A, B, C's (and D)'s for Understanding VARs

The dynamics of a linear (or linearized) dynamic stochastic economic model can be expressed in terms of matrices (A,B,C,D) that define a state space system. An associated state space system (A,K,C,Sigma) determines a vector autoregression for observables available to an econometrician. We review circumstances under which the impulse response of the VAR resembles the impulse response associated with the economic model. We give four examples that illustrate a simple condition for checking whether the mapping from VAR shocks to economic shocks is invertible. The condition applies when there are equal numbers of VAR and economic shocks.

A, B, C’s (And D’s) For Understanding VARS

The dynamics of a linear (or linearized) dynamic stochastic economic model can be expressed in terms of matrices (A,B,C,D) that define a state space system. An associated state space system (A,K,C, Sigma) determines a vector autoregression for observables available to an econometrician. We review circumstances under which the impulse response of the VAR resembles the impulse response associated with the economic model. We give four examples that illustrate a simple condition for checking whether the mapping from VAR shocks to economic shocks is invertible. The condition applies when there are equal numbers of VAR and economic shocks.VARs , Invertibility, Estimation of Dynamic Equilibrium Models, economic shocks, innovations

Chronic Discoid Lupus: An uncommon cause of nail atrophy

Interesting Medical Imag

Political credit cycles: the case of the Euro zone

We study the mechanisms through which the adoption of the Euro delayed, rather than advanced, economic reforms in the Euro zone periphery and led to the deterioration of important institutions in these countries. We show that the abandonment of the reform process and the institutional deterioration, in turn, not only reduced their growth prospects but also fed back into financial conditions, prolonging the credit boom and delaying the response to the bubble when the speculative nature of the cycle was already evident. We analyze empirically the interrelation between the financial boom and the reform process in Greece, Spain, Ireland, and Portugal and, by way of contrast, in Germany, a country that did experience a reform process after the creation of the Euro

Comparative effects of several cyclodextrins on the extraction of PAHs from a real contaminated soil

Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants (POPs) attracting extensive attention worldwide. Soils from many sites, such as areas of coal storage, coke oven plants, manufactured gas plants and areas of coal tar spillage present a high contamination level by PAHs. Due to their low solubility in water, the presence of PAHs in the soil matrix constitutes a long-term source of groundwater contamination, and their toxic, mutagenic and carcinogenic properties are responsible that the remediation of PAH-contaminated soil becomes a major environmental concern. In order to enhance the desorption rate of organic pollutants, various extracting agents have been used. Recently, cyclodextrins (CDs) have been proposed as an alternative agent to enhance the water solubility of hydrophobic compounds and thus their availability for biodegradation. The objectives of the present work were: to identify the level of PAHs of an aged-contaminated soil sample from a former chemical industry plant and to evaluate the ability of a natural cyclodextrin (ß-cyclodextrin, BCD) and three chemically modified cyclodextrins: 2-hydroxypropyl-ß-cyclodextrin (HPBCD), partially methylated-ß-cyclodextrin (PMBCD), and hydroxypropyl-¿-cyclodextrin (HPGCD) to extract the sixteen PAHs considered as priority pollutants by US-EPA. A real contaminated soil from the surrounding area of a deserted chemical industry situated in Asturias (North of Spain) was analyzed exhaustively in order to know its PAHs content. Then extraction experiments using Ca(NO3)2 solution or three types of different cyclodextrins solutions were carried out about the same soil. The results presented in this study show that according to Spanish legislation the analyzed soil had to be considered as contaminated soil. Its total PAHs content was about 1068.77±100.81 mg Kg-1, being phenanthrene, anthracene and naphthalene the most abundant compounds (25.3, 24.7 and 17.1 % of the total PAHs content of the soil, respectively). After the extractions experiments using CDs solutions, it was observed that the percentages of PAHs obtained were always higher than when an aqueous solution was used, although the three chemically modified cyclodextrins achieved higher extractions percentages than the natural cyclodextrin (BCD). From the sixteen selected PAHs, the highest extraction percentages was always obtained for the 3-rings PAHs, what is related with the more appropriated size and shape of this compounds with respect to the CDs cavity dimensions

Input-dependent structural identifiability of nonlinear systems

A dynamic model is structurally identifiable if it is possible to infer its unknown parameters by observing its output. Structural identifiability depends on the system dynamics, output, and input, as well as on the specific values of initial conditions and parameters. Here we present a symbolic method that characterizes the input that a model requires to be structurally identifiable. It determines which derivatives must be non-zero in order to have a sufficiently exciting input. Our approach considers structural identifiability as a generalization of nonlinear observability and incorporates extended Lie derivatives. The methodology assesses structural identifiability for time-varying inputs and, additionally, it can be used to determine the input profile that is required to make the parameters structurally locally identifiable. Furthermore, it is sometimes possible to replace an experiment with time-varying input with multiple experiments with constant inputs. We implement the resulting method as a MATLAB toolbox named STRIKE-GOLDD2. This tool can assist in the design of new experiments for the purpose of parameter estimation