SlideShare a Scribd company logo
1 of 5
Download to read offline
Mia	Attruia	
Econometrics	
STATA	Project	
	
1. The model below is used to test the rationality of assessments of
housing prices. Specifically, consider the simple regression model price =
β0 + β1assess + u, where price is the house price in thousands of dollars,
and assess is the assessed value in thousands of dollars. The assessment is
rational if β1 = 1 and β0 = 0.
(i) After estimating the model by OLS, we obtain: n = 85, SSR =
159, 147.71, R
2
= 0.8164. Test H0 : β1 = 1 against a two-
sided alternative. Perform the test at the 10% significance
level. What do you conclude?
(ii) Now,testH0 :β2 =β3 =β4 =β5 =0(atthe10%level)inthemodel
price = β0 + β1assess + β2lotsize + β3sqrft + β4bdrms +
β5colonial + u, where colonial is a dummy equal to one if the
house is in the colonial style. The SSR from estimating this
model using the same 85 houses is 147,381.38.
Answer
1. (i) The t statistic for H0: b1 = 1 is (0.97 – 1)/0.051 » - 0.588, and the p-value is
0.2776*2 = 0.5552, which is much larger than 0.1. Therefore, we fail to reject b1
= 1 at the 10% significance level.
(ii) We use the SSR form of the F statistic. We are testing q = 4 restrictions and the df
in the unrestricted model is 85 – 5 – 1 = 79. We are given SSRr = 216,264.24 and
SSRur = 164,857.03. Therefore,
F =
(159,147.71-147,381.38)/2
»1.58
147,381.38 / 79
From Table G.3a, the 10% critical value with 4 numerator and 90 denominator
degrees of freedom is 2.01. Because the test statistic is less than the critical value,
we fail to reject H0.
Mia	Attruia	
Econometrics	
STATA	Project	
	
2. An equation explaining chief executive officer salary is ︎ where roe is
return on equity (in percentage form), and finance, consprod, and
utility are dummy variables indicating the financial, consumer
products, and utilities industries. The omitted industry is
transportation.
price = −11.66 + 0.97assess (16.6) (0.051)
log(salary) = 6.84 + 0.006roe + 0.138finance + 0.179consprod −
0.392utility (0.11) (0.005) (0.102) (0.097) (0.113)
n = 209, R
2
= 0.153,
(i) By what percentage is salary predicted to increase if roe increases by
10 points? Does roe have a practically large effect on salary?
(ii) Interpret the coefficient on consprod using the approximation (be
specific).
(iii) Use the formula that we discussed in class to obtain the exact
estimated effect of consprod. Compare it with the answer obtained
in part (ii).
(iv) Is the difference in salaries between the consumer products and
transportation industries statistically significant at the 5% level?
Explain.
(v) What is the approximate percentage difference in estimated salary
between the utilities and finance industries? Explain.
Answer
2. (i) A 10 point ceteris paribus increase in roe is predicted to increase salary by
about 6%, which is a reasonably sizable effect.
(ii) Holding other things fixed, the executive officer salary is about 17.9% higher in
Mia	Attruia	
Econometrics	
STATA	Project	
	
the consumer products industry than in transportation industry.
(iii) Using the formula, the exact estimated effect is [exp(0.179)-1]*100 = 19.6%,
which is somewhat higher than in part (ii).
(iv) The t statistic is 0.179/0.097 » 1.84, p-value = 0.067, which is not statistically
insignificant at the 5% level.
(v) The difference is – 0.392 - 0.138 = - 0.53. That is, the salary is estimated to be
about 53% lower in the utilities than in the finance industry.
Mia	Attruia	
Econometrics	
STATA	Project	
	
