On the statistical identification of DSGE models

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos [Spanos, Aris, 1990. The simultaneous-equations model revisited: Statistical adequacy and identification. Journal of Econometrics 44, 87–105] to criticize traditional evaluation methods of Cowles Commission models, could be relevant for DSGE models. We conclude that the recently proposed model evaluation method, based on the DSGE−VAR(λ), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVAR as a statistically identified benchmark leaves unaltered the support of the data for the DSGE model and that a DSGE-FAVAR can be an optimal forecasting model

Selective discrimination and classification of G-quadruplex structures with a host–guest sensing array

The secondary structures of nucleic acids have an important influence on their cellular functions but can be difficult to identify and classify quickly. Here, we show that an arrayed suite of synthetic hosts and dyes is capable of fluorescence detection of oligonucleotide secondary structures. Multivariate analysis of different fluorescence enhancements—generated using cationic dyes that show affinity for both DNA G-quadruplexes and the synthetic hosts—enables discrimination between G-quadruplex structures of identical length and highly similar topological types. Different G-quadruplexes that display the same folding topology can also be easily differentiated by the number of G-quartets and sequence differences at the 3′ or 5′ ends. The array is capable of both differentiation and classification of the G-quadruplex structures at the same time. This simple non-invasive sensing method does not require the discovery and synthesis of specific G-quadruplex binding ligands, but employs a simple multicomponent approach to ensure wide applicability

Polyethylene Based Ionomers as High Voltage Insulation Materials

Polyethylene based ionomers are demonstrated to feature a thermo-mechanical and dielectric property portfolio that is comparable to cross-linked polyethylene (XLPE), which may enable the design of more sustainable high voltage direct-current (HVDC) power cables, a crucial component of future electricity grids that seamlessly integrate renewable sources of energy. A new type of ionomer is obtained via high-pressure/high-temperature free radical copolymerization of ethylene in the presence of small amounts of ion-pair comonomers comprising amine terminated methacrylates and methacrylic acid. The synthesized ionomers feature a crystallinity, melting temperature, rubber plateau modulus and thermal conductivity like XLPE but remain melt-processable. Moreover, the preparation of the ionomers is free of byproducts, which readily yields a highly insulating material with a low dielectric loss tangent and a low direct-current (DC) electrical conductivity of 1 to 6\ub710−14\ua0S\ua0m−1 at 70\ua0\ub0C and an electric field of 30\ua0kV\ua0mm−1. Evidently, the investigated ionomers represent a promising alternative to XLPE-based high voltage insulation, which may permit to ease the production as well as end-of-use recycling of HVDC power cables by combining the advantages of thermoset and thermoplastic materials while avoiding the formation of byproducts

On the statistical identification of DSGE models

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos(1990) to criticize traditional evaluation methods of Cowles Commission models, could be relevant for DSGE models. We conclude that the recently proposed model evaluation method, based on the DSGE-VAR(λ), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVAR as a statistically identified benchmark leaves unaltered the support of the data for the DSGE model and that a DSGE-FAVAR can be an optimal forecasting model. Keywords: Bayesian analysis; Dynamic stochastic general equilibrium model; Model evaluation,Statistical Identification,Vector autoregression, Factor-Augmented Vector Autoregression. JEL Classification: C11, C5

On the statistical identification of DSGE models

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos [Spanos, Aris, 1990. The simultaneous-equations model revisited: Statistical adequacy and identification. Journal of Econometrics 44, 87–105] to criticize traditional evaluation methods of Cowles Commission models, could be relevant for DSGE models. We conclude that the recently proposed model evaluation method, based on the DSGE–VAR(λ), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVAR as a statistically identified benchmark leaves unaltered the support of the data for the DSGE model and that a DSGE–FAVAR can be an optimal forecasting model

On the Statistical Identification of DSGE Models

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos(1990) to criticize traditional evaluation methods of Cowles Commission models, could be relevant for DSGE models. We conclude that the recently proposed model evaluation method, based on the DSGE-VAR(ë), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVAR as a statistically identified benchmark leaves unaltered the support of the data for the DSGE model and that a DSGE-FAVAR can be an optimal forecasting model.Bayesian analysis; Dynamic stochastic general equilibrium model; Factor-Augmented Vector Autoregression; Model evaluation

On the statistical identification of DSGE models

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos [Spanos, Aris, 1990. The simultaneous-equations model revisited: Statistical adequacy and identification. Journal of Econometrics 44, 87-105] to criticize traditional evaluation methods of Cowles Commission models, could be relevant for DSGE models. We conclude that the recently proposed model evaluation method, based on the DSGE-VAR([lambda]), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVAR as a statistically identified benchmark leaves unaltered the support of the data for the DSGE model and that a DSGE-FAVAR can be an optimal forecasting model.Bayesian analysis Dynamic stochastic general equilibrium model Model evaluation Statistical identification Vector autoregression Factor-augmented vector autoregression

On the Statistical Identification of DSGE Models

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos(1990)to criticize traditional evaluation methods of Cowles Commission models, could be relevant for DSGE models. We conclude that the recently proposed model evaluation method, based on the DSGE ? VAR(?), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVAR as a statistically identified benchmark leaves unaltered the support of the data for the DSGE model and that a DSGE-FAVAR can be an optimal forecasting model.

Synthesis of quinoxaline cavitand baskets

The unique temperature, solvent and pH drivenvase to kite equilibrium in quinoxaline cavitands allows the reversible uptake and release of guests. However, the cavity breathing associated with this conformational switch reduces the strength of complexation. A limited number of solutions have been proposed for the cavity rigidification, using either H-bonding, metal coordination or covalent connections. Here we report the synthesis and structural characterisation of quinoxalinebased cavitand baskets, which present two distal quinoxaline walls linked together. Baskets A and B were obtained through a bridging reaction starting from an AC di-quinoxaline bridged cavitand using two different di-quinoxaline moieties. In both cases, two isomers were obtained: isomer C2, with the linking unit crossing the cavity mouth, and isomer Cs, having the linker sideways. The isomers were identified through 1H NMR analysis. In the case of basket A-Cs, the resolved molecular structure confirmed the Cs symmetry of the basket