Introductory Econometrics ECON2206 Slides01 Lecturer: Minxian Yang ie_Slides01 my‚ School of Economics‚ UNSW 1 About the Course • Staff There will be no lecture in Week 7. – Lecturer: Minxian Yang – Tutors: see Tutorial Contacts • Required textbook – Wooldridge‚ J.M. (2009)‚ Introductory Econometrics: A Modern Approach‚ 4th Edition‚ South-Western • Assessment – Two tutorial assignments (weeks 5 & 12): 20% – One course project (week 9): 20% – Final exam: 60%
Premium Econometrics Economics
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
Premium Standard deviation Statistics
ECON2206 Revision Notes W2 – SIMPLE REGRESSION MODEL MOTIVATION Much of applied econometric analysis are interested in “explaining y in terms of x” and confront three issues: 1) Since there is never an exact relationship between y and x‚ how do we account for the “other unobserved” variables? 2) What
Premium Normal distribution Estimator Scientific method
Project Description Suppose you are an intern in a consulting firm that provides businesses and government agencies with advices on various social and economic issues. You are involved in the project of advising a pharmaceutical company that is interested in penetrating the market of Luckland (a country endowed with rich natural resources). Your supervisor‚ the project manager‚ needs some vital facts about the adult population of Luckland and asks you to answer the following questions. (i) What
Premium Statistics Regression analysis Linear regression
ECON2206/ECON3290: Introductory Econometrics Session 1‚ 2009 Course Project Solution Guide Each question is worth 1 mark - and there are 20 questions in total. Answers should be clear and legible. Note Instruction (d) on the Questions: “when performing statistical tests‚ to always state the null and alternative hypotheses‚ the test statistic and it’s distribution under the null hypothesis‚ the level of significance and the conclusion of the test.” Marks are not awarded when this instruction is not
Premium Regression analysis Obstetrics
Assignment 1 To investigate the effects of the land size (lotsize)and house size (sqrft) on the house price (price) in a particular suburb‚ the following model log()=0+1log()+2log()+ is used. a) What is the meaning of 1in this model? b) Explain why you would (or would not) expect that 1>0. c) Explain the meaning of the zero-conditional-mean assumption for this model. d) Download the description file “hprice1.des” and data file “hprice1.raw” from the course website
Premium Standard deviation Arithmetic mean Sample size
THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF ECONOMICS ECON 2206 INTRODUCTORY ECONOMETRICS FINAL EXAMINATION SESSION 1‚ 2008 1. TIME ALLOWED - 2 Hours. 2. READING TIME = 10 Minutes 3. THIS EXAMATION PAPER HAS 9 PAGES 4. TOTAL NUMBER OF QUESTIONS - 6. 5. ANSWER ALL QUESTIONS. 6. ALL QUESTIONS ARE OF EQUAL VALUE 7. TOTAL MARKS AVAILABLE FOR THIS EXAMATION - 60. 8. THE MARKS AWARDED TO EACH PART OF A QUESTION ARE INDICATED. 9. CANDIDATES MAY BRING THEIR OWN CALCULATORS TO THE EXAM 10. STATISTICAL
Premium Statistical hypothesis testing
In the given function‚ respond is a binary function‚ which is dependant on the other explanatory variable which aligns with the requirement of the linear probability model (LPM). This is an extention to the zero conditional mean condition which assumes that E(ul(resplast)‚(avggift)‚(propresp)‚(mailsyear))=0 and hence allow for E(ylx) to omit the error term producing P(respond = 1lx)= β(0)+ β(1) resplast+ β(2)avggift+ β(3)propresp+ β(4)mailyear. This allows the interpretation of β(1) to be the degree
Premium Regression analysis Statistics Variance
eAUSTRALIAN SCHOOL OF BUSINESS SCHOOL OF ECONOMICS ECON2206 / ECON3290 (ARTS) Introductory Econometrics Course outline SESSION 2‚ 2011 Lecturer in Charge: Dr. Rachida Ouysse Room ASB441 Telephone: 9385 3321 Email: rouysse@unsw.edu.au Lectures: Fridays 9am-11am Venue: Law Theatre G04 Website: http://telt.unsw.edu.au/ TABLE OF CONTENTS 1 STAFF CONTACT DETAILS 1 1 1 1 1 1 2 2 2 2 3 3 3 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 7 9 9 9 10 10 10 12 13 13 13
Premium Economics Business Management
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
Premium Regression analysis Ceteris paribus Linear regression