3. Use the data in WAGE2 for this exercise.
(i) Estimate the model log(wage) = β0 + β1educ + β2exper + β3married +
β4black + u and report the results in a usual equation form (similar to how
we do it in class). Interpret the coefficient on married using the
approximation (be specific).
(ii) Holding other factors fixed, what is the approximate difference in
monthly earnings between blacks and nonblacks? Is this difference
statistically significant? Justify your answer.
(iii) Create an interaction term, marrblack = married ∗ black. Add this
variable in the model and estimate the extended model (it is not necessary
to report the estimated equation). What is the estimated wage differential
between married blacks and married nonblacks? Explain.
Answer
3. (i) The estimated equation is
log(wage) = 5.46 + 0.0719 educ + 0.018 exper + 0.195 married – 0.211 black (0.12)
(0.006) (0.003) (0.041) (0.038)
n = 935, R
2
= 0.1812.
The coefficient on married implies that, holding other factors fixed, married men earn
about 19.5% more than nonmarried men.
(ii) The coefficient on black implies that, holding other factors fixed, black men earn
about 21.1% less than nonblack men. The p-value is 0.000, and so it is very statistically
significant.
(iii) The estimated monthly earnings for the two groups are: ˆˆˆˆˆˆ
Marriedblacks: waˆge=b0 +b1educ+b2 exper+b3 +b4 +b5 ˆˆˆˆ
Marriednonblacks: waˆge=b0 +b1educ+b2 exper+b3 ˆˆ
Mia	Attruia	
Econometrics	
STATA	Project	
	
So, the difference is b4 + b5 » -0.242 + 0.036 = -0.206 . That is, married blacks are
predicted to earn about 20.6% less than married nonblacks.

More Related Content

What's hot

Moving Straight Ahead 2.3
Moving Straight Ahead 2.3Moving Straight Ahead 2.3
Moving Straight Ahead 2.3Kathy Favazza
 
How Business mathematics assist Business in decision making
How Business mathematics assist Business in decision makingHow Business mathematics assist Business in decision making
How Business mathematics assist Business in decision makingFahad Fu
 
Chapter3.1
Chapter3.1Chapter3.1
Chapter3.1nglaze10
 
8.2 Exploring exponential models
8.2 Exploring exponential models8.2 Exploring exponential models
8.2 Exploring exponential modelsswartzje
 
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...Solutions manual for mathematics of finance canadian 8th edition by brown ibs...
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...adelen11
 
Application linear function
Application linear functionApplication linear function
Application linear functionpuspitaaya
 
Minimum Wage Puerto Rico
Minimum Wage Puerto RicoMinimum Wage Puerto Rico
Minimum Wage Puerto RicoTerry Chaney
 
CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...
CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...
CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...ViscolKanady
 
Chapter 19 decision-making under risk
Chapter 19   decision-making under riskChapter 19   decision-making under risk
Chapter 19 decision-making under riskBich Lien Pham
 
Tracking Faces using Active Appearance Models
Tracking Faces using Active Appearance ModelsTracking Faces using Active Appearance Models
Tracking Faces using Active Appearance ModelsComponica LLC
 
Introduction to Regression Analysis
Introduction to Regression AnalysisIntroduction to Regression Analysis
Introduction to Regression AnalysisMinha Hwang
 

What's hot (13)

Distributive property
Distributive propertyDistributive property
Distributive property
 
Distributive property
Distributive propertyDistributive property
Distributive property
 
Moving Straight Ahead 2.3
Moving Straight Ahead 2.3Moving Straight Ahead 2.3
Moving Straight Ahead 2.3
 
How Business mathematics assist Business in decision making
How Business mathematics assist Business in decision makingHow Business mathematics assist Business in decision making
How Business mathematics assist Business in decision making
 
Chapter3.1
Chapter3.1Chapter3.1
Chapter3.1
 
8.2 Exploring exponential models
8.2 Exploring exponential models8.2 Exploring exponential models
8.2 Exploring exponential models
 
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...Solutions manual for mathematics of finance canadian 8th edition by brown ibs...
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...
 
Application linear function
Application linear functionApplication linear function
Application linear function
 
Minimum Wage Puerto Rico
Minimum Wage Puerto RicoMinimum Wage Puerto Rico
Minimum Wage Puerto Rico
 
CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...
CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...
CONSIDER THE INTERVAL [0, ). FOR EACH NUMERICAL VALUE BELOW, IS IT IN THE INT...
 
