Location: Global
Female Representativeness and Covid-19 Policy Responses: Political Representation and Social Representativeness

There is anecdotal evidence that countries with female leadership in policymaking are more efficient in combating the Covid-19 pandemic. This paper studies whether countries with high female representativeness in political and social layers respond differently to the Covid-19 outbreak. We explore patterns at a cross-country level, which enables us to consider the variation of gender implicated institutions. Our findings indicate that it is women’s social representation, rather than female political leadership, that has the potential to capture cross-country variation in Covid-19 policy responses. Our study confirms that well-functioning and effective institutions are not established from the top-down but rather from the bottom-up.
Introduction
In light of the Covid-19 outbreak and the resulting actions developed and implemented by countries worldwide, questions have been raised about government policy responses and what can trigger them. The pandemic brought forward the need for measures that help mitigate the spread of the virus such as hand washing, reduced face touching, face mask policies, and physical distancing. In many countries, the implementation of lockdowns and social distancing measures had a large impact on employment, including reductions in working hours, furloughs, and work from home arrangements (Brodeur et al., 2020; Coibion et al., 2020; Gupta et al., 2020). There are notable concerns about the potential damage non-pharmaceutical interventions can inflict on economies and labor markets (Andersen et al., 2020; Kong and Prinz, 2020). Further, the implementation of these measures requires certain institutional and individual behavioral changes. While some countries were successful in developing and implementing policy responses that addressed the challenges of the pandemic, others have experienced considerable difficulties.
There is anecdotal evidence suggesting that countries with female leadership in governmental policies are more efficient in combating the Covid-19 pandemic. Several articles from prominent media outlets, such as CNN, The Conversation and Forbes, hypothesize that female leaders are systematically better at managing the pandemic and that this divergence can be attributed to gender differences in management style and risk-taking behavior.
This policy paper explores whether countries distinguished by higher female representation in government policies, both in development and implementation, responded differently to the Covid-19 outbreak, and if so, how the response differed from other countries. For this purpose, we identify two layers of female representation: political representation and social representativeness. The layer of political representation considers the role of women’s representation in public policy design and implementation at the top level of executive and legislative institutions. Social representativeness captures women’s representativeness in different layers of society and spheres of life. It reflects social norms, legal inequality between men and women in different spheres of private, economic, and business life, as well as realized gender inequality, e.g., in labor market participation, education, or local leadership.
With respect to political representation, we address the question of whether countries distinguished by a higher female representation at top executive and legislative levels differ in terms of policy responses to Covid-19. With respect to social representativeness, we aim to capture the variation in these responses that may originate from differences in the expected reaction of the public, which in turn is driven by women’s representativeness in different layers of society. We derive evidence-based conclusions capturing the role of female leadership at the country’s executive and legislative level, as well as the role of gender representativeness in other layers and institutions of society.
The motivation for this research stems from the extensive literature on differences in values and social attitudes between men and women. For example, women have been shown to be more trustworthy, public-spirited, and likely to exhibit ‘helping’ behavior (Eagly and Crowley, 1986), vote based on social issues (Goertzel, 1983), score better on ‘integrity tests’ (Ones and Viswesvaran, 1998), take stronger stances on ethical behavior (Glover et al., 1997; Reiss and Mitra, 1998) and behave more generously when faced with economic decisions (Eckel and Grossman, 1998). Thereby, one may ask to which extent these differences transmit to public policies in societies where women are better represented, either politically or socially. While our study primarily concerns Covid-19 policy responses, we discuss other related literature on the relationship between women’s representativeness and public policy in the next section.
Our analysis shows that it is the women’s social representativeness layer, which can explain government reactions to the Covid-19 pandemic. This goes in line with the institutionalist literature, suggesting that more a gender-balanced character of institutions translates into policy measures and related outcomes. With this finding, our study suggests further evidence on the central role of institutions. Consistent with the existing evidence, we claim that well-functioning and effective institutions are not established from the top-down, but rather from the bottom-up (Easterly, 2008; Dixit, 2011; Greif, 2006). In such institutions, women’s participation in labor markets, businesses, and other spheres is essential as these are factors that distinguish countries in their response to the pandemic. While the evidence provided is suggestive, it opens further avenues for studies to assess causal relationships.
Covid-19 Policy Measurements
To conduct our analysis, we collect data from a number of different sources. For data on the Covid-19 situation and government policy responses, we use the Our World in Data portal. This online platform compiles a number of data sources, most of them updated on a daily basis. Statistics on female participation and leadership is retrieved from the World Bank and UNDP. Summary statistics of the variables are reported in Table A1 of the Appendix.
The policy response variables are based on a number of different measures implemented by national governments. These are aggregated into three composite indices: Stringency, Containment & health, and Economic support. (The index methodology can be found here.) We present the components of the three indices in Table 1 and a detailed description of the policy measures and their scoring in Appendix C.
As seen in Table 1, the Stringency and Containment & health indices have some common dimensions; containment & closure policies (C1 – C8) and public information campaign (H1). Both are rescaled to a value from 0 to 100 (100 = strictest). The Economic support index records measures such as income support and debt/contract relief and does not share any common dimensions with the other two policy response indices. The scale of the index also ranges from 0 to 100 (100 = full support). The extent of heterogeneity in government policy responses across countries is illustrated in Figures 1 – 3. While containment and closure policies are stricter in many Asian and Latin American countries, economic support is more extensive in many European countries, Canada, New Zeeland, and few other countries.
Table 1. The structure of the Covid-19 policy measurements.

Note: Categories and assigned values of policy measurements are in Appendix C.
Figure 1. Stringency Index

Note: A choropleth map shows countries/territories by their Stringency index score, based on data collected from the portal of https://ourworldindata.org/policy-responses-covid. Countries are grouped into five groups (quantiles), from the lowest to the highest values of the index.
Figure 2. Economic support index.

Note: A choropleth map shows countries/territories by their economic support index score, based on data collected from the portal of https://ourworldindata.org/policy-responses-covid. Countries are grouped into five groups (quantiles), from the lowest to the highest values of the index.
Figure 3. Containment & health index.

Note: A choropleth map shows countries/territories by their Containment and health index scores, based on data collected from the portal of https://ourworldindata.org/policy-responses-covid. Countries are grouped into five groups (quantiles), from the lowest to the highest values of the index.
Female Representativeness: Layers and Indicators
Multiple studies in economics and political science suggest that the gender of public officials shapes policy outcomes (Chattopadhyay and Duflo, 2004; Iyer et al., 2012; Svaleryd, 2009). Evidence suggests that increasing the number of women in higher ranks of public administration (legislative bodies and ministries) has a substantial impact on the political office and policymaking (Borrelli, 2002; Davis, 1997; Reynolds, 1999). On the other hand, a number of studies demonstrate that gender has no association with policy outcomes (Besley et al., 2007; Besley and Case, 2003; Bagues and Campa, 2021). The role of the institutional setting and environment can, thus, be decisive in this regard. Women are also found to be more concerned about social policy issues and prefer higher social spending than men (Lott and Kenny, 1999; Abrams and Settle, 1999; Aidt and Dallal, 2008). Further, women are more likely to use a collective or consensual approach to problem and conflict resolution rather than an approach founded on unilateral imposition (Rosenthal, 2000; Gidengil, 1995).
In our study, the political representation layer is measured as female leadership at a country’s executive level (representation in government cabinets) and participation at the legislative institution (parliament) level. To assess this, we consider the following indicators: 1) the presence of a female president or prime minister and proportion of women in ministerial positions, and 2) women’s representativeness in legislative bodies measured as the proportion of seats held by women in national parliaments. The variation of these indicators across countries is illustrated in Figures B4 – B6 in the Appendix.
Our approach to social representativeness is in line with social role theory. This framework provides a theoretical explanation of a structural approach to gender differences (Eagly, 1987; Eagly and Karau, 2002; Wood and Eagly, 2009). It claims that men and women behave according to stereotypes associated with the social roles they occupy, and these differences can, in turn, influence the role of women in local governance and leadership. In line with other research on gender, the social role theory proposes a rigorous framework for analyzing the gendered aspect of government organizations. For instance, evidence shows that women tend to be more collaborative and democratic, hence demonstrating a more caring and community-oriented behavior (Eagly and Johannesen-Schmidt, 2001).
The gender aspect of local governance indicates that the personal preferences and opinions of leaders predominate and shape policymaking (Besley and Coate, 1997). Female leaders (including municipality heads) are more inclined to favor the inclusion of citizens in the decision-making process (Fox and Schuhmann, 1999; Rodriguez-Garcia, 2015), implying that the society is a more informed and engaged stakeholder in the public policymaking (Ball, 2009). Given that municipalities are taking on a greater and more interactive role in citizens’ well-being, they become a key channel in reinforcing trust in government. Furthermore, the literature finds an interrelationship between female voters and government outcomes, whereby women’s enfranchisement affects government size and spending (Lott and Kenny, 1999; Miller, 2008, Aidt and Dallal, 2008). As such, this can lead to improvements in government outcomes and policy effectiveness. The evidence from Bloomberg’s Covid-19 Resilience Ranking suggests that success in containing Covid-19 while minimizing disruption appears to rely more on governments fostering a high degree of trust and societal compliance.
Furthermore, the patterns of gender relations in societies reflect formal and informal institutional rules and policies. Gender equality enhances good governance and helps to further improve relationships between government and citizens (OECD 2014). Similarly, Elson (1999) argues that labor markets are structured by practices, norms, and networks that are “bearers of gender”. Societies with better legal frameworks for women have more balanced gender participation in labor markets, governance, and leadership, along with more equal gender roles and less gender-biased stereotypes. We anticipate that better representation of women in policymaking in such societies is also reflected in the choice and effectiveness of Covid-19 policy measures.
Building on the above theories explaining the relevance of women’s representativeness in diverse societal layers for policy development and implementation, we identify three indices that have the potential to capture the effect of social representativeness – Women, Business and the Law index (WBLI), Gender Development Index (GDI) and Gender Inequality Index (GII). The WBLI is composed of eight indicators, covering different areas of the law related to the decisions women make at various stages of their career and life. These indicators include mobility, workplace, salary, marriage, parenthood, entrepreneurship, assets, and pension. Hyland et al. (2020) show that, globally, the largest gender inequalities are observed in the areas of pay and parenthood. That is, women are most disadvantaged by the legal system when it comes to compensation and how they are treated once they have children. The index scales from 0 to 100 (100 = equal opportunities). The diagram in Figure 4 illustrates how the components of the WBLI index measure key activities of economic agents throughout their life.
Figure 4. The linkages of 8 indicators in Women, Business and the Law index (WBLI)

