Plan.be Does Offshoring of Materials and Business Services Affect Employment? Evidence for a small open economy Bernhard Michel (FPB.

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Does Offshoring of Materials and Business Services Affect Employment?

Evidence for a small open economy

Bernhard Michel (FPB and ULB) and François Rycx (ULB)

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Outline

Relevant empirical literature Belgian data on offshoring Estimation framework Results Conclusion

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Relevant empirical literature – Offshoring and the labour market

Pioneering papers: Feenstra & Hanson (1996, 1999)standard measurement of offshoring, US data, relative wages

Follow-up papers: Strauss-Kahn (2002), Falk & Koebel (2002), Hijzen et al. (2005)European countries, employment of low-skilled workers

Extensions and related papers: Egger & Egger (2003), Amiti & Wei (2005, 2006), Falk & Wolfmayr (2005)low-wage countries, services offshoring, total employment

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Offshoring and employment

Impact on total employment:- jobs lost: those employed in the offshored activity- cheaper inputs

productivity gain in downstream production stages further reduction in employment, or expansion of production and employment

- caveats: terms of trade, relative factor demands

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Relevant empirical literature – Offshoring and total employment

Seven papers: Amiti & Wei (2005, 2006), Cadarso et al. (2008), Falk & Wolfmayr (2005, 2008), OECD (2007a, 2007b)

Labour demand framework augmented by offshoring term Individual country vs. Panel of countries Industry-level data Differences: calculation of the offshoring intensity, measure of

employment (FTE or hours), controls, estimation methods,… Different results…

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Relevant empirical literature – comparison of results

Manufacturing industries Service industries

Materials offshoring

Services offshoring

Materials offshoring

Services offshoring

Falk and Wolfmayr (2005)

ns/- x x x

Falk and Wolfmayr (2008)

ns ns x ns/-

OECD (2007a)

- - x x

OECD (2007b)

-/ns -/ns x x

Amiti and Wei (2005)

ns + - -

Amiti and Wei (2006)

ns/+ ns/- x x

Cadarso et al. (2008)

ns/- x x x

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Measuring offshoring

Standard measure (Feenstra & Hanson, 1996): oti = ∑jIIIij / Yi

Mostly computed proportionally using data from Input-Output tables and trade statistics

Split into materials and business services offshoring omi and osi

Split III by country of origin (Egger & Egger, 2003) Narrow offshoring vs Broad offshoring (Feenstra & Hanson, 1999)

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Measuring offshoring

For Belgium:- supply and use tables, 1995-2003- NA vintage 2007- constant prices of 2000- use tables of imports (imported intermediates)- offshoring to different regions (oecd, ceec, asia)

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Total 12.96% -0.2% 2.02% 9.2%

OECD-22 11.33% -0.7% 1.92% 9.0%

CEEC 0.50% 10.8% 0.03% 19.3%

SEAsia 0.50% 4.8% 0.02% 8.1%

Source: own calculations

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Total 12.96% -0.2% 2.02% 9.2%

OECD-22 11.33% -0.7% 1.92% 9.0%

CEEC 0.50% 10.8% 0.03% 19.3%

SEAsia 0.50% 4.8% 0.02% 8.1%

Source: own calculations

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Total 12.96% -0.2% 2.02% 9.2%

OECD-22 11.33% -0.7% 1.92% 9.0%

CEEC 0.50% 10.8% 0.03% 19.3%

SEAsia 0.50% 4.8% 0.02% 8.1%

Source: own calculations

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Total 12.96% -0.2% 2.02% 9.2%

OECD-22 11.33% -0.7% 1.92% 9.0%

CEEC 0.50% 10.8% 0.03% 19.3%

SEAsia 0.50% 4.8% 0.02% 8.1%

Source: own calculations

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Total 12.96% -0.2% 2.02% 9.2%

OECD-22 11.33% -0.7% 1.92% 9.0%

CEEC 0.50% 10.8% 0.03% 19.3%

SEAsia 0.50% 4.8% 0.02% 8.1%

Source: own calculations

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Manufacturing 28.69% -0.5% 1.15% 12.4%

