14 research outputs found

    Labour supply incentives and income support systems in Estonia

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    In this paper we give an overview of labour supply incentives present in the Estonian income support system and how changes during the last ten years in the Estonian benefit system have influenced the incentives. As Estonia belongs to the group of EU countries where both taxes and social expenditures are relatively low, they generate high motivation to actively participate in the labour market, in general. Also the gradual introduction of contribution based and earnings related benefits, such as unemployment insurance benefits, parental benefits, a fully funded pension scheme together with earnings-related public pension scheme have all significantly increased rewards from employment and are often associated with increased labour supply as well as a reduction in undeclared work. The increase of the statutory retirement ages for men and women have increased average employment rates of the elderly, but also retirement through alternative schemes, most notably disability pensions and early retirement pensions. In a few cases, the Estonian benefit schemes generate disincentives to seek for a job or increase labour effort, affecting people both with low and high earnings. In case of unemployment benefits and early retirement benefits, even marginal income from labour leads to loss of all benefits, thus discouraging part time work. Also there are very high effective marginal tax rates when increasing work effort when receiving subsistence benefits and parental benefits, in certain cases. These disincentives become even more significant in this economic crisis when people are faced with long-term unemployment and it is vital that they are encouraged to return to the labour market.Labour supply incentives; social security; Estonia

    Distributional Effects of Environmental Taxes in Estonia

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    This paper analyses the distributional effects of Estonian environmental taxes in 2000-2007 and recent reforms in 2008 using Estonian Household Budget Survey data and a microsimulation model. The results show that the share of environmental taxes in consumption expenditures is about 1-1.5%. Environmental taxes in 2000- 2007 were progressive due to the progressivity of motor fuel excises, which was the largest component of the environmental taxes until 2007. Since 2008, the taxes are less progressive, because of the new electricity excise and increased taxes on gas and other inputs used for distance domestic heating. To minimize the disproportionate effect of future ecological tax reform on low-income households, close monitoring of tax developments is required and necessary compensatory policies need to be implemente

    Sõeluuringu rakendamise põhjendatus osteoporoosi varaseks diagnoosimiseks Eestis

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    Sõeluuringu eesmärgiks on haiguse varajane kindlakstegemine rahvastikus, et võimaldada varajast sekkumist ja tegevuse juhtimist eesmärgiga vähendada haigestumist ja suremust. Sõeluuringu eelduseks on, et uuritaval haigusel on määratletav prekliiniline faas, mille avastamise korral on rakendatav ravi, mis on tõhusam/odavam haiguse ravist kliinilises faasis. Osteoporoos ja sellega seonduvad luumurrud on oluliseks rahvatervise probleemiks, põhjustades haige elukvaliteedi halvenemist ning haigestumise ja suremuse enneaegset kasvu. Artikli eesmärgiks on kaaluda sõeluuringu kui osteoporoosiga seonduvate luumurdude kontrollistrateegia rakendamist Eestis. Uuringus kasutati teaduskirjanduse ja administratiivsete dokumentide analüüsi ning autorite eksperdihinnanguid. Olemasoleva tõenduse põhjal ei saa soovitada rahvastikupõhise osteoporoosi sõeluuringu rakendamist Eestis lähiaastatel. Selle alternatiivina võib kaaluda võimalusepõhise skriiningu rakendamist FRAX-instrumendi abil. Eesti Arst 2009; 88(6):402−41

    Lessons learned from the Baltic countries' response to the first wave of COVID-19.

