Project: FREE policy brief
Indexation Formula for Natural Gas Procurement in Ukraine
Due to the high volatility of natural gas market prices, it is almost impossible to adequately plan the purchases for the year ahead, so contract prices need to be regularly updated. This fact creates uncertainty for the contracting authorities, as well as room for unfair competition and corruption. We offer an indexation formula which uses the European gas prices as a benchmark for procurement prices and calculate the potential economic effect of this formula on the Ukrainian gas procurement market.
Problems with the Public Procurement of Natural Gas
Natural gas procurement poses a number of challenges for the contracting authorities (CAs), suppliers and controllers. Due to price volatility it is almost impossible to adequately plan the purchases for the year ahead, so prices need to be regularly adjusted. After the heating season starts, CAs find themselves in a weak position in price negotiations since they almost never have storage for accumulating stocks, and if the contract is cancelled the new procurement would take at least one month due to the existing public procurement regulations. The new version of the Law on Public Procurement, which was recently adopted by the Ukrainian parliament, addresses this problem by allowing CAs to have a new contract fast in case the previous contact was cancelled because of the supplier.
CAs often lack reliable data on market dynamics. There are cases when unreliable price references are provided by specialized agencies to support higher price claims of suppliers. As a result, CAs bear administrative responsibility if they do not have proper justification for changing contract prices when controlling agencies initiate an audit.
Natural gas suppliers may also find themselves in a situation of unfair competition. Since it is possible to win an open auction (i.e. by quoting a considerably lower than market price) and later raise the price to the market level with an additional contract, honest businesses might feel demotivated to participate in the procurement process. They cannot be sure if the contract price can be changed later because there is no proper legal mechanism to assess the need of such an adjustment.
Previous research shows that every third contract of natural gas purchase was amended with an additional contract at least once, usually raising the price for the customer (Shapoval, Memetova, 2017). Additional contracts are indeed used 1) as a tool for price overstatement by the supplier, 2) as a loophole for corruption, and 3) as a way to get a market price for a supplier who used dumping to win the auction (Gribanovsky, Memetova, 2017).
International Drivers of Gas Prices in Ukraine
Since 2016, the EU has been the only official exporter of natural gas to Ukraine. According to PwC, Ukraine imported 14.1 billion m3 in 2017, which is 44% of total gas consumption – the remaining 56% are extracted locally. In Ukraine, the prices for industrial consumers are not regulated, while the household prices are set by the government. Today, the average price on the unregulated gas market is in line with the prices in neighbouring countries – the Baltic states, Poland, Slovakia and Hungary (PricewaterhouseCoopers Advisory LLC, 2018).
European prices are formed on the large marketplaces. The two biggest hubs, Dutch TTF and British NBP, by far outweigh their competitors (ACER Market Monitoring Report, 2017). However, the third-biggest hub, German NCG, is the closest to the Ukrainian border, so its prices often become the benchmark for private traders. In some cases, NCG is the official benchmark for gas price – for instance, the purchase parity import price in Ukraine in 2017-2018 was based on this hub’s index.
In order to assess the impact of the European natural gas prices on procurement prices in Ukraine, we used the Month+1 futures hub prices from TTF, NCG and Austrian VTP CEGH. Procurement prices were extracted from the analytical module of ProZorro (the Ukrainian e-procurement system which CAs are obliged to use at all levels). We excluded irrelevant procurements and selected the contracts which had information on the volume procured. We calculated the average daily prices weighted by volume. Our dataset covers the time period from January 1, 2017 to December 31, 2018.
Figure 1: Natural gas prices at ProZorro and European hubs
Source: ProZorro data, hubs data
As one can see in Figure 1, hubs prices are highly correlated, so they cannot be used as independent variables within a single model. Thus, we decided to take the NCG Month+1 price as a benchmark for explaining the relation between internal procurement prices and international market prices.
NCG Impact on Procurement Prices in ProZorro
In the period of low business activity on natural gas markets, especially in summer, few contracts are awarded. One might have noticed from Figure 1 that this leads to higher variance in daily prices caused by random factors. Therefore, in our model we decided to use the weighted average of weekly prices instead.
Figure 2: Weekly gas price fluctuations in ProZorro and NCG
Source: ProZorro data, Pegas (https://www.powernext.com/futures-market-data)
Our econometric estimation shows that the NCG Month+1 price influences procurement prices with a lag of 7 weeks. In other words, the price at the German hub becomes relevant for the Ukrainian procurement market after almost 2 months on average.
Figure 3: Correlations between procurement prices and NCG Month+1 with different lags
According to the model, the weighted average gas price in ProZorro is more dependent on the NCG Month+1 gas price than on the reservation price in ProZorro. Thus, a UAH 1 increase in the reservation price adds UAH 0.41 to the final price, while each additional hryvnia of the NCG price leads raises the final price by UAH 0.63 in 7 weeks if the price growth trend is not taken into account.
Potential Cost-Saving Using the Price Indexation Formula
The Price Indexation Formula
As European gas prices strongly influence prices on the internal Ukrainian market, it is obvious that they should be included into the indexation formula, as well as exchange rate fluctuations. After consultations with stakeholders, the Ministry of Economic Development and Trade of Ukraine (MEDT) decided to adjust the initial formula proposed by the KSE and included price fluctuations on the Ukrainian Energy Exchange (UEEx) with a small weight into the formula in order to stimulate UEEx development.
The final formula was officially published in December 2018. This formula is not compulsory for any contract authorities, though it is recommended for use by the smaller public entities who do not have the in-house analytical capacity to make a realistic price assessment during negotiations with the suppliers.
where:
- CP – new price in UAH for 1000 m3 of natural gas (including value-added tax, VAT)
- PCP – current price in UAH for 1000 m3 of natural gas (including VAT) before adjustment
- K(cur) – average National Bank of Ukraine (NBU) UAH/EUR exchange rate for 5 days before the price change
- K(base) – average NBU UAH/EUR exchange rate on the day of the previous price adjustment (contract signed)
- NCG(avg) – average of daily NCG Month+1 index during 20 previous trading days before the day of price amendment, EUR per MW-hour
- NCG(base) – NCG Month+1 index on the day of the previous price amendment (contract signed), EUR per MW-hour
- VAT – rate of value-added tax, which is currently 20% in Ukraine
- CV – heating value of natural gas in MW-hour/1000 m3 on the date of the price adjustment
- UEEx(avg) – weighted monthly average natural gas price of UEEx (including VAT) on the day of price amendment
- UEEx(base) – weighted monthly average natural gas price on the UEEx (including VAT) on the day of the previous price amendment (contract was signed)
Thus, the formula includes current gas price, exchange rate changes, changes in NCG index and UEEx index.
Estimation of Potential Cost-Saving for Contract Authorities
The simplest yet time-efficient way to empirically verify the hypothesis of potential cost-saving after the introduction of the price indexation formula in the gas market is a retrospective analysis of the contracts which had already been signed.
The basic principle of estimation is comparing actual prices with the potential prices calculated based on the price indexation formula. For this, we collected a dataset of natural gas procurement contracts covering the time period from August 2017 to the end of August 2018. This period includes both short-term contracts signed for the heating season or its part (usually signed in August-September, sometimes in January-February) and middle-term contracts which are active for at least one year (usually signed in December-March). We took into account all the additional contracts to these contracts signed before January 1, 2019.
Supply schedules and prices of additional contracts are not readily available in a machine-readable format, so we kept only contracts with the total value higher than UAH 1 million. These are 27.5% of all contracts but they cover 79.3% of the total value of natural gas procurement in Ukraine. The final dataset contains prices of additional contracts and monthly supply schedules.
Our earlier analysis of all the contracts on the shorter time scale showed no correlation between prices and volumes in gas procurement contracts (Shapoval, Memetova et al., 2017), therefore our results can be extrapolated to all the gas contracts.
The biggest gap between actual and indexation prices would be in November 2017, averaging UAH 623. However, until the end of the year the gap reduced threefold to UAH 170.
Figure 4: Monthly increase of gas procurement prices
Source: bipro.ProZorro, ProZorro API
We combined the supply schedules with the prices found in the additional contracts in order to estimate potential savings. Obviously, the highest savings were observed during the heating season. However, in September they were negative (see Figure 6). Thus, while the market prices of natural gas started rising in August, actual procurement prices lagged behind until the end of September-October.
Figure 5: Monthly cost savings in case of applying price indexation formula
Source: bipro.ProZorro, ProZorro API
In total, for contracts of over UAH 1 million, potential cost savings from applying the price indexation formula would have been equal to UAH 120.25 million. If these estimations are extrapolated to all the contracts, this figure would reach UAH151.6 million. This is a rather modest sum in relative terms – only 2.7% of the total contract value. However, using the formula is expected to assist smaller CAs who often lack the knowledge of market dynamics to negotiate the optimal price more effectively and limit their dependence on the suppliers’ estimates.
Besides, the parties concluded the contracts without taking into account the opportunity of using the indexation formula. Therefore, actual cost savings might be lower, first of all because the suppliers’ auction strategy would be different. In particular, the dumping strategy with subsequent price increase through additional contracts would become useless. If the formula is used, a lower starting price would mean a lower increase in absolute terms (UAH per 1000 m3), because the formula calculates the change in relative terms (in per cent). For example, if the market price grows by 15% during the indexation period, the starting price can also be raised by only 15%.
Conclusion
The application of the price indexation formula for natural gas procurement may have a positive impact on the public procurement market. We recommend taking into account the prices of the European hubs adjusted by exchange rate fluctuations.
Had the price indexation formula been used for additional contracts in gas procurement in 2017-2018, the average price would have declined by UAH 623, potentially allowing CAs to save UAH 151.6 million.
Formula pricing would raise the negotiation power of customers (CAs) before the start of the heating season. This is especially true for the smaller ones which are not able to professionalize procurement processes. Natural gas price indexation within clearly defined boundaries will create more favourable conditions for fair competition by eliminating the stimuli for dumping at the auction stage.
References
- ACER Market Monitoring Report, 2017 .
- Gribanovsky Olexiy, Memetova Inna, 2017. “Additional contracts as a result of price dumping” (in Ukrainian).
- Order of CMU 187 of March, 22 2017, http://zakon.rada.gov.ua/laws/show/867-2018-%D0%BF#n127 (in Ukrainian).
- PricewaterhouseCoopers Advisory LLC, 2018. “Ukrainian gas market: Discovering investment potential and opportunities”.
- Shapoval Natalia, Memetova Inna, 2017. “Additional contacts in Ukraine: causes and methods of prevention” (in Ukrainian).
- Shapoval Natalia, Memetova Inna, Gribanovsky Olexiy, Tchmil Olexandra, 2017. “Three Sources of Losses in Natural Gas Public Procurement” (in Ukrainian).
Data Sources
- CEP, 2019. Source code of the project [github repository] https://github.com/cep-kse/natural_gas_formula.
- EUStream, Energy content at Budince. [web page] https://tis.eustream.sk/TisWeb/#/?nav=bd.gcv.
- PowerNext, 2017. Futures market data. [web page]. Retrieved from https://www.powernext.com/futures-market-data.
- ProZorro, 2014-2020. Ukrainian public procurement data. [bi system] http://bi.prozorro.org.
Does Gender Diversity Actually Matter?
