I have a panel data for labor productivity for 74 countries for period of 1992-2016.I am trying to understand the convergence rate based on romers model of convergence.
I attach also the data
I am using xtregar for my model and getting such results.
Code:
. xtregar ln_diff ln_prod_lagged t18-t19 L1.ln_diff L2.ln_diff, fe rhotype(tscorr) twostep FE (within) regression with AR(1) disturbances Number of obs = 1,628 Group variable: id Number of groups = 74 R-sq: Obs per group: within = 0.0917 min = 22 between = 0.0056 avg = 22.0 overall = 0.0043 max = 22 F(5,1549) = 31.26 corr(u_i, Xb) = -0.9112 Prob > F = 0.0000 -------------------------------------------------------------------------------- ln_diff | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---------------+---------------------------------------------------------------- ln_prod_lagged | -.0742815 .0073197 -10.15 0.000 -.088639 -.0599239 t18 | -.038016 .0108618 -3.50 0.000 -.0593213 -.0167108 t19 | .0602955 .0109165 5.52 0.000 .0388827 .0817082 | ln_diff | L1. | .0431449 .0222561 1.94 0.053 -.0005104 .0868002 L2. | -.0367265 .0210011 -1.75 0.081 -.0779201 .0044671 | _cons | .7583084 .0742463 10.21 0.000 .6126746 .9039422 ---------------+---------------------------------------------------------------- rho_ar | -.03962128 sigma_u | .09476397 sigma_e | .09042197 rho_fov | .52343382 (fraction of variance because of u_i) -------------------------------------------------------------------------------- F test that all u_i=0: F(73,1549) = 3.58 Prob > F = 0.0000
1. I am getting 0.52 for rho_fov and with no any linear model i cannot increase it, does it mean this models are not good to use in case of my data?
2. My second question might sound weird but is it possible after estimation of coefficients somehow go deeper and inderstand what the coefficient/rate would be for specific country, for example Armenia as each country has different moving path and the speed can be different.
3.Are GMM models more appropriate for such analysis? I do not understand very well dynamic panel models and what is going on in background, so for now trying to stay away from them.
Thank you very much in advace!
Best,
Sara Zakaryan
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