Web Site for
Advanced Econometrics I (undergraduate) &
Econometircs I (graduate) of 2018SY
Providing information of the class through this WEB pgae.
Students who take this class are expected to browse reguraly.
Course Plan (at 8/22)
The day represented bold letter shows finished contents, and the day represented normal letter shows planned contents.
#  dates  contents of the class  corresponding pages in the textbook 
other  assignment  TA session 
1  April 11  1. Introduction 1.1 What is econometrics 1.2 The structure of this class 1.3 Quizzes for checking your knowledge on statistics 
NONE  [Additional References] HandOut#01 (PDF file) 
NONE  
2  April 18  2. Linear Regression Models and the Ordinary Least Square (OLS) 2.1 Simple linear regression models 2.2 Matrix expression of the linear regression models 
Ch 2 (pp.5264) Ch 3.2 (pp.6668) Ch 3.5 (pp.7981) 
HandOut#02 (PDF file) 
#02 (PDF file) Solution to #02 (PDF file) (4/25) 
TA_1 (PDF file) 
3  April 25  3. Geometry of the OLS 3.1 The Geometry of linear regression 3.2 FWL theorem and its application 
Ch 3.2 (pp.7172) Ch 3.3 (pp.7276) 
[Additonal References] HandOut#03 (PDF file) 
#03 (PDF file) Solution to #03 (PDF file) (5/9) 
TA_2 (PDF file) 
May 2  Ichou Festival (no class)  
4  May 9  4. The Law of Large Numbers and the Central Limit Theorem 4.1 Convergence of Sequence of Functions 4.2 Concepts on Stochastic Convergence 4.3 Order of Magnitude in Random Sequences 4.4 The Law of Large Numbers 4.5 Central Limit Theorem 
Appendix D (pp.11071122)  [Additional References](5/16) HandOut#04 with the appendix (PDF file) 
#04 (PDF file) Solution to #04 (PDF file) (5/16) 
TA 3 (PDF file) 
5  May 16  5. Statistical Properties of the OLS estimator 5.1 Desirable properties of 'good' estimators 5.2 Unbiasness 5.3 Consistency 5.4 Efficiency 5.5 Regression residuals 5.6 The distribution of the OLS estimator b and the distribution of a test statistic 
Ch 4.1 (pp.9192) Ch 4.3 (pp.94103) Ch 4.4 (pp.103112) 
HandOut#05 (PDF file) 
#05 (PDF file) (corrected at 5/18 again) [Note to Assignments #05](5/ Solution to #05 (PDF file) (5/23) 
TA4 (PDF file) 
6  May 23  6. The OLS with Restriction and Other Topics 6.1 Tests of Several Restrictions 6.2 Restricted Least Squares 6.3 Misspecification of the Linear Regression Models 6.4 Prediction 6.5 Multicolinearity 
Ch 5.35.5 (pp.152165) Ch 4.3 (pp.9698) Ch 4.6 (pp.120121) 
[Additional References] [Typos in HandOut#06](6/1) HandOut#06 (PDF file) (corrected at 6/1) 
#06 (PDF file) Solution to #06 (PDF file) (5/30) 
TA5 (PDF file) 
7  May 30  7. The Generalized Least Squares: Overview 7.1 Problems to be considered 7.2 The Generalized Least Squares (GLS) 7.3 The distribution of the GLS estimator 7.4 Some important proofs 7.5 The feasible GLS 7.6 Heteroscedasticity of the disturbances 7.7 Tests for hetroschedasticity 7.8 Calculation of the proper variance of the OLS estimator 
Ch 9.19.2 (pp.297302) Ch 9.3 (pp.304308) Ch 9.6 (pp.317320) Ch 9.5 (pp.315317) Ch 9.4 (pp.312314) Ch 9.7 (pp.320324) 
HandOut#07 (PDF file) (corrected at 6/6) 
#07 (PDF file) (5/31) Solution to #07 (PDF file) (6/7) 
TA6 (PDF file) 
