Recursos de colección
ePub-WU OAI Archive (Vienna Univ. of Econ. and B.A.) (5.708 recursos)
Repository of Vienna University of Economics and Business Administration.
Year = 2000
Repository of Vienna University of Economics and Business Administration.
Year = 2000
Cukrowski, Jacek; Fischer, Manfred M.
The paper is concerned with the impact of market research prior to integration, on
the structures of noncompetitive industries in integrated economy. The analysis focuses
on separated, single commodity, monopolistic markets with stochastic demand.
Monopolistic firms are considered in dynamic multiperiod model, where intertemporal
links are determined by expenditures on market research in a present period and benefits
from this activity (i.e., smaller variance of the prediction error) in the future. Assuming
that each firm maximizes its total discounted expected utility from profit in indefinite
time, we show that the optimal market research strategy is stationary and depends on
market size. Consequently, in the period following integration firms...
Cukrowski, Jacek; Fischer, Manfred M.
The paper presents a formal analysis which incorporates returns to transportation into a Ricardian framework to predict trade patterns. The important point to be gained from this analysis is that increasing returns to transportation, coupled with appropriate distances between trading partners can be shown to reverse Ricardian predictions even when there are no international differences in tastes, technology, or factor endowments. Additional gains from trade may emerge from reductions in aggregate delivery costs owing to scale economies. (authors' abstract)
Fischer, Manfred M.
This article views spatial analysis as a research paradigm that provides a unique set of
specialised techniques and models for a wide range of research questions in which the prime
variables of interest vary significantly over space. The heart of spatial analysis is concerned
with the analysis and modeling of spatial data. Spatial point patterns and area referenced data
represent the most appropriate perspectives for applications in the social sciences. The
researcher analysing and modeling spatial data tends to be confronted with a series of
problems such as the data quality problem, the ecological fallacy problem, the modifiable
areal unit problem, boundary and frame effects, and the...
Fischer, Manfred M.
The main objective of this paper is to provide greater understanding of the systems
of innovation approach as a flexible and useful conceptual framework for spatial innovation
analysis. It presents an effort to develop some missing links and to decrease the conceptual
noise often present in the discussions on national innovation systems. The paper specifies
elements and relations that seem to be essential to the conceptual core of the framework and
argues that there is no a priori reason to emphasize the national over the subnational
(regional) scale as an appropriate mode for analysis, irrespective of time and place. Localised
input-output relations between the actors of the...
Fischer, Manfred M.; Reismann, Martin
This paper exposes problems of the commonly used technique of splitting the available
data in neural spatial interaction modelling into training, validation, and test sets that
are held fixed and warns about drawing too strong conclusions from such static splits.
Using a bootstrapping procedure, we compare the uncertainty in the solution stemming
from the data splitting with model specific uncertainties such as parameter
initialization. Utilizing the Austrian interregional telecommunication traffic data and
the differential evolution method for solving the parameter estimation task for a fixed
topology of the network model [ i.e. J = 9] this paper illustrates that the variation due to
different resamplings is significantly larger...
Fischer, Manfred M.; Varga, Attila
Series: Discussion Papers of the Institute for Economic Geography and GIScience
Sager, Gerhard
Series: Arbeitspapiere des Forschungsinstituts für mittel- und osteuropäisches Wirtschaftsrecht
Knaus, Michael
Series: Arbeitspapiere des Forschungsinstituts für mittel- und osteuropäisches Wirtschaftsrecht
Dür, Mirjam
We investigate the problem of minimizing a nonconvex function with respect to convex constraints, and we study different techniques to compute a lower bound on the optimal value: The method of using convex envelope functions on one hand, and the method of exploiting nonconvex duality on the other hand. We investigate which technique gives the better bound and develop conditions under which the dual bound is strictly better than the convex envelope bound. As a byproduct, we derive some interesting results on nonconvex duality. (author's abstract)
Dür, Mirjam
In multiple criteria programming, a decision maker has to choose a point from the set of efficient solutions. This is usually done by some interactive procedure, where he or she moves from one efficient point to the next until an acceptable solution has been reached. It is therefore important to provide some information about the "size" of the efficient set, i.e. to know the minimum (and maximum) criterion values over the efficient set. This is a difficult problem in general. In this paper, we show that for the bicriteria problem, the problem is easy. This does not only hold for...
