Eiichiro Kazumori

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A. Table of Contents

  1. CV.
  2. Education and Professional Appointments.
  3. Awards and Conference Presentations.
  4. Game theory.
  5. Debt management policy.
  6. Spectrum allocation policy.
  7. Asset pricing.
  8. Blockchain and cryptcurrency.
  9. Macroeconomics and economic growth.
  10. Industrial organization.
  11. Teaching methodology.
  12. Teaching.

B. CV

  1. CV.
  2. Research Statement.
  3. Teaching Statement.
  4. Teaching Evaluations.
  5. Diversity Statement.

C. Education and Professional Appointments

C1. Education

  1. Stanford University. Palo Alto, CA. Department of Economics. Ph.D.
  2. The University of Tokyo. Tokyo, Japan. Graduate School of Economics . Master of Economics.
  3. The University of Tokyo. Tokyo, Japan. College of Arts and Sciences (Social Sciences and International Relations) . Bachelor of Arts.

C2. Professional Appointments

  1. The University of Massachusetts. Economics Department. Lecturer.
  2. The State University of New York at Buffalo. Biostatistics Department. Research Assistant Professor. (Honorary, Non-Benefited.)
  3. The State University of New York at Buffalo. Economics Department. Assistant Professor.
  4. The University of Tokyo. Faculty of Economics. Computing Office. Research Fellow.3
  5. California Institute of Technology. Humanities and Social Sciences. Postdoctoral Fellow.

D. Awards and Conference Presentations

D1. Awards

  1. The State University of New York. The Baldy Center Proposal Development Grants. 2015.
  2. The State University of New York . The Civic Engagement Research Dissemination Fellowship. $3,800, 2014-16.
  3. The State University of New York . The Baldy Center Proposal Development Grants . 2014.
  4. The State University of New York . The Baldy Center for Law and Social Policy Grant. $3,825. 2013-14.
  5. The State University of New York . The Baldy Center Proposal Development Grants. 2013.
  6. The National Science Foundation . SES-1247988 "Market Mechanisms for Allocation of Spectrum" (PI). $65,000. 2012-13.
  7. The State University of New York . Dean's Office Travel Fund. $500. 2012-13.
  8. The State University of New York . The Baldy Center for Law and Social Policy Grant. $1000. 2010-11.
  9. The Japan Society for Promotion of Science. Grant-in-Aid for Scientific Research. PI for Grant No. 208032, 2053226, and 228026. $38,990. 2008-10.
  10. The Nomura Foundation Grant. $1000. 2008.
  11. The Information Processing Agency of the Ministry of Economy, Trade, and Industry. The Exploratory IT Human Resources Project (The MITOH Program). $17,000. 2007.
  12. The European Economic Association . The Young Economist Award . Journal of the European Economic Association, Volume 3, Issue 2-3, 1 May 2005, Pages 791.
  13. Stanford University. R&D Dissertation Fellowship. 2003.
  14. Fulbright Scholarship. The Graduate Grant . (Offered.)

D2. Conference Presentations Since 2012

  1. The 2019 ASSA Annual Meeting. Atlanta, GA. January 4-6, 2019.

  2. The 1st UMass System Economics Conference. Lowell, MA. October 27, 2018.
  3. The 29th International Conference on Game Theory. Stony Brook, NY. July 16-20, 2018.
  4. The 2018 North American Summer Meeting of the Econometric Society. Davis, CA. June 21-24, 2018.
  5. The 19th ACM conference on Economics and Computation (ACM EC’18). Ithaca, NY. June 18-22, 2018.
  6. The 2018 ASSA Annual Meeting. Philadelphia, PA. Jan 05-07, 2018.

  7. CAEC17: Third Cambridge Area Economics and Computation Day. Cambridge, MA. Dec 1, 2017.
  8. The 2017 FMA Annual Meeting. Boston, MA. Oct 11-14, 2017. ( Discussant Slides.)
  9. The 28th International Conference on Game Theory In Honor of Pradeep Dubey and Yair Tauman. Stony Brook, NY. July 17-21, 2017.
  10. The Third Workshop on Marketplace Innovation. Palo Alto, CA. June 1-2, 2017.
  11. The 2017 ASSA Annual Meeting. Chicago, IL. January 6-8, 2017.

