Does money help predict inflation? An empirical assessment for Central Europe

This paper investigates the predictive ability of money for future inflation in the Czech Republic, Hungary, Poland and Slovakia. We construct monetary indicators similar to those the European Central Bank regularly uses for monetary analysis. We find in-sample evidence that money matters for future inflation at the policy horizons that central banks typically focus on, but our pseudo out-of-sample forecasting exercise shows that money does not in general improve the inflation forecasts vis-à-vis some benchmark models such as the autoregressive process. Since at least some models containing money improve the inflation forecasts in certain periods, we argue that money still serves as a useful cross-check for monetary policy analysis.     

Ex ante or ex post competition policy? A progress report

When intervening in markets, say to block a merger, competition authorities are constrained by the limited information they have about the social desirability of the available alternatives. Compared to ex ante control, ex post control is based on the more accurate information that becomes available in the intervening period, but entails temporary losses to social welfare and reversal costs incurred to unscramble the eggs. Through a toy model, we identify situations in which the competition authority finds it optimal to commit to forego the option of ex post review in order to avoid chilling ex ante socially beneficial mergers. On the other hand, the case for ex post review is strengthened if post-merger market conducts can signal the merged firm's private information about the consequences of the merger.     

Ruin probabilities under general investments and heavy-tailed claims

In this paper, the asymptotic decay of finite time ruin probabilities is studied. An insurance company is considered that faces heavy-tailed claims and makes investments in risky assets whose prices evolve according to quite general semimartingales. In this setting, the ruin problem corresponds to determining hitting probabilities for the solution to a randomly perturbed stochastic integral equation. A large deviation result for the hitting probabilities is derived that holds uniformly over a family of semimartingales. This result gives the asymptotic decay of finite time ruin probabilities under sufficiently conservative investment strategies, including ruin-minimizing strategies. In particular, as long as the insurance company invests sufficiently conservatively, the investment strategy has only a moderate impact on the asymptotics of the ruin probability.     

The role of public intervention in R & D

The purpose of this paper is threefold: (1) we emphasize the rule of uncertainty in achieving an efficient allocation of resources to R & D activities; (2) we identify and discuss optional mechanisms that are directed at minimizing the role of uncertainty in determining R & D decisions; and (3) we analyze the role of public intervention in R & D via a formal structure. More specifically, we explain why and under what conditions a risk-averse decision-maker will invest less than a government in research and inventive activities. Sufficient conditions that lead to private underinvestment in these activities are established. Furthermore, if the option of buying information exists, then we identify a set of private governmental contracts that may lead to the acceptance of a research project that a priori is unfeasible.     

An Event Option Pricing Model with Scheduled and Unscheduled Announcement Effects

There is considerable evidence supporting the time-varying distribution of asset returns. There is also ample evidence that scheduled announcement events such as money supply announcements (in the case of foreign exchange), earnings announcements (in the case of stocks), and crop reports (in the case of commodities), as well as random unscheduled events, can affect the level and volatility of asset returns. This study provides an Event Model for European call options which explicitly addresses effects of these two classes of events. This specification requires estimation of more parameters, but it could provide a more accurate basis for pricing options than previous Poisson jump-diffusion models. Parametric analysis shows that the standard models under price the options relative to the Event Model. The Event Model may be particularly useful in pricing short-term deep out-of-the-money options when scheduled events are present in the market.     

Understanding discontinuance: Towards a more realistic model of technological innovation and industrial adoption in Britain

The paper outlines the ideas and theory behind a recently begun research project. The project consists of an investigation of the complexities, and particularly the problems, inherent in introducing technological innovation into production systems in industry. The practical and theoretical need for work of this kind is examined and the character and focus of the proposed investigation sketched. The concept of “discontinuance” is analysed and seen to apply both to the cessation of innovation production by a supplier and the termination of innovation usage by an adoptor. Rogers and Shoemaker's (1971) division of adoptor discontinuance into “replacement” and “disenchantment” discontinuance is considered and reformulated using the terms “replacement adoption”, “negative changeover effects” and “regressive discontinuance”. Finally, a number of models both of innovation development and innovation adoption are considered, synthesized and revised. An initial framework for the comprehension of innovation development and adoption is sketched and some of the potentially important issues therein are highlighted.     

A note on Model Reference Adaptive System (MRAS) estimate with infinite variance

This paper discusses the estimation of a parameter in an autoregressive model with infinite variance. A recursive estimation procedure based on minimizing the prediction errors is provided. It is also shown that the model reference adaptive system estimate for an AR (1) model given in Aase (1983) is a special case.     

A model for identifying and ranking dangerous accident locations: a case study in Flanders

These days, road safety has become a major concern in most modern societies. In this respect, the determination of road locations that are more dangerous than others (black spots or also called sites with promise) can help in better scheduling road safety policies. The present paper proposes a multivariate model to identify and rank sites according to their total expected cost to the society. Bayesian estimation of the model via a Markov Chain Monte Carlo approach is discussed in this paper. To illustrate the proposed model, accident data from 23,184 accident locations in Flanders (Belgium) are used and a cost function proposed by the European Transport Safety Council is adopted to illustrate the model. It is shown in the paper that the model produces insightful results that can help policy makers in prioritizing road infrastructure investments.     

On the socially optimal size of a life-saving facility

The paper examines the simultaneous problem of finding an optimal size of an intensive care unit and an optimal amount of social investment in preventive medicine. The “demand” for ICU services is assumed stochastic. The approach used is to minimize social costs involved in operating the facility and social loss stemming from deaths of untreated patients.

After deriving the optimality conditions the results are applied to recent British data