Hello,
My sample is 27 countries over the period 1970-2019.
I would like to make a table of coefficients, standard error and p-value of significance individual and join of three regression by country.
I begging but I don't know why in my table don't appear Prob F>0.
I obtain:
What can I do?
Greetings,
Sebastián.
My sample is 27 countries over the period 1970-2019.
Code:
* Example generated by -dataex-. For more info, type help dataex clear input float(ln_co2pc ln_co2pc_1 ln_gdppc) str21 Country float year 6.148759 . 15.432597 "Bolivia" 1970 8.097491 . 16.590824 "Argentina" 1970 6.680636 . 15.634053 "Brasil" 1970 6.302356 6.148759 15.46691 "Bolivia" 1971 8.1406765 8.097491 16.630117 "Argentina" 1971 6.777571 6.680636 15.71689 "Brasil" 1971 6.844649 6.777571 15.8056 "Brasil" 1972 8.13736 8.1406765 16.630175 "Argentina" 1972 6.417964 6.302356 15.528253 "Bolivia" 1972 8.172827 8.13736 16.641678 "Argentina" 1973 6.502983 6.417964 15.568973 "Bolivia" 1973 6.985705 6.844649 15.912602 "Brasil" 1973 6.568667 6.502983 15.58286 "Bolivia" 1974 8.155382 8.172827 16.679472 "Argentina" 1974 7.053004 6.985705 15.967343 "Brasil" 1974 7.088357 7.053004 15.99403 "Brasil" 1975 8.113881 8.155382 16.663467 "Argentina" 1975 6.675215 6.568667 15.63812 "Bolivia" 1975 8.141445 8.113881 16.627773 "Argentina" 1976 6.748501 6.675215 15.66816 "Bolivia" 1976 7.160077 7.088357 16.067944 "Brasil" 1976 7.165948 7.160077 16.092398 "Brasil" 1977 6.826501 6.748501 15.695867 "Bolivia" 1977 8.168763 8.141445 16.679825 "Argentina" 1977 6.871734 6.826501 15.695177 "Bolivia" 1978 8.149868 8.168763 16.618837 "Argentina" 1978 7.240816 7.165948 16.117205 "Brasil" 1978 7.281696 7.240816 16.158945 "Brasil" 1979 8.188429 8.149868 16.701134 "Argentina" 1979 6.866856 6.871734 15.67573 "Bolivia" 1979 8.154454 8.188429 16.700838 "Argentina" 1980 7.245173 7.281696 16.223352 "Brasil" 1980 6.855255 6.866856 15.64096 "Bolivia" 1980 6.869163 6.855255 15.622796 "Bolivia" 1981 7.163939 7.245173 16.15637 "Brasil" 1981 8.121045 8.154454 16.631826 "Argentina" 1981 7.164176 7.163939 16.141218 "Brasil" 1982 8.091192 8.121045 16.608477 "Argentina" 1982 6.82934 6.869163 15.561742 "Bolivia" 1982 8.101911 8.091192 16.634943 "Argentina" 1983 7.094753 7.164176 16.088423 "Brasil" 1983 6.755651 6.82934 15.499663 "Bolivia" 1983 7.074131 7.094753 16.118597 "Brasil" 1984 8.075928 8.101911 16.634426 "Argentina" 1984 6.714844 6.755651 15.47671 "Bolivia" 1984 7.984149 8.075928 16.565155 "Argentina" 1985 7.128945 7.074131 16.17257 "Brasil" 1985 6.652743 6.714844 15.43893 "Bolivia" 1985 8.046303 7.984149 16.609022 "Argentina" 1986 7.225423 7.128945 16.224058 "Brasil" 1986 6.644448 6.652743 15.392056 "Bolivia" 1986 8.082119 8.046303 16.620022 "Argentina" 1987 6.693766 6.644448 15.3955 "Bolivia" 1987 7.229693 7.225423 16.2388 "Brasil" 1987 7.218962 7.229693 16.218967 "Brasil" 1988 6.692139 6.693766 15.40321 "Bolivia" 1988 8.102077 8.082119 16.593643 "Argentina" 1988 6.770207 6.692139 15.419538 "Bolivia" 1989 7.226127 7.218962 16.23145 "Brasil" 1989 8.050529 8.102077 16.504366 "Argentina" 1989 7.232979 7.226127 16.16886 "Brasil" 1990 7.970507 8.050529 16.464855 "Argentina" 1990 6.729681 6.770207 15.36385 "Bolivia" 1990 6.722625 6.729681 15.392 "Bolivia" 1991 8.018763 7.970507 16.538239 "Argentina" 1991 7.247776 7.232979 16.161533 "Brasil" 1991 8.033707 8.018763 16.601097 "Argentina" 1992 7.240761 7.247776 16.139006 "Brasil" 1992 6.741838 6.722625 15.384846 "Bolivia" 1992 8.054319 8.033707 16.666912 "Argentina" 1993 