Hello Everyone,
Your cooperation is of great value to me. I am doing my master thesis, where I am analyzing the commuting behavior of male and female in Sweden for three years 2000, 2007 and 2014. I am using Gravity model where
Model : 1
MaleCij = size of origin + size of destination- travel time+ (Control variables)
Size of origin (people employed in origin place or night population employed)
Size of destination (people employed in destination or day population employed)
Control variables include
FemaleCij = size of origin + size of destination- travel time+ (Control variables)
(Control variables)
All are same except I adding here share of people working in public sector instead of manufacture
Main Problem:
In case of Public sector and female commuting:
I am getting negative and significant results for public sector, while it is supposed to be positive. As literature says that women work more in public sector. I have checked for correlation also. When I only enter public sector alone or with other control variable, still I gives negative results.
In case of manufacture sector and male commuting:
I get negative results and insignificant when I enter it as the only control variable. But when I enter it with housing prices, then I get the positive and significant results. But in 2007 the wages become negative.
But for public sector I could not solve it either way. Kindly can anyone guide me what I am missing or doing wrong Your cooperation is of great value to me.
the codes for regression in stata I used are,
reg ln_mCij ln_Oi ln_Dj tij share- higher education share of Manufacture sector if ZeroM==0 & year==2000, robust
reg ln_wCij ln_Oi ln_Dj tij share- higher education share of Public sectorr if ZeroW==0 & year==2000, robust
Your cooperation is of great value to me. I am doing my master thesis, where I am analyzing the commuting behavior of male and female in Sweden for three years 2000, 2007 and 2014. I am using Gravity model where
Model : 1
MaleCij = size of origin + size of destination- travel time+ (Control variables)
Size of origin (people employed in origin place or night population employed)
Size of destination (people employed in destination or day population employed)
Control variables include
- Housing prices in destination place
- Wages in destination place
- Share of people with higher education in origin place
- Share of people working in manufacture sector in destination place
FemaleCij = size of origin + size of destination- travel time+ (Control variables)
(Control variables)
All are same except I adding here share of people working in public sector instead of manufacture
Main Problem:
In case of Public sector and female commuting:
I am getting negative and significant results for public sector, while it is supposed to be positive. As literature says that women work more in public sector. I have checked for correlation also. When I only enter public sector alone or with other control variable, still I gives negative results.
In case of manufacture sector and male commuting:
I get negative results and insignificant when I enter it as the only control variable. But when I enter it with housing prices, then I get the positive and significant results. But in 2007 the wages become negative.
But for public sector I could not solve it either way. Kindly can anyone guide me what I am missing or doing wrong Your cooperation is of great value to me.
the codes for regression in stata I used are,
reg ln_mCij ln_Oi ln_Dj tij share- higher education share of Manufacture sector if ZeroM==0 & year==2000, robust
reg ln_wCij ln_Oi ln_Dj tij share- higher education share of Public sectorr if ZeroW==0 & year==2000, robust