Abstract

A. Objectives

To generate statistics for wage and salary administration and for wage determination in collective bargaining negotiations.

B. Uses of Data

Inputs to wage, income, productivity and price policies, wage fixing and collective bargaining; occupational wage rates can be used to measure wage differentials, wage inequality in typical low wage and high wage occupations and for international comparability; industry data on basic pay and allowance can be used to measure wage differentials across industries, for investment decisions and as reference in periodic adjustments of minimum wages.

C. Main Topics Covered

Occupational wage rates Median basic pay and median allowances of time-rate workers on full-time basis

Geographic coverage

National coverage, 17 administrative egions

Analysis unit

Establishment

Universe

The survey covered non-agricultural establishments employing 20 or more workers except national postal activities, central banking, public administration and defense and compulsory social security, public education services, public medical, dental and other health services, activities of membership organizations, extra territorial organizations and bodies.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Statistical unit: The statistical unit is the establishment. Each unit is classified to an industry that reflects its main economic activity---the activity that contributes the biggest or major portion of the gross income or revenues of the establishment.

Survey universe/Sampling frame: The 2004 BLES Survey Sampling Frame (SSF2004) is a list frame of establishments that is a partial update of the 2003 BLES Sampling Frame based on the status of establishments reported in the 2003 BLES Integrated Survey (BITS) conducted nationwide.

Reports on closures and retrenchments of establishments submitted to the Regional Offices of the Department of Labor and Employment in December 2003 and January 2004 were also considered in updating the 2004 frame.

Sampling design: The OWS is a complete enumeration of non-agricultural establishments employing 50 persons or more. The design does not consider the region as a domain to allow for more industry coverage.

Sample size: For 2004 OWS, number of establishments covered was 8,779 of which, 6,827 were eligible units.

Note: Refer to Field Operations Manual Chapter 1 Section 1.5.

Sampling deviation

While the OWS is a complete enumeration survey, not all of the fielded questionnaires are accomplished. Due to the inadequacy of the frame used, there are reports of permanent closures, nonlocation, duplicate listing and shifts in industry and employment outside the survey coverage. Establishments that fall in these categories are not eligible elements of the frame and their count is not considered in the estimation. In addition to non-response of establishments because of refusals, strikes or temporary closures, there are establishments whose questionnaires contain inconsistent item responses that are not included in the processing as these have not replied to the verification queries by the time output table generation commences. Such establishments are also considered as non-respondents.

Respondents are post-stratified as to geographic, industry and employment size classifications. Non-respondents are retained in their classifications. Sample values of basic pay and allowances for the monitored occupations whose basis of payment is an hour or a day are converted into a standard monthly equivalent, assuming 313 working days and 8 hours per day. Daily rate x 26.08333; Hourly rate x 208.66667.

Mode of data collection

Other [oth] mixed method: self-accomplished, mailed, face-to-face

Research instrument

The questionnaire contains the following sections:

Cover Page (Page 1) This contains the address box, contact particulars for assistance, spaces for changes in the name and location of sample establishment and head office information in case the questionnaire is endorsed to it and status codes of the establishment to be accomplished by BLES and its field personnel.

Survey Information (Page 2) This contains the survey objective and uses of the data, scope of the survey, confidentiality clause, collection authority, authorized field personnel, coverage, periodicity and reference period, due date for accomplishment and expected date when the results of the 2006 OWS would be available.

Part A: General Information (Page 3) This portion inquires on main economic activity, major products/goods or services and total employment.

Part B: Employment and Wage Rates of Time Rate Workers on Full Time Basis (Pages 4-5) This section requires data on the number of time-rate workers on full-time basis by time unit and by basic pay and allowance intervals.

Part C: Employment and Wage Rates of Time Rate Workers on Full Time Basis in Selected Occupations (Pages 6-9) This part inquires on the basic pay and allowance per time unit and corresponding number of workers in the two benchmark occupations and in the pre-determined occupations listed in the occupational sheet to be provided to the establishment where applicable.

