SlideShare a Scribd company logo
1 of 2
Normal Regression
DependentVariable:POVERTY
Method: Panel LeastSquares
Date: 10/20/14 Time:18:26
Sample:2002 2012
Periods included:6
Cross-sections included:8
Total panel (balanced) observations:48
Variable Coefficient Std. Error t-Statistic Prob.
INCOME_INEQUALITY -0.810944 0.604320 -1.341911 0.1864
GROWTH -0.003335 0.001721 -1.937230 0.0590
C 65.86585 17.53023 3.757272 0.0005
R-squared 0.187282 Mean dependentvar 33.79290
Adjusted R-squared 0.151162 S.D. dependentvar 12.08054
S.E. of regression 11.13009 Akaike info criterion 7.717644
Sum squared resid 5574.555 Schwarz criterion 7.834594
Log likelihood -182.2235 Hannan-Quinn criter. 7.761839
F-statistic 5.184895 Durbin-Watson stat 1.124323
Prob(F-statistic) 0.009411
Fixed Effect
DependentVariable:POVERTY
Method: Panel LeastSquares
Date: 10/20/14 Time:18:26
Sample:2002 2012
Periods included:6
Cross-sections included:8
Total panel (balanced) observations:48
Variable Coefficient Std. Error t-Statistic Prob.
INCOME_INEQUALITY 1.353497 0.343255 3.943126 0.0003
GROWTH -0.001332 0.000753 -1.767762 0.0851
C -5.710651 10.18077 -0.560925 0.5781
Effects Specification
Cross-section fixed (dummyvariables)
R-squared 0.886484 Mean dependentvar 33.79290
Adjusted R-squared 0.859599 S.D. dependentvar 12.08054
S.E. of regression 4.526596 Akaike info criterion 6.040869
Sum squared resid 778.6228 Schwarz criterion 6.430703
Log likelihood -134.9809 Hannan-Quinn criter. 6.188188
F-statistic 32.97278 Durbin-Watson stat 1.881175
Prob(F-statistic) 0.000000
Random Effect
DependentVariable:POVERTY
Method: Panel EGLS (Cross-section random effects)
Date: 10/20/14 Time:18:27
Sample:2002 2012
Periods included:6
Cross-sections included:8
Total panel (balanced) observations:48
Swamy and Arora estimator ofcomponentvariances
Variable Coefficient Std. Error t-Statistic Prob.
INCOME_INEQUALITY 0.176665 0.297120 0.594591 0.5551
GROWTH -0.001965 0.000734 -2.679417 0.0103
C 32.28042 8.784750 3.674597 0.0006
Effects Specification
S.D. Rho
Cross-section random 2.579440 0.2451
Idiosyncratic random 4.526596 0.7549
Weighted Statistics
R-squared 0.051060 Mean dependentvar 19.68061
Adjusted R-squared 0.008885 S.D. dependentvar 8.057974
S.E. of regression 8.022097 Sum squared resid 2895.932
F-statistic 1.210668 Durbin-Watson stat 1.120413
Prob(F-statistic) 0.307519
Unweighted Statistics
R-squared 0.081349 Mean dependentvar 33.79290
Sum squared resid 6301.170 Durbin-Watson stat 0.847309

More Related Content

Similar to Output

Minhhoa bai giang kinh te luong
Minhhoa bai giang kinh te luongMinhhoa bai giang kinh te luong
Minhhoa bai giang kinh te luongrobodientu
 
табл гетероскедаст
табл гетероскедасттабл гетероскедаст
табл гетероскедастlpbimo
 
Data equation
Data equation Data equation
Data equation ressas
 
Econometrics Project
Econometrics ProjectEconometrics Project
Econometrics ProjectUday Tharar
 
working data(Group5)
working data(Group5)working data(Group5)
working data(Group5)Kritika Gupta
 
Enflasyon forecast
Enflasyon forecastEnflasyon forecast
Enflasyon forecastmesut bayhan
 
Design of experiment methodology
Design of experiment methodologyDesign of experiment methodology
Design of experiment methodologyCHUN-HAO KUNG
 
Cobb-douglas production function
Cobb-douglas production functionCobb-douglas production function
Cobb-douglas production functionSuniya Sheikh
 
Cobb-douglas production function
Cobb-douglas production functionCobb-douglas production function
Cobb-douglas production functionSuniya Sheikh
 
Durbib- Watson D between 0-2 means there is a positive correlati
Durbib- Watson D between 0-2 means there is a positive correlatiDurbib- Watson D between 0-2 means there is a positive correlati
Durbib- Watson D between 0-2 means there is a positive correlatiAlyciaGold776
 
Doe with response surface model
Doe with response surface modelDoe with response surface model
Doe with response surface modelMark Reich
 
Cross validationreport dataakuisisibaru9720031xv
Cross validationreport dataakuisisibaru9720031xvCross validationreport dataakuisisibaru9720031xv
Cross validationreport dataakuisisibaru9720031xvfarah mutik
 
Autoregressive integrated moving average
Autoregressive integrated moving averageAutoregressive integrated moving average
Autoregressive integrated moving averageMuhammad Khoirul Fuddin
 
Pp Regresi. Jadippt
Pp Regresi. JadipptPp Regresi. Jadippt
Pp Regresi. Jadipptguesta81b5f
 

Similar to Output (20)

Minhhoa bai giang kinh te luong
Minhhoa bai giang kinh te luongMinhhoa bai giang kinh te luong
Minhhoa bai giang kinh te luong
 
