Introduction1
The state has historically been a significant economic actor in the MENA region.2 In the decades following Arab independence, many MENA countries adopted development models based on state capitalism whereby the government spearheaded economic production, investment, and resource allocation. As part of these models, state-owned enterprises (SOEs) were used to support mandates beyond the solely commercial, including to promote industrial and social policies, manage nationalized assets, and create employment (OECD 2012; OECD 2013). Many SOEs in oil-importing countries, such as Jordan, Morocco, and Tunisia, have roots in enterprises inherited from colonial regimes or formed under strategic policies adopted immediately after independence (Amico 2017). Across the MENA region, new SOEs were, and continue to be, established to develop new sectors; for example, between 2001 and 2010, 350 SOEs were established in Morocco alone (OECD 2012). While the number of SOEs varies— ranging from over 300 in Algeria and Egypt to about 20 in Lebanon and Saudi Arabia, among countries with available data— they are key economic actors throughout the region.
The MENA region is at an important crossroad as the state-led growth strategy has begun to reach its limits. In the coming decade, over 100 million people will enter the MENA workforce. Meaningful jobs are vital for their inclusion in economic activities, ensuring their livelihoods, and preserving the social fabric. Strong state involvement may have been a mechanism for nation building in the MENA region in the past, but stagnating growth, high unemployment, and increased inequality in the region point to the need for a different strategy. The average annual total factor productivity growth during the last 10 years has been negative for many countries in the MENA region, and particularly low for oil producers (Figure 3.1). This is a cause for concern as prolonged periods of productivity decline are an eventual drag on economic growth (Eichengreen, Park, and Shin 2012). Yet despite the high levels of public consumption, investment, and employment, the availability and quality of public services have not kept up with the demands of the population. High public debt levels and eroded fiscal space—both exacerbated after the COVID-19 crisis— leave increasingly limited room for the state to continue to subsidize economic activities while also tackling the mounting social and development needs of the rapidly growing population.


Total Factor Productivity Growth in the MENA Region
Source: Penn World Table 9.1.Note: Total factor productivity is a measure of productive efficiency, that is, how much output can be produced with a given amount of inputs. EMDE = emerging market and developing economies; MENA = Middle East and North Africa.
Total Factor Productivity Growth in the MENA Region
Source: Penn World Table 9.1.Note: Total factor productivity is a measure of productive efficiency, that is, how much output can be produced with a given amount of inputs. EMDE = emerging market and developing economies; MENA = Middle East and North Africa.Total Factor Productivity Growth in the MENA Region
Source: Penn World Table 9.1.Note: Total factor productivity is a measure of productive efficiency, that is, how much output can be produced with a given amount of inputs. EMDE = emerging market and developing economies; MENA = Middle East and North Africa.Higher and more inclusive growth going forward requires a transition to private-sector-led activities. The low total factor productivity growth could in part reflect the inefficiencies and resource misallocation associated with the relatively large role of the state in the region. Although certain roles of the state, such as the development of legal and administrative institutions, or interventions to correct market failures (including building essential infrastructures) can have positive effects on productivity growth (Ghali 1998), various studies have shown that an excessively large government sector can generate inefficiencies and policy-induced distortions with a negative impact on overall productivity growth (see, for example, Barro 1991; Dar and AmirKhalkhali 2002; Loko and Diouf 2009). Several studies find that SOEs tend to underperform private sector firms, and are generally characterized by lower revenue, higher costs per employee, and weaker productivity.3 These gaps, in part, reflect the different nature of SOEs, many of which pursue public mandates rather than profit-maximizing goals. However, the lower productivity of public enterprises inevitably lowers the overall productivity of the economy— including indirectly by limiting private sector competition and dynamism— particularly when the public sector is large, as in the MENA region. Ensuring a more inclusive role for the private sector will be key for generating employment opportunities, particularly given over 90 percent of jobs in developing countries are created in the private sector (International Finance Corporation 2013).
This chapter makes the case for a new role for the state focused on addressing hurdles to private sector development in the MENA region, particularly those arising from the large state presence. Making way for the private sector to spur growth and job creation will not be without challenges. The entrenched state presence across economic sectors has given rise to various distortions that have limited the development of the private sector, requiring a comprehensive structural reform toward private-sector-led growth. This chapter will first look at stylized facts on the size of the state in the MENA region compared to other world regions. It then reviews the various distortions and barriers associated with long-term state interventions in economic activities in the region. It then empirically assesses the impact of SOEs on private sector development in the MENA region using firm-level panel data from Orbis over the period 2006–18 and concludes with some policy implications.
How Big is the State’s Footprint in the Mena Region?
The large state footprint in the MENA region is apparent in the region’s high levels of public consumption and investment. At close to 24 percent, the share of public consumption in the MENA region is larger than in any other region (except the Caucasus and Central Asia [CCA], which carries the Soviet legacy of centralized economies) and has shown limited signs of declining over the past two decades (Figure 3.2). Public investment accounts for one third of total investment in the MENA region, again behind the CCA but roughly in line with average levels in Africa and the Western Hemisphere countries.4 High public consumption and investment are fueled by a significant share of credit flowing to the public sector: about one third of domestic credit goes to the public sector in the MENA region compared to less than 25 percent in Europe and less than 20 percent in the CCA, the Western Hemisphere, and the Asia and Pacific regions (Figure 3.2).


The Size of the Public Sector across World Regions
Sources: International Financial Statistics; World Economic Outlook; and National Accounts.Note: Comparator countries are emerging market and developing economies. AFR = Africa; APD = Asia and the Pacific; CCA = Central Asia and the Caucasus; EUR = Europe; MENA = Middle East and North Africa; WHD = Western Hemisphere (North, South, and Central America). Public credit as reported in International Financial Statistics; the total share of public credit may be underestimated if some credit to state-owned enterprises is classified as credit to the private sector.
The Size of the Public Sector across World Regions
Sources: International Financial Statistics; World Economic Outlook; and National Accounts.Note: Comparator countries are emerging market and developing economies. AFR = Africa; APD = Asia and the Pacific; CCA = Central Asia and the Caucasus; EUR = Europe; MENA = Middle East and North Africa; WHD = Western Hemisphere (North, South, and Central America). Public credit as reported in International Financial Statistics; the total share of public credit may be underestimated if some credit to state-owned enterprises is classified as credit to the private sector.The Size of the Public Sector across World Regions
Sources: International Financial Statistics; World Economic Outlook; and National Accounts.Note: Comparator countries are emerging market and developing economies. AFR = Africa; APD = Asia and the Pacific; CCA = Central Asia and the Caucasus; EUR = Europe; MENA = Middle East and North Africa; WHD = Western Hemisphere (North, South, and Central America). Public credit as reported in International Financial Statistics; the total share of public credit may be underestimated if some credit to state-owned enterprises is classified as credit to the private sector.Many countries in the MENA region also have high levels of public employment, usually coupled with relatively high compensation, leading to a high public wage bill. The public sector accounts for 19 percent of employment in the MENA region— a larger share than in sub-Saharan Africa, the Asia and Pacific, or the Western Hemisphere regions.
The public sector wage bill is about 10 percent of GDP, higher than in all regions except Europe, and showing no signs of declining in recent decades. Governments in the region are often perceived as “employers of first resort,” with public sector jobs often used as a mechanism to redistribute wealth or to provide social support. In the wake of the Arab Spring, real wage bills across the MENA region grew more rapidly as various governments increased public employment and compensation as a way to mitigate social discontent (Tamirisa and Duenwald 2018).
The size and scope of SOEs in the MENA region further attest to the large footprint of the state in the economy. The SOE footprint in the MENA region is, on average, larger than in Organisation for Economic Co-operation and Development (OECD) countries, albeit with significant heterogeneity among countries (Figure 3.3). Globally, SOEs are often established in sectors with high natural barriers to entry or high capital intensity (for example, mining, transport, communication), and in sectors where the social rate of return is higher than the private one (for example, health, education). Yet in addition to these “traditional” sectors, SOEs in the MENA region are also active in sectors usually occupied by private firms, including manufacturing and financial services (IMF 2021). In addition to the broad scope, the footprint of SOEs is also deep: MENA governments often hold shares in the largest companies in key economic sectors, such as mining and hydrocarbon, heavy industry (for example, cement production, steel refining), and telecommunications. SOE assets can be substantial, totaling more than the GDP in Morocco and over 50 percent of GDP in Egypt (IMF 2021; OECD 2013).


