Service offshoring and wages: worker-level evidence from Italy

Service offshoring and wages: worker-level evidence from Italy Elisa Borghi Università Carlo Cattaneo - LIUC Rosario Crinò Centro de Estudios Monetarios y Financieros (CEMFI) Final Workshop MIUR-PRIN Project Production, R&D and Knowledge Offshoring: Economic Analyses and Policy Implications September 25,2013

Introduction Research Question Effects of service offshoring on the wages of Italian workers

Introduction Research Question Effects of service offshoring on the wages of Italian workers Methodology Worker-level wage regressions

Introduction Research Question Effects of service offshoring on the wages of Italian workers Methodology Worker-level wage regressions Motivation ICT development and fear of service offshoring

Introduction Research Question Effects of service offshoring on the wages of Italian workers Methodology Worker-level wage regressions Motivation ICT development and fear of service offshoring Main results No significant reductions in workers wages Contribution to widening the wage gap between more and less skilled employees

Literature Fraction of jobs potentially at risk of offshoring is quite large (roughly 25% in developed countries ) [Blinder (2006, 2009); Kroll (2007); Moncarz et al. (2008); Blinder and Krueger (2009); Kletzer (2009)] Actual impact of service offshoring on the labor market has been moderate in many developed countries (2 4% of job separation in U.S. in the first half of past decade) [Bhagwati et al. (2004); Mankiw and Swagel (2006); Kirkegaard (2007)] Industry- or firm-level studies: small effects on domestic employment. (even positive in some cases, by boosting productivity and expanding scale of firms operations) [Recent contributions: Liu and Trefler (2011); Hijzen et al. (2011); Crinò (2012)]

Literature Evidence on Italy: Service offshoring has not caused significant reductions in domestic employment over the last two decades [Falzoni and Tajoli (2011) ; Crinò (2010)]

Literature Evidence on Italy: Service offshoring has not caused significant reductions in domestic employment over the last two decades [Falzoni and Tajoli (2011) ; Crinò (2010)] Service offshoring affects the skill composition of labor demand, favouring high-skilled workers [Crinò (2010a, 2010b, 2012)] Geishecker and Gorg (2012): individual level wage data for U.K.: raise in the skill premium

Focus on wage effects Contribution

Contribution Focus on wage effects Rich micro-level data (matched employer-employee data)

Contribution Focus on wage effects Rich micro-level data (matched employer-employee data) Worker-, firm- and industry-level characteristics considered

Contribution Focus on wage effects Rich micro-level data (matched employer-employee data) Worker-, firm- and industry-level characteristics considered Focus on job stayers: control for worker-firm pairs

Matched Employer-Employee Data Administrative records from the Italian National Social Security Institute (INPS)

Matched Employer-Employee Data Administrative records from the Italian National Social Security Institute (INPS) All individuals born in four different dates with at least one contract registered at INPS in a given year

Employer-employee data Table 2 - Descriptive Statistics on the Matched Employer-Employee Data All sample Manufacturing Services White-Collar Blue-Collar Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. a) Workers Age 35.9 10.54 35.72 10.56 36.08 10.52 37.4 9.71 34.92 10.93 Daily wage 73.6 429.17 69.56 226.41 77.03 545.81 99.6 623.93 56.39 218.28 Gender: Female 0.37 0.48 0.31 0.46 0.42 0.49 0.47 0.50 0.30 0.46 Occupation: Executives 0.01 0.11 0.01 0.12 0.01 0.10 0.03 0.17 - - Occupation: Managers & white-collar 0.39 0.49 0.26 0.44 0.50 0.50 0.97 0.17 - - Occupation: Blue-collar 0.54 0.50 0.66 0.48 0.43 0.50 - - 0.89 0.31 Occupation: Apprentices 0.06 0.24 0.07 0.25 0.05 0.22 - - 0.10 0.30 Industry: Services 0.54 0.50 - - - - 0.69 0.46 0.44 0.50 b) Firms Size (employees) 71.1 591.61 67.5 353.12 74.3 743.18 Organization: Single firm 0.80 0.40 0.85 0.36 0.76 0.42 Organization: Parent firm 0.12 0.33 0.10 0.31 0.14 0.35 Organization: Subsidiary 0.07 0.26 0.05 0.22 0.09 0.29 Industry: Services 0.53 0.50 - - - - Source: Administrative records from INPS.

