Short Bio and Research History: Leigh Tesfatsion

Last Updated: 13 April 2025

Contact Information:
Leigh Tesfatsion
Department of Economics
Iowa State University
Ames, IA 50011-1054
https://www2.econ.iastate.edu/tesfatsi/
tesfatsi AT iastate.edu
Photo of Leigh Tesfatsion

Short Bio

Leigh Tesfatsion received the Ph.D. degree in economics from the University of Minnesota, Mpls., in 1975, with a minor in mathematics. Currently she is Professor Emerita of Economics and Courtesy Research Professor of Electrical & Computer Engineering at Iowa State University. Her principal current research areas are electric power market design and the development of Agent-based Computational Economics (ACE) platforms for the performance testing of these designs. She is the recipient of the 2020 David A. Kendrick Distinguished Service Award from the Society for Computational Economics (SCE) and an IEEE Senior Member. She has served as guest editor and associate editor for a number of journals, including the IEEE Transactions on Power Systems, the IEEE Transactions on Evolutionary Computation, the Journal of Energy Markets, the Journal of Economic Dynamics and Control, the Journal of Public Economic Theory, and Computational Economics.

Research History: A Winding Multi-Disciplinary Path

Thesis research at University of Minnesota (1974-1975) on Games, Goals, and Bounded Rationality

The key idea developed in this thesis is that boundedly-rational decision-makers can supplement partial contingency plans with goals, thus permitting actions to be undertaken in desired directions despite the absence of complete information. An expected utility model permitting goal-directed action choice is formulated and axiomatized for concrete demonstration.

Leigh Tesfatsion (1975), Two Essays on Individual Choice (pdf, 2.5MB), PhD Thesis (76-15,007), Department of Economics, University of Minnesota, Mpls., December.

Work at University of Minnesota (1974-1975) and USC (1975-1984) on Criterion Filtering (CF)

The following question arises for sequential decision-making under uncertainty: Can the associative mapping between decisions and previsioned payoffs be directly updated, without recourse to the updating of probabilities, thus providing a "Bayes' Rule for Utility"?

Criterion Filtering (CF) provides an affirmative answer to this question. CF is a learning algorithm that permits the direct updating of expected utility on the basis of sequentially realized utility outcomes, conditional on prior (initial) utility assessments.

Criterion Filtering (CF): A Dual Approach to Bayesian Inference and Adaptive Control

Work at USC (1975-1990) on Flexible Least Squares (FLS)

Flexible Least Squares (FLS) is a multicriteria optimization method for model specification. FLS permits researchers to derive a "Pareto frontier" of efficiently estimated models conditional on: (i) a given theory; (ii) a given data set; and (iii) a given collection of goodness-of-fit metrics. FLS does not require the ad-hoc specification of conventional stochastic assumptions for "residual error terms" that in fact arise from deterministic model misspecification.

Flexible Least Squares (FLS): A Multicriteria Optimization Method for Model Specification

Work at USC (1975-1990) on Adaptive Computation

An adaptive computation method is a computation method that adapts to the problem at hand rather than requiring the problem to be adapted to the method. During 1975-1990 applied mathematician Robert E. Kalaba and I developed adaptive computation methods for the solution of various types of nonlinear systems.

For example, we developed an adaptive homotopy solution algorithm able, in runtime, to detect and avoid regions where calculations are ill-conditioned due to nearby singularities or bifurcation points. This adaptive capability is achieved by replacing the standard homotopy continuation parameter, moving in a pre-set manner from 0 to 1 along the real line, with a "smart agent" able to construct and traverse an adaptively determined path from 0+0i to 1+0i in the complex plane. The smart agent decides the direction and length of its next step, given its current state, by solving a multi-criteria optimization problem requiring a trade-off between two criteria: (i) maintain a short path length from 0+0i to 1+0i; and (ii) avoid regions in the complex plane where ill-conditioning of calculations is detected.

Adaptive Computation Methods for Nonlinear Systems

Work at USC (1975-1990) and ISU (1990-present) on Modeling of Economies as Open-Ended Dynamic Systems

This work includes research on restrictions sufficient to ensure the First Welfare Theorem guaranteeing Pareto efficiency of competitive equilibria for standard finite-horizon Walrasian general equilibrium economies can be extended to overlapping generation economies.

This work also includes research on the modeling of macroeconomies as DSGL systems, where DSGL = DSG(~E) + Learning. More precisely, DSGL systems are dynamic (D), stochastic (S), and general (G) market-based systems for which decision-making agents have learning (L) capabilities. Equilibrium (E) arises endogenously (if at all) in DSGL systems as a result of successive agent interactions, not from the external imposition of equilibrium constraints.

Optimality and Efficiency of Open-Ended Dynamic Economies

Work at ISU (1990-2001) on the Blending of Game Theory with Matching Theory

Game theory research has traditionally focused on game-partner interactions assuming given game-partner matches, and matching theory research has traditionally focused on partner matching assuming given forms of matched-partner interactions. What happens if game partnering and game-partner interactions are both determined strategically over time?

