Introduction to econometrics II eco 356 faculty of social sciences course guide course Developers: Dr. Adesina-Uthman

INTRODUCTION TO ECONOMETRICS II

ECO 306

NOUN
6 variance, and correlationaredemystified for proper understanding. By the end of this module, you would have been able to understand the basics of regression analysis. Module 2 (units 4-9) explains single-equation regression models. It shows how a hypothetical linear relationship between two variables can be quantified using appropriate data. The principle of least squares regression analysis explained, and expressions for the coefficients are derived.Multicollinearityand multiple regression analysis looked at in units 6. Transformations of Variablesdiscussed in unit 7 while dummy variables as well preliminary skirmish of the specification of regression variables are the topics in units 8 and 9. An exploration of what happens when there is a violation of one of the classical assumptions equal variances (homoscedastic) is carried out in module 3. It demonstrates how properties of estimators of the regression coefficients depend on the properties of the disturbance term in the regression model. Also, in this module, we shall look at some of the problems that arise when violations of the Gauss–Markov conditions the assumptions relating to the disturbance term, are not satisfied. Basic understanding of heteroscedasticity (unequal-variances) will gain thoroughexplanation. The module 4 (unit 13-15) covers an understanding of the basics of econometric modelling. It goes further to give some details on stochastic regression and measurement errors, autocorrelation, econometric modelling and models using time series data. More detail description of an introduction to Consequences of Measurement Errors.Intercorrelation among the Explanatory Variables and Measurement Errors in the Dependent Variable are brought to the students knowledge here. Also, possible causes of Autocorrelation and Detection of First-Order
Autocorrelation using the Durbin–Watson Test are presented in units and 15 of the same module 4. While module 5 with units 16 and provide you with a thorough understanding of the basic rudiments of Simultaneous Equation, Binary Choice, and Maximum Likelihood Estimation. Respectively, study unit will take at least two hours which include anintroduction, objective, main content, examples, In-Text Questions (ITQ) and their solutions, self- assessment exercise, conclusion, summary, and reference. Additional areas border on the Tutor-Marked Assessment (TMA) questions. Some of the ITQ and self-assessment exercise will require you free-associating and solve with some of your colleagues. You are advised to do so to grasp and get familiar with how significant econometrics is in being concerned with measurement and also as a method of causal inference application to economics. There are also econometrics materials, textbooks under the reference and other (online and offline) resources for further studies. These are intended to give you extra facts whenever you allow yourself of such prospect. You are required to study the materials practise the ITQ, self-assessment exercise and TMA questions for better and thorough understanding of the course. In doing these, the identified learning objectives of the course would have been attained. For further reading in this course, the following reference texts and materials are suggested

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