Details

An Introduction to Econometric Theory


An Introduction to Econometric Theory


6. Aufl.

von: James Davidson

66,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 18.07.2018
ISBN/EAN: 9781119484936
Sprache: englisch
Anzahl Seiten: 256

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

<p><b>A guide to economics, statistics and finance that explores the mathematical foundations underling econometric methods</b></p> <p><i>An Introduction to Econometric Theory</i> offers a text to help in the mastery of the mathematics that underlie econometric methods and includes a detailed study of matrix algebra and distribution theory. Designed to be an accessible resource, the text explains in clear language why things are being done, and how previous material informs a current argument. The style is deliberately informal with numbered theorems and lemmas avoided. However, very few technical results are quoted without some form of explanation, demonstration or proof.</p> <p>The author — a noted expert in the field — covers a wealth of topics including: simple regression, basic matrix algebra, the general linear model, distribution theory, the normal distribution, properties of least squares, unbiasedness and efficiency, eigenvalues, statistical inference in regression, t and F tests, the partitioned regression, specification analysis, random regressor theory, introduction to asymptotics and maximum likelihood. Each of the chapters is supplied with a collection of exercises, some of which are straightforward and others more challenging. This important text:</p> <ul> <li>Presents a guide for teaching econometric methods to undergraduate and graduate students of economics, statistics or finance</li> <li>Offers proven classroom-tested material</li> <li>Contains sets of exercises that accompany each chapter</li> <li>Includes a companion website that hosts additional materials, solution manual and lecture slides </li> </ul> <p>Written for undergraduates and graduate students of economics, statistics or finance, <i>An Introduction to Econometric Theory</i> is an essential beginner’s guide to the underpinnings of econometrics. </p> <p> </p>
<p>List of Figures ix</p> <p>Preface xi</p> <p>About the CompanionWebsite xv</p> <p><b>Part I Fitting </b><b>1</b></p> <p><b>1 Elementary Data Analysis </b><b>3</b></p> <p>1.1 Variables and Observations 3</p> <p>1.2 Summary Statistics 4</p> <p>1.3 Correlation 6</p> <p>1.4 Regression 10</p> <p>1.5 Computing the Regression Line 12</p> <p>1.6 Multiple Regression 16</p> <p>1.7 Exercises 18</p> <p><b>2 Matrix Representation </b><b>21</b></p> <p>2.1 Systems of Equations 21</p> <p>2.2 Matrix Algebra Basics 23</p> <p>2.3 Rules of Matrix Algebra 26</p> <p>2.4 Partitioned Matrices 27</p> <p>2.5 Exercises 28</p> <p><b>3 Solving the Matrix Equation </b><b>31</b></p> <p>3.1 Matrix Inversion 31</p> <p>3.2 Determinant and Adjoint 34</p> <p>3.3 Transposes and Products 37</p> <p>3.4 Cramer’s Rule 38</p> <p>3.5 Partitioning and Inversion 39</p> <p>3.6 A Note on Computation 41</p> <p>3.7 Exercises 43</p> <p><b>4 The Least Squares Solution </b><b>47</b></p> <p>4.1 Linear Dependence and Rank 47</p> <p>4.2 The General Linear Regression 50</p> <p>4.3 Definite Matrices 52</p> <p>4.4 Matrix Calculus 56</p> <p>4.5 Goodness of Fit 57</p> <p>4.6 Exercises 59</p> <p><b>Part II Modelling </b><b>63</b></p> <p><b>5 Probability Distributions </b><b>65</b></p> <p>5.1 A Random Experiment 65</p> <p>5.2 Properties of the Normal Distribution 68</p> <p>5.3 Expected Values 72</p> <p>5.4 Discrete Random Variables 75</p> <p>5.5 Exercises 80</p> <p><b>6 More on Distributions </b><b>83</b></p> <p>6.1 Random Vectors 83</p> <p>6.2 The Multivariate Normal Distribution 84</p> <p>6.3 Other Continuous Distributions 87</p> <p>6.4 Moments 90</p> <p>6.5 Conditional Distributions 92</p> <p>6.6 Exercises 94</p> <p><b>7 The Classical RegressionModel </b><b>97</b></p> <p>7.1 The Classical Assumptions 97</p> <p>7.2 The Model 99</p> <p>7.3 Properties of Least Squares 101</p> <p>7.4 The Projection Matrices 103</p> <p>7.5 The Trace 104</p> <p>7.6 Exercises 106</p> <p><b>8 The Gauss-Markov Theorem </b><b>109</b></p> <p>8.1 A Simple Example 109</p> <p>8.2 Efficiency in the General Model 111</p> <p>8.3 Failure of the Assumptions 113</p> <p>8.4 Generalized Least Squares 114</p> <p>8.5 Weighted Least Squares 116</p> <p>8.6 Exercises 118</p> <p><b>Part III Testing </b><b>121</b></p> <p><b>9 Eigenvalues and Eigenvectors </b><b>123</b></p> <p>9.1 The