Lecture_02.xls

Data2013 2013

Country Name Country_C HH_Csmp GDP2005CONS GDP2005

1 Australia AUS 503.8 867.22 Austria AUT 182.9 349.53 Canada CAN 777.7 1319.34 China CHN 1774.8 4864.05 Denmark DNK 130.2 265.16 France FRA 1309.7 2351.97 Finland FIN 114.9 212.68 Germany DEU 1758.7 3161.99 Greece GRC 136.5 201.0

10 Hong Kong SAR, China HKG 153.4 241.011 India IND 883.5 1489.812 Italy ITA 1040.4 1759.613 Ireland IRL 96.6 217.314 Indonesia IDN 267.6 452.315 Korea, Rep. KOR 584.5 1199.916 Malaysia MYS 108.2 207.917 New Zealand NZL 79.6 130.318 Norway NOR 163.5 331.419 Philippines PHL 109.9 155.620 Russian Federation RUS 650.1 993.521 Singapore SGP 65.8 199.222 South Africa ZAF 211.6 323.723 Switzerland CHE 268.9 477.324 Sweden SWE 208.7 437.325 Thailand THA 122.5 230.426 Turkey TUR 447.7 653.627 United Kingdom GBR 1615.4 2578.728 Vietnam VNM 60.9 92.329 Japan JPN 2853.4 4784.5

Mean 575.2 1053.4

CONSUMPTION FUNCTION :: Linear Model2013 2013

Country N Country C GDP2005 (US$Billion) APCCONS GDP2005

1 Australia AUS 503.8 867.2 0.582 Austria AUT 182.9 349.5 0.523 Canada CAN 777.7 1319.3 0.594 China CHN 1774.8 4864.0 0.365 Denmark DNK 130.2 265.1 0.496 France FRA 1309.7 2351.9 0.567 Finland FIN 114.9 212.6 0.548 Germany DEU 1758.7 3161.9 0.569 Greece GRC 136.5 201.0 0.68

10 Hong Kong HKG 153.4 241.0 0.6411 India IND 883.5 1489.8 0.5912 Italy ITA 1040.4 1759.6 0.5913 Ireland IRL 96.6 217.3 0.4414 Indonesia IDN 267.6 452.3 0.5915 Korea, Rep KOR 584.5 1199.9 0.4916 Malaysia MYS 108.2 207.9 0.5217 New Zeala NZL 79.6 130.3 0.6118 Norway NOR 163.5 331.4 0.4919 PhilippinesPHL 109.9 155.6 0.7120 Russian Fe RUS 650.1 993.5 0.6521 Singapore SGP 65.8 199.2 0.3322 South AfricZAF 211.6 323.7 0.6523 Switzerlan CHE 268.9 477.3 0.5624 Sweden SWE 208.7 437.3 0.4825 Thailand THA 122.5 230.4 0.5326 Turkey TUR 447.7 653.6 0.6827 United Ki GBR 1615.4 2578.7 0.6328 Vietnam VNM 60.9 92.3 0.6629 Japan JPN 2853.4 4784.5 0.60

Mean 575.2 1053.4 0.6

HH Consumption (US$ Billion)

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.967578R Square 0.936207Adjusted R Square 0.933844Standard Error 176.7845Observations 29

ANOVAdf SS MS F Significance F

Regression 1 12383745 12383745 396.245 1.148E-17Residual 27 843824.2 31252.75

0 1000 2000 3000 4000 5000 60000

500

1000

1500

2000

2500

3000

HH CONSUMPTION vs GDP

GDP(2005) in US$

HOUS

EHO

LD C

ON

SUM

PTIO

N

Total 28 13227570

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept 43.59777 42.31965 1.030202 0.312056 -43.23498 130.4305 -43.23498 130.4305GDP2005 0.504685 0.025354 19.9059 1.148E-17 0.452664 0.556706 0.452664 0.556706

RESIDUAL OUTPUT

Observation Predicted CONSResiduals1 481.24 22.552 219.99 -37.053 709.42 68.244 2498.39 -723.635 177.41 -47.166 1230.59 79.157 150.90 -35.988 1639.38 119.369 145.05 -8.58

10 165.24 -11.8211 795.47 88.0512 931.62 108.7713 153.25 -56.6614 271.88 -4.2415 649.16 -64.6816 148.55 -40.3317 109.36 -29.7618 210.87 -47.3719 122.13 -12.1920 545.01 105.1221 144.14 -78.3022 206.99 4.6323 284.46 -15.5724 264.30 -55.6125 159.86 -37.3526 373.48 74.2127 1345.02 270.3928 90.17 -29.2729 2458.28 395.10

0 1000 2000 3000 4000 5000 60000

500

1000

1500

2000

2500

3000


GDP(2005) in US$

HOUS

EHO

LD C

ON

SUM

PTIO

N

Upper 95.0%

CONSUMPTION FUNCTION :: LOG_LOG Model2013

Country N Country CCONSUMPTION GDP log(CONS)



Mean 575.2 1053.4 5.7


GDP2005 (US$Billion)

2013 PLOTTING GRAPH

log(GDP2005) log(Consumption) vs Log(GDP)6.85.97.28.55.67.85.48.15.35.57.37.55.46.17.15.34.95.85.06.95.35.86.26.15.46.57.94.58.5

6.3

REGRESSIONModel: log(CONS) = a + b.log(GDP2005)

SUMMARY OUTPUT


4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 90

1

2

3

4

5

6

7

8

9


log(GDP(2005) )

log(

HO

USE

HO

LD C

ON

SUM

PTIO

N)

ANOVAdf SS MS

Regression 1 34.89234 34.89234Residual 27 0.860891 0.031885Total 28 35.75323

CoefficientsStandard Error t StatIntercept -0.513575 0.191682 -2.67931log(GDP2005) 0.98825 0.029874 33.08055

