Labour market analysis: Wages (structure, trends, thematic areas and relation to other major issues including decent work indicators) Monica D. Castillo Chief Decent Work Data Production Unit Chief, Decent Work Data Production Unit ILO Department of Statistics – Geneva castillom@ilo.org National Labour Market Information Training Programme Port of Spain, Trinidad and Tobago 31 October – 11 November 2011 ILO Department of Statistics
Contents • Rationale and context R ti l d t t • Use of current and structural wages statistics • Wage and related indicators in the Decent Work Indicator Framework • Productivity and wages • ILO Global Wage Report: Key Findings • ILO Global Wage Report: Key Findings ILO Department of Statistics
Monitoring wage levels, trends and structure: rationale and structure: rationale • Monitoring of wages levels, trends, structure and related indicators necessary to assess wage policies: necessary to assess wage policies: – Essential for evidence-based policy-making – Can ‘de-politicize’ minimum wage adjustments p g j – Data can serve as reference point for social partners in collective bargaining – Impartial and reliable data help to remove conflict • Wages: just one element in broader context of monitoring progress Wages: just one element in broader context of monitoring progress towards decent work ILO Department of Statistics
Uses of employment-related income and wages statistics and wages statistics • Uses: – Measurement of level of living of workers M t f l l f li i f k – Wage fixing – Collective bargaining Collective bargaining – Economic indicators – Income distribution studies – Empirical data and wage theories – Economic, social and manpower planning, research, analysis – Wage, income and price policies ILO Department of Statistics 4
Different income concepts relate to different functions to different functions • As a price of labour – Concepts: Wage rates Concepts: Wage rates • As the employment income (wellbeing) of workers – Concepts: Earnings, employment-related income related to paid employment C t E i l t l t d i l t d t id l t and to self-employment • As a cost to the employer (firm costs, revenues, profits) – Concepts: Labour cost, compensation of employees No unique concept applicable to all circumstances 5 ILO Department of Statistics
Concepts of employment-related income and cost of labour from worker and employer perspective cost of labour from worker and employer perspective Concepts related to income from Concepts of cost to employing labour employment (workers’ perspective) (employers’ perspective) tion components g complexity of Employees: Employers: components omplexity of Wage rates Wage rates Increasing Labour cost remunerat Increasing c Earnings Income related to paid employment Compensation of employees Labour cost* Self-employed workers (includes some employers): *Excludes employers’ imputed social contributions included in compensation of employees Income related to self-employment ILO Department of Statistics 6
Analysis of wages statistics should be done jointly with other key LM variables! (1) jointly with other key LM variables! (1) Germany Russian Federation (2008Q2 ‐ 2009Q2) (2008Q1 ‐ 2009Q1) 5 5 1 7 1.7 0.4 n.a 0 0 ‐ 3.1 ‐ 5 ‐ 3.7 ‐ 3.3 ‐ 5 ‐ 6.7 6 7 ‐ 10 ‐ 10 ‐ 10.8 ‐ 15 ‐ 15 Real GDP Employment Average hours Compensation Real GDP Employment Average hours Compensation rate c) rate c) United States United States (2008Q2 ‐ 2009Q2) • In 2008-09, economies responded to the crisis 5 mainly through declining employment (e.g. US and 2.2 Russian Federation) and hours of work (e.g. Germany) 0 • T o a lesser extent adjustment through declining wages (e.g. ‐ 1.8 ‐ 5 ‐ 3.8 ‐ 3.8 Russian Federation) ‐ 10 • Compensation rose (modestly) in the majority of G20 countries during the GDP peak-to-trough period as layoffs initially occurred during the GDP peak-to-trough period, as layoffs initially occurred among temporary employees and young workers (low wage earners) ‐ 15 Real GDP Employment Average hours Compensation rate c) Department of Statistics 7
Analysis of wages statistics should be done jointly with other key LM variables! (2) j y y ( ) LATIN AMERICA (18 SELECTED COUNTRIES): INFLATION AND THE REAL MINIMUM WAGE, 2008 (Accumulated change, December to December) Source: ILO Labour Overview Latin America and the Caribbean 2008 Department of Statistics 8