Characteristic Equation 123</p> <p>9.2 Complex Roots 124</p> <p>9.3 Eigenvectors 126</p> <p>9.4 Diagonalization 128</p> <p>9.5 Other Properties 130</p> <p>9.6 An Interesting Result 131</p> <p>9.7 Exercises 133</p> <p><b>10 The Gaussian RegressionModel </b><b>135</b></p> <p>10.1 Testing Hypotheses 135</p> <p>10.2 Idempotent Quadratic Forms 137</p> <p>10.3 Confidence Regions 140</p> <p>10.4 t Statistics 141</p> <p>10.5 Tests of Linear Restrictions 144</p> <p>10.6 Constrained Least Squares 146</p> <p>10.7 Exercises 149</p> <p><b>11 Partitioning and Specification </b><b>153</b></p> <p>11.1 The Partitioned Regression 153</p> <p>11.2 Frisch-Waugh-Lovell Theorem 155</p> <p>11.3 Misspecification Analysis 156</p> <p>11.4 Specification Testing 159</p> <p>11.5 Stability Analysis 160</p> <p>11.6 Prediction Tests 162</p> <p>11.7 Exercises 163</p> <p><b>Part IV Extensions </b><b>167</b></p> <p><b>12 Random Regressors </b><b>169</b></p> <p>12.1 Conditional Probability 169</p> <p>12.2 Conditional Expectations 170</p> <p>12.3 StatisticalModels Contrasted 174</p> <p>12.4 The Statistical Assumptions 176</p> <p>12.5 Properties of OLS 178</p> <p>12.6 The Gaussian Model 182</p> <p>12.7 Exercises 183</p> <p><b>13 Introduction to Asymptotics </b><b>187</b></p> <p>13.1 The Lawof Large Numbers 187</p> <p>13.2 Consistent Estimation 192</p> <p>13.3 The Central LimitTheorem 195</p> <p>13.4 Asymptotic Normality 198</p> <p>13.5 Multiple Regression 201</p> <p>13.6 Exercises 203</p> <p><b>14 Asymptotic Estimation Theory </b><b>207</b></p> <p>14.1 Large Sample Efficiency 207</p> <p>14.2 Instrumental Variables 208</p> <p>14.3 Maximum Likelihood 210</p> <p>14.4 Gaussian ML 213</p> <p>14.5 Properties of ML Estimators 214</p> <p>14.6 Likelihood Inference 216</p> <p>14.7 Exercises 218</p> <p><b>Part V Appendices </b><b>221</b></p> <p>A The Binomial Coefficients 223</p> <p>B The Exponential Function 225</p> <p>C Essential Calculus 227</p> <p>D The Generalized Inverse 229</p> <p>Recommended Reading 233</p> <p>Index 235</p>
<p><b>JAMES DAVIDSON</b> is Professor of Econometrics at the University of Exeter. He has also held teaching posts at the University of Warwick, the London School of Economics, the University of Wales Aberystwyth and Cardiff University, as well as visiting positions at the University of California, Berkeley, the University of California, San Diego, and Central European University, Budapest.
<p><b>A GUIDE TO ECONOMICS, STATISTICS AND FINANCE THAT EXPLORES THE MATHEMATICAL FOUNDATIONS UNDERLING ECONOMETRIC METHODS</b> <p><i>An Introduction to Econometric Theory</i> offers a text to help in the mastery of the mathematics that underlie econometric methods and includes a detailed study of matrix algebra and distribution theory. Designed to be an accessible resource, the text explains in clear language why things are being done, and how previous material informs a current argument. The style is deliberately informal with numbered theorems and lemmas avoided. However, very few technical results are quoted without some form of explanation, demonstration or proof. <p>The author—a noted expert in the field—covers a wealth of topics including: simple regression, basic matrix algebra, the general linear model, distribution theory, the normal distribution, properties of least squares, unbiasedness and efficiency, eigenvalues, statistical inference in regression, t and F tests, the partitioned regression, specification analysis, random regressor theory, introduction to asymptotics and maximum likelihood. Each of the chapters is supplied with a collection of exercises, some of which are straightforward and others more challenging. This important text: <ul> <li>Presents a guide for teaching econometric methods to undergraduate and graduate students of economics, statistics or finance</li> <li>Offers proven classroom-tested material</li> <li>Contains sets of exercises that accompany each chapter</li> <li>Includes a companion website that hosts additional materials, a solution manual and lecture slides</li> </ul> <p>Written for undergraduates and graduate students of economics, statistics or finance, <i>An Introduction to Econometric Theory</i> is an essential beginner's guide to the underpinnings of econometrics.

Diese Produkte könnten Sie auch interessieren:

Designated Drivers
Designated Drivers
von: G. E. Anderson
PDF ebook
22,99 €
Quantitative Financial Economics
Quantitative Financial Economics
von: Keith Cuthbertson, Dirk Nitzsche
PDF ebook
40,99 €