Chapter 19 decision-making under risk
Chapter 19   decision-making under riskChapter 19   decision-making under risk
Chapter 19 decision-making under risk
 
Tracking Faces using Active Appearance Models
Tracking Faces using Active Appearance ModelsTracking Faces using Active Appearance Models
Tracking Faces using Active Appearance Models
 
Introduction to Regression Analysis
Introduction to Regression AnalysisIntroduction to Regression Analysis
Introduction to Regression Analysis
 

Similar to STATA Project

Data Analysison Regression
Data Analysison RegressionData Analysison Regression
Data Analysison Regressionjamuga gitulho
 
Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2
Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2
Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2Daniel Katz
 
Quantitative Methods for Lawyers - Class #22 - Regression Analysis - Part 1
Quantitative Methods for Lawyers - Class #22 -  Regression Analysis - Part 1Quantitative Methods for Lawyers - Class #22 -  Regression Analysis - Part 1
Quantitative Methods for Lawyers - Class #22 - Regression Analysis - Part 1Daniel Katz
 
Quantitative Analysis Homework Help
Quantitative Analysis Homework HelpQuantitative Analysis Homework Help
Quantitative Analysis Homework HelpExcel Homework Help
 
Econ 3022 MacroeconomicsSpring 2020Final Exam - Due A.docx
Econ 3022 MacroeconomicsSpring 2020Final Exam - Due A.docxEcon 3022 MacroeconomicsSpring 2020Final Exam - Due A.docx
Econ 3022 MacroeconomicsSpring 2020Final Exam - Due A.docxtidwellveronique
 
Econ 103 Homework 2Manu NavjeevanAugust 15, 2022S
Econ 103 Homework 2Manu NavjeevanAugust 15, 2022SEcon 103 Homework 2Manu NavjeevanAugust 15, 2022S
Econ 103 Homework 2Manu NavjeevanAugust 15, 2022SEvonCanales257
 
Job Prestige analysis: Adrian Valles
Job Prestige analysis: Adrian VallesJob Prestige analysis: Adrian Valles
Job Prestige analysis: Adrian VallesAdrián Vallés
 
Convenience shoppingSTAT-S301Fall 2019Question Set 1.docx
Convenience shoppingSTAT-S301Fall 2019Question Set 1.docxConvenience shoppingSTAT-S301Fall 2019Question Set 1.docx
Convenience shoppingSTAT-S301Fall 2019Question Set 1.docxbobbywlane695641
 
Intro to econometrics
Intro to econometricsIntro to econometrics
Intro to econometricsGaetan Lion
 
IBM401 Lecture 7
IBM401 Lecture 7IBM401 Lecture 7
IBM401 Lecture 7saark
 
Course Assignment : Skip gram
Course Assignment : Skip gramCourse Assignment : Skip gram
Course Assignment : Skip gramKhalilBergaoui
 
Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...
Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...
Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...Jonathan Zimmermann
 
ISI MSQE Entrance Question Paper (2005)
ISI MSQE Entrance Question Paper (2005)ISI MSQE Entrance Question Paper (2005)
ISI MSQE Entrance Question Paper (2005)CrackDSE
 
Microeconomics Exam Questions and Answers
Microeconomics Exam Questions and AnswersMicroeconomics Exam Questions and Answers
Microeconomics Exam Questions and AnswersLive Exam Helper
 
ISI MSQE Entrance Question Paper (2006)
ISI MSQE Entrance Question Paper (2006)ISI MSQE Entrance Question Paper (2006)
ISI MSQE Entrance Question Paper (2006)CrackDSE
 

Similar to STATA Project (20)

Data Analysison Regression
Data Analysison RegressionData Analysison Regression
Data Analysison Regression
 
2 simple regression
2   simple regression2   simple regression
2 simple regression
 
Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2
Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2
Quantitative Methods for Lawyers - Class #19 - Regression Analysis - Part 2
 
Quantitative Methods for Lawyers - Class #22 - Regression Analysis - Part 1
Quantitative Methods for Lawyers - Class #22 -  Regression Analysis - Part 1Quantitative Methods for Lawyers - Class #22 -  Regression Analysis - Part 1
Quantitative Methods for Lawyers - Class #22 - Regression Analysis - Part 1
 
Quantitative Analysis Homework Help
Quantitative Analysis Homework HelpQuantitative Analysis Homework Help
Quantitative Analysis Homework Help
 
Econ 3022 MacroeconomicsSpring 2020Final Exam - Due A.docx
Econ 3022 MacroeconomicsSpring 2020Final Exam - Due A.docxEcon 3022 MacroeconomicsSpring 2020Final Exam - Due A.docx
Econ 3022 MacroeconomicsSpring 2020Final Exam - Due A.docx
 
Econ 103 Homework 2Manu NavjeevanAugust 15, 2022S
Econ 103 Homework 2Manu NavjeevanAugust 15, 2022SEcon 103 Homework 2Manu NavjeevanAugust 15, 2022S
Econ 103 Homework 2Manu NavjeevanAugust 15, 2022S
 