Integrated sources of information on wages statistics and income from employment 12 th ICLS (1973) and 16 th ICLS (1998) th th Current statistics Structural (non-current) Statistics Statistics s ased surveys (monthly or quarterly) nd surveys (annually, or 3 to 5 years) Serves as Current establishment benchmark Survey on the structure survey on: y censuses an and distribution of earnings and distribution of earnings blishment-ba - earnings and hours worked (or hours paid for); - wage rates and Survey on labour cost Survey on labour cost normal hours of work normal hours of work Estab Industrial Current labour cost is estimated Agricultural surveys with administrative information Household based Surveys Administrative records (agricultural earnings, (agricultural earnings, income from employment) ILO Department of Statistics 9
Short-term objectives and indicators j • Objective: to analyze short-term levels and trends in wages indicators and their relationship with other key labour market variables and their relationship with other key labour market variables • Examples of variables: – Average hourly, weekly, or monthly earnings of employees (by industry) A h l kl thl i f l (b i d t ) • Wage earners • Salaried workers – Average hourly wage rates g y g – Manufacturing wage index – CPI changes – GDP growth – Employees on nonfarm payrolls (by industry) – Employees on nonfarm payrolls (by sex) – Average weekly hours paid of employees (by industry) – Average overtime hours of employees (by industry) A ti h f l (b i d t ) ILO Department of Statistics 10
Data preparation for short-term analysis: seasonal adjustment analysis: seasonal adjustment • Many infra-annual (e.g, monthly, quarterly) employment and unemployment statistics (in some cases also wages) are adjusted for seasonal adjustment (SA). ( g ) j j ( ) • Main objective: to filter out usual seasonal fluctuations and typical calendar effects within the movements of the time series under review. • SA also includes the elimination of calendar fluctuations related to factors involving differences in the number of working or trading days or the dates of particular events which can be statistically proven and quantified (e.g. school and public t hi h b t ti ti ll d tifi d ( h l d bli holidays). • • Therefore the seasonally adjusted data do not show “normal” and repeated events Therefore, the seasonally adjusted data do not show normal and repeated events. • They help to reveal the underlying trends contained in a time series, which is the ultimate goal of SA ultimate goal of SA. ILO Department of Statistics 11
Example of metadata recommended for seasonal adjustment for seasonal adjustment Type of field Field EXAMPLE OF VALUES OTHER POSSIBLE VALUES KIND of adjustment SA NSA, Trend ‐ Cycle Series too short, Note of the non ‐ availability of Series break, SA SA series i N No identifiable seasonal id ifi bl l GENERAL pattern INFORMATION SAMPLE of raw data Q1.2004 ‐ Q4.2008 (number observations) (20) SOURCE of seasonal EUROSTAT, OECD, National ILO adjustment source LINK to source T Trading day effect di d ff ‐‐ Yes Y Easter (Catholic, Orthodox), Moving holidays ‐‐ CALENDAR Ramadan Correction for Outliers: Yes ADJUSMENT and Additive Outliers (AO) AO (M9/2001) other PRE ‐ ‐‐ Transient Changes (TC) AO (M11/2007) ADJUSTMENTS Level Shifts (LS) LS (M1/2008) Mi Missing observations i b ti ‐‐ Y Yes Other regression effects ‐‐ Yes (break in seasonality) Direct or indirect SA Indirect Direct AGGREGATION If Direct SA: Consistency between aggregate and ‐‐ Yes, No components METHOD USED X ‐ 12 TRAMO SOFTWARE used DEMETRA 2.1 SEASONAL Seasonal ARIMA model (0 1 1)(0 1 1) ADJUSTMENT (p,d,q) (P,D,Q) Values of M tests, residual Quality indicators used: autocorrelations, spectral SA quality index [0, 10] q y [ , ] 5.9 analysis l i Type of decomposition LOG ‐ Additive Multiplicative, Additive ILO Department of Statistics 12
Seasonally adjusting short-term wage data reveals underlying trends wage data reveals underlying trends Average nominal hourly earnings of all employees on private non-farm payrolls Seasonally adjusted and not seasonally adjusted series, January-December 2010 (in US dollars) 22.90 22.80 22.70 22.60 22.50 Seasonally adjusted series S ll dj d i Not seasonally adjusted series 22.40 22.30 22.20 22.10 Source: U.S. Bureau of Labor Statistics Department of Statistics 13
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