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National Science Foundation Award #0551175

Optimal Policy in Dynamic Informationally Constrained Economies

Investigator(s):

Aleh Tsyvinski (PI) ; Mikhail Golosov (Co-PI)

Sponsor:

National Bureau of Economic Research Inc, MA 02138 6178683900

Start Date/Expiration Date

2006-02-15 to 2007-01-31 (amended 2006-02-06)

Awarded Amount to Date:

$92,205

Abstract: This project merges techniques from public economics that analyze optimal allocations in the presence of informational frictions with the analysis of dynamic economies common in macroeconomics. The questions that motivate this project are on the intersection of macroeconomics and public economics: 1. Given an informational friction what is an efficient policy? 2. If markets are inefficient (which the investigators show is generally true in the presence of hidden trades) what should be government interventions such as bank regulations, and patents. The investigators have developed a range of techniques in a series of papers on dynamic optimal taxation. In Golosov, Kocherlakota, and Tsyvinski (2003) they derive a general characterization of the optimum for a dynamic Mirrlees economy. In Golosov and Tsyvinski (2003) they study optimal design of a disability insurance system and its implementation in the presence of dynamic private information and private savings. In Golosov and Tsyvinski (2004) they study optimal tax policy in a dynamic informationally constrained environment in the presence of endogenous private markets and they show that competitive markets with hidden trades are inefficient. This project further develops theoretical implications, describes novel applications, and provides quantitative evaluation for optimal policy in informationally constrained dynamic economies with hidden trades. They consider two questions of policy interest in which hidden trades play an important role: liquidity regulations of banks, and theory of optimal patents. While the applications are seemingly different, they share a similar theoretical structure -- how to design optimal policy in a dynamic environment in the presence of private information and hidden trades. First, they determine a general set of circumstances in which banks provide an inefficient level of liquidity in the presence of financial markets (trades), and show that a liquidity adequacy requirement implements the optimum. Second, they develop a model of innovation in which patents preclude hidden trade and copying and determine an optimal patent policy. The first part of the project studies a model of banks as providers of liquidity and risk sharing. There are two types of informational frictions in the model: unobservable demand for liquidity and the presence of financial markets. The investigators show that banks do not take into account how the contracts they offer affect prices on the financial markets and provide too little liquidity compared to the optimum. They then identify a simple intervention -- liquidity adequacy requirement -- that implements the optimal allocation. The second part of the project develops a theory of optimal patent length in a dynamic model of private innovation. The informational frictions are private information of the valuation of the good and possibility of hidden copying and production of a good. The investigators maintain that patents law, by preventing copying or production of a good, allows the innovator to price discriminate. The investigators show that optimal patent length depends on the tradeoff from the losses of price discrimination versus providing incentives to innovate. The investigators determine the optimal length of the patent for two technologies: good-embodied and externality based innovation. The results differ significantly from the literature on innovation that traditionally assumed linear prices. The investigators then provide a quantitative evaluation of both projects. They develop a calibrated general equilibrium model of liquidity provision by banks in the presence of financial markets that allows to numerically evaluate optimal regulation of financial intermediaries over the business cycle. They then study a quantitative model of innovation to determine optimal patents policy. Broader impact: The proposal will help policymakers to improve design of regulations of financial intermediaries and improve patent policy.

NSF Org:

SES - Division of Social and Economic Sciences

Award Number:

0551175

Award Instrument:

Continuing grant

Program Manager:

Daniel H. Newlon
SES Division of Social and Economic Sciences
SBE Directorate for Social, Behavioral & Economic Sciences

NSF Program(s):

ECONOMICS

Field Application(s):

Program Reference Code(s):

UNASSIGNED, 0000

Program Element Code(s):

1320