Rank-invariant estimation of inbreeding coefficients

The two alleles an individual carries at a locus are identical by descent (ibd) if they have descended from a single ancestral allele in a reference population, and the probability of such identity is the inbreeding coefficient of the individual. Inbreeding coefficients can be predicted from pedigrees with founders constituting the reference population, but estimation from genetic data is not possible without data from the reference population. Most inbreeding estimators that make explicit use of sample allele frequencies as estimates of allele probabilities in the reference population are confounded by average kinships with other individuals. This means that the ranking of those estimates depends on the scope of the study sample and we show the variation in rankings for common estimators applied to different subdivisions of 1000 Genomes data. Allele-sharing estimators of within-population inbreeding relative to average kinship in a study sample, however, do have invariant rankings across all studies including those individuals. They are unbiased with a large number of SNPs. We discuss how allele sharing estimates are the relevant quantities for a range of empirical applications.

Impedance Ratio Method for Urine Conductivity-Invariant Estimation of Bladder Volume

Non-invasive estimation of bladder volume could help patients with impaired bladder volume sensation to determine the right moment for catheterisation. Continuous, non-invasive impedance measurement is a promising technology in this scenario, although influences of body posture and unknown urine conductivity limit wide clinical use today. We studied impedance changes related to bladder volume by simulation, in-vitro and in-vivo measurements with pigs. In this work, we present a method to reduce the influence of urine conductivity to cystovolumetry and bring bioimpedance cystovolumetry closer to a clinical application.

A TIME-VARYING APPROACH OF THE US WELFARE COST OF INFLATION

Money-demand specifications exhibit instability, especially for long spans of data. This paper reconsiders the welfare cost of inflation for the US economy using a flexible time-varying (TV) cointegration methodology to estimate the money-demand function. We find evidence that the TV cointegration estimation provides a better fit of the actual data than a time-invariant estimation and that the throughout unitary income elasticity only exists for the log–log form over the entire sample period. Our estimate of the welfare cost of inflation for a 10% inflation rate lies in the range of 0.025–0.75% of gross domestic product (GDP) and averages 0.27%. In sum, our findings fall well within the ranges of existing studies of the welfare cost of inflation. We find that the welfare cost averages 7.4% higher during expansions than recessions for 10% inflation rate. Finally, the interest elasticity of money demand shows substantial variability over our sample period.