.27 60.09 54.16 0 74.41 77.7 76.91 83.65 80.85 55.25 0 72.92 92.59 74.86
Starting a business
(DTF)
73.11 74.76 88.09 73.88 85.5 70.89 82.48 74.55 58.17 90.29 79.07 83.18 78.17 74.34 72.62 83.54 89.96 87.11
Trading across
borders (DTF)
63.74 76.84 71.15 20.64 78.2 68.03 72.3 61.51 55.98 81.99 78.27 77.02 74.06 42.66 59.26 82.17 91.59 85.24
Efficiency of the tax
administration
2.5 3.33 2 0 2 1 1.25 1 2.5 2.5 2.67 2.33 3.67 2 2.25 2.5 3.67 3.37
Index of Regulatory
Quality 284b
-1.21 0.7 -0.75 -1.25 0.08 -0.13 -0.22 -2.19 -0.7 -0.01 0.69 0.57 -0.01 -1.39 -1.67 -0.35 0.98 1.28
Financial
Sector
Banking system
4 10 7 4 9 8 9 4 4 7 7 8 8 3 3 5 7 9.1
Financial freedom
30 80 40 10 60 50 60 20 40 60 60 50 50 30 20 30 50 70.29
Reliability of financial
institutions
0.67 0.92 0.72 0.57 0.73 0.91 0.94 0.66 0.85 0.8 0.86 0.9 0.51 0.61 0.61 0.8 0.83 0.01
Banks' assets to GDP
37.77 89.99 62.98 12.03 109.87 59.77 166.24 18.47 31.53 92.90 48.86 84.61 46.59 12.65 44.41 74.13 79.54 107.50
Private credit by
banks to GDP
15.19 67.39 25.6 6.04 69.27 56.59 89.05 12.79 27.52 69.94 41.37 36.73 37.92 9.22 20.43 69.28 60.32 91.76
65
Frequency of bank
branches
5.12 13.16 4.87 5.51 20.33 15.73 30.02 11.70 4.58 24.42 20.26 13.16 9.00 3.11 3.86 18.35 12.43 29.24
Monetary
Policy
Independence of
Central Banks
1 2 3 3 3 3 3 2 1 3 2 1 1 0 0 3 2 3.76
Anti-inflation/forex
policy
6 8 6 7 9 8 8 4 6 8 8 8 8 2 1 6 8 9.4
Monetary freedom
67.8 78.4 60.5 70 81.3 73.2 74.5 66.9 75.5 78.1 73.6 81.2 68.7 55.8 71.5 75.9 84.6 79.22
Inflation standard
deviation over 5-
years
-2.42 -1.43 -1.54 -2.10 -1.02 -1.07 -2.45 -6.06 -1.11 -0.53 -1.31 -2.27 -1.45 -
10.37
-
18.55 -0.84 -0.67 -1.02
Table 15 – Standardized Data
Standardized
data Indicator
Algeria
Bahrain
Egypt
Iraq
Jordan
Kuwait
Lebanon
Libya
Mauritania
Morocco
Oman
Qatar
Saudi Arabia
Sudan
Syrian
Tunisia
UAE
OECD Average
- Year 2014
Min
Max
Competitive
Environment
Market-based
competition
-0.75 1.57 -0.75 -0.75 -0.17 0.99 0.41 -0.17 -1.33 0.41 0.99 0.99 0.41 -1.33 -1.91 0.41 0.99 2.03 -2.49 2.73
Administered prices
-1.75 1.68 -0.61 0.54 0.54 -0.61 1.68 -0.61 -0.61 0.54 -0.61 -0.61 -0.61 0.54 -0.61 -0.61 1.68 -1.51 -1.75 1.68
Anti-monopoly
policy
-0.22 0.41 1.68 -0.86 1.04 0.41 0.41 -0.86 -1.49 -0.22 -0.86 1.68 -0.22 -0.86 -1.49 0.41 1.04 3.07 -2.12 3.58
Enabling
Environment
for Private
Sector
Contract enforcing
(DTF)
0.17 0.09 -1.14 -0.65 0.34 0.08 0.54 -0.05 0.99 1.24 -0.16 0.73 0.45 -1.66 -2.44 1.36 0.11 2.62 -7.61 7.10
Perception of
standard of living
for entrepreneurs
0.04 0.31 -0.92 0.31 -0.58 -0.03 0.45 0.04 0.04 0.24 0.31 1.13 1.41 -1.26 -2.84 0.24 1.13 2.71 -4.14 2.71
Likelihood of violent
