Wage Estimates Research Articles

Who’s the boss? Exploring public and private wage growth leadership in state-level education and health industries in Australia

ABSTRACT Public sector wage research has evolved beyond the estimation of public sector wage premiums to investigating the nature of interrelationships between public and private wage patterns. This article seeks to extend this wage leadership research to investigate intra-industry linkages and spillovers between public and private sector wage growth in Education and Health industries, using Australia as a case study. The research employs vector error correction models to encompass tests for full wage adaptability, long-run and short-run wage leadership. Results show that the public sector is the long-run leader in all models, regardless of industry and alternative jurisdictions’ public sector wage setting policy. Our findings have important policy implications for public sector wage setting practices, demonstrating that wage policies which may be based on political motivations can have widespread effects on the private sector.

The Role Of Women's Labor Force Participation In Decreasing Aceh Province Poverty Rate

The poverty rate can decrease if there is a dual role of working women, the development of the times has proven to have implications for shifting the role of women in reducing poverty. Acehnese women, who used to be a social construction built on the basis of people's understanding of cultural values ​​and interpretations in the Islamic religion, have shifted to a new era where Acehnese women can take part in the household production process. This paper wants to analyze how big the role of women is working towards poverty reduction in Aceh Province. The results of the study show that the variable number of industries directly (X4) has a negative and not significant effect on wage estimates for Aceh Province

Whether the Salary of Data Scientists Can Be Predicted: New Evidence

This study uses exploratory data analysis and an exploratory prediction model to examine data scientist salaries. The study examines salary determinants, salary trends, and a forecast model for data scientist salaries. The collection includes wage estimates, job descriptions, company evaluations, and industry data. Descriptive statistics and visualizations reveal variable distributions and trends. Linear regression is used to estimate salaries using geography, industry, firm rating, and job description. However, the original model has a large prediction error, requiring refining. The findings present significant implications for job seekers, companies, and policymakers, necessitating a thorough understanding and response from all these stakeholders. Addressing issues related to data availability and biases becomes imperative, as these could potentially distort the insights and the resulting decisions. Therefore, it's crucial to emphasize and encourage future research in this area to ensure a more equitable and comprehensive approach to employment and policy development.

Spatial differencing for sample selection models with ‘site-specific’ unobserved local effects

Summary This paper proposes an estimator which combines spatial differencing with a two-step sample selection estimator. We derive identification, estimation, and inference results from ‘site-specific’ unobserved effects. These effects operate at a spatial scale that cannot be captured by administrative borders. Therefore, we use spatial differencing. We show that under justifiable assumptions, the estimator is consistent and asymptotically normal. A Monte Carlo experiment illustrates the small sample properties of our estimator. We apply our procedure to the estimation of a female wage offer equation in the United States and the results show the relevance of spatial differencing to account for ‘site-specific’ unobserved effects.

A Cost Analysis of Rethink the Strip: De-implementing a Low-value Practice in Primary Care.

Routine self-monitoring of blood glucose is a low-value practice that provides limited benefit for patients with non-insulin-treated type 2 diabetes mellitus. We estimated the costs of Rethink the Strip (RTS), a multistrategy approach to the de-implementation of self-monitoring of blood glucose in primary care. RTS was conducted among 20 primary care clinics in North Carolina. We estimated the non-site-based and site-based costs of the 5 RTS strategies (practice facilitation, audit and feedback, provider champions, educational meetings, and educational materials) from the analytic perspective of an integrated health care system for 12 and 27-month time horizons. Material costs were tracked through project records, and personnel costs were assessed using activity-based costing. We used nationally based wage estimates. Total RTS costs equaled $68,941 for 12 months. Specifically, non-site-based costs comprised $16,560. Most non-site-based costs ($11,822) were from the foundational programming and coding updates to the electronic health record data to develop the audit and feedback reports. The non-site-based costs of educational meetings, practice facilitation, and educational materials were substantially lower, ranging between ~$400 and $1000. Total 12-month site-based costs equaled $2569 for a single clinic (or $52,381 for 20 clinics). Educational meetings were the most expensive strategy, averaging $1401 per clinic. The site-based costs for the 4 other implementation strategies were markedly lower, ranging between $51 for educational materials and $555 for practice facilitation per clinic. This study provides detailed cost information for implementation strategies used to support evidence-based programs in primary care clinics.