RESIDUAL OUTPUT

ObservationPredicted log(CONS)Residuals1 6.172148 0.0500012 5.274155 -0.0649763 6.586852 0.0694454 7.876288 -0.3948675 5.0011 -0.1316616 7.158206 0.019387 4.782897 -0.0386648 7.450671 0.021689 4.727542 0.188552

10 4.906888 0.12629311 6.706955 0.07694812 6.871441 0.0759113 4.804328 -0.23390414 5.529002 0.06067115 6.49309 -0.12236616 4.761007 -0.07690117 4.299092 0.07787918 5.221653 -0.12488919 4.47441 0.22545220 6.306589 0.17058121 4.71862 -0.53140622 5.198465 0.15631523 5.582001 0.01230224 5.495603 -0.15474425 4.862201 -0.05395326 5.892798 0.21128927 7.249165 0.13818328 3.95805 0.15119929 7.86001 0.09625

log(Consumption) vs Log(GDP)

4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 90

1

2

3

4

5

6

7

8

9


log(GDP(2005) )

log(

HO

USE

HO

LD C

ON

SUM

PTIO

N)

F Significance F1094.323 2.184E-23

P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%0.012411 -0.906873 -0.120276 -0.906873 -0.120276

2.184E-23 0.926953 1.049546 0.926953 1.049546

MINCER'S WAGE EQUATION Data: CPS112

wage educ exper hrswk married female metro midwest18.7 16 39 37 1 1 1 0

16.83 13 31 40 0 1 1 022 11 27 40 1 0 1 0

12.7 12 40 40 0 1 0 17.25 12 16 40 0 1 1 0

50 13 18 40 1 1 0 07.5 16 4 40 1 1 0 0

15.55 12 34 40 1 1 1 072.13 12 27 52 1 1 1 0

39.9 13 32 40 1 1 1 08 6 14 40 1 1 1 0

17 14 29 40 0 1 1 013.5 12 7 32 0 1 1 1

14.25 12 46 40 1 0 1 010.5 16 37 38 1 1 1 0

18.52 12 21 40 0 1 1 119.23 14 4 40 0 0 1 118.75 12 29 40 1 0 1 0

30.9 16 35 50 1 1 1 023 13 37 35 0 1 1 0

7 12 14 40 1 1 0 112 16 9 30 0 1 1 010 14 37 40 1 1 1 121 13 9 40 1 0 1 0

22.7 18 29 62 0 0 1 128.72 12 14 46 0 0 1 0

8.25 13 7 40 1 1 0 013.33 12 50 30 1 0 1 0

10 12 39 40 0 1 1 17.6 12 47 5 0 1 0 043 12 29 40 0 0 0 114 16 7 20 0 0 1 1

30.33 18 34 45 1 0 0 113 12 28 40 0 0 1 1

19.24 18 24 50 0 0 1 011 16 43 40 1 0 0 0

24.05 13 35 40 1 0 1 135.25 16 25 60 1 0 1 019.23 16 14 60 0 0 1 013.16 16 4 38 0 1 1 114.16 12 6 38 0 0 1 0

7.5 12 18 40 0 0 1 09.5 12 8 60 0 0 1 0

36.05 16 6 40 1 0 1 113 12 50 40 0 1 1 118 12 30 40 1 0 1 0

14.43 13 41 40 1 1 1 0

15.85 14 47 40 0 1 1 140.15 16 28 40 1 0 1 012.98 13 31 40 1 1 1 010.51 12 38 48 1 1 1 116.25 12 14 40 1 0 1 1

10 16 4 20 0 1 1 010.19 12 38 90 0 1 1 013.88 3 64 40 0 0 0 0

16 10 11 40 1 0 1 08 13 6 0 1 1 1 0

25 12 36 40 1 0 1 013 12 32 40 0 0 1 011 16 20 8 1 1 1 0

38.75 18 23 40 0 1 1 136.05 21 31 40 1 1 1 0

28 16 30 12 1 1 1 042.11 16 44 38 1 0 1 0

28 14 36 50 1 1 0 19 12 16 40 0 0 0 1

15 9 23 50 1 0 0 013.45 12 14 40 0 1 1 0

6.66 12 21 30 0 1 0 150 18 33 40 1 1 1 1

44.23 18 27 40 0 1 1 09 16 3 40 0 1 0 0

21.93 16 17 80 1 0 1 025.25 18 27 40 1 1 1 1

28 21 14 5 1 1 1 136.06 13 34 80 1 0 1 110.49 14 14 45 1 0 1 1

12.9 16 9 40 0 1 1 020.2 12 13 40 1 0 1 08.76 16 32 25 1 1 1 0

21.36 12 38 42 1 0 0 017.96 14 29 45 1 0 1 0

8.65 16 14 40 1 0 1 039.43 12 32 40 1 0 1 0

10 12 11 50 0 0 1 010.85 16 26 40 1 1 0 1

12 12 38 40 0 1 1 112 16 28 15 1 1 0 025 18 26 20 1 1 1 0

6.5 12 54 20 1 1 0 125 21 27 40 1 0 0 014 12 20 40 1 0 1 038 16 15 40 1 1 1 0

35.63 12 22 40 1 0 0 07.9 12 40 40 0 0 0 012 12 30 40 1 0 0 1

24.14 16 14 40 1 0 1 128.83 12 20 40 1 0 1 0

15 12 32 40 0 0 0 119.23 14 24 40 1 1 1 021.25 8 22 40 1 0 1 021.25 16 13 40 0 0 1 0

9 13 10 40 1 0 0 124.03 21 17 65 1 0 1 011.25 12 16 40 1 0 1 010.25 16 38 40 1 1 1 062.03 16 44 40 0 0 1 012.82 14 22 45 0 1 1 021.38 13 11 40 0 0 1 1

