Effects of Terms of Trade Gains and Tariff Changes on the Measurement of US Productivity Growth

The acceleration in US productivity growth since 1995 is often attributed to declining prices for information technology (IT ) goods, and therefore enhanced productivity growth in that sector. We investigate an alternative explanation for these IT price movements: gains in the US terms of trade and tariff reductions, especially for IT products, which led to greater gains than shown by official indexes. We do not, however, investigate the indexes used to deflate the domestic absorption components of GDP, and if upward biases are present in those indexes that could offset some of the effects of mismeasured export and import indexes. (JEL C43, E23, F13, F14, J24

Effects of Terms of Trade Gains and Tariff Changes on the Measurement of U.S. Productivity Growth

Since 1995, growth in productivity in the United States appears to have accelerated dramatically. In this paper, we argue that part of this apparent speed-up actually represents gains in the terms of trade and tariff reductions, especially for information-technology products. We demonstrate how unmeasured gains in the terms of trade and declines in tariffs can cause conventionally measured growth in real output and productivity to be overstated. Building on the GDP function approach of Diewert and Morrison, we develop methods for measuring these effects. From 1995 through 2006, the average growth rates of our alternative price indexes for U.S. imports are 1.5% per year lower than the growth rate of price indexes calculated using official methods. Thus properly measured terms-of-trade gain can account for close to 0.2 percentage points per year, or about 20%, of the 1995-2006 apparent increase in productivity growth for the U.S. economy. Bias in the price indexes used to deflate domestic output is a question beyond the scope of this paper, but if upward bias were also present in those indexes, this could offset some of the effects of mismeasurement of gains in terms of trade.

Disentangling Time-series Spectra with Gaussian Processes: Applications to Radial Velocity Analysis

Measurements of radial velocity variations from the spectroscopic monitoring of stars and their companions are essential for a broad swath of astrophysics; these measurements provide access to the fundamental physical properties that dictate all phases of stellar evolution and facilitate the quantitative study of planetary systems. The conversion of those measurements into both constraints on the orbital architecture and individual component spectra can be a serious challenge, however, especially for extreme flux ratio systems and observations with relatively low sensitivity. Gaussian processes define sampling distributions of flexible, continuous functions that are well-motivated for modeling stellar spectra, enabling proficient searches for companion lines in time-series spectra. We introduce a new technique for spectral disentangling, where the posterior distributions of the orbital parameters and intrinsic, rest-frame stellar spectra are explored simultaneously without needing to invoke cross-correlation templates. To demonstrate its potential, this technique is deployed on red-optical time-series spectra of the mid-M-dwarf binary LP661-13. We report orbital parameters with improved precision compared to traditional radial velocity analysis and successfully reconstruct the primary and secondary spectra. We discuss potential applications for other stellar and exoplanet radial velocity techniques and extensions to time-variable spectra. The code used in this analysis is freely available as an open-source Python package

Disentangling time-series spectra with Gaussian processes : applications to radial velocity analysis

Funding: K.M. is supported at Harvard by NSF grants AST-1211196 and AST-156854. Work by B.T.M. was performed under contract with the Jet Propulsion Laboratory (JPL) funded by NASA through the Sagan Fellowship Program executed by the NASA Exoplanet Science Institute. This material was based upon work partially supported by the National Science Foundation under Grant DMS-1127914 to the Statistical and Applied Mathematical Sciences Institute.Measurements of radial velocity variations from the spectroscopic monitoring of stars and their companions are essential for a broad swath of astrophysics; these measurements provide access to the fundamental physical properties that dictate all phases of stellar evolution and facilitate the quantitative study of planetary systems. The conversion of those measurements into both constraints on the orbital architecture and individual component spectra can be a serious challenge, however, especially for extreme flux ratio systems and observations with relatively low sensitivity. Gaussian processes define sampling distributions of flexible, continuous functions that are well-motivated for modeling stellar spectra, enabling proficient searches for companion lines in time-series spectra. We introduce a new technique for spectral disentangling, where the posterior distributions of the orbital parameters and intrinsic, rest-frame stellar spectra are explored simultaneously without needing to invoke cross-correlation templates. To demonstrate its potential, this technique is deployed on red-optical time-series spectra of the mid-M-dwarf binary LP661-13. We report orbital parameters with improved precision compared to traditional radial velocity analysis and successfully reconstruct the primary and secondary spectra. We discuss potential applications for other stellar and exoplanet radial velocity techniques and extensions to time-variable spectra. The code used in this analysis is freely available as an open-source Python package.Publisher PDFPeer reviewe

