2 Introduction & Outline Introduce meLectures and LabsCourse materialCourse outline and objectives
3 Me Vincent Hogan firstname.lastname@example.org (716) 8300 Room D205, Newman BuildingOffice Hours: Mon 10pm-noon or by appointment
4 Lectures and Labs Lectures: Tues & Thurs 10-12 Theatre Q. Labs Several locations and timesTues D114 & D115 HEAWed G5 DAEThurs G5 & G6 DAE Labs start in week 2
5 Role of Labs Labs are NOT tutorials in the traditional sense. The scheduled labs are merely times where the computer labs are reserved for your use exclusivelyAND where there will be some support for using the course software provided by Phd StudentsYou are not obliged to attend labs but Econometrics is a practical subject so you need to practice either in the supervised labs or on your own
6 Course SoftwareEconometrics is a practical subject that involves the analysis of real world dataWe will use software called stata which can be accessed via NAL on the ucd networkYou cannot access it at homeThere is freeware at gretl.com which will do most of the analysis we need on this courseNeither I nor UCD will offer support for gretl
7 Using Stata Vital to get comfortable with basics in stata Manuals on the course websiteLots of online help for stataPractice its use in the labs where the grad students can help youStata will be needed for assignmentsUnderstanding the output will be key for class and the final exam
8 Course WebsiteThe course material will be available atMaterial will be posted in blog formCourse notesExample dataStata comand filesSoftware manualsSample examsThe blackboard site for this course contains the lecture material from previous years.Not of much relevance
9 Course MaterialYou are strongly advised to bring a printed copy of these notes to the lecture to enable you to follow the material. These notes are not designed to be sufficient on their own.The recommended text book isIntroductory Econometrics by Jeffrey Wooldridge Should be in the campus bookshopSecond hand copies should be fine
10 Alternative TextsAll of these texts should be fine and maybe available second hand“Basic Econometrics”, Damodar Gujurati, McGraw-HillIntroduction to Econometrics” by James Stock and Mark Watson,Modern Econometrics: an introduction”, R L Thomas, Addison-Wesley,“Introduction to Econometrics”, G.S Maddala, Prentice Hall,“A Guide to Econometrics”, Peter Kennedy, Blackwell,“Learning and Practising Econometrics”, Griffith Hill and Judge, John Wiley.
11 Assessment Assessment will be based on 2 pieces of assessed work each worth 10% of the course gradeAn end of year exam worth 80%The projects will involve applying the methods of class to real world data which I will provide.due at end of week 8 and week 10 In addition there will be an assignment every week for practice i.e. not for gradeThe final exam will be slightly more theoretical but will still have a large practical component
12 Introduction to Econometrics What is econometrics?Learning objectivesMethod of teaching.
13 What is EconometricsIn a nutshell Econometrics is statistics applied to economic relationshipsquantify economic relationshipsA simple example:Keynesian Consumption function income today, consumption today or savings todayC=a+b*Y Another Example Return to Education:What is in income from holding a degree
14 Demand for fuel: response of consumer demand to change in excise tax? How much matters to the government
15 Key Issue: Managing Uncertainty Economic Theory defines a relationship between variablesAgents require the size of the effects e.g. MPC, elasticity of demands.Key issue:Whole population never observed only sampleCreates uncertaintyManaging uncertainty is the key point of statistics
16 Steps in the Analysis Economic Model: state theory or hypothesis e.g. Keynesian modelSpecify a mathematical model: single equation or several.e.g. C=a+b*YNote: 1 & 2 from your other coursesSpecify statistical model: how deal with “errors” caused by samplingThis is what makes statisticsGet data: I provide for this courseBut for your own project you will need to get data
17 Steps in the AnalysisEstimate the parameters of the model that best fit to the data. e.g. what “b” gives the best fitReject the Model?Test hypotheses regarding the parameters. e.g. is “b” = 0.8?Not trivial because of samplePrediction: “What if”implicit in everything
18 Learning ObjectivesUnderstand how to perform linear regression analysis of economic data to derives estimates of parameters defined by economic theoryUnderstand how to perform hypothesis tests on the regression results in order to reject (or not) alternative economic theoriesUse the results of the analyses to describe the effects of alternative economic policies and actions
19 Teaching This Course Practical approach Each section will be motivated by a case studyWe will analyse real data in classAddress theoretical issues as they arise in each case studyApply to some other casesFurther applications as homeworkYou should repeat the data analysis in your own time and do the assignments for practiceRemember only 2 are for grade
20 Teaching This CourseFailure to actually use data yourself will inhibit your learningRemember 40% of final exam is based on practical interpretation of stata output
21 Cases & Topics Are women paid less than men? What is the MPC? Intro to statisticsWhat is the MPC?Simple regressionHow low will house prices fall?Multivariate regressionBig is beautiful: Asymptotic theoryMid way review & several examples
22 Cases & Topics What is the return to education? Omitted variables and errors in variablesWhat is the elasticity of demand for fuel?Functional formReview some of the cases for statistical problems of heteroscedasticity and autocorrelation
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