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Why have wage shares fallen? Determinants of functional income distribution. Part of the International Labour Organisation (ILO) project “New Perspectives.

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Presentation on theme: "Why have wage shares fallen? Determinants of functional income distribution. Part of the International Labour Organisation (ILO) project “New Perspectives."— Presentation transcript:

1 Why have wage shares fallen? Determinants of functional income distribution. Part of the International Labour Organisation (ILO) project “New Perspectives on Wages and Economic Growth” March 2013 Engelbert Stockhammer Research assistence: Hubert Kohler Kingston University

2 ILO Project: New Perspectives on Wages and Economic Growth: The potentials of “wage-led growth” Wage-led growth: Concept, theories and policies - Marc Lavoie and Engelbert Stockhammer Why have wage shares fallen? An analysis of the determinants of functional income distribution -Engelbert Stockhammer Is aggregate demand wage-led or profit-led? a global model - Özlem Onaran and Giorgos Galanis Wage-led or Profit-led Supply: Wages, Productivity and Investment- Servaas Storm and C.W.M. Naastepad The role of income inequality as a cause of the Great Recession and global imbalances - Till van Treeck and Simon Sturn Financialisation, the financial and economic crisis, and the requirements and potentials for wage-led recovery - Eckhard Hein and Matthias Mundt

3 3 Motivation Since early 1980 dramatic changes in income distribution → lit on personal income distr wage shares have been falling Well documented for OECD countries, less so for developing economies Until recently little research, then a series of publications on OECD countries,... but little on functional distribution in developing countries ILO project on ‚wage-led growth‘ Aim of paper: identify the relative impacts of financialisation, globalisation, technological change and welfare state retrenchment Panel 71 countries (28 ADV, 43 DVP), max (in fact: mid 80s-early 2000s) Panel of ALL as well as developing (DVP) economies Panel for ADV

4 4 Mainstream story IMF (2007a, p. 161) globalization is one of several factors that have acted to reduce the share of income accruing to labor in advanced economies, although rapid technological change has had a bigger impact (…). countries that have enacted reforms to lower the cost of labor to business and improve labor market flexibility have generally experienced a smaller decline in the labor income share. EC (2007, p. 260) “for the period for which the data is available (i.e. from the mid- 1980s to early 2000s), the estimation results clearly indicate that technological progress made the largest contribution to the fall in the aggregate labour income share“ “Globalisation also had a negative impact on the aggregate labour income share but to a lesser extent”

5 outline framework Literature Data Results ALL, DVP ADV conclusion 5

6 Adjusted Wage Share in advanced (ADV) economies 6

7 Adjusted Wage Share in developing (DVP) economies 7

8 Personal income distribution USA

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10 Correlation top1% and WS 10 AUS-0.68FIN-0.72ARG-0.86 CAN-0.43FRA-0.61CHN-0.83 IRL-0.76ITA-0.83IDN-0.14 GBR-0.71NLD0.46IND-0.18 USA-0.80PRT-0.15ZAF-0.67 ESP-0.16 SWE-0.54 JPN-0.30

11 Framework and comments on the literature 11

12 Literature on income distribution Lots of research on personal distribution Mostly on advanced economies; labour econ and trade theory, often micro Few that combine cross country and time Some lit on developing countries (Goldberg and Pavcnik 2007 JEL) Until recently little on functional distribution Then a series of publications (EC 2007, IMF 2007, OECD 2007) on OECD countries Smaller literature on developing countries Includes capital account liberalisation prominently Daudey and Garcia-Penalosa (2007) negative correlation between changes in personal and functional income distribution (for large sample)

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16 IMF (2007a), Jayadev (2008) IMF (2007a) Estimates adj WS = f(Glob, K/L, ICT, TW, UB) Glob: Px, Pm, offshoring, imigration 18 OECD countries , annual data Panel (OLS with some robustness checks) Story: decline in WS most of all caused by tech change, globalization contributed to decline in WS Then disaggregate for skilled WS and unskilled WS Jayadev (2008) WS = f(Ypc, CA openness [legal], trade openness, tariffs, int, gov’t share) countries 16

17 Main factors in the literature Technological change Globalisation Financialisation Welfare state retrenchment (or ‘bargaining power’, LMI) 17

