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Relationship Between Job Satisfaction and Hours Worked per Week (between age 15-64)
Data Source: https://forscenter.ch/projects/swiss-household-panel/documentation/
Provide summary statistics for your estimation sample
– Table of summary stats (mean, median, sd, min, max, etc.)
– Visualize the outcome (y) and main explanatory variable of interest (x) using histograms, density plots, box plots, etc.
– Descriptive evidence on the relationship of interest: summary statistics and suitable graphs by groups (e.g. histograms or density plots of health status by sports engagement; show mean health status by sports; scatterplots of x and y)
Explicitly show and discuss your estimation equation/approach (e.g. MLR, Fixed effects) Example: y = ß0 +ß1×1 +ß2×2 +…+ßkxk +u
Discuss the (implicit) assumptions you make by using the empirical approach you choose
Critically assess the limitations of your empirical approach
– Is it plausibel to assume that MLR.4 (strict exogeneity) is satisfied in your setup (i.e. are those doing sports directly comparable to those who do not)? Why or why not?
– How do you deal with selection issues and corresponding bias in your estimation approach (i.e. how do you reduce potential biases)? How do you finally interpret your findings? Can you use a causal interpretation?
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