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Economic and Social Context of Domestic Violence: Research Shared at the 2022 FROGEE Conference
This brief summarizes the research papers presented at the 2022 FROGEE conference “Economic and Social Context of Domestic Violence”, which took place on May 11, 2022. It was organized by the Stockholm Institute of Transition Economics (SITE) together with the Centre for Economic Analysis (CenEA) and the FREE Network. Two additional briefs related to the conference are published on the FREE policy briefs website – a brief on gender-based violence in conflict based on the panel discussion, and another sharing preliminary results from the recent FROGEE survey.
While the concerns about domestic violence (DV) and intimate partner violence (IPV) have been gaining prominence since the start of the COVID-19 pandemic, they were further exacerbated by the devastating events happening in Ukraine. Times of crisis or conflict makes the issue more severe, however, gender-based violence is sadly prevalent at normal times too, and a major portion of it is DV and IPV. Limiting violence towards women requires understanding the determinants of DV and IPV and the channels through which they take effect. With this in mind, the Stockholm Institute of Transition Economics (SITE) together with the Centre for Economic Analysis (CenEA) and the FREE Network invited researchers to present their work relating to the economic and social context of domestic violence. This brief provides an account of what was shared at the conference.
Prevention of Domestic Violence: What Works and What Doesn’t?
Three presented studies geared toward evaluating policies aimed to limit violence against women.
Dick Durevall shared his findings on IPV and national policy programs in Colombia, focusing on the laws and policies implemented based on the UN campaign “UNiTE to End Violence Against Women” between 2010 and 2015. To evaluate the effect of these policies, he adopts a differences-in-differences design and compares provinces that had a gender policy before this renewed effort with those that did not. This builds on the idea that provinces that had an IPV policy strategy before UN recommendations were adopted are more efficient in implementing new such policies. It is found that self-reported physical violence falls from 20% to 16% between 2010 and 2015 in provinces that had IPV policies while this number remained at 18% in those that did not. While sexual violence decreased in both groups, provinces with IPV policies experienced a stronger reduction.
Accurate reporting is a key issue when it comes to IPV since it makes up the foundation for designing effective policy. Due to long-lasting and tiresome judicial procedures, threats, social barriers, or emotional costs, victims might choose not to report. Looking at the introduction of specialized IPV courts in Spain, Marta Martínez-Matute presented her paper on how institutions shape reporting. Bestowed with specialized staff, victim-oriented resources, and a swifter judicial process, these courts are specifically designed to deal with IPV cases. Martínez-Matute and co-author investigate if these resources make women more prone to report IPV by exploiting the sequential rollout of specialized courts. They use yearly court-level data on individual IPV cases between 2005 and 2018 in a staggered difference-in-differences framework with matched control districts. The results show that the introduction of an IPV court in a judicial district reduces the length of the judiciary process by 61% and increases the reported number of IPV cases by 22%. Ensuring that this increase is not fully driven by a rise in false reports, it is found that the share of dismissed IPV cases remains unchanged. Further, it is shown that the increase is driven by less severe IPV cases and not aggravated IPV offenses or homicides.
A distinctive feature of DV crimes is that there is a high degree of recidivism, with many women experiencing repeated violence from the same partner. However, little is known about how police should respond to such crimes to ensure safety to those victimized. From one perspective police arrests deter repeated DV crimes since they incapacitate perpetrators and allow police to investigate while offering safety to victims. However, some argue that this safety is merely temporary and that DV arrests might trigger offenders to retaliate against victims, leading to increased long-term DV. Against this reasoning, Victoria Endl-Geyer presented a study on the relationship between police arrests and DV dynamics in the UK. It uses highly granular administrative data on the population of DV incidents in the West Midlands which allows the researchers to observe the detailed information on the incidents’ timing and location as well as on police officers and their crime scene responses. It adopts an instrumental variables approach using the dispatch team’s previous propensity to arrest (measured as the weighted average arrest rate of officers in the team) as an instrument. The results provide evidence consistent with a deterrence effect. While regular OLS estimates show an insignificant impact, the IV results indicate that an on-scene arrest decreases repeat DV incidents by 25-26 percentage points. They find that the effect is the same when restricting the sample to incidents reported by a third party, supporting that this effect is not driven by a change in reporting behavior.
Factors of Domestic Violence and its Mechanisms
Other studies presented at the conference focused less on policy assessment and more on identifying the determinants of IPV and DV.
Losing or obtaining a job causes a shock in the intra-relationship dynamics and changes the economic power balance between spouses. Deniz Sanin presented her paper on the DV effect of women’s employment in the context of Rwanda. Following the government-initiated National Coffee Strategy in 2002, the number of coffee mills in Rwanda increased from 5 to 213 over the course of ten years. This natural experiment allows studying the effect of having a paid job as it captures the shift from unpaid labor on a family farm to paid work on a mill, keeping job-related skills constant. Using survey data on both DV and labor market outcomes along with administrative data on DV hospitalizations, the study adopts a staggered difference-in-differences strategy and compares women before and after mill opening as well as within and outside of the catchment area (a buffer zone surrounding the mill). The results show that upon mill opening, the probability of working for cash increases and that of self-reporting domestic violence in the past 12 months decreases by 26% (relative to the baseline of 0.35). During the harvest months, the only period of the year in which the mills operate, hospitals are significantly less likely to admit DV patients compared to the month before the harvest season, suggesting that the initial results are not driven by reporting bias. Looking at the mechanisms, she finds evidence supporting an increased bargaining power explanation – women in catchment areas who are exposed to mill opening are more likely to have a bigger say in household decisions such as larger household purchases and contraception usage. Increases in husbands’ earnings and decreased exposure are also ruled out as possible channels since a decline in DV is also found among spouses where the husband works in a different occupation with no change in earnings.
Rather than studying the impact of women’s employment status, Cristina Clerici shared a related paper that focuses on male unemployment. To investigate its effect on IPV, the study exploits the exogenous shock to employment caused by COVID-19 containment measures in Uganda. The authors collect individual-level data via phone surveys on the incidence of IPV among food vendors, including information on husbands’ sector of employment. To identify a causal DV effect of male employment exit, the authors distinguish between two groups of women with similar pre-lockdown experiences of abuse: those with spouses employed in sectors where operations were halted by COVID-19 lockdowns (construction workers, taxi drivers, etc.) and those with spouses who were unaffected (food vendors, farmers, etc.). The results show that male unemployment increases the probability of experiencing physical violence by 4.9 percentage points, corresponding to a 45% increase relative to the average likelihood. The effect cannot be explained by increased exposure (the man being more at home) – affected and unaffected women spend on average an equal number of nights in the market, which could be used as a coping mechanism. This suggests it is the change in unemployment status itself that drives the increase in DV.
While most of the literature on domestic abuse has documented that its drivers often come from changing life conditions of the victim or perpetrator, there is broad anecdotal evidence that exogenous events can lead to exacerbations in domestic violence as well. Ria Ivandic presented her paper that documents a causal link between major football games and domestic violence in England. The authors use a dataset on the universe of calls and crimes in the Greater Manchester area. The data provides a time series on the incidence of different types of domestic abuse with information on the timing, relationship to the accused, and individual characteristics of the victim and perpetrator, including whether the perpetrator was under the influence of alcohol at the time of the incident. They adopt an event study approach focusing on the hours surrounding a game and document a substitution effect in that the two-hour duration of a football game is associated with a 5% decline in DV incidents. However, following the game, the initial decrease is offset as DV incidents start increasing and culminate after 10-12 hours, eventually leading to an aggregate positive effect which constitutes a 2.8% hourly increase on days when games are played.
The authors argue that alcohol consumption, rather than emotions, is the main mechanism through which domestic violence is affected by sporting events. Supporting this hypothesis, they first find that the outcome of the game or the associated element of surprise (measured using the ex-ante probability of winning a game through betting markets) does not affect the probability of DV occurring. Second, they show that the increase in DV following a game is solely driven by an increase in alcohol-related DV incidents, while those committed by non-alcoholized men remain constant. Further strengthening this finding, it is shown that for games scheduled early in the day, when perpetrators can start drinking sooner and continue throughout the day, they find a significant increase in DV incidents committed by alcoholized perpetrators while this is not the case for late-scheduled games.
The Role of Women’s Empowerment
In the literature on gender-based violence, there is a common disposition to think about women’s empowerment as a central element of DV mitigation. However, theories point in opposite directions making the effect of women’s economic empowerment rather unclear. On one end of the spectrum, there are bargaining theories indicating that an increase in women’s employment opportunities or income should have a negative effect on DV by creating outside options or increasing the bargaining power in a relationship. At the other end, there are backslash theories arguing that enhancing women’s financial empowerment may further exacerbate violence by undermining the role of the breadwinner, triggering male partners to retaliate with the use of violence in order to restore the power balance. Going in the same direction, theories of instrumental violence point towards that the male partner might also use violence to extract resources.
In her keynote lecture, Bilge Erten outlined the evidence relating to DV and women’s empowerment and discussed to what extent and in which contexts these theories are supported.
The evidence of a positive or negative effect of empowerment may depend on which aspect of it is studied. Education is seen as an important one because it has the potential to raise women’s self-awareness of IPV, increase the likelihood of matching with a well-educated partner (which is negatively correlated to abusive behavior), and improve labor market outcomes. Although evidence is scarce in this area, Erten shared her own findings on the causal effect of education reform on IPV in Turkey. In line with instrumental violence theories, it is found that, while women in cohorts affected by the reform performed better in the labor market, they experienced more psychological violence and financial control behavior, and there was no sign of an effect on DV attitudes, partner-match quality or marriage decisions.
What we know about women’s empowerment and DV is also different across countries. When it comes to the effect of employment, findings from developed countries are generally consistent with bargaining theory explanations while what is found in the developing world is more mixed. This is also the case for studies on unilateral divorce laws – while a negative effect on IPV has been documented in the United States, a positive effect of these laws is found in Mexico.
Assessing the literature on the income effect leads to a somewhat ambiguous verdict too. Although generally, most studies confirm that overall violence declines with women’s income, there is often heterogeneity in the effect. It has for instance been found that the sign of the income effect from cash transfers on DV changes from negative to positive as the size of the transfer increases.
Finally, Erten provided some important policy considerations. There is evidently a widespread backlash problem that can arise after a policy intervention of the types discussed above. Policymakers need to think more about monitoring and protecting victims from more violence when implementing such a policy. Further research assessing post-intervention is also needed to identify interventions that are the most effective in minimizing domestic violence. In particular, a change in broad social norms around gender roles should be a desirable outcome, to the effect that a new, improved status of women in society and in the household becomes more culturally acceptable and needs not lead to backlash. In the case of expressive violence (that is not a rational, calculated response but rather a compulsion in the heat of the moment), mental health interventions should also be considered.
Concluding Remarks
As highlighted by the 2022 FROGEE conference, domestic violence not only has been put in the spotlight following the pandemic or the ongoing conflict in Ukraine, but is widespread across the globe in regular conditions too. The mixed findings shared at the conference suggested that policies limiting gender-based violence should be designed with respect to the cultural and social setting where they are to be implemented as the heterogeneity is very high across contexts. Although research has come a long way, the conference stressed that there is much more to be done, in terms of not only knowledge but also the political will and commitment to seriously address the issue of gender-based violence.
The presentations held at the conference can be viewed at this link and a separate policy brief based on the panel discussion on gender-based violence in times of conflict can be found here.
List of Speakers
- Cristina Clerici, Ph.D. Student in Economics at the Stockholm School of Economics.
- Dick Durevall, Professor at the Department of Economics, University of Gothenburg.
- Victoria Endl-Geyer, Doctoral Student at the IFO Institute.
- Bilge Erten, Associate Professor of Economics and International Affairs at the Institute for Health Equity and Social Justice Research at Northeastern University.
- Ria Ivandic, Associate Researcher at the London School of Economics.
- Marta Martínez-Matute, Assistant Professor at the Department of Economic Analysis at Universidad Autónoma de Madrid.
- Deniz Sanin, Ph.D. Candidate at Georgetown University.
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.
Gender-Based Violence in Conflict
The eruption of war exposes women to increased gender-based violence, in the immediate conflict area as well as in the countries where they seek refuge. Acknowledging the specific conflict-related risks that women face is important, in order to target interventions, especially considering that the actors that sit at peace negotiation tables are predominantly or exclusively men. In this policy brief, we discuss the implications of conflict for gender-based violence, with a special focus on the ongoing war in Ukraine. We also outline some policy interventions that might help mitigate the risks that women face, holding those responsible to account, and building a more gender-equal society from the reconstruction efforts. Our discussion draws from existing academic literature and inputs from the special panel session on conflict during the FROGEE conference “Economic and Social Context of Domestic Violence”.
Gender-Based Violence During Conflicts
During war, as in peacetime, women are exposed to different forms of violence, and to a different extent, as compared to men. In other words, there are gender-specific aspects of conflict-related violence, both in immediate conflict areas and in the places where affected populations might seek refuge.
One form of violence against women in conflict areas is sexual violence and rapes perpetrated by combatants. Scholars and policy analysts tend to portray this violence as a weapon of war (Eriksson and Stern, 2013), meaning that it is a way of humiliating and demoralizing the enemy as individuals and as communities. Differently put, the narrative that portrays sexual violence as, for instance, the consequence of unmet sexual needs among soldiers is increasingly less accepted. Sexual violence against women perpetrated by armed forces in conflict areas is tragically prevalent. While proper quantification of the phenomenon is hard for obvious reasons, it is estimated for example that at least 500,000 women were raped during the Rwandan genocide, and 50,000 during the war in Bosnia (Guarnieri and Tur-Prats, 2022).
Another form of gender-based violence in conflict is that women who are uprooted by war tend to confront a high risk of sexual violence during their journey away from home and in the places where they seek refuge. Vu et al. (2014) estimate, through meta-analysis, that approximately one in five refugees or displaced women in complex humanitarian settings experienced sexual violence. The study also highlights the need for more data to shed light on the characteristics of perpetrators. The presence of aid workers among them appears to persist through several humanitarian crises (Reis, 2021).
Further, women and children fleeing war areas are vulnerable to the risk of trafficking and exploitation for sexual or other work (as highlighted in the FROGEE conference panel). Traffickers and criminal organizations tend to exploit the combination of a mass movement of people in precarious economic situations and the decreased scrutiny generated by the humanitarian emergency.
Finally, war heightens the risk of intimate partner violence (IPV) in conflict areas as well as among refugees and displaced individuals, by causing stress, trauma, economic hardship and increased substance abuse, all of which lead to deterioration in mental health and the quality of relationships (Conference panel). An actual or perceived sense of impunity can also undermine victims’ propensity to report IPV at such a time. A systematic review of the published literature on gender-based violence in conflict finds that estimated rates of IPV across most studies are much higher than the rates of rape and sexual violence perpetrated outside the home (Stark and Ager, 2011).
