Lecture 4: Smart Contracts as a Solution to a Coordination Problem

Overview

Robert Townsend's lecture explores how smart contracts on distributed ledgers can solve coordination problems, particularly in the context of privately issued securities acting as money. He extends economic theory to incorporate risk and intertemporal exchange, using data from village India and Thailand to test implications of consumption smoothing. The lecture then delves into a formal model of fragmented markets and sequential debt issuance, demonstrating how circulating debts can function as money and how coordination failures in their issuance can lead to crises, drawing parallels to historical financial markets like London's inland bills of exchange.

Key takeaways

Economic theory predicts that in a well-functioning system, individual income shocks should be smoothed, leading to co-moving consumption patterns, a testable implication.
Data from village India shows consumption is significantly smoother than income, with only ~7% of income fluctuations appearing in consumption.
Privately issued circulating debts can function as money, but uncoordinated issuance can lead to financial crises due to a lack of information and agreement.
Achieving a complete market equilibrium (Pareto optimal allocation) in fragmented, sequential trading environments requires careful coordination of security issuance.
Smart contracts on platforms like Ethereum generalize blockchain functionality beyond simple value transfer, enabling complex conditional logic and state management.
Historical financial crises, such as those involving London's bills of exchange, can be modeled as coordination failures in the issuance of private debt instruments.

Chapters

0:00 Introduction to Smart Contracts and Coordination Problems

Lecture 4 focuses on smart contracts as a solution to coordination problems, extending distributed ledger theory to include contracting.
The policy objective is Pareto efficiency, addressing fragmented markets and privately issued securities circulating as money.
The core problem is market crises arising from a lack of coordination with smart contracts.

5:11 Economic Theory: Risk, Intertemporal Exchange, and Utility Maximization

Extending theory to explicitly include time and risk, with agents maximizing discounted expected utility.
Commodities are indexed by time and history of states, with utility derived from discounted expected utility.
The problem is framed as a lambda-weighted sum of utilities subject to resource constraints, where consumption equals income.

10:16 Lagrangian Optimization and First-Order Conditions

The maximization problem is set up as a Lagrangian with shadow prices (Lagrange multipliers).
First-order conditions equate lambda-weighted discounted marginal utility of consumption across agents and states.
This leads to a result where consumption allocation depends only on aggregate income, not individual shocks.

14:05 Mutual Insurance Society Analogy and Consumption Smoothing

The model implies a mutual insurance society where individual harvests are pooled.
Consumption depends on aggregate income, not individual shocks, suggesting consumption smoothing.
A key implication is co-movement in consumption across households; consumption should not cross.

17:00 Empirical Testing: Village India Data and Consumption Patterns

Using ICRISAT data from village India (1976-1984) to test theoretical implications.
Income fluctuations are erratic ('Rocky Mountain picture'), but grain consumption is remarkably smooth.
Only about 7% of income fluctuations translate into consumption fluctuations.

23:23 Production, Risk, and Smoothing in Thai Villages

Extending theory to include production, where consumption decisions involve reinvestment.
Producers bear risk, with idiosyncratic risk being potentially smoothable through a 'mutual fund'.
The rate of return on projects is analyzed, with significant diversification of idiosyncratic risk (around 90%).

32:19 Addressing Data Anomalies and Policy Guidance

An audience question highlights potential mismeasurement or specific events (e.g., Buriram's transitions) affecting risk calculations.
The goal is to use data to test theory and provide policy guidance.
The lecture references papers on risk-sharing theory and digital risk-sharing platforms.

36:46 Cross-Country and Cross-Regional Applications of Risk-Sharing Theory

Risk-sharing analysis extends beyond villages to entire countries (Thailand, Cote d'Ivoire) and regions.
Applications include US data on worker betas (co-movements) and EU monetary union countries' consumption patterns.
Lack of consumption co-movement in the Eurozone suggests gains from a cross-country unemployment scheme.

38:52 Privately Issued Debt as Money and Coordination Problems

Focus shifts to high-velocity private debt, or 'privately issued monies', defined by frequent appearance in exchange.
Historical examples like English inland bills of exchange (18th-19th centuries) are discussed.
The problem is a coordination failure in issuing these securities, leading to market crises.

42:28 Fragmented Markets, Sequential Trading, and Debt Chains

Retaining fragmented markets (pairwise trading) and extending to explicit dynamics (maximizing discounted utility).
Agents are self-interested maximizers, requiring computer science for coding solutions.
A model with two locations and four agents illustrates sequential trading, debt issuance, and circulating IOUs.

53:25 Limitations of Pairwise Trading and Debt Redemption

Restricting trade to pairwise and debt securities can lead to autarky (no trade) if debt cannot be redeemed.
Multilateral agreements or complete markets with state-contingent securities are needed for efficient outcomes.
The model highlights the challenge of achieving a complete market equilibrium with sequential, fragmented trading rules.

1:00:13 Payment Matrices, Velocity, and Security Notation

Defining payment matrices and velocity for consumption goods and debts (circulating and non-circulating).
Circulating debts have a velocity of 1, appearing frequently in exchange, analogous to money.
General notation is introduced for J locations and T dates, indexing commodities, endowments, consumption, and securities.

Summary, takeaways, and chapters were generated by AI from the video's transcript and may contain errors. The video belongs to its creator, MIT OpenCourseWare.