Abstract
This paper focuses on the role of the efficiency gap in determining whether or not domestic firms benefit from productivity spillovers from FDI. We use establishment level data for the period 1980–1992 for the UK. Given that there is substantial heterogeneity of productivity across sectors we focus on two manufacturing sectors in detail, namely, electronics and engineering. We allow for different effects of FDI on establishments located at different quantiles of the productivity distribution by using conditional quantile regression. Overall, while there is some heterogeneity in results across sectors and quantiles, our findings clearly suggest that the efficiency gap matters for productivity spillover benefits. We find evidence for a u-shaped relationship between productivity growth and FDI interacted with the efficiency gap. We also analyse in some detail the impact of changes in relative efficiency on establishments’ ability to benefit from spillovers.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Keller (2001) also discusses the role of absorptive capacity for successful technology diffusion.
To the best of our knowledge, there has been only one previous application of quantile regression in the literature on productivity spillovers. Dimelis and Louri (2002) apply this technique to analyse spillovers from FDI for a sample of Greek manufacturing firms using cross-sectional data. They do not allow for an impact of domestic firm’s relative efficiency, however. Also, they only analyse the effect of FDI on domestic labour productivity while we look at total factor productivity.
While much of the literature on productivity spillovers has focused on developing countries, the literature on developed countries has grown substantially in the very recent past. In particular, there have been a number of recent studies on the UK (for example, Driffield 2001, Girma et al. 2001, Girma and Wakelin 2001, Haskel et al. 2002). None of the studies analyses the role of the efficiency gap in such detail as done in this paper.
By contrast, Sjöholm (1999) finds that, in cross-sectional data for Indonesian manufacturing firms, productivity spillovers from foreign to domestic firms are larger the larger the technology gap (also defined in terms of differences in labour productivity) between those groups of firms and the higher the degree of competition in the industry.
We are cautious to point out, however, that TFP is of course only a noisy measure of the technological level of the plant, as there may, for instance, be temporary shocks that affect TFP but do not at the same time change a plants technological capability. If anything, this should cause estimated spillover effects to be downward biased.
We utilise a TFP growth rather than levels equation as this purges any establishment specific time invariant effects that impact on TFP in levels.
Nickell (1996) argues that competition can affect total factor productivity growth. We calculate a Herfindahl index based on plant’s market shares in terms of employment shares. To the extent that more concentrated industries indicate less competitive pressure we expect a negative correlation between plant productivity and the Herfindahl index.
Note that we neglect a regional dimension to spillovers and instead assume that spillovers dissipate through the whole of the industry, regardless of location. Girma and Wakelin (2001) focus on regional spillovers from FDI.
Note that, since we define absorptive capacity as a relative concept, i.e., each establishment’s distance from the industry leader, this should not lead to problems if the industry leader is an extreme outlier or changes over time.
It also alleviates concerns that using current levels of TFP would lead to endogeneity problems.
See Buchinski (1998) for an overview of quantile regression models.
We take reassurance from an earlier paper using data based on the ARD by Girma and Wakelin (2001) which compares results from a standard TFP estimation with those obtained using the Olley and Pakes (1996) method. They find that both approaches yield qualitatively similar conclusions concerning the effect of FDI spillovers.
The estimations of Eq. 6 are not reported here to save space. Note that we have a large number of observations even when estimating the equation for each of the 49 four digit sectors; the minimum number of observations is no less than 170.
These are SIC80 industries 33 and 34 (electronics) and 32 and 37 (mechanical and instrument engineering). We refer to the latter as “engineering” throughout the paper.
For example Cantwell and Iammarino (2000) indicate that in semiconductors the share of foreign-owned firms in total patents was over 60% for the UK as a whole, and 75% for South East England in particular.
Note that over the sample period there has been a general decline in the number of manufacturing establishments in the UK (Haskel et al. 2002).
In Appendix B we also report results for regressions including the simple FDI variable without the EG interaction terms. From these regressions, we do not find robust evidence for spillovers. This highlights the importance of allowing for different effects of FDI for establishments with different levels of efficiency gaps, as we have done in our paper.
We use the median (050th quantile) in order to be consistent with the analysis using quantiles.
They are likely to produce output that is not a close substitute to high productivity establishments’ output. As they are operating in the same narrowly defined sector as the multinational they are still able to benefit from spillovers, however.
In all graphs we assume this FDI growth to be 0.1, a figure that is well within the range of actual values for FDI growth in the data. See also Haskel et al. (2002) who report a rise in their FDI variable by 11 percentage points over the period 1973–1992.
