Narcissa Balta and Juan Delgado

Transcription

1 Home Bias and Market Integration in the EU Narcissa Balta and Juan Delgado

2 Home bias and market integration in the EU Narcissa Balta and Juan Delgado This version: June 2007 Abstract: The Single Market has been one of the core policies of the European Union. This paper evaluates the success of integration policies in the EU by assessing the magnitude and evolution of home bias across Europe in goods and services markets and equity portfolio holdings. Twenty years after the launch of the Single Market Programme national borders still matter in Europe and consumption baskets and investment portfolios of EU countries still contain a predominant share of home products and assets. More worryingly, home bias in goods and services has barely changed in recent years. There are also large differences in the degree of home bias across European countries. This might indicate that traditional integration policies are no longer effective and need to be transformed to continue delivering. We thank comments from our colleagues at Bruegel and especially from Jean Pisani-Ferry. All remaining errors are ours. ULB-ECARES and BRUEGEL BRUEGEL

3 1. Introduction Why do people have a strong preference to consume home products? Why do investors prefer to hold their wealth in domestic equity? The inability of economic theory to explain such empirical observation is known as home bias puzzle (see e.g. Obstfeld and Rogoff, 2000). Market integration policies, which aim at removing those obstacles that prevent mobility of products, capital and people across borders, have been at the core of the economic policy of the European Union (EU). With the objective of enhancing growth and competitiveness in Europe, the EU launched in the mid-80s the so-called Single Market Programme (SMP) which aimed at the creation of an area without internal frontiers in which the free movement of goods, persons, services and capital is ensured. An increasing presence of foreign products in consumption baskets and foreign assets in investment portfolios would be a sign of success of such policies. This paper evaluates the success of integration policies in the EU by looking at the degree and recent evolution of home bias across countries and across markets. A common methodology is applied to goods, services and equity markets with the aim of providing a full picture of the existing degree of home bias across the EU. The purpose of the paper is to shred some light in understanding the cross-market implications of economic integration by looking at a simple indicator built uniformly across goods, services and equity markets. The paper shows that twenty years after the launch of the SMP and in spite of international specialisation and outsourcing and of the increasing globalization of capital markets, national borders still matter in Europe and EU consumption baskets and investment portfolios still contain a predominant share of domestically produced products and domestic assets. The attempts to quantify and explain the home bias puzzle are pervasive in the recent economic literature. McCallum (1995) estimates that trade between Canadian provinces is twenty times greater than trade between border US states and Canadian provinces even if there were no substantial barriers to trade suggesting that national borders in general matter. Nitsch (2000) estimates that on average EU countries internal trade is seven to ten times bigger than trade with partner countries (after adjustment for size, distance and other variables). Wolf (2000) shows that even within the US intra-state trade is much higher than inter-state trade. Equally, for asset holdings, French and Poterba (1991) show that information asymmetry can generate the same patterns in portfolio investment as if the domestic returns on assets were several hundred basis points higher than the foreign returns. Portes and Rey (2005) quantify the size and determinants of financial home bias and show the relevant role of information costs. Again, even within a country, investment managers tend to exhibit strong preferences for locally headquartered firms (See Coval and Moskowitz, 1999 for the case of the US). 2

4 In this paper, we analyse the existence of home bias in goods, services and equity markets. We quantify the degree of home bias across markets and across countries within the EU. The paper also compares the degree of home bias in EU countries with other OECD countries in order to assess how successful integration policies have been across the EU. To measure the degree of home bias in a comparable way across countries we rely on two benchmarks. The Frictionless Economy benchmark considers that, in the absence of home bias, the share of domestic products (equity) equals share of domestic production (market capitalisation) in total OECD production (market capitalisation). The Integrated Economy benchmark assumes that, in the absence of home bias, a country s internal trade would be equal to the trade with a foreign country of similar economic and geographic size. The estimate of internal trade in the absence of home bias can therefore be determined by using trade data. The same reasoning applies to equity markets but considering cross-border investment instead of trade and holding of domestic equity instead of internal trade. The lack of long enough data series for trade in services and for equity holdings does not allow assessing the evolution of home bias for the whole SMP period. However, we can still observe some interesting patterns. For some EU countries home bias is not distinguishable from other OECD countries. Moreover, home bias in goods and services has barely changed in the recent years. This phenomenon is not only due to the increasing weight of services in the economy (which are less tradable and therefore show a higher degree of home bias ) but also to the lack of progress of home bias in goods markets. Finally, there are large differences in the degree of home bias across European countries which might reflect different degrees of success of integration policies. The results have interesting policy implications which are especially relevant in the context of the current review of the integration policies of the EU. 1 First, the fact that the home bias in product markets has stalled in recent years may indicate that traditional integration policies may have lost steam. Second, the heterogeneous degree of home bias across the EU could reduce the effectiveness of other common policies such as monetary policy in the Euroarea. Section 2 discusses the link between home bias and market integration. Section 3 presents the two benchmarks used as reference in the quantification of home bias. Section 4 presents the empirical results for product markets and equity holdings across countries. Finally, section 5 concludes. 2. Is home bias a measure for the degree of market integration? In a world where countries are isolated from each other all products consumed within a country would have to be produced within that country. In such a case, home bias would reach its maximum level. If trade barriers are reduced, goods and services will flow from country to country and the degree of home bias will be reduced. Removing trade barriers allows for increasing trade and will therefore imply lower home bias. However, even if trade barriers were totally removed, home bias could still persist. Why is this? 1 See the European Commission Public consultation on the Future of the Internal Market at 3