  12. INFORMS Annual Meeting. Nashville, TN. November 13-16, 2016.
  13. Workshop on Complex Auctions and Practice. Stony Brook, NY. July 9-11, 2016.
  14. AEA Annual Meeting. San Francisco, CA. January 3-5, 2016.

  15. The 11th World Congress of the Econometric Society. Palais des Congres de Montreal, Canada. August 17-21, 2015.
  16. The 15th SAET Conference on Current Trends in Economics. University of Cambridge, UK. July 27-31, 2015.
  17. The 26th International Conference on Game Theory. Stony Brook University. July 20-24, 2015.
  18. Dynamic Approach to Game and Economic Theory - Celebrating Sergiu Hart's 65th birthday. Hebrew University of Jerusalem. June 21-24, 2015.

  19. The Fall 2014 Midwest Economic Theory and International Trade Meeting. University of Kansas. October 11-13, 2014.
  20. International Workshop on Game Theory and Economic Applications of the Game Theory Society (IWGTS-2014). University of Sao Paulo. July 25-31, 2014.
  21. The 25th Summer Festival on Game Theory. The State University of New York at Stony Brook. July 07-11, 2014.
  22. W-PIN+NetEcon 2014: The Joint Workshop on Pricing and Incentives in Networks and Systems in Conjunction with ACM SIGMETRICS 2014. University of Texas at Austin. June 16-20, 2014.
  23. The 2014 North American Winter Meeting of the Econometric Society. Philadelphia, Pennsylvania. January 3-5, 2014.

  24. The Fall 2013 Midwest Economic Theory and International Trade Meeting. University of Michigan at Ann Arbor. October 11-13, 2013.
  25. NSF Enhancing Access to the Radio Spectrum (EARS) Principal Investigators' Workshop. Washington DC. October 8-9, 2013.
  26. The 24th Summer Festival on Game Theory. Stony Brook, New York. July 08-18, 2013.
  27. The 2013 North American Summer Meeting of the Econometric Society. University of South California, California. July 13-16, 2013.
  28. The 24th Jerusalem School in Economic Theory. Jerusalem, Israel. June 10-19, 2013.
  29. The 5th Israel Game Theory Conference. Tel-Aviv, Israel. June 3, 2013.
  30. The 2013 Second Cambridge Area Economics and Computation Day. MIT, Massachusetts. April 26, 2013.
  31. The University of Tokyo Empirical Microeconomics Research Seminar. Tokyo, Japan. March 2013.
  32. The 2013 North American Winter Meeting of the Econometric Society. San Diego, California. January 4-6, 2013.

  33. The Fall 2012 Midwest Economic Theory and International Trade Meetings. University of Washington St. Louis, Missouri. October 26-28, 2012.
  34. The 4th World Congress of the Game Theory Society. Istanbul, Turkey. June 22-26, 2012.
  35. The 23rd Summer Festival on Game Theory. Stony Brook, New York. June 12-19, 2012.
  36. The University of Tokyo Macro-Finance, Monetary Economics and International Finance Workshop. ("Liquidity-Adjusted Capital Asset Pricing Model in Japanese and US Markets") Tokyo, Japan. June 11, 2012.
  37. The University of Tokyo Empirical Micro Research Seminar. ("Information Aggregation in Large Double Auctions with Interdependent Values") Tokyo, Japan. May 28, 2012.

E. Game Theory

  1. Kazumori, Eiichiro. 2017. Information Aggregation in Double Auction Markets with Interdependent Values: an Asymptotic Approximation Approach
  1. Kazumori, Eiichiro. 2017. The Continuous Approximation Method for Optimal Auction Design .
  1. Kazumori, Eiichiro. 2014. Games where Players Offer Games to Play: A Foundation of Market Design .
  1. Kazumori, Eiichiro. 2007. Paul Milgrom's Putting Auction Theory to Work, Japanese Edition . (Joint with Yumiko Baba, Kunio Kawamata, and Masahiro Okuno-Fujiwara.) Published by Toyo Keizai Shinpo Sha, Tokyo, Japan. ISBN: 9784492313855.

F. Debt Management Policy

  1. Kazumori, Eiichiro. 2018. On the Virtue of Being Regular and Predictable: Evaluating US Treasury Debt Issuance Strategies.
  1. Kazumori, Eiichiro. 2018. On the Virtue of Being Regular and Predictable: A Structural Analysis of the Primary Dealer System in the United States Treasury Auctions.