Measuring the effects of gender diversity on performance is important to understand the impact of gender quotas. However, the effects of gender diversity remain understudied. We need data with a reliable assessment of team member quality to disentangle the effects of diversity from compositional effects (when higher-quality women replace mediocre men). We use the unique database of the trivia game “What? Where? When?” which has information on both the performance and gender composition of the team and allows to track each player individually. We find that the gender diversity of the team has no statistically significant effect once we control for the quality of each player. In this particular environment, with little evidence of gender discrimination, instruments like gender quotas have no merit. This result does not apply to discriminatory environments where gender quotas could bring benefits through compositional effects.
Introduction
As gender quotas have been widely introduced in politics and in the corporate world, the effects of gender diversity have become the center of attention of many economists. Many observational studies find positive effects of gender diversity on corporate boards’ performance (Desvaux, Devillard, & Sancier-Sultan, 2010). Other studies, using the introduction of gender quotas in boards as a natural experiment, find negative effects on stock valuation, which disappear in the longer run (Ahern and Dittmar, 2012; Matsa and Miller, 2013; Eckbo et al., 2019).
The effect of gender diversity on team performance may run through two different mechanisms. One mechanism is compositional effects due to discrimination: if women face a glass ceiling, only the best women get into teams/boards, and they are on average of higher quality than men. Hence, boards with female representatives perform better. The discrimination mechanism has been shown to be at work in the political setting, for example: gender quotas in parties lead to higher-quality women replacing mediocre men (Besley et al., 2017). The other mechanism is the true effect of gender diversity through complementarity between men and women: if they differ substantially in some dimensions, these differences might become the source of better team decisions, or, on the contrary, inefficiencies in decision-making.
To separate between the two mechanisms – compositional effects and diversity effects – we need data with reliable quality measurement for each team member. Controlling for team member quality would take care of the compositional effect, and the gender composition would be significant only if there is a true gender diversity effect.
We use the What? Where? When? trivia game dataset to measure the effects of gender diversity on team performance with and without control for a player’s quality.
The What? Where? When? Game
What? Where? When? (WWW) is a team-played trivia game popular in post-Soviet countries. Teams of six players are asked questions and have one minute to come up with an answer. Typically, in order to find the correct answer, a team needs to combine both logical thinking and knowledge. A tournament usually consists of 36-90 questions. The team with the most correct answers wins the first place. In 2003, a unified database of the game was created. This database contains records of more than 218,000 individuals who have played in at least one of the 6,000 recorded tournaments.
The What? Where? When? Dataset
A unit of observation in our dataset is one game played by a team. It contains the unique ID of the team, the ID of each player, information about the number of games played by the team and by each player, the tournament date, the difficulty of the tournament and the number of teams. We identify the gender of the players through their names and patronymic names. Overall, we use 74,475 team-game observations which were played by 2,854 teams (23,000 single players) from 2013 to 2018.
Performance Measure
The measure of a team’s performance in a tournament is the percentage of correct answers normalized by the average percentage of correct answers in this tournament. We use player’s individual fixed effects as a measure of their quality in our regression analysis.
Gender Aspects in What? Where? When?
Only 31.5% of the players in the sample are female, however, other than that, we fail to find any significant evidence indicating gender discrimination or segregation. Table 1 presents the actual shares of team-game observations by gender composition as well as the predicted shares if assignment to teams was random. The difference between the actual shares and predicted shares does not appear to be economically significant.
Table 1: The actual distribution of women across teams is not different from random
Source: Authors’ calculations based on the What? Where? When? dataset. Random assignment assumes that the share of women across all teams is equal to 31.5% as in the actual data.
Results
The basic model of our analysis, Model 1 examines the association between the performance of a team, normalized by tournament difficulty, with dummy variables for gender diversity (defined as the number of minority gender players in the team, i.e. diversity_1 is true if there is only one woman or only one man on the team). We also include the individual fixed effects of each player in the second specification (Model 2), to control for the quality of players and rule out possible composition effects.
Table 2. Effect of diversity on performance with and without the individual quality controls
Source: Authors’ calculations based on What? Where? When? dataset. Individual fixed effects are included in the specification with the quality control. Only players who played at least a median number of games (62) are included.
The coefficients of Model 1 and 2 are shown in Table 2. While diversity is significant in the first specification, after accounting for the individual quality of players, we cannot reject the hypothesis of insignificance of gender diversity. These results hold under different specifications: with controls for player experience, with different player experience cutoffs, or including the neural network-generated predictions of performance.
Figure 1. The distribution of individual coefficients (proxy for player quality) for female and male players
Source: Authors’ calculations based on the What? Where? When? dataset. Each individual coefficient is a proxy to the player’s quality estimated in the regression from Table 2. Only players who played at least a median number of games (62) are included.
Figure 1 presents the distributions of individual coefficients of female and male players. In our sample, the female distribution centers slightly to the left of the male one. It explains the negative diversity coefficients in the specification without the individual fixed effects – in this case, the diversity dummies capture the lower average quality of female players.
Conclusion
Our study aimed at disentangling compositional and pure effects of gender diversity by using a novel dataset of a team played trivia game. Our main finding is that after accounting for the individual quality of team members, the gender composition of a team does not appear to be significant for a team’s performance.
Although it is always dangerous to extrapolate findings obtained in specific settings, we believe that the positive gender diversity effects found in other studies are often manifestations of the change in the average quality of team/board members i.e. compositional effects rather than gender diversity effects per se. From a policy point of view, this means that while we need gender quotas in areas suffering from gender discrimination, once we reach equal opportunities such instruments may no longer have any positive effects.
References
- Ahern, Kenneth R., and Amy K. Dittmar, 2012. “The changing of the boards: The impact on firm valuation of mandated female board representation.” The Quarterly Journal of Economics 127.1: 137-197.
- Besley, Timothy, Olle Folke, Torsten Persson, and Johanna Rickne, 2017. “Gender quotas and the crisis of the mediocre man: Theory and evidence from Sweden.” American Economic Review 107, no. 8 : 2204-42.
- Desvaux, Georges, Sandrine Devillard, and Sandra Sancier-Sultan, 2010. “Women at the top of corporations: Making it happen.” McKinsey & company : 7-8.
- Eckbo, B. Espen, Knut Nygaard, and Karin S. Thorburn, 2019. “Board Gender-Balancing and Firm Value.” Dartmouth College working paper.
- Matsa, David A., and Amalia R. Miller, 2013. “A female style in corporate leadership? Evidence from quotas.” American Economic Journal: Applied Economics 5.3: 136-69.
Ethnic Geography: Measurement and Evidence
The effects of ethnic geography, i.e. the distribution of ethnic groups across space, on economic, political and social outcomes, are not well understood. We develop a novel index of ethnic segregation that takes both ethnic and spatial distances between individuals into account. Importantly, we can decompose this index into indices of spatial dispersion, generalized ethnic fractionalization, and the alignment of spatial and ethnic distances. We use ethnographic maps, spatially disaggregated population data, and language trees to compute these four indices for 161 countries. We apply these indices to study the relation between ethnic geography and current economic, political and social outcomes. We document that country level quality of government, income and trust increase with the alignment component of segregation.
Ethnic Geography: Key Idea
There is a vast literature on how a country’s ethnic diversity affects economic, political and social outcomes. This literature provides evidence for negative effects of ethnic diversity on e.g. peace, public goods provision, redistribution, the quality of government, and economic development in general. In these studies, ethnic diversity is typically quantified by indices based on the different ethnic groups’ country-wide population shares. By definition, these indices ignore ethnic geography, i.e. the distribution of ethnic groups across space.
Alesina and Zhuravskaya (2011) make an important first step towards taking ethnic geography into account. They construct an index of ethnic segregation that is based on the various ethnic groups’ population shares in different subnational units such as regions or provinces. We contribute to the literature on ethnic diversity by proposing a set of indices that capture important aspects of ethnic geography.
Theory
We derive a new segregation index that is based on both spatial and ethnic distances between pairs of individuals. Starting from a general class of indices that are expressions of the relation between a randomly selected pair of individuals, we uniquely characterize an index via a set of axioms. Our index avoids the standard problems of the so-called a-spatial segregation measures (based on population shares in administrative units), in particular the border dependence mentioned by Alesina and Zhuaravskya (2011) and the checkerboard problem (White 1983, Reardon and O’Sullivan 2004). Both problems are potentially very severe and are illustrated in detail in the paper. Importantly, our index can be decomposed into three (sub)indices: an index of spatial dispersion, a well-known index of generalized ethnic fractionalization (see below), and a measure of the alignment of spatial and ethnic distances between individuals (i.e. ethno-spatial alignment or, simply, alignment hereinafter). Interested readers can also find a stylized illustration of what each component stands for in the paper.
Data and Illustration
We compute these four indices of ethnic geography for 161 countries from all over the world using a combination of digital maps showing the distribution of ethno-linguistic groups all over the world and the current population at a very high resolution. As robustness check, we also compute our measure using historical population maps as well as a simpler map based on global land cover data that should proxy for the exogenous component of the spatial distribution of a country’s population.
This provides us with real world examples of countries that differ in, for example, alignment, but are otherwise similar. For example, Togo and Benin are neighboring countries located in West Africa with comparable climatic, geographic and demographic characteristics. Moreover, they were both French colonies after WWI, became independent in 1960, and started their post-colonial history in tumultuous ways that culminated in coups. The ruling autocrats both managed to stay in power for many years.
Benin and Togo are also comparable in terms of generalized ethnic fractionalization (between the median and the third quartile of our sample) and spatial dispersion (above the third quartile). Ethno-spatial alignment is however considerably higher in Benin (1.35, which is above the third quartile) than in Togo (1.11, which is below the median). Figure 1 shows the different ethnic homelands and the main language groups which these ethnic homelands belong to.
Ethno-spatial alignment is relatively high in Benin as there is a relatively clear divide between Kwa speaking groups in the South, Defoid speaking groups in the Center, Gur speaking groups in the North, and some smaller groups speaking very different languages in the North East. As a result of this divide, linguistically distant individuals tended to live far apart from one another. In contrast, ethno-spatial alignment is relatively low in Togo, mainly because there are Gur and Kwa speaking groups in the country’s South, its Center and its North. As a result of these large and widespread language groups, linguistically distant individuals often lived relatively close to one another.
Figure 1:
Source: Maps of Togo (left) and Benin (right) showing the traditional homelands of language groups according to WLMS and our grid cells. Each grid cell constitutes a different location in the computation of our indices, each color indicates that the corresponding grid cell belongs to the traditional homeland of a certain language group (with the relevant language groups given in the legend), and the brightness of this color indicates the current population (also given in the legend). The legend entries Gur/Kwa and Gur/Defoid indicate the traditional homelands of multiple language groups, some speaking a Gur language and some a Kwa or Defoid language. WLMS indicates no traditional homelands in the white areas.
Empirical Analysis
We use our indices in cross-country regressions to improve our understanding of the role that ethnic geography plays in economic, political and social outcomes around the globe. We first focus on the associations between our index of ethnic segregation on the one hand, and the quality of government, incomes and generalized trust on the other hand. We find a negative relation between ethnic segregation and the quality of government, similar to Alesina and Zhuravskaya (2011) with their index of a-spatial segregation in their sample of 97 countries. We further find that our index of ethnic segregation tends to be negatively associated with incomes, too, but unrelated to generalized trust. See also Ejdemyr et al. (2018) and Tajima et al. (2018) for recent contributions on Malawi and Indonesia.
