Topics on Computational Econometrics
April 10, 12, 14, 15, 17, 19 (TBA)
Kuan-Pin Lin
Professor of Economics
Portland State University and WISE/SOE Xiamen University
(Last updated: 04/15/2017)
Introduction
Economic data observations come in different forms and structures. Data structures such as cross sections,
time series, and panel data are familiar in economics. Based on economic theory and statistical methods,
econometrics addresses issues of causal inference among economic variables.
The goal of econometric analysis is for a reliable prediction and a better decision making.
With the advances of information technology and rapid growth of data collection,
current state of econometric analysis faces the challenge of using massive datasets and computation intensive methods.
This course presents case studies of computational econometrics with open source R/RStudio software.
Suggested Readings
- Kuan-Pin Lin and Yong Wang, Computational Econometrics with R by Examples,
2017, in progress.
- Christian Kleiber and Achim Zeileis, Applied Econometrics with R,
Springer-Verlag, New York, 2008.
- Vikram Dayal, An Introduction to R for Quantitative Economics:
Graphing, Simulating and Computing, Springer Briefs in Economics, Springer (India), 2015.
- Rob J. Hyndman and George Athanasopoulos,
Forecasting: Principles and Practice, Oneline, Open Access Texbooks.
- Florian Heiss, Using R for Introductory Econometrics, CreateSpace, 2016.
Topics
Subject to time constraint and program revision,
the following introductory topics and case studies will be selected and discussed during this short course:
- Economic Data Analysis Using R
- Econometric Computing in the Cloud
- State Space Time Series Analysis and Forecasting
- Case Studies:
-
The Economist's Big Mac Price Index
(1.1, 1.2,
1.3, 1.4,
1.5, 1.6,
1.7)
- Wine Price in Vancouver BC, Canada
(2.1, 2.2,
2.3, 2.4)
- U. S. Misery Index
(3.1, 3.2,
3.3, 3.4,
Notes)
- Chinese Yuan and Stock Market
(6.1, 6.2,
6.3, 6.4)
(7.1, 7.2,
7.3, 7.4, 8.1)
Expectation
- A data project is required for everyone taking this course. A one-page project proposal is due on or before April 20 for approval.
Final report of the project, within 10 pages limit, is due on or before May 15.
- Your grade is solely based on this data project,
which is preferred to be about the Chinese economy or extenstions of the above case studies.
Your project is evaluated based on its originality, creativity and consistency with the course contents.