Thursday, October 29, 2009
Friday, October 23, 2009
Residue Theorem and Its Application
See Wikipedia, http://en.wikipedia.org/wiki/Residue_theorem
The residue theorem and its applications by Oliver Knill:
http://www.math.harvard.edu/~knill/teaching/residues_1996/residue.pdf
The residue theorem and its applications by Oliver Knill:
http://www.math.harvard.edu/~knill/teaching/residues_1996/residue.pdf
Tuesday, October 20, 2009
STATISTICS: REFLECTIONS ON THE PAST AND VISIONS FOR THE FUTURE
STATISTICS: REFLECTIONS ON THE PAST AND VISIONS FOR THE FUTURE
Author: C. Radhakrishna Rao a
Affiliation:
a Pennsylvania State University, PA, U.S.A.
DOI: 10.1081/STA-100107683
Publication Frequency: 20 issues per year
Published in: Communications in Statistics - Theory and Methods, Volume 30, Issue 11 November 2001 , pages 2235 - 2257
Formats available: HTML (English) : PDF (English)
Author: C. Radhakrishna Rao a
Affiliation:
a Pennsylvania State University, PA, U.S.A.
DOI: 10.1081/STA-100107683
Publication Frequency: 20 issues per year
Published in: Communications in Statistics - Theory and Methods, Volume 30, Issue 11 November 2001 , pages 2235 - 2257
Formats available: HTML (English) : PDF (English)
Saturday, October 17, 2009
Wednesday, October 14, 2009
Monday, October 12, 2009
Bootstrap: Collection in Statistical Sicence (2003)
Statistical Science
A Review Journal of The Institute of Mathematical Statistics.
Volume 18, Issue 2
Publication Date: May 2003
A Review Journal of The Institute of Mathematical Statistics.
Volume 18, Issue 2
Publication Date: May 2003
Saturday, October 10, 2009
Wednesday, October 7, 2009
Markov Chain Monte Carlo (1)
Understanding the Metropolis-Hastings Algorithm
Author(s): Siddhartha Chib and Edward Greenberg
Source: The American Statistician, Vol. 49, No. 4 (Nov., 1995), pp. 327-335
Published by: American Statistical Association
Stable URL: http://www.jstor.org/stable/2684568
Explaining the Gibbs Sampler
George Casella; Edward I. George
The American Statistician, Vol. 46, No. 3. (Aug., 1992), pp. 167-174.Stable URL:http://links.jstor.org/sici?sici=0003-1305%28199208%2946%3A3%3C167%3AETGS%3E2.0.CO%3B2-R
Author(s): Siddhartha Chib and Edward Greenberg
Source: The American Statistician, Vol. 49, No. 4 (Nov., 1995), pp. 327-335
Published by: American Statistical Association
Stable URL: http://www.jstor.org/stable/2684568
Explaining the Gibbs Sampler
George Casella; Edward I. George
The American Statistician, Vol. 46, No. 3. (Aug., 1992), pp. 167-174.Stable URL:http://links.jstor.org/sici?sici=0003-1305%28199208%2946%3A3%3C167%3AETGS%3E2.0.CO%3B2-R
Tuesday, September 29, 2009
Mathworks: Matlab tutorial
MATLAB Tutorial
Choose a MATLAB tutorial or other resource that matches your learning style.
MATLAB Tutorial Files
CEE Course Support
Choose a MATLAB tutorial or other resource that matches your learning style.
MATLAB Tutorial Files
CEE Course Support
Superpc for R: Tutorial
Superpc for R: Tutorial
The methodology is described in the papers: Semi-supervised methods for predicting patient survival from gene expression papers (Bair, Tibshirani) PLOS Prediction by supervised principal components (Bair, Hastie, Paul, Tibshirani) Stanford tech report
The methodology is described in the papers: Semi-supervised methods for predicting patient survival from gene expression papers (Bair, Tibshirani) PLOS Prediction by supervised principal components (Bair, Hastie, Paul, Tibshirani) Stanford tech report
Sunday, September 27, 2009
Wednesday, September 23, 2009
Create your own history
Rama is the prince of this blog, who passed the field exam on Sep 1, the cumulative exam on Sep 11, and oral defence today, Sep 23. He motivates us to create our own history and vividly tells us a story that "everything is possible, hardworking making it!"
Tuesday, September 22, 2009
Notation in Econometrics
Notation in econometrics: a proposal for a standard
Authors: Abadir, Karim; Magnus, Jan1
Source: The Econometrics Journal, Volume 5, Number 1, June 2002 , pp. 76-90(15)
Publisher: Blackwell Publishing
Authors: Abadir, Karim; Magnus, Jan1
Source: The Econometrics Journal, Volume 5, Number 1, June 2002 , pp. 76-90(15)
Publisher: Blackwell Publishing
MATRIX ALGEBRA
Title:
MATRIX ALGEBRA, by Karim M. Abadir and Jan R. Magnus, Cambridge University Press, 2005
Source:
Econometric Theory [0266-4666] Otsu, Taisuke (2006) volume: 22 issue: 5 page: 968 -972
MATRIX ALGEBRA, by Karim M. Abadir and Jan R. Magnus, Cambridge University Press, 2005
Source:
Econometric Theory [0266-4666] Otsu, Taisuke (2006) volume: 22 issue: 5 page: 968 -972
Glance at Advanced Statistics: Linear Regression
Advanced Statistics: Linear Regression
Title:
Advanced Statistics: Linear Regression, Part I: Simple Linear Regression
Source:
Academic Emergency Medicine [1069-6563] Marill (2004) volume: 11 page: 87 -93
Title:
Advanced Statistics: Linear Regression, Part II: Multiple Linear Regression
Source:
Academic Emergency Medicine [1069-6563] Marill (2004) volume: 11 page: 94 -102
Title:
Advanced Statistics: Linear Regression, Part I: Simple Linear Regression
Source:
Academic Emergency Medicine [1069-6563] Marill (2004) volume: 11 page: 87 -93
Title:
Advanced Statistics: Linear Regression, Part II: Multiple Linear Regression
Source:
Academic Emergency Medicine [1069-6563] Marill (2004) volume: 11 page: 94 -102
Monday, September 7, 2009
Myopic Loss Aversion and the Equity Premium Puzzle
Benartzi, Shlomo; Richard H. Thaler (February 1995).
"Myopic Loss Aversion and the Equity Premium Puzzle".
The Quarterly Journal of Economics 110 (1): 73–92.
"Myopic Loss Aversion and the Equity Premium Puzzle".
The Quarterly Journal of Economics 110 (1): 73–92.
"The Equity Premium Puzzle in Retrospect".
Mehra, Rajnish; Edward C. Prescott (2003).
"The Equity Premium Puzzle in Retrospect".
in G.M. Constantinides, M. Harris and R. Stulz. Handbook of the Economics of Finance. Amsterdam: North Holland. pp. 889–938.
"The Equity Premium Puzzle in Retrospect".
in G.M. Constantinides, M. Harris and R. Stulz. Handbook of the Economics of Finance. Amsterdam: North Holland. pp. 889–938.
"The Equity Premium: It's Still a Puzzle"
Kocherlakota, Narayana R. (March 1996).
"The Equity Premium: It's Still a Puzzle" (PDF).
Journal of Economic Literature 34 (1): 42–71. http://www.econ.ucdavis.edu/faculty/kdsalyer/LECTURES/Ecn200e/Kocherla.pdf.
"The Equity Premium: It's Still a Puzzle" (PDF).
Journal of Economic Literature 34 (1): 42–71. http://www.econ.ucdavis.edu/faculty/kdsalyer/LECTURES/Ecn200e/Kocherla.pdf.
The equity premium: A puzzle
THE EQUITY PREMIUMA Puzzle*
Rajnish MEHRA
Columbia University, New York, NY 10027, USA
Edward C. PRESCOTTFederal Reserve Bank of MinneapolisUniversity of Minnesota, Minneapolis, MN 5545.5, USA.
Mehra, Rajnish; Edward C. Prescott (1985). "The Equity Premium: A Puzzle" (PDF). Journal of Monetary Economics 15: 145–161
Rajnish MEHRA
Columbia University, New York, NY 10027, USA
Edward C. PRESCOTTFederal Reserve Bank of MinneapolisUniversity of Minnesota, Minneapolis, MN 5545.5, USA.
Mehra, Rajnish; Edward C. Prescott (1985). "The Equity Premium: A Puzzle" (PDF). Journal of Monetary Economics 15: 145–161
Thursday, September 3, 2009
A statistical perspective on ill-posed inverse problems
A statistical perspective on ill-posed inverse problems
F O'Sullivan - Statistical Science, 1986 - jstor.org
Page 1. Statistical Science 1986, Vol. 1, No. 4, 502-527 A Statistical Perspectiveon Ill-posed Inverse Problems Finbarr O'Sullivan Abstract. ...
F O'Sullivan - Statistical Science, 1986 - jstor.org
Page 1. Statistical Science 1986, Vol. 1, No. 4, 502-527 A Statistical Perspectiveon Ill-posed Inverse Problems Finbarr O'Sullivan Abstract. ...
Monday, July 20, 2009
Matlab Symbolic Mathematics
Matlab Symbolic Mathematics
'If you are using the Student Version of MATLAB, then you have access to the optional Symbolic Math Toolbox. If you are using a professional (non-student) version, then you must purchase this toolbox separately. If you do not know whether your version of MATLAB is equipped with the toolbox or not, try a few of the following exercises. If they work, you抳e got it. If not, you will have to skip over any exercise that asks you to perform computations with variables that have not been assigned numeric values and should be treated as symbols. '
See the above link for details.
'If you are using the Student Version of MATLAB, then you have access to the optional Symbolic Math Toolbox. If you are using a professional (non-student) version, then you must purchase this toolbox separately. If you do not know whether your version of MATLAB is equipped with the toolbox or not, try a few of the following exercises. If they work, you抳e got it. If not, you will have to skip over any exercise that asks you to perform computations with variables that have not been assigned numeric values and should be treated as symbols. '
See the above link for details.
Thursday, July 9, 2009
The ET Interview: Professor Jan Kmenta
The ET Interview: Professor Jan Kmenta
John Lodewijks and Jan Kmenta
Econometric Theory, Vol. 21, No. 3 (Jun., 2005), pp. 621-645
Published by: Cambridge University Press
Access article from an external site
John Lodewijks and Jan Kmenta
Econometric Theory, Vol. 21, No. 3 (Jun., 2005), pp. 621-645
Published by: Cambridge University Press
Access article from an external site
Teaching Modeling and Simulation in Economics: A Pleasant Surprise
Teaching Modeling and Simulation in Economics: A Pleasant Surprise
Eshragh Motahar
The Journal of Economic Education, Vol. 25, No. 4 (Autumn, 1994), pp. 335-342
Eshragh Motahar
The Journal of Economic Education, Vol. 25, No. 4 (Autumn, 1994), pp. 335-342
Statistics on Statistics: Measuring Research Productivity by Journal Publications between 1985 and 1995
Statistics on Statistics: Measuring Research Productivity by Journal Publications between 1985 and 1995
Christian Genest
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 25, No. 4 (Dec., 1997), pp. 427-443
Christian Genest
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 25, No. 4 (Dec., 1997), pp. 427-443
A History of the Statistical Society of Canada: The Formative Years
A History of the Statistical Society of Canada: The Formative Years
David R. Bellhouse, Christian Genest
Statistical Science, Vol. 14, No. 1 (Feb., 1999), pp. 80-115
David R. Bellhouse, Christian Genest
Statistical Science, Vol. 14, No. 1 (Feb., 1999), pp. 80-115
The ET Dialogue: A Conversation on Econometric Methodology
The ET Dialogue: A Conversation on Econometric Methodology
David F. Hendry, Edward E. Leamer, Dale J. Poirier
Econometric Theory, Vol. 6, No. 2 (Jun., 1990), pp. 171-261
David F. Hendry, Edward E. Leamer, Dale J. Poirier
Econometric Theory, Vol. 6, No. 2 (Jun., 1990), pp. 171-261
Wednesday, July 8, 2009
Instrumental variable
Instrumental Variable Estimation of the Simple Errors-in-Variables Model
R. L. Carter, Wayne A. Fuller
Journal of the American Statistical Association, Vol. 75, No. 371 (Sep., 1980), pp. 687-692
Instrumental-Variable Estimation of an Error-Components Model
Takeshi Amemiya, Thomas E. MaCurdy
Econometrica, Vol. 54, No. 4 (Jul., 1986), pp. 869-880
Instrumental Variable Estimation in Generalized Linear Measurement Error Models
Jeffrey S. Buzas, Leonard A. Stefanski
Journal of the American Statistical Association, Vol. 91, No. 435 (Sep., 1996), pp. 999-1006
Finite Sample Properties of Instrumental Variable Estimators of Structural Coefficients
Roberto S. Mariano
Econometrica, Vol. 45, No. 2 (Mar., 1977), pp. 487-496
Does More Crime Mean More Prisoners? An Instrumental Variables Approach
Yair Listokin
Journal of Law and Economics, Vol. 46, No. 1 (Apr., 2003), pp. 181-206
Testing Identifiability and Specification in Instrumental Variable Models
John G. Cragg, Stephen G. Donald
Econometric Theory, Vol. 9, No. 2 (Jun., 1993), pp. 222-240
Consistent Estimation with a Large Number of Weak Instruments
John C. Chao, Norman R. Swanson
Econometrica, Vol. 73, No. 5 (Sep., 2005), pp. 1673-1692
Structural Equations, Treatment Effects, and Econometric Policy Evaluation Structural Equations, Treatment Effects, and Econometric Policy Evaluation
James J. Heckman, Edward Vytlacil
Econometrica, Vol. 73, No. 3 (May, 2005), pp. 669-738
R. L. Carter, Wayne A. Fuller
Journal of the American Statistical Association, Vol. 75, No. 371 (Sep., 1980), pp. 687-692
Instrumental-Variable Estimation of an Error-Components Model
Takeshi Amemiya, Thomas E. MaCurdy
Econometrica, Vol. 54, No. 4 (Jul., 1986), pp. 869-880
Instrumental Variable Estimation in Generalized Linear Measurement Error Models
Jeffrey S. Buzas, Leonard A. Stefanski
Journal of the American Statistical Association, Vol. 91, No. 435 (Sep., 1996), pp. 999-1006
Finite Sample Properties of Instrumental Variable Estimators of Structural Coefficients
Roberto S. Mariano
Econometrica, Vol. 45, No. 2 (Mar., 1977), pp. 487-496
Does More Crime Mean More Prisoners? An Instrumental Variables Approach
Yair Listokin
Journal of Law and Economics, Vol. 46, No. 1 (Apr., 2003), pp. 181-206
Testing Identifiability and Specification in Instrumental Variable Models
John G. Cragg, Stephen G. Donald
Econometric Theory, Vol. 9, No. 2 (Jun., 1993), pp. 222-240
Consistent Estimation with a Large Number of Weak Instruments
John C. Chao, Norman R. Swanson
Econometrica, Vol. 73, No. 5 (Sep., 2005), pp. 1673-1692
Structural Equations, Treatment Effects, and Econometric Policy Evaluation Structural Equations, Treatment Effects, and Econometric Policy Evaluation
James J. Heckman, Edward Vytlacil
Econometrica, Vol. 73, No. 3 (May, 2005), pp. 669-738
Calibration
Introduction Calibration and Econometric Research: An Overview
Adrian Pagan
Journal of Applied Econometrics, Vol. 9, Supplement: Special Issue on Calibration Techniques and Eco... more
Published by: John Wiley & Sons
Adrian Pagan
Journal of Applied Econometrics, Vol. 9, Supplement: Special Issue on Calibration Techniques and Eco... more
Published by: John Wiley & Sons
Sunday, July 5, 2009
Statistical Computing with R
Statistical Computing with RMaria L. Rizzo Chapman & Hall/CRC
Cat. #: C5459ISBN: 9781584885450
ISBN 10: 1584885459
Publication Date: 11/15/2007
Table of Contents and description.
