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17 results for “wages”
Institutional arrangements regarding Minimum Wage Setting in 195 countries
<p>Most countries in the world have country-level policies concerning their minimum wage-fixing machinery. These policies vary widely, and therefore it becomes important to have adequate classifications of these policies. This paper reviews databases that classify country-level policies for determining minimum wages. Several databases - we found twelve - classify countries according to their minimum wage-fixing mechanisms and the coverage of these mechanisms. The mechanisms indicate whether the minimum wages are set by Law, by Collective Bargaining or any policy in between, the coverage indicates whether the minimum wages cover the entire dependent labour force or only one or more sections within the labour force. The twelve databases vary with respect to the years covered, the countries covered and the characteristics coded. We restricted our analysis to the years 2011 to 2015. The number of countries covered in these databases range from 29 to 189, with 195 countries in total. The merged database reveals that countries are not classified similarly across databases. Between 75% and 93% of the countries apply a statutory minimum wage-fixing mechanism across years and databases. Less than one in ten countries relies solely on minimum wage setting by collective bargaining. In the EU28 plus Norway this percentage is relatively high, but in countries outside Europe it is far below 10%. Two ILO conventions refer to minimum wage-fixing mechanisms. Across years and databases roughly three in five countries that apply a statutory minimum wage-fixing mechanism have signed the oldest Convention (C26), whereas roughly one in three has done so with the most recent Convention (C131). Obviously, many more countries could have signed the Conventions. Only a few countries have signed the Conventions but do not have a statutory minimum wage-fixing mechanism. Among others a few EU28 countries rely solely on collective bargaining for minimum wage setting, and consider that as a national wide fixing mechanism. If countries apply a statutory wage-fixing mechanism, does the minimum wage then cover the entire dependent labour force? Globally, more than half of the countries with a statutory minimum wage apply differentiated minimum wages. Most frequently reported breakdowns are by industry or occupation. Countries with multiple minimum wage rates mimic collective bargaining, particularly when they break down the rates by industry or occupation. The aim of this paper is to generate a Minimum Wage Policies Database (MWPDB) from the merged dataset. Using a set of rules for generating data from the source databases, we indicate for almost half of the 195 countries the presence or absence of a statutory minimum wage for all five years from 2011 to 2015. For 16 countries no valid data is available for any year. Particularly for Europe and South America, MWPDB has satisfactory number of observations, whereas the opposite holds for the small islands in Oceania. The MWPDB results show that approximately nine in ten countries do apply a minimum wage policy, and that this is slightly increasing between 2011 to 2015. </p>
State Comparison of Peer Recovery Worker Wages with Living Wages
<p>ZipRecruiter provides real time data on wage offers by state. I compared mean wage offers with the Glasmeier's Living Wage Calculator. Because ZipRecruiter data are real time wage offers, they can change from month to month, I archived the state wage offer data from November 30, 2023. These data are entered into an Excel spreadsheet for comparisons with living wages. Because the living wage data in the 2023 calculator are based on 2022 dollars, I inflated living wages to 2022 dollars based on the rise in prices from mid-year 2022 to mid-year 2023. </p>
Evaluation of the Impact of the Educational Revolution in Peru and the Gender Wage Gap, 2017-2021
<p><strong><span>Background:</span></strong><strong><span> </span></strong><span>Women's educational attainment and their generation of value through education has increased the prospects for achieving economic equality between men and women. However, women continue to earn lower wages than men, reflecting growing inequality in several countries. Therefore, the objective of the study is to estimate the impact of education on the gender wage gap in Peru over the period 2017-2021.</span></p> <p><strong><span>Methods:</span></strong><span> Quantitative, explanatory study aimed at identifying the impact of education on the gender wage gap in Peru during the period 2017-2021. The research design is non-experimental and uses a time series that analyses the influence of the latent variable of education on the gender wage gap. This is a continuous variable to estimate the Tobit model.