Source. Women, Business and Law, 2020. World Bank Group.
The second index, the GDI, measures gender inequality in the achievements in three basic dimensions of human development: Health, measured by life expectancy at birth; Education, measured by expected years of schooling for children and mean years of schooling for adults aged above 25; and Command over economic resources, measured by estimated earned income. The same dimensions are included in the Human Development Index (HDI), and the GDI is defined as the female-to-male HDI ratio (i.e. perfect gender equality corresponds to a GDI equal to one).
Turning to the third index measuring social representativeness, the GII reflects gender-based disadvantages in the following dimensions—reproductive health, empowerment, and the labor market. The index measures the loss in potential human development due to gender inequality in achievements across these dimensions. It ranges from zero, where women and men fare equally, to one, where one gender fares as poorly as possible in all measured dimensions. One of the dimensions of the GII, women’s empowerment, has a sub-dimension – “Female and male shares of parliamentary seats”, one of our indicators measuring political representation. Generally, we do not consider the two layers being as mutually exclusive, but intersections are expected to be minimal.
Central to our study, the three indices capturing social representativeness in a country encompass the institutional quality of its society from a gender development perspective. The distribution of each index across countries is shown in Figures B1 – B3 (See Appendix B).
Women’s Representativeness and Covid-19 Policy Responses: Partial Correlation Analysis
In this section, we explore the relationship between Covid-19 policy responses and the measures of political representation and social representativeness. For this purpose, we explore (i) correlations between the indicators and indices of the political and social representation layers and (ii) partial correlations between these measures and policy response indices.
We start with a correlation analysis of the different indicators in the layers. It shows that the WBLI is in high correlation with other representativeness variables. This index captures the legal equality between women and men which has been shown to be “associated with a range of better outcomes for women, such as more entrepreneurship, better access to finance, more abundant female labor supply, and reductions in the gender wage gap”. (WB, 2021). One can think of the GDI and GII indices, as well as the political representativeness indicators, as reflections of a broad policy framework in diverse areas of social, business, and legal activities. A legal environment that promotes gender equality, even if not sufficient by itself, is likely to lead to progress in these areas. Indeed, Hyland et al. (2020) show that greater legal equality between men and women is associated with a lower gender gap in opportunities and outcomes, fewer female workers in vulnerable positions, and greater political representation of women. This way, the WBLI may capture key predispositions for women’s representativeness in society. Further, Hyland et al. (2021) show that the WBLI index is in high (partial) correlation with country GDP per capita, polity score, legal origin, religion and geographic characteristics. This evidence suggests that the WBLI may have the capacity to reflect important country characteristics which ultimately shape cross-country institutional variation.
Table 2. Scatterplot table for GDI, GII and Women, Business and the Law Index, Proportion of seats in parliament held by women and Proportion of ministerial seats held by women.

Note: Scatterplots are constructed for 149 countries. Fitted lines are based on a quadratic function, shaded areas indicate 95 percent confidence intervals and country population is used for weights applied for fitted lines and bubbles. For each scatterplot, correlation coefficients and their significance are reported. *** p<0.01, ** p<0.05, * p<0.1.
Next, we explore partial correlations of these indicators with Covid-19 policy responses (Table 3). In this analysis, we control for a number of factors that potentially confound the relationship between a particular policy response and representation layer. Specifically, we control for (i) the number of infected cases per million inhabitants, (ii) the number of deaths per million, (iii) GDP per capita, and (iv) life expectancy. The number of infected cases and deaths enter the model in order to control for country differences in the spread and consequences of the virus. GDP per capita captures the stage of country development, accounting for cross-country differences in resource capacities and constraints. Both of these control variables are claimed to have an important role in Covid-19 related research (Coscieme et al., 2020; Aldrich and Lotito, 2020; Elgar, Stefaniak and Wohl, 2020; Gibson, 2020; Conyon and Thomsen, 2020). Life expectancy is an important proxy for country inhabitants’ resilience against the virus, conditioned by health and health infrastructures.
Significant correlations are observed between the WBLI and the three policy response indices. The correlation between the WBLI and Stringency (and Containment & health) index is negative, implying that lighter restrictions have been imposed in countries with better business and legal conditions for women. A positive correlation is observed between the WBLI and the economic support index, suggesting that countries with better conditions for women in diverse business and societal areas have provided more extensive economic support in the pandemic. This finding is in line with existing evidence showing that women are more concerned about social policy issues and prefer higher social spending than men (Lott and Kenny, 1999; Abrams and Settle, 1999; Aidt and Dallal, 2008). Also, lighter restrictions and more generous economic support do not presume any trade-off in terms of the allocation of financial resources constrained by a state budget.
Interestingly, we do not observe significant correlations between policy responses and other indicators of women’s representativeness. The only exception is a correlation between GDI and the Containment & health index, which is significant at the 10% level and hinges heavily on two outliers (if we drop the two outliers, the P-value of the correlation increases from 0.0931 to 0.2735).
Table 3. Scatterplots of policy responses and social representativeness and political representation variables.

Note: Scatterplots are constructed for 133 countries. Fitted lines are based on a quadratic function, shaded areas indicate 95 percent confidence intervals and country population is used for weights applied for fitted lines and bubbles. Correlation coefficients are reported with significance levels: *** p<0.01, ** p<0.05, * p<0.1.
In our partial correlation analysis, we do not control for the direct effects of the gender dimension of social norms and practices. Social norms, practices, as well as informal and formal rules can, however, explain a substantial part of the gender gap (Hawkesworth, 2003; Mackay, 2009; Franceschet, 2011; Elson, 1999; Froehlich et al., 2020) relevant for making decisions. Our measures of women’s political and social representativeness do not fully cover gender differences in norms and practices. As Hyland et al. (2020) point out, de-jure female empowerment does not necessarily translate into de-facto empowerment, especially in countries with social norms and informal rules that result in low representation of women in diverse societal spheres. The authors indicate that laws are actionable in a short period, while more time is needed to bring changes in social norms. In our paper (Grigoryan and Khachatryan, 2021), we attempt to address this issue by incorporating the Social Institutions and Gender Index (SIGI) into the model and evaluating the confounding effect on the covariates of the model. We show that the WBLI captures the effect of the gender gap owing to social norms and practices on Covid-19 policy responses as measured by SIGI. This result suggests that the endogeneity arising from the omission of a measure of such a gender gap is likely to be minimal.
Discussion and Conclusions
Our correlation analysis suggests that it is the layer of women’s social representativeness that can explain the policy reactions of governments in times of the Covid-19 pandemic. This result is in line with the institutionalist literature on gender inequality and social role theory, which suggests that a more gender-balanced character of institutions translates into policy measures and related outcomes. Among the three indices constituting the social representativeness layer, the WBLI is, by construction, more inclusive in terms of capturing women’s role in diversified societal areas. From Table 2, we observe that the WBLI is the only index that is in strong correlation with all other indicators. We also identify strong dominance of the WBLI in correlations with policy responses: it is the only indicator that is significantly correlated with all three policy response measurements (Table 3).
To conclude, our results establish an association between female social representativeness, as measured by the (legal) equality of opportunities between men and women, and Covid-19 related policies. One potential interpretation of these findings concerns the central role of the gender balance in different institutions and layers of society in understanding policy responses to the Covid-19 pandemic. While it was parliaments and governments that implemented policies, we find that the measures undertaken correlate more strongly with factors related to the social representativeness of women rather than those related to their political representation. This suggests a dominant role of gender-balanced institutions at the ‘grass root’ level in terms of the scale and scope of the crisis response. Naturally, these institutions may result (or be correlated) with more gender-balanced political representation, but the latter alone is not helpful in explaining the variation in the reaction to the pandemic. These results underline the importance of balanced gender representation in the labor market, business, and other spheres of social life. Further investment and development of ‘grass root’ institutions that improve women’s socioeconomic opportunities, could provide a fundamental foundation for policy development in a crisis situation.
There could also be alternative interpretations of our findings. There is rich evidence that the gender dimension is deeply implicated in institutions (Acker, 1992; Chappell and Waylen, 2013; Lovenduski, 2005). Gender norms and gender practices have been shown to have an influence on the operation and interaction between formal and informal institutions (see, for instance, Chappell, 2010; Krook and Mackay, 2011; Chappell and Waylen, 2013) and the gender dimension of political institutions is reflected in their practices and values, hence affecting their outcomes (such as laws and policies), formation, and implementation (for instance, Acker, 1992). In turn, governmental policies and rules shape societal norms and expectations. These considerations imply that our results could be driven by the overall values, culture, and institutions of respective societies. These factors would both result in a more gender-neutral legal environment and ‘grass-root’ institutions, and ultimately, distinguish countries in their response to the Covid-19 pandemic. In this way, our results open an avenue for future studies in this important domain to better understand the causality of observed relationships.
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(The Appendix can be found in the PDF version of the brief)
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Dimensions of Well-being