R code for examples in the book (by chapter).R code for all examples in a single zip file: SCRcode.zip (revised 04/05/2008)
Errata and Notes (revised 11/26/2008).
Cat. #: C5459ISBN: 9781584885450
ISBN 10: 1584885459
Publication Date: 11/15/2007
Table of Contents and description.
R code for examples in the book (by chapter).R code for all examples in a single zip file: SCRcode.zip (revised 04/05/2008)
Errata and Notes (revised 11/26/2008).
DEA technical efficiency score
function TE=techeff(X,Y)
%% techeff(X,Y) calculates the technical efficiency of decision making units%%% Input:% X: N x J matrix, with N inputs for each unit% Y: M x J matrix, with M outpus for each unit% J: # of decision making units%%% Output:% TE: J x 1 vetctor contains the technical efficiency of each DMU%%% Reference:% Hughes and Yaisawarng, 2004, "Sensitivity and dimensionality tests of DEA% efficiency scores," European Journal of Operational Research, 154,% p.410-422%%% Author information:% Yundong Tu% Department of Economics% University of California, Riverside% e-mail: yundong.tu@gmail.com% July 4, 2009
%check data inputs% if nargin<2% error(' Not enough input arguments to run techeff ')% end
if nargin<2 rand('twister',3); X=3.*rand(5,20); Y=5.*rand(3,20);end
%check dimension compatibilityif size(X,2)~=size(Y,2) error(' Input data are not compatible. Inputs and outputs must have the same collumns, i.e., for the same number of DMUs')end
options=optimset('Display','off');%,'MaxIter',100,'MaxFunEvals',100,'TolX',1e-2,'TolFun',1e-2);for k=1:size(X,2) [z,TE(k,1)]=linprog([zeros(size(X,2),1);1.0], [-Y,zeros(size(Y,1),1);X, -X(:,k)], [-Y(:,k);zeros(size(X,1),1.0)],... [ones(1,size(X,2)),0.0], 1.0,zeros(size(X,2)+1,1),ones(size(X,2)+1,1), 0.5.*ones(size(X,2)+1,1),options);end
%% techeff(X,Y) calculates the technical efficiency of decision making units%%% Input:% X: N x J matrix, with N inputs for each unit% Y: M x J matrix, with M outpus for each unit% J: # of decision making units%%% Output:% TE: J x 1 vetctor contains the technical efficiency of each DMU%%% Reference:% Hughes and Yaisawarng, 2004, "Sensitivity and dimensionality tests of DEA% efficiency scores," European Journal of Operational Research, 154,% p.410-422%%% Author information:% Yundong Tu% Department of Economics% University of California, Riverside% e-mail: yundong.tu@gmail.com% July 4, 2009
%check data inputs% if nargin<2% error(' Not enough input arguments to run techeff ')% end
if nargin<2 rand('twister',3); X=3.*rand(5,20); Y=5.*rand(3,20);end
%check dimension compatibilityif size(X,2)~=size(Y,2) error(' Input data are not compatible. Inputs and outputs must have the same collumns, i.e., for the same number of DMUs')end
options=optimset('Display','off');%,'MaxIter',100,'MaxFunEvals',100,'TolX',1e-2,'TolFun',1e-2);for k=1:size(X,2) [z,TE(k,1)]=linprog([zeros(size(X,2),1);1.0], [-Y,zeros(size(Y,1),1);X, -X(:,k)], [-Y(:,k);zeros(size(X,1),1.0)],... [ones(1,size(X,2)),0.0], 1.0,zeros(size(X,2)+1,1),ones(size(X,2)+1,1), 0.5.*ones(size(X,2)+1,1),options);end
Calling R from within Matlab
The COM interface allows Matlab users to call R from within Matlab. It is quite convenient for matlab users to interact with R functions. To make R project available to your matlab is very simple.
TO DO LIST:
1. Install Matlab: http://www.mathworks.com/
2. Install R: Open http://www.r-project.org/ , choose download R and then select a mirror.
3. Install the R package "rscproxy" in R. The package is available at: http://cran.r-project.org/. Go to package and find rscproxy. This can also be simply done by typing "install.packages('rscproxy') in R prompt. Then choose a mirror. Wait for 2 seconds and it is done.
4. Download R-(D)COM Interface by clicking R_Scilab_DCOM3.0-1B5.exe .
5. Download MATLAB R-link from: http://www.mathworks.com/matlabcentral/fileexchange/5051
6. Unzip the downloaded MATLAB R-link.zip into your current directory in matlab.
7. You can enjoy the convenience of having Matlab to call R now. Test if it is working by type "Rdemo" in Matlab commond window. If you are interested in nonparametric denstiy estimation, run the following MatlabcallRnp.m file
function MatlabcallRnp()
%% MatlabcallRnp() illustrates how to use Matlab to call the %% NP package in R. %% Note: all .m files in the Matlab_RLINK folder should be %% copied into the current directory in Matlab. You do not %% need run R when it is called.% Author Infor.% Yundong Tu% Department of Economics,% Univeristy of California, Riverside% e-mail: yundong.tu@email.ucr.edu
%% Connect to an R SessionopenR
%% Push data into R with putRdata()a = randn(200,1);putRdata('a',a)%%{%% Call the density (R function to estimate density) %% command into Matlab with evalR() %get the evaluation points for the density estimator xx= evalR('density(a)$x'); %get the corresponding evaluation of density fx= evalR('density(a)$y'); %figure subplot(2,1,1) plot(xx,fx); %plot the density function% %the density plot can be also called by R as evalR('plot(density(a),mfrow=c(2,1))');%}
%% Call the npudens (R function to estimate density) %% command into Matlab with evalR() %get the evaluation points for the density estimator evalR('data=data.frame(a)'); evalR('library(np)')
evalR('xx=npudens(data)$eval'); %dataframe xx=evalR('xx[[1]]') %matrix %get the corresponding evaluation of density fx= evalR('npudens(data)$dens') %figure %xy=eda; [xx,ind]=sort(xx); fx=fx(ind); subplot(2,1,2) plot(xx,fx); %plot the density function %the npudens plot can be also called by R as evalR('plot(npudens(a),add=FALSE)');%}%%{%% Run a series of commands and grab %% the result using getRdata()%save time to call density() just once, also get the bandwidthevalR('den=density(a)'); xx=evalR('den$x'); % the same as: evalR('xx=den$x'); xx=getRdata('xx');fx=evalR('den$y'); bw=evalR('den$bw');
figureplot(xx,fx);hold ontitle({['R-output DENSITY'];['Bandwidth=',num2str(bw)]});hold off%}%% Close the connectioncloseR
Other related links:
http://www.cs.ubc.ca/~murphyk/Software/callingRfromMatlab.html
http://webscripts.softpedia.com/script/Scientific-Engineering-Ruby/Statistics-and-Probability/MATLAB-R-link-35485.html
TO DO LIST:
1. Install Matlab: http://www.mathworks.com/
2. Install R: Open http://www.r-project.org/ , choose download R and then select a mirror.
3. Install the R package "rscproxy" in R. The package is available at: http://cran.r-project.org/. Go to package and find rscproxy. This can also be simply done by typing "install.packages('rscproxy') in R prompt. Then choose a mirror. Wait for 2 seconds and it is done.
4. Download R-(D)COM Interface by clicking R_Scilab_DCOM3.0-1B5.exe .
5. Download MATLAB R-link from: http://www.mathworks.com/matlabcentral/fileexchange/5051
6. Unzip the downloaded MATLAB R-link.zip into your current directory in matlab.
7. You can enjoy the convenience of having Matlab to call R now. Test if it is working by type "Rdemo" in Matlab commond window. If you are interested in nonparametric denstiy estimation, run the following MatlabcallRnp.m file
function MatlabcallRnp()
%% MatlabcallRnp() illustrates how to use Matlab to call the %% NP package in R. %% Note: all .m files in the Matlab_RLINK folder should be %% copied into the current directory in Matlab. You do not %% need run R when it is called.% Author Infor.% Yundong Tu% Department of Economics,% Univeristy of California, Riverside% e-mail: yundong.tu@email.ucr.edu
%% Connect to an R SessionopenR
%% Push data into R with putRdata()a = randn(200,1);putRdata('a',a)%%{%% Call the density (R function to estimate density) %% command into Matlab with evalR() %get the evaluation points for the density estimator xx= evalR('density(a)$x'); %get the corresponding evaluation of density fx= evalR('density(a)$y'); %figure subplot(2,1,1) plot(xx,fx); %plot the density function% %the density plot can be also called by R as evalR('plot(density(a),mfrow=c(2,1))');%}
%% Call the npudens (R function to estimate density) %% command into Matlab with evalR() %get the evaluation points for the density estimator evalR('data=data.frame(a)'); evalR('library(np)')
evalR('xx=npudens(data)$eval'); %dataframe xx=evalR('xx[[1]]') %matrix %get the corresponding evaluation of density fx= evalR('npudens(data)$dens') %figure %xy=eda; [xx,ind]=sort(xx); fx=fx(ind); subplot(2,1,2) plot(xx,fx); %plot the density function %the npudens plot can be also called by R as evalR('plot(npudens(a),add=FALSE)');%}%%{%% Run a series of commands and grab %% the result using getRdata()%save time to call density() just once, also get the bandwidthevalR('den=density(a)'); xx=evalR('den$x'); % the same as: evalR('xx=den$x'); xx=getRdata('xx');fx=evalR('den$y'); bw=evalR('den$bw');
figureplot(xx,fx);hold ontitle({['R-output DENSITY'];['Bandwidth=',num2str(bw)]});hold off%}%% Close the connectioncloseR
Other related links:
http://www.cs.ubc.ca/~murphyk/Software/callingRfromMatlab.html
http://webscripts.softpedia.com/script/Scientific-Engineering-Ruby/Statistics-and-Probability/MATLAB-R-link-35485.html
Wednesday, July 1, 2009
It will be a new world
Looking back to my econometric life for the past 5 years, many important persons have come to my life to help me make a difference. And my world has been changing all the time, indeed. There have been lights, heros, mentors, partners, as well as friends. And each experience is so precious and exciting. I feel deeply thankful for all those people there, adding new elements into my life and guiding me to move forward.
It is indeed not easy to stay in academia since there are way many things to learn, Econometric theory, computing techniques, economic applications and new stats elements as well. Deep love of all these rock and sand is sure the way to success in research life and the road to the happiness I have imagined years ago. It would be impossible to know everything, but good to know that there are things that need to learn in each stage as time goes by. To think deeper the questions at hand and the papers in progress, to learn the social skills to get to know the life of other professionals, to get things done more carefully, more precisely, more concisely, more intuitively and more regorously etc, are key steps to achieve academic accomplishment and recognizations. It will be a new world for sure and keep on marching forward.