G. Spectrum Management Policy

  1. Kazumori, Eiichiro. 2017. Simultaneous Deferred Acceptance Auctions for Spectrum Reallocation.
  1. Kazumori, Eiichiro. 2018. Vickrey Auctions versus Proxy Auctions: An Experimental Study .
  1. Kazumori, Eiichiro. 2010. Core-Selecting Auctions: An Experimental Study .
  1. Kazumori, Eiichiro. 2018. T-tree: Tokyo Toolbox for Readymade Economic Experiments.
  1. Kazumori, Eiichiro. 2007. Auctions, Market Design, and Experimental Economics . in T. Saijo (ed), Invitations to Experimental Economics .   NTT Publishing, Tokyo, Japan. ISBN: 978-4757122055.
  2. Kazumori, Eiichiro. 2002. An Efficient Combinatorial Auction for Sequentially Arriving Bidders. (Joint with Hiroki Horiuchi, Satoshi Nishiyama, and Chihiro Ono)
  3. Kazumori, Eiichiro. 2004. Simultaneous Ascending Auctions with Heterogenous Objects .

H. Asset Pricing

  1. Kazumori, Eiichiro. 2017. What Drives Stock Returns of Facebook, Apple, Microsoft, and Google? Industry Structure and Stock Returns in the US Computer Industry, 1965-2017.
  1. Kazumori, Eiichiro. 2017. Asset Pricing with Liquidity Risk: Japanese Market Data. Critical Finance Review, Forthcoming.
  1. Kazumori, Eiichiro. 2017. Tokyo Financial Research Data Services.
  1. Kazumori, Eiichiro. 2004. Asset Pricing in Networks

I. Cryptocurrency and Blockchain

  1. Kazumori, Eiichiro. 2018. Social Cost of Anonymity: Limit of Arbitrage in The Bitcoin Cryptocurrency Protocol.

J. Macroeconomics and Economic Growth

  1. Kazumori, Eiichiro. 2016. Health as Human Capital: Implications on Economic Growth, Trade, and Inequality
  • Julio Elias, Eiichiro Kazumori, and Peter Morgan. 2016. Organizational Design for Innovation and Economic Growth.
  • K. Industiral Organization

    1. Kazumori, Eiichiro. 2004. Markov Industry Dynamics with Network Externality and Switching Costs: Theory, Computation, and Estimation.
    1. Kazumori, Eiichiro and John McMillan. 2005. Selling Online versus Live . Journal of Industrial Economics. 53(4), 543-569.

    2. Kazumori, Eiichiro and John McMillan. 2003. Art Online . Stanford GSB Case EC35. Palo Alto, CA.

    3. Kazumori, Eiichiro. 2003. Coordinaiton and Decomissioning: the NSFNET and the Evolution of the Internet in the United States, 1985-95 .

    K. Teaching Methodology

    1. Kazumori, Eiichiro. 2018. Re-Imagining Introductory Economics: Efficiency Improvements from a Research-Based Instructional Platform . (Joint paper)

    K. Teaching

    K1. Introduction to Microeconomics

    1. Syllabus.

    2. Preston McAfee's Introduction to Economic Analysis.
    3. Lecture Note 1: What is Economics? ( Worksheet. )
    4. Lecture Note 2: Graphs and Functions. ( Worksheet. )
    5. Lecture Note 3: The Economic Problem. ( Worksheet )
    6. Lecture Note 4: Demand and Supply. ( Worksheet )
    7. Lecture Note 5: Elasticity ( Worksheet )
    8. Lecture Note 6: Efficiency of the MarketMechanisms ( Worksheet )
    9. Exam 1.
    10. Lecture Note 7: Consumer Demand. ( Worksheet )
    11. Lecture Note 8: Producer Supply. ( Worksheet )
    12. Lecture Note 9: Perfect Competition. ( Worksheet )
    13. Lecture Note 10: Monopoly. ( Worksheet )
    14. Lecture Note 11: Oligopoly. ( Worksheet )
    15. Exam 2.