The consequences of conflict on IPV can be long-lasting. Evidence from post-genocide Rwanda shows that women who married after the conflict were more likely to be victims of spousal abuse; skewed sex ratios that reduced women’s bargaining power in the marriage market appear to be the relevant channel (La Mattina 2017). Another important factor is posttraumatic stress disorder (PTSD) among veterans: a study of US military personnel shows that assignment to combat in the Global War on Terrorism is associated with higher incidence of domestic violence and lower relationship quality (Cesur and Sabia, 2016). The increased availability of small weapons can also lead to more frequent or more violent instances of domestic abuse (Conference panel).
The War in Ukraine
Reports from the US State Department and Amnesty international document episodes of sexual violence from armed conflict actors in Donetsk and Luhansk since the start of the conflict in 2014 (Amnesty International, 2020). Both Russian and Ukrainian military were involved, speaking to the tragedy that the population close to the “contact area” have witnessed since 2014.
At present, growing evidence is emerging that Ukrainians, especially but not exclusively women and girls, are victims of rape, gang-rape and forced nudity perpetrated by Russian military troops invading the country (United Nations). It is notoriously difficult to collect and verify data and facts on sexual violence during wartime, but these early accounts, and the experience from previous conflicts, call for a high level of scrutiny and readiness to help. Research also suggests some potential factors that aggravate the prevalence of sexual violence in conflict. Guarnieri and Tur-Prats (2020) show that armed actors who hold more gender-unequal norms are more likely to be perpetrators of sexual violence, and that the incidence of sexual violence is highest when the parts in conflict hold gender norms that differ substantially (Guarnieri and Tur-Prats, 2022). Survey data show that the share of people who appear to hold gender-unequal norms in Russia remained high over the years, based on questions on the effectiveness of women and men as political or business leaders (Figures 1 and 2), or the desirability of women earning more than their husbands (not shown).
Figure 1. Men make better political leaders than women do, % agreement
Source: World Value Survey
Figure 2. Men make better business executives than women do, % agreement
Source: World Value Survey
Evidence on the evolution of norms in Ukraine is more mixed (see Figures 1 and 2). All in all, surveys of gender-role attitudes suggest that gender stereotypes persist in Russian society, but it is not obvious that the prevailing gender norms are starkly different between Russia and Ukraine. On the other hand, attitudes toward IPV in the two countries might be evolving differently, at least among the respective elites, based on the fact that legislation on domestic violence recently changed in opposite direction in the two countries. Specifically, Russia decriminalized minor forms of domestic violence in early 2017. Conversely, Ukraine strengthened the legal response to domestic violence in early 2019, in particular making minor but systematic domestic violence criminally punishable, and extending criminal punishment beyond physical violence to include emotional and economic violence.
As a consequence of the war, almost 13 million Ukrainians have left their homes since Russia invaded on Feb. 24, 2022, according to the United Nations. Almost all of them are women and children, since men and boys aged 18 to 60 are required to stay in Ukraine to defend the country. Women traveling alone with their children, especially when fleeing to foreign countries where they often have no connections, are clearly at risk of assault and exploitation. Such risk is heightened by the exceptional speed of the refugee influx, whereby an impromptu response from the host countries is by necessity reliant on individual independent participation. Private hosts have spontaneously been opening their homes to accommodate for days or even weeks Ukrainians fleeing the war. Proper vetting of these offers is made difficult by the sheer number of people who are being welcomed in bordering countries, for instance Poland, as well as by the exceptional response from private individuals. Within a little more than a month from the start of this crisis there had already been a few episodes of sexual violence against Ukrainian refugees in their host countries (specifically in Poland and Germany).
While the current death toll in the war in Ukraine is unlikely to lead to dramatically skewed sex-ratios, this aspect might become more relevant as events evolve, in light also of the fact that nearly the universe of those who fled the country so far consists of women and children.
Finally, in the post-conflict period, the presence of small weapons, which have been made available to civilians to defend the country, is an additional risk factor for IPV (Conference panel).
What Can Be Done?
Academics, international organizations, activists and female politicians from Ukraine have made specific requests to improve the system of protection and accountability in the face of sexual violence against women living in or fleeing from conflict zones. These suggestions include ensuring that the system of transitional justice that will govern the post-conflict period establishes proper investigation and punishment of every form of sexual violence performed by armed actors during the war. To this end, some steps have already been taken. The UN Resolution in favor of the creation of an International Commission of Inquiry refers explicitly to the need to recognize the gender dimension of violations and abuses.
Beyond the horizon of the war, the safety of Ukrainian women in their homes relies on the protection offered by State legislation against domestic violence. In this respect, the Ukrainian government has recently taken a few measures in what the international community deems to be the “right direction”. A very important reform taken in the summer of 2021 allows for the military to be prosecuted for domestic violence on a general basis rather than on the basis of the disciplinary statute as it was before. This is especially important in light of the findings of increased risk of domestic violence in families of veterans (Cesur and Sabia, 2016). However, some critical aspects remain. In the current context, a crucial factor might be the limit of 6 months to prosecute the crime from the occurrence of the violence. An extension of such a period at a time when the normal functioning of many institutions is suspended or subject to delays can attenuate the perception of impunity that the exceptionality of the circumstances creates.
When it comes to refugees, there is as mentioned a need for better vetting of private hosts, although the urgency of action that the current circumstances require makes this a particularly challenging task. State effort in this direction has been complemented by civil society initiatives. For example, in Sweden, Facebook groups that lined up to coordinate the offer of housing are now organizing themselves to create a system for verifying housing and hosts.
Ukrainian politicians have also asked Western countries to be prepared to offer expertise on how to support survivors of rape and other sexual violence in conflict.
Other experts recommend reliance on cultural and linguistic mediators to help refugee women access services for victims of IPV that are already offered by local actors in their temporary host country (Conference panel).
In the longer term, guaranteeing economic safety for refugees is also an effective measure to reduce their vulnerability to exploitation from sex-traffickers and criminal organizations.
Finally, yet importantly, the involvement of women in peace negotiation processes should be sought after. Echoing the discussion on women’s scarcity in leadership positions in peacetime, the gender-unequal composition of peace delegations poses an issue of equality, representativeness, and efficiency (Bertrand 2018). Interestingly, it has been noted that a more truthful narrative of war, which recognizes women’s role not only as victims but also as perpetrators (and the converse for men, although proportions are clearly unbalanced in both cases), might help pave the way for higher female representation at negotiation tables (Conference panel). Relatedly, the European Institute for Gender Equality proposes gender mainstreaming of all policies and programs involved in conflict resolution processes (EIGE). The international community should also consider gender mainstreaming of reconstruction programs, to help build a more gender-equal post-conflict Ukraine.
References
- Amnesty International. (2020). Not a Private Matter. Domestic and Sexual Violence against Women in Eastern Ukraine.
- Baaz, M. E., and Stern, M. (2013). Sexual violence as a weapon of war?: Perceptions, prescriptions, problems in the Congo and beyond. Bloomsbury Publishing.
- Bertrand, M. (2018). Coase lecture–the glass ceiling. Economica, 85(338), 205-231.
- Cesur, R., and Sabia, J. J. (2016). When war comes home: The effect of combat service on domestic violence. Review of Economics and Statistics, 98(2), 209-225.
- Guarnieri, E., and Tur-Prats, A. (2022). Cultural distance and conflict-related sexual violence. Mimeo
- Reis, C. (2021). Sexual abuse during humanitarian operations still happens. What must be done to end it. The Conversation, October 5 2021. https://theconversation.com/sexual-abuse-during-humanitarian-operations-still-happens-what-must-be-done-to-end-it-169223
- Stark, L. and Ager, A. (2011). A systematic review of prevalence studies of gender-based violence in complex emergencies. Trauma, Violence, & Abuse, 12(3), pp.127-134.
- Vu, A., Adam, A., Wirtz, A., Pham, K., Rubenstein, L., Glass, N., Beyrer, C. and Singh, S. (2014). The prevalence of sexual violence among female refugees in complex humanitarian emergencies: a systematic review and meta-analysis. PLoS currents, 6.
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 Energy and Climate Crisis Facing Europe: How to Strike the Right Balance
Policymakers in Europe are currently faced with the difficult task of reducing our reliance on Russian oil and gas without worsening the situation for firms and households that are struggling with high energy prices. The two options available are either to substitute fossil fuel imports from Russia with imports from other countries and cut energy tax rates to reduce the impacts on firms and household budgets, or to reduce our reliance on fossil fuels entirely by investing heavily in low-carbon energy production. In this policy brief, we argue that policymakers need to also take the climate crisis into account, and avoid making short-term decisions that risk making the low-carbon transition more challenging. The current energy crisis and the climate crisis cannot be treated as two separate issues, as the decisions made today will impact future energy and climate policies. To exemplify how large-scale energy policy reforms may have long-term consequences, we look at historical examples from France, the UK, and Germany, and the lessons we can learn to help guide us in the current situation.
The war in Ukraine and the subsequent sanctions against Russia have led to a sharp increase in energy prices in the EU since the end of February 2022. This price increase came after a year when global energy prices had already surged. For instance, import prices for energy more than doubled in the EU during 2021 due to an unusually cold winter and hot summer, as well as the global economic recovery following the pandemic and multiple supply chain issues. Figure 1 shows that the price of natural gas traded in the European Union has increased steadily since the summer of 2021, with a strong hike in March 2022 following the beginning of the war.
Figure 1. Evolution of EU gas prices, July 2021-May 2022
Source: https://tradingeconomics.com/commodity/eu-natural-gas
Concerns about energy dependency, towards Russian gas in particular, are now high on national and EU political agendas. An embargo on imports of Russian oil and gas into the EU is currently discussed, but European governments are worried about the effects on domestic energy prices, and the economic impact and social unrest that could follow. Multiple economic analyses argue, however, that the economic effect in the EU of an embargo on Russian oil and gas would be far from catastrophic, with estimated reductions in GDP ranging from 1.2-2.2 percent. But a reduction in the supply of fossil fuels from Russia would need to be compensated with energy from other sources, and possibly supplemented with demand reductions.
In parallel, on April 4th, the Intergovernmental Panel on Climate Change (IPCC) released a new report on climate change. One chapter analyses different energy scenarios, and finds that all scenarios that are compatible with keeping the global temperature increase below 2°C involve a strong decrease in the use of all fossil fuels (Dhakal et al, 2022). This reduction in fossil fuel usage over the coming decades is illustrated in red in Figure 2.
It is thus important that, while EU countries try to decrease their dependency on Russian fossil fuels and cushion the effect of energy-related price increases, they also accelerate the transition to a low-carbon economy. And how they manage to balance these short- and long-run objectives will depend on the energy policy decisions they make. For instance, if policymakers substitute Russian oil and gas with increased coal usage and new import terminals for LNG, this can lead to a “carbon lock in” and make the low-carbon transition more challenging. In this policy brief, we analyze what lessons can be drawn from past historical events that lead to large-scale structural changes in energy policy. Events that all shaped our current energy systems and conditions for climate policy.
Figure 2. Four energy scenarios compatible with a 2°C temperature increase by 2100.
Source: IPCC sixth assessment report on Mitigation of Climate Change, chapter 3, p23
Structural Changes in Energy Policy in France, the UK, and Germany
We focus on three “energy policy turning points” triggered by three geopolitical, political or environmental crises: the French nuclear plan triggered by the 1973 oil crisis; the UK early closure of coal mines and the subsequent dash for gas in the 1990s, influenced by the election of Margaret Thatcher in 1979; and the German nuclear phase-out triggered by the 2011 Fukushima catastrophe.
In response to the global oil price shock of 1973, France adopted the “Messmer plan”. The aim was to rapidly transition the country away from dependence on imported oil by building enough nuclear capacity to meet all the country’s electricity needs. Two slogans summarised its goals: “all electric, all nuclear”, and “in France, we may not have oil, but we have ideas” (Hecht 2009). The first commissioned plants came online in 1980, and between 1979-1988 the number of reactors in operation in France increased from 16 to 55. As a consequence, the share of nuclear power in the total electricity production rose from 8 to 80 percent, while the share of fossil fuels fell from 65 to 8 percent.
Figure 3. French electricity mix
Source: Data on electricity and heat production in France is provided by the IEA (2022).
In the UK, the election of Margaret Thatcher in 1979 opened the way for large market-based reform of the energy sector. Thatcher’s plan to close dozens of coal pits triggered a year-long coal miners’ strike in 1984-85. The ruling Conservative party eventually won against the miners’ unions and the coal industry was deeply restructured, with a decrease in domestic employment – not without social costs (Aragon et al, 2018) – and an increase in coal imports. At the same time, the electricity market’s liberalization in the 1990s facilitated the development of gas infrastructure. As an indirect and unintended consequence, when climate change became a prominent issue at the global level in the 2000s, there was no strong pro-coal coalition left in the UK (Rentier et al, 2019). Aided by a portfolio of policies making coal-fired electricity more expensive – a carbon tax in particular – the coal phase-out was relatively easy and fast (Wilson and Staffel, 2018, Leroutier 2022): between 2012 and 2020, the share of coal in the electricity production dropped from 40 to 2 percent.
In 2011, the Fukushima nuclear catastrophe in Japan triggered an early and unexpected phase-out of nuclear energy in Germany. The 2011 “Energiewende” (energy transition) mandated a phase-out of nuclear power plants by 2022, while including provisions to reduce the share of fossil fuel from over 80 percent in 2011 to 20 percent in 2050. The share of nuclear energy in the electricity production in Germany was halved in a decade, from 22 percent in 2010 to 11 percent in 2020. At the same time, the share of renewable energy increased from 13 to 36 percent, and that of natural gas from 14 to 17 percent.
In these three examples, climate objectives were never the main driver of the decision. Nevertheless, in the case of France and the UK, the crisis resulted in an energy sector that is arguably more low-carbon than it would have been without the crisis. Although the German nuclear phase-out was accompanied by large subsidies to renewable energies, its effect on the energy transition is ambiguous: some argue that the reduction in nuclear electricity production was primarily offset by an increase in coal-fired production (Jarvis et al, 2022).
The three crises also had different consequences in terms of dependence on fossil fuel imports. The French nuclear plan resulted in an arguably lower energy dependency on imported fossil fuels. The closure of coal mines in the UK had ambiguous effects on energy security, with an increase in coal imports and the use of domestic gas from the North Sea. Finally, Germany’s nuclear phase-out, combined with the objective of phasing out coal, has been associated with an increase in the use of fossil fuels from Russia: gas imports remained stable between 2011 and 2020, but the share coming from Russia increased by 60 percent over the period. In 2020, Russia stood for 66 percent of German gas imports (Source: Eurostat). Which brings us back to the current war in Ukraine.
The Current Crisis is Different
The context in which the current energy crisis is unfolding is different from the three above-mentioned events in two important ways.