More importantly, we study the relation between the three components of our index of ethnic segregation – ethnic fractionalization, spatial dispersion and ethno-spatial alignment – and these outcome variables. Strikingly, we find a positive and statistically significant association between the alignment of ethnic and spatial distances between individuals, and the quality of government, incomes and trust. Hence, societies perform better when ethnically diverse people live far apart, relative to what they would have, had all ethnic groups been represented in all locations with population shares equal to their country shares.
Conclusion
To better understand the role of ethnic geography and to mitigate well-known problems of a-spatial segregation measures, we have developed a new segregation index that is based on ethnic distances between groups and spatial distances between locations rather than categorical data on ethnic groups and administrative units.
The decomposition of our segregation index reveals that it corresponds to the product of generalized ethnic fractionalization, spatial dispersion, and the alignment between ethnic and spatial distances. This ethno-spatial alignment is a novel concept that captures, broadly speaking, whether ethnically different individuals tend to live far from each other, relative to the situation where all groups appeared in each location with population shares equal to their country ones.
Using these indices in cross-country regressions suggests, among other things, that countries with higher ethno-spatial alignment tend to be better governed, richer, and more trusting.
Of course, the indices we have developed can also be applied to measure the ethnic geography of cities. For example, one could use our segregation index instead of a-spatial measures to compare segregation across Russian metropolitan areas or within metropolitan areas over time. Finally, we would like to stress that our theoretical framework is not specific to the ethnic dimension. Instead of categorizing individuals by ethnic groups and measuring linguistic distances, future research could focus on other social or socio-economic cleavages that are believed to be salient in a particular setting.
References
- Alesina, Alberto, and Ekaterina Zhuravskaya, “Segregation and the Quality of Government in a Cross Section of Countries,” American Economic Review, 101 (2011), 1872–1911.
- Ejdemyr, Simon, Eric Kramon, and Amanda Lea Robinson, “Segregation, Ethnic favoritism, and the Strategic Targeting of Local Public Goods,” Comparative Political Studies, 51 (2018), 1111–1143.
- Hodler, Roland, Michele Valsecchi and Alberto Vesperoni, “Ethnic Geography: Measurement and Evidence,” CEFIR Working Paper No. 253, June 2019. http://cefir.ru/download.php?id=4681
- Reardon, Sean F., and David O’Sullivan, “Measures of Spatial Segregation,” Sociological Methodology, 34 (2004), 121–162.
- Tajima, Yuhki, Krislert Samphantharak, and Kai Ostwald, “Ethnic Segregation and Public Goods: Evidence from Indonesia,” American Political Science Review, 112 (2018), 637–653.
- White, Michael J., “The Measurement of Spatial Segregation,” American Journal of Sociology, 88 (1983), 1008–1018.
The Political Economics of Long Run Development in Eastern Europe: Insights from the 2019 SITE Academic Conference
Thirty years after the fall of communism, many assume that the economic transition of Eastern Europe and the former Soviet States towards a system of market economy is complete. But the region faces new challenges, of both economic and political kind, which renders a thorough understanding the past even more important. This policy brief is based on the scientific contributions presented at the 7th SITE Academic Conference held at the Stockholm School of Economics from December 16th to December 17th, 2019. Organized by the Stockholm Institute of Transition Economics (SITE), the conference brought together academics from all over Europe and the United States to share and discuss their research on economic and political development in Eastern Europe.
The Imperial and Soviet Periods
In the first section of the conference, papers with a focus on the long-term history of Eastern Europe and its implications for more recent events were presented. Marvin Suesse presented his research on how the Russian State Bank financed Tsarist Russia´s belated industrialization, a question that had been discussed by historians, but never thoroughly analyzed quantitatively. By geo-coding historical manufacturing censuses around the turn of the century and using distance between bank branches and factory location, the causal impact of the expansion of the State Bank is estimated, revealing large effects on firm revenues and productivity. These effects are largest in areas where alternative means of financing were least available and where human capital was more abundant.
Natalya Naumenko presented her findings on the economic consequences of the 1933 Soviet famine, which in terms of casualties was extremely devastating. She uses the meteorological conditions a year earlier as an instrumental variable and finds that the famine, which was mostly a rural phenomenon, had a persistent negative effect on the urban population while the rural population recovered relatively quickly.
Gerhard Toews discussed the long-term consequences on regional development of the displacement of an estimated 3 million “enemies of the people”, political prisoners typically belonging to the elite of the society, into the gulags in the early years of the Soviet Union. Using archival data, he has constructed a large database describing the gulag population in terms of the shares of “enemies” relative to other prisoners and taking into account their socio-economic characteristics i.e. the much higher levels of education of the former group. Exploiting variation within gulags, the results suggest that a historically higher density of “enemies” means higher economic prosperity today as measured by nightlight intensity.
Taking another angle, Christian Ochsner investigated the effects of the Red Army´s occupation on post-war Europe, using the demarcation line crossing the Austrian state of Styria as a natural experiment. His conclusion is that even the temporary occupation affected the region’s long-term development, the main channel being age-specific migration.
Finally, Andreas Stegman offered an analysis of the effects of the 1972 East German Extended Visitors Program. The program reduced travel restrictions for West German visitors traveling to certain districts of East Germany. Using a geographic regression discontinuity design comparing similar districts with and without the program, he shows that included districts indeed received much more visits from West Germany and that their citizens were more likely to protest against the Communist government and less likely to vote for the ruling party. This suggests that face-to-face interaction can influence beliefs and attitudes in non-democratic regimes, in turn influencing individual behavior and societal outcomes during transition.
Corruption, Conflict and Public Institutions
Another topic of the conference was the current role of corruption, conflict, electoral fraud and public sector effectiveness for the region. Scott Gehlbach presented his most recent research on the ownership patterns and strategies of Ukrainian oligarchs before and after the Orange revolution. By mapping oligarchs to changing political leadership, he shows how firm owners in Ukraine take actions to protect their property depending on their connections with the current government. He finds that obfuscation of ownership behind holding companies and complicated structures is a potentially valuable strategy in this environment in general but becomes particularly important when an oligarch loses direct connections to the ruling regime.
Likewise, Timothy Frye analyzed election subversion by employers in Russia, Argentina, Venezuela, Turkey and Nigeria. He finds that in Russia, public sector employers and especially state-owned firms are more likely to influence their employees’ decision to vote than private companies. Furthermore, work place mobilization by employers in Russia is clearly negatively associated with the freedom of the press. Election subversion is more likely to be successful when the degree of dependence of the employee is high and the employer’s potential threats are credible. Among Russian firm officials, the most frequently named motivations for them to practice election subversion are the desire to improve their relationship with the authority and the intention to help their party.
Michal Myck studied the impact of the transition experience on economic development around the Polish-German border. Polish communities close to the border were economically backward at the beginning of the transition but could potentially benefit from trade opportunities with an opening towards the West. Using similar methods to those of Stegman above, and nightlight intensity as a measure of economic activity as for instance Toews, Myck finds significant evidence for economic convergence both between Germany and Poland, and between Polish border regions and the rest of Poland.
Vasily Korovkin presented his research on the impact of the conflict in Eastern Ukraine on trade in non-conflict areas in Ukraine, hypothesizing that the conflict may cause a trade diversion away from Russia, particularly so in areas with many ethnic Ukrainians. Using variation in the share of the Russian speaking population at the county level as well as detailed firm level export and import data, he finds that the decrease in trade with Russia is negatively correlated with the share of the Russian speaking population. Potential mechanisms include a decline in trust at the firm level and changes in local attitudes including consumer boycotts.
Finally, Tetyana Tyshchuk analyzed the effects of a Ukrainian public sector reform on civil servants’ capacity and autonomy. The reform created public policy directorates parallel to the regular bureaucracy in 10 ministries. Members of the directorates were hired based on a different procedure and different merits relative to regular public servants and received significantly higher salaries. Tyshchuk finds that the better paid civil servants indeed score higher on many, though not all, indicators of capacity and autonomy.
Information, Populism and Authoritarianism Today
The final important theme of the conference was the role of information and media, old and new, in today’s politics. In the event´s first keynote speech, Ruben Enikolopov analyzed the political effects of the Internet and social media whose low entry barriers and reliance on user-generated content make them decisively different from traditional media channels. On the one hand, this represents a chance for opposition leaders and whistleblowers to make their voice heard and may improve government accountability. On the other, these media may also become a platform for extremists. Enikolopov presented some of his work analyzing to what extent social media has contributed to fighting corruption in Russia. Using the timings of blog posts by the famous Russian opposition leader Alexei Navalny on corporate governance violations in state-owned companies, he shows that revelations resulted in an immediate drop in the price of the traded shares of the respective companies. He also finds evidence suggesting that Navalny´s blog posts resulted in management changes in these companies. In related papers, he exploits the spread of VKontakte (VK), the Russian version of Facebook, to better understand the influence of social networks on political activism, voting and the occurrence of hate crime. He finds that the spread of VK is indeed causally related to political protests, though not because it nurtures opposition to the government, but rather because it facilitates protest co-ordination. With respect to hate crime, he finds that social media only has an effect in areas where it falls on fertile grounds and where there already are high levels of nationalism. The tentative conclusion is that in Russia – as in Western countries – social media seems to have increased political polarization.
On a similar topic but taking a more theoretical approach, Galina Zudenkova investigated the link between information and communication technologies (ICT), regime contestation and censorship. In a game theoretical framework, where citizens use ICT both to learn about the competency of the government and to coordinate protests, governments can use different tools to censor information to increase their chances of survival. Zudenkova finds that less competent regimes are more likely to censor coordination, whereas intermediate regimes are more likely to focus on censoring content. These theoretical predictions are then tested using country level data.
The targeted use of information has also played a key role in Putin’s Russia according to Daniel Treisman. In his keynote speech, he argued that while the 20th century dictatorships were mainly based on violence and ideology, the 21st century has been characterized by a sizeable shift towards what he calls “informational autocracy”. Constructing a dataset on the methods used by authoritarian regimes to maintain power between 1946 and 2015, he shows that the use of torture and violence peaked among those dictators who took power in the 1980s and has declined since. Furthermore, he highlights a remarkable shift from topics of violence towards topics of economic competency in dictators’ speeches. However, Treisman finds that by instrumentalizing information, dictators fool the public “but not the elite”. In democratic regimes, those with tertiary education tend to rate their political leaders higher than people without tertiary education. In the new informational authoritarian regime, the opposite seems to be the case. According to Treisman, this is because the “informed elite” has a better understanding of the political reality in places where the media is censored, Putin’s Russia being a good example. Treisman concluded that this new model of authoritarianism has become the prevalent model outside of Europe and today also has its advocates inside the European Union.
The conference ended with a final keynote speech by Sergei Guriev on the political economy of populism. Using existing definitions, he first confirmed that Europe has seen a rise in right-wing populism in the last 20 years. Secular trends, such as globalization and new communication technology, but also the recent global financial crisis, are driving factors behind the rise of populist parties. For instance, analyzing regional variation in voting patterns suggests that the Brexit vote was primarily driven by economic motives rather than by anti-immigrant sentiments. Ironically, though, most evidence suggests that populist governments have a below-average economic performance once in office, the US and Poland being notable exceptions. A key point of Guriev’s presentation was that populism seems to be a good method to obtain power, but, once in power, populists tend to be less successful in promoting citizen welfare. These findings seem to be of high importance given the increasing public support for populist parties around the world and in parts of Eastern Europe
The conference was very well received and on behalf of SITE, the authors would like to express their appreciation to all speakers and participants for sharing their knowledge and to Riksbankens Jubileumsfond for financial support. For those interested to learn more about the papers summarized very briefly above, please visit the conference website and the presenters’ websites as indicated in the text and here below.