18 Technological change Argument come from discussion of personal distribution Tech change, in particular ICT favors skilled workers (complements to ICT) and hurts unskilled workers (substitutes of ICT) Overall this leads to a fall in the wage share Tech change partly implemented through outsourcing Variables in empirical research K-L ratio (Bentolila and Saint-Paul 2003) Time trends (Ellis and Smith 2007, Guscina 2006: after 1985) K-L ratio and ICT: IMF (2007a, EC 2007) 18

19 Globalisation: Stolper-Samuleson vs Political Economy approach Stolper-Samuelson: changes of relative prices of labor and capital; abundant factor wins Outsourcing as a particular form of it =/= bargainging: mobile factor wins, threat effects (Rodrik) General econ perception at odds with specialized literature Problems of SS & HO: comparative advantage can‘t explain actual trade pattern; assumes full employment, homog labour... Stolper-Samuleson predicts positive effect of globalisation on WS in developing economies but globalization led to increased inequality in developing economies (Goldberg and Pavcnik 2007 JEL) Rodrik, Harrison, Jayadev find negative effect on WS in developing countries variables Trade openness (EC 2007) FDI, outsourcing, ToT (IMF 2007a) Tariffs (IMF 2007b, Rodrik 1998) 19

20 Financialisation Increasing importance of financial sector and financial investors („shareholder value orientation“) has shifted power relation at the expense of labor ILO (2008), Rossman (2009): shift in power relations Ex: Private Equity firm buys industrial firm with debt, loads debt onto firm -> firm has to cut costs to survive Epstein and Powers (2003) document increase in rentier income has decreased investment -> unemployment Stockhammer (2004), Lazonick and O‘Sullivan (2000): from ‚retain & reinvest‘ to ‚downsize & distribute‘ variables So far not included in econometric studies on the determinants of the wage share IMF (2007b): effect of financial globalization on personal income distribution Cap Account openness (Jayadev 2007) 20

21 ILO 2008 World of Word Report “financial liberalization that has contributed to growing inequality in some industrialized countries is the even greater importance attached to “shareholder value” maximization and to private equity funds in corporate management. The demand for higher dividend payouts by active shareholders has made managers more resistant to claims for wage increases than in the past, while the threat of outsourcing and downsizing has weakened the bargaining position of workers” (ILO 2008, p. 50) 21

22 Welfare state retrenchment Welare state increases bargaining power of labour Effect on wages depends on elastisticy of labor demand Political science literature on ‚welfare state retrenchment‘ Variables union density, various LMI (IMF 2007a, EC2007) LMI have ‚perverse‘ effect, implying very elastic labor demand LMI: lab mkt flex or bargaining power? Gov’t share (Jayadev 2007) strike (Bentolila and Saint-Paul: national variable in a sectoral panel) 22

23 Determinants of income distribution 23

24 Overview baseline variables WS = f(fin, tech, wfst, glob) 24

25 Data Results for ALL countries Results for ADV countries 25

26 Baseline specification (ALL countries) Baseline equation (ALL countries): WS = f(∆y, FINGLOB, OPEN, GOVT, Y/L, IND, AG) Variables for Globalisation: OPEN Financialisation: FINGLOB Technological + structural change: Y/L, IND, AG Welfare state retrenchment: LMI, gov’t 26

27 Wage share (WS) adjustments Problem: self employment, informal sector Adjusted WS: imputes formal wages to self employed Some recommend: average between adj WS and WS Further adjustments: keeping sectoral composition constant (or at US levels), Kruger (1999), Gollin (2002) Note: I don’t do adjustments (or not) myself Private wage share (WSP) WS = (1- CG)*WSP + CG*WSG WSP = (WS-CG)/(1-CG) 27

28 Data & sources WSAP Adjusted private wage share (1) AMECO, (2) ILO, (3) national ∆ygrowthWB WDI FINGLOB Financial globalisation (A ext +L ext )/Y IMF (Lane & M-F 07) OPENOpenness (X+M)/YWB WDI ToT Terms of trade(1) AMECO, (2) IMF CGGov‘t consumptionPENN UNIONUnion densityBD + BGHS GDPpwGDP per workerPENN AGAgricultural sharePENN ICTICT services/YKLEMS (ADV); ALL: Groningen KLCapital labour ratioKLEMS 28