7.259393 7.240761 16.17043 "Brasil" 1993 6.758414 6.741838 15.403187 "Bolivia" 1993 6.823371 6.758414 15.425656 "Bolivia" 1994 8.079103 8.054319 16.710981 "Argentina" 1994 7.293154 7.259393 16.210972 "Brasil" 1994 8.066797 8.079103 16.669825 "Argentina" 1995 7.351728 7.293154 16.236244 "Brasil" 1995 6.903273 6.823371 15.448823 "Bolivia" 1995 8.107716 8.066797 16.711681 "Argentina" 1996 7.418663 7.351728 16.242205 "Brasil" 1996 6.804934 6.903273 15.46948 "Bolivia" 1996 6.789863 6.804934 15.496119 "Bolivia" 1997 7.445788 7.418663 16.259953 "Brasil" 1997 8.115711 8.107716 16.778076 "Argentina" 1997 7.457252 7.445788 16.248037 "Brasil" 1998 6.819801 6.789863 15.523844 "Bolivia" 1998 8.129745 8.115711 16.804533 "Argentina" 1998 7.492587 7.457252 16.237896 "Brasil" 1999 6.827318 6.819801 15.507175 "Bolivia" 1999 8.159109 8.129745 16.758959 "Argentina" 1999 8.14549 8.159109 16.74003 "Argentina" 2000 6.770886 6.827318 15.50365 "Bolivia" 2000 7.384548 7.492587 16.266598 "Brasil" 2000 7.38936 7.384548 16.266731 "Brasil" 2001 6.728434 6.770886 15.50151 "Bolivia" 2001 8.103066 8.14549 16.684021 "Argentina" 2001 7.431954 7.38936 16.283682 "Brasil" 2002 8.038289 8.103066 16.557837 "Argentina" 2002 6.784127 6.728434 15.50757 "Bolivia" 2002 6.86026 6.784127 15.516167 "Bolivia" 2003 8.097865 8.038289 16.631798 "Argentina" 2003 7.393076 7.431954 16.282452 "Brasil" 2003 7.43983 7.393076 16.32644 "Brasil" 2004 6.938504 6.86026 15.539223 "Bolivia" 2004 8.173456 8.097865 16.707693 "Argentina" 2004 7.436328 7.43983 16.3465 "Brasil" 2005 7.003305 6.938504 15.56497 "Bolivia" 2005 8.202891 8.173456 16.782145 "Argentina" 2005 8.245454 8.202891 16.849388 "Argentina" 2006 7.440323 7.436328 16.374454 "Brasil" 2006 7.07073 7.003305 15.594608 "Bolivia" 2006 8.326015 8.245454 16.925648 "Argentina" 2007 7.161592 7.07073 15.622316 "Bolivia" 2007 7.496171 7.440323 16.423002 "Brasil" 2007 7.226458 7.161592 15.665342 "Bolivia" 2008 8.349349 8.326015 16.955492 "Argentina" 2008 7.558616 7.496171 16.462748 "Brasil" 2008 8.271428 8.349349 16.88449 "Argentina" 2009 7.241869 7.226458 15.68199 "Bolivia" 2009 7.482704 7.558616 16.451868 "Brasil" 2009 8.342472 8.271428 16.970789 "Argentina" 2010 7.317679 7.241869 15.70632 "Bolivia" 2010 7.59013 7.482704 16.515072 "Brasil" 2010 8.379102 8.342472 17.018763 "Argentina" 2011 7.607613 7.59013 16.544888 "Brasil" 2011 7.386178 7.317679 15.7412 "Bolivia" 2011 8.384642 8.379102 16.99798 "Argentina" 2012 7.43899 7.386178 15.775543 "Bolivia" 2012 7.690645 7.607613 16.554981 "Brasil" 2012 7.756489 7.690645 16.575851 "Brasil" 2013 8.402295 8.384642 17.011246 "Argentina" 2013 7.502742 7.43899 15.82627 "Bolivia" 2013 7.55739 7.502742 15.86451 "Bolivia" 2014 7.800936 7.756489 16.57232 "Brasil" 2014 8.376057 8.402295 16.975391 "Argentina" 2014 7.763323 7.800936 16.52783 "Brasil" 2015 7.561952 7.55739 15.897124 "Bolivia" 2015 8.389862 8.376057 16.992117 "Argentina" 2015 7.674804 7.763323 16.486284 "Brasil" 2016 8.375152 8.389862 16.961092 "Argentina" 2016 7.599395 7.561952 15.924203 "Bolivia" 2016 8.350884 8.375152 16.979082 "Argentina" 2017 7.688831 7.674804 16.491356 "Brasil" 2017 7.603081 7.599395 15.950775 "Bolivia" 2017 7.603012 7.603081 15.977754 "Bolivia" 2018 8.3014765 8.350884 16.942955 "Argentina" 2018 7.663756 7.688831 16.501196 "Brasil" 2018 7.568829 7.603012 15.985394 "Bolivia" 2019 8.26208 8.3014765 16.913332 "Argentina" 2019 7.666007 7.663756 16.505816 "Brasil" 2019 end
I begging but I don't know why in my table don't appear Prob F>0.
