There is strong evidence that subjective well-being measures capture in a reliable way specific components of well-being that other non-subjective measures miss. The question of whether subjective well-being is policy amenable is however still largely unexplored in the research. This paper sheds some light on this issue, by looking at the impact of selected labour market and health policies on subjective well-being, using well-being data from the Gallup World Poll on the 34 OECD countries. The paper finds that the generosity of unemployment benefits and the strictness employment protection legislation affects positively life satisfaction, while out-of-pocket health expenses significantly reduce subjective well-being.
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The OECD Better Life Initiative defines well-being in terms of eleven dimensions: income and wealth, jobs and earnings, housing, work and life balance, education and skills, social connections, civic engagement and governance, environmental quality of life, personal security and subjective well-being.
There is a fourth dimension of subjective well-being, eudemonic well-being, which is not covered in this paper.
Despite this, Kahneman and Krueger (2006) argue that measures of affect are, in principle, preferable to measures of life evaluation for policy purposes, as they have better inter-personal comparability and because measures of affect capture the impact of life circumstances on what people actually experience.
Testing for the impact of culture on cross-country differences in average life satisfaction is difficult, as there is no obvious simple method for distinguishing between cultural effects due to culture and those due to some other unobserved country-specific variable. Fleche et al. (2011), use data from the World Values Survey to explore the degree to which country-specific differences in the weights attached to different drivers of well-being affect how countries are ranked in terms of average life satisfaction. They find that heterogeneity in the country-specific weightings assigned to the determinants of life satisfaction has little effect on how countries are ranked.
Among others, Nobel Prize laureate Daniel Kahneman (Eugene Higgins Professor of Psychology at the Woodrow Wilson School at Princeton University), Jeffrey D. Sachs (Director of The Earth Institute, Quetelet Professor of Sustainable Development and Professor of Health Policy and Management at Columbia University) and Angus Deaton (Dwight D. Eisenhower Professor of International Affairs, and Professor of Economics and International Affairs at the Woodrow Wilson School and Department of Economics, Princeton University).
The Gallup Organization generally employs in-person interviews in developing countries and telephone surveys in developed countries where telephone coverage is at least 80 % of the population. The sample is ex-ante designed to be nationally representative of the entire population aged 15 and over (including rural areas), but non-random response patterns are a likely source of ex-post bias. This issue is addressed by the post-stratification weights provided by Gallup.
The data refer to the OECD series: Net replacement rates (NRR) over a 5-year period following unemployment, 2001–2009; as available in OECD (2011).
While health co-payments will also have behavioural effects, these are less obvious than is the case for labour market policy and there is no obvious variable that can be included to control for them.
Ferrer-i-Carbonell and Frijters (2004) who investigated this issue in more detail conclude that, in practice, there is little difference between OLS estimates of subjective well-being functions and theoretically preferable methodologies such as Probit regression.
In the first waves of the survey there was no specific question asking whether people where unemployed or not, as the question was phrased “Do you work or not”.
There is no obvious reason why including employment protection legislation and health co-payments in the model should have this effect, and it is likely that this simply results from the truncated sample of country/year observations included in regression (6). A regression on the same sample but without the inclusion of EPL or Health co-payments finds the unemployment rate not significant at all, suggesting that the truncated sample of country year observations is a problem for this variable.
The policy results in this article are based off only four waves of data, giving a maximum of three policy transitions per country for each policy variable. In practice, the results are driven by a much smaller set of transitions—particularly in the area of employment protection legislation where change occurs only through the legislative process (replacement rates are affected by changes in earned income as well as the underlying rules of the social insurance system).
Boarini, R., Comola, M., Smith, C., Manchin R., & De Keulenaer, F. (2012). What makes for a better life? The determinants of subjective well-being in OECD countries: evidence from the Gallup world poll. OECD Statistics Directorate Working Paper 47.
Carinna, G., Evans, D., Ravindal, F., & Xua, K. (2009). Assessing the reliability of household expenditure data: Results of the World Health Survey. Health Policy, 91, 297–305.
Chapple, S., & D’Addio, A. (2013). Social policy reforms and their impact on subjective well-being. Unpublished.
Di Tella, R., MacCulloch, R., & Oswald, A. (2003). The Macroeconomics of happiness. The Review of Economics and Statistics, 85(4), 809–827.