Speakers at the Conference
Andreas Stegman, briq – Institute on Behavior and Inequality
Christian Ochsner, CERGE-EI and University of Zurich
Daniel Treisman, University of California, Los Angeles
Galina Zudenkova, TU Dortmund University
Gerhard Toews, New Economic School Moscow
Marvin Suesse, Trinity College
Michal Myck, CenEA
Natalya Naumenko, George Mason University
Ruben Enikolopov, New Economic School Moscow
Scott Gehlbach, University of Chicago
Sergei Guriev, Sciences Po Paris
Tetyana Tyshchuk, Kyiv School of Economics
Timothy Frye, Columbia University
Vasily Korovkin, CERGE-EI
Income Inequality in Transition. New Results for Poland Combining Survey and Tax Return Data
We re-examine the evolution of income inequality in Poland in the process of post-socialist transition focusing on the previously neglected problem of under-coverage of top incomes in household survey data. Multiple statistical techniques (Pareto imputation, survey reweighting, and microsimulation methods) are applied to combined household survey and tax return data in order to obtain top-corrected inequality estimates. We find that the top-corrected Gini coefficient grew in Poland by 14-26% more compared to the unadjusted survey-based estimates. This implies that over the last three decades Poland has become one of the most unequal European countries among those for which top-corrected inequality estimates exist. The highest-income earners benefited the most during the post-socialist transformation: the annual rate of income growth for the top 5% of the population exceeded 3.5%, while the median income grew on average by about 2.5% per year. This brief summarizes the results presented in Brzezinski et al. (2019).
Introduction
There is a large economic literature documenting income inequality changes experienced by former communist countries during their post-1989 transformations. While in Russia and in many post-Soviet economies, inequality exploded during the transition, Poland is often perceived as a country where inequality grew rather moderately. However, these conclusions may be unreliable as they are based on inequality measures estimated using income data only from household surveys.
Many recent studies show that surveys are plagued by significant under-coverage of top incomes, which leads to a severe downward bias of the inequality estimates. Several approaches have been proposed to correct for this problem. One of them is to combine survey data with income information taken from administrative sources such as tax returns. While top-corrected inequality estimates have been produced for many advanced economies, transition countries received little attention in this context so far.
For Poland, Bukowski and Novokmet (2019) provided series of top income shares estimated using tax data. However, their estimates are constructed for gross (pre-tax) income distributed among tax units. This kind of income concept deviates considerably from the primary measure of the standard of living analysed in income distribution literature, namely disposable equivalized household income defined for the entire population. Estimates based only on tax data are not directly comparable to standard survey-based measures, which makes it difficult to decide which of the two kinds of results are closer to the underlying inequality trends and levels.
In a recent paper (Brzezinski, Myck, Najsztub 2019), we provide the first estimates of top-corrected inequality trends for real equivalized disposable incomes in Poland over the years 1994-2015. These estimates can be readily compared with standard survey-based estimates available from Statistics Poland or from Eurostat. Our analysis re-evaluates distributional consequences of post-socialist transition in Poland.
According to the standard view, the Polish transition to a market economy was an almost unqualified success story. Poland managed to achieve fast and stable economic growth (around 4.3% per year since 1994) that was at the same time broadly inclusive and shared rather equally by various social classes and segments of the income distribution. Survey-based estimates suggest that the Gini index for Poland has not increased significantly since 1989 and reached the average level among the EU countries in 2015. In contrast to the standard view, our top-corrected results show that the inequality of living standards in Poland grew sharply over 1989-2015. The adjusted Gini index grew by 4-8 p.p. to a level that ranks Poland among the most unequal European countries for which comparable estimates exist.
Data and Methods
We use data from two sources. Our survey income data comes from the representative Polish Household Survey (PHBS) conducted annually by Statistics Poland since 1957. We use the PHBS data for 1994-2015 as the pre-1994 surveys do not contain data on individual incomes (required for our microsimulation modelling) and 2015 is the last year for which estimates of tax-based inequality measures are available. We adjust the baseline PHBS survey weights to match the census-based number of males and females by age groups (population weights). We also create a further adjusted set of weights to match the number of PIT payers in each tax bracket according to the Polish tax scale (tax weights).
Our main income variable is real equivalent household disposable (post tax and transfer) income. We obtain it from the Polish microsimulation model SIMPL applied to the PHBS data. The microsimulation model allows us to construct a gross (before PIT and employee SSCs) income distribution among the tax units, which is unavailable in the raw PHBS data. This is crucial as it is the gross income distribution between tax units to which we impute top incomes estimated using tax-based statistics.
Our second data source is the series of tax-based top income shares for Poland taken from Bukowski and Novokmet (2019). To construct top-corrected inequality estimates, we follow the methodological approach of Bartels and Metzing (2019). Using the microsimulation model applied to the PHBS data we obtain the distribution of gross income among tax units (individuals). In the next step, we use data on top income shares to estimate the parameters of a Pareto distribution for gross income distribution in terms of tax units. Then, we replace the top 1% (or 5%) of tax units’ incomes with the incomes implied by the estimated Pareto distribution. The resulting imputed gross distribution is subsequently reweighted using either population or tax weights. After imputing top incomes, we again use the microsimulation approach to compute top-corrected real equivalized household net incomes.
Corrected Income Inequality Trends
Figure 1: The Gini index for Poland, 1994-2015: unadjusted vs top-corrected estimates
Note: Vertical lines show 95% confidence
Figure 1 presents our income inequality estimates in terms of the Gini coefficient. For the period 1994-2005, we present two top-corrected series, which can be considered as lower and upper bound estimates of the “true” Gini. The results for this period are more uncertain as they are affected by the 2004 tax reform in Poland that introduced an optional flat tax for non-agricultural business income, which reduced the marginal tax rate for the highest income taxpayers from 40% to 19%. Research suggests that before the reform the problems of tax evasion and avoidance could have been more pronounced in Poland and some of the top incomes were unreported or under-reported. The upper bound series on Figure 1 corrects for the possible higher tax evasion and avoidance before 2005.
The unadjusted Gini series suggests that income inequality in Poland was rather stable over 1994-2015. On the other hand, our top-corrected series point to a very different story. Until 2005, our two correction procedures show similar inequality trends, but somewhat different levels. After 2005, our corrected series shows systematic and high divergence between unadjusted and top-corrected Ginis ranging from 4 to 8 p.p. The top-corrected Ginis increase in the range from 14 to 26% over 1994-2015. While according to the unadjusted data Poland is only moderately unequal, the comparison of top-corrected estimates shows that in 2015 Poland has higher level of income inequality than even high-inequality EU countries such as Germany, Spain or UK.
We also show that each percentile of the disposable income distribution in Poland saw income increases in absolute terms between 1994 and 2015. This implies that on average the incomes of all social groups increased during the transition to market economy. However, these gains were shared unequally. According to our adjusted estimates, the cumulative growth in real income over 1994-2015 for the top 1% of Poles reached 122-167%, while for the bottom 10% the corresponding number is at most 57%.
Redistribution and Progressivity of the Tax System
We also analyse how our correction procedures affect measures of redistribution and progressivity of direct taxation (income taxes, employees’ mandatory social security contributions, and health insurance). The top-corrected estimates show that the percentage reduction in the Gini index due to social insurance contributions and PIT has fallen from 19.2% in 1999 to 11.6% in 2015.
While the unadjusted series suggests that the progressivity of the Polish system of PIT and social insurance contributions has decreased only mildly over time, the top-corrected series points to a much steeper fall, especially during 2005-2009. Without the top-correction, the progressivity in 2015 is overestimated by 2.3 p.p. (or by 40%). Much of the decline in tax progressivity over 2005-2009 is due to the reduction from three PIT brackets and marginal tax rates to just two brackets and rates (18% and 32%) in 2009. Even in terms of the unadjusted data, Poland ranks in the recent years as the country with the lowest PIT and SICs progressivity in the EU.
Conclusion
Our recent paper on estimating the top-corrected measures of income inequality shows that while Poland was already a relatively unequal country in the early 1990s, it has become one of the most unequal European countries (not including Russia) among those for which comparable estimates exist. The results have important implications for the assessment of the distributional consequences of post-socialist transformations or modernization processes in emerging countries. They indicate that using income tax data and imputation or reweighting techniques to account for the problem of missing top incomes in survey data can significantly alter the conclusions about income inequality levels and trends. More reliable inequality estimates would contribute not only to a better understanding of economic transformation and modernization processes but could also shed some light on recent political turmoil in many transition and emerging countries (such as Turkey, Hungary or Poland). As suggested by some recent research, the growing distributional tensions in emerging countries of Eastern Europe and Central Asia may be associated with more distrust in governments and an increased propensity to vote for radical political parties.
Acknowledgements
The authors gratefully acknowledge the support of the Polish National Science Centre (NCN) through project number: UMO-2017/25/B/HS4/01360. For the full list of acknowledgements see Brzezinski et al. (2019).
References
- Bartels, C., Metzing, M. (2019). An integrated approach for a top-corrected income distribution. The Journal of Economic Inequality, 17(2), 125-143.
- Brzezinski M., Myck M., Najsztub M. (2019), Reevaluating Distributional Consequences of the Transition to Market Economy in Poland: New Results from Combined Household Survey and Tax Return Data. IZA DP No. 12734.
- Bukowski P., Novokmet F. (2019), Between Communism and Capitalism: Long-Term Inequality in Poland, 1892-2015. CEP Discussion Paper No 1628 June 2019.
From Partial to Full Universality: The Family 500+ Programme in Poland and Its Labour Supply Implications
The implementation of the ‘Family 500+’ programme in April 2016 represented a significant shift in public support for families with children in Poland. The programme guaranteed 500 PLN/month (approx. 120 euros) for each second and subsequent child in the family and the same amount for the first child in families with incomes below a specified threshold. As of July 2019, the benefit has been made fully universal for all children aged 0-17, an extension which nearly doubled its total cost and benefited primarily middle and higher income households. We examine the labour market implications of both the initial design and its recent fully universal version. Using the discrete choice labour supply model, we show that the initial Family 500+ benefits generated strong labour supply disincentives and were expected to result in the withdrawal of between 160-200 thousand women from the labour market. The recent removal of the means test is likely to nullify this negative effect, leading to an approximately neutral impact on labour supply. We argue that when spending over 4% of GDP on families with children, it should be possible to design a more comprehensive system of support, which would be more effective in reaching the joint objectives of low child poverty and high female employment combined with higher fertility rates.
Introduction
Following the 2015 parliamentary elections in Poland the ruling Law and Justice Party was quick to fulfill their campaign promise of implementing a generous quasi-universal family support programme. In April 2016, all families began receiving PLN 500 (approx. 120 euros) per month for each second and subsequent child, while households that passed an income means test were granted the same amount for their first or only child. At a cost of nearly PLN 22 billion (5.2 billion euros, approx. 1.1% of GDP) per year, the Family 500+ benefit became the flagship reform of the Law and Justice government’s first term.
