Exploration and Exploitation in Technology-based Alliance Networks

Although the literature converges regarding the reasons why and how networks of technology alliances are formed, there is still lack of agreement on what constitutes an optimal network structure, once it has been formed. The aim of this paper is to fill this void and to determine what constitutes an optimal network structure for exploration and exploitation within the context of technological innovation. We differentiate among a firm's direct ties, indirect ties and degree of redundancy and analyze their role in the pharmaceutical, chemical and automotive industry. Regarding the role of direct ties, in combination with indirect ties, we find two alternative alliance network structures that are effective for both exploitation and exploration. We also find that redundancy in a firm's alliance network has a positive effect on exploitation. This is not the case for exploration, however, which seems to reveal a new insight into the role of redundancy when firms explore new technological fields. A final point is that our findings remain largely invariant across the three industries, enhancing the generalisability of our results.Networks, Strategic Alliances, Innovation, Learning

Explorative and exploitative learning strategies in technology-based alliance networks

Although the literature converges regarding the reasons why and how networks of technology alliances are formed, there is still lack of agreement on what constitutes an optimal network structure, once it has been formed. The aim of this paper is to fill this void and to determine what constitutes an optimal network structure for exploration and exploitation. To study this, we differentiate among a firm’s direct ties, indirect ties and the redundancy among them. Analyzing their role in the pharmaceutical, chemical and automotive industry we show that the exploration-exploitation distinction forms an important factor for understanding a firm’s optimal network structure, and that the differences in network optimality between both tasks is one of degree. Moreover, we find that this differential role of a firm’s alliance network remains invariant across the three industries, enhancing the generalisability of the empirical results. Finally we discuss an important new insight that arises from some unexpected finding

Central Bank Communication and Monetary Policy: A Survey of Theory and Evidence

Over the last two decades, communication has become an increasingly important aspect of monetary policy. These real-world developments have spawned a huge new scholarly literature on central bank communication—mostly empirical, and almost all of it written in this decade. We survey this ever-growing literature. The evidence suggests that communication can be an important and powerful part of the central bank’s toolkit since it has the ability to move financial markets, to enhance the predictability of monetary policy decisions, and potentially to help achieve central banks’ macroeconomic objectives. However, the large variation in communication strategies across central banks suggests that a consensus has yet to emerge on what constitutes an optimal communication strategy.

Central Bank communication and monetary policy: a survey of theory and evidence

Over the last two decades, communication has become an increasingly important aspect of monetary policy. These real-world developments have spawned a huge new scholarly literature on central bank communication —mostly empirical, and almost all of it written in this decade. We survey this evergrowing literature. The evidence suggests that communication can be an important and powerful part of the central bank’s toolkit since it has the ability to move financial markets, to enhance the predictability of monetary policy decisions, and potentially to help achieve central banks’ macroeconomic objectives. However, the large variation in communication strategies across central banks suggests that a consensus has yet to emerge on what constitutes an optimal communication strategy. JEL Classification: E52, E58Central Bank, communication, monetary policy

Towards A New Early Warning System of Financial Crises

This paper develops a new Early Warning System (EWS) model for predicting financial crises, based on a multinomial logit model. It is shown that EWS approaches based on binomial discrete-dependent-variable models can be subject to what we call a post-crisis bias. This bias arises when no distinction is made between tranquil periods, when economic fundamentals are largely sound and sustainable, and crisis/post-crisis periods, when economic variables go through an adjustment process before reaching a more sustainable level or growth path. We show that applying a multinomial logit model, which allows distinguishing between more than two states, is a valid way of solving this problem and constitutes a substantial improvement in the ability to forecast financial crises. The empirical results reveal that, for a set of 32 open emerging markets from 1993 till the present, the model would have correctly predicted a large majority of crises in emerging markets. Moreover, we derive general results about the optimal design of EWS models, which allows policy-makers to make an optimal choice based on their degree of risk-aversion against unanticipated financial crises.currency crises, Early Warning System, crisis prediction

Towards a new early warning system of financial crises

This paper develops a new Early Warning System (EWS) model for predicting financial crises, based on a multinomial logit model. It is shown that EWS approaches based on binomial discrete-dependent-variable models can be subject to what we call a post-crisis bias. This bias arises when no distinction is made between tranquil periods, when economic fundamentals are largely sound and sustainable, and crisis/post-crisis periods, when economic variables go through an adjustment process before reaching a more sustainable level or growth path. We show that applying a multinomial logit model, which allows distinguishing between more than two states, is a valid way of solving this problem and constitutes a substantial improvement in the ability to forecast financial crises. The empirical results reveal that, for a set of 32 open emerging markets from 1993 till the present, the model would have correctly predicted a large majority of crises in emerging markets. Moreover, we derive general results about the optimal design of EWS models, which allows policy-makers to make an optimal choice based on their degree of risk-aversion against unanticipated financial crises. JEL Classification: F31, F47, F30crisis prediction, currency crises, Early Warning System

How the nervous system responds to and regulates amino acid homeostasis

"For optimal growth, reproduction and lifespan an animal must eat a ‘balanced’ diet. This balanced diet is key in maintaining nutrient homeostasis in the animal. To achieve this balanced diet, the nervous system of an animal must have in place molecular mechanisms in order to both sense nutrient availability and change the feeding behaviour of the animal appropriately so it either selects or rejects particular foods. Whilst this is a rapidly growing field of research, the genes and cellular mechanisms underlying the translation of nutrient information into behavioural modification remains unknown. The work presented in this thesis first addresses the question of what constitutes a ‘balanced diet’.(...)

Random template placement and prior information

In signal detection problems, one is usually faced with the task of searching a parameter space for peaks in the likelihood function which indicate the presence of a signal. Random searches have proven to be very efficient as well as easy to implement, compared e.g. to searches along regular grids in parameter space. Knowledge of the parameterised shape of the signal searched for adds structure to the parameter space, i.e., there are usually regions requiring to be densely searched while in other regions a coarser search is sufficient. On the other hand, prior information identifies the regions in which a search will actually be promising or may likely be in vain. Defining specific figures of merit allows one to combine both template metric and prior distribution and devise optimal sampling schemes over the parameter space. We show an example related to the gravitational wave signal from a binary inspiral event. Here the template metric and prior information are particularly contradictory, since signals from low-mass systems tolerate the least mismatch in parameter space while high-mass systems are far more likely, as they imply a greater signal-to-noise ratio (SNR) and hence are detectable to greater distances. The derived sampling strategy is implemented in a Markov chain Monte Carlo (MCMC) algorithm where it improves convergence.Comment: Proceedings of the 8th Edoardo Amaldi Conference on Gravitational Waves. 7 pages, 4 figure

Computational problems without computation

Problemen uit de discrete wiskunde lijken op het eerste gezicht vaak erg simpel. Ze kunnen meestal gemakkelijk en zonder gebruik te maken van wiskundige begrippen worden geformuleerd. Toch komt het vaak voor dat zo’n ogenschijnlijk eenvoudig probleem nog open is of dat er, zoals bij het handelsreizigersprobleem, wel een oplossing gegeven kan worden,maar alleen een die onbruikbaar is omdat de rekentijd bij grotere getallen te snel groeit. In dit artikel, gebaseerd op zijn voordracht op het NMC 2002, kijkt Gerhard Woeginger naar de tegenovergestelde situatie. Hij introduceert allerlei discrete\ud problemen die onoplosbaar lijken, maar waarvoor er een simpele oplossing bestaat