Discrepancies between ex ante and ex post efficiency under identical subjective probabilities

Summary. Starr (1973) showed that, if people have different subjective probabilities, ex ante and ex post efficiency conflict. Conversely, under the simple preferences that he considered, the discrepancy between ex ante and ex post efficiency disappears when subjective probabilities are identical. Here I consider identical subjective probabilities, but more general preferences. First, risk attraction is admitted. Second, I dispense with the double requirement (dubbed IZU) of additive separability and state-independence of the utility of zero-date consumption, an unrealistic requirement when modeling the investment in durable goods. I find that, under IZU, and as long as ex post preferences satisfy the natural assumption of quasiconcavity (and satisfy some technical qualifications), an ex ante efficient allocation is indeed ex post efficient, but the converse is not necessarily true under risk attraction. If, on the other hand, IZU is violated, then one can have ex ante efficient allocations that are not ex post efficient, and vice-versa, even under risk aversion. Received: June 25, 1999; revised version: March 2001     

Cost implications of improving food safety in the Dutch dairy chain

This paper examines control measures for improving food safetyin the dairy chain, using an integer linear programming model.The chain includes feed (compound feed production and delivery),farm (dairy farm) and dairy processing (transport and processingof raw milk, delivery of pasteurised milk) blocks. Results showthat 65 per cent of the maximum possible food safety improvementcan be achieved at relatively low extra cost per ton of milk(4.27), fairly evenly distributed across the blocks. Highersafety levels can be attained by increasing the farm block'scontribution, but at much higher extra cost (44.37 for the maximumattainable).     

Price and Volatility Transmission and Market Power in the German Fresh Pork Supply Chain

We investigate the relationship between the transmission of price volatility and market power in the German fresh pork supply chain. We use a theoretical model underpinning this relationship followed by an empirical application that uses monthly farm, slaughterhouse and retail pork price data for the period 2000–2011. We examine both the relationships of market power with price level transmission and price volatility transmission in the chain. We use a vector error correction model and least squares regressions to analyse price transmission and price volatility transmissions, respectively. Results show that retail market power limited both types of transmissions. Competition inducing policy measures coupled with measures that support price risk management initiatives of chain actors are suggested.     

A new methodology for the logistic analysis of evolutionary S-shaped processes: Application to historical time series and forecasting

A new multi-logistic methodology to analyze long range time series of evolutionary S-shaped processes is presented. It conceptually innovates over the traditional logistic approach. The ansatz includes computing the residuals to an optimized multi-logistic trend curve least squares fitted to the time-series data. The elements of the residuals series are checked for autocorrelations and once detected the residuals series is further analyzed to search for eventual presence of underlying periodic structures using a truncated Fourier sine series. The method foundations ensures both a universal applicability and a capacity to disclose the existence of active clocks that can be possibly traced to the driving motors of the evolutionary character of the time series, due to the responsiveness of corresponding process to the development of economic cycles. On associating these two views, it is found that the methodology has a strong potential to improve the quality of short-term forecasts. These findings have been put to test through applications of the methodology to studying the time evolution of two commodities of strong economic and social importance (corn and steel) and good results were consistently obtained for both the analytical and forecasting aspects.     

Predicting Corporate Failure Using a Neural Network Approach

This paper investigates the performance of Artificial Neural Networks for the classification and subsequent prediction of business entities into failed and non-failed classes. Two techniques, back-propagation and Optimal Estimation Theory (OET), are used to train the neural networks to predict bankruptcy filings. The data are drawn from Compustat data tapes representing a cross-section of industries. The results obtained with the neural networks are compared with other well-known bankruptcy prediction techniques such as discriminant analysis, probit and logit, as well as against benchmarks provided by directly applying the bankruptcy prediction models developed by Altman (1968) and Ohlson (1980) to our data set. We control the degree of ‘disproportionate sampling’ by creating ‘training’ and ‘testing’ populations with proportions of bankrupt firms ranging from 1% to 50%. For each population, we apply each technique 50 times to determine stable accuracy rates in terms of Type I, Type II and Total Error. We show that the performance of various classification techniques, in terms of their classification errors, depends on the proportions of bankrupt firms in the training and testing data sets, the variables used in the models, and assumptions about the relative costs of Type I and Type II errors. The neural network solutions do not achieve the ‘magical’ results that literature in this field often promises, although there are notable 'pockets' of superior performance by the neural networks, depending on particular combinations of proportions of bankrupt firms in training and testing data sets and assumptions about the relative costs of Type I and Type II errors. However, since we tested only one architecture for the neural network, it will be necessary to investigate potential improvements in neural network performance through systematic changes in neural network architecture.     

Access pricing: A comparison between full deregulation and two alternative instruments of access price regulation,cost-based and retail-minus

In this paper, two instruments of access price regulation, cost-based and retail-minus, are compared with the full deregulation hypothesis. For this purpose, a model that considers an upstream monopolist firm that sells a vital input to an independent firm and to a subsidiary firm in the downstream market is developed. The main conclusion of the paper is that retail-minus regulation avoids foreclosure and leads to better results than cost-based regulation in terms of investment level and consumer surplus. Moreover, retail-minus regulation allows a higher consumer surplus than deregulation of access price as long as the regulator carefully defines the retail-minus instrument.     

Investment, credit, and endogenous cycles

This paper presents a general-equilibrium dynamic Ramsey-type model that can generate endogenous cycle. We assume two different representative agents, borrowers and lenders, and financial intermediaries with inside and outside money. We investigate under which conditions this model presents a cyclical relationship between capital and loans. The sources of endogenous fluctuations in this model come from a credit restriction in the representative-borrower problem.     

Participating in Business-to-Business Trade Fairs: Does the Buying Function Matter?

This research aims at understanding the main reasons for business-to-business trade fair participation and for visitors' interaction with suppliers. The nature of the study is exploratory and combines qualitative interviews with trade fair organizers, experts, and trade fair participants, and a survey administered to visitors of an international trade fair held in Portugal. The study revealed that visitors do not highlight buying at these events and the most experienced visitors are the ones who devalue most buying at trade fairs. Interestingly, even when considering the most important supplier with whom visitors have interacted, they do not underline using the trade fair context to place orders. Such conclusion allows drawing managerial implications for trade fair participants and organizers.