Ex Ante Impact Assessment under Imperfect Information: Biotechnology in New Member States of the EU

Some argue that the lack of modern agricultural development in the former socialist countries of Central and Eastern Europe has made cutting‐edge biotechnology attractive. However, enthusiasm for planting genetically modified (GM) crops varies greatly in the enlarged European Union (EU) and especially among the New Member States (NMS); the Czech GM maize area is progressively growing whereas Hungary imposed a de facto ban on GM crops. Remarkably, the Hungarian ban was not supported by any cost–benefit assessment. In the literature, ex ante impact assessments of monopolistically priced technologies are often based on cross‐sectional comparisons of average cropping budgets. Such assessments ignore heterogeneity of farmers and underestimate the true impact of these technologies because of homogeneity bias. Therefore, we propose an improved method by explicitly modelling farmer heterogeneity under imperfect information, and assess the potential value and benefit sharing of GM crops in the two NMS using a stochastic partial equilibrium model. The total potential value of GM crops is estimated at €82 million for both countries, of which €60 million (73%) accrues to farmers and €22 million (27%) to the gene developers and the seed industry. This is in line with the literature on global benefit sharing of first‐generation GM technologies.     

Tacit Knowledge: Some Suggestions for Operationalization

With the emergence of the resource-based view of the firm and of the concept of core competencies, intangible resources, and tacit knowledge in particular have been argued to occupy a central place in the development of sustainable competitive advantage. This is because tacit knowledge is argued to be difficult to imitate, to substitute, to transfer and it is rare. However, there is little empirical research to support this theoretical proposition. Tacit knowledge has so far resisted operationalization. This paper sets out to define the term tacit knowledge and proposes to redefine it, within the context of the resource-based view of the firm, as tacit skills. A methodology (based on causal mapping, self-Q and storytelling) for empirically researching the subject is outlined.     

A Note on Building a Database on Russian Banks: Fieldwork Against the Odds

This note describes how I constructed a reliable database on Russian banks in early transition. I describe in detail data sourcing, data verification and the representativeness of the resulting database. The note makes available for research a database that captures the genesis of a commercial banking system and is therefore very interesting. Moreover, the note suggests that the availability of data in Russia might in practice be better than generally perceived. Often the data do exist, but it takes a lot of time and effort to find them and turn them into a user-friendly format. Mastering the Russian language and a fair portion of perseverance are a great help in this respect.     

GORDON BROWN COUNTS DEAD CHILDREN: THE TRUE IMPACT OF INHERITANCE TAX

In the Budget and the supporting documents Gordon Brown and the Treasury reported that only 6% of estates pay Inheritance Tax and that the tax is a fair and targeted system. This article shows that for several reasons the tax affects far more than 6% of the community, is iniquitous and poorly targeted.     

Time-varying Integration and International diversification strategies

This paper investigates the impact of globalization and integration on the relative benefits of country and industry diversification. Unlike previous models, our factor model allows asset exposures and volatilities to vary with both structural changes and temporary fluctuations in the economic and financial environment. First, we find that globalization and integration have lead to a gradual convergence of country to industry betas, especially in Europe. Second, the structurally-driven increase in market betas is accompanied by a gradual decrease in country-specific risk. Third, even though the edge has structurally decreased, geographical diversification continues being superior to industry diversification.     

An examination of the relation between asymmetric risk measures,prior returns and expected daily stock returns

We use a sample of individual firm stock returns over the 1988–2009 time period to determine whether: (1) expected daily returns are related to asymmetric risk measures, (2) expected daily returns are related to the directional change of the prior day's price, and (3) our results are robust to the addition of firm size, book-to-market equity and liquidity. We find that investors are compensated for asymmetric risk; however, the positive risk–return relation is present only for our smallest firm quintile. We find a short-term return reversal present in all subgroups, except for the largest firms in our sample. We also document that the low volatility anomaly may be related to firm size and liquidity.     

Estimation of stochastic frontier models based on multimodel inference

In most empirical studies, once the best model has been selected according to a certain criterion, subsequent analysis is conducted conditionally on the chosen model. In other words, the uncertainty of model selection is ignored once the best model has been chosen. However, the true data-generating process is in general unknown and may not be consistent with the chosen model. In the analysis of productivity and technical efficiencies in the stochastic frontier settings, if the estimated parameters or the predicted efficiencies differ across competing models, then it is risky to base the prediction on the selected model. Buckland et al. (Biometrics 53:603?C618, 1997) have shown that if model selection uncertainty is ignored, the precision of the estimate is likely to be overestimated, the estimated confidence intervals of the parameters are often below the nominal level, and consequently, the prediction may be less accurate than expected. In this paper, we suggest using the model-averaged estimator based on the multimodel inference to estimate stochastic frontier models. The potential advantages of the proposed approach are twofold: incorporating the model selection uncertainty into statistical inference; reducing the model selection bias and variance of the frontier and technical efficiency estimators. The approach is demonstrated empirically via the estimation of an Indian farm data set.     

IT jobs: opportunities for all?

This paper examines the opportunities for the unemployed to access information technology jobs. Based on original research, it indicates that, despite initial expectations about an expanding sector of high skill, high wage jobs, recent developments indicate a tight labour market, which has created barriers to these jobs for the unemployed.     

Dealing with dualities

This paper introduces the topic of dealing with dualities, which is the theme of this special issue. We first give a short review of the notion of paradox and duality in management research. After this, we discuss the relevance of dualities for the IMP approach of analyzing industrial networks. Then, we briefly introduce the papers of and their relationship with the theme of this special issue. We conclude with some suggestions for future research.