|
課程名稱 |
賽局實證分析
Empirical Game Theory Analysis |
|
開課學期 |
111-1 |
|
授課對象 |
社會科學院 經濟學系 |
|
授課教師 |
黃景沂 |
|
課號 |
ECON7153 |
|
課程識別碼 |
323 M3720 |
|
班次 |
|
|
學分 |
2.0 |
|
全/半年 |
半年 |
|
必/選修 |
選修 |
|
上課時間 |
星期二3,4(10:20~12:10) |
|
上課地點 |
社科研604 |
|
備註 |
大學生亦可選修。（開學後第三週下載教師同意加簽單加選）
限碩士班以上 或 限博士班
總人數上限：25人 |
|
|
|
|
課程簡介影片 |
|
|
核心能力關聯 |
核心能力與課程規劃關聯圖 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
The goal of this course is to familiarize students with tools to empirically analyze static and dynamic games.
For more details, please refer to the syllabus on
http://homepage.ntu.edu.tw/~chingihuang/teaching/game2022/
|
|
課程目標 |
The goal of this course is to familiarize students with tools to empirically analyze static and dynamic games. Game theory has been applied to study the interaction between actions in many fields of economics, including auctions, bargaining, oligopolies, social network formation, social choice theory, . . . . The equilibrium outcome of a game usually depends on model parameters. To determine these parameters from the real world data, we need econometric tools. Nonetheless, estimating a game-theoretical model often faces some methodological challenges, such as existence of multiple equilibria, the curse of dimensionality.
Recent developments in estimation methodology and computing ability have substantially reduced the difficulty in empirically analyzing a game-theoretical model. In this course, we will introduce these methodological innovations. In particular, we will focus on static and dynamic binary choice games. Most of the applications studies in this course come from the field of industrial organization. Many of them studies the entry/exit or open/closing decision by firms in an oligopoly market.
Topics
‧ Introduction (9/6)
– Structural Estimation
‧ Static Binary Games (9/13 9/20, 9/27, 10/4)
– Entry Games with a Unique Equilibrium
– Entry Games with Multiple Equilibria
– Applications
‧ Dynamic Models with a Single Agent (10/11, 10/18, 11/1, 11/8)
– Optimal Replacement Decision
– Estimation Using Conditional Choice Probabilities
– Applications
‧ Dynamic Games with Multiple Agents (11/22, 11/29, 12/6, 12/13)
– Markov-Perfect Nash Equilibrium
– Estimation Approaches
– Applications |
|
課程要求 |
There is no formal prerequisite. However, you should have learned some econometrics. You are expected to have known OLS, IV estimation, MLE, and GMM. You are also expected to have known basic solution concepts in game theory, such as Nash equilibrium, subgame perfect equilibrium, and perfect Bayesian equilibrium. Undergraduate students can register the course by submitting 教師同意加簽單 between Sept. 19 and 23.
Grades will be determined by classroom participation (20%), one classroom presentation (30%), a take-home midterm exam (25%), and a take-home final exam (25%).
The take-home exams are scheduled to begin on October 25 and December 20, respectively. You will have seven days to finish the exams. Please make sure you can take the exams (due on November 1 and December 27, respectively) before enrolling this course. There will be NO make-up exam.
In the class presentation, you are going to present an assigned paper which uses some game-theoretical model to empirically study some real-world problems. You should introduce the motivation of the research, outline the research approach, and show the main empirical results. The presentation time for each paper is about 25–30 minutes. In order to prepare the assignment list, send me your preferences over the papers with a # mark on the reading list. |
|
預期每週課後學習時數 |
|
|
Office Hours |
|
|
指定閱讀 |
待補 |
|
參考書目 |
See the reading list.
http://homepage.ntu.edu.tw/~chingihuang/teaching/game2022/ |
|
評量方式
(僅供參考) |
|
|