Ten Years After: What is Special about Transition Countries?

Most countries commonly classified as 'in transition' are st ill recognisably different from other countries with a similar income per capita in some respects: a larger share of their work force is in industry, they use more energy, they have a more extensive infrastructure and invest more in schooling. However, in terms of the 'software' necessary for a market economy, two groups emerge: the countries that are candidates for EU membership seem to have partly completed the transition. By contrast, the countries from the former Soviet Union that form the CIS and the South-eastern European (SEE) countries, are still largely lagging behind in terms of the enforcement of property rights and the development of financial markets.Transition economies, development level

Are Cardiovascular Diseases Bad for Economic Growth?

We assess the impact of cardiovascular disease (CVD) mortality on economic growth, using a dynamic panel growth regression framework taking into account potential endogeneity problems. We start from a worldwide sample of countries for which data was available and detect a non-linearity in the influence of working age CVD mortality rates on growth across the per capita income scale. We then split the sample (according to the resulting income threshold) into low- and middle-income countries on one hand, and high-income countries on the other hand. In the latter sample we find a robust negative contribution of increasing CVD mortality rates on subsequent five-year growth rates. Not too surprisingly, we find no significant impact in the low- and middle-income country sample.cardiovascular disease, growth empirics, dynamic panel data estimator

Divergence – Is it Geography?

This paper tests directly a geography and growth model using regional data for Europe, the US, and Japan during di®erent time periods. We set up a standard geography and growth model with a poverty trap and derive a log- linearized growth equation that corresponds directly to a threshold regression technique in econometrics. In particular, we test whether regions with high population density (centers) grow faster and have a permanently higher per capita income than regions with low population density (peripheries). We find geography driven divergence for US states and European regions after 1980. Population density is superior in explaining divergence to initial income which the most important o±cial EU eligibility criterium for regional aid is built on. Divergence is stronger on smaller regional units (NUTS3) than on larger ones (NUTS2). Thus, the wavelength of agglomeration forces seems to be rather small in Europe. Human capital and R&D are transmission channels of divergence processes. Human capital based poverty trap models are an alternative explanation for regional poverty traps.Keywords: threshold estimation, economic geography, regional income convergence, poverty trap, regime shifts, bootstrap

Impact of changes in mode of travel to work on changes in body mass index: evidence from the British Household Panel Survey

BACKGROUND Active commuting is associated with various health benefits, but little is known about its causal relationship with body mass index (BMI). METHODS We used cohort data from three consecutive annual waves of the British Household Panel Survey, a longitudinal study of nationally representative households, in 2004/05 (n=15,791), 2005/06 and 2006/07. Participants selected for the analyses (n=4,056) reported their usual main mode of travel to work at each time point. Self-reported height and weight were used to derive BMI at baseline and after two years. Multivariable linear regression analyses were used to assess associations between switching to and from active modes of travel (over one and two years) and change in BMI (over two years) and to assess dose-response relationships. RESULTS After adjustment for socioeconomic and health-related covariates, the first analysis (n=3,269) showed that switching from private motor transport to active travel or public transport (n=179) was associated with a significant reduction in BMI compared to continued private motor vehicle use (n=3,090) (-0.32kg/m2, 95% CI: -0.60 to -0.05). Larger adjusted effect sizes were associated with switching to active travel (n=109) (-0.45kg/m2, -0.78 to -0.11), particularly among those who switched within the first year and those with the longest journeys. The second analysis (n=787) showed that switching from active travel or public transport to private motor transport was associated with a significant increase in BMI (0.34kg/m2, 0.05 to 0.64). CONCLUSION Interventions to enable commuters to switch from private motor transport to more active modes of travel could contribute to reducing population mean BMI

