Konstantīns Beņkovskis (Bank of Latvia) Julia Wörz (Österreichische Nationalbank) 27 April 2012

1. Evaluation of Non-Price
Competitiveness of Exports from the
Central, Eastern and South-Eastern
European Countries in the EU market
Konstantīns Beņkovskis (Bank of Latvia)
Julia Wörz (Österreichische Nationalbank)
27 April 2012

2. Outline
• Drawbacks of traditional REER indicators
• How to assess non-price competitiveness?
o Theoretical framework
o Elasticities of substitution
o Dynamics in price and non-price competitiveness in
CESEE
o Contribution of non-price factors in some product sectors
of Estonia’s exports
• Conclusions

3. Motivation
REER signal losses in price competitiveness – is it the
whole story?
Real effective exchange rate (36 partner countries, 1999=100)
CPI based ULC based
210 220 Bulgaria
Czech
190 200 Republic
Estonia
180
170 Latvia
160 Lithuania
150 Hungary
140
Poland
130
120 Romania
110 Slovenia
100
Slovakia
90 80
2011
2011
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Source: Eurostat
3

4. Motivation
Markets shares signal improving competitiveness
The share of exports in the World trade (2002=100)
250
Latvia
230
Lithuania
210
Estonia
190 Bulgaria
170 Czech Republic
Hungary
150
Poland
130
Romania
110
Slovakia
90 Slovenia
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Q1-Q3*
Source: WTO
4

5. Motivation
REER indicators have list of drawbacks
• Bad approximation for export prices
o Whole economy, no distinction between domestic and external
markets
o Profit martins are ignored
• Structural issues are not captured:
o Differences in export structure are not taken into account
o Need to analyse competitiveness at disaggregated level
• Focusing on price competitiveness
o Some measures are adjusted for quality (e.g. CPI-based)
o However, many other important factors left aside (e.g. taste,
image of brands)
o Need to consider non-price competitiveness issues

6. Goal of the project
Price and non-price competitiveness of CESEE countries
• Evaluate the price and non-price competitiveness of
CESEE countries
– Latvia, Estonia, Lithuania, Poland, Czech Republic,
Hungary, Slovakia, Slovenia, Romania, Bulgaria
• Due to data constraints we are limiting our analysis
to the exports to the EU
o Still analysing the most part of CESEE exports

7. Short literature review
Several papers dealing with quality and variety issues
• Feenstra, R.C.(1994) “New Product Varieties and the Measurement of
International Prices”, American Economic Review, 84(1), pp.157-177.
• Hummels, D. and Klenow, P.J. (2005) “The Variety and Quality of
Nation’s Exports”, American Economic Review, 95(3), pp.704-723.
• Broda, C. and Weinstein, D.E. (2006) “Globalization and the Gains
from Variety”, Quarterly Journal of Economics, 121(2), pp.541-585.
• Benkovskis, K. and Rimgailaite, R. (2011) “The Quality and Variety of
Exports from the New EU Member States”, Economics of Transition,
19(4), 2011, 723-747.
• Benkovskis, K. and Wörz, J. (2011) “How Does Quality Impact on
Import Prices?”, OeNB Working Papers, 175/2011.
• Benkovskis, K. and Wörz, J. (2012) “Evaluation of Non-Price
Competitiveness of Exports from Central, Eastern and South-Eastern
European Countries at the EU market”, Bank of Latvia Working
Papers, 1/2012.

8. How to evaluate non-price
competitiveness?
• We have trade data on a very disaggregated level:
o prices (unit values, euro/kg)
o volumes (kg)
• Why shouldn’t we combine both sources instead of
focusing just on one?
o If real market share improves when relative export price is
increasing, it gives us some clue about non-price factors
• Consistent theoretical framework needed

9. Theoretical framework
Consumer’s utility function
• First-level CES utility function (imports and domestic good)
κ
κ −1 κ −1
  κ −1

U t =  Dt κ
+ Mt κ  ; κ >1

 
• Second-level CES utility function (different imported goods)
γ
γ −1 γ −1
 
M t =  ∑ M gt
γ 
; γ >1
 g∈G  elasticity of substitution
set of goods   between products
• Third-level CES utility function (different varieties of a good)
σg
σ g −1
 1
 σ g −1
M gt =  ∑ d gct m gct
σg σg 
; σg >1
 c∈C  elasticity of substitution
  between varieties
set of countries
quality or taste parameter

