Hi there, I have a question that I hope will be simple for someone to answer.
I am working with panel data (2011-2016) at local authority (think of it as a different city) level within UK. My dependent variable is life satisfaction which is measured by asking the following question: Overall, how satisfied are you with your life, where 0 is 'not at all satisfied' and 10 is 'completely satisfied'. The life satisfaction score in my data set is an aggregated mean of the entire household for each local authority and most of my data is within the range of 7-8 value. Therefore, the dependent variable is a bounded scaled, which means that the maximum the life satisfaction can be is 10 and over time might not have a visible trend. I will attach a screenshot of how my dataset looks like..My main independent variable would be gross added value per head. With other independent variables being unemployment, life expectancy, obesity prevalence, Utilisation of outdoor space for exercise, violent crime and social isolation. I ran a –xtreg- command, for which the results were insignificant between my dependent and main independent variables. I think that I should address the problem that my dependent variable is bounded.
What statistical method for regression would be best to employ in such a case?
I am working with panel data (2011-2016) at local authority (think of it as a different city) level within UK. My dependent variable is life satisfaction which is measured by asking the following question: Overall, how satisfied are you with your life, where 0 is 'not at all satisfied' and 10 is 'completely satisfied'. The life satisfaction score in my data set is an aggregated mean of the entire household for each local authority and most of my data is within the range of 7-8 value. Therefore, the dependent variable is a bounded scaled, which means that the maximum the life satisfaction can be is 10 and over time might not have a visible trend. I will attach a screenshot of how my dataset looks like..My main independent variable would be gross added value per head. With other independent variables being unemployment, life expectancy, obesity prevalence, Utilisation of outdoor space for exercise, violent crime and social isolation. I ran a –xtreg- command, for which the results were insignificant between my dependent and main independent variables. I think that I should address the problem that my dependent variable is bounded.
What statistical method for regression would be best to employ in such a case?
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