The Impact of Offshoring on Home Country’s Employment

Forte, Rosa; Ribeiro, Rúben

doi:10.1590/0101-41614945rfr

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Artigo de Pesquisa • Estud. Econ. 49 (4) • Oct-Dec 2019 • https://doi.org/10.1590/0101-41614945rfr copy

The Impact of Offshoring on Home Country’s Employment

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Although not a recent phenomenon, offshoring has assumed increasing importance in terms of multinational enterprises’ activities, often being the subject of discussion at the political level, especially in more economically developed countries, which tend to suggest that this phenomenon underlies the poor performance of job creation in these economies, contributing to the relocation of jobs. Despite the increasingly numerous and comprehensive studies, findings insist on presenting rather different ideas concerning the effects on home countries’ employment. Therefore, taking into account the lack of relevant work in this area focused on the Portuguese reality, it is pertinent to bridge this gap, positively contributing to the enrichment of the existing literature and to a better understanding of the effects of offshoring on employment in Portugal. Based on a sample of 14 sectors of the manufacturing industry during the 1995-2009 period, our results suggest that offshoring has a positive but small impact on home country’s employment in the Portuguese case. This result may indicate that due to higher sales induced by productivity gains from offshoring, this contributes to the creation of a greater number of jobs than those who are relocated abroad.

Keywords
Offshoring; International sourcing; Outsourcing; FDI; Employment

Author (year)	Period	Sample / Country	Dependent Variable	Proxies of offshoring	Effects of offshoring on labour demand
Feenstra and Hanson (1996)Feenstra, R. C., and Hanson, G. H. 1996. “Globalization, Outsourcing, and Wage Inequality”. American Economic Review 86 (2): 240-245.	1972- 1992	435 industries / US		Share of imported intermediate inputs in the total purchases of non-energy materials	Positive effect on the demand for skilled labour
Strauss-Kahn (2004)Strauss-Kahn, V. 2004. “The Role of Globalization in the Within-Industry Shift Away from Unskilled Workers in France”. Challenges to Globalization: Analyzing the Economics (pp. 209-233). Chicago and London: University of Chicago Press.	1977- 1993	50 manufacturing industries / France	Share of unskilled workers in industry	Share of imported inputs embodied in production	Negative effect in demand for unskilled labour
Amiti and Wei (2005)Amiti, M., and Wei, S.-J. 2005. “Fear of service outsourcing: is it justified?” Economic Policy 20 (42): 307-347.	1995- 2001	69 manufacturing industries and 9 from services / UK	Employment (thousands)	Share of imported intermediate inputs in the total purchases of non-energy materials; Broad offshoring.	There is no negative effect of offshoring on the growth of employment
Groshen et al. (2005)Groshen, E. L., Hobijn, B., and McConnell, M. M. 2005. “U.S. Jobs Gained and Lost through Trade: A Net Measure”. Current Issues in Economics and Finance 11 (8): 1-7.	1997- 2003	U.S.	-	-	The impact of trade on aggregate US employment is negligible
Geishecker (2006)Geishecker, I. 2006. “Does Outsourcing to Central and Eastern Europe Really Threaten Manual Workers’ Jobs in Germany?” World Economy 29 (5): 559-83.	1991- 2000	23 sectors from manufacturing industry / Germany	The cost share of low-skilled labour (composite measure based on relative employment and relative wages)	Share of intermediate goods imported on total production of the industry - narrow/broad)	Offshoring affects the demand for unskilled labour, benefiting the skill upgrading in the labour market
Hijzen and Swaim (2007)Hijzen, A., and Swaim, P. 2007. “Does offshoring reduce industry employment?” National Institute Economic Review 201 (1): 86-96.	1995- 2000	17 OECD high income countries	Employment measured by total persons engaged	Share of intermediate goods imported on the value added of the industry - narrow and broad.	No effect or a slightly positive effect on total sectoral employment data
*Cadarso et al.* (2008)**Cadarso, M. Á., Gómez, N., López, L. A., and Tobarra, M. Á. 2008. “The EU enlargement and the impact of outsourcing on industrial employment in Spain, 1993-2003”. Structural Change and Economic Dynamics 19: 95-108.	1993- 2003	93 manufacturing industries/ Spain	Employment measured by thousands of yearly worked hours per sector	Share of intermediate goods imported on total production of the industry; Narrow Offshoring;	Negative effect on employment in the home country
Liu and Nunnenkamp (2011)Liu, W.-H., and Nunnenkamp, P. 2011. “Domestic Repercussions of Different Types of FDI: Firm-Level Evidence for Taiwanese Manufacturing”. World Development 39 (5): 808-823	1996	1,770 manufacturing companies / Taiwan	Ordinal variable with three potential outcome categories (2 - positive effect; 1 - neutral effect; 0 - negative effect)	Share of overseas employees in overall employees of Taiwanese MNEs	The probability of FDI have negative effects on production and employment increases with the size of FDI
Lo Turco and Maggioni (2012)Lo Turco, A., and Maggioni, D. 2012. “Offshoring to High and Low Income Countries and the Labour Demand. Evidence from Italian Firms”. Review of International Economics 20 (3): 636-653.	2000- 2004	40,479 manufacturing firms / Italy	Number of workers of the firm operating in an industry	Share of imported inputs from high wage countries and low wage countries on the total sales	Negative impact on the conditional labour demand particularly in more traditional sectors
Michel and Rycx (2012)Michel, B., and Rycx, F. 2012. “Does offshoring of materials and business services affect employment? Evidence from a small open economy”. Applied Economics 44 (2): 229-251.	1995-2003	58 manufacturing industries and 35 from services / Belgium	Employment in each industry measured by the number of hours worked per year	Share of intermediate goods imported on total production of the industry; Broad offshoring.	Offshoring does not produce remarkable effects on job destruction

