Linking Motivation and Effect: The Nature of Inward FDI and its Impact on Productivity Growth in the

1
Linking Motivation and Effect The Nature of
Inward FDI andits Impact on Productivity Growth
in the UK.

• NIGEL DRIFFIELD
• MICHAEL HENRY
• JIM LOVE
• Economics Strategy Group, Aston Business School

2
Introduction

• There is a large and growing literature on the
  impact of inward foreign direct investment (FDI)
  on host economies.
• Much of this literature is concerned with the
  productivity or spillover effects which may
  arise
• This view fits naturally with the dominant
  theoretical perspective on the determinants of
  FDI (Dunning, Caves etc).

3

• Recently, however, there has been increasing
  theoretical and empirical emphasis on technology
  sourcing rather than technology exploitation as a
  motivation for FDI.
• Linked to analysis of FDI flows (Kogut and
  Chang, 1991 Neven and Siotis, 1996), from
  theoretical work (Fosfuri and Motta 1999 Siotis
  1999).

4
However

• impact of inward FDI is largely divorced from
  that which tries to explain the determinants of
  FDI
• ?Technology and cost differences

5
Contribution

• We develop a taxonomy which relates the
  technological and factor price determinants of
  inward FDI.
• This allows us to distinguish clearly between
  technology sourcing and technology exploiting
  FDI, and to identify that which is linked to
  factor cost differentials.
• We then empirically examine the effects of FDI
  into and out of the United Kingdom on domestic
  (i.e. UK) productivity.

6
Taxonomy of motivations for FDI
7
Interpretation
8
The Effects of FDI

• Evidence suggesting that there are substantial
  (intra-industry) spillover effects running from
  MNEs to domestic firms, Blomström and Kokko
  1998)
• The conclusions of early cross-sectional
  industry-level studies have been questioned on
  econometric grounds (Görg and Strobl 2001).
• micro-level panel data research has led to mixed
  results, (Haskel et al., 2002 Keller and Yeaple,
  2003 Aitken and Harrison, 1999).

9
Methodology

• Standard econometric approach to externalities.
• Haskel et al. (2002), Harris (2002), Harris and
  Robinson (2002), Driffield (2001) and the earlier
  literature summarized in Görg and Strobl (2001).
• Where D represents the 4 categories of FDI
  outlined above

10
Estimation

• All these results IV (2sls) panel estimates
  (usual issues relating to lags, differencing
  etc). 1 step estimates or 2 step estimates (get
  total factor productivity based on factor shares
  etc).
• Data weighted in the usual manner for ARD (by
  share of employment in size band)

11
Internal variables

• Q output
• Skilled (non-manual) labour
• Unskilled (manual) labour
• Materials
• Age
• Also herfindahl, market share.
• All data real and in logs, domestic sector only.

12
Externality terms

• Sectoral level FDI based on 4 quadrants, real and
  in logs (not shares).
• The FDI data are at the two digit SIC level and
  represent the lowest level of aggregation
  possible for ascribing different motives for FDI
  based on RD intensities and unit labour costs.
• These countries collectively accounted for 98 of
  the total overseas direct investment stock in the
  UK.

13
Results
14
Results
15
Results

• 1 (technology sourcing / cheap labour)
• 2 technology sourcing
• 3 technology exploiting / cheap labour
• 4 technology exploiting

• negative
• No effect
• Positive
• Positive

16
Interpretation

• 1. Do not treat FDI as homogenous group
• 2. Results in line with theory
• FDI from technology advantaged regions generates
  spillovers, other does not.
• Technology sourcing FDI has a negative effect on
  productivity
• ? what does this say about FDI and technology?

17
FDI and Technology
18
Interpretation

• Low tech sectors drive overall results FDI into
  low tech sectors has largest effect !
• Policy question Do we want to attract low tech
  FDI?
• Med / high sectors some agglomeration, in line
  with Driffield Love (2005)

19
SUMMARY CONCLUSIONS

• FDI does generate spillovers but you have to know
  where to look.
• Explains why previous research yields such
  diverse results.
• We get very similar results with sectoral level
  data