12 16 37 40 1 1 1 116.93 16 8 40 0 1 1 0

8.5 13 22 40 0 0 1 0

67 56 87 37

south west black asian NOB1 0 0 0 1 cps CURRENT POPULATION SURVEY0 0 0 0 2 YEAR 19970 1 0 0 3 sub-sample :0 0 0 0 40 0 1 0 5 wage earning0 0 0 0 6 educ years of education1 0 0 0 7 exper years of working experience1 0 0 0 8 hrswk hours of work per week0 1 0 0 9 married marital status0 0 0 0 10 female dummy var0 0 0 0 11 metro place of living in metropolitan area0 1 0 0 12 midwest location dummy0 0 0 0 13 south location dummy1 0 0 0 14 west location dummy1 0 1 0 15 black race=black0 0 0 0 16 asian race=Asian0 0 0 0 170 1 0 0 181 0 0 0 190 0 0 0 200 0 0 0 211 0 1 0 220 0 0 0 230 1 0 0 240 0 0 0 251 0 0 0 261 0 0 0 270 0 0 0 280 0 0 0 290 0 0 0 300 0 0 0 310 0 0 0 320 0 0 0 330 0 0 0 341 0 0 0 350 0 0 0 360 0 0 0 370 1 0 0 380 0 0 0 390 0 0 0 400 0 0 0 410 0 0 0 421 0 0 0 430 0 0 0 440 0 0 0 450 0 1 0 460 1 0 0 47

0 0 1 0 481 0 0 0 491 0 1 0 500 0 0 0 510 0 1 0 520 0 0 0 531 0 0 0 541 0 1 0 550 0 0 0 561 0 0 0 570 1 0 0 581 0 0 0 590 0 0 0 600 0 0 0 610 1 0 0 620 0 0 0 631 0 0 0 640 0 0 0 650 0 0 0 660 0 0 0 671 0 1 0 680 0 0 0 690 0 0 0 700 0 0 0 710 0 0 0 720 1 0 1 730 0 0 0 740 0 0 0 750 0 0 0 760 0 0 0 770 1 0 0 780 0 0 0 790 0 0 0 800 1 0 0 810 0 0 0 821 0 0 0 831 0 0 0 840 0 0 0 850 0 0 0 860 0 1 0 870 1 0 0 881 0 0 0 890 0 0 0 900 1 0 0 910 1 0 0 921 0 0 0 930 0 0 0 941 0 0 0 950 0 0 0 960 0 0 0 970 0 0 0 98

0 0 0 0 990 0 0 0 1000 0 0 0 1011 0 0 0 1020 0 0 0 1031 0 0 0 1041 0 1 0 1050 0 0 0 1060 0 0 0 1070 1 0 1 1080 0 0 0 1090 0 0 0 1100 1 0 0 1111 0 1 0 112

28 17 12 2

Observation lnWage School Predicted lnWageResidualsCURRENT POPULATION SURVEY 1 2.9285 16.0 2.9500 -0.0214

2 2.8232 13.0 2.7718 0.0513112 observations 3 3.0910 11.0 2.6531 0.4380

4 2.5416 12.0 2.7125 -0.17095 1.9810 12.0 2.7125 -0.7315

years of education 6 3.9120 13.0 2.7718 1.1402years of working experience 7 2.0149 16.0 2.9500 -0.9351hours of work per week 8 2.7441 12.0 2.7125 0.0316marital status 9 4.2785 12.0 2.7125 1.5660dummy var 10 3.6864 13.0 2.7718 0.9145place of living in metropolitan area 11 2.0794 6.0 2.3562 -0.2768location dummy 12 2.8332 14.0 2.8312 0.0020location dummy 13 2.6027 12.0 2.7125 -0.1098location dummy 14 2.6568 12.0 2.7125 -0.0557

15 2.3514 16.0 2.9500 -0.598616 2.9189 12.0 2.7125 0.206417 2.9565 14.0 2.8312 0.125318 2.9312 12.0 2.7125 0.218719 3.4308 16.0 2.9500 0.480820 3.1355 13.0 2.7718 0.363721 1.9459 12.0 2.7125 -0.766522 2.4849 16.0 2.9500 -0.465123 2.3026 14.0 2.8312 -0.528624 3.0445 13.0 2.7718 0.272725 3.1224 18.0 3.0687 0.053726 3.3576 12.0 2.7125 0.645127 2.1102 13.0 2.7718 -0.661628 2.5900 12.0 2.7125 -0.122429 2.3026 12.0 2.7125 -0.409930 2.0281 12.0 2.7125 -0.684331 3.7612 12.0 2.7125 1.048732 2.6391 16.0 2.9500 -0.310933 3.4121 18.0 3.0687 0.343434 2.5649 12.0 2.7125 -0.147535 2.9570 18.0 3.0687 -0.111736 2.3979 16.0 2.9500 -0.552137 3.1801 13.0 2.7718 0.408338 3.5625 16.0 2.9500 0.612539 2.9565 16.0 2.9500 0.006540 2.5772 16.0 2.9500 -0.372841 2.6504 12.0 2.7125 -0.062042 2.0149 12.0 2.7125 -0.697643 2.2513 12.0 2.7125 -0.461244 3.5849 16.0 2.9500 0.634945 2.5649 12.0 2.7125 -0.147546 2.8904 12.0 2.7125 0.177947 2.6693 13.0 2.7718 -0.1025

