Innovation and Market Structure in Pharmaceuticals: An Econometric Analysis on Simulated Data

The contribution of this paper is twofold. First, it presents the results of a "history-friendly" simulation model of evolution of the pharmaceutical industry. Second, it aims at contributing to a more general methodological discussion about agent-based models by proposing an econometric analysis of the results of the simulations. The case of the pharmaceutical industry has been studied extensively by scholars because, despite the high level of R&D intensity, the industry has been characterized by a relatively low levels of concentration. The model is able to reproduce the main stylized facts of the industry in an evolutionary perspective. In this paper we extend the analysis conducted in two previous works (Garavaglia et al. 2012, 2013) by further qualifying the findings with an extensive econometric investigation of the model outputs. The paper focuses the attention on the determinants of market structure, the innovative performance of the industry, the diversification in multiple submarkets and the level of prices. We find that the properties of the technological and demand regimes are key determinants of the patterns of industry evolution and that the main mechanisms driving the model are the random processes of search, the discovery of new submarkets as well as the interactions between patent protection, imitation and price competition. In addition, this paper emphasizes how the emerging leaders in the industry are those innovative early entrants which entered in large submarkets, showing the importance of the first mover advantage and of the size of the "prize" accruing to innovators when they discover a new rich submarket.

Numerical modeling of cohesive sediment transport and bed morphology in estuaries

Célestin Leupi

Two major lines of investigation have been pursued in this thesis: (1) More efficient, robust and realistic numerical techniques are designed for the simulation of complex turbulent fluid flows; (2) A new algorithm and its analysis is performed in the context of multiphasic fluid flow, for a cohesive fine-grained sediment (fluid mud) transport in estuaries. Estuaries exist between marine and freshwater system where waters of different physical, chemical and biological composition meet, combine and disperse primarily due to tidal influences. In the present thesis, the behavior of cohesive sediment in estuaries is reviewed based on the existing literature. Basic theories and recent developments are introduced to describe the formation of fluid mud from a very dilute suspension and its motion down a natural river bed with complex bathymetry. The present work contributes to the numerical simulation of complex turbulent multiphasic fluid flows encountered in estuarine channels, with the aim of the better understanding of the underlying physical processes as well as predicting realistically the cohesive sediment transport and bed morphology in such a zone. The model is based on the mass preserving method by using the so-called Raviart-Thomas finite element on the unstructured mesh in the horizontal plane. In the vertical, the computational domain is divided into number of layers at predefined heights and the method uses a conventional conforming P1 finite element scheme, with the advantage that the lowermost and uppermost layers variable height allow a faithful representation of the time-varying bed and free surface, respectively. Concerning the modeling of turbulence, the research effort focuses on the turbulence two-equation k - ε closure for the vertical parameterization of eddy viscosity. More precisely, a robust up-to-date algorithm is used for this issue. The new methodology is developed with the aim to account for more general relevant effects in the closure. The proposed model offers the capability to cope with the stiffness problem introduced by the large difference between the solid phase flow time scale and the hydrodynamic one, by using a sub-cycling strategy, whereas the splitting scheme is adopted with the aim of stability and the positivity of the relevant turbulent variables. The flexibility of the model and its performance are evaluated on several free-surface flow configurations with increasing complexity : homogeneous unsteady non-uniform flows in plane open channel flows, U-shaped (193°) curved open channel flow. Concerning the cohesive sediment transport, most of the existing models in the literature assume the analogous transport characteristics with that of the coarse sediment and adopt the relevant developed sediment transport for the latter to treat the former. Moreover, these existing models do not account for the consolidation of the mud-bed. The present research effort focused on a novel methodology based on the realistic empirical relationships, which accounts for the mutually exclusive processes for re-suspension and/or erosion and deposition of fine sediment, whereas only a limited range of bed shear stresses is allowed for simultaneous erosion and deposition to occur. Hence, on this basis, the new model investigated the bed morphology evolution by taking into account of the fluidization and/or consolidation of the fluid mud, which was handled by modeling the bed in three layers: (i) the mud-bed layer, (ii) the partially consolidated bed and (iii) the fully consolidated bed. The prediction of deposition/re-suspension using these two different methods lead to a non negligible difference in the results. Therefore, investigation of the true mechanism of erosion/deposition processes for cohesive sediments and their implementation in the numerical model is very important. This suggests that a realistic prediction must account for the fresh mud-bed re-suspension once deposited, as well as the consolidation and/or fluidization of the mud-bed deposits. Finally, the capability and improvements of the model are demonstrated, and its predicting performance is successfully evaluated by applying it to the simulation of the Po River Estuary (PRE) in Italy, which is the main source of river water discharge into the Northern Adriatic Sea. The analysis showed that the consolidation/fluidization process at the bed may have important influence on the prediction of bed morphology evolution. The three-layer approach used in this thesis is a first attempt to model these processes in detail within a numerical model.