Chronic diseases and labor market outcomes in Egypt

By causing a sizeable reduction in employment 6 percent and labor supply 19 percent, chronic diseases are responsible for a major efficiency loss in the Egyptian economy. Furthermore the impact of chronic diseases on the labor market is not uniformly distributed. The older and the less educated suffer a larger drop in the probability of being employed and in their supply of working hours. The authors estimate the reduced form equations of individual employment status, labor supply and the usual wage equation. They control for unobserved ability and individual preferences by means of a within-siblings estimator. Measurement errors in our self-reported health variable have been accounted for.Health Monitoring&Evaluation,Labor Markets,Disease Control&Prevention,Labor Policies,Population Policies

Does social capital determine health? Evidence from eight transition countries

This paper starts from an empirical assessment of different dimensions of social capital in the transition countries of Central and Eastern Europe (CEE) and the Commonwealth of Independent States (CIS). The level of social capital is lower in CEE-CIS countries compared to other countries in Europe and beyond. We then use a unique data source to carefully investigate the impact of social capital on individual self-reported health for eight countries from the Commonwealth of Independent States (Armenia, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Ukraine). We rely on three indicators for social capital – individual degree of trust, participation in local organisations, social isolation – and employ alternative procedures to consistently estimate the impact of social capital on health. We attempt to circumvent the endogeneity problems by using instrumental variable estimates. Our results show that, in the overall sample comprising all eight countries, the individual degree of trust is positively and significantly correlated with health, either in pooling estimation or when we rely on IV estimators with community fixed effects. Similarly, social isolation is negatively and significantly associated with health, irrespective of the procedure of estimation. On the other hand, the effect of being member of a Putnamesque organisation is more ambiguous and usually not significantly related to health. Finally, country-estimates suggest that the impact of social capital on health varies across the eight countries. We argue that the positive effect of membership on health is conditional on the quality of the political institutions and civil liberties, while trust and social isolation seem to influence health independently of those institutional factors.Health; social capital; instrumental variables; transition countries

The effect of health on labour supply in nine former Soviet Union countries.

This paper examines for the first time the consequences of ill health on labour supply for a sample of nine countries from the former Soviet Union (FSU), using a unique multicountry household survey specifically designed for this region. We control for a wide range of individual, household, and community factors, using both standard regression techniques and instrumental variable estimation to address potential endogeneity. Specifically, we find in our baseline ordinary least squares specification that poor health is associated with a decrease in the probability of working of about 13 %. Controlling for community-level unobserved variables slightly increases the magnitude of this effect, to about 14 %. Controlling for endogeneity with the instrumental variable approach further supports this finding, with the magnitude of the effect ranging from 12 to 35 %. Taken together, our findings confirm the cost that the still considerable adult health burden in the FSU is imposing on its population, not only in terms of the disease burden itself, but also in terms of individuals' labour market participation, as well as potentially in terms of increased poverty risk. Other things being equal, this would increase the expected "return on investment" to be had from interventions aimed at improving health in this region

An economic framework for analysing the social determinants of health and health inequalities

Reducing health inequalities is an important part of health policy in most countries. This paper discusses from an economic perspective how government policy can influence health inequalities, particularly focusing on the outcome of performance targets in England, and the role of sectors of the economy outside the health service – the ‘social determinants’ of health - in delivering these targets.

The Economic Costs of Type 2 Diabetes: A Global Systematic Review.

