The importance of flexible hazard functions in the analysis of organizational survival data -- experiences from a cohort of Swedish commercial banks

The survival pattern of Swedish commercial banks during the period 1830--1990 is studied by parametric and non-parametric event-history methods. In particular we study the sensitivity of the conclusions reached with respect to the model used. It is found that the hazard is inversely U-shaped, which means that models that cannot allow for this type of hazard run into difficulties. Thus two of the most popular approaches in the analysis of event history data, the Gompertz and the Weibull models produce misleading results regarding the development of the death risk of banks over time. As regards the effect of explanatory variables on survival, on the other hand, most models are found to be robust and even in cases of misspecified baseline hazards, the estimated effects of the explanatory variables do not seem to be seriously wrong.     

The value of multivariate model sophistication: An application to pricing Dow Jones Industrial Average options

We assess the predictive accuracies of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set of 444 multivariate models that differ in their specification of the conditional variance, conditional correlation, innovation distribution, and estimation approach. All of the models belong to the dynamic conditional correlation class, which is particularly suitable because it allows consistent estimations of the risk neutral dynamics with a manageable amount of computational effort for relatively large scale problems. It turns out that increasing the sophistication in the marginal variance processes (i.e., nonlinearity, asymmetry and component structure) leads to important gains in pricing accuracy. Enriching the model with more complex existing correlation specifications does not improve the performance significantly. Estimating the standard dynamic conditional correlation model by composite likelihood, in order to take into account potential biases in the parameter estimates, generates only slightly better results. To enhance this poor performance of correlation models, we propose a new model that allows for correlation spillovers without too many parameters. This model performs about 60% better than the existing correlation models we consider. Relaxing a Gaussian innovation for a Laplace innovation assumption improves the pricing in a more minor way. In addition to investigating the value of model sophistication in terms of dollar losses directly, we also use the model confidence set approach to statistically infer the set of models that delivers the best pricing performances.     

Using dynamic programming with adaptive grid scheme for optimal control problems in economics

The study of the solutions of dynamic models with optimizing agents has often been limited by a lack of available analytical techniques to explicitly find the global solution paths. On the other hand, the application of numerical techniques such as dynamic programming to find the solution in interesting regions of the state was restricted by the use of fixed grid size techniques. Following Grüne (Numer. Math. 75 (3) (1997) 319; University of Bayreuth, submitted, 2003), in this paper an adaptive grid scheme is used for finding the global solutions of discrete time Hamilton–Jacobi–Bellman equations. Local error estimates are established and an adapting iteration for the discretization of the state space is developed. The advantage of the use of adaptive grid scheme is demonstrated by computing the solutions of one- and two-dimensional economic models which exhibit steep curvature, complicated dynamics due to multiple equilibria, thresholds (Skiba sets) separating domains of attraction and periodic solutions. We consider deterministic and stochastic model variants. The studied examples are from economic growth, investment theory, environmental and resource economics.     

Nonlinearity and temporal dependence

Nonlinearities in the drift and diffusion coefficients influence temporal dependence in diffusion models. We study this link using three measures of temporal dependence: ρ-mixing$\rho \text{-}mixing$, β-mixing$\beta \text{-}mixing$ and α-mixing$\alpha \text{-}mixing$. Stationary diffusions that are ρ-mixing$\rho \text{-}mixing$ have mixing coefficients that decay exponentially to zero. When they fail to be ρ-mixing$\rho \text{-}mixing$, they are still β-mixing$\beta \text{-}mixing$ and α-mixing$\alpha \text{-}mixing$; but coefficient decay is slower than exponential. For such processes we find transformations of the Markov states that have finite variances but infinite spectral densities at frequency zero. The resulting spectral densities behave like those of stochastic processes with long memory. Finally we show how state dependent, Poisson sampling alters the temporal dependence.     

In search of advice for participants in matching markets which use the deferred-acceptance algorithm

Many centralized entry-level labor markets use the firm-proposing deferred-acceptance (DA) algorithm to compute the matching that is implemented among workers and firms. We propose a definition of the strategic options a worker faces in the DA-algorithm. Then we develop a theory to advise workers who distinguish between the firms from which they believe not to receive a proposal, the firms from which they might receive a proposal, and the firms from which they certainly receive a proposal. If a worker is not able to deduce which new proposals she receives after having rejected others, then it is not profitable for her to submit a list that reverses the true ranking of any two acceptable firms. Furthermore, it is not beneficial for her to include a firm in her submitted list that is unacceptable to her.     