With new elections approaching in October this year, the government announced a significant expansion of the programme in May, which made it fully universal. The extended programme is nearly twice as expensive with an additional cost of PLN 18.3 billion (4.3 billion euros) per year, valuing the whole package at over 2% of GDP. This takes the total value of financial support for families with children, including family benefits and child-related tax breaks, to 4% of GDP and it means that as far as family support is concerned, the ruling party has brought Poland from one of the lowest-spending countries in the EU to one of the highest over the course of 4 years.
The initial design of the benefit had a significant impact on childhood poverty in Poland, with an absolute and relative decrease from 9.0 to 4.7 percent and 20.6 to 15.3 percent respectively between 2015 and 2017 (GUS, 2017). While a more targeted design could have made a far greater impact, these changes still reflect a significant improvement in the material situation of families with children. The policy may have also had a modest upward effect on fertility rates in the first years following its implementation, although this is difficult to assess given the parallel roll out of several other fertility-oriented policies and other changes which could have played a role in family decisions. Simultaneously, as argued in the ex-ante analysis by Myck (2016) and ex-post analysis by Magda et al. (2018), these positive outcomes came at the cost of reduced female labour market participation. This reduction primarily affected women with both lower levels of education and living outside of large urban areas (Myck and Trzciński, 2019).
The Family 500+ Reform: Design and Distributional Implications
The initial Family 500+ programme directed funds to 2.7 million families in addition to any already existing financial support and has been excluded from other means-tested support instruments. Since families that had a net income of less than PLN 800 per month per person could receive the benefit for the first or only child, the policy had a distinct redistributive element and meant that the bottom half of the income distribution received nearly 60% of the funds. However, the design was characterised by clear labour market disincentive effects, which were particularly strong for second earners and single parents.
In a one-child household (53.3 percent of families with children, GUS, 2016) with the first earner bringing in an income equivalent to 125% of the national minimum wage, the second earner needed only to earn PLN 940 per month in order for the family to cross the means test threshold and stop receiving the Family 500+ benefits. The benefit design is presented in Figure 1 in the form of budget constraints for the first earner (Case A) and the second earner (Case B) in a couple with one child. In the latter case the first earner is assumed to receive earnings equivalent to 125% of the minimum wage. The disincentive effects of the means test are clear in both cases and we can see that for the second earner, the benefit withdrawal comes at a very low income level – far below the national minimum wage of PLN 2100 per month. The “point withdrawal” of the benefit implied that it was enough for the family to marginally exceed the means test threshold for it to completely lose eligibility for the Family 500+ support for the first child.
The expansion of the Family 500+ programme, which came into effect in July 2019, eliminated the means-tested threshold thus making the policy fully universal. It came, however, at the cost of the redistributive character of the programme. Over 32% of the additional expenditure resulting from the universal character of the policy has been passed on to the top quintile of the income distribution and in its new version, the bottom half of households only receive 45 percent of all spending. The expansion of the programme is thus unlikely to further reduce child poverty significantly and – since its beneficiaries are mainly families with middle and high incomes – it is not expected to bring noticeable changes in fertility levels.
Figure 1: Family budget constraints for the first and second earner
Source: Authors’ calculations using the SIMPL microsimulation model.
Partial and Full Universality of the Family 500+ Programme and the Implications on Female Labour Supply
With the use of modelling tools to simulate the labour market response to changes in financial incentives to work, we have updated the initial simulations of Myck (2016) using the latest pre-reform data and examined the simulated labour supply decisions to the expanded fully universal programme, as if it were implemented instead of the initial version of the benefit. The analysis was conducted with data from the 2015 Polish Household Budget Survey, a detailed incomes and expenditure survey conducted annually by the Polish Central Statistical Office.
Table 1: Effects of the initial and the expanded Family 500+ programme on female labour supply
Results of the simulations are presented in Table 1. Simulations were conducted separately for single women, and under two scenarios for women in couples assuming that both partners adjust their behaviour (Model A) and that the labour market position of the male partner is unchanged (Model B). The simulated labour supply response to the initial reform confirms the magnitude of earlier results and suggests an equilibrium effect of 160-200 thousand women leaving the labour force. This is also consistent with results presented by Magda et al. (2018), who found that female labour market participation decreased by approx. 100 thousand women after the policy had been in place for one year.
However, as we can see in the right-hand part of Table 1, the response to a fully universal design – modelled as if it was introduced in 2016 instead of the means-tested version – is essentially neutral. For single mothers the reduction is only about 3000, while for women in couples, the model suggests a small positive reaction under the Model A specification and a small negative one under Model B. In total, the universal design of Family 500+ benefits can be described as labour supply neutral. Since the reaction has been modelled on pre-reform data, and because some women have already withdrawn from the labour market after the introduction of the initial benefit design in 2016, the remaining uncertainty is whether the new set of incentives will motivate these mothers sufficiently to return to work.
Conclusion
The introduction and subsequent expansion, of the Family 500+ programme has substantially increased financial resources of families with children in Poland. The policy rollout of the initial, partially universal programme has seen substantial changes in the level of child poverty in Poland and may have contributed to a modest increase in fertility in the initial years following the introduction of the reform. The means-tested design of the benefit, however, incentivised a significant number of women to leave the labour market. One year after the introduction of the policy approximately 100,000 women were estimated to have left the labour market (Magda et al. 2018), while the equilibrium effect of the policy suggested long-run implications of over 200,000 (Myck, 2016). The updated simulation results using the latest available data suggest slightly lower, though still substantial equilibrium implications of the initial partially universal design of the Family 500+ programme in the range of between 160,000-200,000. However, as we show in our latest analysis, these labour market consequences could be reversed after the expansion of the programme to a fully universal set-up. The simulated effects of the universal design of the programme, which has been in place in Poland since July 2019, modelled as if it was implemented instead of the initial means-tested version, are broadly neutral for female labour supply. The only question is how likely the mothers who left employment in response to the initial policy will return to work given the new set of financial incentives. Considering these positive implications of the fully universal programme, one has to bear in mind that the extended programme, which will cost over PLN 40 bn per year (approx. 2% of GDP), is unlikely to contribute to the other key objectives set by the government, namely reducing child poverty and increasing fertility. Including the Family 500+ programme, the Polish government currently spends about 4% of GDP on direct financial support for families with children. Given the design of the policies which make up this family package, it seems that the joint objectives of higher fertility, reduced poverty and higher female employment could be achieved more effectively under a reformed structure of support that would be better targeted at poorer households, include specific employment incentives, and incorporate support for childcare, early education and long-term care.
Acknowledgements
This brief summarizes the results presented in Myck and Trzciński (2019). The authors gratefully acknowledge the support of the Swedish International Development Cooperation Agency, Sida, through the FROGEE project. For the full list of acknowledgements see Myck and Trzciński (2019).
References
- Goraus, K. and G. Inchauste (2016), “The Distributional Impact of Taxes and Transfers in Poland”, Policy Research Working Paper 7787, World Bank.
- GUS (2016), “Działania Prorodzinne w Latach 2010-2015”, Główny Urząd Statystyczny – Polish Central Statistical Office, Warsaw.
- GUS (2017), “Zasięg ubóstwa ekonomicznego w Polsce w 2017r.”, Główny Urząd Statystyczny – Polish Central Statistical Office, Warsaw.
- Magda, I., A. Kiełczewska, and N. Brandt (2018), “The Effects of Large Universal Child Benefits on Female Labour Supply”, IZA Discussion Paper No. 11652, IZA-Bonn.
- Myck, M. (2016), “Estimating Labour Supply Response to the Introduction of the Family 500+ Programme”, Working Paper 1/2016, CenEA. Jacobson, L., LaLonde, R. and Sullivan, D. (1993). “Earnings losses of displaced workers”, American Economic Review, 83, pp. 685–709.
- Myck, M. and Trzciński, K. (2019) “From Partial to Full Universality: The Family 500+ Programme in Poland and its Labor Supply Implications”, Ifo DICE report 3 / 2019.
Can Loose Macroeconomic Policies Secure a ‘Growth Injection’ for Belarus?
After a relatively long period of macroeconomic stabilization, Belarus faces the threat of a purposeful deviation from it. However, today there is no room for a ‘growth injection’ by means of monetary policy. Moreover, Belarus still suffers from a problem of unanchored inflation expectations. This prevents monetary policy from being effective and powerful. So, unless inflation expectations have been anchored, any discussion about reshaping monetary policy and making it ‘pro-growth’ is meaningless.
Policy Mix and Macroeconomic Landscape in Belarus
Since 2015, Belarus has considerably improved the quality of its macroeconomic policies. The country has fallen back upon a floating exchange rate, and feasible monetary and fiscal rules. This change followed a long history of voluntary expansionary policy mixes associated with numerous episodes of huge inflation, currency crises, etc.
Due to the new policy mix, the country has been displaying a movement towards macro stability in recent years. For instance, the external position is close to being balanced, the fiscal position has even become positive, while the inflation rate is at historical lows around 5%. For Belarus, these achievements are important, taking in mind a ‘fresh memory’ of price and financial instability. Hence, until recently there were no doubts in the feasibility of the commitments of Belarusian authorities to sound macroeconomic policies.
However, despite a relatively strong macroeconomic performance, the threat of a purposeful and at least temporary deviation from policy commitments seems to strengthen. What is important is that this time, popular simple explanations – e.g. political voluntarism (Belarus will have presidential elections in 2020), a naïve perception of economic policy mechanisms by authorities, etc. – are not sufficient for understanding the phenomenon. Rounds of loosening economic policies tend to be justified as ‘lesser evils’. Exploring some rationality in such a justification requires more insight into the Belarusian macroeconomic landscape.
In recent years, the lack of productivity and output growth has become more evident: in 2015-2019 the average output growth rate has been around 0. The root of the problem is the deficit in productivity and growth (Kruk & Bornukova, 2014; Kruk, 2019), while the rules-based policy mix just uncovered it.
However, this direction of causation tends to be challenged by some policy-makers. In an ’archaic’ manner, the policy mix is accused of blocking any pro-output policy discretion, even if there is a justification for it. For instance, an ‘extra’ need for a ‘growth injection’ may be justified by social challenges. Poor growth in Belarus results in a rather sensitive squeezing of relative levels of well-being in comparison to neighboring countries. Between 2012 and 2019, the well-being shrank from around 78% of the average level in 11 CEE countries down to about 63%. This intensified the labour outflow significantly, including for those employed in socially important industries, say, in healthcare. So, according to this view, the ‘growth injection’ is a lesser evil rather than systemic social threat.
A more advanced ‘accusation’ of the new policy mix assumes that it either causes a too restrictive stance of monetary policy with respect to output or that it ignores complicated transmission channels. For instance, one may argue that too much emphasis on price and financial stability can actually result in undermining them, given the huge debt burden of Belarusian firms. The quality of a considerable portion of the debts in Belarus tends to be sensitive to output growth rates. Hence, according to this argumentation, the monetary policy rule should be ‘more pro-growth’, reflecting the debt-growth-financial stability linkage inside it.
‘Translating’ this policy agenda to a research agenda results in two questions. First, is there room for a more expansionary monetary policy? Second, do financial instability risks require making the monetary policy rule ‘more pro-growth’?