First, scientific evidence on the relationship between fossil fuel use, CO2 emissions and climate damages has never been clearer: we know quite precisely where the planet is heading if we do not drastically reduce fossil fuel use in the coming decade. From recent research in economics, we also know that price signals work and that increased prices on fossil fuels result in lower demand and emission reductions (Andersson 2019; Colmer et al. 2020; Leroutier 2022). High fuel prices can also have long-term impacts on consumption patterns: US commuters that came of driving age during the oil prices of the 70s, when gasoline prices were high, still drive less today (Severen and van Benthem, 2022). The other way around, low fossil fuel prices have the potential to lock in energy-intensive production: plants that open when electricity and fossil fuel prices are low have been found to consume more energy throughout their lifetime, regardless of current prices (Hawkins-Pierot and Wagner, 2022).
Second, alternatives to fossil fuels have never been cheaper. It is most obvious in the case of electricity production, where technological progress and economies of scale have led to a sharp decrease in the cost of renewable compared to fossil fuel technologies. As shown in Figure 4, between 2010 and 2020 the cost of producing electricity from solar PV has decreased by 85 percent and that of producing electricity from wind by 68 percent. From being the most expensive technologies in 2010, solar PV and wind are now the cheapest. Given the intermittency of these technologies, managing the transition to renewables requires developing electricity storage technologies. Here too, prices are expected to decrease: total installed costs for battery electricity storage systems could decrease by 50 to 60 percent by 2030 according to the International Renewable Agency.
Finding alternatives to fossil fuels has historically been more challenging in the transport sector. However, recent reductions in battery costs, and an increase in the variety of electric vehicles available to customers, have led to EVs taking market share away from gasoline and diesel-powered cars in Europe and elsewhere. The costs of the battery packs that go into electric vehicles have fallen, on average, by 89 percent in real terms from 2010 to 2021.
Figure 4. Evolution of the Mean Levelised Cost of Energy by Technology in the US
Source: Lazard
Options for Policy-Makers
Faced with a strong increase in fossil fuel prices and an incentive to reduce our reliance on oil and gas from Russia, policy-makers have two options: increase the availability and decrease the price of low-carbon substitutes – by, for example, building more renewable energy capacity and subsidizing electric vehicles – or cut taxes on fossil fuels and increase their supply, both domestically and from other countries.
Governments have pursued both options so far. On the one hand, the Netherlands, the UK, and Italy announced an expansion of wind capacities compared to what was planned, in an attempt to reduce their dependence on Russian gas, and France ended gas heaters subsidies. On the other hand, half of EU member states have cut fuel taxes for a total cost of €9 billion by the end of March 2022, the UK plans to expand oil and gas drilling in the North Sea, and Italy might re-open coal-fired plants.
To guide policymakers faced with the current energy crisis, there are valuable lessons to draw from the experiences of energy policy reform in France, the UK and Germany. France’s push for nuclear energy in the 1970s shows that large-scale structural reform of electricity and heat production is possible and may lead to large drops in CO2 emissions and an economy less dependent on domestic or foreign supplies of fossil fuels. A similar “Messmer plan” could be implemented in the EU today, with the goal of replacing power plants using coal and natural gas with large-scale solar PV parks, wind farms and batteries for storage. Similarly, the German experience shows the potential danger of implementing a policy to alleviate one concern – the risk of nuclear accidents – with the consequence of facing a different concern later on – the dependence on fossil fuel imports.
One additional challenge is that the current energy crisis calls for a short-term response, while investments in low-carbon technologies made today will only deliver in a few years. Short-term energy demand reduction policies can help, on top of long-term energy efficiency measures. For example, a 1°C decrease in the temperature of buildings heated with gas would decrease gas use by 10 billion cubic meters a year in Europe, that is, 7 percent of imports from Russia. Similarly, demand-side policies could reduce oil demand by 6 percent in four months, according to the International Energy Agency.
Ending the reliance on Russian fossil fuels and alleviating energy costs for firms and households is clearly an important objective for policymakers. However, by signing new long-term supply agreements for natural gas and cutting energy taxes, policymakers in the EU may create a carbon lock-in and increase fossil fuel usage by households, thereby making the inevitable low-carbon transition even more difficult. The solutions thus need to take the looming climate crisis into account. For example, any tax relief or increased domestic fossil fuel generation should have a clear time limit; more generally, all policies decided today should be evaluated in terms of their contribution to domestic and European climate objectives. In this way, the current energy crisis is not only a challenge but also a historic opportunity to accelerate the low-carbon transition.
References
- Andersson, Julius J. 2019. “Carbon Taxes and CO2 Emissions: Sweden as a Case Study.” American Economic Journal: Economic Policy, 11(4): 1-30.
- Aragón, F. M., Rud, J. P., & Toews, G. 2018. “Resource shocks, employment, and gender: Evidence from the collapse of the UK coal industry.” Labour Economics, 52, 54–67. doi: 10.1016/j.labeco.2018.03.007
- Colmer, Jonathan, et al. 2020. “Does pricing carbon mitigate climate change? Firm-level evidence from the European Union emissions trading scheme.” Centre for Economic Performance Discussion Paper, No. 1728, November 2020.
- Dhakal, S., J.C. Minx, F.L. Toth, A. Abdel-Aziz, M.J. Figueroa Meza, K. Hubacek, I.G.C. Jonckheere, Yong-Gun Kim, G.F. Nemet, S. Pachauri, X.C. Tan, T. Wiedmann, 2022: Emissions Trends and Drivers. In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.004
- IPCC. 2022. Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al hourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926
- Hawkins-Pierot, J & Wagner, K. 2022, “Technology Lock-In and Optimal Carbon Pricing,” Working Paper
- Hecht, Gabrielle. 2009. The Radiance of France: Nuclear Power and National Identity after World War II. MIT press.
- Jarvis, S., Deschenes, O., & Jha, A. 2022. “The Private and External Costs of Germany’s Nuclear Phase-Out.” Journal of the European Economic Association, jvac007. doi: 10.1093/jeea/jvac007
- Leroutier, M. 2022. “Carbon pricing and power sector decarbonization: Evidence from the UK.” Journal of Environmental Economics and Management, 111, 102580. doi: 10.1016/j.jeem.2021.102580
- Le Coq, C & Paltseva,E. 2022. “What does the Gas Crisis Reveal About European Energy Security?” FREE Policy Brief
- Rentier, G., Lelieveldt, H., & Kramer, G. J. 2019. “Varieties of coal-fired power phase-out across Europe.” Energy Policy, 132, 620–632. doi: 10.1016/j.enpol.2019.05.042
- Severen, C., & van Benthem, A. A. (2022). “Formative Experiences and the Price of Gasoline.” American Economic Journal: Applied Economics, 14(2), 256–84. doi: 10.1257/app.20200407 :
- Wilson, I.A.G., Staffell, I., 2018. “Rapid fuel switching from coal to natural gas through effective carbon pricing.” Nature Energy 3 (5), 365–372.
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 Transformation and Reconstruction of Ukraine
The war Russia is waging in Ukraine is a humanitarian disaster, and its social and economic repercussions are being felt worldwide. The OECD Council has condemned Russia in the strongest possible terms and is working on a new strategy to support Ukraine, building on a Memorandum of Understanding established with the country in 2014 and renewed in 2021. The OECD Development Centre stands ready to support these efforts, providing expertise in a wide range of policy domains.
On Tuesday, 17 May 2022, the OECD #DevTalks organised a webinar that brought together experts and Development Centre members to discuss Ukraine’s economic and social transformation prior to 2022, the impact of the war, priorities for reconstruction, and the international support needed to realise its vision.
Speakers
- Mathias Cormann, Secretary-General, OECD
- Vadym Omelchenko, Extraordinary and Plenipotentiary Ambassador of Ukraine to France
- Yuriy Gorodnichenko, Quantedge Presidential Professor of Economics, University of California Berkeley
- Nataliia Shapoval, Head of KSE Institute & Vice President for Policy Research, Kyiv School of Economics
- Tymofii Brik, Acting Wartime Vice-president of International Affairs & Head of Sociological Research, Kyiv School of Economics
- Torbjörn Becker, Director, Stockholm Institute of Transition Economics (SITE), Stockholm School of Economics
- William Tompson, Head of Eurasia, Global Relations and Co-operation, OECD
- Ragnheidur Elín Árnadóttir, Director, OECD Development Centre
For more #DevTalks – a series of online panel discussions, along with Development Matters blogs, follow the OECD #DevTalk page.
Disclaimer: Opinions expressed during events and conferences are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Detecting Labor Tax Evasion Using Administrative Data and Machine-Learning Techniques
Labor tax evasion is a major policy issue that is especially salient in transition and post-transition countries. In this brief, we use firm-level administrative data, tax authorities’ audit data and machine learning techniques to detect firms likely to be involved in labor tax evasion in Latvia. First, we show that this approach could complement tax authorities’ regular practices, increasing audit success rate by up to 35%. Second, we estimate that about 30% of firms operating in Latvia between 2013 and 2020 are likely to underreport the wage of (some of) their employees, with a slightly negative trend.
Introduction
Tax evasion is a major policy issue that is especially salient in transition and post-transition countries. In particular, “envelop wage”, i.e., an unofficial part of the wage paid in cash, is a widespread phenomenon in Eastern Europe (European Commission, 2020). Putnins and Sauka (2021) estimate that the share of unreported wages in Latvia amounts to more than 20%. Fighting labor tax evasion is a key objective of tax authorities, which face two main challenges. The first is to make the best use of their resources. Audits are costly, so the choice of firms to audit is crucial. The second challenge is to track the evolution of the prevalence of labor tax evasion. For this purpose, most of the existing literature relies on survey data.
In our forthcoming paper (Gavoille and Zasova, 2022), we propose a novel methodology aiming at detecting tax-evading firms, using administrative firm-level data, tax authorities’ audit data and machine learning techniques.
This study provides two main contributions. First, this approach can help tax authorities to decide which firms to audit. Our results indicate that the audit success rate could increase by up to 20 percentage points, resulting in a 35% increase. Second, our methodology allows us to estimate the share of firms likely to be involved in labor tax evasion. To our knowledge, this paper is the first to provide such estimates, which are however of primary importance in guiding anti-tax evasion policy. We estimate that over the 2013-2020 period, about 30% of firms operating in Latvia are underreporting (at least some of) their workers’ wages.
Methodology
The general idea of our approach is to train an algorithm to classify firms as either compliant or tax-evading based on observed firm characteristics. Tax evasion, like any financial manipulation, results in artifacts in the balance sheet. These artifacts may be invisible to the human eye, but machine learning algorithms can detect these systematic patterns. Such methods have been applied to corporate fraud detection (see for instance Cecchini et al. 2010, Ravisankar et al. 2011, West and Bhattacharya 2016).
The machine learning approach requires a subsample of firms for which we know the “true” firm behavior (i.e., tax-evading or compliant) in order to train the algorithm. For this purpose, we propose to use a dataset on tax audits provided by the Latvian State Revenue Service (SRS), which contains information about all personal income tax (PIT) and social security contributions (SSC) audits carried out by SRS during the period 2013-2020, including the outcome of the audit. The dataset also contains a set of firm characteristics and financial indicators, covering both audited and non-audited firms operating in Latvia (e.g., turnover, assets, profit). Assuming that auditors are highly likely to detect misconduct (e.g., wage underreporting) if present, audit outcomes provide information about a firm’s tax compliance. Firms sanctioned with a penalty for, say, personal income tax fraud are involved in tax evasion, whereas audited-but-not-sanctioned firms can be assumed compliant. The algorithm learns how to disentangle the two types of firms based on the information contained in their balance sheets. Practically, we randomly split the sample of audited firms into two parts, the training and the testing subsamples. In short, we use the former to train the algorithm, and then evaluate its performance on the latter, i.e., on data that has not been used during the training stage. If showing satisfying performance on the training sample, we can then apply it to the whole universe of firms and obtain an estimate of the share of tax-evading firms.
In this study, we successively implement four algorithms that differ in the way they learn from the data: (1) Random Forest, (2) Gradient Boosting, (3) Neural Networks, and (4) Logit (for a review of machine learning methods, see Athey and Imbens, 2019). These four data mining techniques have previously been used in the literature on corporate fraud detection (see Ravisankar et al. 2011 for a survey). Each of these four algorithms has specific strengths and weaknesses, motivating the implementation and comparison of several approaches.
Results
Predictive Performance
Table 1 provides the out-of-sample performance of the four different algorithms. In other words, it shows how precise the algorithm is at classifying firms based on data that has not been included during the training stage. Accuracy is the percentage of firms correctly classified (i.e., the model prediction is consistent with the observed audit’s outcome). In our sample, about 44% of audited firms are required to pay extra personal income tax and social security contributions. This implies that a naive approach predicting all firms to be evading would be 44% accurate. Similarly, a classification predicting all firms to be tax compliant would be correct in 56% of the cases. This latter number can be used as a benchmark to evaluate the performance of the algorithms. ROC-AUC (standing for Area Under the Curve – Receiver Operating Characteristics) is another widespread classification performance measure. It provides a measure of separability, i.e., how well is the model able to distinguish between the two types. This measure is bounded between 0 and 1, the closer to 1 the better the performance. A score above 0.8 can be considered largely satisfying.
Table 1. Performance measures
Source: authors’ calculations
Random Forest is the algorithm providing the best out-of-sample performance, with more than 75% of the observations in the testing set correctly classified. Random Forest is also the best performing model according to the ROC-AUC measure, with performance slightly better than Gradient Boosting.
Our results imply that a naive benchmark prediction is outperformed by almost 20 percentage points by Random Forest and Gradient Boosting in terms of accuracy. It is important to emphasize that this improvement in performance is achieved using a relatively limited set of firm-level observable characteristics that we obtained from SRS (which is limited compared to what SRS has access to), and that mainly come from firms’ balance sheets. This highlights the potential gain of using data-driven approaches for the selection of firms to audit in addition to the regular practices used by the fiscal authorities. It also suggests a promising path for further improvements, as in addition to this set of readily available information the SRS is likely to possess more detailed limited-access firm-level data.
Share of Tax-Evading Firms Over Time and Across NACE Sectors
We can now apply these algorithms to the whole universe of firms (i.e., to classify non-audited firms). Figure 1 shows the share of firms classified as tax-evading over the years 2014 to 2019 for our two preferred algorithms – Gradient Boosting and Random Forest. Random Forest (the best performing algorithm) predicts that 30-35% of firms are involved in tax evasion, Gradient Boosting predicts a slightly higher share (around 40%). Both algorithms, especially Random Forest, suggest a slight reduction in the share of tax-evading firms since 2014.
Figure 1. Share of tax-evading firms over time
Source: authors’ calculations
The identified reduction, however, does not necessarily imply that the overall share of unreported wages has declined. In fact, existing survey-based evidence (Putnins and Sauka, 2021) indicate that the size of the shadow economy as a share of GDP remained roughly constant over the 2013-2019 period, and that there was no reduction in the contribution of the “envelope wages”. With our method, we are estimating the share of firms likely to be involved in labor tax evasion. Unlike the survey approach, our methodology does not allow the measurement of tax-evasion intensity. In other words, the share of non-tax compliant firms may have decreased, but the size of the envelope may have increased in firms involved in this scheme.