SOE Footprint in the MENA Region
Source: IMF (2021), based on survey of national country authorities.Note: In panel 1, blue bars show data from surveys of national country authorities and yellow bars show data from alternative data sources as indicated in IMF (2021); Saudi Arabia reporting is limited to the portfolio of entities under the remit of the reporting institution and therefore cannot be considered wholly representative of the national SOE portfolio; and the number of SOEs in Algeria is representative of SOEs with 90 percent to 100 percent government ownership. OECD = Organisation for Economic Co-operation and Development; MENA = Middle East and North Africa; SOEs = state-owned enterprises. The figure uses International Organization for Standardization (ISO) country codes.
SOE Footprint in the MENA Region
Source: IMF (2021), based on survey of national country authorities.Note: In panel 1, blue bars show data from surveys of national country authorities and yellow bars show data from alternative data sources as indicated in IMF (2021); Saudi Arabia reporting is limited to the portfolio of entities under the remit of the reporting institution and therefore cannot be considered wholly representative of the national SOE portfolio; and the number of SOEs in Algeria is representative of SOEs with 90 percent to 100 percent government ownership. OECD = Organisation for Economic Co-operation and Development; MENA = Middle East and North Africa; SOEs = state-owned enterprises. The figure uses International Organization for Standardization (ISO) country codes.SOE Footprint in the MENA Region
Source: IMF (2021), based on survey of national country authorities.Note: In panel 1, blue bars show data from surveys of national country authorities and yellow bars show data from alternative data sources as indicated in IMF (2021); Saudi Arabia reporting is limited to the portfolio of entities under the remit of the reporting institution and therefore cannot be considered wholly representative of the national SOE portfolio; and the number of SOEs in Algeria is representative of SOEs with 90 percent to 100 percent government ownership. OECD = Organisation for Economic Co-operation and Development; MENA = Middle East and North Africa; SOEs = state-owned enterprises. The figure uses International Organization for Standardization (ISO) country codes.Distortions Associated With Long-Term State Interventions
In many MENA countries, SOEs suffer from low profitability and must balance commercial and noncommercial mandates. There is no regular comprehensive reporting on the financial performance of SOEs; while Figure 3.3, panel 3 suggests the overall SOE sector is profitable in some countries, many individual SOEs are in a weak financial position: IMF (2021) finds that almost 40 percent of SOEs in the MENA region incurred losses in 2019, including 30 percent of SOEs in Egypt and Morocco, over 50 percent of those in Afghanistan, and over two-thirds of the largest SOEs in Tunisia IMF (2021). SOE losses can be sizable, ranging between 0.6 and 6 percent of GDP per year in Egypt, Iraq, Morocco, and Tunisia (World Bank 2015a). Often, poor SOE performance is a direct result of lack of autonomy to establish clear commercial mandates. The OECD (2013), for example, finds that in air transport and heavy industry, SOE profitability in the MENA region appears to depend on the extent of operational autonomy and the existence of a clear commercial mandate.
Several forms of direct and indirect support allow SOEs to survive even when operating at a loss. SOEs often benefit from direct fiscal support in the form of budget transfers or on-lending; this support is sizable, amounting to 2 percent of GDP in the region (Figure 3.4). SOEs also benefit from other privileges, such as exclusive rights to operate as monopolies; better or subsidized access to land; or the ability to circumvent bureaucratic red tape. For many countries (for example, Algeria, Iraq, Jordan, Kuwait, Libya, Qatar, Syria, Saudi Arabia, Tunisia, and Yemen), SOEs are de jure subject to the same tax system as private companies but de facto benefit from various exemptions from corporate income taxes. In Lebanon and Libya, SOEs are not subject to income tax law, while oil-producing countries often allow tax privileges for SOEs in the oil sector (World Bank 2019). Such advantages enable many SOEs to provide lower-priced products, making it difficult for private companies to compete, even if the latter are more efficient.


Fiscal Support and Administrative and Credit Advantages for SOEs
Sources: IMF (2021); and WB Enterprise Surveys.Note: AFR = Africa; APD = Asia and the Pacific; CCA = Central Asia and the Caucasus; EUR = Europe; MENA = Middle East and North Africa; SOE = state-owned enterprises; WHD = Western Hemisphere (North, South, and Central America). The figure uses International Organization for Standardization (ISO) country codes.
Fiscal Support and Administrative and Credit Advantages for SOEs
Sources: IMF (2021); and WB Enterprise Surveys.Note: AFR = Africa; APD = Asia and the Pacific; CCA = Central Asia and the Caucasus; EUR = Europe; MENA = Middle East and North Africa; SOE = state-owned enterprises; WHD = Western Hemisphere (North, South, and Central America). The figure uses International Organization for Standardization (ISO) country codes.Fiscal Support and Administrative and Credit Advantages for SOEs
Sources: IMF (2021); and WB Enterprise Surveys.Note: AFR = Africa; APD = Asia and the Pacific; CCA = Central Asia and the Caucasus; EUR = Europe; MENA = Middle East and North Africa; SOE = state-owned enterprises; WHD = Western Hemisphere (North, South, and Central America). The figure uses International Organization for Standardization (ISO) country codes.SOEs in the MENA region also benefit from easier access to credit. On average, SOEs have been found to face lower debt-financing costs than their private sector counterparts (IMF 2020). Moreover, MENA firms with partial state ownership appear to have more ample access to credit, reporting a higher share of bank financing than private sector firms (Figure 3.4). Government guarantees to SOEs can lower borrowing costs relative to similar private sector firms by reducing credit risks. In the MENA region, this practice is widespread, with the stock of public credit guarantees ranging between 2 to 55 percent of GDP IMF (2021). SOEs also benefit from implicit guarantees, given government propensity to bail out failing public enterprises. Moreover, state-owned banks (SOBs) serve as a reliable source of financing for SOEs, due to strategic rather than commercial considerations (OECD 2012). The use of SOBs to finance SOEs at nonmarket terms has at times led to high levels of nonperforming loans (as previously seen in Algeria and Egypt), which, in turn, further restrict the ability of these banks to lend to the private sector (OECD 2013). IMF (2019) illustrates risks from the SOE– SOB nexus, whereby SOB lending to SOEs without rigorous oversight can have fiscal and financial stability implications. Cheaper and more ample credit for SOEs due to the aforementioned advantages implies a lower marginal product of capital vis-à-vis private firms, which points to capital misallocation (Hsieh and Klenow 2009, and Chapter 2 in this book).
The large public sector employment in the MENA region distorts labor markets and hampers the private sector’s job creation potential. Previous research suggests the public-private wage gap is quite high in the MENA region; for example, public wages in Gulf Cooperation Council (GCC) countries are, on average, two to three times higher than private sector wages, even prior to accounting for substantial nonwage benefits such as pensions and job security (Purfeld and others 2018; Tamirisa and Duenwald 2018). A public sector wage premium not justified by differences in skill levels or job characteristics distorts labor allocation by making it difficult for productive private firms to attract productive workers. Moreover, more generous wages and nonwage benefits in public employment can lead job seekers to wait for a public sector job rather than accept a private sector one. Referred to as “queuing,” this phenomenon partly explains high and often long-term unemployment among young and highly educated workers in the region (Purfeld and others 2018). Large wage gaps also lead to skill mismatches, with the education system in the MENA region primarily targeted toward preparation for government employment rather than private sector jobs (World Bank 2018; Purfeld and others 2018). These factors likely contribute to the smaller share of private firms’ employment creation in the MENA region compared to other regions.
The dominance of the state in economic activities may distort market neutrality, alter the perception of risk-return tradeoffs, and ultimately stifle competition and private sector development. Previous studies find that private sector firms in the MENA region are generally smaller, fewer in number, and older than in other regions, suggesting they face barriers to entry and growth; for example, the share of firms with fewer than ten workers is much higher than in other emerging markets (EMs), and small firms account for over 40 percent of firms in Jordan, Yemen, and the West Bank (Purfeld and others 2018). Studies also find evidence of low business dynamism: MENA countries outside the GCC have fewer newly registered firms per working age population than any other world region, while evidence of a low correlation between entry and exit within sectors implies that firm turnover in the region is not driven by creative destruction (Purfeld and others 2018; World Bank 2015b). Moreover, Arezki, Belhaj, and Mohieldin (2019) argue that the large role of the state in the region shields private citizens from risk-taking, ultimately stifing entrepreneurship and innovation. This argument appears to be supported by data on patent applications— a proxy for innovation rates (Figure 3.5).