Just look at an earlier blog about things econometricians do at
http://toyond.blogspot.com/2009/05/behave-as-econometrician.html
It is indeed not easy to stay in academia since there are way many things to learn, Econometric theory, computing techniques, economic applications and new stats elements as well. Deep love of all these rock and sand is sure the way to success in research life and the road to the happiness I have imagined years ago. It would be impossible to know everything, but good to know that there are things that need to learn in each stage as time goes by. To think deeper the questions at hand and the papers in progress, to learn the social skills to get to know the life of other professionals, to get things done more carefully, more precisely, more concisely, more intuitively and more regorously etc, are key steps to achieve academic accomplishment and recognizations. It will be a new world for sure and keep on marching forward.
Just look at an earlier blog about things econometricians do at
http://toyond.blogspot.com/2009/05/behave-as-econometrician.html
Tuesday, June 30, 2009
What’s New in Econometrics: Time Series, 2008
NATIONAL BUREAU OF ECONOMIC RESEARCH, INC.
SUMMER INSTITUTE 2008
What’s New in Econometrics: Time Series
James H. Stock and Mark W. Watson, Organizers
SUMMER INSTITUTE 2008
What’s New in Econometrics: Time Series
James H. Stock and Mark W. Watson, Organizers
The Credit Crisis Visually Explained
Thanks to Shruti, who brought this wonderful video explanation of the credit crisis into our sight. The illustration is provided by Jonathan Jarvis.
Thursday, June 25, 2009
The role of Economic constraints in Econometrics
NONPARAMETRIC KERNEL REGRESSIONSUBJECT TO MONOTONICITY CONSTRAINTS by Peter Hall and Li-shan Huang, 2001, AS
NONPARAMETRIC ESTIMATION WHEN DATA ONDERIVATIVES ARE AVAILABLE by Peter Hall and Adonis Yatchew, 2007, AS
CONSTRAINED NONPARAMETRIC KERNEL REGRESSION:ESTIMATION AND INFERENCE by JEFFREY S. RACINE, CHRISTOPHER F. PARMETER, AND PANG DU
NONPARAMETRIC ESTIMATION WHEN DATA ONDERIVATIVES ARE AVAILABLE by Peter Hall and Adonis Yatchew, 2007, AS
CONSTRAINED NONPARAMETRIC KERNEL REGRESSION:ESTIMATION AND INFERENCE by JEFFREY S. RACINE, CHRISTOPHER F. PARMETER, AND PANG DU
Tuesday, June 23, 2009
Art of Publishing Workshop: Event Video
The Art of Publishing Workshop was organized by Emory University Economics Department in last April. Editors of top journals in Economics, Political Science, and Sociology offered their perspectives on important issues related to publishing in leading journals.
Strategies for dealing with editors and reviewers, optimum journal selection given various journal ranking, impact of technological innovation on publishing, planning for and handling the publication lag for junior faculty, and current trends in respective disciplines and their impact on success rate are among the topics that editors from /Journal of Political Economy, American Economic Review, American Political Science Review, American Sociological Review, Journal of Politics, Journal of Econometrics, Econometric Reviews, Industrial and Labor Relations Review, Managerial & Decision Economics, /and /Journal of Financial Economics //will be discussing./
See at:
Art of Publishing Workshop: Event Video
Strategies for dealing with editors and reviewers, optimum journal selection given various journal ranking, impact of technological innovation on publishing, planning for and handling the publication lag for junior faculty, and current trends in respective disciplines and their impact on success rate are among the topics that editors from /Journal of Political Economy, American Economic Review, American Political Science Review, American Sociological Review, Journal of Politics, Journal of Econometrics, Econometric Reviews, Industrial and Labor Relations Review, Managerial & Decision Economics, /and /Journal of Financial Economics //will be discussing./
See at:
Art of Publishing Workshop: Event Video
Monday, June 22, 2009
Econometrics___Bruce E. Hansen
Here is the link to the pdf version of Professor Hansen's graduate level text book:
Econometrics. Although it is still in its infancy, it is one of the best books for beginners. His way of understanding and presenting the material is not only deep, but easier for readers.
Econometrics. Although it is still in its infancy, it is one of the best books for beginners. His way of understanding and presenting the material is not only deep, but easier for readers.
Sunday, June 21, 2009
Happy Fathe's Day
Sunday, June 14, 2009
Summer on the go
This summer will be the most valuable one for my future academic career. Several things are urgent to be done as descriped in the check-list below:
1. A complete summary of the basics of Econometrics( Regression analysis/Time series models/Nonparametrics/Panel data models/Bootstrap/...)
2. A review of basics of R/Matlab/GAMS programming
3. Several research papers to be completed
4. Econometrics Society Meeting in Tokyo
1. A complete summary of the basics of Econometrics( Regression analysis/Time series models/Nonparametrics/Panel data models/Bootstrap/...)
2. A review of basics of R/Matlab/GAMS programming
3. Several research papers to be completed
4. Econometrics Society Meeting in Tokyo
GAMS---General Algebraic Modeling System
The General Algebraic Modeling System (GAMS) is a high-level modeling system for mathematical programming and optimization. It consists of a language compiler and a stable of integrated high-performance solvers. GAMS is tailored for complex, large scale modeling applications, and allows you to build large maintainable models that can be adapted quickly to new situations.
Welcome to the GAMS Home Page!
The General Algebraic Modeling System (GAMS) is a high-level modeling system for mathematical programming and optimization. It consists of a language compiler and a stable of integrated high-performance solvers. GAMS is tailored for complex, large scale modeling applications, and allows you to build large maintainable models that can be adapted quickly to new situations.
An Introduction to GAMS
Documentation (including FAQ)
Contributed Documentation
Presentations, Books, Posters
Download Current GAMS System
Download Older GAMS Systems
Contributed Software
Courses and Workshops
The GAMS Mailing List and Newsletter
Visit our European Web Site
The GAMS World
Solution Specialists
Other Sites on the Web
Welcome to the GAMS Home Page!
The General Algebraic Modeling System (GAMS) is a high-level modeling system for mathematical programming and optimization. It consists of a language compiler and a stable of integrated high-performance solvers. GAMS is tailored for complex, large scale modeling applications, and allows you to build large maintainable models that can be adapted quickly to new situations.
An Introduction to GAMS
Documentation (including FAQ)
Contributed Documentation
Presentations, Books, Posters
Download Current GAMS System
Download Older GAMS Systems
Contributed Software
Courses and Workshops
The GAMS Mailing List and Newsletter
Visit our European Web Site
The GAMS World
Solution Specialists
Other Sites on the Web
Monday, June 8, 2009
The recovery is not robust
According to Hamilton, it not a rubust recovery:
http://www.econbrowser.com/archives/2009/06/not_a_robust_re.html
http://www.econbrowser.com/archives/2009/06/not_a_robust_re.html
Thursday, June 4, 2009
The Dragon Boat Festival
The Dragon Boat Festival was in the last month, and I realized that we should have known some of the basics as listed here.
转自：中国英语网
The Dragon Boat Festival(端午节，字面意思是龙舟节), also called Double Fifth Festival, is celebrated on the fifth day of the fifth moon of the lunar calendar. It is one of the most important Chinese festivals, the other two being the Autumn Moon Festival and Chinese New Year. The origin of this summer festival centers around a scholarly government official named Chu Yuan. He was a good and respected man, but because of the misdeeds of jealous rivals he eventually fell into disfavor in the emperor's court.
Unable to regain the respect of the emperor, in his sorrow Chu Yuan threw himself into the Mi Low river. Because of their admiration for Chu Yuan, the local people living adjacent to the Mi Lo River rushed into their boats to search for him while throwing rice into the waters to appease the river dragons.
Although they were unable to find Chu Yuan, their efforts are still commemorated today during the Dragon Boat Festival.
端午节的由来
端午节，又称为五五节，因为端午节是在农历的五月五日，是三个重要的中国节庆之一，其它两个分别是中秋节和农历新年。 这个节日的由来是古代中国有一位博学多闻的官吏屈原，他是一位爱民而且又受到尊崇的官吏，但是由于一位充满嫉妒的官吏陷害，从此在朝廷中被皇帝所冷落。由于无法获得皇帝的重视，屈原在忧郁的情况下投汨罗江自尽。由于对屈原的爱戴，汨罗江畔的居民匆忙的划船在江内寻找屈原，并且将米丢入汨罗江中，以平息汨罗江中的蛟龙。即使他们当时并没有找到屈原，但是他们的行为，直到今天在端午节的时候，仍然被人们传颂纪念着。
Dragon Boat race Traditions At the center of this festival are the dragon boat races. Competing teams drive their colorful dragon boats forward to the rhythm of beating drums. These exciting races were inspired by the villager's valiant attempts to rescue Chu Yuan from the Mi Lo river. This tradition has remained unbroken for centuries.
Tzung Tzu A very popular dish during the Dragon Boat festival is tzung tzu. This tasty dish consists of rice dumplings with meat, peanut, egg yolk, or other fillings wrapped in bamboo leaves. The tradition of tzung tzu is meant to remind us of the village fishermen scattering rice across the water of the Mi Low river in order to appease the river dragons so that they would not devour Chu Yuan.
Ay Taso The time of year of the Dragon Boat Festival, the fifth lunar moon, has more significance than just the story of Chu Yuan. Many Chinese consider this time of year an especially dangerous time when extra efforts must be made to protect their family from illness. Families will hang various herbs, called Ay Tsao, on their door for protection. The drinking of realgar wine is thought to remove poisons from the body. Hsiang Bao are also worn. These sachets contain various fragrant medicinal herbs thought to protect the wearer from illness.
风俗习惯
端午节最重要的活动是龙舟竞赛，比赛的队伍在热烈的鼓声中划着他们多彩的龙舟前进。这项活动的灵感是来自于当时汨罗江畔的居民，在江中划船救屈原，而这个传统也一直保持了数个世纪。
在端午节时受欢迎的食物就是粽子，粽子是以米包着肉、花生、蛋黄及其它材料，再以竹叶包裹。而粽子的传统则来由于汨罗江边的渔夫，将米丢入江中平息江中的蛟龙，希望他们不要将屈原吃掉。
农历的五月，也就是端午节的这个时节，对中国人而言，除了屈原的故事还有许多其它重要的意义。许多中国人相信五月是一年中容易引发疾病的危险时节，因此必须有许多防备家人生病的措施。许多家庭会将一种特别的植物-艾草挂在门口，作为保护之用，而人们也会挂带香包，它是以含有多种香味的药用植物所做成，也可以保护人们远离疾病。
There is a very famous traditional Chinese story that has a close connection to the Dragon Boat Festival. Once upon a time on E-Mei mountain there lived two snake spirits, White Snake and Green Snake. These snakes, being magical, turned themselves into beautiful maidens and set off on a journey to the West Lake of Hang Zhou.
When they arrived at West Lake they met a man named Xu Xian. White Snake quickly fell in love with Xu Xian and they were soon married. A Buddhist monk, named Fa Hai, warned Xu Xian of his wife's deceptive appearance and suggested to him a plan.
On the day of the Dragon Boat Festival White Snake wished to stay home so as to avoid the Ay Tsao, used for protection from spirits, hanging on the doors of people's houses. Her husband prepared, according to Fa Hai's instruction, some realgar wine, as this was a tradition during the Dragon boat festival. White Snake, thinking her magic would protect her from the effects of the realgar wine accepted a cup. After she drank the wine she became very ill and was barely able to get to her bed.
When her husband came to her side, he found not his wife but a huge white snake. So great was Xu Xian's shock that he fell to the floor dead.
After recovering from the realgar wine and regaining her human form, White Snake was grief-stricken to find her husband dead. She set off on a journey to obtain a potent medicinal herb, which could revive her husband. After returning and reviving her husband with the medicine, she explained to Xu Xian that the white snake he saw was actually a dragon and that this vision was indeed a very good omen. Xu Xain's fears were put to rest for the moment by his wife's fanciful story…
白蛇传
另一个与端午节息息相关的中国传统故事是「白蛇传」。 从前，在伊眉山上有两只蛇精，白蛇与青蛇。这两只蛇精运用法力将自己变成美丽的女子，并到杭州溪湖游玩。
当他们在西湖游玩时，遇到一位名叫许仙的男子，白蛇与许仙很快的相恋并且随即结婚。当时一位名叫法海的和尚，曾经警告许仙注意他妻子惑人的外表，并建议他一个知道真相的计画。 端午节当天，白蛇待加家里以避开人们挂在门上驱邪的艾草，而许仙则依照法海的建议准备了大家在端午节时都会喝的雄黄酒。白蛇自认魔力可以抵挡雄黄酒对他的影响，因此喝了一杯。但是在他喝下那杯酒之后，他却变得精疲力竭，几乎走不到床上。当许仙回到白蛇身边，看到的不是自己美丽的妻子，而是一只巨大的白蛇，许仙震惊不已且跳楼自杀。
当白蛇恢复精力及人形时，他才发现自己丈夫已经身亡，因此白蛇外出寻找能使许仙起死回生的强效药草。许仙在服用药草，并起死回生之后，白蛇告诉许仙他看到的那条白蛇，其实是一只代表吉相的龙。而在那时，许仙也在白蛇引人入胜的故事中将恐惧拋诸脑后…
More at http://www.yeeyi.net/word/zldq/102.html
Dragon Boat Festival（端午节）The Dragon Boat Festival, also called the Duanwu Festival, is celebrated on the fifth day of the fifth month according to the Chinese calendar. For thousands of years, the festival has been marked by eating zong zi (glutinous rice（糯米）wrapped to form a pyramid using bamboo or reed leaves) and racing dragon boats.