The Monetary Policy Stance: Causality and Causes
Monetary policy, as a rule, aims to be counter-cyclical, i.e. generate expansionary incentives during cyclical downturns, and vice versa. In this respect, its stance should be matched to the estimate of the output gap. From this view, given dominating estimates of a near-zero output gap for 2019 in Belarus (National bank, 2019; Kruk, 2019), today’s monetary policy should be roughly neutral. However, analyzing monetary policy stance together with the estimates of the output gap is not a univocal option, especially given doubts about the consistency of any estimate of the output gap (Coibion et al., 2017).
From this point of view, a direct measurement of the monetary policy stance – matching ex-post real interest rate vs. an ex-ante one – is a worthwhile alternative. If the ex-post real interest exceeds the ex-ante rate, it means that the interest rate policy by a central bank is restrictive, while an opposite situation witnesses its expansionary stance (e.g. Gottschalk, 2001). A methodology for identifying inflation expectations by Kruk (2016) allows detecting restrictive and expansionary stances as well. Moreover, doing it in this way allows simultaneously tracing the stance of actual and expected inflation, and study its possible impact on monetary policy (Figure 1).
Figure 1. Monetary Policy Stance, Actual Inflation and Inflation Expectations in Belarus
Note: Positive sign means restrictive stance of monetary policy, while negative sign means expansionary stance.
Source: Own elaboration according to methodology in Kruk (2016) and based on data from the National Bank of Belarus.
First, this diagnostic shows that the stance of the monetary policy today is roughly neutral, which conforms to the diagnosis based on matching with the output gap. In this respect, it means that there is no room for monetary policy softening today.
However, eventually the situation may change and a need for an expansionary monetary policy may indeed arise. Can the National Bank of Belarus unconditionally satisfy such demand? Second, and the more important conclusion, is that the National Bank cannot. Figure 1 also demonstrates that the monetary policy stance in Belarus is very sensitive to the stance of inflation expectations. From this view, the restrictive monetary policy, say in 2015-2016 and 2018, reflected shocks in inflation expectations. The National Bank had to take a mark-up in the expected inflation in respect to the actual one into account and to transform it to the mark-up of the interest rate. If the National Bank ignores such shocks and nevertheless softens monetary policy, it will undermine price stability due to a powerful transmission effect from expected inflation to the actual one. Moreover, a reverse linkage from actual inflation to the expected one is likely to result in a prolonged inflationary period, causing a so-called ‘abnormal’ stance of the monetary environment (Kruk, 2016).
So, a generalized policy diagnosis for today looks as follows. Monetary policy has reached a roughly neutral level due to a considerable reduction in inflation expectations. The latter, in turn, happened due to a prolonged period of a restrictive policy stance (in 2015-2016), which suppressed actual inflation by means of sacrificing output in a sense (the period of cyclical downturn could have been shorter without such limitations in monetary policy).
Unanchored Expectations Bar a More ‘Pro-Growth’ Policy
A deeper cause of the limited room for monetary policies is unanchored inflation expectations. Statistical properties of the inflation expectations series (Kruk, 2019 and 2016), as well as the polls of households and firms by the National Bank, suggest that despite the reduction of the level of inflation expectations, the issue of it being unanchored is still on the agenda. In this respect, expected inflation in Belarus tends to be sensitive to numerous kinds of actual and information shocks, e.g. domestic and global output dynamics, interest rate levels and spreads, exchange rates, financial stability issues, etc. Hence, unless expectations have been anchored, the monetary policy would still suffer from a lack of power. This means that anchoring inflation expectations is the core precondition for normalizing the monetary environment and the power of any monetary policy.
For the monetary rule, this means that it cannot become more ‘pro-growth’, keeping in mind the risks to financial stability. Otherwise, it can spur price destabilization, which may also trigger financial instability. Hence, the logic of a ‘lesser evil’ does not work. Indeed, there are risks to financial stability stemming from poor growth. But combating them through a more ‘pro-growth’ policy will cause price instability and financial instability stemming from that. But what is more important, the logic of a ‘lesser evil’ itself is doubtful with respect to monetary policy. Recognizing the linkage between monetary policy and financial stability does not mean that risks to the latter should be directly traced by the former. Financial stability issues can and should primarily be tackled through macroprudential tools.
Conclusions
After a relatively long period of macroeconomic stabilization, Belarus faces some risk with respect to it. However, today’s monetary policy stance is roughly neutral in Belarus. Hence, a ‘growth injection’ may result in inflation resurgence. Moreover, even today’s near-neutral monetary policy stance is a considerable achievement, as the country still experiences the challenge of unanchored inflation expectations. This issue is a deep underlying problem, which keeps the monetary policy from being more effective and powerful. So, unless inflation expectations have been anchored, any discussion about reshaping it and making it ‘pro-growth’ is meaningless.
As for today’s justifications for monetary policy softening – poor growth and financial instability risks – they hardly relate with the monetary policy agenda. The challenge of poor growth requires thinking in terms of productivity issues, while financial stability risks in terms of macroprudential tools first.
References
- Coibion, O., Gorodnichenko, Y, Ulate, M. (2017). The Cyclical Sensitivity in Estimates of Potential Output, National Bureau of Economic Research, Working Paper No. 23580.
- Gottschalk, J. (2001). Monetary Conditions in the Euro Area: Useful Indicators of Aggregate Demand Conditions? Kiel Institute for the World Economy Working Paper No. 1037.
- Kruk, D. (2019). Belarusian Economy in Mid-2019: the Results of the Recovery Growth Period, BEROC Policy Paper No. 69.
- Kruk, D. (2016). SVAR Approach for Extracting Inflation Expectations Given Severe Monetary Shocks: Evidence from Belarus BEROC Working Paper No. 39.
- Kruk, D., Bornukova, K. (2014). Belarusian Economic Growth Decomposition, BEROC Working Paper No. 24.
- National Bank of the Republic Belarus (2019). Information on the Dynamics of Consumer Prices and Tariffs and Factors of Changes Therein, 2019Q3.
Buyer Competence and Procurement Renegotiations
This brief deals with the extent to which a more competent public bureaucracy can contribute to better economic outcomes. It addresses this question in the context of public procurement, governments’ purchase of goods and services from private contractors, which accounts for about 15% of GDP in most economies and is on the rise. The efficiency of the procurement process directly influences the prices and quality of many government-provided goods and services that are crucial to social welfare objectives and sustained economic growth. Several issues challenge this efficiency. Media attention is typically on episodes of corruption, which can of course be a major source of waste. Here, we focus on a less glamorous, often overlooked, but potentially even more important source of waste, the lack of procurement competence.
Public procurement is a complex task. Contracting authorities must know market characteristics, design and implement efficient award mechanisms, balance risks and incentives in drafting contracts, effectively manage the contracts in the execution phase, etc. Effective procurement, in particular for complex services or works, requires teams endowed with legal, marketing, engineering, and economic/strategic expertise. The World Bank‘s Benchmarking Public Procurement 2017 compares the quality of the legal and regulatory environments of 180 countries and reveals the existence of great heterogeneity in the quality of the procurement processes across countries. Saussier and Tirole (2015) focus on the case of France, documenting that 63% of the staff of French contracting authorities do not have a legal profile, and only 39% have qualifications specific for managing public purchases.
Recent research focusing on prices of standardized goods showed that (lack of) buyer competence among public buyers could make an even bigger impact on the waste of public funds than corruption. For example, Bandiera, Prat and Valletti (2009) estimate that Italian public buyers would save 21 percent of their expenditures if they all paid the same as the buyers at the 10th percentile of the estimated procurement price distribution. Savings could reach 1.6-2.1 percent of the Italian GDP per year. They then estimate that bureaucratic inefficiency also linked to incompetence is the main cause of waste, accounting for 83 percent of total estimated waste, compared to only 17 percent due to corruption. In a similar vein, Best, Hjort and Szakonyi (2017) report that over 40 percent of within-product price variation on standardized goods in Russia in 2011-2015 can be ascribed to the bureaucrats and organizations in charge of procurement. They estimate that if the least effective quartile of bureaucrats and organizations had the effectiveness of the 75th percentile, the Russian government would save around $13 billion per year – roughly one fifth of the total amount spent on health care by the Russian government at federal, regional, and municipal level combined.[1]
The role of competence in complex procurement
This problem is becoming even more serious now that, being under fiscal pressure after the crises, many governments are promoting the use of public procurement not only as a tool to save budgets – sometimes at the expense of quality – but also to achieve more complex objectives like fostering innovation, protecting the environment, and promoting social objectives, a multiplicity of goals that per se makes the procurement mission even more complex.
Little is known about the importance of procurement competence in more complex procurements, not least because it is very difficult to measure performance in these environments. In our paper (Decarolis et al. (2019)) we try to make a step in this direction by focusing on works and services, typically more complex than goods. We use data from the US, probably the country with the most well-developed system of production and certification of procurement competences. Thus, our estimates of the effect of lack of competences should provide a lower bound of most other countries.
We combine, for the first time, three large databases: contract-level data on procurement performance in the Federal Procurement Data System (FPDS); bureau-level data from a survey conducted by the Office of Personnel Management since 2002 on federal employees, the Federal Employee Viewpoint Survey (FEVS); and Federal Workforce Data (FedScope) containing information on characteristics of the public workforce at the employee level.
To quantify the extent to which the government-bureau-level competencies determine procurement outcomes, we use the first database to construct procurement performance measures and the second dataset to build measures of procurement offices’ competence. We then use the third database to construct instruments that help us addressing important endogeneity issues. Our identification strategy exploits the exogeneity of death events involving public officials to allow for a causal interpretation of bureau competence on procurement performance.
Measurement Challenges
Indeed, there are three main challenges that our analysis needs to overcome. The first is how to measure procurement performance. Unit price comparisons have been used for standardized goods, but they are not suitable for the more complex procurements we focus on as they are heterogeneous in many non-recorded dimensions and their contracts are often incomplete. We use FPDS instead to construct three proxies of performance based on time delays, cost overruns, and the number of renegotiations. Although the first two measures are widely used in the literature, we are careful to take into account that cost overruns and delays may be due to new or additional work requested by the public buyer, in which case they should not be viewed as indicative of a poor outcome. We, therefore, consider only those which have occurred to deliver the work or service that was originally tendered. The third performance measure, the overall number of renegotiation episodes, is new and aims at capturing Williamson’s “haggling costs,” which are a pure deadweight loss present whatever the reason behind the renegotiation and have been shown to be economically sizeable for complex contracts. Our data reveals a surprising and persistent heterogeneity along these three dimensions across US federal bureaus.
The second challenge is the measurement of bureaucratic competence. Other papers in the field have measured it using buyer fixed effects. We use a novel approach based on the mentioned survey of employees’ subjective evaluations (FEVS). The survey is extremely rich, and we chose the most general question as an overall measure for competence (How would you rate the overall quality of work done by your work unit?). Responses to this question should be seen as measures of the overall efficacy of the workflow and processes within the bureau, hence proxying for the ideal measure of competence on the many different aspects relevant to procurement. An extensive set of robustness checks support our idea of measuring competence through the FEVS data.
The third measurement problem is the association between more complex contracts and more competent buyers: the most competent buyers may consistently produce poor performance because they are allocated the most complicated procurements. This point is well illustrated in a case study showing that the performance of the agencies that are worst in terms of competence (the Department of Veterans Affairs and the Department of Justice) is superior to that of the two most competent agencies (the NASA and the Nuclear Regulatory Commission) in terms of both delays and cost overruns. This striking inversion indicates that any straightforward regression of performance on competence would grossly underestimate the impact of competence.
