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Compensation of Government Employees

Compensation of Government Employees. Operational Material. Outline. Topics to be covered Introduction to Government Expenditures Compensation of Government Employees Pay and Expenditure Structure Indicators Timeline Introduction to Validation. Introduction to Government Expenditures (1).

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Compensation of Government Employees

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  1. Compensation of Government Employees • Operational Material

  2. Outline • Topics to be covered • Introduction to Government Expenditures • Compensation of Government Employees • Pay and Expenditure Structure Indicators • Timeline • Introduction to Validation

  3. Introduction to Government Expenditures (1) Individual consumption expenditure by government Housing Health Expenditures by government Education Recreation and Culture Social Protection Collective consumption expenditure by government Collective Services

  4. Introduction to Government Expenditures (2) Compensation of Employees Health Benefits and Reimbursements Intermediate Consumption Gross Operating Surplus Health Production of Health Services Net Taxes on Production Receipts from Sales Compensation of Employees Education Benefits and Reimbursements Intermediate Consumption Gross Operating Surplus Education Production of Education Services Net Taxes on Production Receipts from Sales Compensation of Employees Intermediate Consumption Collective Services Collective Services Gross Operating Surplus Net Taxes on Production Receipts from Sales

  5. Compensation of Government Employees 1. Concept Remunerations Expenditures • Government • Expenditure • Compensation of Government Employees • Pay & Employment Structure Indicators (For Validation) • PPPs • for Compensation of Government Employees

  6. 2. Data Collection 1 2 3 Government Expenditure • Compensation of Government Employees Pay & Employment Structure Indicators From • Official government pay scales • Final government accounts • Relevant official statistics For • 44 typical occupations • (4 levels of experience each) • 2 categories of government (Central + Sub-national) • General indicators Data • Data Collection Form (DCF): • Basic pay • Cash allowances • Income in kind • Employers’ social security contributions • Information on hours worked • Questionnaire: • Wages and salaries in cash • Employers contribution to social security funds • Benefits in kind • Information related to fixed capital formation • Aggregated indicators: • General Indicators such as GDP and population • Government Recurrent Expenditures Indicators • Wage bill Indicators • Employment Indicators Note • Covers 3 BHs (Health, Education and Collective services) • Report separately for Health, Education and Collective services • Additional ratios will be computed automatically (ICP-Kit) Reference : ICP website - Operational Material 3.1.01. Information required on Government for the ICP 2011 3.1.02. Government Occupations, DCF & Indicators 3.1.03. Questionnaire on Government Expenditure

  7. 2. Data Collection 1 2 3 Government Expenditure • Compensation of Government Employees Pay & Employment Structure Indicators From • Official government pay scales • Final government accounts • Relevant official statistics For • General indicators • 44 typical occupations • (4 levels of experience each) • 2 categories of government (Central + Sub-national) • Covers 3 BHs (Health, Education and Collective services) • Reported separately for Health, Education and Collective services Data • Data Collection Form (DCF): • Basic pay • Cash allowances • Income in kind • Employers’ social security contributions • Information on hours worked • Questionnaire: • Wages and salaries in cash • Employers contribution to social security funds • Benefits in kind • Information related to fixed capital formation • Aggregated indicators: • General Indicators such as GDP and population • Government Recurrent Expenditures Indicators • Wage bill Indicators • Employment Indicators Reference : ICP website - Operational Material 3.1.01. Information required on Government for the ICP 2011 3.1.02. Government Occupations, DCF & Indicators 3.1.03. Questionnaire on Government Expenditure

  8. Used in calculation of all three BHs 3-1. Example of Government Occupations 20 years 4 Levels of Experience: 0 year 5 years 10 years for each occupation (starting salary) 44 occupationsX 4 levels = 176

