Bayesian analysis of a general growth curve model with predictions using power transformations and AR(1) autoregressive dependence

In this paper, we consider a Bayesian analysis of the unbalanced (general) growth curve model with AR(1) autoregressive dependence, while applying the Box-Cox power transformations. We propose exact, simple and Markov chain Monte Carlo approximate parameter estimation and prediction of future values. Numerical results are illustrated with real and simulated data.     

Differential Recovery Migration across the Rural–Urban Gradient: Minimal and Short-Term Population Gains for Rural Disaster-Affected Gulf Coast Counties

Places affected or threatened by extreme environmental disturbances confront a number of significant issues, including whether their populations will stay the same or change through migration. Research on Hurricanes Katrina and Rita shows some displaced residents returned to their disaster-affected communities once the built environment was restored, new migrants settled in affected places as part of the rebuilding effort, and the regional migration system grew more urbanized and spatially concentrated during post-disaster years. Research also shows that not all disaster-affected places recovered their populations. Our study examines whether differential recovery is systematically patterned along the rural–urban gradient. Using U.S. Census Bureau estimates and IRS county-to-county migration data, we investigate whether the 2005 hurricane season differentially exacerbated or altered previous migration trends across a rural–urban gradient that incorporates proximity to metropolitan areas and disaster-related housing loss. We find a rural–urban differential in Gulf Coast recovery migration: The disaster boosted migration among non-metropolitan counties, yet these increases were smaller and short-lived compared to the patterns found for metropolitan counties, most especially high loss metropolitan counties. Our findings encourage theories of environmental migration to incorporate spatial differentiation and scenarios of environmental changes to account for differential impacts on settlement patterns across the rural–urban continuum.     

Self-interest and the theory of action

The concept of self-interest remains underdeveloped in sociology although central to economics. Recent methodological and social trends render sociological indifference to the concept untenable. The term has enjoyed historical predominance in the West since the sixteenth century. While it is seen in modern economics as a singular motivating force, Adam Smith regarded self-interest in economic action as necessarily moderated by sympathy. In addition to its problematic economic conceptualization self-interest has an experiential basis in unequal power relations. An alternative to the concept of self-interest is presented by Amartya Sen in his account of commitment; its inconsistencies, however, render Sen's statement unsatisfactory. Differences between present and future interests indicate that the distinction between self-interested and other-interested action is not sustainable.     

Modeling Synergy and Learning under Multiple Advanced Manufacturing Technologies

The advent of the wide variety of new, highly integrated, advanced manufacturing technologies available for acquisition by a firm's managers has brought to light an accompanying set of unexpected issues. These issues include expectations for the benefits and costs of these technologies, determining the appropriate order of implementation and finding a way to justify acquisition when many of the benefits are a function of the technology's learning and synergistic effects on other operations and technologies. We present here a model that captures the interaction effects of these highly integrated technologies and discuss the data requirements for application of the construct. We then illustrate the model's workings with a number of multitechnology examples and show the danger of ignoring the synergistic and learning effects of these technologies when considering their acquisition.     

DIVERSIFICATION GAINS FROM INCLUDING REAL ESTATE IN MIXED-ASSET PORTFOLIOS*

Diversification gains in mean-variance efficiency derived from including real estate in financial asset portfolios are examined. Optimal financial and mixed-asset portfolios were generated by selecting from an investment universe including several distinct financial and real estate media. Deficiencies of previous studies were overcome by employing data with improved representativeness and comparability. The efficient mixed-asset portfolios dominated the efficient financial asset portfolios implying that purely financial asset diversification is inefficient. The optimal mixed-asset portfolio prescribed that approximately two-thirds of the investment wealth be allocated to real estate and one-third to the financial media.     

SPECTRAL ANALYSIS IN BUSINESS FORECASTING: THE WIENER-KOLMOGOROV METHOD *

The objective of this paper is to introduce the Wiener-Kolmogorov (WK) method to business researchers and to applied workers who have an interest in spectral techniques. It is seen that the advantage of the WK method is that it provides better forecasts than autoregressive regression analysis when the order of the true autoregressive process is large. The paper outlines the steps involved in the WK method. Also discussed is a labor-saving feature to guide one at the outset as to whether the WK algorithm should be used. A numerical example is given to illustrate the application of the method in time-series forecasting.