I have four attributes as independent variables as Reduction in CO2 (% reduction), Energy Independence (% domestic production), Energy Sector Employment (jobs), Time to Transition (years), Household Energy Prices (% of the bill), and the dependent variable is rank (generate from best and worst option selected by respondents).
I am performing Rank ordered Logit model
rologit altchrank att_reductionco2 att_indepenergy att_employmentch att_timetrans att_priceenergy, group(ID)
Iteration 0: log likelihood = -21166.353
Iteration 1: log likelihood = -20999.962
Iteration 2: log likelihood = -20999.96
Refining estimates:
Iteration 0: log likelihood = -20999.96
Rank-ordered logistic regression Number of obs = 21,246
Group variable: ID Number of groups = 568
Ties adjustment: exactm Obs per group:
min = 36
avg = 37.40
max = 39
LR chi2(5) = 332.79
Log likelihood = -20999.96 Prob > chi2 = 0.0000
----------------------------------------------------------------------------------
altchrank | Coefficient Std. err. z P>|z| [95% conf. interval]
-----------------+----------------------------------------------------------------
att_reductionco2 | -.0026621 .0012179 -2.19 0.029 -.0050492 -.000275
att_indepenergy | -.0007554 .0006097 -1.24 0.215 -.0019503 .0004396
att_employmentch | -.0000134 7.71e-07 -17.39 0.000 -.0000149 -.0000119
att_timetrans | .0010265 .003067 0.33 0.738 -.0049847 .0070377
att_priceenergy | .0014721 .0003046 4.83 0.000 .0008751 .0020691
----------------------------------------------------------------------------------
My two main attributes are insignificant; I try to run Iter(50) but cannot. Also, I want to find MWTP(a) (% price rise), WTP(b) 95% Confidence Interval, and MWTA Employment Change(c).
a Marginal Willingness to Pay (MWTP): as noted in the description of the attribute levels earlier, the regression analysis is done with the percentage change in
electricity bills, such that the MWTP is in terms of percentage increase or decrease in electricity per unit of that attribute.
b The WTP 95% confidence intervals throughout the paper are all calculated using the nlcom command in Stata which applies the delta method approximation for the
confidence intervals.
c As employment loss is a key factor in the choice decision results as well as for concern of policymakers and the public, we present the results of marginal willingness
to accept job loss for each other variable as well.
I confused in state command
I am performing Rank ordered Logit model
rologit altchrank att_reductionco2 att_indepenergy att_employmentch att_timetrans att_priceenergy, group(ID)
Iteration 0: log likelihood = -21166.353
Iteration 1: log likelihood = -20999.962
Iteration 2: log likelihood = -20999.96
Refining estimates:
Iteration 0: log likelihood = -20999.96
Rank-ordered logistic regression Number of obs = 21,246
Group variable: ID Number of groups = 568
Ties adjustment: exactm Obs per group:
min = 36
avg = 37.40
max = 39
LR chi2(5) = 332.79
Log likelihood = -20999.96 Prob > chi2 = 0.0000
----------------------------------------------------------------------------------
altchrank | Coefficient Std. err. z P>|z| [95% conf. interval]
-----------------+----------------------------------------------------------------
att_reductionco2 | -.0026621 .0012179 -2.19 0.029 -.0050492 -.000275
att_indepenergy | -.0007554 .0006097 -1.24 0.215 -.0019503 .0004396
att_employmentch | -.0000134 7.71e-07 -17.39 0.000 -.0000149 -.0000119
att_timetrans | .0010265 .003067 0.33 0.738 -.0049847 .0070377
att_priceenergy | .0014721 .0003046 4.83 0.000 .0008751 .0020691
----------------------------------------------------------------------------------
My two main attributes are insignificant; I try to run Iter(50) but cannot. Also, I want to find MWTP(a) (% price rise), WTP(b) 95% Confidence Interval, and MWTA Employment Change(c).
a Marginal Willingness to Pay (MWTP): as noted in the description of the attribute levels earlier, the regression analysis is done with the percentage change in
electricity bills, such that the MWTP is in terms of percentage increase or decrease in electricity per unit of that attribute.
b The WTP 95% confidence intervals throughout the paper are all calculated using the nlcom command in Stata which applies the delta method approximation for the
confidence intervals.
c As employment loss is a key factor in the choice decision results as well as for concern of policymakers and the public, we present the results of marginal willingness
to accept job loss for each other variable as well.
I confused in state command