табл гетероскедаст
табл гетероскедасттабл гетероскедаст
табл гетероскедаст
 
Ujian ekonometrika
Ujian ekonometrikaUjian ekonometrika
Ujian ekonometrika
 
Data equation
Data equation Data equation
Data equation
 
Econometrics Project
Econometrics ProjectEconometrics Project
Econometrics Project
 
Lampiran error correction model
Lampiran error correction modelLampiran error correction model
Lampiran error correction model
 
Lampiran uji kointegrasi
Lampiran uji kointegrasiLampiran uji kointegrasi
Lampiran uji kointegrasi
 
working data(Group5)
working data(Group5)working data(Group5)
working data(Group5)
 
Enflasyon forecast
Enflasyon forecastEnflasyon forecast
Enflasyon forecast
 
Design of experiment methodology
Design of experiment methodologyDesign of experiment methodology
Design of experiment methodology
 
Cobb-douglas production function
Cobb-douglas production functionCobb-douglas production function
Cobb-douglas production function
 
Cobb-douglas production function
Cobb-douglas production functionCobb-douglas production function
Cobb-douglas production function
 
Appendix
AppendixAppendix
Appendix
 
GARCH
GARCHGARCH
GARCH
 
Durbib- Watson D between 0-2 means there is a positive correlati
Durbib- Watson D between 0-2 means there is a positive correlatiDurbib- Watson D between 0-2 means there is a positive correlati
Durbib- Watson D between 0-2 means there is a positive correlati
 
Doe with response surface model
Doe with response surface modelDoe with response surface model
Doe with response surface model
 
Lampiran uji kointegrasi
Lampiran uji kointegrasiLampiran uji kointegrasi
Lampiran uji kointegrasi
 
Cross validationreport dataakuisisibaru9720031xv
Cross validationreport dataakuisisibaru9720031xvCross validationreport dataakuisisibaru9720031xv
Cross validationreport dataakuisisibaru9720031xv
 
Autoregressive integrated moving average
Autoregressive integrated moving averageAutoregressive integrated moving average
Autoregressive integrated moving average
 
Pp Regresi. Jadippt
Pp Regresi. JadipptPp Regresi. Jadippt
Pp Regresi. Jadippt
 

Recently uploaded

Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application ) Sakshi Ghasle
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxmanuelaromero2013
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionSafetyChain Software
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991RKavithamani
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...Marc Dusseiller Dusjagr
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfchloefrazer622
 

Recently uploaded (20)

INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application )
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptx
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory Inspection
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdf
 

Output

  • 1. Normal Regression DependentVariable:POVERTY Method: Panel LeastSquares Date: 10/20/14 Time:18:26 Sample:2002 2012 Periods included:6 Cross-sections included:8 Total panel (balanced) observations:48 Variable Coefficient Std. Error t-Statistic Prob. INCOME_INEQUALITY -0.810944 0.604320 -1.341911 0.1864 GROWTH -0.003335 0.001721 -1.937230 0.0590 C 65.86585 17.53023 3.757272 0.0005 R-squared 0.187282 Mean dependentvar 33.79290 Adjusted R-squared 0.151162 S.D. dependentvar 12.08054 S.E. of regression 11.13009 Akaike info criterion 7.717644 Sum squared resid 5574.555 Schwarz criterion 7.834594 Log likelihood -182.2235 Hannan-Quinn criter. 7.761839 F-statistic 5.184895 Durbin-Watson stat 1.124323 Prob(F-statistic) 0.009411 Fixed Effect DependentVariable:POVERTY Method: Panel LeastSquares Date: 10/20/14 Time:18:26 Sample:2002 2012 Periods included:6 Cross-sections included:8 Total panel (balanced) observations:48 Variable Coefficient Std. Error t-Statistic Prob. INCOME_INEQUALITY 1.353497 0.343255 3.943126 0.0003 GROWTH -0.001332 0.000753 -1.767762 0.0851 C -5.710651 10.18077 -0.560925 0.5781 Effects Specification Cross-section fixed (dummyvariables) R-squared 0.886484 Mean dependentvar 33.79290 Adjusted R-squared 0.859599 S.D. dependentvar 12.08054 S.E. of regression 4.526596 Akaike info criterion 6.040869 Sum squared resid 778.6228 Schwarz criterion 6.430703 Log likelihood -134.9809 Hannan-Quinn criter. 6.188188 F-statistic 32.97278 Durbin-Watson stat 1.881175 Prob(F-statistic) 0.000000
  • 2. Random Effect DependentVariable:POVERTY Method: Panel EGLS (Cross-section random effects) Date: 10/20/14 Time:18:27 Sample:2002 2012 Periods included:6 Cross-sections included:8 Total panel (balanced) observations:48 Swamy and Arora estimator ofcomponentvariances Variable Coefficient Std. Error t-Statistic Prob. INCOME_INEQUALITY 0.176665 0.297120 0.594591 0.5551 GROWTH -0.001965 0.000734 -2.679417 0.0103 C 32.28042 8.784750 3.674597 0.0006 Effects Specification S.D. Rho Cross-section random 2.579440 0.2451 Idiosyncratic random 4.526596 0.7549 Weighted Statistics R-squared 0.051060 Mean dependentvar 19.68061 Adjusted R-squared 0.008885 S.D. dependentvar 8.057974 S.E. of regression 8.022097 Sum squared resid 2895.932 F-statistic 1.210668 Durbin-Watson stat 1.120413 Prob(F-statistic) 0.307519 Unweighted Statistics R-squared 0.081349 Mean dependentvar 33.79290 Sum squared resid 6301.170 Durbin-Watson stat 0.847309