Final Exam, section 2. Tuesday, December hour, 30 minutes
|
|
- Polly Lang
- 5 years ago
- Views:
Transcription
1 San Francisco State University Michael Bar ECON 312 Fall 2018 Final Exam, section 2 Tuesday, December 18 1 hour, 30 minutes Name: Instructions 1. This is closed book, closed notes exam. 2. You can use one double-sided sheet of paper, letter size (8½ 11 in or mm), with any content you want. 3. No calculators of any kind are allowed. 4. Show all the calculations, and explain your steps. 5. If you need more space, use the back of the page. 6. Fully label all graphs. Good Luck
2 1. (40 points). Jennifer is close to completing her bachelor s degree in economics, and she considers pursuing a master s degree. For her ECON 690 project she collected a sample of workers with either bachelor s degree or master s degree, with the following variables: inc - respondent s total annual income (in $) afqt - percentile score on U.S. Armed Forces Qualifying Exam female - dummy (=1 if female, 0 otherwise) black - dummy (=1 if black, 0 otherwise) ma - dummy (=1 if highest level of education is master s degree, 0 if highest level of education is bachelor s degree) Jennifer estimated two models, and her results are reported in the next table. The numbers in parentheses are 95% confidence intervals. Dependent variable: log(inc) model1 model2 Constant *** (10.234, ) *** (10.231, ) afqt *** (0.004, 0.007) *** (0.004, 0.007) female *** (-0.388, ) *** (-0.395, ) black (-0.094, 0.115) (-0.112, 0.102) ma * (-0.017, 0.226) (-0.124, 0.216) female:ma (-0.189, 0.298) black:ma (-0.087, 0.680) Observations R Adjusted R Residual Std. Error (df = 843) (df = 841) F Statistic *** (df = 4; 843) *** (df = 6; 841) Note: * p<0.1; ** p<0.05; *** p<0.01 a. Demonstrate how you would use the fitted equation from model1 to predict the total income of a Hispanic female with master s degree, who scored at the 95 th percentile on her Armed Forces Qualifying Exam (afqt = 95). No need to calculate the final number, just write the fitted equation and substitute the values. ıııııı = exp(bb 1 + bb 2 ssssssss + bb 3 ffffffffffff + bb 4 bbbbbbbbbb + bb 5 mmmm) = exp( ) = exp ( ) We exponentiate because the dependent variable is log(inc). 1
3 b. Interpret the estimated coefficient on ma in model1. bb 5 = means that workers with master s degree are earning 10.4% more in annual income than workers with bachelor s degree, holding all other regressors the same (i.e. gender, race, and score on the Armed Forces Qualifying Exam). c. Interpret the estimated coefficient on black in model1. bb 4 = means that black workers annual income is approximately 1% higher than that of non-black workers, holding all other regressors the same (i.e. gender, education level, and score on the Armed Forces Qualifying Exam). Remark. Notice that this difference is not significant, so this data gives no evidence that income of black workers differ from income of non-black workers. Perhaps the racial gap shrinks among workers of advanced degrees (remember that this sample consists of workers with bachelor s and master s degrees only. d. Suppose that Jennifer wants to test whether female workers income is lower than the income of male workers. Write the null and alternative hypotheses for her test, based on model1. HH 0 : ββ 3 = 0 HH 1 : ββ 3 < 0 2
4 e. Interpret the estimated coefficient on black:ma in model2. bb 7 = is the difference between the benefit from master s degree for black and for nonblack. That is, black workers income benefit from master s degree is 29.6%% more than nonblack workers, holding other regressors fixed (gender, and score on the Armed Forces Qualifying Exam). Steps. bbbbbbbbbbbbtt bbbbbbbbbb,mmmm = ıııııı bbbbbbbbbb,mmmm ıııııı bbbbbbbbbb,bbbbbbh = bb 4 + bb 7 bbbbbbbbbbbbtt nnnnnn bbbbbbbbbb,mmmm = ıııııı nnnnnn bbbbbbbbbb,mmmm ıııııı nnnnnn bbbbbbbbbb,bbbbbbh = bb 4 Thus, the difference between the benefit of black and non-black is: bbbbbbbbbbbbbb bbbbbbbbbb,mmmm bbbbbbbbbbbbbb nnnnnn bbbbbbbbbb,mmmm = bb 7 f. Suppose that Jennifer wants to test whether female workers benefits from master s degree are different from benefits of male workers from master s degree. Write the null and alternative hypotheses for her test, based on model2. HH 0 : ββ 6 = 0 HH 1 : ββ 6 0 g. Based on the reported confidence intervals, what is your conclusion about the test in the last section? Explain your answer. The 95% confidence interval for ββ 6 is (-0.189, 0.298), contains all the null values of ββ 6 which cannot be rejected at significance level of αα = 5% against a two-sided alternative. Since the reported confidence interval contains 0, we fail to reject the null hypotheses at significance level αα = 5%. We conclude that female workers benefits from master s degree are NOT different from benefits of male workers from master s degree. 3
5 h. Suppose that Jennifer wants to test whether income of female workers with master s degree is higher than the income of female workers with bachelor s degree. Write the null and alternative hypotheses for her test, based on model2. HH 0 : ββ 5 + ββ 6 = 0 HH 1 : ββ 5 + ββ 6 > 0 2. (5 points). P-value for a test is (circle the correct answer): a. The probability of accepting a true null hypothesis. b. The probability of rejecting a true null hypothesis. c. The probability of accepting a false null hypothesis. d. The probability of rejecting a false null hypothesis. e. None of the above. 3. (5 points). An estimator θθ nn of the unknown population parameter θθ, based on random sample of size nn, is efficient if (circle the correct answer): a. vvvvvv(θθ ) = 0 nn. b. vvvvvv(θθ nn ) 0 as nn. c. bbbbbbbb(θθ nn ) 0 as nn. d. EE θθ nn θθ = 0 nn. e. None of the above. 4
