Optimal Contracts for Teams of Money Managers

The optimal organizational form and optimal incentive contract are characterized for a team of money managers, assuming that the investor (principal) is risk averse and that each manager's (agent's) actions affect both that manager's expected return and the correlation of returns between managers. If the managers are risk tolerant, then a noncooperative team organization and a strictly competitive contract, in which each manager is rewarded both for doing well and for doing better than the team, is the most efficient way to discourage herding within the team. This is despite the fact that, in such a contract total wages paid are a concave function of total returns, and so using the contract to discourage herding (and thus achieve lower risk) is in direct conflict with the investor's objective of using the contract to transfer risk onto the managers. As the risk aversion of both the investor and the managers increases, cooperation among managers becomes the optimal way to organize the team. For some parameter values, if everyone is risk averse, first-best can be achieved under cooperation. First-best without herding can never be achieved if the managers are risk tolerant, or if cooperation is infeasiblecontracts for teams, money managers

On the accuracy of low-order projection methods

We use low-order projection methods to compute numerical solutions of the basic neoclassical stochastic growth model. We assess the quality of the obtained solutions, and compare them to numerical approximations derived with first and second-order perturbation techniques. We show that projection methods perform surprisingly poor when the degree of approximation is very low, and we provide some intuition behind this finding.numerical accuracy

In search of grammaticalization in synchronic dialect data: General extenders in north-east England

In this paper, we draw on a socially stratified corpus of dialect data collected in north-east England to test recent proposals that grammaticalization processes are implicated in the synchronic variability of general extenders (GEs), i.e., phrase- or clause-final constructions such as and that and or something. Combining theoretical insights from the framework of grammaticalization with the empirical methods of variationist sociolinguistics, we operationalize key diagnostics of grammaticalization (syntagmatic length, decategorialization, semantic-pragmatic change) as independent factor groups in the quantitative analysis of GE variability. While multivariate analyses reveal rapid changes in apparent time to the social conditioning of some GE variants in our data, they do not reveal any evidence of systematic changes in the linguistic conditioning of variants in apparent time that would confirm an interpretation of ongoing grammaticalization. These results lead us to questio

Evaluating Approximate Equilibria of Dynamic Economic Models

This paper evaluates the performances of Perturbation Methods, the Parameterized Expectations Algorithm and Projection Methods in finding approximate decision rules of the basic neoclassical stochastic growth model. In contrast to the existing literature, we focus on comparing numerical methods for a given functional form of the approximate decision rules, and we repeat the evaluation for many di®erent parameter sets. We ¯nd that signi¯cant gains in accuracy can be achieved by moving from linear to higher-order approximations. Our results show further that among linear and quadratic approximations, Perturbation Methods yield particularly good results, whereas Projection Methods are well suited to derive higher-order approximations. Finally we show that although the structural parameters of the model economy have a large e®ect on the accuracy of numerical approximations, the ranking of competing methods is largely independent from the calibration.

Forecasting with estimated dynamic stochastic general equilibrium models: The role of nonlinearities

In this paper we study the e®ects of nonlinearities on the forecast- ing performance of a dynamic stochastic general equilibrium model. We compute ¯rst and second-order approximations to a New Keyne- sian monetary model, and use arti¯cial data to estimate the model's structural parameters based on its linear and quadratic solution. We and that, although our model in not far from being linear, the fore- casting performance improves by capturing the second-order terms in the solution. Our ¯ndings suggest that accounting for nonlinearities will improve the predictive abilities of DSGE models in many appli- cations.