</span></p> <p><strong><span>Results:</span></strong><strong><span> </span></strong><span>The results show that the gender gap in Peru exhibited a decreasing trend between men and women during the period 2017-2020, with an average reduction of 10% until 2020 due to the health crisis. The highest average salary was achieved by men in 2019, reaching S/2289.97 soles, while women reached an average salary of S/1368.85 soles. In the post-pandemic scenario for 2021, the gender gap increased by 3%, with men earning an average salary of S/1999.63 soles and women earning an average salary of S/1281.16 soles. The analysis from 2017-2021 shows that years of education had a positive impact on the gender wage gap in Peru based on the Tobit model estimation.</span></p> <p><strong><span>Conclusions:</span></strong><strong><span> </span></strong><span>During the analysis period of 2017-2021, years of education had a positive impact on the gender wage gap in Peru, with the greatest impact occurring during the health crisis. The probability of women's incomes improving with an increase in years of education was 2.35%, while for men, the highest impact was in 2018, with a probability of income improvement of 2.16% in terms of marginal effect.</span></p>
Wage data for benchmarking CROMP model
<p>Data used for benchmarking the CROMP model (doi: https://doi.org/10.5281/zenodo.7152807).</p> <p>This is a synthetic wage data created from Data scientist salary dataset in Kaggle (https://www.kaggle.com/datasets/nikhilbhathi/data-scientist-salary-us-glassdoor). The detailed methodology behind creation of this dataset is explained in the unpublished paper associated with the CROMP model cited above, titled "Constrained Regression with Ordered and Margin-sensitive Parameters: Application in improving interpretability for wage models with prior knowledge" written by this author.</p> <p>The "hc_data" sheet is used for benchmarking the CROMP model.</p>
Wages and Work Survey 2020 Bangladesh - dataset
<p>Management summary</p> <p>Decent Wage Bangladesh phase 1</p> <p><strong>The aims of the project</strong> <a href="https://wageindicator.org/Wageindicatorfoundation/projects/decent-wage-bangladesh-phase-1"><em>Decent Wage Bangladesh phase 1</em></a> aimed to gain insight in actual wages, the cost of living and the collective labour agreements in four low-paid sectors in three regions of Bangladesh, in order to strengthen the power of trade unions. The project received funding from <a href="https://www.fnv.nl/mondiaal-fnv">Mondiaal FNV</a> in the Netherlands and seeks to contribute to the to the knowledge and research pathway of Mondiaal’s theory of change related to social dialogue. Between August and November 2020 five studies have been undertaken. In a face-to-face survey on wages and work 1,894 workers have been interviewed. In a survey on the cost-of-living 19,252 prices have been observed. The content of 27 collective agreements have been analysed. Fifth, desk research regarding the four sectors was undertaken. The project was coordinated by <a href="https://wageindicator.org/">WageIndicator Foundation</a>, an NGO operating websites with information about work and wages in 140 countries, a wide network of correspondents and a track record in collecting and analysing data regarding wage patters, cost of living, minimum wages and collective agreements. For this project WageIndicator collaborated with its partner <a href="https://www.bids.org.bd/">Bangladesh Institute of Development Studies</a> (BIDS) in Dhaka, with a track record in conducting surveys in the country and with whom a long-lasting relationship exists. Relevant information was posted on the WageIndicator <a href="https://mywage.org.bd/">Bangladesh website</a> and visual graphics and photos on the <a href="https://wageindicator.org/Wageindicatorfoundation/projects/decent-wage-bangladesh-phase-1">project webpage</a>. The results of the Cost-of-Living survey can be seen <a href="https://wageindicator.org/salary/living-wage/bangladesh-living-wage-series-september-2020">here</a>.</p> <p><strong>Ready Made Garment (RMG), Leather and footwear, Construction and Tea gardens and estates</strong> are the key sectors in the report. In the <em>Wages and Work Survey </em>interviews have been held with 724 RMG workers in 65 factories, 337 leather and footwear workers in 34 factories, 432 construction workers in several construction sites and 401 workers in 5 tea gardens and 15 tea estates. The <em>Wages and Work Survey 2020</em> was conducted in the Chattagram, Dhaka and Sylhet Divisions.