The festival is best known for its dragon-boat races, especially in the southern provinces where there are many rivers and lakes. This regatta（赛舟会）commemorates the death of Qu Yuan , an honest minister who is said to have committed suicide by drowning himself in a river.
Qu was a minister of the State of Chu situated in present-day Hunan and Hubei provinces, during the Warring States Period (475-221BC)（战国时期）. He was upright, loyal and highly esteemed for his wise counsel that brought peace and prosperity to the state. However, when a dishonest and corrupt prince vilified Qu, he was disgraced and dismissed from office. Realizing that the country was now in the hands of evil and corrupt officials, Qu grabbed a large stone and leapt into the Miluo River on the fifth day of the fifth month. Nearby fishermen rushed over to try and save him but were unable to even recover his body. Thereafter, the state declined and was eventually conquered by the State of Qin.
The people of Chu who mourned the death of Qu threw rice into the river to feed his ghost every year on the fifth day of the fifth month. But one year, the spirit of Qu appeared and told the mourners that a huge reptile（爬行动物）in the river had stolen the rice. The spirit then advised them to wrap the rice in silk and bind it with five different-colored threads before tossing it into the river.
During the Duanwu Festival, a glutinous rice pudding called zong zi is eaten to symbolize the rice offerings to Qu. Ingredients such as beans, lotus seeds（莲子）, chestnuts（栗子）, pork fat and the golden yolk of a salted duck egg are often added to the glutinous rice. The pudding is then wrapped with bamboo leaves, bound with a kind of raffia and boiled in salt water for hours.
The dragon-boat races symbolize the many attempts to rescue and recover Qu's body. A typical dragon boat ranges from 50-100 feet in length, with a beam of about 5.5 feet, accommodating two paddlers seated side by side.
A wooden dragon head is attached at the bow, and a dragon tail at the stern（船尾）. A banner hoisted on a pole is also fastened at the stern and the hull is decorated with red, green and blue scales edged in gold. In the center of the boat is a canopied shrine behind which the drummers, gong（铜锣）beaters and cymbal（铙钹）players are seated to set the pace for the paddlers. There are also men positioned at the bow to set off firecrackers, toss rice into the water and pretend to be looking for Qu. All of the noise and pageantry creates an atmosphere of gaiety and excitement for the participants and spectators alike. The races are held among different clans, villages and organizations, and the winners are awarded medals, banners, jugs of wine and festive meals.
转自：中国英语网
The Dragon Boat Festival(端午节，字面意思是龙舟节), also called Double Fifth Festival, is celebrated on the fifth day of the fifth moon of the lunar calendar. It is one of the most important Chinese festivals, the other two being the Autumn Moon Festival and Chinese New Year. The origin of this summer festival centers around a scholarly government official named Chu Yuan. He was a good and respected man, but because of the misdeeds of jealous rivals he eventually fell into disfavor in the emperor's court.
Unable to regain the respect of the emperor, in his sorrow Chu Yuan threw himself into the Mi Low river. Because of their admiration for Chu Yuan, the local people living adjacent to the Mi Lo River rushed into their boats to search for him while throwing rice into the waters to appease the river dragons.
Although they were unable to find Chu Yuan, their efforts are still commemorated today during the Dragon Boat Festival.
端午节的由来
端午节，又称为五五节，因为端午节是在农历的五月五日，是三个重要的中国节庆之一，其它两个分别是中秋节和农历新年。 这个节日的由来是古代中国有一位博学多闻的官吏屈原，他是一位爱民而且又受到尊崇的官吏，但是由于一位充满嫉妒的官吏陷害，从此在朝廷中被皇帝所冷落。由于无法获得皇帝的重视，屈原在忧郁的情况下投汨罗江自尽。由于对屈原的爱戴，汨罗江畔的居民匆忙的划船在江内寻找屈原，并且将米丢入汨罗江中，以平息汨罗江中的蛟龙。即使他们当时并没有找到屈原，但是他们的行为，直到今天在端午节的时候，仍然被人们传颂纪念着。
Dragon Boat race Traditions At the center of this festival are the dragon boat races. Competing teams drive their colorful dragon boats forward to the rhythm of beating drums. These exciting races were inspired by the villager's valiant attempts to rescue Chu Yuan from the Mi Lo river. This tradition has remained unbroken for centuries.
Tzung Tzu A very popular dish during the Dragon Boat festival is tzung tzu. This tasty dish consists of rice dumplings with meat, peanut, egg yolk, or other fillings wrapped in bamboo leaves. The tradition of tzung tzu is meant to remind us of the village fishermen scattering rice across the water of the Mi Low river in order to appease the river dragons so that they would not devour Chu Yuan.
Ay Taso The time of year of the Dragon Boat Festival, the fifth lunar moon, has more significance than just the story of Chu Yuan. Many Chinese consider this time of year an especially dangerous time when extra efforts must be made to protect their family from illness. Families will hang various herbs, called Ay Tsao, on their door for protection. The drinking of realgar wine is thought to remove poisons from the body. Hsiang Bao are also worn. These sachets contain various fragrant medicinal herbs thought to protect the wearer from illness.
风俗习惯
端午节最重要的活动是龙舟竞赛，比赛的队伍在热烈的鼓声中划着他们多彩的龙舟前进。这项活动的灵感是来自于当时汨罗江畔的居民，在江中划船救屈原，而这个传统也一直保持了数个世纪。
在端午节时受欢迎的食物就是粽子，粽子是以米包着肉、花生、蛋黄及其它材料，再以竹叶包裹。而粽子的传统则来由于汨罗江边的渔夫，将米丢入江中平息江中的蛟龙，希望他们不要将屈原吃掉。
农历的五月，也就是端午节的这个时节，对中国人而言，除了屈原的故事还有许多其它重要的意义。许多中国人相信五月是一年中容易引发疾病的危险时节，因此必须有许多防备家人生病的措施。许多家庭会将一种特别的植物-艾草挂在门口，作为保护之用，而人们也会挂带香包，它是以含有多种香味的药用植物所做成，也可以保护人们远离疾病。
There is a very famous traditional Chinese story that has a close connection to the Dragon Boat Festival. Once upon a time on E-Mei mountain there lived two snake spirits, White Snake and Green Snake. These snakes, being magical, turned themselves into beautiful maidens and set off on a journey to the West Lake of Hang Zhou.
When they arrived at West Lake they met a man named Xu Xian. White Snake quickly fell in love with Xu Xian and they were soon married. A Buddhist monk, named Fa Hai, warned Xu Xian of his wife's deceptive appearance and suggested to him a plan.
On the day of the Dragon Boat Festival White Snake wished to stay home so as to avoid the Ay Tsao, used for protection from spirits, hanging on the doors of people's houses. Her husband prepared, according to Fa Hai's instruction, some realgar wine, as this was a tradition during the Dragon boat festival. White Snake, thinking her magic would protect her from the effects of the realgar wine accepted a cup. After she drank the wine she became very ill and was barely able to get to her bed.
When her husband came to her side, he found not his wife but a huge white snake. So great was Xu Xian's shock that he fell to the floor dead.
After recovering from the realgar wine and regaining her human form, White Snake was grief-stricken to find her husband dead. She set off on a journey to obtain a potent medicinal herb, which could revive her husband. After returning and reviving her husband with the medicine, she explained to Xu Xian that the white snake he saw was actually a dragon and that this vision was indeed a very good omen. Xu Xain's fears were put to rest for the moment by his wife's fanciful story…
白蛇传
另一个与端午节息息相关的中国传统故事是「白蛇传」。 从前，在伊眉山上有两只蛇精，白蛇与青蛇。这两只蛇精运用法力将自己变成美丽的女子，并到杭州溪湖游玩。
当他们在西湖游玩时，遇到一位名叫许仙的男子，白蛇与许仙很快的相恋并且随即结婚。当时一位名叫法海的和尚，曾经警告许仙注意他妻子惑人的外表，并建议他一个知道真相的计画。 端午节当天，白蛇待加家里以避开人们挂在门上驱邪的艾草，而许仙则依照法海的建议准备了大家在端午节时都会喝的雄黄酒。白蛇自认魔力可以抵挡雄黄酒对他的影响，因此喝了一杯。但是在他喝下那杯酒之后，他却变得精疲力竭，几乎走不到床上。当许仙回到白蛇身边，看到的不是自己美丽的妻子，而是一只巨大的白蛇，许仙震惊不已且跳楼自杀。
当白蛇恢复精力及人形时，他才发现自己丈夫已经身亡，因此白蛇外出寻找能使许仙起死回生的强效药草。许仙在服用药草，并起死回生之后，白蛇告诉许仙他看到的那条白蛇，其实是一只代表吉相的龙。而在那时，许仙也在白蛇引人入胜的故事中将恐惧拋诸脑后…
More at http://www.yeeyi.net/word/zldq/102.html
Dragon Boat Festival（端午节）The Dragon Boat Festival, also called the Duanwu Festival, is celebrated on the fifth day of the fifth month according to the Chinese calendar. For thousands of years, the festival has been marked by eating zong zi (glutinous rice（糯米）wrapped to form a pyramid using bamboo or reed leaves) and racing dragon boats.
The festival is best known for its dragon-boat races, especially in the southern provinces where there are many rivers and lakes. This regatta（赛舟会）commemorates the death of Qu Yuan , an honest minister who is said to have committed suicide by drowning himself in a river.
Qu was a minister of the State of Chu situated in present-day Hunan and Hubei provinces, during the Warring States Period (475-221BC)（战国时期）. He was upright, loyal and highly esteemed for his wise counsel that brought peace and prosperity to the state. However, when a dishonest and corrupt prince vilified Qu, he was disgraced and dismissed from office. Realizing that the country was now in the hands of evil and corrupt officials, Qu grabbed a large stone and leapt into the Miluo River on the fifth day of the fifth month. Nearby fishermen rushed over to try and save him but were unable to even recover his body. Thereafter, the state declined and was eventually conquered by the State of Qin.
The people of Chu who mourned the death of Qu threw rice into the river to feed his ghost every year on the fifth day of the fifth month. But one year, the spirit of Qu appeared and told the mourners that a huge reptile（爬行动物）in the river had stolen the rice. The spirit then advised them to wrap the rice in silk and bind it with five different-colored threads before tossing it into the river.
During the Duanwu Festival, a glutinous rice pudding called zong zi is eaten to symbolize the rice offerings to Qu. Ingredients such as beans, lotus seeds（莲子）, chestnuts（栗子）, pork fat and the golden yolk of a salted duck egg are often added to the glutinous rice. The pudding is then wrapped with bamboo leaves, bound with a kind of raffia and boiled in salt water for hours.
The dragon-boat races symbolize the many attempts to rescue and recover Qu's body. A typical dragon boat ranges from 50-100 feet in length, with a beam of about 5.5 feet, accommodating two paddlers seated side by side.
A wooden dragon head is attached at the bow, and a dragon tail at the stern（船尾）. A banner hoisted on a pole is also fastened at the stern and the hull is decorated with red, green and blue scales edged in gold. In the center of the boat is a canopied shrine behind which the drummers, gong（铜锣）beaters and cymbal（铙钹）players are seated to set the pace for the paddlers. There are also men positioned at the bow to set off firecrackers, toss rice into the water and pretend to be looking for Qu. All of the noise and pageantry creates an atmosphere of gaiety and excitement for the participants and spectators alike. The races are held among different clans, villages and organizations, and the winners are awarded medals, banners, jugs of wine and festive meals.
Visual Understanding of Higher-Order Kernels
Visual Understanding of Higher-Order Kernels
Author(s): J. S. MarronSource: Journal of Computational and Graphical Statistics, Vol. 3, No. 4 (Dec., 1994), pp. 447-458
Published by: American Statistical Association, Institute of Mathematical Statistics, andInterface Foundation of America
Stable URL: http://www.jstor.org/stable/1390905
Author(s): J. S. MarronSource: Journal of Computational and Graphical Statistics, Vol. 3, No. 4 (Dec., 1994), pp. 447-458
Published by: American Statistical Association, Institute of Mathematical Statistics, andInterface Foundation of America
Stable URL: http://www.jstor.org/stable/1390905
Computationally Efficient Classes of Higher-Order Kernel Functions
Computationally Efficient Classes of Higher-Order Kernel Functions
Author(s): Belkacem Abdous
Source: The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 23, No. 1(Mar., 1995), pp. 21-27
Published by: Statistical Society of CanadaStable URL: http://www.jstor.org/stable/3315548
Author(s): Belkacem Abdous
Source: The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 23, No. 1(Mar., 1995), pp. 21-27
Published by: Statistical Society of CanadaStable URL: http://www.jstor.org/stable/3315548
Biometrika Centenary: Nonparametrics
Author(s): Peter Hall
Source: Biometrika, Vol. 88, No. 1 (Mar., 2001), pp. 143-165
Published by: Biometrika
TrustStable URL: http://www.jstor.org/stable/2673677
Peter Hall has reviewed the contribution of Biometricka to the development in the Nonparametircs literature.
Source: Biometrika, Vol. 88, No. 1 (Mar., 2001), pp. 143-165
Published by: Biometrika
TrustStable URL: http://www.jstor.org/stable/2673677
Peter Hall has reviewed the contribution of Biometricka to the development in the Nonparametircs literature.
Thursday, May 28, 2009
Wednesday, May 27, 2009
Finite sample theory: A discussion
9:59 PM Amy: about Prof. Ullah's paper last Friday, what's the main point? Have he and Yongbao developed some estimation even when the error term is nonnormal?
