Causal Effects Model 的估計

==Causal Effects 估計範例==

in Angrist and Pischke (2017, JEP, p130-132),主要提出觀念的是 Dale and Kruger (2002, QJE)

他們想估計美國唸私立大學和唸公立大學的差異,用較明確的因果關係為主的估計法。

Casusal Effect: 在申請入學時,同時接到私大和州大入學許可,但最後後選擇唸私大、或州大的學生為樣本:

Yi: 全部的樣本的畢業生所得,可觀察的,其中又分為兩類

Y1i : 第 i 個樣本的「受私校教育後」所得

Y0i : 第 i 個樣本的「受州校教育後」所得

以上兩個,令

Pi: =1 if 第 i 個樣本唸私立,=0 otherwise 唸州立大學

合理的假設是,每個人在受大學教育之前,原本就有一定的能力

Y10 : 第 i 個樣本的原來能力
重點:美國私立大學教學效果,是否來自教學,還是學生的本質。

因為好學生集中去唸名私校,所以畢業後收入高,不見得是私校的努力。這個稱為 selection bias 樣本選擇偏誤。

私校的教學效果 (用大概畢業20年後的 earning 來衡量) 之差異為:

Y1i – Y0i

若教學有效的話,然後差異的平均是 β

H0 : E(Y1i – Y0i) = β>0

假設E(Y0i) = α, 即

Y0i =α + ηi

α 為學生原來的潛力, ηi是誤差,或個別差異,這個個別差異會和選私校有關係,例如家庭背景、爸媽是否畢業於私立..。
Caussal-Effect model

Yi = α+βPi+ηi

Pi 和 ηi 是(統計上)不獨立的,也就是無法滿足迴歸上原來的獨立性要求。

這個 causal-effect model 的想法創新就在此,他們提出比較不嚴格的「條件獨立性假設」(conditional independence assumption),

E(ηi|Pi,Xi) = E(ηi|Xi)

所以要找其它的可能影響畢業後所得能力的變數 X (例如 SAT 的分數…),來加入估計,觀念上是

E(ηi|Pi,Xi) = E(ηi|Xi) = E(ηi|Xi)

所以, causal-effect model 最後就變成

Yi=α+βPi+γXi+ηi

此法可建構出 unbias 和 consistent 的 β 估計,而且它有明確的意義:唸私校和唸公校的「效果差異」平均值。
==ref==

Angrist, Joshua D., and Jörn-Steffen Pischke. “Undergraduate econometrics instruction: through our classes, darkly." Journal of Economic Perspectives, 31.2 (2017): 125-44.

Dale, Stacy Berg, and Alan B. Krueger. “Estimating the payoff to attending a more selective college: An application of selection on observables and unobservables." The Quarterly Journal of Economics, 117.4 (2002): 1491-1527.

廣告

New directions for modelling strategic behavior: Game-theoretic models of communication, coordination, and cooperation in economic relationships

Crawford, Vincent P. “New directions for modelling strategic behavior: Game-theoretic models of communication, coordination, and cooperation in economic relationships." Journal of Economic Perspectives 30.4 (2016): 131-50.

URL:http://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.30.4.131

==original Abstract==

In this paper, I discuss the state of progress in applications of game theory in economics and try to identify possible future developments that are likely to yield further progress. To keep the topic manageable, I focus on a canonical economic problem that is inherently game-theoretic, that of fostering efficient coordination and cooperation in relationships, with particular attention to the role of communication. I begin with an overview of noncooperative game theory’s principal model of behavior, Nash equilibrium. I next discuss the alternative “thinking" and “learning" rationales for how real-world actors might reach equilibrium decisions. I then review how Nash equilibrium has been used to model coordination, communication, and cooperation in relationships, and discuss possible developments

GIMS, an open source market software

S. Palan, GIMS-Software for asset market experiments. J. Behav. Exp. Finance 5, 1–14, (2015). Medline doi:10.1016/j.jbef.2015.02.001 (可免費閱讀)

==by YNY==

GIMS 是架在 z-Tree 上,專門用來跑財務資產市場 (又稱 double auction asset market) 的實驗平台軟體,採開放源碼 (open source) 授權。

此文亦介紹、比較了其它相關的財務市場實驗平台軟體,參見文中的 Table 1。

  • EconPort MarketLink(based on Java and experiments can be run over the internet)
  • Flex-E-Markets(not open source)
  • GIMS(based on z-Tree)
  • jMarkets (open-source software based on Java)
  • Rotman Interactive Trader (非免費)
  • SoPHIE Labs (非免費)

Continuous double auction market interface

Evaluating replicability of laboratory experiments in economics

C. F. Camerer, A. Dreber, E. Forsell, T.-H. Ho, J. Huber, M. Johannesson, M. Kirchler, J. Almenberg, A. Altmejd, T. Chan, E. Heikensten, F. Holzmeister, T. Imai, S. Isaksson, G. Nave, T. Pfeiffer, M. Razen, H. Wu. Evaluating replicability of laboratory experiments in economics. Science, 2016; DOI: 10.1126/science.aaf0918