48 2.7632 14.0 2.8312 -0.068049 3.6926 16.0 2.9500 0.742750 2.5634 13.0 2.7718 -0.208451 2.3523 12.0 2.7125 -0.360152 2.7881 12.0 2.7125 0.075653 2.3026 16.0 2.9500 -0.647454 2.3214 12.0 2.7125 -0.391055 2.6304 3.0 2.1781 0.452456 2.7726 10.0 2.5937 0.178957 2.0794 13.0 2.7718 -0.692458 3.2189 12.0 2.7125 0.506459 2.5649 12.0 2.7125 -0.147560 2.3979 16.0 2.9500 -0.552161 3.6571 18.0 3.0687 0.588462 3.5849 21.0 3.2468 0.338163 3.3322 16.0 2.9500 0.382264 3.7403 16.0 2.9500 0.790365 3.3322 14.0 2.8312 0.501066 2.1972 12.0 2.7125 -0.515267 2.7081 9.0 2.5343 0.173768 2.5990 12.0 2.7125 -0.113569 1.8961 12.0 2.7125 -0.816370 3.9120 18.0 3.0687 0.843371 3.7894 18.0 3.0687 0.720772 2.1972 16.0 2.9500 -0.752773 3.0879 16.0 2.9500 0.137974 3.2288 18.0 3.0687 0.160175 3.3322 21.0 3.2468 0.085476 3.5852 13.0 2.7718 0.813477 2.3504 14.0 2.8312 -0.480878 2.5572 16.0 2.9500 -0.392779 3.0057 12.0 2.7125 0.293280 2.1702 16.0 2.9500 -0.779881 3.0615 12.0 2.7125 0.349182 2.8881 14.0 2.8312 0.056983 2.1576 16.0 2.9500 -0.792484 3.6745 12.0 2.7125 0.962185 2.3026 12.0 2.7125 -0.409986 2.3842 16.0 2.9500 -0.565887 2.4849 12.0 2.7125 -0.227588 2.4849 16.0 2.9500 -0.465189 3.2189 18.0 3.0687 0.150290 1.8718 12.0 2.7125 -0.840791 3.2189 21.0 3.2468 -0.028092 2.6391 12.0 2.7125 -0.073493 3.6376 16.0 2.9500 0.687694 3.5732 12.0 2.7125 0.860795 2.0669 12.0 2.7125 -0.645696 2.4849 12.0 2.7125 -0.227597 3.1839 16.0 2.9500 0.233998 3.3614 12.0 2.7125 0.6490

99 2.7081 12.0 2.7125 -0.0044100 2.9565 14.0 2.8312 0.1253101 3.0564 8.0 2.4750 0.5814102 3.0564 16.0 2.9500 0.1064103 2.1972 13.0 2.7718 -0.5746104 3.1793 21.0 3.2468 -0.0675105 2.4204 12.0 2.7125 -0.2921106 2.3273 16.0 2.9500 -0.6227107 4.1276 16.0 2.9500 1.1777108 2.5510 14.0 2.8312 -0.2802109 3.0625 13.0 2.7718 0.2906110 2.4849 16.0 2.9500 -0.4651111 2.8291 16.0 2.9500 -0.1209112 2.1401 13.0 2.7718 -0.6318

Model : logWAGE = a + b.EDUC

SUMMARY OUTPUT



Regression 1 3.1429 3.1429 11.2806 0.0011Residual 110 30.6475 0.2786Total 111 33.7904

CoefficientsStandard Error t Stat P-value Lower 95% Upper 95%Intercept 1.9999 0.2505 7.9850 0.0000 1.5036 2.4963044EDUC 0.0594 0.0177 3.3587 0.0011 0.0243 0.0944101

RESIDUAL OUTPUT Correlation Coefficient Matrix

Observation Predicted lnWageResiduals wage1 2.949959 -0.021435 wage 1.00002 2.7718319 0.0513311 educ 0.27263 2.6530805 0.4379619 exper 0.11204 2.7124562 -0.170854 hrswk 0.17135 2.7124562 -0.731455 married 0.19286 2.7718319 1.1401911 female -0.09607 2.949959 -0.935056 metro 0.13988 2.7124562 0.0316044 midwest -0.05129 2.7124562 1.5660138 south -0.0679

10 2.7718319 0.9145444 west 0.127711 2.3562021 -0.276761 black -0.201112 2.8312076 0.0020057 asian -0.026313 2.7124562 -0.10976714 2.7124562 -0.05569915 2.949959 -0.59858416 2.7124562 0.20639517 2.8312076 0.125263918 2.7124562 0.218737519 2.949959 0.480797220 2.7718319 0.363662321 2.7124562 -0.766546

22 2.949959 -0.46505223 2.8312076 -0.52862324 2.7718319 0.272690525 3.0687104 0.053654526 2.7124562 0.645137527 2.7718319 -0.66161928 2.7124562 -0.12243929 2.7124562 -0.40987130 2.7124562 -0.68430831 2.7124562 1.048743932 2.949959 -0.31090233 3.0687104 0.343426934 2.7124562 -0.14750735 3.0687104 -0.11171936 2.949959 -0.55206437 2.7718319 0.408303138 2.949959 0.612506539 2.949959 0.006512540 2.949959 -0.37277741 2.7124562 -0.06203542 2.7124562 -0.69755343 2.7124562 -0.46116444 2.949959 0.634947945 2.7124562 -0.14750746 2.7124562 0.177915547 2.7718319 -0.10252348 2.8312076 -0.06803849 2.949959 0.742663450 2.7718319 -0.20842251 2.7124562 -0.36012952 2.7124562 0.075636753 2.949959 -0.64737454 2.7124562 -0.39104955 2.178075 0.45237456 2.5937049 0.178883957 2.7718319 -0.6923958 2.7124562 0.506419659 2.7124562 -0.14750760 2.949959 -0.55206461 3.0687104 0.588420462 3.2468375 0.338069463 2.949959 0.382245564 2.949959 0.790326265 2.8312076 0.500996966 2.7124562 -0.51523267 2.5343292 0.17372168 2.7124562 -0.11347769 2.7124562 -0.81633770 3.0687104 0.843312671 3.0687104 0.720692972 2.949959 -0.752734