This brief summarizes the insights shared in the online workshop “Dimensions of Well-being“, where participants presented and discussed their latest research relating to the dimensions of well-being. The two-day workshop was organized by the Stockholm Institute of Transition Economics (SITE) as part of the Forum for Research on Gender Economics (FROGEE) and took place on 28-29 June, 2021.
Introduction
It has been roughly 18 months since the first cases of Covid-19 were reported in Europe. So far the total number of deaths worldwide has passed 4.4 million (John Hopkins University, 2021), unemployment is trending upward in most countries (ILOSTAT, 2021), roughly half of the world’s students have been affected by school closures (UNESCO, 2021), and an alarming increase in domestic violence has been reported across the globe (UN Women, 2020).
It is safe to say that this pandemic crisis has had a multifaceted impact on our lives. Identifying what factors contribute to overall well-being and understanding how they interact with one another is central in designing and implementing solid and effective recovery policies.
Stockholm Institute of Transition Economics invited international experts to an online workshop where they discussed and presented their recent research relating to the dimensions of well-being. The workshop was organized as part of the Forum for Research on Gender Economics (FROGEE).
Well-being in a Pandemic
The government response policies intended to contain the spread of Covid-19 have undoubtedly had a major impact on society. However, estimating the overall effect of these policies on individuals’ well-being is not necessarily straightforward. Economic support policies likely have a positive effect on income and decrease poverty. But at the same time, other responses such as lockdowns and mobility restrictions may not only have an opposite effect on these outcomes but also influence other known determinants of well-being such as social life or education.
Anthony Lepinteur, researcher at the University of Luxembourg, presented his recent work on the well-being consequences of the pandemic policy responses in Germany, France, Spain, Italy, and Sweden. Lepinteur and co-authors link survey data on subjective well-being measures to data on government economic policy and stringency indices. The former index records financial policies such as income support, furlough schemes, and debt relief while the latter measures the strictness of Covid-19 containment and closure policies. The results show that more stringent policies reduce life satisfaction, and this negative effect is stronger for women, the unemployed, and those with relatively high incomes. Economic support policies are found to have no significant impact on reported life satisfaction.
As many countries have experienced major disruptions in many sectors of their economy, concerns have been raised about deteriorating labor markets and the effect this might have on living conditions and, ultimately, the well-being of individuals. Knar Khachatryan, associate professor at the American University of Armenia, shared research studying the impact of Covid-19 on multidimensional deprivation from labor market opportunities in Armenia. Knachatryan and co-authors base their analysis on two surveys from 2018 and 2020. To measure labor market opportunities, they adopt the “Alkire-Foster method” to develop a multidimensional index of labor market deprivation – a basket of indicators explaining an individual’s degree of labor market opportunities (e.g. education, employment status, income, type of work contract, and union membership). With respect to this index, they find that education is the most important determinant of multidimensional labor market deprivation – those having less than a bachelor’s degree are very likely to be deprived in terms of labor market opportunities. The results also show that the pandemic has widened the gender gap in labor opportunities. The number of people classified as deprived has increased more for women than men during the pandemic. This is primarily because women experienced stronger income reductions and more frequent job losses.
Thesia Garner, researcher at the U.S. Bureau of Labor Statistics, discussed how ex-ante levels of well-being have affected the outcomes of economic support policies during the pandemic. More specifically, her study investigates the role of individual’s well-being in determining their reported use of economic impact payments (EIP) in the U.S. Garner and co-author assess well-being using both objective measures (e.g. income sources, employment status) and subjective ones (e.g. depression, financial difficulty, expectations about job-loss or eviction). The findings show that those who report lower levels of subjective well-being are more likely to use the EIP to pay off debt, and this likelihood increases as the well-being measures worsen. Respondents who report having experiences of financial difficulty and negative expectations about the economy are more likely to spend the stimulus on nondurables and tend to allocate it to a wider range of spending categories.
In contrast to the U.S. and most other countries in the world, Belarus’ government offered very little support to its citizens during the pandemic. Lev Lvovskiy, researcher at BEROC, presented findings on how different sectors of the Belarusian economy and society were affected by the pandemic. Using the BEROC/Satio survey data, Lvovskiy and co-authors examine that the country still had sharp drops in mobility and economic shocks mainly caused by lockdowns of major trade partners. The pandemic significantly increased the probability of income reductions and they show that financial distress associates with the incidence of depression of Belarusians.
Gender and Wellbeing
Another central topic discussed at the workshop concerned the gender aspects of well-being and other related topics from gender economics.
An essential channel through which gender differences in well-being can arise is unequal representation in politics. Sonia Bhalotra, professor at the University of Warwick, presented a study on the relationship between maternal mortality and women’s political power in 174 countries. Maternal mortality is the leading cause of death and disability for women aged 15-44, and significantly higher in low-income countries – at levels similar to what high-income countries had in the early 1900s. Bhalotra and co-authors document that the costs of providing access to prenatal health services, antibiotics, and skilled birth attendance are relatively low. They therefore argue that there are likely other barriers to adopting these solutions. Male policymakers might have a weaker preference for preventing maternal mortality or less information on its prevalence and treatment. To gain insight, the authors use a staggered event-study approach and study the effect of gender quota implementations on the maternal mortality ratio (MMR, maternal mortality per birth). They find that, in countries that adopted quotas, the MMR declined by 10% following implementation, and this effect is stronger for larger quotas. Focusing on the mechanisms, the results show that gender quotas lead to a 5-8 percentage point (p.p.) increase in skilled birth attendance, a 4-8 p.p. increase in prenatal care utilization, 6-7 % decline in birth rates, and an increase in girl’s education by 0.5 years.
Elizaveta Pronkina, researcher at Université Paris-Dauphine, also shared findings relating to gender and politics but from a historical perspective. Her research studies historic institutional differences across communist regimes and women’s work experiences. The paper focuses on Lithuania and Poland, two countries that experienced different gender policies under a communist regime. After the second world war, Lithuania was controlled by the central government of the Soviet Union while Poland’s government was able to preserve its independence although being part of the Soviet bloc. Based on anecdotal evidence, the two countries had the same religious and political policies but different enforcement – Lithuania faced a hard and Poland a soft form of communism. To isolate the impact of the Soviet policies on women’s life decisions and account for differences in the countries’ pre-communist era, the authors only include regions that were part of the Russian empire until the end of the first world war. The findings show that women living under the Soviet regime were more likely to educate themselves and have on average two additional years of work experience (by 50 years of age).
A productive environment and reliable social interactions at work are also likely to be formative elements of people’s well-being, and gender might factor in here. Yuki Takahashi, PhD candidate in economics at the University of Bologna, presented his paper on how being corrected by others affects one’s willingness to collaborate with them in future work, as well as gender differences in these responses. Takahashi conducts a quasi-experimental design in which roughly 3000 participants individually and collectively solve a puzzle. The setting allows the researcher to observe individual ability, number of corrections, as well as whether the corrections were good (i.e., a mistake was corrected), or bad (i.e., a good move was corrected). The study analyzes how the different factors affect an individual’s likelihood of being selected as a collaborator in a last puzzle-solving stage where both participants win cash earnings based on joint performance. The results show that both genders respond negatively to a correction, but women more so than men. Men are less likely to collaborate with a person who has corrected their mistake, particularly men with high ability. The gender of the corrector is found not to matter.
Domestic violence (DV) is another gender aspect of well-being that has become particularly concerning during the pandemic. For many victims, lockdowns and curfews have meant more exposure to their perpetrator. Mobility restrictions have also implied more social isolation from family members and friends as well as increased economic distress, two other factors known to exacerbate DV. In a preliminary study presented by Damian Clarke, associate professor at the University of Chile, he and co-authors address the relationship between DV and quarantines in Chile. They use longitudinal data on police DV hotline calls and use of women’s shelters to measure DV incidence, criminal complaints of DV to police to measure reporting, and mobile phone data to measure mobility. Exploiting municipal variation in the timing of lockdown entry and exit, the study shows that lockdowns lead to more DV incidence and less reporting. DV shelter use increased on average by 11% with entry and reversed with exit. DV calls to the police hotline increased by 86% and persists after lockdown exit. DV crime reports decrease by 5% and increases by 10% with exit. Moreover, the authors document that lockdowns activate both DV mechanisms – increased economic distress and decreased mobility. In municipalities where lockdowns had a stronger impact on unemployment and mobility, they also find larger changes in DV.
Expectations About the Future and Parenthood
Two other studies presented at the workshop discussed the relationship between future expectations and well-being. Claudius Garten, researcher at the Technical University of Dortmund, presented findings on the role of homeownership. Garten and co-authors utilize individual-level survey data from 2007 covering 14 European countries. It contains information on homeownership status and wellbeing measures expressed as respondents’ expectations about future living standards five years from today. They find that expectations about future living standards are higher among homeowners relative to renters and strongly associated with the value of housing assets, suggesting that material security through housing ownership works as a channel for future wellbeing. Garten further argued that since most countries included in the sample have experienced rising house property prices and increased rents since 2007, the divergence between renters and owners is likely to be even more significant today, especially in urban areas.
The second presentation that discussed expectations about well-being in later life was by Alina Schmitz, researcher at the Technical University of Dortmund. Unlike housing, which is seen as a form of material security, Schmitz’s study focuses on the role of health infrastructure quality. Availability of care services may be seen as a safety net in case of illness and care dependency and should thus have a positive effect on wellbeing. The study performs a multilevel analysis on the individual, regional and, country level using micro-survey data on individuals’ life satisfaction and macro-data on the availability of long-term care beds, covering 96 regions from six European countries in 2015. The results show that the quality of care infrastructure is significantly related to the wellbeing of those aged above 50. Moreover, care infrastructure is particularly important for the wellbeing of those with health limitations (i.e. those who require that infrastructure either now or in the future).
Parenthood is another factor that is commonly thought of as a source of happiness. Contrary to this idea, European populations are aging rapidly and the young today have fewer children than the generations before them. The reason why people choose to have few children could be several – e.g. high opportunity costs and/or low benefits of having a large family. Is the fertility rate we see in the developed world today a result of the well-being-maximizing decisions of individuals? This is the main question asked in the paper presented by Barbara Pertold-Gebicka, assistant professor at the Institute of Economic Studies at Charles University. Her study utilizes European survey data to investigate the effect of having an additional unplanned child in five developed countries. To measure the effect of an additional unplanned child and deal with the fact that happy individuals tend to have more children, Pertold-Gebicka and co-author compare people who had twin births in their second pregnancy with parents of two children. Apart from life satisfaction, the most common wellbeing measure, the authors construct a second measure of wellbeing denoted as the happiness index – normalized value summarizing five questions about feelings over the last 5 months, interpreted as the relative frequency of positive feelings. They find no significant effect of having a third child on the well-being of parents. However, when separately looking at groups divided by age of children, they find that the effect of having an additional child on well-being is negative for fathers of younger children and positive for those of teenagers. For the parents of younger children, they show that the negative effect of having a third child is likely driven by increased feelings of nervousness and problems relating to accommodation.
Measuring Inequality and Social Deprivation
Some aspects of wellbeing such as feelings of unfairness or social connections can be quite ambiguous to study as they depend on context and are hard to quantify.
Nicolai Suppa, researcher at the Centre for Demographic Studies at the UAB, presented his research aimed to improve the measurement of deprivation in social participation (DSP) and complementing previous work with an additional outcome variable measuring a different dimension of deprivation. The study uses German survey data to measure how often common social activities are performed and then uses an intersectional approach (similar to the “Alkire-Foster method”) to assign individuals as deprived based on if and how often they practice these activities. The findings show that while the DSP measure correlates positively both with income poverty and material deprivation measures, it identifies a different sample of individuals. Being deprived in terms of social participation is associated with a significant loss of life satisfaction, a magnitude comparable to the loss of being unemployed.
Ingrid Bleynat, researcher at Kings College London, also discussed how to improve measurement but presented a study focusing on a different dimension of well-being, inequality. While quantitative approaches may give little account of the detailed mechanisms of inequality and its multidimensionality, qualitative studies often focus on a subset of the population which make results difficult to generalize. Bleynat and co-authors suggest a mixed approach, combining quantitative and qualitative assessments of inequality. They utilize neighborhood-level data on average household income in Mexico City to randomly select five households in each decile of the income distribution and conduct semi-structured interviews in these households to better understand the nuances of inequality. Based on these interviews they construct two qualitative measures. The first is called inequality of lived experiences and measures qualitative experiences in work, education, and health services across the income distribution. The second is called lived experiences of inequality, and measures feelings of stigma, discrimination, and social hierarchy across gender, ethnicity and location. The quantitative data confirms that Mexico City is highly unequal across the income distribution in terms of not only income but also social factors such as housing, health and food security. The results concerning the qualitative measures, such as inequalities in lived experiences or lived experiences of inequality confirm the existing understanding – e.g., that households belonging to the lower deciles are more likely to be mistreated in the public health sector, have a hostile school environment, and worse working conditions, or that women across the income distribution bear most of the childcare responsibilities, – but provide nuanced details on the interaction between material inequality and the reported experiences.
Conclusion
There is no doubt that the impact of Covid-19 on our well-being has been many-sided, and the presentations of the workshop have clearly demonstrated the broad spectrum of related problems and concerns, as well as their variation across institutional, social, political, economic, and cultural contexts.
Although we are well underway, further research and comprehensive data collection on how people have coped with and responded to the pandemic is needed to design sensible recovery policies and incentivize governments to implement them.
On behalf of the Stockholm Institute of Transition Economics, we would like to thank the experts who shared their insightful research and participated in “Dimensions of Well-being“.
List of Participants
- Sonia Bhalotra (University of Warwick)
- Ingrid Bleynat (King’s College London)
- Damian Clarke (University of Chile)
- Thesia Garner (US Bureau of Labor Statistics)
- Claudius Garten (TU Dortmund)
- Barbara Pertold-Gebicka (Charles University)
- Knar Khachatryan (American University of Armenia)
- Anthony Lepinteur (University of Luxembourg)
- Lev Lvovskiy (BEROC)
- Elizaveta Pronkina (University Carlos III)
- Alina Schmitz (TU Dortmund)
- Nicolai Suppa (Centre for Demographic Studies at the UAB)
- Yuki Takahashi (University of Bologna)
Part 1 | Online Workshop on Dimensions of Well-being
Part 2 | Online Workshop on Dimensions of Well-being
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.
Dimensions of Well-being