EPFL2005

Bayesian risk analysis of financial time series

Christophe Osinski

This thesis is a contribution to financial statistics. One of the principal concerns of investors is the evaluation of portfolio risk. The notion of risk is vague, but in finance it is always linked to possible losses. In this thesis, we present some measures allowing the valuation of risk with the help of Bayesian methods. An exploratory analysis of data is presented to describe the sampling properties of financial time series. This analysis allows us to understand the origins of the daily returns studied in this thesis. Moreover, a discussion of different models is presented. These models make strong assumptions on investor behaviour, which are not always satisfied. This exploratory analysis shows some differences between the behaviour anticipated under equilibrium models, and that of real data. The Bayesian approach has been chosen because it allows one to incorporate all the variability, in particular that associated with model choice. The models studied in this thesis allow one to take heteroskedasticity into account, as well as particular shapes of the tails of returns. ARCH type models and models based on extreme value theory are studied. One original aspect of this thesis is its use of Bayesian analysis to detect change points in financial time series. We suppose that a market has two phases, and that it switches from a state to the other at random. Another new contribution is a model integrating heteroskedasticity and time dependence of extreme values, by superposition of the model proposed by Bortot and Coles (2003) and a GARCH process. This thesis uses simulation intensively for the estimation of risk measures. The drawback of simulation is the amount of time needed to obtain accurate estimates. However, simulation allows one to produce results when direct calculation is not feasible. For example, simulation allows one to compute risk estimates for time horizons greater than one day. The methods presented in this thesis are illustrated on simulated data, and on real data from European and American markets. This thesis involved the construction of a library containing C and S code to perform risk analysis using GARCH and extreme value theory models. The results show that model uncertainty can be incorporated, and that risk measures for time horizons greater than one can be obtained by simulation. The methods presented in this thesis have a natural representation involving conditioning. Thus, they permit the computation of both conditional and unconditional risk estimates. Three methods are described: the GARCH method; the two-state GARCH method; and the HBC method. Unconditional risk estimation using the GARCH method is satisfactory on data which seem stationary, but not reliable on data which are non-stationary, such as data with change points. The two-state GARCH model does a little better, but gives very satisfactory results when the risk is estimated conditionally on time. The HBC method does not give satisfactory results.

EPFL2006

Corporate Science and Voluntary Disclosure

Markus Simeth

The dissertation investigates the phenomenon of firms that make voluntary contributions to the stock of scientific knowledge. Such a firm behaviour appears counterintuitive from a traditional viewpoint, since no direct financial returns can be expected while the disclosure of research outcomes may lead to knowledge spillovers to competing firms. This raises the questions why firms engage in those boundary-spanning activities, how scientific disclosure strategies are implemented, and to what extent scientific disclosure strategies affect the firm performance. The dissertation provides empirical evidence on these questions using representative firm-level data and econometric analysis techniques. The first chapter of the dissertation reviews the relevant literature, underlines the relevance of doing research on this topic by providing descriptive evidence on the amounts of scientific contributions by firms, and includes some novel insights from interviews which I conducted at several large R&D performing firms. I discuss the potential benefits, costs and organizational challenges of scientific disclosure strategies and position scientific publications as an expression of openness in the light of alternative openness definitions prevalent in innovation research. The second chapter focuses on the question why firms publish in scientific journals using a cost-benefit framework. In particular, I analyse whether scientific contributions of firms are used as an instrument to get access to academic knowledge networks. Moreover, I explore environmental conditions by considering the effectiveness of appropriation instruments and the spillover levels in a sector that may impact the firms’ decision-making process. The analysis relies on data from the French Innovation survey and provides evidence for the predictions that firms show reciprocal behaviour in exchange of obtaining valuable academic knowledge. However, the propensity of firms to publish is rather sensitive to the spillover threats. The third chapter examines how are firms able to publish by testing the requirements and origins of scientific contributions by firms. I explicitly consider the heterogeneity of scientific outputs and provide a complementary view on the requirements for the creation of inventive outcomes. The requirements considered can be classified according to the research orientation and the demographic composition of the R&D labs. The analysis revealed that scientific disclosure strategies require specific resource allocations and capabilities, which are in part not necessary for the generation of inventive outcomes. The findings support the view that disclosure strategies can be costly and are not only a by-product of the “usual” R&D activities. The fourth chapter addresses the performance effects of scientific activities of firms. More specifically, I examine whether scientific publications stocks provide valuable information to the financial markets, potentially leading to different valuations. I consider the heterogeneity of scientific and inventive outcomes and found evidence for a positive impact of scientific contributions on the firm’s Tobin’s Q beyond the effects of R&D stocks, patent stocks and patent quality.

EPFL2013