Accounting for Wealth Concentration in the United States

We assess the empirical relevance of different macroeconomic modeling approaches to wealth concentration, using the joint distribution of earnings, capital income and net worth in combination with an OLG model of household heterogeneity. We find large earnings disparities to be the primary source of US wealth concentration. This reflects the fact that labor income, from salaries but also from entrepreneurship, is a major income source for top income and wealth groups in the data. Bequests and differences in rates of return on capital together explain about half the holdings of the wealthiest of households, but much less for the rest.

Accounting for Wealth Concentration in the US

Comment

The double one percent: Identifying an elite and a super-elite using the joint distribution of income and net worth

Retention in randomised controlled trials is crucial to maximising study power and generalisability. A Study Within A Trial (SWAT) evaluated if sending a Thank You card improved 6-month questionnaire return rates in the SWHSI-2 trial. A two-arm SWAT, using 1:1 (intervention:control) allocation, embedded withinthe SWHSI-2 trial. The primary outcome was the difference in the return rate of the 6-month questionnaire. Secondary outcomes were the difference in return rate of the 12-month questionnaire, questionnaire completeness, need for a reminder, and cost. The primary analysis was conducted using mixed-effects logistic regression adjusted for main trial allocation as a fixed effect and site as a random effect. Random-effects meta-analysis combined all available data for this intervention. A total of 560 participants were included in the SWAT. There was no difference in the 6-month questionnaire return rate between the Thank You card group and the no Thank You card group (OR 1.04, 95% CI 0.73 to 1.50, p = 0.87). The 12-month retention rate was slightly higher in the Thank You card group, but the difference was not statistically significant (OR 1.15, 95% CI 0.81 to 1.62, p = 0.43). Findings were very similar in sensitivity analyses accounting for intervention participants who did not receive their card. There was no evidence of difference for any of the remaining secondary outcomes. Meta-analysis of the 12-month return rate suggests that Thank You cards may provide slight improvements in questionnaire response rates; however there is uncertainty in this estimate (OR 1.07, 95% CI 0.79 to 1.45). It remains unclear if a Thank You card increased the rate of 6-month follow-up questionnaire completion in the SWHSI-2 trial. This is further amplified by the limited number of SWAT replications completed to date and included in the meta-analysis (n=2). The SWATs to date have primarily been undertaken in trials with a predominantly older, white, male, population. Further SWAT replications are therefore required in other populations to ensure generalisability of a cumulative SWAT finding. Host Trial: ISRCTN26277546. Prospectively registered on 25th March 2019. SWAT: MRC Hub for Trials Methodology Research SWAT repository #119 can be found at: https://www.qub.ac.uk/sites/TheNorthernIrelandNetworkforTrialsMethodologyResearch/FileStore/Filetoupload,959362,en.pdf .

Against the ongoing assessment of the root causes of rising economic inequality in industrialized countries, analyses of the distribution of savings along the income and wealth distribution are of high interest. We analyze the concentration of household savings in Germany by estimating saving amounts, saving rates and shares in aggregate savings across income and wealth groups. Our calculations are based on the Sample Survey of Household Income and Expenditure (EVS), containing more than 40,000 households in Germany. We show that the concentration of savings is substantial: while the top income decile’s share in total savings reaches 60 percent, the lower half of the income distribution on average does not save at all. Across wealth groups the concentration of savings is somewhat less pronounced. We also look beyond the top income threshold underlying the EVS (18,000 euros of monthly net household income) and demonstrate that corrected saving rates for the top income groups are considerably higher than those derived from the EVS alone. Hence, the top income groups’ shares in aggregate savings exceed estimated shares solely based on EVS data, revealing a substantially more pronounced concentration of savings along the income distribution.

Wealth inequality and the contribution of wealth to households' well-being have received an increasing attention during the last years. This study examines the patterns of wealth inequality and the correspondence between the distributions of income and wealth. It takes advantage of a unique and multidisciplinary longitudinal survey on people aged 50 and older in Israel, conducted as part of the SHARE project (Survey of Health, Aging and Retirement in Europe). SHARE includes detailed information on disposable income and on the value of the various components of real assets, financial assets and debts. All this information allows us to construct a broad net worth measure on the household level. Based on the third wave of SHARE-Israel, the distributions of wealth and of income are examined by several measures: the mean to median ratio; the value of wealth at different percentile points of the distribution and percentile ratios; inequality measures - Gini coefficient and the General Entropy measure (?=2); and transition matrices based on the quintile distributions of income and net worth.We found that similarly to European countries, patterns in wealth inequality (stock data) differ strongly from patterns of income inequality. Wealth is more unequal distributed than income: the Lorenz curve for net worth is further away from the 45 degree line and its Gini coefficient is larger (0.573 versus 0.422). The median to mean ratio is 0.56 and 0.80 for net worth and income, respectively. Net worth of the 25th percentile was about 40% of the median, while the net worth of the 90th percentile was 4.3 times that of the median wealth. The corresponding findings for the income are 50% and 2.5 times, respectively. The relative share of the highest decile of the population is closed to 40% of total net worth, 65% of total financial wealth and to 28% of total income. The transition matrix shows that about 34% of the families are ranked in the same quintile according to net worth and income, about 35% of families are ranked higher by net worth than by income and 31% were ranked higher by income than net worth (found below the diagonal of the transitions matrix).Keywords: Inequality, wealth, net worth, income, SHARE ? Israel. .

