Ανεργία στο Ιόνιο 1998 - 2013, Ανάλυση Stata

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  1. 1. 1998 - 2013 : 8130096 : . 1
  2. 2. Stata/MP 13 . 2
  3. 3. Ioni__un 3
  4. 4. Plot ioni__un time 1 time 64 +----------------------------------------------------------------+ 3.4 + ** * | ** ** * * * * | * ** | * * * | * * * * * * | * * * * * * | * * n | * * * * u | * * * * * * * * _ | * * * * * _ | * * * * i | * * * n | * * o | * * i | * | | * * * | | | * 23.8 + . plot ioni__un time 4
  5. 5. q2 q3 q4 (0 1) Q1 , 5
  6. 6. Regress ioni__un q2 q3 q4 _cons 15.325 .9360402 16.37 0.000 13.45264 17.19736 q4 -2.6375 1.323761 -1.99 0.051 -5.285416 .0104155 q3 -8.58125 1.323761 -6.48 0.000 -11.22917 -5.933334 q2 -5.6375 1.323761 -4.26 0.000 -8.285416 -2.989584 ioni__un Coef. Std. Err. t P>|t| [95% Conf. Interval] Total 1502.6023 63 23.8508302 Root MSE = 3.7442 Adj R-squared = 0.4122 Residual 841.12435 60 14.0187392 R-squared = 0.4402 Model 661.477949 3 220.49265 Prob > F = 0.0000 F( 3, 60) = 15.73 Source SS df MS Number of obs = 64 . regress ioni__un q2 q3 q4 q2 q3 q4 6
  7. 7. resQ Residuals 7
  8. 8. Predict resQ, res more 1 time 64 +----------------------------------------------------------------+ -6.1875 + ** | * | * * * * * | * * * * * | * * * * * | * * * * ** * s | * ** * *** l | * ** * * a | * **** * * u | * * d | * * ** i | * s | * * e | R | * * | ** ** | * * | * | * | * 8.475 + . plot resQ time . predict resQ, res , 2 , 2 8 back
  9. 9. time2 time3 time4 time. , . 9
  10. 10. regress ioni__un q2 q3 q4 time time2 time3 time4 time5 _cons 9.883518 1.760364 5.61 0.000 6.35567 13.41137 time5 -3.32e-07 1.98e-07 -1.68 0.099 -7.29e-07 6.44e-08 time4 .0000485 .0000323 1.50 0.139 -.0000162 .0001132 time3 -.0021532 .0019109 -1.13 0.265 -.0059827 .0016763 time2 .0246947 .0494313 0.50 0.619 -.0743679 .1237573 time .304846 .5288751 0.58 0.567 -.7550433 1.364735 q4 -3.251528 .7176825 -4.53 0.000 -4.689796 -1.81326 q3 -8.997275 .71314 -12.62 0.000 -10.42644 -7.56811 q2 -5.847875 .7104521 -8.23 0.000 -7.271653 -4.424098 ioni__un Coef. Std. Err. t P>|t| [95% Conf. Interval] Total 1502.6023 63 23.8508302 Root MSE = 2.0067 Adj R-squared = 0.8312 Residual 221.477809 55 4.02686925 R-squared = 0.8526 Model 1281.12449 8 160.140561 Prob > F = 0.0000 F( 8, 55) = 39.77 Source SS df MS Number of obs = 64 . regress ioni__un q2 q3 q4 time time2 time3 time4 time5 5 . 10
  11. 11. regress ioni__un q2 q3 q4 time time2 time3 time4 , _cons 8.153499 1.450063 5.62 0.000 5.248673 11.05832 time4 -5.47e-06 3.20e-06 -1.71 0.093 -.0000119 9.41e-07 time3 .0009785 .0004195 2.33 0.023 .0001382 .0018189 time2 -.0526257 .0182199 -2.89 0.005 -.0891244 -.0161269 time 1.047265 .2946272 3.55 0.001 .4570555 1.637474 q4 -3.382887 .7248872 -4.67 0.000 -4.83501 -1.930763 q3 -9.084094 .7227115 -12.57 0.000 -10.53186 -7.636329 q2 -5.892416 .7213851 -8.17 0.000 -7.337524 -4.447308 ioni__un Coef. Std. Err. t P>|t| [95% Conf. Interval] Total 1502.6023 63 23.8508302 Root MSE = 2.039 Adj R-squared = 0.8257 Residual 232.823334 56 4.15755953 R-squared = 0.8451 Model 1269.77897 7 181.396995 Prob > F = 0.0000 F( 7, 56) = 43.63 Source SS df MS Number of obs = 64 . regress ioni__un q2 q3 q4 time time2 time3 time4 11
  12. 12. regress ioni__un q2 q3 q4 time time2 time3 ! _cons 9.675736 1.163599 8.32 0.000 7.345668 12.0058 time3 .0002669 .0000526 5.07 0.000 .0001615 .0003722 time2 -.0227311 .0052006 -4.37 0.000 -.033145 -.0123171 time .6075427 .1460807 4.16 0.000 .3150212 .9000643 q4 -3.382887 .7370101 -4.59 0.000 -4.858724 -1.907049 q3 -9.07133 .7347588 -12.35 0.000 -10.54266 -7.600001 q2 -5.879652 .7334101 -8.02 0.000 -7.348281 -4.411024 ioni__un Coef. Std. Err. t P>|t| [95% Conf. Interval] Total 1502.6023 63 23.8508302 Root MSE = 2.0731 Adj R-squared = 0.8198 Residual 244.973638 57 4.29778313 R-squared = 0.8370 Model 1257.62866 6 209.604777 Prob > F = 0.0000 F( 6, 57) = 48.77 Source SS df MS Number of obs = 64 . regress ioni__un q2 q3 q4 time time2 time3 12