17 industries, ATECO81 Offshoring Indicators

Offshoring Indicators 17 industries, ATECO81 Share of imported private services in total input purchases

Offshoring Indicators 17 industries, ATECO81 Share of imported private services in total input purchases Imports of services: ISTAT s Import Matrices

Offshoring Indicators 17 industries, ATECO81 Share of imported private services in total input purchases Imports of services: ISTAT s Import Matrices Total input purchases: ISTAT s Input-Output accounts 4 different services:

Offshoring indicators M sht = imports of services (s= service; h= industry; t= time)

Offshoring indicators M sht = imports of services (s= service; h= industry; t= time) Total service imports at the industry level: MS ht = 4 s=1 M sht

Offshoring indicators M sht = imports of services (s= service; h= industry; t= time) Total service imports at the industry level: MS ht = 4 s=1 M sht Proxy for service offshoring (normalizing by the total purchases of intermediate inputs in each industry, I ) SOS ht = MS ht I ht

Offshoring indicators Table 3 - Descriptive Statistics on the Offshoring Indicators a) Manufacturing Mean St. dev 1998 2002 change % SOS 1.50 1.527 1.51 1.53 0.02 SOS_FI 0.29 0.271 0.30 0.32 0.01 SOS_CI 0.31 0.801 0.28 0.30 0.02 SOS_RD 0.10 0.107 0.11 0.10-0.01 SOS_BS 0.80 0.518 0.81 0.81 0.00 MOS 26.30 11.572 24.65 26.09 1.44 b) Services Mean St. dev 1998 2002 change % SOS 1.90 1.437 2.09 1.85-0.23 SOS_FI 0.46 0.309 0.53 0.50-0.03 SOS_CI 0.19 0.146 0.18 0.18 0.00 SOS_RD 0.03 0.033 0.04 0.03-0.01 SOS_BS 1.21 0.989 1.34 1.14-0.20 MOS 2.84 0.967 2.93 2.66-0.26 SOS: service offshoring, aggregate; SOS_FI: Finance and insurance; SOS_CI: computer and information; SOS_RD: R&D; SOS_BS: business services; MOS: Material offshoring. Source: ISTAT.

Empirical model where: ln w ijht = α ij + α t + β 1 Γ ht + θ Θ it + ω Ω jt + λ Λ ht + ε ijht Γ ht = service offshoring

Empirical model ln w ijht = α ij + α t + β 1 Γ ht + θ Θ it + ω Ω jt + λ Λ ht + ε ijht where: Γ ht = service offshoring Θ it = individual characteristics

Empirical model ln w ijht = α ij + α t + β 1 Γ ht + θ Θ it + ω Ω jt + λ Λ ht + ε ijht where: Γ ht = service offshoring Θ it = individual characteristics Ω jt =firm characteristics

Empirical model ln w ijht = α ij + α t + β 1 Γ ht + θ Θ it + ω Ω jt + λ Λ ht + ε ijht where: Γ ht = service offshoring Θ it = individual characteristics Ω jt =firm characteristics Λ ht = industry characteristics

Results: Service Offshoring and workers wages Benchmark Individual Charact. Firm Charact. Material Offsh. (1) (2) (3) (4) SOS -0.042-0.044-0.043-0.022 [0.031] [0.029] [0.029] [0.029] age 0.085*** 0.084*** 0.085*** [0.004] [0.004] [0.004] age2-0.001*** -0.000*** -0.000*** [0.000] [0.000] [0.000] Occup: Managers -0.126** -0.126** -0.125** [0.053] [0.053] [0.053] Occup: Blue coll. -0.165** -0.165** -0.164** [0.060] [0.060] [0.060] Occup: Apprentices -0.238*** -0.239*** -0.239*** [0.052] [0.053] [0.053] Occup: Others -0.041-0.037-0.036 [0.085] [0.083] [0.083] Employees 0.005 0.004 [0.004] [0.005] MOS -0.002** [0.001] Observations 497.141 497.141 496.024 496.024 R-squared 0.070 0.075 0.075 0.075 Groups 208.814 208.814 208.249 208.249 The dependent variable is log daily wages. All specifications control for worker-firm and year fixed effects. Standard errors reported in brackets are corrected for clustering within industry. ***, ** and * denote significance at the 1, 5 and 10 percent level, respectively.