73 2.949959 0.137896674 3.0687104 0.160115875 3.2468375 0.08536776 2.7718319 0.813352377 2.8312076 -0.48078578 2.949959 -0.39273279 2.7124562 0.293226480 2.949959 -0.77976381 2.7124562 0.349063882 2.8312076 0.056939483 2.949959 -0.792484 2.7124562 0.962070785 2.7124562 -0.40987186 2.949959 -0.56579487 2.7124562 -0.2275588 2.949959 -0.46505289 3.0687104 0.150165490 2.7124562 -0.84065491 3.2468375 -0.02796292 2.7124562 -0.07339993 2.949959 0.687627194 2.7124562 0.860731795 2.7124562 -0.64559396 2.7124562 -0.2275597 2.949959 0.233911298 2.7124562 0.648960399 2.7124562 -0.004406

100 2.8312076 0.1252639101 2.4749535 0.5814034102 2.949959 0.1063979103 2.7718319 -0.574607104 3.2468375 -0.067534105 2.7124562 -0.292088106 2.949959 -0.622681107 2.949959 1.1776591108 2.8312076 -0.280201109 2.7718319 0.290624110 2.949959 -0.465052111 2.949959 -0.120872112 2.7718319 -0.631766

Lower 95.0%Upper 95.0%1.5035914 2.49630440.0243413 0.0944101

Correlation Coefficient Matrix

educ exper hrswk married female metro midwest south west

1.0000-0.1554 1.0000-0.0586 0.0303 1.00000.1148 0.1140 -0.0503 1.00000.1804 0.0860 -0.3000 -0.0546 1.00000.1451 -0.1297 0.1044 -0.0457 0.0214 1.00000.0491 0.0345 -0.0031 -0.1213 0.0569 -0.1706 1.00000.0238 0.0088 0.0761 0.0105 -0.0412 0.1114 -0.4055 1.00000.0968 -0.0080 0.1100 0.1437 -0.0249 0.0475 -0.2971 -0.2442 1.0000

-0.2006 0.0818 -0.0254 -0.1283 0.0577 0.1164 -0.0592 0.2667 -0.14650.0533 -0.0589 0.2430 -0.0270 0.0000 0.0723 -0.0947 -0.0778 0.3188

black asian

1.0000-0.0467 1.0000

BOX-COX TEST2013 2013

Country NameY X

1 Australia AUS 503.8 867.22 Austria AUT 182.9 349.53 Canada CAN 777.7 1319.34 China CHN 1774.8 4864.05 Denmark DNK 130.2 265.16 France FRA 1309.7 2351.97 Finland FIN 114.9 212.68 Germany DEU 1758.7 3161.99 Greece GRC 136.5 201.0

10 Hong Kong SAR, China HKG 153.4 241.011 India IND 883.5 1489.812 Italy ITA 1040.4 1759.613 Ireland IRL 96.6 217.314 Indonesia IDN 267.6 452.315 Korea, Rep. KOR 584.5 1199.916 Malaysia MYS 108.2 207.917 New Zealand NZL 79.6 130.318 Norway NOR 163.5 331.419 Philippines PHL 109.9 155.620 Russian Federation RUS 650.1 993.521 Singapore SGP 65.8 199.222 South Africa ZAF 211.6 323.723 Switzerland CHE 268.9 477.324 Sweden SWE 208.7 437.325 Thailand THA 122.5 230.426 Turkey TUR 447.7 653.627 United Kingdom GBR 1615.4 2578.728 Vietnam VNM 60.9 92.329 Japan JPN 2853.4 4784.5

AverageGeom_Mea

Country Code



lnY LnX Y* lnY* Model 1* linear Y* = a+bX6.2221 6.7652 1.6329 0.49045.2092 5.8565 0.5930 -0.5226 SUMMARY OUTPUT6.6563 7.1848 2.5207 0.92457.4814 8.4896 5.7526 1.7497 Regression Statistics4.8694 5.5802 0.4222 -0.8623 Multiple R 0.9675787.1776 7.7630 4.2453 1.4458 R Square 0.9362074.7442 5.3594 0.3725 -0.9875 Adjusted R 0.9338447.4724 8.0589 5.7007 1.7406 Standard E 0.573024.9161 5.3034 0.4423 -0.8157 Observatio 295.0332 5.4849 0.4973 -0.69866.7839 7.3064 2.8638 1.0521 ANOVA6.9474 7.4728 3.3723 1.2156 df SS4.5704 5.3811 0.3131 -1.1613 Regression 1 130.107682955.5897 6.1144 0.8675 -0.1421 Residual 27 8.86549330616.3707 7.0900 1.8945 0.6390 Total 28 138.973176264.6841 5.3373 0.3508 -1.04774.3770 4.8699 0.2580 -1.3548 CoefficientsStandard Error5.0968 5.8034 0.5299 -0.6350 Intercept 0.1413 0.13724.6999 5.0473 0.3563 -1.0319 X 0.0016 0.00016.4772 6.9013 2.1073 0.7454 RSS1 = 8.86554.1872 5.2944 0.2134 -1.54465.3548 5.7800 0.6859 -0.37705.5943 6.1681 0.8716 -0.1375 RESIDUAL OUTPUT5.3409 6.0806 0.6764 -0.39094.8082 5.4397 0.3971 -0.9235 ObservationPredicted Y Residuals6.1041 6.4825 1.4511 0.3723 1 1.559854 0.07308522887.3873 7.8550 5.2361 1.6556 2 0.713072 -0.1200875694.1092 4.5248 0.1974 -1.6225 3 2.29949 0.22119527557.9563 8.4731 9.2488 2.2245 4 8.098139 -2.34552579