Yundong Tu to Amy show details 10:18 PM (19 hours ago) Reply
Their papers are not to develope estimation result but to provide finite sample approximation for higher order moments of the estimators ( estimators, say beta hat, are taken as given, which can be MLE, GMM, IV, LS, etc.). The other paper is about expectation of quadradict form. They also provide finite sample approximation for these terms. Finite sample approximation differs when the error terms are nonnormally distributed from normally distributed case. These approximation results, however, could be used to study the properties of some other estimators, for example, the estimator of rho in the spatial autoregressive model, or the estimators of the coefficients in the MA or AR models.
10:29 PM Amy: so when error tems are nonnormal, we can still estimate the coefficients such as in VAR models. What 's the difference between this way and other methods approximating nonnormal errors to a normal distribution?
10:31 PM me: yes, you still can estimate using the same method as if the error term is normal
Amy: in Ullah's way?
me: no the classical way he is sillent about the estimation approach he is only concerned with the moments of the estimators
10:32 PM which is not quite a concern in macro, i think
Amy: but you say we can still estimate the coefficients me: yes
Amy: That's what I am considering
me: but we do not know the higher oder moments the properties of that is provided by Ullah and Bao
10:33 PM Amy: when the error term is nonnormal, could we use some methods of finite sample to estimate> Since they mention the MLE
me: finite sample is not to estimate the coefficients but to approximate higher order moments, say skewness and kurtosis of the estimators
10:34 PM Amy: I see. I am not familiar with finte sample
me: yes, you can still use MLE, GMM, IV and LS, etc. for the estimation purpose but once you get these estimators, you might be interested in its higher order properties the estimator you get would be not normally distributed
10:35 PM especially when the error term is not normally distributed and when the sample is small or even moderate large not even close to normal
Amy: I c.
me: finite sample approach is one method to tell how far is your estimator from a normal random variable
10:36 PM typical way to examine this is to check the property of skewness and kurtosis and see how far they are from those of normal distribution
10:37 PM in large sample, everything (estimator) is normally distributed, so there is no difference but what we have usually is not large sample observations
10:38 PM this leaves a room for finite sample theory to improve upon the large sample theory to get more accurate properties of the estimators we derived
Amy: But what will we do if we find the estimator is not normal distribution?
10:39 PM me: we impose finite sample corrections then
10:41 PM you know that for normally distributed random variable, skewness is zero and kurtosis is 3. if it is not normally distributed Ullah and Bao provide formula for those, which should also be used when sample size is small
10:42 PM Amy: I know that. But how to corret them?
10:43 PM me: use the fomula in Ullah and Bao for Skewness and Kurtosis
Amy: and then?
me: In Ullah's book, there should be fomula for mean and variance
10:45 PM Amy: I see. Maybe I should read the book firstly. But is there any way to use this correction way for estimation?
me: no it is not for estimation of the coefficient in econometric models like y=xb+e
10:46 PM their method is silent about the estimation approach, as i said earlier it can be used for a general class of estimators called extremum estimators
10:47 PM Amy: I c. Thank you. me: their approximation result depends on the following assumption sqrt(n)(bhat-b) converges to a normal distribution it's a pleasure
10:48 PM Amy: see. Thanks a million~~ I am looking at your pics in picasa
10:49 PM me: :)
10:51 PM Amy: ok, night~~ good dream.
me: u2
Yundong Tu to Amy show details 10:18 PM (19 hours ago) Reply
Their papers are not to develope estimation result but to provide finite sample approximation for higher order moments of the estimators ( estimators, say beta hat, are taken as given, which can be MLE, GMM, IV, LS, etc.). The other paper is about expectation of quadradict form. They also provide finite sample approximation for these terms. Finite sample approximation differs when the error terms are nonnormally distributed from normally distributed case. These approximation results, however, could be used to study the properties of some other estimators, for example, the estimator of rho in the spatial autoregressive model, or the estimators of the coefficients in the MA or AR models.
10:29 PM Amy: so when error tems are nonnormal, we can still estimate the coefficients such as in VAR models. What 's the difference between this way and other methods approximating nonnormal errors to a normal distribution?
10:31 PM me: yes, you still can estimate using the same method as if the error term is normal
Amy: in Ullah's way?
me: no the classical way he is sillent about the estimation approach he is only concerned with the moments of the estimators
10:32 PM which is not quite a concern in macro, i think
Amy: but you say we can still estimate the coefficients me: yes
Amy: That's what I am considering
me: but we do not know the higher oder moments the properties of that is provided by Ullah and Bao
10:33 PM Amy: when the error term is nonnormal, could we use some methods of finite sample to estimate> Since they mention the MLE
me: finite sample is not to estimate the coefficients but to approximate higher order moments, say skewness and kurtosis of the estimators
10:34 PM Amy: I see. I am not familiar with finte sample
me: yes, you can still use MLE, GMM, IV and LS, etc. for the estimation purpose but once you get these estimators, you might be interested in its higher order properties the estimator you get would be not normally distributed
10:35 PM especially when the error term is not normally distributed and when the sample is small or even moderate large not even close to normal
Amy: I c.
me: finite sample approach is one method to tell how far is your estimator from a normal random variable
10:36 PM typical way to examine this is to check the property of skewness and kurtosis and see how far they are from those of normal distribution
10:37 PM in large sample, everything (estimator) is normally distributed, so there is no difference but what we have usually is not large sample observations
10:38 PM this leaves a room for finite sample theory to improve upon the large sample theory to get more accurate properties of the estimators we derived
Amy: But what will we do if we find the estimator is not normal distribution?
10:39 PM me: we impose finite sample corrections then
10:41 PM you know that for normally distributed random variable, skewness is zero and kurtosis is 3. if it is not normally distributed Ullah and Bao provide formula for those, which should also be used when sample size is small
10:42 PM Amy: I know that. But how to corret them?
10:43 PM me: use the fomula in Ullah and Bao for Skewness and Kurtosis
Amy: and then?
me: In Ullah's book, there should be fomula for mean and variance
10:45 PM Amy: I see. Maybe I should read the book firstly. But is there any way to use this correction way for estimation?
me: no it is not for estimation of the coefficient in econometric models like y=xb+e
10:46 PM their method is silent about the estimation approach, as i said earlier it can be used for a general class of estimators called extremum estimators
10:47 PM Amy: I c. Thank you. me: their approximation result depends on the following assumption sqrt(n)(bhat-b) converges to a normal distribution it's a pleasure
10:48 PM Amy: see. Thanks a million~~ I am looking at your pics in picasa
10:49 PM me: :)
10:51 PM Amy: ok, night~~ good dream.
me: u2
Tuesday, May 26, 2009
An interesting corelation question
Today, I was confronted by an interesting macroeconomic question, which turns out to be a statistical question. The setup of the question is as follows: say x, and z are procyclical for y (output), that is, cov(x,y)>0 and cov(z,y)>0. Is it possible that cov(x,z)<0? If it is, find out the conditions for this to hold. Note that the covariance operator only captures the linear relationship while the nonlinear relationship is here to paly a role to make x and z negatively related. The solution would simplify once we assume that y is a symmetrically distributed random variable with mean zero. Also, the relationship between x and y and that between z and y are charactorized by x=f(y), z=g(y), respectively. Assuming f() and g() having zero derivatives for order higher than 2 will easily give the following condition for cov(x,z)<0 to hold:
00 and g'>0.
That is, the curvature of f and g must be different, with one being convex and the other being concave. Other than this, we need have abs(f ''(0)g''(0)) very large or y with high kurtosis for the condition to hold.
0
That is, the curvature of f and g must be different, with one being convex and the other being concave. Other than this, we need have abs(f ''(0)g''(0)) very large or y with high kurtosis for the condition to hold.
Monday, May 25, 2009
Saturday, May 23, 2009
A Future Role for the Econometric Society in International Statistics
Charles F. Roos
Econometrica, Vol. 16, No. 2 (Apr., 1948), pp. 127-134
Published by: The Econometric Society A Future Role for the Econometric Society in International Statistics
Econometrica, Vol. 16, No. 2 (Apr., 1948), pp. 127-134
Published by: The Econometric Society A Future Role for the Econometric Society in International Statistics
The Economics of Star Trek
The new movie Star Trek was commented by Mankiw regarding its use of economic terms: excludable and rival. See Mankiw's Blog
Thursday, May 21, 2009
Finite-Sample Asymptotics
Small Sample Asymptotics
Author(s): Michael A. FlignerSource: Journal of Educational Statistics, Vol. 13, No. 1 (Spring, 1988), pp. 53-61
Author(s): Michael A. FlignerSource: Journal of Educational Statistics, Vol. 13, No. 1 (Spring, 1988), pp. 53-61
Tuesday, May 19, 2009
Vector Generalized Linear and Additive Models
The litteratur that is new to econometricans has already there in statistics, with link
http://www.iq.harvard.edu/blog/sss/archives/2009/04/yee_on_vector_g.shtml
Thomas Yee's abstract of the article is also given at the above link.
http://www.iq.harvard.edu/blog/sss/archives/2009/04/yee_on_vector_g.shtml
Thomas Yee's abstract of the article is also given at the above link.
Fisher's exact test
Fisher's exact test is described at
http://en.wikipedia.org/wiki/Fisher's_exact_test
with references
Fisher, R. A. (1922). "On the interpretation of χ2 from contingency tables, and the calculation of P". Journal of the Royal Statistical Society 85 (1): 87–94. JSTOR: 2340521.
Fisher, R. A. 1954 Statistical Methods for Research Workers. Oliver and Boyd.
^ Mehta, Cyrus R; Patel, Nitin R; Tsiatis, Anastasios A (1984), "Exact significance testing to establish treatment equivalence with ordered categorical data", Biometrics 40: 819–825, doi:10.2307/2530927, http://www.jstor.org/stable/2530927
^ Mehta, C. R. 1995. SPSS 6.1 Exact test for Windows. Englewood Cliffs, NJ: Prentice Hall.
^ mathworld.wolfram.com Page giving the formula for the general form of Fisher's exact test for m x n contingency tables
Andrew Gelman wrote a blog about it and introduces some of his work,
http://www.stat.columbia.edu/~cook/movabletype/archives/2009/05/i_hate_the_so-c.html
http://en.wikipedia.org/wiki/Fisher's_exact_test
with references
Fisher, R. A. (1922). "On the interpretation of χ2 from contingency tables, and the calculation of P". Journal of the Royal Statistical Society 85 (1): 87–94. JSTOR: 2340521.
Fisher, R. A. 1954 Statistical Methods for Research Workers. Oliver and Boyd.
^ Mehta, Cyrus R; Patel, Nitin R; Tsiatis, Anastasios A (1984), "Exact significance testing to establish treatment equivalence with ordered categorical data", Biometrics 40: 819–825, doi:10.2307/2530927, http://www.jstor.org/stable/2530927
^ Mehta, C. R. 1995. SPSS 6.1 Exact test for Windows. Englewood Cliffs, NJ: Prentice Hall.
^ mathworld.wolfram.com Page giving the formula for the general form of Fisher's exact test for m x n contingency tables
Andrew Gelman wrote a blog about it and introduces some of his work,
http://www.stat.columbia.edu/~cook/movabletype/archives/2009/05/i_hate_the_so-c.html
College is also part of consumption
Econjeff wrote a blog which share the same idea I have had since 2006. The article is available at
http://econjeff.blogspot.com/2009/05/college-as-consumption.html
So given the fact that the return on the ivestment in college is less than the cost, Chinese people are still rational to maximize their utility. This argument kills the debate whether it is worthwhile to go to college or not that prevailing in the last few years.
http://econjeff.blogspot.com/2009/05/college-as-consumption.html
So given the fact that the return on the ivestment in college is less than the cost, Chinese people are still rational to maximize their utility. This argument kills the debate whether it is worthwhile to go to college or not that prevailing in the last few years.
Monday, May 18, 2009
The deterioration continues
James D. Hamilton, Econbrowser
http://www.econbrowser.com/archives/2009/05/the_deteriorati.html
http://www.econbrowser.com/archives/2009/05/the_deteriorati.html
Asymmetric Loss Functions
Optimal prediction under asymmetric loss: Christoffersen, FX Diebold - Econometric Theory, 1997 - jstor.org
Further results on forecasting and model selection under asymmetric loss: Christoffersen, FX Diebold - Journal of Applied Econometrics, 1996 - jstor.org
Financial Asset Returns, Direction-of-Change Forecasting, and ... :Christoffersen, FX Diebold - Management Science, 2006
Further results on forecasting and model selection under asymmetric loss: Christoffersen, FX Diebold - Journal of Applied Econometrics, 1996 - jstor.org
Financial Asset Returns, Direction-of-Change Forecasting, and ... :Christoffersen, FX Diebold - Management Science, 2006
Friday, May 15, 2009
Normal distribution and dependence
Normally distributed and uncorrelated does not imply independent
http://en.wikipedia.org/wiki/Normally_distributed_and_uncorrelated_does_not_imply_independent
A counterexample
The fact that two random variables X and Y both have a normal distribution does not imply that the pair (X, Y) has a joint normal distribution. A simple example is one in which Y = X if X > 1 and Y = −X if X < 1.
http://en.wikipedia.org/wiki/Multivariate_normal_distribution
http://en.wikipedia.org/wiki/Normally_distributed_and_uncorrelated_does_not_imply_independent
A counterexample
The fact that two random variables X and Y both have a normal distribution does not imply that the pair (X, Y) has a joint normal distribution. A simple example is one in which Y = X if X > 1 and Y = −X if X < 1.
http://en.wikipedia.org/wiki/Multivariate_normal_distribution
Perturbation methods
Chapter II: Introduction to perturbation methods by Johan Byström, Lars-Erik Persson, and Fredrik Strömberg
Introduction to regular perturbation theory by Eric Vanden-Eijnden (PDF)
Duality in Perturbation Theory
Perturbation Method of Multiple Scales
Retrieved from "http://en.wikipedia.org/wiki/Perturbation_theory"
Introduction to regular perturbation theory by Eric Vanden-Eijnden (PDF)
Duality in Perturbation Theory
Perturbation Method of Multiple Scales
Retrieved from "http://en.wikipedia.org/wiki/Perturbation_theory"
Wednesday, May 13, 2009
Hotelling, Harold, 1895-1973
Leading mathematical economists, also known as mathematical statistician. Famous in economics for his Hotelling's Lemma and in statistics for his T_squared statistic.
