Family firm’s management composition: the role played by family members’ age in TMT and supervisor levels

Quality & Quantity - Family firms (FFs) are the backbone of entrepreneurial fabric in many countries. Management of such businesses is complex because of their features: the overlap between...     

Inequality foundations of concentration measures: An application to the Hannah-Kay indices

The aim of this paper is to provide a connection between concentration and inequality. In particular, we show that the general entropy inequality indices are, among inequality measures, those consistent with the whole set of Hannah-Kay concentration indices. We isolate the inequality component underlying concentration measures, obtaining an explicit additive decomposition of the change in concentration into the change in its two components, i.e., inequality and the number of firms. This relationship proves to be valid for the whole set of Hannah-Kay concentration indices, and embodies as particular cases some others previously found in the literature. We are particularly grateful to Emilio Cerdá for helpful comments on the mathematical formulation of the paper. The second author also acknowledges support through the European Commission Project #ERBCHRXCT980248.     

A Common Pool Resource Game with Sequential Decisions and Experimental Evidence

We describe a common pool resource game in which players choose how much of the stock to extract in a sequential manner. There are two choices and one represents taking a larger proportion of the stock than the other. After a player makes a choice, the remaining stock grows at a constant rate. We consider a game with a finite number of alternating moves. It is shown that changes in the larger proportion of the stock that the players are allowed to take and the growth rate affect equilibrium, but have little effect on behavior in the laboratory. In addition to observing more cooperation than predicted, we observe that parameters that are strategically irrelevant affect behavior. The results of this research might help policy makers in developing adequate policies to prevent overexploitation of some natural renewable resources.     

Behavior in one-shot traveler’s dilemma games: model and experiments with advice

We report results of one-shot traveler’s dilemma game experiments to test the predictions of a model of introspection. The model describes a noisy out-of-equilibrium process by which players reach a decision of what to do in one-shot games. To test the robustness of the model and to compare it to other models of introspection without noise, we introduce non-binding advice. Advice has the effect of coordinating all players’ beliefs onto a common strategy. Experimentally, advice is implemented by asking subjects who participated in a repeated traveler’s dilemma game to recommend an action to subjects playing one-shot games with identical parameters. In contrast to observations, models based on best-response dynamics would predict lower claims than the advised. We show that our model’s predictions with and without advice are consistent with the data.      

ASSESSING THE EFFECT OF PUBLIC SUBSIDIES ON FIRM R&D INVESTMENT: A SURVEY

This survey examines the empirical literature on the relationship between public R&D subsidies and private R&D investment over the past five decades. The survey reveals a considerable heterogeneity of empirical results that cannot be explained fully by methodological issues. We aim to provide further explanations of the possible causes of that heterogeneity. In particular, we emphasise a set of issues that, in our view, are critical to understanding the potential effect of public R&D subsidies on private R&D spending. Special attention is paid to the dynamic aspects and composition of firm R&D, the constraints faced by the firm (such as financial constraints), and the amount and source of public subsidies. None of these issues have been investigated in depth. We formulate a set of research assumptions to guide future empirical research in this field.     

Success factors in a CRM strategy: technology is not all

Organisations today need to create, maintain and reinforce relationships with customers. Customer Relationship Management (CRM) seems to have helped firms to better understand their relationships. However, past studies have looked at technology and customer orientations (COs) as key factors. This paper aims to analyse the simultaneous effect of Market Orientation (MO) (rather than CO), Knowledge Management (KM) and other organisational factors in order to explain how to implement a successful CRM. Findings suggest that MO and KM may influence CRM success. Data also suggest that particular organisational factors such as employees, leadership and specific know-how may be key factors in determining the success of CRM. For efficiency resource management, this paper recommends to focus not as much in technology, but on programmes for selection, training and motivation of employees which may enhance CRM objectives. Companies may also pursue a higher customer value by putting in place and reinforcing KM schemes in specific know-hows about CRM.     

Institutional dimensions underlying public trust in information on technological risk

This paper examines the determinants of trust in public information on technological risk in a petrochemical complex located in Tarragona (Spain). Data from focus groups (eight) and a questionnaire survey (N = 400) are drawn together to analyse how two local communities exposed to major chemical hazards perceive information on risk and its sources. Results show how trust relies on two main factors, namely expertise and trustworthiness, that are significantly influenced by a third one, antagonism. Results also illustrate the relevance of the institutional context when understanding how communities give meaning to the available information on risk.     

Semiparametric Estimation of a Duration Model

Within the framework of the proportional hazard model proposed in Cox (1972), Han and Hausman (1990) consider the logarithm of the integrated baseline hazard function as constant in each time period. We, however, proposed an alternative semiparametric estimator of the parameters of the covariate part. The estimator is considered as semiparametric since no prespecified functional form for the error terms (or certain convolution) is needed. This estimator, proposed in Lewbel (2000) in another context, shows at least four advantages. The distribution of the latent variable error is unknown and may be related to the regressors. It takes into account censored observations, it allows for heterogeneity of unknown form and it is quite easy to implement since the estimator does not require numerical searches. Using the Spanish Labour Force Survey, we compare empirically the results of estimating several alternative models, basically on the estimator proposed in Han and Hausman (1990) and our semiparametric estimator.     

New imported inputs,new domestic products

We study the relationship between new imported inputs and the introduction of new domestic products. To this purpose, we assemble a novel data set covering 25 European countries over 1995–2007 and containing information on domestic production and bilateral trade for the universe of goods. We develop a procedure to identify new imported inputs and new domestic products, while dealing with the complications raised by the yearly changes in the commodity classifications. We augment these data with information on prices and novel estimates of quality. We organize the empirical analysis around a version of the endogenous growth model with expanding variety, in which inputs are allowed to be heterogeneous in terms of quality. In line with this framework, we find three main results. First, new imported inputs have a strong positive effect on product creation in Europe. Second, they work through a combination of mechanisms, allowing countries to benefit from both wider and better sets of intermediate products. Finally, new imported inputs give a substantial boost to output growth in manufacturing.     

When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators

The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the performance of nine improved covariance estimation procedures using daily returns of 90 highly capitalized US stocks for the period 1997–2007. We find that the usefulness of covariance matrix estimators strongly depends on the ratio between the estimation period T and the number of stocks N, on the presence or absence of short selling, and on the performance metric considered. When short selling is allowed, several estimation methods achieve a realized risk that is significantly smaller than that obtained with the sample covariance method. This is particularly true when T/N is close to one. Moreover, many estimators reduce the fraction of negative portfolio weights, while little improvement is achieved in the degree of diversification. On the contrary, when short selling is not allowed and T?>?N, the considered methods are unable to outperform the sample covariance in terms of realized risk, but can give much more diversified portfolios than that obtained with the sample covariance. When T?<?N, the use of the sample covariance matrix and of the pseudo-inverse gives portfolios with very poor performance.