Decomposition of wage losses due to job displacement Pedro Raposo - PowerPoint PPT Presentation

Decomposition of wage losses due to job displacement Pedro Raposo (Catolica Lisbon SBE, Universidade Catolica Portuguesa) Pedro Portugal (Banco de Portugal, NOVA SBE and IZA Bonn) Anabela Carneiro (Universidade do Porto and CETE) Paris, OECD, May 2013 Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 1 / 21

Introduction Monthly earnings of workers separating in year 2002 and non-displaced workers 2000 ¡ 1800 ¡ 1600 ¡ 1400 ¡ 1200 ¡ 1000 ¡ 800 ¡ 600 ¡ 400 ¡ 200 ¡ 0 ¡ 1997 ¡ 1998 ¡ 1999 ¡ 2000 ¡ 2002 ¡ 2003 ¡ 2004 ¡ 2005 ¡ 2006 ¡ 2007 ¡ 2008 ¡ Non-­‑displaced ¡ Firm ¡closure ¡ Collec=ve ¡dismissals ¡ Individual ¡dismissals ¡ Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 2 / 21

Introduction Motivation Displaced workers experience substantial and persistent reductions in earnings - on the order of 8 to 25 percent for prime-aged workers, in comparison with their non-displaced counterparts (Couch and Placzek, 2010) lasting over 15-20 years (Wachter, 2010). The contribution of human capital to the wage growth has been decomposed in several components general human capital firm specific human capital job (or task)-specific human capital. Explain the sources of wage losses Wage policy of firms Job title assignment Selection into employment Accounting for idiosyncratic trends Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 3 / 21

Introduction Worker (constant) heterogeneity Worker heterogeneity and the Diamond’s paradox Worker observed permanent characteristics: Gender and race Formal education (if it does not change over the working life) Birth cohort Worker unobserved permanent characteristics Ability education quality Family background Employment cohort (which may be unobserved) Risk aversion Colour of the eyes Beauty (assuming it does not change over the sample period...Heroic!) DNA (which of, course, includes gender, race, eyes’s coulor, freckles, etc.) Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 4 / 21

Introduction Wage policy heterogeneity among firms Theories that explain why firms find it profitable to pay non-competitive wages Implicit contracts, principal-agent, efficiency-wages, rent-sharing, and insider-outsider considerations Firms design incentive schemes to retain their workers, attract better workers, and enhance their productivity (compensation and retention policies) Labor market frictions explanations for the wage differentials: job search and matching literature Permanent characteristics of firms: Location and industry Managerial ability and managerial organization Hiring and firing policies ...as long they do not change over the sample period Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 5 / 21

Introduction Job title heterogeneity Job title heterogeneity has been neglected...at most some, attention has been placed on the role of occupations There are compensating differentials for certain occupations involving: Risks of accidents/injuries Stressful working conditions Complexity of tasks (requiring specific training or unusual skills) Unions may limit or speed up the accession to job-titles Closed shops Promotion policies Definition of job-titles (and its level of stratification) Persistent oversupply of labor for some occupations (teachers) Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 6 / 21

Introduction Previous Literature Addison and Portugal (1989):Wage losses are significantly influenced by the length of joblessness (elasticity around -0.1). Earnings losses (JLS, 1993: high-tenure displaced workers long-term earnings losses averaging 25 % per year six years after displacement). Couch and Placzek (2010): estimates are roughly half those found for Pennsylvania. Greater among unemployment insurance recipients. Farber(2011): full-time job losers who find new full-time jobs earned 11 percent less. Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 7 / 21

Introduction Previous Literature: transferability of human capital Most losses result from the loss of accumulated firm-specific human capital (Lefranc, 2003). Unskilled workers benefit from being attached to a particular firm while skilled workers benefit from the acquisition of transferable skills (Dustmann and Meghir, 2005). Impact of general skills and firm-specific skills to the wage growth. This allows them to find that longer lasting matches are characterized by high wage growth in the first five years and higher wages on average (Amann and Klein, 2012). The task-specific human capital explains up to 52% of overall wage growth over the career. Wage losses of displaced workers will be 10 percentage points larger for workers reemployed in a very distant occupation (Gathmann and Schonberg, 2010). Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 8 / 21

Introduction Our study Two main objectives drive the investigation: 1 Follow JLS (1993) methodology to investigate the monthly earnings losses, including transitions to zeros whenever the individuals are out of work. 2 Extend the JLS methodology by incorporating firm and job title fixed effects in the monthly wage equation (excluding transitions to zeros), allowing us to estimate the monthly wage losses of displaced workers. We decompose the monthly wage losses into their main sources using the methodology developed in Gelbach (2010) (omitted variables bias). Basically, we use the fixed effects to disentangle part of the wage loss. Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 9 / 21

Data Data used: Quadros de Pessoal Rich set of information available in the longitudinal matched employer-employee dataset for Portugal, on: The collective agreement that regulates the employment contract applicable to each worker (300 negotiated per year, on average) Detailed occupational categories defined for each collective agreement (100 categories defined by each collective agreement, on average) Job title: combination of collective agreement and professional category (around 30,000 per year) All the population - covers all personnel working for an establishment Very rich in worker and firm specific information (gender, age, schooling, region, industry, firm size) Period: 1997-2008 Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 10 / 21

Data Data used: Variables and definitions Displaced: all workers who separate from a dying firm in a given year. Such workers are unlikely to have left as a result of their own poor performance and therefore it attenuates the curse self-selection. Non-displaced workers (the control group) includes all individuals that were employed at year t in a firm that did not close in year t+1 and the firm’s employment did not drop 30 percent or more and they were not subject to an individual dismissal. A firm closure is observed if the identification number of one firm appeared in period t but did not appear in t+1 and t+2. Monetary variables deflated with the Consumer Price Index (2008 prices) Hourly wage = (sum of 5 comp. of wages)/(sum of 2 types of hours) Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 11 / 21

Data Data used: Sample Reference year: 2002 Workers with at least three years of tenure by the time of the reference year (all years between 2002 and 2006). Full-time wage earners in the private non-farm sector Aged between 20 and 49 years Employed in a firm with at least 20 employees. Reference Period: 2002-2006 Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 12 / 21

Empirical strategy Empirical strategy JLS(1993) m � D k w it = α i + γ t + β X it + it δ k + ǫ it k ≥− m JLS(1993) detrend estimator (with worker-specific time trends): m � D k w it = α i + ω i t + γ t + β X it + it δ k + ǫ it k ≥− m Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 13 / 21

Empirical strategy Empirical framework: Linear wage equation with worker, firm, and job title fixed effects w ijft = α i + θ f + λ j + γ t + β X ift + ǫ ijft (1) w ijft represents the monthly wage for each individual i, in job j, working for firm f in year t X fit are observed time-varying characteristics of individual i in year t Workers time-varying characteristics (age, age squared) α i is a worker fixed effect θ f is a firm fixed effect λ j is a job title fixed effect γ t are 18 year dummies ǫ ijft is assumed to follow the conventional assumptions Raposo, Portugal, Carneiro (2013) Decomposition of wage losses Paris, OECD, May 2013 14 / 21