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Quantitative Methods in Social Sciences (E774)

Quantitative Methods in Social Sciences (E774). Swiss socio-economic development: More than just money ! Julia Federico Hao Li Claudia Möri Elisabeth Schaffer 4 December 2009. Public health. MORT. LE. PHYPC. BIRDS. CO2. FOSFU. WOMPAR. WAGEWM. WPST. MOBP. INTU.

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Quantitative Methods in Social Sciences (E774)

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  1. Quantitative Methods in Social Sciences (E774) Swiss socio-economic development: More than just money ! Julia Federico Hao Li Claudia Möri Elisabeth Schaffer 4 December 2009

  2. Public health MORT LE PHYPC BIRDS CO2 FOSFU WOMPAR WAGEWM WPST MOBP INTU Introduction • There is a significant socio-economical improvement between the two time periods in Switzerlangd (Ho: µ1 = µ2; Ha1: µ1 < µ2 and Ha2 : µ1 > µ2 • Indicators for socioeconomic standing of Switzerland 1990-2007 • Indicators for 4 sectors: • Missings in both time periods • Reliability: No information about the collection of the data QM_MDEV_E774(2009)

  3. Testing the hypothesis • Calculate the means & compare the changes • Two-mean-test to check whether there is a significant difference between the means • Check correlation between income & other socio-economic indicators & do regression analysis QM_MDEV_E774(2009)

  4. Background policy information • Federal Health Insurance Act of 18 March 1994 (“LAMal”) made basic health insurance mandatory • Swiss Law of CO2 2000: By 2010, CO2 emissions from burning fossil energy sources have to drop 10% below the level of 1990. This signifies 4 million tons less of CO2 • Federal Gender Equality Act (1995): Increase both in data available and women's wages QM_MDEV_E774(2009)

  5. Sampling & mean Sampling: two time periods; picking out the relevant variables (criteria: socio-economic indicators with improvement over time) Compare the means of the two time periods Source: Swiss Socio-Economic Data 2009 QM_MDEV_E774(2009)

  6. Two sample mean test Ho: µ1 = µ2; Ha1: µ1 < µ2 Table 2: Comparingthe means of BIRD STATA command: ttest bird == bird2,unpaired QM_MDEV_E774(2009)

  7. Correlation: Pearson‘s r Ho=rxy=ryx=0 r is the correlation coefficient r2 is the explanatory power of the set of x-variables Source: Swiss Socio-Economic Data 2009 Note: No data for the year 2007 is available and data for wpst for 1990 is missing. Small p-value implies stronger evidence against Ho QM_MDEV_E774(2009)

  8. Regression • Test the relationships between x and y variables (how does the mean y change according to the value of x) • We assume a linear regression model: Y=α+βx • Small p-value for Ho means that the regression line does not have a zero slope • In our case, y was income, x-variables were for example LE, MORT and PHYPC. Source: Swiss Socio-Economic Data 2009 QM_MDEV_E774(2009)

  9. Results Policy Paper 1 Comparison of Two Time Period Means, 1990-1999 and 2000-2007 Source: Swiss Socio-Economic Data 2009 QM_MDEV_E774(2009) QM_MDEV_E774(2009)

  10. Results Policy Paper 2 Table 3: Two sample mean test for variable CO2 (both time periods) Source: Data_3 Swiss Given Data Notes: diff = mean(co2) - mean(co22) t = 2.3287 Ho: diff = 0 degrees of freedom = 13 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9817 Pr(|T| > |t|) = 0.0367 Pr(T > t) = 0.0183 QM_MDEV_E774(2009)

  11. Results Policy Paper 3 How do our variables relate with national income (GDP per capita) at the two time periods? Scatter plot of GDP, WPST, MOBP, and INTU 2000-2007 Source: Swiss Socio-Economic Data 2009 Source: Swiss Socio-Economic Data 2009 QM_MDEV_E774(2009)

  12. Results Policy Paper 3 Correlation Coefficients (Pearson’s r) and Coefficients of Determination (r^2) for Socioeconomic Indicators and GDP per capita at two time periods Source: Swiss Socio-Economic Data 2009 QM_MDEV_E774(2009)

  13. Regression Finding the best fitted line STATA command: reg gdp2 wpst2 Plotting the regression GDP per capita on WPST (2000-2007) Residuals versus fitted graph, GDP/capita on WPST (2000-2007) STATA command: avplot wpst2 STATA command: rvfplot, yline(0) QM_MDEV_E774(2009)

  14. Conclusions Looking at social indicators as measurements of wellbeing Significant socioeconomic improvements Correlation coefficients between income and other indicators are not statistically significant Reduce fossil fuels and pay discrimination between men and womenfossil fuels and pay discrimination between men and women QM_MDEV_E774(2009)

  15. Future work • Shortcomings of dataset: incomplete data • Missing elements of research and analysis: examine indicators which showed negative growth • Possible areas of future research: identify direction of causality between different social and economic indicators QM_MDEV_E774(2009)

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