A Review of:
 Sung, J. S., & Tolppanen, B. P. (2013). Do library fines work?: Analysis of the effectiveness of fines on patron’s return behavior at two mid-sized academic libraries. Journal of Academic Librarianship, 39(6), 506-511. http://dx.doi.org/10.1016/j.acalib.2013.08.011
 
 Abstract
 
 Objectives – To quantify library fines and their impact on patron return behaviour. 
 
 Design – Hypothesis testing of data extracted from integrated library systems.
 
 Setting – Two midsize academic libraries, including one from the Pacific, University of Hawaii at Manoa (UHM), and one from the Midwest, Eastern Illinois University (EIU).
 
 Subjects – Undergraduates, graduate students, and faculty. 
 
 Methods – The authors collected data from two midsized universities. The universities have identical integrated library systems, which allowed for uniform data extraction. The authors counted book returns in each population group (undergraduates, graduate students, and faculty) for those books that were returned before and after the due dates with a focus on late fees as the primary variable. The authors tested the following five hypotheses: 
 
 • Hypothesis 1: “There is no difference in return rates before due dates among the UHM patron groups because the fine policy is the same for all patron groups” (p. 507). 
 • Hypothesis 2: “Before 2006, the EIU undergraduate students’ return rates before due dates should be the highest among the three EIU groups because this was the only group which had overdue fines. . . . There should be no difference in the return rates before due dates between EIU faculty and EIU graduate students (both groups had no overdue fines)” (p. 507). 
 • Hypothesis 3: “EIU graduate students’ return rates before due dates was lower for 2002–2006 than 2007–2011” (p. 507). This hypothesis tests the impact of a change in fine policy that the library implemented in the fall of 2006. 
 • Hypothesis 4: “UHM undergraduate students’ return rates before due dates is higher than that of EIU undergraduate students” because there is no grace period for UHM undergraduates (p. 507). EIU undergraduate students have a 10-day grace period. 
 • Hypothesis 5: “UHM faculty’s return rates before due dates is higher than that of EIU faculty” (p. 507). UHM faculty incur overdue fines, but EIU faculty encounter no penalty for overdue materials. 
 
 From the integrated library systems, the authors extracted data for the number of books returned before due dates and after overdue notices and for the number of books borrowed by the different populations for the time period starting with Fall 2002 and ending with Spring 2011. The authors analyzed the data using Statistical Package for Social Science (SPSS) and made comparisons using analysis of variance (ANOVA) expressed with an F-ratio and p-value < 0.01 as the level of significance. 
 
 Main Results – The findings did not support hypotheses 1 or 2. For hypothesis 1, in which fines were the same for undergraduates, graduate students, and faculty, return rates increased with academic level and faculty groups. The rates were 90.4%, 93.9%, and 95.7%, respectively (F = 112.1, p < 0.001). For hypothesis 2, the return rate was 88.8% for undergraduates, 92.6% for graduate students, and 80.1% for faculty. The group difference was small but still statistically significant (F = 171.4, p < 0.001). The graduate students, who were not fined, had significantly higher return rates before due dates than undergraduates who incurred fines. Graduate students had higher return rates than faculty, though both groups had no fines.
 
 The data did not support hypotheses 3 and 4. For hypothesis 3, no significant change occurred in return rates before and after imposing fines (F = 5.75, p = .031). For hypothesis 4, the return rates of undergraduates at the university with a grace period showed no statistically significant difference in return rates from those undergraduates with no grace period (F = 4.355, p = .044). 
 
 The findings supported hypothesis 5. The return rates indicated a statistically significant difference between faculty with fines for overdue books and those with no fines (F = 1701, p < 0.001). For those hypotheses for which the differences were not significant, the authors cite other variables, including reminders, grace periods, maturity of the borrower, withholding of privileges, fees, and lost book charges, that may contribute to return rates.
 
 Conclusions – In answer to the main research question, the authors conclude that “fines indeed make a difference” (p. 511) in patron book return conduct. However, they also note that fines can mar the reputation of the library creating a barrier to access and that courtesy notices and overdue notices are also effective ways to ensure timely return of materials.

