Tag: Economic development

Georgia’s Growth Dilemma: Structural Transformation, Inequality, and the Future of Inclusive Development

Posted on May 19, 2025 | Policy Papers

Georgia Growth Dilemma Image

This policy paper examines Georgia’s economic growth and labor market developments between 2017 and 2023, with a focus on structural transformation and income distribution. While growth has been strong and absolute poverty has declined, challenges remain in labor reallocation, wage inequality, and regional disparities. Redistribution mechanisms, particularly social transfers, have played an important role in mitigating poverty; however, the pace of inclusive structural change has been limited. Key policy priorities include fostering productivity growth, expanding employment opportunities, and addressing inequality through targeted labor market and social policies.

Georgia’s Economic Rebound: Growth Beyond Recovery or Superficial Expansion?

In recent years, Georgia’s economy has demonstrated remarkable resilience and dynamism. Following a sharp contraction of real GDP by approximately 6.8 percent in 2020 due to the Covid-19 pandemic, the economy rebounded strongly, posting a growth rate exceeding 10 percent in 2021. This robust performance was maintained also in 2022 and 2023. The recovery was among the fastest in the region, fueled by a combination of strong private consumption, booming external demand, and exceptional inflows of remittances and capital.

According to national accounts data, output in 2023 not only recovered the losses sustained during the pandemic but significantly surpassed pre-pandemic levels. Georgia’s real GDP is on a trajectory above its previous trend, with potential output estimates also being revised upward (see Figure 1). Potential output — the level of economic activity the country can sustain without triggering inflation — is not directly observable and was estimated using a statistical technique known as the Kalman filter. This method uses historical GDP data and economic patterns to produce a smooth estimate of potential output over time, allowing policymakers to assess the gap between actual and sustainable growth. The economy’s output gap, which turned sharply negative during the pandemic, gradually closed by 2022 and moved into slightly positive territory by 2023, indicating that output had surpassed its estimated potential level as the recovery matured.

Figure 1. Output Growth, Output Gap, and Potential Output in Georgia

Source: Geostat. Author’s calculations.

Georgia’s recent economic growth is largely propelled by geopolitical factors linked to the Russo-Ukraine war. The sharp increase in remittance inflows from Russia — which soared by 403 percent to $2.1 billion in 2022 — provided a major boost to domestic consumption. At the same time, the relocation of capital, businesses, and skilled individuals intensified, with over 30,000 Russian-owned firms registered and nearly 115,000 Russian migrants arriving between 2022 and 2023, significantly stimulating investment and labor market activity. In addition, the rapid expansion of re-exports — particularly of motor vehicles and machinery — further accelerated external trade, with re-exports to Russia, Armenia, Kazakhstan, and Kyrgyzstan rising 6.6 times in 2024 compared to 2019, which strengthened the logistics and transport sectors.At the same time, substantial fiscal stimulus during the pandemic years, followed by a gradual normalization of fiscal policy, helped support aggregate demand without triggering immediate macroeconomic instability. Monetary policy remained broadly accommodative, while inflationary pressures — although pronounced — were largely kept under control relative to peer economies.

Despite these positive developments, the underlying composition of growth raises important questions. High headline growth figures do not automatically translate into widespread improvements in living standards or reductions in inequality. Growth that is driven by consumption booms, remittance surges, or temporary trade redirection may lack the deep, productivity-enhancing underpinnings necessary for long-term sustainability. Without broad-based sectoral upgrading and inclusive labor market outcomes, there is a risk that economic expansion will remain concentrated in a few dynamic sectors while leaving large parts of the population behind.

Moreover, the post-pandemic growth episode coincided with rising concerns about external vulnerabilities, including Georgia’s dependence on remittances (17.5 and 13.5 percent of GDP in 2022 and 2023, respectively (NBG, Geostat)) and commodity prices, as well as regional political risks. If these external drivers were to weaken, maintaining high growth rates without deeper structural changes could become increasingly difficult.

Therefore, while Georgia’s recent economic record is impressive by regional standards, it is crucial to assess whether this growth has been accompanied by meaningful structural transformation — namely, a reallocation of labor from low to high-productivity sectors, rising labor incomes, and reduced inequality. A deeper analysis of sectoral dynamics and employment patterns is required to determine whether Georgia’s economy is evolving toward a more inclusive and sustainable growth model.

Structural Shifts of the Economy: Progress Without Transformation?

The structural transformation of Georgia’s economy between 2017 and 2023 (see Figure 2) reveals both encouraging and concerning trends. The analytical framework used to assess structural transformation in Georgia between 2017 and 2023 draws on the methodology developed by McMillan and Rodrik (2011). This influential study emphasizes the role of labor reallocation across sectors as a key driver of aggregate productivity growth in developing and transition economies.

The analysis of the change in sectoral employment shares against relative sectoral productivity shows that, broadly speaking, labor reallocation has followed a growth-enhancing direction. The fitted trend line across sectors exhibits a positive slope, suggesting that workers have been moving, though slowly, away from low-productivity sectors and toward relatively higher-productivity activities. However, the shallow gradient of the trend line indicates that the pace and quality of this transformation have been modest. The most significant dynamic during this period is the continued exit of labor from agriculture. Agriculture remains a highly unproductive sector, with a large share of labor in subsistence agriculture, and experienced a substantial decline in its employment share—a positive signal for economic modernization. Nevertheless, much of the displaced labor appears to have been absorbed by mid-productivity services such as construction, retail trade (wholesale and retail trade; repair of motor vehicles and motorcycles), accommodation and food service activities, and transportation. These sectors have seen rising employment shares but remain relatively close to or below the economy-wide average in terms of labor productivity. Consequently, while labor mobility is evident, the migration has largely been into sectors that do not substantially enhance overall economic efficiency.

Figure 2. Structural Transformation and Productivity Alignment in Georgia, 2017–2023

Source: Geostat. Author’s calculations. Note: Each bubble represents a sector, with its position determined by the change in its employment share (horizontal axis) and its relative productivity level (vertical axis). Bubble size corresponds to the sector’s share of total employment in 2017. The positive slope of the fitted trend line indicates modest progress in reallocating labor toward more productive activities, although the shift remains shallow and incomplete.

In contrast, high-productivity sectors, notably information and communication, financial and insurance activities, and real estate, have exhibited strong relative productivity but absorbed very limited shares of the labor force. These findings point to persistent barriers in accessing higher-value employment opportunities, likely stemming from skill mismatches, limited educational attainment, and structural rigidities in the labor market.

Public administration, education, and health — traditionally labor-intensive sectors — have maintained relatively large shares of employment while operating below average productivity levels, reflecting a lack of dynamism in these essential public service areas.

Overall, the observed pattern suggests that Georgia’s recent economic growth has been accompanied by low-quality structural transformation. Although there has been a reallocation of labor from extremely low-productive sectors, the transition has not been sufficient to significantly lift aggregate productivity or to broaden access to high-wage, high-skill employment.

These trends underscore the critical need for policy interventions aimed at improving the quality of labor mobility. Investment in education and vocational training to match labor supply with demand in high-productivity sectors is essential. Moreover, facilitating entrepreneurship, promoting innovation in services and manufacturing, and supporting labor market flexibility could help ensure that future structural changes generate more inclusive and sustainable economic growth.

Labor Market Dynamics: Recovery in Numbers, Challenges in Structure

Following the period of sectoral shifts and structural transformation outlined above, it is equally important to examine how the Georgian labor market has evolved in recent years. Labor market dynamics provide critical insight into the inclusiveness and sustainability of economic growth. Between 2017 and 2023, the number of employed individuals exhibited a general upward trajectory, particularly after the sharp decline during the Covid-19 pandemic in 2020 (see Figure 3). Employment numbers, which fell significantly in 2020 and 2021, recovered steadily in the following years, reaching approximately 1.33 million in 2023. Preliminary assessments suggest that this recovery is expected to continue into 2024, further consolidating the labor market’s post-pandemic rebound.

Figure 3. Employment and Unemployment Trends in Georgia

Source: Geostat. Author’s calculations.

This recovery has been accompanied by notable improvements in Georgia’s wage dynamics. After a period of stagnation in nominal and real wages between 2018 and 2020, the economy experienced a sharp acceleration in wage growth, beginning in 2021. Average nominal wages rose rapidly, while real wage growth, which accounts for inflation, also turned positive after years of stagnation (see Figure 4). These wage dynamics indicate that the labor market tightening contributed to upward pressure on wages, suggesting better bargaining conditions for workers in certain sectors.

Figure 4. Nominal and Real Wage Dynamics in Georgia

Source: Geostat. Author’s calculations.

At the same time, unemployment rates declined significantly. The unemployment rate, which had hovered between 17 and 20 percent prior to the pandemic, began a gradual downward trend from 2021 and onwards, falling to approximately 14 percent by 2023 (see Figure 3). This suggests that job creation in the recovery phase was relatively strong. However, the persistently high levels of unemployment earlier in the period underscore structural issues that remain unresolved.