Need for living wages in India: Case studies of agricultural workers in rural Madhya Pradesh

AbstractThe present study discusses the current wage situation in India and the need for living wages as workers and employees grapple with the cost of living crisis. A case study of two districts of Madhya Pradesh (MP) state is presented to demonstrate how the living wage benchmarks based on the Anker Methodology compare with existing minimum wage fixations and other development indicators. The living wage benchmarking is based on field surveys conducted in Ratlam and Chhindwara districts in October–December 2021, and a rigorous analysis of nationally representative consumption and expenditure surveys conducted by the National Sample Survey Organisation and the Centre for Monitoring Indian Economy. Our living wage estimates are 1.8 times the minimum wages for agricultural labourers and 43% more than those earned by non-agricultural unskilled labourers. Moreover, the actual wages reported are less than half of the estimated living wages, indicating that the current incomes and wages for workers and farmers of rural MP are far from adequate to lead a decent life.

Gendered Divergence in the Impact of Parenthood on Wages: The Role of Family Size, Human Capital and Working Time

While gender pay disparity is a frequently researched area, few have focused on how parenthood and family size impact the wages of mothers and fathers together. The purpose of this study is therefore to take a broader view of this pivotal topic, one which has continued relevance as governments and organisations seek to advance gender equality. The findings show clear gendered divergence in the impact of parenthood on wages, with ‘motherhood wage penalties’ and ‘fatherhood wage premiums’ in both annual and hourly wage. The widest gap in earnings between women and men occurs at three or more children even when human capital and labour market selectivity factors are controlled for. For women, the largest penalty occurs at one and three or more children while for men, having two children represents the peak point in terms of wage gains to parenthood. Accounting for working time through hourly wage estimations narrows but does not eliminate parental wage gaps, pointing to other factors such as occupational segregation.

What Can Unions Do? An Impact Estimate for an Increase in the US Private-Sector Unionization Rate on Workers’ Earnings

Unions are known to increase earnings and wage equality. Therefore, indications for recent union revitalization provoke the question of what unions would do today were they to restore their union density and hence power to the level of the early 1980s (about 20%). This article presents wage estimates for 1983 to 2020, assuming a 20% union density from 1983 onward, revealing higher earnings and lower wage inequality. However, since union membership today typifies low-wage workers with weaker bargaining power than formerly, the benefits from restoring union density and power will likely be lower today than in the past.

Dilemmas relating to mode estimation of wages and salaries

The mode of wages and salaries is an important indicator describing their distribution; however, due to the strong asymmetry of the distribution of this feature in Poland, mode estimation is not a standard procedure in the analysis of the structure of wages and salaries. The aim of the article is to discuss selected methods of estimating the mode and to compare the mode estimation results obtained by means of various methods. The research is based on data on individual gross wages and salaries registered in October 2018 in Poland. The data came from a survey of the structure of wages and salaries conducted by Statistics Poland. In the case of the standard method based on the interpolation formula and histogram, the mode estimate is sensitive to the assumed span of intervals in the frequency table and the beginning of the first interval. Reducing the span of the intervals causes the mode to reach the value of the minimum wage. The application of advanced methods, including those using a kernel estimator, leads to significantly different estimates of the mode depending on the method used (the dispersion reaches the value of approximately PLN 800). Additionally, the analysis of the obtained results gives grounds to considering a thesis that wage and salary distribution is a mixture of the following distributions: discrete (for the minimum wage) and continuous (for wages and salaries above the minimum wage), and is characterised by cyclicality (in Poland, more contracts offer remunerations which are a multiple of PLN 50 or PLN 100 than remunerations for other amounts).

The evolution of wages in early modern Normandy (1600–1850)

AbstractThis article presents new estimates of wages for Normandy between 1600 and 1850. We use a vast array of primary and secondary sources to assemble two new databases on wages and commodity prices to establish a new regional consumer price index (CPI) and twelve regional wage series. We find that unskilled labourers earned similar wages across the agricultural, maritime, and textile sectors. Historical evidence suggests that Norman employers grappled with a tight labour market, which placed more pressure on wage increases. We posit that this situation is best explained by the combination of the early fertility transition, resulting in slow demographic growth and the rapid development of the textile industry accelerated by the arrival of cotton. Finally, we also provide tentative evidence suggesting that labourers with stable employment could have earned a little less than their English counterparts during this period.

Political Commitment, Policy Consequences, and Moral Beliefs: Survey Evidence on the Minimum Wage

Abstract Does information regarding the economic consequences of a minimum wage affect the level of support for or opposition to minimum wage policy? We conduct an online survey of 2242 US respondents to study this question. We randomly assign differing, empirically plausible estimates of minimum wage impacts on three outcomes—employment, the distribution of minimum wage gains to households, and comparative impacts of a government transfer program versus a minimum wage— in order to explore the relationship between minimum wage consequences and political commitment. Our results show that while political commitment is indeed influenced by information on the policy’s consequences, such information rarely leads to fundamental changes in political commitment. This is consistent with findings in the larger literature on the effects of information provision on political commitment. We offer a novel explanation for such findings by surveying respondents on their moral beliefs regarding the minimum wage, focusing on the extent to which these beliefs are consequentialist or non-consequentialist in nature. We find that non-consequentialist moral beliefs are prevalent among survey respondents and that the more intense are these beliefs, the less likely people are to be swayed by the policy’s consequences.

The Egyptian Labour Market, Determinants of Employment and Wage Estimation

This study empirically evaluates the factors influencing employment in Egypt by using the recently published cross-sectional Egyptian Labour Force Survey, 2019. The logistic regression analysis revealed that being older, male, married, and living in a rural region increased the probability of an individual being employed. Contrary to the assumption of the human capital theory, the attainment of all education levels appeared to reduce the likelihood of attaining employment in the Egyptian labour market. Moreover, the multiple linear regression reveals significant factors influencing wage estimation in the Egyptian labour market. Some of those factors were related to individual characteristics, while others related to employer characteristics, emphasising the critical role of both sides of the labour market in estimating wages. However, other socioeconomic factors should be determined in order to increase the overall model interpretation.

Introducing Modeled Wage Estimates by grouped work levels

The Modeled Wage Estimates (MWE) provide annual estimates of average hourly wages for occupations by job characteristics and within a given geographical location. These estimates are produced by borrowing from the strength and breadth of the Occupational Employment and Wage Statistics (OEWS) and National Compensation Survey (NCS) programs to provide more details on occupational wages than either program provides individually. Job characteristics refer to the attributes of workers within an occupation and include worker bargaining status (union and nonunion), work status (part-time and full-time), basis of pay (incentive-based or time-based), and work level (levels 1–15). In this article, we present experimental estimates calculated by grouping work-level data. Grouped level estimates may help researchers, human resources professionals, jobseekers, and other data users to get a better understanding of how pay varies for entry, intermediate, and experienced work levels.

Working hours and gender wage differentials: Evidence from the American Working Conditions Survey

Using the 2015 American Working Conditions Survey (AWCS), the study investigates gender wage differentials conditional on weekly working hours. Wage estimations controlling for the labour supply at the extensive and intensive margins confirm the presence of a female wage gap. A triangular joint estimation framework that identifies the wage determinants and the gender wage gap controls for the labour supply both in reservation hours and in actual working hours. The joint estimation of hourly wages, desired and actual weekly working hours, with the wages-hours relationship allowed to take non-linear forms, reduces the gender wage differentials and renders the gap insignificant for jobs that do not permit remote work.

