I have an unbalanced panel data set of countries in the period 2002-2015 and I want to explain:
Dep. var: Total Entrepreneurship Activity (tea) across a set of groups.
Groups: Development stages (based on GDP)
Ind. var: Economic freedom (property_rights, government_integrity, tax_burden, government_spenditure, fiscal_health, business_freedom labor_freedom monetary_freedom trade_freedom investment_freedom financial_freedom)
Control: Unemployment, potentially GDP with the groups
The prior hypothesis is that the different variables of economic freedom vary in importance of boosting entrepreneurship depending on the stage of develpoment for a coutry.
To investigate this hypothesis I have modelled every variable seperately to overcome multicollinearity, using fixed effects or random effects - most Hausman tests point to fe, but some turn out negative and other produce the following error: (v_b-v_b is not positive definite) stata.
I have applied two variations:
1. Including main effects and the interactions term:
Here, I am comparing development stage 2 and 3 to rest, respectively.
Code:
. xtreg tea c.property_rights##i.stage_of_dev_3 unemployment, fe Fixed-effects (within) regression Number of obs = 571 Group variable: stage_of_~3c Number of groups = 3 R-sq: Obs per group: within = 0.1423 min = 88 between = 0.3803 avg = 190.3 overall = 0.1300 max = 278 F(6,562) = 15.53 corr(u_i, Xb) = 0.0416 Prob > F = 0.0000 -------------------------------------------------------------------------------------------------- tea | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---------------------------------+---------------------------------------------------------------- property_rights | 1.957176 .8453467 2.32 0.021 .2967506 3.617601 | stage_of_dev_3 | 2 | 2.932931 3.202161 0.92 0.360 -3.356734 9.222595 3 | -3.210716 3.449857 -0.93 0.352 -9.986905 3.565473 | stage_of_dev_3#c.property_rights | 2 | -2.624536 .8740177 -3.00 0.003 -4.341276 -.9077955 3 | -1.46376 .87046 -1.68 0.093 -3.173513 .2459919 | unemployment | -.2270513 .0404756 -5.61 0.000 -.3065532 -.1475495 _cons | 11.64089 3.131846 3.72 0.000 5.48934 17.79245 ---------------------------------+---------------------------------------------------------------- sigma_u | 4.6860432 sigma_e | 5.3212088 rho | .43678413 (fraction of variance due to u_i) -------------------------------------------------------------------------------------------------- F test that all u_i=0: F(2, 562) = 30.61 Prob > F = 0.0000
Here, I extract an effect for each stage, so by itself more desireable, but I am not aware of potential flaws for this method.
Code:
. xtreg tea c.property_rights#i.stage_of_dev_3 unemployment, fe Fixed-effects (within) regression Number of obs = 571 Group variable: stage_of_~3c Number of groups = 3 R-sq: Obs per group: within = 0.1219 min = 88 between = 0.1388 avg = 190.3 overall = 0.0757 max = 278 F(4,564) = 19.58 corr(u_i, Xb) = -0.0542 Prob > F = 0.0000 -------------------------------------------------------------------------------------------------- tea | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---------------------------------+---------------------------------------------------------------- stage_of_dev_3#c.property_rights | 1 | 1.61722 .3570775 4.53 0.000 .9158554 2.318584 2 | -.1800884 .1853185 -0.97 0.332 -.544087 .1839103 3 | .0394411 .148583 0.27 0.791 -.2524025 .3312848 | unemployment | -.2391922 .0402427 -5.94 0.000 -.318236 -.1601483 _cons | 12.29739 1.006851 12.21 0.000 10.31975 14.27502 ---------------------------------+---------------------------------------------------------------- sigma_u | 5.1240393 sigma_e | 5.3743468 rho | .47617108 (fraction of variance due to u_i) -------------------------------------------------------------------------------------------------- F test that all u_i=0: F(2, 564) = 36.92 Prob > F = 0.0000
Thanks for any advice,
Laurence
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