Organisation de Coopération et de Développement Economiques Organisation for Economic Co-operation and Development

New uses of PPP data within the EU

Eurostat

Agenda item n° 6

JOINT WORLD BANK – OECD SEMINAR ON PURCHASING POWER PARITIES

Recent Advances in Methods and Applications

WASHINGTON D.C.

30 January – 2 February 2001 NEW USES OF PPP DATA WITHIN THE EU

John Astin, Head of Price Comparisons Unit, Eurostat.

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SUMMARY

This short paper describes the increasing uses within the European Commission of price microdata collected as part of its regular PPP work. This has led to the opening up of new sources of funding which are expected to lead to benefits for the basic PPP work as well as for the new uses. Given the precarious state of PPP work at the global level, other organisations may find it helpful to consider whether similar “by-products” may extend the scope of PPP work and its potential sources of funding.

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1. For many years, Eurostat has coordinated price surveys required for producing annual PPPs for its multilateral comparison group, now totalling 31 countries. These surveys cover private consumption goods and services, products used in the equipment goods sector, as well as for construction, rents, and public administration. The private consumption surveys have an additional use within the Commission: the calculation of “correction coefficients”, or adjustment factors used to equalise the purchasing power of salaries paid to EC staff serving in different duty stations around the EU.

2. This second use of price microdata has not in general produced any fundamental problems or conflicts of interest, although occasionally this has happened. For example, the products selected for PPP purposes are supposed to be representative of national consumption patterns, whereas those used for correction coefficient purposes should – in principle – be representative of the patterns of consumption of the population of international officials for whom they are designed. Normally this is taken care of by using a different weighting structure; the products themselves are assumed to be the same. But in a few cases, such as international air fares and telephone calls, special products are used for the correction coefficients to reflect international officials’ greater use of international services. As such cases are few and far between, it has not raised any serious problems for the PPP surveys.

3. More recently there have been several new demands for price microdata from within the European Commission.

Price dispersion is a function of many variables, inter alia, the degree of competition amongst producers and retailers or the degree of market integration. The Internal Market Directorate-General (DG) needs to have reliable and timely average prices at the level of individual products to evaluate European market integration by measuring price dispersion of similar products sold throughout the EU and changes over time in price dispersion. Regional price differences are also sought. The Internal Market DG also needs to analyse price differences of products purchased by public authorities in Member States to ensure that the public procurement rules work effectively. The Health and Consumer Protection DG is anxious to obtain evidence by which it can judge if the differences between product prices within the EU are such that they jeopardize consumers' interests – and, of course, to identify the reasons behind these differences.

A common feature of the needs of both of these DGs is that they need information at item level (average prices) and that (part of) the product basket for which the prices are collected should remain the same over several years to allow comparison of price developments over time.

4. The European Commission is also interested in judging the price-convergence effects of the introduction of the euro in 1999. The effects are expected to accelerate from 2002 when the euro currency is introduced and the existing national currencies withdrawn. It is expected that the transparency of price differentials brought about by a single currency will have an effect on competition and lead to a reduction in price levels, particularly in border zones.

5. There is also a considerable public interest in international price comparisons associated with the growth in international travel for leisure, study, business and employment purposes. This demand is reflected in the increasing growth of press articles – often misinformed and ill-judged – concerning international price comparisons.

6. Private consultancy firms are also showing an interest in these data. For example, Dresdner Kleinwort Benson Research are now publishing regular analyses of price convergence within the EU. Another firm, Ing-Barings, are doing work in the same field. (See, for example, their latest publications attached to this paper).

7. As far as PPPs themselves are concerned, the Regional Policy DG has requested the availability of regional PPPs in time for the next round of Structural Fund allocations, due to be made in 2006. Eurostat is about to award an external contract to study the implications of this new demand in terms of methodology and data requirements.

8. It is clear, then, that there is a wide and growing range of new uses of both PPPs and their underlying microdata which poses both threats and opportunities for mainstream PPP work.

9. Let us consider first the requests for detailed microdata on consumer prices. The data collected for PPP purposes is in principle suitable for the analysis of price dispersion. But in practice there are some fundamental problems. For PPPs, the primary object is to calculate PPPs at the level of GDP and its main aggregates. The calculation process produces PPPs also at lower levels of aggregation down to Basic Heading level, but the main attention is focused on PPPs at the GDP level and on their quality. This has important consequences. Because prices are collected for some 3500 items and then aggregated at various stages, from the theoretical point of view it

3 is not necessary to aim at maximum robustness at the product level (average prices) or even at the Basic Heading level (BH parities): in the aggregation process errors at these levels may be assumed to cancel out, and the reliability of the aggregate results should be sufficient. Thus for a single product only a limited number of items are priced. No statistical error estimates can be made as to the quality of the results. The unreliability of detailed average prices is also the reason why Eurostat has been reluctant to publish results or to make them available at a more detailed level.

10. The new uses relating to consumer protection and price convergence, on the other hand, require reliable data at the individual product level. Up till now, it has not been possible to provide this information from the existing PPP database for the reasons mentioned above. With PPP development in its present phase, it would be impossible to demand the participating countries to make large-scale increases in the sample size of price quotations in order to provide more reliable average prices at the detailed product level. To do so would jeopardise the core work on PPPs. Thus the threat. But of course to have a larger and more reliable sample is precisely what is required to improve PPP quality in general. Thus the opportunity! Eurostat cannot yet pretend to have an answer to this problem. But the way ahead may perhaps lie in the exploitation of new sources of price data. A pilot project – jointly funded by client DGs - is currently underway with three large market research companies (AC Nielsen, Taylor Nelson Sofres, and GfK) to determine whether or not barcode scanner databases can be used for extracting data on prices for a wide range of consumer products. The first results of this project are expected soon. But in principle it seems certain that this approach offers a technique – perhaps the only technique – for obtaining average product prices based on very large sample sizes. (“Very large” in this context can mean millions rather than tens of prices). The larger coverage and number of observations should make it possible to identify not only differences in price dispersion betwee member states but also within them, and hence to indicate if price dispersion between member states differs significantly from that within member states.

11. It is conceivable that the result of this pilot project will be that this technique would be acceptable (and affordable) to the client DGs in the Commission, but not to Eurostat (e.g. for reasons of cost). This would be a most unfortunate outcome. If the technique is successful for the microdata purposes, then it should be incumbent on Eurostat (in agreement with the member states) to find a way of using the same data sources for mainstream PPP purposes.

12. Let us consider next the requirement for measures of price convergence over time. Other papers are on the agenda at this seminar on this specific topic, and the author is not therefore intending to say much on this issue. But one thing needs to be unequivocally stated: PPPs are based on snapshots at a point (normally a year) in time. They are not designed for time series linking and comparison. Research papers have shown that that they cannot be so used. Nevertheless, they are used to make comparisons over time, and as producers we have a duty to users to provide guidance. In the author’s view, it is not sufficient to tell users that they should not make temporal comparisons of annual PPP results. We should be producing results which optimise the spatial and temporal aspects of PPPs. PPPs are the only way of assessing price-level convergence over time, and there is a clear and growing demand for such

4 data. We have to react to it, and do so quickly. Not to do so would provide yet another weapon in the hands of the opponents of PPPs.

13. What has Eurostat done in this connection? So far, we have provided microdata to the client DGs concerned: in the case of the Internal Market DG this has resulted in the publication of tables and charts in their bi-annual Single Market Scoreboard (see, for example, Annex A). Secondly, we have recently made a commitment to the European Parliament (following a direct request to the Director- General of Eurostat) to begin publishing by 2002 reports on price convergence in the EU. Thirdly, we are about to award an external contract with the aim of proposing a methodology for optimising the space/time comparability of national PPPs. The contract will also study the scope for exploiting CPI databases for PPP purposes – a topic also covered in another paper on the agenda of this seminar.