Effects of social capital on processes in a regional strategic network

Understanding the role of social capital is vital for implementing cluster policies as regional strategic networks and cluster initiatives are influenced by the local socio-economic context and its social capital. Social capital can create value for companies by closure of the network structure (bonding), which maintains internal mutual trust but bonding can also over-embed companies in their social context, whereas sparse networks that provide links to other parts of relevant business networks (bridging) often provide greater innovation benefits. We provide a conceptual framework applied to a case study of a Swedish regional strategic network, and examples mostly of positive effects of bridging social capital and negative effects of the bonding form are identified. This is interpreted against the background of the regional dependence-oriented culture.     

Trust breeds trust: How taxpayers are treated

Tax compliance has been studied in economics by analysing the individual decision of a representative person between paying and evading taxes. A neglected aspect of tax compliance is the interaction of taxpayers and tax authorities. The relationship between the two actors can be understood as an implicit or “psychological” contract. Studies on tax evasion in Switzerland show that the more strongly the political participation rights are developed, the more important this contract is, and the higher tax morale is. In this paper, empirical evidence based on a survey of tax authorities of the 26 Swiss states (cantons) is presented, indicating that the differences in the treatment of taxpayers by tax authorities can be explained by differences in political participation rights as well. Received: June 2000 / accepted: November 2000     

Messaging specifications, properties and gratifications as institutions: How messaging institutions shaped wireless service diffusion in Norway and Japan

We address the following question: why have a large number of mobile services been successful in Japan but received only lukewarm response in Norway despite Norway’s lead in the late 1990s in wireless messaging? Current explanations are not sufficient in explaining this dilemma. We approach mobile service diffusion through the lens of new institutionalism by analyzing how messaging institutions emerged both on supply and demand sides that enabled and constrained mobile service innovation. A tripartite framework of institutional fields consisting of architectural service specifications, service properties, and use gratifications is formulated. Using secondary data we show that mobile service specifications in Japan integrated better interpersonal communication and data services and thereby allowed instrumental and aesthetic properties to align with expressive properties of messaging. In Norway disjoint service specifications caused service properties and gratifications to remain disconnected, which inhibited data service adoption and channeled data service adoption towards simple SMS based messaging solutions. Differences in service specifications and prospective gratifications not only account for differences in overall service diffusion, but offer valuable insights into institutional forces that shape complex mobile service innovation.     

Strategic entrepreneurship and knowledge spillovers: spatial and aspatial perspectives

The literature in the Strategic Entrepreneurship (SE) is increasingly embracing the concept and implications of knowledge spillovers. In this paper, we add to the theoretical repertoire on SE and knowledge spillovers by investigating the types of knowledge spillovers and what they imply for various dimensions of SE. On the one hand, we distinguish between spatial and aspatial knowledge spillovers. On the other hand, we distinguish between three dimensions of SE, i.e. inputs, resource orchestration, and output. Finally, we conceptually link the various types of knowledge spillovers and dimensions of SE and discuss the implications. Doing so, we argue that spatial knowledge spillovers (inter-firm) has received the major attention in previous research in increasing the amount of ‘inputs’ dimension of SE, while the aspatial knowledge (either inter-regional or intra-firm) has been relatively neglected not only for ‘inputs’, but also for ‘resource orchestration’ dimension. At the end, the paper provides suggestions for future research.     

A model for outsourcing and governing of maintenance within the process industry

Many industrial firms motivate structural changes by an increased focus on core activities and reduced ownership of non-core activities. However, classifying maintenance activities as either core or non-core can be difficult, since maintenance is a support function strongly linked to the production core within a manufacturing firm. Based on a multiple case study that included four buying firms and four suppliers within the process industry, this paper investigates how the relative capabilities of the firms affect the governance decision about maintenance outsourcing. A conceptual framework built on a distinction between core-close and core-distant maintenance and between different maintenance capabilities is presented. The subsequent empirical analysis illustrates how the developed framework can be used for both analyzing and guiding firms’ decisions about outsourcing and governance regarding maintenance.