Patent Applications
(Per million people)
Source: World Intellectual Property Organization; and IMF staff calculations.Note: EMs = emerging markets; UAE = United Arab Emirates.
Patent Applications
(Per million people)
Source: World Intellectual Property Organization; and IMF staff calculations.Note: EMs = emerging markets; UAE = United Arab Emirates.Patent Applications
(Per million people)
Source: World Intellectual Property Organization; and IMF staff calculations.Note: EMs = emerging markets; UAE = United Arab Emirates.The MENA region sees significantly lower patent application rates than other EMs, albeit with some notable exceptions in Iran and GCC countries (see Box 3.1). Finally, fiscal support to SOEs and high public wages divert resources away from public investments that would enhance private sector productivity and stimulate a more inclusive and dynamic growth.
The Impact of Soes on Private Sector Firms in the Mena Region: An Empirical Analysis
This section uses firm-level data to explore how SOEs differ from private sector firms, and how the presence of SOEs affects market dynamics. We use firm-level balance sheet data from Bureau van Dijk’s Orbis database, one of the few harmonized, cross-country, firm-level datasets that include both SOEs and privately owned firms (both listed and non-listed). The dataset used covers eight MENA countries (Morocco, Algeria, Egypt, Saudi Arabia, Oman, Iran, Kuwait, and Jordan) and 66 countries in other world regions, over the period 2006–18. SOEs are identified based on the reported firm owner (frms owned by “Public authority, state, government”). Only firm-year observations where data on assets, liabilities, revenues, and costs are available are included. (More details about the data are in Annex 3.2.)
A New Generation of SOEs in the GCC
In recent years, Gulf Cooperation Council (GCC) countries have adopted an economic strategy that includes using state-owned enterprises (SOEs) to expand to new high-tech sectors, including aviation, semiconductors, and green energy. Sometimes referred to as “third generation SOEs,” these SOEs are often funded through Sovereign Wealth Funds (OECD 2013). Examples include Mubadala Holding Company in the United Arab Emirates, which owns a variety of assets and invests in aerospace, renewable energy, and semiconductors; Saudi Aramco, which provides direct support to small and medium enterprises and conducts research in a variety of areas; and state-owned entities created to invest in solar energy and real estate in Qatar (OECD 2013).
In these cases, state involvement is intended to initiate economic development in high-productivity and high-externality sectors, thus continuing historic growth strategies of the state as a first mover to overcome market failures, resulting in hurdles for private sector expansion. These hurdles include limited incentives for diversification given the economic dominance of the oil sector, the high costs of credit for private start-ups, and the hesitancy of domestic lenders to provide credit in new sectors given inexperience in pricing risks (OECD 2013; Vorisek and others 2021).
There is some evidence that diversification efforts have begun to bear fruit. Patent grants in the GCC increased tenfold between 2009 and 2019, much more rapidly than in any other world region. Patent applications were largely driven by SOEs and public investment; for example, in 2020, Saudi Aramco alone accounted for nearly half of international patent applications from Saudi Arabia. Trends in patent publications show expansion of GCC economies into varied fields: IT, electronics, and telecommunication account for the majority of patent publications in Qatar today, while biology and pharmaceuticals and civil engineering account for a significant share in the United Arab Emirates and Saudi Arabia, respectively. These developments have also started to affect labor composition: Saudi Arabia has seen the largest increase among Group of Twenty countries in university and secondary school graduates in the job market in the last five years (World Economic Forum 2020). However, it remains to be seen whether these patents are successfully commercialized, and whether such diversification efforts will also create space for and draw in private sector entrepreneurship.


Patent Publications by Sector
Source: World Intellectual Property Organization.Note: UAE = United Arab Emirates.
Patent Publications by Sector
Source: World Intellectual Property Organization.Note: UAE = United Arab Emirates.Patent Publications by Sector
Source: World Intellectual Property Organization.Note: UAE = United Arab Emirates.

Saudi Arabia Patent Publications
Source: World Intellectual Property Organization.
Saudi Arabia Patent Publications
Source: World Intellectual Property Organization.Saudi Arabia Patent Publications
Source: World Intellectual Property Organization.Data availability and representativeness vary across countries. SOE presence, measured through their shares of sectors’ assets, varies across time and across sectors both within and outside the MENA region. SOE presence in the MENA region is, on average, larger than in other world regions, especially in the mining, information and communication, and transport sectors (Figure 3.6). Within the MENA region, the dataset is strongly representative of the universe of both private firms and SOEs for Morocco and Algeria. After substantive data cleaning, we used this data to find a few stylized facts on the productivity and profitability of SOEs in the MENA region, and to run a series of panel regressions linking these characteristics to firm-specific factors (such as age and size) and sector-specific factors (like sectoral investment, concentration, and entry rates). Empirical results are shown in Annex 3.3.


Sectoral Asset Shares of SOEs, the MENA Region and the Rest of the World, 2006–18
Source: Orbis.Note: Ag = agriculture; Cnst = construction; FinS = other financial services; ICT = information and communications technology; MCh = chemicals manufacturing; MENA = Middle East and North Africa; Min = mining; MMt = other materials manufacturing; MonI = monetary intermediation; MOt = other manufacturing; OSv = other services; Res = real estate; SOE= state-owned enterprise; Trd = trade and repair; Tsp = transportation and storage; Utl = uitlities and sanitary. “Whole” refers to all sectors.
Sectoral Asset Shares of SOEs, the MENA Region and the Rest of the World, 2006–18
Source: Orbis.Note: Ag = agriculture; Cnst = construction; FinS = other financial services; ICT = information and communications technology; MCh = chemicals manufacturing; MENA = Middle East and North Africa; Min = mining; MMt = other materials manufacturing; MonI = monetary intermediation; MOt = other manufacturing; OSv = other services; Res = real estate; SOE= state-owned enterprise; Trd = trade and repair; Tsp = transportation and storage; Utl = uitlities and sanitary. “Whole” refers to all sectors.Sectoral Asset Shares of SOEs, the MENA Region and the Rest of the World, 2006–18
Source: Orbis.Note: Ag = agriculture; Cnst = construction; FinS = other financial services; ICT = information and communications technology; MCh = chemicals manufacturing; MENA = Middle East and North Africa; Min = mining; MMt = other materials manufacturing; MonI = monetary intermediation; MOt = other manufacturing; OSv = other services; Res = real estate; SOE= state-owned enterprise; Trd = trade and repair; Tsp = transportation and storage; Utl = uitlities and sanitary. “Whole” refers to all sectors.Our analysis reveals that SOEs in the MENA region differ from private sector firms in several key dimensions:
Compared to private firms, SOEs in the MENA region (but also in other world regions) have larger sales and assets upon establishment; however, they see lower growth rates over time (Figure 3.7).
SOEs in the MENA region are less profitable than private sector firms (they have a lower average Returns on Equity even when controlling for firm-and sector-specific characteristics; see Annex Table 3.3.1). However, the profitability gap is smaller in the MENA region compared to the rest of the world (7.5 percentage points compared to 15.6 percentage points).
The smaller profitability gap for MENA SOEs may reflect their privileged access to factors of production. Indeed, contrary to the rest of the world, SOEs in the MENA region have lower imputed interest rates than private sector firms (by about 1–2 percentage points; see Annex Table 3.3.3).5 On the other hand, we could not find evidence that SOEs report paying lower imputed tax rates compared to private sector firms.
MENA SOEs are on average less productive than private sector firms, with lower returns on capital (Annex Table 3.3.2), a pattern that stands in contrast to the rest of the world.6