The teaching of statistics and probability, Statistical Science 3 (1) (1988), 63-71 reprinted from Annals of Mathematical Statistics 11 (1940), 457-470.
The place of statistics in the university, Statistical Science 3 (1) (1988), 72-83 reprinted from Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability (ed. J Neyman), Berkeley: California U. Press 1949, pp. 21-40.
Comment: Academic politics and the teaching of statistics, Statistical Science 3 (1) (1988), 92-95
Harold Hotelling 1895-1973 by Adrian C Darnell Statistical Science 3 (1) (1988), 57-62.
The teaching of statistics and probability, Statistical Science 3 (1) (1988), 63-71 reprinted from Annals of Mathematical Statistics 11 (1940), 457-470.
The place of statistics in the university, Statistical Science 3 (1) (1988), 72-83 reprinted from Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability (ed. J Neyman), Berkeley: California U. Press 1949, pp. 21-40.
Comment: Academic politics and the teaching of statistics, Statistical Science 3 (1) (1988), 92-95
Harold Hotelling 1895-1973 by Adrian C Darnell Statistical Science 3 (1) (1988), 57-62.
Kolmogorov, Andrei Nikolaevich, 1903-1987
(``Andrei Nikolaevich Kolmogorov,'' CWI Quarterly, 1(1988), pp. 3-18.) by Paul M.B. Vitanyi, CWI and University of Amsterdam
Andrei Nikolaevich Kolmogorov, born 25 April 1903 in Tambov, Russia, died 20 October 1987 in Moscow. He was perhaps the foremost contemporary Soviet mathematician and counts as one of the great mathematicians of this century. His many creative and fundamental contributions to a vast variety of mathematical fields are so wide-ranging that I cannot even attempt to treat them either completely or in any detail. For now let me mention a non-exhaustive list of areas he enriched by his fundamental research: The theory of trigonometric series, measure theory, set theory, the theory of integration, constructive logic (intuitionism), topology, approximation theory, probability theory, the theory of random processes, information theory, mathematical statistics, dynamical systems, automata theory, theory of algorithms, mathematical linguistics, turbulence theory, celestial mechanics, differential equations, Hilbert's 13th problem, ballistics, and applications of mathematics to problems of biology, geology, and the crystallization of metals.
Full Article
More about Kolmogorov
Site devoted to the life and work of Kolmogorov
Andrei Nikolaevich Kolmogorov, born 25 April 1903 in Tambov, Russia, died 20 October 1987 in Moscow. He was perhaps the foremost contemporary Soviet mathematician and counts as one of the great mathematicians of this century. His many creative and fundamental contributions to a vast variety of mathematical fields are so wide-ranging that I cannot even attempt to treat them either completely or in any detail. For now let me mention a non-exhaustive list of areas he enriched by his fundamental research: The theory of trigonometric series, measure theory, set theory, the theory of integration, constructive logic (intuitionism), topology, approximation theory, probability theory, the theory of random processes, information theory, mathematical statistics, dynamical systems, automata theory, theory of algorithms, mathematical linguistics, turbulence theory, celestial mechanics, differential equations, Hilbert's 13th problem, ballistics, and applications of mathematics to problems of biology, geology, and the crystallization of metals.
Full Article
More about Kolmogorov
Site devoted to the life and work of Kolmogorov
Friday, May 8, 2009
R-np package
The following are from Racine's webpage:
Software
The np package (current version 0.30-1) for R (www.r-project.org) Obtaining: Available directly from the Comprehensive R Archive Network (cran.r-project.org)
Direct link to the np package on CRAN
Announcement on the R-packages mailing list
October 2007 Rnews article (pdf)
Manual (pdf)Vignette (pdf)FAQ (pdf) (html)
Software
The np package (current version 0.30-1) for R (www.r-project.org) Obtaining: Available directly from the Comprehensive R Archive Network (cran.r-project.org)
Direct link to the np package on CRAN
Announcement on the R-packages mailing list
October 2007 Rnews article (pdf)
Manual (pdf)Vignette (pdf)FAQ (pdf) (html)
Nonparametric Econometrics: A Primer
Racine, J. S. (2008), "Nonparametric Econometrics: A Primer," Foundations and Trends in Econometrics: Vol. 3: No 1, pp 1-88. http://dx.doi.org/10.1561/0800000009
Wednesday, May 6, 2009
Jefferey Racine is Visiting UCR on May 7th and 8th
The world's most well-known computational/Nonparametric Econometrician, Jefferey Racine, a prior student of Aman Ullah, is visiting UCR on May 7th and 8th. Racine is known already for his nonparamtric-package in R, beside his nonparametric book, Nonparamtric Econometrics---Theory and Practice, written together with Qi Li.
This time he will present a paper on economic constraints in nonparametric modelling. His visit to US including UCLA, UCSD and UCR. Although he has visited UCR for several times, his coming this time is highly appreciated and expected.
This time he will present a paper on economic constraints in nonparametric modelling. His visit to US including UCLA, UCSD and UCR. Although he has visited UCR for several times, his coming this time is highly appreciated and expected.
Behave as an Econometrician
Dream of being an Econometrican? Look at what they do, as follows,
1. Study Economics
2. Develope Econometric tools
3. Reading econometric journal articles
4. Learning mathematics and statistics
5. Improve programming skills
6. Go to seminars and comment on others work
7. Referee journal articles
8. Reading history of Econometrics
9. Teach econometrics in a way that could be understood to child and the old as well
10. Go to conferences and present papers
11. Educate young economics Ph. D. students
12. Sell Econometrics to applied economists, financialists, government agents and other institutions as well
13. Travel for tour sight-seeing
14. Help to develope economic research centers and institutes
15. Provide deeper insight into economic questions
16. Writing and publishing articles on top journals
17. Passing down anecdotes of great econometricans to the next generations
18. Create their own history of contributing to a better/more desirable world to live
19. Talk and write in symbols
20. Enjoy their lives with their families
21. Invest their time and money in a way to minimize SSR
22. Estimate whatever they do not know
23. Live on statistics and produce statistics as well
24. Being smart everyday
25. Ask quantitive questions
26. Writing books for the young and others interested
27. Welcomed everywhere except by those economists in history
28. Great heros
Not enough? Add more to the list!
1. Study Economics
2. Develope Econometric tools
3. Reading econometric journal articles
4. Learning mathematics and statistics
5. Improve programming skills
6. Go to seminars and comment on others work
7. Referee journal articles
8. Reading history of Econometrics
9. Teach econometrics in a way that could be understood to child and the old as well
10. Go to conferences and present papers
11. Educate young economics Ph. D. students
12. Sell Econometrics to applied economists, financialists, government agents and other institutions as well
13. Travel for tour sight-seeing
14. Help to develope economic research centers and institutes
15. Provide deeper insight into economic questions
16. Writing and publishing articles on top journals
17. Passing down anecdotes of great econometricans to the next generations
18. Create their own history of contributing to a better/more desirable world to live
19. Talk and write in symbols
20. Enjoy their lives with their families
21. Invest their time and money in a way to minimize SSR
22. Estimate whatever they do not know
23. Live on statistics and produce statistics as well
24. Being smart everyday
25. Ask quantitive questions
26. Writing books for the young and others interested
27. Welcomed everywhere except by those economists in history
28. Great heros
Not enough? Add more to the list!
Saturday, May 2, 2009
Seashells: the Plainness and Beauty of Their Mathematical Description
by Jorge Picado
Departamento de Matemática
Universidade de Coimbra
picado@mat.uc.pt
Fulltext
Abstract:
One might at first tend to think that the growth of plants and animals, because of their elaborate forms, are ruled by highly complex laws. However, this is surprisingly not always true: many aspects of the growth of plants and animals may be described by remarkably simple mathematical laws. An obvious example of this are the seashells and snails, as we show here: with a very simple model it is possible to describe and generate any of the many types of seashells that one may find classified in a good seashell bookguide. The fact that the animal which lives at the open edge of the shell places new shell material always in that edge, and faster on one side than the other, makes the shell to grow in a spiral. The rates at which shell material is secreted at different points of the open edge are presumably determined by the anatomy of the animal. And, surprisingly, even fairly small changes in such rates can have quite tremendous effects on the overall shape of the shell, which is in the origin of the existence of a great diversity of shells.
Departamento de Matemática
Universidade de Coimbra
picado@mat.uc.pt
Fulltext
Abstract:
One might at first tend to think that the growth of plants and animals, because of their elaborate forms, are ruled by highly complex laws. However, this is surprisingly not always true: many aspects of the growth of plants and animals may be described by remarkably simple mathematical laws. An obvious example of this are the seashells and snails, as we show here: with a very simple model it is possible to describe and generate any of the many types of seashells that one may find classified in a good seashell bookguide. The fact that the animal which lives at the open edge of the shell places new shell material always in that edge, and faster on one side than the other, makes the shell to grow in a spiral. The rates at which shell material is secreted at different points of the open edge are presumably determined by the anatomy of the animal. And, surprisingly, even fairly small changes in such rates can have quite tremendous effects on the overall shape of the shell, which is in the origin of the existence of a great diversity of shells.
The ET Interview: Professor H. O. A. Wold: 1908-1992 The ET Interview: Professor H. O. A. Wold: 1908-1992
David F. Hendry, Mary S. Morgan, H. O. A. Wold
Econometric Theory, Vol. 10, No. 2 (Jun., 1994), pp. 419-433
Sadly, Herman Wold died on February 16, 1992, before agreeing to the final version of this interview. We are indebted to his son, Professor Svante Wold, for his kind permission to publish. We hope that this record of our discussions with Herman Wold, who, together with his two great Norwe- gian compatriots Ragnar Frisch and Trygve Haavelmo, helped lay the sta- tistical foundations of modern econometrics, will contribute to his memory. From our personal perspective, Herman Wold was an enthusiastic suppor- ter of our early incursions into the history of econometrics (see The History of Econometric Ideas by Mary Morgan, 1990), and we know that there are many like us who will greatly miss his stimulating contributions. Herman Wold was born on Christmas day, 1908, at Skien, Norway. His family moved to a small town outside Stockholm in 1912, and he lived in Sweden for the remainder of his life. He enrolled at Stockholm University in 1927 to study physics, mathematics, and economics but switched to study- ing statistics with Harald Cramer. After his undergraduate degree, he stud- ied the theory of risk with Cramer, then worked for an insurance company for a period, returning to Stockholm University in 1936. His doctoral the- sis of 1938, A Study in the Analysis of Stationary Time Series, embodies the famous Wold Decomposition theorem. In 1942, he moved to the Chair of Statistics in Uppsala and held that post until 1970, when he went to Goteborg for five years, finally becoming Professor Emeritus at Uppsala in 1975. He became a Fellow and later President of the Econometric Society; was Vice-President of the International Statistical Institute; a Foreign Honor- ary Member of both the American Economic Association and the Ameri- can Academy of Arts and Sciences; an Honorary Fellow of the Royal Statistical Society; a member of the Swedish Royal Academy of Sciences, serving on the Nobel Prize Committee in Economics from 1968 until 1980; and was the recipient of several honorary doctorates. In retirement, he was Professeur Invite at the University of Geneva until 1980.
Econometric Theory, Vol. 10, No. 2 (Jun., 1994), pp. 419-433
Sadly, Herman Wold died on February 16, 1992, before agreeing to the final version of this interview. We are indebted to his son, Professor Svante Wold, for his kind permission to publish. We hope that this record of our discussions with Herman Wold, who, together with his two great Norwe- gian compatriots Ragnar Frisch and Trygve Haavelmo, helped lay the sta- tistical foundations of modern econometrics, will contribute to his memory. From our personal perspective, Herman Wold was an enthusiastic suppor- ter of our early incursions into the history of econometrics (see The History of Econometric Ideas by Mary Morgan, 1990), and we know that there are many like us who will greatly miss his stimulating contributions. Herman Wold was born on Christmas day, 1908, at Skien, Norway. His family moved to a small town outside Stockholm in 1912, and he lived in Sweden for the remainder of his life. He enrolled at Stockholm University in 1927 to study physics, mathematics, and economics but switched to study- ing statistics with Harald Cramer. After his undergraduate degree, he stud- ied the theory of risk with Cramer, then worked for an insurance company for a period, returning to Stockholm University in 1936. His doctoral the- sis of 1938, A Study in the Analysis of Stationary Time Series, embodies the famous Wold Decomposition theorem. In 1942, he moved to the Chair of Statistics in Uppsala and held that post until 1970, when he went to Goteborg for five years, finally becoming Professor Emeritus at Uppsala in 1975. He became a Fellow and later President of the Econometric Society; was Vice-President of the International Statistical Institute; a Foreign Honor- ary Member of both the American Economic Association and the Ameri- can Academy of Arts and Sciences; an Honorary Fellow of the Royal Statistical Society; a member of the Swedish Royal Academy of Sciences, serving on the Nobel Prize Committee in Economics from 1968 until 1980; and was the recipient of several honorary doctorates. In retirement, he was Professeur Invite at the University of Geneva until 1980.