Market services 4.32% 2.7% 2.77% 7.8%

Source: own calculations

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Manufacturing 28.69% -0.5% 1.15% 12.4%

Market services 4.32% 2.7% 2.77% 7.8%

Source: own calculations

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Measuring offshoring – Data for Belgium

  Materials offshoring Services offshoring

  2003 03/95 2003 03/95

Manufacturing 28.69% -0.5% 1.15% 12.4%

Market services 4.32% 2.7% 2.77% 7.8%

Source: own calculations

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Estimation framework

Conditional labour demand in log-linear form:Lit = α + β1 wit + β2 rit + γ Yit

Augment by offshoring variables in logs: omit and osit

Make it testable (time and industry dummies, disturbance term, lags of explanatory variables):

Lit = αt + β1 wit + β2 wit-1 + γ1 Yit + γ2 Yit +

(θ1 omit + θ2 osit + θ3 omit-1 + θ4 osit-1) + εi + uit

Regional splits (oecd, ceec, asia) can also be introduced Estimate (fixed effects) for 58 manufacturing and 35 service

industries

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Results – data used

Dependent variable: employment in hours (employees) Controls:

- wage rate: deflated compensation of employees per hour- value-added

Offshoring (see above) Source: national accounts

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Results – manufacturing sector

Fixed effects estimation, 1995-2003, dependent variable employmentFixed effects estimation, 1995-2003, dependent variable employment

tottot k=oecdk=oecd k=ceeck=ceec k=asiak=asia

ConstantConstant yesyes yesyes yesyes yesyes

ControlsControls okok okok okok okok

omomtt0.0350.035

omomt-1t-1 0.046**0.046**

osostt0.0130.013

osost-1t-1 -0.004-0.004

om_kom_ktt0.0120.012 -0.004-0.004 0.034***0.034***

om_kom_kt-1t-1 0.0250.025 -0.011-0.011 0.0190.019

os_kos_ktt0.0130.013 0.0120.012 0.0130.013

os_kos_kt-1t-1 -0.004-0.004 -0.004-0.004 -0.004-0.004

NN 464464 464464 464464 464464

RR22 0.9340.934 0.9370.937 0.9170.917 0.9230.923

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Results – service sector

Fixed effects estimation, 1995-2003, dependent variable employmentFixed effects estimation, 1995-2003, dependent variable employment

tottot k=oecdk=oecd k=ceeck=ceec k=asiak=asia

ConstantConstant yesyes yesyes yesyes yesyes

ControlsControls okok okok okok okok

omomtt-0.018-0.018

omomt-1t-1 -0.009-0.009

osostt-0.017-0.017

osost-1t-1 0.0010.001

om_kom_ktt-0.018-0.018 0.0280.028 -0.045-0.045

om_kom_kt-1t-1 -0.009-0.009 0.041**0.041** 0.0180.018

os_kos_ktt-0.016-0.016 0.0090.009 -0.004-0.004

os_kos_kt-1t-1 -0.000-0.000 0.0050.005 0.0070.007

NN 280280 280280 280280 280280

RR22 0.8010.801 0.8020.802 0.7760.776 0.8030.803

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Results – summary

Controls:- w: negative significant elasticity- Y: positive significant elasticity

Offshoring variables: almost always not significant, in some cases om has a small positive impact on employment in manufacturing industries

Offshoring does not have a significant impact on total employment in Belgium, the number of jobs lost due to offshoring is small compared to total labour market turnover.

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Robustness tests

Measure offshoring as share in total intermediate inputs instead of output

Apply an industry-level correction for self-employed Estimate unconditional labour demand replacing output in

volume by its price Specify a dynamic model with an autoregressive term and

estimate it using GMM (dif and sys)

The offshoring coefficients remained overwhelmingly non-significant.

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Conclusion

Improved measure for offshoring (data on imported intermediates, coherent constant price dataset)

First estimations for Belgium Estimations for both manufacturing and market service sectors Results: offshoring has no significant impact on total employment

- in line with earlier findings- small job loss compared to overall labour market turnover

Further research:- impact of offshoring on productivity- impact on employment of low-skilled workers