Dear fellow Stata users,
The estimated coefficients for capital and labor of a Cobb-Douglas production function using levpet (LP) and xtreg, fe (FE) strongly differ with the estimated coefficients obtained by OLS, GEE, RE, and BE. Please, see results below.
I wonder if the discrepancy is because I have only two time periods, or because I have a reduced number of firms with observations in both periods, or because I am not properly using some command, among other reasons. I would highly appreciate your help as I am mainly interested in utilizing the results obtained by levpet (LP).
Results:
Stata commands:
Some definitions:
k=ln(K): Capital
lw=ln(LW): Labor
va=ln(VA): Value added
VA=Y-M-E
M: Raw materials and intermediate goods
E: Electricity
Data characteristics:
My final goal is to determine Total Factor Productivity (TFP). After a data cleaning process, I have an unbalanced panel of 888 firms. Only 83 firms have observations in both time periods which give me a total number of observations of 971. All observations belong to the same 4-digit level International Standard Industrial Classification (ISIC) code.
The estimated coefficients for capital and labor of a Cobb-Douglas production function using levpet (LP) and xtreg, fe (FE) strongly differ with the estimated coefficients obtained by OLS, GEE, RE, and BE. Please, see results below.
I wonder if the discrepancy is because I have only two time periods, or because I have a reduced number of firms with observations in both periods, or because I am not properly using some command, among other reasons. I would highly appreciate your help as I am mainly interested in utilizing the results obtained by levpet (LP).
Results:
Code:
---------------------------------------------------------------------------------------- (OLS) (GEE) (RE) (BE) (FE) (LP) va va va va va va ---------------------------------------------------------------------------------------- k 0.379*** 0.377*** 0.363*** 0.400*** 0.122** 0.0538 (0.0276) (0.0239) (0.0273) (0.0253) (0.0596) (0.107) lw 0.709*** 0.703*** 0.709*** 0.678*** 0.532** 0.542*** (0.0376) (0.0347) (0.0385) (0.0364) (0.228) (0.0459) _cons 5.915*** 5.944*** 6.063*** 5.774*** 9.280*** (0.243) (0.203) (0.239) (0.213) (0.996) ---------------------------------------------------------------------------------------- N 971 971 971 971 971 971 R-sq 0.671 0.666 0.163 adj. R-sq 0.670 0.665 0.161 rmse 1.100 0.610 1.102 0.175 ---------------------------------------------------------------------------------------- Standard errors in parentheses * p<0.10, ** p<0.05, *** p<0.01
Code:
xtset idpanel year *OLS regress va k lw, vce(cluster idpanel) *GEE xtgee va k lw *RE xtreg va k lw, re vce(cluster idpanel) *BE xtreg va k lw, be *FE xtreg va k lw, fe vce(cluster idpanel) *LP levpet va, free(lw) proxy(e) capital(k) valueadded reps(250)
k=ln(K): Capital
lw=ln(LW): Labor
va=ln(VA): Value added
VA=Y-M-E
M: Raw materials and intermediate goods
E: Electricity
Data characteristics:
My final goal is to determine Total Factor Productivity (TFP). After a data cleaning process, I have an unbalanced panel of 888 firms. Only 83 firms have observations in both time periods which give me a total number of observations of 971. All observations belong to the same 4-digit level International Standard Industrial Classification (ISIC) code.
Code:
xtdescribe idpanel: 101078, 101081, ..., 503957 n = 888 year: 1, 2, ..., 2 T = 2 Delta(year) = 1 unit Span(year) = 2 periods (idpanel*year uniquely identifies each observation) Distribution of T_i: min 5% 25% 50% 75% 95% max 1 1 1 1 1 2 2 Freq. Percent Cum. | Pattern ---------------------------+--------- 479 53.94 53.94 | 1. 326 36.71 90.65 | .1 83 9.35 100.00 | 11 ---------------------------+--------- 888 100.00 | XX
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