Cognitive abilities and portfolio choice

We study the relation between cognitive abilities and stockholding using the recent Survey of Health, Ageing and Retirement in Europe (SHARE), which has detailed data on wealth and portfolio composition of individuals aged 50+ in 11 European countries and three indicators of cognitive abilities: mathematical, verbal fluency, and recall skills. We find that the propensity to invest in stocks is strongly associated with cognitive abilities, for both direct stock market participation and indirect participation through mutual funds and retirement accounts. Since the decision to invest in less information-intensive assets (such as bonds) is less strongly related to cognitive abilities, we conclude that the association between cognitive abilities and stockholding is driven by information constraints, rather than by features of preferences or psychological traits.     

Innovation and the Economy

Unemployment has remained at relatively high levels across most European countries for a generation now. There have been a number of suggested explanations for this, with correspondingly different policy implications. Two of the major hypotheses relate, first, to the impact on the European economies from increased international competition, and 'globalisation' more generally, and, secondly, to the effects of new technology and innovation. The effects of both globalisation and technology on growth and employment in Europe have been researched over the past two years through an EU-funded project, the results of which, relating in particular to innovation, are reported in this Special Issue of the International Review of Applied Economics. (The results relating to globalisation were reported in a Special Issue of the Journal of Interdisciplinary Economics , Volume 13.) It is clear from the empirical work reported that the effects of technological innovation have been mixed. There is no doubt that some innovation has had a negative effect on employment, without the compensatingly positive effects that new technology usually brings in its wake. However, in high technology manufacturing sectors there is scope for boosting both productivity and employment. But this requires an appropriate policy environment, conducive to increased investment in capital, R&D and the workforce itself.     

Measuring intensity of technological change: The seismic approach

The abundance of typologies, within the economics of innovation, has resulted in the same name being used for different innovation types and the same innovation being classified under different typologies. The present research introduces the Scale of Innovation Intensity (SIIN) based on metataxonomy that subsumes other, less comprehensive taxonomies. The SIIN is similar to the seismic Mercalli's scale used to measure the intensity of earthquakes. The impact of technological change is measured by an indicator, called magnitude, based on the impact of technological innovations on the economic system. The theory is applied to some product and process innovations such as agricultural mechanization, aircraft technology, muffler catalytic, aluminum processing, etc. The results show that some innovations have a higher technological intensity and energy (economic impact) on well-being than others. Some concluding remarks are discussed in the final part of this research.     

Innovation and Productivity in European Industries

The labour productivity impact of innovation is investigated in this paper combining neo-Schumpeterian insights on the variety of innovation with the importance of industrial structures and firm size; two models are proposed for explaining productivity and export success in European manufacturing industries and firm-size classes. The empirical estimates are based on data from the European innovation survey (CIS 2), covering Austria, France, Italy, the Netherlands, and the UK, broken down by 22 sectors and for large, medium, and small firms. The econometric results, obtained adopting cross-sectional estimation methodologies able to account for unobserved industrial characteristics, show that productivity in Europe relies on product and process innovation, with the support of the efficiency gains provided by grouped business structures. Conversely, in Italy the introduction of new machinery linked to innovation appears as the key mechanism supporting domestic productivity. When export success is considered, all countries have to rely on an innovation-based model of competitiveness.     

R&D financing and growth

ABSTRACT

R&D investment are an important engine of growth and development. Yet economists have often claimed underinvestment, based on the consideration that these projects are more costly to finance, especially, due to the asymmetric information between inside and outside investors. Coherently, a recent empirical evidence has shown that firms intensively active in R&D are less leveraged and rely more heavily on internal finance. Motivated by this evidence, we study the effects of asymmetric information and financial frictions within a GE economy of Schumpeterian tradition. The model and equilibrium concept are rich enough to represent investment and innovation decisions, technology adoption/diffusion through patent licensing and, most importantly, firms' financial decisions. In this representation, R&D-intensive firms might effectively rely more on internal sources and equity than on debt financing, relative to what would happen in frictionless markets. Further, financial decisions affect aggregate investment and income dynamics.     

Markov decision processes under model uncertainty

We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle, we obtain a local-to-global paradigm, namely solving a local, that is, a one time-step robust optimization problem leads to an optimizer of the global (i.e., infinite time-steps) robust stochastic optimal control problem, as well as to a corresponding worst-case measure. Moreover, we apply this framework to portfolio optimization involving data of the . We present two different types of ambiguity sets; one is fully data-driven given by a Wasserstein-ball around the empirical measure, the second one is described by a parametric set of multivariate normal distributions, where the corresponding uncertainty sets of the parameters are estimated from the data. It turns out that in scenarios where the market is volatile or bearish, the optimal portfolio strategies from the corresponding robust optimization problem outperforms the ones without model uncertainty, showcasing the importance of taking model uncertainty into account.     

Optimal insurance under maxmin expected utility

We examine a problem of demand for insurance indemnification, when the insured is sensitive to ambiguity and behaves according to the maxmin expected utility model of Gilboa and Schmeidler (J. Math. Econ. 18:141–153, 1989), whereas the insurer is a (risk-averse or risk-neutral) expected-utility maximiser. We characterise optimal indemnity functions both with and without the customary ex ante no-sabotage requirement on feasible indemnities, and for both concave and linear utility functions for the two agents. This allows us to provide a unifying framework in which we examine the effects of the no-sabotage condition, of marginal utility of wealth, of belief heterogeneity, as well as of ambiguity (multiplicity of priors) on the structure of optimal indemnity functions. In particular, we show how a singularity in beliefs leads to an optimal indemnity function that involves full insurance on an event to which the insurer assigns zero probability, while the decision maker assigns a positive probability. We examine several illustrative examples, and we provide numerical studies for the case of a Wasserstein and a Rényi ambiguity set.