Statistical data integration using multilevel models to predict employee compensation

AbstractThis article considers the case where two surveys collect data on a common variable, with one survey being much smaller than the other. The smaller survey collects data on an additional variable of interest, related to the common variable collected in the two surveys, and out‐of‐scope with respect to the larger survey. Estimation of the two related variables is of interest at domains defined at a granular level. We propose a multilevel model for integrating data from the two surveys, by reconciling survey estimates available for the common variable, accounting for the relationship between the two variables, and expanding estimation for the other variable, for all the domains of interest. The model is specified as a hierarchical Bayes model for domain‐level survey data, and posterior distributions are constructed for the two variables of interest. A synthetic estimation approach is considered as an alternative to the hierarchical modelling approach. The methodology is applied to wage and benefits estimation using data from the National Compensation Survey and the Occupational Employment Statistics Survey, available from the Bureau of Labor Statistics, Department of Labor, United States.

A Living Wage for The Bahamas: Estimates, Potentials, and Problems

This report describes how living wage estimates were calculated for New Providence and Grand Bahama. This report uses primary and secondary sources and is inspired by the Anker methodology. We calculated that $2625 and $3550 were needed each month as the gross living wage for a full-time worker who must sustain a family of four in New Providence and Grand Bahama, respectively. We estimated the net living wage to be $2500 per month for New Providence and $3400 for Grand Bahama. Our estimates are almost 200% higher than the minimum wage and nearly 130% higher than the poverty line for New Providence; for Grand Bahama, they are almost 300% higher than the minimum wage and 160% higher than the poverty line. The study should inform national discussions on public policy matters related to reducing the country’s cost of living, improving its income equity, and pursuing economic justice for all.

Wages in Russia in 2015-2021

The article presents analysis of the wage dynamics in the Russian Federation in 2015-2020 and the first half of 2021. In 2018 Russia changed the methodology for calculating separate items in the Balance sheet of the population monetary income and expenses. This concerned, among other things, the item of payment for work, from which hidden (officially unaccounted for) wages and other cash receipts were excluded, and payroll fund of employees in organizations was singled out. Besides, Rosstat developed methods for estimating average wages of all employees (working in organizations, for individual entrepreneurs, farmers and individuals) and published the results for 2015-2021. The article also presents author's estimation of the average wages of employees working for individual entrepreneurs, farmers, and individuals in 2018-2020. In 2020 average wages of these categories of workers made 72.9% of the average wages of all employees and 60.2% of the employed in organizations. Due to lack of official data on the wage differentiation of all employees, the article provides variants of its estimation for 2017-2019 using primary data from SSPI. Low wages of those working for individual entrepreneurs, farmers and individuals serve as a factor of higher earnings inequality of all categories of employees. In 2019 R/P 10% ratio made by different calculation algorithms 18.5 and 15.7 times against 13 times for those employed in organizations. There are provided results on the impact of the minimum wage on the level and differentiation of wages.

Higher education widening access initiatives—An estimation of wage returns from Scottish Articulation

AbstractWe estimate the wage returns of undergraduates who attained their degree via Scotland's Further Education College Articulation policy. We contribute to existing literature by adding to the research on varying returns based on paths to acquiring a degree, while also being the first paper to examine the returns associated with Scottish Articulation. While Articulation students receive a wage premium relative to college students, we find lower returns for Articulation students relative to those from older and higher ranking university institutions in Scotland. This result questions whether improving educational equality, translates to improved income equality between low versus higher income backgrounds.

MP27-08 CLINICAL CORRELATES AND ECONOMIC CONSEQUENCES OF EMPLOYER BENEFIT EXCLUSION FOR PENILE PROSTHESIS IMPLANTATION FOR ERECTILE DYSFUNCTION