14. Finally, the question of regional PPPs. As already mentioned above, Eurostat is about to award an external contract to study the question of how regional PPPs could be produced, and it would be premature to make any firm statements on this at present. But what seems clear is that the production of regional PPPs in the EU (and the soon-to-be-enlarged EU) cannot be based simply on a geographical extension of existing capital-city price surveys. The costs and staff resources required would be prohibitive. Two main lines come to mind. One is the exploitation of barcode scanner databases discussed above: national and international market research companies possess data relating to nationwide transactions, from which regional analyses can be extracted. The other approach would be to use existing CPI databases as a link between the regions and the capital city, limiting the benchmark PPP surveys to capital cities, as at present. This could also offer a better method of extrapolating capital city prices to national averages, currently a weak feature of PPP methodology in the EU. A combination of these two techniques could also be envisaged.

CONCLUSIONS

15. This brief paper has attempted to demonstrate two things. Firstly, the production of PPPs involves the collection of price data which have a high value for purposes unrelated to PPPs. This offers the possibility of obtaining support – both political and financial – from a wholly new group of data users. Care needs to be taken that new uses do not impose unacceptable changes to the methodology required for PPP purposes, but on the other hand there may be minor compromises to be made in exchange for considerable benefits such as larger sample sizes.

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Luxembourg Jan 2001

5 Europe 6 November 2000 Economics European Economics For Investors Pricing convergence, the end game

Despite significant moves towards convergence in some areas, the DKBR European pricing survey revealed a high degree of pricing dispersion. The survey also showed that convergence in goods’ prices has been down, not towards an average. Here we forecast the ‘end game’ – what would a pricing survey show in five years time?

Despite a trend of price convergence over the last year and before EMU, the Leo Doyle level of price dispersion in Europe remains high. Tax differentials, national +44 20 7475 2423 [email protected] preferences and other slow moving aspects of market structure explain some of this dispersion.

But the gap between high levels of European price dispersion and the low levels of dispersion within countries looks unsustainable. Roughly half of this ‘dispersion gap’ is likely to be eliminated within five years.This note suggests how much convergence and price pressure to expect for each commodity group and for each country. In tradable goods this process will have a downward price bias (on average prices fall by around 3% in total).

Much of the ‘required’ price convergence in durable goods within the Euro area has already happened – though global price convergence will still bring prices lower. The greatest scope for additional European convergence is now in non-durables like personal and household goods, books, electronic media, clothing and branded foods.

Forecast European price change by commodity % (due to single currency effect) -1% -8% -6% -4% -2% 0 2% 5% All items % change in EU % change in E11 Food & soft drink

Alcoholic drink Clothing & footwear Household & personal non-durables Books and magazines

Electrical non-durable goods

Electrical durable goods

Miscellaneous items

Source: DKBR

On line research: www.dresdnerkb.com/ORIS Kleinwort Benson Securities Limited, Regulated by SFA and a Member Firm of the London Stock Exchange PO Box 560, 20 Fenchurch Street, London EC3P 3DB Telephone +44 20 7623 8000 Telex: 916486 Registered in England No. 1767419 Registered Office: 20 Fenchurch Street, London EC3P 3DB. A Member of the Dresdner Bank Group. 6 November 2000 European Economics For Investors

European prices in 2005

An earlier Economics for Investors (27 September) described the main findings of the DKBR European pricing survey. The survey in spring of this year covered fourteen cities and around two hundred mainly branded goods with a total sample size of over 4000. It showed that in most commodities there had been significant convergence since the 1999 version of the survey. Convergence was particularly marked in electrical durable goods and in household & personal non-durables. Despite this trend the remaining price discrepancies look unsustainable. In this note we try and forecast how our survey will look in five years time.

To do this we first ask what would be a sustainable competitive level of price dispersion? We then ask how quickly, or if at all, the Euro area will get there?

The US benchmark of price What would pricing have looked like if Europe had always been a single market? As a convergence... starting point one can look at price dispersion within the US. The logic of looking at the US example is that the economy is of similar ‘economic’ size to Western Europe (a third larger than the E11) and it probably has the most competitive market structure for consumer goods in the world. A single currency adds to the competitive pressure in Europe, by enhancing price transparency.

The European pricing survey at a detailed commodity level showed that the typical standard deviation of prices in the Euro area is equal to around 22% of the average price. A smaller DKBR survey of the US in 1999 showed an average standard deviation of just 3.2% (see table). Other studies of the US show greater dispersion but generally below 10%. We are probably safe to say that price dispersion in the US is no more than half that seen in the Euro area and probably less.

USA branded goods pricing survey (4 cities) Pricing dispersion SD% USA (%) E11 (%)

All items 3.2 21.9 Food & soft drink 2.2 21.6 Clothing & footwear 3.1 23.4 Household & personal non-durables 5.9 21.3 Books and magazines 0.0 62.1 Electrical non-durable goods 4.8 16.6 Electrical durable goods 2.3 7.8 Source DKBR

...exaggerates the plausible The degree of price dispersion in the US is an exaggeration of the potential for price European outcome convergence in the Euro area. Transportation costs do limit convergence but in practice this is not the main difference between the US and Europe. There are more important structural differences that can slow down and inhibit price convergence like tax differentials, national preferences, non-tariff barriers and market structures. All these vary more between European countries than between regions of the US. We look at these factors later.

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An additional practical problem with using the US as a benchmark for European pricing is that the basket of goods consumed on both sides of the Atlantic does differ. Our survey of branded goods pricing in the US in 1999 in many cases was based on an alternative sample to our European survey. An alternative benchmark As an alternative benchmark this year’s pricing survey introduced intra-national comparisons within European countries based on prices in two cities in the five largest EU economies. In using an identical basket of goods to our international European pricing survey this approach ensures that our comparisons are being made ‘like-with- like’.

Just as with the US example, our intra-national comparison is likely to exaggerate the degree of likely convergence due to the single currency. Retailing structures, taxes and local preferences all differ much more between European countries than within individual countries.

Despite these problems we did use intra-national comparisons as a starting point for assessing the ultimate scope for convergence. For each commodity group we then made a judgement as to how much taxes, national preferences, market structures and transportation costs would limit convergence towards intra-national levels of dispersion. Price dispersion within European countries Dispersion within countries is For Germany, France, Italy and Spain with the E11 and for the UK, our branded goods low survey compared prices in two cities. The cities chosen were Frankfurt and Madrid, Paris and Marseille, Rome and Milan, Madrid and Barcelona, London and Glasgow. All broad commodity groups show less price dispersion within countries than across countries (see chart).

Intra-national & international price dispersion

05%10% 15% 20% 25% 30% 35% All items

Food & soft drink Intra-national Alcoholic drink dispersion SD% Clothing & footwear International dispersion SD% Household & personal non-durables

Books and magazines * Truncated bar, value = 62.1% Electrical non-durable goods

Electrical durable goods

Miscellaneous goods

Miscellaneous services

Source: DKBR European Pricing Survey 2000

The table below shows the shows a weighted average of the detailed commodity dispersion within each country. The top row shows the average dispersion between cities in the five countries – the measure used is the standard deviation as a percent of

3 6 November 2000 European Economics For Investors

the mean. All of these intra-national comparisons had low price dispersion relative to our cross-country survey. On average the intra-national dispersion was 8.2%. The right hand column shows the average intra-national dispersion by broad commodity group as shown in the chart above.

Intra-national price dispersion (DKBR pricing survey spring 2000) Frankfurt vs Paris vs Rome vs Madrid vs London vs Average Munich Marseille Milan Barcelona Glasgow intra-national SD % SD % SD % SD % SD % SD %

All items 11.5 10.0 7.0 6.2 6.5 8.2 Food & soft drink 11.1 6.5 5.7 5.3 2.9 6.3 Alcoholic drink 10.5 22.7 4.0 5.8 2.2 9.0 Clothing & footwear 24.2 16.0 9.4 10.3 9.2 12.7 Household & personal non-durables 9.9 4.0 5.8 2.0 5.5 5.0 Books, newspapers & magazines 0.0 0.9 0.0 6.9 0.0 3.5 Electrical non-durable goods 4.7 7.9 13.0 9.5 5.4 8.1 Electrical durable goods 6.0 4.0 14.9 3.3 4.7 5.2 Miscellaneous goods 13.8 0.0 0.0 4.8 20.2 9.7 Miscellaneous services 3.2 33.9 2.6 6.4 14.8 13.8

The ‘dispersion gap’ requires The intra-national and cross-country comparisons do reveal a different ranking of price justification dispersion by commodity group. It is these differences that are interesting. If a commodity has a comparatively low dispersion within individual countries but a high dispersion between countries then it needs some explaining. Either it could reflect structural factors like taxes or national preferences that may change only slowly or it is indicative of uncompetitive pricing.