6 4. (20 points). Simone serves as an expert witness in a discrimination lawsuit against a major mortgage lending company. She collected data on 2,380 loan applications from that company, with the following variables: deny = 1 if mortgage application was denied, 0 otherwise black = 1 if applicant is black, 0 in non-black dir ratio of debt payments to total income of applicant, in % lvr ratio of loan amount to value of property, in % cs credit score (in points, higher value is better) dmi = 1 if applicant was denied mortgage insurance, 0 otherwise Simone estimated the probit and logit models, and her results (marginal effects) are given in the next table. Estimated standard errors are in parentheses, and the constant is omitted: Dependent variable: deny Probit mfx Logit mfx black *** (0.0215) *** (0.0197) dir *** (0.0006) *** (0.0006) lvr *** (0.0004) *** (0.0004) cs *** (0.0031) *** (0.0027) dmi *** (0.0605) *** (0.0585) Pseudo R p-value 0 0 Observations 2,381 2,381 Log Likelihood Akaike Inf. Crit. 1, , Note: * p<0.1; ** p<0.05; *** p<0.01 a. Interpret the estimated marginal effect of black in the logit model. mmmmmm(bbbbbbbbbb) = , means that black applicants are 7.38% more likely to be denied a mortgage, than non-black applicants, holding all other regressors (mortgage characteristics) at their sample means values. 5
7 b. Suppose Simone wants to test statistically whether the lending company discriminates against black applicants. Write the null and alternative hypotheses of this test. Let ββ 2 be the unknown marginal effect on black. The test is therefore: HH 0 : ββ 2 = 0 HH 1 : ββ 2 > 0 Remark: If black applicants are being discriminated, then their chances of being denied a mortgage are higher, i.e. this is upper-tail test. c. Interpret the estimated marginal effect of lvr in the logit model. mmmmmm(llllll) = means that a 1% increase in the ratio of loan amount to value of property, increases the chances of mortgage application denial by 0.14%, holding all regressors at the sample average values. d. Interpret the estimated marginal effect of cs class in the logit model. mmmmmm(cccc) = means that a 1 point increase in applicant s credit score, lowers the chances of mortgage application denial by 0.262%, holding all regressors at the sample average values. 6
8 5. (10 points). Suppose that you estimated a regression model using OLS, and the plot of residuals against the fitted values looks like the next figure. Heteroscedasticity. a. (3 points). What kind of econometric problem your model likely suffers from? b. (4 points). What are the consequences of the problem in the previous section? OLS estimators are inefficient Estimated standard errors are biased, and therefore statistical hypotheses tests are invalid. c. (3 points). Propose a practical solution to the problem you identified in section a. The most practical solution to compute and report robust standard errors (in R, using the sandwich package). 7
9 6. (10 points). Suppose that Kevin estimated two models, and his fitted equations are: EEEEEEEEEEEEEEEE = bb 1 + 3SS + 3EEEEEE EEEEEE = dd 1 0.2SS Where SS is schooling and EEEEEE is experience. Dray is another researcher who estimated the following model: EEEEEEEEEEEEEEEE = bb 1 + bb 2 SS a. (3 points). Suppose that Kevin s model is the correct one. What is the econometric problem in Dray s model? Omitted variable bias. b. (4 points). What are the likely consequences of the problem in the previous section? i. Biased and inconsistent estimator of the coefficient on the schooling, ii. Biased standard errors of estimators, which makes all statistical tests invalid. c. (3 points). What would be the value of Dray s estimated coefficient on schooling, bb 2? bb 2 = bb 2 + bb 3 dd 2 = ( 0.2) = 2.4 8
10 7. (10 points). Suppose that you are planning to use time series data that looks like the following two variables. Trends in variables. a. (3 points). What kind of econometric problem you are likely to face when using time series data that looks like the above two variables? b. (4 points). What are the consequences of the problem in the previous section? Spurious regression, which leads to biased and inconsistent estimators (similar to omitted variable bias). c. (3 points). Propose one practical solution to the problem you identified in section a. i. Detrending (removing the trend from variables) before using them in regression. ii. Normalizing expressing the variables in terms of ratios of the original variable to some other key variable. For example, CC tt cc tt =, or dddddd GGGGPP tt = DDDDDD tt tt GGGGPP tt are normalized consumption and normalized deficit, both expressed as a fraction of GDP. iii. Including time as a regressor. 9
Final Exam, section 1. Tuesday, December hour, 30 minutes
San Francisco State University Michael Bar ECON 312 Fall 2018 Final Exam, section 1 Tuesday, December 18 1 hour, 30 minutes Name: Instructions 1. This is closed book, closed notes exam. 2. You can use
More informationFinal Exam, section 1. Thursday, May hour, 30 minutes
San Francisco State University Michael Bar ECON 312 Spring 2018 Final Exam, section 1 Thursday, May 17 1 hour, 30 minutes Name: Instructions 1. This is closed book, closed notes exam. 2. You can use one
More informationFinal Exam - section 1. Thursday, December hours, 30 minutes
Econometrics, ECON312 San Francisco State University Michael Bar Fall 2013 Final Exam - section 1 Thursday, December 19 1 hours, 30 minutes Name: Instructions 1. This is closed book, closed notes exam.