Part D: Certification (Page 10) This portion is provided for the respondent's name/signature, position, telephone no., fax no. and e-mail address and time spent in answering the questionnaire.

Appropriate spaces are also provided to elicit comments on data provided for the 2006 OWS; results of the 2004 OWS; and presentation/packaging, particularly on the definition of terms, layout, font and color

Part E: Survey Personnel (Page 10) This portion is for the particulars of the enumerators and area/regional supervisors and reviewers at the BLES and DOLE Regional Offices involved in the data collection and review of questionnaire entries.

Part F: Industries With Selected Occupations (Page 11) The list of industries for occupational wage monitoring has been provided to guide the enumerators in determining the correct occupational sheet that should be furnished to the respondent.

Results of the 2004 OWS (Page 12) The results of the 2004 OWS are found on page 12 of the questionnaire. These results can serve as a guide to the survey personnel in editing/review of the entries in the questionnaire.

Note: Refer to questionnaire and List of Monitored Occupations.

Cleaning operations

Data are manually and electronically processed. Upon collection of accomplished questionnaires, enumerators perform field editing before leaving the establishments to ensure completeness, consistency and reasonableness of entries in accordance with the field operations manual. The forms are again checked for data consistency and completeness by their field supervisors.

The BLES personnel undertake the final review, coding of information on classifications used, data entry and validation and scrutiny of aggregated results for coherence. Questionnaires with incomplete or inconsistent entries are returned to the establishments for verification, personally or through mail.

Note: Refer to Field Operations Manual Chapter 1 Section 1.10.

Response rate

The response rate in terms of eligible units was 82.1%.

Sampling error estimates

Estimates of the sampling errors are not computed.

Data appraisal

The survey results are checked for consistency with the results of previous OWS data and the minimum wage rates corresponding to the reference period of the survey.

Average wage rates of unskilled workers by region is compared for proximity with the corresponding minimum wage rates during the survey reference period.

Dependent employment relationships,gross hourly earnings: Germany, Entry Month, Gender, Earning Size Classes

Quarterly series on labour productivity growth and related variables have been published for the first time on December 20th, 2000. These statistical series go back to the first quarter of 1981. The data are published two months after the reference quarter. The quarterly productivity measures are meant to assist in the analysis of the short-run relationship between the fluctuations of output, employment, compensation and hours worked. This measure is fully comparable with the United States quarterly measure. The quarterly estimations of this table are limited to the overall business sector. This aggregate excludes government and non-profit institutions expenditures on primary factors as well as the output of households (including the rental value of owner-occupied dwellings). Corresponding exclusions are also made to labour compensation and hours worked to make output and labour input data consistent with one another. The real output of the business sector is constructed using a Fisher-chained index, after excluding from GDP at market prices the real gross value added of the government sector, of the non-profit institutions and of households (including the rental value of owner-occupied dwellings). This approach is similar to that used for the quarterly productivity of the business sector in the United States. The estimate of the total number of jobs covers four main categories: employee jobs, work owner of an unincorporated business, own account self-employment, and unpaid family jobs. This last category is found mainly in sectors where family firms are important (agriculture and retail trade, in particular). Jobs data are consistent with the System of National Accounts. This is the quarterly average of hours worked for jobs in all categories. The number of hours worked in all jobs is the quarterly average for all jobs times the annual average hours worked in all jobs. According to the retained definition, hours worked means the total number of hours that a person spends working, whether paid or not. In general, this includes regular and overtime hours, breaks, travel time, training in the workplace and time lost in brief work stoppages where workers remain at their posts. On the other hand, time lost due to strikes, lockouts, annual vacation, public holidays, sick leave, maternity leave or leave for personal needs are not included in total hours worked. Labour productivity is a measure of real gross domestic product (GDP) per hour worked. The ratio between total compensation for all jobs, and the number of hours worked. The term hourly compensation" is often used to refer to the total compensation per hour worked." This measures the cost of labour input required to produce one unit of output, and equals labour compensation in current dollars divided by the real output. It is often calculated as the ratio of labour compensation per hour worked and labour productivity. Unit labour cost increases when labour compensation per hour worked increases more rapidly than labour productivity. It is widely used to measure inflation pressures arising from wage growth. Unit non-labour payments are the non-labour payments associated with each unit of output of goods and services, and they are calculated as the non-labour payments divided by the real output. The implicit price deflator is equal to current-dollar output, divided by real output. The output measure is consistent with the Quarterly Income and Expenditure Accounts, prepared by the National Economic Accounts Division. Labor share is equal to the labour compensation divided by current dollar output. The output measure is consistent with the Quarterly Income and Expenditure Accounts, prepared by the National Economic Accounts Division. Current-dollar gross domestic product (GDP) in business sector equals current-dollar GDP in the economy less the gross value added of government, nonprofit institutions, households, and the rental of owner-occupied-dwellings. The output measure is consistent with the Quarterly Income and Expenditure Accounts. The total compensation for all jobs consists of all payments in cash or in kind made by domestic producers to workers for services rendered. It includes wages and salaries and employer's social contributions of employees, plus an imputed labour income for self-employed workers. Non-labour payments are the excess of current-dollar output in the business sector over corresponding labour compensation, and include non-labour costs as well as corporate profits and the profit-type income of proprietors. Non-labour costs include interest, depreciation, rent, and indirect business taxes. Unit labour cost in United States dollars is the equivalent of the ratio of Canadian unit labour cost to the exchange rate. This latter corresponds to the United States dollar value expressed in Canadian dollars.