Nevertheless, despite these positive headline trends, several deeper challenges persist within Georgia’s labor market. Employment growth has been concentrated primarily in low- and mid-productivity service sectors, as indicated previously. Informality remains high, particularly in agriculture and small-scale services, and labor underutilization (32.1 percent) — including underemployment and discouraged workers— continues to affect a significant segment of the workforce.

Moreover, the share of labor income relative to GDP provides important additional context (see Figure 5). As shown in Figure 5, the wage share of GDP fluctuated throughout the period, declining during the pandemic years and rebounding sharply in 2023. While this recovery is promising, it may however partially reflect inflationary effects or nominal wage adjustments rather than deep, productivity-driven gains.

Figure 5. Share of Wages in GDP and Economic Growth

Source: Geostat. Author’s calculations.

Taken together, recent labor market developments in Georgia reflect a cyclical recovery reinforced by external demand and domestic consumption. Yet, the underlying structure of employment, informality, and the relatively slow reallocation of labor into high-productivity sectors suggest that the labor market’s transformation remains incomplete. Sustainable improvements in labor incomes and employment quality will require addressing skills mismatches, boosting formal sector job creation, and ensuring that future growth translates into widely shared labor market opportunities.

Despite the improvements in employment and wage dynamics, it remains critical to assess whether these labor market gains have translated into broader improvements in income distribution and living standards. Strong aggregate indicators do not necessarily imply that growth has been inclusive or that inequality has diminished. The following section examines how the distribution of income has evolved in recent years, focusing on wage structures, inequality measures, and the extent to which economic growth has been shared across different segments of the population.

Income Inequality and Distributional Shifts: A Fragile Middle and Growing Extremes

Following the developments observed in the labor market, it is crucial to assess how economic growth and labor dynamics have translated into income distribution outcomes. Understanding the evolution of income inequality provides deeper insight into whether the benefits of growth have been broadly shared or have remained concentrated.

Wage income distribution patterns between 2017 and 2023 show a complex trajectory. The wage distribution curve (see Figure 6) reveals that while average earnings have increased over time, the overall shape of the distribution has also evolved significantly. The peak of the distribution has become sharper and shifted toward higher income brackets, particularly around the 1200–2400 GEL range. However, the right-hand tail of the distribution has simultaneously elongated, suggesting the emergence of a relatively small group of very high-income earners.

Figure 6. Wage Income Distribution Curves, 2017–2023

Source: RevenueServices. Author’s calculations.

This dual movement — a general upward shift combined with increasing dispersion — is captured through key statistical measures:

First, the standard deviation of incomes, which reflects the average distance of individual incomes from the mean, increased notably (57 percent) between 2017 and 2023. An increasing standard deviation indicates that income differences within the population have become more pronounced, with greater dispersion around the average wage. In simple terms, not only are people earning more on average, but the spread between low and high earners has widened substantially.

Second, the changes in skewness and kurtosis provide further depth to this picture. Skewness measures the asymmetry of the income distribution. In 2017, the distribution had a skewness of about 1.74, indicating a moderate right-skew, with income values concentrated around the lower and middle ranges and a gradual tapering toward higher incomes. By 2023, skewness had increased to 3.81, suggesting that the income distribution has become much more asymmetrical. A few individuals or households are earning disproportionately high incomes compared to the rest of the population. The visible downward shift in the 2023 wage distribution curve at the lower income ranges likely reflects two reinforcing trends. First, persistent inflation during the post-pandemic recovery years eroded the real value of wages, effectively pushing nominal incomes upward and compressing the lower tail of the distribution. Many workers who previously occupied the lowest wage brackets may have moved into higher nominal categories without corresponding improvements in purchasing power (average real wages declined until 2021, after which they began to recover, rebounding steadily through 2023 following the Covid-19 shock (See Figure 4)). Second, due to low rate of job creation, Georgia has experienced a high rate of labor emigration in recent years, especially to the EU and the U.S., particularly among low-skilled workers. This outflow of labor likely reduced the number of individuals earning wages in the lowest income ranges, further contributing to the observed contraction of the left side of the distribution curve. Together, these factors help explain why the red curve in 2023 dips below previous years in the lowest wage intervals.

Kurtosis, meanwhile, captures the “tailedness“ or the concentration of extreme outcomes. Georgia’s wage distribution moved from a kurtosis of about 5.16 in 2017 to 15.75 in 2023. Higher kurtosis indicates that extreme deviations (very low or very high incomes) have become more common relative to a normal distribution. In Georgia’s case, it points to an increasingly peaked distribution with fat tails: most people are concentrated around a modal income, but extreme earnings at the high end have become more significant.

In parallel, the Lorenz curves for 2017 and 2023 (see Figure 7) offer a graphical representation of these dynamics. The curve for 2023 lies slightly closer to the line of equality than that of 2017, reflecting a marginal improvement in income equality in the early part of the period. However, the difference is modest, and the curve’s arched shape hints at a persistent structural inequality. It should be mentioned that the calculations are based on household expenditures and therefore reflect the redistributive effects of government fiscal policy on income inequality. The Gini index, a summary statistic derived from the Lorenz curve, plots the cumulative share of income held by cumulative shares of the population. It measures income inequality on a scale from 0 (perfect equality) to 1 (perfect inequality) and thus provides a concise way to track changes in distributional dynamics over time.

In the case of Georgia, the index supports the discussion regarding the Lorenz curve. Between 2017 and 2021, the Gini index declined from 0.3711 to 0.3090, suggesting a reduction in income inequality during these years, likely influenced by pandemic-driven wage compression, social transfers, and temporary labor market adjustments. However, from 2021 onwards, inequality began creeping upward again, reaching 0.3271 in 2023. This suggests that the initial equalizing effects of crisis responses were short-lived and that structural disparities in income distribution have reasserted themselves as the economy recovered.

Figure 7. Lorenz Curves (2017 and 2023 comparison)

Source: Geostat. Author’s Calculations.

Together, these metrics paint a coherent picture: the Georgian economy experienced nominal wage growth and a partial strengthening of middle-income segments during the recovery phase, however, this was accompanied by greater income dispersion, higher asymmetry (favoring high-income earners), and an increased concentration of wealth at the very top.

Thus, although the average worker is better off in absolute terms compared to 2017, the relative disparities within the labor force have widened, especially after 2021. Growth has been unevenly distributed, increasingly favoring highly skilled, capital-intensive, or well-connected sectors and workers.

Poverty trends during 2017–2023 (see Figure 8) add an important additional dimension to the analysis of income distribution. Over this period, Georgia achieved a substantial reduction in absolute poverty, with the share of the population unable to meet basic consumption needs falling from 21.9 percent in 2017 to 11.8 percent in 2023. This sharp decline reflects real improvements in living standards for a significant portion of the population and indicates that economic growth, combined with social policy interventions, had a meaningful impact in alleviating extreme deprivation. However, developments in relative poverty tell a more nuanced story.

Relative poverty, which measures economic disadvantage in relation to the median income, declined only modestly from 22.3 percent to 19.8 percent over the same period. The persistence of relative poverty, despite improvements in absolute poverty, suggests that while more people were able to meet basic needs, the income distance between lower-income households and the median population did not significantly narrow. This implies that, although economic growth has lifted many out of extreme poverty, underlying income inequality has remained largely intact. Crucially, redistribution plays a central role in shaping these poverty outcomes. Although Georgia’s tax system is largely regressive and heavily reliant on indirect taxes, fiscal transfers — particularly the old-age pension — play a powerful equalizing role. The pension system alone is estimated to reduce the national poverty rate by up to 18 percentage points, highlighting the critical role of targeted redistribution in mitigating deprivation. These fiscal tools are especially important in the absence of highly progressive taxation, and they help explain why absolute poverty declined so markedly despite ongoing structural labor market weaknesses. At the same time, the relatively limited change in relative poverty underlines the limits of redistribution in addressing inequality in the absence of more inclusive labor market outcomes and equitable income growth.

Figure 8. Evolution of Absolute and Relative Poverty Rates in Georgia, 2017–2023

Source: RevenueServices. Author’s calculations.

An important part of the labor market story is the role of public employment initiatives, particularly those targeting the labor market. While government employment programs have had a visible impact on official labor statistics (see Figure 9), particularly in peripheral regions, a closer examination reveals critical concerns regarding the quality and sustainability of the jobs created. Many of the positions facilitated through this program are characterized by very low wages, limited or no skills development opportunities, and lack of formal career advancement paths. Rather than serving as a bridge to stable, productive employment, these jobs often appear to fulfill administrative or social functions, providing basic income support without contributing meaningfully to workers’ long-term economic mobility.