Pazman, Andrej; Müller, Werner
In this paper we consider optimal design of experiments in the case of correlated observations, when no replications are possible. This situation is typical when observing a random process or random field with known covariance structure. We present a theorem which demonstrates that the computation of optimum exact designs corresponds to solving minimization problems in terms of design measures. (author's abstract)
Pötzelberger, Klaus
Let P be a Borel probability measure on Rd. We characterize the maximal elements p E M(P,m) with respect to the Bishop-De Leeuw order, where p E M(P, m) if and only if p P and [supp(p)] m. The results obtained have important consequences for statistical inference, such as tests of homogeneity or multivariate cluster analysis and for the theory of comparison of experiments. (author's abstract)
Frühwirth-Schnatter, Sylvia; Otter, Thomas; Tüchler, Regina
In this paper we head for a fully Bayesian analysis of the latent class model with a priori unknown number of classes. Estimation is carried out by means of Markov Chain Monte Carlo (MCMC) methods. We deal explicitely with the consequences the unidentifiability of this type of model has on MCMC estimation. Joint Bayesian estimation of all latent variables, model parameters, and parameters determining the probability law of the latent process is carried out by a new MCMC method called permutation sampling. In a first run we use the random permutation sampler to sample from the unconstrained posterior. We will...
Kaufmann, Sylvia; Frühwirth-Schnatter, Sylvia
We consider a time series model with autoregressive conditional heteroskedasticity that is subject to changes in regime. The regimes evolve according to a multistate latent Markov switching process with unknown transition probabilities, and it is the constant in the variance process of the innovations that is subject to regime shifts. The joint estimation of the latent process and all model parameters is performed within a Bayesian framework using the method of Markov Chain Monte Carlo simulation. We perform model selection with respect to the number of states and the number of autoregressive parameters in the variance process using Bayes factors...
Frühwirth-Schnatter, Sylvia
In the present paper we study switching state space models from a Bayesian point of view. For estimation, the model is reformulated as a hierarchical model. We discuss various MCMC methods for Bayesian estimation, among them unconstrained Gibbs sampling, constrained sampling and permutation sampling. We address in detail the problem of unidentifiability, and discuss potential information available from an unidentified model. Furthermore the paper discusses issues in model selection such as selecting the number of states or testing for the presence of Markov switching heterogeneity. The model likelihoods of all possible hypotheses are estimated by using the method of bridge...
Pötzelberger, Klaus
We show that results on the characterization of admissible quantizations, which have been derived in Potzelberger [3], have to be modified in case the probability distribution has linear components. Furthermore, we provide an example, where the limit of optimal quantizations is not admissible. (author's abstract)
Frühwirth-Schnatter, Sylvia
In the present paper we explore various approaches of computing model likelihoods from the MCMC output for mixture and switching models, among them the candidate's formula, importance sampling, reciprocal importance sampling and bridge sampling. We demonstrate that the candidate's formula is sensitive to label switching. It turns out that the best method to estimate the model likelihood is the bridge sampling technique, where the MCMC sample is combined with an iid sample from an importance density. The importance density is constructed in an unsupervised manner from the MCMC output using a mixture of complete data posteriors. Whereas the importance sampling...
Davies, Brian E.; Gladwell, Graham M. L.; Leydold, Josef; Stadler, Peter F.
We give a detailed proof for two discrete analogues of Courant's Nodal Domain Theorem. (author's abstract)
Davies, Brian E.; Leydold, Josef; Stadler, Peter F.
We give a detailed proof for two discrete analogues of Courant's Nodal Domain Theorem. (author's abstract)
Leydold, Josef
We use inequalities to design short universal algorithms that can be used to generate random variates from large classes of univariate continuous or discrete distributions (including all log-concave distributions). The expected time is uniformly bounded over all these distributions for a particular generator. The algorithms can be implemented in a few lines of high level language code. (author's abstract)