Thursday, April 30, 2009
Incidental Prameter Problem
Neyman and Scott (1948) have noticed this problem in statistics and econometrics more than 50 years ago and their paper titled 'Consistent estimates based on partially consistent observations' was published in Econometrica. It incites researches over this topic in both economics and other natural science subjects, besides Bayesian and Conditional frequentist approach developed in Statistics literature. Lancaster reviewed the development up to 2000 and cast new insight into this problem.
Consistent Estimates Based on Partially Consistent Observations
J. Neyman and Elizabeth L. Scott
Econometrica, Vol. 16, No. 1 (Jan., 1948), pp. 1-32
The incidental parameter problem since 1948
Tony Lancaster
Journal of EconometricsVolume 95, Issue 2, April 2000, Pages 391-413
Consistent Estimates Based on Partially Consistent Observations
J. Neyman and Elizabeth L. Scott
Econometrica, Vol. 16, No. 1 (Jan., 1948), pp. 1-32
The incidental parameter problem since 1948
Tony Lancaster
Journal of EconometricsVolume 95, Issue 2, April 2000, Pages 391-413
Sunday, April 26, 2009
On The Economy, Obama Gets Mixed Marks
On Wednesday, President Obama will have been in office for 100 days. All this week, NPR is looking at the new administration and measuring its progress against the goals and benchmarks Obama himself laid out.
The president's most immediate challenge as he took office was finding a way to stabilize the economy and lift it out of a severe recession.
More at NPR.org
The president's most immediate challenge as he took office was finding a way to stabilize the economy and lift it out of a severe recession.
More at NPR.org
Yongmiao Hong is visiting UCR on April 27th and 28th
Yongmiao Hong at Cornell is visiting UCR as a distinguished visitor on 27th and 28th. He will give a lecture on Nonparametric Financial Economics, besides a seminar talk.
See: www.economics.ucr.edu
See: www.economics.ucr.edu
Celebrating Four Years Of 'This I Believe'
One of NPR's best programs has gone through four years. 'This I Believe' tells story of what a normal being's personal belief and experience with the belief.
During its four years on NPR, This I Believe engaged listeners in a discussion of the core beliefs that guide their daily lives. We heard from people of all walks of life — the very young and the very old, the famous and the previously unknown, Nobel laureates, teachers, prison inmates, students, politicians, farmers, poets, entrepreneurs, activists and executives.
View at THIS I BELIEVE.
During its four years on NPR, This I Believe engaged listeners in a discussion of the core beliefs that guide their daily lives. We heard from people of all walks of life — the very young and the very old, the famous and the previously unknown, Nobel laureates, teachers, prison inmates, students, politicians, farmers, poets, entrepreneurs, activists and executives.
View at THIS I BELIEVE.
Thursday, April 23, 2009
The ET Interview: Gregory C. Chow
Author(s): Adrian Pagan and Gregory C. Chow
Source: Econometric Theory, Vol. 11, No. 3 (Aug., 1995), pp. 597-624
Gregory Chow has been an important figure in econometrics for almost four decades. There can be few students of quantitative economics who have not been taught the "Chow test" for structural change in regression and equally few applied studies that do not report it. But Gregory's work has been much broader than this-techniques developed in papers on the stock adjustment model, dynamic responses, and control methods have all become part of the milieu of the practicing econometrician. It is notable that this work has never been "theory for theory's sake"; behind it has always been the desire to fash- ion tools that would be immediately useful for the analysis of economic data. It has also been strongly oriented toward the analysis of systems, and his interest in systems has played itself out in many ways -from simulta- neous equation estimation and analysis through control methods to prob- lems of the Chinese economy. There can be few econometricians who have made contributions across such a wide spectrum of issues.Asymptotic Theory and Econometric Practice with Large Dimension of Parameters
Asymptotic Theory and Econometric Practice
Author(s): Roger Koenker
Source: Journal of Applied Econometrics, Vol. 3, No. 2 (Apr., 1988), pp. 139-147
Koenker addressed the issue of estimation of models with increasing dimensionality in parameters when the number of observations are increasing, which is first noticed by Huber,
Robust Regression: Asymptotics, Conjectures and Monte Carlo
Peter J. Huber
The Annals of Statistics, Vol. 1, No. 5 (Sep., 1973), pp. 799-821
Author(s): Roger Koenker
Source: Journal of Applied Econometrics, Vol. 3, No. 2 (Apr., 1988), pp. 139-147
Koenker addressed the issue of estimation of models with increasing dimensionality in parameters when the number of observations are increasing, which is first noticed by Huber,
Robust Regression: Asymptotics, Conjectures and Monte Carlo
Peter J. Huber
The Annals of Statistics, Vol. 1, No. 5 (Sep., 1973), pp. 799-821
Tuesday, April 21, 2009
The ET Interview: Professor Phoebus J. Dhrymes
Econometric Theory, Vol. 18, No. 5 (Oct., 2002), pp. 1221-1272
Phoebus J. Dhrymes is one of the best known econometricians of the last 40 years. He has made substantial contributions to econometric theory through articles in leading journals and by way of a series of outstanding texts on the foundations and methods of econometrics. His early research began with an applied econometric focus on problems of production and investment. His later contributions concentrated on the foundations of econometric methodology, including systems of simultaneous equations. Throughout the econometrics community, Dhrymes is well known for his influential textbooks, some of which have been translated into several languages. His 1970 book Econometrics: Sta- tistical Foundations and Applications provided an accessible and rigorous foun- dation for both students and teachers of econometrics. His subsequent books have continued to treat foundational issues and have tracked new areas of econometric interest through to his 1998 book Time Series, Unit Roots, and Cointe- gration. Reading his books reveals Dhrymes as a teacher, synthesizer, and master expositor. As he says in the interview that follows, "my books are not typical textbooks. I perceive them more as books that bridge the gap between ordinary textbooks and journal articles and as filters that distill and synthesize the wisdom of many contributors to the subject. On this score I was influ- enced in my writing by the way I learn when studying by myself."
Phoebus J. Dhrymes is one of the best known econometricians of the last 40 years. He has made substantial contributions to econometric theory through articles in leading journals and by way of a series of outstanding texts on the foundations and methods of econometrics. His early research began with an applied econometric focus on problems of production and investment. His later contributions concentrated on the foundations of econometric methodology, including systems of simultaneous equations. Throughout the econometrics community, Dhrymes is well known for his influential textbooks, some of which have been translated into several languages. His 1970 book Econometrics: Sta- tistical Foundations and Applications provided an accessible and rigorous foun- dation for both students and teachers of econometrics. His subsequent books have continued to treat foundational issues and have tracked new areas of econometric interest through to his 1998 book Time Series, Unit Roots, and Cointe- gration. Reading his books reveals Dhrymes as a teacher, synthesizer, and master expositor. As he says in the interview that follows, "my books are not typical textbooks. I perceive them more as books that bridge the gap between ordinary textbooks and journal articles and as filters that distill and synthesize the wisdom of many contributors to the subject. On this score I was influ- enced in my writing by the way I learn when studying by myself."
Saturday, April 18, 2009
To be great is not a one day job
Several lessons have been learned recently. The first one comes into mind is that to be great is not a one day job. Persistence in working hard is definitely a necessary condition to success, besides inexhausted passion. As one earlier blog noted, march forward a little bit each day.
Wednesday, April 15, 2009
National Financial Crisis: Voice from Yale
the following video is available on YOUTUBE.com
Yale Economists Discuss the National Financial Crisis
Yale Economists Discuss the National Financial Crisis
Monday, April 13, 2009
LungFei Lee is visiting UCR on April 16th and 17th
The world leading Econometrican, Professor LungFei Lee at OSU, is visiting UC, Riverside on 16th and 17th, April 2009. He will give a lecture on Spatial Panel data models on Thursday from 5:10 to 6:30 and present in Econometrics seminar on Friday.
Sunday, April 12, 2009
Saturday, April 11, 2009
Friday, April 10, 2009
Computing Power and the Power of Econometrics
By Hamilton J.D. Computing Power and the Power of Econometrics, Medium Econometrische Toepessingen, 2006, volume 14, number 2, pp. 32-38.
NBER Macroeconomic Anual Conference
NATIONAL BUREAU OF ECONOMIC RESEARCH
Twenty-fourth Annual Conference on Macroeconomics
Daron Acemoglu, Kenneth Rogoff and Michael Woodford, Organizers
April 10-11, 2009
The Royal Sonesta Hotel
Riverfront Room
40 Edwin H. Land Blvd.
Cambridge, MA
Twenty-fourth Annual Conference on Macroeconomics
Daron Acemoglu, Kenneth Rogoff and Michael Woodford, Organizers
April 10-11, 2009
The Royal Sonesta Hotel
Riverfront Room
40 Edwin H. Land Blvd.
Cambridge, MA
Thursday, April 9, 2009
C.R. Rao
Wikipedia has the following,
Calyampudi Radhakrishna Rao (Kannada: ಕಲ್ಯಾಂಪುದಿ ರಾಧಾಕೃಷ್ಣ ರಾಯ) FRS (born September 10, 1920) is an Indian born statistician and currently Professor emeritus at Penn State University. He was born in Hadagali, in the state of Karnataka, India.
He received an M.S. degree in Mathematics from Andhra University and an M.S. degree in Statistics from Calcutta University in 1943.
Rao worked at the Indian Statistical Institute and the Anthropological Museum in Cambridge before acquiring a Ph.D. degree at King's College in Cambridge University under R.A. Fisher in 1948, to which he added a Sc.D. degree, also from Cambridge, in 1965.
Among his best-known discoveries are the Cramér-Rao bound and the Rao-Blackwell theorem both related to the quality of estimators. Other areas he worked in include Multivariate analysis, estimation and Differential geometry.
Rao is a Samuel S. Wilks and Mahalanobis medalist; a member of eight National Academies in India, the United Kingdom, the United States, and Italy; he has received dozens of medals, citations, awards, and other honors for his contributions to statistics and science. Rao was awarded the United States National Medal of Science, that nation's highest award for lifetime achievement in fields of scientific research, in June 2002.
Also see The ET Interview with Professor C.R. Rao
Calyampudi Radhakrishna Rao (Kannada: ಕಲ್ಯಾಂಪುದಿ ರಾಧಾಕೃಷ್ಣ ರಾಯ) FRS (born September 10, 1920) is an Indian born statistician and currently Professor emeritus at Penn State University. He was born in Hadagali, in the state of Karnataka, India.
He received an M.S. degree in Mathematics from Andhra University and an M.S. degree in Statistics from Calcutta University in 1943.
Rao worked at the Indian Statistical Institute and the Anthropological Museum in Cambridge before acquiring a Ph.D. degree at King's College in Cambridge University under R.A. Fisher in 1948, to which he added a Sc.D. degree, also from Cambridge, in 1965.
Among his best-known discoveries are the Cramér-Rao bound and the Rao-Blackwell theorem both related to the quality of estimators. Other areas he worked in include Multivariate analysis, estimation and Differential geometry.
Rao is a Samuel S. Wilks and Mahalanobis medalist; a member of eight National Academies in India, the United Kingdom, the United States, and Italy; he has received dozens of medals, citations, awards, and other honors for his contributions to statistics and science. Rao was awarded the United States National Medal of Science, that nation's highest award for lifetime achievement in fields of scientific research, in June 2002.
Also see The ET Interview with Professor C.R. Rao
Wednesday, April 8, 2009
Everyday March Forward a Little Bit
Tseng Tzu said, ' Everyday I examine myself on three counts. In what I have undertaken on another's behalf, have I failed to do my best? In my dealings with my friends have I failed to be trustworthy in what I say? Have I passed on others anything that I have not tried out myself?'
In Econometrics, three basic thinking everyday should be as follows, ' In all the Economic questions that I have ever known, have I failed to understand them better? In all the basic Econometric approaches that we have undertaken, have I failed to approach them in the right and accurate way? In the broad Economic complex, have I failed to get to know more interesting questions that are critical to advance the research of Economics?'
In Econometrics, three basic thinking everyday should be as follows, ' In all the Economic questions that I have ever known, have I failed to understand them better? In all the basic Econometric approaches that we have undertaken, have I failed to approach them in the right and accurate way? In the broad Economic complex, have I failed to get to know more interesting questions that are critical to advance the research of Economics?'
Monday, April 6, 2009
Testing Stationary Ergodicity
Check the following papers by Mahmoud A. El-Gamal
“A Consistent Nonparametric Test of Stationary Ergodicity for Time Series withApplications,” (with Ian Domowitz), Journal of Econometrics 102, 2001, pp. 365398.
“A Consistent Test of StationaryErgodicity,”(with Ian Domowitz), Econometric Theory 9(4), 1993, pp. 589601.
“A Consistent Nonparametric Test of Stationary Ergodicity for Time Series withApplications,” (with Ian Domowitz), Journal of Econometrics 102, 2001, pp. 365398.
“A Consistent Test of StationaryErgodicity,”(with Ian Domowitz), Econometric Theory 9(4), 1993, pp. 589601.
