Summer Session 2017

Introduction to Economics of IS and Research Methodology

  • This session is designed to discuss how to apply research methodologies into academic papers by focusing on the literature on "Economics of IS", consisting of three parts: (1) Econometrics, (2) Data Analytics and Machine Learning, (3) Behavioral Research Methodology.
  • All materials can be downloaded at each page.
  • Contributors: Jiyong Park (Organizer, jiyong.park@kaist.ac.kr), Junyeong Lee (junyeonglee@ustc.edu.cn), Hyeokkoo Eric Kwon (hkkwon7@business.kaist.ac.kr), Yoonseock Son (yoonism@business.kaist.ac.kr), Jongho Kim (jonghkim@kaist.ac.kr)
  • If you are interested in being a contributor about any topics (even not included in the lists), please feel free to contact Jiyong Park.

1st Week

(6/29, 14:00~15:30)

  • Introduction
  • What is Economics of IS?

1st Week

(8/10, 14:00~15:30)

  • Causal Inference versus Prediction

- Are they substitutes or complements?

1st Week

(8/3, 14:00~15:30)

  • Structural Equation Model for Survey Data (1)

2nd Week

(7/6, 14:00~15:30)

  • Regression Framework

- Why is ordinary least square (OLS) not enough?

2nd Week

(8/16, 14:00~15:30)

  • Predictive Analytics

2nd Week

(8/7, 14:00~15:30)

  • Structural Equation Model for Survey Data (2)

3rd Week

(7/13, 14:00~15:30)

  • Instrumental Approach

- Two-stage least square (2SLS)

- Selection model

3rd Week

(8/23, 14:00~15:30)

  • Machine Learning and Deep Learning

- How can it be applied to the empirical research?

4th Week

(7/20, 14:00~15:30)

  • Experimental Approach

- Randomized experiment

- (Natural) Quasi-experiment

4th Week

(8/19, 15:00~16:30)

  • (Technical Session) Exploiting Unstructured Data

(Step 1) Web crawling

5th Week

(7/27, 14:00~15:30)

  • Identification Strategy and Model Uncertainty

5th Week

(8/26, 15:00~16:30)

  • (Technical Session) Exploiting Unstructured Data

(Step 2) Applying cloud-based APIs