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.

Part 1. Econometrics

Part 2. Data Analytics and Machine Learning

Part 3. Behavioral Research Methodology

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

Google Sites

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