5 Product physical characteristics determine in some way the tradability of a product. Some goods and especially some services are not easily transportable or tradable and require proximity between sellers and buyers. Therefore, even in the absence of trade barriers, consumers will consume a large share of domestically produced products (see e.g. Jensen and Kletzer, 2005, for an analysis of tradability of services within the US). Moreover, consumer preferences might also play an important role in the degree of home bias. For example, Head and Meyer (2000) show that home bias in final goods consumption is larger than home bias in intermediate goods where consumer preference do not play an important role. Finally, mutual trust between trading partners and sharing a common institutional setting contribute to reduce home bias. Zingales et al (2004) model trust as a function of cultural and historical factors and proximity of legal regimes. They find that lower relative levels of trust toward citizens of a country lead to less trade with that country and less portfolio investment. Antras (2003) and Antras and Helpman (2006) show that, since bilateral trade flows between any two countries is mainly intra-firm, incomplete contracts between final goods producers and intermediate suppliers and the lack of a common institutional setting could play an important role in explaining home bias. In the case of equity holdings the reasons for the presence of home bias other than cross border barriers to investment are somewhat different. First, an efficient investment portfolio might well contain a large share of domestic equity. Cai and Warnock (2006) show for example that US home bias in equity holdings is mainly due to the fact that US investors can find enough foreign diversification at home. Institutional investors in US favour the domestic firms that provide the greatest international diversification benefits (i.e. domestic multinationals). Second, home bias in equity might also be determined by the existence of home bias in trade (see Lane and Milesi-Ferretti, 2005). Finally, high real exchange rate volatility favours investment in domestic assets with relatively low local currency return volatility (see Fidora et al, 2006). Therefore, the existence of home bias is not always a sign of lack of market integration. As explained above, there are many non-policy related reasons that could determine the existence of home bias. In principle, in a perfect integrated market one would expect to observe zero home bias. Successful market integration policies should therefore have as a consequence the decrease of home bias. However, there is evidence of home bias even within a country. In the United States, on average the internal flow of trade within states is three times higher than the trade between US states (Wolf, 2000). US citizens also disproportionately invest in stocks of companies headquartered in their home region (Coval and Moskowitz, 1999). It is therefore difficult to disentangle to what extent home bias is due market imperfections that can be corrected by policies and to what extent it is due to non-policy related reasons such as consumer preferences or product characteristics. Hence, the use of home bias measures to assess market integration should be made keeping in mind such caveats. The comparative analysis across countries and the evolution of home bias provides however an indication on to what extent home bias can be reduced. 4

6 The use of home bias indicators based on trade data has however a number of caveats: first, the increasing weight of services in the economy, which are generally less tradable than goods, can make home bias increase without necessarily meaning that the economies are less integrated. If the economy becomes less tradable in global terms, global home bias will increase all other things equal. Second, the analysis of home bias also ignores an important source of market integration which is foreign direct investment. If firms decide to establish and produce in the destination markets, imports would be replaced by local production and therefore home bias would increase. 2 However, the internationalization of firms has also proved to boost intra-industry trade: trade of intermediate goods has replaced trade of final goods. Also, foreign direct investment does not always happen in final markets but often in areas that allow better access to inputs. It is therefore not obvious that trade should decrease, and consequently home bias should increase, as firms decide to grow through foreign direct investment. On the other hand, in recent years progress in communication and information technologies and decrease in transportation costs have allowed for an increasing tradability of goods and services. Moreover, such developments have facilitated the internationalisation of production chains trough outsourcing and offshoring. The possibility to trade goods and services that were not tradable previously and the increase in intra-industry trade due to offshoring and outsourcing should have contributed to boost trade and consequently reduce home bias. Keeping in mind the caveats of using home bias indicators to assess market integration, we next develop two benchmarks that aim to represent a fully integrated market. In the first benchmark, a fully integrated market means that each country is represented in each consumption basket/investment portfolio according to its total production/market capitalisation. In the second benchmark, a fully integrated market means that each country trades with itself (and invest in domestic equity) the same as it would trade with another country of similar geographical and economic size. Obviously, neither benchmark captures the share of home bias due to consumer preferences or to product characteristics so their absolute values should be interpreted with care. However, such benchmarks allow for a more consistent comparison of home bias across countries. 2. Consumption and equity investment in the absence of home bias A large country generally produces more of everything than a small country. Just as a result of simple probability, in a fully integrated market consumers from large countries will be more likely to consume domestic products than consumers from small countries. This implies that the fact that Germans consume 85 percent of domestic products and the Portuguese 82 percent does not necessarily mean than Germany is more home-biased than Portugal: Germany produces 9 percent of the goods and services in the OECD while Portugal produces less than 1 percent. 2 Veron (2006) analyses the process of internationalisation of the 100 larger European firms and confirms the increasing Europeanisation of European firms in recent years. 5

