Econometrics and Data Analysis for Developing Countries [NOOK Book]

Overview

Getting accurate data on less developed countries has created great problems for studying these areas. Yet until recently students of development economics have relied on standard econometrics texts, which assume a Western context. Econometrics and Data Analysis for Developing Countries solves this problem. It will be essential reading for all advanced students of development economics.
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Econometrics and Data Analysis for Developing Countries

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Overview

Getting accurate data on less developed countries has created great problems for studying these areas. Yet until recently students of development economics have relied on standard econometrics texts, which assume a Western context. Econometrics and Data Analysis for Developing Countries solves this problem. It will be essential reading for all advanced students of development economics.
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Editorial Reviews

Booknews
A textbook on data analysis and econometrics as research tools in the analysis of development issues. Covers the foundations of data analysis, regression and data analysis, analyzing cross-section data, regression with time-series data, and simultaneous equation models. The data diskette that accompanies the book contains data sets relating to problems of developing countries in LOTUS and ASCII formats. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

  • ISBN-13: 9781136144684
  • Publisher: Taylor & Francis
  • Publication date: 9/13/2013
  • Series: Priorities for Development Economics
  • Sold by: Barnes & Noble
  • Format: eBook
  • Pages: 520
  • File size: 12 MB
  • Note: This product may take a few minutes to download.

Table of Contents

List of figures
List of tables
List of boxes
Preface
Introduction 1
Pt. I Foundations of data analysis 21
1 Model specification and applied research 23
2 Modelling an average 44
3 Outliers, skewness and data transformations 75
Pt. II Regression and data analysis 109
4 Data analysis and simple regression 111
5 Partial regression: interpreting multiple regression coefficients 163
6 Model selection and misspecification in multiple regression 208
Pt. III Analysing cross-section data 249
7 Dealing with heteroscedasticity 251
8 Categories, counts and measurements 279
9 Logit transformation, modelling and regression 302
Pt. IV Regression with time-series data 333
10 Trends, spurious regressions and transformations to stationarity 335
11 Misspecification and autocorrelation 366
12 Cointegration and the error correction model 393
Pt. V Simultaneous equation models 413
13 Misspecification bias from single equation estimation 415
14 Estimating simultaneous equation models 437
App. A The data sets used in this book 455
App. B Statistical tables 463
References 481
Index 485
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