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    Quiz 3 LBYACC2

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    on duty (sales_per) has a significant impact on the number of cars sold (num_cars). The dataset is assumed to be in the file name Problem4.csv. It is assumed to be located in the working directory C:\Users\LBYACC2\Problem4. REQUIREMENT: Provide ALL STATA commands necessary to input the data and to create the regression model as well as all necessary tests of robustness for the model. Be sure to store the results in a log file with the following file name “Name_Quiz3_Problem4.” 5. Use the following

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    Tero Bau

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    Homework-3 solution Research Methodology 1.The following table gives data on imports‚ GDP and the Consumer Price Index(CPI) for the United states over the period 1970-1998. You are asked to consider the following model: Ln(Imports)t=[pic] a. Estimate the parameters of this model using the data given in the table. b. Do you suspect that there is multicollinearity in the data? Table: US Imports‚ GDP and CPI‚ 1970-1998 |Observation |CPI |GDP

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    1978‚ "A Theory of Extramarital Affairs." Journal of Political Economy 86‚ no.1: p. 45-61 Wooldridge‚ Jeffrey M‚ 2009‚ Introductory Econometrics: A Modern Approach‚ 4th Edition‚ South-Western Cengage Learning‚ United States of America Stata output: White test: F = 29.08 (p-val = 0.0000)‚ LM = 53.27 (p-val = 0.0000).

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    Linear Probability Model

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    The linear probability model‚ ctd. When Y is binary‚ the linear regression model Yi = β0 + β1Xi + ui is called the linear probability model. • The predicted value is a probability: • E(Y|X=x) = Pr(Y=1|X=x) = prob. that Y = 1 given x • Yˆ = the predicted probability that Yi = 1‚ given X • β1 = change in probability that Y = 1 for a given ∆x: Pr(Y = 1 | X = x + ∆x ) − Pr(Y = 1 | X = x ) β1 = ∆x 5 Example: linear probability model‚ HMDA data Mortgage denial v. ratio of debt payments to income (P/I

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    Assignment 231541251

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    Assignment 2 This assignment is based on the data set in “CHARITY.RAW”‚ see also tutorial exercises C2.7 and C7.14. The definitions of variables are in the file “CHARITY.DES”. To examine what influence individuals’ decisions on donations‚ the linear regression model respond = β0 + β1 resplast + β2 avggift + β3 propresp + β4 mailsyear +u is used. For hypothesis-testing questions‚ please always present hypotheses‚ test statistic and its distribution under the null‚ decision rule and conclusion

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    Econ2206 Assignment

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    ECON2206/3290  Introductory Econometrics  Assignment 1  Due Week 5   [Total 10 points including 1 point for presentation]   To investigate whether fast‐food restaurants charge higher prices in areas with a larger  concentration of blacks‚ you obtain ZIP‐level data on prices for various items at fast‐food  restaurants‚ along with characteristics of the zip code population‚ in two US cities New Jersey  and Pennsylvania.  The data set is in DISCRIM.RAW which can be found on Blackboard in the  course website

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    Table of Contents Contents PROJECT: Determinants of Extramarital Affairs Introduction Wiederman (1997) emphasises the fact that 22.7% of married men and 11.6% of women have had extramarital sex during their marriage. Thompson (1993) identifies three determinants of extramarital affairs‚ being; gender‚ race and age. It is believed that males‚ African Americans and newly married couples‚ are most prone to extramarital affairs. Furthermore‚ Prins et.al (1999)‚ suggests that among men

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    Research

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    ECON2206‚ Introductory Econometrics‚ 2013 S1 Course Project 1. This project has a value of 15% of the total assessment. In addition‚ there is a teamwork component worth 5%. The teamwork mark will be based on the online self and peer assessment (see Teamwork Assessment section below). 3. Each group must submit one hard copy of the project and one online (soft) copy. 2. This project must be completed in a group of 3 or 4 students. The members of a group come from the same tutorial class. Groups

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    ECON 300 HW9

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    Weekly Homework 9: Detection of Heteroskedasticity 1. Heteroskedasticity (1 point each) 1) Carefully explain the difference between pure and impure heteroskedasticity and their consequences in OLS. Answer: -Pure heteroskedasticity is caused by the error term of the correctly specified equation. Impure heteroskedasticity is caused by a specification error such as an omitted variable. -Pure heteroskedasticity does not cause bias in the coefficient estimates. However‚ it typically causes

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    INDUSTRIAL ATTACHMENT REPORT

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    KIGALI INSTITUTE OF SCIENCE AND TECHNOLOGY Avenue de l’armée‚ P.O. Box. 3900 Kigali/Rwanda Tel: +250 576996/574698‚ Fax: +250 571925/571924 Website: www.kist.ac.rw FACULTY OF APPLIED SCIENCES DEPARTMENT OF MATHEMATICS STATISTICS OPTION INDUSTRIAL ATTACHMENT REPORT DONE IN MINISTRY OF PUBLIC SERVICE AND LABOUR Done by: Pacifique ICYINGENEYE (GS 20080096) Supervised by: Consolate MUKESHIMANA Academic Year: 2011 TOWARDS A BRIGHTER FUTURE Industrial Attachment Report DECLARATION I‚ Pacifique

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