On trends and constants in periodic autoregressions

Periodic autoregressions are characterised by autoregressive structures that vary with the season. If a time series is periodically integrated, one needs a seasonally varying differencing filter to remove the stochastic trend. When the periodic regression model contains constants and trends with unrestricted parameters, the data can show diverging seasonal deterministic trends. In this paper we derive explicit expressions for parameter restrictions that result in common deterministic trends under periodic trend stationarity and periodic integration.     

EMPIRICALLY ACCELERATED CONVERGENCE OF THE SPACINGS STATISTICS TO NORMALITY

If the asymptotic normality of a statistic is inadequate for approximating its distribution in practice, then the statistic may be transformed in order to improve the approximation by accelerating the convergence to normality. We treat a goodness-of-fit statistic, the sum of the logarithms of generalized uniform spacings introduced by Cressie (1976, 1978), in this spirit. Specifically, we apply the method of maximum likelihood to simulations of the statistic in order to estimate a power transformation, as in Box & Cox (1964), and hence develop a small sample normal approximation. This approximation provides a more versatile method of applying the statistic than currently available tables of percentiles.     

Evaluating Application Service Provisioning Using System Dynamics Methodology

Despite the hype surrounding the value‐added potential of e‐business for contemporary firms, the recent technology downturn was marked by poor customer satisfaction from investment in e‐business initiatives. An apparent mismatch between customer expectations and vendor offerings suggested a lack of appropriate methods and techniques for evaluating e‐business. This article draws from a longitudinal research study on the deployment, hosting and integration of application service provisioning (ASP), an e‐business model targeted mainly at small and medium‐sized businesses (SMBs). Using system dynamics as a methodology that addresses the inherent complexity of the ASP model, the article demonstrates how a series of complex inter‐relationships between key performance indicators (KPIs) will impact the business value for customers from ASP vendor products and services. The lessons from this research will be particularly relevant for existing and future ASP vendors and customers.     

Public and private employment over the business cycle: A ratchet theory of government growth

Previous researchers have attempted to explain the growth in the size of government over time. Some have observed a “ratchet” effect and have attributed these observed jumps in the relative size of government to ideological shifts in response to severe crises. We explain these observed ratchets as the consequence of asymmetries in the response of government employment to the business cycle. A public-choice oriented model of the employment response to the cycle is developed and applied to state and local government employment data. The data confirm the presence of ratchet effects that correspond to the business cycle. Moreover, virtually all of the growth in the ratio of state and local government employment to private employment has occurred during recessions. The authors greatly appreciate the extensive comments of Randall 0. Holcombe and the late Richard McHugh on an earlier draft of this paper. Don Bellantés work on this paper was aided by a grant from the John M. Olin Institute for Employment Practice and Policy.     

Does 'hardiness' predict adaptation to shiftwork?

This longitudinal study examined whether the dimensions of hardiness (commitment, control and challenge) predicted psychological symptoms and dissatisfaction with shiftwork, and whether or not the relationships identified were confounded with neuroticism and extraversion. Female nurses were studied during their first 15 months of shiftwork. Thirty-six nurses worked on a 2-shift (day and evening) schedule throughout and 66 transferred from the 2-shift schedule to a 3-shift (day, evening and night) schedule after 6 months. Hardiness, neuroticism, extraversion and symptoms were measured before the respondents began shiftwork (Stage 1). Symptoms and dissatisfaction were measured after 6 months (Stage 2) and 15 months (Stage 3). Multiple regressions indicated that the hardiness dimensions did not predict dissatisfaction at Stages 2 or 3, or symptoms at Stage 3. They also failed to buffer the effect of night-work on symptoms. However, commitment did predict symptoms at Stages 1 and 2 and challenge predicted symptoms at Stage 2. Although these effects were confounded with neuroticism, commitment showed weak evidence of independent prediction. In general, hardiness was a very poor predictor of shiftwork tolerance.