Sales over Time of SOEs and Private Firms
Source: Orbis.Note: SOE = state-owned enterprise.
Sales over Time of SOEs and Private Firms
Source: Orbis.Note: SOE = state-owned enterprise.Sales over Time of SOEs and Private Firms
Source: Orbis.Note: SOE = state-owned enterprise.Moreover, we found that the presence of SOEs has a negative impact on competition and business dynamism. Output market concentration, measured by the Herfndahl-Hirschman Index (HHI), is higher in sectors with larger SOE presence. This effect is stronger in the MENA region: for each 1 percentage point increase in the SOE asset share in a sector, the HHI increases by 0.26 in the MENA region compared to only 0.1 in other regions (Annex Table 3.3.4). Moreover, business dynamism, measured through entry and exit rates, is lower in sectors with higher SOE asset share, even when controlling for concentration: 1 percentage point of additional SOE asset share in a sector is associated with a 0.2 percentage point decrease in entry rates and a 0.1 percentage point decrease in exit rates (Annex Table 3.3.6). Given the larger market presence of SOEs in the MENA region, the impact on competition is especially large.
Finally, a higher SOE presence is also associated with lower private investment and lower competition in input markets. We find that a larger SOE presence in a specific sector is associated with lower investment by private firms in the same sector in the MENA region by about $600 a year, controlling for firm-specific factors. The presence of SOEs also leads to increased concentration in input markets in the MENA region (but not in the rest of the world): for every percentage point higher SOE asset share in a country, the HHI for capital inputs in that country is 0.8 point higher, and the HHI for labor inputs is higher by 0.5. The positive relationship between SOE presence and concentration in input markets suggests that the large size of the SOE sector limits competition for capital and labor, which can lead to some of the distortions in resource allocation documented previously.
These empirical findings attest to the distortive effect of state involvement in the economy in the MENA region on competition in output and input markets and on business dynamism. While some of these distortions are also observed outside the MENA region, the larger market share of SOEs in the MENA region— associated with the region’s state-led growth model— translates to a more substantial effect on private sector exclusion.
How the State can Foster Private-sector-Led Growth
Our results point to a need for a broad reform of SOEs within a more general reassessment of the role of the state in MENA economies. Fostering a private-sector-led growth model does not mean that the state will not have an important role to play. Rather, it calls for a change in roles, from that of an active player in the economy to that of enabler of private sector development. This would first require the development of a state ownership policy to articulate (1) the rationale for the state’s involvement in the various economic sectors, (2) the objectives and activities of the SOEs, and (3) their governance structure. The state ownership policy could then underpin a strategy for privatizing SOEs where there is no clear rationale for state involvement. The ownership reform should be accompanied by a modernization of the legal, accounting, and operational frameworks of SOEs with a view to increase transparency and limit fiscal contingent liability risks. SOEs’ financial reports should be published on a regular basis, and their financial performances benchmarked against the same standards as the private sector. Currently, no MENA country requires the separation of commercial and noncommercial activities of SOEs (World Bank 2019); however, best practice would call for operations that fulfill social policy mandates to be clearly separated from SOEs’ commercial activities, with the costs of the former explicitly recognized on the government’s budget for transparency.
Fostering private sector development would require reforming competition policies. Ensuring a level playing field or “competitive neutrality” for all market players is key for private sector growth. As a first step, as recommended in IMF (2021), regular or exceptional government support to SOEs should be governed by clearly circumscribed conditions in order to limit distortionary subsidies. Doing so will not only incentivize better performances by SOEs but also encourage greater participation by the private sector. It is also important to subject SOEs to the same laws, regulations, and tax provisions that apply to their private sector counterparts, (including on public procurement). Reforms to support competitive and regulatory neutrality should include establishing regulatory agencies that have the necessary autonomy, resources, and authority to enforce law and regulations (Aghion, Cherif, and Hasanov 2021). While SOEs will naturally have some advantages over private firms, such as more favorable debt financing costs, ensuring that they operate within the same regulatory environment as their private sector counterparts will greatly reduce distortions and allow for more inclusive growth based on stronger contributions of private entrepreneurs to the economy.
Improving the business environment is also an important step for private sector growth. In addition to the uneven playing field, the MENA region’s private sector contends with several other hurdles to doing business. Removing such hurdles would require:
Improving infrastructure. Despite progress made in the last few decades, many countries in the region still face poor transport infrastructure (roads, ports, and airports) and uneven access to broadband connectivity. Investments in infrastructure have both immediate and long-term payoffs in supporting a more inclusive growth; the World Bank estimates that $1 billion of infrastructure investment in the MENA region could increase growth by 0.5 percentage point and create over 130,000 jobs in the short term, and some additional 400,000 jobs over the long term due to crowding-in effects on business activities.7 The transition toward greener and more sustainable development models could offer many economies in the MENA region an opportunity to revamp their infrastructure investment agenda (see Chapter 8 of this book).
Improving SMEs’ access to finance. Higher collateral requirements, limited banking competition, and relatively shallow capital markets in the MENA region make access to credit more challenging than in other regions (OECD 2019). These challenges are particularly detrimental for SMEs: while it is estimated that SMEs in the MENA region represent about 96 percent of registered companies and about half of the employment, they account for only 7 percent of total bank lending— the lowest proportion in the world (EBRD 2016; Purfeld and others 2018). Chapters 2 and 6 of this book and IMF (2019) show that SMEs’ financial inclusion can lead to economic growth, job creation, and greater effectiveness of fiscal and monetary policy. IMF (2019) estimates that closing the region’s financial inclusion gap with EMs’ average could boost annual growth rates by up to 1 percentage point over the medium term, potentially adding about 16 million new jobs by 2025. Improving access to finance for SMEs would require improving the legal and regulatory frameworks, including on collateral registration and insolvency and creditors’ rights, and fostering the development of digital banking and e-payment systems.
Reducing red tape and scope for corruption. As discussed in Chapter 2, cumbersome regulation and the low quality of governance are serious barriers to entry and could well result in resource reallocation from low to high productivity firms. Firms in the region report tax policy and administration to be particularly cumbersome (World Bank Enterprise Survey database; EBRD 2016). Moreover, over half of private (and public sector) firms in the MENA region report corruption as a major constraint in the latest Enterprise Surveys, well above levels reported in other regions (Figure 3.8). Corruption also favors publicly owned firms: a third of private firms in the MENA region report being expected to give bribes to secure government contracts (compared to less than 10 percent of SOEs); and one in five private firms (vs. one in nine SOEs) are expected to give gifts to public officials for regular activities. Streamlining regulations and administrative procedures (for example, customs, tax, business registration, permits), including via digitalization, would be a crucial step in reducing the scope for rent-seeking behaviors and the cost of doing business in the region.


