1. Understanding Wage and Productivity Dispersion in the United Kingdom by Giulia Faggio, Kjell G. Salvanes and John Van Reenen Preliminary

2. Contents of the presentation Motivations Review of the literature Data Description of the trends Decomposition of wage and productivity dispersion Analysis of Total Factor Productivity (TFP) Conclusions

3. Motivations I Wage inequality has increased substantially in the US and the UK over the last 30 years. A large proportion of this increase has been explained as a within-group phenomenon (i.e. by education, skill, occupation or industry group). Many theories have been proposed to explain this within- group inequality. They assume that increasing inequality takes place between firms within industries rather than within firms. There is almost no evidence on the impact of these between- firm effects on the aggregate increase in wage inequality and this paper tries to fill this gap.

4. Motivations II Looking at firm productivity, previous studies have analysed: –the cross-sectional distribution of firm productivity (e.g. Haltiwanger, Lane and Spletzer, 1999) –the evolution of average productivity (e.g. Foster, Haltiwanger and Krizan, 1998 and 2002) Very few studies have looked at the changes of the distribution of firm productivity over time: –Dunne, Foster, Haltiwanger and Troske (2002): they find a large increase in wage and productivity dispersion between 1975-1992 across US manufacturing plants. –Haskel and Martin (2002): they look at the changes in productivity dispersion focusing on UK manufacturing plants. This paper tries to carefully document changes in productivity dispersion over time looking at both manufacturing and non- manufacturing.

5. Literature We consider three classes of theories that have tried to explain the rising in within-group wage inequality: 1.the first group emphasizes the impact of a technological revolution that has caused differential adoption of new technology by firm (e.g. Caselli, 1999) 2.the second group links increased inequality to increased segmentation of workers by skill (e.g. Kremer and Maskin, 1996) 3.the third group argues that institutional change (e.g. union decline) has an impact on wage inequality and thus potentially on productivity dispersion

6. Caselli (1999) He models the impact of a technological revolution (e.g. the ICT revolution) on productivity and wage dispersion. Implications: –High skilled workers will benefit the most (if the technology is skilled-biased), but all workers in the more productive plants will tend to receive higher wages, –A skilled-biased technological revolution leads to an increase in the dispersion of wages and TFP across plants, –These increases are modelled as between firm within industry effects.

7. Kremer and Maskin (2000) They model the simultaneous existence of increased wage inequality and increased segregation of workers by skill across plants. Implications: –If the distribution of skills across workers is dispersed & because of the complementary between tasks, an increase in the mean skill level leads to a separating equilibrium: High skill/high productivity firms and low skill/low productivity firms can exist in equilibrium, Increased wage inequality is associated with increased labour productivity across firms (non necessarily with TFP), These rises are modelled as between firm with industry effects.

8. Union decline Union declines allows low wage/low productivity firms to enter the market. Under strong union power, these firms were non- viable because they could not satisfy union demands over wages. The entrance of low wage firms raises wage dispersion and thus potentially productivity dispersion. –If low wage firms employ mostly low skill workers, they will be characterised by low productivity as well.

9. Our Strategy Descriptive analysis of trends in wage dispersion and productivity dispersion –There is limited evidence on the changes in productivity dispersion and ours is one of the first attempts. Decomposition of trends in wage and productivity dispersion –Is the rising wage dispersion a within- or between-firm phenomenon? –Is the rising productivity dispersion a between-firm within-industry or between-industry phenomenon? Analysis of Total Factor Productivity (TFP) –Caselli (1999)’s model implies a positive link between wage and TFP dispersion. –Kremer and Maskin (2000)’s model suggests a positive link between wage and labour productivity dispersion, but not necessarily TFP dispersion. Evaluation of the theoretical explanations of these changes Cross-country analysis – Since theories suggest that these are global phenomena, we want to conduct an international comparison between the UK, Norway, France and the US.

10. Description of the data We use 2 different data sets for the UK: –Financial Analysis Made Easy (FAME) data set: Consolidated company account data for the UK manufacturing and non-manufacturing firms Sample period: 1984-2002. –New Earnings Survey (NES) data set: Employee data taken from the UK National Insurance Database It samples 1 % of the UK population Sample period: 1975-1999.

11. Description of the trends the UK: –Wage dispersion in private services and manufacturing: using data at the individual level (log real annual wage) using data at the firm level (log real annual average firm wage) –Labour Productivity dispersion in private services and manufacturing: using data at the firm level (log real value added per worker)

12. Wage dispersion in the UK: private services, individual data

13. Wage dispersion in the UK: manufacturing, individual data

14. Wage dispersion in the UK: private services, firm level data

15. Wage dispersion in the UK: manufacturing, firm level data

16. Productivity dispersion in the UK: private services, firm level data

17. Productivity dispersion in the UK: manufacturing, firm level data

18. Summary of the evidence Using individual level data: –Wage inequality was increasing in both private services and manufacturing until the early 1990s; then it continued to increase in private services but not in manufacturing. Using firm level data: –Wage inequality as well as productivity dispersion is increasing substantially in private services. Limited increase in manufacturing.