8  June 6  8. The Generalized Least Squares: Application (1) 8.1 Autocorrelated Disturbances: Overview 8.2 The GLS estimation for AR(1) disturbances 8.3 A test for serially correlated disturbances 
Ch 20.2 (pp.947948) Ch 20.3 (pp.949952) Ch 20.4 (p.953) Ch 20.7 (p.963) Ch 20.9 (pp.966969) Ch 14.7 (pp.597599) 
HandOut#08 (PDF file) 
#08 (PDF file) (6/11) Solution to #08 (PDF file) (6/20) 
TA7 (PDF file) 
9  June 13  Summary I (Midterm exam)  [Coverage of the Midterm exam] [Items which are allowed to place on the desk at the Midterm exam] 
Solution to Midterm exam (PDF file) (corrected at 6/20) 
TA8 (PDF file) 

10  June 20  9. Analysis of Panel Data (The GLS: Application (2)) 9.1 Models for panel data 9.2 Proposed models for effects 9.3 Estimation of Fixed Effect Models 9.4 Estimation of Random Effect Models 9.5 The GLS Estimation of Random Effect Models 9.6 Attention to Estimating Random Effect Models 9.7 Seemingly Unrelated Regression: SUR 
Ch 11.2 (pp.384389) Ch 11.3 (pp.389392) Ch 11.3 (pp.397398) Ch 11.4 (pp.399410) Ch 11.5 (pp.410420) Ch 10.2 (pp.332336) 
[Typos in HandOut#10] HandOut#10 (PDF file) 
#10 (PDF file) Solution to #10 (PDF file) (7/4) 

11  June 27  10. Instrumental Variables Estimation 10.1 The Problem that We Have to Care 10.2 Instrumental Variables Estimators 10.3 The TwoStage Least Squares (the 2SLS) 10.4 Small Sample Properties of the IV Estimator 
Ch 8.1 (pp.259262) Ch 8.2 (pp.263264) Ch 8.3 (pp.265273) Ch 8.7 (pp.289291) 
HandOut#11 (PDF file) 
#11 (PDF file) (6/28) Solution to #11 (PDF file) 
TA10 (PDF file) 
12  July 4  10.5 Hypothesis Tests 11. Maximum Likelihood Estimation 11.1 Foundation of the Maximum Likelihood Method 11.2 The Distribution of the MLE 11.3 Asymptotic Efficiency of the MLE 11.4 An Example of the ML estimation: Inference of p for the Bernoulli Distribution 
Ch 8.4 (pp.273279) Ch 14.2 (pp.549551) Ch 14.3 (pp.551553) Ch 14.4 (pp.553563) 
HandOut#12 (PDF file) 
#12 (PDF file) Solution to #12 (PDF file) 
TA11 (PDF file) 
13  July 11  12. Tests Based on the Likelihood Ratio 12.1 What is a "Good" Test? 12.2 Example: Linear Regression with Normal Errors 
Ch 14.6 (pp.564572) Ch 14.9 (pp.588592) 
[Typo in HandOut#13] HandOut#13 (PDF file) 
#13 (PDFfile) Solution to #13 (PDF file) 
TA12 (PDF file) 
14  July 18  13. Time Series Models 13.1 Supplementary Topics for Univariate Time Series 13.2 Multivariate Time Series Models 13.3 Model Selection 
Ch 20.4 (pp.952957) Ch 10.6 (pp.357358) Ch 14.6 (pp.573576) 
[Typo in HandOut#14] [Additonal References] HandOut#14 (PDF file) updated at 7/25 
#14(PDF file) Solution to #14 (PDF file) 
TA13 (PDF file) updated at 7/19 21:20 
15  July 25  14. Unit Root and Cointegration  Ch 21.2 (pp.982995) Ch 21.3 (pp.9991010) 
[Additional References] HandOut#15 (PDF file) 
None  None 
16  August 1  Final Exam  Solution to FinalExam (PDF file) (tentative) Comment on the Final Exam (PDF file) 
Supplementary notes, etc.
[Addtional references]
The article on the emergence of econometrics which I introduced in the class is
Frish, R. (1933), "Editor's Note," Econometrica, Vol.1 (1), pp.14.
In addition,
Roos, C.F. (1933), "Constitution of the Econometric Society," Econometrica, Vol. 1 (1), pp. 106108.
