Tag: public finances
Active Labor Market Policy in the Baltic-Black Sea Region
This brief outlines the characteristics of active labor market policy (ALMP) in four countries in the Baltic-Black Sea region: Belarus, Lithuania, Poland, and Ukraine. An analysis of the financing expenditure structure within this framework reveals significant differences between the countries, even for Poland and Lithuania, where the policies are to be set within a common EU framework. Countries also differed in terms of their ALMP reaction to the economic challenges brought about by the Covid-19 pandemic, as Poland and Lithuania increased their ALMP spending, while Ukraine, and, especially, Belarus, lagged behind. Despite these differences, all four countries are likely to benefit from a range of common recommendations regarding the improvement of ALMP. These include implementing evidence-informed policymaking and conducting counterfactual impact evaluations, facilitated by social partnership. Establishing quantitative benchmarks for active labor market policy expenditures and labor force coverage by active labor market measures is also advised.
Introduction
This policy brief builds on a study aimed at conducting a comparative analysis of labor market regulation policies in Belarus, Ukraine, Lithuania, and Poland. In comparing the structure of labor market policy expenditures, the aim was to identify common features between Poland and Lithuania, both of which are part of the EU and employ advanced labor market regulation approaches. We also assessed Ukraine’s policies, currently being reformed to align with EU standards, contrasting them with Belarus, where economic reforms are hindered by the post-Soviet authoritarian regime.
The analysis of the labor market policies for the considered countries is based on an evaluation of the structure of pertinent measures between 2017 and 2020 (Mazol, 2022). We used the 2015 OECD systematization of measures of active labor market policy, as presented in the first column of Table 1.
Our study reveals substantial differences in active labor market policies within the four considered countries. Still, motivated by OECD’s approach to ALMP, we provide a range of common policy recommendations that are relevant for each country included in the study. Arguably, aligning with the OECD approach would have more value for current EU and OECD members, Poland and Lithuania, and the aspiring member, Ukraine. However, these recommendations also hold value when considering a reformation of the Belarusian labor market policy.
ALMP Expenditures in Belarus, Lithuania, Poland and Ukraine
Labor market policy comprises of active and passive components. Active labor market policy involves funding employment services and providing various forms of assistance to both unemployed individuals and employers. Its primary objective is to enhance qualifications and intensify job search efforts to improve the employment prospects of the unemployed (Bredgaard, 2015). Passive labor market policy (PLMP) encompasses measures to support the incomes of involuntarily unemployed individuals, and financing for early retirement.
Poland and Lithuania are both EU and OECD members, so one would expect their labor market policies to be driven by the EU framework, and, thus, mostly aligned. However, our analysis showed that the structure of their expenditures on active labor market policies in 2017-2019 differed (Mazol, 2022). In Lithuania, the majority of the funding was allocated to employment incentives for recruitment, job maintenance, and job sharing. From 2017 to 2019, the share for these measures was between 18 and 28 percent of all expenditures for state labor market regulation. In Poland, the majority of funding was allocated to measures supporting protected employment and rehabilitation. The spending on these measures fluctuated between 23 and 34 percent of all expenditures for state labor market regulation between 2017 and 2019.
The response to the labor market challenges during the Covid-19 pandemic in Poland and Lithuania resulted in a notable surge in state labor market policy spendings in 2020, amounting to 1.78 percent of GDP and 2.83 percent of GDP, respectively. Both countries sharply increased the total spending on employment incentives (see Table 1 which summarizes the expenditure allocation for 2020). Poland experienced a nine-fold increase in costs for financing these measures (29.4 percent of total expenditures on state labor market regulation). Meanwhile, in Lithuania, financing for employment incentives increased more than tenfold, amounting to 42.5 percent of all expenditures for state labor market regulation. In both countries it became the largest active labor market policy spending area.
Table 1. Financing of state labor market measures in Baltic-Black Sea region countries in 2020 (in millions of Euro).
In Ukraine, the primary focus for active labor market policy expenditures was, from 2017 to 2020, directed towards public employment services, comprising 18 to 24 percent of total labor market policy expenditures. Notably, despite the Covid-19 pandemic, there were no significant changes in either the structure or the volume of active labor market policy expenditures in Ukraine in 2020. Despite Ukraine’s active efforts to align its economic and social policies with EU standards, the government has underinvested in labor market policy, with expenditures accounting for only 0.33-0.37 percent of GDP between 2017 and 2020. This is significantly below the levels observed in Lithuania and Poland.