Trade network games are explored for concrete demonstration. The sequential choice and refusal of trade partners (matching theory) is modeled, together with the sequential determination of trade strategies (evolutionary game theory). At the start-time for each successive trading period, traders direct trade offers to preferred trade partners and preferentially accept or refuse trade offers received from other traders, based on their own current states (data, attributes, and/or methods). Each matched pair of traders then participates in a trade process modeled as a two-player game, using trade strategies each has selected to maximize their own expected net gain conditional on their own current state. At the completion of these trade processes, each trader adaptively updates their own current state based on trade outcomes they have experienced or observed during this latest trading period.

The Trade Network Game (TNG) Laboratory is open-source software permitting the beautiful run-time visualization of endogenous trade-network formation among strategic traders (buyers, sellers, and/or dealers) in a sequential trade network game.

Endogenous Trade Network Formation and the TNG Laboratory

Work at ISU (1990-present) on Completely Agent-Based Modeling (c-ABM) and Agent-based Computational Economics (ACE)

Scientists and engineers seek to understand how real-world systems work, and how real-world systems could work better. Any modeling approach devised for such purposes must simplify reality. Ideally, however, the modeling approach should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand.

Modeling flexibility and logical rigor have been the two key goals motivating my development of completely Agent-Based Modeling (c-ABM) and Agent-based Computational Economics (ACE) for science-with-practice research. c-ABM is a variant of agent-based modeling characterized by seven modeling principles. Any model adhering to these seven modeling principles is a computational laboratory permitting explorations of computational systems in a manner analogous to biological experimentation with cultures in Petri dishes. The ACE modeling approach is a specialization of c-ABM to economic systems.

c-ABM: The Right Mathematics for Social Science? (KeynoteAddress,SSC2021)

c-ABM for Science-with-Practice Research (GMURoundtable,2025)

Work at ISU (1998-present) on Design and Performance of Grid-Supported Electric Power Markets

Power supplies and demands in grid-supported U.S. RTO/ISO-managed wholesale power markets are becoming increasingly volatile and uncertain due to: (i) increasing reliance on intermittent power suppliers, e.g., wind and PV solar power facilities not fully firmed by storage; and (ii) increasingly diverse power customers. This is hindering the ability of RTOs/ISOs to ensure the continual nodal balancing of power supplies and demands for these markets, a necessary requirement for grid reliability as well as economic efficiency.

Below are linked materials that summarize research I have conducted on proposed design changes for these markets to improve the reliability and efficiency of their operations.

Leigh Tesfatsion (2024), Economics of Grid-Supported Electric Power Markets: A Fundamental Reconsideration, Foundations and Trends in Electric Energy Systems, Vol. 8, No. 1, NOW Publishers, Delft, The Netherlands, 123pp. (Preprint,pdf), (KeyPoints,pdf).

Leigh Tesfatsion (2025), Linked Listing (pdf) of publications, reports, and presentations on the design and performance of grid-supported U.S. RTO/ISO-managed wholesale power markets.

Work at ISU (2006-present) on Integrated Transmission and Distribution (ITD) Systems

FERC Order 2222 (Final Rule) -- released by the U.S. Federal Energy Regulatory Commission in September 2020 -- encourages increased participation in grid-supported U.S. RTO/ISO-managed wholesale power markets by managed aggregations of distribution-level customers. Transactive Energy System (TES) designs, pioneered by researchers at the Pacific Northwest National Laboratory (PNNL), provide important support for FERC Order 2222 objectives. A TES design is a collection of economic and control mechanisms that allows the dynamic balancing of power supply and demand across an entire electrical infrastructure, using value as the key operational parameter.

The following materials provide pointers to my collaborative research on the conceptualization and performance testing of IDSO-managed TES designs for Integrated Transmission and Distribution (ITD) systems, supported by the development of agent-based computational platforms capturing salient features of actual U.S. ITD systems.

ITD Project: ISU Homepage

Leigh Tesfatsion (2025), "Smart Grids as Strongly Coupled Physical and Economic Systems" (Slide-Set,pdf) MSA Monthly Seminar Series, Alberta, Canada.

Work at ISU (2011-present) on Many-to-One Measurement Issues for Grid-Supported Electric Power Markets

Locational Marginal Price (LMP) settlements for grid-delivered energy in grid-supported U.S. RTO/ISO-managed wholesale power markets are conceptually problematic due to a fundamental many-to-one economic measurement problem.

LMP(b,T) ($/MWh) is a per-unit price assigned to amounts E(b,T) (MWh) of grid-delivered energy, conditional on grid delivery location b and delivery period T. Here E(b,T) denotes an accumulation of power p(t) (MW) injected and/or withdrawn at b during T, where the duration of T is measured in hours (h).

The conceptual coherency of these per-unit prices requires a unit homogeneity property: namely, given E(b,T), each energy trader must consider all possible "next" units (MWh) of grid-delivered energy at b during T to be perfect substitutes for each other. In reality, the benefit/cost valuation that a market participant or RTO/ISO assigns to each possible "next" unit (MWh) of grid-delivered energy at b during T will typically depend strongly on the dynamic properties of the particular power-path (i.e., flow of power) used to implement this delivery at b during T -- for example, the ramp-rate profile and/or the voltage profile of this power-path at b during T.