More informationFinal Exam, section 1
San Francisco State University Michael Bar ECON 312 Fall 2015 Final Exam, section 1 Monday, December 14, 2015 Time: 1 hour, 30 minutes Name: Instructions: 1. This is closed book, closed notes exam. 2.
More informationCHAPTER 11 Regression with a Binary Dependent Variable. Kazu Matsuda IBEC PHBU 430 Econometrics
CHAPTER 11 Regression with a Binary Dependent Variable Kazu Matsuda IBEC PHBU 430 Econometrics Mortgage Application Example Two people, identical but for their race, walk into a bank and apply for a mortgage,
More informationReview questions for Multinomial Logit/Probit, Tobit, Heckit, Quantile Regressions
1. I estimated a multinomial logit model of employment behavior using data from the 2006 Current Population Survey. The three possible outcomes for a person are employed (outcome=1), unemployed (outcome=2)
More informationa. Explain why the coefficients change in the observed direction when switching from OLS to Tobit estimation.
1. Using data from IRS Form 5500 filings by U.S. pension plans, I estimated a model of contributions to pension plans as ln(1 + c i ) = α 0 + U i α 1 + PD i α 2 + e i Where the subscript i indicates the
More informationTests for the Odds Ratio in a Matched Case-Control Design with a Binary X
Chapter 156 Tests for the Odds Ratio in a Matched Case-Control Design with a Binary X Introduction This procedure calculates the power and sample size necessary in a matched case-control study designed
More information[BINARY DEPENDENT VARIABLE ESTIMATION WITH STATA]
Tutorial #3 This example uses data in the file 16.09.2011.dta under Tutorial folder. It contains 753 observations from a sample PSID data on the labor force status of married women in the U.S in 1975.
More informationECO671, Spring 2014, Sample Questions for First Exam
1. Using data from the Survey of Consumers Finances between 1983 and 2007 (the surveys are done every 3 years), I used OLS to examine the determinants of a household s credit card debt. Credit card debt
More informationName: 1. Use the data from the following table to answer the questions that follow: (10 points)
Economics 345 Mid-Term Exam October 8, 2003 Name: Directions: You have the full period (7:20-10:00) to do this exam, though I suspect it won t take that long for most students. You may consult any materials,
More informationTable 4. Probit model of union membership. Probit coefficients are presented below. Data from March 2008 Current Population Survey.
1. Using a probit model and data from the 2008 March Current Population Survey, I estimated a probit model of the determinants of pension coverage. Three specifications were estimated. The first included
More informationINSTITUTE AND FACULTY OF ACTUARIES. Curriculum 2019 SPECIMEN EXAMINATION
INSTITUTE AND FACULTY OF ACTUARIES Curriculum 2019 SPECIMEN EXAMINATION Subject CS1A Actuarial Statistics Time allowed: Three hours and fifteen minutes INSTRUCTIONS TO THE CANDIDATE 1. Enter all the candidate
More informationYour Name (Please print) Did you agree to take the optional portion of the final exam Yes No. Directions
Your Name (Please print) Did you agree to take the optional portion of the final exam Yes No (Your online answer will be used to verify your response.) Directions There are two parts to the final exam.
