Use costs in a two-R&D-sector model

In this paper we assess the properties of scale-free endogenous growth models in presence of use costs for the final users. As bench-mark we use Segerstrom (2000) two R&D sector model. When use costs apply to both types of innovation we find counterintuitive results with respect to the standard Endogenous Growth literature ; use costs can increase growth. This is due to the presence of both increasing returns in the research functions and the population growth condition. When costs apply to vertical innovations only we can establish more intuitive results : under mild conditions use costs decrease the rate of vertical innovation and of overall economic growth.Endogenous Growth; Scale effect; Adoption costs

Capital Market Frictions and the Business Cycle

We augment a RBC model with capital and labor market frictions. We follow the approach of Wasmer and Weil (2004) which model market imperfections as search processes : firms must sequentially find a match with a bank first and then with a worker in order to start production. We show that the interactions between labor and capital market frictions may generate a financial accelerator or decelerator, depending on a parameter condition. We compare our model with US National Accounts data and with the empirical findings of Dell’Ariccia and Garibaldi (2005) : we find that the financial accelerator as well as real wage rigidities help in improving the statistical propqerties of the model

Estimating DGSE models with long memory dynamics

Recent literature clams that key variables such as aggregate productivity and inflation display long memory dynamics. We study the impllications of this high degree of persistence on the estimation of Dynamic Stochastic General Equilibrium (DGSE) models. We show that long memory data produce substantial bias in the deep parameter estimates when a standard Kalman Filter-MLE procedure is used. We propose a modification of the Kalman Filter procedure, we mainly augment the state space, which deals with this problem. By the means of the augmented state space we can consistently estimate the model parameters as well as produce more accurate out-of-sample forecasts compared to the standard Kalman filter.

Aggressiveness pattern and second primary tumor risk associated with basaloid squamous cell carcinoma of the larynx

Basaloid squamous cell carcinoma (BSCC) is a rare, aggressive and distinct variant of squamous cell carcinoma (SCC) of the upper respiratory and digestive tract. We have evaluated disease specific survival (DSS) and overall survival (OS) through Kaplan-Meier method and mortality risk through univariate statistical analysis of Cox in 42 cases of BSCC and other 42 of laryngeal SCC (LSCC) matched for both age and sex. We demonstrated that laryngeal BSCC is a more aggressive tumor than LSCC as is associated to higher nodal recurrence of pathology (5 vs 2 patients, median survival, OR 2.7), a reduced survival (median survival 34 vs 40 months, OR 3.2 for mortality); in addition, basaloid patients have a higher risk to be affected by second primary tumors (13 vs 3 patients, OR 5.8) and a higher probability to die for this second tumor (Hazard Risk, HR 4.4). The analysis of survival shows an increased mortality risk concurrent with the parameters assessed by univariate analyses that assume a predictive and statistical significance in second tumor and grading in basaloid LSSC.Basaloid squamous cell carcinoma (BSCC) is a rare, aggressive and distinct variant of squamous cell carcinoma (SCC) of the upper respiratory and digestive tract. We have evaluated disease specific survival (DSS) and overall survival (OS) through Kaplan-Meier method and mortality risk through univariate statistical analysis of Cox in 42 cases of BSCC and other 42 of laryngeal SCC (LSCC) matched for both age and sex. We demonstrated that laryngeal BSCC is a more aggressive tumor than LSCC as is associated to higher nodal recurrence of pathology (5 vs 2 patients, median survival, OR 2.7), a reduced survival (median survival 34 vs 40 months, OR 3.2 for mortality); in addition, basaloid patients have a higher risk to be affected by second primary tumors (13 vs 3 patients, OR 5.8) and a higher probability to die for this second tumor (Hazard Risk, HR 4.4). The analysis of survival shows an increased mortality risk concurrent with the parameters assessed by univariate analyses that assume a predictive and statistical significance in second tumor and grading in basaloid LSSC

Impact of neuropeptide substance P an inflammatory compound on arachidonic acid compound generation