Next, we disaggregate the share of tax-evading firms by the NACE sector. Figure 2 displays the results obtained with Random Forest, our best performing algorithm.
Figure 2. Share of tax-evading firms by NACE, based on Random Forest
Source: authors’ calculations
First, the sector where tax evasion is the most prevalent is the accommodation/food industry, where the predicted share of tax-evading firms is 70-80%. Second, our results indicate that the overall decrease in the share of firms likely to evade is not uniform. It is mostly driven by the accommodation/food and manufacturing sectors. Other sectors remain nearly flat. This highlights the fact that labor tax evasion varies both in levels and in changes across sectors.
Conclusion
We show that machine learning techniques can be successfully applied to administrative firm-level data to detect firms that are likely to be involved in (labor) tax evasion. Machine learning techniques can be used to improve the selection of firms to audit in order to maximize the probability to detect tax-evading firms, in addition to the regular practices already used by SRS. Our preferred algorithms – Random Forest and Gradient Boosting – outperform the naive benchmark classification by almost 20 percentage points, which is a substantial improvement. Once implemented, the use of these tools can improve the audit effectiveness at virtually no extra cost.
Our findings also suggest a promising path for further improvements in the application of such methods. The improvement in predictive power achieved by our proposed algorithm is attained by using a limited set of variables readily available from the firms’ balance sheets. Given that SRS is likely to have access to more detailed firm-level information that cannot be provided to third parties, there is clear room for improving the performance of the algorithms by using such limited-access data.
Acknowledgement: The authors gratefully acknowledge funding from the Latvian State Research Programme “Reducing the Shadow Economy to Ensure Sustainable Development of the Latvian State”, Project “Researching the Shadow Economy in Latvia (RE:SHADE)”; project No VPP-FM-2020/1-0005.
References
- Athey, Susan, and Guido Imbens. 2019. “Machine Learning Methods That Economists Should Know About.” Annual Review of Economics 11: 685–725.
- Cecchini, Mark, and Haldun Aytug, and Gary J. Koehler, and Praveen Pathak, 2010. “Detecting management fraud in public companies“. Management Science 56, 1146-1160.
- European Commission, 2020. “Undeclared Work in the European Union. Special Eurobarometer 498” (Report)
- Gavoille, Nicolas and Anna Zasova, 2022. “Estimating labor tax evasion using tax audits and machine learning”, SSE Riga/BICEPS Research papers, forthcoming.
- Putnins, Talis, and Arnis Sauka, 2021. “Shadow Economy Index for the Baltic Countries 2009–2020” (Report), SSE Riga
- Ravisankar, Pediredla, and Vadlamani Ravi, and Gundumalla Raghava Rao, and Indranil Bose, 2011. “Detection of financial statement fraud and feature selection using data mining techniques“. Decision Support Systems, 50(2), 491-500.
- West, Jarrod, and Maumita Bhattacharya, 2016. “Intelligent financial fraud detection: a comprehensive review“. Computers & security, 57, 47-66
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.
Understanding the Economic and Social Context of Gender-based and Domestic Violence in Central and Eastern Europe – Preliminary Survey Evidence
This brief presents preliminary findings from a cross-country survey on perceptions and prevalence of domestic and gender-based violence conducted in September 2021 in eight countries: Armenia, Belarus, Georgia, Latvia, Poland, Russia, Sweden and Ukraine. We discuss the design and content of the study and present initial information on selected topics that were covered in the survey. The collected data has been used in three studies presented at the FROGEE Conference on “Economic and Social Context of Domestic Violence” and offers a unique resource to study gender-based violence in the region.
While the COVID-19 pandemic has amplified the academic and policy interest in the causes and consequences of domestic violence, the Russian invasion of Ukraine has tragically reminded us about the gender dimension of war. There is no doubt that a gender lens is a necessary perspective to understand and appreciate the full consequences of these two ongoing crises.
The tragic reason behind the increased attention given to domestic violence during the COVID-19 lockdowns is the substantial evidence that gender-based violence has intensified to such an extent that the United Nations raised the alarm about a “shadow pandemic” of violence against women and girls (UN Women on-line link). Already before the pandemic, one in three women worldwide had experienced physical or sexual violence, usually at the hands of an intimate partner, and this number has only been increasing. The tragic reports from the military invasion of Ukraine concerning violence against women and children, as well as information on the heightened risks faced by war refugees from Ukraine, most of whom are women, should only intensify our efforts to better understand the background behind these processes and study the potential policy solutions to limit them to a minimum in the current and future crises.
The most direct consequences of gender-based and domestic violence – to the physical and mental health of the victims – are clearly of the highest concern and are the leading arguments in favour of interventions aimed at limiting the scale of violence. One should remember though, that the consequences and the related social costs of gender-based and domestic violence are far broader, and need not be caused by direct acts of physical violence. Gender-based and domestic violence can take the form of psychological pressure, limits on individual freedoms, or access to financial resources within households. As research in recent decades demonstrates, such forms of abuse also have significant consequences for the psychological well-being, social status, and professional development of its victims. All these outcomes are associated with not only high individual costs, but also with substantial social and economic costs to our societies.
This policy brief presents an outline of a survey conducted in eight countries aimed at better understanding the socio-economic context of gender-based violence. The survey, developed by the FREE Network of independent research institutes, has a regional focus on Central and Eastern Europe, with Sweden being an interesting benchmark country. The data was collected in September 2021 in Armenia, Belarus, Georgia, Latvia, Poland, Russia, Sweden and Ukraine. The socio-economic situation of all these countries irrevocably changed with the Russian invasion of Ukraine on 24 February 2022, the ongoing war, and its dramatic consequences. The world’s attention focused on the unspeakable violence committed by the Russian forces in Ukraine, the persecution in Belarus and Russia of their own citizens who were protesting against the invasion, and the challenges other neighbouring countries have faced as a result of an unprecedented wave of Ukrainian refugees. This change, on the one hand, calls for a certain distance with which we should judge the survey data and the derived results. On the other hand, the data may serve as a unique resource to support the analysis of the pre-war conditions in these countries with the aim to understand the background driving forces behind this dramatic crisis. In as much as the gender lens is necessary to comprehend the full scale of the consequences of both the COVID-19 pandemic and the war in Ukraine, it will be equally indispensable in the process of post-war development and reconciliation once peace is again restored.
Survey Design, Countries, and Samples
The survey was conducted in eight countries in September 2021 through as a telephone (CATI) survey using the list assisted random digit dialling (LA-RDD) method covering both cell phones and land-lines, and the sampling was carried out in such a way as to make the final sample representative of the respective populations by gender and three age group (18-39; 40-54; 55+). The collected samples varied from 925 to 1000 individuals. The same questionnaire initially prepared as a generic English version was fielded in all eight countries (in the respective national languages). The only deviations from the generic version were related to the education categories and to a set of final questions implemented in Latvia, Russia and Ukraine with a focus on the evaluation of national IPV legislation.
Table 1 presents some basic sample statistics, while Figure 1 shows the unweighted age and gender compositions in each country. The proportion of women in the sample varies between 49.4% in Sweden and 55.0% in Belarus, Russia and Ukraine. The average sample age is between 43 (Armenia) and 51 (Sweden), while the proportion of individuals with higher education is between 29.3% in Belarus and 55.4% in Georgia. The highest proportion of respondents living in rural areas could be found in Armenia at 62.9%, while the lowest was in Georgia at 24.1%. Figure 1 illustrates good coverage across age groups for both men and women.
Table 1. FROGEE Survey: samples and basic demographics
Source: FROGEE Survey on Domestic and Gender-Based Violence.
Figure 1. FROGEE Survey: gender and age distributions
Source: FROGEE Survey on Domestic and Gender-Based Violence.
Socio-economic Conditions and Other Background Characteristics
To be able to examine the relationship between different aspects of domestic and gender-based violence to the socio-economic characteristics of the respondents, an extensive set of questions concerning the demographic composition of their household and their material conditions were asked at the beginning of the interview. These questions included information about partnership history and family structure, the size of the household and living conditions, education and labour market status (of the respondent and his/her partner) and general questions concerning material wellbeing. In Figure 2 we show a summary of two of the latter set of questions – the proportion of men and women who find it difficult or very difficult to make ends meet (Figure 2A) and the proportion who declared that the financial situation of their household deteriorated in the last two years, i.e. since September 2019, which can be used as an indicator of the material consequences of the COVID-19 pandemic. We can see that the difficulties in making ends meet are by far lowest in Sweden, and slightly lower in the other EU countries (Latvia and Poland). The differences are less pronounced with regard to the implication of the pandemic, but also in this case respondents in Sweden seem to have been least affected.
Figure 2. Making ends meet and the consequences of COVID-19
a. Difficulties in making ends meet
b. Material conditions deteriorated since 2019
Source: FROGEE Survey on Domestic and Gender-Based Violence.
Perceptions and Incidence of Domestic and Gender-Based Violence and Abuse
Frequency of differential treatment and abuse
The set of questions concerning domestic and gender-based violence started with an initial module related to the different treatment of men and women, with respondents asked to identify how often they witnessed certain behaviours aimed toward women. The questions covered aspects such as women being treated “with less courtesy than men”, being “called names or insulted for being a woman” and women being “the target of jokes of sexual nature” or receiving “unwanted sexual advances from a man she doesn’t know”, and the respondents were to evaluate if in the last year they have witnessed such behaviours on a scale from never, through rarely, sometimes, often, to very often. We present the proportion of respondents answering “often” or “very often” to two of these questions in Figure 3A (“People have acted as if they think women are not smart”) and 3B (“A woman has been the target of jokes of a sexual nature”). We find significant variation across these two dimensions of differential treatment, and we generally find that women are more sensitive to perceiving such treatment. It is interesting to note that the proportion of women who declared witnessing differential treatment in Sweden is very high in comparison to for example Latvia or Belarus, which, as we shall see below, does not correspond to the proportion of women (and men) witnessing more violent types of behaviour against women.
Figure 3. Frequency of differential treatment (often or very often)
a. People have acted as if they think women are not smart
b. A woman has been the target of jokes of a sexual nature
Source: FROGEE Survey on Domestic and Gender-Based Violence.
Questions on the frequency of witnessing physical abuse were also asked in relation to the scale of witnessed behaviour. Here respondents were once again asked to say how often “in their day-to-day life” they have witnessed specific behaviours. These included such types of abuse as: a woman being “threatened by a man”, “slapped, hit or punched by a man”, or “sexually abused or assaulted by a man”. The proportion of respondents who say that they have witnessed such behaviour with respect to two of the questions from this section are presented in Figure 4. In Figure 4A we show the proportion of men and women who have witnessed a woman being “slapped, hit or punched” (sometimes, often or very often), while in Figure 4B being “touched inappropriately without her consent”. Relative to the perceptions of differential treatment the incidence of a woman being hit or punched (4A) declared by the respondents seems more intuitive when considered against the overall international statistics of gender equality. The proportions are lowest in Sweden and Poland, and highest in Armenia and Ukraine. However, the perception of inappropriate touching by men with respect to women (Figure 4B) shows a similar extent of such actions across all analysed countries.
Figure 4. Frequency of abuse (sometimes, often or very often)
a. A woman has been slapped, hit or punched by a man
b. A woman has been touched inappropriately, without her consent, by a man
Source: FROGEE Survey on Domestic and Gender-Based Violence.
Perceptions of abuse
The questions concerning the scale of witnessed behaviours were complemented by a module related to the evaluation of certain behaviours from the perspective of their classification as abuse and the degree to which certain types of gender-specific behaviours are acceptable. Thus, for example respondents were asked if they consider “beating (one’s partner) causing severe physical harm” to be an example of abuse within a couple (Figure 5A) or if “prohibition to dress as one likes” represents abuse (Figure 5B). This module included an extensive list of behaviours, such as “forced abortion”, “constant humiliation, criticism”, “restriction of access to financial resources”, etc. As we can see in Figure 6, with respect to the clearest types of abuse – such as physical violence – respondents in all countries were pretty much unanimous in declaring such behaviour to represent abuse. With respect to other behaviours the variation in their evaluation across countries is much greater – for example, while nearly all men and women in Sweden consider prohibiting a partner to dress as he/she likes to be abusive (Figure 5B), only about 57% of women and 36% of men in Armenia share this view.
The questionnaire also included questions specifically focused on the perception of intimate partner violence. These asked respondents if they knew about women who in the last three months were “beaten, slapped or threatened physically by their intimate partner”, and the evaluation of how often intimate partners act physically violent towards their wives.
Figure 5. Perceptions of abuse: are these examples of abuse within a couple?
a. Beating causing severe physical harm
b. Prohibition to dress as one likes
Source: FROGEE Survey on Domestic and Gender-Based Violence.
A further evaluation of attitudes towards violent behaviour was done with respect to the relationship between a husband and wife and his right to hit or beat the wife in reaction to certain behaviours. In Figure 6 we show the distribution of responses regarding the justification for beating one’s wife in reaction to her neglect of the children (6A) or burning food (6B). The questions also covered such behaviour as arguing with her husband, going out without telling him, or refusing to have sex. As we can see in Figure 6, once again we find substantial country variation in the proportion of the samples – both men and women – who justify such violent behaviour within couples. This was particularly the case when respondents were asked about justification of violent behaviour in the case of a woman neglecting the children. In Armenia as many as 30% of men and 22% of women agree that physical beating is justified in those cases. These proportions are manyfold greater than what can be observed in countries such as Latvia, where 3% of men and women agreed that abuse was justifiable under these circumstances, or Sweden, where only 1% of men and women agreed.
Figure 6. Perceptions of abuse: is a husband justified in hitting or beating his wife
a. If she neglects the children
b. If she burns the food
Source: FROGEE Survey on Domestic and Gender-Based Violence.
Seeking help and the legal framework
The final part of the questionnaire focused on the evaluation of different reactions to incidents of domestic and gender-based violence. Respondents were first asked if a woman should seek help from various people and institutions if she is beaten by her partner – respondents were asked if she should seek help from the police, relatives or friends, a psychologist, a legal service or if, in such situations, she does not need help. In Figure 7 we show the proportion of people who agreed with the last statement, i.e. claimed that it is only the couple’s business. The proportions of respondents who declare such an attitude is higher among men than women within each country, and is highest among men in Armenia (48%) and Georgia (25%). Again, these proportions are in stark contrast to men in Sweden, or even Poland, where only 4% and 8% of men agreed, respectively. Nevertheless, looking at the total survey sample, a vast majority believe that a woman who is a victim of domestic violence should seek help outside of her home, indicating that at least some forms of institutionalised support for women are popular measures with most people.
Figure 7. Proportions agreeing that domestic violence is only the couple’s business
Source: FROGEE Survey on Domestic and Gender-Based Violence.