More informationForecasting Real Estate Prices
Forecasting Real Estate Prices Stefano Pastore Advanced Financial Econometrics III Winter/Spring 2018 Overview Peculiarities of Forecasting Real Estate Prices Real Estate Indices Serial Dependence in Real
More informationFinal Exam. Friday, July 7. 1 hour, 30 minutes
San Francisco State University Michael Bar ECON 102 Summer 2017 Final Exam Friday, July 7 1 hour, 30 minutes Name: Student ID: Instructions 1. This is closed book, closed notes exam. 2. No calculators
More informationFinal Exam. Friday, July 7. 1 hour, 30 minutes
San Francisco State University Michael Bar ECON 102 Summer 2017 Final Exam Friday, July 7 1 hour, 30 minutes Name: Student ID: Instructions 1. This is closed book, closed notes exam. 2. No calculators
More informationMay 9, Please put ONLY your ID number on the blue books. Three (3) points will be deducted for each time your name appears in a blue book.
PAD 705: Research Methods II R. Karl Rethemeyer Department of Public Administration and Policy Rockefeller College of Public Affair & Policy University at Albany State University of New York Final Exam
More informationEcon 371 Problem Set #4 Answer Sheet. 6.2 This question asks you to use the results from column (1) in the table on page 213.
Econ 371 Problem Set #4 Answer Sheet 6.2 This question asks you to use the results from column (1) in the table on page 213. a. The first part of this question asks whether workers with college degrees
More informationPoint-Biserial and Biserial Correlations
Chapter 302 Point-Biserial and Biserial Correlations Introduction This procedure calculates estimates, confidence intervals, and hypothesis tests for both the point-biserial and the biserial correlations.
More informationSupporting Information for:
Supporting Information for: Can Political Participation Prevent Crime? Results from a Field Experiment about Citizenship, Participation, and Criminality This appendix contains the following material: Supplemental
More informationThe Impact of the Minimum Wage on Employment and Hours Worked for the Young and Low-Educated: An Analysis of the United States North East
Skidmore College Creative Matter Economics Student Theses and Capstone Projects Economics 2018 The Impact of the Minimum Wage on Employment and Hours Worked for the Young and Low-Educated: An Analysis
More informationSoftware Made Simple: Effort Adjustment Factors and the Accuracy of the Estimate
Software Made Simple: Effort Adjustment Factors and the Accuracy of the Estimate June 13, 2018 Jeremy Goucher Space Solutions 2016 MCR, LLC Distribution prohibited without express written consent of MCR,
More informationtm / / / / / / / / / / / / Statistics/Data Analysis User: Klick Project: Limited Dependent Variables{space -6}
PS 4 Monday August 16 01:00:42 2010 Page 1 tm / / / / / / / / / / / / Statistics/Data Analysis User: Klick Project: Limited Dependent Variables{space -6} log: C:\web\PS4log.smcl log type: smcl opened on:
More informationNPTEL Project. Econometric Modelling. Module 16: Qualitative Response Regression Modelling. Lecture 20: Qualitative Response Regression Modelling
1 P age NPTEL Project Econometric Modelling Vinod Gupta School of Management Module 16: Qualitative Response Regression Modelling Lecture 20: Qualitative Response Regression Modelling Rudra P. Pradhan
More informationPublic-private sector pay differential in UK: A recent update
Public-private sector pay differential in UK: A recent update by D H Blackaby P D Murphy N C O Leary A V Staneva No. 2013-01 Department of Economics Discussion Paper Series Public-private sector pay differential
More informationUnderstanding Differential Cycle Sensitivity for Loan Portfolios
Understanding Differential Cycle Sensitivity for Loan Portfolios James O Donnell jodonnell@westpac.com.au Context & Background At Westpac we have recently conducted a revision of our Probability of Default
More informationM249 Diagnostic Quiz
THE OPEN UNIVERSITY Faculty of Mathematics and Computing M249 Diagnostic Quiz Prepared by the Course Team [Press to begin] c 2005, 2006 The Open University Last Revision Date: May 19, 2006 Version 4.2
More informationThe Influence of Race in Residential Mortgage Closings
The Influence of Race in Residential Mortgage Closings Authors John P. McMurray and Thomas A. Thomson Abstract This study examines how applicants identified as Asian, Black or Hispanic differ in mortgage
More informationTests for Two Means in a Cluster-Randomized Design
Chapter 482 Tests for Two Means in a Cluster-Randomized Design Introduction Cluster-randomized designs are those in which whole clusters of subjects (classes, hospitals, communities, etc.) are put into
More informationSALARY EQUITY ANALYSIS AT ARL INSTITUTIONS
SALARY EQUITY ANALYSIS AT ARL INSTITUTIONS Quinn Galbraith, MSS & MLS - Sociology and Family Life Librarian, ARL Visiting Program Officer Michael Groesbeck, BS - Statistician Brigham R. Frandsen, PhD -
More informationAre Greek budget deficits 'too large'? National University of Ireland, Galway
Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published version when available. Title Are Greek budget deficits 'too large'? Author(s) Fountas, Stilianos
More informationFall 2004 Social Sciences 7418 University of Wisconsin-Madison Problem Set 5 Answers
Economics 310 Menzie D. Chinn Fall 2004 Social Sciences 7418 University of Wisconsin-Madison Problem Set 5 Answers This problem set is due in lecture on Wednesday, December 15th. No late problem sets will
More informationWeb Appendix Figure 1. Operational Steps of Experiment
Web Appendix Figure 1. Operational Steps of Experiment 57,533 direct mail solicitations with randomly different offer interest rates sent out to former clients. 5,028 clients go to branch and apply for
More informationLabor Force Participation and the Wage Gap Detailed Notes and Code Econometrics 113 Spring 2014
Labor Force Participation and the Wage Gap Detailed Notes and Code Econometrics 113 Spring 2014 In class, Lecture 11, we used a new dataset to examine labor force participation and wages across groups.