7 In order to take into account this fact, we construct two benchmarks. The first benchmark, the frictionless economy benchmark, assumes that in the absence of home bias the consumption of domestic goods in each country equals the share of domestic products in total production. In a more sophisticated way, the second benchmark, the integrated economy benchmark, takes into account the economic and geographic size of countries to estimate domestic trade in the absence of home bias. This benchmark makes use of trade data to estimate how much a country would trade with a country of similar economic and geographical size. The estimated trade of a country with itself is used as a proxy for domestic trade in the absence of home bias. The degree of home bias is calculated as the deviation of the observed ratios from each of the defined benchmarks. Equivalent benchmarks can be constructed for equity markets to proxy investment in domestic equity in the absence of home bias. For clarity, we will only define here the benchmarks for product markets. We refer to Annex V for a detailed definition of the benchmarks for product and equity markets Frictionless Economy Benchmark If we conceive an integrated market as a market where the production of all countries is pooled together and consumers randomly pick up products from that pool, the share of a country in any consumption basket would be determined by the relative production of that country within the OECD. We describe this extreme scenario as a Frictionless Economy. Thus, the Frictionless Economy benchmark assumes that a country is not home-biased if the share of consumption of domestic products equals the share of the production of that country in the OECD production, 3 i.e., Production Exports to non-oecd Frictionless Economy Benchmark = Total OECD Production Total Exports to non-oecd Through this benchmark, we remove in a simple way the home country size effect which allows us to compare across countries the extent to which demand in one country is biased towards domestic products. In the case of equity markets, this benchmark is consistent with the capital asset pricing model which assumes symmetry across investors and countries and predicts that all agents would hold the same market portfolio in which the fraction of investment at home is equal to the value of the domestic stock market relative to the value of the world stock market Integrated Economy Benchmark A home-biased country would consume a larger number of domestic products than products from an imaginary identical (superposed) country. Home bias can also be 3 We limit our analysis to goods and services that are produced and consumed within the OECD. 4 See Cochrane (2001). 6

8 interpreted as how much a country trades internally in excess of what it would trade with a country of similar economic and geographic size. Using data on foreign trade (which, by definition, is absent of home bias ) one can estimate how trade depends on size of trading partners and on distance between them. Based on these estimates, one can construct an imaginary identical country and estimate how much a country would trade with such an imaginary trade partner. 5 This would be equivalent to domestic trade in the absence of home bias. We define an Integrated Economy as an economy where countries trade as much internally as they would trade with an identical partner. The Integrated Economy benchmark assumes a country is not home-biased if domestic trade (i.e. a country s trade with itself) equals the trade it would have with a country of equivalent economic size and distance. 6 To construct this benchmark, we use data on current bilateral trade to estimate, by means of a standard gravity trade equation, 7 how trade depends on economic size of partners, distance 8 and other variables. On the basis of the estimates, we calculate the value of goods and services a country would import from a partner of equal economic and geographic size. This would be equivalent to the demand of domestic products in the absence of home bias. (See Annex V for more details). The Integrated Economy benchmark would be therefore be given by Estimated Demand Domestic Products (no Home Bias) Integrated Economy Benchmark = Total Demand 3. Home bias in the EU To determine the degree of home bias we measure to what extent demand for domestic products and investment in domestic equity deviate from the defined benchmarks. The home bias indicators express how much a country s demand for domestic products and for domestic equity exceeds the benchmarks which are meant to represent the absence of home bias. That is, home bias in product markets reflects the excess of internal trade over what the internal trade would be in the absence of home bias (i.e. the definition of internal trade being given by the two benchmarks). Similarly, home bias in equity markets reflects the excess of investment in home equity over what the investment in home equity would be in the absence of home bias. 5 This is equivalent to the home bias benchmarks used commonly in the gravity models literature. See, e.g., Nitsch (2000). 6 Internal distance measures take into account the country size and the distribution of population within the country. The distance within a country is increasing on the size of the country and decreasing on the concentration of population. See section 3.1 on data for more details. 7 For an overview of recent research on the success of gravity models in explaining border effects see Baldwin (2005) and Balta (2005). 8 Distance is a proxy not only for physical distance but also for information and other trade costs. 7