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31 Robustness tests WS = f(∆y, finglob, open, govt, Y/L, ag, ind) Obs 1450 (dvp 614) Estimation method Fixed effects model: (annual) levels + autocorr correction First differences (annual) Non-overlapping 5 yr averages (NO5YA) GMM Results by country groups (ADV vs DVP) Robustness checks Finref Other fin LMI Glob By income group 31

32 Baseline specification (ALL) dep var: WSAP 32 coefft-value GROWTH *** LOG(FINGLOB) *** OPEN *** LOG(GDPPW) CG *** AG *** IND ** obs1450 adj r20.98 dw1.72

33 Baseline specification (DEV) dep var: WSAP 33 coefft-value GROWTH *** LOG(FINGLOB) *** OPEN ** LOG(GDPPW) CG *** AG ** IND obs595 adj r20.98 dw1.78

34 Table 3. Results for the baseline specification and variations GROWTH t-value-4.167***-4.172***-4.254***-3.774***-3.872***-3.007***-3.310***-4.803***-3.493*** LOG(FINGLOB) t-value-6.997***-6.932***-5.258***-5.141***-7.017***-2.554**-7.049***-5.623***-1.5 OPEN t-value-3.211***-2.540**-3.191***-4.436***-2.869***-2.595***-3.306***-3.141***-1.905* LOG(GDPPW) t-value * CG t-value3.975***3.972***3.995***2.052**4.210*** ***3.490*** AG t-value-2.719***-2.721***-2.621*** ***-2.195**-2.744***-2.683***-2.464** IND t-value-2.457** **-3.697***-2.731***-2.861***-2.524**-2.324**-4.026*** OPEN*D_HIGHIN t-value LOG(FINGLOB)*D_HIGHIN t-value TOT t-value-3.253*** UNEMPL t-value-4.743***-4.030*** LOG(ICT_CB) t-value D_CRISIS t-value D_EXCRIS t-value-2.590*** obs adj r dw

35 Table 3. Results for the baseline specification and variations GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND OPEN*D_HIGHIN LOG(FINGLOB)*D_HIGHIN TOT UNEMPL LOG(ICT_CB) D_CRISIS D_EXCRIS obs adj r20.98 dw

36 Table 10. Baseline specification and different estimation methods – adv countries FEdiff5yrGMMFEdiff5yrGMM lag.dep.var GROWTH LOG(FINGLOB) OPEN TOT CG UNION LOG(KL_KLEMS) LOG(ICT_KLEMS) UNEMPL obs adj r NA NA dw NA NA

37 Table 8. Results with financial reform variables GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND FINREF_CC-0.66 FINREF_IRC-0.21 FINREF_EB-0.11 FINREF_PRIV-0.30 FINREF_ICF0.08 FINREF_SM-0.41 FINREF_XN-3.10 obs adj r20.98 dw

38 Table 9. Results with labour market institutions variables GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND MW_MNW-0.48 UB_GRR UB_COVERAGE0.51 EPL_AN4Y-1.22 EPL_SP4Y0.08 LOG(LF)5.00 LOG(POP)-9.75 obs adj r dw

39 Other variations IMF LMI dataset (minW, UB, EPL) Nothing IMF financial reform (8 variables) Globalisation X have neg, M have pos effect FDI: no effect Priv credit, interest rate: some pos effect 39

40 Contributions to changes in the wage share, ALL countries, 1990/ /04 40

41 Contributions by estimation method 41

42 Contributions to the change in the wage share, developing economies, 1990/ /04 42

43 Baseline specification (ADV) Baseline equation (advanced ADV countries): WS = f(∆y, FINGLOB, TOT, OPEN, govt, UNION, K/L, ICT) Variables for Globalisation: OPEN, TOT Financialisation: FINGLOB Technological + structural change: Y/L, ICT Welfare state retrenchment: gov’t, UNION 43

44 Baseline specification (ADV) 44 coefft-value GROWTH *** LOG(FINGLOB) *** OPEN *** TOT ** CG *** UNION * LOG(KL_KLEMS) * LOG(ICT_KLEMS) obs470 adj r20.94 dw1.81

