Introduction to Applied Econometrics (with CD-ROM)

by Stewart, Kenneth

• ISBN13: 9780534369163
• ISBN10: 0534369162
• Edition: 1st
• Format: Hardcover
• Copyright: 2004-07-30
• Publisher: South-Western College Pub

Summary

You'll find the "econ" back in econometrics with INTRODUCTION TO APPLIED ECONOMETRICS and its accompanying CD.. You'll have the opportunity to replicate classic empirical findings using original data sets and will develop an understanding of the relevance of economic theory to empirical analysis. The author integrates classic empirical examples and applications and builds toward a self-contained four-chapter introduction to time series analysis. The CD includes data sets formatted for STATA, Eviews, Excel, Minitab, SAS and ASCII, as well as an appendix presenting multiple regression in matrix form and another on treating portfolio theory and the capital asset pricing model.

Table of Contents

Economic Data And Economic Models

Economic Data

Economic Models

Descriptive Statistics VersusStatistical Inference

Statistical Inference

Populations, Samples and Parameters

Statistics and SamplingDistributions

Properties of Estimators

Derivation of Estimators

Hypothesis Testing

Further Topics in Hypothesis Testing

Inferenceis Conditional on the Model

Econometrics and Statistics

StatisticalMethodology and the Philosophy of Science

Relationships between variables

Covariance and Correlation

Regression

Deviation Form Notation

Conclusions

Simple Regression

Model Specification

Least Squares Estimation

Sampling Properties of the Least Squares Estimators

The Sampling Distributions of ^a and ^B

Hypothesis Testing

Decomposition of Sample Variation

Presentation of Regression Results

Scaling and Units of Measure

Sampling, Numerical, and Invariance Properties

Application: Output and Production Costs

Supplementary Topics In Regression

Forecasting

RegressionThroughtheOrigin

WhenRegressionGoesWrong

Matters Of Functional Form

Loglinear Models

Log-Lin Models

Lin-Log Models

Reciprocal Models

Application: Engel Curves

Conclusions

Applications To Production Functions

General Features of ProductionFunctions

The Cobb-DouglasProduction Function

Technical Change

Testing MarginalProductivity Conditions

Conclusions

Multiple Regression

Model Specification

LeastSquares Estimation

Properties of Least SquaresEstimators

Hypothesis Testing

Decomposition of a Sample Variation

Application: Electricity Demand

Multicollinearity

Application:the Quadratic CostFunction

ModelMisspecification

Pre-TestEstimation

Application to Economic Growth

Introduction

The Textbook

Solow-Swan Model

Human Capital in the Solow-Swan Model

Summary: Mankiw, Romer, and Weil in a Nutshell

Conclusions

Dummy Variables And Restricted Coefficients

Dummy Variables

Restricted Coefficients

Identification

Applications To Cost Functions

The Cost Function

Deriving the Cost Function

Using the CostFunction

Returns to Scale in Electricity Generation

The TranslogCost Function

Consumer Demand

Further Reading

Model Discovery

Data Mining

SpecificationTesting

Non-nestedTesting

ModelChoice

Should theEquationBe Part of aSystem?

Conclusions

Nonlinear Regression

Introduction

Nonlinear LeastSquares

ComputerNumerics

Reparameterization

Identification

Sampling Properties of NLS Estimators

EstimatingSigma

Hypothesis Testing

Conclusions

Heteroskedasticity

Consequences for Ordinary Least Squares

Heteroskedasticity-RobustTests

WeightedLeastSquares

Testing forHeteroskedasticity

Time Series: Some Basic Concepts

Introduction

White Noise

Measuring Temporal Dependence

Stationarity and Nonstationarity

Trend Stationary Processes

A Random Walk

A RandomWalkwithDrift

KeyPropertiesofRandomWalks

Conclusions

Fluctuations

Introduction

Moving AverageProcesses

AutoregressiveProcesses

TheStationarity Condition

Key Properties ofMoving Average andAutoregressiveProcesses

Autoregressive-Moving Average Processes

Trends

The Constant Growth Model Revisited

Trend and Difference Stationary Processes

Testing for StochasticTrends

Higher Orders of Integration

Cointegration

Long Run RelationshipsBetween Variables

Relationships BetweenVariables

The Arithmetic ofIntegrated Processes

Cointegration

TheEngle-Granger Test forCointegration

Testing Restrictions onthe Cointegrating Vector

ErrorCorrection Models

The ECMof VAR

CointegratingRank

Conclusions and Further Reading

Lawsof Summation And Deviation Form

Laws ofSummation

Laws ofDeviation Form

Distribution Theory

Random Variables and Probability Distribution

MathematicalExpectation

Expected Value of a Function

Variance

Varianceof a Function

Standardized Random Variables

Bivariate Distributions

Conditional Distributions and Expectation

Statistical Independence

Functions of Two Random Variables

Variance of a Linear Comb

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