Dividends and Taxes

How do dividend taxes affect firm behavior and what are their distributional and efficiency effects? To answer these questions, the first problem is coming up with an explanation for why firms pay dividends, in spite of their tax penalty. This paper surveys three different models for why firms pay dividends, and then uses each model to examine the behavioral and efficiency effects of dividend taxes. The three models examined are: the %u201Cnew view,%u201D an agency cost explanation, and a signaling model. While all three models forecast dividends, their forecasts regarding other firm behavior, and their forecasts for the efficiency and distributional effects of a dividend tax, often differ. Given the evidence to date, we find the agency model is the one most consistent with the data.

Orbital optimization in the perfect pairing hierarchy. Applications to full-valence calculations on linear polyacenes

We describe the implementation of orbital optimization for the models in the perfect pairing hierarchy [Lehtola et al, J. Chem. Phys. 145, 134110 (2016)]. Orbital optimization, which is generally necessary to obtain reliable results, is pursued at perfect pairing (PP) and perfect quadruples (PQ) levels of theory for applications on linear polyacenes, which are believed to exhibit strong correlation in the {\pi} space. While local minima and {\sigma}-{\pi} symmetry breaking solutions were found for PP orbitals, no such problems were encountered for PQ orbitals. The PQ orbitals are used for single-point calculations at PP, PQ and perfect hextuples (PH) levels of theory, both only in the {\pi} subspace, as well as in the full {\sigma}{\pi} valence space. It is numerically demonstrated that the inclusion of single excitations is necessary also when optimized orbitals are used. PH is found to yield good agreement with previously published density matrix renormalization group (DMRG) data in the {\pi} space, capturing over 95% of the correlation energy. Full-valence calculations made possible by our novel, efficient code reveal that strong correlations are weaker when larger bases or active spaces are employed than in previous calculations. The largest full-valence PH calculations presented correspond to a (192e,192o) problem.Comment: 19 pages, 4 figure

The Productivity Slowdown, Measurement Issues, and the Explosion of Computer Power

macroeconomics, Productivity Slowdown, Measurement Issues, Computer Power

Global Research Report – South and East Asia

Global Research Report – South and East Asia by Jonathan Adams, David Pendlebury, Gordon Rogers & Martin Szomszor. Published by Institute for Scientific Information, Web of Science Group

Carbon emissions reduction and net energy generation analysis in the New Zealand electricity sector through to 2050

Carbon Emissions Pinch Analysis (CEPA) and Energy Return On Energy Investment (ERoEI) analysis are combined to investigate the feasibility of New Zealand reaching and maintaining a renewables electricity target of above 80% by 2025 and 2050, while also increasing electricity generation at an annual rate of 1.5%, and with an increase of electricity generation in the distant future to accommodate a 50% switch to electric vehicle transportation. To meet New Zealand’s growing electricity demand up to 2025 the largest growth in renewable generation is expected to come from geothermal generation (four-fold increase) followed by wind and hydro. To meet expected demand up to 2050 and beyond, including electric vehicle transportation, geothermal generation will expand to 17% of total generation, wind to 16%, and other renewables, such as marine and biomass, will make up about 4%. Including hydro, the total renewable generation in 2050 is expected to reach 82%

How accurate is density functional theory at predicting dipole moments? An assessment using a new database of 200 benchmark values

Dipole moments are a simple, global measure of the accuracy of the electron density of a polar molecule. Dipole moments also affect the interactions of a molecule with other molecules as well as electric fields. To directly assess the accuracy of modern density functionals for calculating dipole moments, we have developed a database of 200 benchmark dipole moments, using coupled cluster theory through triple excitations, extrapolated to the complete basis set limit. This new database is used to assess the performance of 88 popular or recently developed density functionals. The results suggest that double hybrid functionals perform the best, yielding dipole moments within about 3.6-4.5% regularized RMS error versus the reference values---which is not very different from the 4% regularized RMS error produced by coupled cluster singles and doubles. Many hybrid functionals also perform quite well, generating regularized RMS errors in the 5-6% range. Some functionals however exhibit large outliers and local functionals in general perform less well than hybrids or double hybrids.Comment: Added several double hybrid functionals, most of which turned out to be better than any functional from Rungs 1-4 of Jacob's ladder and are actually competitive with CCS

Thermodynamic data for fifty reference elements

This report is a compilation of thermodynamic functions of 50 elements in their standard reference state. The functions are C(sub p)(sup 0), (H(sup 0)(T) - H(sup 0)(0)), S(sup 0)(T), and -(G(sup 0)(T) - H(sup 0)(O)) for the elements Ag, Al, Ar, B, Ba, Be, Br2, C, Ca, Cd, Cl2, Co, Cr, Cs, Cu, F2, Fe, Ge, H2, He, Hg, I2, K, Kr, Li, Mg, Mn, Mo, N2, Na, Nb, Ne, Ni, O2, P, Pb, Rb, S, Si, Sn, Sr, Ta, Th, Ti, U, V, W, Xe, Zn, and Zr. Deuterium D2 and electron gas e(sup -) are also included. The data are tabulated as functions of temperature as well as given in the form of least-squares coefficients for two functional forms for C(sub p)(sup 0) with integration constants for enthalpy and entropy. One functional form for C(sub p)(sup 0) is a fourth-order polynomial and the other has two additional terms, one with T(exp -1) and the other with T(exp -2). The gases Ar, D2, e(sup -), H2, He, Kr, N2, Ne, O2, and Xe are tabulated for temperatures from 100 to 20,000 K. The remaining gases Cl2 and F2 are tabulated from 100 to 6000 K and 1000 to 6000 K. The second functional form for C(sub p)(sup 0) has an additional interval from 6000 to 20,000 K for the gases tabulated to 20,000 K. The fits are constrained so that the match at the common temperature endpoints. The temperature ranges for the condensed species vary with range of the data, phase changes, and shapes of the C(sub p)(sup 0) curves