Share of Firms Reporting Facing Corruption
Source: WB Enterprise Surveys.Note: AFR = Africa; APD = Asia and the Pacific; EUR = Europe; MENA = Middle East and North Africa; WHD = Western Hemisphere (North, South, and Central America).
Share of Firms Reporting Facing Corruption
Source: WB Enterprise Surveys.Note: AFR = Africa; APD = Asia and the Pacific; EUR = Europe; MENA = Middle East and North Africa; WHD = Western Hemisphere (North, South, and Central America).Share of Firms Reporting Facing Corruption
Source: WB Enterprise Surveys.Note: AFR = Africa; APD = Asia and the Pacific; EUR = Europe; MENA = Middle East and North Africa; WHD = Western Hemisphere (North, South, and Central America).Conclusions
Fostering private sector development in the MENA region will require the state to pivot toward facilitating rather than leading business activities in the region. The absence of a robust private sector that can generate vast employment opportunities and maintain social cohesion has been used as a justification for the large state’s role in economic activities in the MENA region. But this development model has perpetuated a cycle where the private sector and its employment capacity in the economy are held back due to the state’s large footprint. Gradually rolling back the state’s role and focusing resources on facilitating private sector growth can lead to greater efficiency, higher productivity, and hence the economy’s ability to sustain higher growth. Doing so will also free up fiscal space for pursuing policies that would promote inclusion and ultimately ensure social cohesion.
Annex 3.1. Country Groups
Africa (AFR)

Africa (AFR)
| Angola Benin Botswana Burkina Faso Burundi Cabo Verde Cameroon Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Cote d’Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone South Africa |
South Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe Asia and the Pacific (APD) Bangladesh Bhutan Brunei Darussalam Cambodia China Fiji India Indonesia Kiribati Lao PDR Malaysia Maldives Marshall Islands Micronesia Mongolia Myanmar Nauru Nepal Palau Papua New Guinea Philippines Samoa Solomon Islands Sri Lanka Thailand Timor-Leste Tonga Tuv alu Vanuatu Vietnam |
Central Asia and the Caucasus (CCA) Armenia Azerbaijan Georgia Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan Europe (EUR) Albania Belarus Bosnia and Herzegovina Bulgaria Croatia Kosovo Macedonia, FYR Moldova Montenegro Poland Romania Russian Federation Serbia Turkey Ukraine Gulf Cooperation Council (GCC) Bahrain Kuwait Oman Qatar Saudi Arabia United Arab Emirates Middle East and North Africa (MENA) Afghanistan Algeria Bahrain |
Djibouti Egypt Iran Iraq Jordan Kuwait Lebanon Libya Mauritania Morocco Oman Qatar Saudi Arabia Somalia Sudan Syria Tunisia United Arab Emirates Yemen Western Hemisphere (WHD) Antigua & Barbuda Argentina Bahamas, The Barbados Belize Bolivia Brazil Chile Colombia Costa Rica Dominica Dominican Republic Ecuador El Salvador Grenada |
Guatemala Guyana Haiti Honduras Jamaica Mexico Nicaragua Panama Paraguay Peru St. Kitts & Nevis St. Lucia St. Vincent & the Grenadines Suriname Trinidad & Tobago Uruguay Venezuela |
Africa (AFR)
| Angola Benin Botswana Burkina Faso Burundi Cabo Verde Cameroon Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Cote d’Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone South Africa |
South Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe Asia and the Pacific (APD) Bangladesh Bhutan Brunei Darussalam Cambodia China Fiji India Indonesia Kiribati Lao PDR Malaysia Maldives Marshall Islands Micronesia Mongolia Myanmar Nauru Nepal Palau Papua New Guinea Philippines Samoa Solomon Islands Sri Lanka Thailand Timor-Leste Tonga Tuv alu Vanuatu Vietnam |
Central Asia and the Caucasus (CCA) Armenia Azerbaijan Georgia Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan Europe (EUR) Albania Belarus Bosnia and Herzegovina Bulgaria Croatia Kosovo Macedonia, FYR Moldova Montenegro Poland Romania Russian Federation Serbia Turkey Ukraine Gulf Cooperation Council (GCC) Bahrain Kuwait Oman Qatar Saudi Arabia United Arab Emirates Middle East and North Africa (MENA) Afghanistan Algeria Bahrain |
Djibouti Egypt Iran Iraq Jordan Kuwait Lebanon Libya Mauritania Morocco Oman Qatar Saudi Arabia Somalia Sudan Syria Tunisia United Arab Emirates Yemen Western Hemisphere (WHD) Antigua & Barbuda Argentina Bahamas, The Barbados Belize Bolivia Brazil Chile Colombia Costa Rica Dominica Dominican Republic Ecuador El Salvador Grenada |
Guatemala Guyana Haiti Honduras Jamaica Mexico Nicaragua Panama Paraguay Peru St. Kitts & Nevis St. Lucia St. Vincent & the Grenadines Suriname Trinidad & Tobago Uruguay Venezuela |
Annex 3.2. Data Description
The empirical analysis in this paper uses data from Bureau van Dijk’s Orbis database. The sample covers eight Middle East and North African region (MENA) countries (Morocco, Algeria, Egypt, Saudi Arabia, Oman, Iran, Kuwait, and Jordan) and 66 countries in other world regions, over the period 2006–18. State-owned enterprises (SOEs) are identified based on the reported firm owner (that is, firms with majority ownership by “public authority, state, government”).
The Orbis database is one of the few harmonized, cross-country, firm-level datasets of key financial variables that include both SOEs and privately owned firms (both listed and non-listed), allowing for rich quantitative analyses of SOEs. As with most datasets, however, there are some limitations. These include uneven firm coverage across countries, unbalanced data panel, and the inability to identify indirect SOEs (for example, firms owned by state-owned banks). Extensive data cleaning and robustness checks of the empirical results were done to ensure that data limitations do not result in biased findings.

| Variable | Definition |
|---|---|
| ROE | Return on equity, computed as firm’s profit divided by equity |
| ROK | Return on capital, computed as firm’s revenue divided by its fixed assets |
| ROL | Return on labor, computed as firm’s revenue divided by its employee cost |
| R | Interest rate faced by the firm, computed as the firm’s interest expenditure divided by total liabilities excluding equity |
| HHI | Herfndahl-Hirshman Index, ∑i(frm i’s revenue/sector’s revenue)2, a measure of market concentration (a value of 1 reflects monopolistic market) |
| HHIK | Herfndahl-Hirshman Index, ∑i(frm i’s fixed assets/sector’s total assets)2, a measure of market concentration for the capital input market |
| HHIL | Herfndahl-Hirshman Index, ∑i(frm i’s employee cost/sector’s total employee cost)2, a measure of market concentration for the labor input market |
| Entry/Entry rate | Number of new private firms (based on the year of establishment) divided by number of firms in the sample in that period |
| Exit | Number of private firms that exit sample (based on last observation) divided by number of firms in the sample in that period |
| Investment | Change in the firm’s fixed assets from the previous year |
| SOE | Dummy variable for firms that are more than 50 percent owned by public authority, state, or government |
| SOE share | Share of SOE assets in the sector’s total assets |
| MENA | Dummy variable for firms located in the MENA region |
| Age | Age of the firm |
| Size | (Log of) Assets |
| Leverage | Firm’s total liabilities divided by total assets |
| Current asset ratio | Firm’s stock of current assets divided by current liabilities |
| Maturity | Firm’s noncurrent liabilities divided by total liabilities |
| Equity ratio | Firm’s equity divided by total liabilities |
| Inventory turnover | Inventory turnover, a measure of efficiency of inventory usage, computed as the firm’s inventory divided by its revenue |
| Variable | Definition |
|---|---|
| ROE | Return on equity, computed as firm’s profit divided by equity |
| ROK | Return on capital, computed as firm’s revenue divided by its fixed assets |
| ROL | Return on labor, computed as firm’s revenue divided by its employee cost |
| R | Interest rate faced by the firm, computed as the firm’s interest expenditure divided by total liabilities excluding equity |
| HHI | Herfndahl-Hirshman Index, ∑i(frm i’s revenue/sector’s revenue)2, a measure of market concentration (a value of 1 reflects monopolistic market) |
| HHIK | Herfndahl-Hirshman Index, ∑i(frm i’s fixed assets/sector’s total assets)2, a measure of market concentration for the capital input market |
| HHIL | Herfndahl-Hirshman Index, ∑i(frm i’s employee cost/sector’s total employee cost)2, a measure of market concentration for the labor input market |
| Entry/Entry rate | Number of new private firms (based on the year of establishment) divided by number of firms in the sample in that period |
| Exit | Number of private firms that exit sample (based on last observation) divided by number of firms in the sample in that period |
| Investment | Change in the firm’s fixed assets from the previous year |
| SOE | Dummy variable for firms that are more than 50 percent owned by public authority, state, or government |
| SOE share | Share of SOE assets in the sector’s total assets |
| MENA | Dummy variable for firms located in the MENA region |
| Age | Age of the firm |
| Size | (Log of) Assets |
| Leverage | Firm’s total liabilities divided by total assets |
| Current asset ratio | Firm’s stock of current assets divided by current liabilities |
| Maturity | Firm’s noncurrent liabilities divided by total liabilities |
| Equity ratio | Firm’s equity divided by total liabilities |
| Inventory turnover | Inventory turnover, a measure of efficiency of inventory usage, computed as the firm’s inventory divided by its revenue |
Annex 3.3. Regression Results
Firm Proftability