The COVID-19 pandemic has affected our well-being in many dimensions. Understanding how these dimensions interact and what factors influence the overall level of well-being can be instrumental in policy design today and in the process of recovery once the pandemic is over. With this in mind, the Stockholm Institute of Transition Economics, the Centre for Economic Analysis and the FREE Network invite you to participate in an online academic workshop on ‘Dimensions of well-being’.
Register
- RSVP: Monday, June 28, 2021, 23:59 (CET, Sweden).
- Location: Online. A link to the webinar will be sent to you 4-5 hours ahead of the start of the webinar.
- Registration: Please register via the Eventbrite platform (see here).
Speakers
The online workshop will be moderated by Michal Myck, Director of the Centre for Economic Analysis (CenEA/Poland).
Day 1
Time: 10:40 – 16:30 CEST, Stockholm time
Gender economics of well-being
- Sonia Bhalotra (University of Warwick)
- Yuki Takahashi (University of Bologna)
- Damian Clarke (University of Chile)
Well-being in the COVID-19 pandemic
- Anthony Lepinteur (University of Luxembourg)
- Lev Lvovskiy (BEROC)
- Knar Khachatryan (American University of Armenia)
- Thesia Garner (US Bureau of Labor Statistics)
Day 2
Time: 9:45 -16:00 CEST, Stockholm time
Identifying determinants of well-being
- Claudius Garten (TU Dortmund)
- Barbara Pertold-Gebicka (Charles University)
Inequality and deprivation
- Ingrid Bleynat (King’s College London)
- Nicolai Suppa (Centre for Demographic Studies at the UAB)
Regions, institutions and later life outcomes
- Elizaveta Pronkina (University Carlos III)
- Alina Schmitz (TU Dortmund)
Program
The program of the webinar includes a special session focused on the consequences of the COVID-19 pandemic for different aspects of well-being. The workshop will be organised as part of the Forum for Research on Gender Economics (FROGEE) supported by the Swedish International Development Cooperation Agency (Sida).
Carbon Tax Regressivity and Income Inequality

A common presumption in economics is that a carbon tax is regressive – that the tax disproportionately burdens low-income households. However, this presumption originates from early research on carbon taxes that used US data, and little is known about the factors that determine the level of regressivity of carbon taxation across countries. In this policy brief, I explore how differences in income inequality may determine the distribution of carbon tax burden across households in Europe. The results indicate that carbon taxation will be regressive in high-income countries with relatively high levels of inequality, but closer to proportional in middle- and low-income countries and in countries with low levels of income inequality.
Introduction
Climate change is one of the main challenges facing us today. To reduce emissions of greenhouse gases, and thereby mitigate climate change, economists recommend the use of a carbon tax. The environmental and economic efficiency of carbon taxation is often highlighted, but the equity story is also of importance: who bears the burden of the tax?
How the burden from a carbon tax is shared across households is important since it affects the political acceptability of the tax. For instance, the “Yellow Vests” protests against the French carbon tax started due to concerns that the tax burden is disproportionately large on middle- and working-class households. Research in economics also shows that people prefer a progressive carbon tax (Brännlund and Persson, 2012).
In this brief, I explore what we know about the distributional effects of carbon taxes and analyze the link between carbon tax regressivity and levels of income inequality in theory and in application to Sweden as well as other European countries.
Carbon Tax Burden Across Households
It is a common finding in the economics literature that carbon taxes are, or would be, regressive (Hassett et al., 2008; Grainger and Kolstad, 2010). However, most of the earlier literature is based on US data, and the US is unrepresentative of an average high-income country in terms of variables that are arguably important for carbon tax incidence. Compared to most countries in Europe, income in the US is high but unequally distributed, carbon dioxide emissions per capita are high, the gasoline tax rate is low, and the access to public transport is poor. If we want to understand the likely distributional effects of carbon taxes across Europe, we thus need to look beyond the US studies.
A recent study by Feindt et al. (2020) examines the consumer tax burden from a hypothetical EU-wide carbon tax. They find that the distributional effect at the EU-level is regressive, driven by the high carbon intensity of energy consumption in relatively low-income countries in Eastern Europe. At the national level, however, carbon taxation in Eastern European countries is slightly progressive due to car ownership and transport fuel being luxuries. Conversely, in high-income countries – where transport fuel is a necessity – carbon taxation is slightly regressive.
That the incidence of carbon and gasoline taxation varies across countries with different levels of income, has been found in numerous studies (Sterner, 2012; Sager, 2019). To understand the source of this variation, we need to identify the determinants of the incidence of carbon taxes.
The Role of Income Inequality
In a recent paper, I, together with Giles Atkinson at the London School of Economics, present a simple model where the variation in the carbon tax burden across countries and time can be determined by two parameters: the level of income inequality and the income elasticity of demand for the taxed goods (Andersson and Atkinson, 2020). The income elasticity specifies how the demand for a good, such as gasoline, responds to a change in income. If the budget share decreases as income increase, we refer to gasoline as a necessity. If the budget share increases with income, we refer to gasoline as a luxury good. Our model predicts that rising inequality increases the regressivity of a carbon tax on necessities. Similarly, we will see a more progressive incidence if inequality increases and the taxed good is a luxury.
To mitigate climate change, a carbon tax should be applied to goods responsible for the majority of greenhouse gas emissions: transport fuel, electricity, heating, and food. To estimate the distribution of carbon tax burden, we must then first establish if these goods are necessities or luxuries, respectively. Gasoline is typically found to be a luxury good in low-income countries but a necessity in high-income countries (Dahl, 2012). Food, in the aggregate, is consistently found to be a necessity. A carbon tax on food would, however, mainly increase the price of red meat – beef has a magnitude larger carbon footprint than all other food groups – and red meat is generally a luxury good, even in high-income countries (Gallet, 2010). Lastly, electricity and heating are necessities, with little variation across countries in the level of income elasticities. A broad carbon tax would thus likely be regressive in high-income countries, but more proportional, maybe even progressive, in low-income countries. The overall effect in low-income countries depends on the relative budget shares of transport fuel and meat (luxuries) versus electricity and heating (necessities). A narrow carbon tax on transport fuel has a less ambiguous incidence: it will be regressive in high-income countries where the good is a necessity and proportional to progressive in low-income countries where the good is a luxury.
The income elasticities of demand, however, only provide half of the picture. To understand the degree of regressivity from carbon taxation, we also need to take into account the level of income inequality in a country. Our model predicts that a carbon tax on necessities will be more regressive in countries with relatively high levels of inequality. And increases in inequality over time may turn a proportional tax incidence into a regressive one.
To test our model’s prediction, we analyze the distributional effects of the Swedish carbon tax on transport fuel and examine previous studies of gasoline tax incidence across high-income countries.
Empirical Evidence from Sweden
The Swedish carbon tax was implemented in 1991 at $30 per ton of carbon dioxide and the rate was subsequently increased rather rapidly between 2000-2004. Today, in 2021, the rate is above $130 per ton; the world’s highest carbon tax rate imposed on households. The full tax rate is mainly applied to transport fuel, with around 90 percent of the revenue today coming from gasoline and diesel consumption.
Figure 1. Carbon tax incidence and income inequality in Sweden

