Is Religion an Evolutionary Adaptation?

Religious people talk about things that cannot be seen, stories that cannot be verified, and beings and forces beyond the ordinary. Perhaps their gods are truly at work, or perhaps in human nature there is an impulse to proclaim religious knowledge. If so, it would have to have arisen by natural selection. It is hard to imagine how natural selection could have produced such an impulse. There is a debate among evolutionary scientists about whether or not there is any adaptive advantage to religion at all (Bulbulia 2004a; Atran and Norenzayan 2004). Some believe that it has no adaptive value itself and that it is just a hodge podge of of behaviors that have evolved because they are adaptive in other non-religious contexts. The agent-based simulation described in this article shows that a central unifying feature of religion, a belief in an unverifiable world, could have evolved along side of verifiable knowledge. The simulation makes use of an agent-based communication model with two types of information: verifiable information (real information) about a real world and unverifiable information (unreal information) about about an imaginary world. It examines the conditions necessary for the communication of unreal information to evolved along side the communication of real information. It offers support for the theory that religion is an adaptive complex and it disputes the theory that religion is a byproduct of unrelated adaptive processes.Religion, Myth, Deception, Empirical Reasoning, Rationality

Noise Trading, Delegated Portfolio Management, and Economic Welfare

In 1992, turnover on the New York Stock Exchange was 48 percent. While there is no convincing theoretical prediction for assessing this number, observers may have the view that turnover is very high. The increase in turnover has been accompanied by a rise in institutional ownership. A regression of turnover on institutional ownership and real commissions per share shows that institutional ownership is still highlysignificant in explaining turnover. The available evidence is at least suggestive of a causal link between turnover and institutional control. It seems difficult to explain the level of trading activity purely on the basis of 'rational' motives for trade. The authors argue that the motive stems from a contracting problem between professional traders and their clients or employers. The contracting problem in the authors model is whether the delegated portfolio manager can convince the client/employer that inactivity was his best strategy. The difficulty is that the employer cannot distinguish "actively doing nothing" in this sense from "simply doing nothing." If the contract allows a reward for not trading, portfolio managers may simply do nothing; the contract may either attract incompetent managers or lead competent managers to shirk. If this makes it impossible to reward inactivity, and limited liability prevents punishing ex post incorrect decisions, then the optimal contract may induce trading by the portfolio manager which is simply a gamble to produce a satisfactory outcome by change. The authors call this noise trading or churning and show that the noise trade will occur in equilibrium. The paper then considers the implication of noise trading for agents welfare. Noise trading would appear to be costly for the employer since it lowers the expected rate of return on the portfolio. It will benefit hedgers; if managed portfolios earn lower rates of return, then uninformed hedgers earn higher returns. The higher return earned by the hedgers effectively reduces the cost of hedging; as a result they will trade larger amounts. In turn, this increase in volume can support a larger amount of investment by an informed fund manager. If the manager earns a smaller (percentage) return on a sufficiently increased investment, then he will be better off. The model is a general equilibrium model of portfolio management in a security market. The authors conclude that a portfolio manager will frequently find that the best investment policy is simply to hold the existing portfolio. The question is whether, in this situation, he will be able to credibly convince his client or employer that he is 'actively' doing nothing. The client may instead believe that he is simply doing nothing. He may think that the portfolio manager has not spent any effort on producing information or he has no talent. The paper describes a contractualrelationship, and its economic consequences, where actively doing nothing is indistinguishable from simply doing nothing. Ultimately it is an empirical question as to when these are indistinguishable. Designing a contractual relationship for portfolio management is to a large extent a matter of maximizing this distinction. Noise trade is a manifestation of this agency problem. Because all agents objectives are specified, the authors can examine the welfare implications of this agency problem. The example discussed shows that noise trade, by making the market more liquid, can benefit everyone. This illustrates that welfare effects can be more subtle and more complex than is allowed by standard models with exogenous noise traders.

Dynamic Regulation of Fisheries: the Case of the Bowhead Whale

The regulation of fisheries often requires finding numerical solutions to dynamic optimization problems. This paper presents a version of the "multiple shooting" algorithm and uses it to approximate the dynamic solution to a fisheries problem examined by Conrad (1989): the hunting of the Bowhead whale in the Western Arctic. It is found that the inclusion of dynamic considerations can significantly alter the nature of the policy if the regulated population is not near its steady state.Bowhead whale, multiple shooting, numerical methods, regulation of fisheries., Environmental Economics and Policy,

Noise Traders

Noise traders are agents whose theoretical existence has been hypothesized as a way of solving certain fundamental problems in Financial Economics. We briefly review the literature on noise traders. The is an entry for The New Palgrave: A Dictionary of Economics, 2nd Edition (Palgrave Macmillan: New York), edited by Steven N. Durlauf and Lawrence E. Blume, forthcoming in 2008.

Resistance to Change

Established firms often fail to maintain leadership following disruptive market shifts. We argue that such firms are more prone to internal resistance. A radical adjustment of assets affects the distribution of employee rents, creating winners and losers. Losers resist large changes when strong customer goodwill cushions the consequences. Partial adaptation may lead winners to depart to form new firms with no goodwill, but no internal resistance.Resistance to Change, Leadership, Adaptation

Equilibrium Asset Prices Under Imperfect Corporate Control

Shareholders have imperfect ontrol over the decisions of the management of a firm. We integrate a widely accepted version of the separation of ownership and control -- Jensen's (1986) free cash flow theory--into a dynamic equilibrium model and study the effect of imperfect corporate control on asset prices and investment. We assume that firms are run by empire-building managers who prefer to invest all free cash flow rather than distributing it to shareholders. Sharefholders are aware of this problem but it is costly for them to intervene to increase earnings payouts. Our corporate finance approach suggests that the aggregate free cash flow of the corporate sector is an important state variable in explaining asset prices and investment. We show that the business cycle variation in free cash flow helps explain the cyclical behavior of interest rates and the yield curve. The stochastic variation in free cash flow sheds light on risk premia in corporate bonds and out-of-the-money put options. We show that the financial friction causes shocks to affect investment, and causes otherwise i.i.d. shocks to be transmitted from period to period. Unlike the existing macroeconomics literature on financial frictions, the shocks propagate through large firms and during booms.

Alien Registration- Dow, James E. (Brunswick, Cumberland County)

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