  9. 3-2. Government Expenditure

  10. 3-3. Pay and Employment Structure Indicators The following indicators are automatically calculated in the ICP-Kit module.  they give insights when comparing countries / economies (1) Wage bill Indicators • Government wage bill per GDP • for General/Central/Sub-national Government (2) Compression Ratios (Ratio of average total remuneration) • Managerial-professional ratio • Managerial-clerical ratio • for Health/Education/Collective (3) Public Sector Remuneration per GDP/capita • Managerial • Professional • Clerical • for Health/Education/Collective (4) Employment Indicators • Employment per capita • Employment per labor force (LF)

  11. Actual Data Collection Forms DATA PROCESSING TOOLS 3-1. Compensation of Government Employees ICP-Kit “Compensation” module 3-2. Government Expenditure Government Expenditure Questionnaire (Excel) 3-3. Pay and Employment Structure Indicators

  12. Validation Process Data Compilation (Annual Data) NATIONAL LEVEL (Intra-Country Validation) Initial Data Validation Finalization of Data 1 Data Transmission NCA  RCA REGIONAL LEVEL (Inter-Country Validation) Analytical Tables Initial DataValidation Temporal Analysis Finalization of Data 3 2 PPPs, PLIs, etc. Data Transmission RCA  GO GLOBAL LEVEL

  13. Validation Steps(1) 1. NATIONAL Initial Data Validation Step1: Add remunerations and metadata to data collection tool Step2: Check added codes and metadata for errors and discrepancies Step3: Check that remunerations are plausible within the same occupation a. Within the same level of experience b. With different levels of experience • Usually one observation per occupation • Sometimes different salary scales in different local governments • Usually, remunerations increase as experience increases e.g. Database administrator 35,256 (Municipal A, 5-year experience) Database administrator 74,662 (Municipal B, 5-year experience) e.g. Hospital doctor 50,653 (0 year of experience) Hospital doctor 45,367 (10 years of experience) ? ? Step4: Check that remunerations are plausible between related occupations <Within the same level of experience> e.g. 1 Hospital Doctor (5 years) 62,556 Hospital Nurse (5 years) 75,698 e.g. 2 Hospital Doctor (0 year) 62,556 Hospital Nurse (20 years) 65,698 ? 

  14. Validation Steps(2) 1. NATIONAL Initial Data Validation – cont’d Step5: Check that remunerations are temporally plausible by comparing them to previous ICP round Step6: Compare remuneration data and expenditure data by using structure indicators. (Remuneration x Employment  Expenditure) Step7: Analyze price data and metadata for flagged cases

  15. Validation Steps(3) 2. REGIONAL Initial Data Validation Step1: Add remunerations and metadata to data validation tool Step2: Re-base data from all the countries to reference hours worked e.g. • Re-base *Recommended to use “actual hours” if information is available. Step3: • Convert remunerations in local currency into base currency using annual average exchange rate

  16. Validation Steps(4) 2. REGIONAL Initial Data Validation – cont’d Step4: Check that remunerations are plausible within a country e.g. University teacher < Firefighter e.g. Primary school teacher > Secondary school teacher ? ? 4,221 560 18,199 Step5: Check that remunerations are plausible for a remuneration across the countries ? e.g. 560 in country A could be too small. 18,199 in country C would be too large. Step6: Check that remunerations are temporally plausible by comparing them to previous ICP round Step7: Analyze price data and metadata for flagged cases

  17. Validation Steps(5) 3. REGIONAL Analytical Tables  Temporal Analysis As same as HHC, analysis using Tables make it possible to conduct detailed comparisons. iteration • Quaranta Tables • Dikhanov Tables • Temporal Analysis – with data from previous round PPPs, PLI, C.V., CUP ratio, etc. Analytical Tables

  18. Timeline Latest Year 2011 data 1st Quarter, 2012 4th Quarter, 2012 1st Quarter, 2012 4th Quarter, 2012 Data Transmission (all data) NCA  RCA Data Transmission (all data) NCA  RCA 2nd Quarter, 2012 1st Quarter, 2013 Data Transmission (all data) RCA  GO Data Transmission (all data) RCA  GO

  19. THANK YOU

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