International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food

Purchasing power adjusted incomes applied in cross-country comparisons are measured with bias. In this paper, we estimate the purchasing power parity (PPP) bias in Penn World Table incomes and provide corrected incomes. The bias is substantial and systematic: the poorer a country, the more its income tends to be overestimated. Consequently, international income inequality is substantially underestimated. Our methodological contribution is to exploit the analogies between PPP bias and the bias in consumer price index (CPI) numbers. The PPP bias and subsequent corrected incomes are measured by estimating Engel curves for food, which is an established method of measuring CPI bias.

Older or Wealthier? The Impact of Age Adjustment on Cross-Sectional Inequality Measures.

Differences in individual wealth holdings are widely viewed as a driving force of economic inequality. However, as this finding relies on cross-section data, a concern is that one confuses older with wealthier. We propose a new method to adjust for age effects in cross-sections, which eliminates wealth inequality due to age, yet preserves inequality arising from other factors. Using a new cross-country comparable database, we examine the impact of age adjustments on wealth inequality across countries and over time. We find that the most widely used method yield a substantially different picture of age adjusted wealth inequality than our method.Wealth inequality; Life cycle; Age adjustments; Gini coefficient.

Older or wealthier? The impact of age adjustments on the wealth inequality ranking of countries

Differences in individual wealth holdings are widely viewed as a driving force of economic inequality. However, as this finding relies on cross-section data, we may confuse older with wealthier. We propose a new method to adjust for age effects in cross-sections, which eliminates transitory wealth inequality due to age, yet preserves inequality arising from other factors. This new method is superior to existing methods, like the much used Paglin-Gini, which is shown to have several problems. A new cross-country comparable database reveals that the choice of method is empirically important: Existing methods yield erroneous wealth inequality rankings of countries.Wealth inequality, Life cycle, Age adjustments, Gini coeffcient.

International income inequality : measuring PPP bias by estimating Engel curves for food

Price-adjusted data on national incomes applied in cross-country compar- isons are measured with bias. By studying micro data, this paper ¯nds that the bias is systematic: the poorer a country is, the more its income tends to be overestimated. Consequently, international income inequalities are under- estimated. The bias in the macro price variables (PPPs), is caused by factors ana- logues to those creating bias in consumer price index numbers (CPIs). Ex- ploiting this fact, the PPP bias is measured by estimating Engel curves for food, a method already established to measure CPI bias

Baby Booming Inequality? Demographic Change and Earnings Inequality in Norway, 1967-2000

In this paper, we demonstrate how age-adjusted inequality measures can be used to evaluate whether changes in inequality over time are due to changes in the age structure. To this end, we use administrative data on earnings for every male Norwegian during 1967-2000. We find that the substantial rise in earnings inequality over the 1980s and into the early 1990s, is to some extent driven by the fact that the large baby boom cohorts are approaching the peak of the age-earnings profile. We further demonstrate that the impact of age adjustments on the trend in inequality during the period from 1993-2000 is highly sensitive to the method used: while the most widely used age-adjusted inequality measure indicates little change in inequality over this period, a new and improved age-adjusted measure suggests a decline in inequality.inequality trend, age structure, age-earnings profile, Gini coefficient

Hormone references for ultrasound breast staging and endocrine profiling to detect female onset of puberty