Figure 9. Share of Social Service Agency (SSA) Program Employment in Total Regional Employment (2023)

Source: Social Service Agency, Geostat, Author’s Calculations. Note: Bars represent regions in Georgia.

Moreover, there is evidence that the expansion of employment facilitated by the government program has, in some regions, been used as a tool for political management, particularly at the municipal level. By creating a network of publicly funded low-skill jobs tied to local government structures, employment program may inadvertently reinforce patronage systems and political dependence, particularly around electoral cycles.

This raises important concerns about the role of public employment programs in structural transformation. While temporary income support can be vital for vulnerable populations, overreliance on low-productivity public sector jobs can entrench regional stagnation and undermine incentives for private sector dynamism. For employment programs to contribute positively to structural transformation, it is essential that they be reoriented toward genuine skills development, pathways into productive sectors, and integration with broader labor market activation strategies.

Taken together, these trends suggest that while Georgia’s economic growth has lifted many individuals out of absolute poverty and improved average incomes, it has also led to greater wage dispersion, increasing concentration of incomes at the top end, and significant concerns about the depth and quality of labor market transformations. Without deliberate policy efforts to promote inclusive structural change, Georgia risks entrenching a dualistic economy, where prosperity coexists with persistent inequality and regional marginalization.

Conclusion and Policy Recommendations

In light of the findings discussed above, a set of targeted policy actions is proposed to foster a more inclusive, sustainable, and equitable economic transformation in Georgia. These recommendations aim to address the structural weaknesses identified in the labor market, income distribution, and regional economic development, ensuring that future growth benefits a broader cross-section of the population.

The findings of this policy paper highlight the need for a more deliberate approach to structural transformation in Georgia. While recent economic growth has been strong, labor reallocation toward high-productivity sectors remains incomplete, income distribution dynamics point to persistent inequalities, and improvements in living standards have not been evenly shared. To ensure that growth translates into broad-based prosperity, the following policy actions are recommended:

Georgia must accelerate the movement of labor from low-productivity sectors, particularly agriculture and informal services, into higher-productivity activities. Policymakers should prioritize sectoral strategies that support emerging dynamic industries — such as ICT, logistics, manufacturing, and modern services — while also upgrading traditional sectors like agriculture and tourism to enhance productivity and employment absorption.

Addressing skill mismatches is essential to enable labor mobility toward productive sectors. Investment in vocational education, digital skills training, and sector-specific workforce programs must be intensified, especially targeting young people, rural workers, and displaced labor from declining industries.

While public employment programs can play a stabilization role, the primary engine of sustainable job creation must be the private sector. Georgia should focus on creating an enabling environment for small and medium sized enterprises, supporting entrepreneurship, streamlining business regulations, and improving access to finance, especially outside of the capital Tbilisi.

Reducing regional disparities is critical for equitable growth. Targeted infrastructure investment, decentralized support for business development, and place-based labor market policies are needed to ensure that structural transformation benefits all regions, not only urban centers.

Promoting formal labor relations through fiscal incentives, simplified compliance procedures, and stronger enforcement can raise job quality and income security. At the same time, reinforcing social protection systems can mitigate inequality without discouraging labor market participation, helping to build a more resilient workforce.

Ongoing reforms must be informed by robust, high-frequency data. Strengthening labor market information systems, expanding coverage of income and employment surveys, and integrating administrative data into policymaking will enhance the government’s ability to monitor progress on structural transformation and distributional outcomes.

References

  • McMillan, M. S., & Rodrik, D. (2011). Globalization, structural change and productivity growth. NBER Working Paper No. 17143. National Bureau of Economic Research.

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Russia in Africa: What the Literature Reveals and Why It Matters

Posted on September 23, 2024 | Policy Brief

Industrial oil factory in Africa symbolizing Russia’s influence on Africa's resources and economy.

Following the full-scale invasion of Ukraine in February 2022, Russia has become increasingly isolated. In an attempt to counter Western powers’ efforts to suppress its economy and soft power impacts, Russia has tried to increase its influence in other parts of the world. In particular, Russia is increasingly active in Africa, having become a key partner to several African regimes, typically operating in areas with weak institutions and governments. Additionally, Russia’s approach has a different focus and objectives compared to other foreign actors, which may have both short and long term consequences for the continent’s development. Deepening our understanding of Russia’s distinct approach alongside those of other global actors, as well as the future implications of their involvement on the continent is, thus, of crucial importance.

Introduction

The new Foreign Policy Concept, adopted by the Russian government in March 2023, dedicates, for the first time, a separate section to Africa. The previous versions of the policy grouped North Africa with the Middle East and contained only a single paragraph, kept unchanged over time, about Sub-Saharan Africa. In the midst of its war against Ukraine, Russia is getting serious about Africa. What do we know about the reasons for and implications of this trend?

A relatively large literature in economics, political science, international relations, and other related fields has dealt with the Soviet Union’s engagement with African regimes (see overviews in Morris, 1973 and Ramani, 2023). However, the number of studies following the evolution of these relations since the collapse of the Soviet Union is significantly smaller, reflecting Russia’s strategic withdrawal from the region between 1990 and 2015. Following the full-scale invasion of Ukraine, Russia’s increased interest in and engagement on the African continent has been increasingly discussed by security analysts and think tanks (see for instance Siegel, 2021; Stanyard, Vircoulon and Rademeyer, 2023; Jones, et al., 2021). Primarily highlighted are Russia’s interest in mineral deposits, its large-scale arms’ exports to African regimes, its dominance on the nuclear energy market with resulting dependency on Russian nuclear fuels, and its ambition to undermine Western capacities by the spread of Russian propaganda and anti-Western sentiments (Lindén, 2023). Each of these dimensions carries potentially profound and far-reaching implications for the continent’s development, as underscored by various strands of literature. Research contributions on this specific new trend are however still very limited and predominantly of a qualitative and exploratory nature.

There is, however, substantial general knowledge about the various forms that foreign interests can take, including trade, investment, development aid, propaganda, election interference, and involvement in conflicts, and their potential consequences for development. This brief presents an overview of selected literature that most closely relates to foreign influence in Africa.

Background: Theories of Foreign Policy

Two contrasting approaches are used to describe the way countries engage with the international community. The first one is the so-called realist perspective, which emphasizes the role of power, national interests, and security in shaping foreign policy (Mearsheimer, 1995). In this model, countries act in their self-interest, and often in competition or even conflict with other countries. Strategic alliances and a willingness to use force to advance one’s interests are contemplated under this perspective. The second approach is the idealist perspective, in which foreign policy is used to promote democratic values, human rights, and international cooperation, prioritizing tools such as diplomacy, international law, and multilateral institutions (Lancaster, 2008). For countries at the receiving end of major powers’ foreign policy agendas, and particularly for developing countries, the implications from the contrasting approaches will be widely different. While even a realist foreign policy may ostensibly incorporate concerns about the welfare and development of its allies, these are often not more than a thin disguise for the ultimate objective of buying political support and commercial advantages. A genuine interest in the welfare and development of receiving partners only finds a place under the idealist perspective, although even idealism is at times claimed to “greenwash” state actors’ own interests (Delmas and Burbano, 2011). While this claim has some substance to it, such accusations can also stem from the anti-western rhetoric typically pursued by Russia and aimed at undermining the credibility of actors with good intentions.

In practice, most countries’ foreign policies incorporate elements of both realism and idealism, although the balance between the two may vary. Some countries may have a predominantly realist approach, while others may prioritize idealist goals. Additionally, the same country may shift its approach over time, depending on changing circumstances and priorities. Idealism may be more prominent during periods of stability and prosperity, when countries have the resources and political will to pursue more ambitious foreign policy goals. Realism tends to become more prominent in times of crisis, when countries face serious threats to their national security or economic well-being. Historical examples of the latter are the aftermath of World War II, the Cold War, and even the 2008 global financial crisis (Roberts, 2020).

Comparative Analysis of Foreign Influence

A few studies, recent enough to encompass Russia’s renewed interest in Africa post-2015 but not enough to cover the current day resurgence, explicitly compare the strategy of different actors and their long-term influence. Trunkos (2021) develops a new soft power measure for the time-period 1995–2015, to test the commonly accepted claim in the political science literature that American soft power use has been declining while Russian and Chinese soft power use has been increasing. In the author’s own words, “the findings indicate that surprisingly the US is still using more soft power than Russia and China. The data analysis also reveals that the US is leading in economic soft power actions over China and in military soft power actions over Russia as well.”

Castaneda Dower et al. (2021) take a longer-term perspective and categorize African countries into two blocs one Western-leaning and one pro-Soviet, based on a game-theoretical model of alliances. This categorization aligns well with UN voting patterns during the Cold War, but it does not predict alignment as effectively in the post-Cold War period. The study finds no significant difference in average GDP growth between the two blocs for the period from 1990 to 2016. However, the bloc with Western-like characteristics shows higher levels of inequality and greater reliance on the market economy – as opposed to the planned one. It also has higher human capital, more gender parity (in education), and better democracy scores, but lower infrastructure capital compared to the other bloc.