The interview also included questions on the need for specific legislation aimed at punishing intimate partner violence and on the existence of such legislation in the respondents’ countries. The latter questions were extended in three countries – Latvia, Russia and Ukraine – to evaluate the specific sets of regulations implemented recently in these countries and to facilitate an analysis of the role IPV legislation can play in reducing violence within households. Legislation on domestic violence is relatively recent. During the last four decades, though, changes accelerated in this respect around the world. Legislative measures have been introduced in many countries, covering different aspects of preventing, protecting against and prosecuting various forms of violence and abuse that might happen within the marriage or the family. Research strives to offer evaluations on what legal provisions are most effective, in a setting in which statistics and information are still far from perfect, and as a consequence of the dearth of strong evidence the public debate on the matter is often lively. For legislation to have an effect on behaviour through shaping the cost of committing a crime, on the one hand, and the benefit of reporting it or seeking help, on the other, or more indirectly through changing norms in society, information and awareness are key. For how can deterrence be achieved if people do not know what the sanctions are? And how can reporting be encouraged if victims do not know their rights? The evidence on legislation awareness is unfortunately quite scarce. A survey of the criminology field (Nagin, 2013) concludes that this is a major knowledge gap.
Figure 8 shows the proportions of answers to questions concerning the need for and existence of legislation specifically targeted towards intimate partner violence. We can see that while support for such legislation is quite high (Figure 8A), it is generally lower among men (in particular in Armenia, Russia and Belarus). Awareness of existence of such laws, on the other hand, is much lower, and it is particularly low among women. It should be pointed out that all countries have in fact implemented provisions against domestic violence in their criminal code, but only around half of the population, sometimes much fewer, are aware of that.
Figure 8. Need for and awareness of IPV legislation
a. State should have specific legislation aimed at punishing IPV
b. Country has specific legislation aimed at punishing intimate partner violence
Source: FROGEE Survey on Domestic and Gender-Based Violence.
Recent reforms of DV legislation that were implemented in Russia in 2017, in Ukraine in 2019 and in Latvia just a few months ago (at the time of the survey, the changes were at the stage of a proposal) were the subject of the final survey questions in these countries. We find that awareness of these recent reforms is very low in all three countries, and knowledge about the reform content (gauged with the help of a multiple-choice question with three alternative statements) is even lower. Our analysis suggests that gender and family situation are the two factors that most robustly predict support for legislation, while education and age are associated with awareness and knowledge of the reforms. Minority Russian speakers are less aware of the reforms in both Ukraine and Latvia, in Ukraine are also less likely to answer correctly about the content of the reform, and in Latvia are less supportive of DV legislation in general.
Analyses of this type are useful for policy design, to better understand which groups lack relevant knowledge and should be targeted by, for example, information campaigns to combat DV, such as those many governments around the world implemented during the covid-19 pandemic.
Future Work Based on the Survey
The above is just a small sample of the rich source of information that has resulted from conducting the survey. Already from this simple overview we can see some interesting results. There are, for example, clear differences between men and women in perceptions of how common certain types of abusive behaviour are. However, for many questions differences between countries are larger than those between men and women within a country. Interestingly such differences are also different depending on the severity of the abuse or violence. In Sweden the perception of women being victims of less violent abuse is higher than in some other countries where instead some more violent types of abuse are reported as being more common. This could, of course, be due to actual differences in actual events but it is also possible that there are differences in what types of behaviour are considered to represent harassment and abuse in different societies. More careful data work is needed to try to answer questions like this and many others. Currently there are a number of ongoing research projects based on the survey results, three of which will be presented at the FREE-network conference on “Economic and Social Context of Domestic Violence” in Stockholm on May 11, 2022. Our hope is that this work will help in taking actions to prevent gender-based abuse and domestic violence based on a better understanding of underlying cross-country differences in social norms and attitudes and their relation to socio-economic factors.
About FROGEE Policy Briefs
FROGEE Policy Briefs is a special series aimed at providing overviews and the popularization of economic research related to gender equality issues. Debates around policies related to gender equality are often highly politicized. We believe that using arguments derived from the most up to date research-based knowledge would help us build a more fruitful discussion of policy proposals and in the end achieve better outcomes.
The aim of the briefs is to improve the understanding of research-based arguments and their implications, by covering the key theories and the most important findings in areas of special interest to the current debate. The briefs start with short general overviews of a given theme, which are followed by a presentation of country-specific contexts, specific policy challenges, implemented reforms and a discussion of other policy options.
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 Effects of Sanctions
Sanctions imposed on Russia after its invasion of Ukraine are argued to be the strongest and farthest-reaching imposed on a major power after WWII, more numerous and more comprehensive than all other measures currently in force against all other sanctioned countries. A question often asked, which is hard to answer, is whether sanctions are effective. In the present case, the effect most associate with success would be a swift end of the hostilities, perhaps accompanied by a regime change in Russia. But even when it seems these prizes are out of reach, sanctions certainly have effects, all too often glossed over by the debate but nonetheless of significance.
Why Are Sanctions Seen as Ineffective?
Sanctions are restrictions imposed on a country by one or more other countries with the intent to pressure in effect some desirable outcome, or conversely to condemn and punish some undesired action already taken. When evaluating sanctions, therefore, the focus is naturally on whether they succeed to discourage this particular course of action, or to remove the decision-makers responsible for it. And on this account, sanctions are overwhelmingly seen as unsuccessful. However, a few complications cloud this conclusion.
First of all, sanctions that are implemented already failed at the threat stage. If the threat of a well-specified and credible retribution did not deter the receiving part from pursuing the sanctioned course of action, it is because they reckoned that they can afford to ignore it. So, unless this punishment goes beyond what was expected, in scope or in time, its implementation will also fall flat. This implies that any effort to evaluate sanctions retrospectively suffers from the negative selection problem, when almost exclusively cases of failure, intended in this particular sense, are observed.
Second, sanctions are a rather blunt instrument, that often cannot be targeted with the precision one would desire. Even though sanctions have over time become “smarter”, in the sense that stronger efforts are made to target the regime, or elites that may have the clout to actually affect the regime (think the oligarchs in Russia), they often fail to reach or affect in a meaningful way those individuals that are the real objective, for various reasons. Instead, they can cause significant “collateral damage”, to groups of a population that often are quite far removed from any real decisional power, including those in the sending countries, and even third parties who are extraneous to the situation. The damage inflicted to those parties can only in very special circumstances be part of a causal link eventually impacting the intended outcome. For instance, citizens struggling in an impoverished economy could be led to a riot, or in some other way put pressure on their government – but this implies that the country is sufficiently free for riots to take place or for voters’ opinions to be taken into consideration.
To this, it should be added that, once a course of action has been taken, it might be not obvious how to change or undo it, notwithstanding the signaled displeasure from the sanctioning parties. Sanctions are therefore rarely working in isolation. When positive outcomes are achieved, it is often the case that diplomatic channels were kept open and clear incentives offered for a way out. But then it might be unclear whether it was the sanctions or something else that led to the success.
Other Effects of Sanctions
The pitfalls highlighted above, which make it tricky to answer whether sanctions are effective at reaching their aim, also apply when studying other effects that sanctions might have. There is of course a range of outcomes that might be affected: in this literature we find studies looking at inequality (Afesorgbor et al., 2016), exchange rates (Dreger et al., 2016), trade (Afesorgbor, 2019; Crozet et al. 2020), the informal sector (Early et al, 2019), military spending (Farzanegan, 2019), women’s rights (Drury, 2014), and many more. But as it often happens the most studied outcome is GDP, as this is a measure that efficiently summarizes the whole economy and correlates very nicely with many other outcomes we care about.
Suppose then that we would like to investigate what is the effect of sanctions on a target country’s GDP. One problem is identifying an appropriate counterfactual; to observe what would have happened in the target country in the absence of sanctions. It is also an issue that the incidence of international sanctions is often a product of a series of events in the target or sender country (e.g. the Iraqi invasion of Kuwait or the apartheid system in South Africa), which also have impacts on the economy that would need to be isolated from the impact of sanctions themselves.
A variety of econometric techniques can be of help in this situation. One first idea is to use, as a reference, cases where sanctions were almost implemented. Gutmann et al. (2021) compare countries under sanctions to countries under threat of sanctions, while Neuenkirch and Neumeier (2015) contrast implemented sanctions to vetoed sanctions, in the context of UN decisions. Both studies find a relatively sizeable negative impact on GDP, in a large group of countries over a long period of time. In the first study, the target country’s GDP per capita decreases on average by 4 percent over the two first years after sanctions imposition and shows no signs of recovery in the three years after sanctions are removed. The second study estimates a reduction in GDP growth that starts at between 2,3 and 3,5 percent after the imposition of UN sanctions and, although it decreases over time, only becomes insignificant after ten years. It should be considered that a lower growth rate compounds over time: experiencing a slower growth even by only 1 percent over ten years implies a total loss of almost 15 percent. As a comparison, the average GDP loss due to the Covid-19 pandemic is estimated to be 3,4 percent in 2020.
These studies have limitations. Countries under threat of sanctions are probably making efforts to avoid punishment, which might imply that these countries are precisely the ones who would be most negatively affected by the sanctions. If so, the impact found by Gutmann et al. (2021) is probably underestimated. Neuenkirch and Neumeier (2015) only look at UN sanctions, which on one hand might give a larger impact because of the multilateral coordination. But on the other hand, the issue of an appropriate counterfactual emerges again: countries whose sanctions are vetoed might be larger, more influential, and better connected within the international community or to some of the major powers, which may also affect their economic success in other ways.
Kwon et al. (2020) adopt a different technique and come to a different conclusion. They use an instrumental variable (IV) approach and find that standard OLS overestimates the negative effect of sanctions, in other words, that sanctions’ effects are less negative than we think. They find an instantaneous effect on per capita GDP that becomes insignificant in the long run, just as if sanctions never happened.
Our confidence in these estimates hinges upon the validity of the IV used. In this case, the actual imposition of sanctions is replaced by its estimated likelihood based on sender countries’ variation in institutions and diplomatic policies (which are exogenous to the target country’s economic developments) and pre-determined country-pair characteristics (trade and financial flows, travels, colonial ties). Therefore, episodes where sanctions are imposed because the sender country happens to be in a period of hawkish foreign policy and because the target does not have strong historical relations with them are contrasted to episodes in which the opposite is true, and sanctions are therefore not implemented, everything else being equal.
The results also show that there is heterogeneity across types of sanctions, with trade sanctions having both a short and long run negative impact, while smart sanctions (i.e. sanctions targeted on particular individuals or groups) have positive effects on the target country’s economy in the long run. This is quite an important point in itself. Often, sweeping statements about effectiveness of “sanctions” lump all the different measures together, and fail to appreciate that there may be substantial differences. However, the effect of one or another type of sanctions will vary depending on the structure of the economy that is hit.
A third approach is the synthetic control method. Here the researcher tries to replicate as closely as possible the path of economic development in the target country up to the point of sanctions’ implementation, using one or a weighted average of several other countries. In this way, evolution after sanctions’ inception can be compared between the actual country and its synthetic control. Gharehgozli (2017) builds a replica of Iran based on a weighted combination of eight OPEC member countries, two non-OPEC oil-producing countries and three neighboring countries, that match a set of standard economic indicators for Iran over the period 1980-1994. The study finds that over the course of three years the imposition of US sanctions led to a 17.3 percent decline in Iran’s GDP, with the strongest reduction occurring in 2012, one year after the intensification of sanctions (2011-2014) was initiated.
This is a stronger effect than those presented earlier. However, it only speaks to the special case of Iran, rather than estimating a broader global average effect. Another study focusing on Iran (Torbat, 2005) makes the important point that the effect of sanctions varies by type: financial sanctions are found to be more effective (in lowering Iran’s GDP) than trade sanctions – which contrasts with what is found to be true on average by Kwon et al. (2020).
Finally, the relation between economic damage and the effectiveness of sanctions in terms of reaching their goals is debatable. In a theoretical model, Kaempfer et al. (1988) suggest that this relation might even be negative and that the most effective sanctions are not necessarily the most damaging in economic terms. The sanctions most likely to facilitate political change in the target country are those designed to cause income losses on groups benefiting from the target country’s policies, according to the authors.
The Effect of Sanctions on Russia
Are these results from previous studies useful to form expectations about the effects of the current sanctions on Russia? The invasion of Ukraine which started at the end of February was a relatively unexpected event, at least in character and scale, in contrast to what can be said in the majority of situations involving sanctions. However, the context leading up to it was not one of normality either. Besides the global pandemic, Russia was already under sanctions following the Crimean Crisis in 2014. The impact of those economic sanctions, and of the counter-sanctions imposed by Russia as retaliation, is still unclear – and will be in all probability completely dwarfed by the current sanction wave as well as other exogenous shocks, such as significant changes in oil prices in this period. Kholodilin et al. (2016) estimated the immediate loss of GDP in Russia to be 1,97 percent quarter-on-quarter, while no impact on the aggregate Euro Area countries’ GDP could be observed. A Russian study (Gurvich and Prilepsky, 2016) forecasted for the medium term a loss of 2,4 percentage points by 2017 as compared to the hypothetical scenario without sanctions. This pales in comparison to the magnitude of consequences that are being contemplated now. Even the potentially optimistic, or at least conservative, assessment of the current situation by the Russian Federation’s own Accounts Chamber, in the words of its head Alexei Kudrin, suggests that: “For almost one and a half to two years we will live in a very difficult situation.” At the end of April, they published revised forecasts on the economic situation, among which the one for GDP is shown below. Russian Central Bank chief Elvira Nabiullina also sounded bleak, speaking in the State Duma: “The period when the economy can live on reserves is finite. And already in the second – the beginning of the third quarter, we will enter a period of structural transformation and the search for new business models.” The World Bank has forecasted that Russia’s 2022 GDP output will fall by 11.2% due to Western sanctions. These numbers do not yet factor in the announcement of the sixth EU sanction package, which famously includes an oil embargo (see an earlier FREE Policy Brief on the dependency of Russia on oil export).
Figure 1. Revised forecasts of growth rates for the Russian economy
Source: Macroeconomic survey of the Bank of Russia, April 2022.
Are these estimates realistic, and what would have been the counterfactual development without sanctions? If we believe the studies reviewed in the previous section, and also taking into account the unprecedented scale and reach of the current sanctions, at least the time horizon, if not the size, of the consequences forecast by Russian authorities is, though substantial, certainly underestimated. But there is too much uncertainty at the moment, hostilities are still ongoing and sanctions are not being lifted for quite some time in any foreseeable scenario. One reason why these sanctions are not likely to be relaxed, and why their impact is expected to be more severe than in most cases, is that a very broad coalition of countries is backing them. Not only this but the sanctioning countries see Russia’s conduct as a potential threat to the existing world order, so their motivation to contrast it is particularly strong relative to, say, the cases of Iran, North Korea, or Burma.
