Location Choices of the Pharmaceutical Industry in Europe after 1992

1
Location Choices of the Pharmaceutical Industry
in Europe after 1992

• Prof. Frances P. Ruane
• The Economic and Social Research Institute,
  Ireland and The Institute for International
  Integration Studies, Trinity College Dublin,
  Ireland
• Xiaoheng Zhang
• The Institute for International Integration
  Studies and the Department of Economics, Trinity
  College Dublin, Ireland

2
Context

• The Single Market Programme (1st, January, 1993)
  removed the non-tariff barriers between EU Member
  States to allow free movement of goods, capital,
  people and services.
• Multinationals rationalize their production by
  consolidating production facilities within a
  country or across countries to fully utilize
  economies of scale.
• Pharmaceuticals become a focus because it is an
  important industry to the EU economy and European
  people.
• We expect its significant response to the Single
  Market because this industry is able to benefit a
  lot from rationlization due to high increasing
  returns to scale.

3
Geographic Concentration Trend

• Measure the geographic concentration of
  pharmaceutical production across 14 EU countries
  using Theil Index and Location Gini coefficient
  (1993 to 2002)
• - Data source OECD STructural ANalysis
  (STAN) database
• Pharmaceutical
  production and employment at country level

where is the production in country i
in the country set that under investigation, and
n is the number of countries. Location Gini
coefficient of concentration is defined as the
area between the Lorenz curve and 45 degree line
in a space where , the pharmaceutical
production share of country i in the data set
that under investigation, is cumulated on the
Y-axis and the number of countries cumulated on
the X-axis with equal interval of width 1/N.
Countries are ranked by .
4

• Theil Indices of Geographic Concentration of
  Pharmaceutical Production EU15
• (OECD STAN data, EU 15, exclude Luxembourg)

5

• Location Gini coefficient
• (OECD STAN data, EU 15, exclude Luxembourg)

6
Theoretical explanations of the
agglomeration/dispersion

• New Economic Geography (NEG) theories
• Theories to analyse the spatial
  distribution of the economic activities between
  two or more regions. The subject is increasing
  returns to scale industry.
• Krugman (1991), Venables (1996), Baldwin
  (1997), Baldwin (2002), Puga (1999)
• Two different predictions on the relationship
  between trade costs and agglomeration.

7

• Krugman (1991) Monotonic relationship
  Puga (1999) Bell-shaped curve
• X-axis trades costs level
• Y-axis share of the industry in each of two
  regions

8
Implication to the EU Single Market and the
Pharmaceutical industry

• Dispersion trend in the pharmaceutical industry
  and low trade cost imply that the agglomeration
  process of this industry may be at the left half
  of the Bell-shaped curve high wages and
  congestion in the agglomerated region drive the
  industry to the less agglomerated regions.
• Empirical question
• - What are the determinants of
  pharmaceutical multinationals location choice?
• - Main focuses
• Country level agglomeration
  Corporate tax rate Market size

9

• A Discrete-choice Framework (I)
• Multinationals choose a country from a set of
  alternative countries to expand their production
  or build up new facilities. Selected country is
  supposed to be able to maximize the
  multinationals profit. Profit depends on the
  observable attribute of the alternative
  countries.
• The Conditional Logit Model (CLM) McFadden
  (1974)

10

• The problems with CLM
• - Simple but restrictive assumption on error
  term
• ?The ratio of probabilities of any
  two alternatives being
• chosen is independent on any
  other alternatives. This is
• called Independence from
  Irrelevant Alternatives (IIA).
• ? Individual taste behaves as an
  individual effect ?
• correlation between error
  terms of alternatives ? violation
• of IIA and inconsistent ML
  estimation
• - Not able to accommodate complicated
  individual structure in our
• case several location choices made by
  the same MNE

11

• A discrete-choice framework (II)
• The Mixed Logit Model (MXL)
  Train (2003)
• Rabe-Hesketh et al. (2004)
• - Coefficient follows a normal
  distribution (random effect)
• - Control for MNE parent-Subsidiaries
  hierarchy

12
Data

• Subjects Pharmaceutical MNEs subsidiaries in
  11 out of EU15 countries
• Data source Amadeus data Collection of
  European firms accounts
• Samples High-performance sample 224 existing
  
• pharmaceutical firms
  experiencing
• above-median expansion of
  turnover b/w 1995
• and 2003
• New firms sample 119 firms
  that were
• established after 1993

13
Major Explanatory Variables
14
Empirical Models

• High-performance Sample
• New-firm Sample
• For both CLM and MXL. Only agglomeration
  variables, tax rate and market size are treated
  as random-effect variables.

15
Results High-performance Sample

• Effective tax rate, market size, agglomeration of
  the
• pharmaceutical industry matter.
• Firm heterogeneity shows up through interaction
  terms.
• Hausman test rejects IIA for Germany, Portugal,
  Spain and Sweden if they are excluded.
• CLM and MXL show
• similar results.

16
Results New-firm Sample

• Only distance to Brussels and familiarity matter.
• Firm heterogeneity isnt found.
• Hausman test cannot rejects IIA
• CLM and MXL show
• similar results.

17
Future Improvement

• Endogeneity in estimation of High-performance
  sample
• Petrin and Train (2002) a control
  function approach
• Lewbel (2004) very
  exogenous variable approach
• Adding variables to the models to test the
  assumptions of NEG models
• Krugmans assumption inter-region labour
  mobility ? use skilled pharma workers in
  neighbouring countries to proxy potential labour
  flow
• Venerable/Pugas assumption intra-region
  labour mobility ? use workers in Chemical
  industry in the same country to proxy potential
  intra-region labour flow

18
Conclusions

• Evidence is found to support Puga and Venables
  models of a non-monotonic relationship between
  industrial agglomeration and trade costs.
• The expansion in production at existing plants in
  Europe may contribute to Europe-level geographic
  dispersion of pharmaceutical production.
• The use of the conditional logit model in this
  research is justified by comparing its
  performance with those of the mixed logit models.
  
• Any comments and critiques are welcome!