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What steps should be taken (mention all of them) in order to successfully specify/estimate a regression equation?

What steps should be taken (mention all of them) in order to successfully specify/estimate a regression equation?

Algebra: Structure And Method, Book 1
Algebra: Structure And Method, Book 1
(REV)00th Edition
ISBN:9780395977224
Author:Richard G. Brown, Mary P. Dolciani, Robert H. Sorgenfrey, William L. Cole
Publisher:Richard G. Brown, Mary P. Dolciani, Robert H. Sorgenfrey, William L. Cole
Chapter2: Working With Real Numbers
Section2.3: Rules For Addition
Problem 7P
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What steps should be taken (mention all of them) in order to successfully specify/estimate a regression equation? 

Below 4 equations for calculation of wages in Latvia (ALGA, EUR) are given, depending on productivity (PRODUKTIVITATE, thsd EUR), price level (CENA), unemployment rate (BEZDARBS, %) and ratio of GDP of Latvia and the EU (IKP_ATTIECIBA). Which equation would you use, why (for justification use all the indicators known from the lectures)? (t-stat = 2,14; t- F-stat 0,05;3;13 stat 0,05;15 = 2,13; t-stat0,05;16 = 2,12; = 3,29; F-stat 0,05;2;13 = 3,63; F-stat 0,05;2;14 = 3,59)
Transcribed Image Text:Below 4 equations for calculation of wages in Latvia (ALGA, EUR) are given, depending on productivity (PRODUKTIVITATE, thsd EUR), price level (CENA), unemployment rate (BEZDARBS, %) and ratio of GDP of Latvia and the EU (IKP_ATTIECIBA). Which equation would you use, why (for justification use all the indicators known from the lectures)? (t-stat = 2,14; t- F-stat 0,05;3;13 stat 0,05;15 = 2,13; t-stat0,05;16 = 2,12; = 3,29; F-stat 0,05;2;13 = 3,63; F-stat 0,05;2;14 = 3,59)
Dependent Vanabe: LOG(ALGA) Method: Least Squares Included observations: 17 after adjustments Vanable LOG(CENA) LOG PRODUKTIVITATE) BEZDARBS C R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat Coefficient R-squared Adjusted R-squared S.E. of regression Sum squared resid Log Ikelihood Durbin-Watson stat 1.733446 0.143014 0.316520 0.181278 -0.011502 7.202105 0.003949 0.314418 Dependent Variable: LOG(ALGA) Method: Least Squares Included observations: 17 after adjustments Variable LOG(CENA) BEZDARBS C Std. Error Coefficient 0.995794 Mean dependent var S.D. dependentvar 0.994823 0.040174 Akake into criterion 0.020981 Schwarz ofterion 32.80553 F-statistic 1.840821 Prob (F-statistic) 1.974777 -0.016842 7.747829 t-Statistic Std. Emor 12.12084 1.746049 -2.912980 22.90614 t-Statistic 0.039330 50.21103 0.002674 -8.297883 0.037767 205.1410 0.994807 Mean dependent var 0.994065 S.D. dependent var 0.043013 Akaike info criterion 0.025901 Schwarz criterion 31.01477 F-statistic 1.929371 Prob(F-statistic) Prob 0.0000 0.1044 0.0121 0.0000 Dependent Varable: LOG(ALGA) Method: Least Squares Included observations: 17 after adjustments Prob. 7.959451 R-squared 0.558335 Adjusted R-squared -3.388885 S.E. of regression -3.192835 Sum squared resid 1025.827 Log Ikelihood 0.000000 Duroin-Watson stat 0.0000 0.0000 0.0000 Variable 7.959451 0.558335 -3.295855 -3.148817 1340.984 0.000000 LOG (CENA) LOG(KP_ATTIECIBA) BEZDARBS C Coefficient Std. Error 1.682538 0.613199 -0.003104 0.005984 7.906579 0.071659 0.996479 0.995666 0.036756 0.017563 34.31709 1.765948 0.122338 