課程名稱 |
賽局實證分析 Empirical Game Theory Analysis |
開課學期 |
106-1 |
授課對象 |
社會科學院 經濟學研究所 |
授課教師 |
黃景沂 |
課號 |
ECON7153 |
課程識別碼 |
323 M3720 |
班次 |
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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 |
總人數上限:25人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1061ECON7153 |
課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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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/game2017/
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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.
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課程要求 |
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%). There will be NO make-up exam. Please make sure you can take the exams (due on November 7 and January 9, respectively) before enrolling this course.
Send me your preferences over the papers with a # mark on the reading list. The presentation time is about 30–40 minutes.
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
待補 |
參考書目 |
See the reading list.
http://homepage.ntu.edu.tw/~chingihuang/teaching/game2017/
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評量方式 (僅供參考) |
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