In Belarus, labor market policy financing is one of the last priorities for the government. In 2020, financing accounted for about 0.02 percent of GDP, amounts clearly insufficient for having a significant impact on the labor market. Moreover, Belarus stood out as the sole country in the reviewed group to have reduced its funding for labor market policies, including both active and income support measures, during the Covid-19 pandemic. The majority of the financing for labor market policy has been directed towards protected and supported employment and rehabilitation, including job creation initiatives for former prisoners, the youth and individuals with disabilities.
ALMP Improvement Recommendations
As illustrated above, the countries under review do not have a common approach to active labor market policy spendings. Further, countries like Poland and Lithuania took a more flexible stance on addressing labor market challenges caused by the Covid-19 pandemic, by implementing additional financial support for active labor market policies. However, Ukraine and Belarus did not adjust their expenditure structures accordingly. Part of these cross-country differences can be attributed to differing legal framework: Poland and Lithuania are OECD and EU member states, and, thus, subject to corresponding regulations. Ukraine is in turn motivated by the prospects of EU accession, while Belarus currently has no such prosperities to take into account.
Another important source of deviation arises from the differences in current labor market and economic conditions in the respective countries, and the governments’ need to accommodate these. While such a market-specific approach is well-justified, aligning expenditure structures with current labor market conditions necessitates obtaining updated and reliable information about the labor market situation and the effectiveness of specific labor market measures or programs. An effective labor market policy thus requires establishing a reliable system for assessing the efficiency of government measures, i.e., deploying evidence-informed policy making (OECD, 2022).
To achieve this, it is crucial to establish a robust system for monitoring and evaluating the implementation of specific measures. This involves leveraging data from various centralized sources, enhancing IT infrastructure to support data management, and utilizing modern methodologies such as counterfactual impact evaluations (OECD, 2022).
Moreover, an effective labor market regulation policy necessitates the ability to swiftly adapt existing active measures and service delivery methods in response to changes in the labor market. This might entail rapid adjustments in the legal framework, underscoring the importance of close cooperation and coordination among key stakeholders, and a well-functioning administrative structure (Lauringson and Lüske, 2021).
To accomplish this objective, it is vital to foster close collaboration between the government and institutions closely intertwined with the labor market, capable of providing essential information to labor market regulators. One of the most useful tools in this regard appears to be so-called social partnerships – a form of a dialogue between employers, employees, trade unions and public authorities, involving active information exchange and interaction (OECD, 2022).
A reliable system to assess labor market policy and in particular to facilitate their targeting, is an essential component of this approach.
Ukraine and Belarus are underfunding their labor market policies, both in comparison to the levels observed in Poland and Lithuania, and in absolute terms. It is therefore advisable to establish quantitative benchmark indicators to act as guidance for these countries, in order to ensure that any labor market policy implemented is adequately funded. Here, a reasonable approach is to align the costs of implementing labor market measures with the average annual levels for OECD countries (which are 0.5 percent of GDP for active measures and 1.63 percent for total labor market policy expenditures (OECD, 2024). Furthermore, it’s essential to ensure a high level of labor force participation in active labor market regulation measures. A target standard could be set, based on the average annual coverage from active labor market measures, at 5.8 percent of the national economy labor force, as observed in OECD countries (OECD, 2024).
Conclusion
The countries under review demonstrate varying structures of active labor market expenditures. Prior to the Covid-19 pandemic, employment incentives received the most financing in Lithuania. In Poland the largest share of expenditures was instead directed to measures to support protected employment and rehabilitation. In Ukraine, the main expenditures were directed towards financing employment services and unemployment benefits while Belarus primarily allocated funds to protected and supported employment and rehabilitation. Notably, Lithuania and Poland responded to the economic challenges following Covid-19 by significantly increasing spending on employment incentives, while Ukraine and Belarus did not undertake such measures.
Part of the diverging patterns may be attributable to the countries varying legal framework and differences in the countries respective labor market and economic conditions.
While some of the differences in labor market policies are thus justified, ensuring funding at the OECD level for labor market measures, alongside adequate tools for monitoring and evaluating labor market policies, are likely to benefit all four Baltic-Black Sea countries.
References
- Bredgaard, T. (2015). Evaluating What Works for Whom in Active Labour Market Policies. European Journal of Social Security, 17 (4), 436-452.
- DGESAI. (Directorate-General for Employment, Social Affairs and Inclusion). (2023. Expenditure by LMP intervention – country https://webgate.ec.europa.eu/empl/redisstat/databrowser/explore/all/lmp?lang=en&subtheme=lmp_expend.lmp_expend_me&display=card&sort=category&extractionId=LMP_EXPME
- Lauringson, A. and Lüske M. (2021). Institutional Set-up of Active Labour Market Policy Provision in OECD and EU Countries: Organisational Set-up, Regulation and Capacity. OECD Social, Employment and Migration Working Papers no. 262.