Results: Service Offshoring and workers wages Industry Charact. Openness Import Penetration Exports & Imports (5) (6) (7) (8) SOS -0.065-0.052-0.061-0.046 [0.040] [0.038] [0.042] [0.041] Production 0.083 0.084 0.096 0.123 [0.167] [0.137] [0.150] [0.136] Full-time equivalent 0.047-0.037-0.024-0.075 [0.135] [0.146] [0.134] [0.146] Capital intensity -0.024*** -0.024*** -0.022*** -0.023*** [0.006] [0.007] [0.006] [0.007] Material intensity -0.106-0.118-0.141-0.135 [0.115] [0.113] [0.120] [0.121] Openness -0.028** [0.011] Import penetration -0.031*** [0.010] Exports -0.022* [0.011] Imports -0.026*** [0.008] Observations 417.016 417.016 417.016 417.016 R-squared 0.079 0.079 0.079 0.079 Groups 176.335 176.335 176.335 176.335 The dependent variable is log daily wages. All specifications control for worker-firm and year fixed effects. Standard errors reported in brackets are corrected for clustering within industry. ***, ** and * denote significance at the 1, 5 and 10 percent level, respectively.

Results: Service Offshoring and skill premium Benchmark Individual Charact. Firm Charact. Material Offsh. Industry Charact. Openness Import Exports & Penetration Imports (1) (2) (3) (4) (5) (6) (7) (8) SOS -0.031-0.048-0.047-0.026-0.069-0.056-0.065-0.050 [0.028] [0.030] [0.030] [0.030] [0.041] [0.039] [0.043] [0.041] SOS wc -0.025*** 0.010 0.010 0.009 0.014* 0.014* 0.013* 0.013* [0.007] [0.008] [0.008] [0.008] [0.007] [0.007] [0.006] [0.006] Observations 497,141 497,141 496,024 496,024 417,016 417,016 417,016 417,016 R-squared 0.071 0.075 0.075 0.075 0.079 0.079 0.079 0.079 Number of groups 208,814 208,814 208,249 208,249 176,335 176,335 176,335 176,335 The dependent variable is log daily wages. All specifications control for worker-firm and year fixed effects. Standard errors reported in round brackets are corrected for clustering within industry. ***, ** and * denote significance at the 1, 5 and 10 percent level, respectively.

Results: Offshoring of individual services and wages Benchmark Individual Charact. Firm Charact. Material Offsh. Industry Charact. Openness Import Exports & Penetration Imports (1) (2) (3) (4) (5) (6) (7) (8) SOS_FI 0.017 0.023 0.022 0.005-0.061-0.040-0.061-0.042 [0.066] [0.053] [0.052] [0.047] [0.074] [0.074] [0.075] [0.074] SOS_RD 0.041 0.045 0.053 0.056-0.031-0.058-0.037-0.068 [0.113] [0.100] [0.100] [0.087] [0.086] [0.098] [0.093] [0.101] SOS_CI 0.026 0.036* 0.036* 0.094*** 0.007 0.008 0.006 0.007 [0.020] [0.020] [0.019] [0.027] [0.028] [0.028] [0.026] [0.029] SOS_BS -0.133-0.150* -0.148* -0.112-0.257** -0.233** -0.254** -0.220** [0.078] [0.075] [0.074] [0.069] [0.085] [0.080] [0.087] [0.080] Observations 497,141 497,141 496,024 496,024 417,016 417,016 417,016 417,016 R-squared 0.071 0.075 0.076 0.076 0.079 0.079 0.079 0.079 Number of groups 208,814 208,814 208,249 208,249 176,335 176,335 176,335 176,335 The dependent variable is log daily wages. All specifications control for worker-firm and year fixed effects. Standard errors reported in round brackets are corrected for clustering within industry. ***, ** and * denote significance at the 1, 5 and 10 percent level, respectively.

Conclusion Service offshoring does not cause significant reductions in workers wages

Conclusion Service offshoring does not cause significant reductions in workers wages Service offshoring may contribute to widening the wage gap btw. more and less skilled employees (but small effect)

Conclusion Service offshoring does not cause significant reductions in workers wages Service offshoring may contribute to widening the wage gap btw. more and less skilled employees (but small effect) Offshoring of business services exerts negative effects on wages, while offshoring of other services has virtually no impact. Implications: