The Pareto Curve and Its Utility for Open-Ended Income Distributions in Survey Research

Parker, Robert Nash; Fenwick, Rudy

doi:10.1093/sf/61.3.872

Cited by 126 publications

(96 citation statements)

References 14 publications

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“…Results reported here and below also did not differ substantively when using the full sample and replacing top coded values with calculated values based on formulas for the mean of open-ended income categories derived from Pareto curve estimation (Parker and Fenwick 1983) or imputing a top-code value suggested by Autor, Katz, and Krueger (1997, p.A1). …”

mentioning

confidence: 66%

Computers and the Wage Structure

Handel

2007

Research in Labor Economics

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mentioning

confidence: 66%

Computers and the Wage Structure

Handel

2007

Research in Labor Economics

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“…Respondents' earnings were initially measured in ten income categories, beginning with less than $10,000 and ending with an open-ended category of greater than $90,000. The nine closed categories were recoded to the midpoint, while the value of the open-ended upper category was estimated using the technique developed by Parker and Fenwick (1983). An additional work-related control variable was tenure, measured in years that the respondent has worked for his/her current employer.…”

Section: Measurement Methodsmentioning

confidence: 99%

Job stress and poor sleep quality: Data from an American sample of full-time workers

Knudsen

Ducharme

Roman

2007

Social Science & Medicine

202

139

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Given the associations between poor quality sleep and health, it is important to consider whether job stressors are related to sleep-related outcomes. Studies from Europe and Japan suggest that these stressors negatively impact sleep, but there are few studies of job stressors and sleep quality that draw upon large representative samples of workers in the USA. Using data collected via telephone interviews from a nationally representative random sample of 1,715 American full-time employees, this research considers three dependent variables of past-month poor sleep quality: number of days the respondent had difficulty initiating sleep, number of days of difficulty maintaining sleep, and number of days of non-restorative sleep. Negative binomial regression was used to estimate a count data model of the associations between the frequency of these three types of poor sleep quality and the job stressors of work overload, role conflict, autonomy, and repetitive tasks, while controlling for socio-demographic characteristics. The average American worker reported 5.3 days of difficulty falling asleep, 6.6 days of trouble staying asleep, and 5.0 days of trouble waking up for work in the past month. Across the three types of poor sleep quality, work overload was positively associated with the frequency of poor sleep quality. Role conflict was positively associated with difficulty initiating sleep and non-restorative sleep. Repetitive tasks were associated with more days of difficulty initiating sleep and maintaining sleep. Job autonomy was negatively associated with nonrestorative sleep. Given that sleep quality is associated with other health outcomes, future research should continue to explore the associations between job-related stressors, sleep quality, and workers' health status.

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“…To create a continuous income measure, individuals were assigned the midpoints of their bracketed income. The top category was assigned a value of USD 122,189, derived from a two-category, median-based Pareto curve method [Parker and Fenwick, 1983]. In some cases, participants were categorized as 'over USD 20,000' and 'under USD 20,000'.…”

Section: Family Incomementioning

confidence: 99%

Family Income and Tooth Decay in US Children: Does the Association Change with Age?

et al. 2012

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This study explored whether the association of family income with tooth decay changes with age among children in the United States. A second objective was to explore the role of access to dental health care services in explaining the interrelationships between family income, child age and tooth decay. Data from 7,491 2- to 15-year-old children who participated in the 1999–2004 National and Health and Nutrition Examination Survey were analyzed. The association of family income with the prevalence of tooth decay in primary, permanent and primary or permanent teeth was first estimated in logistic regression models with all children, and then, separately in four age groups that reflect the development of the dentition (2–5, 6–8, 9–11 and 12–15 years, respectively). Findings showed that the income gradient in tooth decay attenuated significantly in 9- to 11-year-olds only to re-emerge in 12- to 15-year-olds. The age profile of the income gradient in tooth decay was not accounted for by a diverse set of family and child characteristics. This is the first study providing some evidence for age variations in the income gradient in tooth decay among children in the United States.

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The Pareto Curve and Its Utility for Open-Ended Income Distributions in Survey Research

Cited by 126 publications

References 14 publications

Computers and the Wage Structure

Computers and the Wage Structure

Job stress and poor sleep quality: Data from an American sample of full-time workers

Family Income and Tooth Decay in US Children: Does the Association Change with Age?

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