High precision registration of complicated longitudinal and cross-sectional data

In the article are given examples showing how, by using musical notation in registering (complicated) developments, considerably more qualitative variables may be taken into account than we were used to; furthermore, the temporal element may be represented with a degree of precision that corresponds to our needs. In case of cross-sectional data modifications of musical notation may be used. However, we have to recognize that there are also variables, maybe important ones, that — for several reasons — cannot be registered with a very high precision. Other complications are hinted at. The method described is rather a working method by means of which to improve the basis for a further quantitative analysis than a method suitable for showing final research results.     

Distortionary company car taxation: deadweight losses through increased car ownership

We analyse the effects of distortionary company car taxation through increased household car consumption for the Netherlands. We use several identification strategies and demonstrate that for about 20 % of households company car possession increases car ownership. The annual welfare loss of distortionary company taxation through increased car ownership is generally rather small, maximally €120 per company car, and much less than the welfare loss through increased expenditure on the company car. However, for policies that exempt households from paying tax on their company car, the annual deadweight loss is likely higher. Our first-best tax policy recommendation is to increase company car tax rates. However, our current results suggest that a second-best policy, which keeps average company car taxation constant but which reduces the marginal tax on cheaper cars and increases the marginal tax on expensive cars, would be welfare improving as overconsumption of company cars will be reduced.     

Asset pricing with adaptive learning

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy. We find that (a) recursive least squares learning has almost no effects on asset price behavior, since the algorithm converges relatively fast to rational expectations, (b) constant gain learning may contribute towards explaining the stock price and return volatility as well as the predictability of excess returns in the endowment economy but (c) in the production economy the effects of constant gain learning are mitigated by the persistence induced by capital accumulation. We conclude that in the context of these two commonly used models, standard linear self-referential learning does not resolve the asset pricing puzzles observed in the data.     

The Impact of Automation in Service Industries＂ An Empirical Study

Academic research into service industries has explored the characteristics of interpersonal interactions between employees and customers, but there are few studies addressing the issues of consumer interaction with technology and its influence on the objectives and results of the operations subsystem. This study examines the elements of the service encounter, and the changes automation originates in them and their relationships. The paper also examines changes in the elements and results of the operations subsystem, as a result of automation. We propose that the customer＇s relationship with employees and/or technology and automated systems for the service impact the objectives and results of the operations subsystem, all of which could have an effect on the company＇s competitive position. The empirical study is focused on four industries, namely, toll motorways, car parks, carwash and video/DVD rental companies, in an attempt to identify objectives that lead companies to implement automated processes affecting the customer＇s relationship with the company. The hypotheses generated are contrasted with a structural equation modelling. The results confirm that the customer＇s relationship with employees and automated systems for the service impacts the objectives and results of the operations subsystem. Also, the results show how automation can enable firms simultaneously to achieve acceptable levels of flexibility and productivity, two dimensions that have traditionally been considered opposites.     

Sovereign asset values and implications for the credit market

Using the contingent claim approach and market data on sovereign credit default swaps we assess the drivers of a country's risk perception. Deriving market-based asset values for a set of advanced economies we gain insights into the capital markets' perspectives on sovereign creditworthiness. We find the market-based asset values to be positively influenced by debt and to be an early risk indicator for economic developments. In a cross-section analysis we identify drivers of the economic risk of countries. Clustering the countries according to their debt to asset value ratios provides further insights into the market perceptions of sovereign credit risk. For example we find that the asset values of countries with higher ratios react to changes in the global equity market. Countries with a lower ratio react more to the political stability within the country.     

Barycentric algorithm for computing D-optimal size- and cost-constrained designs of experiments

In this paper, we study the problem of D-optimal experimental design under two linear constraints, which can be interpreted as simultaneous restrictions on the size and on the cost of the experiment. For computing a size- and cost-constrained approximate D-optimal design, we propose a specification of the “barycentric” multiplicative algorithm with sequential removal of redundant design points. We analytically prove convergence results for the proposed algorithm and numerically demonstrate its favorable properties compared to competing methods.     

Fundamental Drivers of Dependence in REIT Returns

We analyse the empirical relationships between firm fundamentals and the dependence structure between individual REIT and stock market returns. In contrast to previous studies, we distinguish between the average systematic risk of REITs and their asymmetric risk in the sense of a disproportionate likelihood of joint negative return clusters between REITs and the stock market. We find that REITs with low systematic risk are typically small, with low short-term momentum, low turnover, high growth opportunities and strong long-term momentum. Holding systematic risk constant, the main driving forces of asymmetric risk are leverage and, to some extent, short-term momentum. Specifically, we find that leverage has an asymmetric effect on REIT return dependence that outweighs the extent to which it increases the average sensitivity of REIT equity to market fluctuations, explaining the strong negative impact of leverage on firm performance especially during crisis periods that has been documented in recent empirical work.     

Authenticity: is it real or is it marketing?

Marty Echt, the new head of marketing at Hunsk Engines, is determined to bring the motorcycle maker back to its roots. He says it's not enough to project authenticity to customers--employees must personally subscribe to the brand's values. Should the company's CEO support Marty's "real deal" vision? Five experts comment on this fictional case study. Bruce Weindruch, the founder and CEO of the History Factory, says that an authenticity-based campaign can be effective--but only if it's truly drawn from history. Marketers like Marty often remember their organization's past in a golden haze. Weindruch recommends exploring old engineering drawings, ads, and product photos in order to understand what customers and employees really valued back in the day. Gillian Arnold, a consultant to luxury fashion and fine jewelry brands, thinks Marty's approach is right: People in key marketing posts must be passionate about their products and know them inside and out. She argues that the CEO needs to commit more fully to the new campaign and address the significant gap between the staff and the brand. James H. Gilmore and B. Joseph Pine II, the cofounders of Strategic Horizons, point out that Hunsk needs to manage customers' perceptions rather than trying to be a "real company" or forming a management team whose personal interests match the brand. People purchase a product if it conforms to their self-image; that alone determines the brand's authenticity. Glenn Brackett of Sweetgrass Rods, a maker of bamboo fly-fishing rods, says Marty seems to be one of the few people who understand Hunsk motorcycles. If employees bring blood, sweat, heart, and soul to a product, it will manifest that spirit, and customers will line up for it.     

Berechnung des Xgen unter Verwendung von Regressionsmethoden

The “CPI-X” regulation allows a dynamic adjustment of the revenue cap. The general X factors is a correction term for the consumer price index (CPI), since the CPI does not represent the development of the efficient costs in the network sector. This article shows how the general X factor can be calculated using regression analysis and discusses its applicability in the German regulation context. The results show that the general X factor can be calculated using suitable panel methods, but also shows the practical limits of this approach: panel models often do not converge in short time series. In addition, regression analysis can only provide a prognosis for the future general X factor if stable economic and regulation conditions can be assumed. This is currently not the case in the German regulatory context.