INSTRUCTOR: Ebenge Usip, Ph. D.
OFFICE: 307 DeBartolo Hall; Hrs. TTh. 12-2, Wed. 11-12; Phone: 742-1682; Email: firstname.lastname@example.org
TEXT: Introducing Econometrics --- by Wooldridge, 2E
RECOMMENDED SUPPLEMENTS -- Eviews 4.2 (student ed.).
-- Articles/Handouts (as deemed necessary).
-- WBI materials from my homepage: people.ysu.edu/~eeusip/
APPROXIMATE SCALE: Will be discussed in
Note: Last Day to withdraw with a "W" is March 24 (by NOON)
I. Introduction: The Nature of Econometrics and Economic Data -- chapter 1
II. Regression Analysis with Cross-sectional Data
● The Simple Regression Model -- chapter 2
● Multiple Regression Analysis: Estimation -- chapter 3
● Multiple Regression Analysis: Inference -- chapter 4
● Multiple Regression Analysis: OLS Asymptotic -- chapter 5
● Multiple Regression Analysis: Further Issues -- chapter 6
● Multiple Regression Analysis with Qualitative Information -- chapter 7
● Heteroskedasticity: chapter 8
III: Regression Analysis with Time-Series (TS) Data
● Basic Regression Analysis with TS Data -- chapter 10
● Further Issues in Using OLS with TS Data -- chapter 11
● Serial Correlation and Heteroskedasticity in TS Regression -- chapter 12
● Advanced Time Series Topics (Unit Roots, and Cointegration & Error Correction Models) -- ch. 18
IV: Other Topics
● More on Specification and Data Problems -- chapter 9
● Carrying out an Empirical Project -- chapter 19
● Prerequisites: Econ 6904.
● Class attendance is highly recommended. No make-up exams will be administered. Late homework will not be graded.
● It is the student's responsibility to be familiar with the assigned materials covered during lectures. Class Participation is encouraged and rewarded.
COURSE OVERVIEW: Goals and Objectives
Econometrics can be studied at the applied or theory level. This course will introduce you to econometric modeling and techniques with emphasis on applied econometrics. Econometric theory will also be examined albeit with minimal emphasis on proofs and derivations. There are two reasons for adopting this unified approach. First, this may be a terminal econometrics course for some of you who may not want to pursue a doctorate degree but wish to work as econometric practitioners with the MA diploma. The course will provide those students with a variety of applications so that they can carry out empirical work successfully in the real world. Second, for those wishing to pursue the Ph. D. degree, the course will provide them with the theoretical background necessary for taking advanced econometrics courses. To achieve a sufficient balance between applied econometrics and theoretical econometrics, the material will therefore be presented without resorting to matrix algebra, serious calculus, or mathematical statistics beyond the elementary material covered in appendices A, B and C of the textbook. As you will soon discover, econometrics is an amalgam of economic theory, mathematical economics, mathematical statistics, and proficiency in computer application. Although no advanced skill in mathematical statistics is required, you must however be prepared to adapt to new statistical concepts and symbols commonly used in discussing econometric theory.
Econometrics is a highly specialized field of economics that deals specifically with the formulation (model-building) and estimation of casual relationships among economic variables. Using applied econometrics, an economist can accomplish the following objectives: (1) perform structural analysis of the effects (marginal and partial) of exogenous factors on the variable whose behavior we seek to explain; (2) test hypotheses about new and existing economic theories; and (3) evaluate and implement policy in government and business using the estimated econometric model: Where application involves time series data, forecasting (the art of projecting the estimated economic relationships beyond the sample period) is often carried out for the purpose of planning and control. We will demonstrate how the tools of econometrics can be used to fulfill these objectives.
analysis is indeed the 'heart' of econometrics. Therefore, those
students who are already familiar with the regression technique (Econ 3780 &
3781 or equivalent) will find the material in the first two chapters reasonably
familiar. Your background in mathematical economics may vary from minimal (non
economic majors) to intermediate (Econ 6904) level. It thus recommended that you read appendix A concurrently.
Selected topics from Appendix B and C will be covered during lectures as needed.
I have also integrated Web-based instruction (WBI) via the Internet into this course (and other quantitative courses offered by the department). The WBI materials are in the form of tutorials, research guidelines, and active links to sources of economic data. Assignments and their solutions, and even this syllabus are available at my home page: The Center for Web-Based Instruction in Quantitative Economics. You can access the homepage via the following Internet address: www.cc.ysu.edu/~eeusip/. Explore the site carefully particularly the material under Research Guidelines. If you do not have access to the Internet, you can obtain a Unix account from the YSU computer center, Meshell Hall (fourth floor). With the account, you can set up your desktop or laptop computer to access the Web using the point-to-point protocol (PPP) connection via a modem. Details about the use of the Web will be provided in the class.
Implementing econometric procedures involve messy calculations. In today's computerized environment, the optimal strategy in teaching econometrics places less emphasis on hand/manual computation and more on concepts, model building, and derivation of the estimators and their desirable properties. For this reason, computer application is an integral part of this course. From Econs 3780 and 3781 some of you are already familiar with the Statistical Package for Social Science (SPSS) program (see my book " Learning Economics and Business Statistics with SPSS/win" 5ed.). Those from the mathematics department are perhaps familiar with the SAS for Windows (SAS/win) program. These programs are designed for general statistical analysis and may not be capable of implementing specialized econometric procedures without tedious programming. For instance, the SAS/ETS component can implement many of the techniques presented in the text but it is incapable of carrying out some econometric tests unless one writes a special program using the SAS programming syntax. Econometrics Views, or Eviews, is the most popular and powerful econometrics software program in the market today that is widely used in the industry and academia. Luckily, the student version (Eviews 4.1) is bundled with the text at a minimal cost. Like SPSS/win and SAS/win, Eviews runs under the Microsoft Windows OS but unlike these two programs all of the procedures in the text including econometric tests can be carried out without writing a single program code. The full version of the program is available at a reduced academic rate from the program developer, Quantitative Micro Software (QMS). If you are interested; I can help you buy a copy at the academic price.
This course may be scarier than it really is because of its quantitative nature. You will enjoy it however if you are willing to put in a minimum amount of effort. Most of the material is pretty straightforward and the text has done a fine job by adopting an approach that is both systematic and unified: Part 1 treats the analysis of cross-sectional data; part 2 focuses on the analysis of time-series data; and the discussion of advanced econometric topics is presented in part 3. Due to the cumulative nature of the material those who get too far behind will obviously find it difficult to catch up. Be sure to read the assigned chapter/material before coming to class; also, come to class regularly and stop by my office at the first sign of trouble.
wonderful and successful semester.
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