- Mazol, A. (2022). Active Labor Market Policy in the Countries of the Baltic-Black Sea Region. BEROC Policy Paper Series, PP no. 115.
- OECD. (2015). OECD Employment database – Labour market policies and institutions https://www.oecd.org/employment/Coverage-and-classification-of-OECD-data-2015.pdf
- OECD. (2022). Impact Evaluation of Vocational Training and Employment Subsidies for the Unemployed in Lithuania. Connecting people with jobs. Paris: OECD Publishing.
- OECD. (2024). OECDstats: Labor market programs https://stats.oecd.org
- World Bank. (2023). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators
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.
Public Healthcare Expenditures in Transition Countries: Does Government Spending Respond to Public Preferences?
The transition from centrally planned to free-market economies in 1989 initiated a period of social and economic upheaval in post-communist countries, which affected healthcare quality, expenditures, and outcomes. We use data from the Life in Transition Survey (LiTS) to demonstrate that in spite of improvements across various measures of these facets of the healthcare system, it remains the first choice for additional government spending among the public in all countries of the region included in this study. Preferences in priorities for extra budget spending were similar among men and women in respective countries, but the preference for additional healthcare spending was stronger among women than men. The transition countries are compared with Germany and Italy – two Western European LiTs survey participants, countries with higher spending, and better healthcare outcomes.
Introduction
Across the globe, the outbreak of the COVID-19 pandemic has brought a new spotlight to the preparedness of healthcare systems for profound shocks (Anser et al, 2020). Critical care is a particularly costly element of healthcare provision, and thus, under-resourced systems are uniquely susceptible to spikes in mortality resulting from an oversaturation of intensive care units during an epidemiological crisis of this sort. (Fowler et al, 2008; Mannucci et al, 2020) Considering the widespread discussion surrounding health system capacity and the necessity for implementing economically painful lockdowns when those limits are reached, pressure from society to increase public spending may grow even further. With these developments in mind, in this policy paper, we confront past expressions of preferences regarding public expenditures with changes in government spending on healthcare between 2006 and 2017. The analysis draws on the one hand on the data from the Life in Transition Survey (LiTS), and on the other on publicly available data on government expenditures and outcomes.
In the context of preferences for additional public spending, we present a descriptive summary of trends in government expenditures on healthcare in Armenia, Belarus, Estonia, Georgia, Latvia, Lithuania, Moldova, Poland, Russia, and Ukraine. We include Italy and Germany as wealthier Western benchmarks, for which the data became available in the second wave of the survey in 2010. Data on public healthcare spending shows that despite a clear and strong public preference for increased investment in healthcare provision, additional spending as a proportion of total government expenditures between 2006 and 2017 has been moderate in most countries, and even negative in some. It must be underlined that expenditures are not always reflected in healthcare outcomes, quality, and coverage. Issues of efficiency, system design, and underlying health conditions of the population play a significant role in the returns on investment. For instance, the United States has spent drastically more per capita on healthcare than any other country and yet ranked lowest in the Healthcare Access and Quality (HAQ) Index among comparable countries (Fullman et al, 2016). However, due to the focus of the survey on government spending, we emphasize government expenditures on healthcare as a pertinent measure, especially in relation to overall GDP, per capita spending, and the public budget as a whole.
There is mounting evidence that one of the most important elements in the mitigation of COVID-19 mortality is the ability to expand system capacity and acquire the necessary equipment (e.g. respirators, ventilators) while ensuring that there is equitable access to measures for spread prevention (e.g. testing) (Khan et al, 2020; Ranney et al, 2020; Wang and Tang, 2020). The increasing pressure on healthcare systems, coupled with the additional fiscal strain resulting from the economic fallout of the pandemic, could lead to further divergence between public preferences and government spending on healthcare.
Healthcare Systems During the Transition
The ability of transition countries to absorb the risks and short-term economic shocks associated with pivoting from a centrally planned to a free-market economy has had dramatic implications for healthcare systems. Although countries in this region were divergent in terms of underlying health conditions, levels of expenditures, and health outcomes, most of them fell victims to deficient funding and additional health risks associated with the initial increases in poverty that were commonplace (Adeyi et al, 1997)
Compared to other transition countries, Georgia and Armenia faced a sharper economic collapse as well as armed conflicts, which caused scarcity in the availability of public healthcare providers and spikes in out-of-pocket expenses. Belarus was slower in the implementation of economic reforms and faced issues of fiscal sustainability further down the line (Balabanova et al, 2012). However, following this short tumultuous period, countries transitioning away from centrally planned economies have generally invested heavily in healthcare since the early 1990s. In many cases, these investments were facilitated by rapid GDP growth and accompanied by significant improvements in life expectancy. For example, between 1989 and 2012, Latvia, Lithuania, and Poland increased their per capita healthcare expenditures by more than 1,000 PPP per year, with an increase in life expectancy ranging from 1.7 years in Lithuania to 5.8 years in Poland (Jakovljevic et al, 2015). Despite heterogeneous and extensive reforms in many of these countries, as well as mixed results in measurements of efficiency and outcomes, healthcare expenditures consistently rank as the top priority for further government spending among both men and women in each country. This consistency lends itself to further policy considerations.