==YNY==

終於有人系統性地檢視經濟實驗, 雖然只挑 AER 和 QJE 所發表的, 但經得起「重覆實驗」來驗證結果的研究, 才符合科學的精神…

Monetization Strategies for Internet Companies

Date: 2016
By: Voigt, Sebastian
URL: http://d.repec.org/n?u=RePEc:dar:wpaper:83314&r=net
Many Internet service companies such as providers of two-sided markets, social networks, or online games rely on the social interaction between their user base and thus capitalize from positive network effects. For such companies, a common strategy is to offer (basic) services for free (and thereby abolish entry barrier of a one-off or recurring price) and to charge their users for premium services. Companies such as eBay, PayPal, LinkedIn, or Skype added paid services to their originally free business models, either via subscriptions, PAYG, or direct sales of virtual items. Their strategy how to make money and whom to bill however differs widely. In the Internet business, ‘monetization’ has become a frequently used buzzword for all aspects of a company’s revenue strategy which includes the decision who should be billed (e.g., for a two-sided market: seller vs. buyer vs. advertisers only), with which price model (e.g., mandatory subscription vs. optional subscriptions vs. selling virtual currency or items) and price level (e.g., differentiated between user groups), and – in case of a freemium strategy – how a new (free) user can be converted most efficiently into a paying and remunerative customer (e.g., via effective CRM measures). The overarching objective of all monetization measures is to maximize the company’s revenue and/or profit. The field of monetization offers a wide field of research opportunities. Four of these are covered in this dissertation: The Name-your-own-price model, users’ spending behavior in virtual communities, the monetization of network effects in social networks, and the legal boundaries of social network usage. As a result, this dissertation solves a series of questions currently being worked on by practitioners and uses a wide range of methods from various disciplines such as economic, psychological, and game theory.

Network economics and the environment: insights and perspectives

Date: 2015-09
By: Sergio Currarini
Carmen Marchiori
Alessandro Tavoni
URL: http://d.repec.org/n?u=RePEc:ehl:lserod:63951&r=net
Local interactions and network structures appear to be a prominent feature of many environmental problems. This paper discusses a wide range of issues and potential areas of application, including the role of relational networks in the pattern of adoption of green technologies, common pool resource problems characterized by a multiplicity of sources, the role of social networks in multi-level environmental governance, infrastructural networks in the access to and use of natural resources such as oil and natural gas, the use of networks to describe the internal structure of inter-country relations in international agreements, and the formation of bilateral “links” in the process of building up an environmental coalition. For each of these areas, we examine why and how network economics would be an effective conceptual and analytical tool, and discuss the main insights that we can foresee.
Keywords: networks; environmental externalities; technological diffusion; gas pipelines; common-pool-resources; multi-level governance; coalitions

Econometrics of network models

Date: 2015-09
By: Áureo de Paula (Institute for Fiscal Studies and University College London)
URL: http://d.repec.org/n?u=RePEc:ifs:cemmap:52/15&r=net
In this article I provide a (selective) review of the recent econometric literature on networks. I start with a discussion of developments in the econometrics of group interactions. I subsequently provide a description of statistical and econometric models for network formation and approaches for the joint determination of networks and interactions mediated through those networks. Finally, I give a very brief discussion of measurement issues in both outcomes and networks. My focus is on identification and computational issues, but estimation aspects are also discussed.

Trading in Networks: a Classroom Experiment

==noted by yinung==
分組, 在圈形的網路 topoloty 中, 隨機選兩組進行貿易, 但 transport 經過各組 node 時要付費
===參考===
  • S. Choi, A. Galeotti, S. Goyal.Trading in networks: theory and experiments, -Cambridge-INET Working Paper, 2014
  • M. Kosfeld. Economic Networks in the Laboratory: A Survey, Institute for Empirical Research
    in Economics, University of Zurich, 2015.
Date: 2015-10
By: Paul Johnson (Department of Economics and Public Policy, University of Alaska Anchorage)
Qiujie Zheng (Department of Economics and Public Policy, University of Alaska Anchorage)
URL: http://d.repec.org/n?u=RePEc:ala:wpaper:2015-03&r=net
This paper describes a classroom experiment that demonstrates coordination and competition between traders in a network. Students test theoretical predictions concerning the emergence of equilibrium and the division of surplus between buyers and sellers. The experiment is appropriate for use in teaching intermediate microeconomics, industrial organization, transportation economics and game theory.
Keywords: Experimental Economics, Classroom Experiment, Trading in Networks
JEL: A22 B21 C92

A Short Survey of Network Economics

Shy, Oz. “A short survey of network economics." Review of Industrial Organization 38.2 (2011): 119-149.

Abstract

This article surveys a variety of topics that are related to network economics. Topics covered include: consumer demand under network effects, compatibility decisions and standardization, technology advances in network industries, two-sided markets, information networks and intellectual property, and social influence.

Keywords

Survey Network economics Network industries Network effects Network externalities

JEL Classification

D4 L1 L8 Z1