More informationTests for the Difference Between Two Linear Regression Intercepts
Chapter 853 Tests for the Difference Between Two Linear Regression Intercepts Introduction Linear regression is a commonly used procedure in statistical analysis. One of the main objectives in linear regression
More informationThe model is estimated including a fixed effect for each family (u i ). The estimated model was:
1. In a 1996 article, Mark Wilhelm examined whether parents bequests are altruistic. 1 According to the altruistic model of bequests, a parent with several children would leave larger bequests to children
More informationSTA 4504/5503 Sample questions for exam True-False questions.
STA 4504/5503 Sample questions for exam 2 1. True-False questions. (a) For General Social Survey data on Y = political ideology (categories liberal, moderate, conservative), X 1 = gender (1 = female, 0
More informationLecture 10: Alternatives to OLS with limited dependent variables, part 1. PEA vs APE Logit/Probit
Lecture 10: Alternatives to OLS with limited dependent variables, part 1 PEA vs APE Logit/Probit PEA vs APE PEA: partial effect at the average The effect of some x on y for a hypothetical case with sample
More informationOne-Sample Cure Model Tests
Chapter 713 One-Sample Cure Model Tests Introduction This module computes the sample size and power of the one-sample parametric cure model proposed by Wu (2015). This technique is useful when working
More informationTOTAL SCORE EXE 1 EXE 2 EXE 3 MC
TOTAL SCORE EXE 1 EXE 2 EXE 3 MC Econ 002- INTRO MACRO Prof. Luca Bossi December 15, 2016 FINAL EXAM SUGGESTED SOLUTIONS My signature below certifies that I have complied with the University of Pennsylvania's
More informationThe University of Chicago, Booth School of Business Business 41202, Spring Quarter 2009, Mr. Ruey S. Tsay. Solutions to Final Exam
The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2009, Mr. Ruey S. Tsay Solutions to Final Exam Problem A: (42 pts) Answer briefly the following questions. 1. Questions
More informationProblem Set 6 ANSWERS
Economics 20 Part I. Problem Set 6 ANSWERS Prof. Patricia M. Anderson The first 5 questions are based on the following information: Suppose a researcher is interested in the effect of class attendance
More informationMultinomial Logit Models - Overview Richard Williams, University of Notre Dame, https://www3.nd.edu/~rwilliam/ Last revised February 13, 2017
Multinomial Logit Models - Overview Richard Williams, University of Notre Dame, https://www3.nd.edu/~rwilliam/ Last revised February 13, 2017 This is adapted heavily from Menard s Applied Logistic Regression
More informationPOLYTECHNIC OF NAMIBIA SCHOOL OF MANAGEMENT SCIENCES DEPARTMENT OF ACCOUNTING, ECONOMICS AND FINANCE ECONOMETRICS. Mr.
