Expectations‚ Variances & Covariances The Rules of Summation n å xi ¼ x1 þ x2 þ Á Á Á þ xn covðX; YÞ ¼ E½ðXÀE½XÞðYÀE½YÞ i¼1 n ¼ å å ½x À EðXÞ½ y À EðYÞ f ðx; yÞ å a ¼ na x y i¼1 n covðX;YÞ r ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi varðXÞvarðYÞ n å axi ¼ a å xi i¼1 n i¼1 n n i¼1 i¼1 E(c1X þ c2Y ) ¼ c1E(X ) þ c2E(Y ) E(X þ Y ) ¼ E(X ) þ E(Y ) å ðxi þ yi Þ ¼ å xi þ å yi i¼1 n n n i¼1 i¼1 å ðaxi þ byi Þ ¼ a å xi þ b å yi i¼1 n var(aX þ bY þ cZ ) ¼ a2var(X) þ b2var(Y ) þ c2var(Z
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Luc Bauwens . Winfried Pohlmeier David Veredas (Eds.) High Frequency Financial Econometrics Recent Developments With 57 Figures and 64 Tables Physica-Verlag A Springer Company High Frequency Financial Econometrics Recent Developments Prof. Winfried Pohlmeier Department of Economics University of Konstanz 78457 Konstanz Germany winfried.pohlmeier@uni-konstanz.de Prof. Luc Bauwens CORE Voie du Roman Pays 1348 Louvain-la-Neuve Belgium bauwens@ucl.ac.be Prof. David
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eAUSTRALIAN SCHOOL OF BUSINESS SCHOOL OF ECONOMICS ECON2206 / ECON3290 (ARTS) Introductory Econometrics Course outline SESSION 2‚ 2011 Lecturer in Charge: Dr. Rachida Ouysse Room ASB441 Telephone: 9385 3321 Email: rouysse@unsw.edu.au Lectures: Fridays 9am-11am Venue: Law Theatre G04 Website: http://telt.unsw.edu.au/ TABLE OF CONTENTS 1 STAFF CONTACT DETAILS 1 1 1 1 1 1 2 2 2 2 3 3 3 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 7 9 9 9 10 10 10 12 13 13 13
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ECON2206/ECON3290: Introductory Econometrics Session 1‚ 2009 Course Project Solution Guide Each question is worth 1 mark - and there are 20 questions in total. Answers should be clear and legible. Note Instruction (d) on the Questions: “when performing statistical tests‚ to always state the null and alternative hypotheses‚ the test statistic and it’s distribution under the null hypothesis‚ the level of significance and the conclusion of the test.” Marks are not awarded when this instruction is not
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Question 1: Run the regression Report your answer in the format of equation 5.8 (Chapter 5‚ p. 152) in the textbook including and the standard error of the regression (SER). Interpret the estimated slope parameter for LOT. In the interpretation‚ please note that PRICE is measured in thousands of dollars and LOT is measured in acres. Model 1: OLS estimates using the 832 observations 1-832 Dependent variable: price VARIABLE COEFFICIENT STDERROR T STAT P-VALUE
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Crime Rates: An Econometric Analysis using population‚ unemployment and growth Table of Contents I. Introduction A.) Background of the Study B.) Problem Statement C.) Objectives D.) Significance of the Study E.) Scope and Limitations II. Review of Related Literature III. Operational Framework A.) Variable List B.) Model Specification C.) A-priori Expectations IV. Methodology A.) Data B.) Preliminary Tests V. Results and Discussions VI. Conclusion
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BPBE 361.3(2012-13 Winter Term) Intermediate Statistics and Decision Making (CRN 27699) Eviews Manual for Lab session Lab: 2:30 – 4:40pm‚ Wednesday Venue: 3D67 Starting Eviews Steps: ➢ Click on the Start button on the taskbar ➢ Look for All programs and click on it ➢ Click on Eviews 7 folder ➢ Double click on Eviews to lunch it Eviews Window Creating a workfile and importing data Steps: ➢ Click on File in the already opened Eviews Window ➢ Click on
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4) [Wooldridge C3.8] (i) Wiew/Descriptive statistics INCOME PRPBLCK Mean 47053.78 0.113486 Median 46272.00 0.041444 Maximum 136529.0 0.981658 Minimum 15919.00 0.000000 Std. Dev. 13179.29 0.182416 Skewness 0.962831 2.700012 Kurtosis 7.551386 10.56841 Jarque-Bera 416.2135 1473.100 Probability 0.000000 0.000000 Sum 19244998 46.41594 Sum Sq. Dev. 7.09E+10 13.57651 Observations 409 409 The average of prpblck is .113 with standard
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PART TWO Solutions to Empirical Exercises Chapter 3 Review of Statistics Solutions to Empirical Exercises 1. (a) Average Hourly Earnings‚ Nominal $’s Mean AHE1992 AHE2004 AHE2004 − AHE1992 (b) Average Hourly Earnings‚ Real $2004 Mean AHE1992 AHE2004 AHE2004 − AHE1992 15.66 16.77 Difference 1.11 SE(Mean) 0.086 0.098 SE(Difference) 0.130 95% Confidence Interval 15.49−15.82 16.58−16.96 95% Confidence Interval 0.85−1.37 11.63 16.77 Difference 5.14 SE(Mean) 0.064 0.098 SE(Difference) 0.117 95%
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Solutions Manual Econometric Analysis Fifth Edition William H. Greene New York University Prentice Hall‚ Upper Saddle River‚ New Jersey 07458 Contents and Notation Chapter 1 Introduction 1 Chapter 2 The Classical Multiple Linear Regression Model 2 Chapter 3 Least Squares 3 Chapter 4 Finite-Sample Properties of the Least Squares Estimator 7 Chapter 5 Large-Sample Properties of the Least Squares and Instrumental Variables Estimators 14 Chapter 6 Inference and Prediction 19 Chapter 7
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