Another strand of literature has looked into the deep changes that have occurred over time within the global development architecture, highlighting changes in donor and partner motivations after the end of the Cold War (Boschini and Olofsgård, 2007; Frot, Olofsgård and Perrotta Berlin, 2014), through the Arab Spring (Challand, 2014), and more recently under the emergence of new actors, chiefly China (Blair, Marty and Roessler, 2021). Studies in this area aim to highlight what implications the varying ideologies and motivation for cooperation in the donor countries have for countries at the receiving end. Competing aid regimes generate soft power through public diplomacy, often in the form of branding (for instance through putting origin “flags” on aid projects or investments). This type of positive association has been shown to generate ‘positive affect’ toward donors (Andrabi and Das, 2010), and to strengthen recipients’ perceptions of the models of governance and development that such donors promote – liberal democracy, for example, or free market capitalism (Blair, Marty and Roessler, 2021).

Emerging Players on the African Stage

An extensive literature has examined the various facets of established power actors’ presence on the continent, spanning foreign aid, diplomatic relations, and military involvement, revealing significant impacts on local economic development through multiple channels. The United States, along with other former colonial powers and major Western donors, plays a particularly prominent role in this context. Against this background, recent research has increasingly focused on the rise of new actors, and in particular China’s expanding role as a donor and investor in Africa (Bluhm, 2018; Brautigam, 2008; Brazys, Elkink and Kelly, 2017; Dreher et al. 2018). While the consensus is still unclear on whether China’s approach to aid attracts support among African citizens (Lekorwe et al. 2016; Blair, Marty, and Roessler, 2021), recent research also shows that Chinese aid exacerbates corruption and undermines collective bargaining in recipient countries (Isaksson and Kotsadam 2018a; 2018b).

As mentioned, there are as yet very few recent articles concerned with the reasons for Russia’s renewed interest in Africa (see Marten, 2019; Akinlolu and Ogunnubi, 2021; Ramani, 2023), and even fewer analyzing the potential impacts from it. One working paper, not citable due to the authors’ wishes, has quantitatively mapped and explicitly analyzed the impact of Russian military presence (in particular, of the Wagner Group) in Africa. The study found that the infamous paramilitary group faces fewer repercussions for human rights violations and commits more lethal actions than the state actors that employ them. In another recent study on the Central African Republic (CAR), Gang et al. (2023) found not only mortality levels in CAR to be four times higher than what estimated by the UN but also that Wagner mercenaries have contributed to “increased difficulties of survival” for the population in affected areas. Pardyak, M. (2022) explores the communication strategies employed by the key actors in the war, specifically focusing on how these strategies are received in African societies. Based on the analysis of over 140 media articles published in several African countries up to 15 October 2022, complemented by street surveys in Cairo, and in-depth interviews with Egyptians and Sudanese migrants, the study concludes that Russia’s multipolar perspective on the international order is more widely supported in Africa than Western strategies.

When viewed in a historical context, however, Russia’s actions reflect a longstanding adherence to a realist approach in its foreign policy endeavors. Throughout its trajectory, Russia has consistently prioritized national security and economic interests, frequently leveraging military and economic means to safeguard these interests (Tsygankov and Tsygankov, 2010). Presently, amid mounting pressures from the Western democratic world following the full-scale invasion of Ukraine in February 2022, Russia finds itself increasingly reliant on a realist approach. While the Chinese engagement in Africa is also characterized by realist principles, it’s important to emphasize that the Russian approach diverges from that of China. China is focused on a long-term presence, infrastructure building and investments. It has no interest in democracy and human rights, is efficient and cheap though not always loved (Isaksson and Kotsadam, 2018b). Russia’s interest is more short term and opportunistic, seeking out countries rich in natural resources with unstable governments and weak institutions, such as Libya, Sudan, Mozambique, the Central African Republic, Mali, Burkina Faso and Madagascar. Russia typically targets undemocratic elites or military juntas, offering political support, military equipment sales, and security cooperation (in particular through the Wagner Group) in exchange for access to natural resources, concession rights and influence. State of the art research on a previous period (Berman et al., 2017, spanning 1997 to 2010), although not exclusively focused on Russia, finds that rents from mineral contracts, captured by swings in global mineral prices for a causal interpretation, lead to a higher likelihood of local conflicts, and furthermore that the control of mining areas by rebel groups can escalate violence beyond the local level.

Russia is pursuing a range of strategic goals that include diplomatic legitimization, media influence, military presence, elite influence, arms export, and shaping voting patterns in international organizations (Lindén, 2023). Like China, Russia is uninterested in democracy or human rights. Moreover, what Russia stands for is in stark contrast to the Western model. Russia embodies autocracy and backward revisionist values (for instance in areas such as attitudes to gender equality and the sustainability agenda) while the West generally promotes democracy and progressive inclusive solutions (Lindén, 2023). What also especially characterizes Russia is the particular attraction towards the presence of anti-West sentiment, which it fuels through populistic anti-colonial disinformation and propaganda. This approach has been criticized for potentially weakening democratic norms and sidelining African agency (Akinlolu and Ogunnubi, 2021). Additionally, Russia’s disregard for the socio-political realities in Africa, typically associated with a self-interested realist approach, can lead to ineffective engagement and unintended negative consequences, undermining the long-term sustainability of both social and economic developments in the region.

Conclusion

Many African countries find themselves in a delicate balancing act, as they cannot afford to push away Russia nor displease their historical Western partners. This attempt to balance between actors poses several risks and potentially detrimental consequences, including reduced development cooperation, slower democratization, limited progress on human rights, and increased conflicts. Additionally, Russia’s growing presence in Africa can have implications for the interests and policies of the European Union (EU) and its member states as well as global actors, including impacts on migration, terrorism, the energy sector as well as on trade and aid flows.

In light of the diverse strategies foreign powers use in their relations with African countries and the significant impact these strategies have, it is crucial to deepen our understanding of foreign engagements in Africa. By examining Russia’s distinct approach alongside those of other global actors, we can gain valuable insights into the complex dynamics shaping the continent’s political, economic, and social landscape, both now and in the future. Expanding research in this area is not only desirable but essential for informing policy and development strategies.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Will Entrepreneurs Be Able to Reactivate the Belarusian Economy?

Posted on June 13, 2022 | Policy Brief

20220613 Will Entrepreneurs Be Able Image 01

Based on data from two recent waves of the Global Entrepreneurship Monitor (GEM), we demonstrate that the Coronacrisis gave birth to many new necessity-driven entrepreneurs who will likely alleviate the current challenges of unemployment and income losses in the short- and medium-term. The readiness and willingness of Belarusians to become entrepreneurs in a harsh business environment could be considered a good sign for the economy and society. However, such businesses may fail to deliver a positive long-term impact on the economy, while the detrimental consequences of the war in Ukraine undermine the potential and sustainability of growth-driving businesses with international and innovative orientation.

Crises and Entrepreneurial Activity in Belarus

During the past 15 years, the Belarusian economy and, in particular, Belarusian entrepreneurs have experienced several crises of different scopes, nature, and origins (in 2009, 2011, 2015-2016, 2020). During these periods, Belarusian private enterprises responded faster to both negative and positive trends in the economy compared to state-owned firms. This has for instance manifested itself in private sector firms being swifter in decreasing or increasing the size of the work force in recessions or recoveries (IMF, 2019).  Stagnating demand also led to deteriorating business opportunities that in turn incited a decrease in the number of both nascent and matured entrepreneurs. In line with Cowling et al. (2015), these circumstances suggest the presence of a procyclical trend in the entrepreneurship development in the country. In the same vein, the period of economic growth brought new entrepreneurs to the market to pursue business opportunities.

However, results from two waves of the Global Entrepreneurship Monitor (GEM), conducted in May-June 2019 and June-July 2021 demonstrate that notwithstanding the Coronacrisis, political unrest, and worsening business climate, the Belarusian economy experienced an influx of entrepreneurs (not necessarily officially registered as a firm or sole proprietor). These findings contribute to the discussion on the motivation, potential, and effectiveness of this wave of entrepreneurs for the economy.

Belarusian Context for Entrepreneurs in 2019-2021

After the 2015-2016 economic crisis, 2019 represented the third consecutive year of moderate economic growth in Belarus. The gradual liberalization of the economic activity, as well as the give-and-take relationship with Eastern-European neighbors and the West, fueled the enthusiasm of Belarusian entrepreneurs, especially in the medium- and high-tech sectors. The year 2019 was supposed to be highly conducive to entrepreneurship. These conditions were captured by the GEM Belarus 2019/2020 (2020).