The two following charts show how the dispersion of prices compares between the two surveys. The first one shows the absolute % gap between cross-country price and intra-national price dispersion. The second shows the ‘ratio of dispersions’.

Difference in price dispersions (international minus intra-national) 05% 10% 15% 20%

All items

Food & soft drink

Alcoholic drink

Clothing & footwear

Household & personal non-durables

Books & magazines * Truncated bar, value = 58.6%

Electrical non-durable goods

Electrical durable goods

Miscellaneous goods

Miscellaneous services

Source: DKBR European Pricing Survey 2000

4 6 November 2000 European Economics For Investors

Ratio of price dispersions (International vs intra-national) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

All items

Food & soft drink

Alcoholic drink

Clothing & footwear

Household & personal non-durables

Books & magazines * Truncated bar, value = 17.6

Electrical non-durable goods

Electrical durable goods

Miscellaneous goods

Miscellaneous services

Source: DKBR European Pricing Survey 2000

Suspiciously large ‘dispersion The small sample grouping of books and magazines is the most extreme case, having gap’ in non-durables the most divergent prices across countries and the least divergent within countries – in the charts its values have been truncated. Price dispersion of alcoholic drink in the international survey is three times that of the intra-national survey – obviously taxes playing a significant part here. The ‘ratio of dispersions’ between the two surveys is similar for food prices. For clothing the cross border dispersion is ‘only’ double that of intra-national dispersion, and the same is true of electrical non-durables (videos, CDs etc). For household and personal non-durables the contrast in dispersion is even greater – a standard deviation of 5% in the two city comparisons compares with nearly 22% in the E11 comparison. In electrical durable goods the substantial price convergence within the EMU countries in the past year has taken the E11 dispersion down to 7.8%, which does not look that out of line with the intra-national dispersion of 5.2%. Limits on convergence Most people accept that the gaps between international and intra-national price dispersion will close, but how much and how quickly? What proportion of the gap is due to structural factors that will change only slowly if at all? Tax differentials Tax effects are quite localised Tax differentials are capable of explaining and sustaining an element of price dispersion. In general the effects are not that significant. Differences in VAT regimes can alter the detailed country rankings for individual prices, but sometimes these tax differences work to reduce price dispersion rather than increase it. Excluding food, drink and books there is very little difference in average price dispersion including or excluding VAT. For food, VAT differences account for about 4 percentage points (or one sixth) of price variation in the EU. For Books and magazines, VAT accounts for 5 percentage points of price dispersion.

5 6 November 2000 European Economics For Investors

Excise duties add to price dispersion in alcoholic drink and also for two commodities, tobacco and fuel that are not covered by our survey. In the EU tax differences account for around 5 percentage points of price dispersion for alcoholic drink. This is one quarter of the total price dispersion. If one purely looks at the euro area, the contribution of tax differences falls to around 2 percentage points.

The euro and the ongoing single market program are adding to pressures for greater tax harmonisation, but the process is only likely to happen slowly. However, the key point is that tax differentials do not explain a large proportion of the high price dispersion in Europe. Other key factors that work to sustain price dispersion across Europe of tradable goods are local demand preferences, non-tariff barriers and market structure. Local preferences Local preferences vary widely Variation in local preferences will be much greater between European countries than across Europe... within those countries (or for that matter compared to regional differences within the US). Demand for individual items is likely to vary in all our commodity groups. Books and magazines is a prime example. It is difficult to establish cross-country appeal for published material written in one language. A popular magazine in one country may be an expensive niche import translated into the language of another country.

Apart from published material we would identify food, drink, clothing, personal goods and electronic media as areas covered by our survey where demand for individual items varies substantially across Europe. The least variation is probably in the demand for electrical durable goods.

...but this needn’t hold up However, the existence of demand differences does not necessarily explain a large convergence part of Europe’s high price dispersion. If barriers to entry, transportation costs and ‘search’ costs are all fairly low then supply should adjust to mirror local demand differences. Variation in demand is likely to increase price dispersion where brands in some countries achieve the status of luxuries, or fashion goods, while in other countries they do not. It is not so much the local demand variation that delivers price dispersion, rather it is market segmentation and non-tariff barriers like high advertising costs. Market structure Market strcutrues are limiting The structure of retailing is another factor that influences price dispersion. The lack of convergence multinational retailers with genuine pan-European market penetration prevents the kind of equality of pricing that is on offer in different parts of the US by Wal-Mart (47.40). Large dominant players will not always mean the most competitive pricing structure but they are likely to bring greater price convergence. Indeed one could argue that a store that charges the same price in all parts of a single market is not pricing in a competitive way. Competitive prices should imply some price variation to reflect differential retailing costs (in particular rents). But, competitive or not, common pricing strategies by ubiquitous retailers do increase price convergence.

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Most price dispersion cannot A study by DRI Europe for the European Commission in 1997 attempted to estimate be justified how much of Europe’s high price variation could be explained by policy factors (tax and regulation), structural market factors (demand differences, market segmentation and transport costs) and behavioural factors. Policy factors and structural factors relate to the nature of the market, which might be expected to change only slowly over time. Behavioural factors include company strategies to control distribution, market-sharing agreements and other attempts increase barriers to entry. Behavioural strategies that have sustained price dispersion are under serious threat from the visibility of the single currency. DRI’s work suggested that only 30% of the observed price variation could be explained by policy and structural factors. What is a sustainable rate of price dispersion? Since DRI’s study three years of convergence should have raised the proportion of the remaining dispersion that is genuinely structural. However, the convergence we have seen in that time would still leave a substantial amount of ‘non-structural’ price dispersion.

We assume half of the For each commodity group we made a judgement over the scope for competition to ‘dispersion gap’ is closed close the ‘dispersion gap’ (between cross-country and intra-national price dispersion). Aggregated up these judgements suggested that roughly half of the gap will be closed on a five year time horizon. The forecasts of price convergence by broad commodity group are shown in the table below.

Forecast price dispersion in the Euro area by broad commodity group Euro area (E11) Change in Proportion of E11 2005 (e) 2000 dispersion ‘dispersion gap’ that Products SD % SD % (%) is closed (*) (%)

All items 14.4 21.9 -7.5 50.6 Food & soft drink 14.9 21.6 -6.7 41.6 Alcoholic drink 19.4 26. -6.9 36.6 Clothing & footwear 17.0 23.4 -6.4 47.0 Household & personal non-durables 12.4 21.3 -8.9 62.4 Books & magazines 18.6 62.1 -43.5 72.0 Electrical non-durable goods 13.1 16.6 -3.5 41.8 Electrical durable goods 6.3 7.8 -1.5 53.6 Miscellaneous items 14.0 20.1 -6.0 53.3 * Dispersion gap refers to the difference between cross-country and intra-national price dispersion

A slower rate of convergence, Interestingly this would imply a very slightly lower rate of price convergence on average but not yet across all groups than is evident between the 1999 and 2000 DKBR European pricing surveys. Convergence is however likely to be tailing off through the end of our five year time horizon. In the next two years we do not look for any easing in the average rate of convergence although this will vary by sector.

The potential for convergence does vary considerably between our commodity groups. The particularly sharp decline in price dispersion for books and magazines should be read with care. It partly reflects the fact that we do not completely trust our current measure of price dispersion. There is also some genuine convergence in prospect for published products.

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Substantial convergence due in Apart from books the greatest convergence is projected for personal and household non-durables non-durable goods. A comparison of our 2000 and 1999 pricing surveys indicated that this category has already experienced particularly rapid convergence post EMU. The current level of dispersion still looks implausibly high.

For food, alcoholic drink and clothing we assumed a below average proportion of the dispersion gap is closed. Tax differentials and/or market structures offer greater resistance to market pressures. However, the gulf between cross-country dispersion and intra- national dispersion is large enough that there is still significant convergence in the forecast.