Preferences for Government Spending in Transition Countries
As is demonstrated by Figure 1, in 2016, healthcare was the most common answer to the question – “Which field should be the first priority for extra government spending?”- for all ten post-transition countries included in our analysis (the other options were: education, housing, pensions, assisting the poor, public infrastructure, the environment, and other). The survey was carried out on a representative sample that covers approximately 1,000+ respondents from each of the 29 countries in wave I and up to 1,500+ respondents from each of the 34 countries in wave III (EBRD: LiTS, 2020). Despite intercountry differences, in 2016 healthcare persisted as the top priority for both men and women in every transition country we studied apart from Belarus. While healthcare remained the top priority on average, men expressed a higher preference for additional investment in education. In the countries where preferences for health were particularly strong, healthcare was the first priority for as many as 53.5% of Latvians, 47.7% of Poles, and 43.9% of Moldovans (Figure 1a). Notwithstanding some fluctuations in scale, these preferences were not only common across countries but also across time, with people expressing very similar preferences in the first two waves of the survey in 2006 and 2010. (See Annex Figure A1 and Figure A2). While healthcare remained a popular choice in Germany and Italy, spending on healthcare as a percentage of GDP was nearly twice that of any transition country in Germany. There, education outweighed healthcare among men and women in both available waves (II and III), while pensions surpassed healthcare among men in the latter wave. In Italy, despite a more comparable level of healthcare spending relative to the transition countries, a drastic shift took place as healthcare fell from being the first priority by a large margin of 24.9 percentage points (pp) in 2010 to becoming the second priority after pensions in 2016. This can likely be attributed to the prominence of pensions as a major political campaign issue following the austerity-driven reforms of 2011 (Alfonso and Bulfone, 2019).
Figure 1: 1a (left) : Preferences for additional government spending, 2016. / 1b (right): Preferences for additional healthcare spending by gender, 2016
Moreover, it is evident that men and women within countries have rather similar preferences, as far as extra government spending is concerned. Not only is healthcare the first priority in all ten transition countries, but their second, third, and fourth choices are also very similar. When digging deeper into the differences that do exist, in every country except for Georgia women had a stronger preference for healthcare than men, and by as much as 8.8 pp, 8.4 pp, 7.8 pp, and 7.9 pp in Latvia, Germany, Belarus, and Russia respectively (Figure 1b). Conversely, in every case except for Georgia and Ukraine, men had a stronger preference for additional spending on education than women, most notably in Armenia – by 7.8 pp, Germany – by 5.7 pp, Lithuania – by 4.6 pp and Poland – by 3.9 pp. It is apparent that despite rapid investment in healthcare over the first two decades of the transition, there remains a widespread desire for further expansion of expenditures in this area.
Trends in Government Expenditures, 2006-2017
Considering the primacy of healthcare as the priority for additional government spending in all ten studied transition countries, we look at trends in aggregate statistics on government expenditures on healthcare over the surveyed period to explore the extent to which these preferences have been reflected in government spending. Taking the most basic measure into account in Figure 2a, i.e. public health expenditures as a percentage of GDP, among the transition countries only Georgia and Estonia have significantly increased their healthcare expenditures, by 1.6 pp and 1.2 pp, respectively. Lithuania, Poland, and Russia saw more moderate increases in the range of 0.6 pp and 0.2 pp. Other countries have remained essentially stagnant, apart from Moldova and Ukraine which saw a notable drop of 0.8 pp. Considering that this measure is sensitive to fluctuations in GDP growth, we also consider public health spending as a proportion of all government expenditures (see figure A3 in the Annex), which is a better indicator of government priorities for additional spending from 2006 until 2017. Georgia was the only transition country with a significant increase in healthcare spending proportional to total government expenditures, nearly doubling it from 5.2% to 9.5%. Belarus, Estonia, Lithuania, Poland have implemented a more moderate redirection of the budget towards healthcare, increasing proportional expenditures by a factor of 1.26, 1.15, 1.21, and 1.21 respectively. In spite of public preferences, Armenia decreased the proportional share of the budget dedicated to healthcare by as much as 2.6 pp, Moldova, Russia, and Ukraine by 1.3 pp, and Latvia by 0.8 pp. Regardless of the direction of the trend, notwithstanding some slight convergence, no transition country spent as much of its budget on healthcare as Italy and Germany. The latter spent nearly two to four times as much on healthcare as a proportion of total expenditures compared to the studied transition countries, and this gap has been widening relative to all of those included in the analysis, apart from Georgia.
Figure 2: Public healthcare expenditures (% of GDP)
While expenditures per capita are less indicative of government priorities in the budget, they are a better comparative measure for assessing the changes in healthcare provision, barring differences in efficiency. This comes with a huge caveat, namely that it is well established in the literature that additional healthcare expenditures often translate into “small to moderate” direct improvements in healthcare quality and outcomes due to inefficient spending or underlying factors (e.g. lifestyle choices, poverty) that are not addressed by investment in the healthcare system itself (Hussey et al, 2013; Self and Grabowski, 2003). Nevertheless, this measure is more likely to translate to an improvement in the quality of care each person receives, and the data paints a more positive picture considering the clear preference of both men and women for higher spending. In Figure 3 we present healthcare expenditures per capita in USD, and apart from Italy and Ukraine, all of the countries have significantly increased spending between 2006 and 2017. While expenditures per capita in transition countries are dwarfed by Germany and Italy, Estonia, Georgia, and Lithuania have more than doubled their expenditures, and Armenia has more than tripled. Belarus, Latvia, Poland, Moldova, and Russia have also significantly increased their per capita spending on healthcare, by factors in the range of 1.54 and 1.91. However, while expenditures per capita is one indicator of improving healthcare quality, it does not identify government priorities and is largely dependent on overall economic growth (Fuchs, 2013; Bedir, 2016).
Figure 3: Health care expenditure per capita, USD
In every country we include, increasing healthcare expenditure per capita is accompanied by advancements in many measures of healthcare outcomes for men and women. Between 2006-2017, life expectancy at birth increased across the board, with men in Russia experiencing the greatest improvement of 7.1 years (Figure 4a). These are promising trends – for women, life expectancy at birth improved by a larger margin in each transition country than in Germany or Italy, and the same can be said for men in every country apart from Armenia. Furthermore, the Healthcare Access and Quality (HAQ) index, which is composed of 32 indicators related to preventable causes of mortality, has improved across all 12 countries between 2005-2016. The change was most notable in Armenia, Belarus, Estonia, and Russia, constituting as much as 8.7, 10.2, 8.9, and 8.9 points out of a hundred, respectively (Figure 4b). These trends indicate convergence in the quality of healthcare as they significantly outpaced improvements in the HAQ index in Italy (3.1 points) and Germany (3.9 points). As of 2016, among the countries of interest, Georgia (67.1 points) and Moldova (67.4) had the lowest scores, while Germany (92.0) and Italy (94.9) scored highest, as could be expected based on healthcare spending measures presented in Figures 2 and 3.
Figure 4: 4a (left): Change in life expectancy, 2006-2017 / 4b (right): HAQ index
However, as presented in Figure 5, there is no clear relationship between the strength of the preference for additional healthcare spending and the scale of expansion in spending. Taking three of the four countries (Armenia, Belarus, and Russia) with the greatest improvement in the HAQ index as an example, there was virtually no change in healthcare spending as a percentage of GDP over the same period. These countries were also different in terms of how strong the preferences were for additional spending on healthcare as the first priority in 2006.
Figure 5: Public preferences and government healthcare spending (% of GDP)
Conclusion
As we have demonstrated in this brief, in the ten post-communist countries for which we have analyzed LiTS data, there was a consistent and common preference for healthcare as the first priority for extra government spending between 2006 and 2016. We also find that in each country except Georgia, on average, women had a stronger preference for additional public healthcare spending, supporting a wealth of literature that suggests that women utilize healthcare services more frequently and spend more out of pocket on healthcare than men (Owens, 2008; Cylus et al, 2011; Williams et al, 2017). However, over the period we study, these preferences have not translated directly into a reallocation of budgetary resources. The countries with the strongest preferences for additional healthcare spending in 2006 did not experience the highest increases in any of the discussed measures of public healthcare expenditures since then.
