Spare parts demand: Linking forecasting to equipment maintenance

Demand for spare parts is typically intermittent and forecasting the relevant requirements constitutes a very challenging exercise. Why is the demand for spare parts intermittent and how can we use models developed in maintenance research to forecast such demand? We attempt to answer these questions; we present a novel idea to forecast demand that relies upon the very sources of the demand generation process and we compare it with a well-known time-series method. We conclude that maintenance driven models are associated with a better performance under certain conditions. We also outline an inter-disciplinary agenda for further research in this area.     

Tunneling,propping, and expropriation: evidence from connected party transactions in Hong Kong

We examine a sample of connected transactions between Hong Kong listed companies and their controlling shareholders. We address three questions: What types of connected transactions lead to expropriation of minority shareholders? Which firms are more likely to expropriate? Does the market anticipate the expropriation by firms? On average, firms announcing connected transactions earn significant negative excess returns, significantly lower than firms announcing similar arm's length transactions. We find limited evidence that firms undertaking connected transactions trade at discounted valuations prior to the expropriation, suggesting that investors cannot predict expropriation and revalue firms only when expropriation does occur.     

Estimating the costs and benefits of soil conservation in Europe

Economics is about problems of choice. In erosion control, both public authorities and private land users are faced with such problems. What is the impact of erosion, both on-site and off-site, and to what extent can this impact be quantified? If we conceptualize this impact in terms of sustainability, how can we compare one type of effect against another? The former question can be answered only by natural scientists, the latter by economists and other social scientists. Weighing different aspects of sustainability requires value judgments, and economists are sometimes accused of having a jaundiced view of reality, wrongly supposing that decisions are based on rationality and denying the importance of emotion.However, let us assume that there is some mileage to be gained out of attempting to estimate the cost of erosion in an economic sense—which consists of converting the various effects into a common denominator: euros. If we can predict the impact of erosion control measures on erosion rates, we can know the benefit of these measures. The cost also needs to be calculated, not in terms of money but in terms of resources expended (which could have been used for other purposes) and in terms of possible negative impacts of erosion control (for instance, increased use of herbicides in reduced-tillage systems).There are important other considerations which economists may study. Firstly, there is the comparison of present versus future costs and benefits: how much can we sacrifice today for higher sustainability tomorrow?Secondly, there is the issue of private versus public costs and benefits: how do the goals of private land users differ from (those of?) the public good, how can this help us to predict land users’ behaviour, and what incentives would be appropriate to make them behave in such a way as to maximize the public good? Thirdly, how do we deal with uncertainty and risk?These problems loomed large in a study to support an extended impact assessment for the EU Soil Thematic Strategy, in 2005. Whereas much research has been done on erosion and its impact, much of this is on a small scale. The extent of the problem on a national, let alone a continental or a global scale, is still poorly known. The paper discusses how these problems were faced, which is not the same as saying they were resolved.     

On Modelling Speculative Prices: The Empirical Literature

Traditionally, financial theory and in particular asset pricing models have assumed (implicitly or explicitly) a certain probabilistic structure for speculative prices. The probabilistic structure is usually defined in terms of specific statistical models and relates to the dependence, heterogeneity and the distribution of such prices. The primary objective of this paper is to trace the development of various statistical models proposed since Bachelier (1900), in an attempt to assess how well these models capture the empirical regularities exhibited by data on speculative prices.     

Revisiting Error‐Autocorrelation Correction: Common Factor Restrictions and Granger Non‐Causality*

The paper questions the appropriateness of the practice known as ‘error‐autocorrelation correcting’ in linear regression, by showing that adopting an AR(1) error formulation is equivalent to assuming that the regressand does not Granger cause any of the regressors. This result is used to construct a new test for the common factor restrictions, as well as investigate – using Monte Carlo simulations – other potential sources of unreliability of inference resulting from this practice. The main conclusion is that when the Granger cause restriction is false, the ordinary least square and generalized least square estimators are biased and inconsistent, and using autocorrelation‐consistent standard errors does not improve the reliability of inference.