We, therefore, develop an instrumental variable strategy exploiting exogenous changes in competence. We use FedScope to build instruments for bureaus’ competence based on the deaths of specific types of employees: bureau managers and white-collar employees who are relatively young and earn a relatively high wage. The idea is that more competent offices adopt better managerial practices, routines and processes that are more resilient to risks, such that of an unexpected loss of a key employee, and less dependent on specific individuals. This is precisely what the first stage of our IV strategy documents. Our instruments perform well in terms of their statistical properties and they allow us to estimate a causal effect of bureau competence on procurement outcomes that is an order of magnitude larger than the corresponding OLS estimate.
Results
We find that one standard deviation increase in competence reduces the number of days of delay by 23 percent, cost overruns by 29 percent and the number of renegotiations by half. This implies that if all federal bureaus were to obtain NASA’s high level of competence – corresponding to the top 10th percentile of the competence distribution – delays in contract execution would decline by 4.8 million days, and cost overrun would drop by $6.7 billions over the entire sample analyzed. We also find a consistently negative effect of greater competence on the number of renegotiations: one standard deviation increase in competence causes 0.5 (39%) and 0.8 (71%) fewer cost renegotiations and time renegotiations, respectively.
Finally, we try to understand what exactly makes a bureau ‘competent’ using the FEVS data to identify three different components: cooperation among employees, incentives and skills. Separately estimating their causal effects is unfeasible with instruments like the two described above as the validity of the exclusion restriction, which can be argued to be satisfied when measuring a broadly defined notion of bureau competence, is unlikely to hold for more specific components. However, we provide multiple pieces of evidence suggestive that cooperation is the key driver behind the positive effects of bureau competence. This finding conforms with the view that successful procurement requires appropriate coordination of a multiplicity of tasks involving different individuals. We also consider the extent to which the role of cooperation is due to the presence of capable managers, able to lead a group to effective cooperation, exploiting the heterogenous effects obtained through instruments considering the deaths of different subgroups of employees. We find that the deaths that matter the most are those of relatively young and best paid white-collar employees.
These results point at the large potential improvement in the performance of public contracts that could be achieved by investing more resources in increasing the competence of contracting authorities, even in a country with long-established procurement training and certification institutions such as the US. In Europe, recent policy initiatives see the introduction of qualification systems for public procurers as a necessary response to the generally lower procurement competence coupled with the greater discretion granted by the 2014 Procurement Directives. Our results on the role of cooperation suggest that certification programs would be also useful at the level of the procuring office, and should include features such as the organisation of the acquisition process and the prevailing management practices, as is often done for private firms.
References
- Bandiera, Oriana, Andrea Prat, and Tommaso Valletti. (2009). “Active and passive waste in government spending: Evidence from a policy experiment.” American Economic Review, 99(4): 1278-1308.
- Best, Michael Carlos, Jonas Hjort, and David Szakonyi. (2017). “Individuals and Organizations as Sources of State Effectiveness, and Consequences for Policy.” NBER Working Paper 23350.
- Bucciol, A., Camboni R., and P. Valbonesi. (2017). ”Buyers’ Ability in Public Procurement: A Structural Analysis of Italian Medical Devices.” Working Paper n.17, Department of Economics, University of Verona.
- Decarolis, F, L Giuffrida, E Iossa, V Mollisi, and G Spagnolo. (2019 revision), “Bureaucratic Competence and Procurement Outcomes”, NBER Working Paper 24201.
- Saussier, S, and J Tirole. (2015). “Strengthening the Efficiency of Public Procurement”, French Council of Economic Analysis, April.
- World Bank (2017), Benchmarking Public Procurement 2017, The World Bank.
[1] See also, Bucciol et al (2017) who study procurement of standardized medical devices purchased by local Italian purchasing bodies, finding that the price for the same medical devices paid by Italian public buyers differ substantially, and that the differences are explained by ‘buyers fixed effects’ capturing all specific buyers characteristics, including their competence levels.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The Long Shadow of Transition: The State of Democracy in Eastern Europe
In many parts of Eastern Europe, the transition towards stronger political institutions and democratic deepening has been slow and uneven. Weak political checks and balances, corruption and authoritarianism have threatened democracy, economic and social development and adversely impacted peace and stability in Europe at large. This policy brief summarizes the insights from Development Day 2019, a full-day conference organized by SITE at the Stockholm School of Economics on November 12th. The presentations were centred around the current political and business climate in the Eastern European region, throwing light on new developments in the past few years, strides towards and away from democracy, and the challenges as well as possible policy solutions emanating from those.
The State of Democracy in the Region
From a regional perspective, Eastern Europe has seen mixed democratic success over the years with hybrid systems that combine some elements of democracy and autocracy. Based on the V-Dem liberal democracy index, ten transition countries that have joined the EU saw rapid early progress after transition. In comparison, the democratic development in twelve nations of the FSU still outside of the EU has been largely stagnant.
In recent years, however, democracy in some of those EU countries, such as Bulgaria, the Czech Republic, Hungary, Poland and Romania have been in decline. Poland, one of the region’s top performers in terms of GDP growth and life expectancy, has experienced a sharp decline in democracy since 2015. Backlashes have often occurred after elections in which corruption and economic mismanagement have led to the downfall of incumbent governments and a general distrust of the political system. Together with low voter turnout, this created fertile ground for more autocratic forces to gain power helped by demand for strong leadership.
An example from Ukraine illustrated the role of media, both traditional and social, for policy-making. In some countries of the region, traditional media is strictly state-controlled with obvious concerns for democracy. This is less the case in Ukraine, where also social media plays an important role in forming political opinions. The concern is that, as elsewhere, opinions that gain traction on social media may not be impartial or well informed, affecting public perception about policy-making. A recent case showing the popular reaction to an attack on the former governor of the Central Bank suggests that those implementing important reforms may not get due credit when biased and partial information dominates the political discourse on social media.
Another case is the South Caucasian region: Armenia, Georgia and Azerbaijan. The political situation there has been characterized as a “government by day, government by night” dichotomy, implying that the real political power largely lies outside the official political institutions. In Georgia, the situation can be described as a competition between autocracy and democracy, with a feudalistic system in which powerful groups replace one another across time. As a result, trust in political institutions is low, as well as citizens’ political participation.
In the case of Azerbaijan, there is an elected presidency, but in reality, power has been passed on hereditarily, becoming a de facto patrimonial system. Lastly, in Armenia, the new government possesses democratic credentials, but the tensions with neighbouring Azerbaijan and Turkey have given increasing power to the military and important economic powers. Overall, democratisation in these countries has been hindered by a trend for powerful politicians to form parties around themselves and to retain power after the end of their mandates. Also, the historical focus on nation-building in these countries has led to a marked exclusion of minorities and a conflict of national identities.
The last country case in this part of the conference focused on the current political situation in Russia and on the likely outcomes after 2024. The social framework in Russia appears constellated by fears – a fear of a world war, of regime tightening and mass repressions, and of lawlessness – all of them on the rise. Similarly, the economy is suffering, in particular from low business activity, somewhat offset by a boost in social payments. Nonetheless, it was argued that it is not economic concerns, but rather political frustration, that has recently led citizens to take to the street. Despite this, survey data shows that trust in Putin is still over 60%, and that most people would vote for him again. However, survey data also points out that the most likely determinant of this trust is the lack of another reference figure, and that citizens are not averse to the idea of political change in itself. Lastly, Putin will most likely retain some political power after 2024, transiting “from father to grandfather of the nation”.
Voices from the civil society in the region also emphasized the importance of a free media and an active civil society to prevent the backsliding of democracy. With examples from Georgia and Ukraine, it was argued that maintaining the independence of the judiciary, as well as the public prosecutor’s office, can go a long way in building credibility both among citizens and the international community. The European Union can leverage the high trust and hopeful attitudes it benefits from in the region to push crucial reforms more strongly. For example, more than 70% of Georgians would vote for joining the EU if a referendum was held on the topic and the European Union is widely regarded as Georgia’s most important foreign supporter.
Weak Institutions and Business Development
The quality of political and legal institutions strongly affects the business environment, in particular with regards to the protection of property rights, rule of law, regulation and corruption. Research from the European Bank for Reconstruction and Development (EBRD) highlights that the governance gap between Eastern Europe and Central Asia and most advanced economies is still large, even though progress in this area has actually been faster than for other emerging economies since the mid-‘90s. This is measured through enterprise surveys as well as individual surveys. In Albania, for instance, a perception of lower corruption was linked to a decrease in the intention to emigrate equivalent to earning 400$ more per month. Another point concerned the complexity of measuring the business environment and the benefits of firm-level surveys asking firms directly about their own actual experience of regular enforcement. For example, in countries such as Poland, Latvia and Romania the actual experience of business regulation measured via the EBRD’s Business Environment Enterprise Performance Survey, is far worse than one would expect from the World Bank’s well known Doing Business rating.
From the perspective of Swedish firms, trade between Sweden and the region has remained rather flat in the past years, as the complexity and risks of these markets especially discourage SMEs. Business Sweden explained that Swedish firms considering an expansion in these markets are concerned with issues of exchange rate stability, and the institutional-driven presence of unfair competition and of excessive bureaucracy. Moreover, inadequate infrastructure and the presence of bribery and corruption make everyday business operations risky and costly. It was generally emphasized that countries have to create a safe investment environment by reducing corruption, establishing a clear and well enacted regulatory environment, having dependable courts and strengthening domestic resource mobilization. Swedish aid can play a part, but there is a need to develop new ways of delivering aid to make it more effective.
An interesting example is Belarus, that has seen more economic and political stability than most neighbours, but at the same time a lack of both economic and political reforms towards market economy and democracy. Gradually the preference towards private ownership, as opposed to public, has increased in recent years and the country has seen a rising share of the private sector, even without specific privatization reforms. Nonetheless, international businesses are still reluctant to invest due to high taxes, a lack of access to finance as well as to a qualified workforce, but most importantly due to the weak legal system. An exception has been China, and Belarus has looked at the One Belt One Road Initiative as a promising bridge to the EU. Scandals connected with the two main Chinese-invested projects have damped the enthusiasm recently, though.
The economic and political risks of extensively relying on badly diversified energy sources, as is the case with natural gas imports from Russia in many transition states were also discussed. It was shown how some countries such as Ukraine, Poland and Lithuania have improved their energy security by either benefitting from reverse-flow technology and the EU’s bargaining power or building their own LNG terminals to diversify supply sources. However, either of these, as well as other energy security improving solutions are likely to come with an economic cost, though, that not all countries in the region can afford.
A Government Perspective
The main focus of this section was the Swedish government’s new inspiring foreign policy initiative, “Drive for Democracy”. Drawing from a definition of democracy by Kerstin Hesselgren, an early Swedish female parliamentarian, democracy enables countries to realize and utilize the forces of the individual and draw them into a life-giving, value-creating society. It was emphasized that the values of democracy are objectives by themselves (e.g. freedom of expression, respect for human rights) but also that democracy has important positive effects in other areas of human welfare. The Swedish government views democracy as the best foundation for a sustainable society, equality of opportunity and absence of gender or racial bias.