Christ, C.F. (1953), "History of the Cowles Commission 19321952," in Cowles Commission for Research
in Economics eds., Economic theory and measurement; a twenty year research report, 19321952,
U. of Chicago. (available from http://cowles.yale.edu/sites/default/files/files/pub/misc/historycowles.pdf )
are also existed.
On the relation among philosopy of science, economics, and econometrics, please read
Chap.6 "Progress in Economics" of
Dow, S.C. (2002), Economic Methodology: an inquiry, Oxford U.P. ,
for example.
For the history of econometics,
Morgan, M.S. (1990), The history of econometric ideas, Cambridge U. P.
is higly recomended.
[Additional references]
For detailed explanation on issues which handled in Today's class,
reading pp.4275 of
Davidson, R. and MacKinnon, J.G. (2004), Econometric Theory and Methods, Oxford U.P.
is highly recommended.
[Additional references]
The following books would be helpful for reviewing Today's class.
Chapter 1820 and 2223 of Davidson, J. (1994) Stochastic Limit Theory, Oxford Univ. Press.
Chapter 17, 18, 20, and 21 of Jacod, J. and Protter, P. (2004) Probability Essentials, Springer.
Chapter 6 and 7 of Bierens, H.J. (2004) Introduction to the Mathematical and Statistical Foundations
of Econometrics, Cambridge Univ. Press
[Note to Assignments #05] (announced at 5/17 20:00 5/18 16:15)
(1) Please add the following sentence in Q2; we assume that X is nonstochastic
(2) Please correct the sectence in Q1;
<old> Suppose A is a positive definite matrix.
<new> Suppose A is a k x k symmetric and positive definite matrix.
(The PDF file is replaced at 20:00 May 17 16:15 May 18.)
[Additional reference]
For more detailed explanation of the ridge regression, the followings
would be helpful.
pp.6061 of Amemiya, T. (1985) Advanced Econometrics, Harvard Univ. Press.
Hoerl, A.E. and Kennard, R.W. (1970), "Ridge Regression: Biased Estimation for Nonorthogonal Problems,"
Technometrics, 12 (1), pp.5567.
Conniffe, D. and Stone, J. (1973) "A Critical View of Ridge Regression," Journal of the Royal Statistical Society,
Series D (The Statistician), 22 (3), pp.181187.
[Typos in HandOut#06] (announced at 6/1 21:15)
A student find that some typos exist in page 6 of HandOut#06.
Please replace the corrected version which is downloadable from this
Web page.
[Coverage of the Midterm exam]
The Coverage is from #02 to #07.
[Items which are allowed to place on the desk at the Midterm exam]
pen, pencil, eraser, watch, electronic calculator, and IC dictionary
<NOTE> cell phone and smartphone are not allowed to place on the desk.
[Typos in HandOut#10] (announced at 6/20 19:50)
There are many typos in HandOut#10 which was distributed in the class.
Please replace the corrected version which is downloadable from this
Web page.
[Typo in HandOut#13] (announced at 7/11 20:55)
A student find a typo in (12.2.10) of page 15 in HandOut#13 which was
distributed in the class.
The correct equation of (12.2.10) is
f=((RRSSURSS)/l)/(URSS/(nk)).
Please replace the corrected version which is downloadable from this
Web page.
[Typos in HandOut#14] (announced at 7/18 19:00 7/25 17:40)
There are many typos in HandOut#14 which was distributed in the class.
(The section number is wrong; not 14 but 13. Other typos exist in page
4, 5, 8, 9, and 10.)
Please replace the corrected version which is downloadable from this Web page.
(Highly Recommended)
A student found that some typos still exist in the corrected version.
As the 2nd corrected version is downloadable since 7/25 17:40, please
replace !
[Additional References]
For VAR models, the followings would be helpful.
Chapter 11 of Hamilton, J.D. (1994), Time Series Analysis, Princeton
Univ. Press.
Chapter 9.4 of Verbeek, M. (2012), A Guide to Modern Econometrics, 4th
ed., Wiley.
[Additional References]
For nonstationary time series, the followings would be helpful.
Chapter 1719 of Hamilton, J.D. (1994), Time Series Analysis, Princeton
Univ. Press.
Banerjee, A. et. al (1993), CoIntegration, ErrorCorrection, and the
Econometric
Analysis of NonStationary Data, Oxford Univ. Press.