Moreover, these loss estimates do not yet factor in the announcement of the sixth EU sanction package, which famously includes an oil embargo. Oil is a fundamental driver of growth in Russia. An earlier FREE Policy Brief shows how two-thirds of Russia’s growth can be explained by changes in international oil prices. This is not because oil constitutes such a large share of GDP but because of the secondary effect oil money generates in terms of domestic consumption and investment. Reducing export revenues from the sale of oil and gas will therefore have significant effects on Russia’s GDP, well beyond what the first-round effect of restricting the oil sector would imply.
In short, it is too early to venture an assessment in detail, however, the scale of loss that can be expected is clear from these and many other indicators. In the longer run, it will only be augmented by the relative isolation in which Russia has ended up, implying lower investments and subpar capital inputs at inflated prices, and by the ongoing brain drain (3,8 million people have already left the country since the war began).
Conclusion
In conclusion, the debate about economic sanctions as a tool of foreign policy is often restricted to a binary question: do they work or not? There is ample support in the literature studying sanctions to say that this question is too simplistic. Even if we do not see immediate success in reaching the main aim of the sanction policy, they do cause damage, in many dimensions, and such damage is non-negligible. The political will and the regime behind it may be unaffected, but the resources they need to continue with their course of action will unavoidably shrink in the longer run.
References
- Afesorgbor, S. K. (2019). The impact of economic sanctions on international trade: How do threatened sanctions compare with imposed sanctions?. European Journal of Political Economy, 56, 11-26.
- Afesorgbor, S. K., & Mahadevan, R. (2016). The impact of economic sanctions on income inequality of target states. World Development, 83, 1-11.
- Crozet, M., & Hinz, J. (2020). Friendly fire: The trade impact of the Russia sanctions and counter-sanctions. Economic Policy, 35(101), 97-146.
- Dreger, C., Kholodilin, K. A., Ulbricht, D., & Fidrmuc, J. (2016). Between the hammer and the anvil: The impact of economic sanctions and oil prices on Russia’s ruble. Journal of Comparative Economics, 44(2), 295-308.
- Drury, A. Cooper and Dursun Peksen. “Women and economic statecraft: The negative impact international economic sanctions visit on women.” European Journal of International Relations 20 (2014): 463 – 490.
- Early, B., & Peksen, D. (2019). Searching in the shadows: The impact of economic sanctions on informal economies. Political Research Quarterly, 72(4), 821-834.
- Farzanegan, Mohammad Reza. (2019). “The Effects of International Sanctions on Military Spending of Iran: A Synthetic Control Analysis.” Organizations & Markets: Policies & Processes eJournal .
- Gharehgozli, O. (2017). An estimation of the economic cost of recent sanctions on Iran using the synthetic control method. Economics Letters, 157, 141-144.
- Gurvich E., Prilepskiy I. (2016). The impact of financial sanctions on the Russian economy. Voprosy Ekonomiki. ;(1):5-35. (In Russ.) https://doi.org/10.32609/0042-8736-2016-1-5-35
- Gutmann, J., Neuenkirch, M., and Neumeier, F., 2021. ”The Economic Effects of International Sanctions: An Event Study” CESifo Working Paper No. 9007
- Kaempfer, W. H., & Lowenberg, A. D. (1988). The theory of international economic sanctions: A public choice approach. The American Economic Review, 78(4), 786-793.
- Kholodilin, Konstantin A. and Netsunajev, Aleksei. (2016) Crimea and Punishment: The Impact of Sanctions on Russian and European Economies. DIW Berlin Discussion Paper No. 1569, SSRN: https://ssrn.com/abstract=2768622
- Kwon, O., Syropoulos, C., & Yotov, Y. V. (2020). Pain and Gain: The Short-and Long-run Effects of Economic Sanctions on Growth. Manuscript.
- Neuenkirch, M., & Neumeier, F. (2015). The impact of UN and US economic sanctions on GDP growth. European Journal of Political Economy, 40, 110-125.
- Torbat, A. E. (2005). Impacts of the US trade and financial sanctions on Iran. World Economy, 28(3), 407-434.
- World Bank. (2022). “War in the Region” Europe and Central Asia Economic Update (Spring), Washington, DC: World Bank.
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 Impact of Rising Gasoline Prices on Swedish Households – Is This Time Different?
The world is currently experiencing what can be labelled as a global energy crisis, with surging prices for oil, coal, and natural gas. For households in Sweden and abroad, this translates into higher gasoline and diesel prices at the pump as well as increased electricity and heating costs. The increase in energy-related costs began in 2021, as the world economy struggled with supply chain issues, and intensified as Russia invaded Ukraine at the end of February this year. In response, the Swedish government announced on March 14th this year that the tax rate on transport fuels would be temporarily reduced by 1.80 SEK per liter (€0.17) and that every car owner would receive a one-off lump-sum transfer of 1000 SEK in compensation (1500 SEK for car owners in rural areas). This reduction in transport fuel tax rates in Sweden is unprecedented. Since 1960, the nominal tax rate on gasoline has only been reduced three times – and then only by very small amounts, ranging from 0.04 to 0.22 SEK per liter. In this policy brief, we put the current gasoline price in Sweden into a historical context and answer two related questions: are Swedish households paying more today for gasoline than ever before? And should policymakers respond by reducing gasoline taxes?
The Price of Gasoline in Sweden
Sweden has a long history of using excise taxes on transport fuel as a means to raise revenue for the government and to correct for environmental externalities. As early as 1924, Sweden introduced an energy tax on the price of gasoline. Later in 1991, this tax was complemented by a carbon tax levied on the carbon content of transport fuels. On top of this, Sweden extended the coverage of its value-added tax (VAT) to include transport fuels in 1990. The VAT rate of 25 percent is applied to all components of the consumer price of gasoline: the production cost, producer margin, and excise taxes (energy and carbon taxes). Before the announced tax cut this year, the combined rate of the energy and carbon tax was 6.82 SEK per liter of gasoline. Adding the VAT that is applied on these taxes, amounting to 1.71 SEK, yields a total excise tax component of 8.53 SEK. This amount is fixed in the short run and does not vary with changes in the oil price.
Figure 1. Gasoline pump price: 2000-2022
Source: Monthly data on gasoline prices are provided by SPBI (2022).
Figure 1 shows the monthly average real price of gasoline in Sweden from 2000 to March of 2022. The price has increased over the last 20 years and is today historically high. Going back even further, the price is higher today than at any point since 1960. Swedish households are thus paying more for one liter of gasoline than ever before.
Figure 2. Gasoline expenditure per 100 km
Source: Trafikverket (2022).
However, a narrow focus on the price at the pump does not take into consideration other factors that affect the cost of personal transportation for households. First, the average fuel efficiency of the vehicle fleet has improved over time. New vehicles sold today in Sweden can drive 50 percent further on a liter of gasoline compared to new vehicles sold in 2000. Arguably, what consumers care about most is not the cost of one liter of gasoline per se but the cost of driving a certain distance – the utility we derive from a car is the distance we can travel. Accounting for the improvement over time in the fuel efficiency of new vehicles (Figure 2), we find that even though it is still comparatively expensive to drive today, the current price level no longer constitutes a historical peak. In fact, the cost of driving 100 km was as high, or higher, in the period from 2000-2008.
Second, any sensible discussion of the cost of personal transportation for households should also factor in changes in household income over time. The average real hourly wage has increased by close to 40 percent between 2000 and 2022. As such, the cost of driving 100 km, measured as a share of household income, has steadily gone down over time. Even more, this pattern is similar across the income distribution; for instance, the cost trajectory of the bottom decile group is similar to that of all employees. This is illustrated in Figure 3. In 1991, when the carbon tax was implemented, an average household had to spend around two-thirds of an hour’s wage to be able to drive a distance of 100 km. By 2020, that same household only had to spend one-third of an hour’s wage to drive the same distance. There is an increase in the cost of driving over the last two years but it is still cheaper today to drive a certain distance, in relation to income, compared to any year before 2012.
Taken all of this together, we have seen that over time, vehicles use fuel more efficiently on the expenditure side, and households earn higher wages on the income side. Based on this, we can conclude that the cost of travelling a certain distance by car is not historically high today. On the contrary, when measured as a share of income, it was 50 percent more expensive for most of the 21st century.
Figure 3. Cost of driving as a share of income
Source: Data on average hourly real wages are provided by Statistics Sweden (2022).
Response From Policymakers
It is, however, of little comfort for households to know that it was more expensive to drive their car – as a share of income – 10 or 20 years ago. We argue that what ultimately matters for the household is the short run change in cost – and the speed of this change. If the cost rises too fast, households cannot adjust their expenditure pattern quickly enough and thus feel that the price increase is unaffordable. And the change in the gasoline price at the pump has been unusually rapid over the last 12 months. From the beginning of 2021 until March of 2022, the pump price has risen by around 50 percent.
So, should policymakers respond by lowering gasoline taxes? The possibly surprising answer is that lowering existing gasoline tax rates would be counter-productive in the medium and long run. Since excise taxes are fixed and do not vary with the oil price, they reduce the volatility of the pump price by cushioning fluctuations in the market price of crude oil. The total excise tax component including VAT constitutes more than half of the pump price in Sweden, a level that is similar across most European countries. This stands in stark contrast with the US, where excise taxes only make up around 15 percent of the consumer price of gasoline. As a consequence, a doubling of the price of crude oil only increases the consumer price of gasoline in Sweden by around 35 percent, but in the US by around 80 percent. Furthermore, households across Sweden, Europe, and the US have adapted to the different levels of gasoline tax rates by purchasing vehicles with different levels of fuel efficiency. New light-duty vehicles sold in Europe are on average 45 percent more fuel-efficient compared to the same vehicle category sold in the US (IEA 2021). As such, US households do not necessarily benefit from lower gasoline taxation in terms of household expenditure on transport fuel and are even more vulnerable to rapid increases in the price of crude oil. Having high gasoline tax rates thus reduces – and not increases – the short run welfare impact on households. Hence, policymakers should resist the temptation to lower gasoline tax rates even during the current energy crisis. In the medium and long run, households would buy vehicles with higher fuel consumption and would be more exposed to price surges in the future, again compelling policymakers to adjust tax rates and creating a downward spiral. Instead, alternative measures should be considered to alleviate the effects of heavy price pressure on low-income households – for instance, revenue recycling of the carbon tax revenue and increased subsidies for public transport.
Conclusion
To reach environmental and climate goals, Sweden urgently needs to phase out the use of fossil fuels in the transport sector, which is Sweden’s largest source of carbon dioxide emissions. This is exactly what a gradual increase of the tax rate on gasoline and diesel would achieve. At the same time, it would benefit consumers by shielding them from the adverse effects of future oil price volatility.
The most common response from policymakers goes in the opposite direction. In Sweden, the Social Democrats – the governing party – have announced a tax cut on gasoline and diesel of 1.80 SEK per liter but the political parties in opposition have promised even larger tax cuts. Some proposals would even effectively abolish the entire energy and carbon tax on gasoline. Similar tax cuts have been announced for example in Belgium, France, the Netherlands, and Germany. Therefore, this time is indeed different – but in terms of the exceptional reactions from policymakers rather than in terms of the cost of gasoline that households face.
References
- IEA. (2021). “Fuel Consumption of Cars and Vans” Tracking Report, International Energy Agency, November 2021.
- SPBI. (2022). “Svenska Petroleum och Biodrivmedel Institutet: Data Set” SPBI. drivkraftsverige.se/statistik/priser/bensin/
- Statistics Sweden. (2022). “Average hourly wage statistics”. Available: http://www.statistikdatabasen.scb.se
- Trafikverket. (2022). “Vägtrafikens utsläpp 2021” Tech. rep., Swedish Transport Administration, February 7th 2022.
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.
Financial Aid to Ukrainian Reconstruction: Loans Versus Grants
This brief provides an overview of the discussion on the relative merits of grants and loans in the literature on foreign aid, including a short section on debt relief initiatives. These claims are then tested against the context of Ukrainian post-war reconstruction, and it is argued that the case for providing grants is very strong. This argument is based on the magnitude of the investments needed, the need to create a long-run sustainable economy, the road towards a future EU membership, and the global value of a democratic and prosperous Ukraine as a bulwark against autocratic forces.
Introduction
One topic in the discussion on the post-war reconstruction of Ukraine is to what extent foreign support should come as loans or grants. The case at hand regards reconstruction in the aftermath of a military invasion by an aggressive neighbor. Therefore, Ukrainian reconstruction is sometimes compared to the Marshall Plan, the US package to help rebuild Europe after World War II. But this choice is also part of the more general discussion on foreign aid, comparing concessional loans (loans with lower interest rates than the market rate) with grants (financial transfers with no expectation of repayment), not least since many aid receiving countries have been highly indebted. What are then the arguments in favor of one or the other in the foreign aid literature? And how should we think about this in the context of the Ukraine crisis?
The Case for Loans
From a donor perspective, loans could be preferred from a purely financial viewpoint, as long as they are repaid. This must be put into the perspective of the purpose of foreign aid, though. If the purpose is to increase the welfare of the poor, and if loans cause macroeconomic imbalances that eventually lead to a debt crisis, using loans for aid will defeat its purpose. It is thus important, even from a donor perspective, to differentiate between the pure financial costs and the effectiveness and efficiency of foreign aid in relation to the stated goals. Yet, the paradigm on which development banks such as the World Bank motivate their strategy is that, even from an effectiveness perspective, loans may outperform grants. In their model, the bank has a broad portfolio of investments across multiple countries prioritized in order of the social rate of return. By lending out money, the bank can invest the returns from the most prioritized project into the second-most prioritized project, most likely in a different country. If the money instead had been given as a grant, the best possible outcome is that the receiving country can now invest the returns in the next best project within that country. This argument thus relies on the assumption that development banks can continually identify the most promising recipients among their wide portfolio of alternatives.
It has also been argued that grants may reduce incentives to raise tax revenues, and encourage government consumption over investments, as there is no need to generate net revenues to repay the debt (e.g., Clements et al. 2004; Djankov et al. 2004). From a donor perspective, it can also be argued that the monitoring of grants may be weaker because donors have no direct financial interest in the success of a project if it is financed by a grant. The disciplining effect of loans, though, relies on the absence of moral hazard problems. If receiving governments expect debt to be forgiven anyway when it is perceived as unsustainable and counterproductive to the country’s development, loans may be no better.
Based on arguments such as those above, part of the literature suggests that concessional loans are more likely than grants to promote growth in recipient countries, at least in good institutional environments. Cordella and Ulku (2007) look into this in detail and develop a model linking the degree of concessionality, for a given level of foreign aid (i.e. the extent to which finances are on preferential terms compared to market rates), to the receiving country’s economic growth rate, in a world where default is possible. Concessionality varies from 100 percent grants to 100 percent loans on market terms. The model suggests that a country with better policies and stronger institutions has a higher absorptive capacity for investments, meaning it can handle a lower level of concessionality (i.e., more loans, fewer grants) without going into default. They also argue that the immediate incentives for default on a loan are higher for a poorer and more indebted country as the cost of servicing the loan is higher. This would motivate relatively more grants and fewer loans to countries that are poor and highly indebted. Taking this to the data, they find in consistence with their theory that for any given level of total assistance, the impact on growth is increasing with the degree of concessionality for poor countries with weak policy and institutional environments, whereas this matters less for richer countries with better policies and stronger institutions. Looking at the level of indebtedness, the results are inconclusive.
