Hello,
After a month of work I have started to doubt the validity of using dynamic panel approach in Stata and even any software. I discovered that the generated results can vary tremendously depending on your lag assumptions and that the results in general are chaotic.
My understanding is that dynamic models shouldn't lead to huge differences in results from OLS and Fixed Effects models especially that I don't have a small sample issue.
My results for Fixed Effects and Pooled OLs are very powerful, they suit well my hypotheses and are in accordance with the theory. But when I applied the regressions in a dynamic model setting using xtabond2 (theoretically dynamic are the ones to be used when the dependent variable is explained by its value since the the lagged dependent is correlated with the error term). I have been trying for one month to generate feasible results, however I am receiving completely different coefficients that are very far from the OLS and Fixed Effects results and are not theoretically justified. This convinced me that either Dynamic panel results are chaotic and arbitrary or that I am overlooking a simple procedure to generate results that make sense.
Here are my results for the OLS and Fixed Effects regressions:
I appreciate any feedback that could shed a light on this implausible issue,
After a month of work I have started to doubt the validity of using dynamic panel approach in Stata and even any software. I discovered that the generated results can vary tremendously depending on your lag assumptions and that the results in general are chaotic.
My understanding is that dynamic models shouldn't lead to huge differences in results from OLS and Fixed Effects models especially that I don't have a small sample issue.
My results for Fixed Effects and Pooled OLs are very powerful, they suit well my hypotheses and are in accordance with the theory. But when I applied the regressions in a dynamic model setting using xtabond2 (theoretically dynamic are the ones to be used when the dependent variable is explained by its value since the the lagged dependent is correlated with the error term). I have been trying for one month to generate feasible results, however I am receiving completely different coefficients that are very far from the OLS and Fixed Effects results and are not theoretically justified. This convinced me that either Dynamic panel results are chaotic and arbitrary or that I am overlooking a simple procedure to generate results that make sense.
Here are my results for the OLS and Fixed Effects regressions:
Code:
. //pooled OLS . regress roeavgw L.roeavgw lconw LConNegavgw lcoffw LCoffNegavgw DLL DLLNegavgw carw CARNegavgw Drg DrgNegavgw costincomew > costincomeNegavg eqcgtaw revdivw sizeassetsw gdpg gap hh inflation i.year Source | SS df MS Number of obs = 256,215 -------------+---------------------------------- F(32, 256182) = 16321.62 Model | 6949199.83 32 217162.495 Prob > F = 0.0000 Residual | 3408554.45 256,182 13.3052067 R-squared = 0.6709 -------------+---------------------------------- Adj R-squared = 0.6709 Total | 10357754.3 256,214 40.4261839 Root MSE = 3.6476 ----------------------------------------------------------------------------------- roeavgw | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------------------+---------------------------------------------------------------- roeavgw | L1. | .3971417 .0015851 250.55 0.000 .3940349 .4002484 | lconw | .0274215 .0006878 39.87 0.000 .0260734 .0287695 LConNegavgw | .0179526 .0022544 7.96 0.000 .0135341 .0223712 lcoffw | -.0154726 .0027088 -5.71 0.000 -.0207818 -.0101634 LCoffNegavgw | .1270667 .0079808 15.92 0.000 .1114245 .1427088 DLL | -.0168602 .0006222 -27.10 0.000 -.0180797 -.0156408 DLLNegavgw | -.113601 .0010032 -113.24 0.000 -.1155673 -.1116347 carw | .0160214 .0022626 7.08 0.000 .0115867 .0204561 CARNegavgw | .1614652 .0038218 42.25 0.000 .1539745 .1689559 Drg | 1237.047 84.7893 14.59 0.000 1070.862 1403.231 DrgNegavgw | 6894.579 248.1179 27.79 0.000 6408.275 7380.883 costincomew | -.1372356 .0008017 -171.18 0.000 -.1388069 -.1356642 costincomeNegavgw | -.0360034 .001089 -33.06 0.000 -.0381378 -.0338689 eqcgtaw | -.161473 .0029454 -54.82 0.000 -.1672458 -.1557001 revdivw | .1374203 .0011855 115.92 0.000 .1350967 .1397439 sizeassetsw | -.3366174 .0107229 -31.39 0.000 -.3576339 -.3156008 gdpg | .2105167 .0058221 36.16 0.000 .1991055 .2219279 gap | .000367 .0001817 2.02 0.043 .0000108 .0007232 hh | -.0000786 5.38e-06 -14.61 0.000 -.0000891 -.000068 inflation | -1.12732 .003604 -312.80 0.000 -1.134383 -1.120256 | year | 2002 | -.7356892 .0484119 -15.20 0.000 -.8305753 -.6408032 2003 | -.6645746 .0514692 -12.91 0.000 -.7654528 -.5636964 2004 | -.208966 .0500894 -4.17 0.000 -.3071398 -.1107921 2005 | .1314741 .0506474 2.60 0.009 .0322066 .2307417 2006 | .0016818 .0515721 0.03 0.974 -.099398 .1027617 2007 | -1.141754 .05628 -20.29 0.000 -1.252062 -1.031447 2008 | -.1841005 .0701736 -2.62 0.009 -.3216388 -.0465621 2009 | -1.5462 .0637728 -24.25 0.000 -1.671193 -1.421208 2010 | -.3790909 .0665499 -5.70 0.000 -.509527 -.2486548 2011 | -.1778272 .066232 -2.68 0.007 -.3076401 -.0480143 2012 | .5179759 .0694484 7.46 0.000 .3818589 .6540929 2013 | .1009313 .0678153 1.49 0.137 -.0319849 .2338475 | _cons | 14.76652 .1427936 103.41 0.000 14.48665 15.04639 ----------------------------------------------------------------------------------- . . regress roeavgw L.roeavgw lconw LConNegavgw lcoffw LCoffNegavgw DLL DLLNegavgw carw CARNegavgw Drg DrgNegavgw costincomew > costincomeNegavg eqcgtaw revdivw sizeassetsw gdpg gap hh inflation i.year if sz_large == 1 Source | SS df MS Number of obs = 2,854 -------------+---------------------------------- F(32, 2821) = 202.57 Model | 119108.133 32 3722.12916 Prob > F = 0.0000 Residual | 51835.7242 2,821 18.3749465 R-squared = 0.6968 -------------+---------------------------------- Adj R-squared = 0.6933 Total | 170943.857 2,853 59.91723 Root MSE = 4.2866 ----------------------------------------------------------------------------------- roeavgw | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------------------+---------------------------------------------------------------- roeavgw | L1. | .4478967 .0143403 31.23 0.000 .4197781 .4760153 | lconw | -.0112788 .0102626 -1.10 0.272 -.0314018 .0088441 LConNegavgw | .032871 .0129993 2.53 0.012 .0073819 .0583602 lcoffw | .0181506 .0267296 0.68 0.497 -.0342608 .0705621 LCoffNegavgw | .0601 .0353409 1.70 0.089 -.0091967 .1293967 DLL | -.0014191 .0070631 -0.20 0.841 -.0152685 .0124303 DLLNegavgw | -.0772503 .0078993 -9.78 0.000 -.0927393 -.0617613 carw | .0707043 .0366496 1.93 0.054 -.0011583 .142567 CARNegavgw | .0441851 .0258885 1.71 0.088 -.0065772 .0949473 Drg | -2844.248 1371.875 -2.07 0.038 -5534.227 -154.2693 DrgNegavgw | 8238.426 1519.591 5.42 0.000 5258.803 11218.05 costincomew | -.1137821 .0110077 -10.34 0.000 -.135366 -.0921981 costincomeNegavgw | -.0442549 .0118836 -3.72 0.000 -.0675564 -.0209534 eqcgtaw | -.1946006 .0276027 -7.05 0.000 -.2487241 -.1404771 revdivw | .1350576 .0101463 13.31 0.000 .1151626 .1549525 sizeassetsw | -.5806133 .2793035 -2.08 0.038 -1.128273 -.0329535 gdpg | .1978534 .0622663 3.18 0.002 .0757614 .3199454 gap | -.0000512 .0019546 -0.03 0.979 -.0038838 .0037814 hh | -.0000747 .0000461 -1.62 0.105 -.0001652 .0000157 inflation | -1.34687 .0372393 -36.17 0.000 -1.419889 -1.273851 | year | 2002 | -1.024305 .4651085 -2.20 0.028 -1.936292 -.1123175 2003 | -.9640165 .5134956 -1.88 0.061 -1.970881 .0428485 2004 | -.894301 .4736394 -1.89 0.059 -1.823016 .0344136 2005 | -.643246 .4720555 -1.36 0.173 -1.568855 .282363 2006 | -.4326105 .4677691 -0.92 0.355 -1.349815 .4845936 2007 | -2.533086 .4949623 -5.12 0.000 -3.50361 -1.562561 2008 | -3.201493 .6268909 -5.11 0.000 -4.430704 -1.972282 2009 | -4.378072 .6884812 -6.36 0.000 -5.72805 -3.028095 2010 | -2.830637 .690961 -4.10 0.000 -4.185477 -1.475797 2011 | -1.003674 .717223 -1.40 0.162 -2.410009 .4026601 2012 | -1.038119 .7168958 -1.45 0.148 -2.443812 .3675743 2013 | -1.736967 .7367133 -2.36 0.018 -3.181518 -.2924156 | _cons | 20.27332 4.231452 4.79 0.000 11.97626 28.57037 ----------------------------------------------------------------------------------- . . //Fixed Effect . xtreg roeavgw L.roeavgw lconw LConNegavgw lcoffw LCoffNegavgw DLL DLLNegavgw carw CARNegavgw Drg DrgNegavgw costincomew c > ostincomeNegavg eqcgtaw revdivw sizeassetsw gdpg gap hh inflation i.year, fe Fixed-effects (within) regression Number of obs = 256,215 Group variable: rssd9001 Number of groups = 8,463 R-sq: Obs per group: within = 0.5921 min = 1 between = 0.7628 avg = 30.3 overall = 0.6412 max = 52 F(32,247720) = 11236.87 corr(u_i, Xb) = 0.0972 Prob > F = 0.0000 ----------------------------------------------------------------------------------- roeavgw | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------------------+---------------------------------------------------------------- roeavgw | L1. | .2181716 .0016662 130.94 0.000 .2149059 .2214374 | lconw | .03776 .0013078 28.87 0.000 .0351969 .0403232 LConNegavgw | .0244018 .0024762 9.85 0.000 .0195485 .029255 lcoffw | .0889885 .0044246 20.11 0.000 .0803164 .0976607 LCoffNegavgw | .0467325 .0091096 5.13 0.000 .0288778 .0645871 DLL | .0012758 .0007983 1.60 0.110 -.0002888 .0028404 DLLNegavgw | -.1444623 .0010513 -137.42 0.000 -.1465228 -.1424018 carw | .0218343 .0023238 9.40 0.000 .0172798 .0263888 CARNegavgw | .1542742 .0040023 38.55 0.000 .1464298 .1621186 Drg | 284.7925 91.50798 3.11 0.002 105.4393 464.1457 DrgNegavgw | 6855.552 266.6159 25.71 0.000 6332.992 7378.112 costincomew | -.195189 .0013185 -148.04 0.000 -.1977732 -.1926049 costincomeNegavgw | -.0237514 .0011927 -19.91 0.000 -.0260891 -.0214138 eqcgtaw | -.1005786 .0050358 -19.97 0.000 -.1104487 -.0907085 revdivw | .1454887 .0019641 74.08 0.000 .1416392 .1493382 sizeassetsw | -.7470183 .0419119 -17.82 0.000 -.8291645 -.664872 gdpg | .1440672 .0053648 26.85 0.000 .1335523 .154582 gap | .0014688 .000168 8.74 0.000 .0011396 .001798 hh | -2.80e-06 7.73e-06 -0.36 0.717 -.0000179 .0000123 inflation | -1.024179 .0037139 -275.77 0.000 -1.031458 -1.0169 | year | 2002 | -.5752657 .046052 -12.49 0.000 -.6655263 -.4850051 2003 | -.114553 .0507574 -2.26 0.024 -.2140361 -.0150699 2004 | .3188279 .0515795 6.18 0.000 .2177335 .4199224 2005 | .4477712 .051978 8.61 0.000 .3458957 .5496468 2006 | -.0036491 .0522223 -0.07 0.944 -.1060034 .0987052 2007 | -1.413015 .0563046 -25.10 0.000 -1.523371 -1.302659 2008 | -.8616926 .0700671 -12.30 0.000 -.9990223 -.7243628 2009 | -1.65588 .0682372 -24.27 0.000 -1.789623 -1.522137 2010 | -.457155 .0738302 -6.19 0.000 -.6018603 -.3124497 2011 | .1503186 .0753015 2.00 0.046 .0027298 .2979075 2012 | 1.071721 .0802658 13.35 0.000 .9144027 1.22904 2013 | 1.001874 .0814396 12.30 0.000 .8422547 1.161494 | _cons | 21.73754 .519171 41.87 0.000 20.71998 22.7551 ------------------+---------------------------------------------------------------- sigma_u | 2.3559056 sigma_e | 3.3317545 rho | .33333323 (fraction of variance due to u_i) ----------------------------------------------------------------------------------- F test that all u_i=0: F(8462, 247720) = 7.01 Prob > F = 0.0000 . . xtreg roeavgw L.roeavgw lconw LConNegavgw lcoffw LCoffNegavgw DLL DLLNegavgw carw CARNegavgw Drg DrgNegavgw costincomew c > ostincomeNegavg eqcgtaw revdivw sizeassetsw gdpg gap hh inflation i.year if sz_large == 1, fe Fixed-effects (within) regression Number of obs = 2,854 Group variable: rssd9001 Number of groups = 251 R-sq: Obs per group: within = 0.6100 min = 1 between = 0.6969 avg = 11.4 overall = 0.6606 max = 46 F(32,2571) = 125.65 corr(u_i, Xb) = 0.0652 Prob > F = 0.0000 ----------------------------------------------------------------------------------- roeavgw | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------------------+---------------------------------------------------------------- roeavgw | L1. | .2522249 .0158255 15.94 0.000 .2211929 .2832569 | lconw | -.00023 .0198824 -0.01 0.991 -.0392171 .038757 LConNegavgw | .0051098 .017249 0.30 0.767 -.0287136 .0389332 lcoffw | .0944378 .0554664 1.70 0.089 -.0143255 .2032011 LCoffNegavgw | .0981468 .0461399 2.13 0.034 .0076717 .188622 DLL | -.0391742 .0114804 -3.41 0.001 -.061686 -.0166624 DLLNegavgw | -.0835019 .0091809 -9.10 0.000 -.1015047 -.0654991 carw | .0330242 .0456547 0.72 0.470 -.0564995 .122548 CARNegavgw | .0486497 .0320658 1.52 0.129 -.0142277 .111527 Drg | -4816.351 1651.257 -2.92 0.004 -8054.281 -1578.422 DrgNegavgw | 7752.787 1914.667 4.05 0.000 3998.342 11507.23 costincomew | -.1468866 .0178185 -8.24 0.000 -.1818268 -.1119465 costincomeNegavgw | -.0375357 .0148414 -2.53 0.011 -.066638 -.0084335 eqcgtaw | -.1470841 .054429 -2.70 0.007 -.2538132 -.0403549 revdivw | .1900046 .0190765 9.96 0.000 .1525978 .2274115 sizeassetsw | -2.190867 .7146737 -3.07 0.002 -3.592262 -.7894731 gdpg | .1716367 .0592037 2.90 0.004 .0555449 .2877285 gap | -.0002034 .0018777 -0.11 0.914 -.0038853 .0034785 hh | -.0001164 .0000787 -1.48 0.139 -.0002708 .000038 inflation | -1.386672 .0417323 -33.23 0.000 -1.468505 -1.30484 | year | 2002 | -.9735441 .4713765 -2.07 0.039 -1.89786 -.049228 2003 | -1.277842 .5518724 -2.32 0.021 -2.360001 -.1956822 2004 | -1.653339 .5452736 -3.03 0.002 -2.722559 -.5841189 2005 | -1.679689 .5423525 -3.10 0.002 -2.743181 -.6161968 2006 | -1.372545 .5466321 -2.51 0.012 -2.444428 -.3006607 2007 | -3.615571 .5784606 -6.25 0.000 -4.749866 -2.481275 2008 | -3.451909 .7047984 -4.90 0.000 -4.833939 -2.069879 2009 | -3.676669 .8217015 -4.47 0.000 -5.287933 -2.065405 2010 | -2.309551 .8710174 -2.65 0.008 -4.017518 -.6015843 2011 | -.6592042 .9113234 -0.72 0.470 -2.446207 1.127798 2012 | -.7587979 .9294192 -0.82 0.414 -2.581284 1.063688 2013 | -2.225555 .9646078 -2.31 0.021 -4.117042 -.3340679 | _cons | 48.25691 10.95059 4.41 0.000 26.78404 69.72978 ------------------+---------------------------------------------------------------- sigma_u | 3.2985744 sigma_e | 3.9477583 rho | .41112538 (fraction of variance due to u_i) ----------------------------------------------------------------------------------- F test that all u_i=0: F(250, 2571) = 3.02 Prob > F = 0.0000 .
I appreciate any feedback that could shed a light on this implausible issue,
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