However, as in most other countries, small businesses were more affected by the pandemic than large enterprises in Belarus. Moreover, many of them were left to fend for themselves in dealing with COVID-related challenges, as only a small portion of enterprises benefitted from state support measures (Marozau et al., 2021). The recovery period was abrupted by the political crisis that broke out after the presidential elections in August 2020. This political unrest resulted in increased pressure on the private sector and NGOs as well as tensions with EU countries and Ukraine. Many famous entrepreneurs were forced to immigrate and re-locate their businesses. Consequently, GEM Belarus 2021/2022 (2022) captured a new reality of the Belarusian entrepreneurial ecosystem.

How the Entrepreneurship Indicators Changed

According to the GEM 2021/22 survey, Belarus experienced an increase in the percentage of the adult population (18-64 years old) involved in all stages of the entrepreneurial process (Figure 1). Nevertheless, the level of the total early-stage entrepreneurial activity (which includes nascent entrepreneurs – up to 3 months old businesses and baby businesses – 4–42 months old) is still lower than one might predict based on the country’s level of economic development (Figure 2).

These positive changes are paradoxical because, according to the survey, Belarusians were not enthusiastic about the opportunities to start a business – respondents reported a high level of fear of business failure, and that the entrepreneurial framework conditions had deteriorated.

Figure 1. Percentage of the adult population involved in the entrepreneurial process

Source: GEM Belarus 2019/2020 & 2021/2022

Figure 2. Early-stage entrepreneurship rates and GDP per capita.

Source: GEM 2021/22 Global Report (Hill et al., 2022)

Moreover, the GEM survey reveals that the profile of early-stage entrepreneurs changed between 2019 and 2021 – the educational level of early-stage entrepreneurs increased, while their income level followed a negative trend. A plausible explanation for these changes could be that a relatively well-educated part of the population, employed in the sectors that were harshly hit by the pandemic (HoReCa, Sport & Leisure, etc), decided to start a business out of necessity due to wage shrinkages or layoffs. Therefore, neither a low level of opportunity perception nor an aggravating business climate kept them from starting an enterprise.

Support for this argument can be found if we examine the reasons why Belarusians started businesses in 2021 (Figure 3). The shares of both nascent entrepreneurs and owners of baby businesses that report ‘earning a living because jobs are scarce’ increased by about 20 percentage points. This phenomenon, when a depressive market reduces employment opportunities and forces individuals into becoming entrepreneurs, is regarded as necessity-driven entrepreneurship (Gonzalez-Peña et al., 2018).

Figure 3. Reasons to start a business

Source: GEM Belarus 2019/2020 & 2021/2022. Note: Respondents could strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree with statements reflecting the reasons they were trying to start a business. Figure 3 provides the cumulative share of those who strongly agree and somewhat agree.

Keeping in mind that the unit of analysis in the GEM is on the individual and not the enterprise level, we can suggest a cautious hypothesis that the trend in entrepreneurship development in Belarus has changed from being pro-cyclical to countercyclical in the short term.

It is already obvious that the negative impact of the pandemic and political unrest on Belarusian businesses cannot be compared with the devastating effects of the Russian invasion of Ukraine. In this context, the countercyclical trend or, in other words, the readiness and willingness of Belarusians to become entrepreneurs against all odds, could be considered a good sign for the economy and society. However, such necessity-driven entrepreneurs are more focused on achieving a sufficient standard of living than on expansion and innovation. It is known that the growth and innovative orientations of businesses (product and process innovation, activity in technologically intensive sectors) are important predictors of technological change and total factor productivity (Erken et al, 2018). From this perspective, according to the GEM 2021/2022, Belarus is still doing relatively well in terms of impactful early-stage entrepreneurship (international and innovative orientation, growth expectations, and technological intensity). However, businesses with these characteristics are usually led by opportunity-driven entrepreneurs and are more sensitive to changes in the external environment. Therefore, the detrimental consequences of the Russian aggression against Ukraine (difficulties with payments and logistics, export/import restrictions, and tarnished reputation of Belarus) have already undermined the potential and sustainability of most such businesses and jeopardized the socioeconomic development of the country.

So, the answer to the question of whether Belarusian entrepreneurs will be able to reactivate the economy is rather ‘no’. Based on GEM 2021/2022 data, we argue that the augmented entrepreneurial activity rate will plausibly alleviate the problems of unemployment and income losses in the short- and medium-term, but may not have a strong and long-lasting effect on the economy as a whole.

Conclusion

The 2021 wave of the GEM survey has documented an increase in the share of the population involved in the different stages of the entrepreneurial process in Belarus. This, however, appears to be the outcome of the pandemic-related economic crisis, which manifests itself in income losses and layoffs. As a result, the crisis produced new necessity-driven entrepreneurs with vague prospects.

In this regard, policymakers should realize that stimulating self-employment and small-scale entrepreneurship may indeed be a temporary solution to unemployment issues. If this is the aim, the toolkit to support such businesses is well elaborated and accessible to the government (it includes educational & consulting services, easy access to finance, etc.).

As for impactful entrepreneurship, hardly anything can be done by the current government to retain innovative and international business in Belarus against the backdrop of the consequences and global reactions to the war in Ukraine.

References

  • Cowling, M., Liu, W., Ledger, A., & Zhang, N. (2015). “What really happens to small and medium sized enterprises in a global economic recession? UK evidence on sales and job dynamics”, International Small Business Journal, 33(5), 488-513.
  • Erken, H., Donselaar, P., & Thurik, R. (2018). “Total factor productivity and the role of entrepreneurship”. The Journal of Technology Transfer, 43(6), 1493-1521.
  • GEM Belarus 2019/2020, (2020). “Global Entrepreneurship Monitor Report GEM Belarus 2019/2020”.
  • GEM Belarus 2021/2022. (2022). “Global Entrepreneurship Monitor Report GEM Belarus 2021/2022”.
  • González-Pernía, J. L., Guerrero, M., Jung, A., & Pena-Legazkue, I. (2018). “Economic recession shake-out and entrepreneurship: Evidence from Spain”. BRQ Business Research Quarterly, 21(3), 153-167
  • Hill, S., Ionescu-Somers, A., Coduras, A., Guerrero, M., Roomi, M. A., Bosma, N., … & Shay, J. (2022). “Global Entrepreneurship Monitor 2021/2022 Global Report: Opportunity Amid Disruption”.
  • IMF. (2019). “Reassessing the Role of State-Owned Enterprises in Central, Eastern, and Southeastern Europe”, 19/11.
  • Marozau, R., Akulava, M., & Panasevich, V. (2021). “Did the Government Help Belarusian SMEs to Survive in 2020?” FREE Network Policy Brief Series.

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Did the Government Help Belarusian SMEs to Survive in 2020?

Posted on June 14, 2021 | Policy Brief

Enterprises During Pandemic representing Belarus

Capitalizing on the dataset obtained from five waves of the Covideconomy Project business survey, we explore how pandemic-related shocks and state economic policy responses influenced the performance of Belarusian small and medium enterprises (SMEs) in 2020. We find that Belarusian SMEs were left on their own with the COVID-related economic challenges, and only a small portion of enterprises could benefit from state support measures. Only two sectors (Manufacturing and Construction) derived advantages from soft loans provided to state-owned enterprises. The implementation of new, pandemic-adjusted business models did not result in an increase of revenues of Belarusian SMEs, at least not in the short run.

Small and Medium Enterprises During the Pandemic

According to OECD estimates (2020), the small and medium-sized enterprise (SME) sector has been more affected by the COVID-19 pandemic compared to large enterprises. Besides being highly concentrated in the most affected sectors, the main reasons for SMEs experiencing stronger COVID-related shocks are a lower level of cash cushion and limited access to external funds (Goodhart et al., 2021). Next, the stock of supplies and materials, as well as the range of suppliers, are usually lower for SMEs (WTO, 2020). This makes any price changes or abruptions more detrimental for them in comparison to large companies. Lastly, the availability of digital technologies and skills needed to implement new business formats appeared as an additional constraint for the SME sector during the pandemic. Indeed, per the World Bank’s business surveys, the most frequently mentioned effects of COVID-19 on SMEs in Central and Eastern European countries were a drop in sales, liquidity problems, limited access to finance, and breakdowns in supply. In this context, only 35% of SMEs in the region were able to adapt quickly to new conditions by introducing new business models such as online sales, delivery services, and remote work. At the same time, many SMEs in the region laid off employees, reduced wages, or initiated furloughs as alternatives to closing the business altogether.

In this regard, the SME support measures became an extremely important task for national governments to conduce to faster economic recovery and job creation. As a result, a wide range of monetary and non-monetary measures was implemented in various countries to support SMEs.

