Hello all,
In Stata 14, I am currently trying to run a regression to estimate the affects of capital accumulation on labor, controlling for industry, sex, and skill level of the employees. Specifically, I want to know what the affects of capital accumulation on labor supply is by skill level. That is, how does capital affect labor supply in high, medium, and low skill level jobs, respectively? I'm having a little bit of trouble commanding Stata what I want to do, but maybe it's just a struggle with the interpretation of the results.
The variables I have are the following: employmentnumber, skill level (ranging from 1 = low to 3 = high), industry, wages(USD) capitalvalue (in USD), and sex (as a dummy variable, where female = 1, male = 0). I also have a variable country, which has 6 different countries as subgroups
So I've tried the following. Here is an example for mid-skill workers (I am separating regressions by country):
I do get results, however by splitting up each regression by their skill level, I get number of observations < 20, which is smaller than what I'd like (and what it would be if I analyzed all the levels together). However, if I do the following, using skill level = 2 as a base:
I feel like the output says how skill level moves the intercept for employmentnumber, rather than how employmentnumber in a specific skill level responds to capitalvalue, wages, etc. Is this reasoning wrong or are the two above codes 'similar' commands? If not, is there an alternative way I can tell stata to analyze the affects of capital on labor supply per skill level?
Also, if I were to control for industry as well, and follow the very first code above, would it be something like the following?
Additionally, I will be doing a panel regression using a fixed-effect model for 'reference' to the country-by-country regressions. Since I have too many time period observations per panel observation, but need them to run my analyses, I performed the following (for mid-skill workers as an example):
The code runs and I get results, however I'm finding results that don't seem to follow typical economic intuition, (higher capital --> 'slightly' higher labor supply) and I'm concerned that I am not correctly analyzing by skill level, and have done something else wrong in my analyses.
Thank you for any help!
In Stata 14, I am currently trying to run a regression to estimate the affects of capital accumulation on labor, controlling for industry, sex, and skill level of the employees. Specifically, I want to know what the affects of capital accumulation on labor supply is by skill level. That is, how does capital affect labor supply in high, medium, and low skill level jobs, respectively? I'm having a little bit of trouble commanding Stata what I want to do, but maybe it's just a struggle with the interpretation of the results.
The variables I have are the following: employmentnumber, skill level (ranging from 1 = low to 3 = high), industry, wages(USD) capitalvalue (in USD), and sex (as a dummy variable, where female = 1, male = 0). I also have a variable country, which has 6 different countries as subgroups
So I've tried the following. Here is an example for mid-skill workers (I am separating regressions by country):
Code:
regress employmentnumber capitalvalue wages female if(country =="Country1" & skill level == 2)
Code:
regress employmentnumber capitalvalue wages i2.level female if(country =="Country1")
Also, if I were to control for industry as well, and follow the very first code above, would it be something like the following?
Code:
regress employmentnumber capitalvalue i.industry wages female if(country =="Country1" & skill level == 2)
Additionally, I will be doing a panel regression using a fixed-effect model for 'reference' to the country-by-country regressions. Since I have too many time period observations per panel observation, but need them to run my analyses, I performed the following (for mid-skill workers as an example):
Code:
xtset country xtreg employmentnumber capitalvalue i.industry wages female if(level == 2), fe"
Thank you for any help!
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