In 1979, the median usual weekly earnings of a full-time employee amounted to *** current U.S. dollars. In 2023, this number had risen to ***** current U.S. dollars. The term current U.S. dollars describes the value of the currency in that particular year. Wages adjusted for inflation can be found here.

Wages in Manufacturing in Taiwan increased to 56697 TWD/Month in April from 55313 TWD/Month in March of 2025. This dataset provides - Taiwan Average Monthly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Wages in Manufacturing in Ireland increased to 1084.60 EUR/Week in the fourth quarter of 2024 from 1059.60 EUR/Week in the third quarter of 2024. This dataset provides - Ireland Average Weekly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This statistic shows the percentage increase in median hourly wages that can be expected with each additional year spent in further education in the United States. Differences can be seen for 1973, 1989 and 2007. In 2007, those who had completed 15 years of education could expect a median increase in their hourly wage of 14 percent as compared to 14 years of education.

This dataset provides valuable insights into the wage gap between Hispanic and White workers in the United States.

The wage gap is expressed as a percentage by which hourly wages of Hispanic workers are less than those of White workers.

It is an essential measure for understanding income disparities and examining trends over time.

Interesting Task Ideas:

1. Analyze the Hispanic-White wage gap trends over the years.
2. Explore the variations in median and average wages between Hispanic and White workers.
3. Investigate the gender-specific wage gap and identify any disparities between Hispanic and White men and women.
4. Conduct regression analysis to analyze the wage gap while controlling for relevant factors such as education, age, and geographic location.
5. Visualize the wage gap data to emphasize the magnitude of disparities and highlight any patterns over time.
6. Discover the potential effects of policy changes or economic transformations on the wage gap.

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Minimum Wages in Thailand increased to 374 THB/Day in 2025 from 363 THB/Day in 2024. This dataset provides - Thailand Minimum Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

When adjusted for inflation, the 2024 federal minimum wage in the United States is over 40 percent lower than the minimum wage in 1970. Although the real dollar minimum wage in 1970 was only 1.60 U.S. dollars, when expressed in nominal 2024 dollars this increases to 13.05 U.S. dollars. This is a significant difference from the federal minimum wage in 2024 of 7.25 U.S. dollars.

AME: Male: ID: Mfg: Basic Metal data was reported at 55,075.000 NTD in Sep 2018. This records an increase from the previous number of 55,074.000 NTD for Aug 2018. AME: Male: ID: Mfg: Basic Metal data is updated monthly, averaging 40,241.000 NTD from Jan 1973 (Median) to Sep 2018, with 549 observations. The data reached an all-time high of 139,406.000 NTD in Feb 2007 and a record low of 2,570.000 NTD in Feb 1973. AME: Male: ID: Mfg: Basic Metal data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G032: Average Monthly Earnings.

AME: Male: ID: MQ: Sand, Stone & Clay Quarrying data was reported at 35,453.000 NTD in May 2018. This records an increase from the previous number of 34,506.000 NTD for Apr 2018. AME: Male: ID: MQ: Sand, Stone & Clay Quarrying data is updated monthly, averaging 30,726.000 NTD from Jan 1973 (Median) to May 2018, with 545 observations. The data reached an all-time high of 69,266.000 NTD in Jan 1998 and a record low of 2,365.000 NTD in Feb 1973. AME: Male: ID: MQ: Sand, Stone & Clay Quarrying data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G033: Average Monthly Earnings.

Abstract copyright UK Data Service and data collection copyright owner.

The aim of these studies is to examine the positions of the low paid, the subemployed (men and women unemployed for over 4 weeks in the last 12 months), the disabled and immigrants in two local labour markets. There were two main sources of data:
1) All members not in full-time education and under 71 of a simple random sample of households in 2 urban areas (230).
2) Follow-up survey of all individuals in 1, who fell into any one of four special categories (231).
i) low paid (less than 55p for males over 18, less than 35p for females over 18)
ii) subemployed (unemployed for more than 4 weeks in last 12 months)
iii) disabled
iv) immigrants (not born in UK or Eire)

Main Topics:

