I am currently working on panel data which consists of 36 industrial sectors over 5 years, n=180. I have 5 independent variables which are proxy variables for technological progress such as: R&D expenditures, number of patent applications...etc. The dependent variable is the annual number of employees. I have already run a fixed effect regression to estimate the effect of technological upgrading on employment growth. I am now interested in estimating the effect among different industrial sectors. So I categorized the 36 industrial sectors into: high-technology level sectors, medium-high, medium-low, and low-technology. I know that I cannot include time-invariant dummies in a fixed effect model so I have run a between estimator regression; however, I am not sure if that is correct or not and how can I explain the beta coefficients of the dummies. In this case, the baseline is high-technology level industries. Below are the codes and the output results.
Thanks so much in advance.
Thanks so much in advance.
Code:
label define technology_level 1 "high_technology" 2 "medium_high_technology" 3 "medium_low_technology" 4 "low_technology" . . . . gen byte technology_level:technology_level=1 if inlist(id, 20, 29, 31, 32) (160 missing values generated) . . replace technology_level=2 if inlist(id, 19, 21, 27, 28, 30) (25 real changes made) . . replace technology_level=3 if inlist(id, 1, 2, 3, 4, 5, 18, 22, 23, 24, 25, 26, 33, 34, 35, 36) (75 real changes made) . . replace technology_level=4 if inlist(id, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17) (60 real changes made) . . xi: xtreg $ylist $xlist i.technology_level, be i.technology_~l _Itechnolog_1-4 (naturally coded; _Itechnolog_1 omitted) Between regression (regression on group means) Number of obs = 180 Group variable: id Number of groups = 36 R-sq: Obs per group: within = 0.0083 min = 5 between = 0.7639 avg = 5.0 overall = 0.6563 max = 5 F(8,27) = 10.92 sd(u_i + avg(e_i.))= 1195228 Prob > F = 0.0000 --------------------------------------------------------------------------------------------- Employees_number | Coef. Std. Err. t P>|t| [95% Conf. Interval] ----------------------------+---------------------------------------------------------------- RD_expenditures | .7916889 .5450573 1.45 0.158 -.3266763 1.910054 RD_projects | 104.9565 73.54601 1.43 0.165 -45.94746 255.8604 New_products_expenditures | -.5771447 .6376137 -0.91 0.373 -1.88542 .7311306 NumberofPatentApplicationsp | 22.05046 36.91679 0.60 0.555 -53.69654 97.79745 NumberofInventionsinForcep | 25.06571 29.79686 0.84 0.408 -36.07239 86.20382 _Itechnolog_2 | 384517.3 921242 0.42 0.680 -1505715 2274750 _Itechnolog_3 | 2380854 985924.9 2.41 0.023 357902.9 4403804 _Itechnolog_4 | 3031953 1032893 2.94 0.007 912631.1 5151274 _cons | -1441437 1038321 -1.39 0.176 -3571895 689021.1 ---------------------------------------------------------------------------------------------
Comment