Structural Equation Modelling and the Causal Effect of Permanent Income on Life Satisfaction: The Case of air Pollution Valuation in Switzerland

Giovanis, Eleftherios; Özdamar, Öznur

doi:10.1002/9781119328223.ch3

Cited by 13 publications

(22 citation statements)

References 88 publications

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“…This pattern is also consistent with the education and matching skills to job. More specifically, those with first degree in some cases report lower levels of job satisfaction, which is consistent with other studies, arguing that more educated people have higher expectations about their pecuniary and non-pecuniary returns form their job and thus are more easily disappointed and dissatisfied Hamermesh, 2000;Giovanis and Ozdamar, 2016). The same applies with the matching skills to job.…”

Section: Ols Estimatessupporting

confidence: 87%

Do the flexible employment arrangements increase job satisfaction and employee loyalty Evidence from Bayesian networks and instrumental variables

Giovanis

2019

IJCEE

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This study explores the relationship between job satisfaction, employee loyalty and two types of flexible employment arrangements; teleworking and flexible timing. The analysis relies on data derived by the Workplace Employee Relations Survey (WERS) in 2004 and 2011. We apply the propensity score matching approach and least squares regressions. Furthermore, we employ the Bayesian Networks (BN) and Directed Acyclic Graphs (DAGs) to confirm the causality between employment types explored and the outcomes of interest. Additionally, we propose an instrumental variables (IV) approach based on the BN framework. The results support that a positive causal effect from these employment arrangements on job satisfaction and employee loyalty is present.

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Section: Ols Estimatessupporting

confidence: 87%

Do the flexible employment arrangements increase job satisfaction and employee loyalty Evidence from Bayesian networks and instrumental variables

Giovanis

2019

IJCEE

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“…This suggests that as the income is increased, the income inequality initially is increased as well up to a certain point and thereafter pollution starts to decline. The majority of the studies exploited panel data based on country level and they found that the EKC hypothesis holds Krueger, 1991, 1995;Panayotou, 1997;Selden and Song, 2004;Vollebergh et al, 2009;Giovanis, 2013;Bölük and Mert, 2014;Giovanis and Ozdamar, 2016;Sinha, 2006;Sinha and Sudipta, 2016Sinha and Bhattacharya, 2016, 2017. Thus, the correlation standalone is not enough to reveal the relationship between income and pollution, where a quadratic relationship between air pollution and income may be present.…”

Section: Summary Statisticsmentioning

confidence: 99%

“…Furthermore, there is no detailed recording for other pollutants in every monitoring station and along the period examined, including P b , Z n and NO 3 -. For example the studies by Krueger (1991, 1995), Panayotou (1997), Selden and Song (2004), Vollebergh et al (2009), Giovanis and Ozdamar (2016), Sinha andBhattacharya (2016, 2017), include income and population density as main factors of air pollution. Since our variables are based on individual and household level, household size is used as a proxy for the population density, as we have mapped the air pollution on municipality level.…”

Section: Datamentioning

confidence: 99%

“…According to earlier studies we implement fixed effects models since we have location-municipality fixed effects and using the control variables that we explore in more details in the data section (Jones, 2009;Lavain, 2015;Giovanis and Ozdamar, 2016;Sinha andBhattacharya, 2016, 2017).…”

Section: Fixed Effectsmentioning

confidence: 99%

“…A similar explanation can be given for the education level and age, where the older, more educated and more experienced workers are more likely to telework. Income is an important factor, according to the environmental Kuznets curve (EKC) hypothesis, where the air quality is deteriorated up to a certain point and after this point is improved Krueger, 1991, 1995;Panayotou, 1997;Selden and Song, 2004;Vollebergh et al, 2009;Giovanis and Ozdamar, 2016;Sinha andBhattacharya, 2016, 2017). Household size and marital status can be related to traffic, as larger households may make more use of transportation leading to higher levels of air pollution.…”

Section: Datamentioning

confidence: 99%

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Teleworking Effect on Traffic and Air Pollution

Giovanis¹

2017

Preprint

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Traffic congestion is one of the foremost problems confronted by the urban and suburban tenants of today. Traffic congestion increases vehicle emissions and degrades air quality. Urban planners and policy makers have consequently been always investigating choices to alleviate traffic congestion and to enhance air quality. Teleworking is one option that has received significant consideration and has been studied in the recent past. The aim of the study is to explore the relationship between teleworking, air quality and traffic in Switzerland. The analysis relies on panel individual and household level data over the period 2002-2013. We examine five main air pollutants; the sulphur dioxide (SO 2 ), the ground-level ozone (O 3 ) the nitrogen dioxide (NO 2 ), the carbon monoxide (CO) and the particulate matter less than 10 microns (PM 10 ). Based on the fixed effects estimates, teleworking reduces traffic volume by 1.9 per cent. Furthermore, the reduction observed on air pollution is higher for NO 2 , CO and PM 10 ranging between 3.3-3.7 per cent, followed by O 3 at 2.3 per cent and SO 2 at 2.1 per cent. According to instrumental variable (IV) approach and the two stage least squares (2SLS) method, the effect is higher ranging between 2.6-4.1 per cent. The respective reduction on traffic becomes 2.7 per cent. Overall, the main concluding remark of the study is that teleworking can be a promising tool for urban planning and development, focusing at the traffic volume reduction, and the air quality improvement. Additional policy implications of teleworking and its beneficial effects for the society are further discussed.

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Worthy to lose some money for better air quality: applications of Bayesian networks on the causal effect of income and air pollution on life satisfaction in Switzerland

Giovanis

2018

Empir Econ

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One important determinant of well-being is the environmental quality. Many countries apply environmental regulations, reforms and policies for its improvement. However, the question is how the people value the environment, including the air quality. This study examines the association between air pollution and life satisfaction using the Swiss Household Panel survey over the years 2000-2013. We follow a Bayesian network (BN) strategy to estimate the causal effect of the income and air pollution on life satisfaction. We look at five main air pollutants: the ground-level ozone (O 3), sulphur dioxide (SO 2), nitrogen dioxide (NO 2), carbon monoxide (CO) and particulate matter of 10 micrometres (PM 10). Then, we calculate the individuals' marginal willingness to pay (MWTP) of reducing air pollution that aims to improve their life satisfaction. Beside the BN model, we take advantage of the panel structure of our data and we follow two approaches as robustness check. This includes the adapted probit fixed effects and the generalised methods of moments system. Our findings show that O 3 and PM 10 present the highest MWTP values ranging between $8000 and $12,000, followed by the remained air pollutants with MWTP extending between $2000 and $6500. Applying the BNs, we find that the causal effect of income on life satisfaction is substantially increased. We also show the causal effects of air pollutants remain almost the same, leading to lower values of willingness to pay.

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Structural Equation Modelling and the Causal Effect of Permanent Income on Life Satisfaction: The Case of air Pollution Valuation in Switzerland

Cited by 13 publications

References 88 publications

Do the flexible employment arrangements increase job satisfaction and employee loyalty Evidence from Bayesian networks and instrumental variables

Do the flexible employment arrangements increase job satisfaction and employee loyalty Evidence from Bayesian networks and instrumental variables

Teleworking Effect on Traffic and Air Pollution

Worthy to lose some money for better air quality: applications of Bayesian networks on the causal effect of income and air pollution on life satisfaction in Switzerland

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