A nonlinear simultaneous probit-model for the investigation of decision-making processes: modelling the process of setting up a family in partnerships

This article proposes an approach for modelling the interactive influences of two (or more) actors in decision-making processes. We use a nonlinear simultaneous probit-model and show how the problem of identification for estimating the relative effects of the actors can be solved. The formal model will be applied to examine the decision-making process for setting up a family in partnerships. We model a trivariate distribution consisting of the wifes’ desire to have a child or disposition toward the generative decision, the husbands’ disposition and the joint generative decision. We show how the parameter can be used to assess the relative importance of both partners’ dispositions for the decision, the reciprocal influence of both partners’ dispositions within the interaction process, and the relevance of both partners’ biographical contexts in relation to their own disposition as well as to that of the partner. The analysis is based on a three-stage estimation strategy which is implemented in MECOSA 3 and we use data from the Bamberger married couple panel.     

A Regime‐Switching Approach to Modeling Rental Prices of U.K. Real Estate Sectors

This article uses regime‐switching models of the threshold type to analyze the adjustment process of rental prices for three U.K. commercial real estate sectors over the period 1974–2008. The nonlinear models outperform their linear counterparts in in‐sample fit. Their out‐of‐sample forecasting ability is better whenever the corresponding linear models contain a significant amount of neglected nonlinearity. Regime switches are triggered when the growth rates of rental price exceed certain threshold levels. For the industrial and retail sectors such regime switches occur in situations of strong excess demand, for the office sector they occur when there is strong excess supply.     

Analysis of space–time variability in agriculture and the environment with geostatistics

This paper gives an overview of space–time variability in agriculture and the environment. Analysis is based upon geostatistics in the framework of linear regression theory. Common procedures for spatial data are extended towards the space–time domain. Several practical studies are presented. The first study describes the use of REML to estimate semi-variogram models within the presence of trends. The second study describes the use of probability maps in an environmental statistical study. The third study describes the use of geostatistics in modelling the development of a disease in cabbage. Studies are evaluated using quadratic scoring rules.     

Recognising Uniqueness in the Technology Key Learning Area: The Search for Meaning

The purpose of this study was to investigate areas of significance which were related to the understanding of technology and technology education, identified by teachers introducing the key learning area, technology, into their primary school classrooms for the first time. Working from Australia's national document on technology education, A Statement on Technology for Australian Schools (Curriculum Corporation, 1994), two teachers wrestled with how to fit this new curriculum area into their current classroom programs, their understandings of technology as a phenomenon and with their beliefs about teaching and learning in general. The study showed that the teachers made sense of technology education as it related to, from their perspectives, ideas about and aspects of primary school classrooms with which they felt comfortable. Implications for professional development include the need to acknowledge and value the prior experiences and understandings of primary teachers. The challenge for teachers in implementing technology education is gaining a conceptualisation of the learning area, which in some respects, is very like other more familiar learning areas in the primary curriculum, but in many other respects, unique.     

Resource degradation and adoption of land conservation technologies in the Ethiopian Highlands: A case study in Andit Tid,North Shewa

This paper reports results from a study of resource degradation and conservation behavior of peasant households in a degraded part of the Ethiopian highlands. Peasant households' choice of conservation technologies is modeled as a two-stage process: recognition of the erosion problem, and adoption and level of use of control practices. An ordinal logit model is used to explain parcel-level perception of the threat of the erosion problem and the extent of use of conservation practices. Results show the importance of perception of the threat of soil erosion, household, land and farm characteristics; perception of technology-specific attributes, and land quality differentials in shaping conservation decisions of peasants. Furthermore, where poverty is widespread and appropriate support policies are lacking, results indicate that population pressure per se is unable to encourage sustainable land use. The challenge of breaking the poverty-environment trap and initiating sustainable intensification thus require policy incentives and technologies that confer short-term benefits to the poor while conserving the resource base.     

The Price Impact of Lending Relationships

This study analyzes the impact of bank relationships on a firm's borrowing costs. We find that a firm's borrowing costs decrease with relationship strength, proxied by the share of bank debt provided by the lender. Borrowing costs, however, rise with relationship length. While the increase over time is weak on average, bank‐dependent borrowers face a substantial premium after several relationship years. Switching the lender initially leads to only a small price discount on average. However, the discount is considerable for borrowers that switch and had a strong relationship with their previous lender. Our results suggest that close lending relationships lead to benefits for the firm, but may also imply hold‐up costs in the long term.     

Retaining volunteers for the cause: Hope and pride associated with cause-related charity events in cancer control

Special charity events are an important source of revenue for non-profit organisations in cancer control yet volunteering is declining and turnover is high. Experiences at cause-related events may influence retention, particularly emotions connected to the cause and ceremonies which honour cancer survivors and remember loved ones. We explore the degree to which emotions associated with cause-related volunteering and collective action in the literature are felt in response to Relay For Life and what emotions predict three indicators of retention: intention to return for future events, satisfaction with volunteering, and organisational commitment. Volunteers (n = 410) completed a cross-sectional survey at Relay For Life events in Queensland, Australia. Multiple regression analyses examined whether emotions associated with events predicted each indicator of retention, adjusting for number of years spent volunteering for events. Sixty-two percent reported an intention to return the following year. The most commonly reported event-related emotions were hope, pride, and empathy (62–69%). Intention to return, satisfaction, and commitment were each significantly predicted by hope and pride. The findings suggest special charity events in cancer control could retain volunteers by fostering pride and hope (e.g., for a cancer free future); however, future prospective research which examines the mechanisms of these relationships is warranted.     

A reduced lattice model for option pricing under regime-switching

We present a binomial approach for pricing contingent claims when the parameters governing the underlying asset process follow a regime-switching model. In each regime, the asset dynamics is discretized by a Cox–Ross–Rubinstein lattice derived by a simple transformation of the parameters characterizing the highest volatility tree, which allows a simultaneous representation of the asset value in all the regimes. Derivative prices are computed by forming expectations of their payoffs over the lattice branches. Quadratic interpolation is invoked in case of regime changes, and the switching among regimes is captured through a transition probability matrix. An econometric analysis is provided to pick reasonable volatility values for option pricing, for which we show some comparisons with the existing models to assess the goodness of the proposed approach.