Competition and Inflation in CESEE: A Sectoral Analysis

1. Competition and Inflation in CESEE: A Sectoral Analysis* Reiner Martin (ECB) Julia Wörz (OeNB) Dubrovnik, June 2011 *All views expressed are those of the author and do not necessarily represent the opinions of, and should not be attributed to, the European Central Bank or Oesterreichische Nationalbank.

2. Outline • Introduction • Descriptive Analysis • Empirical Analysis • Conclusions

3. Introduction • Focus of existing work on competition in CESEE tends to be on competition policy (often with a legal focus)… • …or on the link between competition and (sectoral or economy-wide) growth. • There are only few studies looking at • (1) country- / sector-specific differences in competition and • (2) the impact of competition on inflation. • There is no cross-country study looking at the link between competition and inflation in CESEE countries.

4. Introduction • Analysis of competition based on firm-level Amadeus database • Database has obvious caveats (but robustness checks with employment data suggest reasonably good coverage in most countries / sectors). • Data covers the period 1999 – 2007 (excluding the crisis period) • Choice of countries and sectors determined by data availability and comparability with HICP components

5. Introduction • Study covers the 10 CESEE EU countries and Croatia. • We look at 20 sectors in 4 groups: • 3 manufacturing sectors • 7 wholesale trade sectors • 7 retail trade sectors • 3 consumer services • Some sectors (e.g. textiles, food & beverages) can be followed through the production chain.

6. Descriptive Analysis • Literature suggests various potentially suitable indicators for competition. ‘Profit’ and competition indicators frequently used. • Choice of indicators in the paper restricted by data availability in Amadeus. • Return on assets (RoA) selected as ‘main’ indicator for empirical analysis. • Sales concentration as additional indicator for descriptive analysis. • Recent competition studies prefer profit over concentration measures.

7. Descriptive Analysis • Return on Assets: • Profit and Loss before taxes over total assets (fixed and current) in % • Herfindahl index of sales concentration: • where , aj…sales of firm j • Higher level  generally assumed to imply less competition

8. Descriptive Analysis • The economic interpretation of indicators can be very difficult! • Return on assets: • A priori: high RoA  less intense competition • But: low or negative RoA may indicate predatory behavior of (some) market participants • ‘Normal’ RoAs depend strongly on industry characteristics • Concentration: • A priori: low sales concentration  strong competition • But: aggressive firm behavior may drive out less efficient firms and increase concentration

9. Concentration index + A priori unclear (competition likely to be relatively strong) Competition ↓ Return on assets - 0 + A priori unclear (competition likely to be relatively weak) Competition ↑ - Descriptive Analysis

10. Descriptive Analysis • Distribution of RoA fairly concentrated across countries • Estonia and Slovenia may be seen as exceptions • Some sector-specific outliers

11. Descriptive Analysis • Variation more pronounced across sectors than across countries • A number of sectors appear to be outliers

12. Descriptive Analysis • Trend increase in returns on assets over time (related to catching-up?) • Strongest increase in wholesale and retail trade • More moderate rise in manufacturing • Consumer services in between other sectors

13. Descriptive Analysis • Sales concentration on a downward trend • Consumer services characterised by highest levels and strongest decline in concentration • Developments in other sectors much less pronounced.

14. Descriptive Analysis

15. Descriptive Analysis • On sectoral basis no clear pattern regarding the changes over time. • Around half of the sectors are in the ‘twilight’ quadrants. • Differences across sectors more pronounced than across countries.

16. Empirical Analysis • Intensity of competition is expected to impact price developments over shorter horizons. • Simple empirical approach to test this hypothesis is including competition variable (RoA) in sectoral inflation estimations. • Other variables include money growth, output gap, lagged inflation, oil prices and sector-specific cost variables. • Period and country coverage in line with descriptive analysis above (11 countries, 20 sectors).

17. Empirical Analysis

18. Empirical Analysis

19. Empirical Analysis • RoA significant determinant for inflation in 8 (7) out of 20 sectors. • Except for the retail (and wholesale) part of the textiles & clothing sector the coefficients have the expected sign. • Significant sectors belong to all sector ‘types’ - but more so wholesale sectors • The sectors ‘food & beverages retail’ as well as ‘housing & utilities’ warrant particular attention from an inflation perspective.

20. Conclusions • Research on the intensity of competition in the CESEE region still rather limited – largely due to lack of data. • This limits also the scope for analyses of the link between competition and price developments. • Results suggest, however, that the link matters – notably at a time of resurging inflation in the region. • Besides refining the approach pursued in this paper, sector-specific studies may be a good way forward.

21. Thank you for your attention!

22. Descriptive Analysis

23. Details of sectoral breakdown