References
Aitken BJ, Harrison AE (1999) Do domestic firms benefit from direct foreign investment? Evidence from Venezuela. Am Econ Rev 89:605–618
Baltagi BH, Griffin JM (1997) Pooled estimators versus their heterogeneous counterparts in the context of the dynamic demand for gasoline. J Econom 77:303–327
Barnes M, Martin R (2002) Business data linking: an introduction. Econ Trends 581:34–41
Bartelsman EJ, Doms M (2000) Understanding productivity: lessons from longitudinal microdata. J Econ Lit 38:569–595
Buchinski M (1998) Recent advances in quantile regression models. J Hum Resour 33:88–126
Cantwell J, Iammarino S (2000) Multinational corporations and the location of technological innovation in the UK regions. Reg Stud 34:317–332
Dimelis S, Louri H (2002) Foreign direct investment and efficiency benefits: a conditional quantile analysis. Oxf Econ Pap 54:449–469
Driffield N (2001) The impact on domestic productivity of inward investment in the UK. Manch Sch 69:103–119
Driffield N, Love J (2006) Does the motivation for foreign direct investment affect productivity spillovers to the domestic sector? Applied Economics Quarterly 52:3–27
Findlay R (1978) Relative backwardness, direct foreign investment, and the transfer of technology: a simple dynamic model. Q J Econ 92:1–16
Fosfuri A, Motta M (1999) Multinationals without advantages. Scand J Econ 101:617–630
Girma S, Wakelin K (2001) Regional underdevelopment: is FDI the solution? A semiparametric analysis. CEPR Discussion Paper 2994
Girma S, Greenaway D, Wakelin K (2001) Who benefits from foreign direct investment in the UK? Scott J Polit Econ 48:119–133
Glass A, Saggi K (1998) International technology transfer and the technology gap. J Dev Econ 55:369–398
Görg H, Greenaway D (2004) Much ado about nothing? Do domestic firms really benefit from foreign direct investment? World Bank Res Obs 19:171–197
Görg H, Strobl E (2001) Multinational companies and productivity spillovers: a meta-analysis. Econ J 111:F723–F739
Griffith R, Simpson H (2004) Characteristics of foreign-owned firms in British manufacturing. In: Blundell R, Card D, Freeman R (eds) Creating a premier league economy. Chicago University Press, Chicago
Griffith R, Simpson H, Redding S (2002) Productivity convergence and foreign ownership at the establishment level. IFS Working Paper 02/22, Institute for Fiscal Studies, London
Haskel JE, Pereira SC, Slaughter MJ (2002) Does inward foreign direct investment boost the productivity of domestic firms? CEPR Discussion Paper 3384
Head K (1998) Comment on ‘comparing wages, skills, and productivity between domestically and foreign-owned manufacturing establishments in the United States.’ In: Baldwin R, Lipsey R, Richardson JD (eds) Geography and ownership as bases for economic accounting. Chicago University Press, Chicago, pp 255–258
Keller W (2001) International technology diffusion. CEPR Discussion Paper 3133
Koenker R, Bassett G (1978) Regression quantiles. Econometrica 50:43–61
Kokko A (1994) Technology, market characteristics, and spillovers. J Dev Econ 43:279–293
Kokko A, Tansini R, Zejan MC (1996) Local technological capability and productivity spillovers from FDI in the Uruguayan manufacturing sector. J Dev Stud 32:602–611
Levinsohn J, Petrin A (2003) Estimating production functions using inputs to control for observables. Rev Econ Stud 70:317–341
Nickell SJ (1996) Competition and corporate performance. J Polit Econ 104:724–746
Olley S, Pakes A (1996) The dynamics of productivity in the telecommunications equipment industry. Econometrica 64:1263–1297
Pesaran MH, Smith R (1995) Estimating long-run relationship from dynamic heterogeneous panels. J Econom 68:79–112
Sjöholm F (1999) Technology gap, competition and spillovers from direct foreign investment: evidence from establishment data. J Dev Stud 36:53–73
Acknowledgement
Thanks are due to David Greenaway, Steve Redding, Beata Smarzynska Javorcik, Eric Strobl, Dieter Urban, an anonymous referee and participants at workshops and conferences in Kiel, Oslo, Dublin, and Warwick for helpful comments. This work contains statistical data from ONS which is Crown copyright and reproduced with the permission of the controller of HMSO and Queen’s Printer for Scotland. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. Financial support from the European Commission (Grant nos. HPSE-CT-1999-00017 and SERD-2002-00077) and the Leverhulme Trust (Grant no. F114/BF) is gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Appendices
Appendix A
1.1 Description of the data
The ARD consists of individual establishments’ records that underlies the Annual Census of Production. As Barnes and Martin (2002) provide a very useful introduction to the data set, we only include a brief discussion of some of the features of the data that are relevant to the present work. For each year the ARD consists of two files. What is known as the ‘selected file,’ contains detailed information on a sample of establishments that are sent inquiry forms. The second file comprises the ‘non-selected’ (non-sampled) establishments and only basic information such as employment, location, industry grouping and foreign ownership status is recorded. Some 14,000–19,000 establishments are selected each year, based on a stratified sampling scheme. The scheme tends to vary from year to year, but for the period under consideration establishments with more than 100 employees were always sampled.
In the ARD, an establishment is defined as the smallest unit that is deemed capable of providing information on the Census questionnaire. Thus a ‘parent’ establishment reports for more than one plant (or ‘local unit’ in the parlance of ARD). For selected multi-plant establishments, we only have aggregate values for the constituent plants. Indicative information on the ‘children’ is available in the ‘non-selected’ file.
Like the majority of researchers using the ARD (e.g., Haskel et al. 2002) we use data on multi-plant establishments as they are. In our sample period (1980–1992), about 95% of the establishments in these industries are single-plant firms. In the actual sample we used for the econometric estimation this figure is around 80%. Hence, most of the data used is actually plant level data and we, therefore tend to use the terms plant and establishment interchangeably.
There are, however, two important ways in which we have made use of the local unit information in the non-selected file. The first is in the construction of measures of regional FDI. Foreign presence in a region and sector is defined as the proportion of employment accounted for by foreign multinationals. Simply relying on establishment data could be misleading, as they could report for plants across different regions or sectors. However, by extracting the employment, ownership and industrial affiliation data of the ‘children’ in the ‘non-selected’ file, it was possible to calculate correctly the regional FDI variables. The second way information in the non-selected file was used is in the identification of single location (region) and multiple location establishments.
Appendix B
Rights and permissions
About this article
Cite this article
Girma, S., Görg, H. The Role of the Efficiency Gap for Spillovers from FDI: Evidence from the UK Electronics and Engineering Sectors. Open Econ Rev 18, 215–232 (2007). https://doi.org/10.1007/s11079-007-9031-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11079-007-9031-y