5 0.575041 -0.1528627195.7318 6 3.988764 0.2565684158

308.5138 7 0.489111 -0.116616548 5.313796 0.38687631659 0.470165 -0.027823338

10 0.535603 -0.0383141911 2.578379 0.285385606912 3.019718 0.352547812113 0.496735 -0.18366984814 0.881272 -0.0137312315 2.104142 -0.2096380216 0.481492 -0.13073427817 0.354478 -0.09647824418 0.68349 -0.15355548419 0.395856 -0.03952804520 1.766575 0.340716905821 0.46721 -0.253802341

22 0.670916 0.015009136823 0.922038 -0.05047135524 0.856681 -0.18023872125 0.518171 -0.12105150626 1.210565 0.24053372327 4.359691 0.876432286128 0.292267 -0.0948659929 7.968151 1.2806444997

Model 2*

TS = 33.81333 SUMMARY OUTPUT

χ-sq crit(1)= 3.84 alfa=5% Regression StatisticsMultiple R 0.987887R Square 0.975921Adjusted R 0.975029Standard E 0.178563Observatio 29

ANOVAMS F Significance F df

130.1077 396.245005 1.148E-17 Regression 10.328352 Residual 27

Total 28

t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0% Coefficients1.0302 0.312056097 -0.14014 0.422771 -0.14014 0.422771 Intercept -6.2453

19.9059 1.148042E-17 0.001467 0.001804 0.001467 0.001804 ln X 0.9882RSS2 = 0.8609

RESIDUAL OUTPUT

ObservationPredicted Y1 0.4403812 -0.4576113 0.8550864 2.1445215 -0.7306676 1.426447 -0.9488698 1.7189059 -1.004225

10 -0.82487811 0.97518912 1.13967513 -0.92743814 -0.20276415 0.76132316 -0.9707617 -1.43267418 -0.51011319 -1.25735720 0.57482321 -1.013147

22 -0.53330123 -0.14976524 -0.23616325 -0.86956526 0.16103227 1.51739828 -1.77371729 2.128243

lnY* = a'+ b"ln X

SS MS F Significance F34.89234 34.89234 1094.323 2.184E-230.860891 0.03188535.75323

Standard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%0.1917 -32.5818 3.259E-23 -6.63864 -5.852043 -6.63864 -5.8520430.0299 33.0806 2.184E-23 0.926953 1.049546 0.926953 1.049546

Residuals0.050001

-0.0649760.069445

-0.394867-0.131661

0.01938-0.038664

0.021680.1885520.1262930.076948

0.07591-0.2339040.060671

-0.122366-0.0769010.077879

-0.1248890.2254520.170581

-0.531406

0.1563150.012302

-0.154744-0.0539530.2112890.1381830.151199

0.09625

The MacKinnon, White, Davidson (MWD) Test2013

Country N Country CCONS GDP log(CONS)



Mean 575.2 1053.4 5.7

REGRESSION Linear ModelModel: CONS = a + B GDP + e

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.967578R Square 0.936207Adjusted R 0.933844Standard E 176.7845Observatio 29




Regression 1 12383745 12383745.45244 396.245005028 1.148042239779E-17Residual 27 843824.2 31252.74841397Total 28 13227570

CoefficientsStandard Error t Stat P-value Lower 95%Intercept 43.59777 42.31965 1.030201658198 0.31205609653 -43.2349768316207GDP 0.504685 0.025354 19.90590377321 1.14804224E-17 0.452663882395376

RESIDUAL OUTPUT

ObservationPredicted CONSResiduals1 481.2366 22.54782 219.9926 -37.048673 709.4243 68.241794 2498.387 -723.6275 177.408 -47.160256 1230.588 79.154897 150.8975 -35.977818 1639.379 119.35679 145.0524 -8.583882

10 165.2408 -11.8204511 795.4654 88.0453912 931.6246 108.765913 153.2497 -56.6646814 271.8844 -4.23627315 649.1567 -64.6762116 148.5468 -40.3333217 109.3615 -29.7648718 210.8659 -47.3739819 122.1269 -12.1949520 545.0126 105.115921 144.1406 -78.3015122 206.9869 4.63052523 284.4614 -15.5711124 264.298 -55.6061325 159.8628 -37.3460626 373.4759 74.2079627 1345.025 270.391428 90.16843 -29.2674629 2458.284 395.0964

2013 PLOTTING GRAPH

log(GDP2005)6.85.97.28.55.67.85.48.15.35.57.37.55.46.17.15.34.95.85.06.95.35.86.26.15.46.57.94.58.5

6.3

REGRESSIONModel: log(CONS) = a + b.log(GDP2005) + e

SUMMARY OUTPUT


ANOVAdf

Regression 1Residual 27Total 28

Upper 95% Lower 95.0% Upper 95.0% Coefficients130.430526297573 -43.234976832 130.430526298 Intercept -0.513575

0.556706198594248 0.4526638824 0.55670619859 log(GDP2005) 0.98825

RESIDUAL OUTPUT

ObservationPredicted log(CONS)1 6.1721482 5.2741553 6.5868524 7.8762885 5.00116 7.1582067 4.7828978 7.4506719 4.727542

10 4.90688811 6.70695512 6.87144113 4.80432814 5.52900215 6.4930916 4.76100717 4.29909218 5.22165319 4.4744120 6.30658921 4.7186222 5.19846523 5.58200124 5.49560325 4.86220126 5.89279827 7.24916528 3.9580529 7.86001

log-log Modellog(CONS) = a + b.log(GDP2005) + e

SS MS F Significance F34.89234 34.89234 1094.323 2.184E-230.860891 0.03188535.75323

Standard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%0.191682 -2.67931 0.012411 -0.906873 -0.120276 -0.906873 -0.1202760.029874 33.08055 2.184E-23 0.926953 1.049546 0.926953 1.049546