The Case for Grants
The arguments above generally favor loans over grants, but it is of course crucial to also consider the risks and consequences of excessive debt burdens and sovereign default. Perhaps the most dramatic example of the potential consequences of shouldering a country with an excessive debt burden comes from Germany after the end of World War I. The economic struggles and sense of humiliation that followed have been argued to have contributed to German grievances leading up to World War II. Less dramatic but still with significant implications is the “lost decade” affecting Latin American middle-income countries in the 1980s. The combination of cheap credit from oil-exporting countries and the sudden dramatic increase of international interest rates following US policies in the early 1980s resulted in unsustainable levels of commercial loans. This crisis led to a US initiative, the Brady Plan, by which bank loans were consolidated and partially backed by the US government.
Excessive lending is often the result of distorted incentives. Within development banks, there are widely recognized internal incentives to get projects “through the door” (e.g., Briggs 2021). This “aid pushing” happens for both grants and loans, but the consequences can be more detrimental for loans if this leads to unsustainable debt levels. Similarly, there is evidence of defensive lending, where countries receive loans simply to be able to repay previous loans. Birdsall et al. (2003) find that donors lent more to African countries with bad policies if they had a large existing debt. On the other side, recipient country governments with short-term horizons and in environments with weak institutional checks and balances do not necessarily internalize the full costs of excessive lending. Due to these incentives on both sides, loans too often reach unsustainable levels, with debt to GDP ratios and debt to net export revenues becoming increasingly alarming.
With increased recognition of the costs of development of unsustainable levels of official lending, debt negotiations targeting highly indebted low-income countries have become common. These negotiations have often taken place through the Paris Club (a group of 22 high or upper-middle income creditor nations, including Russia) or through the HIPC (Highly Indebted Poor Countries) initiative (e.g. Birdsall et al. 2002). These debt reduction agreements have been continuously renegotiated, offering more and more generous conditions including debt forgiveness, rescheduling of existing loan terms, and more focus on grants in the portfolios of official financing.
Of particular relevance for this note, though, are the discussions around these initiatives that illustrate the different arguments made in favor of, or against, debt relief. As brought up in Birdsall et al. (2002), critique against the HIPC initiatives came from both sides. On the one hand, some argued that debt forgiveness was just more aid “down the rathole”, encouraging irresponsible policies by receiving governments (e.g. Easterly 2001), and fuelled by commercially motivated bilateral donors and multilateral institutions with misguided bureaucratic incentives. In order for aid to be effective, much more stringent conditionality was needed, and if that didn’t work, stricter selectivity in terms of which governments to partner with. On the other hand, others argued that the initiatives did not go far enough (e.g. Sachs, 2002). The economic arguments largely relied on concepts of a poverty trap, impossible to escape under conditions of a heavy debt burden requiring scarce foreign exchange to be used for debt service and discouraging investments. These countries were perceived as particularly vulnerable to adverse economic shocks, and as such, in need of insurance mechanisms that wouldn’t burden them with claims hampering their ability to prosper looking forward. But there was also a moral dimension, with blame focused on the creditor side, arguing that citizens of poor nations could not be burdened by debt issued for political reasons by creditors looking the other way when receiving rulers used proceeds for personal purposes.
Financing Post-war Recovery
The discussion above relates to foreign aid in general. The situation of financing post-war recovery is more specific, but past examples may give some points of reference. It should be noted, however, that every situation is unique in terms of the level of destruction, preconditions for a quick recovery, the political ramifications, and the risk of a resurgence of violence. And all these factors matter for the ability and willingness of foreign actors to step in and help.
An often-made reference in conjunction with Ukrainian recovery plans is the Marshall Plan, also known as the European Recovery Plan following World War II. Through this plan, financed by the US, initially 16 countries in Europe were getting “help to self-help” at an amount corresponding to roughly 10,5 percent of the countries’ GDP at the time (roughly about $13 billion, or $138 billion in 2019 dollars). The resources were spent differently across receiving countries, depending on the level of physical destruction. Importantly, grants accounted for as much as 90% of the total resources (Becker et al. 2022). More generally, grants usually account for a more significant share of aid flows when it comes to post-war reconstruction. This is natural, as a large share of the funding typically goes to humanitarian relief, and war-torn countries tend to be saddled with debt and a low capacity to raise domestic revenues in the short to medium term given the destruction of the war.
The common reference to the Marshall Plan in the context of Ukraine is probably partly geographically motivated: it is another war in Europe. But there are also other reasons, such as the direct unprovoked aggression by one of the world’s leading military powers, and the potential ramifications for world peace and the existing world order. The Marshall plan was motivated by the desire to avoid the mistakes from the peace agreements after WWI, and to help create a unified western Europe as a bulwark against further communist expansion from the Soviet Union. There are similar arguments to be made for the case of Russia’s war on Ukraine.
Implications for Ukraine Reconstruction
According to World Bank statistics, the total external debt stock of Ukraine in 2020 was $130 billion in current values, or 81,4 % of Gross National Income (GNI). This is already quite high, but the war has of course completely upended the situation and the IMF argued that Ukraine was facing debt sustainability issues already by the beginning of March 2022. Public finances are in the short run facing double pressure from a steep fall in revenues as economic activity drops and the ability to raise taxes is eroded, and an increase in expenditures on defence and humanitarian relief. Looking ahead, estimates of the Ukrainian costs of the war range between $440 and $1 000 billion by end of March 2022, but there is of course high uncertainty, and the bill is increasing for each day that the war goes on (Becker et al. 2022). This could be compared to the 2021 estimate of Ukraine’s GDP at around $165 billion. Even in the most optimistic scenarios, the rebuilding effort will be very costly, and will require massive amounts of foreign capital.
The sheer amount of effort needed in itself speaks to the need for grant financing. Rebuilding will require both public and private capital, and attracting new investments will necessitate an economic environment that is perceived as stable, dynamic, and conducive to long-term growth. As in the discussion on debt forgiveness for low-income countries above, such new investments are unlikely to materialize if the debt situation is deemed unsustainable. Furthermore, arguments in favor of loans over grants on grounds of fostering domestic macroeconomic responsibility and reducing moral hazard problems, fall flat when a country is invaded by an aggressive neighbor. Ukraine has had its share of bad politics, but the current situation is not caused by poor policies, lack of reform, or irresponsible lending under the assumption of future bailouts.
It should also be noted that both the Ukrainian government and representatives of the European Union (EU) have emphasized the long-term ambition that Ukraine should join the EU. This will not be possible, however, unless the country’s economy is in order, including a sustainable debt level, according to EU requirements for all joining members. Were Ukraine to shoulder excessive levels of debt at this moment it would thus jeopardize this ambition. And not least, Ukraine is fighting for its survival, but the war is also part of a wider emerging struggle between democratic and authoritarian forces over the future world order. The result of the war is of great significance for all democratic countries, though it’s the people of Ukraine that are facing the immediate horrific consequences. It is thus in our common interest to rebuild a prosperous and democratic Ukraine also as a bulwark against further authoritarian ambitions to change the existing world order. A Ukraine saddled with an unsustainable debt burden runs completely counter to the interests of the democratic world.
The Marshall Plan was successful in its goal “to permit the emergence of political and social conditions in which free institutions can exist”. This allowed for economic and political cooperation to take roots in western Europe, also contributing to political stability and prosperity. This cooperation expanded further east after 1989 with the inclusion of new member states into the European Union, largely solidifying a move towards market-based democracy in the region (despite some recent setbacks, primarily in Hungary). Let us build on these successful examples. The current situation offers an opportunity to bring an additional 44 million people into the European umbrella of peaceful cooperation in the near future. This ambition would become much more difficult, though, if Ukraine was saddled with an excessive debt burden.
References
- Becker, Torbjörn, Barry Eichengreen, Yuriy Gorodnichenko, Sergei Guriev, Simon Johnson, Tymofiy Mylovanov, Kenneth Rogoff, and Beatrice Weder di Mauro. (2022). “A Blueprint for the Reconstruction of Ukraine” Rapid Response Economics 1, CEPR Press.
- Birdsall, Nancy, John Williams, and Brian Deese. (2002). “Delivering on Debt Relief: From IMF Gold to a New Aid Architecture”, Peterson Institute for International Economics, Washington DC.
- Birdsall, Nancy, Stijn Claessens, and Ishac Diwan. (2003). “Policy Selectivity Forgone: Debt and Donor Behavior in Africa” World Bank Economic Review 17 (3): 409–35.
- Briggs, R. C. (2021). “Why does aid not target the poorest” International Studies Quarterly 65 (3), 739-752.
- Benedict Clements, Sanjeev Gupta, Alexander Pivovarsky, and Erwin R. Tiongson. (2004). “Foreign Aid: Grants versus Loans” Finance and Development, September, pp. 46–49.
- Cordella, Tito and Hulya Ulku. (2007). “Grants vs. Loans” IMF Staff Papers, 54(1), 139-162.
- Djankov, Simeon, Jose G. Montalvo, and Marta Reynal- Querol. (2004). “Helping the Poor with Foreign Aid: The Grants vs. Loans Debate” World Bank, Washington, D.C.
- Easterly, William. (2001). “Debt Relief”, Foreign Policy 126, 20-26.
- Sachs, Jeffrey. (2002). “Resolving the Debt Crisis of Low-Income Countries” Brookings Papers on Economic Activity 1, Brookings Institution Press.
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 EU Import Bill and Russian Energy Sanctions
Since the beginning of the Russia-Ukraine war, the West has been contemplating sanctions on Russian oil and gas imports. For the EU, this plan poses a significant challenge due to the long-existing sizable dependency on Russian energy. In this brief, we outline the possible effects of banning Russian oil and gas on the energy import bill across the EU. While the effects of such a ban will go beyond a direct increase in the import costs of oil and gas, our estimates provide a useful reference point in discussing the impact of such sanctions on the EU. Our estimates suggest that the relative increase in the import costs in the case of an oil embargo would be more evenly spread across the Member States, than in the case of a natural gas ban. This parity makes an EU-wide Russian oil embargo a more straightforward sanction policy. In turn, a full replacement of Russian gas imports across the EU – due to either a gas embargo or retaliation from Russia in response to an oil ban – is likely to require some kind of solidarity mechanism.
Introduction
Since the beginning of the Russian invasion of Ukraine, the West has been discussing the idea of sanctioning the aggressor by banning Russian energy imports. The motivation is quite straightforward. In 2021, Russian oil and gas exports constituted 49% of Russian goods exports or 14 % of Russian GDP, and the Western world (in particular, the European Union) is the main recipient of these exports. Banning Russian oil and gas export would, thus, lead to heavy pressure on the Russian economy.
The discussion has been quite heated. The US actually implemented a ban on Russian oil and gas in early March 2022, but this gesture has been largely seen as relatively symbolic, as the US dependency on Russian energy imports is quite limited. EU politicians have voiced different opinions about the feasibility of Russian energy sanctions. While some advocate an immediate ban, others argue for a more gradual decrease in imports or even for continuing imports effectively in a business-as-usual fashion. While the EC has announced plans to cut down the consumption of Russian gas by two-thirds in 2022 and mentioned the implementation of “some form of oil embargo” as part of their 6th sanction package, there is still no consensus across the EU. Sanctions on Russian oil and gas imports have not been implemented in the EU by the time of writing this brief.
The main reason for this hesitation is the extent to which Russia remains the main energy supplier. In 2020, 39% of gas and 36% of oil and oil products in the EU were imported from Russia, and the feasibility and consequences of replacing these with alternative supplies are debatable. Since the beginning of the war academics, international organizations and consultancies have offered a variety of analytical materials on the feasibility and implications of such energy sanctions (see e.g., Bachmann et al. 2022. Chepeliev et al, 2022, Fulwood et al., 2022, Guriev and Itskhoki, 2022, Hilgenstock and Ribakova, 2022, IEA, 2022, RYSTAD 2002a,b, Stehn, 2022 to name just a few).
This brief contributes to these estimates by discussing how a Russian oil and gas ban could affect the energy import bill across individual EU countries. We start by providing details on the EU’s dependency on Russian oil and gas imports. We then proceed to access the scope of the costs that a ban on Russian energy could imply for the EU energy sector. We conclude with a discussion about the feasibility of political agreement on such sanctions.
Import Dependency and Dependency on Russian Energy Across the EU
The two primary channels through which a Russian energy ban would affect the vulnerability of an EU country are the dependency on Russian oil and gas, and the overall energy import dependency. The former matters since a ban would imply an immediate necessity to replace missing volumes of energy. This would lead to an increase in energy prices widely across markets, thereby signifying the importance of the latter channel, the overall import dependency.
Figures 1 and 2 depict the dependency on Russian oil and gas across the EU member states. In Figure 1, the dependency is measured as a ratio of Russian energy imports to the gross available energy for each energy type separately – crude oil, oil and oil products, and natural gas. However, this measure may not reflect the importance of the respective energy type in a country’s energy portfolio. For example, in Finland, Russian gas imports constitute 67% of gross available natural gas. However, natural gas is less than 7% of the country’s energy mix, thus the overall effect of Russian gas on the Finnish energy sector and economy is rather limited. To account for this, Figure 2 offers an overview of the contribution of Russian energy imports to the cumulative energy portfolio across the EU.
Both figures show that there is a large variation both in terms of the contribution of individual energy types and in terms of overall dependency on Russian fuels. For example, the latter is almost negligible for Cyprus and well over 50% for Lithuania (however, Figure 2 accounts for re-exports and, thus, overestimates the role of Russian energy imports for Lithuanian domestic available energy in 2020.
Figure 1. Share of Russian energy imports in gross available energy, by fuel, 2020.
Note: Gross available energy indicates the overall available energy supply on the territory of the country. It is defined as Gross available energy = Primary production + Recovered and recycled products + Imports – Exports + Change in stock. . In several EU member states natural gas transit may be included in the imports. As a result, the high share of Russian energy may reflect not only imports for consumption but also for transit, as well as fuels for refinement and further export (e.g. oil products in Estonia (cut at Figure 1, 285%), Lithuania (cut at Figure 1, 201%), Slovakia and Finland). Austrian data on natural gas imports from Russia are confidential and not represented in the diagram. Denmark and Croatia did not report Russian gas imports data for 2020 to Eurostat. Source: Eurostat
Figure 2. Share of Russian energy imports in total gross available energy, 2020. Source: Eurostat
Note: See Figure 1. Source: Eurostat
While the above data summarizes the EU dependency on Russian energy imports in volume terms, it is also useful to have a sense of the costs of this dependency. As we are not aware of any source that has accurate data on the value of imports across the EU states, we construct a back-of-the-envelope assessment of the costs of Russian energy imports to the EU in 2021 using the available trade data for 2021 and the allocation of imports across the EU Member States for 2020 (see Appendix 1 for more details). Admittedly, these estimates only account for the differences in prices of energy imports from Russia vs. other suppliers; it does not capture e.g., the difference in prices of Russian gas across the Member States. Still, they offer useful insight into the scope of these expenses, in levels (Figure 3) and the share of GDP (Figure 4).
