Optimal Diversity in Investments with Recombinant Innovation

The notion of dynamic, endogenous diversity and its role in theories of investment and technological innovation is addressed. We develop a formal model of an innovation arising from the combination of two existing modules with the objective to optimize the net benefits of diversity. The model takes into account increasing returns to scale and the effect of different dimensions of diversity on the probability of emergence of a third option. We obtain analytical solutions describing the dynamic behaviour of the values of the options. Next diversity is optimized by trading off the benefits of recombinant innovation and returns to scale. We derive conditions for optimal diversity under different regimes of returns to scale. Threshold values of returns to scale and recombination probability define regions where either specialization or diversity is the best choice. In the time domain, when the investment time horizon is beyond a threshold value, a diversified investment becomes the best choice. This threshold will be larger the higher the returns to scale.

The complexity of transitions

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75%-efficiency blue generation from an intracavity PPKTP frequency doubler

We report on a high-efficiency 461 nm blue light conversion from an external cavity-enhanced second-harmonic generation of a 922 nm diode laser with a quasi-phase-matched KTP crystal (PPKTP). By choosing a long crystal (LC=20 mm) and twice looser focusing (w0=43 $\mu$m) than the "optimal" one, thermal lensing effects due to the blue power absorption are minimized while still maintaining near-optimal conversion efficiency. A stable blue power of 234 mW with a net conversion efficiency of eta=75% at an input mode-matched power of 310 mW is obtained. The intra-cavity measurements of the conversion efficiency and temperature tuning bandwidth yield an accurate value d33(461 nm)=15 pm/V for KTP and provide a stringent validation of some recently published linear and thermo-optic dispersion data of KTP

Behavioural models of technological change

Technological change still remains an important driver of the economy. This thesis studies the endogenous forces of technological change stemming from behavioural interactions within populations of many agents. Four theoretical models are proposed that describe consumers’ and suppliers’ behaviour affecting decision making about technology. The models produce a rich variety of emergent patterns of simulated technologies, markets and industry dynamics. We are able to reproduce various stylized facts of technological change, including path dependence and learning curves. In two cases a policy perspective is adopted, focusing on the role of technological innovation to deal with pressing environmental and energy challenges

A discrete choice model of transitions to sustainable technologies.

We propose a discrete choice model of sustainable transitions from dirty to clean technologies. Agents can adopt one technology or the other, under the influence of social interactions and network externalities. Sustainable transitions are addressed as a multiple equilibria problem. A pollution tax can trigger a sudden transition as a bifurcation event, at the expenses of large policy efforts. Alternatively, periodic dynamics can arise. Technological progress introduced in the form of endogenous learning curves stands as a fundamental factor of sustainable transitions. For this to work, the positive feedback of network externalities and social interaction should be reduced initially, for instance by promoting niche markets of clean technologies and making technological standards and infrastructure more open. Traditional policy channels such as pollution tax and feed-in-tariffs have an auxiliary - yet important - role in our model. Compared to feed-in-tariffs, a pollution tax promotes smoother and faster transitions

Costly innovators versus cheap imitators: a discrete choice model

Two alternative ways to an innovative product or process are R&D investment or imitation of others’ innovation. In this article we propose a discrete choice model with costly innovators and free imitators and study the endogenous dynamics of price and demand in a market with many firms producing a homogeneous good. The basic idea is that imitation works better the more innovators are around, with a trade off between the advantages of the two strategies. First we look at innovation as costs reduction in a perfectly competitive market. Here we also study the stabilizing or destabilizing effect of memory and asynchronous updating of strategies. Then we introduce endogenous technological progress and analyze the determinants of the speed of price reduction as well as the occurrence of an initial oscillatory phase that precedes convergence. An extension of the model introduces product differentiation addressing the effects of innovation on demand. While the basic version of the model have stable equilibrium or cyclical behaviour, there are conditions for chaotic behaviour of price and agents’ choices. This is the case of long memory and asynchronous updating of strategies, as well as with innovations affecting demand. These results indicate how the dynamical interplay of innovators and imitators can contribute to markets variability