9 We first describe the data and data sources and then proceed to the analysis and discussion of the results Data Data on production and goods trade is obtained from the OECD STAN Database on Production and on Bilateral Trade in Goods. Data on services trade comes from OECD Statistics on International Trade in Services. All nominal yearly values in millions of U.S. dollars are deflated by the US GDP deflator (from IMF s IFS database) so that the indicators are based on volumes. We calculate the demand for home goods and services as the difference between domestic production and exports. For goods the data set covers the period while for services the period covered is The analysis covers OECD countries. For the analysis of services, we have excluded from the sample Ireland, Luxembourg, Australia, Iceland, Korea, New Zealand, Switzerland, Mexico, Poland and Turkey due to lack of data either on production or trade in services. For the analysis of goods we have excluded Belgium, Ireland, Luxembourg, Australia, Iceland, Korea, New Zealand and Turkey. The analysis of goods and services jointly includes the same sample of countries as in the case of services. Production is defined as the value of goods and services produced in a year, whether sold or stocked. It includes intermediate inputs (such as energy, materials and services required to produce final output). Exports data might include re-exports which makes possible that exports are larger than production (we have excluded Belgium from our analysis of goods market for this reason). Data on cross-border equity holdings is obtained from the IMF Consolidated Portfolio Investment Survey (CPIS) and stock market capitalisation data from Eurostat. CPIS provides data for 1997, for each participating country with a geographical decomposition across 218 destinations. Due to missing observations for a significant subsample of countries for 1997, we focus on the period CPIS data is not completely accurate since some countries might be under-reporting and in most cases there is no clear tracking of the end investor. Luxembourg and Ireland are excluded from the sample because the impossibility to track end investors does not allow determining the amount of investment that remains in the country and the volume which is redirected to third countries. 9 Netherlands and Portugal are excluded due to lack of data on domestic market capitalisation. Iceland, Korea, New Zealand, Mexico and Turkey are also excluded. The value of domestic holdings of home equity is determined as the difference between domestic market capitalisation and the value of equity held by foreign investors. In order to construct the Integrated Economy Benchmark we estimate a simple gravity equation (Equation (1) in Annex V for goods and services and Equation (2) in Annex V for equity 9 For a detailed description of this dataset see Lane and Milesi-Feretti (2004, 2005). 8

10 holdings). We use data on GDP from IMF s IFS database and data on distance between countries, language and borders from CEPII. 10 The estimated value of home bias in gravity models depends crucially on the measure of internal distance. Overestimation or underestimation of internal distances relative to international distances may create illusory border effects. 11 CEPII offers alternative measures of distances between and within countries. 12 The measure we use calculates distance between two countries (or within a country) based on bilateral distances between the biggest cities of those two countries (or the biggest cities within a country in case of internal distances). The inter-city distances are weighted by the share of the city in the overall country s population Empirical Results We limit our analysis to OECD countries since OECD countries constitute a relatively homogeneous set of economies with similar structures and trade patterns. Thus, our home bias measures provide an indication of how integrated countries are within the group of OECD countries. 14 Countries with low indicators would show they are well integrated within the OECD block. The indicators do not however provide a measure on to what extent countries are integrated within the world economy unless one considers OECD as a good proxy for the world. Trade within OECD countries accounts for nearly 70 per cent of total world trade, but the share of trade with OECD countries changes substantially from country to country. For example, the US and Japan (and to a lesser extent Greece) trade substantially more with partners outside the OECD than other countries. In the case of equity, OECD countries account for 90 per cent of the world stock market capitalisation. Therefore, the sample can be considered as a good proxy for global integration in world equity markets. Detailed results per country are shown in Annex IV Home bias in product markets Europeans have a strong bias for goods and services produced within the EU. The share of domestic consumption of EU15 products in the total OECD products consumed within the EU15 is 96 per cent. The weight of domestic consumption of home goods and services in domestic demand is similar in the US. On average, a EU15 country spends 86 per cent in home products, 10 per cent in products from other EU15 countries and 4 per cent in products from other OECD countries (Annex I, Chart 1 in Figure 1) See Head and Mayer (2000) on this debate This distance measure corresponds to the distance distw as described in Notes on CEPII s distances measures by T. Mayer and S. Zignago at 14 Note that the measures of home bias we use depend on the countries we include in the sample and are not comparable for different sample sizes. 9