The results suggest that, while the expenses are quite sizable – e.g., the total value of Russian fossil energy imports to the EU in 2021 exceeds 110 bln EUR, – they correspond to around 0.7% of European GDP. Again, there is variation across the Member States, but in most cases – effectively all cases that do not account for re-export – the share of Russian energy imports is below 2% of GDP.
Figure 3. Value of Russian fossil energy imports, bln EUR, 2021.
Source: Eurostat, GazpromExport, Central Bank of Russia, author’s own calculations, see Appendix 1.
Figure 4. Share of oil, oil products and gas imports in GDP, 2021.
Source: Eurostat, GazpromExport, Central Bank of Russia, author’s own calculations, see Appendix 1.
Figure 4 also touches upon the second source of vulnerability towards a ban on Russian energy, mentioned at the beginning of this section. It depicts not only the value of Russian oil and gas imports as a percent of GDP but the overall dependency on imports of oil and gas as a share of GDP. The larger this dependency is, the bigger is the impact of an increase in energy prices for a country. Figure 4 not only confirms the abovementioned variation across the Member States but also shows that some countries with little-to-moderate direct dependency on Russian oil and gas – e.g., Portugal or Spain, – are still likely to experience a sizable negative shock to their energy expenses due to the market price increase.
Importantly, these figures give only a very rough representation of the potential damage that a ban on Russian energy imports may cause to the EU economies. Two EU Member States with a comparable dependency could react to the shortage of Russian gas in very different ways, depending on a variety of other factors – the extent and scalability of domestic production, diversification of their remaining energy portfolio in terms of energy suppliers and types of oil the economy relies on (e.g., light vs. heavy), energy infrastructure (e.g., LNG regasification facilities or storage), consumption structure, etc. Le Coq and Paltseva (2009, 2012) discuss in detail some of these factors, and the possibilities to account for them. However, for the sake of simplicity, in this brief we focus on the (volume- and value-based) measures of dependency.
Potential Costs of Russian Energy Import Ban
In this section, we discuss the potential implications of banning imports of Russian oil and gas on the costs of fossil energy imports in the EU. We offer a few historical parallels in order to assess the potential scope of the price reaction to such a ban. Furthermore, we proceed to provide estimates of the costs of oil and gas imports across the EU Member States, would such sanctions be implemented.
Oil Imports Ban
We start with a potential ban on Russian oil and oil product imports. To put things in perspective, it might be useful to present some numbers. According to the IEA, Russia recently surpassed Saudi Arabia as the world’s largest oil and oil products exporter. In December 2021, global Russian crude and oil product exports constituted 7.8 million barrels per day (mb/d), with exports of crude oil and condensate at 5 mb/d. Out of the total 7.8 mb/d, exports to OECD countries constituted 5.6 mb/d, with crude oil exports amounting to 3.9 mb/d. Assuming that the size of the global oil market in 2021 returns to its pre-pandemic 2019 level (the actual data for 2021 global oil consumption is not available yet), Russian crude oil exports to the OECD constitute 8.6% of global crude exports. The corresponding figure for oil products is 6.8% (BP, 2021).
So, what would happen if the developed world – which for the purpose of this analysis we proxy by OECD – bans Russian oil exports? In the recent public discussion, many voices have compared this potential development to the 1973 oil crisis. This crisis was initiated by OAPEC’s – the Arab members of OPEC, – oil embargo on the US in response to their support of Israel during the Yom Kippur War. The OAPEC, the biggest group of oil exporters at the time, completely banned oil exports to the US (and a number of other western countries), and also introduced production restraints that affected the global oil market. The (WTI) oil price during this episode went up by a factor of three (see, e.g, Baumeister and Kilian, 2016).
However, a few important features are likely to differ between the oil crisis of 1973 and the potential impact of the Russian imports ban. First, the net loss of oil supplies during the Arab embargo was around 4.4 mb/d, which at that point constituted around 14% of traded oil (Yergin, 1992). Recall that Russian supplies to OECD are around half of this share. Moreover, it is likely that the ban would not lead to a complete withdrawal of these amounts from the market, but rather to a partial rerouting of Russian oil to Asia and, consequently, a readjustment of world oil trade flows. Second, Yergin (1992) points out that, at the time of the 1973 oil crisis, oil consumption was growing at 7.5% per year, which exacerbated the impact of the embargo. In contrast, the current assessments of oil demand growth are at around 2% per year (IEA, 2022). Third, the energy portfolios are much more diversified now than in 1973, with gas and renewables playing a more substantial role. In the case of an isolated oil imports ban (not extending to gas imports), this would argue in favor of a more moderate price impact. Finally, the oil embargo of 1973 was a never-seen-before episode in the history of the oil market. The uncertainty about future developments has likely contributed to the oil price increase. While there is substantial uncertainty associated with the impact of a Russian oil imports ban, it is arguably lower than in 1973. Based on these considerations, a three-fold oil price increase in the case of a Russian oil export ban seems highly unlikely.
As a possible lower bound of the price impact, one can consider a much more recent price shock brought about by drone attacks on the oil processing facilities Abqaiq and Khurais in Saudi Arabia in 2019. In the initial assessment of the damage, Saudi Arabian authorities stated that the attack decreased the national oil production by 5.7 mb/d – which is more than the total of Russian oil exports to OECD. As a reaction, the intraday oil price went up by 20 %, and the daily oil price by 12%. In two weeks, production and export capacity was almost back to normal and the price returned to pre-shock levels.
Notice that the scale of the daily shortage in this episode exceeds the likely shortage under the Russian imports ban. However, a moderate price reaction, in this case, was clearly driven by expectations for the temporary nature of the shortage, as the damage was to be repaired in a matter of a few weeks, if not days. In comparison, the Russian oil ban is likely to last much longer. In this way, a price increase of 12%, or even 20%, would be an underestimation of the effect of a Russian oil imports ban.
While the above discussion suggests some bounds for the possible price effects of a Russian oil ban, the uncertainty around such price developments is very high. Figure 5 shows the cost estimates of oil and oil products imports to the EU for two potential price levels – $120/b, and $180/b. Each price would roughly correspond to an increase of 33%, and 100%, respectively, relative to the pre-invasion price of $90/b. In the estimation, we simplistically assume that the price of oil products increases by the same amount as the price of crude oil. We also assume that the missing Russian oil can be replaced by alternatives, such that oil consumption does not change compared to the 2021 level for the lower price scenario and that it decreases by 2% for the high-cost scenario due to the demand adjustments.
Figure 5. Estimated effect of Russian oil ban on oil and gas imports in 2022: value of oil and oil products imports, EUR bln (left axis), and oil import expenses relative to 2021 level (right axis).
Source: Eurostat, GazpromExport, Central Bank of Russia, author’s own calculations, see Footnote 1.
The estimates suggest that the total oil and oil products import costs for the EU would be just above EUR 640 bln for the $120/b price level and EUR 940 bln for the $180/b price level. Furthermore, the costs across the EU Member States would vary greatly depending on the size of the economy and its exposure to oil imports.
This shows that – provided that the Russian oil will be fully replaced but at a higher price – the expected cost of this is in the range of 1.7-1.9 times the 2021 expenses at 120$/b, and 2.5-2.8 times that if the price would be 180$/b. While there is some variation across Member States, mostly driven by the removal of the somewhat cheaper Russian oil from the consumption basket, it is rather limited. Figure 5 also demonstrates that the ban on Russian oil imports is going to affect not only countries that directly depend on Russian oil but also countries with large oil and oil products imports due to the market price effects.
Gas Imports Ban
Now we proceed to discuss the costs of banning Russian gas imports into the EU. While LNG has increased the fungibility of the natural gas market, it remains sizably segmented. Therefore, we concentrate on the effect on the European market.
Russian gas constituted around 39% of the EU gas consumption volumes in 2020, and just below 30% in 2021 due to restricted supply during the second half of the year (McWilliams, Sgaravatti and Zachmann, 2021). It is currently a common understanding that fully substituting 155 Bcm of Russian gas imports in 2021 with imports from other pipeline suppliers, LNG, storage, and increasing domestic production is not feasible in 2022. Different sources have given different estimates on the extent of the resulting shortage, see e.g. Table 1.
Table 1. Alternatives to replace EU imports of Russian natural gas
Source: Rystad Energy (2022a, 2022b), Fulwood et.al (2022), IEA (2022).
As shown in Table 1, the net missing gas consumption ranges between 12% and 22% across different scenarios. As there are no historical episodes in the gas market to which such a development can be compared, it is difficult to assess the potential price reaction. One rough comparison can be made based on the oil market situation during the Arab oil embargo of 1973 discussed above. Then, the net loss of oil constituted about 9% of the oil consumption in “the free world” (Yergin, 1982), even lower than the most optimistic prognosis in Table 1. However, 33 Mcb of Russian gas (or 6% of 2021 the EU’s gas consumption) has already been imported to the EU since the beginning of 2022, making the potential gas shortage quite comparable to the oil shortage of 1973. Subject to all differences between the two shocks, one can, perhaps, still argue that the gas price increase following a ban on Russian gas imports should not exceed three-fold from before the invasion.
It is important to stress here that the EU gas market situation in the case of the Russian gas embargo would be principally different from the oil market one. Due to supply shortage not coverable by the alternative gas sources, a gas embargo would lead not only to a stronger price increase than in the case of oil, but also to significant downward demand adjustments, rationing and, perhaps, even price controls. (This, again, parallels the developments during the 1973 oil crisis). The negative effect of such rationing is not accounted for by the import bill. On the contrary, a shortage of supply would imply lower gas import volumes, biasing the impact on the gas import bill downward. In this way, an import bill reaction to sanctions in the case of natural gas may more strongly underestimate the overall impact on the economy than in the case of oil.
While the above argument suggests a higher price increase in the case of a gas embargo in comparison to an oil ban, there is still a lot of uncertainty in forecasting the gas price. Figure 6 depicts the estimates for the natural gas cost across the EU for two potential price levels – EUR 160/Mwh, and EUR 240/Mwh, a two- and three-fold increase relative to the pre-invasion price level of EUR 80/Mwh. Both estimates assume a (moderate) 8% decrease in the demand reflecting the abovementioned supply shortage and demand adjustments. We assume that the shortage is affecting both the importers of Russian gas and those who use other suppliers due to the common gas market in the EU and the use of reverse flow technology – as was the case for Poland which was denied Russian gas on April 27th, 2022 due to not paying for it in Rubles (see Appendix 1 for a discussion of implications of this assumption).
Not surprisingly, the gas import costs increase drastically in comparison to 2021. The total figures for the EU would be just below EUR 680 bln in the two-fold price increase scenario, and exceed 1 trn EUR in the case of a three-fold increase, in contrast to EUR 185 bln in 2021. Again, the largest economies bear the highest costs in absolute value.
When it comes to the relative increase in gas import value, two further observations follow from Figure 6. First, there is a huge variation in the increase in the value of gas imports across the Member States, from no effect in Cyprus which does not import natural gas, to 7.7 times in the case of a price doubling and 11.5 times in the case of a price tripling. Again, this variation originates from the necessity to replace cheaper Russian gas with more expensive gas sources, and the effect is much stronger than for oil. However, just like in the oil case, the states not directly importing Russian gas will still experience a huge negative shock from such a price hike. (Recall also, that the variation of the impact across the Member States is likely underestimated here, as the gas bill does not account for potential rationing which may differentially impact the importers of Russian gas).
Second, the increase in the value of gas imports exceeds the scale of the price increase even for the least affected Member States (excluding Cyprus). This is due to the unprecedented gas price increase during the EU gas crisis that took place between late 2021 and the beginning of 2022. Due to this increase, the pre-invasion gas price in February 2022 was 60% higher than the average gas price in 2021.
Figure 6. Estimated effect of Russian natural gas ban on gas imports in 2022: value of gas imports, EUR bln (left axis), and gas import expenses relative to 2021 level (right axis).
Source: Eurostat, GazpromExport, Central Bank of Russia, author’s own calculations, see Footnote 1.
Conclusions
The above estimates suggest that a ban on Russian oil and gas imports is going to be costly for the EU. While uncertainty is very high concerning the possible energy price increase following such a ban, historical parallels together with the market characteristics suggest that both the price increase and the rise in the value of imports are going to be stronger for natural gas. The resulting increase in the EU-wide import values relative to 2021 ranges from 1.8 to 2.6 times for the considered oil scenarios, and from 3.7 to 5.5 times for the natural gas scenarios.
Unsurprisingly, the most sizable import costs will be faced by the larger EU Member States, as well as those most dependent on oil and gas imports. However, all EU countries are going to be affected due to the market price increase. While the relative rise in the import costs of oil and oil products will be fairly uniformly met across the EU states, the increase in the costs of gas exports will vary greatly, with the largest relative losses faced by the EU states that are currently more exposed to Russian gas imports.
The above figures provide a rough assessment of the potential costs of a Russian fossil fuels ban. The approach does not take into account substitutability between different fuels and resulting cross-effects on prices, which implies that the costs could be both under- and overestimated. It has a very limited and simplistic take on the demand reaction to a price increase, which again may lead to either over- or underestimation of the effect. Neither does it account for the consequences of such price increases on the costs of electricity and implications for the non-energy sector within the economies. The latter may, again, be differentially affected depending on the industrial composition and their relative energy intensity. Another factor to consider is the interconnectivity between the EU economies – for example, an increase in Germany’s energy bill is likely to have a large impact on the entire EU. Moreover, the use of the import bill as a proxy for the overall effect on the economy may have further limitations in the case of supply shortage and rationing. To provide a more precise estimate of the impact of such a ban on the entire economy, for instance on GDP, one would require an extensive and sophisticated model along the lines of the CGE approach, relying on large amounts of data (Bachmann et al. (2022) provide an excellent example of such a study of the effect on Germany). This, however, is beyond the scope of the current assessment.
Still, even this relatively simplistic assessment of import costs of a Russian energy ban offers sufficient food for thought for the discussion of the scale of damage across the EU Member States and the feasibility of oil and gas sanctions. For example, the assessment suggests that an oil ban is likely to yield relative parity across the Member States in terms of the increase in the 2022 oil import bill as compared to the 2021 level. This would imply that, were the EU to decide on a gradual sanctioning of Russian oil and gas, it would be easier to reach an EU-wide agreement on oil sanctions. In turn, moving away from Russian gas – due to either the decision to ban gas imports or retaliation from Russia in response to oil sanctions, -implies very uneven import cost exposure. Thus, to face the challenge of replacing Russian gas imports, the EU would likely need to implement some kind of energy solidarity mechanism.
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