demonstrations
0.29 -0.61 -1.52 -0.61 0.29 1.20 -0.61 -0.16 -0.61 0.29 0.29 2.11 1.20 -0.61 -1.52 -0.61 1.20 1.06 -1.52 2.11
Getting credit (DTF)
0.18 0.18 0.97 -1.38 -0.99 0.18 0.58 -1.77 -0.99 0.58 0.97 0.18 1.75 -0.99 -0.99 0.58 0.97 1.95 -2.56 3.71
Foreign trade risk
-0.60 0.73 -0.31 -0.53 0.14 0.87 0.14 -0.60 -0.45 -0.05 1.32 1.32 1.02 -1.93 -1.93 -0.31 1.17 0.98 -2.37 1.76
Red Tape &
Regulations
Dealing with
construction
permits (DTF)
0.03 0.81 -0.05 0.22 0.08 -0.12 -0.34 -2.42 0.44 0.56 0.53 0.79 0.68 -0.30 -2.42 0.38 1.13 0.45 -2.42 1.42
Starting a business
(DTF)
-0.64 -0.44 1.18 -0.55 0.87 -0.91 0.50 -0.47 -2.46 1.45 0.08 0.58 -0.03 -0.49 -0.70 0.63 1.41 1.06 -9.55 2.63
66
Trading across
borders (DTF)
-0.25 0.53 0.19 -2.81 0.61 0.00 0.26 -0.38 -0.71 0.83 0.61 0.54 0.36 -1.50 -0.52 0.84 1.40 1.02 -4.03 1.90
Efficiency of the tax
administration
0.32 1.18 -0.19 -2.26 -0.19 -1.23 -0.97 -1.23 0.32 0.32 0.50 0.15 1.54 -0.19 0.07 0.32 1.54 1.22 -2.26 1.88
Index of Regulatory
Quality 284b
-0.89 1.21 -0.38 -0.93 0.53 0.30 0.20 -1.96 -0.33 0.43 1.20 1.07 0.43 -1.08 -1.39 0.06 1.52 1.85 -2.30 3.19
Financial
Sector
Banking system
-1.00 1.62 0.31 -1.00 1.18 0.75 1.18 -1.00 -1.00 0.31 0.31 0.75 0.75 -1.44 -1.44 -0.57 0.31 1.23 -2.32 1.62
Financial freedom
-0.74 1.99 -0.19 -1.83 0.90 0.35 0.90 -1.28 -0.19 0.90 0.90 0.35 0.35 -0.74 -1.28 -0.74 0.35 1.46 -2.37 3.08
Reliability of
financial institutions
-0.65 1.20 -0.28 -1.40 -0.21 1.13 1.35 -0.73 0.68 0.31 0.76 1.05 -1.84 -1.10 -1.10 0.31 0.53 -5.57 -5.63 1.79
Banks' assets to
GDP
-0.64 0.68 0.00 -1.29 1.19 -0.08 2.61 -1.13 -0.80 0.76 -0.36 0.55 -0.42 -1.28 -0.47 0.28 0.42 1.13 -1.60 3.93
Private credit by
banks to GDP
-1.04 0.98 -0.64 -1.40 1.06 0.57 1.83 -1.14 -0.56 1.08 -0.03 -0.21 -0.16 -1.27 -0.84 1.06 0.71 1.93 -1.63 2.25
Frequency of bank
branches
-0.95 0.06 -0.98 -0.90 0.96 0.38 2.18 -0.12 -1.02 1.47 0.95 0.06 -0.46 -1.20 -1.11 0.71 -0.03 2.08 -1.59 2.65
Monetary
Policy
Independence of
Central Banks
-0.87 0.05 0.97 0.97 0.97 0.97 0.97 0.05 -0.87 0.97 0.05 -0.87 -0.87 -1.78 -1.78 0.97 0.05 1.67 -1.78 1.89
Anti-inflation/forex
policy
-0.23 0.65 -0.23 0.21 1.09 0.65 0.65 -1.12 -0.23 0.65 0.65 0.65 0.65 -2.00 -2.44 -0.23 0.65 1.27 -2.44 1.53
Monetary freedom
-0.67 0.75 -1.65 -0.37 1.14 0.05 0.23 -0.79 0.36 0.71 0.11 1.13 -0.55 -2.28 -0.17 0.42 1.58 0.86 -9.77 3.65
Inflation standard
deviation over 5-
years
0.18 0.39 0.37 0.25 0.48 0.47 0.17 -0.61 0.46 0.59 0.42 0.21 0.39 -1.54 -3.30 0.52 0.56 0.48 -4.05 0.70
Table 16 – Aggregated Data
Aggregated
Data Indicator
Algeria
Bahrain
Egypt
Iraq
Jordan
Kuwait
Lebanon
Libya
Mauritania
Morocco
Oman
Qatar
Saudi Arabia