The “Drive for Democracy” specifically identifies Eastern Europe as one of the main frontiers between democracy and autocracy, and the Swedish government promotes human rights and stability through various bilateral programmes through the Swedish International Development Cooperation Agency, Sida, and multilateral initiatives within the EU, such as the Eastern Partnership. It was also emphasized that democracy is a continuous process that can always be improved, as indeed experienced by Sweden. Political rights were granted to women only in 1919 followed by convicts and prisoners in 1933 and to the Roma people only in 1950. Political and democratic rights are thus never once and for all given, and it is crucial that the dividends from democracy are carried forward to the younger generation.
Conclusion
In sum, the day illustrated clearly how democracy engages all segments of society, from the business sector to civil society, and the potential for but also challenges involved for democratic deepening in Eastern Europe. To get more information about the presentations during the day, please visit our website.
Participants at the Conference
- PER OLSSON FRIDH, State Secretary, Ministry for Foreign Affairs.
- ALEXANDER PLEKHANOV, Director for Transition Impact and Global Economics at EBRD.
- TORBJÖRN BECKER, Director, SITE.
- CHLOÉ LE COQ, Associate Professor, SITE and Professor of Economics, University of Paris II Panthéon-Assas.
- THOMAS DE WAAL, Senior Fellow at Carnegie Endowment for International Peace.
- NATALIIA SHAPOVAL, Vice President for Policy Research at Kyiv School of Economics.
- ILONA SOLOGUB, Scientific Editor at VoxUkraine and Director for Policy Research at Kyiv School of Economics.
- KETEVAN VASHAKIDZE, President at Europe Foundation, Georgia.
- MARIA BISTER, Senior Policy Specialist, Sida.
- HENRIK NORBERG, Deputy Director, Ministry for Foreign Affairs.
- YLVA BERG, CEO and President, Business Sweden.
- LARS ANELL, Ambassador and formerly Volvo’s Senior Vice President.
- ERIK BERGLÖF, Professor in Practice and Director of the Institute of Global Affairs, London School of Economics and Political Science.
- KATERYNA BORNUKOVA, Academic Director, BEROC, Minsk.
- ANDREI KOLESNIKOV, Senior Fellow, Carnegie Moscow Center.
Gender Gaps in Wages and Wealth: Evidence from Estonia
This policy brief introduces two related papers examining two types of gender gaps in Estonia. First, it presents the work of Vahter and Masso (2019), who study the wage gender gaps in foreign-owned firms and compare this gap with the situation in domestic ones. Then it summarizes a paper of Meriküll, Kukk, and Rõõm (2019), who focus on the wealth gender gaps and highlight the role of entrepreneurship in this gap.
Gender inequality is not only a moral issue. An extensive literature has highlighted the cost of gender inequality in terms of economic (in)efficiency. Most of the academic work has, however, focused on either the US and Western Europe or developing countries. Research focusing on systematic gender disparities in Eastern Europe is rather scarce. Yet, there is much to be learned from this region. The purpose of the FROGEE (Forum for Research on Gender in Eastern Europe) project is to study several issues related to gender inequality in former socialist countries.
This policy brief summarizes two papers presented at the 2nd Baltic Economic Conference at the Stockholm School of Economics in Riga, on June 10-11, where a special session on gender economics was held with the support of the FROGEE project. The event, organized by the Baltic Economic Association (see balticecon.org), gathered more than 85 researchers from the Baltics and all over the world. These two papers focus on Estonia, one of the most successful economies among the transition countries, where however the gender wage gap is among the largest in the European Union.
Firm ownership and gender wage gap
An important source of wage inequality originates in firm-specific pay schemes (see for instance Card et al. 2016). Understanding the characteristics of firms associated with a gender pay gap is thus a necessary step to design relevant policy responses. In a paper entitled “The contribution of multinationals to wage inequality: foreign ownership and the gender pay gap”, Jaan Masso and Priit Vahter, both at the University of Tartu, compare the situation in foreign-owned firms with domestic ones. The fact that foreign-owned firms provide on average higher wages to their employees is well documented. However, the question of whether this premium differs between men and women remains largely overlooked.
A potential channel linking firm ownership and gender wage gap is the transfer of management practices from the home country of the investor to the affiliate. The great majority of FDI in Estonia originates from Finland and Sweden, two countries that regularly top international rankings on gender equality and that have set the fight against gender inequality as a top priority. Observing a lower level of gender wage gap in firms owned by Swedish and Finnish capital would suggest the existence of such a mechanism, even if there is evidence that Scandinavian countries do not stand out in a positive way when it comes to women in the top of the distribution (see for instance Boschini et al., 2018, and Bobilev et al., 2019).
On the other hand, Goldin (2014) has shown that a large part of the gender wage gap in the US can be explained by differences in job “commitment”: firms disproportionately reward workers willing to be available 24/7, more flexible regarding business trips, spending longer hours in the office, etc. Such workers happen to be more often men than women. Multinational firms may require such commitment and flexibility to a larger extent than domestic firms, due for instance to their higher exposure to international competition. This would imply a larger gender pay gap in foreign-owned firms compared to local firms.
To investigate this issue, Masso and Vahter (2019) rely on Estonian administrative data, providing information on the whole universe of workers and of firms in the country between 2006 and 2014. This matched employer-employee dataset allows to track the wage of individuals over the years, but also to compare wages both across and within firms. It thus becomes possible to estimate the gender wage gap at the firm level (controlling for relevant individual-level factors affecting wages, such as age and experience), and then to check whether this measure systematically differs between domestic and foreign-owned firms.
However, simply comparing the gender pay gap between these two types of firms could lead to spurious conclusions. Foreign-owned firms have on average different characteristics than domestic ones: they do not operate in the same sectors, they do not have the same size nor the same productivity. To overcome this issue, the authors rely on a matching method: for each foreign-owned firms, they match a domestic firm with similar (observable) characteristics.
They find that in domestic firms, women are on average paid 19% less than men, even after accounting for many other factors associated with wage. In foreign-owned companies, both men and women are better paid. However, both genders do not benefit from the same premium: men are paid roughly 15% more in foreign-owned firms, whereas the premium for women is only 5.4%. This difference implies an even larger gender wage gap in multinational firms. To illustrate the economic significance of these results, for a man and a woman earning a monthly wage of 1146 euros (the average gross wage in Estonia in 2016), the premium for switching from a domestic to a foreign-owned firm is respectively 171 and 62 euros. Further, they provide some evidence that lower “commitment” is associated with a stronger wage penalty in foreign-owned firms. All in all, these results suggest that there is not necessarily a relationship between a multinational wage policy (especially in its gender wage-gap dimension) and the gender norms prevailing in its country of incorporation.
Gender and wealth gap
The vast majority of academic papers studying gender inequality focuses on the wage gap. But gender inequality can affect other types of economic outcomes, such as labor force participation, unemployment duration, or wealth. The latter is of particular interest since wealth can greatly contribute to empowerment. Merike Kukk, Jaanika Meriküll and Tairi Rõõm, all at the Bank of Estonia, extend the literature with a paper entitled “What explains the Gender Gap in Wealth? Evidence from Administrative Data”. This paper is one of the first to study the gender wealth gap in a post-transition country. The literature on the gender wealth gap is rather scarce because of a lack of suitable data: wealth measures are often computed at the household level, while individual-level data is necessary for such a study.
The main aim of this paper is to depict a precise portrait of this phenomenon in Estonia. In particular, the authors do not simply estimate the overall wealth gap but investigate the magnitude of the gap across the wealth distribution. In other words, is there a difference between the poorest men and the poorest women? Or on the other side of the distribution, are the richest men more wealthy than the richest women?
For this purpose, Kukk, Meriküll and Rõõm combine administrative individual-level data on wealth with survey results. The administrative data are generally considered of much better quality than the other, but they do not provide a lot of additional information on individuals. On the other hand, survey data provide a wealth of information about individual characteristics. Merging allows getting the best of both worlds. Regarding the methodology, the authors use unconditional quantile regression to track gender differences at different deciles of the wealth distribution. They further decompose this “raw” gender gap into two components: the “explained” part, i.e., the part of the gap resulting in differences in characteristics between men and women (demographics, education, etc.), and the “unexplained” part.
This study estimates the raw, unconditional gender wealth gap in Estonia to be 45%, which is of similar magnitude as in Germany. Interestingly, this difference is essentially driven by differences in the top of the distribution: there is a large gap between the richest men and the richest women. This “raw” difference is however explained by a single variable: self-employment, as men are much more likely to have business assets than women. Once controlling for the entrepreneurship status, the wealth difference between the richest Estonians becomes insignificant. This suggests the need to support policies encouraging female entrepreneurship and to remove barriers particularly affecting women. For instance, the literature has previously pointed out that women have less access to external sources of capital than men (e.g., Aidis et al., 2007). Such distortions can ultimately result in a wealth gap at the top of the distribution, as documented by this paper.
In addition, the literature has proposed several mechanisms that could result in gender-specific patterns of wealth accumulation. The simplest channel is through the wage gap, as it can be seen as the accumulation of the wage gap over time (e.g. Blau and Kahn, 2000). The authors thus compare the gender gaps in wealth and income. They uncover a strong wage gap, with men earning significantly more than women starting at the 6th decile: the higher we go in the income distribution, the larger the wage gap. How to reconcile this finding with the absence of a wealth gap conditional on entrepreneurship status? A possible explanation suggested by the authors is that women simply accumulate wealth better than men do.
Conclusion
These two papers illustrate two different mechanisms explaining gender-specific economic outcomes. The larger wage gap observed in multinational companies can be explained by a stronger commitment penalty for women, mostly because of childcare. This asks for two potential policy interventions. First, the development of childcare could facilitate the reduction in the “commitment gap” that disrupts women’s careers. Second, institutions could support a more flexible repartition of childcare responsibilities. Note however that Estonia already has the longest duration of leave at full pay (85 weeks), and that this leave can be freely split between parents. As for the wealth gap at the top of the wealth distribution, it can to a large extent be explained by the entrepreneurship status. This difference could partly be explained by differences in preferences and risk-aversion, which would require long-run policies to be mitigated. But in the short run, there is room for specific policies supporting female entrepreneurship and removing barriers particularly affecting women, such as a tighter credit constraint.
References
- Aidis, R., Welter, F., Smallbone, D., & Isakova, N. (2007). Female entrepreneurship in transition economies: the case of Lithuania and Ukraine. Feminist Economics, 13(2), 157-183.
- Blau, F. D., & Kahn, L. M. (2000). Gender differences in pay. Journal of Economic perspectives, 14(4), 75-99.
- Bobilev, R., Boschini, A., & Roine, J. (2019). Women in the Top of the Income Distribution: What Can We Learn From LIS-Data?. Italian Economic Journal, 1-45.
- Boschini, A., Gunnarsson, K., & Roine, J. (2018). Women in Top Incomes: Evidence from Sweden 1974-2013. IZA Discussion Paper No. 10979 .
- Card, D., Cardoso, A. R., & Kline, P. (2015). Bargaining, sorting, and the gender wage gap: Quantifying the impact of firms on the relative pay of women. The Quarterly Journal of Economics, 131(2), 633-686.
- Goldin, C. (2014). A grand gender convergence: Its last chapter. American Economic Review, 104(4), 1091-1119.
- Meriküll, J., Kukk, M., & Rõõm, T. (2019). What explains the gender gap in wealth? Evidence from administrative data. Bank of Estonia WP No. 2019-04.
- Vahter, P., & Masso, J. (2019). The contribution of multinationals to wage inequality: foreign ownership and the gender pay gap. Review of World Economics, 155(1), 105-148.