Diener, E., Scollon, C. K. N., Oishi, S., Dzokoto, V., & Suh, E. M. (2000). Positivity and the construction of life satisfaction judgements, global happiness is not the sum of its parts. Journal of Happiness Studies, 1, 159–176.
Diener, E., & Tov, W. (2012). National accounts of well-being. Handbook on social indicators and quality of life research (pp. 137–157). Berlin: Springer.
Dolan, P., & Metcalfe, R. (2008). Comparing willingness-to-pay and subjective well-being in the context of non-market goods. CEP Discussion paper No 890. London School of Economics.
Dolan, P., Peasgood, T., & White, M. (2008). Do we really know what makes us happy? A review of the economic literature on the factors associated with subjective well-being. Journal of Economic Psychology, 29, 94–122.
Dolan, P., & White, M. P. (2007). How can measures of subjective well-being be used to inform public policy? Perspectives on Psychological Science vol, 2(1), 71–85.
Eid, M., & Diener, E. (2004). Global judgements of subjective well-being: Situational variability and long-term stability. Social Indicators Research, 65, 245–277.
Ferrer-i-Carbonell, A., & Frijters, P. (2004). How important is methodology for the estimates of the determinants of happiness? The Economic Journal, 114, 641–659.
Fleche, S., Smith, C., & Sorsa, P. (2011). Exploring determinants of subjective well-being in OECD countries: Evidence from the World Values Survey. OECD Statistics Directorate Working Paper 46.
Frey, B. S., & Stutzer, A. (2000). Happiness, economy and institutions. The Economic Journal, 110, 918–938.
Frey, B. S., & Stutzer, A. (2005). Happiness research: State and prospects. Review of Social Economy, 63(2), 207–228.
Greve, B. (ed). (2010). Happiness and Social Policy in Europe. Edward Elgar Publishing.
Harmatz, M. G., Well, A. D., Overtree, C. E., Kawamura, K. Y., Rosal, M., & Ockene, I. S. (2000). Seasonal variation of depression and other mood: A longitudinal approach. Journal of Biological Rhythms, 15(4), 344–350.
Helliwell, J. F. (2008). Life satisfaction and the quality of development. NBER Working Paper No 14507, National Bureau of Economic Research.
Kahneman, D., & Krueger, A. B. (2006). Developments in the measurement of subjective well-being. Journal of Economic Perspectives, 20(1), 19–20.
Kroh, M. (2006). An experimental evaluation of popular well-being measures. German Institute for Economic Research Discussion Paper 546. January 2006, Berlin.
Krueger, A. B., & Schkade, D. A. (2008). The reliability of subjective well-being measures. Journal of Public Economics, 92(8–9), 1833–1845.
Lucas, R. (2007). Long-term disability is associated with lasting changes in subjective well-being: Evidence from two nationally representative longitudinal studies. Journal of Personality and Social Psychology, 92(4), 717–730.
Lucas, R. E., & Lawless, N. M. (2011). Predictors of regional well-being: A county-level analysis. Social Indicators Research, 101, 341–357.
Ochsen, C., & Welsch, H. (2012). Who benefits from labor market institutions? Evidence from surveys of life satisfaction. Journal of Economic Psychology, 33(1), 112–124.
OECD. (2011). Benefits and wages: Statistics, directorate for employment, labour, and social affairs. Paris: OECD.
OECD. (2013). OECD guidelines for the measurement of subjective well-being. Paris: OECD Publishing.
Rässler, S., & Riphahn, R. T. (2006). Survey item nonresponse and its treatment. Allgemeines Statistisches Archiv, 90, 217–232.
Stiglitz, J. E., Sen, A., & Fitoussi, J. P. (2009). Report by the Commission on the Measurement of Economic Performance and Social Progress, http://www.stiglitz-sen-fitoussi.fr/documents/rapport_anglais.pdf.
A longer version of this paper is in Boarini et al. (2012).
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Boarini, R., Comola, M., de Keulenaer, F. et al. Can Governments Boost People’s Sense of Well-Being? The Impact of Selected Labour Market and Health Policies on Life Satisfaction. Soc Indic Res 114, 105–120 (2013). https://doi.org/10.1007/s11205-013-0386-8
- Life satisfaction
- Labour market policy
- Health policy
- Subjective well-being