Code:
collect clear collect _r_b _r_se, tag(model["(1)"] pais["Agrupado"]): qui reg ln_co2pc ln_gdppc collect p_d = r(p), tag(model["(1)"] pais["Agrupado"]): qui testparm ln_gdppc collect _r_b _r_se, tag(model["(2)"] pais["Agrupado"]): qui reg ln_co2pc ln_gdppc ln_co2pc_1 collect p_d = r(p), tag(model["(2)"] pais["Agrupado"]): qui testparm ln_gdppc ln_co2pc_1 collect _r_b _r_se, tag(model["(3)"] pais["Agrupado"]): qui reg ln_co2pc ln_gdppc ln_co2pc_2 collect p_d = r(p), tag(model["(3)"] pais["Agrupado"]): qui testparm ln_gdppc ln_co2pc_2 collect _r_b _r_se, tag(model["(4)"] pais["Agrupado"]): qui reg ln_co2pc ln_gdppc ln_co2pc_1 ln_co2pc_2 collect p_d = r(p), tag(model["(4)"] pais["Agrupado"]): qui testparm ln_gdppc ln_co2pc_1 ln_co2pc_2 levelsof pais, local(xvalues) foreach x of local xvalues { local v : label(pais)`x' collect _r_b _r_se, tag(model["(1)"] pais["`v'"]): qui reg ln_co2pc ln_gdppc if Country=="`v'" collect p_d = r(p), tag(model["(1)"] pais["`v'"]): qui testparm ln_gdppc collect _r_b _r_se, tag(model["(2)"] pais["`v'"]): qui reg ln_co2pc ln_gdppc ln_co2pc_1 if Country=="`v'" collect p_d = r(p), tag(model["(2)"] pais["`v'"]): qui testparm ln_gdppc ln_co2pc_1 collect _r_b _r_se, tag(model["(3)"] pais["`v'"]): qui reg ln_co2pc ln_gdppc ln_co2pc_2 if Country=="`v'" collect p_d = r(p), tag(model["(3)"] pais["`v'"]): qui testparm ln_gdppc ln_co2pc_2 collect _r_b _r_se, tag(model["(4)"] pais["`v'"]): qui reg ln_co2pc ln_gdppc ln_co2pc_1 ln_co2pc_2 if Country=="`v'" collect p_d = r(p), tag(model["(4)"] pais["`v'"]): qui testparm ln_gdppc ln_co2pc_1 ln_co2pc_2 } collect style header model, title(hide) collect style column, dups(center) collect layout (pais) (model#colname[ln_gdppc ln_gdppc ln_co2pc_1 ln_gdppc_1 ln_co2pc_2]#result[_r_b _r_se _r_p p_d]) collect label levels result _r_b "Coeff" _r_se "SE" _r_p "P>|t|" p_d "Prob > F", modify collect style cell, nformat(%4.2f) border(right, pattern(nil)) collect style column, delimiter(" x ") collect label values colname ln_gdppc "ln_gdppc" ln_co2pc_1 "ln_co2pc_1" ln_co2pc_2 "ln_co2pc_2" ln_gdppc "ln_gdppc" ln_gdppc_1 "ln_gdppc_1" ln_gdppc_2 "ln_gdppc_2" _cons "Constant", modify collect preview
Code:
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- > ------------------------ (1) (2) (3) (4) > ln_gdppc ln_gdppc ln_co2pc_1 ln_gdppc ln_co2pc_2 ln_gdppc ln_co2 > pc_1 ln_co2pc_2 Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff SE P>|t| Coeff S > E P>|t| Coeff SE P>|t| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- > ------------------------ Agrupado 1.11 0.03 0.00 1.11 0.03 0.00 0.03 0.01 0.00 0.03 0.01 0.00 0.97 0.01 0.00 0.07 0.01 0.00 0.07 0.01 0.00 0.93 0.01 0.00 0.03 0.01 0.00 0.03 0.01 0.00 1.05 0.0 > 3 0.00 -0.09 0.03 0.01 Argentina 0.73 0.04 0.00 0.73 0.04 0.00 0.41 0.06 0.00 0.41 0.06 0.00 0.46 0.08 0.00 0.57 0.06 0.00 0.57 0.06 0.00 0.27 0.07 0.00 0.42 0.06 0.00 0.42 0.06 0.00 0.52 0.1 > 3 0.00 -0.06 0.11 0.56 Bolivia 1.75 0.17 0.00 1.75 0.17 0.00 0.24 0.07 0.00 0.24 0.07 0.00 0.88 0.04 0.00 0.51 0.10 0.00 0.51 0.10 0.00 0.75 0.05 0.00 0.10 0.07 0.16 0.10 0.07 0.16 1.40 0.1 > 4 0.00 -0.46 0.13 0.00 Brasil 1.14 0.04 0.00 1.14 0.04 0.00 0.38 0.11 0.00 0.38 0.11 0.00 0.64 0.08 0.00 0.70 0.12 0.00 0.70 0.12 0.00 0.37 0.09 0.00 0.41 0.11 0.00 0.41 0.11 0.00 0.82 0.1 > 5 0.00 -0.19 0.12 0.13 Chile 0.78 0.03 0.00 0.78 0.03 0.00 0.34 0.07 0.00 0.34 0.07 0.00 0.58 0.09 0.00 0.57 0.07 0.00 0.57 0.07 0.00 0.31 0.09 0.00 0.36 0.07 0.00 0.36 0.07 0.00 0.76 0.1 > 4 0.00 -0.21 0.12 0.08 Colombia 0.44 0.03 0.00 0.44 0.03 0.00 0.21 0.06 0.00 0.21 0.06 0.00 0.53 0.11 0.00 0.30 0.06 0.00 0.30 0.06 0.00 0.30 0.13 0.02 0.20 0.06 0.00 0.20 0.06 0.00 0.54 0.1 > 5 0.00 -0.02 0.14 0.90 Costa Rica 1.03 0.06 0.00 1.03 0.06 0.00 0.26 0.11 0.02 0.26 0.11 0.02 0.72 0.10 0.00 0.59 0.13 0.00 0.59 0.13 0.00 0.40 0.12 0.00 0.29 0.11 0.01 0.29 0.11 0.01 0.95 0.1 > 5 0.00 -0.25 0.14 0.08 Ecuador 1.90 0.10 0.00 1.90 0.10 0.00 0.40 0.13 0.00 0.40 0.13 0.00 0.75 0.06 0.00 0.74 0.16 0.00 0.74 0.16 0.00 0.54 0.07 0.00 0.37 0.12 0.00 0.37 0.12 0.00 1.01 0.1 > 4 0.00 -0.25 0.12 0.05 El Salvador 1.97 0.27 0.00 1.97 0.27 0.00 0.02 0.12 0.89 0.02 0.12 0.89 0.97 0.05 0.00 0.15 0.18 0.43 0.15 0.18 0.43 0.90 0.07 0.00 -0.00 0.13 0.98 -0.00 0.13 0.98 1.09 0.1 > 5 0.00 -0.11 0.15 0.47 Guatemala 2.22 0.13 0.00 2.22 0.13 0.00 0.61 0.26 0.02 0.61 0.26 0.02 0.74 0.11 0.00 1.36 0.30 0.00 1.36 0.30 0.00 0.42 0.13 0.00 0.66 0.28 0.02 0.66 0.28 0.02 0.83 0.1 > 6 0.00 -0.12 0.15 0.42 Guyana 0.65 0.05 0.00 0.65 0.05 0.00 0.34 0.07 0.00 0.34 0.07 0.00 0.54 0.10 0.00 0.50 0.07 0.00 0.50 0.07 0.00 0.29 