ETFOptimize | High-performance ETF-based Investment Strategies

Quantitative strategies, Wall Street-caliber research, and insightful market analysis since 1998.


ETFOptimize | HOME
Close Window

Examining the limitations of digital market design for public goods

Cambridge, MA, Aug. 28, 2024 (GLOBE NEWSWIRE) -- The California electricity crisis in 2000 was one of the greatest financial disasters of the past century. Decades later, the question remained: Why did the newly created electricity markets fail? 

In his new book, “Failure by Design: The California Energy Crisis and the Limits of Market Planning”, MIT Sloan School of Management assistant professor and sociologist Georg Rilinger explores practical obstacles to market design to offer a new explanation for the crisis — one that moves beyond previous explanations that have typically blamed incompetent politicians or corrupt energy sellers. 

Rilinger reveals that the crisis was a case of market design failure. California’s electricity markets were the product of deliberate design. Market designers build digital platform architectures that structure the interactions between buyers and sellers. They pursue a distinct project of engineering, trying to nudge market actors toward desirable behavior. “This is really an experiment in social engineering,” Rilinger said. Despite careful planning by some of the world’s leading experts, California’s markets became susceptible to persistent forms of manipulative behavior that derailed designers’ goals. 

Originally a rather academic pursuit, Rilinger noted, market design is quickly becoming the guiding principle behind the organization of commerce in the digital age. As more and more of our economic life migrates into the platform economy, the opportunities for “economic engineering” multiply. If designers succeed, the markets identify the cheapest combination of generators to serve demand. In the case of electricity, the system operator always ensures that there is enough electricity to go around, and the markets are designed to identify the best way to deploy the existing generators.

“Using the creation and collapse of California’s first electricity markets as a case study, I identified several practical problems that make it difficult for market designers to strike the right balance between different strategies to enforce the desired behavior among market actors. These difficulties are particularly salient when they try to build markets for complex allocation problems,” Rilinger said. 

“While designer markets are a great tool to solve problems that are well defined and can easily be separated from their environment—like assigning students to schools, or auctioning spectrum licenses — my study suggests that they are most likely not great for problems that require the failure-resistant management of complex infrastructures — like electricity, health care, and water,” he noted. 

Why is this? A combination of factors that prevent designers from striking a workable balance among simplifying, bounding, and controlling:

  • The organizational structures that designers adopt to build complex platform markets can introduce inconsistencies that are difficult to identify and fix; this runs up against the imperative of simplification — one of the key strategies to control designer markets.  
  • Professional differences between economists, engineers, computer scientists, and other market designers can both create and obscure structural problems in different parts of the system; this tends to run up against strategies to bound and control the system effectively. 

As Rilinger shows in the book, and in the case of California, these practical obstacles to the success of the market design explain why the markets were built in a way that became susceptible to undesirable behavior — including manipulation or fraud — by market actors. They can render market design solutions infeasible when the markets are supposed to help with the management of complex infrastructures. 

“The reason is that the platform software for complex optimization problems needs to meet very high consistency standards to create the correct incentives for market actors.” Rilinger said. “This is hard to accomplish for political, organizational, and professional reasons when building complex market systems. Market designers are not a unified group of experts but come from several different disciplines that may be talking past each other, and they often have difficulty achieving political influence. It is hard to coordinate work between disparate design teams in complex organizations.”

More broadly, Rilinger’s book explores the coordination challenges involved in planning markets, to understand practical limitations of market design on its own terms. “Designers are trying to match users to behaviors that fit the logic of an algorithm that solves an optimization problem. Usually we plan organizations and most of our theories are about how we can coordinate people in organizations successfully,” Rilinger said. 

“The book suggests that planned markets operate differently than formal organizations and that we cannot simply port our organizational theories to these markets. It suggests that market planning is harder than organization design, because markets cannot necessarily rely on the cooperative orientation of employees and the managerial tools that this makes available to designers.”

Attachment


Matthew Aliberti
MIT Sloan School of Management
7815583436
malib@mit.edu

Recent Quotes

View More
Symbol Price Change (%)
AMZN  220.69
+3.55 (1.63%)
AAPL  271.49
+5.24 (1.97%)
AMD  203.78
-2.24 (-1.09%)
BAC  51.56
+0.56 (1.10%)
GOOG  299.65
+9.67 (3.33%)
META  594.25
+5.10 (0.87%)
MSFT  472.12
-6.31 (-1.32%)
NVDA  178.88
-1.76 (-0.97%)
ORCL  198.76
-11.93 (-5.66%)
TSLA  391.09
-4.14 (-1.05%)
Stock Quote API & Stock News API supplied by www.cloudquote.io
Quotes delayed at least 20 minutes.
By accessing this page, you agree to the Privacy Policy and Terms Of Service.


 

IntelligentValue Home
Close Window

DISCLAIMER

All content herein is issued solely for informational purposes and is not to be construed as an offer to sell or the solicitation of an offer to buy, nor should it be interpreted as a recommendation to buy, hold or sell (short or otherwise) any security.  All opinions, analyses, and information included herein are based on sources believed to be reliable, but no representation or warranty of any kind, expressed or implied, is made including but not limited to any representation or warranty concerning accuracy, completeness, correctness, timeliness or appropriateness. We undertake no obligation to update such opinions, analysis or information. You should independently verify all information contained on this website. Some information is based on analysis of past performance or hypothetical performance results, which have inherent limitations. We make no representation that any particular equity or strategy will or is likely to achieve profits or losses similar to those shown. Shareholders, employees, writers, contractors, and affiliates associated with ETFOptimize.com may have ownership positions in the securities that are mentioned. If you are not sure if ETFs, algorithmic investing, or a particular investment is right for you, you are urged to consult with a Registered Investment Advisor (RIA). Neither this website nor anyone associated with producing its content are Registered Investment Advisors, and no attempt is made herein to substitute for personalized, professional investment advice. Neither ETFOptimize.com, Global Alpha Investments, Inc., nor its employees, service providers, associates, or affiliates are responsible for any investment losses you may incur as a result of using the information provided herein. Remember that past investment returns may not be indicative of future returns.

Copyright © 1998-2017 ETFOptimize.com, a publication of Optimized Investments, Inc. All rights reserved.