The economics of happiness: does smoking behaviour bring life (dis)satisfaction

In the probit estimation we cannot interpret the coefficients in a similar way to the OLS estimation, here we will only look at the signs of the coefficients of the corresponding variables. By observing the obtained results from Table 3 given above, we can notice that all the coefficients are of the expected sign apart from dummy, but this is consistent with OLS estimation output for this variable and the explanation for such an outcome was given in the OLS interpretation. Compared to the OLS, now dummy becomes insignificant. In addition to is also insignificant. Except for these two dummies all the other variables are significant and of the anticipated sign. Overall, it is critical to mention that the coefficients of the ordered probit model are actually greater in size compared to those of the OLS which is consistent with the research of Awaworyi Churchill and Farrell (2017).

Nevertheless, we are able to obtain the marginal effects that all the explanatory variables included in the ordered probit have on the life satisfaction. With their benefit some interpretation of the outcomes can be provided.

Table 4. Marginal effects of the variables on life satisfaction (Source: received from STATA MP)

Table 4 Note: screenshots of marginal effects are provided in Appendix 5.

According to the Table 4 provided above, the resulting marginal effects which are connections of a certain variable in the model with life satisfaction are consentient to the anticipated links and the connection of smoking status to satisfaction with life does not change with using this method of estimation to the previously applied methods like OLS and Lewbel's IV.

Moving on to the interpretation of the given outcomes, we obtain the following: if an individual currently smokes, they have a higher chance (3.99%) of being reported as not very satisfied with their life. What is more, if a person has a job (employed=1), they are about 4.85% more probably to be identified as more likely satisfied. On the contrary, the married respondents compared to those who are single, widowed, divorced or not cohabiting are approximately 7.31 percentage points more probably to be described as more likely satisfied.

Apart from that, those who are in good or excellent health in contrast to those who are in poor, very poor or average health are around 4.4% more likely to fall into the category of fully satisfied with life. However, those who experience stress in comparison with those who do not are approximately 3.88 percentage points less likely to be fully satisfied and about 11.54% less likely to be reported as more likely satisfied. In addition, a person who resides in a city with population over 1000000 people are around 2.4 percentage points more likely to be identified as not very satisfied and 1.27% more probably to be classified as completely dissatisfied. What is more, if a person has consumed any alcoholic beverages for the past 30 days, they are only 1.04% more likely to report being completely satisfied. Furthermore, as age rises, a respondent becomes less satisfied with their life. Particularly, as age rises by one year, a person is 1.76% less likely to be more likely satisfied with their life and almost 13.12% more likely to be not very satisfied with life. Additionally, with a rise in the logarithm of income per head in the household by 1 unit, an individual is 4.98% more likely to be completely satisfied and 8.2 percent less likely to be classified as not very satisfied. Also, if a number of children that an individual has increases by 1 unit, they are 2.13% more probably to be more likely satisfied with life. It is assumed that any shifts in a certain variable in average terms, all other variables kept constant.

Conclusion

The key incentive of this thesis consisted in establishing whether current smokers in Russia are most probably to bear diminished contentment with living as distinguished from those respondents that have a negative attitude towards smoking and are not in the habit of smoking tobacco. The outcomes from Russian Longitudinal Monitoring Survey for 2016 depict that approximately half the respondents are content with their life, while 27.26% of them currently smoke. In addressing the issue of nicotine addiction, the investigation of this link and the obtained outcomes of this research might be used to update the existing measures trying to constrain smoking in Russia such as anti-tobacco regulations and government health programs. This paper contributes new findings of the impact of smoking behavior on life satisfaction in Russia and other emerging countries. Particularly, by applying different methodological approaches as an attempt for robustness check including ordered probit and OLS kinds of estimation as well as a brand-new Lewbel (2012)'s instrumental variable approach helping to deal with the endogeneity problem and apart from that a wider set of controls including drinking, vulnerability to stress and self-reported health level, I found that those who currently smoke do tend to report being less content with the quality of their life as opposed to non-smokers. These results are concordant with the study of Awaworyi Churchill and Farrell (2017) conducted on the English sample who also stated that smoking habit and smoking addiction are indeed related to reduced levels of subjective wellbeing or happiness regardless of the method of estimation used. Furthermore, these outcomes are as well constituent with the findings of Wilmans and Rashied (2020) who conclude that smoking behavior in a developing state significantly negatively affects subjective welfare of its residents, notably, smokers in South Africa are not so likely to have greater levels of happiness in comparison with non-smokers. However, the findings of my work are at variance with the conclusions drawn in the scientific publication of Chang et al. (2016) that show that smoking addiction brings about higher levels of happiness to smokers as opposed to non-smokers. This distinction might be explained by variations in the sample chosen for the analysis that includes the macro data of several nations as well as the problem of endogeneity not handled in their research as the endogeneity problem might lead to the biased magnitude and direction of coefficients of variables. Another reason might be that emotional wellbeing advantages can potentially overshadow the drawbacks of physical health and this way people self-select tobacco consumption.

Overall, from the outcomes of this research paper it might be concluded that nicotine dependence does have a tremendous adverse influence on life satisfaction and actions ought to be taken to tackle this damage by further identifying the underlying triggers.

Nevertheless, this study might have its limitations due to the absence of a good external instrumental variable which might have been used for the instrumental variable approach. Specifically, the potential theoretical instrument for smoking which is the logarithm of cigarette prices for which each particular respondent buys cigarettes that is assumed to be correlated with smoking status and not correlated with life satisfaction does not have enough data to be able to run an IV regression with it and get the outcomes controlling for the endogeneity. Moreover, the panel data analysis might have been employed, however, over the matter of autocorrelation together with heteroskedasticity hurdles prevailing within the data an IV estimation method does not give us efficient estimates as it does so only in the case of homoscedasticity.

Further research might involve panel data analysis with application of instrumental variables to tackle the endogeneity issue in order to see whether the change in smoking behavior within one individual leads to the changes in levels of happiness.

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Appendix

Descriptive statistics for cross-section 2016 (received from STATA MP):

OLS estimation results (received from STATA MP):

Instrumental variables 2SLS estimation results(received from STATA MP):

Ordered probit estimation results (received from STATA MP):

Marginal effects for ordered probit (received from STATA MP):

All estimation results in one table:

Note for Appendix 6: ***significant at 1 %, **significant at 5%, *significant at 10% and robust standard errors are given in parentheses, the signs are reversed when interpreting the effect of variables on life satisfaction.

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