The impact of taxes and wasteful government spending on giving

We examine how taxes impact charitable giving and how this relationship is affected by the degree of wasteful government spending. In our model, individuals make donations to charities knowing that the government collects a flat-rate tax on income (net of charitable donations) and redistributes part of the tax revenue. The rest of the tax revenue is wasted. The model predicts that a higher tax rate increases charitable donations. Surprisingly, the model shows that a higher degree of waste decreases donations (when the elasticity of marginal utility with respect to consumption is high enough). We test the model’s predictions using a laboratory experiment with actual donations to charities and find that the tax rate has an insignificant effect on giving. The degree of waste, however, has a large, negative and highly significant effect on giving.

     

Accounting for preference dependency in target costing – a note

Review of Quantitative Finance and Accounting - Target costing is a well-established strategic cost management tool in theory and practice. The original target costing model implies independence of...     

Central Bank Communication and Financial Market Comovements in the Euro Area

Open Economies Review - We examine whether unscheduled communication of members of the European Central Bank’s (ECB) Governing Council affects financial market comovements. To assess...     

Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model

The aim of this paper is to extend the index of financial safety (IFS) approach with improving its predictive performance and to show the applicability of artificial neural networks to economic and financial short time series. To this end, prediction is performed by means of the nonlinear autoregressive with exogenous inputs (NARX) model that represents the neural networks and can emulate any nonlinear dynamic state space model. Thus, a NARX model, trained by means of Levenberg–Marquardt algorithm, was chosen since it gave the best performance. Results reveal that the NARX models are suitable for performing short time series composite indexes prediction.

     

Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries

This paper considers the application of copula models to study the shifts in extremal economic dependence of the Eastern European countries, i.e., Ukraine and its neighbouring countries, from 1969 to 2014. Extremal economic dependence is analysed in terms of poverty and affluence and with regard to growth rate. This paper contributes to the previous literature by applying the copula approaches to derive the measurements of the economic interdependence in terms of poverty and affluence. The received results depict the pattern of the (inter)dependence and its evolution across the analysed countries. Dependence on other countries in the extreme values can potentially be useful in adjustments of the economic policy of a country to minimize poverty and prevent high inequality.

     

Testing the bivariate mixture hypothesis using German Stock market data

According to the bivariate mixture hypothesis (BMH) as proposed by Tauchen and Pitts (1983) and Harris (1986, 1987) the daily price changes and the corresponding trading volume on speculative markets follow a joint mixture of distributions with the unobservable number of daily information events serving as the mixing variable. Using German stock market data of 15 major companies the distributional properties of the BMH is tested employing maximum-likelihood as well as generalised method of moments estimation techniques. In addition to providing a new approach for the pointwise estimation of the latent information arrival rate based on the maximum-likelihood method, we investigate the time-series properties of the BMH. the major results can be summarised as follows: (i) the distributional characteristics of the data (especially leptokurtosis and skewness in the distribution of price changes and volume respectively) cannot be explained satisfactorily by the BMH; univariate mixture models for price changes and trading volume separately reveal a possible specification error in the model; (ii) a univariate normal mixture model can account for the observed distributional characteristics of price changes; (iii) the estimated process of the latent information rate cannot fully explain the time-series characteristics of the data (especially the volatility clustering or ARCH-effects).     

Management of dispersed product development teams: the role of information technologies

In recent years, international corporations such as IBM are increasingly relying on dispersed R&D teams in order to keep pace with resource availability and the demands of global markets. The advantages of this approach arise mainly from the utilization of differences in personnel costs and gaining access to a broader knowledge base to satisfy the demands of international clients. The disadvantages of teams of this kind are obvious: geographic distances, differences in culture and work habits as well as the necessity to bridge time zones place greater demands on communication, synchronization and management.
The application of specific project management methods and the intensive use of information technology (IT) lessens the disadvantages in transnational development projects. Recently completed projects involving large-scale commercial software development at IBM demonstrate the potentials of IT in transnational development. The authors advocate the application of IT adapted to specific situations. The central fields of application of IT in dispersed R&D teams are the development of a personal network, the promotion of creativity, the exchange of technical information, and the coordination of decentralized project activities.     

Technological substitution forecasting with a model based on biological analogy

Although many models of technological substitution processes exist, only a few deal with multilevel technological substitution and still fewer may be easily applied to forecasting of real multilevel substitution processes. We propose a stochastic model of multilevel technological substitution and a forecasting method based on this model. In the author's opinion, the developed algorithm may be easily applied to forecasting various technological substitution processes. An example of the application of this algorithm to forecasting of world energy consumption is presented. The algorithm makes possible an investigation of the impact of future innovation on the system's behavior.     

Shopping hours and price competition

This paper develops an argument why retail prices may rise in response to the deregulation of opening hours. We make this point in a model of imperfect duopolistic competition. In a deregulated market retailers view the choice of opening hours as a means to increase the degree of perceived product differentiation thus relaxing price competition. If the consumers’ preference intensity for time is sufficiently high the equilibrium configuration has asymmetric shopping hours where one retailer stays open for longer than the other. Both retailers charge higher prices than under regulation, and both are strictly better off.