0.246822 t-Statistic 13.75320 2.484378 -0.518692 110.3366 Mean dependent var S.D. dependent var Akake into criterion Schwarz criterion F-statistic Prob(F-statistic) Prob. Dependent Variable: LOG(ALGA) Method: Least Squares Included observations: 18 after adjustments Variable 0.0000 LOG(CENA) 1.588128 0.0274 LOG(IKP_ATTIECIBA) 0.718542 0.6127 C 7.940545 0.0000 Coefficient 7.959451 R-squared 0.558335 Adjusted R-squared -3.566716 S.E. of regression -3.370666 Sum squared resid 1226.321 Log likelihood 0.000000 Durbin-Watson stat Std. Emor +-Statistic 0.073034 21.71778 0.0000 0.119047 6.035777 0.0000 0.087802 117.4806 0.0000 Prob. 0.994508 Mean dependent var 0.993778 S.D. dependent var 0.048459 Akake into criterion 0.032377 Schwarz criterion 31.34517 F-statistic 1.965028 Prob(F-statistic) 7.904990 0.588888 -3.149484 -3.001068 1358.142 0.000000
Transcribed Image Text:Dependent Vanabe: LOG(ALGA) Method: Least Squares Included observations: 17 after adjustments Vanable LOG(CENA) LOG PRODUKTIVITATE) BEZDARBS C R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat Coefficient R-squared Adjusted R-squared S.E. of regression Sum squared resid Log Ikelihood Durbin-Watson stat 1.733446 0.143014 0.316520 0.181278 -0.011502 7.202105 0.003949 0.314418 Dependent Variable: LOG(ALGA) Method: Least Squares Included observations: 17 after adjustments Variable LOG(CENA) BEZDARBS C Std. Error Coefficient 0.995794 Mean dependent var S.D. dependentvar 0.994823 0.040174 Akake into criterion 0.020981 Schwarz ofterion 32.80553 F-statistic 1.840821 Prob (F-statistic) 1.974777 -0.016842 7.747829 t-Statistic Std. Emor 12.12084 1.746049 -2.912980 22.90614 t-Statistic 0.039330 50.21103 0.002674 -8.297883 0.037767 205.1410 0.994807 Mean dependent var 0.994065 S.D. dependent var 0.043013 Akaike info criterion 0.025901 Schwarz criterion 31.01477 F-statistic 1.929371 Prob(F-statistic) Prob 0.0000 0.1044 0.0121 0.0000 Dependent Varable: LOG(ALGA) Method: Least Squares Included observations: 17 after adjustments Prob. 7.959451 R-squared 0.558335 Adjusted R-squared -3.388885 S.E. of regression -3.192835 Sum squared resid 1025.827 Log Ikelihood 0.000000 Duroin-Watson stat 0.0000 0.0000 0.0000 Variable 7.959451 0.558335 -3.295855 -3.148817 1340.984 0.000000 LOG (CENA) LOG(KP_ATTIECIBA) BEZDARBS C Coefficient Std. Error 1.682538 0.613199 -0.003104 0.005984 7.906579 0.071659 0.996479 0.995666 0.036756 0.017563 34.31709 1.765948 0.122338 0.246822 t-Statistic 13.75320 2.484378 -0.518692 110.3366 Mean dependent var S.D. dependent var Akake into criterion Schwarz criterion F-statistic Prob(F-statistic) Prob. Dependent Variable: LOG(ALGA) Method: Least Squares Included observations: 18 after adjustments Variable 0.0000 LOG(CENA) 1.588128 0.0274 LOG(IKP_ATTIECIBA) 0.718542 0.6127 C 7.940545 0.0000 Coefficient 7.959451 R-squared 0.558335 Adjusted R-squared -3.566716 S.E. of regression -3.370666 Sum squared resid 1226.321 Log likelihood 0.000000 Durbin-Watson stat Std. Emor +-Statistic 0.073034 21.71778 0.0000 0.119047 6.035777 0.0000 0.087802 117.4806 0.0000 Prob. 0.994508 Mean dependent var 0.993778 S.D. dependent var 0.048459 Akake into criterion 0.032377 Schwarz criterion 31.34517 F-statistic 1.965028 Prob(F-statistic) 7.904990 0.588888 -3.149484 -3.001068 1358.142 0.000000
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