CCE estimation of factor-augmented regression models with more factors than observables

This paper considers estimation of factor-augmented panel data regression models with homogenous slope coefficients. One of the most popular approaches towards this end is the pooled common correlated effects (CCE) estimator of Pesaran (2006). For this estimator to be consistent at the usual sqrt-NT rate, where N and N denote the number of cross-section and time series observations, respectively, the number of factors cannot be larger than the number of observables. This is a problem in the typical application involving only a small number of regressors. The current paper proposes a simple extension to the CCE procedure by which the requirement can be relaxed. The CCE approach is based on taking the cross-section average of the observables as an estimator of the common factors. The idea put forth in the current paper is to consider not only the average but also other cross-section combinations. The asymptotic properties of the resulting combination-augmented CCE (C3E) estimator are provided and verified in small samples using Monte Carlo simulation

The impact of natural hazards on migration in the United States and the effect of spatial dependence

In this paper, we analyze the effect of natural hazards on migration in the United States (US) and the importance of spatial dependence in such assessments. We use two measures of migration: migration rates and flows. The model for migration flows is estimated using the gravity model, whereas out- and in-migration rates are analyzed using the spatial Durbin model. Our results indicate there is a major and significant impact of economic damage caused by natural hazards on out-migration rates and outward migration flows. In the spatial Durbin model and in the gravity model, a $1,000 dollar damage per capita is associated with an increase in out-migration of 16.0% and 9.1%, respectively. However, when spatial dependence is not accounted for, the effect of natural hazards on migration is substantially overestimated: the coefficients are 1.5–2 times larger when spatial dependence is not considered

Felodipine induces autophagy in mouse brains with pharmacokinetics amenable to repurposing.

Neurodegenerative diseases like Alzheimer's disease, Parkinson's disease and Huntington's disease manifest with the neuronal accumulation of toxic proteins. Since autophagy upregulation enhances the clearance of such proteins and ameliorates their toxicities in animal models, we and others have sought to re-position/re-profile existing compounds used in humans to identify those that may induce autophagy in the brain. A key challenge with this approach is to assess if any hits identified can induce neuronal autophagy at concentrations that would be seen in humans taking the drug for its conventional indication. Here we report that felodipine, an L-type calcium channel blocker and anti-hypertensive drug, induces autophagy and clears diverse aggregate-prone, neurodegenerative disease-associated proteins. Felodipine can clear mutant α-synuclein in mouse brains at plasma concentrations similar to those that would be seen in humans taking the drug. This is associated with neuroprotection in mice, suggesting the promise of this compound for use in neurodegeneration

Electron-topological, energetic and π-electron delocalization analysis of ketoenamine-enolimine tautomeric equilibrium

The ketoenamine-enolimine tautometic equilibrium has been studied by the analysis of aromaticity and electron-topological parameters. The influence of substituents on the energy of the transition state and of the tautomeric forms has been investigated for different positions of chelate chain. The quantum theory of atoms in molecules method (QTAIM) has been applied to study changes in the electron-topological parameters of the molecule with respect to the tautomeric equilibrium in intramolecular hydrogen bond. Dependencies of the HOMA aromaticity index and electron density at the critical points defining aromaticity and electronic state of the chelate chain on the transition state (TS), OH and HN tautomeric forms have been obtained

Estimating the Speed of Adjustment of Leverage in the Presence of Interactive Effects

Dynamic panel data regression models with fixed effects to account for unobserved heterogeneity are standard econometric tools. It is not until recently, however, that the problems involved when fitting such regressions to leverage data have been investigated. The main problem is that models of leverage are extremely noisy, much more so than what can be accommodated using fixed effects. The present article can be seen as a reaction to this. The purpose is to consider a more general interactive effects model in which there are multiple time effects, each with their own firm-specific sensitivities. Our empirical results suggest that proper accounting for the interactive effects and the bias that they cause leads to a marked increase in the estimated speed of adjustment to target leverage

Synthesis and structural characterization of (1,3-bis(methoxyethyl)-4,5-bis(2,4,6-trimethylphenyl)-imidazolidin-2-ylidene)chloro(1,5-cyclooctadiene)rhodium(I)

WOS: 000236471400009A new N-heterocyclic carbene (NHC) ligand with bulky substituents and functionalized methoxy-donor side arms complexed with Rh(I) was synthesized and characterized by elemental analysis, H-1 and C-13 NMR, and IR spectroscopy. The crystal and molecular structure was determined by single-crystal X-ray diffraction techniques. Two carbon atoms in the cyclooctadiene ring and three ortho methyl groups have positional and orientational disorder, respectively. Rhodium has square-planar coordination geometry

The synthesis, structural characterization and conformational analysis of (1,3-bis(2-methyl-4-diethylaminophenyl)imidazolidin-2-ylidene)chloro(1,5-cyclooctadiene)rhodium(I)

WOS: 000232258300004A four-coordinated Rh(l) complex with a new heterocyclic carbene ligand, functionalized by amino donor pendants, 4, was synthesized and characterized by elemental analyses, NMR and IR spectroscopy, and the molecular structure of the title compound has been determined by Xray crystallography. Crystallographic data: monoclinic, P2(1)/m, a = 7.9307(5), b = 25.0061(12), c = 8.0780(6) angstrom, 0 = 101.366(6)degrees, V = 1570.58(17) angstrom(3), rho(calc), = 1.3515(l) gcm(-3), Z = 2. The experimentally obtained structural parameters for compound 4 compare reasonably well with those calculated at the semi-empirical ZINDO/1 level of theory carried out to elucidate conformational flexibility and steric hindrances