Page 81 |
Save page Remove page | Previous | 81 of 171 | Next |
|
small (250x250 max)
medium (500x500 max)
Large (1000x1000 max)
Extra Large
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
|
72
verify that the results are consistent, I run the baseline regressions using ordered probit
and OLS. All of the female-male differences in life satisfaction that are significant in
OLS regressions are also significant in the order probit regressions. Greece and
Lithuania are the only countries where the differences are significant in the ordered probit
regression and not in the OLS regression.
Because the number of observations changes depending on the variables included
in the analysis, the coefficients on female from the regressions with controls are always
compared to the coefficients on female when there are no controls, after restricting the
number of observations to that in the controls case. For example, when I present the
results for equation (2.2) against equation (2.1), I plot the coefficients from (2.2) against
the coefficients from a regression of life satisfaction on female without controls for
observations where age, marital status, and education level are also available.
It is possible that the observations that are dropped in each specification are not
random and could bias the results. Therefore, I do a Wald test of the equality of the
female-male differences in life satisfaction in the baseline regressions with all
observations and with only the observations available with controls. For each
specification, I cannot reject the null hypothesis that the no-controls coefficients are equal
to the no-controls coefficients limited to the observations available when the control
variables are included in the specification.
Concern that the missing observations are non-random is particularly important
when the economic variables are included in the model. It is possible that the income
variable would be missing more for women than for men. If that is true, and the women
72
Object Description
| Title | Essays on health and well-being |
| Author | Zweig, Jacqueline Smith |
| Author email | smith2@usc.edu; jackiesmith04@yahoo.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Economics |
| School | College of Letters, Arts and Sciences |
| Date defended/completed | 2011-03-23 |
| Date submitted | 2011 |
| Restricted until | Restricted until 26 Apr. 2012. |
| Date published | 2012-04-26 |
| Advisor (committee chair) |
Easterlin, Richard A. Ham, John C. |
| Advisor (committee member) | Melguizo, Tatiana |
| Abstract | This dissertation is comprised of three chapters that use microeconometric techniques to investigate the factors that affect people’s well-being. In the first two chapters, well-being is defined as life satisfaction or health satisfaction. The first chapter explores how the movement from socialism to capitalism affected the life satisfaction and health satisfaction of East Germans relative to West Germans after reunification. The second chapter examines whether women are happier, less happy, or equally happy as men in countries at various stages of development. The third chapter examines whether pollution affects the academic performance of school children; their academic performance and achievements will have important implications for their future well-being. |
| Keyword | happiness; well-being |
| Geographic subject | Germany |
| Geographic subject (state) | California |
| Geographic subject (country) | USA |
| Coverage date | 1990/2010; 2002/2008 |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m3782 |
| Contributing entity | University of Southern California |
| Rights | Zweig, Jacqueline Smith |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Zweig-4500 |
| Archival file | uscthesesreloadpub_Volume23/etd-Zweig-4500.pdf |
Description
| Title | Page 81 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 72 verify that the results are consistent, I run the baseline regressions using ordered probit and OLS. All of the female-male differences in life satisfaction that are significant in OLS regressions are also significant in the order probit regressions. Greece and Lithuania are the only countries where the differences are significant in the ordered probit regression and not in the OLS regression. Because the number of observations changes depending on the variables included in the analysis, the coefficients on female from the regressions with controls are always compared to the coefficients on female when there are no controls, after restricting the number of observations to that in the controls case. For example, when I present the results for equation (2.2) against equation (2.1), I plot the coefficients from (2.2) against the coefficients from a regression of life satisfaction on female without controls for observations where age, marital status, and education level are also available. It is possible that the observations that are dropped in each specification are not random and could bias the results. Therefore, I do a Wald test of the equality of the female-male differences in life satisfaction in the baseline regressions with all observations and with only the observations available with controls. For each specification, I cannot reject the null hypothesis that the no-controls coefficients are equal to the no-controls coefficients limited to the observations available when the control variables are included in the specification. Concern that the missing observations are non-random is particularly important when the economic variables are included in the model. It is possible that the income variable would be missing more for women than for men. If that is true, and the women 72 |
