Social decision rules are not immune to conflict

Why is rent-seeking so endemic in societies? Might it not be possible to design a Pareto-improving social decision rule that sidesteps the inefficient waste of resources resulting from conflict? We study this question for a multi-player contest. We assume that a benevolent planner knows the winning payoffs, the effectiveness of each rent-seeker, that the cost of expending resources is isoelastic, and that it is the same across all players. But she does not know the precise value of this elasticity. We show that this minimal lack of information leads to the impossibility of a Pareto-improving social decision rule, as long as there are at least four agents. Received: June 1999 / Accepted: January 24, 2000     

Utility and entropy

Summary. In this paper we study an astonishing similarity between the utility representation problem in economics and the entropy representation problem in thermodynamics. Received: May 17, 1999; revised version: October 16, 2000     

LIFE‐CYCLE LABOR SEARCH WITH STOCHASTIC MATCH QUALITY

In the United States, unemployment, job finding, and separation rates decline as worker age increases. To explain these facts, we build a search and matching model of the labor market that incorporates a life‐cycle structure and features random match quality as well as human capital accumulation. The calibrated model successfully reproduces the empirical patterns of unemployment and job transition rates over the life cycle and generates plausible wage implications. We then explore the efficiency implications of the model and find that the differences between the market and planner allocations are more important for older workers.     

Estimating the effect of technological factors from samples affected by collinearity: a data-weighted entropy approach

Measuring the effect of technological activities on productivity growth is an issue that attracted much attention in recent works on empirical econometric studies. Specifically, in the field of regional economics, several attempts have been made in order to quantify the contribution of R&D to labor productivity growth at a regional scale, considering both the internal R&D and the effects obtained by geographical spillovers. The results obtained, however, are characterized by a huge variability and in many cases there is no empirical evidence of positive contributions of R&D activities to productivity growth. Our argument is that this can be a consequence of dealing with samples’ affect by a high level of collinearity. This paper proposes the use of the data-weighted prior (DWP) estimator suggested by Golan (J Econom 101:165–193, 2001). The main advantage of this estimator is that it discriminates between relevant and irrelevant regressors better than other estimators when dealing with highly collinear samples. We evaluate the performance of the DWP estimator by Monte Carlo simulations and illustrate how it works by means of a real-world example.     

Competition effects in EU external aid supply tenders funded with the Pre-accession and Neighbourhood instruments

Empirica - This paper investigates empirically the competition effects on procurement costs for Europe Aid funded supply tenders in countries benefiting from the EU Pre-accession (IPA) and...     

Neural networks for estimating Macro Asset Pricing model in football clubs

The recent crisis caused by COVID-19 directly affected consumption habits and the stability sof financial markets. In particular, the football industry has been hit hard by this pandemic and therefore has more volatile stock prices. Given this new scenario, further research is needed to accurately estimate the value of the shares of football clubs. In this paper, we estimate an asset pricing model in football clubs with different compositions of risk nature using non-linear techniques of artificial neural networks. Usually, asset pricing models have been estimated with linear methods such as ordinary least squares. Our results show a precision higher than 90% for all the estimated models, which far exceeds those shown by linear methods in the previous literature. We find that the residual represents about 40% of the variance of the price-dividend ratio. Long-term risks follow in importance, and above all, the habit component and its behaviour in the face of changes. The importance of the residual component exists due to a low correlation between the asset price and consumer behaviour, but to a much lesser extent than that shown in previous studies. The estimation carried out with artificial neural networks, both the Deep Learning methods and especially the Quantum Neural Network, opens up new possibilities to estimate more efficiently the pricing of financial assets in the football industry.     

Factors that determine the degree of fulfilment of expectations for entrepreneurs from the business incubator programmes

International Entrepreneurship and Management Journal - The uncertain economic situation that was experienced because of the global financial crisis in 2008 and the exponential growth in the use of...