Firm Proftability
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Variables | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t |
| SOE | -8.05*** | -33.5 | -33.3 | -15.6*** | -50.3*** | -50.3*** |
| (1.81) | (25.2) | (25.3) | (0.11) | (0.64) | (0.64) | |
| MENA | 12.3 | 0.94 (34.8) | -0.26 (51.7) | |||
| MENA × SOE | 8.11*** (1.81) | 1.54 (1.83) | 1.62 (1.83) | |||
| Age | -0.19*** | -0.19*** | -0.40*** | -0.40*** | ||
| (0.030) | (0.030) | (0.0014) | (0.0014) | |||
| Age × SOE | 0.25*** | 0.25*** | 0.38*** | 0.38*** | ||
| (0.079) | (0.079) | (0.0029) | (0.0029) | |||
| Size | -0.64*** | -0.64*** | -1.16*** | -1.16*** | ||
| (0.21) | (0.21) | (0.0092) | (0.0092) | |||
| Size × SOE | 1.28 | 1.27 | 2.12*** | 2.12*** | ||
| (1.29) | (1.29) | (0.039) | (0.039) | |||
| Leverage | -0.00045*** | -0.00045*** | -0.00017 | -0.00017 | ||
| (0.000037) | (0.000037) | (0.00017) | 0.00017) | |||
| Current asset ratio | -0.0027*** | -0.0027*** | -6.9e-09 | -6.9e-09 | ||
| (0.00090) | (0.00090) | (1.0e-08) | (1.0e-08) | |||
| Equity ratio | -0.00013*** | -0.00013*** | -0.00046*** | -0.00046*** | ||
| (9.8e-06) | (1.0e-05) | (0.000063) | (0.000063) | |||
| Inventory turnover | -0.00000014** | -0.00000014** | -0.00000014** | -0.00000014** | ||
| (0.0000064) | (0.0000064) | (0.00000063) | (0.00000063) | |||
| HHI (Sector) | 4.97 (4.11) | -5.56*** (0.60) | ||||
| Entry rate (Sector) | 3.91 (35.9) | 77.4*** (2.27) | ||||
| Investment | -0.00022 | 0.00039 | ||||
| (Sector) | (0.00079) | (0.00080) | ||||
| Fixed effects | Country X Sector | Country X Sector | Country X Sector | Country X Sector | Country X Sector | Country X Sector |
| Country X Year | Country X Year | Country X Year | Country X Year | Country X Year | Country X Year | |
| Observations | 54.7k(MN) | 50.0k(MN) | 50.k(MN) | 41.1m | 39.3m | 39.3m |
| R-squared | 0.040 | 0.035 | 0.035 | 0.037 | 0.041 | 0.041 |
Firm Proftability
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Variables | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t | ROEi{c,s},t |
| SOE | -8.05*** | -33.5 | -33.3 | -15.6*** | -50.3*** | -50.3*** |
| (1.81) | (25.2) | (25.3) | (0.11) | (0.64) | (0.64) | |
| MENA | 12.3 | 0.94 (34.8) | -0.26 (51.7) | |||
| MENA × SOE | 8.11*** (1.81) | 1.54 (1.83) | 1.62 (1.83) | |||
| Age | -0.19*** | -0.19*** | -0.40*** | -0.40*** | ||
| (0.030) | (0.030) | (0.0014) | (0.0014) | |||
| Age × SOE | 0.25*** | 0.25*** | 0.38*** | 0.38*** | ||
| (0.079) | (0.079) | (0.0029) | (0.0029) | |||
| Size | -0.64*** | -0.64*** | -1.16*** | -1.16*** | ||
| (0.21) | (0.21) | (0.0092) | (0.0092) | |||
| Size × SOE | 1.28 | 1.27 | 2.12*** | 2.12*** | ||
| (1.29) | (1.29) | (0.039) | (0.039) | |||
| Leverage | -0.00045*** | -0.00045*** | -0.00017 | -0.00017 | ||
| (0.000037) | (0.000037) | (0.00017) | 0.00017) | |||
| Current asset ratio | -0.0027*** | -0.0027*** | -6.9e-09 | -6.9e-09 | ||
| (0.00090) | (0.00090) | (1.0e-08) | (1.0e-08) | |||
| Equity ratio | -0.00013*** | -0.00013*** | -0.00046*** | -0.00046*** | ||
| (9.8e-06) | (1.0e-05) | (0.000063) | (0.000063) | |||
| Inventory turnover | -0.00000014** | -0.00000014** | -0.00000014** | -0.00000014** | ||
| (0.0000064) | (0.0000064) | (0.00000063) | (0.00000063) | |||
| HHI (Sector) | 4.97 (4.11) | -5.56*** (0.60) | ||||
| Entry rate (Sector) | 3.91 (35.9) | 77.4*** (2.27) | ||||
| Investment | -0.00022 | 0.00039 | ||||
| (Sector) | (0.00079) | (0.00080) | ||||
| Fixed effects | Country X Sector | Country X Sector | Country X Sector | Country X Sector | Country X Sector | Country X Sector |
| Country X Year | Country X Year | Country X Year | Country X Year | Country X Year | Country X Year | |
| Observations | 54.7k(MN) | 50.0k(MN) | 50.k(MN) | 41.1m | 39.3m | 39.3m |
| R-squared | 0.040 | 0.035 | 0.035 | 0.037 | 0.041 | 0.041 |
Firm Productivity