For electrical non-durables like videos, CDs and software we anticipate less convergence. Language differences and national preferences is one factor slowing price convergence here. Another ironically is the Internet. While e-tailing allows much greater price visibility and potential for price convergence in the long tem, the near term effect can be somewhat different. Differential rates of Internet penetration have actually led to varying rates of price deflation and increasing price dispersion over the last year. Also electronic media goods already have below average price dispersion and are not too far away from our target ‘end-game’ dispersion.

Durable convergence has in This is even more the case for electrical durable goods. There is little protection from large part happened... the pressures for price convergence in this category. However, a large proportion of the convergence ‘required’ by the pressure of the European single market and single currency has already happened. This is less true for the UK and the EMU-outs, where price convergence has further to go.

...but price deflation will It is worth noting that for both electrical durables and electrical non-durables price continue deflation will remain the norm. Technology and wider pressure for global convergence in tradable prices will continue to bear down on European consumer prices. All we are saying in our table here is that the additional pressure for price convergence coming from the single currency is moving away from electrical goods and on to other areas. Deflation pressures A lack of price convergence need not mean a lack of deflationary pressure, but the presence of convergence is likely to mean the addition of deflationary pressure. In non- tradable services it is plausible that convergence will be towards an average price. In tradable goods, theory predicts a downward bias to convergence. Our survey evidence supports this.

A downward bias to tradable The branded goods that converged the most between 1999 and 2000 tended to have goods convergence... lower inflation rates and a bigger downward change in inflation rates. The association is far from perfect but the chart below shows at a broad commodity level there is a correlation. The implication is that prices are converging downwards.

8 6 November 2000 European Economics For Investors

Inflation and change in price dispersion

Electrical durable goods

Household & personal non-durables

Food & soft drink

Electrical non-durable goods Inflation (-disinflation)

Change in dispersion Clothing & footwear

Miscellaneuos goods & services

Books, newspapers & magazines

-8.00% -6.00% -4.00% -2.00% 0.00% 2.00% 4.00%

Source: DKBR European pricing survey 2000

...but not to the lowest price That said, we do not assume that prices will converge down to that of the lowest price country in the region. If competitive pressure on prices comes from demand shifting towards the cheapest producer it is likely that capacity constraints will mean some rise in the lowest price. The general assumption in our forecasts is that prices converge on average to half way between the lowest and the average price (more accurately we rank the prices in order and construct a hypothetical 25th percentile price). The forecast Putting together the forecast convergence with the bias up or down in that process we arrive at a complete forecast of all the countries and commodities covered in our basket of goods.

An average 3.1% price cut in The average decline in all commodities and for the Euro area is 3.1%. This may not Euro area, 3.6% in Europe sound much over five years but the implication for profits is significant. This figure represents the downward pressure on prices specifically related to Euro area convergence – on top of general globalisation forces. The downward pressure on price has no easy counter in terms of cost reduction – wages will not converge downwards.

With costs unchanged a 3.1% price cut could imply an average 15% cut in profits. Our forecast says nothing about how this is split between retailers and manufacturers, but someone would take a sizeable hit. Country prospects Only Spain of the big Within the Euro area Italy appears most vulnerable to convergence pressures with an economies gets inflationary average forecast price decline of 4.7%. There is particular pressure from food, household convergence non-durables and clothing prices. Germany and France and Belgium also experience average price cuts of over 3%. In France the commodity breakdown is somewhat different with deflationary pressure particularly concentrated in clothing and recreational non- durables (both electronic media and books & magazines). The Netherlands gets away with a more modest average price fall. Only Spain of our sample countries experiences upward price pressure from the convergence pressure.

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Forecast price change by country % (due to single currency effect)

Europe

Euro area

Switzerland

Sweden

UK

Belgium

Netherlands

Spain

Italy France

Germany

-7% -6% -5% -4% -3% -2% -1% 0 1% 2% 3% 4%

Source: DKBR

Micro-convergence supports It is worth noting that these country conclusions from micro level analysis amplify the macro forces for divergence in predicted result from macroeconomic growth divergence. At a macro level, the adoption growth rates of a single interest rate across Europe and the process of nominal GDP convergence implies rising inflationary pressure in Spain, and some of the so-called ‘peripheral’ economies relative to the ‘core’ economies. Our micro work points in the same direction.

EMU-outs are not immune It is likely that pressure for convergence in the Euro area is influencing pricing in the EMU-out countries. In our calculations we assume that the indirect pressures to bring EMU-out prices into line with EMU area prices are roughly half as great as for ‘EMU- ins’. On this basis one might have expected less deflationary pressure from EMU convergence. In practice the prices in the UK, Sweden and Switzerland are so much above the EMU averages that even with less market pressure for convergence the price cuts are even greater than in the actual Euro area countries. The UK has an average price decline of 5%. The pricing survey this spring was conducted with sterling at £/E0.61. If sterling were to remain at its higher current level then the projected decline in UK prices would be greater still. On the other hand for the UK a sharp decline in sterling represents an alternative mechanism for making some of the projected price equalisation without price cuts. The same is true of Sweden and Switzerland who in our projections are due for similar substantial price cuts. Commodity prospects A changing pattern of A comparison of our 2000 and 1999 surveys highlights durable goods as one of the convergence areas that has experienced the most convergence post-Emu and as a result experienced downward pressure on prices. Downward pressure on prices is likely to remain evident in durable goods from the wider forces of globalisation and new technology. But, our projections do suggest that additional downward pressure from the visibility of pricing within a single currency will ease. Our survey does not include cars, where there may be more residual pressure for price convergence and additional deflation.

10 6 November 2000 European Economics For Investors

In contrast to electrical durables we do not see any easing in the deflation associated with price convergence in personal and household non-durable goods. In the last year this group saw rapid price convergence but we have argued there is much further to go. A downward bias to this process leads us to project an average 5.6% cut in Eurozone prices because of the transparency of pricing with the single currency. Only our book and magazine group is due for greater deflationary pressure from convergence.

For food and clothing, price Apart from alcoholic drink all other non-durables groups are projected to experience convergence is set to accelerate further deflationary forces from remaining price convergence. For food the forecast decline is in line with the all-items average at 3%. This may not seem much but it is worth noting that our survey did not indicate that convergence had happened much over the past year in food prices. In our forecast the rate of convergence increases. The forecast 3% cut to average food prices is additional deflationary pressure to that already evident from other structural forces. The same is also true for clothing, where again our survey shows that convergence has been limited up to now. The forecast convergence pressures here bring an average 4.4% price cut in the Euro area.

Services do not ‘converge In the few miscellaneous service sector components of our survey we think that down’... convergence pressures will not involve a downward bias to price changes. For services we expect the main driver of price equalisation to be nominal GDP convergence and because of downward wage rigidity this is unlikely to see service sector price convergence show a downward bias. Indeed were it not for margin pressure from new entrants we would look for an upward bias to price convergence in services.

...and taxes could ‘converge up’ In alcoholic drink we actually forecast an upward bias of 2% to prices in the Euro area from price convergence. The driver here is a slow process in the direction of tax harmonisation, which we think would have an upward bias. In the ‘expensive’ EU countries of UK and Sweden taxes might eventually be driven down, but in the Euro area duty increases are more likely than duty cuts.

As for other non-durables goods, most will never reach the levels of convergence one would predict for durable goods. But, current levels of price dispersion for non-durable goods are still unsustainable. At some point the speed of convergence is likely to accelerate. One major catalyst may be the actual introduction of Euro notes and coins in 2000 and the withdrawal of national currencies from July of that year – consumers and businesses will be forced to ‘think in euros’. But, we may not have to wait that long. Our survey shows that in household and personal household goods substantial price convergence was already evident last year.

For durables, price pressures Big-ticket items like cars and electrical durable goods were always likely to be amongst remain even if convergence is the first areas where the single currency would bring price convergence pressures – over and it has. Although that process is not complete, much of the convergence has happened. European price convergence will pose less of a threat to durable goods pricing in the next five years, than it has in the past two years. However, that does not mean an end to falling durable goods prices. European price convergence may ease, but global price convergence has much further to run.

11 6 November 2000 European Economics For Investors

The first table below summarizes the forecasts by country and broad commodity group within the Euro area. The second table extends the forecast to the EMU-outs. The following charts show in pictures our forecast of the convergence effect in each country for the main commodity groups of our survey.