Job Prestige analysis: Adrian Valles
Job Prestige analysis: Adrian VallesJob Prestige analysis: Adrian Valles
Job Prestige analysis: Adrian Valles
 
Convenience shoppingSTAT-S301Fall 2019Question Set 1.docx
Convenience shoppingSTAT-S301Fall 2019Question Set 1.docxConvenience shoppingSTAT-S301Fall 2019Question Set 1.docx
Convenience shoppingSTAT-S301Fall 2019Question Set 1.docx
 
Numerical Computation
Numerical ComputationNumerical Computation
Numerical Computation
 
Demand Estimation
Demand EstimationDemand Estimation
Demand Estimation
 
Intro to econometrics
Intro to econometricsIntro to econometrics
Intro to econometrics
 
Chapitre08_Solutions.pdf
Chapitre08_Solutions.pdfChapitre08_Solutions.pdf
Chapitre08_Solutions.pdf
 
IBM401 Lecture 7
IBM401 Lecture 7IBM401 Lecture 7
IBM401 Lecture 7
 
Course Assignment : Skip gram
Course Assignment : Skip gramCourse Assignment : Skip gram
Course Assignment : Skip gram
 
exercises.pdf
exercises.pdfexercises.pdf
exercises.pdf
 
Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...
Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...
Problem set 3 - Statistics and Econometrics - Msc Business Analytics - Imperi...
 
ISI MSQE Entrance Question Paper (2005)
ISI MSQE Entrance Question Paper (2005)ISI MSQE Entrance Question Paper (2005)
ISI MSQE Entrance Question Paper (2005)
 
Microeconomics Exam Questions and Answers
Microeconomics Exam Questions and AnswersMicroeconomics Exam Questions and Answers
Microeconomics Exam Questions and Answers
 
ISI MSQE Entrance Question Paper (2006)
ISI MSQE Entrance Question Paper (2006)ISI MSQE Entrance Question Paper (2006)
ISI MSQE Entrance Question Paper (2006)
 

Recently uploaded

如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证
如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证
如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证ju0dztxtn
 
NOAM AAUG Adobe Summit 2024: Summit Slam Dunks
NOAM AAUG Adobe Summit 2024: Summit Slam DunksNOAM AAUG Adobe Summit 2024: Summit Slam Dunks
NOAM AAUG Adobe Summit 2024: Summit Slam Dunksgmuir1066
 
如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证
如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证
如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证zifhagzkk
 
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证dq9vz1isj
 
MATERI MANAJEMEN OF PENYAKIT TETANUS.ppt
MATERI  MANAJEMEN OF PENYAKIT TETANUS.pptMATERI  MANAJEMEN OF PENYAKIT TETANUS.ppt
MATERI MANAJEMEN OF PENYAKIT TETANUS.pptRachmaGhifari
 
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...ssuserf63bd7
 
SCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarj
SCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarjSCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarj
SCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarjadimosmejiaslendon
 
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证acoha1
 
Genuine love spell caster )! ,+27834335081) Ex lover back permanently in At...
Genuine love spell caster )! ,+27834335081)   Ex lover back permanently in At...Genuine love spell caster )! ,+27834335081)   Ex lover back permanently in At...
Genuine love spell caster )! ,+27834335081) Ex lover back permanently in At...BabaJohn3
 
Audience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptxAudience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptxStephen266013
 
原件一样伦敦国王学院毕业证成绩单留信学历认证
原件一样伦敦国王学院毕业证成绩单留信学历认证原件一样伦敦国王学院毕业证成绩单留信学历认证
原件一样伦敦国王学院毕业证成绩单留信学历认证pwgnohujw
 
社内勉強会資料_Object Recognition as Next Token Prediction
社内勉強会資料_Object Recognition as Next Token Prediction社内勉強会資料_Object Recognition as Next Token Prediction
社内勉強会資料_Object Recognition as Next Token PredictionNABLAS株式会社
 
Displacement, Velocity, Acceleration, and Second Derivatives
Displacement, Velocity, Acceleration, and Second DerivativesDisplacement, Velocity, Acceleration, and Second Derivatives
Displacement, Velocity, Acceleration, and Second Derivatives23050636
 
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...ssuserf63bd7
 
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...ThinkInnovation
 
原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证
原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证
原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证pwgnohujw
 
1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证
1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证
1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证ppy8zfkfm
 