Firm Productivity
| (1) | (2) | (3) | |
|---|---|---|---|
| Variables | ROKi,t | ROKi,t | ROLi,t |
| SOE | -2286.6 (1522.3) |
-587.3*** (207.9) |
353.8*** (147.7) |
| MENA | 28270.1 | -287.4 (261.0) |
|
| MENA × SOE | 2179.5*** (832.8) |
46.2 (82.4) |
|
| Age | -10.1*** (1.07) |
-0.99 (1.82) |
-3.24*** (0.50) |
| Age × SOE | -12.2 (1.07) |
5.93* (1.82) |
-0.019 (0.85) |
| Size | 55.8*** (19.3) |
8.17 (14.0) |
47.8*** (6.78) |
| Size × SOE | 249.0* (139.7) |
12.1 (12.1) |
-28.9*** (8.85) |
| Leverage | 0.0044 (0.0043) |
0.056 (0.061) |
0.00028* (0.00016) |
| Current asset ratio | 0.00034 (0.00036) |
-0.015 (0.013) |
-0.0000039** (0.0000018) |
| Inventory turnover | -0.000027*** (0.0000085) |
-0.00016** (0.000066) |
-0.000052*** (0.0000091) |
| Equity ratio | -0.060*** (0.0021) |
0.00026 (0.00020) |
-0.00015 (0.00016) |
| HHI (Sector) | 4912.1 (4915.9) |
-183.9 (134.9) |
-82.1 (138.4) |
| Entry rate (Sector) | -819.0 (632.0) |
-1068.1 (2339.5) |
-126.3 (321.8) |
| Investment (Sector) | 0.18 (0.38) |
0.079 (0.099) |
-0.17 (0.19) |
| Fixed effects | Country X Sector | Country X Sector | Country X Sector |
| Country X Year | Country X Year | Country X Year | |
| Observations | 38.7mn | 52.6k | 26.5mn |
| Sample region | All | MENA | All |
| R-squared | 0.00043 | 0.00041 | 0.000093 |
Firm Productivity
| (1) | (2) | (3) | |
|---|---|---|---|
| Variables | ROKi,t | ROKi,t | ROLi,t |
| SOE | -2286.6 (1522.3) |
-587.3*** (207.9) |
353.8*** (147.7) |
| MENA | 28270.1 | -287.4 (261.0) |
|
| MENA × SOE | 2179.5*** (832.8) |
46.2 (82.4) |
|
| Age | -10.1*** (1.07) |
-0.99 (1.82) |
-3.24*** (0.50) |
| Age × SOE | -12.2 (1.07) |
5.93* (1.82) |
-0.019 (0.85) |
| Size | 55.8*** (19.3) |
8.17 (14.0) |
47.8*** (6.78) |
| Size × SOE | 249.0* (139.7) |
12.1 (12.1) |
-28.9*** (8.85) |
| Leverage | 0.0044 (0.0043) |
0.056 (0.061) |
0.00028* (0.00016) |
| Current asset ratio | 0.00034 (0.00036) |
-0.015 (0.013) |
-0.0000039** (0.0000018) |
| Inventory turnover | -0.000027*** (0.0000085) |
-0.00016** (0.000066) |
-0.000052*** (0.0000091) |
| Equity ratio | -0.060*** (0.0021) |
0.00026 (0.00020) |
-0.00015 (0.00016) |
| HHI (Sector) | 4912.1 (4915.9) |
-183.9 (134.9) |
-82.1 (138.4) |
| Entry rate (Sector) | -819.0 (632.0) |
-1068.1 (2339.5) |
-126.3 (321.8) |
| Investment (Sector) | 0.18 (0.38) |
0.079 (0.099) |
-0.17 (0.19) |
| Fixed effects | Country X Sector | Country X Sector | Country X Sector |
| Country X Year | Country X Year | Country X Year | |
| Observations | 38.7mn | 52.6k | 26.5mn |
| Sample region | All | MENA | All |
| R-squared | 0.00043 | 0.00041 | 0.000093 |
Interest Rates

Interest Rates
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Variables | Ri,t | Ri,t | Ri,t | Ri,t | Ri,t | Ri,t |
| SOE | -0.018*** (0.0035) |
-0.012*** (0.0039) |
-0.015*** (0.0038) |
0.48* (0.29) |
-0.31*** (0.26) |
-0.36 (0.26) |
| MENA | -0.80 (1.03) |
-1.06 (0.71) |
-0.99 (0.66) |
|||
| MENA × SOE | -0.74 (1.34) |
0.016 (0.39) |
-0.14 (0.54) |
|||
| Size | -0.0062** (0.0025) |
-0.0040** (0.0017) |
-0.042 (0.072) |
-0.046 (0.067) |
||
| Age | 0.00031* (0.00018) |
0.00034* (0.00018) |
0.016 (0.014) |
0.016 (0.014) |
||
| ROE | -0.00013*** (0.000030) |
0.00016*** (0.000039) |
0.00093 (0.00082) |
0.00079 (0.00076) |
||
| Leverage | 0.0020 (0.0021) |
0.000011 (0.000016) |
||||
| Current asset ratio | 0.0015 (0.0010) |
0.0000020 (0.0000017) |
||||
| Maturity | -0.0018 (0.0012) |
9.8e-07 (8.3e-07) |
||||
| Equity ratio | 0.031 (0.019) |
0.0000051 0.0000050 | ||||
| Fixed effects | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year |
| Observations | 54.7k | 50.0k | 50.k | 41.1mn | 39.3mn | 39.3mn |
| Sample region | MENA | MENA | MENA | All | All | All |
| R-squared | 0.040 | 0.035 | 0.035 | 0.037 | 0.041 | 0.041 |
Interest Rates
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Variables | Ri,t | Ri,t | Ri,t | Ri,t | Ri,t | Ri,t |
| SOE | -0.018*** (0.0035) |
-0.012*** (0.0039) |
-0.015*** (0.0038) |
0.48* (0.29) |
-0.31*** (0.26) |
-0.36 (0.26) |
| MENA | -0.80 (1.03) |
-1.06 (0.71) |
-0.99 (0.66) |
|||
| MENA × SOE | -0.74 (1.34) |
0.016 (0.39) |
-0.14 (0.54) |
|||
| Size | -0.0062** (0.0025) |
-0.0040** (0.0017) |
-0.042 (0.072) |
-0.046 (0.067) |
||
| Age | 0.00031* (0.00018) |
0.00034* (0.00018) |
0.016 (0.014) |
0.016 (0.014) |
||
| ROE | -0.00013*** (0.000030) |
0.00016*** (0.000039) |
0.00093 (0.00082) |
0.00079 (0.00076) |
||
| Leverage | 0.0020 (0.0021) |
0.000011 (0.000016) |
||||
| Current asset ratio | 0.0015 (0.0010) |
0.0000020 (0.0000017) |
||||
| Maturity | -0.0018 (0.0012) |
9.8e-07 (8.3e-07) |
||||
| Equity ratio | 0.031 (0.019) |
0.0000051 0.0000050 | ||||
| Fixed effects | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year | Ctry. X Sector Ctry. X Year |
| Observations | 54.7k | 50.0k | 50.k | 41.1mn | 39.3mn | 39.3mn |
| Sample region | MENA | MENA | MENA | All | All | All |
| R-squared | 0.040 | 0.035 | 0.035 | 0.037 | 0.041 | 0.041 |
The Impact of SOE Presence on Output Market Concentration

The Impact of SOE Presence on Output Market Concentration
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Variables | HHIc,s,t | HHIc,s,t | HHIc,s,t | HHIc,s,t |
| SOE shareHHIc,s,t | 0.11*** (0.012) |
0.095*** (0.012) |
0.095*** (0.012) |
0.096*** (0.012) |
| MENA × SOE shareHHIc,s,t | 0.16*** (0.052) |
0.16*** (0.052) |
0.16*** (0.053) |
|
| Entry | 0.10 (0.083) |
0.088 (0.084) |
||
| InvestmentHHIc,s,t | 0.000016 (0.000011) |
|||
| Fixed effects | Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
| Observations | 8,504 | 8,504 | 8,504 | 8,497 |
| Sample region | All | All | All | All |
| R-squared | 0.406 | 0.408 | 0.408 | 0.408 |
The Impact of SOE Presence on Output Market Concentration
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Variables | HHIc,s,t | HHIc,s,t | HHIc,s,t | HHIc,s,t |
| SOE shareHHIc,s,t | 0.11*** (0.012) |
0.095*** (0.012) |
0.095*** (0.012) |
0.096*** (0.012) |
| MENA × SOE shareHHIc,s,t | 0.16*** (0.052) |
0.16*** (0.052) |
0.16*** (0.053) |
|
| Entry | 0.10 (0.083) |
0.088 (0.084) |
||
| InvestmentHHIc,s,t | 0.000016 (0.000011) |
|||
| Fixed effects | Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
| Observations | 8,504 | 8,504 | 8,504 | 8,497 |
| Sample region | All | All | All | All |
| R-squared | 0.406 | 0.408 | 0.408 | 0.408 |
The Impact of SOE Presence on Input Market Concentration

