Code:
* Example generated by -dataex-. To install: ssc install dataex clear input str3 country int year float(y k l) double pop "AUS" 2010 12062 125 1266931 22031800 "AUS" 2011 12097 125 1331552.4 22340000 "AUS" 2012 11804 125 1372073.3 22733500 "AUS" 2013 11927 320 1383774 23128100 "AUT" 2010 6105 156 400250 8363400 "AUT" 2011 5910 157 407280 8391600 "AUT" 2012 5929 161 414700 8430000 "AUT" 2013 5954 163 419940 8479800 "BEL" 2010 7634 116 529000 10895600 "BEL" 2011 7406 118 545900 11038300 "BEL" 2012 7407 118 558500 11106900 "BEL" 2013 7423 121 567700 11159400 "CAN" 2010 22427 281 1782535 34004900 "CAN" 2011 22418 293 1817985 34339300 "CAN" 2012 22698 308 1832145 34714200 "CAN" 2013 22866 312 1856910 35083000 "CZE" 2010 14061 66 298508 10474400 "CZE" 2011 13344 72 306410 10496100 "CZE" 2012 13458 73 310430 10510800 "CZE" 2013 13556 78 312427 10514300 "DEU" 2010 76107 2211 4875000 81776900 "DEU" 2011 73488 2317 4965000 80275000 "DEU" 2012 71494 2305 5086000 80425800 "DEU" 2013 70713 2332 5192000 80645600 "ESP" 2010 27978 558 1327400 46576900 "ESP" 2011 27643 643 1353300 46742700 "ESP" 2012 27190 691 1311000 46773100 "ESP" 2013 26921 715 1294000 46620000 "EST" 2010 2015 11 33800 1331500 "EST" 2011 1867 13 34120 1327400 "EST" 2012 1882 13 34820 1322700 "EST" 2013 1728 15 36040 1318000 "FIN" 2010 4325 100 372000 5363400 "FIN" 2011 4163 109 382000 5388300 "FIN" 2012 4150 117 392400 5414000 "FIN" 2013 4010 120 395900 5439000 "GBR" 2010 52018 411.32 3642401 62766400 "GBR" 2011 49173 440.52 3689673 63258800 "GBR" 2012 48532 456.1 3710859 63700200 "GBR" 2013 48319 461.53 3808592 64128300 "HUN" 2010 17497 30 265258 10000000 "HUN" 2011 17220 30 276400 9971700 "HUN" 2012 17143 28 270666 9920400 "HUN" 2013 16603 30 279869 9893100 "ISL" 2010 132 7 20200 318000 "ISL" 2011 128 7 19800 319000 "ISL" 2012 132 7 19900 320700 "ISL" 2013 148 7 20200 323800 "KOR" 2010 26747 985 1162000 49554100 "KOR" 2011 26118 1062 1328200 49936600 "KOR" 2012 26250 1173 1415300 50199900 "KOR" 2013 25569 1228 1565500 50428900 "LTU" 2010 5975 15 87619.26 3097300 "LTU" 2011 5808 18 87363.11 3028100 "LTU" 2012 5708 30 85478.87 2987800 "LTU" 2013 5563 31 84770.83 2957700 "LUX" 2010 328 7 32115 507000 "LUX" 2011 306 7 33880 518299.99999999994 "LUX" 2012 279 7 36024 530900 "LUX" 2013 321 7 38707 543400 "NLD" 2010 11417 203 1394000 16615400.000000002 "NLD" 2011 11124 215 1420000 16693099.999999998 "NLD" 2012 11223 198 1436000 16755000 "NLD" 2013 10701 193 1427000 16804400 "SVN" 2010 1731 16 54797.85 2048600 "SVN" 2011 1693 18 55898.38 2052800.0000000002 "SVN" 2012 1641 18 57453.17 2057199.9999999998 "SVN" 2013 1646 19 57681.16 2060000 "TUR" 2010 49379 678 590375 73142200 "TUR" 2011 50573 709 692675 74223600 "TUR" 2012 50149 720 807950 75175800 "TUR" 2013 59183 751 858125 76147600 end
Code:
*==================== * Prepare data for modelling *==================== * Encode country encode country, gen(country_encoded) * Transform variables into ln form (I'm estimating a Cobb-Douglas model) foreach var in y k l d pop { gen ln`var' = ln(`var') } * Do xtset xtset country_encoded year *==================== * Apply one-step difference GMM *==================== xtabond2 lny l.lny lnk lnl lnpop i.year, gmm(l.lny lnk lnl lnpop, collapse) iv(i.year) noleveleq nodiffsargan robust small
Code:
predict r, residuals histogram r
Thanks!
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