  13. 13. regress , r robust . 13
  14. 14. regress ioni_un q2 q3 q4 time time2 time3, r _cons 9.675736 .8181827 11.83 0.000 8.037353 11.31412 time3 .0002669 .0000477 5.60 0.000 .0001714 .0003623 time2 -.0227311 .0046558 -4.88 0.000 -.0320541 -.013408 time .6075427 .1202947 5.05 0.000 .3666567 .8484287 q4 -3.382887 .9053217 -3.74 0.000 -5.195762 -1.570011 q3 -9.07133 .7290871 -12.44 0.000 -10.5313 -7.611359 q2 -5.879652 .8004959 -7.35 0.000 -7.482618 -4.276687 ioni__un Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust Root MSE = 2.0731 R-squared = 0.8370 Prob > F = 0.0000 F( 6, 57) = 86.07 Linear regression Number of obs = 64 . regress ioni__un q2 q3 q4 time time2 time3, r 14
  15. 15. Predict CycleiC, res 1 time 64 +----------------------------------------------------------------+ -4.52839 + * | * * * | * * * * | * * | * * ** * * | * * * * s | * * l | * * ** * * a | * * u | * * ** * d | * * * * i | * * * * * s | * * * * * e | * * * * R | * ** * * * * | * | * | | * | * 5.04697 + . plot CycleiC time . predict CycleiC, res , . 15
  16. 16. icycle1 icycle2 (0 1) . CycleiC. 16
  17. 17. regress ioni_un q2 q3 q4 time time2 time3 icycle1 icycle2, r _cons 12.18663 1.588765 7.67 0.000 9.002677 15.37059 icycle2 -3.384269 .7906453 -4.28 0.000 -4.968758 -1.799781 icycle1 -1.750442 1.108307 -1.58 0.120 -3.971538 .470655 time3 .0000906 .0000633 1.43 0.158 -.0000363 .0002174 time2 -.0064051 .0064293 -1.00 0.323 -.0192898 .0064795 time .2181866 .1867907 1.17 0.248 -.1561504 .5925235 q4 -3.07948 .8001803 -3.85 0.000 -4.683078 -1.475883 q3 -9.048444 .624026 -14.50 0.000 -10.29902 -7.797868 q2 -5.814108 .6787971 -8.57 0.000 -7.174447 -4.453768 ioni__un Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust Root MSE = 1.7977 R-squared = 0.8817 Prob > F = 0.0000 F( 8, 55) = 73.16 Linear regression Number of obs = 64 . regress ioni__un q2 q3 q4 time time2 time3 icycle1 icycle2, r . 17
  18. 18. Excel StataSE 18
  19. 19. plot cycleC time -4000000.00 -3000000.00 -2000000.00 -1000000.00 0.00 1000000.00 2000000.00 3000000.00 4000000.00 5000000.00 6000000.00 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 cycleC cycleC 19
  20. 20. Plot cycleCb time -4000000.00 -3000000.00 -2000000.00 -1000000.00 0.00 1000000.00 2000000.00 3000000.00 4000000.00 5000000.00 6000000.00 time 3,00 8,00 12,00 16,00 24,00 27,00 29,00 32,00 36,00 40,00 44,00 47,00 50,00 52,00 53,00 54,00 56,00 63,00 cycleC cycleC cycleCb cycleC 21-45 54-63 20
  21. 21. : 0.00 200000.00 400000.00 600000.00 800000.00 1000000.00 1200000.00 1400000.00 1600000.00 1800000.00 0.00 22.5 57.5 cycleC cycleC 1998, cycleCb. , time time2. 21
  22. 22. : 22
  23. 23. 23 -4000000.00 -3000000.00 -2000000.00 -1000000.00 0.00 1000000.00 2000000.00 3000000.00 4000000.00 5000000.00 6000000.00 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 Res cycleC cycleC
  24. 24. StataSe : 24
  25. 25. regress ioni__un q2 q3 q4 time time2 time3 cycle1 cycle2, r 25. _cons 6.935683 1.095513 6.33 0.000 4.740226 9.13114 cycle2 3.210405 .9126783 3.52 0.001 1.381357 5.039453 cycle1 1.925555 .9993352 1.93 0.059 -.0771572 3.928268 time3 .0002892 .0000437 6.62 0.000 .0002017 .0003768 time2 -.0256592 .0042091 -6.10 0.000 -.0340943 -.0172241 time .7343702 .1008238 7.28 0.000 .5323147 .9364256 q4 -3.353378 .68731 -4.88 0.000 -4.730778 -1.975978 q3 -9.013013 .6141836 -14.67 0.000 -10.24386 -7.782161 q2 -5.911447 .6782324 -8.72 0.000 -7.270655 -4.552239 ioni__un Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust Root MSE = 1.757 R-squared = 0.8870 Prob > F = 0.0000 F( 8, 55) = 83.25 Linear regression Number of obs = 64 . regress ioni__un q2 q3 q4 time time2 time3 cycle1 cycle2, r