Goodwill write-off and financial market behaviour: An analysis of possible relationships

The aim of this contribution is to verify whether there exists a reaction of financial markets to the new accounting method for goodwill introduced by SFAS 142 and IAS 36. Our research hypothesis is that financial markets should have no significant reaction to the goodwill write-off following the impairment test, since the latter's outcome represents an economic estimate without financial significance. The hypothesis was checked by the analysis of the companies added to the Standard & Poor's Europe 350 index over a three-year period, taking note of goodwill write-off announcements and relating them with the stock market prices and their volatility. The results demonstrate a correlation between the goodwill write-off and the behaviour of financial markets, while the same connection cannot be evinced for prices volatility. Also, what comes out from our analysis is that markets need a relatively long period, over one semester, before absorbing in full the effects resulting from the write-off announcement.     

A baseline model of industry evolution

The paper analyses some general dynamic properties of industries characterized by heterogeneous firms and continuing stochastic entry.After a brief critical assessment of some significant drawbacks of recent contributions to modeling of stochastic industrial dynamics, we propose a novel analytical apparatus able to derive some generic properties of the underlying competition process combining persistent technological heterogeneity, differential growth of individual firms and turnover. The basic model, we suggest, is indeed applicable with proper modifications to a large class of evolutionary processes, well beyond industrial dynamics.JEL Classification: L11, O30, C60Support to this research by the International Institute for Applied Systems Analysis (IIASA), Austria; the Fujitsu Research Institute for Advanced Information (FRI), Japan; the Italian National Research Council (CNR), the Italian Ministry of Education, University and Research (MIUR, prot. 2002132413 003) and the Free University of Bozen Bolzano, Italy, is gratefully acknowledged. Comments by Andrea Bassanini, Francesca Chiaromonte, Steven Klepper, Uwe Cantner, Drew Fudenberg and the anonymous referees helped in shaping the paper to its present form. Mariele Berté provided the computer simulations of the model. The usual caveats apply.Correspondence to: G. Dosi     

Expropriation risk and discounting

This paper focuses on time preference and individual measures of expropriation risk. We use survey data on Italian households and on the 50+ population in eleven European countries. The surveys provide measures of discount rate and proxies for expropriation due to criminal offenses. We show that impatience increases with expropriation risk.     

Gender Differences in Recruitment Outcomes

The paper tests the hypothesis that female applicants have a lower probability of being hired from a pool of applicants than their male counterparts. The results indicate that male and female candidates have about the same probability of being hired independently of the type of vacancy. The probability of hiring a candidate of a certain sex is therefore determined by the gender composition of the pool of applicants who have selected themselves on the basis of job characteristics, hiring standards and the type of sector. This indicates that male and female job-seekers select themselves in such a way that they have equal probabilities of being accepted.     

Fitting dynamic factor models to non-stationary time series

Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some idiosyncratic behaviour of each individual series. To capture serial correlation in the common components, a dynamic structure is used as in traditional (uni- or multivariate) time series analysis of second order structure, i.e. allowing for infinite-length filtering of the factors via dynamic loadings. In this paper, motivated from economic data observed over long time periods which show smooth transitions over time in their covariance structure, we allow the dynamic structure of the factor model to be non-stationary over time by proposing a deterministic time variation of its loadings. In this respect we generalize the existing recent work on static factor models with time-varying loadings as well as the classical, i.e. stationary, dynamic approximate factor model. Motivated from the stationary case, we estimate the common components of our dynamic factor model by the eigenvectors of a consistent estimator of the now time-varying spectral density matrix of the underlying data-generating process. This can be seen as a time-varying principal components approach in the frequency domain. We derive consistency of this estimator in a “double-asymptotic” framework of both cross-section and time dimension tending to infinity. The performance of the estimators is illustrated by a simulation study and an application to a macroeconomic data set.     

ON TECHNOLOGY COMPETITION: A FORMAL ANALYSIS OF THE ‘SAILING-SHIP EFFECT’

One of the key features of our economies consists of the coexistence of different technologies supplying similar products and services. We often observe that an old technology is improved when a new one appears; behind this process of improvement often lies an intentional research activity. There thus begins a competition between the two technologies whose performances are improved via R&D. We focus our attention on this competition process and supply a formal model, based on the optimization of R&D expenditure of both technologies, which can describe the dynamics of the delayed overtaking of the new technology over the old one.     

Filling vacancies: an empirical analysis of the cost and benefit of search in the labour market

This paper investigates empirically the factors that affect the cost–benefit ratio of employers’ search. The empirical analysis is based on a small Dutch data set containing individual information on filled vacancies. It is found that firms that use advertisements during recruitment are sensitive to labour market conditions; their search cost per applicant rises (drops) in tight (slack) labour markets because of the diminished ability of advertisements to generate applicants in tight labour markets. Furthermore, it is found that the high search cost incurred by posting identical vacancies is more than compensated for by the benefits from having a larger flow of applicants.