You have accessJournal of UrologySexual Function/Dysfunction: Evaluation I (MP27)1 Sep 2021MP27-08 CLINICAL CORRELATES AND ECONOMIC CONSEQUENCES OF EMPLOYER BENEFIT EXCLUSION FOR PENILE PROSTHESIS IMPLANTATION FOR ERECTILE DYSFUNCTION Sirikan Rojanasarot, Samir Bhattacharyya, and Arthur L. Burnett Sirikan RojanasarotSirikan Rojanasarot More articles by this author , Samir BhattacharyyaSamir Bhattacharyya More articles by this author , and Arthur L. BurnettArthur L. Burnett More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002024.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Employed men with erectile dysfunction (ED) covered by employer-sponsored health insurance (ESHI) often have limited access to penile prosthesis implantation (PPI). This study quantified the clinical correlates and economic consequences of the benefit exclusion by examining the prevalence and comorbid correlations of ED among men with ESHI; the population size of ED men affected by the issue; and the economic impact of work productivity loss due to benefit exclusion for PPI. METHODS: A cost-consequence analysis was developed to quantify the impact of employer exclusion for PPI. The analysis was selected as it displays results in natural units of effect, including the number of men affected and the days and costs of work productivity lost, enabling clinicians and decision makers to select the most relevant components to them. IBM MarketScan Commercial data from 2010-2018 were analyzed to determine the prevalence and comorbid correlations of ED. The American Community Survey and published literature were used to estimate the number of ED men with ESHI affected by benefit exclusion for PPI. The economic impact of work productivity loss due to ED was calculated using National Occupational Employment and Wage Estimates and converted into 2019 US dollars. RESULTS: The prevalence rates of ED among men with ESHI increased from 1.6% in men aged 18-24 years to 24.6% in men aged 55-64 years (Figure). Most ED men were ≥45 years of age (78.5%), had a Charlson Comorbidity Index of 0 (76.1%). Common comorbidities were hyperlipidemia (48.0%) and hypertension (46.4%). An estimated 1.29 million men with ESHI in 2019 were affected by benefit exclusion for PPI. Men with ED had an additional 283 hours/year of work impairment compared to men without ED, resulting in an annual indirect mean cost of $7,270. An average US company with 5,000 employees that excluded PPI from their plan could lose $1.28 million of work productivity due to additional work impairment from ED. CONCLUSIONS: The extent of men with ED affected by benefit exclusion for PPI as well as economic impact of work productivity loss due to this exclusion issue are substantial. Removing benefit exclusion for PPI may improve patient access to effective ED treatment and reduce the burden of ED on both patients and employers . Source of Funding: Boston Scientific © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e474-e474 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Sirikan Rojanasarot More articles by this author Samir Bhattacharyya More articles by this author Arthur L. Burnett More articles by this author Expand All Advertisement Loading ...

The “cost” of noise at work: an occupational injustice among low wage workers and communities

BACKGROUND AND AIM: Noise exposure is ubiquitous in the US and has been associated with various health outcomes. Chronic occupational noise exposure of an 8-hour time weighted average (TWA) ≥85 A-weighted decibels (dBA) leads to permanent noise-induced hearing loss, which has major social impacts and may cost $100 billion annually in lost wages alone. It is estimated that tens of millions of workers are exposed to hazardous levels of occupational noise. Understanding potential occupational and environmental injustices in the distribution of occupational noise across communities and worker income groups is important to examine whether those exposed to hazardous levels of occupational noise are also disproportionately burdened populations. METHODS: Publicly available noise measurements from the US noise job exposure matrix (JEM) and wage estimates from the Bureau of Labor Statistics (BLS) Occupational Employment Statistics (OES) were utilized in mixed-effects logistic regression to analyze (1) national-level job-title noise exposure and the odds of earning $39,810 (median national salary), and (2) metropolitan/nonmetropolitan- (M/NM) level population-weighted occupational noise estimates and the odds of a M/NM area earning $36,020 (median M/NM-level salary). RESULTS:A one-dBA increase in the average noise exposure experienced at work is significantly associated with 1.19 (95% CI: 1.03, 1.38) times higher odds of earning $39,810, and 1.21 (95% CI: 1.03, 1.42) higher odds when controlling for total employment count. A one-dBA increase in a M/NM area’s population-weighted occupational noise estimate is significantly associated with 2.46 (95% CI: 1.50, 4.03) higher odds of a M/NM area earning $36,020, and 1.75 (95% CI: 1.06, 2.89) times higher odds when controlling for rural/urban area. CONCLUSIONS:Higher occupational noise exposure is unequally distributed among lower wage-earning jobs and communities. KEYWORDS: Noise, occupational exposures, socio-economic factors, environmental disparities