19. Decomposition of trends in wage and productivity dispersion Following Davis and Haltiwanger (1991), we decompose wage dispersion into between and within firm components: –Within firm component –Between firm within industry component –Between industry component Where: - W kij is the wage for worker k at firm i in sector j, - W ij is the average wage at firm i in sector j and - W is the mean wage across all workers in all firms and sectors. k=worker i=firm j=sector

20. Variance decomposition Multiplying and dividing the first term of the right-hand side of equation (1) by Nij (Nij = total number of workers k in firm i): Calling Vij the estimated variance of wages across workers of firm i, equation (2) becomes: Total varianceWithin firm componentBetween firm component

21. Variance decomposition Dividing through by N, the total number of workers in the economy, we obtain the decomposition of overall variation into within-firm (WF) and between-firm (BF) components:

22. Variance decomposition – Between component It is possible to decompose the between-firm variation as: –the sum of total variation of firm average wage relative to the sector average (V BFI = between firm/within industry) –the total variation of the sector average wage relative to the average of the whole economy (V BI = between industry): V BF = V BFI + V BI V= V WF + V BFI + V BI The variance decomposition of the between component is also applied to firm productivity

23. Variance decomposition of yearly wages We combine the individual level data from the NES with the firm level data from FAME at the 2-digit industry level: –We estimate total wage variance (V) directly from the NES. –We estimate the between components (V BFI & V BI ) directly from FAME. –The within firm component (V WF ) can be estimated as a residual. FAME data give a measure of total annual remuneration at the firm level while NES data provide a measure of weekly gross pay. In order to make the measures comparable: 1.We adjust total annual remuneration by a coefficient (0.92) taken from a regression of log wage on log remuneration with industry, firm size and year dummies. 2.We express both measures at the annual level and in real terms (deflated by the RPI)

24. Variance decomposition of yearly wages

25. Variance decomposition of yearly wages further decomposition of the between component

26. Variance decomposition of yearly wages UK private services

28. Variance decomposition of yearly wages UK manufacturing

30. Variance decomposition of labour productivity

31. Variance decomposition of labour productivity UK private services

32. Variance decomposition of labour productivity UK manufacturing industries

33. Summary of the results Evidence indicates that wage inequality and labour productivity dispersion have increased in the UK over the period 1984-99. The rises in wage dispersion and in productivity dispersion are driven by increases in private services. We find that rising wage dispersion is largely a between-firm within-industry phenomenon rather than a within firm phenomenon. We find that rising labour productivity dispersion is largely a between-firm within-industry phenomenon rather than a between-industry phenomenon. These findings appear to give some support to explanations (e.g. Caselli, 1999, Kremer and Maskin, 2000) that link rising wage inequality to between firm effects.

34. Variance decomposition of TFP 1.α = 0.7 as average share of labour (L) in the economy, 2.α = industry specific weights (i.e. ratio of total wage bill over value added at the 2-digit industry level), 3.α = firm specific weights (i.e. ratio of total wage bill over value added at the firm level). A preliminary analysis uses α = 0.7. We define TFP simply as:

35. Variance decomposition of TFP

36. Variance decomposition of TFP UK private services

37. Variance decomposition of TFP UK manufacturing industries

38. Summary of the results - TFP As for wage and labour productivity dispersion, the rise in TFP dispersion is mostly driven by increases in private services. We find that rising TFP dispersion is largely a between-firm within-industry phenomenon rather than a between-industry phenomenon. However, the between-industry component seems more important in explaining TFP dispersion rather than labour productivity dispersion. These findings appear to give some support to Caselli (1999)’s model.

39. Next steps Distinguishing between theories: –Caselli(1999) versus Kremer and Maskin(2000) –Institutional change versus Caselli(1999) Measurement error issues: –We do not have information about skills, gender and part- time/full-time workers at the firm level. Increased wage dispersion might be due to: Changes in the composition of workers in the firm Higher female participation Larger share of part-time workers –We use remuneration instead of hourly wages –Analysis of TFP: we do not measure all inputs properly –Using employer-employee data on Norway we can deal with some of these issues

40. Institutional change versus Caselli(1999): a simple framework UK/US: union decline and reduction in the share of workers covered by collective agreements France/Norway: union decline but very high share (95%in france) of workers covered by collective agreements UK/USFrance/Norway Caselli (1999) Institutional change σw ↑ σp ↑ σw ↑ σp ↑ σ w - σ p ↑ σ w - σ p - Caselli’s channel is from productivity to wages. Institutional channel goes from changes in wage to changes in productivity.