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Indicators of quality of work as predictors of quality of life

Indicators of quality of work as predictors of quality of life. Alina Măriuca Ionescu, Alexandru Ioan Cuza University of Iași. Purpose of the paper.

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Indicators of quality of work as predictors of quality of life

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  1. Indicators of quality of work as predictors of quality of life Alina Măriuca Ionescu, Alexandru Ioan Cuza University of Iași

  2. Purpose of the paper • Relying on the idea that work represents an important dimension of individuals’ life, the paper aims to explore the extent to which one can identify good predictors of quality of life among the indicators of quality of work.

  3. Data About quality of work: • Data source: European Working Conditions Survey (EWCS). (www.eurofound.europa.eu). • Data on answers to 12 questions covering 7 dimensions of quality of work were extracted, both for 2005 and 2010, from EWCS database available on Eurofound website. • Extracted data cover EU27 countries, plus Norway, Croatia, Turkey and Switzerland in 2005 and EU27, Norway, Croatia, the Former Yugoslav Republic of Macedonia, Turkey, Albania, and Montenegro in 2010.

  4. Data

  5. Data For the assessment of quality of life: Four well-known composite indicators were considered: • Economist Intelligence Unit (EIU) Quality of Life Index [The Economist Intelligence Unit, 2005] (Calculated for 2005) • Satisfaction With Life Scale (SWLS) [Adrian G. White, 2006] (Available for 2006) • OECD Life Satisfaction Indicator (Extracted for 2009 from OECD database, www.oecdbetterlifeindex.org) • Human Development Index (HDI) [UNDP, since 1990] (Available both for 2005 and 2010) Apart from OECD Life Satisfaction Indicator, which misses data for 10 countries, all other three indicators of quality of life totally cover the samples.

  6. Method • A series of multiple linear regressions using stepwise algorithm (available in SPSS for Windows) were run within each set of quality of work indicators in order to identify the most relevant predictors of quality of life indicators.

  7. Results • Percentage of those who are very satisfied or satisfied with working conditions in their main paid jobis the main predictor both of EIU Quality of Life Index (R square = 0.429), of HDI 2005 (R square = 0.619) and of SWLS (R square = 0.61). Fig. 1: Quality of work indicators as predictors of EIU Quality of Life Index

  8. Results Fig. 2: Quality of work indicators as predictors of Satisfaction With Life Scale. Fig. 3: Quality of work indicators as predictors of Human Development Index (2005)

  9. Results Percentage of those who agree that their job offers them good prospects for career advancement explains 68.4% of the total variance in OECD Life Satisfaction indicator, while together with working hours - family/ social commitments outside work fit and proportion of those usually working less than 30 hours per week in their main paid job account for 79.5% of the total variance in the predicted variable. HDI 2010 values are the best predicted by the percentage of those who agree that they might lose their job in the next 6 months (R square = 0.624).

  10. Conclusion • If the dataset for 2005 shows the percentage of those who are very satisfied or satisfied with working conditions in their main paid job as the main predictor of all the three composite indicators of quality of life, the second dataset identifies substantial differences for different indicators of quality of life, as well as for the same indicator (HDI) at different moments (2005 and 2010). • Although there are indicators of quality of work which could explain high proportions of the variance in quality of life indicators, results don’t allow identifying a predictor that is stable both in time and among different measures of quality of life.

  11. Acknowledgements • This work was possible with the financial support of the Sectoral Operational Programme for Human Resources Development 2007-2013, under the project number POSDRU/89/1.5/S/49944 with the title Dezvoltarea capacităţii de inovare şi creşterea impactului cercetării prin programe post-doctorale.

  12. Thank you for your attention!

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