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    The Baltic countries of Estonia, Latvia, and Lithuania shared a similar response to the first wave of the COVID-19 pandemic. Using the information available on the COVID-19 Health System Response Monitor platform, this article analyzed measures taken to prevent transmission, ensure capacity, provide essential services, finance the health system, and coordinate their governance approaches. All three countries used a highly centralized approach and implemented restrictive measures relatively early, with a state of emergency declared with fewer than 30 reported cases in each country. Due to initially low COVID-19 incidence, the countries built up their capacities for testing, contact tracing, and infrastructure, without a major stress test to the health system throughout the spring and summer of 2020, yet issues with accessing routine health care services had already started manifesting themselves. The countries in the Baltic region entered the pandemic with a precarious starting point, particularly due to smaller operational budgets and health workforce shortages, which may have contributed to their escalated response aiming to prevent transmission during the first wave. Subsequent waves, however, were much more damaging. This article focuses on early responses to the pandemic in the Baltic states highlighting measures taken to prevent virus transmission in the face of major uncertainties

    Distributional Effects of Environmental Taxes in Estonia

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    This paper analyses the distributional effects of Estonian environmental taxes in 2000-2007 and recent reforms in 2008 using Estonian Household Budget Survey data and a microsimulation model. The results show that the share of environmental taxes in consumption expenditures is about 1-1.5%. Environmental taxes in 2000- 2007 were progressive due to the progressivity of motor fuel excises, which was the largest component of the environmental taxes until 2007. Since 2008, the taxes are less progressive, because of the new electricity excise and increased taxes on gas and other inputs used for distance domestic heating. To minimize the disproportionate effect of future ecological tax reform on low-income households, close monitoring of tax developments is required and necessary compensatory policies need to be implemente

    Health as Factor of Economic Growth: the Estonian Case

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    The aim of the paper is to analyze the relationship between health and economic growth in Estonia. Health determines the quality of the human capital, which modern economic theories consider the principal factor of economic growth. On the basis of survey data we estimate the effect of self-assessed health on labor supply and wages applying econometric methods. We find that poor health is significantly related to lower wages and employment probability. We also calculate average days and hours lost from work due to ill health or injury in 2001. The plausible direct loss in GDP due to health problems is about 1-2 per cent. We conclude that although health has had overall a marginal effect on economic growth during the transition period, it is still important and its impact may increase in the future, when the population’s health capital deteriorates further as a result of the population getting older and young generations having damaging health behavior.health, economic growth

    ECONOMETRIC ANALYSIS OF INCOME CONVERGENCE IN SELECTED EU COUNTRIES AND THEIR NUTS 3 LEVEL REGIONS

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    The paper estimates equations for regional income convergence in selected EU countries and their NUTS 3 level regions during the European Union pre-enlargement period (1995–2002), using both spatial and non-spatial approaches. There has been absolute income convergence between regions in both the groups of countries looked at, the countries of the EU15, or the old member states, and the new member states or NMS. When national effects are included in convergence equations using country dummies, no evidence of regional income convergence can be observed. The results of the analysis assert the importance of regional policies in inhibiting the increase of regional income disparities and improving conditions for income growth, particularly within the new member states.

    Cross-population evaluation of cervical cancer risk prediction algorithms

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    Background - Cervical cancer is a preventable disease, despite being one of the most common types of female cancers worldwide. Integrating existing programs for cervical cancer screening with personalized risk prediction algorithms can improve population-level cancer prevention by enabling more targeted screening and contrive preventive healthcare innovations. While algorithms developed for cervical cancer risk prediction have shown promising performance in internal validation on more homogeneous populations, their ability to generalize to external populations remains to be assessed. Methods - To address this gap, we perform a cross-population comparative study of personalized prediction algorithms for more personalized cervical cancer screening. Using data from the Norwegian and Estonian populations, the algorithms are validated on internal and external datasets to study their potential biases and limitations when applied to different populations. We evaluate the algorithms in predicting progression from low-grade precancerous cervical lesions, simulating a clinically relevant application of more personalized risk stratification. Results - As expected, our numerical experiments show that algorithm performance varies depending on the population. However, some algorithms show strong generalization capacity across different data sources. Using Kaplan-Meier estimates, we demonstrate the strengths and limitations of the algorithms in detecting cancer progression over time by comparing to the trends observed from data. We assess their overall discrimination performance in personalized risk predictions by analyzing the accuracy and confidence in individual risk estimates. Discussion and Conclusion - This study examines the effectiveness of personalized prediction algorithms across different populations. Our results demonstrate the potential for generalizing risk prediction algorithms to external populations. These findings highlight the importance of considering population diversity when developing risk prediction algorithms
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