Hawai`i Supernova Flows: A Peculiar Velocity Survey Using Over a Thousand Supernovae in the Near-Infrared

We introduce the Hawai`i Supernova Flows project and present summary statistics of the first 1218 astronomical transients observed, 669 of which are spectroscopically classified Type Ia Supernovae (SNe Ia). Our project is designed to obtain systematics-limited distances to SNe Ia while consuming minimal dedicated observational resources. This growing sample will provide increasing resolution into peculiar velocities as a function of position on the sky and redshift, allowing us to more accurately map the structure of dark matter. This can be used to derive cosmological parameters such as $\sigma_8$ and can be compared with large scale flow maps from other methods such as luminosity-line width or luminosity-velocity dispersion correlations in galaxies. Additionally, our photometry will provide a valuable test bed for analyses of SNe Ia incorporating near-infrared data. In this survey paper, we describe the methodology used to select targets, collect and reduce data, and calculate distances.Comment: 33 pages, 23 figure

The DEHVILS Survey Overview and Initial Data Release: High-Quality Near-Infrared Type Ia Supernova Light Curves at Low Redshift

While the sample of optical Type Ia Supernova (SN Ia) light curves (LCs) usable for cosmological parameter measurements surpasses 2000, the sample of published, cosmologically viable near-infrared (NIR) SN Ia LCs, which have been shown to be good "standard candles," is still $\lesssim$ 200. Here, we present high-quality NIR LCs for 83 SNe Ia ranging from $0.002 < z < 0.09$ as a part of the Dark Energy, H$_0$, and peculiar Velocities using Infrared Light from Supernovae (DEHVILS) survey. Observations are taken using UKIRT's WFCAM, where the median depth of the images is 20.7, 20.1, and 19.3 mag (Vega) for $Y$, $J$, and $H$-bands, respectively. The median number of epochs per SN Ia is 18 for all three bands ($YJH$) combined and 6 for each band individually. We fit 47 SN Ia LCs that pass strict quality cuts using three LC models, SALT3, SNooPy, and BayeSN and find scatter on the Hubble diagram to be comparable to or better than scatter from optical-only fits in the literature. Fitting NIR-only LCs, we obtain standard deviations ranging from 0.128-0.135 mag. Additionally, we present a refined calibration method for transforming 2MASS magnitudes to WFCAM magnitudes using HST CALSPEC stars that results in a 0.03 mag shift in the WFCAM $Y$-band magnitudes.Comment: 24 pages, 9 figures. Accepted by MNRA

Qatar-2: A K dwarf orbited by a transiting hot Jupiter and a more massive companion in an outer orbit

We report the discovery and initial characterization of Qatar-2b, a hot Jupiter transiting a V = 13.3 mag K dwarf in a circular orbit with a short period, P_ b = 1.34 days. The mass and radius of Qatar-2b are M_p = 2.49 M_j and R_p = 1.14 R_j, respectively. Radial-velocity monitoring of Qatar-2 over a span of 153 days revealed the presence of a second companion in an outer orbit. The Systemic Console yielded plausible orbits for the outer companion, with periods on the order of a year and a companion mass of at least several M_j. Thus Qatar-2 joins the short but growing list of systems with a transiting hot Jupiter and an outer companion with a much longer period. This system architecture is in sharp contrast to that found by Kepler for multi-transiting systems, which are dominated by objects smaller than Neptune, usually with tightly spaced orbits that must be nearly coplanar

Feasibility of detecting single atoms using photonic bandgap cavities

We propose an atom-cavity chip that combines laser cooling and trapping of neutral atoms with magnetic microtraps and waveguides to deliver a cold atom to the mode of a fiber taper coupled photonic bandgap (PBG) cavity. The feasibility of this device for detecting single atoms is analyzed using both a semi-classical treatment and an unconditional master equation approach. Single-atom detection seems achievable in an initial experiment involving the non-deterministic delivery of weakly trapped atoms into the mode of the PBG cavity.Comment: 11 pages, 5 figure