More on Fisher
Fisher in 1921 By Stephen Stigler, in Statistical Science and
On the Theoretical Foundations of Mathematical Statistics By Blair Christian
On the Mathematical Foundations of Theoretical Statistics By R.A. Fisher
On the Theoretical Foundations of Mathematical Statistics By Blair Christian
On the Mathematical Foundations of Theoretical Statistics By R.A. Fisher
How to Accuse the Other Guy of Lying with Statistics
See the interesting article from Statistical Science:
How to Accuse the Other Guy of Lying with Statistics by Charles Murray
How to Accuse the Other Guy of Lying with Statistics by Charles Murray
Sunday, April 5, 2009
A Conversation with Hirotugu Akaike
A Conversation with Hirotugu Akaike
By David F. Findley and Emanuel Parzen
So the question about how did AIC come into being is answered as in the following remark, followed by the original article,
A remark on 1974 paper, 1981
A New Look at the Statistical Model Identification, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. AC-19, KO. 6, DECEMBER 1974
By David F. Findley and Emanuel Parzen
So the question about how did AIC come into being is answered as in the following remark, followed by the original article,
A remark on 1974 paper, 1981
A New Look at the Statistical Model Identification, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. AC-19, KO. 6, DECEMBER 1974
A Conversation with Leo Breiman
By Richard Olshen
A Conversation with Leo Breiman
Wikipedia commented the following about Leo breiman:
Leo Breiman (January 27, 1928 – July 7, 2005) was a distinguished statistician at the University of California, Berkeley. He was the recipient of numerous honors and awards, and was a member of the United States National Academy of Science.
Breiman's work bridged the gap between statisticians and computer scientists, particularly in the field of machine learning. Perhaps his most important contributions were his work on classification and regression trees and ensembles of trees fit to bootstrap samples. Bootstrap aggregation was given the name bagging by Breiman. Another of Breiman's ensemble approaches is the random forest.
A Conversation with Leo Breiman
Wikipedia commented the following about Leo breiman:
Leo Breiman (January 27, 1928 – July 7, 2005) was a distinguished statistician at the University of California, Berkeley. He was the recipient of numerous honors and awards, and was a member of the United States National Academy of Science.
Breiman's work bridged the gap between statisticians and computer scientists, particularly in the field of machine learning. Perhaps his most important contributions were his work on classification and regression trees and ensembles of trees fit to bootstrap samples. Bootstrap aggregation was given the name bagging by Breiman. Another of Breiman's ensemble approaches is the random forest.
Murray Rosenblatt: His Contributions to Probability and Statistics
By T. C. Sun
The paper is in honor of Rosenblatt's 70th birthday, which summarize his major contribution to mathematics and statistics. Read the paper at:
Murray Rosenblatt: His Contributions to Probability and Statistics
The paper is in honor of Rosenblatt's 70th birthday, which summarize his major contribution to mathematics and statistics. Read the paper at:
Murray Rosenblatt: His Contributions to Probability and Statistics
Great Statisticians
List of Statisticians from Wikipedia
PORTRAITS OF STATISTICIANS from University of York
A
Hirotugu Akaike (ISM)
B
PORTRAITS OF STATISTICIANS from University of York
A
Hirotugu Akaike (ISM)
B
Moulinath Banerjee
Richard A. Berk (UPenn)
C
Tianxi Cai (Harvard)
Tony Cai (UPenn)
F
Thomas S. Ferguson (UCLA)
G
Jayanta K. Ghosh (Purdue) Tilmann Gneiting (UWashington)
H
Peter Hall (UCD)
K
Michael R. Kosorok (UNC)
L
Erich Leo Lehmann (UC Berkeley)
M
Elias Masry (UCSD) Jason Morton (PSU)
F
Thomas S. Ferguson (UCLA)
G
Jayanta K. Ghosh (Purdue) Tilmann Gneiting (UWashington)
H
Peter Hall (UCD)
K
Michael R. Kosorok (UNC)
L
Erich Leo Lehmann (UC Berkeley)
M
Elias Masry (UCSD) Jason Morton (PSU)
Hans-Georg Müller(UC,Davis)
N
Vinh Quang Nguyen (UCI)
P
David Pollard (Yale)
R
Adrian E. Raftery(UWashington) Joseph P. Romano (Stanford)
Murray Rosenblatt (UCSD) Linda Rothschild (UCSD)
S
Pranab K. Sen (UNC)
V
Sara van de Geer (ETHZ)
Aad van der Vaart (Vrije Universiteit)
W
Jon A. Wellner (UWashiton) Tim Wright (UMissouri)
R
Adrian E. Raftery(UWashington) Joseph P. Romano (Stanford)
Murray Rosenblatt (UCSD) Linda Rothschild (UCSD)
S
Pranab K. Sen (UNC)
V
Sara van de Geer (ETHZ)
Aad van der Vaart (Vrije Universiteit)
W
Jon A. Wellner (UWashiton) Tim Wright (UMissouri)
Z
Harry Huibin Zhou (Yale)
Friday, April 3, 2009
2008-2009: Econometricians on the market
See the job market candidate list from econjobrumor.
Compiled List VII (11/07/2008) (not a complete list at all)
1) Rodrigo A. Alfaro2) Dante Amengual3) Arie Beresteanu4) Gray Calhoun5) Su-Hsin Chang6) Guo Chen7) Qingqing Chen8) Xu Cheng9) Richard Chiburis10) Richard K. Crump11) Pierangelo De Pace12) Ibrahim Ergen13) Yunjong Eo14) Qu Feng15) Sebastian Fossati16) Antonio F Galvao17) Nandita G. Gawade18) Bertrand Hounkannounon19) Meng Huang20) David T. Jacho-Chavez21) Ilze Kalnina22) Karthik Kalyanaraman 23) Young Gui Kim24) Kun-Ho Kim25) Toru Kitagawa26) Xianghua Liu27) Konrad Menzel28) Sung Yong Park29) Wang Peng30) Panutat Satchachai31) Ahmad Shahidi32) Dajing Shang33) Natalia M. Sizova34) Wei-Siang Wang35) Jisong Wu36) Yohei Yamamoto37) Ping Yu38) Julia Hui Zhu
Compiled List VII (11/07/2008) (not a complete list at all)
1) Rodrigo A. Alfaro2) Dante Amengual3) Arie Beresteanu4) Gray Calhoun5) Su-Hsin Chang6) Guo Chen7) Qingqing Chen8) Xu Cheng9) Richard Chiburis10) Richard K. Crump11) Pierangelo De Pace12) Ibrahim Ergen13) Yunjong Eo14) Qu Feng15) Sebastian Fossati16) Antonio F Galvao17) Nandita G. Gawade18) Bertrand Hounkannounon19) Meng Huang20) David T. Jacho-Chavez21) Ilze Kalnina22) Karthik Kalyanaraman 23) Young Gui Kim24) Kun-Ho Kim25) Toru Kitagawa26) Xianghua Liu27) Konrad Menzel28) Sung Yong Park29) Wang Peng30) Panutat Satchachai31) Ahmad Shahidi32) Dajing Shang33) Natalia M. Sizova34) Wei-Siang Wang35) Jisong Wu36) Yohei Yamamoto37) Ping Yu38) Julia Hui Zhu
Great Econometricians
Updated version of Yixiao Sun's Econometricians
Under construction, March 13, 2011 updated
A
Under construction, March 13, 2011 updated
A
Yong Bao (Purdue)
Robert L. Basmann(BinghamtonU) Anil K. Bera (UIUC)
Herman J. Bierens (PSU) Lynne Billard (UGorgia)
Robert L. Basmann(BinghamtonU) Anil K. Bera (UIUC)
Herman J. Bierens (PSU) Lynne Billard (UGorgia)
David Brownstone (UCI) Moshe Buchinsky (UCLA)
Ivan Canay (NWU)
Raymond Carroll (TAMU)
Karim Chalak (BC)
Xu Cheng (UPenn)
Peter .F. Christoffersen (McGill)
Todd .E. Clark (Clevelandfed)
Mike Clements (Warwick)
D
Russell Davidson (Marseille) Aureo de Paula (UPenn)
Phoebus J Dhrymes (Columbia) Francis Diebold(UP)
D
Russell Davidson (Marseille) Aureo de Paula (UPenn)
Phoebus J Dhrymes (Columbia) Francis Diebold(UP)
Miller Doug (UCD) Steven N. Durlauf (UWMadison)
E
Graham Elliott (UCSD) Kirill Evdokimov (Princeton)
F
Yanqin Fan (Vanderbilt) Jianqin Fan (Princeton)
Jon Faust (JHU)
G
E
Graham Elliott (UCSD) Kirill Evdokimov (Princeton)
F
Yanqin Fan (Vanderbilt) Jianqin Fan (Princeton)
Jon Faust (JHU)
G
Amos Golan (AmericanU)
William Greene (NYU) Eric GHYSELS (UNC)
H
James D. Hamilton (UCSD) Bruce E. Hansen (UW-Madison)
Peter Reinhard Hansen (Stanford)
Matthew Harding (Stanford) Jerry Hausman (MIT)
Daniel Henderson (Binghamton)
David F. Hendry (Oxford) Eric Hillebrand (LSU)
Stephan Hoderlein (BC) Han Hong (Stanford)
William Greene (NYU) Eric GHYSELS (UNC)
H
James D. Hamilton (UCSD) Bruce E. Hansen (UW-Madison)
Peter Reinhard Hansen (Stanford)
Matthew Harding (Stanford) Jerry Hausman (MIT)
Daniel Henderson (Binghamton)
David F. Hendry (Oxford) Eric Hillebrand (LSU)
Stephan Hoderlein (BC) Han Hong (Stanford)
Yongmiao Hong (Cornell)
Joel L. Horowitz (NWU)
Rustam Ibragimov (Harvard)
Emma Iglesias (MSU)
Guido W. Imbens (UCB) Atsushi Inoue(NCSU)
J
Michael Jansson (Berkeley) Sainan Jin (SMU)
K
Emma Iglesias (MSU)
Guido W. Imbens (UCB) Atsushi Inoue(NCSU)
J
Michael Jansson (Berkeley) Sainan Jin (SMU)
K
Hiroaki Kaido (BU) Shakeeb Khan (Duke)
Lutz Kilian(UM) Min Seong Kim (UCSD)
Jan F. Kiviet (UAmsterdam) Frank Kleibergen (Brown)
Patrick Kline (UCB)
Roger Koenker (UIUC) Tatiana Komarova (LSE)
Dennis Kristensen (Columbia) Subal C. Kumbhakar(Binghamton)
L
Kajal Lahiri (Albany) LungFei Lee (OSU) Tae-Hwy Lee (UCR)
Qi Li (TAMU) Zhipeng Liao (Yale)
L
Kajal Lahiri (Albany) LungFei Lee (OSU) Tae-Hwy Lee (UCR)
Qi Li (TAMU) Zhipeng Liao (Yale)
Jan R. Magnus (TilburgU)
Enno Mammen (UMannheim ) CHARLES F. MANSKI(NWU)
Vadim Marmer (UBC)
Carlos Martins-Filho (Colorado) Esfandiar (Essie) Maasoumi (EmoryU)
Rosa L. Matzkin (UCLA) MICHAEL W. MCCRACKEN (St. Louis Fed)
Carlos Martins-Filho (Colorado) Esfandiar (Essie) Maasoumi (EmoryU)
Rosa L. Matzkin (UCLA) MICHAEL W. MCCRACKEN (St. Louis Fed)
Konstantinos Costas Meghir (UCL)
Konrad Menzel (NYU) Anna Mikusheva (MIT)
Hyungsik Roger Moon (USC)
N
Whitney Newey (MIT) Serena Ng (Columbia)
Hyungsik Roger Moon (USC)
N
Whitney Newey (MIT) Serena Ng (Columbia)
O
Harry Paarsch (UMelbourne)
Ariel Pakes (Havard)
Christopher Parmeter (VTech) M. Hashem Pesaran (Cambridge)
Gary C.D. Phillips(Cardiff)
Peter Charles Bonest Phillips (Yale) James L. Powell (UCB)
R
Jeffrey S. Racine(McMaster U) David Rapach (SLU)
Christopher Parmeter (VTech) M. Hashem Pesaran (Cambridge)
Gary C.D. Phillips(Cardiff)
Peter Charles Bonest Phillips (Yale) James L. Powell (UCB)
R
Jeffrey S. Racine(McMaster U) David Rapach (SLU)
Eric Renault (UNCarolina)
Shinichi Sakata (UBC) Andres Santos (UCSD)
Shu Shen (UCD)
Robert Sherman (CalTech) Xiaoxia Shi (UW-Madison)
Mototsugu Shintani (VanderbiltU)
Matt Shum (CalTech)
Robin C. Sickles (RiceU) Léopold Simar(UCdL)
Aaron Smith (UCD) Jeremy Smith (Warwick)
Robin C. Sickles (RiceU) Léopold Simar(UCdL)
Aaron Smith (UCD) Jeremy Smith (Warwick)
DOUGLAS G. STEIGERWALD (UCSB)
Thanasis Stengos(Guelph)
Maxwell B Stinchcombe (UT-Austin)
Kenneth F. Wallis (Warwick)
Mark Watson (Princeton) Ken D. West (UW, Madison)
Halbert White (UCSD) Paul W. Wilson (Clemson)
Jonathan Wright(JHU)
Ximing Wu (TAMU)
X
Halbert White (UCSD) Paul W. Wilson (Clemson)
Jonathan Wright(JHU)
Ximing Wu (TAMU)
X
Y
Jun Yu (SMU)
Z
John Zedlewski (Harvard)
Guofu Zhou (WUSTL)
Victorial Zinde-Walsh (McGill)
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