POLYTECHNIC OF NAMIBIA SCHOOL OF MANAGEMENT SCIENCES DEPARTMENT OF ACCOUNTING, ECONOMICS AND FINANCE COURSE: COURSE CODE: ECONOMETRICS ECM 312S DATE: NOVEMBER 2014 MARKS: 100 TIME: 3 HOURS NOVEMBER EXAMINATION:
More informationAssessing Model Stability Using Recursive Estimation and Recursive Residuals
Assessing Model Stability Using Recursive Estimation and Recursive Residuals Our forecasting procedure cannot be expected to produce good forecasts if the forecasting model that we constructed was stable
More information1 Inferential Statistic
1 Inferential Statistic Population versus Sample, parameter versus statistic A population is the set of all individuals the researcher intends to learn about. A sample is a subset of the population and
More informationEcon Spring 2016 Section 12
Econ 140 - Spring 2016 Section 12 GSI: Fenella Carpena April 28, 2016 1 Experiments and Quasi-Experiments Exercise 1.0. Consider the STAR Experiment discussed in lecture where students were randomly assigned
More informationCameron ECON 132 (Health Economics): FIRST MIDTERM EXAM (A) Fall 17
Cameron ECON 132 (Health Economics): FIRST MIDTERM EXAM (A) Fall 17 Answer all questions in the space provided on the exam. Total of 36 points (and worth 22.5% of final grade). Read each question carefully,
More informationProblem Set 9 Heteroskedasticty Answers
Problem Set 9 Heteroskedasticty Answers /* INVESTIGATION OF HETEROSKEDASTICITY */ First graph data. u hetdat2. gra manuf gdp, s([country].) xlab ylab 300000 manufacturing output (US$ miilio 200000 100000
More informationThe Two-Sample Independent Sample t Test
Department of Psychology and Human Development Vanderbilt University 1 Introduction 2 3 The General Formula The Equal-n Formula 4 5 6 Independence Normality Homogeneity of Variances 7 Non-Normality Unequal
More informationUniversity of Nottingham
University of Nottingham BUSINESS SCHOOL A LEVEL 2 MODULE, SPRING SEMESTER 2011 2012 INTRODUCTORY ECONOMETRICS Time allowed TWO hours Candidates must NOT start writing their answers until told to do so
More informationMixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
Chapter 375 Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization) Introduction This procedure calculates power and sample size for a three-level
More informationTwo-Sample T-Test for Superiority by a Margin
Chapter 219 Two-Sample T-Test for Superiority by a Margin Introduction This procedure provides reports for making inference about the superiority of a treatment mean compared to a control mean from data
More informationEstimation of a credit scoring model for lenders company
Estimation of a credit scoring model for lenders company Felipe Alonso Arias-Arbeláez Juan Sebastián Bravo-Valbuena Francisco Iván Zuluaga-Díaz November 22, 2015 Abstract Historically it has seen that
More informationCredit Scores and Credit Market Outcomes: Evidence from the SSBF and KFS
Credit Scores and Credit Market Outcomes: Evidence from the SSBF and KFS Rebel A. Cole DePaul University 1 E Jackson Blvd. Suite 5531 Chicago, IL 60602 USA Ph: 1-312-362-6887 Email: rcole@depaul.edu Abstract:
More informationAnalyzing the Determinants of Project Success: A Probit Regression Approach
2016 Annual Evaluation Review, Linked Document D 1 Analyzing the Determinants of Project Success: A Probit Regression Approach 1. This regression analysis aims to ascertain the factors that determine development
More informationBooth School of Business, University of Chicago Business 41202, Spring Quarter 2014, Mr. Ruey S. Tsay. Solutions to Midterm
Booth School of Business, University of Chicago Business 41202, Spring Quarter 2014, Mr. Ruey S. Tsay Solutions to Midterm Problem A: (30 pts) Answer briefly the following questions. Each question has
More informationFIGURE I.1 / Per Capita Gross Domestic Product and Unemployment Rates. Year
FIGURE I.1 / Per Capita Gross Domestic Product and Unemployment Rates 40,000 12 Real GDP per Capita (Chained 2000 Dollars) 35,000 30,000 25,000 20,000 15,000 10,000 5,000 Real GDP per Capita Unemployment
More informationThis homework assignment uses the material on pages ( A moving average ).
Module 2: Time series concepts HW Homework assignment: equally weighted moving average This homework assignment uses the material on pages 14-15 ( A moving average ). 2 Let Y t = 1/5 ( t + t-1 + t-2 +
More informationNCC5010: Data Analytics and Modeling Spring 2015 Exemption Exam
NCC5010: Data Analytics and Modeling Spring 2015 Exemption Exam Do not look at other pages until instructed to do so. The time limit is two hours. This exam consists of 6 problems. Do all of your work
More informationFinal Exam. Tuesday, December hour, 30 minutes
San Francisco State University Michael Bar ECON 0 Fall 04 Final Exam Tuesday, December 6 hour, 30 minutes Name: Student ID: Instructions. This is closed book, closed notes exam.. No calculators or electronic
More informationTwo-Sample T-Test for Non-Inferiority
Chapter 198 Two-Sample T-Test for Non-Inferiority Introduction This procedure provides reports for making inference about the non-inferiority of a treatment mean compared to a control mean from data taken
More informationAmath 546/Econ 589 Univariate GARCH Models: Advanced Topics
Amath 546/Econ 589 Univariate GARCH Models: Advanced Topics Eric Zivot April 29, 2013 Lecture Outline The Leverage Effect Asymmetric GARCH Models Forecasts from Asymmetric GARCH Models GARCH Models with
More informationWhy Pay for Paper? An Analysis of the Internet's Effect on Print Newspaper Subscriber Retention
Clemson University TigerPrints All Theses Theses 5-2011 Why Pay for Paper? An Analysis of the Internet's Effect on Print Newspaper Subscriber Retention Kevin Payne Clemson University, kmpayne@clemson.edu
More informationWRITTEN PRELIMINARY Ph.D. EXAMINATION. Department of Applied Economics. January 28, Consumer Behavior and Household Economics.