This dataset provides annual and hourly minimum wages by country with both nominal and purchasing power parity (PPP) scales.

Source

This dataset is a capture of data from Wikipedia - "List of minimum wages by country" (https://en.wikipedia.org/wiki/List_of_minimum_wages_by_country) The capture is done on 27 December 2020,

In 2022, it was estimated that the CEO-to-worker compensation ratio was 344.3 in the United States. This indicates that, on average, CEOs received more than 344 times the annual average salary of production and nonsupervisory workers in the key industry of their firm.

[ Derived from parent entry - See data hierarchy tab ]

Given the importance of sub-daily extreme precipitation events for the occurrence of pluvial floods, it is a key component in climate change adaptation to quantify the likelihood of such extreme events under current and future climate conditions. Such assessments are usually limited by a lack of sufficiently dense and sub-daily precipitation observations, (ii) high-resolution convection-permitting regional climate model (CPM) simulations that realistically represent sub-daily precipitation extremes, and (iii) statistical methods that allow us to extrapolate extreme precipitation return levels under limited data availability and non-stationary conditions (i.e., climate change) based on the main governing physical processes. We overcome these constraints through the utilization of kilometer-scale hourly radar precipitation estimates (RADKLIM) and spatially disaggregated observed daily temperature data (HYRAS-DE-TAS), and the implementation of a novel CPM ensemble covering the entirety of Germany, obtained from the NUKLEUS project within the BMBF-funded RegIKlim (Regionale Information zum Klimahandeln) initiative. Additionally, we introduce the Temperature-dependent Non-Asymptotic statistical model for eXtreme return levels (TENAX) model, a new approach that integrates daily temperature as a covariate, aligning with observed Clausius-Clapeyron scaling rates. This innovation results in a groundbreaking dataset of hourly extreme precipitation for Germany, marking the first instance of accounting for non-stationary climate conditions, i.e., in a +2K and +3K warmer world. The new dataset contains kilometer-scale hourly precipitation extremes for the return level of a 100-year event. Due to the inherent biases of radar-based estimates compared to ground observations, the precipitation extremes have been bias-adjusted on return level basis using KOSTRA.