Conceptual Foundations of Modelling of Innovative Production Projects

At the moment there is a lack of methodological approaches to formalization of management of innovative projects relating to production systems, as well as to adaptation and practical use of the existing approaches. This article is about one potential approach to the management of innovative projects, which makes the building of innovative process models possible based on objective approach. It outlines the frameworks for the building of innovative project models, and describes the method of transition from conceptual modelling to innovative project management. In this case, the model alone and together with parameters used for evaluation of the project may be unique and depends on the special features of the project, preferences of decision-making person, and production and economic system in which it is to be implemented. Unlike existing approaches, this concept does not place any restrictions on types of models and makes it possible to take into account the specificities of economic and production systems. Principles embodied in the model allow its usage as a basis for simulation model to be used in one of specialized simulation systems, as well as for information system providing information support of decision-making process in production and economic systems both newly developed by the company (enterprise) and designed on the basis of available information systems that interact through the exchange of data. In addition, this article shows that the development of conceptual foundations of innovative project management in the economic and production systems is inseparable from the development of the theory of industrial control systems, and their comprehensive study may be reduced to a set of elements represented as certain algorithms, models and evaluations. Thus, the study of innovative process may be conducted in both directions: from general to particular, and vice versa.

Financial development, labor and market regulations and growth

This paper investigates the importance that market regulation and financial imperfections have on firm growth. We analyse institutions af- fecting labor market as Employment Protection Laws (EP) and Product Market Regulation (PM). We show that together with the beneficial effects of financial development, a firm will get less financing, and thus investless, in a weak financial market (finance effect), the strictness of product and labor market regulations also affect firm growth (labor effect). In particular, we show that the stricter the rules the more detrimental the influence on growth in sectoral value added for a large number of countries. We also show that the labor effect overcomes the positive finance effect.

Governance mechanisms in Spanish financial intermediaries

This paper examines the governance of Spanish Banks around two main issues. First, does a poor economic performance activate those governance interventions that favor the removal of executive directors and the merger of non-performing banks? And second, does the relationship between governance intervention and economic performance vary with the ownership form of the bank? Our results show that a bad performance does activate governance mechanisms in banks, although for the case of Savings Banks intervention is confined to a merger or acquisition. Nevertheless, the distinct ownership structure of Savings Banks does not fully protect non-performing banks from disappearing. Product-market competition compensates for those weak internal governance mechanisms that result from an ownership form which gives voice to several stakeholder groups.

Are one factor logarithmic volatility models useful to fit the features of financial data? An application to microsoft data.

This paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.

Financial intermediation in a model of growth through creative destruction

This paper presents an endogenous growth model in which the research activity is financed by intermediaries that are able to reduce the incidence of researcher's moral hazard. It is shown that financial activity is growth promoting because it increases research productivity. It is also found that a subsidy to the financial sector may have larger growth effects than a direct subsidy to research. Moreover, due to the presence of moral hazard, increasing the subsidy rate to R\&D may reduce the growth rate. I show that there exists a negative relation between the financing of innovation and the process of capital accumulation. Concerning welfare, the presence of two externalities of opposite sign steaming from financial activity may cause that the no-tax equilibrium provides an inefficient level of financial services. Thus, policies oriented to balance the effects of the two externalities will be welfare improving.

Financial integration, productivity and capital accumulation

Understanding the mechanism through which financial globalization affects economic performance is crucial for evaluating the costs and benefits of opening financial markets. This paper is a first attempt at disentangling the effects of financial integration on the two main determinants of economic performance: productivity (TFP) and investments. I provide empirical evidence from a sample of 93 countries observed between 1975 and 1999. The results suggest that financial integration has a positive direct effect on productivity, while it spurs capital accumulation only with some delay and indirectly, since capital follows the rise in productivity. I control for indirect effects of financial globalization through banking crises. Such episodes depress both investments and TFP, though they are triggered by financial integration only to a minor extent.

Financial incentives in academia: research versus development

This paper investigates the effects of monetary rewards on the pattern of research. We build a simple repeated model of a researcher capable to obtain innovative ideas. We analyse how the legal environment affects the allocation of researcher's time between research and development. Although technology transfer objectives reduce the time spent in research, they might also induce researchers to conduct research that is more basic in nature, contrary to what the skewing problem would presage. We also show that our results hold even if development delays publication.

Locations and Relocations:Modelling, Determinants, and Interrelations

Empirical studies on industrial location do not typically distinguish between new and relocated establishments. This paper addresses this shortcoming using data on the frequency of these events in municipalities of the same economic-administrative region. This enables us to test not only for differences in their determinants but also for interrelations between start-ups and relocations. Estimates from count regression models for cross-section and panel data show that, although partial effects differ, common patterns arise in “institutional” and “neoclassical” explanatory factors. Also, start-ups and relocations are positive but asymmetrically related. JEL classification: C25, R30, R10. Keywords: cities, count data models, industrial location

Individual-based modelling of bacterial cultures to study the lag ohase

Els bacteris són la forma dominant de vida del planeta: poden sobreviure en medis molt adversos, i en alguns casos poden generar substàncies que quan les ingerim ens són tòxiques. La seva presència en els aliments fa que la microbiologia predictiva sigui un camp imprescindible en la microbiologia dels aliments per garantir la seguretat alimentària. Un cultiu bacterià pot passar per quatre fases de creixement: latència, exponencial, estacionària i de mort. En aquest treball s’ha avançat en la comprensió dels fenòmens intrínsecs a la fase de latència, que és de gran interès en l’àmbit de la microbiologia predictiva. Aquest estudi, realitzat al llarg de quatre anys, s’ha abordat des de la metodologia Individual-based Modelling (IbM) amb el simulador INDISIM (INDividual DIScrete SIMulation), que ha estat millorat per poder fer-ho. INDISIM ha permès estudiar dues causes de la fase de latència de forma separada, i abordar l’estudi del comportament del cultiu des d’una perspectiva mesoscòpica. S’ha vist que la fase de latència ha de ser estudiada com un procés dinàmic, i no definida per un paràmetre. L’estudi de l’evolució de variables com la distribució de propietats individuals entre la població (per exemple, la distribució de masses) o la velocitat de creixement, han permès distingir dues etapes en la fase de latència, inicial i de transició, i aprofundir en la comprensió del que passa a nivell cel•lular. S’han observat experimentalment amb citometria de flux diversos resultats previstos per les simulacions. La coincidència entre simulacions i experiments no és trivial ni casual: el sistema estudiat és un sistema complex, i per tant la coincidència del comportament al llarg del temps de diversos paràmetres interrelacionats és un aval a la metodologia emprada en les simulacions. Es pot afirmar, doncs, que s’ha verificat experimentalment la bondat de la metodologia INDISIM.

Three essays on the psychology of investment and financial markets

Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.