Residuals0.050001

-0.0649760.069445

-0.394867-0.131661

0.01938-0.038664

0.021680.1885520.1262930.076948

0.07591-0.2339040.060671

-0.122366-0.0769010.077879

-0.1248890.2254520.170581

-0.5314060.1563150.012302

-0.154744-0.0539530.2112890.1381830.151199

0.09625

++ TESTING FINCTIONAL FORM :: LINEAR vs LOG_LOG Model++ The MacKinnon, White, Davidson (MWD) Test

++++++ Country N logCONS LogGDP DIFF2 Predicted CONS antilog(lnY_HAT)++ Australia 6.7652 6.2221 2.02 481.24 479.21++ Austria 5.8565 5.2092 24.77 219.99 195.23++ Canada 7.1848 6.6563 -16.07 709.42 725.49++ China 8.4896 7.4814 -135.69 2498.39 2634.08++ Denmark 5.5802 4.8694 28.83 177.41 148.58++ France 7.7630 7.1776 -54.02 1230.59 1284.60++ Finland 5.3594 4.7442 31.45 150.90 119.45++ Germany 8.0589 7.4724 -81.64 1639.38 1721.02++ Greece 5.3034 4.9161 32.04 145.05 113.02++ Hong Kong 5.4849 5.0332 30.02 165.24 135.22++ India 7.3064 6.7839 -22.61 795.47 818.08++ Italy 7.4728 6.9474 -32.71 931.62 964.34++ Ireland 5.3811 4.5704 31.21 153.25 122.04++ Indonesia 6.1144 5.5897 19.99 271.88 251.89++ Korea, Rep 7.0900 6.3707 -11.40 649.16 660.56++ Malaysia 5.3373 4.6841 31.68 148.55 116.86++ New Zeala 4.8699 4.3770 35.73 109.36 73.63++ Norway 5.8034 5.0968 25.63 210.87 185.24++ Philippines 5.0473 4.6999 34.38 122.13 87.74++ Russian Fe 6.9013 6.4772 -3.16 545.01 548.17++ Singapore 5.2944 4.1872 32.13 144.14 112.01++ South Afric 5.7800 5.3548 25.99 206.99 180.99++ Switzerlan 6.1681 5.5943 18.86 284.46 265.60++ Sweden 6.0806 5.3409 20.68 264.30 243.62++ Thailand 5.4397 4.8082 30.55 159.86 129.31++ Turkey 6.4825 6.1041 11.06 373.48 362.42++ United Ki 7.8550 7.3873 -61.90 1345.02 1406.93++ Vietnam 4.5248 4.1092 37.81 90.17 52.36++ Japan 8.4731 7.9563 -133.26 2458.28 2591.55++++++++ Testing log-log vs linear model (MWD TEST)++++++ SUMMARY OUTPUT++++ Regression Statistics++ Multiple R 0.9909++ R Square 0.9819++ Adjusted R 0.9805++ Standard E 0.1579++ Observatio 29++

++ ANOVA++ df SS MS F Significance F++ Regression 2 35.0791 17.5395519714657 703.853361972 2.2944E-23++ Residual 26 0.647902 0.02491932683582++ Total 28 35.72701++++ CoefficientsStandard Error t Stat P-value Lower 95%++ Intercept 1.5704 0.3481 4.5116 0.00012 0.85493++ lnGDP 0.8274 0.0609 13.5907 0.00000 0.70225++ DIFF2 -0.0041 0.0014 -2.9192 0.00715 -0.00703++++++++ RESIDUAL OUTPUT++++ ObservationPredicted Y Residuals++ 1 6.7102 0.0550++ 2 5.7782 0.0783++ 3 7.1441 0.0408++ 4 8.3204 0.1693++ 5 5.4804 0.0999++ 6 7.7320 0.0310++ 7 5.3660 -0.0065++ 8 8.0898 -0.0309++ 9 5.5058 -0.2023++ 10 5.6109 -0.1260++ 11 7.2766 0.0297++ 12 7.4536 0.0193++ 13 5.2231 0.1580++ 14 6.1128 0.0017++ 15 6.8885 0.2014++ 16 5.3153 0.0220++ 17 5.0445 -0.1746++ 18 5.6817 0.1217++ 19 5.3172 -0.2699++ 20 6.9426 -0.0413++ 21 4.9023 0.3921++ 22 5.8937 -0.1137++ 23 6.1213 0.0468++ 24 5.9041 0.1766++ 25 5.4226 0.0171++ 26 6.5752 -0.0927++ 27 7.9381 -0.0830++ 28 4.8143 -0.2896++ 29 8.7032 -0.2301++++++++++++

++++++++++++++++++++++++++++++++++++

Country N CONSUMPTIOGDP Diff1Australia 503.8 867.2 -0.00421Austria 182.9 349.5 -0.11944Canada 777.7 1319.3 0.02240China 1774.8 4864.0 0.05289Denmark 130.2 265.1 -0.17735France 1309.7 2351.9 0.04296Finland 114.9 212.6 -0.23370Germany 1758.7 3161.9 0.04860Greece 136.5 201.0 -0.24955Hong Kong 153.4 241.0 -0.20052India 883.5 1489.8 0.02803Italy 1040.4 1759.6 0.03451Ireland 96.6 217.3 -0.22774Indonesia 267.6 452.3 -0.07637Korea, Rep 584.5 1199.9 0.01742Malaysia 108.2 207.9 -0.23989New Zeala 79.6 130.3 -0.39557Norway 163.5 331.4 -0.12957Philippines 109.9 155.6 -0.33065Russian Fe 650.1 993.5 0.00578Singapore 65.8 199.2 -0.25217South Afric 211.6 323.7 -0.13419Switzerlan 268.9 477.3 -0.06860Sweden 208.7 437.3 -0.08147Thailand 122.5 230.4 -0.21211Turkey 447.7 653.6 -0.03006United Ki 1615.4 2578.7 0.04500Vietnam 60.9 92.3 -0.54363Japan 2853.4 4784.5 0.05279