10. Theoretical framework
Minimum unit-cost function
• After solving the utility maximization problem
1
 1−σ g 
1−σ g
φ gt =  ∑ d gct p gct 
 c∈C 
o minimum unit-cost depend on price, quality or taste
parameter and set of partner countries (variety)
• The exact import price index for good g is defined
as:
φ gt
Pg =
φ gt −1

11. Theoretical framework
Relative price on a single market
• Our goal, however, is to evaluate quality-adjusted relative
export price index
o We can interpret xgct as country’s c exports of a product g
o We propose to define changes of relative export price as follows
(p p gkt −1 )(d gkt d gkt −1 )
1
φ k
φk
gt −1
1−σ g
RXPgkt = =
gt gkt
−k −k − −
φ gt φgt −1 φ gtk φ gtk−1
where
• φgtk – minimum unit-cost of good g in case it is exported only by
country k
• φgt-k – minimum unit-cost of good g in case it is exported by all
countries except k

12. Theoretical framework
Change of a relative price on a single market
• Relative price of a good g imported from country k relative to
other origins:
−k
−k 1 wgct
wgct
 p gkt p gct −1   λ− k  1−σ g  d gkt d gct −1 1−σ g
RXPgct = ∏    gt  ∏k  d d 
 
c∈C g k  p gct p gkt −1 
 λ− k   
−
 gt −1  c∈C g  gct
−
gkt −1 
where
o Cg-k – set of countries exporting to a particular market in both periods,
excluding country k
o w-kgct – Sato-Vartia weights of exporters, excluding county k
o ∑p −
gct xgct ∑p −
x
gct −1 gct −1
c∈C g k −k c∈C g k
−k
λ = λ =
∑ pgct xgct ∑p
gt gt −1
x
gct −1 gct −1
− −
c∈C gtk c∈C gtk−1

13. Theoretical framework
Change of a relative price in a single market
• Relative price of a good g imported from country k relative to
other origins:
−k
−k 1 wgct
wgct
 p gkt p gct −1   λ− k  1−σ g  d gkt d gct −1 1−σ g
RXPgct = ∏    gt  ∏k  d d 
   λ− k   
c∈C g k  p gct p gkt −1 
−
 gt −1  c∈C g  gct
−
gkt −1 
1 2 3
1. Traditional relative price index – increase denotes worsening price
competitiveness
2. Adjustment for changes in monopoly power of exporters. If set of
partner countries is increasing, relative price index increase as well
3. Adjustment for changes in quality or taste. Rise in relative quality or
taste decrease relative price index and improve competitiveness

14. Theoretical framework
How to estimate quality/taste parameter?
• After solving utility maximization problem:
relative prices (UVX) relative quantities (kg)
1  d gct   p gct  1  x gct 
ln  = ln + ln 
σ g  d gkt



p
 gkt
 σ
 g
x
 gkt


benchmark country
• Relative quality or taste depends on relative prices
and relative volumes of sales
• It also depends on elasticity of substitution
o relative quantities are not important for perfect competition

15. Theoretical framework
Aggregated relative export price
• Relative price indices on a particular market (RXP(i)gkt) should
now be aggregated by products (g) and by export markets (i)
• Weights from exporter side should be used
RXPkt = ∏∏ RXP(i )gkt
igt W
i∈I g∈G
where
o RXPkt – aggregated relative export price index
o Wigt is weight of a product g exported to country i in total exports to
country k

16. Estimation of elasticities
System of demand and supply equations
• We need to estimate elasticities of substitution
• Elasticity of substitution between varieties estimated from the
system
o Relative demand equation:
∆ ln s gct ∆ ln p gct
= −(σ g − 1) + ε gct ; ε gct = ∆ ln d gct
∆ ln s gkt ∆ ln p gkt
o Relative supply equation:
∆ ln p gct ω g ∆ ln s gct
= + δ gct
∆ ln p gkt 1 + ω g ∆ ln s gkt
• Absence of exogenous variables to identify the system and
estimate elasticities

17. Estimation of elasticities
Transformation of the system
• In order to take advantage of the independence of ε gct an
δ gct , these two equations are multiplied together to obtain
(Leamer’s, 1981, approach):
2 2
 ∆ ln p gct   ∆ ln s gct   ∆ ln p gct  ∆ ln s gct 
  = θ1   + θ2    + u gct
 ∆ ln p   ∆ ln s   ∆ ln p  ∆ ln s 
 gkt   gkt   gkt  gkt 
ωg 1 − ω g (σ g − 2 )
θ1 = θ2 = u gct = ε gctδ gct
(1 + ω g )(σ g − 1) ; (1 + ω )(σ
g g − 1)
;
• Relative price x market shares are correlated with error term,
estimates will be biased
• However, we can obtain consistent estimates by exploiting the
panel nature of the data