Sources: Andersson and Atkinson (2020). Gini coefficients are provided by Statistics Sweden.
Using household-level data on transport fuel expenditures and annual income between 1999-2012, we find that the Swedish carbon tax is increasingly regressive over time, which is highly correlated with an increase in income inequality. Figure 1 shows the strong linear correlation between the incidence of the tax and the level of inequality across our sample period. The progressivity of the tax is measured using the Suits index (Suits, 1977), a summary measure of tax incidence that spans from +1 to -1. Positive (negative) numbers indicate that the tax is overall progressive (regressive) and a proportional tax is given an index of zero. The level of income inequality, in turn, is summarized by the Gini coefficient (0-100), with higher numbers indicating higher levels of inequality.
In 1991, when the Swedish carbon tax was implemented, income inequality was relatively low, with a Gini of 20.8. If we extrapolate, the results presented in Figure 1 indicate that the tax incidence in 1991 was proportional to slightly progressive. Since the early 1990s, however, Sweden has experienced a rise in inequality. Today, the Gini is around 28 and the carbon tax incidence is rather regressive. This can be a potential concern if people start to perceive the distribution of the tax burden as unfair and call for reductions in the tax rate.
Empirical Evidence Across High-Income Countries
Figure 2 presents the results of our analysis of previous studies of gasoline tax incidence across high-income countries. Again, we find a strong correlation with inequality; the higher the level of inequality, the more regressive are gasoline taxes. In the bottom-right corner, we locate the results from studies on gasoline tax incidence that have used US data. The level of inequality in the US has been persistently high, and the widespread assumption that gasoline and carbon taxation is regressive is thus based to a large part on studies of one highly unequal country. Looking across Europe we find that the tax incidence is more varied, with close to a proportional outcome in the (relatively equal) Nordic countries of Denmark and Sweden.
Figure 2. Gasoline tax incidence and income inequality in OECD countries

Sources: Andersson and Atkinson (2020). Gini coefficients are from the SWIID database (Solt, 2019).
Conclusion
A carbon tax is economists’ preferred instrument to tackle climate change, but its distributional effect may undermine the political acceptability of the tax. This brief shows that to understand the likely distributional effects of carbon taxation we need to take into account the type of goods that are taxed – necessities or luxuries – and the level and direction of income inequality. Carbon taxation will be closer to proportional in European countries with low levels of inequality, whereas in countries with relatively high levels of inequality the carbon tax incidence will be regressive on necessities and progressive for luxury goods.
This insight may explain why we first saw the introduction of carbon taxes in the Nordic countries. Finland, Sweden, Denmark, and Norway all implemented carbon taxes between 1990-1992, and income inequality was relatively, and historically, low in this region at the time. Policymakers in the Nordic countries thus didn’t need to worry about possibly regressive effects. Looking across Europe today, many of the countries that have relatively low levels of inequality have either already implemented carbon taxes or, due to the size of their economies, have a low share of global emissions. In countries that are responsible for a larger share of global emissions – such as, the UK, Germany, and France – inequality is relatively high, and they may find it to be politically more difficult to implement carbon pricing as the equity argument becomes more salient and provides opportunities for opponents to attack the tax.
To increase the political acceptability and perceived fairness of carbon pricing, policymakers in Europe should consider a policy design that offsets regressive effects by returning the revenue back to households, either by lump-sum transfers or by reducing tax rates on labor income.
References
- Andersson, Julius and Giles Atkinson. 2020. “The Distributional Effects of a Carbon Tax: The Role of Income Inequality.” Grantham Research Institute on Climate Change and the Environment Working Paper 349. London School of Economics.
- Brännlund, Runar and Lars Persson. 2012. “To tax, or not to tax: preferences for climate policy attributes.” Climate Policy 12 (6): 704-721.
- Dahl, Carol A. 2012. “Measuring global gasoline and diesel price and income elasticities.” Energy Policy 41: 2-13.
- Feindt, Simon, et al. 2020. “Understanding Regressivity: Challenges and Opportunities of European Carbon Pricing.” SSRN 3703833.
- Gallet, Craig A. 2010. “The income elasticity of meat: a meta-analysis.” Australian Journal of Agricultural and Resource Economics 54(4): 477-490.
- Grainger, Corbett A and Charles D Kolstad. 2010. “Who pays a price on carbon?” Environmental and Resource Economics 46(3): 359-376.
- Hassett, Kevin A, Aparna Mathur, and Gilbert E Metcalf. 2009. “The consumer burden of a carbon tax on gasoline.” American Enterprise Institute, Working Paper.
- Sager, Lutz. 2019. “The global consumer incidence of carbon pricing: evidence from trade.” Grantham Research Institute on Climate Change and the Environment Working Paper 320. London School of Economics.
- Thomas, Sterner. 2012. Fuel taxes and the poor: the distributional effects of gasoline taxation and their implications for climate policy. Routledge.
- Suits, Daniel B. 1977. “Measurement of tax progressivity.” American Economic Review 67(4): 747-752.
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.
Changing Prices in a Changing Climate: Electoral Competition and Fossil Fuel Taxation

When do governments increase the price of fossil fuels? Charting the theoretical territory between climate change politics and long-term policymaking. Join SITE brown bag seminar as Jared Finnegan highlights the role of electoral competition in shaping how politicians respond to the intertemporal tradeoff fossil fuel taxation represents.
About the speaker
Jared J. Finnegan is a S.V. Ciriacy-Wantrup Postdoctoral Fellow in the Department of Environmental Science, Policy, and Management at UC Berkeley. He is also a Visiting Fellow at the Grantham Research Institute on Climate Change and the Environment at the London School of Economics and Political Science (LSE). Previously, he was a Postdoctoral Fellow at the Niehaus Center for Globalization and Governance at Princeton University. He studies the comparative political economy of the high-income democracies. His research investigates how governments, voters, and business understand and address long-term societal challenges, particularly climate change.
Abstract
When do governments increase the price of fossil fuels? Charting the theoretical territory between climate change politics and long-term policymaking, this paper highlights the role of electoral competition in shaping how politicians respond to the intertemporal tradeoff fossil fuel taxation represents. The more secure the government is in office, the more insulated it is from the vagaries of political competition, and the more likely it is to impose costs on constituents today to generate a future stable climate. By influencing governments’ time preferences, competition structures the myopia of elected officials. I test the arguments using an original dataset of gasoline taxation across high-income democracies between 1988-2013. I find robust evidence that higher levels of electoral competition are associated with lower gasoline tax rates, and that the relationship is moderated by the level of costs imposed on voters, but not government partisanship. The analysis points to a crucial mechanism that plausibly accounts for the differential ability of governments to tackle a wider range of long-term policy challenges.
Registration
Please contact site@hhs.se and type the subject box with “Brown bag seminar *INSERT TITLE* at SITE” and describe in short who you are and why you want to join. Afterwards, the Zoom link will be sent to you by email with further instructions!
Read the full working paper
Changing Prices in a Changing Climate: Electoral Competition and Fossil Fuel Taxation (2018)
ISET Gender Policy Conference

ISET Policy Institute, International School of Economics at TSU (ISET), and Forum for Research On Eastern Europe and Emerging Economies (FREE Network) are holding an online Gender Policy Conference.
At the Conference ISET Policy institute will introduce a Gender Equality Index for the former Soviet countries, a unique tool developed by ISET-PI. The Index will be of special interest to policymakers, NGO advocates, researchers working on gender issues, scholars of FSU, and the general public. It is offering an impartial, data-driven birds-eye-view of gender equality evolution in the post-soviet space, and can be used to track and benchmark progress on gender issues in individual countries within the region. The Index is based on an established methodology used to capture and compare gender equality progress in the EU member states. ISET Policy institute has adapted the Index methodology and developed indicators for twelve former soviet transition countries, benchmarking the results to the best and worst EU performers in gender equality.
Agenda
The conference will be opened by the Minister of Economy and Sustainable Development of Georgia, Ms Natia Turnava, Head of Swedish Development Cooperation and Deputy Head of Mission, Mr Erik Illes, and Director of Stockholm Institute of Transition Economics, Dr Torbjörn Becker.
The event will bring together top experts from Armenia, Georgia, Moldova and Ukraine for the Policy Panel Discussion on gender-related issues, country specific experiences and challenges. The discussion will be followed by Reflections from the FREE Network representatives. The event will be moderated by Tamar Sulukhia, Director of ISET and ISET Policy Institute.
The full conference agenda can be found here.
Register
In order to attend the conference, please register here.
The working language of the event will be English.
Corruption, Tax Evasion and Institutions

