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on Economics of Happiness |
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Issue of 2021‒07‒12
three papers chosen by |
| By: | Nie, Peng (Xi’an Jiaotong University); Li, Qiaoge (Xi’an Jiaotong University); Sousa-Poza, Alfonso (University of Hohenheim) |
| Abstract: | Using the 2012-2018 waves of the China Family Panel Studies, we investigate the impact of energy poverty (EP) on subjective well-being (SWB) among Chinese adults aged 18 and over. In addition to documenting EP rates in the range of 13.2% to 35.3% (dependent on measurement used), we show that EP lowers life satisfaction, with more pronounced impacts among males, the poor, and those residing in central regions. These results are robust to both alternative EP and SWB measures and to a series of estimation approaches that control for endogeneity. An additional structural equation modelling analysis of underlying mechanisms confirms that individual self-reported health, housing quality, and household food expenditure mediate the EP-SWB relation. |
| Keywords: | energy poverty, life satisfaction, happiness, depression, China |
| JEL: | I10 I12 R21 |
| Date: | 2021–05 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14429&r= |
| By: | Marsden, David |
| Abstract: | This paper seeks to contribute to the current debate about corporate governance and work relations in two ways: it extends the analysis to include employees’ subjective well-being and it considers a wider range of ownership models using Hansmann's typology as a guide. It argues that a key input into subjective well-being is provided by the scope to undertake work that is intrinsically as well as extrinsically rewarding. Rosen's theory of compensating wage differences is used as a lens to examine the problems of contracting over the intrinsic and extrinsic benefits of jobs as the former are largely intangible, whereas the latter are more easily codified and enforced. This asymmetry gives rise to moral hazard problems, which make the former more dependent on trust. Ownership models help to resolve this because they provide clear signals about an employer's value priorities, and its likely adherence to them after hiring. The study uses data from the British Workplace Employment Relations Survey. The results suggest that ownership models do indeed facilitate different trade-offs between intrinsic and extrinsic rewards that may be beneficial to many workers, warranting more attention to alternative forms of ownership to promote greater employee well-being. |
| Keywords: | Wiley deal |
| JEL: | R14 J01 |
| Date: | 2021–04–13 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:109009&r= |
| By: | Mateusz Kijewski (Faculty of Economic Sciences, University of Warsaw); Szymon Lis (Faculty of Economic Sciences, University of Warsaw); Michał Woźniak (Faculty of Economic Sciences, University of Warsaw); Maciej Wysocki (Faculty of Economic Sciences, University of Warsaw) |
| Abstract: | Current scientific knowledge allows us to assess the impact of socioeconomic variables on musical preferences. The research methods in these studies were psychological experiments and surveys conducted on small groups or analyzing the influence of only one or two variables at the level of the whole society. Instead inspired by the article of The Economist about February being the gloomiest month in terms of music listened to, we have created a dataset with many different variables that will allow us to create more reliable models than the previous datasets. We used the Spotify API to create a monthly dataset with average valence for 26 countries for the period from January 1, 2018, to December 1, 2019. Our study almost fully confirmed the effects of summer, December, and number of Saturdays in a month and contradicted the February effect. In the context of the index of freedom and diversity, the models do not show much consistency. The influence of GDP per capita on the valence was confirmed, while the impact of the happiness index was disproved. All models partially confirmed the influence of the music genre on the valence. Among the weather variables, two models confirmed the significance of the temperature variable. All in all, effects analyzed by us can broaden artists' knowledge of when to release new songs or support recommendation engines for streaming services. |
| Keywords: | valence, spotify, happiness, statistical panel analysis, explainable machine learning |
| JEL: | C01 C23 I31 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:war:wpaper:2021-12&r= |