18. Estimation of elasticities
GMM estimates
• Broda and Weinstein (2006) argue that one needs to define a
set of moment conditions for each good g by using the
independence of unobserved demand and supply disturbances
for each country over time:
G(β g ) = Et (u gct (β g )) = 0 ∀c
β g = (σ g , ω g )
• For each good g the following GMM estimator is obtained
β g = arg min G * (β g )′WG* (β g )
ˆ
β ∈B
o solved as constrained minimization problem. B is a set of
economically feasible values of β (σg>1, ωg≥0)

19. Estimation of elasticities
Results for big EU countries
Distribution of elasticities of
Median Median substitution
1200
elasticity mark-up
Germany
Germany 6.19 19.3% 1000
France
France 5.39 22.8% 800 UK
Italy
Italy 5.76 21.0% 600
UK 4.91 25.6% 400
… … …
200
0
121.5 - 148.4
221.4 - 270.4
403.4 - 492.7
735.1 - 897.8
1.0 - 1.2
1.8 - 2.2
3.3 - 4.1
6.0 - 7.4
11.0 - 13.5
20.1 - 24.5
36.6 - 44.7
66.7 - 81.5

20. Database and coverage
Eurostat Comext data
• Eurostat Comext
o Import data for all 27 EU countries
o 8-digit CN classification level
• approx. 10 000 products
o 1999 to 2010, annual data
o 50 main partner countries
• All EU countries, US, Japan, China, India, Brazil,
Canada, Russia etc.
• Therefore, we are assessing competitiveness of
CESEE countries on EU market
o Still analysing the most part of CESEE exports

21. Relative export price indices
Baltic countries and Bulgaria
Latvia Estonia
140 140
130 130
120 120
110 110
100 100
90 90
80 80
70 70
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Conventional Adjusted by non-price factors Conventional Adjusted by non-price factors
Lithuania Bulgaria
140 140
130 130
120 120
110 110
100 100
90 90
80 80
70 70
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Conventional Adjusted by non-price factors Conventional Adjusted by non-price factors

22. Relative export price indices
Vyshegrad group countries
Poland Czech Republic
140 140
130 130
120 120
110 110
100 100
90 90
80 80
70 70
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Conventional Adjusted by non-price factors Conventional Adjusted by non-price factors
Slovakia Hungary
140 140
130 130
120 120
110 110
100 100
90 90
80 80
70 70
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Conventional Adjusted by non-price factors Conventional Adjusted by non-price factors

23. Relative export price indices
Romania and Slovenia
Romania Slovenia
140 140
130 130
120 120
110 110
100 100
90 90
80 80
70 70
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Conventional Adjusted by non-price factors Conventional Adjusted by non-price factors

24. Relative quality/taste of Estonia’s exports
By main export sectors
Cumulated contribution of relative quality to export competitiveness (1999=100)
220 340
200 300
180 260
160 220
140 180
120 140
100 100
80 60
60 20
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Machinery and mechanical appliances Wood and wood products
Base metals and articles thereof Prepared foodstuffs
Chemical products Mineral products (RHS) 24

25. Relative quality/taste of Estonia’s exports
By main export markets
Cumulated contribution of relative quality to export competitiveness (1999=100)
250 600
220 500
190 400
160 300
130 200
100 100
70 0
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Finland Sweden Latvia
Lithuania Denmark Germany (RHS) 25

26. Conclusions
Quality/taste of CESEE exports is increasing
• The traditional competitiveness measures based on
unit values show that CESEE export prices increased
faster than export prices of competitors
o Is it creating a problem for export competitiveness?
• Our analysis indicates that it was driven by faster
increase in quality/taste of CESEE exports
o In fact, aggregate competitiveness (including price and
non-price factors) of CESEE even improved

27. Further plans
Needs for improvement in methodology, other database
• No effect on relative price index from changes in set
of export products/markets
o Gains from diversification?
o Theoretical framework should be more developed for
supply side
• separate taste from quality?
• Due to data constraint we analyse only
competitiveness on the EU market
o Competitiveness on the World market
o UN Comtrade database