analysis while electricity (or power) generated is the desirable output. As
mentioned the sample consists of plants of various vintages, some plants
are new and are constructed with relatively better and efficient
technologies and thus emit less CO2 than the plants which are very old
and pollute more per unit of output. In order to differentiate plants that
are old and have not installed any equipment to control their emissions
i.e., the dirty plants, from the plants that use new technology which is
less polluting and plants which have old technology but have installed
equipment or have taken additional measure to restrict emissions and
hence pollute less i.e., the cleaner plants, a dummy variable5 is
introduced in the model. The output distance function is initially
estimated without making any distinction between the dirty and cleaner
plants. This is our Model-1. The estimation of the output distance
function is again carried out, now by incorporating the dummy variable to
distinguish the dirty plants from the cleaner ones. This is called Model-2.
The estimated parameters of both the models are presented in Table 3.
Table 3: Estimated Parameters
Parameter |
Value |
Parameter |
Value | ||
Model-1 |
Model-2 |
Model-1 |
Model-2 | ||
α o |
5.713907 |
8.265383 |
αYY |
-0.073590 |
-0.069163 |
βL |
-0.756283 |
-0.168085 |
αYP |
0.073590 |
0.069163 |
βK |
0.526069 |
0.947600 |
α PP |
-0.073590 |
-0.069163 |
βF |
-1.875104 |
-2.727518 |
γ LY |
-0.253212 |
-0.306170 |
αY |
-0.892840 |
-0.409482 |
γ LP |
0.253212 |
0.306170 |
αP |
1.892840 |
1.409482 |
γ KY |
-0.103620 |
-0.017939 |
β LL |
-0.005172 |
-0.100494 |
γ KP |
0.103620 |
0.017939 |
β LK |
0.148123 |
0.205437 |
γ FY |
0.261308 |
0.220088 |
β LF |
-0.013652 |
-0.036834 |
γ FP |
-0.261308 |
-0.220088 |
β KK |
0.126568 |
0.060381 |
γt |
-0.010469 |
-0.007900 |
β KF |
-0.181760 |
-0.210416 |
γ tt |
0.001046 |
0.000761 |
β FF |
0.163526 |
0.250791 |
Dummy |
- |
0.051274 |
Note: In Model 2 we have used Dummy D = 1 for plants which are dirty and
used dated technology and D = 0 for plants which are clean.
20
More intriguing information
1. Lumpy Investment, Sectoral Propagation, and Business Cycles2. AJAE Appendix: Willingness to Pay Versus Expected Consumption Value in Vickrey Auctions for New Experience Goods
3. Importing Feminist Criticism
4. Opciones de política económica en el Perú 2011-2015
5. Governance Control Mechanisms in Portuguese Agricultural Credit Cooperatives
6. Improving Business Cycle Forecasts’ Accuracy - What Can We Learn from Past Errors?
7. Biologically inspired distributed machine cognition: a new formal approach to hyperparallel computation
8. Modelling the health related benefits of environmental policies - a CGE analysis for the eu countries with gem-e3
9. An Estimated DSGE Model of the Indian Economy.
10. Computing optimal sampling designs for two-stage studies