Attitudinal/Behavioural Questions
This dataset contains data from source 1.
a) Terms and Conditions of Employment
Holidays, sick pay, pension, notice, contract, journey to work (time, weekly cost), normal starting time, outdoors or indoors (shelter, tea/coffee, toilet, washing facilities, place to eat, place for storage, first aid, phone call, heating), place for coats etc., adjustable lighting, details of fringe benefits received.
Amount of heaving, lifting, sitting down, whether work dangerous, noisy or tiring. Security, promotion prospects, trade union (membership), reasons if no trade union, opinion on whether union would be advisable (reasons), reasons for non-membership. Number of employees, immediate work group, autonomy, number in same job (as a proportion of the labour force), origin of workmates, earnings relative to others, low paid men/women. Influence on pay (union/employer or other), assessment of employer (reasons). Net/gross wages last time paid, hours worked/overtime during last pay week, period of payment, number of weeks worked in past year, average hourly earnings, variations in pay during last month (specific details). Promotion/demotion (reasons and description of job change).
Labour force status, internal movement, number of employers/ occupations/industries/jobs/skill level changes in last 5 and last 10 years. Number of job changes, number of periods of unemployment, length of time unemployed, size of works closure, redundancy pay received, job offers, help finding a job (type). Average gross/net earnings, average hours worked/period of payment. Additions to pay, tax rebate, tax paid direct, work expenses, number of weeks paid holiday, income fluctuations (reasons), deductions, time off work (reasons), sick pay, number of weeks sickness, strike pay, number of weeks on strike, pay for other reasons, number of weeks absent for other reasons. Length of time out of work/on short time/part time (reasons).
b) Previous occupation
Reason for leaving; type; location; hours per week; gross/net earnings; payment period; date left work.
c) First job
Social class; source of information; starting date; method of application; reasons for acceptance.
d) Second job
Social class; gross/net income.
e) Housewives
Attitude to work; reasons for not working; whether job taken if help given with family; suitable conditions-hours, location, pay, type of job.
Method of job search, interviews, refusals, whether job held in last 5 years. Previous job; type, employment status, location, hours per week, gross/net earnings, payment period, reason for leaving, date of leaving.
f) Retired
As for housewives, plus reason for retirement; when started drawing pension.
Background Variables
Age, sex, marital status, place of birth, ethnic origin, educational status, school-leaving age, number of years of schooling, qualifications, further education, job-specific training. Driving licence, general health condition, specific troubles/illnesses, health effect on work, employment status. Number of households at address, number in household with: four or more weeks unemployed in last 12 months; low pay; disability; number of immigrants. Number in household, number aged 71 and over, number aged 15 and under, number aged 15 and over in education, number currently with paid job. Household type, number of rooms, amenities, structural defects, tenure, business purposes, net household income, rent rebate, number of weeks rent paid, rates, rate rebate (owner occupiers only), whether house paid for, presence of lodgers/boarders and sub-tenants, persons per room, cost of repairs over previous year, housing cost weekly. Family allowances received, retirement pension, widows pension.
Benefits received - sickness, unemployment, supplementary, industrial injury, industrial disability, war disability, maternity, death. Income received from property, assets and savings (value), number of weeks worked in past year, average hourly earnings, length of residence in study area/in North East/in GLC, local papers read.
Relatives in area (father, mother, siblings, children,...

AME: Female: ID: Manufacturing data was reported at 39,179.000 NTD in Sep 2018. This records a decrease from the previous number of 39,413.000 NTD for Aug 2018. AME: Female: ID: Manufacturing data is updated monthly, averaging 23,064.000 NTD from Jan 1973 (Median) to Sep 2018, with 549 observations. The data reached an all-time high of 72,264.000 NTD in Jan 2017 and a record low of 1,547.000 NTD in Feb 1973. AME: Female: ID: Manufacturing data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G032: Average Monthly Earnings.

From 1950 to 1973, Italy's social and economic structure underwent its largest transformation in modern history. Following the Second World War, the Italian government's restrictive policies that prioritized agriculture and limited both migration and urbanization were scrapped, and mass industrialization took place. Not only did this result in millions flocking from the countryside to cities in search of work, but this coincided with the expansion of welfare, healthcare, and education systems, which provided further employment opportunities in service industries. Increased industrialization and consumerism also resulted in the growth of the retail sector (included in services), and all of these factors contributed to the drastic drop in agricultural employment. Despite agriculture's share of total employment dropping by 80 percent over these 23 years, mechanization and investment meant that agricultural output in the 1950s and 1960s generally grew as the industry became more efficient. Over these decades, Italy's status as a poor and underdeveloped, rural nation changed, as it emerged as one of the world's largest and fastest-growing economies, even becoming the fourth-largest economy in the world for a brief period in the 1980s.