Internationally, direct support was provided in the form of wage subsidies, cash grants and transfers, tax holidays, reductions, or deferrals that could prevent unemployment growth. In addition, liquidity problems of SMEs were addressed by introducing rental fee deferral or reduction, repayment holidays as well as providing micro and short-term loans.

In many countries, specific measures were aimed to support the digitalization of SMEs (e.g., in China, France, Latvia, Italy, Slovenia, South Korea) by offering subsidies, financial support, training, and consulting services, developing e-commerce sales channels to respond to pandemic-related challenges (OECD, 2020).

Figure 1 demonstrates shares of SMEs in Central and Eastern European countries that benefitted from state support measures and SMEs’ perceived importance of these measures. Wage subsidies (65.1%) and direct cash transfers and grants (47.1%) appeared as the most commonly used measures, while fiscal exemption and reductions were regarded as the most important and relevant ones.

Concurrently, at the macro level, some governments eased requirements on banks’ emergency funds and reduced base rates to provide more and cheaper financial resources as loans for the enterprise sector.

Figure 1: Scope and importance of SME support measures

Source: World Bank data on Belarus, Russia, Poland, Estonia, Latvia, Lithuania, Georgia, Moldova, Slovakia, Czech Republic, Bulgaria, Romania, Hungary.

In general, the scope and target groups of the support programs depended on financial resources at the disposal of governments, access to capital markets, macroeconomic conditions (public debt, exchange rates, unemployment rates), as well as the structure of the economy.

In this brief, we discuss how the macroeconomic environment and the Belarusian government’s policy reaction to the pandemic affected revenues of Belarusian SMEs in 2020.

The Belarusian Economy in 2020

The official statistics reported outstanding results of the Belarusian economy, despite it being expected to be hit harder than other countries in the region. The COVID-19 pandemic-related shocks were aggravated in Belarus by endemic ones: the early-2020 oil-supply dispute with Russia, the sociopolitical crisis that broke out after the presidential elections in August (Bornukova et al., 2021), and the concomitant sharp devaluation of the Belarusian ruble (22.59% to US dollar in 2020) in March and August. Against this backdrop, the 0.9% decrease in GDP, 4.6% increase in real disposable incomes, and stable unemployment rate (at 4.0%) together look like an economic miracle. Some of the rationales behind these figures include the absence of lockdowns and substantial mobility restrictions throughout the year, as well as easy access to bank loans for state-owned enterprises (SOEs) that faced an export shock. At the same time, ad-hoc sampled population and business surveys documented income reductions of Belarusians and a substantial decrease in business revenues in many sectors (Covideconomy project, 2021). Figure 2 displays the shares of SMEs in different sectors whose revenues dropped by more than 20% in the month before being surveyed.

Figure 2. Share of SMEs with loss of revenue >20%  

Source: Own elaboration based on five ways of business surveys

The Belarusian government was substantially restricted in terms of financial resources as well as fiscal and external loan opportunities to extensively support businesses suffering from the COVID-related economic crisis. According to experts’ estimations, Belarus lags behind other Eurasian Economic Union members (Russia, Armenia, Kazakhstan, Kyrgyzstan) in terms of the estimated share of GDP spent on crisis response measures – 1.5% (Russian Academy of Foreign Trade & Research Institute of VEB, 2020). While the most suffering sectors (trade, transportation, hotels, restaurants, tourism, education, leisure, sport, etc.) could benefit from the deferral of profit, real estate and land taxes, as well as rental fees till the end of 2020, obtaining any type of support appeared bureaucratically challenging and imposed exigent obligations for the future. Overall, the support was perceived as negligible and far below expectations both in terms of financial resources saved by businesses and coverage. Thus, in May-October 2020, about 50 thousand businesses (incl. sole proprietors) received cumulative support for a total amount of $26 Million or $536 per business (National Center of Legal Information of the Republic of Belarus, 2020). According to the Covideconomy project, in May-July, less than 5% of SMEs reported getting support from the state.

What Affected Belarusian SMEs?

Motivated by the specific reaction of the Belarusian government and its very limited support to SMEs, we explore what enterprise- and country-level factors affected SME revenues across industries during the pandemic. In pursuit of this objective, we use data obtained from five waves of the business survey conducted within the Covideconomy project (2020) on 359 SMEs amounting to 947 observations, and perform a regression analysis with a set of ordered logistic models. Particularly, we test whether the (i) self-isolation of population, (ii) currency devaluation, (iii) volume of loans provided to SOEs, and (iv) new business models implemented by Belarusian SMEs impacted their revenues.

These hypotheses are based on the following arguments:

  1. In the absence of restrictive measures and lockdowns, entrepreneurs and citizens made conscious decisions about self-isolation and remote work. To minimize personal contact, many people reduced the number of visits to public places as well as various group activities. Such responsible behavior could hurt business income, primarily in the areas of catering, hotels, entertainment, transport, and consumer services, in which SMEs are widely represented.
  2. The sharp devaluation of the Belarusian ruble is, and has traditionally been, a significant problem for Belarusian businesses. The rise in prices of imported goods and services, inflation, and the fall in household incomes in dollar terms harm domestic demand, leading to a drop in sales in many sectors. The exceptions could be export-oriented enterprises, which mostly use materials and supplies produced in Belarus, as well as enterprises that are suppliers and contractors of exporters.
  3. To minimize the impact of the pandemic-related shocks, the Belarusian government continued its habitual practice of providing soft loans for SOEs to maintain their production volumes and pay wages. Arguably, this could bolster demand for SMEs’ goods and services from the side of SOEs’ employees and prevent a deeper recession. In addition, SMEs that were suppliers and contractors of SOEs could also benefit from this policy measure.
  4. The pandemic significantly accelerated SMEs’ processes of finding and realizing opportunities to develop. This became key in the survival of many businesses. We thus expect that the implementation of new business models could have had a positive impact on revenues of SMEs.

In our models, we use the size of SMEs, location in the capital city, and whether a firm belongs to one of the most suffering sectors (HoReCa, Transportation, Leisure & Sport) as control variables. To capture the effect of factors across different sectors, we use interaction terms between the aforementioned factors and dummies indicating different sectors.

The results of the regression analysis (summarized in a stylized way in Table 1) demonstrate that the impact of the selected factors is not consistent across sectors and that none of the factors appear significant when considering the entire sample of SMEs.

Table 1. Impact on SMEs’ revenues

Source: Own estimates based on 947 observations from 359 SMEs.

Not surprisingly, self-isolation behavior negatively affects only the HoReCa and Leisure & Sports sectors. Currency devaluation does not significantly influence the revenues of SMEs. Only the ICT sector, which is export-oriented and does not depend on imported materials, easily adapted to remote work and increased demand for IT-related services and experienced a positive shock. The state policy that provided soft loans to SOEs helped SMEs in the manufacturing and construction sectors that are, supposedly, contractors and suppliers of SOEs. The implementation of new business models did not result in an increase in the revenues of Belarusian SMEs, at least not in the short run. A possible explanation for this finding could be that firms responded by adopting new business models only if they experienced a very steep fall in revenues.

As for the control variables, we find that larger enterprises better adapted to the crisis and their decrease in sales appear smaller. Interestingly, SMEs located in the capital city –  Minsk – suffered more from the crisis in 2020, likely, due to a higher concentration of SMEs in the most affected sectors and a quicker reaction of citizens to economic and political shocks.

Conclusion

Based on our analysis, we can deduce that Belarusian SMEs were left on their own with the COVID-related economic challenges. Only a small share of enterprises could benefit from the state support measures and only two sectors (Manufacturing and Construction) derived advantages from soft loans provided to SOEs.

At the same time, the absence of lockdowns and other restrictions – the laissez-faire approach (Bornukova et al., 2021) – propped up most of the sectors except those that suffered from voluntary self-isolation of customers (HoReCa, Leisure, Sport, Beauty).

The ongoing crisis substantially changes the economic landscape, management practices, and business models of SMEs. The most flexible, competitive, and proactive businesses have been capable of identifying and exploiting the emerged opportunities. From this point of view, Belarusian businesses and entrepreneurs have outstanding experience in surviving and developing during recurrent crises (Marozau et al., 2020). This must be an important pre-condition for the future economic recovery of Belarus.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Resource Discoveries, FDI Bonanzas and Local Multipliers: Evidence from Mozambique

Posted on November 5, 2018 | Policy Brief

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Giant oil and gas discoveries in developing countries trigger FDI bonanzas. Across countries, it is shown that in the 2 years following a discovery, the creation of FDI jobs increases by 54% through the establishment of new projects in non-resource sectors such as manufacturing, retail, business services and construction. Using Mozambique’s gas driven FDI bonanza as a case study we show that the local job multiplier of FDI projects in Mozambique is large and results in 4.4 to 6.5 additional jobs, half of which are informal.