The FREE Network member BICEPS will hold the second “Corruption, Tax Evasion, and Institutions” conference, following the initial event that took place in May 2017 (see here). The conference will take place on May 27-28, 2021.
The conference aims to promote and diffuse high-quality economic research on the mechanisms driving corruption and tax evasion, their relationships with institutions and their consequences on economic outcomes. A specific feature of this conference is to get insights from investigative journalism. In addition to an academic keynote speaker, the conference will host a high-profile journalist working on tax evasion and money laundering cases for a keynote talk.
The conference is organized by the Baltic International Centre for Economic Policy Studies (BICEPS) and Centre for Media Studies at SSE Riga, with financial support from the project “Institutions and Tax Enforcement in Latvia” (InTEL), funded by the Latvian Science Council.
KEYNOTE SPEAKERS
Ruben Enikolopov (Rector and professor at the New Economic School, Moscow)
Ruben Enikolopov is Professor and Rector of the New Economic School (Moscow), Associate Professor at the Universitat Pompeu Fabra, ICREA Research Professor at Barcelona Institute for Political Economy and Governance (IPEG) and Barcelona GSE Affiliated Professor. He is also a CEPR research fellow. Ruben holds a PhD from Harvard University. He has been a consultant to the World Bank (2005-10) and the United Nations Food and Agriculture Organization (2007-08). He is a Co-Editor of the Journal of Comparative Economics and a member of the Editorial Board of the Review of Economic Studies and Journal of the European Economic Association. Ruben published articles in reviews such as Econometrica, Review of Economic Studies, Quarterly Journal of Economics, American Economic Review, Journal of Public Economics.
Linda Larsson Kakuli (Investigative journalist at SVT, Stockholm)
Linda Larsson Kakuli is a researcher for the news department at SVT, the Swedish public service television company. As a researcher, she worked on several big global stories, as Panama & Paradise Papers and she’s been awarded Guldspaden (the golden shovel) twice and nominated to Stora Journalistpriset (the Swedish Grand Prize for Journalism). In 2007 she received the Ludvig Nordström-prize for her inspirational work. Linda Larsson Kakuli is part of a new team at SVT for advanced data journalism, together with Helena Bengtsson and she previously worked as a researcher for investigative programmes Striptease, Faktum and Uppdrag Granskning, all at Swedish Television.
REGISTRATION
The conference will be held on Zoom. To register, fill in the registration form no later than May 25. The keynote speeches will be live broadcasted on the BICEPS Facebook page.
IMPORTANT DATES
Deadline for paper submission – January 31, 2021
Notifications of acceptance by February 15, 2021
Conference dates – May 27-28, 2021
SCIENTIFIC COMMITTEE
- Zareh Asatryan (ZEW, Mannheim)
- Audinga Baltrunaite (Bank of Italy)
- Nicolas Gavoille (Stockholm School of Economics in Riga)
- Boris Ginzburg (Universidad Carlos III de Madrid)
- Mihails Hazans (University of Latvia)
- Anders Olofsgard (SITE, Stockholm School of Economics)
- Alari Paulus (Bank of Estonia)
- Marc Sangnier (University of Namur)
- Arnis Sauka (Stockholm School of Economics in Riga)
- Konstantin Sonin (University of Chicago)
- Pilar Sorribas-Navarro (Universitat de Barcelona & IEB)
- Giancarlo Spagnolo (SITE, Stockholm School of Economics)
- Anna Zasova (BICEPS)
CONTACT
Contact Nicolas Gavoille (nicolas.gavoille[at]sseriga.edu) and Anna Zasova (anna[at]biceps.org) for any questions about the conference. Access the call for papers here. See the conference program here.
Energy Storage: Opportunities and Challenges

As the dramatic consequences of climate change are starting to unfold, addressing the intermittency of low-carbon energy sources, such as solar and wind, is crucial. The obvious solution to intermittency is energy storage. However, its constraints and implications are far from trivial. Developing and facilitating energy storage is associated with technological difficulties as well as economic and regulatory problems that need to be addressed to spur investments and foster competition. With these issues in mind, the annual Energy Talk, organized by the Stockholm Institute of Transition Economics, invited three experts to discuss the challenges and opportunities of energy storage.
Introduction
The intermittency of renewable energy sources poses one of the main challenges in the race against climate change. As the balance between electricity supply and demand must be maintained at all times, a critical step in decarbonizing the global energy sector is to enhance energy storage capacity to compensate for intermittent renewables.
Storage systems create opportunities for new entrants as well as established players in the wind and solar industry. But they also present challenges, particularly in terms of investment and economic impact.
Transitioning towards renewables, adopting green technologies, and developing energy storage can be particularly difficult for emerging economies. Some countries may be forced to clean a carbon-intensive power sector at the expense of economic progress.
The 2021 edition of Energy Talk – an annual seminar organized by the Stockholm Institute of Transition Economics – invited three international experts to discuss the challenges and opportunities of energy storage from a variety of academic and regulatory perspectives. This brief summarizes the main points of the discussion.
A TSO’s Perspective
Niclas Damsgaard, the Chief strategist at Svenska kraftnät, gave a brief overview of the situation from a transmission system operator’s (TSO’s) viewpoint. He highlighted several reasons for a faster, larger-scale, and more variable development of energy storage. For starters, the green transition implies that we are moving towards a power system that requires the supply of electricity to follow the demand to a much larger extent. The fact that the availability of renewable energy is not constant over time makes it crucial to save power when the need for electricity is low and discharge it when demand is high. However, the development and facilitation of energy storage will not happen overnight, and substantial measures on the demand side are also needed to ensure a more dynamic energy system. Indeed, Damsgaard emphasized that demand flexibility constitutes a necessary element in the current decarbonization process. However, with the long-run electrification of the economy (particularly driven by the transition of the transport industry), extensive energy storage will be a necessary complement to demand flexibility.
It is worth mentioning that such electrification is likely to create not only adaptation challenges but also opportunities for the energy systems. For example, the current dramatic decrease in battery costs (around 90% between 2010 and 2020) is, to a significant extent, associated with an increased adoption of electric vehicles.
However, even such a drastic decline in prices may still fall short of fully facilitating the new realities of the fast-changing energy sector. One of the new challenges is the possibility to store energy for extended periods of time, for example, to benefit from the differences in energy demand across months or seasons. Lithium-ion batteries, the dominant battery technology today, work well to store for a few hours or days, but not for longer storage, as such batteries self-discharge over time. Hence, to ensure sufficient long-term storage, more batteries would be needed and the associated cost would be too high, despite the above-mentioned price decrease. Alternative technological solutions may be necessary to resolve this problem.
Energy Storage and Market Structure
As emphasized above, energy storage facilitates the integration of renewables into the power market, reduces the overall cost of generating electricity, and limits carbon-based backup capacities required for the security of supply, creating massive gains for society. However, because the technological costs are still high, it is unclear whether the current economic environment will induce efficient storage. In particular, does the market provide optimal incentives for investment, or is there a need for regulations to ensure this?
Natalia Fabra, Professor of Economics and Head of EnergyEcoLab at Universidad Carlos III de Madrid, shared insights from her (and co-author’s) recent paper that addresses these questions. The paper studies how firms’ incentives to operate and invest in energy storage change when firms in storage and/or production have market power.
Fabra argued that storage pricing depends on how decisions about the storage investment and generation are allocated between the regulator and the firms operating in the storage and generation markets. Comparing different market structures, she showed as market power increases, the aggregate welfare and the consumer surplus decline. Still, even at the highest level of market concentration, an integrated storage-generation monopolist firm, society and consumers are better off than without energy storage.
Fabra’s model also predicts that market power is likely to result in inefficient storage investment.
If the storage market is competitive, firms maximize profits by storing energy when the prices are low and releasing when the prices are high. The free entry condition implies that there are investments in storage capacity as long as the marginal benefit of storage investment is higher than the marginal cost of adding an additional unit of storage. But this precisely reflects the societal gains from storage; so, the competitive market will replicate the regulator solution, and there are no investment distortions.
If there is market power in either generation or storage markets, or both, the investment is no longer efficient. Under market power in generation and perfectly competitive storage, power generating firms will have the incentive to supply less electricity when demand is high and thereby increase the price. As a result, the induced price volatility will inflate arbitrage profits for competitive storage firms, potentially leading to overinvestment.
If the model features a monopolist storage firm interacting with a perfectly competitive power generation market, the effect is reversed. The firm internalizes the price it either buys or sells energy, so profit maximization makes it buy and sell less energy than it would in a competitive market, in the exact same manner as the classical monopolist/monopsonist does. This underutilization of storage leads to underinvestment.
If the model considers a vertically integrated (VI) generation-storage firm with market power in both sectors, the incentives to invest are further weakened: the above-mentioned storage monopolist distortion is exacerbated as storage undermines profits from generation.
Using data on the Spanish electricity market, the study also demonstrated that investments in renewables and storage have a complementary relationship. While storage increases renewables’ profitability by reducing the energy wasted when the availability is excess, renewables increase arbitrage profits due to increased volatility in the price.
In summary, Fabra’s presentation highlighted that the benefits of storage depend significantly on the market power and the ownership structure of storage. Typically, market power in production leads to higher volatility in prices across demand levels; in turn, storage monopolist creates productive inefficiencies, two situations that ultimately translate into higher prices for consumers and a sub-optimal level of investment.
Governments aiming to facilitate the incentives to invest in the energy storage sector should therefore carefully consider the economic and regulatory context of their respective countries, while keeping in mind that an imperfect storage market is better than none at all.
The Russian Context
The last part of the event was devoted to the green transition and the energy storage issue in Eastern Europe, with a specific focus on Russia.
Alexey Khokhlov, Head of the Electric Power Sector at the Energy Center of Moscow School of Management, SKOLKOVO, gave context to Russia’s energy storage issues and prospects. While making up for 3% of global GDP, Russia stands for 10% of the worldwide energy production, which arguably makes it one of the major actors in the global power sector (Global and Russian Energy Outlook, 2016). The country has a unified power system (UPS) interconnected by seven regional facilities constituting 880 powerplants. The system is highly centralized and covers nearly the whole country except for more remote regions in the northeast of Russia, which rely on independent energy systems. The energy production of the UPS is strongly dominated by thermal (59.27%) followed by nuclear (20.60%), hydro (19.81%), wind (0.19%), and solar energy (0.13%). The corresponding ranking in capacity is similar to that of production, except the share of hydro-storage is almost twice as high as nuclear. The percentage of solar and wind of the total energy balance is insignificant
Despite the deterring factors mentioned above, Khokhlov described how the Russian energy sector is transitioning, though at a slow pace, from the traditional centralized carbon-based system towards renewables and distributed energy resources (DER). Specifically, the production of renewables has increased 12-fold over the last five years. The government is exploring the possibilities of expanding as well as integrating already existing (originally industrial) microgrids that generate, store, and load energy, independent from the main grid. These types of small-scaled facilities typically employ a mix of energy sources, although the ones currently installed in Russia are dominated by natural gas. A primary reason for utilizing such localized systems would be for Russia to improve the energy system efficiency. Conventional power systems require extra energy to transmit power across distances. Microgrids, along with other DER’s, do not only offer better opportunities to expand the production of renewables, but their ability to operate autonomously can also help mitigate the pressure on the main grid, reducing the risk for black-outs and raising the feasibility to meet large-scale electrification in the future.
Although decarbonization does not currently seem to be on the top of Russia’s priority list, their plans to decentralize the energy sector on top of the changes in global demand for fossil fuels opens up possibilities to establish a low-carbon energy sector with storage technologies. Russia is currently exploring different technological solutions to the latter. In particular, in 2021, Russia plans to unveil a state-of-the-art solid-mass gravity storage system in Novosibirisk. Other recently commissioned solutions include photovoltaic and hybrid powerplants with integrated energy storage.
Conclusion
There is no doubt that decarbonization of the global energy system, and the role of energy storage, are key in mitigating climate change. However, the webinar highlighted that the challenges of implementing and investing in storage are both vast and heterogenous. Adequate regulation and, potentially, further government involvement is needed to correctly shape incentives for the market participants and get the industry going.
On behalf of the Stockholm Institute of Transition Economics, we would like to thank Niclas Damsgaard, Natalia Fabra, and Alexey Khokhlov for participating in this year’s Energy Talk. The material presented at the webinar can be found here.
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.
For a Better Budget Management of Infrastructure Investments