    16. Harvard Kennedy School Policy Memo Guide. ( Video ),
    17. Simon Board on Case Presentation
    18. Policy Memo Example: "A Report to the National Security Council - NSC 68."
    19. Policy Memo Example: Minimum Wage.
    20. Case: Artificial Intelligence ( Susan Athey Videos )
    21. Case: Globalization and Unemployment ( Michael Spence Videos ).
    22. Case: Globalization and Inequality. ( Eric Maskin Videos ).
    23. Case: Emission Trading
    24. Case: Property Rights
    25. Case: The Evolution of Cooperation. ( Robert Axerlod Videos ).
    26. Case: "The Antitrust Revolution."
    27. Case: Market Design. ( Al Roth Videos )
    28. Case: NRMP
    29. Case: Kidney Exchange
    30. Case: School Choice
    31. Case: Prediction Markets.
    32. Case: Northwestern Purple Pricing. ( Jeff Ely Videos ),
    33. Case: "Feeding America" ( Canice Prendergast Videos )

    34. Case Study Preparation Guide.
    35. Case Study Example: Kayak.
    36. Case: Google
    37. Case: Yelp
    38. Case: Facebook
    39. Case: LinkedIn
    40. Case: Amazon
    41. Case: Dropbox
    42. Case: Spotify
    43. Case: Netflix
    44. Case: Tesla
    45. Case: Bitcoin
    46. Case: Uber
    47. Case: Airbnb

    K2. Re-Imagining Introductory Economics: A Market Design Approach

    1. Course Proposal
    2. Sample Lesson Plan: Autonomous Vehicles and Truck Industry (Introduction to Microeconomics)
    3. Sample Lesson Plan: Autonomous Vehicles and Economic Growth (Introduction to Macroeconomics) ( Matlab Script )
    4. Prototype Course Website (Introduction to Microeconomics)
    5. Prototype Course Website (Introduction to Macroeconomics)
    6. Preston McAfee's Introduction to Economic Analysis.
    7. Section I. Introduction
    8. Section II. Digitalization
    9. Topic 1: Google and the PageRank Algorithm (Jeff Dean Videos)
    10. Topic 2: Facebook and the Social Network
    11. Topic 3: Big Data
    12. Topic 4: Silicon Valley and Route 128
    13. Topic 5: Social Media and 2016 Presidential Election
    14. Section III Globalization and Inequality
    15. Topic 6: Apple's Global Supply Chain
    16. Topic 7: The China Syndrome?
    17. Topic 8: How Computers Changed the Labor Market
    18. Topic 9: Income Inequality in the US
    19. Topic 10: Recruiting Talents
    20. Section IV. Sharing Economy
    21. Topic 11. Uber
    22. Topic 12. Airbnb
    23. Section V. Market Design for the Social Good
    24. Topic 13. Emission Trading
    25. Topic 14. School Choice
    26. Topic 15. Kidney Exchange
    27. Topic 16. Feeding America

    K3. Mathematics for Economics

    1. Class 1: Syllabus.
    2. Class 2 and 3: Lecture Note 1: One Variable Calculus (Videos )
    3. Class 4 and 5: Lecture Note 2: Eucledean Spaces (Videos )
    4. Class 6 and 7: Lecture Note 3: Linear Independence (Videos )
    5. Class 8 and 9: Lecture Note 4: Functions of Several Variables (Videos )
    6. Class 10 and 11: Lecture Note 5: Calculus of Several Variables (Videos )
    7. Class 12 and 13: Lecture Note 6: Implicit Functions and Their Derivatives (Videos )
    8. Class 14: Homework 1 ( Hw1 Solutions )
    9. Class 14: Mathematica Homework 1 ( Mathematica Hw1 Solutions )
    10. Class 15: Exam 1
    11. Class 16 and 17: Lecture Note 7: Quadratic Forms and Definite Matrices ( Videos )
    12. Class 18 and 19: Lecture Note 8: Unconstrained Optimization ( Videos )
    13. Class 20 and 21: Lecture Note 9: Constrained Optimization ( Videos )
    14. Class 22 and 23: Lecture Note 10: Envelope Theorem ( Videos )
    15. Class 24 and 25: Lecture Note 11: Convex Analysis ( Videos )
    16. Class 26: Homework 2 ( Hw2 Solutions )
    17. Class 26: Mathematica Homework 2 ( Mathematica Hw2 Solutions )
    18. Class 27: Exam 2
    19. Class 28: Case: The Springfield Nor'easters: Maximizing Revenues in the Minor Leagues, Case: Hanson Production: Pricing for Opening Day
    20. Class 29: Case: Price Discrimination in Broadway Theatre , Case: The Fashion Channel
    21. Class 30: Case: Avari Ramada Hotel: Pricing Hotel Rooms

