Hi, I have run the two regressions below. The method variables are different for Dry Recycling and Compost. Is there a test that I can use to compare the coefficients these regressions for example, whether the effect of income on Dry Recycling rates is statistically different from the effect of income on Compost rates?
VARIABLES Dry Recycling VARIABLES Compost
ln(income) -1.610 ln(income) 1.092
(2.575) (2.023)
ln(population density) -3.752 ln(population density) 0.186
(2.336) (3.571)
ln(household size) -48.76* ln(household size) 33.88
(24.80) (22.82)
Waste Method
1Wheeled Bin 100-150l		 0.272 Waste Method
1Wheeled Bin 100-150l		 -0.525
(0.475) (0.330)
1Wheeled Bin 150-250l -0.640 1Wheeled Bin 150-250l -0.328
(0.401) (0.382)
1Wheeled Bin 251-350l -0.988* 1Wheeled Bin 251-350l 0.272
(0.541) (0.408)
1Wheeled Bin>350l -0.136 1Wheeled Bin>350l -0.00640
(0.472) (0.280)
1Plastic Sacks 0.569 1Plastic Sacks 0.144
(0.590) (0.338)
1Refuse Bins 0.259 1Refuse Bins 0.246
(0.745) (0.841)
1Communal Bin -0.304 1Communal Bin -0.0781
(0.385) (0.344)
1No method -0.209 1No method 0.372
(0.649) (0.470)
1Other method 0.0609 1Other method 0.131
(0.467) (0.866)
Dry Recycling Method
2Kerbside Box<35l		 -1.455*** Compost Method
3Reusable Sacks		 -0.0396
(0.539) (0.586)
2Kerbside Box 35-50l -0.937* 3Non Reusable Sacks 0.353
(0.500) (0.271)
2Kerbside Box>35l -1.285** 3Wheeled bin<120l 0.133
(0.510) (0.728)
2Reusable Sacks 0.223 3Wheeled Bin 120-180l -0.0179
(0.547) (0.317)
2Non Reusable Sacks 0.418 3Wheeled Bin 180-240l 1.190***
(0.407) (0.407)
2Wheeled Bin >120l 0.151 3Wheeled Bin 241l+ 0.511
(0.931) (0.411)
2Wheeled Bin 120-180l 0.553 3Other -0.0887
(0.392) (0.337)
2Wheeled Bin 181-240l 1.409*** Waste Average Frequency 2.221***
(0.375) (0.611)
2Wheeled Bin 241l+ 0.412 Compost Average Frequency -2.434***
(0.303) (0.653)
No Method of containment 0.182 quarter2 11.89***
(0.697) (0.318)
Other 0.461 quarter3 11.35***
(0.375) (0.316)
Waste Average Frequency 1.424** quarter4 4.956***
(0.570) (0.141)
Dry Average Frequency -0.630 Constant -28.97*
(0.642) (16.34)
Quarter 2 -4.473***
(0.122) Observations 5,544
Quarter 3 -4.172*** Number of Local Authorities 299
(0.118) R-squared 0.695
Quarter 4 -2.505***
(0.101)
Constant 91.31***
(16.95)
Observations 5,862
Number of local authorities 311
R-squared 0.359
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1