Natural Resources, FDI Job Multiplier and Economic Development

Large resource wealth has for several decades been associated with a curse, slowing economic growth in resource-rich developing countries (Venables, 2016). More recently, this wisdom has been questioned by several studies. Arezki et al. (2017) point out that giant discoveries trigger short-run economic booms before windfalls from resources start pouring in. And Smith (2017) provides evidence for a positive relationship between resource discoveries and GDP per capita across countries, which persists in the long term.

In a new paper (Toews and Vézina, 2018) we contribute to this research by showing that giant oil and gas discoveries in developing countries trigger foreign direct investment (FDI) bonanzas in non-extraction sectors. FDI has long been considered a key part of economic development since it is associated with transfers of technology, skills, higher wages, and with backward and forward linkages with local firms (Hirschman, 1957; Javorcik, 2015). Using Mozambique, where a giant offshore gas discovery has been made in 2009, as a case study,  we estimate the local multiplier of FDI projects. We find that the FDI job multiplier in Mozambique is large, highlighting the job creation potential of FDI in developing countries.

Resource Discoveries and FDI Bonanzas

In our study we focus on jobs created by FDI bonanzas triggered by resource discoveries. Multinationals might invest in countries being blessed by giant discoveries for a variety of reasons before production starts. First, they might expect to benefit from the decisions of oil and gas companies to increase investment in local infrastructure and to increase demand for local services provided by law firms and environmental consultancies. Second, multinationals may also expect governments and consumers to bring forward expenditure and investment by borrowing. Finally, multinationals might invest since particularly large discoveries have the potential to operate as a signal leading to a coordinated investment by a large number of multinationals from a variety of industries and countries.

Using data from fDi Markets we show that, indeed, FDI flows into non-extraction sectors following a discovery. FDI increases across sectors and by doing so creates jobs in industries such as manufacturing, retail, business services and construction. Using Mozambique as a case study we show that following the gas discovery, multinationals decided to invest in Mozambique triggering job creation in non-extraction FDI to skyrocket (see Figure 1).

Figure 1. FDI Bonanza in Mozambique

Source: Author’s calculations using fDiMarkets data.

FDI Job Multiplier

Using the FDI bonanza in Mozambique as a natural experiment, we proceed by estimating the FDI job multiplier for Mozambique. The concept of the local job multiplier boils down to the idea that every time a job is created by attracting a new business, additional jobs are created in the same locality. In our case, FDI jobs are expected to have a multiplier effect due to two distinct channels. Newly created and well paid FDI jobs are likely to increase local income and in turn the demand for local goods and services (Moretti, 2010). Additionally, backward and forward linkages between multinationals and local firms increase the demand for local goods and services (Javorcik, 2004).

Using concurrent waves of household surveys and firm censuses we estimate the local FDI multiplier for Mozambique to be large. In particular, we find that every additional FDI job results in 4.4 to 6.5 additional local jobs. Due to the combined use of household survey and the firm census we are also able to conclude that only half of these jobs are created in the formal sector, while the other half of the jobs are created informally.

Conclusion

Our results suggest that giant oil and gas discoveries in developing countries lead to simultaneous foreign direct investment in various sectors including manufacturing. Our results also highlight the job creation potential of FDI projects in developing countries. Jointly, our results imply that giant discoveries do have the potential to trigger extraordinary employment booms and, thus, provide a window of opportunity for a growth takeoff in developing countries.

References

  • Arezki, R., V. A. Ramey, and L. Sheng (2017): “News Shocks in Open Economies: Evidence from Giant Oil Discoveries,” The Quarterly Journal of Economics, 132, 103.
  • Hirschman, A. O. (1957): “Investment Policies and “Dualism” in Underdeveloped Countries,” The American Economic Review, 47, 550 – 570.
  • Javorcik, B. S. (2004): “Does Foreign Direct Investment Increase the Productivity of Domestic Firms? In Search of Spillovers Through Backward Linkages,” American Economic Review, 94, 605 – 627.
  • Javorcik, B. S. (2015): “Does FDI Bring Good Jobs to Host Countries?” World Bank Research Observer, 30, 74 – 94.
  • Moretti, E. (2010): “Local Multipliers,” American Economic Review, 100, 373 – 377.
  • Smith, Brock. “The resource curse exorcised: Evidence from a panel of countries.” Journal of Development Economics: 116 (2015): 57-73.
  • Toews and Vézina, (2018): “Resource discoveries, FDI bonanzas and local multipliers: An illustration from Mozambique” Working Paper.
  • Venables, A. J. (2016): “Using Natural Resources for Development: Why Has It Proven So Difficult?” Journal of Economic Perspectives, 30, 161 – 84.

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

The Russian economy under Putin (so far)

Posted on March 15, 2018 | Policy Brief

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Russians are heading to the polling booths on March 18, but where will the economy head after Putin has been elected president again? This brief provides an overview of the economic progress Russia has made since 2000 as well as an economic scorecard of Putin’s first three tenures in the Kremlin and uses this to discuss what can be expected for the coming six years. Although significant growth has been achieved since 2000, all of this came in the first two tenures of Putin in the Kremlin on the back of increasing oil prices. In order to generate growth in his upcoming presidential term, Putin and his team will need to address the significant needs for reforms in the institutions that form the basis for modern market economies. Otherwise, Russia will continue to be hostage to the whims of the international oil market and eventually lose most of its exports and government revenues as the world moves towards a carbon free future. Perhaps this is beyond the scope of Putin as president, but not beyond the horizon of young Russians that will be casting their votes on Sunday and in future elections.

Let’s assume that Putin will be elected president again on March 18 (for once a very realistic assumption made by an economist). What will this mean for the Russian economy in the coming six years given what happened during his previous and current tenures in the Kremlin? To assess the future as well as to understand Putin’s power and popularity, this brief starts by looking back at the economic developments in Russia since Putin first became president.

Although many different factors enter the power and popularity function of Putin, economic developments have a special role in providing the budget constrain within which the president can operate. A higher income level means more resources to devote to any particular sector, project, voting group or power base. This is not unique to Russia, but sometimes forgotten in discussions about Russia, that often instead only focus on military power or control of the security apparatus and media. These are of course highly relevant dimensions to understand power and popularity in Russia, but so is economic development, particularly in the longer run.

Russia’s economy in the world

The economic greatness and progress of a country is usually assessed in terms of the size of the economy, how much growth that has been generated, and how well off the citizens are relative to the citizens of other countries. So, by our common indicator gross domestic product (GDP), has Russia become a greater and more powerful country since Putin first became president? Table 1 shows two things, the absolute level of GDP measured in USD at market exchange rates and the rank this gives a country in a sample of 192 countries in the world that the IMF collects data on (this brief is too short for a long discussion of the most relevant GDP measure, but GDP at market exchange rates makes sense when comparing the economic strength of countries in a global context, Becker 2017 provides a discussion of alternative measures as well). When Putin become president for the first time in 2000, the value of domestic production was estimated at $279 billion, which implied a 19th place in the world rankings of countries’ GDP. In 2016, almost three presidential terms of Putin later, Russia’s GDP had increased by 4½ times to $1281 billion and its ranking improved to 12th place in the world. This clearly is an impressive record by most standards. However, the Russian economy is still the smallest economy of the BRIC countries and corresponds to only 7 percent of the US economy in 2016. In other words, impressive progress by Russia but the country is (still) not a global superpower in the economic arena.

Table 1. Russia in the world (GDP in USD bn)

Source: IMF (2017)

For the average Russian, income per capita is a measure more closely connected to consumption and investment opportunities or ‘welfare’. Progress in this area is also more likely to affect how individuals assess the performance of its political leaders. Of course, progress in terms of overall GDP and GDP per capita is closely linked unless something unusual is happening to population growth. Therefore, it is not surprising that GDP per capita also increased by around 4½ times between 2000 and 2016 (Table 2). This is the first order effect of the economic development in Russia, but in addition, citizens of Russia moved up from a world income rank of 92nd to 71st. This has implications when Russian’s compare themselves with other countries and can in itself provide a boost of national pride.

It also directly affects opportunities and status for Russians visiting other countries. Being at place 71 may not be fully satisfactory to many, but we should remember that due to the rather uneven income distribution in Russia, many of the people that travel abroad are far higher up on the global income ranking than what this table indicate. Nevertheless, Russia is far behind the Western and Asian high-income countries in terms of GDP per capita. And although the picture would look less severe if purchasing power parity measures are used, the basic message is the same; Russia has still a lot of catching up to do before its (average) citizens enjoy the economic standards of high-income countries.