WRITTEN PRELIMINARY Ph.D. EXAMINATION Department of Applied Economics January 28, 2016 Consumer Behavior and Household Economics Instructions Identify yourself by your code letter, not your name, on each
More informationFINANCIAL ECONOMETRICS AND EMPIRICAL FINANCE MODULE 2
MSc. Finance/CLEFIN 2017/2018 Edition FINANCIAL ECONOMETRICS AND EMPIRICAL FINANCE MODULE 2 Midterm Exam Solutions June 2018 Time Allowed: 1 hour and 15 minutes Please answer all the questions by writing
More informationPhD Qualifier Examination
PhD Qualifier Examination Department of Agricultural Economics May 29, 2015 Instructions This exam consists of six questions. You must answer all questions. If you need an assumption to complete a question,
More informationPhd Program in Transportation. Transport Demand Modeling. Session 11
Phd Program in Transportation Transport Demand Modeling João de Abreu e Silva Session 11 Binary and Ordered Choice Models Phd in Transportation / Transport Demand Modelling 1/26 Heterocedasticity Homoscedasticity
More informationVariance clustering. Two motivations, volatility clustering, and implied volatility
Variance modelling The simplest assumption for time series is that variance is constant. Unfortunately that assumption is often violated in actual data. In this lecture we look at the implications of time
More informationInternet Appendix: High Frequency Trading and Extreme Price Movements
Internet Appendix: High Frequency Trading and Extreme Price Movements This appendix includes two parts. First, it reports the results from the sample of EPMs defined as the 99.9 th percentile of raw returns.
More informationThe Extended Exogenous Maturity Vintage Model Across the Consumer Credit Lifecycle
The Extended Exogenous Maturity Vintage Model Across the Consumer Credit Lifecycle Malwandla, M. C. 1,2 Rajaratnam, K. 3 1 Clark, A. E. 1 1. Department of Statistical Sciences, University of Cape Town,
More informationIntroduction to Population Modeling
Introduction to Population Modeling In addition to estimating the size of a population, it is often beneficial to estimate how the population size changes over time. Ecologists often uses models to create
More informationQuantitative Techniques Term 2
Quantitative Techniques Term 2 Laboratory 7 2 March 2006 Overview The objective of this lab is to: Estimate a cost function for a panel of firms; Calculate returns to scale; Introduce the command cluster
More informationPolicy Analysis Field Examination Questions Spring 2014
Question 1: Policy Analysis Field Examination Questions Spring 2014 Answer four of the following six questions As the economic analyst for APEC City, you need to calculate the benefits to city residents
More informationGGraph. Males Only. Premium. Experience. GGraph. Gender. 1 0: R 2 Linear = : R 2 Linear = Page 1
GGraph 9 Gender : R Linear =.43 : R Linear =.769 8 7 6 5 4 3 5 5 Males Only GGraph Page R Linear =.43 R Loess 9 8 7 6 5 4 5 5 Explore Case Processing Summary Cases Valid Missing Total N Percent N Percent
More informationUniversity of New South Wales Semester 1, Economics 4201 and Homework #2 Due on Tuesday 3/29 (20% penalty per day late)
University of New South Wales Semester 1, 2011 School of Economics James Morley 1. Autoregressive Processes (15 points) Economics 4201 and 6203 Homework #2 Due on Tuesday 3/29 (20 penalty per day late)
More information1) The Effect of Recent Tax Changes on Taxable Income
1) The Effect of Recent Tax Changes on Taxable Income In the most recent issue of the Journal of Policy Analysis and Management, Bradley Heim published a paper called The Effect of Recent Tax Changes on
More informationEconometric Methods for Valuation Analysis
Econometric Methods for Valuation Analysis Margarita Genius Dept of Economics M. Genius (Univ. of Crete) Econometric Methods for Valuation Analysis Cagliari, 2017 1 / 25 Outline We will consider econometric
More informationHow Does Education Affect Mental Well-Being and Job Satisfaction?
A summary of a paper presented to a National Institute of Economic and Social Research conference, at the University of Birmingham, on Thursday June 6 How Does Education Affect Mental Well-Being and Job
More information1/2 2. Mean & variance. Mean & standard deviation
Question # 1 of 10 ( Start time: 09:46:03 PM ) Total Marks: 1 The probability distribution of X is given below. x: 0 1 2 3 4 p(x): 0.73? 0.06 0.04 0.01 What is the value of missing probability? 0.54 0.16
More informationModelling Household Consumption: a long-term forecasting approach. Rossella Bardazzi University of Florence
Modelling Household Consumption: a long-term forecasting approach Rossella Bardazzi University of Florence A Multi-Sectoral Approach to model Household Consumption Cross-section Analysis (Income and Demographic
More informationSan Francisco State University ECON 560 Summer Problem set 1
San Francisco State University Michael Bar ECON 60 Summer 2018 Due Wednesday, July 11 Problem set 1 Name Assignment Rules 1. Homework assignments must be typed. For instructions on how to type equations
More informationLecture 2 Describing Data
Lecture 2 Describing Data Thais Paiva STA 111 - Summer 2013 Term II July 2, 2013 Lecture Plan 1 Types of data 2 Describing the data with plots 3 Summary statistics for central tendency and spread 4 Histograms
More informationA1. Relating Level and Slope to Expected Inflation and Output Dynamics
Appendix 1 A1. Relating Level and Slope to Expected Inflation and Output Dynamics This section provides a simple illustrative example to show how the level and slope factors incorporate expectations regarding
More informationStat 101 Exam 1 - Embers Important Formulas and Concepts 1
1 Chapter 1 1.1 Definitions Stat 101 Exam 1 - Embers Important Formulas and Concepts 1 1. Data Any collection of numbers, characters, images, or other items that provide information about something. 2.
