Spatial analysis of the U.S. lodging industry, 1963–1977

Data from the U.S. Department of Commerce Census of Business in 1963, 1972, and 1977 were compared on a state by state basis and by standard metropolitan statistical areas in order to analyze the spatial growth points of the U.S. lodging industry. The results point to major lodging growth areas in the Sunbelt states with central Florida, Las Vegas, Nevada and Hawaii as outstanding nodes of development. Metropolitan lodging growth has taken place in the Sunbelt cities with populations of 100,000 to one million, with above average growth in those cities located in the coastal zone.     

Spillovers in Space: Does Geography Matter?

Using U.S. firm level panel data we simultaneously assess the contributions to productivity of three potential sources of research and development spillovers: geographic, technological, and product market (“horizontal”). To do so, we construct new measures of geographic proximity based on the distribution of a firm's inventor locations as well as its headquarters. We find that geographic location is important for productivity, as are technology (but not product) spillovers, and that both intra and inter–regional (counties) spillovers matter. The geographic location of a firm's researchers is more important than its headquarters. These benefits may be the reason why local policy makers compete so hard for the location of local R&D labs and high tech workers.     

Crisis Management Competencies

Since public networks became widespread, doubts have arisen over how to make them succeed. Scholars have traditionally addressed the issue in different ways, thus variously shedding light on the network structure, mechanisms, or managers as predictors of the network performance. The aim of our article is to explore the possibility of an interaction effect between the abovementioned factors. Our results show that there may be a relationship between network structure, mechanisms, and managers that jointly affects network performance. Therefore, important suggestions can be made about how to manage public networks successfully: (1) ensure that your network mechanisms and managerial abilities are coherent with the structure of your network; and (2) if you are in a well-established and integrated network, allow yourself some flexibility. Data were collected through a multiple case study that focused on collaboration for joint provision of home care services in Switzerland.     

Collegiality under pressure: the effects of family demands and flexible work arrangements in the Netherlands

Collegial relationships at work have become more important now that organizations increasingly use team-based work processes. Collegiality is also facing new challenges, however: more employees are meeting heavy demands beyond the workplace and making more frequent use of flexible work arrangements. This study seeks to explain the effect of employees’ family demands on collegiality and evaluates whether the use of flexible work arrangements improves or impedes collegial behaviour. Moreover, we aim to investigate collegial behaviour as an exchange process between co-workers, and therefore also take family demands and the use of flexible work arrangements by co-workers into account as predictors of employee collegiality. Based on a sample of 1114 employees from 30 organizations, the results show that when used by the employee and co-workers, flexitime decreases collegiality. Collegiality is decreased when the employee has young children, but increased when co-workers have older children. The implications of these findings for HR practices are discussed.     

Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model

We extend the class of dynamic factor yield curve models in order to include macroeconomic factors. Our work benefits from recent developments in the dynamic factor literature related to the extraction of the common factors from a large panel of macroeconomic series and the estimation of the parameters in the model. We include these factors in a dynamic factor model for the yield curve, in which we model the salient structure of the yield curve by imposing smoothness restrictions on the yield factor loadings via cubic spline functions. We carry out a likelihood-based analysis in which we jointly consider a factor model for the yield curve, a factor model for the macroeconomic series, and their dynamic interactions with the latent dynamic factors. We illustrate the methodology by forecasting the U.S. term structure of interest rates. For this empirical study, we use a monthly time series panel of unsmoothed Fama–Bliss zero yields for treasuries of different maturities between 1970 and 2009, which we combine with a macro panel of 110 series over the same sample period. We show that the relationship between the macroeconomic factors and the yield curve data has an intuitive interpretation, and that there is interdependence between the yield and macroeconomic factors. Finally, we perform an extensive out-of-sample forecasting study. Our main conclusion is that macroeconomic variables can lead to more accurate yield curve forecasts.     

Estimating household demand for housing attributes in rent-controlled markets

We estimate the household’s marginal willingness to pay for housing attributes in the rent-controlled sector, so where rents are not freely market determined. The application of hedonic price approaches to obtain estimates of the household’s value of housing characteristics is then invalid. We apply an alternative estimation approach based on residential mobility. In our application, we focus on the households’ willingness to pay for number of rooms as well as the willingness to pay to avoid a long commuting distance. Our estimates appear plausible. For example, for households in the rent-controlled sector are willing to pay about 7% of their household income for an additional room. The implied marginal costs of commuting are about €0.17–€0.23 per (one-way) kilometre.     

The relative income hypothesis

Despite its theoretical dominance, the empirical case in favor of the permanent income hypothesis is weak. Contrary to one of its basic implications, a growing body of evidence suggests that rich households save a higher proportion of their permanent income than poor households. We propose an overlapping-generations economy where households care about relative consumption. As a result, an individual's consumption is driven by the comparison of his lifetime income and the lifetime income of his reference group; a permanent income version of Duesenberry's (1949) relative income hypothesis. Across households the savings rate increases with income while aggregate savings are independent of the income distribution.     

The impact of coding time on the estimation of school effects

Multilevel growth curve models are becoming invaluable in educational research because they model changes in student outcomes efficiently. The coding of the time variable in these models plays a crucial role as illustrated in this study for the case of a three-level quadratic growth curve model. This paper shows clearly how the choice of a time coding affects school effects estimates and their interpretation. A new definition for school effects for growth curve models with random intercepts and slopes is proposed. This study recommends that the choice of a time coding should not only be based on the ease of interpretation and model convergence but also on its consequences on the student status and growth parameter estimates. The current application illustrates that in general the school effects for student growth in well-being and language achievement in secondary school, are greater for student growth than for student status.