Can intellectual property rights impact directly on productivity: a case study in manufacturing industries

According to the institutional economics thesis the role of IPRs is one of the relevant determinants of economic growth in long run. Measures of IPRs have been limited and empirical studies have not been able to evaluate their impacts on productivity growth. The major conclusion that the author can be drawn from his estimations is that the extent to which patent rights and trademarks, ceteris paribus, positively correlated with output per capita depends on the intensity of technology.

Neural networks would 'vote' according to Borda's Rule

Can neural networks learn to select an alternative based on a systematic aggregation of convicting individual preferences (i.e. a 'voting rule')? And if so, which voting rule best describes their behavior? We show that a prominent neural network can be trained to respect two fundamental principles of voting theory, the unanimity principle and the Pareto property. Building on this positive result, we train the neural network on profiles of ballots possessing a Condorcet winner, a unique Borda winner, and a unique plurality winner, respectively. We investigate which social outcome the trained neural network chooses, and find that among a number of popular voting rules its behavior mimics most closely the Borda rule. Indeed, the neural network chooses the Borda winner most often, no matter on which voting rule it was trained. Neural networks thus seem to give a surprisingly clear-cut answer to one of the most fundamental and controversial problems in voting theory: the determination of the most salient election method.