In 2022 the IEEE Working Group tasked with the revision of the 2019 IEEE Standard 1459 operational definitions for active power and other key power concepts reported that important operational issues for electric power grids can be traced back to a fundamental many-to-one physical measurement problem associated with these power definitions. Briefly stated, these definitions -- expressed in static root-mean-square time-averaged form for an electric power grid during a conventionally designated time-interval T -- can correspond to multiple underlying dynamic realities with important distinct effects on the actual physical operation of the electric power grid during T.

As detailed in the following materials, this physical measurement problem arising for power valuations is conjoined with the economic measurement probrem arising for LMP valuations in the core Optimal Power Flow (OPF) formulations currently underlying the operations of grid-supported U.S. RTO/ISO-managed wholesale power markets.

Leigh Tesfatsion (2024), "Locational Marginal Pricing: A Fundamental Reconsideration" (IEEE Xplore), IEEE Open Access Journal of Power and Energy, Vol. 11 (Feb), pp. 104-116.

Leigh Tesfatsion (2024), Economics of Grid-Supported Electric Power Markets: A Fundamental Reconsideration, Foundations and Trends in Electric Energy Systems, Vol. 8, No. 1, NOW Publishers, Delft, The Netherlands, 123pp. (Preprint,pdf), (KeyPoints,pdf). (FERCTalk,pdf).

Work at ISU (2011-present) on a proposed Linked Swing-Contract Market Design for Grid-Supported Wholesale Power Markets

The Linked Swing-Contract Market Design includes three innovative features to facilitate the efficient and reliable operation of grid-supported U.S. RTO/ISO-managed wholesale power markets as they transition to decarbonized grid operations with increasingly diverse participants. These three features can be succinctly summarized, as follows, in comparison with the current reliance of these markets on Locational Marginal Pricing (LMP):

    More emphasis on L;  Less emphasis on M;  Dynamic insurance-based valuation in place of P.

The first innovative feature is a fundamental change in the current conceptually-problematic focus of the RTO/ISO on grid-delivered energy (MWh) as the basic transacted product. Under the proposed design, the basic transacted product is instead conceived to be reserve. Here reserve consists of physically-covered insurance taking the following specific form: a contractually guaranteed availability of power production capabilities for possible RTO/ISO dispatch during designated future operating periods at designated grid locations to protect against volumetric grid risk (power imbalance).

The second innovative feature is a fundamental change in the current contractual forms for supply offers. Under the proposed design, dispatchable power resources participate as reserve suppliers in a linked collection of RTO/ISO-managed bid/offer-based forward reserve markets M(T) for future operating periods T. Reserve suppliers are permitted to submit their supply offers in a two-part pricing swing-contract form. The "swing" (flexibility) in these supply offers facilitates flexible reserve availability, enabling efficient RTO/ISO dispatch of just-in-time power deliveries at various grid locations to meet just-in-time customer power demands and grid reliability requirements. The two-part pricing feature of these supply offers permits cleared suppliers to ensure their revenue sufficiency.

The third innovative feature is a fundamental change in the current primary focus of the RTO/ISO on short-run (day-ahead, intra-day) markets for grid-delivered energy, supported by ancillary services and supplemental capacity commitment and procurement processes. Under the proposed design, the primary focus of the RTO/ISO is instead envisioned to be the advance procurement of reserve in linked bid/offer-based forward reserve markets M(T) for protection against volumetric grid risk during future operating periods T. The look-ahead horizon LAH(T) between the close of a market M(T) and the start of T can range in duration from years to seconds, as can the duration of T itself.

Leigh Tesfatsion (2021), A New Swing-Contract Design for Wholesale Power Markets, John Wiley & Sons, Inc. (IEEE Press Series on Power Engineering), Hoboken, New Jersey, USA, 288pp. (TOC/Intro/Refs;pdf), (FERCTalk,SlideSet,pdf), (WileyBookFlyer,pdf).

Work at ISU (1990-present) on A Right Mathematics for a Theory of Everything?

A Theory of Everything (ToE), the Holy Grail of physics, must encompass living entities. An essential aspect of many types of observed living entities is "encapsulated intentionality."

Encapsulated intentionality is the intrinsic, evolved, or designed ability to hide from external view a next intended action. Encapsulated intentionality can render interacting entities unpredictable to one another even if the encapsulated states (data, attributes, and/or methods) determining the intended actions of these entities do not entail true randomness.

The only mathematics known to me that permits direct modeling of encapsulated intentionality for open-ended dynamic systems of interacting entities whose dynamics are driven entirely by these interactions, conditional on initially given entity states, is completely Agent-Based Modeling (c-ABM) characterized by seven modeling principles. This suggests the following useful mathematical progression for science-with-practice research:

Vectors    →    Tensors    →    Agents

These points are discussed at greater length in the following materials:

c-ABM: A Right Mathematics for Coupled Physical and Economic Systems? (SlideSet,pdf)

Agent-Based Computational Economics: A c-ABM Approach to the Study of Economic Systems (Resource Site)

Agent-Based Computational Economics: Overview and Brief History (Book Chapter, 2023)

Selected Publications