Hello,
I'm working on a project testing the strength of the Phillips curve, but am very unfamiliar with STATA and panel data econometrics.
I'd like to test the relation between unemployment and inflation (CPI) and see if the relationship is still significantly significant post-financial crisis, compared to pre.
I've never conducted panel data analysis, and have little experience with STATA.
I've gathered CPI and Unemployment data from Jan 1983-Feb2017 for 10 provinces in Canada and cleaned the data on an excel file.
My data:
10 provinces, dates (monthly starting Jan 1983), unemployment rate (monthly), and CPI (monthly)
I've attached a spreadsheet for reference.
https://docs.google.com/spreadsheets...it?usp=sharing
I've been recommended to include dummies for the provinces, dummies for the year (to account for general time trends), and dummies for every month (to account for seasonality).
I've been able to create dummies for the provinces (using "tabulate prov, gen(p)"), but am getting confused when creating dummies for the year and months:
1. I can't figure out how to create a dummy for a year, rather than monthly because my data is entered monthly
2. I believe I created dummies monthly (tabulate Date, gen(d)) but it looks strange --> D1, Date == 8401.0000 ????
How can I be sure if I did this correctly, and if so, how would I interpret the results?
Am I better off creating all of those dummy variables as recommended (there would be a very large amount) or should I be using the xtreg / areg function?
I'm not familiar with the xtreg or areg function (never used before)
but when I used the function "xi: regress Unem CPI i.prov" it looked quite clean.

What is the simplest way to remove the fixed effects and test if the relation between inflation and unemployment is still strong?
I'm working on a project testing the strength of the Phillips curve, but am very unfamiliar with STATA and panel data econometrics.
I'd like to test the relation between unemployment and inflation (CPI) and see if the relationship is still significantly significant post-financial crisis, compared to pre.
I've never conducted panel data analysis, and have little experience with STATA.
I've gathered CPI and Unemployment data from Jan 1983-Feb2017 for 10 provinces in Canada and cleaned the data on an excel file.
My data:
10 provinces, dates (monthly starting Jan 1983), unemployment rate (monthly), and CPI (monthly)
I've attached a spreadsheet for reference.
https://docs.google.com/spreadsheets...it?usp=sharing
I've been recommended to include dummies for the provinces, dummies for the year (to account for general time trends), and dummies for every month (to account for seasonality).
I've been able to create dummies for the provinces (using "tabulate prov, gen(p)"), but am getting confused when creating dummies for the year and months:
1. I can't figure out how to create a dummy for a year, rather than monthly because my data is entered monthly
2. I believe I created dummies monthly (tabulate Date, gen(d)) but it looks strange --> D1, Date == 8401.0000 ????
How can I be sure if I did this correctly, and if so, how would I interpret the results?
Am I better off creating all of those dummy variables as recommended (there would be a very large amount) or should I be using the xtreg / areg function?
I'm not familiar with the xtreg or areg function (never used before)
but when I used the function "xi: regress Unem CPI i.prov" it looked quite clean.
What is the simplest way to remove the fixed effects and test if the relation between inflation and unemployment is still strong?
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