</p> <p><strong>Earnings</strong> have been measured in great detail. Monthly median wages for a standard working week are BDT 3,092 in tea gardens and estates, BDT 9,857 in Ready made garment, Bangladeshi Taka (BDT) 10,800 in leather and footwear and BDT 11,547 in construction. The females’ median wage is 77% lower than that of the males, reflecting the gender pay gap noticed around the world. The main reason is not that women and men are paid differently for the same work, but that men and women work in gender-segregated parts of the labour market. Women are dominating the low-paid work in the tea gardens and estates. Workers aged 40 and over are substantially lower paid than younger workers, and this can partly be ascribed to the presence of older women in the tea gardens and estates. Workers hired via an intermediary have higher median wages than workers with a permanent contract or without a contract. Seven in ten workers report that they receive an annual bonus. Almost three in ten workers report that they participate in a pension fund and this is remarkably high in the tea estates, thereby partly compensating the low wages in the sector. Participation in an unemployment fund, a disability fund or medical insurance is hardly observed, but entitlement to paid sick leave and access to medical facilites is frequently mentioned. Female workers participate more than males in all funds and facilities. Compared to workers in the other three sectors, workers in tea gardens and estates participate more in all funds apart from paid sick leave. Social security is almost absent in the construction sector. Does the employer provide non-monetary provisions such as food, housing, clothing, or transport? Food is reported by almost two in ten workers, housing is also reported by more than three in ten workers, clothing by hardly any worker and transport by just over one in ten workers. Food and housing are substantially more often reported in the tea gardens and estates than in the other sectors. A third of the workers reports that overtime hours are paid as normal hours plus a premium, a third reports that overtime hours are paid as normal hours and another third reports that these extra hours are not paid. The latter is particularly the case in construction, although construction workers work long contractual hours they hardly have “overtime hours”, making not paying overtime hours not a major problem.</p> <p><strong>Living Wage</strong> calculations aim to indicate a wage level that allows families to lead decent lives. It represents an estimate of the monthly expenses necessary to cover the cost of food, housing, transportation, health, education, water, phone and clothing. The prices of 61 food items, housing and transportation have been collected by means of a <em>Cost-of-Living Survey,</em> resulting in 19,252 prices. In Chattagram the living wage for a typical family is BDT 13,000 for a full-time working adult. In Dhaka the living wage for a typical family is BDT 14,400 for a full-time working adult. In both regions the wages of the lowest paid quarter of the semi-skilled workers are only sufficient for the living wage level of a single adult, the wages of the middle paid quarter are sufficient for a single adult and a standard 2+2 family, and the wages in the highest paid quarter are sufficient for a single adult, a standard 2+2 family, and a typical family. In Sylhet the living wage for a typical family is BDT 16,800 for a full-time working adult. In Sylhet the wages of the semi-skilled workers are not sufficient for the living wage level of a single adult, let alone for a standard 2+2 family or a typical family. However, the reader should take into account that these earnings are primarily based on the wages in the tea gardens and estates, where employers provide non-monetary provisions such as housing and food. Nevertheless, the wages in Sylhet are not sufficient for a living wage.</p> <p><strong>Employment contracts. </strong>Whereas almost all workers in construction have no contract, in the leather industry workers have predominantly a permanent contract, specifically in Chattagram. In RMG the workers in Chattagram mostly have a permanent contract, whereas in Dhaka this is only the case for four in ten workers. RMG workers in Dhaka are in majority hired through a labour intermediary. Workers in the tea gardens and estates in Chattagram in majority have no contract, whereas in Sylhet they have in majority a permanent contract. On average the workers have eleven years of work experience. Almost half of the employees say they have been promoted in their current workplace.</p> <p><strong>COVID-19</strong> Absenteeism from work was very high in the first months of the pandemic, when the government ordered a general lock down (closure) for all industries. Almost all workers in construction, RMG and leather reported that they were absent from work from late March to late May 2020. Female workers were far less absent than male workers, and this is primarily due to the fact that the tea gardens and estates with their highly female workforce did not close. From 77% in March-May absenteeism tremendously dropped till 5% in June-September. By September the number of absent days had dropped to almost zero in all sectors. Absenteeism was predominantly due to workplace closures, but in some cases due to the unavailability of transport. More than eight all absent workers faced a wage reduction. Wage reduction has been applied equally across the various groups of workers. The workers who faced reduced earnings reported borrowing from family or friends (66% of those who faced wage reduction), receiving food distribution of the government (23%), borrowing from a micro lenders (MFI) (20%), borrowing from other small lenders (14%), receiving rations from the employer (9%) or receiving cash assistance from the government or from non-governmental institutions (both 4%). Male workers have borrowed from family or friends more often than female workers, and so did workers aged 40-49 and couples with more than two children.