AME: Male: ID: Mfg: Fabricated Metal Products data was reported at 38,217.000 NTD in May 2018. This records an increase from the previous number of 37,370.000 NTD for Apr 2018. AME: Male: ID: Mfg: Fabricated Metal Products data is updated monthly, averaging 33,907.000 NTD from Jan 1973 (Median) to May 2018, with 545 observations. The data reached an all-time high of 73,055.000 NTD in Jan 1998 and a record low of 2,097.000 NTD in Feb 1973. AME: Male: ID: Mfg: Fabricated Metal Products data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G033: Average Monthly Earnings.

AME: Female: ID: Electricity & Gas Supply data was reported at 64,641.000 NTD in Sep 2018. This records a decrease from the previous number of 75,975.000 NTD for Aug 2018. AME: Female: ID: Electricity & Gas Supply data is updated monthly, averaging 51,640.000 NTD from Jan 1973 (Median) to Sep 2018, with 549 observations. The data reached an all-time high of 245,442.000 NTD in Jan 1998 and a record low of 3,973.000 NTD in Apr 1973. AME: Female: ID: Electricity & Gas Supply data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G032: Average Monthly Earnings.

AME: ID: Mfg: Furniture data was reported at 29,671.000 NTD in May 2018. This records a decrease from the previous number of 30,793.000 NTD for Apr 2018. AME: ID: Mfg: Furniture data is updated monthly, averaging 25,438.000 NTD from Jan 1973 (Median) to May 2018, with 545 observations. The data reached an all-time high of 57,889.000 NTD in Jan 2016 and a record low of 1,664.000 NTD in Feb 1973. AME: ID: Mfg: Furniture data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G033: Average Monthly Earnings.

Taiwan Average Earnings Index: Construction data was reported at 162.270 2016=100 in Jan 2019. This records an increase from the previous number of 97.280 2016=100 for Dec 2018. Taiwan Average Earnings Index: Construction data is updated monthly, averaging 81.220 2016=100 from Jan 1973 (Median) to Jan 2019, with 553 observations. The data reached an all-time high of 162.270 2016=100 in Jan 2019 and a record low of 5.030 2016=100 in Feb 1973. Taiwan Average Earnings Index: Construction data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G034: Average Earnings Index: 2016=100.

AME: Male: ID: Mfg: Electrical Equipment data was reported at 40,642.000 NTD in May 2018. This records a decrease from the previous number of 40,876.000 NTD for Apr 2018. AME: Male: ID: Mfg: Electrical Equipment data is updated monthly, averaging 34,292.000 NTD from Jan 1973 (Median) to May 2018, with 545 observations. The data reached an all-time high of 98,940.000 NTD in Jan 2017 and a record low of 1,687.000 NTD in Feb 1973. AME: Male: ID: Mfg: Electrical Equipment data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G033: Average Monthly Earnings.

AME: Female: ID: Mfg: Leather, Fur & Allied Products data was reported at 37,716.000 NTD in May 2018. This records a decrease from the previous number of 38,659.000 NTD for Apr 2018. AME: Female: ID: Mfg: Leather, Fur & Allied Products data is updated monthly, averaging 21,167.000 NTD from Jan 1973 (Median) to May 2018, with 545 observations. The data reached an all-time high of 87,293.000 NTD in Jan 2017 and a record low of 1,251.000 NTD in Feb 1973. AME: Female: ID: Mfg: Leather, Fur & Allied Products data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G033: Average Monthly Earnings.

Taiwan Average Earnings Index: Industry data was reported at 188.860 2016=100 in Jan 2019. This records an increase from the previous number of 101.030 2016=100 for Dec 2018. Taiwan Average Earnings Index: Industry data is updated monthly, averaging 66.510 2016=100 from Jan 1973 (Median) to Jan 2019, with 553 observations. The data reached an all-time high of 188.860 2016=100 in Jan 2019 and a record low of 3.780 2016=100 in Feb 1973. Taiwan Average Earnings Index: Industry data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G034: Average Earnings Index: 2016=100.