Forecast price change in the Euro area due to convergence (%) Product groups Germany France Italy SpainNetherlands Belgium Euro area (%) (%) (%) (%) (%) (%) (%)

All items average -3.6 -3.5 -4.7 3.1 -2.1 -3.8 -3.1 Food & soft drink -4.9 -0.8 -6.2 4.1 -1.3 -1.9 -3.0 Alcoholic drink 2.7 -1.2 1.0 12.2 3.5 -0.5 2.2 Clothing & footwear -3.3 -7.0 -5.6 0.4 -4.0 -4.3 -4.4 Household & personal non-durables -7.6 -1.9 -8.2 1.0 -1.2 -9.6 -5.3 Books, newspapers & magazines -2.3 -25.7 -8.5 19.4 -14.6 -18.6 -8.6 Electrical non-durable goods -2.8 -6.6 -2.9 -1.9 -4.6 -4.3 -3.8 Electrical durable goods -2.0 -2.4 -0.6 -1.3 -0.1 -2.1 -1.6 Miscellaneous goods -4.3 -3.4 0.3 -1.1 -6.7 -1.0 -2.9 Miscellaneous services -0.4 6.8 -4.2 11.0 6.3 1.6 2.2

Forecast price change in the EMU-out countries due to convergence (%) Product groups Euro area UK Sweden Switzerland Europe (%) (%) (%) (%) (%)

All items average -3.1 -4.9 -6.0 -4.7 -3.6 Food & soft drink -3.0 -4.8 -6.5 -5.5 -3.5 Alcoholic drink 2.2 -8.6 -10.4 1.3 0.0 Clothing & footwear -4.4 -6.8 -6.7 -5.2 -4.9 Household & personal non-durables -5.3 -3.0 -1.3 -6.9 -4.9 Books, newspapers & magazines -8.6 -1.7 -15.1 -3.6 -8.4 Electrical non-durable goods -3.8 -6.5 -6.7 -4.7 -4.4 Electrical durable goods -1.6 -2.4 -5.7 -3.2 -1.9 Miscellaneous goods -2.9 -6.1 -3.3 -1.7 -3.4 Miscellaneous services 2.2 -1.6 -2.8 -6.3 1.1

Forecast European price change by commodity % (due to single currency effect) -1% -8% -6% -4% -2% 0 2% 5%

All items % change in EU % change in E11 Food & soft drink

Alcoholic drink

Clothing & footwear Household & personal non-durables

Books and magazines

Electrical non-durable goods

Electrical durable goods

Miscellaneous items

Source: DKBR

12 6 November 2000 European Economics For Investors

Forecast price change due to Euro area convergence

Food & non-alcoholic drink

-10.00% -8.00% -6.00% -4.00% -2.00% 0.00% 2.00% 4.00%

Germany

France Italy

Spain

Netherlands

Belgium

UK Sweden

Switzerland Euro area

Europe

Source: DKBR Alcoholic drink -15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0%

Germany

France Italy

Spain

Netherlands

Belgium UK

Sweden Switzerland Euro area

Europe

Source: DKBR Alcoholic drink -15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0%

Germany

France Italy

Spain

Netherlands

Belgium UK

Sweden Switzerland Euro area

Europe

Source: DKBR

13 6 November 2000 European Economics For Investors

Forecast price change due to Euro area convergence

Household & personal non-durable goods

-10.0% -8.0% -6.0% -4.0% -2.0% 0.0% 2.0% 4.0%

Germany France Italy Spain Netherlands Belgium UK Sweden Switzerland Euro area Europe

Source: DKBR Elecrical media & non-durables

-10.0% -8.0% -6.0% -4.0% -2.0% 0.0% 2.0% 4.0%

Germany France Italy Spain Netherlands Belgium UK Sweden Switzerland Euro area Europe

Source: DKBR Elecrical durable goods

-10.0% -8.0% -6.0% -4.0% -2.0% 0.0% 2.0% 4.0%

Germany France Italy Spain Netherlands Belgium UK Sweden Switzerland Euro area Europe

Source: DKBR

14 6 November 2000 European Economics For Investors

Notes

15 6 November 2000 European Economics For Investors

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16 Europe 22 September 2000 Economics European Economics For Investors DKBR pricing survey 2000

This year’s DKBR European pricing survey suggests that the average price of branded goods is similar across the ‘core’ Euro area. The UK, Sweden and Switzerland remain expensive. We do find evidence of commodity price convergence compared to 1999. However the degree of price dispersion remains very high. There is much further to go.

The DKBR European pricing survey covered fourteen cities and around two Leo Doyle hundred mainly branded goods with a total sample size of over 4000. Apart +44 20 7475 2423 [email protected] from Spain our ‘core’ Euro countries appear fairly similar in terms of overall cost of the sample. The UK’s expensive shopping basket implies a near 20% overvaluation of sterling.

Netherlands has the price structure that is closest to the Euro average. Prices in Germany, France and Italy are on average over 20% away from the Euro average (some prices higher, some lower).

However, the survey does some provide evidence of price convergence. This year the average standard deviation of prices is 18.5% of the mean. In spring 1999 this dispersion measure was 20%.

At a component level price dispersion is still very high. Typically standard deviations of prices across Euro area members are twice as high as price deviations within countries. Price convergence has much further to go.

DKBR price survey 2000 :Overall commodity basket relative to E11 average price (%)

Spain (Madrid & Barcelona)

Netherlands (Amsterdam)

Germany (Frankfurt & Munich) 'Cheap' Belgium (Brussels) 'expensive' France (Paris & Marseille)

Italy (Rome & Milan)

Switzerland (Zurich)

UK(London & Glasgow)

Sweden (Stockholm)

-25 -15 -5 5152535

Source: DKBR price survey 2000

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DKBR pricing survey 2000

This note is the first of three looking at the issue of price convergence. In subsequent documents we will attempt to measure whether the rate of price convergence has changed and whether prices have been converging up or down. We will also forecast the ‘end-game’ of where convergence should take prices and estimate the resultant impact on inflation. In this piece we summarize the current state of play. We look at patterns of pricing dispersion in Spring 2000 and compare this to the results from the spring 1999 survey. The basis of this analysis is the DKBR European pricing survey. About the Survey Eurostat provides the most comprehensive guide to relative prices for all goods and services annually as part of their Purchasing Power Parity (PPP) estimates. The most recent of these surveys however refers to relative prices in 1997. Our survey is an aim to get a more timely measure of relative prices. We are also able to ensure that we are comparing like-with-like in different cities by focussing on branded items. Some non- branded items were included to give an up-to-date idea of price dispersion in other areas.

The main omissions in our survey relative to a CPI basket are the costs of housing, utilities, transport and recreational services. In addition we exclude cars as the European Commission already provide a very detailed and fairly timely survey of car prices.

Our basket of items is not meant to be comprehensive, but it is extensive. It covers around 240 items in fourteen cities. In each city we tried to use at least three outlets (thanks to Katrina Allen for the shopping). As with the Spring ‘99 survey we covered Frankfurt, Paris, Rome, Madrid, Amsterdam and Brussels from the Euro area and London, Stockholm and Zurich from ‘outside’. In addition we extended the survey to a second city in the bigger economies, adding Munich, Marseille, Milan, Barcelona and Glasgow. Apart from improving the reliability of our country comparisons this allows us to look at the degree of intra-national price dispersion. Overall price levels Shopping outside of EMU is The survey’s prime purpose is to shed light on price dispersion at a commodity level. It expensive can also serve as a guide to purchasing power parity exchange rates at an aggregate level. In the 1999 survey Stockholm, London and Zurich were the most expensive cities with prices well ahead of the Euro area cities. This has not changed. The most expensive city is Stockholm, with a ‘cost of shopping’ some 33% above the Euro area average. Zurich is 23% above the average and London is around 20% ‘over priced’.

The UK figures shown in the front-page chart and in subsequent tables are a combination of London and Glasgow (with 2/3, 1/3 weights). Weighted combinations are also used for Germany, France, Italy and Spain. Interestingly London was only 1.5% more

2 22 September 2000 European Economics For Investors

expensive than Glasgow. Of course if one included housing and services then the differences between London and Glasgow, or Paris and Marseille would be that much greater.