People living in Italy and Germany chose an increase in public spending on healthcare as their first priority less frequently than residents of post-transition countries. Better understanding these differences requires further research, but there is likely a combination of factors that play into this effect. For one, wealthier Western countries performed better when looking at simple measures of healthcare outcomes such as life expectancy and deaths from non-communicable diseases (WHO, 2020), and hence other priorities may have gained in salience. Furthermore, they allocated a greater proportion of the public budget towards healthcare. This in part stems from the significant challenges associated with the transition following 1989. Healthcare systems in post-communist countries experienced a fiscal shock when joining the global economy, with the loss of centrally controlled price mechanisms causing an increase in the relative prices of healthcare inputs such as medicines and equipment (Obrizan, 2017). This was exacerbated by a shrinking capability of governments to spend more on healthcare related to the general economic shocks at that time and led to the passing over of costs to patients in the form of out-of-pocket expenses (Balabanova, et al. 2012). Although access to healthcare and the quality of that care have improved after the transition (Romaniuk and Szromek, 2016), these have failed to converge towards Western European countries on a number of substantial measures up to this point. Before the commencement of the COVID-19 pandemic, government healthcare spending did not reflect the preferences of the public in any of the ten studied transition countries. The outbreak of the pandemic has not only intensified the pressure on the healthcare system but also brought about a number of negative economic consequences. This combination can be expected to simultaneously increase the strain on the public budget and necessitate difficult decisions of reallocation at a time when fiscal sustainability during a global recession is already being brought under question (Creel, 2020).
References
- Adeyi, O., Chellaraj, G., Goldstein, E., Preker, A. and Ringold, D., 1997. Health status during the transition in Central and Eastern Europe: development in reverse?. Health Policy and Planning, 12(2), pp.132-145.
- Afonso, A. and Bulfone, F., 2019. Electoral coalitions and policy reversals in Portugal and Italy in the aftermath of the eurozone crisis. South European Society and Politics, 24(2), pp.233-257.
- Anser, M.K., Yousaf, Z., Khan, M.A., Nassani, A.A., Alotaibi, S.M., Abro, M.M.Q., Vo, X.V. and Zaman, K., 2020. Does communicable diseases (including COVID-19) may increase global poverty risk? A cloud on the horizon. Environmental Research, 187, p.109668.
- Balabanova, D., Roberts, B., Richardson, E., Haerpfer, C. and McKee, M., 2012. Health Care Reform in the Former Soviet Union: Beyond the Transition. Health services research, 47(2), pp.840-864.
- Bedir, S., 2016. Healthcare expenditure and economic growth in developing countries. Advances in Economics and Business, 4(2), pp.76-86.
- Creel, J., 2020. Fiscal space in the euro area before Covid-19. Economics Bulletin, 40(2), pp.1698-1706.
- Cylus, J., Hartman, M., Washington, B., Andrews, K. and Catlin, A., 2011. Pronounced gender and age differences are evident in personal health care spending per person. Health Affairs, 30(1), pp.153-160.
- Fuchs, V.R., 2013. The gross domestic product and health care spending. N Engl J Med, 369(2), pp.107-109.
- EBRD, 2020. Life in Transition Survey (LiTS). European Bank for Reconstruction and Development.
- Fowler, R.A., Adhikari, N.K. and Bhagwanjee, S., 2008. Clinical review: critical care in the global context–disparities in burden of illness, access, and economics. Critical Care, 12(5), p.225.
- Fullman, N., Yearwood, J., Abay, S.M., Abbafati, C., Abd-Allah, F., Abdela, J., Abdelalim, A., Abebe, Z., Abebo, T.A., Aboyans, V. and Abraha, H.N., 2018. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016. The Lancet, 391(10136), pp.2236-2271.
- Global Burden of Disease Collaborative Network, 2018. Global Burden of Disease Study 2016 (GBD 2016) Healthcare Access and Quality Index Based on Amenable Mortality 1990–2016. Seattle, United States: Institute for Health Metrics and Evaluation (IHME).
- Hussey, P.S., Wertheimer, S. and Mehrotra, A., 2013. The association between health care quality and cost: a systematic review. Annals of internal medicine, 158(1), pp.27-34.
- Mannucci, E., Silverii, G.A. and Monami, M., 2020. Saturation of critical care capacity and mortality in patients with the novel coronavirus (COVID-19) in Italy. Trends in Anaesthesia and Critical Care.
- Jakovljevic, M.B., Vukovic, M. and Fontanesi, J., 2016. Life expectancy and health expenditure evolution in Eastern Europe—DiD and DEA analysis. Expert Review of Pharmacoeconomics & Outcomes Research, 16(4), pp.537-546.
- Obrizan, M., 2017. Does EU membership prevent crowding out of public health care? Evidence from 28 transition countries.
- Owens, G., 2008. Gender differences in health care expenditures, resource utilization, and quality of care. Journal of Managed Care Pharmacy, 14(3), pp.2-6.
- Ranney, M.L., Griffeth, V. and Jha, A.K., 2020. Critical supply shortages—the need for ventilators and personal protective equipment during the Covid-19 pandemic. New England Journal of Medicine, 382(18), p.41.