    K4. Introduction to Auction Theory and Applications

    K5. Introduction to Options, Futures, and Derivatives

    1. Class 1: Syllabus, Lecture Note 1: Introduction, ( Videos )
    2. Class 2 and 3: Lecture Note 2: Mechanics of Futures Markets ( Videos )
    3. Class 4 and 5: Lecture Note 3: Hedging Strategies Using Futures ( Videos )
    4. Class 6 and 7: Lecture Note 4: Interest Rates ( Videos )
    5. Class 8 and 9: Lecture Note 5: Determination of Forward and Futures Prices ( Videos )
    6. Class 10: Homework 1 ( Hw1 Solutions )
    7. Class 11: Bloomberg Homework 1 ( Bloomberg Hw1 Solutions )
    8. Class 12: Exam 1 ,
    9. Class 13 and 14: Lecture Note 6: Interest Rate Futures ( Videos )
    10. Class 15 and 16: Lecture Note 7: Swaps ( Videos )
    11. Class 17 and 18: Lecture Note 8: Mechanics of Options Markets ( Videos )
    12. Class 19 and 20: Lecture Note 9: Properties of Stock Options ( Videos )
    13. Class 21 and 22: Lecture Note 10: Trading Strategies Involving Options ( Videos )
    14. Class 23 and 24: Lecture Note 11: Binomial Trees ( Videos )
    15. Class 25: Homework 2 ( Hw2 Solutions )
    16. Class 25: Bloomberg Homework 2 ( Bloomberg Hw2 Solutions ).
    17. Class 26: Exam 2.
    18. Class 27: Case: Unusual Option Market Activity and the Terrorist Attacks of September 11, 2001
    19. Class 27: Case: Fuel Hedging at Jetblue Airways
    20. Class 28: Case: Foreign Exchange Hedging Strategies at General Motors
    21. Class 28: Case: Walmart's Use of Interest Rate Swaps
    22. Class 29: Case: Goldman Sachs and the Big Short
    23. Class 29: Case: Commercializing Biomedical Research Through Securitization Techniques. ( Andrew Lo Videos ).
    24. Class 30: Summary.

    K6. Introduction to Risk Management for Financial Institutions

    1. Class 1: Syllabus.
    2. Class 1 and 2: Lecture Note 1: CAPM ( Videos )
    3. Class 3: Lecture Note 2: Banks ( Videos )
    4. Class 4: Lecture Note 3: Insurance Companies ( Videos )
    5. Class 5: Lecture Note 4: Mutual Funds and Hedge Funds ( Videos )
    6. Class 6: Lecture Note 5: Financial Instruments ( Videos )
    7. Class 7: Lecture Note 6: Review of Options and Margins ( Videos )
    8. Class 8 and 9: Lecture Note 7: How Traders Manage Their Exposures ( Videos )
    9. Class 10 and 11: Lecture Note 8: Greek Letters ( Videos )
    10. Class 12 and 13: Lecture Note 9: Duration and Hedging of Interest Rate Risk ( Videos ),
    11. Class 14: Homework 1 ( Hw1 Solutions )
    12. Class 14: Bloomberg Homework 1 ( Bloomberg Hw1 Solutions )
    13. Class 15: Exam 1
    14. Class 16 and 17: Lecture Note 10: Value at Risk ( Videos ),
    15. Class 18: Lecture Note 11: Volatility ( Videos ),
    16. Class 19: Lecture Note 12: Correlations and Copulas ( Videos ),
    17. Class 20: Lecture Note 13: BASEL ( Videos ),
    18. Class 21 and 22: Lecture Note 14: Copulas ( Videos ),
    19. Class 23 and 24: Lecture Note 15: Credit Risk. ( Videos ).
    20. Class 25: Homework 2 ( Hw2 Solutions )
    21. Class 25: Bloomberg Homework 2 ( Bloomberg Hw2 Solutions )
    22. Class 26: Exam 2
    23. Class 27: Case: Understanding Corporate Value at Risk through a Comprehensive and Simple Example
    24. Class 27: Case: Risk Management at Wellfleet Bank
    25. Class 28: Case: Risk Management at Lehman Brothers, 2007-2008
    26. Class 28: Case: Deciphering the Liquidity and Credit Crunch 2007-2008
    27. ( Hyun Shin, Markus Brunnermeier, Harrison Hong, and Paul Krugman Videos ).
    28. Class 29: Case: The Failure Mechanics of Dealer Banks ( Darrel Duffie Videos. )
    29. Class 30: Case: BASEL III.
    30. Class 30: Case: IMF Global Financial Stability Report. ( IMF GFSR videos ).