Identify Customer Segments to Create Customer Offers for Each Segment - Appli...
Identify Customer Segments to Create Customer Offers for Each Segment - Appli...Identify Customer Segments to Create Customer Offers for Each Segment - Appli...
Identify Customer Segments to Create Customer Offers for Each Segment - Appli...ThinkInnovation
 
如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一
如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一
如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一fztigerwe
 

Recently uploaded (20)

如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证
如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证
如何办理英国卡迪夫大学毕业证(Cardiff毕业证书)成绩单留信学历认证
 
NOAM AAUG Adobe Summit 2024: Summit Slam Dunks
NOAM AAUG Adobe Summit 2024: Summit Slam DunksNOAM AAUG Adobe Summit 2024: Summit Slam Dunks
NOAM AAUG Adobe Summit 2024: Summit Slam Dunks
 
如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证
如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证
如何办理(Dalhousie毕业证书)达尔豪斯大学毕业证成绩单留信学历认证
 
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
 
MATERI MANAJEMEN OF PENYAKIT TETANUS.ppt
MATERI  MANAJEMEN OF PENYAKIT TETANUS.pptMATERI  MANAJEMEN OF PENYAKIT TETANUS.ppt
MATERI MANAJEMEN OF PENYAKIT TETANUS.ppt
 
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
 
SCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarj
SCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarjSCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarj
SCI8-Q4-MOD11.pdfwrwujrrjfaajerjrajrrarj
 
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
 
Genuine love spell caster )! ,+27834335081) Ex lover back permanently in At...
Genuine love spell caster )! ,+27834335081)   Ex lover back permanently in At...Genuine love spell caster )! ,+27834335081)   Ex lover back permanently in At...
Genuine love spell caster )! ,+27834335081) Ex lover back permanently in At...
 
Abortion pills in Riyadh Saudi Arabia (+966572737505 buy cytotec
Abortion pills in Riyadh Saudi Arabia (+966572737505 buy cytotecAbortion pills in Riyadh Saudi Arabia (+966572737505 buy cytotec
Abortion pills in Riyadh Saudi Arabia (+966572737505 buy cytotec
 
Audience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptxAudience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptx
 
原件一样伦敦国王学院毕业证成绩单留信学历认证
原件一样伦敦国王学院毕业证成绩单留信学历认证原件一样伦敦国王学院毕业证成绩单留信学历认证
原件一样伦敦国王学院毕业证成绩单留信学历认证
 
社内勉強会資料_Object Recognition as Next Token Prediction
社内勉強会資料_Object Recognition as Next Token Prediction社内勉強会資料_Object Recognition as Next Token Prediction
社内勉強会資料_Object Recognition as Next Token Prediction
 
Displacement, Velocity, Acceleration, and Second Derivatives
Displacement, Velocity, Acceleration, and Second DerivativesDisplacement, Velocity, Acceleration, and Second Derivatives
Displacement, Velocity, Acceleration, and Second Derivatives
 
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
 
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
 
原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证
原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证
原件一样(UWO毕业证书)西安大略大学毕业证成绩单留信学历认证
 
1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证
1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证
1:1原版定制利物浦大学毕业证(Liverpool毕业证)成绩单学位证书留信学历认证
 
Identify Customer Segments to Create Customer Offers for Each Segment - Appli...
Identify Customer Segments to Create Customer Offers for Each Segment - Appli...Identify Customer Segments to Create Customer Offers for Each Segment - Appli...
Identify Customer Segments to Create Customer Offers for Each Segment - Appli...
 
如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一
如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一
如何办理哥伦比亚大学毕业证(Columbia毕业证)成绩单原版一比一
 