- Romaniuk, P. and Szromek, A.R., 2016. The evolution of the health system outcomes in Central and Eastern Europe and their association with social, economic and political factors: an analysis of 25 years of transition. BMC health services research, 16(1), p.95.
- Self, S. and Grabowski, R., 2003. How effective is public health expenditure in improving overall health? A cross–country analysis. Applied Economics, 35(7), pp.835-845.
- Wang, Z. and Tang, K., 2020. Combating COVID-19: health equity matters. Nature Medicine, 26(4), pp.458-458.
- Williams, J.S., Bishu, K., Dismuke, C.E. and Egede, L.E., 2017. Sex differences in healthcare expenditures among adults with diabetes: evidence from the medical expenditure panel survey, 2002–2011. BMC health services research, 17(1), p.259.
- World Bank, 2020. Data Bank: World Development Indicators. Washington D.C., World Bank Group.
- World Health Organization, 2020. Global Health Observatory (GHO) data.
Note: Annex included in the attached PDF.
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.
Socio-Economic Policy in Poland: A Year of Major Changes in Benefits, Taxes, and Pensions
2016 was the first full calendar year of the new Polish government elected to power in October 2015. The year marked a number of major changes legislated in the area of socio-economic policy some of which have already been implemented and others that will take effect in 2017. In this policy brief, we analyse the distributional consequences of changes in the direct tax and benefit system, and discuss the long-term implications of these policies in combination with the policy to reduce the statutory retirement age.
The Law and Justice party (Prawo i Sprawiedliwość, PiS) won an absolute majority of seats in both houses of the Polish Parliament in the parliamentary elections of October 2015. Earlier that year, Andrzej Duda of PiS was elected President of the Polish Republic. In both cases, the electoral victories came on the wave of pledges of significant financial support to families with children and to low-income households, especially pensioners. The new president pledged to cut back the pension age to the levels prior to the 2012 reform, which introduced a gradual increase from 60 and 65 to 67 for both women and men, and to nearly triple the income tax allowance. Following Duda’s victory in May 2015, PiS reiterated these pledges in the parliamentary election campaign and added the promise to increase the total level of financial support for families with children by over 140% through a nearly universal benefit called “Family 500+” and to hike the minimum wage by over 8%.
Despite a rather tight budget situation, the government went ahead with the “Family 500+” and successfully rolled it out in April 2016 (Myck et al., 2016a). The new instrument directs support of 500 PLN per child per month (110 EUR) to all second and subsequent children in the family in the age group between 0 and 17. Benefits for the first child in the family in this age group are granted conditional on overcoming an income threshold of 800 PLN (180 EUR) per person per month. Since April 2016, over 2.7 million families have received the benefit and 60% of them received the means tested support (if they have more than one child this is paid out in combination with the universal benefit).
The second key electoral pledge – to increase the tax allowance from 700 to 1,850 EUR at an estimated cost of 4.8 billion EUR – has so far been postponed (CenEA, 2015a). Increases in the allowance became a major policy issue in October 2015 when the Constitutional Tribunal ruled that maintaining its level below minimum subsistence, as it was at the time, was unconstitutional. To satisfy the Tribunal’s ruling, the allowance would have to increase to ca. 1,500 EUR at a cost of nearly 15 billion PLN (3.4 billion EUR, and about 0.8% of GDP, CenEA 2015b). Instead of a simple increase in the allowance, the government decided to implement a digressive tax allowance for 2017. This raised the value to the required minimum subsistence level for the lowest income tax payers, but since it is rapidly withdrawn as taxable income rises, the allowance will be unchanged to a large majority of taxpayers and will cost the public purse only 0.2 billion EUR (CenEA, 2016). This policy will be more than paid for by the fiscal drag given the decision to freeze all other parameters of the tax system, which will cost the taxpayers 0.5 billion EUR (Myck et al., 2016b).
The policies that directly affect household budgets will in total amount to about 5.5 billion EUR in 2017 (1.3% of GDP and 6.2% of the planned central budget expenditures) and will include also an increase in the minimum pension to benefit about 1.5 million pensioners. The cost of the “Family 500+” reform makes up the large majority of this value (5.4 billion EUR). Households from the lower income decile groups will benefit the most from this reform package, with their monthly disposable income increasing on average by 15.1% (ca. 60 EUR). High-income households from the top income decile will see their income grow on average by only 0.5% (see Figure 1). Overall, nearly all of the gains will go to families with children, with single parents gaining on average about 95 EUR and married couples with children about 84 EUR per month. Other types of families will, on average, see negligible changes in their household disposable incomes (see Figure 2). Thus, the implemented package clearly has a very progressive nature and redistributes significant resources to families with children.