There is much evidence that neuropeptide substance P is involved in neurogenic inflammation and is an important neurotransmitter and neurmodulator compound. In addition, substance P plays an important role in inflammation and immunity. Macrophages can be activated by substance P which provokes the release of inflammatory compounds such as interleukins, chemokines and growth factors. Substance P is involved in the mechanism of pain through the trigeminal nerve which runs through the head, temporal and sinus cavity. Substance P also activates mast cells to release inflammatory mediators such as arachindonic acid compound, cytokines/chemokines and histamine. The release of these chemical mediators is crucial for inflammatory response. Among these mediators there are prostoglandins and leukotrines. Here we review the impact of substance P on inflammatory compounds

Opsonin-deficient nucleoproteic corona endows unPEGylated liposomes with stealth properties in vivo

For several decades, surface grafted polyethylene glycol (PEG) has been a go-to strategy for preserving the synthetic identity of liposomes in physiological milieu and preventing clearance by immune cells. However, the limited clinical translation of PEGylated liposomes is mainly due to the protein corona formation and the subsequent modification of liposomes’ synthetic identity, which affects their interactions with immune cells and blood residency. Here we exploit the electric charge of DNA to generate unPEGylated liposome/DNA complexes that, upon exposure to human plasma, gets covered with an opsonin-deficient protein corona. The final product of the synthetic process is a biomimetic nanoparticle type covered by a proteonucleotidic corona, or “proteoDNAsome”, which maintains its synthetic identity in vivo and is able to slip past the immune system more efficiently than PEGylated liposomes. Accumulation of proteoDNAsomes in the spleen and the liver was lower than that of PEGylated systems. Our work highlights the importance of generating stable biomolecular coronas in the development of stealth unPEGylated particles, thus providing a connection between the biological behavior of particles in vivo and their synthetic identity

The benefits and costs of adjusting bank capitalisation: evidence from Euro Area countries

El artículo propone un marco para evaluar el impacto de los colchones de capital a nivel de todo el sistema y a nivel bancario. La evaluación se basa en un modelo FAVAR (Factor-Augmented Vector Autoregression) que relaciona los ajustes bancarios individuales con la dinámica macroeconómica. El modelo FAVAR se estima individualmente para once economías de la zona del euro y se identifican impactos estructurales, lo que permite diagnosticar las principales vulnerabilidades de los sistemas bancarios nacionales y al mismo tiempo estimar los costes económicos a corto plazo del aumento de capital de los bancos. Sobre esta base, se realiza una evaluación completa de la relación coste-beneficio de un incremento en los colchones de capital. Los beneficios están relacionados con un aumento en la capacidad de resistencia de los bancos a perturbaciones adversas. Una mayor capitalización permite a los bancos hacer frente a impactos negativos y modera la reducción del crédito a economía real que se produce en circunstancias adversas. Los costes se relacionan con pérdidas transitorias de crédito y producción que son evaluadas tanto a nivel agregado como bancario. Se obtiene que un aumento en los ratios de capital tienen un impacto muy diferente en la actividad crediticia y económica, dependiendo de la forma en que los bancos se ajustan, es decir, bien a través de cambios en los activos o en capital.The paper proposes a framework for assessing the impact of system-wide and bank-level capital buffers. The assessment rests on a factor-augmented vector autoregression (FAVAR) model that relates individual bank adjustments to macroeconomic dynamics. We estimate FAVAR models individually for eleven euro area economies and identify structural shocks, which allow us to diagnose key vulnerabilities of national banking systems and estimate short-run economic costs of increasing banks’ capitalisation. On this basis, we run a fullyfledged cost-benefit assessment of an increase in capital buffers. The benefits are related to an increase in bank resilience to adverse shocks. Higher capitalisation allows banks to withstand negative shocks and moderates the reduction of credit to the real economy that ensues in adverse circumstances. The costs relate to transitory credit and output losses that are assessed both on an aggregate and bank level. An increase in capital ratios is shown to have a sharply different impact on credit and economic activity depending on the way banks adjust, i.e. via changes in assets or equity

Use costs in a two-R&D-sector model

In this paper we assess the properties of scale-free endogenous growth models in presence of use costs for the final users. As bench-mark we use Segerstrom(2000) two R&D sector model. When use costs apply to both types of innovation we find counterintuitive results with respect to the standard Endogenous Growth literature: use costs can increase growth. This is due to the presence of both increasing returns in the research functions and the population growth condition. When costs apply to vertical innovations only we can establish more intuitive results: under mild conditions use costs decrease the rate of vertical innovation and of overall economic growth