Many developing countries rely on investment-to-GDP metrics as a sign of progress towards their development goals. Unfortunately, too often the focus on investment pushes aside the issues of adequately maintaining existing infrastructure. The result could be disastrous to human lives, health, and well-being. Lack of maintenance of existing infrastructure is a well-known problem, not only in developing economies but also in some developed countries. However, how much the government should plan to spend on maintenance over the lifetime of infrastructure assets is neither a simple nor straightforward question. In this policy brief, we examine the cases of two transition economies – Georgia and Estonia – and provide a more general discussion of the challenges and possible solutions to infrastructure maintenance issues. We argue that relevant research along with properly aligned incentives could help the countries overcome these problems and optimize infrastructure spending.
Introduction
The efficiency of infrastructure investment has gotten quite some attention in the past years. A recent book by G. Schwartz et al. (2020) shows that countries waste about 1/3 (and some even more) of their infrastructure spending due to inefficiencies. With poor management, the major budgetary efforts undertaken to make room for infrastructure investments go to waste. The question of how much the country should plan to spend on maintenance over the lifetime of infrastructure assets is neither simple nor straightforward. In two recent ISET-PI blog posts, Y. Babych and L. Leruth (2020a, b) stress the importance of striking the right balance between new infrastructure investments and the rehabilitation and maintenance of existing infrastructure. Without this balance, the up-keep of public infrastructure could either be too expensive for the budget to handle, or, at the other extreme, would quickly deteriorate to the point where it is no longer operational and needs to be rebuilt from the ground up (which is the case in many developing countries, including Georgia, Armenia, Ukraine, and others). This policy brief focuses on the reasons why developing (and even some developed) countries tend to invest too little in public infrastructure maintenance and what can be done to solve this problem. We first examine the cases of Georgia and Estonia, two post-Soviet transition economies with different approaches to infrastructure maintenance financing. This analysis is then followed by a more general discussion about the infrastructure maintenance challenges and potential solutions.
Maintenance vs. Investment: the Cases of Georgia and Estonia
Developing countries tend to use investment (public or private) as a share of GDP to measure their economic progress and prospects. Georgia is one of the countries that has invested a lot in public infrastructure. Public investment grew sharply between 2003-2007 to 8% of GDP and settled at 6% of GDP after 2017 (PIMA GEO 2018). The capital stock is about 90% of GDP. In comparison, in Estonia, another post-Soviet economy, public investment was about 4% of GPD, whereas the capital stock was 57% of GDP in 2015. Yet, the quality of Georgia’s public infrastructure is much lower than in Estonia (Georgia is in 69th place globally according to Global Competitiveness Index 2017-2018, while Estonia is in 32nd place). The reason for this is quite simple: management, especially the maintenance of public infrastructure. Both countries recently went through a Public Investment Management Assessment (PIMA), a comprehensive framework developed by the IMF to assess infrastructure governance. The results suggest that Georgia is much weaker than Estonia in planning, budgeting, and maintenance. (A complete summary of the assessment results can be found here).
Georgia’s case is far from unique. The country belongs to the vast majority of emerging economies that have not efficiently linked their medium- and long-term infrastructure plans within a sustainable fiscal framework. Moreover, infrastructure planning deficiencies spread way beyond the emerging markets: Allen et al. (2019) estimate that 56% of all world countries do not have a proper Public Investment Program.
Why is Infrastructure Maintenance a Challenge for Many Countries?
Even though maintenance, rehabilitation, and new investments are intrinsically linked, the practical process of integrating these three infrastructure components is complex. Blazey et al. (2019), for example, identify the following reasons:
- Political economy reasons—governments will opt for a ribbon-cutting rather than maintaining existing assets;
- Fiscal reasons—budget funding for operations and maintenance is prone to be cut when fiscal space is limited;
- Institutional reasons—in many countries, separate agencies still prepare investment and current expenditure budgets;
- Capacity reasons— up-to-date information on the state of assets may not be readily available.
A number of international studies (usually sectorial) point to the high cost of neglecting maintenance. A study on the upkeep of bridges and roads in the US shows that 1$ of deferred maintenance will cost over 4$ in future repairs. The same holds for airports. In Africa, the World Bank estimates that timely road expenditure of $12 billion spent in the 80s would have saved $45 billion in reconstruction costs during the next decade. It is not only rehabilitation costs that increase with poor maintenance: user costs can increase dramatically (Escobal and Ponce, 2003); health costs in terms of injuries or deaths; and ecological costs (the water lost daily because of leaks could satisfy the needs of 200 million people according to the World Bank, 2006).
Conceptually, however, the link between maintenance, rehabilitation, and new investments is simple to understand. Figure 1 below, adopted from Thi Hoai Le et al. (2019), clarifies this point. As discussed in Babych and Leruth (2020b), when planned maintenance activities (such as planned repair, upkeep, etc.) are insufficient, then the rate at which infrastructure is deteriorating will be high, and the unplanned maintenance costs will increase as well. This response would, in turn, result in a higher total cost. If the amount of planned maintenance activities is excessive, then the unplanned costs may be low, but the total cost is higher than optimal. In order to strike the optimal balance, there need to be just enough planned maintenance activities.
Figure 1. Optimal zone of maintenance.

