Economics Insights @ CBS

In this article, we define good scholarship, highlight our points of disagreement with Locke and Latham (2009), and call for further academic research to examine the full range of goal setting's effects. We reiterate our original claim that goal setting, like a potent medication, can produce both beneficial effects and systematic, negative outcomes, and as a result, it should be carefully prescribed and closely monitored.

Recent empirical evidence supports the view that the income process has an individual-specific growth rate component [Baker (1997), Guvenen (2007b), and Huggett, Ventura, and Yaron (2007)]. Moreover, the individual-specific growth component may be stochastic. Motivated by these empirical observations, I study an individual's optimal consumption-saving and portfolio choice problem when he does not observe his income growth. As in standard income fluctuation problems, the individual cannot fully insure himself against income shocks.

This paper provides an optimal filtering methodology in discretely observed continuous-time jump-diffusion models. Although the filtering problem has received little attention, it is useful for estimating latent states, forecasting volatility and returns, computing model diagnostics such as likelihood ratios, and parameter estimation. Our approach combines time-discretization schemes with Monte Carlo methods. It is quite general, applying in nonlinear and multivariate jump-diffusion models and models with nonanalytic observation equations.

Generalizing earlier work on staffing and routing in telephone call centers, we consider a processing network model with large server pools and doubly stochastic input flows. In this model the processing of a job may involve several distinct operations. Alternative processing modes are also allowed. Given a finite planning horizon, attention is focused on the two-level problem of capacity choice and dynamic system control. A pointwise stationary fluid model (PSFM) is used to approximate system dynamics, which allows development of practical policies with a manageable computational burden.

We investigate determinants of slave family discounts in the New Orleans slave market. We find large price discounts for families unrelated to scale effects, childcare costs, legal restrictions, or transport costs. We posit that because family members voluntarily cared for each other, sellers sometimes found it advantageous to keep families together (when families included needy or dependent members). Evidence from ship manifests carrying slaves for sale in New Orleans provides direct evidence for selectivity bias in explaining slave family discounts.