High signal-to-noise ratio observations and the ultimate limits of precision pulsar timing

We demonstrate that the sensitivity of high-precision pulsar timing experiments will be ultimately limited by the broadband intensity modulation that is intrinsic to the pulsar's stochastic radio signal. That is, as the peak flux of the pulsar approaches that of the system equivalent flux density, neither greater antenna gain nor increased instrumental bandwidth will improve timing precision. These conclusions proceed from an analysis of the covariance matrix used to characterise residual pulse profile fluctuations following the template matching procedure for arrival time estimation. We perform such an analysis on 25 hours of high-precision timing observations of the closest and brightest millisecond pulsar, PSR J0437-4715. In these data, the standard deviation of the post-fit arrival time residuals is approximately four times greater than that predicted by considering the system equivalent flux density, mean pulsar flux and the effective width of the pulsed emission. We develop a technique based on principal component analysis to mitigate the effects of shape variations on arrival time estimation and demonstrate its validity using a number of illustrative simulations. When applied to our observations, the method reduces arrival time residual noise by approximately 20%. We conclude that, owing primarily to the intrinsic variability of the radio emission from PSR J0437-4715 at 20 cm, timing precision in this observing band better than 30 - 40 ns in one hour is highly unlikely, regardless of future improvements in antenna gain or instrumental bandwidth. We describe the intrinsic variability of the pulsar signal as stochastic wideband impulse modulated self-noise (SWIMS) and argue that SWIMS will likely limit the timing precision of every millisecond pulsar currently observed by Pulsar Timing Array projects as larger and more sensitive antennae are built in the coming decades.Comment: 16 pages, 9 figures, accepted for publication in MNRAS. Updated version: added DOI and changed manuscript to reflect changes in the final published versio

The Spanish term structure of interest rates revisited: cointegration with multiple structural breaks, 1974-2010

In this paper we consider the possibility that a linear cointegrated regression model with multiples structural changes would provide a better empirical description of the term structure model of interest rates. Our methodology is based on instability tests recently proposed in Kejriwal and Perron (2010) as well as the cointegration test in Arai and Kurozumi (2007) and Kejriwal (2008) developed to allow for multiple breaks under the null hypothesis of cointegration.Term structure of interest rates; Cointegration; Multiple Structural Breaks.

Firm Characteristics, Economic Conditions and Capital Structure Adjustment

We use a dynamic framework and panel methodology to investigate the determinants of a firms’ time-varying capital structure. Our sample comprises 706 European firms from France, Germany, Italy and the U.K. over the period from 1983 to 2002. If capital structure adjustment is costly, firms may deviate temporarily from their target debt ratios. Therefore, we endogenize the adjustment process and analyze the impact of firm-specific characteristics as well as macroeconomic factors on the speed of adjustment towards target leverage. We find that larger and faster growing firms as well as firms that are further away from their targets adjust more readily. Additionally, we document interesting relations between well-known business cycle variables and the adjustment speed. In a nutshell, firms adjust faster in favorable macroeconomic conditions, e.g., if interest rates are low and the risk of disruptions in the global financial system are negligible. We also document that capital structure decision are largely determined by financial constraints. Finally, we shed new light on the interdependence between book value based and market value based measures of leverage as well as on capital structure rebalancing issues.Capital Structure, dynamic analysis, panel data

Transaction based indices for the UK commercial property market : exploration and evaluation using IPD data

Publisher PD

Lessons Learned and Next Steps in Energy Efficiency Measurement and Attribution: Energy Savings, Net to Gross, Non-Energy Benefits, and Persistence of Energy Efficiency Behavior

This white paper examines four topics addressing evaluation, measurement, and attribution of direct and indirect effects to energy efficiency and behavioral programs: Estimates of program savings (gross); Net savings derivation through free ridership / net to gross analyses; Indirect non-energy benefits / impacts (e.g., comfort, convenience, emissions, jobs); and, Persistence of savings