Periodic Reporting for period 3 - APMPAL-HET (Asset Prices and Macro Policy when Agents Learn and are Heterogeneous)
Reporting period: 2020-11-01 to 2022-03-31
Financial investments and policy often have to be decided in the face of partial knowledge about the economy. Dissatisfied with the conventional approaches, we have been developing two methods to address these issues. First, we develop Optimal Signal Extraction (OSE) to solve for optimal policy with partial knowledge and, second use an alternative to the standard modelling approach of consumers and investors’ expectations that we call Internally Rational (IR) learning.
The conventional approach to understand asset prices is that the price of a given asset must reflect an objective measure of it future vale. For examples, stock prices should reflect the discounted value of current and future dividends, and bond prices the value of future bond payments. This gives rise to the so- called efficient market hypothesis. Under this hypothesis policy interventions in asset markets are undesirable as they would only disrupt prices and markets that properly reflect the actual value of the asset.
In previous research we showed that stock price data could be understood much better under the hypothesis that investors can not perfectly understand how dividends are related to prices, but investors’ behavior is fully optimal given the knowledge about prices that they do have. We call this concept “internal rationality” learning. In this project we show a similar effect for bond prices, option prices and business cycle models: using survey data on bond yields and wage expectations we show the need for our expectations approach, and we find that some well known puzzles of bond price behavior can be well understood if investors in bond markets form expectations about bond yields and workers about wages.
In this setup asset prices are not efficient even if investors are very sophisticated and it leaves much more room for policy intervention in stock and bond markets.
Our project has also studied issues of redistribution of wealth through taxation, exiting the euro, risk-sharing, exchange of information and risk-sharing in networks, and income risk variability.
The conventional approach to understand asset prices is that the price of a given asset must reflect an objective measure of it future vale. For examples, stock prices should reflect the discounted value of current and future dividends, and bond prices the value of future bond payments. This gives rise to the so- called efficient market hypothesis. Under this hypothesis policy interventions in asset markets are undesirable as they would only disrupt prices and markets that properly reflect the actual value of the asset.
In previous research we showed that stock price data could be understood much better under the hypothesis that investors can not perfectly understand how dividends are related to prices, but investors’ behavior is fully optimal given the knowledge about prices that they do have. We call this concept “internal rationality” learning. In this project we show a similar effect for bond prices, option prices and business cycle models: using survey data on bond yields and wage expectations we show the need for our expectations approach, and we find that some well known puzzles of bond price behavior can be well understood if investors in bond markets form expectations about bond yields and workers about wages.
In this setup asset prices are not efficient even if investors are very sophisticated and it leaves much more room for policy intervention in stock and bond markets.
Our project has also studied issues of redistribution of wealth through taxation, exiting the euro, risk-sharing, exchange of information and risk-sharing in networks, and income risk variability.
Many other papers on the topics described have been written, they have been presented in a number of seminars and conferences in universities and policy institutions. Some papers are already being submitted to journals for publication. So far the paper “Optimal Policy under General Signal Extraction” by Hauk, Lanteri and Marcet has been published in the Journal Of Monetary Economics. Also, “Informal Risk Sharing with Local Information” by Ambrus Gao and Milan has been accepted at the Review of Economic Studies.
In the last two decades more policy institutions, including central banks, are using macroeconomic models to guide their decisions. The developments on OSE and IR in our project should allow us to develop a number of applications to policy-making that go beyond the standard approach used so far by these institutions.