11 The Frictionless Economy benchmark only takes into account the economic size of the home country. As the EU15 countries share of domestic products is well above their share in OECD production, they appear to be highly home-biased (Annex I, Chart 2 in Figure 1). By contrast, the U.S. which accounts for close to 45 per cent of OECD production appears to be much less home-biased (Chart 2 in Figure 1: 51 per cent in the US as compared to 89 per cent for the average EU15 country in 2003). The same is actually true, though to a lesser extent, if we consider EU15 as a whole (i.e. as a single country) for which home bias is 60 per cent. The Integrated Economy benchmark allows taking into account both the economic and geographic size of countries. Including both variables implies a decrease in home bias for most EU15 countries (Annex I, Chart 3 in Figure 1) but trade within the typical EU15 country still remains much higher than one would expect in an Integrated Economy. The picture changes for the US, however in the opposite way: it now becomes more home-biased than EU15 countries. 15 Home bias within the EU Both benchmarks depict a similar picture for the EU (Annex I, Chart 2 and 3 in Figure 1). Home bias is generally lower in core EU15 countries (Netherlands, Belgium, Austria and Germany) than in the periphery (Greece, Italy, Spain, Nordic countries). Surprisingly, some of the countries that run large trade deficits such as Greece, Italy and Spain are amongst the most home-biased. This implies that not only their imports are low but also their export performance is poor. Amongst the new member states in the sample, the Czech Republic and Hungary have a lower degree of home bias in goods and services than the EU15 average, which reflects the increasing integration of these countries with Western Europe. Goods and services In order to assess to what extent the degree of home bias is driven by the increasing role of services (which are generally less tradable) we analyse the goods market and the services market separately. As expected, the share of home goods in total demand for goods is much lower than the share of home services in total demand for services. (Annex I, Chart 1 in Figure 2 shows the share of home goods in total demand for goods and Chart 1 in Figure 3 the share of home services in total demand for services). Average home bias is lower in goods than in services reflecting the fact that services are less tradable than goods. Home bias in a typical EU15 country is 60 per cent for goods and 94 per cent for services (Annex I, Chart 3 in Figure 2 and Chart 3 in Figure 3). In the case of goods, the least home-biased countries are the Netherlands, Austria and Denmark 16. On the other end, Greece, Spain and Finland have a high degree of home bias. 15 As explained before, the measure of home bias provided by this indicator relies on the measure of internal distance considered which is especially sensitive for very large and very small countries. 16 Belgium, which is excluded from the sample (see section on Data) would also be within this group. 10

12 For services there are barely differences across countries. Most countries home bias in services is above 90 per cent. Services still represent a very small share of international trade. The potential for trade of services varies substantially from sector to sector. A more realistic benchmark of home bias would have to take into account the product characteristics and the feasibility of international trade. In addition, services trade statistics are less reliable than goods trade statistics due to the difficulty to measure some forms of trade in services (e.g. when it is the provider and not the service itself the one that crosses the border). Recent evolution of home bias Between 2000 and 2003 home bias in goods and services has barely changed (Figure 6 in Annex II and Table A3 in annex IV). If we look separately at goods and services we observe that the tendency is similar so the increasing weight of services in the economy cannot be blamed for the stalled evolution of home bias. Unfortunately, there is no comparable data for trade in services before However, looking at data on goods for the period (see Figure 6 in Annex II and Table A5 in annex IV) we observe a substantial decrease in home bias for most countries (generally above 5 percentage points). This evolution is truncated from 2000 onwards. This is consistent with the fact that intra-eu trade in goods grew faster than GDP between the mid-90s and 2000, but it stalled in early Since services account on average for 75 per cent of production in the average OECD country, the large home bias in goods and services is highly determined by the large home bias in services. However, between 2000 and 2003, the degree of home bias has not changed not only due to the increasing weight of services but also due to the stalled evolution of trade in goods. Sensitivity analysis The magnitude of the Integrated Economy benchmark depends on the underlying gravity model used to obtain the estimate of internal trade in the absence of home bias. In order to estimate the demand for domestic products in an integrated economy, we have used a simple standard gravity equation that accounts for economic size of the countries of origin and destination and distance (Equation 1 in Annex V). In order to get a true sense of the estimated errors (i.e. of the fitted value for internal trade that we have considered in building the benchmark), we have analyzed other model specifications with additional controls that reflect proxies for trade costs. The results for goods and services are reported in Table 1. The results for goods and services separately are reported in Annex III (Tables A1 and A2). We start by estimating a simple model where only the GDP of the country of origin and destination and distance between the trade partners are considered as independent variables and we subsequently add additional controls to end up estimating the equation below. 11