STATA Project

  • 1. Mia Attruia Econometrics STATA Project 1. The model below is used to test the rationality of assessments of housing prices. Specifically, consider the simple regression model price = β0 + β1assess + u, where price is the house price in thousands of dollars, and assess is the assessed value in thousands of dollars. The assessment is rational if β1 = 1 and β0 = 0. (i) After estimating the model by OLS, we obtain: n = 85, SSR = 159, 147.71, R 2 = 0.8164. Test H0 : β1 = 1 against a two- sided alternative. Perform the test at the 10% significance level. What do you conclude? (ii) Now,testH0 :β2 =β3 =β4 =β5 =0(atthe10%level)inthemodel price = β0 + β1assess + β2lotsize + β3sqrft + β4bdrms + β5colonial + u, where colonial is a dummy equal to one if the house is in the colonial style. The SSR from estimating this model using the same 85 houses is 147,381.38. Answer 1. (i) The t statistic for H0: b1 = 1 is (0.97 – 1)/0.051 » - 0.588, and the p-value is 0.2776*2 = 0.5552, which is much larger than 0.1. Therefore, we fail to reject b1 = 1 at the 10% significance level. (ii) We use the SSR form of the F statistic. We are testing q = 4 restrictions and the df in the unrestricted model is 85 – 5 – 1 = 79. We are given SSRr = 216,264.24 and SSRur = 164,857.03. Therefore, F = (159,147.71-147,381.38)/2 »1.58 147,381.38 / 79 From Table G.3a, the 10% critical value with 4 numerator and 90 denominator degrees of freedom is 2.01. Because the test statistic is less than the critical value, we fail to reject H0.
  • 2. Mia Attruia Econometrics STATA Project 2. An equation explaining chief executive officer salary is ︎ where roe is return on equity (in percentage form), and finance, consprod, and utility are dummy variables indicating the financial, consumer products, and utilities industries. The omitted industry is transportation. price = −11.66 + 0.97assess (16.6) (0.051) log(salary) = 6.84 + 0.006roe + 0.138finance + 0.179consprod − 0.392utility (0.11) (0.005) (0.102) (0.097) (0.113) n = 209, R 2 = 0.153, (i) By what percentage is salary predicted to increase if roe increases by 10 points? Does roe have a practically large effect on salary? (ii) Interpret the coefficient on consprod using the approximation (be specific). (iii) Use the formula that we discussed in class to obtain the exact estimated effect of consprod. Compare it with the answer obtained in part (ii). (iv) Is the difference in salaries between the consumer products and transportation industries statistically significant at the 5% level? Explain. (v) What is the approximate percentage difference in estimated salary between the utilities and finance industries? Explain. Answer 2. (i) A 10 point ceteris paribus increase in roe is predicted to increase salary by about 6%, which is a reasonably sizable effect. (ii) Holding other things fixed, the executive officer salary is about 17.9% higher in
  • 3. Mia Attruia Econometrics STATA Project the consumer products industry than in transportation industry. (iii) Using the formula, the exact estimated effect is [exp(0.179)-1]*100 = 19.6%, which is somewhat higher than in part (ii). (iv) The t statistic is 0.179/0.097 » 1.84, p-value = 0.067, which is not statistically insignificant at the 5% level. (v) The difference is – 0.392 - 0.138 = - 0.53. That is, the salary is estimated to be about 53% lower in the utilities than in the finance industry.
  • 4. Mia Attruia Econometrics STATA Project 3. Use the data in WAGE2 for this exercise. (i) Estimate the model log(wage) = β0 + β1educ + β2exper + β3married + β4black + u and report the results in a usual equation form (similar to how we do it in class). Interpret the coefficient on married using the approximation (be specific). (ii) Holding other factors fixed, what is the approximate difference in monthly earnings between blacks and nonblacks? Is this difference statistically significant? Justify your answer. (iii) Create an interaction term, marrblack = married ∗ black. Add this variable in the model and estimate the extended model (it is not necessary to report the estimated equation). What is the estimated wage differential between married blacks and married nonblacks? Explain. Answer 3. (i) The estimated equation is log(wage) = 5.46 + 0.0719 educ + 0.018 exper + 0.195 married – 0.211 black (0.12) (0.006) (0.003) (0.041) (0.038) n = 935, R 2 = 0.1812. The coefficient on married implies that, holding other factors fixed, married men earn about 19.5% more than nonmarried men. (ii) The coefficient on black implies that, holding other factors fixed, black men earn about 21.1% less than nonblack men. The p-value is 0.000, and so it is very statistically significant. (iii) The estimated monthly earnings for the two groups are: ˆˆˆˆˆˆ Marriedblacks: waˆge=b0 +b1educ+b2 exper+b3 +b4 +b5 ˆˆˆˆ Marriednonblacks: waˆge=b0 +b1educ+b2 exper+b3 ˆˆ
  • 5. Mia Attruia Econometrics STATA Project So, the difference is b4 + b5 » -0.242 + 0.036 = -0.206 . That is, married blacks are predicted to earn about 20.6% less than married nonblacks.