Hi everyone!
I want to perform a linear regression with two interacting independent variables but I am not sure on how to formulate it.
Sample: 57 countries
DV: Country prevalence rate of social entrepreneurship (continuous variable reported as %)
IV 1: Government size (Continuous variable reported as amount of government spending as % of GDP)
IV 2: Government quality (Continuous variable reported as score between -2.5 and +2.5)
I want to find the coefficient for when government size goes down while government quality goes up, as my paper's hypothesis is as follows:
A relatively smaller government size and relatively higher government quality is the most beneficial for prevalence of social entrepreneurship.
This is what I have tried so far, but I'm strongly doubting that I'm measuring what I want to measure in this way.
(SE_ALL1 is rate of social entrepreneurship) (excluded controls for clarity)
Array
Any help would be greatly appreciated!
Daan Clappers
Related Posts with Regressing an interaction of two independent variables, of which one should get lower and one higher, on a dependent variable
Hausman test has suggested Random effects model but I want to use Fixed effectsHello everyone, I am using EU dataset for 27 countries for 5 different years. My goal is to determi…
Is it possible to use itsa for interrupted time series with multiple panels all affected by a policy?Hi, I am running an interrupted time series analysis to assess the impact of a policy on medicine c…
Panel data: Identify change in id of respondent for imputation Dear statalist community, I have a panel of around 12,000 individuals and four rounds, where the i…
log fileDear All, just a quick question. I am running some estimates and producing a log file. The latter i…
Sorting panel data with numerous conditionsHi. I am currently working with longitudinal data I have converted to panel data and I now need some…
Subscribe to:
Post Comments (Atom)
0 Response to Regressing an interaction of two independent variables, of which one should get lower and one higher, on a dependent variable
Post a Comment