Table 2. Russian’s in the world (GDP/capita)

Source: IMF (2017)

The macro scorecard of Putin

So what generated the impressive 4½ times increase in income in USD terms from 2000 to 2016 and can we expect high growth during Putin’s next six years in office? The short answer to the first question is the rise in international oil prices and to the second question, we don’t know. Table 3 provides a comparison of different economic indicators for Putin’s two first terms in office compared with his current term (where GDP data ends in 2016 so the sample is cut short by a year). It is evident that the impressive growth over the full period is entirely due to the strong growth performance in the first two presidential tenures. Rather than generating growth in the most recent period, the economy has shrunk. This is explained by the evolution of international oil prices, which quadrupled in the first eight years and instead halved in the more recent period. These swings in oil prices have also been accompanied by significant shifts in foreign exchange reserves, the exchange rate, and the value of the stock market.

In Becker (2017) I discuss in more detail the importance of international oil prices in understanding the macro economic development in Russia. In particular, it is important to note that it is changes in oil prices that correlate with GDP growth and other macro variables and that the problems with predicting oil prices makes it very hard to make good predictions of Russian growth.

Table 3. A macro scorecard of Putin in office

Source: Becker (forthcoming)

Policy conclusions

To break the oil dependence and take control of the economic future of Russia, the president will need to implement serious institutional reforms that constitute the basis for a modern, well-functioning market economy in his next term. Otherwise, Russia will continue to be hostage to unpredictable swing in international oil prices and nobody—including the president, the central bank, the IMF and financial markets—will be able to predict where the Russian economy is heading in the next couple of years.

Figure 1. Reforms (still) needed

Source: World Bank (2017)

In the longer run, the prediction is much easier. With the world moving towards a green economy, the price of oil will see a structural decline that will rob Russia (and other oil exporters) of most of its export and government revenues. The reforms which basically every economist agree are needed are related to market institutions and Figure 1 provides a clear illustration of key reform areas. The progress during Putin’s years in office has been modest at best. Swedish institutions in 2016 have been added to the figure as a comparison and it is clear that the institutional gap between Russia and Sweden is significant. Of course, all countries are different, but Russian policy makers that are interested in reforming its economy are most welcome to Sweden for a discussion of what we have done to build our institutions.

References

  • Becker, T. (2017). ‘Macroeconomic Challenges’, in Rosefielde, S., Kuboniwa, M., Mizobata, S. and Haba K. (eds.) The Unwinding of the Globalist Dream: EU, Russia and China, Singapore: World Scientific Publishing.
  • Becker, T. (forthcoming), ‘Russia’s economy under Putin and its impact on the CIS region’, Chapter 2 in T. Becker and S. Oxenstierna (eds.) Perspectives on the Russian Economy under Putin, London: Routledge.
  • IMF (2017), World Economic Outlook database, April 2017 edition available at http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx
  • World Bank (2017), Worldwide Governance Indicators (WGI), 2017 update available at http://info.worldbank.org/governance/wgi/index.aspx#home

Trust and Economic Reforms

Posted on May 19, 2014 | Policy Brief

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This brief discusses the importance of trust in economic development. In the aftermath of the 2008 financial crisis, many countries experienced a decline in the level of both general trust and trust and confidence in the government and market institutions. Trust is important for economic growth as it facilitates economic transactions by reducing uncertainty and risk. A lack of trust in the government hinders implementation of structural reforms needed for economic development. Hence, policies aimed at rebuilding trust in the government and institutions become especially important for countries like Ukraine.

Recent events in Ukraine have highlighted an acute crisis of trust in the Ukrainian society (such as trust in the government, politicians, institutions, etc.). Over the past two decades, in the absence of a fair and transparent legal and court system, Ukrainians have become accustomed to relying on informal and often corrupt ways of living and doing business. According to a poll conducted in December 2013, less than 20 percent of the Ukrainian population said that they trust the government, police and courts.

A low level of trust in society is not, however, limited to Ukraine; this problem is also pronounced in many other parts of the world. According to the 2012 Edelman Trust Barometer survey, the general level of trust in most countries surveyed decreased compared to 2011. The most notable decline was in Brazil (36.3%), Japan (33.3%) and Spain (27.5%). These countries also experienced large drops in the level of confidence in the government: Brazil went down by 62.4%, Japan by 51% and Spain by 53.5%. According to the OECD report, generally, less than half (40%) of the citizens trust their government (OECD, 2013).

General trust is important for economic life as it reduces uncertainty and costs associated with economic transactions. Trust affects the functioning of businesses, financial markets, and government intuitions. The level of general trust varies significantly across countries (see Figure 1). While only 3.8 percent of people in Trinidad and Tobago fully trust most people, the Scandinavian countries’ share of trusting people exceeds 60 percent (Algan and Cahuc, 2013).

Economists have in their studies repeatedly appealed to the problem of trust because there are several channels through which trust may influence economic development. First, trust creates favorable conditions for long-term investment and financial market development (Algan and Cahuc, 2013). Second, a higher level of trust in various regulatory authorities increases the level of compliance with the rules and regulations if citizens believe in the fairness of such rules and regulations (Murthy, 2004). In Tabellini (2010), the level of economic development (measured by GDP per capita) of different regions of the EU member countries is compared to their level of trust (defined as in the Figure 1) and respect (defined as the proportion of people who mentioned the quality “tolerance and respect for other people” as being important). Using data from the World Value Survey rounds conducted in the 1990s, he shows that regions with a high level of trust and respect are also the regions that are the most economically developed.

In his Master thesis, the graduate of the Kyiv School of Economics Oleksii Khodenko (Khodenko 2013) analyzed the relationship between the level of trust in the government and the attitude towards market economy (in particular, the attitude towards competition and private property). For this purpose, he used data from the World Values Survey and the European Values Survey. His results have different implications for developed and less developed countries. While a lack of trust in the government in developed countries is transformed into a desire to see more market mechanisms in the economy, this mistrust of the government in developing countries (including Ukraine) undermines the faith in the entire market economy.

Khodenko’s results highlight important policy implications for transition countries: people who grew up in a centrally planned economy tend to underestimate the benefits of the free market and, therefore, only puts confidence in the government and the state as a whole to achieve the development of market mechanisms. Thus a lack of trust hinders, or even prevents implementation of structural economic reforms, which are often “painful” for some groups or for society as a whole. In countries with a low level of trust, the long-term promise of the implemented reforms to improve the lives of people is not perceived as credible. Instead of being viewed by the general public as a today’s sacrifice in the name of future prosperity, they are rather viewed as a deadweight loss (Györffy, 2013).

Figure 1. The Level of Trust in the World
KEI_May2014_PB_Trust and economic reforms
Source: Yann and Cahuc (2013), Figure 1.
Note: Trust is computed as the country average from responses to the trust question in the five waves of the World Values Survey (1981-2008), the four waves of the European Values Survey (1981-2008) and the third wave of the Afrobarometer (2005). The question regarding trust asks: “Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?” Trust is equal to 1 if the respondent answers ”Most people can be trusted” and 0 otherwise.

Moreover, low levels of trust affect all types of structural reforms. Elgin and Garcia (2012) show that the effect of the tax reform on the economy can significantly differ depending on the level of trust in the government; under low levels of trust the announced tax cuts do not lead to exit from the informal sector.

The question is then how to revive or rebuild trust? Knack and Zak (2003) argue that the most efficient policies for building general trust are policies that (1) reduce income inequality since people in countries with more equal income distribution tend to have higher levels of interpersonal trust, and (2) strengthen civil society to increase government accountability. Income inequality often resulting from unequal opportunities can be reduced via increases in educational attainment and income redistribution programs. The presence of a strong civil society with free press ensures that the government is accountable and responsive to its citizens. A government needs to be reliable, open and transparent to effectively address citizens’ demands (OECD, 2013). All these policies cannot be implemented without a fair legal system that guarantees equal treatment of all citizens.

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References

  • Algan, Y. and P. Cahuc (2013) “Trust, Growth and Well-being: New Evidence and Policy Implications”, IZA Discussion Paper No. 7464
  • Elgin, C. and M. Solis-Garcia (2012), “Public Trust, Taxes and the Informal Sector”, Journal Review of Social, Economic and Administrative Studies, 26(1), pp. 27-44
  • Györffy, D. (2013), Institutional Trust and Economic Policy: Lessons from the History of the Euro, Central European University Press
  • Knack, S. and P.J. Zak (2003), “Building Trust: Public Policy, Interpersonal Trust, and Economic Development”, Supreme Court Economic Review, 10, pp.91-107
  • Khodenko, Oleksii (2013). How Does Confidence in the State Authorities Shape Pro-market Attitudes?
  • Murthy, K. (2004), “The Role of Trust in Nurturing Compliance: A Study of Accused Tax Avoiders”, Centre for Tax System Integrity, Working paper No49
  • OECD (2013), Government at a Glance 2013, OECD Publishing.
  • Tabellini, G. (2010), “Culture and Institutions: Economic Development in the Regions of
  • Europe”, Journal of the European Economic Association, 8(4), pp. 677–71