The Impact of SOE Presence on Input Market Concentration
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Variables | HHIkc,t | HHIkc,t | HHIkc,t | HHIkc,t |
| SOE sharec,t | -0.038 (0.087) |
0.74*** (0.11) |
-0.35** (0.17) |
0.51*** (0.19) |
| MENA × SOE sharec,t | 0.80*** (0.14) |
0.89*** (0.27) |
||
| Fixed effects | Country Year | Country Year | Country Year | Country Year |
| Observations | 917 | 78 | 917 | 78 |
| Sample region | All | MENA | All | MENA |
| R-squared | 0.593 | 0.817 | 0.476 | 0.545 |
The Impact of SOE Presence on Input Market Concentration
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Variables | HHIkc,t | HHIkc,t | HHIkc,t | HHIkc,t |
| SOE sharec,t | -0.038 (0.087) |
0.74*** (0.11) |
-0.35** (0.17) |
0.51*** (0.19) |
| MENA × SOE sharec,t | 0.80*** (0.14) |
0.89*** (0.27) |
||
| Fixed effects | Country Year | Country Year | Country Year | Country Year |
| Observations | 917 | 78 | 917 | 78 |
| Sample region | All | MENA | All | MENA |
| R-squared | 0.593 | 0.817 | 0.476 | 0.545 |
The Impact of SOE Presence on Business Dynamism

The Impact of SOE Presence on Business Dynamism
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Variables | Entryc,s,t | Entryc,s,t | Entryc,s,t | Entryc,s,t | Entryc,s,t | Entryc,s,t |
| SOE sharec,s,t | -0.0021* (0.0012) |
-0.0021* (0.0012) |
-0.0020* (0.0012) |
-0.012*** (0.0044) |
-0.011*** (0.0043) |
-0.011*** (0.0043) |
| MENA × SOE sharec,s,t | 0.00036 (0.0047) |
0.00053 (0.0047) |
-0.015 (0.030) |
-0.015 (0.030) |
||
| HHIc,s,t | 0.0017 (0.0016) |
0.0017 (0.0016) |
0.0017 (0.0016) |
0.025** (0.010) |
0.025** (0.011) |
0.025** (0.011) |
| Investmentc,s,t | 2.2e-06*** (5.1 e-07) |
-7.9e-06*** (2.1 e-06) |
||||
| Fixed effects | Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
| Observations | 8,504 | 8,504 | 8,497 | 7,820 | 7,820 | 7,814 |
| Sample region | All | All | All | All | All | All |
| R-squared | 0.590 | 0.590 | 0.592 | 0.491 | 0.491 | 0.491 |
The Impact of SOE Presence on Business Dynamism
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Variables | Entryc,s,t | Entryc,s,t | Entryc,s,t | Entryc,s,t | Entryc,s,t | Entryc,s,t |
| SOE sharec,s,t | -0.0021* (0.0012) |
-0.0021* (0.0012) |
-0.0020* (0.0012) |
-0.012*** (0.0044) |
-0.011*** (0.0043) |
-0.011*** (0.0043) |
| MENA × SOE sharec,s,t | 0.00036 (0.0047) |
0.00053 (0.0047) |
-0.015 (0.030) |
-0.015 (0.030) |
||
| HHIc,s,t | 0.0017 (0.0016) |
0.0017 (0.0016) |
0.0017 (0.0016) |
0.025** (0.010) |
0.025** (0.011) |
0.025** (0.011) |
| Investmentc,s,t | 2.2e-06*** (5.1 e-07) |
-7.9e-06*** (2.1 e-06) |
||||
| Fixed effects | Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
Country Sector Year |
| Observations | 8,504 | 8,504 | 8,497 | 7,820 | 7,820 | 7,814 |
| Sample region | All | All | All | All | All | All |
| R-squared | 0.590 | 0.590 | 0.592 | 0.491 | 0.491 | 0.491 |
The Impact of SOE Presence on Private Firm Investment

The Impact of SOE Presence on Private Firm Investment
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Variables | Investmenti,t | Investmenti,t | Investmenti,t | Investmenti,t |
| SOE sharec,s,t | -835.1 (547.58) |
-594.6* (343.93) |
19210.3 (18734.84) |
3322.3 (11016.82) |
| MENA × SOE sharec,s,t | -19736.0 (18624.46) |
-16115.4 (13904.51) |
||
| MENA | 8851.4 (9274.4) |
270685.6 (193959.99) |
||
| Size | 156.0*** (45.70) |
155.8*** (45.61) |
1343.3*** (245.63) |
|
| Age | -6.85* (4.07) |
-6.84* (4.07) |
-109.5*** (23.12) |
|
| Leverage | 0.018** (0.01) |
0.021** (0.01) |
0.053* (0.03) |
|
| Current asset ratio | -0.019 (0.02) |
-0.013 (0.02) |
-0.000040* (0.00) |
|
| Equity ratio | 0.0011* (0.00) |
0.0017* (0.00) |
-0.00071* (0.00) |
|
| Inventory turnover | -0.00029*** (0.00) |
-0.00024*** (0.00) |
0.00029 (0.00) |
|
| HHI (Sector) | -912.9 (1166.36) |
41145.1 (27849.4) |
||
| Entry (Sector) | -12726.0 (10657.45) |
12138.2 (9263.7) |
||
| Fixed effects | Country X Sector Country X Year | Country X Sector Country X Year | Country X Sector Country X Year | Country X Sector Country X Year |
| Observations | 45,010 | 45,010 | 39.29 mn | 37.69 mn |
| Sample region | MENA | MENA | All | All |
| R-squared | 0.0047 | 0.0051 | 0.00079 | 0.00080 |
The Impact of SOE Presence on Private Firm Investment
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Variables | Investmenti,t | Investmenti,t | Investmenti,t | Investmenti,t |
| SOE sharec,s,t | -835.1 (547.58) |
-594.6* (343.93) |
19210.3 (18734.84) |
3322.3 (11016.82) |
| MENA × SOE sharec,s,t | -19736.0 (18624.46) |
-16115.4 (13904.51) |
||
| MENA | 8851.4 (9274.4) |
270685.6 (193959.99) |
||
| Size | 156.0*** (45.70) |
155.8*** (45.61) |
1343.3*** (245.63) |
|
| Age | -6.85* (4.07) |
-6.84* (4.07) |
-109.5*** (23.12) |
|
| Leverage | 0.018** (0.01) |
0.021** (0.01) |
0.053* (0.03) |
|
| Current asset ratio | -0.019 (0.02) |
-0.013 (0.02) |
-0.000040* (0.00) |
|
| Equity ratio | 0.0011* (0.00) |
0.0017* (0.00) |
-0.00071* (0.00) |
|
| Inventory turnover | -0.00029*** (0.00) |
-0.00024*** (0.00) |
0.00029 (0.00) |
|
| HHI (Sector) | -912.9 (1166.36) |
41145.1 (27849.4) |
||
| Entry (Sector) | -12726.0 (10657.45) |
12138.2 (9263.7) |
||
| Fixed effects | Country X Sector Country X Year | Country X Sector Country X Year | Country X Sector Country X Year | Country X Sector Country X Year |
| Observations | 45,010 | 45,010 | 39.29 mn | 37.69 mn |
| Sample region | MENA | MENA | All | All |
| R-squared | 0.0047 | 0.0051 | 0.00079 | 0.00080 |
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We thank Shant Arzoumanian for providing excellent research assistance.
For this chapter, the Middle East and North Africa (MENA) region refers to the following countries: Afghanistan, Algeria, Bahrain, Djibouti, Egypt, Islamic Republic of Iran, Jordan, Kuwait, Lebanon, Libya, Mauritania, Morocco, Oman, Pakistan, Qatar, Saudi Arabia, Tunisia, Yemen, and UAE.
See, for example, DeWenter and Malatesta (2001), Wang and Shailer (2018), IMF (2019), Jurzyk and Ruane (2021), and IMF (2020).
Imputed interest rate is computed as the total interest expenditures divided by total liabilities excluding equity.
Returns on capital and on labor are measured as the firm’s revenue divided by its fixed assets and employee costs, respectively.