0.11 0.01 0.34 0.07 0.00 0.34 0.07 0.00 0.62 0.1 > 5 0.00 -0.10 0.13 0.44 Honduras 2.01 0.16 0.00 2.01 0.16 0.00 0.23 0.18 0.20 0.23 0.18 0.20 0.89 0.08 0.00 0.13 0.27 0.65 0.13 0.27 0.65 0.89 0.12 0.00 0.25 0.21 0.25 0.25 0.21 0.25 0.94 0.1 > 7 0.00 -0.07 0.20 0.74 Jamaica 1.25 0.17 0.00 1.25 0.17 0.00 0.37 0.12 0.00 0.37 0.12 0.00 0.77 0.07 0.00 0.73 0.15 0.00 0.73 0.15 0.00 0.55 0.09 0.00 0.33 0.12 0.01 0.33 0.12 0.01 1.03 0.1 > 5 0.00 -0.27 0.13 0.05 México 1.27 0.07 0.00 1.27 0.07 0.00 0.18 0.08 0.04 0.18 0.08 0.04 0.78 0.06 0.00 0.31 0.09 0.00 0.31 0.09 0.00 0.61 0.06 0.00 0.18 0.08 0.03 0.18 0.08 0.03 0.69 0.1 > 6 0.00 0.06 0.14 0.65 Nicaragua 0.37 0.09 0.00 0.37 0.09 0.00 0.09 0.06 0.15 0.09 0.06 0.15 0.81 0.08 0.00 0.20 0.09 0.03 0.20 0.09 0.03 0.59 0.11 0.00 0.09 0.07 0.19 0.09 0.07 0.19 0.95 0.1 > 5 0.00 -0.16 0.15 0.29 Olade 0.99 0.02 0.00 0.99 0.02 0.00 0.38 0.09 0.00 0.38 0.09 0.00 0.58 0.08 0.00 0.67 0.09 0.00 0.67 0.09 0.00 0.29 0.08 0.00 0.35 0.08 0.00 0.35 0.08 0.00 0.94 0.1 > 5 0.00 -0.32 0.11 0.01 Panamá 0.60 0.06 0.00 0.60 0.06 0.00 0.17 0.07 0.01 0.17 0.07 0.01 0.77 0.09 0.00 0.27 0.08 0.00 0.27 0.08 0.00 0.61 0.12 0.00 0.18 0.07 0.01 0.18 0.07 0.01 0.79 0.1 > 6 0.00 -0.02 0.16 0.90 Paraguay 1.47 0.07 0.00 1.47 0.07 0.00 0.38 0.14 0.01 0.38 0.14 0.01 0.74 0.09 0.00 0.85 0.18 0.00 0.85 0.18 0.00 0.43 0.11 0.00 0.42 0.15 0.01 0.42 0.15 0.01 0.99 0.1 > 5 0.00 -0.29 0.13 0.04 Perú 0.85 0.04 0.00 0.85 0.04 0.00 0.41 0.07 0.00 0.41 0.07 0.00 0.56 0.09 0.00 0.62 0.07 0.00 0.62 0.07 0.00 0.33 0.09 0.00 0.40 0.08 0.00 0.40 0.08 0.00 0.69 0.1 > 5 0.00 -0.14 0.12 0.27 República Dominicana 0.81 0.05 0.00 0.81 0.05 0.00 0.14 0.08 0.07 0.14 0.08 0.07 0.80 0.08 0.00 0.27 0.09 0.01 0.27 0.09 0.01 0.63 0.11 0.00 0.14 0.08 0.09 0.14 0.08 0.09 0.80 0.1 > 5 0.00 0.00 0.15 0.97 Suriname -0.32 0.15 0.03 -0.32 0.15 0.03 0.01 0.08 0.95 0.01 0.08 0.95 0.89 0.07 0.00 0.01 0.11 0.90 0.01 0.11 0.90 0.79 0.10 0.00 0.02 0.08 0.84 0.02 0.08 0.84 0.85 0.1 > 5 0.00 0.03 0.15 0.82 Uruguay 0.26 0.09 0.01 0.26 0.09 0.01 0.09 0.06 0.18 0.09 0.06 0.18 0.74 0.10 0.00 0.18 0.08 0.03 0.18 0.08 0.03 0.49 0.12 0.00 0.10 0.07 0.15 0.10 0.07 0.15 0.80 0.1 > 5 0.00 -0.10 0.15 0.52 -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- > ------------------------
Greetings,
Sebastián.