Source: Thi Hoai Le et al., (2019).
Conceptually simple maybe, but the devil(s) is (are) in the details. We have already listed above some of the reasons why integration is complex. Data availability is another issue raised by numerous Public Investment Management Assessments made by the IMF. The reporting standards are simply not built in a way that would allow for the compilation of maintenance and rehabilitation data (although aggregate estimates of investment data are available). In any case, the Government Finance Statistics Manual of the IMF (2014) does not separate maintenance expenditure, which is undoubtedly an area that requires further deepening. More fundamentally perhaps, as pointed out long ago by Schick (1966), there is an additional issue relating to governance philosophy: “planning and budgeting have run separate tracks and have invited different perspectives, the one conservative and negativistic, the other innovative and expansionist …”. Finally, with governments looking for the ‘cheap’ route through public-private partnerships (PPPs) to finance infrastructure development, fiscal risks have increased in advanced and emerging economies in the early 2000s (IMF, 2008). To our knowledge, there have been no systematic assessments of PPP-related fiscal risks since IMF’s report in 2008, but as fiscal positions have deteriorated with the Covid-19 pandemic, PPP projects are likely even riskier today.
What Can Be Done to Improve Infrastructure Maintenance?
Leaving the data, PPPs, and inter-departmental culture issues aside, several considerations that emerge from a closer look at Figure 1 can feed the policy discussions. Let us first consider the notion of planned maintenance (the orange line). In principle, as a project is developed, the cost of maintenance is projected over its life cycle. If the infrastructure is maintained accordingly, its life span may even exceed the projections. At the time the project is conceived, a schedule of maintenance expenditure is also planned and integrated into the analysis. In the figure above, one would expect that these cost assumptions are located in the ‘optimal maintenance zone’ with a limited amount to be spent on unplanned maintenance later on. This level of planned maintenance should then be integrated as a ‘given’ in all subsequent budgets. Usually, as we have already mentioned, it is not.
If we now move to ‘unplanned’ maintenance (the line in blue), we are really referring to situations when infrastructure must be brought back to shape after months (or even years) of neglect. In some cases, this can no longer be labeled as maintenance, and it becomes rehabilitation. Reduce regular maintenance a bit more and the authorities must start over.
Finally, the continuity of the curves is misleading: it is wrong to say that things are necessarily smooth even in the optimal zone.
Let us look more closely at the leading causes and the ways to overcome the problems that arise when optimizing maintenance expenditure.
Setting benchmarks: One explanation for the shortage of maintenance planning outlined above is the lack of information on the practical implementation of such planning. There are too few studies on maintenance expenditure for policymakers to set benchmarks and develop reliable estimates. The existing studies in this area tend to focus on OECD countries (where data availability is less of a constrain) and on the transportation sector (roads, rail, etc.) perhaps because the private sector is more often involved (see, for example, the American Society of Civil Engineers from 2017, that concluded that 9 percent of all bridges are structurally deficient). Some studies have looked at buildings (e.g., Batalovic et al., 2017 or the Ashrae database, 2021) and unsurprisingly concluded that the age of the construction and its height are significant variables to explain maintenance outlays. However, we are not aware of studies that would, for example, distinguish between different types of maintenance in order to limit overall costs. We are neither aware of studies investigating which organizational arrangements are the most efficient (as discussed by Allen et al., 2019). The bottom line is that there is not much to use as a benchmark, and an effort must be made to build reliable estimates.
Policy dialogue on maintenance is needed: The abovementioned considerations of the consequences of delayed, unplanned, and sometimes unexpected maintenance bring us to our next point. Things break down when they are not maintained (and sometimes break down when they are maintained too), and such long-term aspects must be more present in the policy dialogue with developing countries. Clearly, delaying maintenance increases fiscal costs in the short- and longer-term (Blazey et al., 2019).
The smoothness of the curves in Figure 1 can be misleading because insufficient maintenance may suddenly trigger a major problem (a bridge or a dam can collapse, as it happened in Italy and in India recently,) and this will entail high costs, even disasters involving in human lives. The major collapses of nuclear plants (as in Chornobyl, Ukraine, and more recently in Fukushima, Japan) are other examples of the same problem. In addition, studies estimate that poor maintenance of transmission lines could be one of the reasons for electricity blackouts (Yu and Pollitt, 2009). In fact, the lack of maintenance increases the speed at which the value of the existing capital of infrastructure is eroding. While politicians may well hope that this will not happen during their tenure, the probability of a failure increases as maintenance decreases.
On top of the above, inefficiency in maintenance expenditures can be aggravated by wrongly set incentives, both for domestic actors and foreign donors. Indeed, the latter play an important role in infrastructure investment in many developing countries. In Georgia, for example, 40% of infrastructural projects are funded by foreign donors. Setting the right incentives for both parties, as well as their interplay, are thus of immense importance.
Aligning the incentives: Incentives are against maintenance. As pointed out by Babych and Leruth (2020a), capital investment and rehabilitation look good on paper. Maintenance, on the other hand, is considered a current expenditure item in the Government Finance Statistics (GFS) (IMF, 2014). Spending more on maintenance will therefore not look good since 1) more maintenance will reduce government savings in the short term; 2) spending less on maintenance will increase the need for virtuous-looking investment expenditure in the medium and long term. Yet, in spite of the lack of clear benchmarks, donors can play an essential role by stressing the need to systematically integrate maintenance in the budget and in the Medium-Term Expenditure Framework (MTEF). To some extent, it is already the case. In Georgia, projects that are funded by donors tend to follow better appraisal procedures. However, ex-post audits are irregular – e.g., no individual projects audits were completed by State Audit Office during 2015-2017 (PIMA GEO, 2018). If donors could include these audits in their dialogue, it would clearly be helpful. Training subnational governments in proper maintenance management would be even more critical as capacities tend to be weaker than in the center.
Overcoming a potential moral hazard problem of donor involvement: Excessive donor involvement in new investments could also be counterproductive. Donors should carefully examine the need to build new infrastructure and first consider the possibility of performing some rehabilitation while holding the authorities accountable for the maintenance of existing ones. If the authorities are expecting a donor to eventually replace a piece of infrastructure that does not function, the incentives to maintain it are greatly reduced.
Conclusion
- Developing economies, but also emerging ones like Georgia, as well as Armenia, Ukraine and others, would benefit from proper incentives and support from the international donors to integrate maintenance into the infrastructure planning framework;
- This is especially important for local governments, who lack the financial and human capital resources to maintain local infrastructure properly, making regions outside of the capital city less attractive places to invest or live in;
- Given the absence of transparent and comparable sources of information about the composition of maintenance expenditures – for example, the Government Finance Statistics (IMF), which does not distinguish between maintenance and rehabilitation expenditures, – donors could insist that governments compile these expenditures and report on them, at least for the major projects;
- The culture of maintaining rather than rehabilitating or replacing is directly linked to the sustainable development goals and the circular economy concept. In light of their commitment to Agenda 2030, the international community and the national governments in countries like Georgia should consider prioritizing and implementing the set of reforms suggested in their respective PIMAs.
References
- Allen, R., M. Betley, C. Renteria and A. Singh, “Integrating Infrastructure Planning and Budgeting,” in Schwartz et al. (2020), pp. 225-244 (2019).
- American Society of Civil Engineers, Infrastructure Report Card, Reston, Va, (2017).
- ASHRAE, Purpose of The Service Life and Maintenance Cost Database, available at., (2021).
- Babych, Y., and L. Leruth, “Tbilisi: a Growing City with Growing Needs,” ISET-PI Blog available at, (2020a).
- Babych, Y., and L. Leruth, “To Prevent, to Repair, or to Start Over: Should Georgia Put’ Maintenance’ Ahead of ‘Investment’ in Its Development Dictionary?,” ISET-PI Blog available at, (2020b).
- Batalovic, M., K. SokolijaM. Hadzialic, and N. Batalovic, “Maintenance and Operation Costs Model for University Buildings,” Tehnicki Vjesnik, 23(2), pp. 589-598, (2017).
- Blazey, A., F. Gonguet, and P. Stokoe, “Maintaining and Managing Public Infrastructure Assets,” in Schwartz et al. (2020), pp. 265-281 (2019).
- Escobal, J. and C. Ponce, “The Benefits of Rural Roads: Enhancing Income Opportunities for the Rural Poor,” Working Paper 40, Grupo de Analysis Para el Desarrollo (GRADE), Lima, Peru, (2003).
- IMF, “Fiscal Risks—Sources, Disclosure, and Management,” Fiscal Affairs Department, Washington DC,(2008).
- IMF, GFS, Government Finance Statistics Manual, IMF, Washington DC, (2014).
- PIMA EST, Republic of Estonia: Technical Assistance Report-Public Investment Management Assessment, IMF, Washington DC, (2019).
- PIMA GEO, Republic of Georgia: Technical Assistance Report-Public Investment Management Assessment, IMF, Washington DC, (2018).
- Rozenberg, J., and M. Fay, eds, “Beyond The Gap: How Countries Can Afford The Infrastructure They Need While Protecting The Planet,” Sustainable Infrastructure Series, The World Bank, Washington DC, (2019)
- Schick, A., “The Road to PPB: The Stages of Budget Reform,” Public Administration Review, 26(4), pp. 243-258, (1966).
- Schwartz, G., M. Fouad, T. Hansen, and G. Verdier, Well Spent : How Strong Infrastructure Governance Can End Waste in Public Investment, IMF, Washington DC, (2020).
- Thi Hoai Le, A., N. Domingo, E. Rasheed, and K. Park, “Building Maintenance Cost Planning and Estimating: A Literature Review,” 34th Annual ARCOM Conference, Belfast, UK (2019).
- World Bank, The Challenge of Reducing Non-Revenue Water in Developing Countries – How The Private Sector Can Help,” Water Supply and Sanitation Board Discussion Paper Series No 8, Washington DC, (2006).
- Yu, W., and M. Pollitt, “Does Liberalization Cause More Electricity Blackouts?,” EPRG Working Paper 0827, Energy Policy Research Group, University of Cambridge, United Kingdom, (2009).
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.
Energy Storage: Opportunities and Challenges

The Stockholm Institute of Transition Economics (SITE) organizes its 2021 SITE Energy Talk devoted to the economic and environmental effects of energy storage adoption.
To tackle climate change, governments around the world are incentivizing the build-out of renewable energy sources. However, the inherent intermittency of wind and solar energy can only be managed with extensive energy storage capacities. Storage systems create opportunities for new entrants as well as established players in the wind and solar industry. But they also present challenges, particularly in terms of investment and economic impacts.
The webinar will therefore shed light on why market power and the ownership structure of storage could potentially distort the incentives to invest and use the storage facilities efficiently, which runs the risk of jeopardizing their potential benefits.
Special guests
Natalia Fabra
Professor of Economics and Head of EnergyEcoLab at Universidad Carlos III de Madrid. Natalia works in the field of Industrial Organization, with emphasis on Energy and Environmental Economics, and Regulation and Competition Policy.
Learn more about Natalia Fabra
Alexey Khokhlov
Head of the Electric Power Sector at the Energy Center of Moscow School of Management, SKOLKOVO. Alexey regularly comments on the current energy issues in national business media and presents at various industry events.
Learn more about Alexey Khokhlov
Niclas Damsgaard
Chief strategist at Svenska kraftnät (the Swedish TSO). He has previously close to 15 years of experience from consultancy, most recently as director and head of Energy Markets and Strategies at Sweco. He holds a PhD in economics from the Stockholm School of Economics and is specialized in deregulation and regulation of markets with a focus on the electricity market.
Learn more about Niclas Damsgaard
Register here
Due to the pandemic, the event will be virtual this year, and preregistration for this webinar is required. We invite you to register as soon as possible, but no later than April 12, 23:30 CEST, Sweden time.
Date: Tuesday, April 13, 2021, 12:00 – 14:00 (CET, Sweden)
Location: Online. A link to the webinar will be sent to you 4-5 hours ahead of the start of the webinar.
Registration: Will remain open until the start of the webinar.