13 X = α + hom ebias+ α GDP + α GDP + α dist + homeeu+intraeu15+ com _ border+ com _ lang + u ij 1 2 i 3 j 4 ij ij where X ij is the exports from country i to country j, homebias is a dummy variable that takes value one for domestic trade and zero otherwise, GDP i is real GDP of country i, dist ij is the distance between country i and country j, homeeu is a dummy variable that takes value one for domestic trade in EU15 countries, intraeu15 is a dummy variable that takes value one for trade between EU15 countries 17 and zero otherwise, com_language/com_border are dummy variables that equal one when countries share a common language/border 18 and u ij is the error term. The estimated model also includes yearly dummies. Our sample is not randomly generated: a large exporter will generally export more to all countries which implies that exports originated in one country will be correlated and so the estimation errors. We therefore use GLS with random effects by country of origin as estimation method which allows for a common error term for each country of origin, i.e., the error term is decomposed as uij = ei + vij Trade is increasing in the GDP of the countries of origin and destination and decreasing in distance. The values of the coefficients are consistent with those obtained in the literature (e.g. Nitsch, 2000). Average home bias for OECD countries in the sample is estimated to be 3.36 in the simplest specification of the model, indicating that a country trades about 28.8 times (i.e. exp [3.36] = 28.8) more with itself than with a foreign country of similar economic and geographic size. Home bias is slightly lower for EU15 countries which trade about 22 times (i.e. exp [ ] = 21.9) more internally than with a trading partner of similar size. The fact that we include both trade in goods and services in our equations makes that our estimates of home bias are higher than in previous work which focussed only on goods (e.g. Nitsch, 2000, and Wolf, 2000). All the results should however be interpreted with caution since there still might be an omitted variable bias stemming out from elements that are correlated with the homebias dummy and not included in the regression causing an upward bias in the estimates. However, this is a caveat of all gravity models due to omission of a range of factors that are likely to affect bilateral trade and are difficult to capture (e.g. see Baldwin, 2006, for a detailed analysis of the caveats of gravity models). In constructing our benchmark, we have used the estimates from the simplest specification that gives the smallest value for home bias. Home bias increases as we add more control variables implying that the benchmark for an integrated economy would be lower if we used more comprehensive specifications of the gravity equation. 17 This dummy takes value one only for trade between EU15 countries but not for trade within EU15 countries. The role of this variable is to analyse whether EU15 countries trade more among themselves than other countries. 18 All specifications contain yearly dummies. 12

14 Tables A1 and A2 in Annex III confirm that home bias is higher for services than for goods. For the case of goods, the average country trades about 11.5 times (i.e. exp [2.44] = 11.5) more internally than with a trade partner of equal size and distance while for services this figure is 129 (i.e. exp [4.86] = 129). Both for trade in goods and trade in services, the average home bias in EU15 countries is lower than the average home bias in OECD countries (i.e. exp [ ] = 7.2 times for goods and exp [ ] = 97.5 times for services, respectively). In the case of goods, the estimates are found to be lower than those of Nitsch (2000), who estimates for the period that an EU country exports to itself times more than to other countries. Finally, as one could expect, geographical and cultural proximity (i.e. sharing a border and a language) is more important for trading services than for trading goods. Table 1. Home Bias in Goods and Services Dependent variable: Log of Export volume (1) (2) (3) (4) (5) (6) GDP origin 0.87 (0.04)* 0.87 (0.04)* 0.88 (0.04)* 0.85 (0.04)* 0.86 (0.04)* 0.84 (0.04)* GDP destination 0.93 (0.01)* 0.93 (0.01)* 0.93 (0.01)* 0.90 (0.01)* 0.92 (0.01)* 0.90 (0.01)* Distance (0.02)* (0.02)* (0.02)* (0.02)* (0.02)* (0.02)* Home bias 3.36 (0.09)* 3.94 (0.15)* 3.92 (0.15)* 4.24 (0.15)* 4.02 (0.14)* 4.24 (0.14)* Home bias EU (0.17)* (0.17)* (0.17)* (0.17)* (0.17)* Intra-EU trade (0.04) 0.02 (0.04) (0.04) 0.02 (0.04) Common border 0.60 (0.05)* 0.48 Common language # observations R 2 overall Estimation method Random effects GLS Random effects GLS Random effects GLS Random effects GLS Random effects GLS Note: Standard errors in brackets; *, **, *** denote significance at 1, 5, and 10 per cent levels, respectively. Results on constant and yearly dummies are not reported. Sample includes OECD countries except Ireland, Luxembourg, Australia, Iceland, Korea, New Zealand, Switzerland, Mexico, Poland and Turkey. Sample period: Random effects GLS 13

15 Home Bias in Equity Markets Europeans also invest heavily in the EU15: 83 per cent of their equity wealth is invested within the EU15 which is slightly lower than the share Americans invest within the US. The average EU15 country invests around 65 per cent of its equity wealth at home, 18 per cent in other EU15 countries and 17 per cent in other OECD countries. On average, EU15 countries invest at home less than OECD countries, which invest domestically 80 per cent of their equity wealth (Annex I, Chart 1 in Figure 4). In a Frictionless Economy (Annex I, Chart 2 in Figure 4), once again since EU15 countries market capitalisation is small with reference to total OECD market capitalisation, their home bias appears high. The US, even though it invests more than EU countries at home, appears less home-biased than the typical EU15 country since it accounts for half of the total OECD market capitalisation. Home bias in the EU15 as a whole (i.e. as a single country) is around 58 per cent. Using the Integrated Economy benchmark does not change much the picture for EU15 countries (Annex I, Chart 3 in Figure 4). However, it does for the US, which now appears to be much more home-biased than the average EU country. Home bias within the EU The situation within the EU is rather heterogeneous: holdings of domestic equity range from 41 per cent in Austria to 93 per cent in Greece. Austria, Belgium, Italy, Sweden and Germany invest the least in domestic equity while Greece and Spain invest heavily in domestic equity. New Member States equity holdings are mainly domestic. Recent evolution of home bias Unlike in the case of goods and services, home bias has decreased substantially in the recent years (see Figure 7 in Annex II and Table A6 in Annex IV) probably not only due to European integration policies but also due to the global process of financial integration. The significant decrease in home bias is not homogeneous across the EU. For example, the decrease has been substantial in Belgium, Germany, France and the Nordic country but more modest in Greece and Spain. In Austria, which has one of the lowest degrees of home bias in the EU, home bias has increased. Barriers to cross border financial investment have been substantially reduced in recent years. The preference for home companies stocks remains probably higher than what can be explained by information asymmetries, but change is without doubt under way Sensitivity analysis As in the case of goods and services, the estimate of the Integrated Economy benchmark depends on the specification of the gravity equation. To calculate the integrated economy benchmark we use a simple version of the standard gravity equation. We next analyse how the measure of home bias is affected by including additional control variables. 14