    K7. Financial Economics.

    K8. Introduction to Market Microstructure

    1. Class 1: Syllabus.
    2. Class 1-4: Lecture Note 1: The Walrasian Asset Pricing Theory:
    3. Class 5: Institutional Background: Lecture Note 2: Instruments
    4. Class 6: Lecture Note 3: Market Participants
    5. Class 7: Lecture Note 4: Fixed Income Markets
    6. Class 8: Lecture Note 5: Equity Markets
    7. Class 9: Lecture Note 6: Currency Markets.
    8. Class 10: Models of Market Microstructure: Lecture Note 7: Market Microstructure Introduction
    9. Class 11: Lecture Note 8: Standard Auction Theory
    10. Class 12: Lecture Note 9: Double Auctions
    11. Class 13 and 14: Lecture Note 10: Continuous Auction Models
    12. Class 15 and 16: Lecture Note 11: Information-based Models of Specialist Behavior
    13. Class 17 and 18: Lecture Note 12: Inventory Model of Specialist Behavior
    14. Class 19 and 20: Lecture Note 13: Search Models of OTC Markets
    15. Class 21 and 22: Investor Behavior and Asset Pricing: Lecture Note 14: Evidences on Standard Asset Pricing Models,
    16. Class 23 and 24: Lecture Note 15: Factor Models ,
    17. Class 25 and 26: Lecture Note 16: Momentum Strategies ,
    18. Class 27 and 28: Lecture Note 17: Mutual Funds and Hedge Funds,
    19. Class 29 and 30: Lecture Note 18: Liquidity Asset Pricing.
    20. Appendix. Using the Financial Market Data: A. Bloomberg ( Note on Using Bloomberg )
    21. B. Wharton Reserch Data Services ( Note on Using WRDS )
    22. C. Nikkei Financial Database.

    K8. Teaching Evaluations

    1. Fall 2017. Introductory Microeconomics. Teaching Evaluation ("Rating the Course"). 4.83/5 and 4.53/5. Department Average 4.34/5.
    2. Spring 2015. ECO529. Teaching Evaluation. 4.5/5. Department Average 3.9/5.
    3. Spring 2015. ECO515+451. Teaching Evaluation. 4.3/5. Department Average 3.9/5.
    4. Fall 2014. ECO592. Teaching Evaluation. 4.6/5. Department Average 3.8/5.
    5. Fall 2014. ECO515+451. Teaching Evaluation. 4.1/5. Department Average 3.8/5.
    6. Spring 2014. ECO529. Teaching Evaluation.4.5/5. Department Average 3.8/5.
    7. Spring 2014. ECO515+451. Teaching Evaluation. 4.6/5. Department Average 3.8/5.
    8. Fall 2013. ECO710. Teaching Evaluation. 4.8/5. Department Average 3.8/5.
    9. Fall 2013. ECO592. Teaching Evaluation. 4.44/5. Department Average 3.8/5.
    10. Caltech. EC173. Teaching Evaluation. 6.5/7.

    L. Links

    1. Matlab Primer .
    2. Matlab Data Import and Export .
    3. Matlab Mathematics .
    4. Matlab Data Analysis .
    5. Matlab Programming Fundamentals .
    6. Matlab Graphics .
    7. Matlab Function References .
    8. Matlab Function References .

    9. PC benchmark: Geekbench.com.
    10. Laptop reviews: Notebookcheck .

    1. Research and teaching materials are currently available through research, education, and government servers. I would very much appreciate your understandings.
    2. Students fill evaluation online.
    3. "Professional Staff for Administration of Computing/Network Facilities."