The table below shows the relative price levels for each country in the main commodity group. Using a weighted average the top row shows an average price level relative to the Euro area average of 100 (shown graphically on the front page chart). The bottom row translates this into a ‘fair-value’ exchange rate and the implicit currency overvaluation/ undervaluation.

Sterling almost 20% In the case of the EMU-outs the survey results obviously depend on the exchange rate overvalued at the time of the Survey. In the spring survey sterling was £/E 0.61. The UK’s expensive shopping basket translates into a ‘fair-value’ exchange rate of £/E 0.72 (DM/£ 2.70). Our last fair-value estimate for sterling based on trade flows was around £/E 0.70 Relative price levels aggregated by commodity group (Euro area = 100) Product groups Germany France Italy Spain Netherlands Belgium UK Sweden Switzerland

All items 98.3 103.6 106.2 86.4 98.6 102.6 118.6 132.7 116.9 Food & soft drink 105.2 95.8 105.5 84.6 89.3 99.1 110.7 125.1 127.0 Alcoholic drink 97.1 114.4 101.4 70.1 95.7 108.4 180.8 219.1 98.1 Clothing & footwear 85.1 110.3 117.3 88.6 99.1 101.3 128.4 140.2 118.7 Household & personal non-durables 101.8 94.3 108.2 86.8 102.7 112.5 101.7 104.1 118.1 Books, newspapers & magazines 84.4 154.0 99.6 59.8 114.0 126.1 93.8 159.4 99.5 Electrical non-durable goods 93.8 112.7 96.7 92.3 111.3 100.5 116.0 129.0 104.6 Electrical durable goods 100.8 102.4 94.9 97.7 95.0 107.8 113.2 143.3 112.2 Miscellaneous goods 104.7 86.7 103.3 99.1 116.9 95.1 112.6 108.5 95.4 Miscellaneous services 105.5 98.6 112.8 79.6 87.7 86.9 130.2 118.9 137.9 Implied PPP exchange rate vs Euro 1.92 6.80 2056.82 143.76 2.17 41.38 0.72 11.19 1.88 Fixed rate/(Latest rate for ‘EMU-outs’) 1.96 6.56 1936.27 166.39 2.20 40.34 0.61 8.37 1.53 Overvaluation(+)/Undervaluation(-) (%) -1.7 3.6 6.2 -13.6 -1.4 2.6 19.2 33.6 23.2 Source: DKBR Cost of living is similar in Euro Within the Euro area, the differences in the overall price level are quite small if one area except low priced Spain allows for the nature of the sample. In being based on one or two cities in each country and in omitting some important living costs the sampling variability should be much higher than in Eurostat’s comprehensive PPP estimates. Despite this Germany, France, the Netherlands and Belgium are all within 5% of the EU average, and Italy is just outside this band, being 6% expensive. Only Spain, our one ‘peripheral’ economy in the sample, is significantly away from the average. Indeed for all our broad commodity groups in the table below Spain is cheaper than the average. In aggregate the peseta is nearly 14% undervalued. Dispersion beneath the surface The fairly narrow range of the price levels in the core Euro area countries obscures a high degree of divergence at a detailed commodity level. To some degree this can be seen in the broad commodity groups in the table. Take France for example. The French pay 13% more than the Euro area average for electrical non-durable goods (CDs, videos, computer software etc) but 6% less for household non-durables. Note the 54% extra that the French pay to buy a magazine could be a spurious result as it was on a very small sample.

3 22 September 2000 European Economics For Investors

These broader commodity groups do however hide a much wider dispersion at a component level. In Germany, household and personal non-durable goods prices when taken in aggregate are close to the Euro area average. But within this group Nurofen tablets are 59% more expensive than the average while our sample of branded deodorants is 30% cheap. Price dispersion by commodity Our survey does allow us to look at patterns of price dispersion on a bilateral basis within the sample. In an annex we look at this in some detail. Although the degree of price dispersion does vary between different countries, it varies much more between the detailed commodities in the sample.

To measure the commodity price dispersion we use two measures. The first is the standard deviation of prices expressed as a share of the mean (otherwise called the coefficient of variation). This is the standard measure employed in other surveys of price convergence.

One problem with such a measure is that it puts equal importance on the dispersion between smaller economies in Europe as between the bigger four. As such we also show a weighted standard deviation which puts more emphasis on the convergence between the larger economies.

Dispersion increases outside of Our entire sample has an average standard deviation of 22.7% for the Euro area and the Euro area 19.4% for using our weighted measure. When the EMU-outs are included the dispersion is greater, with 25.7% for the standard deviation and 22.3% when weighted. This is more than double the typical dispersion in surveys of prices across the US.

Size matters... Which commodities explain this high dispersion? In the chart opposite we summarise the detailed results by taking an average of the dispersion measures for each broad commodity group. The chart uses an unweighted standard deviation for the Euro area. This shows that the most convergent group is electrical durable goods. Electrical non- durables like CDs, videos, etc are also more convergent than the average but they still have twice the dispersion of durable goods.

...and so do tax rates Our grouping of books and magazines is the most divergent by a long way. Although this probably is an area with quite high dispersion rates our sample is small and the result probably overstates the true picture. Of the groupings with bigger samples it is alcoholic drink that is the most divergent. Clearly this reflects differential tax rates. Next in the divergence ranking comes clothing. The dispersion of both food prices and household & personal non-durable goods prices is pretty close to the average.

4 22 September 2000 European Economics For Investors

Price dispersion in the Euro area (SD % by broad product group) 0% 5% 10% 15% 20% 25% 30%

All items

Food & soft drink

Alcoholic drink

Clothing & footwear Insert leoefv3 Household & personal non-durables 62.1% Books, newspapers & magazines (small sample) Electrical non-durable goods

Electrical durable goods

Miscellaneous goods

Miscellaneous services

Source: DKBR price survey 2000

The table below shows the dispersion measures including the EMU-outs as well as the Euro area. In all the broad groups other than the erratic books & magazines dispersion rates are increased by adding the EMU outs. No surprise here given the lack of historic exchange rate stability. The increase in divergence when including the EMU-outs is even greater for alcohol where the differential rate of duty are even more marked.

Summary of price dispersion (DKBR European pricing survey 2000) Euro area sample (E11) Western Europe sample (EU) Sample average st dev weighted st dev weighted Products size * price SD (%) SD (%) mean SD (%) SD (%)

All items 702 25.31 22.7 19.4 26.42 25.7 22.3 Food & soft drink 164 1.84 21.6 17.9 1.96 24.2 20.5 Alcoholic drink 40 5.15 26.3 22.6 6.16 40.5 33.9 Clothing & footwear 147 42.92 23.4 22.5 45.80 27.6 25.1 Household & personal non-durables 109 4.17 21.3 17.9 4.23 21.5 19.0 Books, newspapers & magazines 20 6.46 62.1 39.1 6.74 53.5 37.7 Electrical non-durable goods 93 26.50 16.6 15.8 26.47 20.2 19.1 Electrical durable goods 58 136.89 7.8 6.3 145.05 14.1 10.2 Miscellaneous goods 37 102.35 17.3 14.9 104.25 18.3 16.1 Miscellaneous services 34 3.37 22.8 19.2 3.75 26.1 22.8 * Number of cities multiplied by the number of products. In addition many products will be the average of more than one brand (eg. Bottled water, CD’s) and each detailed product is sampled in more than one store. In total the number of prices checked was over 4000 - thanks Katrina

5 22 September 2000 European Economics For Investors

Ranking of price dispersion These group measures of average dispersion obscure some interesting detail. The table opposite shows a ranking of the commodities surveyed which had at least six cities in the sample. The ordering is from most divergent to least divergent using and average of dispersion measures (vs EU and E11, weighted and un-weighted). The ranking sheds some light on what is behind the dispersion.

Taxes, regulations and national Amongst the most divergent items are those with an element of tax and regulation like preferences bring most Lager, Wine and Nurofen. The other key factor that plays a part is national preferences. divergence The position of fashion magazines at the top of the list reflects another key factor, differing national tastes. This probably also plays a part in the dispersion of bottled water prices and book prices (though government policies also play a role in the latter.

