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Unformatted text preview: Econ 1002: Applied Economics Matthew Wakefield University College London and Institute for Fiscal Studies m.wakefield (at) ucl.ac.uk Jan  Mar 2009 Oﬃce Hour: Tues 33.55, Room 209, Drayton www.ucl.ac.uk/economics/degreecourses/undergraduate/courselist/courses/econ1002 coursepage or link from: www.ucl.ac.uk/economics/degreecourses/undergraduate/courselist/courses/appliedeconomics Thanks to the previous two lecturers, Professors Ian Preston and James Banks, for much of the content of this course. Econ 1002 Matthew Wakefield Outline The Exam Ordinary Least Squares Inference Functional Form Assumptions Wage Equations Consumer Demand Expenditure Shares Specification Doublelog specification Quality as omitted variable Labour Supply Consumption / Saving Differencein differences Outline Revision 1 The Exam 2 Ordinary Least Squares Inference Functional Form Assumptions 3 Wage Equations 4 Consumer Demand Expenditure Shares Specification Doublelog specification Quality as omitted variable 5 Labour Supply 6 Consumption / Saving 7 Differenceindifferences Matthew Wakefield (UCL/IFS) Econ 1002 Jan  Mar 2009 2 / 47 Econ 1002 Matthew Wakefield Outline The Exam Ordinary Least Squares Inference Functional Form Assumptions Wage Equations Consumer Demand Expenditure Shares Specification Doublelog specification Quality as omitted variable Labour Supply Consumption / Saving Differencein differences The Exam Course presented OLS regression tool, and then used it in 5 applications: Wage Equations Consumer Demand Labour Supply Consumption/Saving Differenceindifferences policy evaluation Twohour exam has two parts Part A: One compulsory question Part B: Choose 2 from 5 questions Each question based on one of the applications Matthew Wakefield (UCL/IFS) Econ 1002 Jan  Mar 2009 3 / 47 Econ 1002 Matthew Wakefield Outline The Exam Ordinary Least Squares Inference Functional Form Assumptions Wage Equations Consumer Demand Expenditure Shares Specification Doublelog specification Quality as omitted variable Labour Supply Consumption / Saving Differencein differences Ordinary Least Squares Basic Regression OLS regression estimates relationships of the form: y i = α + β x 1 i + γ x 2 i + ε i May have more only one independent ( x ) variable (aka regressors), or more than 2 The LHS variable y is the dependent variable ε is the error term α is the “intercept” or “constant”, and β and γ are coeﬃcients Matthew Wakefield (UCL/IFS) Econ 1002 Jan  Mar 2009 4 / 47 Econ 1002 Matthew Wakefield Outline The Exam Ordinary Least Squares Inference Functional Form Assumptions Wage Equations Consumer Demand Expenditure Shares Specification Doublelog specification Quality as omitted variable Labour Supply Consumption / Saving Differencein differences Ordinary Least Squares Example ln w i = 0 . 792 + 0 . 069 edu i + 0 . 009 jbten i + e i ln w is log wage edu is age finished formal schooling jbten is job tenure (years in current job) Interpretation Can use regression to predict log wage...
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This note was uploaded on 03/03/2010 for the course ECON 1002 taught by Professor Matthewwakefield during the Spring '09 term at UCL.
 Spring '09
 matthewwakefield
 Economics

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