Context - Application of ultrasound (US) to evaluate attainment and morphology of glandular tissue provides a new rationale for evaluating onset and progression of female puberty, but currently no hormone references complement this method. Furthermore, previous studies have not explored the predictive value of endocrine profiling to determine female puberty onset. Objective - To integrate US breast staging with hypothalamic-pituitary-gonadal hormone references and test the predictive value of an endocrine profile to determine thelarche. Design Setting and Participants - Cross-sectional sample of 601 healthy Norwegian girls, ages 6 to 16 years. Main Outcome Measures - Clinical and ultrasound breast evaluations were performed for all included girls. Blood samples were analyzed by immunoassay and ultrasensitive liquid chromatography–tandem mass spectrometry (LC-MS/MS) to quantify estradiol (E2) and estrone (E1) from the subpicomolar range. Results - References for E2, E1, luteinizing hormone, follicle-stimulating hormone, and sex hormone–binding globulin were constructed in relation to chronological age, Tanner stages, and US breast stages. An endocrine profile index score derived from principal component analysis of these analytes was a better marker of puberty onset than age or any individual hormone, with receiver-operating characteristic area under the curve 0.91 (P < 0.001). Ultrasound detection of nonpalpable glandular tissue in 14 out of 264 (5.3%) girls with clinically prepubertal presentation was associated with significantly higher median serum levels of E2 (12.5 vs 4.9 pmol/L; P < 0.05) and a distinct endocrine profile (arbitrary units; P < 0.001). Conclusions - We provide the first hormone references for use with US breast staging and demonstrate the application of endocrine profiling to improve detection of female puberty onset

Testicular ultrasound to stratify hormone references in a cross-sectional Norwegian study of male puberty

Context: Testicular growth represents the best clinical variable to evaluate male puberty, but current pediatric hormone references are based on chronological age and subjective assessments of discrete puberty development stages. Determination of testicular volume (TV) by ultrasound provides a novel approach to assess puberty progression and stratify hormone reference intervals. Objective: The objective of this article is to establish references for serum testosterone and key hormones of the male pituitary-gonadal signaling pathway in relation to TV determined by ultrasound. Design, Setting, and Participants: Blood samples from 414 healthy Norwegian boys between ages 6 and 16 years were included from the cross-sectional “Bergen Growth Study 2.” Participants underwent testicular ultrasound and clinical assessments, and serum samples were analyzed by liquid chromatography tandem–mass spectrometry and immunoassays. Main Outcome Measures: We present references for circulating levels of total testosterone, luteinizing hormone, follicle-stimulating hormone, and sex hormone–binding globulin in relation to TV, chronological age, and Tanner pubic hair stages. Results: In pubertal boys, TV accounted for more variance in serum testosterone levels than chronological age (Spearman r = 0.753, P < .001 vs r = 0.692, P < .001, respectively). Continuous centile references demonstrate the association between TV and hormone levels during puberty. Hormone reference intervals were stratified by TV during the pubertal transition. Conclusions: Objective ultrasound assessments of TV and stratification of hormone references increase the diagnostic value of traditional references based on chronological age or subjective staging of male puberty.acceptedVersio

Reference curves for pediatric endocrinology: leveraging biomarker z-scores for clinical classifications

Context: Hormone reference intervals in pediatric endocrinology are traditionally partitioned by age and lack the framework for benchmarking individual blood test results as normalized z-scores and plotting sequential measurements onto a chart. Reference curve modeling is applicable to endocrine variables and represents a standardized method to account for variation with gender and age. Objective: We aimed to establish gender-specifc biomarker reference curves for clinical use and benchmark associations between hormones, pubertal phenotype, and body mass index (BMI). Methods: Using cross-sectional population sample data from 2139 healthy Norwegian children and adolescents, we analyzed the pubertal status, ultrasound measures of glandular breast tissue (girls) and testicular volume (boys), BMI, and laboratory measurements of 17 clinical biomarkers modeled using the established “LMS” growth chart algorithm in R. Results: Reference curves for puberty hormones and pertinent biomarkers were modeled to adjust for age and gender. Z-score equivalents of biomarker levels and anthropometric measurements were compiled in a comprehensive beta coeffcient matrix for each gender. Excerpted from this analysis and independently of age, BMI was positively associated with female glandular breast volume (β = 0.5, P < 0.001) and leptin (β = 0.6, P < 0.001), and inversely correlated with serum levels of sex hormone-binding globulin (SHBG) (β = −0.4, P < 0.001). Biomarker z-score profles differed signifcantly between cohort subgroups stratifed by puberty phenotype and BMI weight class. <p<Conclusion: Biomarker reference curves and corresponding z-scores provide an intuitive framework for clinical implementation in pediatric endocrinology and facilitate the application of machine learning classifcation and covariate precision medicine for pediatric patients