16 Similarly to the case of goods and services, we start by estimating a simple model where only GDP of the countries of origin and destination and distance are included as independent variables and we subsequently add additional controls to end up estimating the equation below. 19 E = α + home+ α GDP + α GDP + α dist + homeeu+intraeu15+com_border+com_lang+u ij 1 2 i 3 j 4 ij ij where E ij represents equity of country j hold by investors from country i and the rest of the variables are defined as in the gravity equation for goods and services. Table 2 shows the estimation results. Home bias appears to be higher for equity holdings than for goods and services. This might be misleading given than in principle equity portfolios seem to be more diversified than consumption baskets. This is however explained by the fact that the estimate of home equity investment in the absence of home bias is much lower than the true value (i.e. investment in home equity in the absence of home bias is much lower than demand for domestic products relative to real investment and demand respectively). The home bias coefficient is therefore much larger for equity markets than for product markets. Also, the gravity equation fits much better the data on trade in goods and services than the data on cross-border equity investment so results have to be compared with caution. The economic size of the country of origin becomes more important in determining the patterns of investment than the patterns of trade while distance plays a less relevant role than in the case of goods and services (the coefficient is 50 percent higher for the size of the country of origin and between 10 and 50 percent lower for distance). This is somehow logical: the wealth of the country of origin is more relevant for investment decisions than the wealth of the country of destination. Also, obstacles correlated to distance 20 are lower for equity investment than for trade. The coefficient of intra-eu investment is large and positive showing the preference of EU15 investors for EU15 equity. The average home bias in the OECD in the simple specification shows that domestic investors hold domestic equity 72 times (i.e. exp [4.28] = 72.2) more than in a partner of equal economic and geographic size. For the average EU15 country the home bias in equity holdings is less than half the average home bias in OECD countries (i.e. exp [ ] = 35.2 times). 19 Several papers use gravity models to explain cross-border equity holdings. For example, Faruqee et al (2004) find that the market size, transaction cost and information asymmetry are major determinants in cross-border portfolio choice. 20 Distance in the case of equity holdings is a proxy for transaction and especially information costs. 15

17 Table 2. Home Bias in Equity Holdings Dependent variable: Log of cross border stock holdings (1) (2) (3) (4) (5) (6) GDP origin 1.59 (0.15)* 1.59 (0.16)* 1.54 (0.14)* (0.13)* (0.14)* (0.14)* GDP destination 0.99 (0.03)* 0.99 (0.03)* 0.96 (0.03)* 0.92 (0.03)* 0.92 (0.03)* 0.91 (0.03)* Distance (0.05)* (0.05)* (0.05)* (0.05)* Home bias 4.28 (0.24)* 5.06 (0.32)* 5.50 (0.32)* 5.90 (0.31)* 5.96 (0.32)* 6.06 (0.32)* Home bias EU (0.41)* (0.41)** (0.40)** (0.41)*** (0.40)*** Intra-EU trade 1.17 (0.12)* 1.24 (0.12)* 1.26 (0.12)* 1.27 (0.12)* Common border 0.60 (0.15)* 1.47 (0.15)* Common language 0.91 (0.16)* 0.37 (0.16)** # observations R 2 overall Estimation method Random effects GLS Random effects GLS Random effects GLS Random effects GLS Random effects GLS Random effects GLS Note: Standard errors in brackets; *, **, *** denote significance at 1, 5, and 10 per cent levels, respectively. Results on constant and yearly dummies are not reported. Sample includes OECD countries except Luxembourg and Ireland, Portugal, Netherlands, Iceland, Korea, New Zealand, Mexico, and Turkey. Sample period: Product vs. equity markets As shown in the previous sections, the degree of home bias in product markets and equity holding varies significantly from country to country. But how do home bias in product markets and equity holdings compare? Frictions in the financial markets are not sufficient to explain the high degree of home bias observed in financial markets. Obstfeld and Rogoff (2000) analyse with a theoretical model how frictions in trade can induce home bias in investors portfolios. They predict that frictions in product markets could be responsible not only for home bias in product markets but also for the excessive home bias in financial markets that otherwise would not be consistent with the current degree of globalization of financial markets. Their underlying argument is that more openness to trade will imply more competition in product markets which will make prices and profits more volatile. To protect against this increasing volatility of the economy investors will tend to diversify their portfolios and consequently home bias in equity holdings will be lower. Lane and Milesi-Ferretti (2004) test this model empirically and find empirical evidence of this link. 16