Price divergence varies with There are also very high dispersion rates for some of our non-branded generic clothing brand strength items like cotton socks, white T-shirts and non-branded jeans. This is in sharp contrast with the branded jeans which are amongst the most convergent of prices. One explanation is that in choosing non-brand items we were not really comparing like with like. This is possible but is unlikely to explain much of the divergence. It seems more likely that on items that are not internationally known brands retailers are more able to charge a price that reflects their local costs of sale (wages and rent). With a brand like Levi-501 jeans any discrepancies in price are easily arbitraged away by importers.

One interesting example is the Timberland brand. Their main brand, the Timberland boot has a similar price across Europe but the less well-established item, the Timberland logo sweatshirt was one of the most convergent. Again this may reflect the fact that the retailers are unable to charge differential prices on their ‘flagship’ items, but are able to do so on subsidiary items.

Durables prices are already very As already mentioned electrical durable goods stand out as the most convergent group. similar The most convergent of all the items in our survey is the Rowenta PPP2 Iron, but our sample of personal Hi-Fi’s, cameras, shavers and kettles all have quite small price differences across Europe. Prices of CDs and video games are also within a narrow range in our sample countries. Software prices exhibit greater divergence, as do other non-durables that are not vehicles for electronic information like blank video cassettes and batteries.

Non-durables show a mixed It is difficult to explain the different results in some of the personal and household non- pattern durable goods group. Our samples of Shampoo brands are fairly convergent in price while deodorants are divergent. National preferences may again be part of the explanation but it also looks like this is an area where a more consistently convergent picture should develop over time.

Two of the three service sector items in the survey, cinema admission and a bistro cup of coffee have quite high price dispersion. This may reflect the fact that these services are not always identical. The most homogeneous of services, a take-away ‘Big-mac’ from McDonalds, is much more evenly priced across Europe.

6 22 September 2000 European Economics For Investors

Dispersion in Euro area ranked by degree of price dispersion Average Euro area Europe dispersion weighted weighted Detailed products measure % SD % SD % SD % SD (%) Magazines (elle & cosmopolitan) 64.2 88.8 47.0 76.1 45.0 Nurofen Original 62.7 77.9 56.8 59.2 57.0 Lager (3 brands) 40.1 34.2 32.5 50.5 43.2 Socks: Cotton Black 39.2 28.5 35.6 46.1 46.5 Bottled water (2 brands) 36.5 40.2 34.3 39.4 31.9 Sweatshirt:Timberland Logo 36.3 38.4 36.0 36.9 33.8 T-Shirt: Plain White 35.0 33.1 32.2 40.1 34.8 Jeans (non-brand) 34.2 36.9 34.2 34.1 31.5 Bistro/Cafe coffee:Tall Caffe Latte 34.1 37.3 37.1 29.5 32.6 Videa cassettes blank (TDK HS180 x3) 32.2 31.5 35.5 29.4 32.3 Books (best seller fiction) 32.0 35.4 31.2 30.9 30.3 Wine (varied sample) 29.4 25.1 19.6 41.9 30.8 Vegetable oil 27.0 31.4 25.2 26.5 25.1 Polo Shirt 26.8 24.0 24.9 30.3 27.8 Trousers: Cargo Pants 25.2 28.3 22.6 27.3 22.5 Trousers: Plain Work Style 24.7 27.9 20.8 27.1 22.9 Jam:Bonne Maman Strawberry 24.3 23.9 21.8 27.6 23.9 Cinema entry 23.6 22.0 13.8 33.7 24.9 Ice Cream Magnum 3 pack 23.2 18.0 10.4 38.2 26.2 Spirits (3 brands) 23.0 19.5 15.8 29.0 27.5 Margerine 22.6 21.2 24.7 21.2 23.1 Coca Cola 22.1 20.6 17.7 24.1 26.0 Deodorant 22.1 21.8 24.6 19.6 22.3 Software (3 packages) 21.4 19.6 15.6 27.6 22.9 Leather Belt: Black 21.2 18.4 21.7 23.3 21.5 Batteries:Duracell AA x4 21.1 20.8 18.9 22.0 22.6 Candrel Sugar 20.5 18.9 16.2 25.2 21.8 Heinz Tomato Ketchup 19.8 21.0 15.4 24.0 18.9 Tennis Racquet: Wilson Power 19.7 19.9 18.9 21.1 19.0 Instant coffee 19.1 20.9 16.5 22.6 16.5 Camera film 18.3 14.0 12.4 23.8 22.9 Spaghetti 18.2 19.4 15.0 20.3 18.0 Shaving foam:Gillette Series 17.4 16.4 12.3 21.5 19.7 White Long Sleeve Shirt 17.2 17.0 17.6 16.5 17.8 Videos (sample of 4 films) 16.9 16.9 16.5 18.2 16.1 Instant soup 16.8 21.6 13.6 18.2 13.9 Cornflakes 16.3 16.0 14.1 19.9 15.2 Chanel No5 - Eau de Parfum 16.2 17.0 13.3 18.8 15.6 Tampons: Tampax Regular 15.5 14.3 15.7 16.6 15.4 Milk Local Brand 15.0 17.3 14.6 14.8 13.3 Ariel Detergent Powder Normal 14.6 15.3 12.1 18.4 12.7 Trousers: Cotton Leisure 14.6 12.4 10.5 21.4 14.1 SWATCH Watch “The Classic” 14.1 15.0 12.4 15.1 13.8 Toosthpaste:Colgate Total Normal 13.9 13.2 9.3 20.2 13.0 Mars Bars 13.1 12.2 10.4 16.4 13.4 Timberland Boots 13.0 8.4 5.9 18.4 19.4 Shampoo (3 kinds) 12.9 13.6 13.2 12.3 12.6 Kettle: Tefal Vitesse automatic 12.3 8.7 5.5 20.8 14.3 McDonalds Bic Mac 10.5 9.0 6.9 14.9 11.1 Nappies:Pampers Newborn 10.4 10.1 7.2 15.1 9.1 Shavers 10.2 10.7 9.3 11.8 8.9 Cameras 9.7 8.3 8.9 11.3 10.4 Razors 9.6 9.2 9.6 10.2 9.4 Personal HiFi 9.2 7.7 5.7 14.2 9.1 CD’s (sample of 4 discs) 8.6 8.0 6.4 11.0 9.1 Jeans (Levi, 501 Blue) 8.2 7.5 7.6 9.2 8.6 Video games (sample of 4 games) 6.9 5.5 5.0 9.4 7.6 Iron: Rowenta PPP2 6.6 3.6 2.3 12.4 8.2 Source: DKBR

7 22 September 2000 European Economics For Investors

Convergence since 1999 This is the picture of price dispersion in 2000. How has this changed? The spring 1999 survey did not include as many cities or as many items but the matched sample is large enough to identify the main changes between the two years. This does provide clear evidence of price convergence. The average standard deviation of prices for all items fell by 1.5% of the mean. Our preferred weighted measure converged by 1.8%.

Strong convergence in The chart below shows the change in the dispersion by broad commodity group. The durables and household non- most striking moves towards convergence were electrical durables and household and durables personal non-durables. The change in food and clothing prices was much less marked. The erratic books & magazines category converged on our weighted measure but diverged on a simple standard deviation basis.

Change in Euro area price dispersion (2000 vs 1999 weighted SD%)

-5% -4% -3% -2% -1% 0%

All items

Food & soft drink

Clothing & footwear

Household & personal non-durables

Books, newspapers & magazines

Electrical non-durable goods

Electrical durable goods

Source: DKBR price survey 2000

Change in price dispersion by broad commodity group (matched sample) 2000 1999 Change in Sample 2000 1999 weighted weighted Change in weighted Change in price dispersion size(1) SD (%) SD (%) SD (%) SD (%) SD (%) SD (%)

All items 226 18.5% 20.0% 14.7% 16.5% -1.5% -1.8 Food & soft drink 60 22.0% 23.7% 17.4% 18.7% -1.7% -1.3 Clothing & footwear 39 20.4% 19.5% 15.1% 15.7% 0.9% -0.7 Household & personal non-durables 38 14.3% 19.2% 12.2% 17.0% -4.9% -4.8 Books, newspapers & magazines 8 27.9% 20.4% 18.7% 20.6% 7.5% -1.9 Electrical non-durable goods 39 18.0% 17.9% 16.4% 16.2% 0.0% 0.2 Electrical durable goods 24 8.5% 16.7% 6.8% 11.7% -8.2% -4.9 Miscellaneuos goods & services 18 19.1% 17.1% 14.7% 14.6% 2.0% 0.0 (1) Number of countries X number of products Source: DKBR

8 22 September 2000 European Economics For Investors

The most interesting development is the lack of convergence in the electrical non- durable group. In particular this is due to CDs and videos. One possibility is that this reflects different rates of Internet penetration. As Internet usage increases one might expect convergence of ‘information’ goods to resume.