Testing linear vs log-log (MWD TEST)

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.9693R Square 0.9396Adjusted R 0.9349Standard E 175.3412Observatio 29

ANOVASignificance F df SS MS

Regression 2 12428212 6214106Residual 26 799358 30744.54Total 28 13227570

Upper 95% Lower 95% Upper 95% CoefficientsStandard Error t Stat2.28594 0.85493 2.28594 Intercept 112.2219 70.8371 1.5842260.95252 0.70225 0.95252 GDP 0.4777 0.0337 14.1784

-0.00122 -0.00703 -0.00122 DIFF1 347.4647 288.9215 1.202627

RESIDUAL OUTPUT

Observation Predicted Y Residuals1 525.0112 -21.22682 237.6900 -54.74613 750.2511 27.41504 2454.2104 -679.45025 177.2580 -47.01036 1250.7095 59.03387 132.5842 -17.66468 1639.6153 119.12079 121.5440 14.9245

10 157.6926 -4.272211 833.6504 49.860312 964.7864 75.604113 136.8825 -40.297514 301.7721 -34.124015 691.4727 -106.992216 128.2083 -19.994817 37.0260 42.570618 225.5310 -62.039019 71.6650 38.267020 588.8509 61.277621 119.7721 -53.932922 220.2537 -8.636223 316.3796 -47.489424 292.8191 -84.127225 148.5716 -26.054926 414.0291 33.654727 1359.7389 255.677228 -32.5882 93.489129 2416.2169 437.1637

Predicted log(CONS)6.17636 6.17215 r =correlation coeff (Y, antilog(lnY_HAT))=5.39359 5.27416 r - sq = r^2 = 0.937116.56445 6.586857.82340 7.87629 Model: Y = a + b.antilog(LnY-HAT)5.17845 5.00110 SUMMARY OUTPUT7.11525 7.158215.01660 4.78290 Regression Statistics7.40207 7.45067 Multiple R 0.9680444.97710 4.72754 R Square 0.937115.10740 4.90689 Adjusted R Square 0.9347816.67893 6.70696 Standard Error 175.52916.83693 6.87144 Observations 295.03207 4.804335.60538 5.52900 ANOVA6.47567 6.49309 df SS MS5.00090 4.76101 Regression 1 12395687 123956874.69466 4.29909 Residual 27 831882.7 30810.475.35122 5.22165 Total 28 132275704.80506 4.474416.30081 6.30659 CoefficientsStandard Error t Stat4.97079 4.71862 Intercept 37.35703 42.20806 0.8850685.33266 5.19847 antilog(LnY_HAT) 0.932395 0.046485 20.057935.65060 5.582005.57708 5.495605.07432 4.862205.92285 5.892807.20417 7.249164.50168 3.958057.80722 7.86001

lnŶ


P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%0.125232 -33.38575 257.8296 -33.38575 257.8296

9.558E-14 0.408459 0.546973 0.408459 0.5469730.239959 -246.422 941.3514 -246.422 941.3514

0.968044


P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%0.383934 -49.24676 123.9608 -49.24676 123.9608

9.467E-18 0.837015 1.027774 0.837015 1.027774

Table 4.1 Infant mortality, life expectancy and public expenditure on health1 2 3

1999 1960 1999Australia 78.78 20.2 4.9Austria 77.93 37.5 4.4Belgium 78.03 31.2 5.38Canada 79.03 27.3 5.3France 78.51 27.4 4.8Germany 76.99 35 4.83Ireland 76.12 29.3 5.5Italy 78.29 43.9 5.43Japan 80.63 30.4 3.6Netherlands 77.65 17.9 5.1New Zealand 77.39 22.6 5.23Norway 78.48 18.9 4.02Spain 77.91 43.7 5.3Sweden 79.26 16.6 3.6Switzerland 79.56 21.1 4.56UK 77.25 22.5 5.7USA 76.91 26 6.9Denmark 75.87 21.5 4.65Finland 77.26 21.4 4.08South Africa 48.47 88.6 61.52Singapore 77.55 34.8 3.2Malaysia 72.34 70.6 7.9Indonesia 65.72 137.8 41.92Bangladesh 60.74 154.8 61.2

Mean 75.28 41.71 11.21

NA = Not Available

Life expenctancy (average in years)

Infant Mortality (death per 100 live births)

Infant Mortality (death per 100 live births)

4 5

1960 19982.4 5.93.1 5.82.1 7.92.3 6.42.5 7.33.2 7.9

3 4.73 5.6

1.8 5.91.3 63.5 6.22.6 7.40.9 5.43.4 6.7

2 7.63.3 5.61.3 5.83.2 6.82.3 5.2NA 3.3NA 1.2NA 1.4NA 0.7NA 1.7

2.48 5.35

Public Health Expenditure (% of GDP)

Public Health Expenditure (% of GDP)

Table 3.2 Data on Aviation Demand and Revenue

ln(X)

1991 1135 9.6 7.0341992 1146 9.2 7.0441993 1142 9.2 7.0411994 1233 9.2 7.1171995 1304 9.4 7.1731996 1391 9.1 7.2381997 1457 8.8 7.2841998 1471 8.6 7.2941999 1562 8.3 7.3542000 1672 8.3 7.4222001 1640 7.9 7.4022002 1639 7.8 7.4022003 1691 8 7.4332004 1887 8.2 7.543

Change 0.66 -0.15

X = Number of Passengers (million)

Y = Revenue per passenger-km (US

cents)

ln(Y)

2.2622.2192.2192.2192.2412.2082.1752.1522.1162.1162.0672.0542.0792.104

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