Sudan
Syrian
Tunisia
UAE
OECD Average
- Year 2014
Min
Max
EJ Index
Competitive
Environment
-0.89 1.26 0.02 -0.40 0.41 0.34 0.79 -0.51 -1.16 0.26 -0.04 0.72 -0.08 -0.63 -1.39 0.11 1.21 1.28 -2.12 2.66
Enabling
Environment for
Private Sector
-0.07 0.27 -0.46 -0.56 -0.18 0.43 0.29 -0.55 -0.19 0.43 0.65 1.02 1.15 -1.42 -1.98 0.28 0.91 1.86 -3.64 3.48
Red Tape &
Regulations
-0.22 0.59 0.21 -1.45 0.39 -0.42 -0.07 -1.13 -0.59 0.76 0.53 0.57 0.59 -0.76 -0.91 0.52 1.39 1.04 -4.11 2.20
Financial Sector
-0.88 1.28 -0.20 -1.31 0.94 0.55 1.51 -0.98 -0.57 0.74 0.40 0.42 -0.01 -1.19 -1.12 0.02 0.40 0.81 -2.52 2.55
Monetary Policy
-0.32 0.47 -0.09 0.26 0.89 0.54 0.49 -0.66 -0.03 0.71 0.35 0.31 0.03 -1.87 -2.11 0.36 0.69 1.03 -4.51 1.94
EJ Score
-0.48 0.77 -0.11 -0.69 0.49 0.29 0.60 -0.77 -0.51 0.58 0.38 0.61 0.33 -1.17 -1.50 0.26 0.92 1.20 -3.38 2.57
67
Table 17 – Benchmarked Data and other indices
Benchmarked
Data
Algeria
Bahrain
Egypt
Iraq
Jordan
Kuwait
Lebanon
Libya
Mauritania
Morocco
Oman
Qatar
Saudi
Arabia
Sudan
Syrian
Tunisia
UAE
OECD
Average
EJ % (0-100)
49% 70% 55% 45% 65% 62% 67% 44% 48% 67% 63% 67% 62% 37% 32% 61% 72% 77%
HDI (0-1)
0.74 0.82 0.69 0.65 0.75 0.82 0.77 0.72 0.51 0.63 0.80 0.85 0.84 0.48 0.59 0.72 0.84 0.89
GCI (1-7)
3.79 4.45 3.63 0.00 4.20 4.56 3.77 3.73 3.19 4.11 5.64 5.24 5.10 0.00 3.85 4.06 5.11 4.91
IEF (0-100)
50.80 75.10 52.90 0.00 69.20 62.30 59.40 35.90 53.20 58.30 67.40 71.20 62.20 48.78 0.00 57.30 71.40 71.27
GII(0-1)
0.43 0.23 0.57 0.53 0.48 0.33 0.38 0.17 0.63 0.49 0.28 0.54 0.26 0.57 0.55 0.29 0.23 0.13
WGI (-2.5;+2.5)
Control for
Corruption
-0.62 0.30 -0.59 -1.34 0.15 -0.26 -1.06 -1.61 -0.92 -0.26 0.31 1.09 0.10 -1.45 -1.55 -0.09 1.23 1.22
Regulatory
Quality
-1.28 0.70 -0.74 -1.25 0.08 -0.13 -0.22 -2.11 -0.78 -0.12 0.69 0.57 -1.46 -1.67 -0.39 0.98 -0.01 1.28
Government
Effectiveness
-0.48 0.59 -0.84 -1.13 0.13 -0.15 -0.38 -1.71 -0.99 -0.07 0.27 0.99 -1.56 -1.44 -0.12 1.48 0.23 1.30
Rule of Law
-0.73 0.45 -0.60 -1.36 0.48 0.05 -0.76 -1.53 -0.82 -0.05 0.49 0.99 -1.14 -1.34 -0.13 0.71 0.27 1.36
Political Stability
and Absence of
Violence
-1.17 -0.93 -1.61 -2.49 -0.55 0.13 -1.69 -2.35 -0.61 -0.43 0.73 0.98 -2.38 -2.76 -0.85 0.76 -0.28 0.69
Voice and
Accountability
-0.82 -1.32 -1.14 -1.22 -0.77 -0.65 -0.46 -1.13 -0.92 -0.74 -1.09 -0.99 -1.75 -1.80 0.16 -1.06 -1.80 1.12
% Youth
Unemployment
25.69 5.08 38.62 32.89 30.50 16.07 20.11 47.23 16.06 19.92 45.29 0.73 30.88 21.49 32.99 37.04 11.82 15.99
Income Level
Upper
middle High
Lower
middle
Upper
middle
Upper
middle High
Upper
middle
Upper
middle
Lower
middle
Lower
middle High High High
Lower
middle
Lower
middle
Lower
middle High