45 45

46 Conclusion 46

47 Conclusion Main causes of changes in income distribution financial globalization and welfare state retrenchment as main causes for decline in wage share Developing economies: similar to ADVs Globalisation and financial globalisation have negative effects on WS – opposite to what Stolper & Samuelson predict Positive effect of technological change Unemployment has weaker effects Advanced economies (ADVs) financial globalization and welfare state retrenchment as main causes for decline in wage share Moderate negative effects of technological change 47

48 Policy conclusions Part of project on ‘potentials of wage-led growth’ Neoliberalism has given rise to debt-led or export-led growth regimes (Lavoie and Stockhammer 2012; Hein 2012). Both rely on wage suppression Both are economically unstable and socially unbalanced Explore macroeconomic potential of wage-led growth Positive effects on demand (Onaran and Galanis 2012) Positive effects on productivity (Storm and Naastepad 2012) To increase wage share: tackle financialisation and strengthen the welfare state (role of unions) 48

49 Appendix. Results ALL, DP 49

50 Table 4. Results by income group lowinlowmidinupmidinhighinhighinoecd GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND obs adj r dw

51 Table 5. Results by estimation method FEdiff5yrGMM lag.dep.var.0.57 GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND obs adj r NA dw NA

52 Table 6. Results with different wage share variables (all countries) wsapwsaws_unws_unido GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND obs adj r dw

53 Table 7. Results with different wage share variables (developing countries) wsapwsaws_unws_unido GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND obs adj r dw

54 Table 8. Results with financial reform variables GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND FINREF_CC-0.66 FINREF_IRC-0.21 FINREF_EB-0.11 FINREF_PRIV-0.30 FINREF_ICF0.08 FINREF_SM-0.41 FINREF_XN-3.10 obs adj r20.98 dw

55 Table 9. Results with labour market institutions variables GROWTH LOG(FINGLOB) OPEN LOG(GDPPW) CG AG IND MW_MNW-0.48 UB_GRR UB_COVERAGE0.51 EPL_AN4Y-1.22 EPL_SP4Y0.08 LOG(LF)5.00 LOG(POP)-9.75 obs adj r dw

56 Appendix. Results ADV 56

57 Table 10. Baseline specification and different estimation methods – adv countries FEdiff5yrGMMFEdiff5yrGMM lag.dep.var GROWTH LOG(FINGLOB) OPEN TOT CG UNION LOG(KL_KLEMS) LOG(ICT_KLEMS) UNEMPL obs adj r NA NA dw NA NA

58 Table 11. Labour market institutions var. (Aleksynska & Schindler dataset), adv. countries GROWTH LOG(FINGLOB) OPEN TOT CG UNION LOG(KL_KLEMS) LOG(ICT_KLEMS) MW_MNW UB_GRR UB_COVERAGE EPL_AN4Y EPL_SP4Y obs adj r dw

59 Table 12. Labour market institutions var. (Bassanini & Duval dataset), adv. countries GROWTH LOG(FINGLOB) OPEN TOT CG UNION LOG(KL_KLEMS) LOG(ICT_KLEMS) EPL_BD BENDUR_BD GRR_BD0.02 PMR_BD TW_BD-0.04 obs adj r dw

60 Table 13. Results with financial reform variables, advanced countries GROWTH LOG(FINGLOB) OPEN TOT CG UNION LOG(KL_KLEMS) LOG(ICT_KLEMS) FINREF_CC FINREF_IRC FINREF_EB FINREF_PRIV FINREF_ICF FINREF_SM FINREF_XN Obs adj r20.94 Dw

61 Table 14. Results with technological change variables, advanced countries GROWTH LOG(FINGLOB) OPEN TOT CG UNION LOG(ICT_KLEMS) LOG(ICT_KLEMS)^20.16 LOG(KL_KLEMS)-7.03 LOG(KL_HOURS_KLEMS)-6.82 LOG(KL_AMECO) LOG(GDPPW)-8.85 obs adj r20.94 dw

62 Table 15. Results with globalisation variables, advanced countries GROWTH LOG(FINGLOB) OPEN TOT CG UNION LOG(KL_KLEMS) LOG(ICT_KLEMS) OPEN_x FDI_in-1.05 FDI_out0.27 KOF_glob_ec-0.12 KOF_glob_soc KOF_glob_pol0.001 obs470 adj r20.94 dw

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