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Does Development Increase Level of Happiness?

Does Development Increase Level of Happiness?. Grace Choi gc7186b@american.edu American University School of International Service. Research Question & Research hypothesis. Research Question:

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Does Development Increase Level of Happiness?

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  1. Does Development Increase Level of Happiness? Grace Choi gc7186b@american.edu American University School of International Service

  2. Research Question & Research hypothesis • Research Question: Does gender, age, level of income, education, and development influence happiness and explain change in the suicide rate of South Korea? • Research hypotheses: • Males will have greater feelings of unhappiness • Younger groups will be less happy • People with higher income will be happier • Education: more educated groups will express unhappiness • people in rural areas will be happier

  3. Background Info/ Lit. Review • Theory #1: WHO data of injury mortality rate; suicides deaths are higher than deaths caused by violence or conflict and war. Furthermore, “suicide mortality rate has shifted from Western Europe to Eastern Europe and now has shifted to Asia.” (PeeterVarnik 2012) • Findings : Suicide in Asia is about 500 thousand out of 782 thousand deaths world wide. Asian countries like South Korea and Japan continue to experience a rising suicide trend while European region experiences a decline • Theory #2: World Bank’s annual PPP-adjusted GDP per capita verses suicide statistics from mortality database between 1980 and 2007 (Blasco-Fontecilla H, Perez-Rodriguez MM, Garcia-Nieto R, et al, 2011) • Findings : European countries and wealthier developing countries saw a decline in suicide rates; in high income developing countries in Asia, South Korea and Japan were an exception with a rising trend • Theory #3: Health at a Glance 2011: OECD Indicators • Findings : South Korea has the highest suicide rate amongst all OECD countries; beats OECD average, 28 to 11.3 per 100,000 • Gaps in Theories?? Various studies discusses the global trend in suicide rates but fails to examine variables that may influence the rising trend of suicide rate in Asia, particularly South Korea, with the highest suicide rate.

  4. Data • Unit of analysis/study : South Korea • Source of the data: Pew Data 2011 • Reliability of the data: data collected from a sample of 706 people (representation too small; may not necessarily reflect the overall population) • Dependent variable/s • Happiness/ life’s contentment • Binary measurement: happy with how things are going in you life? dissatisfied (0) verses satisfied (1) • Independent Variable • Gender: Male (1), Female (2) • Age: 18-75 • Education: Primary & below (1), Junior High (2), at least highschool (3), college (4) • Income: Low income (1), middle income (2), mid-high income (3), High income (4) • Urbanity: Metropolitan (1), small/medium city (2), rural (3)

  5. Descriptive Statistics Table or/and Graphics

  6. Bivariate analysis - Categorical LOM • Report Table with Gama/Lambda/Chi square statistic for association of ordinal/nominal data. • Report Table with T test/F test statistic for association of ordinal/nominal dependent variable and I-R variables. • Interpretation of reported statistics in these tables: • i)Does the association/ exists, i.e. is your measure of association/correlation statistically significant? • ii) If the association/correlation exists how strong it is? Check the value of the gamma or lambda statistic; • iii) What is the direction of the association? Remember that this is for gamma statistic, for I_R and ordinal LOM variables only. • Remember that chi square and lambda/gamma statistics may show ambiguous results, i.e. On of the measures suggest associations and the other suggests no association.

  7. Probit Regression: Effects & Estimates • Interpretations: • i) coefficient >.05 • ii) adj. R square statistics are too small • iii) based on sample (N) the Chi-squared is too small * p<0.05, ** p<0.01, *** p<0.001

  8. Findings & Policy Implications of the Research • Findings: All independent variables that measure rate of development are not associated with the rate of happiness for South Koreans • Reject research hypothesis; development does NOT lead people to live happier lives in South Korea • What are the policy implications? • Consider development in relation to culture. How has development impacted South Korean culture? • Possible future study: increased in development= increased in the level of anxiety? • Recognize mental health as an issue and figure out what social factors contribute to high level of unhappiness. Develop a unique model for South Koreans to live happier lives!

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