Introduction to econometrics / Christopher Dougherty.
By: Dougherty, Christopher.
Material type: BookPublisher: New York : Oxford University Press, 1992Description: xii, 399 p. : ill. ; 25 cm. + hbk.ISBN: 0195043464.Subject(s): EconometricsDDC classification: 330.015195Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds |
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General Lending | MTU Bishopstown Library Lending | 330.015195 (Browse shelf(Opens below)) | 1 | Available | 00018025 |
Enhanced descriptions from Syndetics:
A basic introduction written in non-technical language, this remarkable text keeps mathematical demands to a minimum so that students can spend less time on technicalities and more on understanding basic concepts. With many exercises in the text, a floppy disk containing data sets on expenditure and price for different commodities, an unusually detailed teacher's manual with additional exercises and masters for overhead transparencies, and spectacular video graphic sequences, this uniquely rich introductory text will transform the teaching of the subject.
Bibliography: (pages 386-389) and indexes.
Review: Random variables and sampling theory -- Covariance, variance and correlation -- I: Basic theory -- Simple regression analysis -- Properties of the regression coefficients and hypothesis testing -- Transformations of variables -- Multiple regression analysis -- II: Problems and completion -- Specification of regression variables: A preliminary skirmish -- Heteroscedasticity and autocorrelated disturbance terms -- Stochastic regressors and measurement errors -- III: Further developments -- Dummy variables -- Modeling dynamic processes -- Simultaneous equations estimation -- What next?
Table of contents provided by Syndetics
- 1 Covariance, Variance, and Correlation
- 2 Simple Regression Analysis
- 3 Properties of the Regression Coefficients
- 4 Multiple Regression Analysis
- 5 Transformation of Variables
- 6 Dummy Variables
- 7 Specification of Regression Variables
- 8 Heterodasticity
- 9 Stochastic Regressors and Measurement Errors
- 10 Simultaneous Equations Estimation
- 11 Binary Choice Models and Maximum Likelihood Estimation
- 12 Models Using Time Series Data
- 13 Autocorrelation
- 14 Introduction to Nonstationary Processes