18 Our sample shows a slightly positive correlation between home bias in product markets and equity holdings (see Figure 5 in Annex I). Belgium and Austria appear to be the least home-biased countries in the EU. On the other end, Greece and Spain are the most homebiased both in product markets and equity holdings. Germany shows a relatively low degree of home bias in product markets and a rather diversified equity portfolio. However, this later figure has to be interpreted with caution since Germany has one of the smallest market capitalisation to GDP ratios in the EU Therefore, the fact that German investors invest more in foreign equity could be a consequence of the lack of supply of domestic equity rather than a higher degree of integration. Italy, Finland and Sweden have relatively large home bias in consumption and fairly diversified portfolio holdings. In the case of Italy, as for Germany, the fact that the equity portfolio is diversified could respond to the small size of its domestic equity market. The two new Member States in the sample, Hungary and the Czech Republic, have rapidly integrated their product markets but their equity portfolios remain largely local. The good performance of their stock markets in recent years might have prevented investors from investing abroad. In case this pattern of investment continued to hold as equity markets grow, this could entangle some risks for these countries economies. If there were a loss in competitiveness of domestic industries in international markets and investment portfolios were mainly composed of national equity, the potential loss of country wealth would not only occur via product markets but also via equity markets. As in most of the new member states, stock markets in Hungary and Czech Republic are still underdeveloped and do not constitute either an important source of funding for firms or an important savings instrument. Therefore, such risks at the moment would be limited. 5. Concluding remarks and policy implications In this paper we assess the degree of home bias in the EU for product markets and equity holdings by comparing the demand for home products and the holding of home equity to two benchmarks that take in to account the economic and geographical size of countries. The home bias indicators allow for assessing the performance of integration policies in the EU and to compare the level of integration in terms of trade and investment of EU15 countries with other countries. Europeans mostly shop and to a large extent invest at home. Despite the process of European integration, the degree of home bias in the product markets and equity holdings remains considerably high. The evidence shows that (a) national borders still matter (b) their importance varies considerably from country to country and (c) while there is momentum in financial markets, it has stalled in product markets. In general, EU15 countries consume home products and invest in home equity well in excess of the benchmarks. This is not only the case for services, which could be expected given their lower tradability, but also, though to a lesser extent for goods and equity. In 21 The market capitalisation to GDP ratio of the EU15 is close to 70 per cent while in Germany is under 40 per cent. 17

19 comparison to their economic size, EU15 countries are more home-biased than other OECD countries such as Japan and the US. However, EU15 countries appear to be less home-biased when geographic size and economic size of partners are taken into account. Home bias has stalled after 2000 for goods and services while in equity markets it has decreased substantially in the recent years. The preference for home companies stocks remains probably higher than what can be explained by information asymmetries, but change is without doubt under way (see De Santis and Gerard, 2006). It is not possible to track back the evolution of home bias for services and equity holdings before 2000 because of the lack of available data on services trade and on cross border equity holdings. However, in the case of goods we find that home bias decreased between the mid-90s and 2000 but it stagnated afterwards. The stagnation of home bias after 2000 might indicate a lack of effect of integration policies which might be calling for a review of the assumptions the Single Market strategy was based on. The economic context nowadays is not the same as twenty years ago when the SMP was designed and implemented. The degree of home bias varies across Europe. While countries such as the Netherlands, Belgium, Austria and Germany appear to be well integrated, some others such as Greece and Spain show a low level of demand for foreign products and equity. The new EU member states in the sample show a degree of home bias in product markets similar to the EU15 average. However, their equity portfolios remain very home-biased. A homogeneous degree of integration of goods and capital markets is essential for the effectiveness of macroeconomic policies. Within the Euroarea, exchange rates and interest rates are no longer available to tackle the consequences of asymmetric shocks. Therefore, in order to make sure that monetary policy responds effectively to the needs of the economy it is important that countries have similar levels of integration. Also, asymmetries within countries can also involve risks, especially when product markets are more open than financial markets as it is currently the case in Hungary and the Czech Republic. A loss in competitiveness of their domestic industry would be immediately translated into their financial markets, increasing the effect of the shock in the country s wealth. While significant, the effects of the Single Market on goods trade as well as those of overall liberalisation seem not to have thus been sustained enough to compensate the move to a more service-based economy. Progress however continues to be substantial in financial markets. The current momentum of financial integration and reform could certainly help reform in other fields. But financial integration can hardly continue advancing if there is no progress in product and labour markets. The current imbalances in the progress of integration make the whole process fragile and undermines the ability of the EU to make the most of one of its greatest achievements the Single Market. 18

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