Figure 1. Distributional consequences of changes in direct tax and benefit measures implemented between 2016-2017
Source: calculations using CenEA’s microsimulation model SIMPL based on PHBS 2014 data.
The pension age and public finances in the years to come
The most recent major reform, legislated at the end of 2016 and which will come into effect in October 2017, represents an implementation of yet another costly electoral pledge. This policy has overturned gradual increases in the statutory retirement age, initiated by the previous government in 2012. Despite the very rapid ageing of the Polish population, the new government decided to return to the pre-2012 retirement ages of 60 and 65 for women and men, respectively. This comes at a time when, according to EUROSTAT (Eurostat, 2014), the old-age dependency ratio in Poland, i.e. the proportion of the 65+ population to the working-age population, will grow from the current 24% to 27% in 2020 and to 40% in 2040. With the defined contribution pension system, the shorter working lives resulting from this change will be reflected in significantly reduced benefits (Figure 2). For example, pension benefits of men retiring in 2020 will on average be 13.5% lower than the pre-reform value. For women that retire in 2040, the pension benefits will on average fall by 15.2%, which corresponds to a 43% lower benefit than the pre-reform value, and with consequences of the reform becoming more severe over time. The reform will also be very costly to the government budget. In 2017, it is expected to cost 1.3 billion EUR and its full effect will kick in after 2021, when the cost of the reform will exceed 3.9 billion EUR per year (Figure 2).
Figure 2. Reducing the statutory retirement age and its implications on pension benefits and public finances
Source: Based on data from Council of Ministers (2016).
Conclusion
Since coming to power in October 2015, the PiS government has implemented a majority of its costly electoral pledges. Direct changes in taxes and benefits will cost 5.5 billion EUR in 2017 and benefit primarily those in the lower end of the income distribution and in particular families with children. The reduced statutory retirement age will add an extra 1.3 billion EUR in 2017 and as much as 3.9 billion EUR four years later. The very generous “Family 500+” programme has significantly reduced child poverty and may have important positive long-term effects in terms of health and education for today’s beneficiaries. However, its fertility implications are still uncertain and the programme is expected to reduce the employment rate among mothers. While the government maintains that its financing is secured, it is becoming clear that maintaining the policy will not be possible without higher taxes.
The government came to power claiming that the implementation of this programme will be based on reducing tax fraud and that only a small fraction will be financed from tax increases. While it seemed likely at the time when these declarations were made, the expected major shift in the reduction of tax fraud has yet not materialised. The government have withdrawn from the pledge of reducing the VAT and from assisting those with mortgages denominated in Swiss Francs, while its income tax allowance reform was nearly thirty times less expensive compared to that announced in its electoral programme.
With a very tight budget for 2017 based on relatively optimistic assumptions, the key factors determining further realisations of the generous programme will be the rate of economic growth and related dynamics on the labour market. Developments of the labour market will also be essential for the longer-term economic success of the implemented reform package. This relates both to the future level of participation of women and to the success of extend working lives of people who will soon reach the new reduced retirement age.
References
- CenEA (2015a) Konsekwencje prezydenckiej propozycji podwyższenia kwoty wolnej od podatku (Consequences of the presidential proposal to raise the incoem tax allowance), CenEA press release, 3 December 2015.
- CenEA (2015b) Co z kwotą wolną od podatku po wyroku Trybunału Konstytucyjnego? (what will happen to the income tax allowance after the decision of the Constitutional Tribunal?), CenEA press release, 13 November 2015.
- CenEA (2016) Zmiany w kwocie wolnej od podatku za 800 mln rocznie (Changes in the income tax allowance at the cost of 800m per year), CenEA press release, 29 November 2016.
- EUROSTAT (2014) Eurostat – Population projections EUROPOP2013, access 21 December 2016.
- Myck, M., Kundera, M., Najsztub, M., Oczkowska, M. (2016a) 25 miliardów złotych dla rodzin z dziećmi: projekt Rodzina 500+ i możliwości modyfikacji systemu wsparcia. (25bn for families with children: plans for the Family 500+ reform and other options to modify the system of support.), CenEA Commentaries, 18 January 2016.
- Myck, M., Kundera, M., Najsztub, M., Oczkowska, M., 2016b, Zamrożony PIT i utrzymane wyższe stawki VAT – jak brak zmian w podatkach wpłynie na budżety gospodarstw domowych? (Frozen PIT and higher VAT – how lack of changes in taxees will affect househod budgets?), CenEA Commentaries, 05 October 2016.
- Council of Ministers (2016) Position of the Council of Ministers on the presidential bill proposal, Warsaw, 25 July 2016.