</p> <p><strong>COVID-19 </strong><strong>Hygiene at the workplace</strong> After return to work workers have assessed hygiene at the workplace and the supply of hygiene facilities. Workers are most positive about the safe distance or space in dining seating areas (56% assesses this as a low risk), followed by the independent use of all work equipment, as opposed to shared (46%). They were least positive about a safe distance between work stations and number of washrooms/toilets, and more than two in ten workers assess the number of washrooms/toilets even as a high risk. Handwashing facilities are by a large majority of the workers assessed as adequate with a low risk. In contrast, gloves were certainly not adequately supplied, as more than seven in ten workers state that these are not adequately supplied. This may be due to the fact that use of gloves could affect workers’ productivity, depending on the occupations.</p>
Replication data for "Raided by the storm: How three decades of thunderstorms shaped U.S. incomes and wages"
<p>Replication data for "Raided by the storm: How three decades of thunderstorms shaped U.S. incomes and wages" (Coronese et al., JEEM 2024) - <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jeem.2024.103074" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.jeem.2024.103074</span></span></a></p> <p>This repository contains raw data supporting the replication of figures and tables presented in both the main paper and the Supplementary Information. Replication codes are available at: <a href="https://github.com/CoMoS-SA/thunderstorms" target="_new" rel="noopener">https://github.com/CoMoS-SA/thunderstorms</a></p>
Replication package for: Monopsony power and wages: Evidence from the introduction of serfdom in Denmark
<p>This is the replication package for Gary et al. (forthcoming). It contains all data sets and STATA code to replicate all results of the paper. For a full description please see the "readme" file contained in the zip file under 3. replication package,</p>
Effects of Wages on the Well-being of University Teachers in China
<p>This dataset contains survey data on the job well-being of university teachers in China, including variables such as salary satisfaction, perceived workload, organizational culture, and student interaction. Data were collected in 2023 from 283 teachers through an online questionnaire and are stored in SAV format.</p>
Wages in Spain (1964-2021)
<p>The files include raw data from the 'Encuestas de Salarios' of the Instituto Nacional de Estadística de España, from 1964 to 1980; from the series 'Salarios en la Industria y los Servicios' from 1981 to 2001 and from the 'Encuesta de Costes Laborales' from 2001 to 2021.</p>
Increasing Implementation of Evidence-based Interventions at Low-wage Worksites
ClinicalTrials.gov study NCT02005497. IPD Sharing: UNDECIDED. Countries: 1. Publications: 6.
Effect of Lost Wage Reimbursement to Kidney Donors on Living Donation Rates
ClinicalTrials.gov study NCT03350269. IPD Sharing: NO. Countries: 1. Publications: 23.
ORGANIZATION AND IMPROVEMENT OF PAYMENT OF WAGES IN INDUSTRIAL ENTERPRISES IN THE CONDITIONS OF ECONOMIC LIBERALIZATION
Open the record for dataset details and reuse information.
Effects of Wages on the Well-being of University Teachers in China
<p>This dataset contains survey data on the job well-being of university teachers in China, including variables such as salary satisfaction, perceived workload, organizational culture, and student interaction. Data were collected in 2023 from 283 teachers through an online questionnaire and are stored in SAV format.</p>
Testing the Effects of the CDSMP Among Lower-to-Middle Wage Workers
ClinicalTrials.gov study NCT04116463. IPD Sharing: YES. Countries: 1. Publications: 0.
A Natural Experiment Evaluating the Effect of a Minimum Wage Increase on Obesity and Diet-related Outcomes
ClinicalTrials.gov study NCT03962712. IPD Sharing: NO. Countries: 1. Publications: 0.
Impact of COVID-19 Pandemic on Out-of-Pocket Costs, Lost Wages, and Unemployment in Patients With Breast Cancer Undergoing Breast Surgery
ClinicalTrials.gov study NCT04169542. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Living Kidney Donor Lost Wages Trial
ClinicalTrials.gov study NCT03268850. IPD Sharing: NO. Countries: 1. Publications: 0.
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