Commoditised convergence With the exception of this group, the general picture is one in which the change in dispersion depends on the homogeneity of the commodity. This is just as one would expect with pressures for price convergence from a single market.

The process of convergence is far from finished. We have noted that measures of price dispersion in the Euro area are much greater than across the US. This is true even when differences in tax rates are taken into consideration.

Inter-city brenchmark... Our latest survey offers an alternative benchmark by looking at the dispersion between the two cities in the big five European economies. On average for all items in our survey the deviation between the two cities in the same country is 8.2%. The greatest similarity in price is between Madrid and Barcelona and the biggest difference in price structure is between Frankfurt and Munich.

The table below shows the intra-national dispersion for our five countries. The individual country results may not be that reliable given the sample size but the average of the five intra-national measures should be reasonably reliable. In the last column we again show the cross-country dispersion by commodity group.

Intra-national price dispersion (between cities in the same country) Frankfurt vs Paris vs Rome vs Madrid vs London vs Average E11 Munich Marseille Milan Barcelona Glasgow intra-national average Intra-national deviation SD (%) SD (%) SD (%) SD (%) SD (%) SD (%) SD (%)

All items 11.5 10.0 7.0 6.2 6.5 8.2 22.7 Food & soft drink 11.1 6.5 5.7 5.3 2.9 6.3 21.6 Alcoholic drink 10.5 22.7 4.0 5.8 2.2 9.0 26.3 Clothing & footwear 24.2 16.0 9.4 10.3 9.2 12.7 23.4 Household & personal non-durables 9.9 4.0 5.8 2.0 5.5 5.0 21.3 Books, newspapers & magazines 0.0 0.9 0.0 6.9 0.0 3.5 62.1 Electrical non-durable goods 4.7 7.9 13.0 9.5 5.4 8.1 16.6 Electrical durable goods 6.0 4.0 14.9 3.3 4.7 5.2 7.8 Miscellaneous goods 13.8 0.0 0.0 4.8 20.2 9.7 17.3 Miscellaneous services 3.2 33.9 2.6 6.4 14.8 13.8 22.8% Source: DKBR

...suggests much more Durable goods prices in the Euro area are already quite close to the typical inter-city convergence to come dispersion. In other categories the differences are very high. There are two very good reasons why one would not expect the same degree of price convergence across Europe as one will get within the same country. The first is differences in government policy (taxes and regulations), and the second is national preferences. We find it implausible however that the process of convergence is over.

9 22 September 2000 European Economics For Investors

Annex: Which is the most ‘European’ country?

The DKBR pricing survey allows us to compare the structure of each countries shopping basket with the Euro area average. The overall French and German price levels are quite close to the Euro area average but the divergence from the average at a component level is still high. On average French prices are 18% away (plus or minus) from the Eurozone average; In Germany the average absolute divergence is 14%. This is the lowest divergence amongst our sample countries. However the result is biased down by the inclusion of Germany in the calculation of the Euro average price. If one measures prices in Germany against an average of the Euro area prices excluding Germany itself, then the average absolute price divergence rises to 24.1%. In France the figure is even higher at 24.5%. Indeed of the Euro area countries France and Germany have the greatest divergence on this basis. Only the EMU-outs are further from the Euro area average. In contrast the Netherlands and Belgium have the lowest divergence with the Euro area with figures of 15.9% and 17.1% respectively. This is the result one would expect with the small, open nature of these economies (high import/GDP ratios).

Average component price divergence with the Euro area by country in absolute % terms 0% 5% 10% 15% 20% 25% 30% 35% 40%

Germany

France

Italy

Spain

Netherlands vs Euro average

vs Euro avge. excluding country in question Belguim

UK

Sweden

Switzerland

Source: DKBR price survey 2000

10 22 September 2000 European Economics For Investors

The table below offers more detail on the commodity groups where prices are most out of line in terms of absolute divergence with the Euro area average.

Average absolute price differential with Euro area (%) Average of Germany France Italy Spain Netherlands Belguim UK Sweden Switzerland product groups (%) (%) (%) (%) (%) (%) (%) (%) (%)

All items average 24.1 24.5 22.4 20.4 15.9 17.1 27.8 41.8 25.4 Food & soft drink 27.4 15.3 22.8 22.0 16.3 22.2 24.6 32.2 35.1 Alcoholic drink 29.2 41.8 13.0 31.7 24.3 23.5 80.8 119.1 13.0 Clothing & footwear 24.9 26.9 40.3 18.4 13.3 14.3 34.5 53.0 35.3 Household & personal non-durables 44.6 21.1 14.1 21.8 18.1 15.6 14.3 30.8 18.1 Books, newspapers & magazines 22.6 86.2 28.8 42.5 15.1 27.5 18.6 75.4 9.2 Electrical non-durable goods 18.6 32.1 9.7 14.8 17.3 9.9 28.1 29.0 17.6 Electrical durable goods 8.5 6.8 6.2 7.8 10.7 9.1 13.2 43.3 12.2 Miscellaneous goods 7.7 22.3 22.0 16.8 18.3 8.5 21.4 25.6 4.6 Miscellaneous services 11.4 24.6 30.4 22.0 13.0 23.5 30.2 18.9 37.9 Source: DKBR

Country correlations An alternative way to compare each countries pricing structure is to look at the bilateral divergence between countries. The table below shows the average standard deviation in percentage terms between our sample countries, the lower the figure the greater is the correlation between two countries price structures. For example reading down the columns one sees that French prices are more closely correlated with Belgian prices than with Italian prices. Germany’s prices are most like Dutch prices and least like those in Spain within the Euro area. Italy also has its lowest divergence with the Netherlands and Belgium. All of the Euro area countries have their greatest price differentials with Sweden. The UK in contrast has a relatively similar price structure to Sweden.

Price dispersion matrix Coefficient of variation Italy France Netherlands Belgium Spain Germany UK Sweden Switzerland between countries (%) (%) (%) (%) (%) (%) (%) (%) (%)

Italy 19.6 15.8 14.6 17.8 17.9 18.5 24.2 17.8 France 19.6 14.4 14.0 18.5 19.3 20.0 23.3 19.2 Netherlands 15.8 14.4 14.4 16.7 15.8 19.4 23.7 20.9 Belgium 14.6 14.0 14.4 17.8 17.3 17.4 23.3 14.5 Spain 17.8 18.5 16.7 17.8 20.2 24.9 30.4 23.8 Germany 17.9 19.3 15.8 17.3 20.2 20.7 25.9 19.4 UK 18.5 20.0 19.4 17.4 24.9 20.7 17.7 20.0 Sweden 24.2 23.3 23.7 23.3 30.4 25.9 17.7 24.2 Switzerland 17.8 19.2 20.9 14.5 23.8 19.4 20.0 24.2 Average deviation vs E11 (%) 17.11 17.15 15.44 15.62 18.19 18.09 20.14 25.15 19.25 Average deviation vs EU (%) 18.26 18.54 17.65 16.65 21.25 19.55 19.81 24.09 19.95 Source: DKBR

Although the degree of price dispersion does vary between different sub-sets of countries, the differences between different commodities are more extreme. More on how convergence is likely to develop next week.

11 22 September 2000 European Economics For Investors

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DRESDNER KLEINWORT BENSON RESEARCH – RECOMMENDATION DEFINITION (Expected performance over next 12 months) Buy Outperform by 10% or more Reduce Underperform, but by less than 10% Core and Non-Core reflect long-term views, i.e. whether stocks should Add Outperform, but by less than 10% Sell Underperform by 10% or more. form a significant part of a portfolio beyond the 12-month period. Hold Track market Mailing list UECO, PECO

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