BACKGROUND: There has been a widely documented and recognized increase in diabetes prevalence, not only in high-income countries (HICs) but also in low- and middle-income countries (LMICs), over recent decades. The economic burden associated with diabetes, especially in LMICs, is less clear. OBJECTIVE: We provide a systematic review of the global evidence on the costs of type 2 diabetes. Our review seeks to update and considerably expand the previous major review of the costs of diabetes by capturing the evidence on overall, direct and indirect costs of type 2 diabetes worldwide that has been published since 2001. In addition, we include a body of economic evidence that has hitherto been distinct from the cost-of-illness (COI) work, i.e. studies on the labour market impact of diabetes. METHODS: We searched PubMed, EMBASE, EconLit and IBSS (without language restrictions) for studies assessing the economic burden of type 2 diabetes published from January 2001 to October 2014. Costs reported in the included studies were converted to international dollars ($) adjusted for 2011 values. Alongside the narrative synthesis and methodological review of the studies, we conduct an exploratory linear regression analysis, examining the factors behind the considerable heterogeneity in existing cost estimates between and within countries. RESULTS: We identified 86 COI and 23 labour market studies. COI studies varied considerably both in methods and in cost estimates, with most studies not using a control group, though the use of either regression analysis or matching has increased. Direct costs were generally found to be higher than indirect costs. Direct costs ranged from$242 for a study on out-of-pocket expenditures in Mexico to $11,917 for a study on the cost of diabetes in the USA, while indirect costs ranged from$45 for Pakistan to $16,914 for the Bahamas. In LMICs-in stark contrast to HICs-a substantial part of the cost burden was attributed to patients via out-of-pocket treatment costs. Our regression analysis revealed that direct diabetes costs are closely and positively associated with a country's gross domestic product (GDP) per capita, and that the USA stood out as having particularly high costs, even after controlling for GDP per capita. Studies on the labour market impact of diabetes were almost exclusively confined to HICs and found strong adverse effects, particularly for male employment chances. Many of these studies also took into account the possible endogeneity of diabetes, which was not the case for COI studies. CONCLUSIONS: The reviewed studies indicate a large economic burden of diabetes, most directly affecting patients in LMICs. The magnitude of the cost estimates differs considerably between and within countries, calling for the contextualization of the study results. Scope remains large for adding to the evidence base on labour market effects of diabetes in LMICs. Further, there is a need for future COI studies to incorporate more advanced statistical methods in their analysis to account for possible biases in the estimated costs.The work of MS on this paper was partially funded by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council (ESRC), Medical Research Council (MRC), the National Institute for Health Research, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged.This is the final published version. It first appeared at http://link.springer.com/article/10.1007%2Fs40273-015-0268-9

Evaluating causal relationships between urban built environment characteristics and obesity: a methodological review of observational studies.

BACKGROUND: Existing reviews identify numerous studies of the relationship between urban built environment characteristics and obesity. These reviews do not generally distinguish between cross-sectional observational studies using single equation analytical techniques and other studies that may support more robust causal inferences. More advanced analytical techniques, including the use of instrumental variables and regression discontinuity designs, can help mitigate biases that arise from differences in observable and unobservable characteristics between intervention and control groups, and may represent a realistic alternative to scarcely-used randomised experiments. This review sought first to identify, and second to compare the results of analyses from, studies using more advanced analytical techniques or study designs. METHODS: In March 2013, studies of the relationship between urban built environment characteristics and obesity were identified that incorporated (i) more advanced analytical techniques specified in recent UK Medical Research Council guidance on evaluating natural experiments, or (ii) other relevant methodological approaches including randomised experiments, structural equation modelling or fixed effects panel data analysis. RESULTS: Two randomised experimental studies and twelve observational studies were identified. Within-study comparisons of results, where authors had undertaken at least two analyses using different techniques, indicated that effect sizes were often critically affected by the method employed, and did not support the commonly held view that cross-sectional, single equation analyses systematically overestimate the strength of association. CONCLUSIONS: Overall, the use of more advanced methods of analysis does not appear necessarily to undermine the observed strength of association between urban built environment characteristics and obesity when compared to more commonly-used cross-sectional, single equation analyses. Given observed differences in the results of studies using different techniques, further consideration should be given to how evidence gathered from studies using different analytical approaches is appraised, compared and aggregated in evidence synthesis.The work was undertaken by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council (MRC), Medical Research Council, the National Institute for Health Research, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. David Ogilvie is also supported by the MRC [Unit Programme number MC_UU_12015/6].This is the final published version. It originally appeared at http://www.ijbnpa.org/content/11/1/142/abstract