Colorectal cancer (CRC) is one of the most common cancers in the USA. In 2017, an estimated 135,420 people were diagnosed with CRC and 50,260 people died from CRC. Several screening modalities are recommended by the United States Preventive Services Task Force (USPSTF), including annual stool tests that are usually completed at home and under-used compared with colonoscopy despite stated patient preferences for an alternative to colonoscopy. The Community Preventive Services Task Force recommends use of small media interventions (SMIs) to increase CRC screening and calls for a greater understanding of its independent impact on screening participation. This study tested whether a SMI increased the likelihood of participant return of a USPSTF recommended Fecal Immunochemical Test (FIT). In total, 804 individuals participated in a two-group, prospective randomized controlled trial. Descriptive statistics with chi-square tests compared differences in participant characteristics and return rates. Multivariable log-binomial modeling estimated combined effects of patient characteristics with FIT return rates. No differences in return rates were observed overall or by participant characteristics other than the year of enrollment. A multivariable model controlling for all covariates, found gender, insurance type, and regular place for healthcare to be significantly associated with return rates. Receipt of the SMI did not independently increase overall return rates but it may have improved the ease of completing the FIT by some participants, particularly women, those with insurance, and those with a regular place for healthcare.

Although radio telemetry can provide useful information, the possible negative effects of transmitters, including biased results and detrimental effects on the birds, must also be considered. Several investigators have examined the effects of transmitters on larger birds, but few have examined their possible long-term effects, as assessed by return rates, on small passerines. We examined the possible negative effects of transmitters on a small (15.5 g) passerine. We used glue to attach radio transmitters to 40 male Swainson's Warblers (Limnothlypis swainsonii) at two study sites in Arkansas in 2005 and 2006. To assess possible effects of transmitters on survival, we compared the following-year return rates of radio-tagged birds to birds that were captured and color banded, but did not receive transmitters. Least squared mean return rates for all birds ranged between 0.46 and 0.57. We found no significant difference in the following-year return rate of radio-tagged and nonradio-tagged birds. In addition, we found no significant differences in return rates between study sites or years, and no significant interactions between any combination of radio transmitter (radio tagged or not), site, and year. Our results indicate that attachment of transmitters did not affect return rates of male Swainson's Warblers and that the glue-on technique is a good option for short-term studies of small passerines. RESUMEN. Efecto de radiotransmisores en las tasas de retorno de individuos de Limnoth- lypis swainsonii Aunque la radiotelemetr´ oa puede proveer de informaci´ on de utilidad, el posible efecto negativo de estos, incluyendo sesgo en la informaciy efecto detrimental, tambidebe tomarse en consideraci´

Income Inequality in France, 1900-2014: Evidence from Distributional National Accounts (DINA)

Income Inequality in France, 1900-2014: Evidence from Distributional National Accounts (DINA)

Two field studies used 2400 “lost letters” to test the hypothesis that return rates would be greater from smaller rural communities (population Ms = 1729) than from a city (population M = 60,591), unless the addressee was affiliated with a socially or politically deviant group. Addresses' affiliations were significantly associated with different rates of return in both studies. In Study A, community size and addressees' affiliations were significantly associated with different rates of return in the city and smaller rural communities, rates generally being greater in the city even when the people in need of help were affiliated with the deviant “For Prostitution, or Female and Male Sex Workers.” Destinations were not associated with return rates in either study. In Study B, community size and addressees' affiliation were significantly associated with different rates of return in only smaller rural communities. Return rates were lower than those from the city except when the person was affiliated with the deviant “NORML or Legalized Prostitution” addressees.

The present article concerns taking into account risk when valuing specialized industrial properties with the use of income methods. The uniqueness of industrial properties means, that even in the most developed capital markets (real estate and business markets) there is a lack of reliable, comparable data that can be used in a valuation. Industrial properties are often a complex set of assets, which include land, specialized buildings, installations and other elements that function within the operational activities of a Going Concern - GC. Simplifying the matter, one may summarize, that indirect methods of income valuations of industrial properties are based on the valuation of a part of the business, from which the value of land is derived. The purpose of this article is to present possibilities of applying, in the valuation of specialized industrial properties, the concept of different rates of return for real estate and for the operational activities of a business. When valuing such properties, the lack of market information about transaction prices and rents brings about valuations based on dividing the determined value of the going concern among its assets, where different rates of return are used for different assets which comprise the going concern. The level of rates of return for the real estate component depends mainly on the difficulty level of converting the land into an alternative use. The expected rate of return in such situations is inversely proportional to the easiness with which the propertyis use may be changed. In the present paper, an example of an indirect income valuation of an industrial property is presented and different rates of return are applied to the real estate and the going concern.

Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for France (1800-2014)