Essays in formulating and estimating DSGE models

From the seminal work of Kydland and Prescott (1982) a huge amount of ef- fort and work has been devoted in order to improve our understanding of how an economy works. After the breakthrough of general equilibrium analysis, macroeconomics rapidly became a mathematical science based on the paradigm that economies can be described as intertemporal equilibria. A Dynamic Stochastic General Equilibrium model (DSGE) describes the over time evolution of an economy as function of primitive objects, so called deep pa- rameters, which relate to preference, technology and endowments of economic agents, namely firms, households and government. It is a Stochastic model as the source of economic fluctuations is provided by random shocks. Those latter can be measured and named, but their ultimate explanation is left out of the model. It is Dynamic General Equilibrium since agents take optimal intertem- poral decisions (under the constraints they face) which are mutually consistent, without being necessarily optimal from a social welfare point of view. This thesis is an attempt to add one further page to the book of knowledge of DSGE models. In particular, in each chapter I treat a different issue concerning the link between exogenous shocks and macroeconomic variables. In the first chapter I answer the following: ’How does credit relate to the transmission mechanism of shocks into macroeconomic variables ?’ We introduce liquidity frictions into a standard Real Business Cycle model. While stan- dard models assume that business projects can immediately find financing, in our set-up we introduce a lengthy search process for potential Entrepreneurs to match with loans from financial intermediaries. Every period spent on the search process entails a cost. When a match occurs the Entrepreneur can start a business and she is willing to give up part of her profit to the intermediary in exchange for not getting back into the search process. This is a kind of liquidity premium which is paid by active firms on top of the risk-free rate: when credit markets are tight, meaning that Entrepreneurs are abundant compared to avail- able loans, the premium is higher. We show that when labor markets are perfect, the effects of our liquidity premium on economic dynamics are small. Instead, when also labor markets are subject to frictions, i.e. workers and firms are in another search process to find one another, credit frictions can either accelerate or reduce the impact of the stochastic shocks hitting the economy, depending on the value of deep parameters. For realistic calibrations of the model, based one US data, an accelerating effect seems to be in place. The second chapter deals with the econometric estimation of DSGE mod- els. Earlier contributions used simple models as small laboratory experiments which could be calibrated in order to reproduce relevant features of an econ- omy. As the discipline evolved, models were taken to the data by the means of more formal econometric techniques. Our second question is as follows: ’Pro- vided the generating process of shocks is unknown to researchers what is the best way to bring a model to the data ?’. This work relaxes one of the com- mon assumption used in the literature, that is the statistical form of exogenous shocks is known to the researcher. We extend Kalman Filter Maximum Like- lihood methods to cope with the problem at hand. We report better estimates of the deep parameters of the economy (i.e. more in line with those obtained by using other sources of data) and a large and statistically significant improve- ment in out-of-sample forecast of macroeconomic variables. We also provide empirical reasons to believe that long memory can be a relevant issue concern- ing DSGE models, a feature much overlooked in the literature. The ingenuity of our method is that it is an effective way of filtering out from the data the amount of persistence which would be left unexplained by the model. In the last chapter I take a Bayesian point of view to estimating DSGE mod- els. A bayesian researcher uses not only the set of data at hand, but also his prior knowledge. The contribution of the chapter is twofold. On the one hand we investigate some earlier problematic results, namely those of Negro and Schorfheide (2008). A critical issue in their procedure is fully exposed and some ways to solve it are outlined. Then we propose a simple way of eliciting priors, which is to use information concerning so called impulse response functions. Impulse responses are the responses of macroeconomic variables, conditional on some exogenous shock occurring in the economy. Those are the most stud- ied object in modern macroeconomics and they constitute an ideal source of prior knowledge. Some implications of the use of impulse responses as prior knowledge are explored in this chapter. The technical evolution of the chapters (from calibration to Bayesian Esti- mation) reflects the evolution of the literature on DSGE models and also the learning process of the author himself.(ECON 3) -- UCL, 201