A Systemic Approach to Money Demand Modeling

This paper uses a consumer theory-based systemic approach to model the demand for monetary liquid asset holdings. We implement the suggestions and caveats of aggregation theory for the estimation of a demand system for liquid assets (monies) in static, dynamic and time-varying parameters setups. Our results are robust and theoretically consistent with consumer theory restrictions, as system derived from a utility maximizing framework and a well-behaved utility function. In our estimations we find stability of interest-rate and total-expenditure elasticities, in contrast to previous literature. We also document evidence that long (short) maturity rates are associated to less (more) liquid assets and that the vigorous growth of M1 during the last five of years is not accounted for by low interest rates alone. Policy implications are straightforward; there is stable relationship between monies and interest rates, but the former do not respond exclusively to the latter.

Flares in Open Clusters with K2. I. M45 (Pleiades), M44 (Praesepe) and M67

The presence and strength of a stellar magnetic field and activity is rooted in a star's fundamental parameters such as mass and age. Can flares serve as an accurate stellar "clock"? To explore if we can quantify an activity-age relation in the form of a flaring-age relation, we measured trends in the flaring rates and energies for stars with different masses and ages. We investigated the time-domain photometry provided by Kepler's follow-up mission K2 and searched for flares in three solar metallicity open clusters with well-known ages, M45 (0.125 Gyr), M44 (0.63 Gyr), and M67 (4.3 Gyr). We updated and employed the automated flare finding and analysis pipeline Appaloosa, originally designed for Kepler. We introduced a synthetic flare injection and recovery subroutine to ascribe detection and energy recovery rates for flares in a broad energy range for each light curve. We collected a sample of 1 761 stars, mostly late-K to mid-M dwarfs and found 751 flare candidates with energies ranging from $4\cdot10^{32}$ erg to $6\cdot10^{34}$ erg, of which 596 belong to M45, 155 to M44, and none to M67. We find that flaring activity depends both on $T_\mathrm{eff}$, and age. But all flare frequency distributions have similar slopes with $\alpha \approx2.0-2.4$, supporting a universal flare generation process. We discuss implications for the physical conditions under which flares occur, and how the sample's metallicity and multiplicity affect our results.Comment: 17 pages, 11 figures, appendix. Accepted to A&

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

We have determined refined multidimensional chemical shift ranges for intra-residue correlations ([superscript 13]C–[superscript 13]C, [superscript 15]N–[superscript 13]C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 [superscript 13]C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited “hand-picked” data sets, we show that ~94 % of the [superscript 13]C NMR data and almost all [superscript 15]N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6 % of the [superscript 13]C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. −2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra-residue cross peaks by inspection or by using a provided command-line Python script (PLUQin), which should be useful in protein structure determination. The refined chemical shift distributions are utilized in a simple quality test (SQAT) that should be applied to new protein NMR data before deposition in a databank, and they could benefit many other chemical-shift based tools.National Institutes of Health (U.S.) (Grant GM066976