More informationFixed Effects Maximum Likelihood Estimation of a Flexibly Parametric Proportional Hazard Model with an Application to Job Exits
Fixed Effects Maximum Likelihood Estimation of a Flexibly Parametric Proportional Hazard Model with an Application to Job Exits Published in Economic Letters 2012 Audrey Light* Department of Economics
More informationThe Role of Exponential-Growth Bias and Present Bias in Retirment Saving Decisions
The Role of Exponential-Growth Bias and Present Bias in Retirment Saving Decisions Gopi Shah Goda Stanford University & NBER Matthew Levy London School of Economics Colleen Flaherty Manchester University
More informationTests for the Matched-Pair Difference of Two Event Rates in a Cluster- Randomized Design
Chapter 487 Tests for the Matched-Pair Difference of Two Event Rates in a Cluster- Randomized Design Introduction Cluster-randomized designs are those in which whole clusters of subjects (classes, hospitals,
More information6 Multiple Regression
More than one X variable. 6 Multiple Regression Why? Might be interested in more than one marginal effect Omitted Variable Bias (OVB) 6.1 and 6.2 House prices and OVB Should I build a fireplace? The following
More informationOne Proportion Superiority by a Margin Tests
Chapter 512 One Proportion Superiority by a Margin Tests Introduction This procedure computes confidence limits and superiority by a margin hypothesis tests for a single proportion. For example, you might
More informationSTAT 1220 FALL 2010 Common Final Exam December 10, 2010
STAT 1220 FALL 2010 Common Final Exam December 10, 2010 PLEASE PRINT THE FOLLOWING INFORMATION: Name: Instructor: Student ID #: Section/Time: THIS EXAM HAS TWO PARTS. PART I. Part I consists of 30 multiple
More informationDummy variables 9/22/2015. Are wages different across union/nonunion jobs. Treatment Control Y X X i identifies treatment
Dummy variables Treatment 22 1 1 Control 3 2 Y Y1 0 1 2 Y X X i identifies treatment 1 1 1 1 1 1 0 0 0 X i =1 if in treatment group X i =0 if in control H o : u n =u u Are wages different across union/nonunion
More informationModeling wages of females in the UK
International Journal of Business and Social Science Vol. 2 No. 11 [Special Issue - June 2011] Modeling wages of females in the UK Saadia Irfan NUST Business School National University of Sciences and
More informationChapter 4 Level of Volatility in the Indian Stock Market
Chapter 4 Level of Volatility in the Indian Stock Market Measurement of volatility is an important issue in financial econometrics. The main reason for the prominent role that volatility plays in financial
More informationσ 2 : ESTIMATES, CONFIDENCE INTERVALS, AND TESTS Business Statistics
σ : ESTIMATES, CONFIDENCE INTERVALS, AND TESTS Business Statistics CONTENTS Estimating other parameters besides μ Estimating variance Confidence intervals for σ Hypothesis tests for σ Estimating standard
More informationAN EMPIRICAL ANALYSIS OF GENDER WAGE DIFFERENTIALS IN URBAN CHINA
Kobe University Economic Review 54 (2008) 25 AN EMPIRICAL ANALYSIS OF GENDER WAGE DIFFERENTIALS IN URBAN CHINA By GUIFU CHEN AND SHIGEYUKI HAMORI On the basis of the Oaxaca and Reimers methods (Oaxaca,
More informationObesity, Disability, and Movement onto the DI Rolls
Obesity, Disability, and Movement onto the DI Rolls John Cawley Cornell University Richard V. Burkhauser Cornell University Prepared for the Sixth Annual Conference of Retirement Research Consortium The
More informationAppendix B: Methodology and Finding of Statistical and Econometric Analysis of Enterprise Survey and Portfolio Data
Appendix B: Methodology and Finding of Statistical and Econometric Analysis of Enterprise Survey and Portfolio Data Part 1: SME Constraints, Financial Access, and Employment Growth Evidence from World
More informationTests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
Chapter 439 Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design Introduction Cluster-randomized designs are those in which whole clusters of subjects (classes, hospitals,
More information