Variables		Proxy	Expected impact on labour demand
Offshoring	Offn	Narrow offshoring (ratio between the imports of intermediate goods by a given industry from the same industry and their value added)	+/-
Offshoring	Offb	Broad offshoring (ratio of imports of intermediate goods by an industry from all other industries and their value added)	+/-
Output	Y	Value added of each industry in constant prices	+
Labour costs	W	Real wage rate per worked hour	-

Variables		Mean	Minimum	Maximum	Std. Deviation
Worked hours (millions)	L	118.232	1.269	499.263	96.984
Wage rate per hour (national currency)	W	9.275	3.428	103.534	9.559
Value added (in million of national currency)	Y	1169.050	7.300	2596.458	635.261
Narrow offshoring (%)	Offn	9.699	0.619	27.888	7.886
Broad offshoring (%)	Offb	15.092	4.426	81.542	17.137

Variables	OLS		Fixed Effects
Variables	Model I - narrow offshoring	Model II - broad offshoring	Model I - narrow offshoring	Model II - broad offshoring
Wages	-1.080^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. (0.042)	-1.001^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. (0.050)	-0.313^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. (0.027)	-0.320^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. (0.028)
Output	0.875^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. (0.077)	0.848^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. (0.098)	0.136 (0.102)	0.135 (0.103)
Offshoring	0.089^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. (0.022)	-0.133^* * p<0.1; (0.079)	0.030 (0.108)	0.053 (0.111)
Crisis	-0.062 (0.053)	-0.056 (0.050)	-0.067^* * p<0.1; (0.034)	-0.068^* * p<0.1; (0.033)
R-squared	0.945	0.944
Test F			104.06^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms.	85.97^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms.
Observations	210	210	210	210

Variable	OLS		Fixed Effects		Difference GMM		System GMM
Variable	Model I narrow offshoring	Model II broad offshoring	Model I narrow offshoring	Model II broad offshoring	Model I narrow offshoring	Model II broad offshoring	Model I narrow offshoring	Model II broad offshoring
L1.Emp	0.879^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.080)	0.885^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.076)	0.680^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.061)	0.681^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.065)	0.758^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.089)	0.771^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.093)	0.876^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.010)	0.892^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.019)
Wages	-0.126 (0.092)	-0.124 (0.086)	-0.158^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.011)	-0.156^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.009)	-0.117^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.035)	-0.117^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.031)	-0.106^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.030)	-0.103^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.031)
Output	0.115 (0.071)	0.119^* * p<0.1; (0.072)	0.234^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.045)	0.230^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.049)	0.011 (0.038)	-0.005 (0.037)	0.136^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.024)	0.131^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.023)
Offshoring	0.002 (0.007)	0.016^ p<0.05; (0.008)	-0.034 (0.027)	-0.019 (0.046)	0.032 (0.025)	0.073^* * p<0.1; (0.036)	-0.007 (0.015)	0.028 (0.028)
Crisis	-0.027^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.008)	-0.027^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.009)	-0.037^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.007)	-0.036^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.007)	-0.029^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.003)	-0.032^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.004)	-0.028^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.009)	-0.028^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments. (0.010)
R-Squared	0.997	0.997
F-Satistic			682.17^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments.	1383.83^* ***** p<0.01; Standard errors in parentheses; All variables, except Crisis, are in logarithms. GMM-DIF (one step) using Lt-2, Yt-2 and Wt-1 as instruments.
Groups/Instruments					14/17	14/17	14/34	14/34
Sargan test (Sarganp)					22.62 (0.031)	21.93 (0.038)	83.74 (0.000)	82.89 (0.000)
Hansen test (Hansenp)					13.15 (0.358)	12.33 (0.419)	11.56 (0.997)	11.50 (0.998)
Observations	196	196	196	196	182	182	196	196

Sector	Code	Employment (Worked hours)	Value Added	Wages	Narrow offshoring	Broad Offshoring
Food, beverages and tobacco	15t16	207.708	1944.605	5.279	0.017	0.110
Textiles and textile	17t18	409.629	2321.384	4.459	0.115	0.054
Leather, leather and footwear	19	114.257	597.165	3.633	0.115	0.073
Wood and of wood and cork	20	92.657	649.136	5.688	0.047	0.083
Pulp, paper, printing and publishing	21t22	90.140	1478.050	9.023	0.076	0.063
Coke, refined petroleum and nuclear fuel	23	2.159	86.952	30.024	0.013	0.740
Chemicals and chemical	24	42.290	1069.204	13.208	0.165	0.057
Rubber and plastics	25	45.888	580.005	7.408	0.034	0.212
Other non-metallic mineral	26	123.399	1730.269	7.826	0.018	0.089
Basic metals and fabricated metal	27t28	170.308	1586.211	6.501	0.213	0.050
Machinery, Nec	29	82.001	769.005	6.839	0.086	0.158
Electrical and optical equipment	30t33	85.618	1586.738	13.169	0.224	0.123
Transport equipment	34t35	70.486	1345.816	12.790	0.220	0.141
Manufacturing nec; recycling	36t37	118.701	622.162	3.999	0.017	0.158
Total		118.232	1169.05	9.275	0.097	0.151

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