Sebastián Nieto Parra
email: sebastian.nietoparra@sciences-po.org

Javier Santiso
email: javier.santiso@oecd.org

Mike Buchanan

Arnab Das

Juan Flores

Michael Gavin

Lawrence Goodman

Juan Martinez

Walter Molano

Elizabeth Nash

Gray Newman

Eduardo Pedreira

Nilson Teixeira All

The Usual Suspects: Investment Banks' Recommendations and Emerging Markets FIRST DRAFT

Keywords: Brokers Research, Portfolio Flows, Information Asymmetries, Emerging Markets JEL Number: F21, F32, F34, G15, G14

The paper addresses two core questions: do recommendations have an impact on the allocation of flows in the asset class? Above all, are we facing in this asset class major problems of asymmetries of information? In order to answer these questions, we used untapped and rich datasets. We constructed a unique database covering the period 1997-2006 for all the bond recommendations by the major Wall Street and City investment banks that dominate the emerging bond markets. The most important and relevant results are as follows. First, 90% of the underwriters recommend, at the announcement date of the issue, to buy or to maintain in their portfolio the bonds issued by the countries where they are acting as lead managers. Second, there is an additional bias, investment banks' recommendations depend also on the relative size of the secondary bond market. In fact, there is a phenomenon that we call "too big to underwrite" meaning that investment banks do not send negative signals to investors of countries that, given their size, are considered important for their business. Finally, by using a simple cross-section analysis, we found that the impact of investment banks' recommendations on capital flows is more significant and more predictable than some macroeconomic variables such as interest rates, economic growth and inflation.

Introduction

Since the beginning of the XXIst century, emerging markets have reached a kind of nirvana. The global search for higher returns led to record inflows of liquidity into dedicated emerging markets' bond and equity funds, especially in 2005 and 2006. In 2005, emerging market equity funds absorbed more than USD 20 bn on net inflows, five times more than the previous year and beating the record of 2003, according to data from Emerging Portfolio Fund Research, a US company that tracks fund flows around the world. Emerging bond markets also soared, breaking the previous record of inflows as more than USD 10 bn flew to these funds in 2005 against a meager USD 3 bn in 2004. The year 2006 saw an even more impressive turn of events: in January, global net inflows into emerging markets equities topped more than USD 11 bn, that is more than half of last year's total in a single month. In the first quarter alone of 2006, inflows exceeded those received during the whole of 2005.

The search for yield explains much of this story. Historically low interest rates in developed countries and soaring global liquidity, combined with structural macroeconomic improvements in the emerging markets asset class, led to an impressive search for yield that benefited emerging markets. This environment has been particularly favorable for investment banks with huge amounts of money pouring into the asset class, fees burgeoning and massive deals in the pipeline. The multilateral officials were probably the only unhappy people in the crowd, fearing that their institutions could be relegated to the trash heap of history. In Wall Street and the City, while yield-hungry buyers were casting the net wider in the hunt for returns, analysts and investment bankers were opening champagne.

However, this emerging market boom is not new. During the late nineteenth century, Latin American countries, for example, already experienced a massive foreign investment boom. A major part of the inflows took the form of sovereign debt, the bonds being traded in European financial centers. By that time, the market value of emerging market debt traded in London was impressive: at the turn of the XXth century, by 1905, its value was equivalent to 12% of world GDP. One century later, in 1999, the total volume of emerging debt market traded was however a meager 2,7% of world GDP. The recent allure of emerging markets has seen debt trading value jump to USD 5 500 bn in 2005 (roughly 12% of world GDP), which is simply restoring the position already reached 100 years ago.

Therefore, even if in nominal terms we are witnessing an explosion of bond flows towards emerging markets, this pales in comparison to the previous globalization era, in relation to the size of the world's economies. Not only was the previous era of global finance much more open in terms of total capital flows but emerging markets were also very present within London asset managers and bank portfolios. The largest bondholder of long-term cross border investments at the turn of the XXth Century was the United Kingdom, accounting for nearly half of all cross-border investments in the early XXth Century. At the time, about 30% of its investments were in government debt, 40% in railways, 10% in mining, and 5% in utilities. According to estimates from Mauro et al (Mauro et al., 2002), by 1905, the market value of emerging markets bonds traded in London reached 25% of all government bonds traded in the City! By comparison, in recent years, US institutional investors have had barely 10% of their portfolios invested in foreign securities, with a meagre fraction of that capital devoted to emerging markets.

The asymmetries of information were also impressive by that time. In both periods of finance globalization news about wars or episodes of politically-motivated violence have been a significant and robust determinant of spreads. One difference is that in the first era, country-specific fundamentals account for a greater share of variation in spreads than they do today (Mauro, Sussman, and Yafeh, 2006). Another is that information asymmetries tend to be lower today than in the previous era, as also reflected by risk premiums. Although it is now hard to imagine a story such as that of Gregor McGregor, a Scottish trader and adventurer who "invented" a country, Poyais, and subsequently paper traded on that country in London during the 1820s, asymmetries of information still remain a concern today. Poyais was a fictious state that nevertheless borrowed on the London market in 1822. When investors discovered the fraud one year later and ceased to traded the worthless papers it ended in one of the first big series of Latin defaults. By the mid XIXth Century, as illustrated by the fictitious Poyais country, which managed to borrow on the same terms as legitimate states such as Chile, Colombia or Peru, the ability to distinguish between Latin American countries was scarce.

Today a repeat of this story is impossible: the levels of information are higher, the density and complexity of players is also greater. However asymmetries of information remain. One, in particular, which concerns mostly developed economies and equity markets is related to the autonomy of financial research. Most of the studies underline the bias with which the industry is plagued. However the empirical evidence on emerging markets is pretty scarce. If some studies have been conducted on emerging equity analysts, hardly any exist on emerging bond markets. Our study provides a first attempt to fill this gap. It addresses two core questions: are broker recommendations useful in emerging bond markets? In other terms do buy or sell recommendations have an impact on the allocation of flows in the asset class? Above all are we facing in this asset class similar problems of asymmetries of information? Are brokers' recommendations biased towards positive outlooks?

The remainder of this article is organized as follows. In Section two, we provide a review of the literature. In Section three, we describe the datasets we used, among them a unique and untapped dataset of all brokers' recommendations between 1997 to 2006 for Latin American emerging markets. In the fourth section, we study the relationship between investment banks' recommendations and some aspects related to the business of these banks (in particular sell-side business). This section gives some preliminary results in order to understand whether banks' advice to investors is biased. For that we analyzed firstly underwriters' recommendations and secondly the relationship between the size of emerging markets and recommendations. Section five analyzes the impact of broker recommendations on private capital flows towards emerging markets, matching the aforementioned database with another one on private portfolio flows. Lastly in the sixth section we conclude by giving the most important results of this paper and we open the door to future research by employing the newly constructed database.

Overview of the literature

One of the most important factors affecting the efficiency of capital markets is the problem of asymmetry information between financial actors. More precisely, in an Initial Public Offering (IPO), an information advantage can arise concerning "fundamentals" of the security for the agent in charge of the underwriting (the bank) over the buyer of the security (the investor). This advantage allows underwriters, through reports made by market analysts, to send to investors recommendations biased towards increasing underwriters' profits, given that part of the payment made by the issuer to the underwriter depends on the "success" of the issue in the primary market.

Empirical literature has mainly investigated these stock market issues in relation to OECD countries. [START_REF] Womack | Do brokerage analysts' recommendations have investment value?[END_REF], for example, studied the impact that a recommendation may have on the price of a share issued in the American market by analyzing the excess return in the short and medium-term following a buy or sell recommendation made by analysts of the major brokerage firms. More recently, [START_REF] Jackson | Trade Generation, Reputation, and Sell-Side Analysts[END_REF] instances the Australian equity market to demonstrate that analysts are confronted by a trade-off between sending true signals to the market (thereby building up one's reputation) and sending optimistic recommendations to obtain the short-term benefit of higher commissions.

Studies of the relation between underwriters and recommendations are scarcer, and the results suggest there is a conflict of interest between different sides of an investment bank department, such as between the side charged with issuing securities and the research department. Analyzing the US equity market, [START_REF] Roni | Conflict of interest and the credibility of underwriter analyst recommendations[END_REF] found for example that 'stocks that underwriter analysts recommend perform more poorly than "buy" recommendations by unaffiliated brokers prior to, at the time of, and subsequent to the recommendation date', which suggests that recommendations by underwriter-analysts are biased.

From a theoretical point of view, the research literature concerning this topic is rich and useful. [START_REF] Myers | Corporate Financing and Investment decisions when firms have information that investors do not have[END_REF] studied an asymmetric information problem involving managers of a firm about to issue stock to raise cash and potential investors. In the same vein, [START_REF] Stein | Efficient Capital Markets, Inefficient Firms: A model of Myopic Corporate Behavior[END_REF] modelled a non-cooperative game between managers and rational investors that yielded the short-term behaviour of equity prices following earnings manipulations by the managers. More relevant to our research, [START_REF] Benabou | Using privileged information to manipulate markets: insiders, gurus and credibility[END_REF] studied the manipulation of prices by the effect of private and preannouncements on prices. However, they noted that under some conditions investors can resolve this problem in the long run by reassessing the credibility of the individuals offering private information (the research analysts).

The purpose of our study is to focus on emerging markets that have not yet been analyzed from this angle. More precisely we intend to analyze this asymmetric information problem in relation to the bonds issued by Latin American governments through international banks (the underwriters) in the US and European capital markets. Our point of departure is [START_REF] Santiso | The Political Economy of Emerging Markets: Actors, Institutions and Financial Crises in Latin America[END_REF], which analyzes the political economy of Latin American emerging markets, focusing the attention on actors and institutions.

Research analysts play a centre role in financial markets. Together with fund managers they are at the heart of the confidence game [START_REF] Santiso | The Political Economy of Emerging Markets: Actors, Institutions and Financial Crises in Latin America[END_REF]. Their recommendations influence the price of a company's stock or a sovereign bond. They live in a forward-looking world where anticipation and prediction (of rises or falls) is the key to reaching a financial nirvana measured in extra bonuses. Their cognitive regime is imbedded in short-term horizons, research and trade priorities and therefore potential conflicts of interest.

These research analysts study companies and sovereigns in emerging markets and make buy and sell recommendations on the securities of the firms they cover. They are usually specialized in a particular industry, sector or, for emerging markets, particular countries and areas, Latin America being in itself an asset class. Whether or not a company or country is covered by research analysts is a central issue. Without significant coverage by the industry, the company or country simply does not exist in the financial world 3 . Obviously being positively or negatively covered also matters as the analysts' outputs and opinions about a firm or a country are precious signals to which investors react. As underlined by academics, investors react to the information contained in analysts' earnings forecasts, stock recommendations and also target prices 4 .

One major concern during the 1990s has been both their influence and independence. Analysts belong to institutions, for example investment banks, that are not homogeneous entities. Within each institution, each division and each department pursues certain goals and strategies that are linked with the firm, but that may conflict with one another. Investment banks for example have at least three identified sources of income that are basically brokerage services; (i) corporate finance activities, issuance of securities; (ii) merger and acquisitions advisory services; and (iii) proprietary trading. These three sources of income may create conflicts of interest within the firm, between departments and divisions, but also outside the firm with its potential or current clients. A frequent and observable conflict of interest occurs between investment banking and brokerage activities. The corporate division of a bank is responsible for the issuance of an 3 The consequence of this is that companies or countries have to fight to be included in indexes or simply to be covered by analysts. This means for a company, for example, to present coherent products and corporate strategies easily and clearly indentifiable by stock market analysts. As underlined by Ezra Zuckerman, « a firm that participates in a given industry but does not draw attention from industry socialists can be described as suffering from coverage » and tend to contribute to diversifying strategies by corporate managers in order that their stock could be more easily understood by financial analysts. See Ezra Zuckerman, « Focusing the corporate product: securities analysts and de-diversification », Administrative Science Quarterly, n° 45, 2000, pp. 591-619. 4 See Alon Brav and Reuven Lehavy, « An empirical analysis of analysts' target prices: short term informativeness and long term dynamics », Duke University and University of California at Berkeley, May 2001 (unpublished) ; Mark Bradshaw, « How do analysts use their forecasts ? », Harvard Business School Working Paper, 2000 (unpublished). initial public offering (IPO) or a merger and acquisition for a client. The brokerage house of the firm, through its equity department, is responsible for covering the stock with a clear objective of delivering timely, unbiased and high quality information to clients that are investors. Clearly the objectives of the corporate division can clash with those of the equity research department.

In this case, analysts will do their best to deliver the most valuable and independent opinion. For this they use a narrow range of terms to qualify their recommendations -buy, strong buy, hold, neutral, over-perform or under-perform. However, one of the paradoxes underlined by the US Securities Exchange Commission in 2001, is that these analyses are rarely « sell » recommendations: in the year 2000, for example, less than 1% of all Wall Street brokerage house analysts' recommendations were « sell » or « strong sell » recommendations. In fact all analysts at investment banks tread a thin line and are caught in potential conflicts of interest. On the one hand, investors, their major clients, want « sell-side firms » to give honest opinions and be successful over time. On the other hand, an analyst's objectivity and independence can be threatened by several potential conflicts of interest, most of them stemming from the blurring of the lines between research and investment banking 5 . Several factors can shape the investment recommendation as stressed by the US Securities Exchange Commission (SEC): the analyst's firm may be underwriting the offering of a company covered by the analysts ; client companies will prefer positive research reports therefore negative ones could damage the investment firm's efforts to build long term and lucrative client relationships with a corporate or a sovereign; analyst compensation and bonuses can be linked to the number of deals done; and last but not least, the broker, the analyst or any other employee in the firm may own interests in the company covered. A US SEC Staff analysis released in 2001 of nine Wall Street firms found the following: seven of them reported that « investment banking had input into analysts' bonuses and the analyst hiring process »; although there is no formal supervision of analysts by investment banking « it is well understood by all these analysts that they were not permitted to issue negative opinions about investment banking clients »; in a total of 308 out of 317 IPOs examined, the firm that underwrote the security also provided research coverage 6 ; and finally «about one quarter of the analysts inspected own securities in companies they cover ». The interest of US regulators in analysts' conflicts of interests prompted the industries associations to provide answers. The Securities Industry Association, for example, issued in 2001 a « best practices for research » in order to consolidate the « integrity of research » recommending for example that research should not report to investment banking and that analysts should not be directly linked to specific investment banking transactions7 . At the same time, firms started reviewing their internal procedures to manage conflicts in a response to increasing pressure from former clients. Several of them, from Credit Suisse First Boston to Merrill Lynch, started in 2001 to adopt policies prohibiting analysts to own securities in companies they covered8 . Analysts do not only face a myriad of conflicts of interest. Most worrying is the predictive imperative they face. Here the paradox is that, in spite of academic studies pointing to lack of efficiency, research departments of brokerage houses continue to spend large amounts of money on research analysis. They are not, however, totally wrong in doing so. It is true that the financial industry during the 1990s experienced a dramatic change with the boom of the investment banking business. This trend spreads the belief that analysts became increasingly focused on attracting clients rather on writing independent reports. The answer is partly true if we take into account that « sell » or « strong sell » recommendations almost disappeared. However, some academic research is helpful to nuance this perception.

Two recent academic studies pointed to this change and underlined that, during the period of 1986-1996 (a time with less influence from investment banking)9 , sell-side recommendations had significant value, and the same also applies for the period 1996-2000. In fact, according to a study based on First Call data recording 160 000 real-time recommendations made by 299 brokerage houses10 , most highly rated stocks outperformed the less favourable ones during all the period 1996-2000 and this in every year but one : in 2000, the trends were very different and the reverse is true. During this period, analysts became increasingly positive with the percentage of « buy/strong buy » recommendations jumping from 65% to more than 70% over the period analyzed. Above all, this research underlines a singular behaviour for 2000, reversing the one prevailing during the previous years. The most highly recommended stocks in 2000 returned 31.2 % less than the market, on average, while the least favourably recommended stocks gained almost 49 % more than the market. This data also confirms the very few « sell/strong sell recommendations » found by previous studies : the percentage of negative recommendations on stock fell from 3,4% in 1996 to a mere 1,8% in 2000, meaning that nearly to negative opinion is being issued by analysts.

Another line of research has being trying to foresee if analyst recommendations tend to have an impact. Here again, the bulk of the research has been heavily concentrated in developed countries. As for the previous questioning, there has been fewer, not to say no analysis conducted on emerging markets. Some papers focused for example on trading activities on security analyst recommendations, finding that both large and small traders tend to react to these recommendations [START_REF] Mikhail | When security analysts talks who listens?[END_REF]. Prior work has also documented that market reaction to upgrades is less pronounced than the market reaction to downgrades by analysts (see [START_REF] Asquith | Information content of equity analyst reports[END_REF][START_REF] Hirst | Investor reactions to financial analysts' research reports[END_REF][START_REF] Jegadeesh | Analyzing analysts: when do recommendations add value?[END_REF][START_REF] Womack | Do brokerage analysts' recommendations have investment value?[END_REF]. All of this research has been focused on developing countries. Not all analysts and brokerage houses are equals. Investment banks and securities houses differ in their strategies, structures and performances. Individual analysts differ also according to their « performance », some being more appreciated than others for their recommendations. In general, buy recommendations of the largest brokerage houses tend to outperform those of the smallest by about 3% annually on a market-adjusted basis 11 . Because of their closer ties with corporate management or sovereign officials, their greater resources to support research and their larger number of analysts, bigger investment firms tend to outperform their smaller counterparts. The analyst forecast accuracy tends to increase with the size of the investment boutique to which the research analyst belongs, not only because the biggest investment houses tend to hire the best analysts but also because they offer them greater resources to carry out their research (databases, bloombergs, etc.). You can be the best analyst and be off the map simply because you do not belong to one of the top institutions. You can also be the best analyst but remain unknown because your research is not referenced in the media, newspapers or research providers like Bloomberg, Reuters, Investext or Multext). Lastly, depending on the type of firm you are working for, your track record can be better or worse, depending whether you are in the sell side industry or in the buy side [START_REF] Brown | Are two heads better than one? The case of analyst forecast accuracy[END_REF].

In spite of the amount of literature on broker recommendations, analysts' bias, and fund managers' relations, very little has been written on emerging markets. Among the rare research devoted to emerging markets [START_REF] Santiso | The Political Economy of Emerging Markets: Actors, Institutions and Financial Crises in Latin America[END_REF], some papers underline that there is strong evidence that foreign financial analysts outperform local analysts in these markets, as they tend to produce more timely and more accurate forecasts [START_REF] Bacmann | Who are the best? Local versus foreign analysts on the Latin American stock markets[END_REF][START_REF] Seasholes | Smart foreign traders in emerging markets[END_REF] 12 . In a recent paper Seasholes investigated information asymmetries in emerging stock markets and found that there was little evidence that locals were better informed than foreigners and there is evidence that foreign investors 11 See Brad Barber, Reuven Lehavy and Brett Trueman, « Are all brokerage houses created equal ? Testing for systematic differences in the performance of brokerage house stock recommendations », University of California at Davis and University of California at Berkeley, March 2000 (unpublished). This research shows also that surprisingly smaller brokers tend to make twice as much « sell » recommendations than the biggest investment boutiques (14% of sell/strong sell against 6% for the big brokers houses during the period studied 1986-1998). The smallest brokers tend also to have superior « sell » recommendations than their bigger competitors, this may be linked to the fact the big broker houses have stronger interests and incentives for preserving existing or potential client relationships). 12 Bolliger finds however that local houses in Europe have an advantage over foreign ones [START_REF] Bolliger | The characteristics of individual analysts' forecasts in Europe[END_REF], sharing the same kind of results as other studies on OECD countries [START_REF] Orpurt | Local analyst earnings forecast advantages in Europe[END_REF]. can outperform locals when trading specific stocks [START_REF] Seasholes | Re-examining information asymmetries in emerging stock markets[END_REF]. Other studies, using a sample of 32 countries, among them some emerging ones, tend to find on the contrary a local advantage for the period 2001-2003 and in particular US investors tend to underweight a country's stocks more in their portfolio if that country has a higher analyst local advantage (i.e. countries where earnings are smoothed more and less information is disclosed by firms) [START_REF] Bae | Do local analysts know more? A cross-country study of the performance of local analysts and foreign analysts[END_REF].

During the 90s, the emerging equity markets industry boomed, with the number of stocks covered rising from 150 to nearly 500 between 1993 and 2000, according to some estimates [START_REF] Bacmann | Who are the best? Local versus foreign analysts on the Latin American stock markets[END_REF]. The number of brokers covering emerging stocks also increased (from 66 to 170) as well as the number of analysts (from around 260 to more than 1650 for the same period). The average number of analysts employed by foreign brokerage houses amounted to 8 while the average was 5.5 for local ones. Local analysts tended however to be more active, producing forecasts every 76 days (while their foreign peer produced every 71 days) and changing their firm forecasts on average 1.5 times per firm each year (against 1.16). As shown also by another study, the variation of analysts per country varies a lot: while South Africa has only 3 firms and Brazil has 23, the former had 126 analysts covering stocks (85 of them foreign) and the latter only 28 (11 of them foreign) [START_REF] Bae | Do local analysts know more? A cross-country study of the performance of local analysts and foreign analysts[END_REF].

Other micro-focused studies analyzed individual investor behaviour (for example the 90 500 actively investing individuals within the People's Republic of China by the beginning of the 2000s, [START_REF] Feng | A profile of individual investors in an emerging stock market[END_REF] and mutual funds investment strategies in emerging markets [START_REF] Kaminsky | Managers, investors, and crises: mutual fund strategies in emerging markets[END_REF] or the extent and accuracy of analyst activity across 47 countries (15 of them emerging markets) [START_REF] Chang | Analyst activity around the world[END_REF].

All in all, studies focused on emerging markets analysts, brokers and investors tend to be scarce. When they exist, they are concentrated on equity markets. None as far as we know investigated the confidence game within emerging bond markets. This is in fact quite surprising when compared to the density of studies issued on financial analysts over the past years. Since 1992 no less than 250 papers related to financial analysts have been published in the nine major research journals, one of the most complete reviews of the literature [START_REF] Ramnath | A review of research related to financial analysts' forecasts and stock recommendations[END_REF].

Our study proposes to cover this gap. We used untapped and rich datasets, entirely built on their own, as explained in the following section. We wanted first to determine whether bond analyst recommendations are biased and depend first on the underwriting mandate and second on the size of a specific country's bond market. The second objective of the paper was to study the impact of investment banks' recommendations on fund flows. In other terms whether these analyses are relevant or useful to understand capital flows towards emerging economies. For that we constructed a unique database covering the period 1997-2006 for all the bond recommendations by the major Wall Street and City brokerage firms dominating the emerging bond markets, and more precisely the Latin American segment where we focused our attention, the region being the most active in bond markets.

Description of the data

In this section we present the source and the relevance of the data used for this paper. The data could be divided into three different types. Firstly, we have the information provided by brokerage houses to investors about the sentiment vis-à-vis an emerging economy. Secondly, we employ data related to the structure of the Latin American Bond Market. More precisely, we use issues, size of each country in the market and credit risk given by the market to emerging countries. Finally, we have taken some macroeconomic variables of Latin American economies such as capital flows, economic activity, interest rates, exchanges rates and inflation rates.

The most important and innovative aspect of our paper is the construction of a new untapped database containing the recommendations given by the major investment banks of the Latin American bond markets. Indeed, this is the first publication that studies the impact that investment banks' recommendations may have on Latin American Capital Markets. By using simple statistical analyses we give a primer result of the impact of research publications on emerging capital markets.

For this purpose we have used the publications produced by the major investment banks operating in emerging markets. In their monthly or quarterly publications they published the recommendation for each emerging country, giving their recommendations to the clients, namely the "buy side" industry of asset managers, mutual funds, hedge funds, pension funds, etc. An interesting point is that these publications are only available for clients and are not therefore public information. Indeed, they represent a direct and strict link between financial intermediaries and investors. We managed to build the database for 10 brokers, all of them dominant players in emerging bond markets as underwriters. All of them are from developed countries' brokerage houses, which are in fact the market makers: ABN AMRO, Barclays Capital, Citibank, Credit Suisse First Boston (now Credit Suisse), Deutsche Bank, Goldman Sachs, JP Morgan, Lehman Brothers, Merrill Lynch, Morgan Stanley.

The period of the recommendations that we have used goes from July 1997 to March 2006 13 and the number of recommendations is over 3,300 14 . As shown in table 1, we have taken 11 emerging countries for this research. Indeed they are the Latin American countries that are studied in these publications and that represent more than 90% of the GDP of the region. They also concentrated over the period the major bond issuers within the emerging market asset class. With regard to investment banks, our database is constructed from 10 investment banks which represent more than 80% of the investment banks present in the Latin American sovereign IPOs.

The frequency of these publications is in most cases monthly, and the recommendations that we have used are those given to sovereign external debt. In order to compare the view of each bank towards Latin American countries at the same time, we have classified three types of recommendations, which are Overweight (that takes the value of 1), Neutral (0) and Underweight (-1), assimilated to the cases of buying, maintaining and selling with respect to an index (e.g. EMBI+ calculated by JPMorgan). This means that given portfolio restrictions, a buying recommendation must be compensated by a selling advice, implying that investment banks are constrained to underweight countries in the composition of the portfolio when they have a favourable view of a particular country. In annex 1, we give an example of the research publication's recommendations given by one of the largest investment banks present in Latin America In order to compare these recommendations with one of the most important businesses of investment banks in emerging countries, we have constructed a database that contains the Latin American Sovereign Bond Issues from January 1999 to March 2006. The source of information was Bloomberg which, among other things, includes the lead managers (or underwriters), the amount outstanding, and the issue and maturity date of each issue. The most important reason for choosing Bloomberg as a source of information is that their database is one of the most important benchmarks for marketmakers in relation to the list of leaders in the underwriting business. Indeed, the "League Table" calculated yearly and from 1999 by Bloomberg represents an important guide for investors, issuers and actors about the reputation (measured as the market share) of each investment bank 15 . In order to define the issues that can be included in this "League Table ", Bloomberg has specified the characteristics of these issues.

As shown in table 2, the data used is composed by 411 underwriters and corresponds to 250 sovereign issues. 16 In particular, almost 75% of the underwriters are located in Brazil, Argentina, Colombia and Mexico. More interesting is that Argentina, in 1999, had to use 60% of the underwriters presented that year in Latin America in order to place a huge number of bonds, which in fact complicated even more the resolution of the Argentinean crisis. In 1999 alone, Argentina issued a total of 52 bonds, compared with 17 for Brazil and 8 for Mexico. The most active issuer in our sample over the period studied is also the largest economy of the region, namely Brazil, which happens to be also the most liquid Latin American market. With the purpose of studying the size of the bond market for each Latin American Country, we took the weight of each country in the JP Morgan Emerging Markets Bond Index Global (EMBI Global). This index is a reference of the bonds stock for marketmakers, financial researchers and policy makers, which are, for each country, placed in the secondary market.

The countries that are included in that index have been -during two consecutive years -low/middle income countries (as defined by the World Bank). Concerning the characteristics of the securities, only bonds that have an issue size higher than US$500 millions and a maturity of at least 2.5 years are incorporated in that index 17 . As it is noted by JP Morgan Securities (2004), "the weight of each instrument in the EMBI Global is determined by dividing the issue's market capitalization by the total market capitalization for instruments in the index." Therefore "country weights for the EMBI Global are easily calculated by aggregating the weights of the instruments for each country". 16 Indeed, the number of Lead Managers used today for most of the Latin American Emerging Bond Issues is two. 17 For a more detailed description of the construction of that index, see JP Morgan Securities (2004).

In figure 1 we have the market weight of the three principal Latin American countries that compose that index today. Brazil and Mexico are by far the largest Latin American Bond Issuers (nearly 35% of the total index). Indeed, they represent more than 60% of the Latin American Weight of that Index. Argentina nearly disappeared after 2001 and its massive default but one year before it was still a major heavyweight, representing nearly a quarter of the total index. To calculate the perception of investors towards country credit risk, we have employed the spread of the EMBI Global which is measured as the credit risk premium over US Treasury Bonds and it is calculated as the difference between the yield to maturity bond and the yield to maturity of the corresponding point on the US treasury spot curve. For the country weights and the spreads we had information on a monthly basis from 1997 until today for the most important bond issuers in the region. In contrast, for Chile, Dominican Republic and Uruguay the period starts in June 1999, October 2001 and June 2001 respectively.

With the aim of studying the impact of investment banks' recommendations on capital flows, we have used the database created by the Boston based private consulting firm Emerging Portfolio Fund Research which is constituted by the percentage allocated in each emerging country by funds. 18 We then possess information on the country average weightings of all funds that invest in Latin American Equity and Bond Markets. The most important advantage of this database is that it contains information on a monthly basis about what differs with respect to other databases, such as the CPIS (Coordinated Portfolio Investment Survey sponsored by the IMF) 19 that includes portfolio investment assets on an annual basis and is produced by multilateral organizations (IMF, BIS, OECD and WB). 18 See http://www.emergingportfolio.com for a detailed description of that database. 19 For more information about this database see http://www.imf.org/external/np/sta/pi/cpis.htm Concerning equity flows, the period that we have used starts in July 1997 and ends in January 2006 for most of the Latin American countries of our sample20 . In contrast, the bond flows database is constituted only from April 2002 and ends also in January 2006 21 .

In order to test the impact of investments banks' recommendations on capital (bond and equity) flows, we have used some macroeconomic variables as control variables. These variables are on a monthly basis and are economic activity growth, inflation rate, exchange rate, interest rate and the spread of the EMBI Global. The sources of information of these variables are Bloomberg and Financial Thomson Datastream, and cover the period June 1997 -January 2006.

For the case of economic activity growth, for some countries (e.g. Brazil and Colombia), given there is no monthly indicator of economic activity, we have taken as proxy industrial production due to the strong relationship between this variable and GDP. For the case of Venezuela, given the lack of a robust monthly indicator we have transformed GDP (that is calculated on a quarterly basis) on a monthly basis. For that, we have used [START_REF] Boot | Further Methods of Derivation of Quarterly Figures from Annual Data[END_REF] methodology that consist of minimizing the sum of squares of the second differences. Concerning the other macroeconomic variables we have used the most relevant indicator for each country22 .

Investment banks' business and research publications

In this section we present some empirical evidence of the relationship between investment banks' recommendations and some aspects related to the business of these banks (in particular sell-side business). This section gives some preliminary results in order to understand whether banks' advice to investors is biased. For that, we first analyzed the recommendations given by underwriters during the announcement date of an IPO. Secondly, we studied the possible impact that the market size of an emerging country could have on the recommendation given by banks.

Underwriters' recommendations: a simple statistical analysis

With the aim of investigating possible incentives that investment banks could have to concede a favourable recommendation to a specific emerging country, we have studied the behaviour of investment banks during sovereign bond issues. More specifically, we have integrated underwriters of the Latin American bonds issues with their recommendations, in order to analyze their recommendations in an IPO.

Our database is composed of 160 underwriters' recommendations during approximately seven years (July 1999-March 2006). By giving the value of 1 to overweight recommendations (buy advices), 0 to neutral recommendations (maintain the same percentage of an asset in the portfolio) and -1 to underweight recommendations (sell advices), we have constructed a database that allows us to give a first simple result on whether investment banks' recommendations are biased and therefore dependent on the IPOs business. As we have noted before, given portfolio restrictions, these recommendations can not be overweight for all countries; a favourable recommendation for one country has to be compensated with a pessimistic view of another country. In table 3, we present the recommendations given by banks that have been underwriters for Latin American sovereign bond issues. The most important and relevant result is that 90% (i.e. 144 of 160) of the underwriters recommend, at the announcement date of the issue, to buy or to maintain in their portfolio the bonds issued by the countries where they are acting as lead managers. Indeed, given that only 10% of the recommendations are negative, we could note that banks' recommendations are biased and depend on the underwriting process in which banks are involved.

By analyzing each Latin American country, all of them (except Argentina and Panama) have a higher percentage of optimistic underwriters' recommendations than pessimistic recommendations.

The Argentinean case is very useful and interesting. All the issues that we have included were previous to the 2001 Argentinean Default and some of them just a few months before the crisis. It is worth pointing out that even if we have not noted an overweight recommendation, 67% of the recommendations were to maintain the positions in Argentinean External Debt, even in the months previous to the default. Indeed, some of the comments given by banks months before the crisis were, at least, unrealistic and biased, given that macroeconomic perspective was unsustainable 23 . By analyzing the first three countries where we have the higher number of observations (Brazil, Colombia and Mexico) or underwriters' recommendations, we note that for all of them, underwriters have, in most cases, a positive view about the country (100% for Colombia and Brazil, and 84% for Mexico). By analyzing underweight recommendations, Brazil and Colombia have never obtained a pessimistic view from brokers (even though Colombia once lost its investment grade), and in Mexico less than 2 out of 10 recommendations were pessimistic. Therefore, it is clear from empirical evidence that during the last years banks' recommendations were favourable in regard to the country for which they acted as underwriters.

What is the incentive for underwriters to give a favourable recommendation at the announcement date of an issue? Firstly, positive recommendations could have an impact on the success of the "book-building" process in which underwriters are designated to place the bonds through institutional investors. If your view is positive or at least neutral of the country, your likelihood of getting the mandate will probably increase. The refutation of this hypothesis would be that brokers recommending to sell a sovereign could get an underwriting mandate.

Secondly, because one of the roles of underwriters is to participate in the secondary market to stabilize the price and avoid volatility of the new issue 24 , by giving favourable advice to investors regarding external debt issued, underwriters could send positive signals about that country and then avoid a decrease in the price 25 .

In order to prove that underwriters' recommendations are biased and depend on the sell side business of investment banks, we have compared these recommendations with recommendations given by other investment banks during the announcement date of the issue of a bond. 23 Here we impart some of the biased views concerning the Argentinean Crisis. Credit Suisse First Boston: "Argentina. Remain market-weight. We believe the expected debt exchange will be a key driver of Argentine asset prices during the month"…. "Over the next month we expect to see many more specifics of the economic program, both on the fiscal side -to be released in the IMF Letter of Intent -as well as on the deregulation front, which should reduce uncertainty." CSFB May 2001 and "The successful debt exchange in Argentina should give the market some stability in the near-term horizon, which should be most beneficial to Brazil." CSFB June 2001. Salomon Smith Barney: "The successful implementation of the IMF support package -with the associated debt management transactions -and the change in the global outlook probably increases the chances that economic activity will pick up in the second half of the year. We therefore recommend a neutral position in external bonds and local currency instruments." Salomon Smith Barney January 17, 2001 JPMorgan: "Argentina: Marketweight. Favorable technicals underpin our portfolio allocation this month. ." JP Morgan 5 April 2001 and "Argentina: Marketweight. The improved near-term outlook appears mostly priced in, although we like the short end of the curve from a relative value perspective." JP Morgan 8 February 2001. Morgan Stanley: "We are maintaining our Market Perform recommendation on Argentine bonds….Relaxation of fiscal targets and an innovative IMF-led financial package from creditors both improve Argentina's credit outlook. Argentina needs to raise an estimated $2.6 billion to fulfil its first quarter financing requirements. New issues are expected to total $5.6 billion in 2001. Growth and fiscal performance are becoming the focus of investors' attention." Morgan Stanley January 26, 2001 24 As it is noted on the prospectus of the bonds, although the underwriter is not obligated to make a secondary market for the bonds, it plans to make one: "The issuer has been advised by the underwriters that the underwriters intend to make a market in the global bonds but are not obligated to do so and may discontinue market making at any time without notice. No assurance can be given as to the liquidity of the trading market for the global bonds." 25 it would be interesting to analyse the impact of recommendations on the secondary market price of sovereign bonds. With respect to that subject, some important studies have been developed in the US equity market.

As shown in figure 2, on average (period 1999-2006), for all countries underwriters' recommendations to Latin American countries are higher than or at least equal to no-underwriters' recommendations. Additionally, by taking the weighted average, underwriters' recommendations are 25% larger (0.3 vs. 0.2) with respect to those of No-Lead managers. This is particularly the case for Colombia, Ecuador, Peru and Venezuela. Interestingly, in the case of Brazil, the biggest and most liquid market, such a bias is less marked, while in the case of Mexico it is the opposite. Tot. Aver. Weigth. Aver.

Source: The authors, april 2006

Underw riter

No underw riter Moreover, by comparing the recommendation made at the announcement date by underwriters and no-underwriters, we discovered that 75% of the lead managers' advice was higher than or equal to that made by other investment banks during 1999-2006 and for a sample of 149 recommendations26 . In particular, as we can see in table 4, for all countries excluding Panama, with respect to no-underwriters' recommendations, the percentage of higher underwriters' recommendations was superior to lower underwriters' recommendations. By analyzing the results showed in the precedent paragraphs we obtained two interesting findings. First, given that a large part of underwriters' recommendations are positive, it suggests that they are biased and depend on the sell side business. Second, despite the fact that in most cases lead managers' recommendations are higher than or equal to no-lead managers' advice, this result is less evident than the first finding. Therefore there is a remaining question that is related to the incentive that nounderwriters could have to give an equal or better recommendation than underwriters. For that we have analysed the structure of the underwriter in Latin America.

In table 5 we present the participation of the underwriters in the Latin American Sovereign Bond Market. As noted before, the number of underwriters in the Sovereign Bond Market is small. Indeed, for most of the Latin American countries, during 1999-2006, 90% of the issues are realized by 10 investment banks. However, from the point of view of governments, we observe a diversification in the choice of underwriters, which results in a change over time of the underwriters with the purpose of reducing the dependence to a single Lead Manager. In the major countries' issuers (Argentina, Brazil, Colombia, Mexico, Uruguay and Venezuela), the market share of a lead manager does not exceed 30%, which corroborates that there is no specific leader in the underwriter market, at least for the most important countries' issuers. Another way to arrive at a similar conclusion is by analyzing the concentration of the underwriting market (table 6). By calculating the Herfindahl-Hirschman Index (HHI) 27 for each Latin American Country during 1999-2005 (see table 5), we obtained two important results. Firstly, despite the fact that the underwriting concentration in the Latin American Bond Market could be considered by the U.S. Department of Justice as highly concentrated28 , given the reduced number of actors, the concentration index is not so elevated. Secondly, during the last seven years, we note that the concentration has remained stable (around 0.22) and we have seen neither an increase in the number of actors in this game nor an increase in the participation of a single underwriter. Concentration (Herfindahl-Hirschman Index) in the Underwriting Market 27 The Herfindahl-Hirschman Index (HHI) is a standard measure of concentration in Industrial Organization and is defined as:

∑ = = N i i x HHI 1 2 where i
x is the participation rate of firm i in a market composed by N firms.

Theoretically, then Emerging Sovereign Bond Markets are characterized by an imperfect competitive market in which underwriters are playing a repeated game. By taking investment banks' recommendations as a marketing product, it is then advantageous to investment banks, given the dynamic of the "underwriting game", to recommend positively a country (or client) even if at that period they have not been underwriters. Therefore, it is not sure that no-underwriters recommendations could be taken as a control variable to test if underwriters' recommendations are biased. In fact, this may explain why the result showed in table 4 (underwriters' vs. no-underwriters' recommendations) is less robust than that obtained by analyzing the percentage of positive underwriters' recommendations (table 3) to show that the recommendations are biased and depend on the Underwriting Market.

Size of the emerging markets and recommendations: empirical evidence and implications

In the last sub-section we have studied the relationship between investment banks' recommendations and the process of bond issues in the primary market. Here we study the possible influence of the size of the secondary bond market on investment banks' recommendations.

Indeed, in addition to the underwriting process, part of investment banks' business is also related to the bonds that have already been issued. Because one of the most important aspects for investment banks is the sale of portfolios to a large variety of financial intermediaries (mutual funds, pension funds, commercial banks, insurance companies,…), the stability asset prices that compose these portfolios is relevant. For that purpose, investment banks' publications may be a useful tool to influence the asset prices.

Concerning Emerging Bond Markets, it is evident that the percentage invested in these portfolios increases relative to the size of each emerging country. In order to calculate the relative size of each Latin American country in the Emerging Bond Markets, we have used the weight of each country in the EMBI-Global (Emerging Market Bond Index) that can be used as the magnitude in the Secondary Bond Market of each Latin American country.

The weight of each emerging country in this database is similar to that obtained in other databases. For example, by comparing the EMBI-Global with the Joint External Debt Hub (JEDH) database29 which provides the stock of international debt securities, we get a high correlation between both weights for the Latin American Emerging Countries (0.70 and 0.98 by excluding Argentina).

In order to verify if investment banks' recommendations are biased and depend on the size of the market of each emerging economy, we have compared the EMBI-Global weight of each Latin American country with the average of the total investment banks' recommendations between July 1997 and March 2006. As shown in table 7, by realizing a simple cross-section analysis, we discovered that, excluding Argentina, there is a high correlation between investment banks' recommendations and the size of the markets (0.8 for 10 Latin American Countries). Including Argentina the correlation is lower (0.6) because their size in the market was substantial (11.4%) vis-à-vis their recommendations (-0.19). In fact, if we compare the average of the recommendations for Argentina (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) with the present weight in the EMBI-Global (1.8% in March 2006), the correlation between both variables for the total of Latin American countries is 0.8 (see figure 3). Recommendations Average (1997Average ( -2006) ) Correlation: 0.8

The main result then is that as the size of the market increases the recommendation is more favorable. That is the case of Brazil and Mexico, whose market share in the Emerging market is the highest for all the emerging countries (19.4% and 16.8% respectively) and consequently their recommendations are the most elevated of our sample (0.35 and 0.33 respectively). By contrast, for countries which are less relevant in the Sovereign Bond Market, such as Dominican Republic or Uruguay (0.3% and 0.6% respectively of the total Emerging Bond Market), the recommendations are negative or at least neutral (-0.01 and -0.32).

In order to test, in a simple way, the robustness of this result, we have analyzed the relationship between investment banks' recommendations and credit risk 30 . Intuitively, if we assume that recommendations are unbiased and then objective, as credit risk is higher the recommendations would be more favorable. However, as is shown in table 7 column 3, we obtained that there is no correlation between both variables (-0.14 by excluding Argentina and -0.4 by including Argentina).

An interesting case is that of Chile, that it is well known today as an exceptional country from the point of view of macroeconomic soundness and stability. During the period that we have studied, the spread of the Chilean Bonds were on average 142 basis points over Treasury Bills, the lowest of Latin American countries. By contrast, their recommendations were below those of Brazil, Colombia, Mexico and Venezuela and close to neutral (0.05).

By using a simple statistical analysis, we have two main results in this subsection. First, investment banks' recommendations are biased and depend on the relative size of the secondary bond market. By taking as analogy the famous term of "too big to fail" that refers to the case in which governments will bailout only financial intermediaries which are considered to be of "systematic" importance, we obtained a similar result but in a contrary direction and that we call "too big to underwrite". Indeed, investment banks will not send negative signals to investors of countries or governments that are considered to be important for their business given their size in the market. Second, from this simple analysis, it seems that credit risk is not a relevant variable to determine the direction of the recommendations.

Emerging markets capital flows and investment banks recommendations: preliminary results

In the last section, from a simple statistical analysis, we have concluded that investment banks' recommendations are biased and depend on the business of these banks in emerging economies. Therefore, it is crucial to analyze the possible impact that these recommendations could have on emerging economies. In other terms, a remaining aspect is the impact that asymmetric information and imperfect microeconomic factors could have on investors' behaviour.

In order to answer this question we have studied the relationship between brokers' recommendations and fund flows in the most important Latin American economies (i.e. Argentina, Brazil, Chile, Colombia, Mexico, Peru and Venezuela). More precisely, on a monthly basis, we have taken the average of the recommendations given by investment banks for each Latin American economy and the percentage allocated by funds in these countries with respect to the total amount invested in emerging economies. Indeed, we preferred to use weighted flows instead of nominal flows with the purpose of studying the discriminatory role of investors among countries.

A first simple statistical analysis was to calculate the correlation between fund flows and brokers' recommendations. In the following figures (from figure 4 to figure 7) we showed, for instance, the case of Argentina and Brazil31 . Concerning Bond flows, there is a positive and significant correlation with recommendations for both countries. By contrast, by analyzing Equity flows, for Argentina again there is a strong relationship with recommendations while for Brazil this partnership is less evident. In order to analyze the determinants of capital flows to Latin American emerging countries, we have realized a simple cross-section econometric model that uses, in addition to investment banks' recommendations (that may be considered as a microeconomic variable), macroeconomic variables. These macroeconomic variables could de divided into two groups. First, we have taken variables whose trend can be directly influenced by financial intermediaries and are then defined by capital markets. These variables are the spread of Emerging Sovereign Bonds (over US treasury Bills) and the exchange rate. Second, we have used variables whose real sector is determinant to define their evolution and where financial intermediaries play an indirect role. These variables are economic activity, interest rate and inflation rate 32 .

In order to test the impact of recommendations on capital flows (Equity flows and Bond flows respectively), we have used a panel data model that presents the following two basic equations: 32 See section three for a description of the variables taken for each country.

it it it it it al Market c Equity ε γ δ β α + ⋅ + ⋅ + ⋅ + = Re Re (i) it it it it it al Market c Bond ε γ δ β α + ⋅ + ⋅ + ⋅ + = Re Re (ii)
where Recit represents investment banks' recommendations given to country i in period t, Marketit represents macroeconomic variables defined by capital markets (exchange rate and spread of sovereign Bonds) and Realit macroeconomic variables that are strongly influenced by real sector (economic activity, inflation rate and interest rate).

We started the estimation technique with the current practice, OLS estimation. Since these are known to deal inadequately with time series and cross-section heterogeneity, we reported also GLS estimates (random effects on countries).

Concerning Equity flows, results are presented in tables A1 and A2 and for Bond flows results are reported in tables B1 and B2. The results for Equity and Bond flows are too similar and can be summarized as follows.

By using OLS estimation, we find, as we would expect, a positive and significant effect of Rec and a negative and significant effect of exchange rate depreciation and spreads of bonds. Concerning Real variables, only economic activity has the expected sign but all of them are significant. By differentiating between Market and Rec variables with Real variables, the most important and relevant results are first that Real variables do not have a prediction capability to explain capital flows. Second, by analyzing only Market variables the prediction capacity is higher than using only Real variables. Finally, the impact of Rec on capital flows is important and increases the R-squared of the regressions. Indeed, Rec explains better capital flows than Real variables.

A second step of this analysis was to calculate the impact of lag explanatory variables on capital flows. We find the same results noted above. In particular, by analyzing only Market and Rec variables we obtain that they have a prediction capacity higher than Real variables. In addition, by associating first exchange rate and Rec and then by connecting exchange rate and spread we find that the first case has a higher Rsquared.

By realizing a GLS estimation (random effects on countries), we have obtained the same results presented above. In summary, we find that variables that are determined by financial intermediaries (Rec and Market) play a crucial role to explain capital flows. In particular, by including Rec in the analysis, the results are more robust than before and the explanatory capacity of this variable is then more important than Real variables.

In conclusion, investment banks' recommendation is a determinant variable to explain capital flows. In particular, for most of the results shown in tables A1, A2, B1 and B2, we find that by including this new microeconomic variable, among macroeconomic variables, the robustness of the regressions improves considerably.

Conclusions

In order to analyze analysts and to determine the possible macroeconomic implications of investment banks' recommendations we have constructed a unique database covering the period 1997-2006 for all the bond recommendations by the major Wall Street and City investment banks that dominate the emerging bond markets. Indeed, we managed to build the database for 10 brokers, all of them dominant players in emerging bond markets as underwriters. All of them are from developed countries' brokerage houses, which are in fact the market makers.

In order to investigate if investments banks' recommendations are biased and are related to the banks' business we have first studied the structure of the primary bond market in Latin American countries and second the stock of bonds already issued by these countries and placed in the secondary market.

The most relevant results of that study are first that 90% of the underwriters recommend, at the announcement date of the issue, to buy or to maintain in their portfolio the bonds issued by the countries where they are acting as lead managers. Indeed, given that only 10% of the recommendations are negative, we could note that banks' recommendations are biased and depend on the underwriting process in which banks are involved.

Second, there is an additional bias. Investment banks' recommendations are biased and depend on the relative size of the secondary bond market, phenomenon that we call "too big to underwrite". Indeed, investment banks will not send negative signals to investors of countries or governments that are considered to be important for their business given their size in the market (e.g., Brazil and Mexico vs. Chile). Therefore, it seems that credit risk is not a relevant variable to determine the direction of the recommendations.

Given that these results reveal that signals sent by investments banks' to investors are imperfect and biased, we have studied a possible effect of these recommendations on emerging economies.

To that purpose, by using a simple cross-section analysis, we introduced recommendations as a new variable that could explain capital flows towards emerging economies. The most important result is that the impact of investment banks' recommendations on capital flows is more significant and more predictable than some macroeconomic variables such as interest rates, economic growth and inflation.

In summary, investment banks' recommendations are a biased microeconomic variable that explain, among other variables, capital movements and then could affect emerging economies' business cycles. It seems then that this new database is a useful and powerful tool to understand banks' and investors' behaviour. Therefore, it could be used for further research, for example, to ascertain the impact that electoral years could have on these recommendations.

  Figure1EMBI Global(Brazil, Mexico and Venezuela)

  Figure 2Underwriters vs No-Underwriters' recommendations(Announcement date, Average 1999[START_REF] Flores | A microeconomic analysis of the Baring crisis, 1880-1890[END_REF]

  Figure 3 Recommendations vs. Country weights EMBI Global (%)

  Figure 4Figure5

Table 1 INVESTMENT BANKS' RECOMMENDATIONS DATABASE. NUMBER OF OBSERVATIONS (July 1997-March 2006)

 1

		ABN	BARCLY CITI	CSFB	DB	GS	JPM	LB	ML	MS	TOTAL
	Argentina	1 4	46 9	5 65 02 4	5 9	1 9	1 8	2 63 3 9
	Brazil	11	14	73	58	50	25	58	19	27	25	360
	Chile	11	14	78	58	0	25	55	19	0	0	260
	Colombia	11	15	77	58	50	25	59	19	26	25	365
	Dom. Rep.	00	9	002	4 2	0	2 7	1 5	9 5
	Ecuador	1	1 5	7 6	5 85 02 5	5 9	1 9	2 7	2 43 5 4
	Mexico	11	15	78	58	50	25	59	19	27	24	366
	Panama	0	14	61	58	49	25	58	0	27	24	316
	Peru	1	1 4	7 8	5 85 02 5	5 9	1 9	2 7	2 43 5 5
	Uruguay	0	0	21	57	0	16	52	19	27	0	192
	Venezuela	11	13	81	58	50	25	59	19	27	24	367
	TOTAL	71	118	701	577	399	242	619	171	260	211	3369
	Part. Underwriting	2%	2%	12%	7%	10%	10%	22%	0%	6%	13%	84%

Source: The authors from investment banks' publications (for recommendations) and Bloomberg (for underwriting), april 2006

Table 2

 2

		1999	2000	2001	2002	2003 2004 2005 2006 march TOTAL
	Argentina	52	21	5						78
	Brazil	17	21	12	8	8	12	18	6	102
	Chile	22	5	2	2			1 3
	Colombia	51 2	2 4	45	5	9		6 4
	Dom. Rep.			22			2	6
	Ecuador							22
	Mexico	878	6	1 2	9	5	2	5 7
	Panama	223	2	1	3	2		1 5
	Peru				442	5		1 5
	Uruguay	14	1 0	2			6	4	2 7
	Venezuela		21 0		47	9		3 2
	TOTAL	87	69	76	31	38	40	56	14	411
	Source: The authors from Bloomberg, april 2006

Number of Lead Managers (Latin American Soverreign Bonds Issues).

Table 3 Underwriters' recommendations (Announcement date of the issue) Jan. 1999 -March 2006

 3

		OVER.	NEUTRAL	UNDER.	OBSERV.
	Argentina	0%	67%	33%	9
	Brazil	59%	41%	0%	37
	Chile	20%	60%	20%	5
	Colombia	35%	65%	0%	31
	Dom. Rep.	0%	100%	0%	2
	Ecuador	50%	50%	0%	2
	Mexico	29%	55%	16%	31
	Panama	0%	71%	29%	14
	Peru	46%	38%	15%	13
	Uruguay	0%	100%	0%	1
	Venezuela	67%	27%	7%	15
	TOTAL	38%	52%	10%	160
	Source: The authors from Investment Banks' recommendations
	and Bloomberg, april 2006

Table 4 Underwriters' recommendations vs. Other investment banks' recommendations (1999-2006)

 4

		HIGHER	EQUAL	LOWER	OBSERV.
	Argentina	20%	80%	0%	5
	Brazil	39%	33%	28%	36
	Chile	20%	60%	20%	5
	Colombia	28%	62%	10%	29
	Dom. Rep.	0%	100%	0%	2
	Ecuador	100%	0%	0%	2
	Mexico	39%	29%	32%	28
	Panama	8%	46%	46%	13
	Peru	54%	8%	38%	13
	Uruguay	100%	0%	0%	1
	Venezuela	53%	27%	20%	15
	TOTAL	36%	39%	25%	149
	Source: The authors from Investment Banks' recommendations
	and Bloomberg, april 2006

Table 5 #

 5 Issues

			ABN BARCLY. C	CSFB DB GS JPM ML	MS UBS TOTAL
	Argentina	53	1.0	1.4	7.7	9.9	17.3 6.2 19.2 2.3 17.6 0.0	82.7
	Brazil	53	0.9	0.4	10.9	4.2	9.4 12.0 16.9 9.1 12.9 5.1	81.7
	Chile

of the underwriters in Latin American Countries (Jan. 1999-March 2006)

	Participation (%)
							8 4.8	3.8	7.2	100.0
	Uruguay	18	1.4	0.0	19.2	6.9	18.6 0.0 13.3 11.9 7.8	16.0 95.2
	Venezuela	17	20.6	3.4	2.9	20.6 14.0 0.0 14.9 3.4	0.0	9.7	89.5
	Source: The authors from Bloomberg, April 2006

Table 6

 6

		1999	2000	2001	2002	2003 2004 2005
	Argentina	0.14	0.14	0.34
	Brazil	0.18	0.17	0.17	0.18	0.19	0.15	0.12
	Chile	0.50		0.50	0.51	0.50	0.50
	Colombia	0.28	0.27	0.11	0.25	0.39	0.54	0.19
	Dom. Rep.			0.50		0.50
	Ecuador							0.50
	Mexico	0.24	0.29	0.33	0.18	0.26	0.14	0.21
	Panama	0.50	0.50	0.53	0.50	1.00	0.50	0.68
	Peru				0.38	0.36	0.53	0.22
	Uruguay	1.00	0.53	0.14	0.53			0.31
	Venezuela		0.50	0.50		0.41	0.20	0.28
	Weighted Average	0.22	0.21	0.23	0.20	0.26	0.22	0.20
	Source: The authors from Bloomberg, april 2006

Table 7

 7

	Recommendations vs.
		Average Recommendation	EMBI-Global country weights EMBI-Global spreads
	Argentina	-0.19	11.4	2620
	Brazil	0.35	19.4	795
	Chile	0.05	1.0	142
	Colombia	0.14	2.2	508
	Dom. Rep.	-0.01	0.3	686
	Ecuador	-0.04	1.3	1426
	Mexico	0.33	16.8	349
	Panama	-0.03	1.9	384
	Peru	0.05	1.7	497
	Uruguay	-0.32	0.6	634
	Venezuela	0.11	5.2	822
	Correlation with recomm. (with Argentina)	0.61	-0.40
	Correlation with recomm. (without Argentina)	0.81	-0.14
	Source: The authors, from Investment banks' publications and JP Morgan, april 2006

Credit Risk and Size of the Countries (Average 1997-2006)

TABLE A1

 A1

	Dependent variable: Equity
		I	II	III	IV	V	VI	VII	VIII	IX
	Rec	2.33			2.27
		9.95			8.91
	Exchange Rate (Market )	-0.005		-0.003	-0.003
		-16.84		-15.45	-15.97
	Spread (Market )	-0.0012		-0.0092	-0.0007
		-10.8		-7.66	-5.83
	Inflation rate (Real )	0.05	-0.032
		8.81	-8.75
	Economic Activity (Real )	0.104	0.07
		4.68	2.6
	Interest rate (Real )	0.11	0.062
		9.19	4.41
	Rec -1					2.37			2.58	2.31
						10.17			10.39	9.09
	Exchange Rate -1 (Market )					-0.005		-0.003	-0.025 -0.00267
						-16.91		-15.33	-14.96	-15.89
	Spread -1 (Market )					-0.001		-0.0009		-0.0006
						-10.82		-7.59		-5.72
	Inflation rate -1 (Real )					0.516	-0.03
						8.93	-8.68
	Economic Activity -1 (Real )					0.108	0.077
						4.9	2.86
	Interest rate -1 (Real )					0.116	0.064
						9.35	4.53
	Cons	3.76	3.18	5.82	5.22	3.7	3.12	5.8	4.46	5.18
		14.76	10.23	27.33	25.04	14.6	10.03	27.11	26.27	24.82
	N	657	714	698	660	650	707	691	671	653
	N-k	650	710	695	656	643	703	688	668	649
	Adjusted R-squared	0.47	0.12	0.28	0.35	0.48	0.11	0.27	0.31	0.35
	t-statistics are in italic

OLS Impact of Recommendations on Equity Flows: OLS and Random Effects

As underlined by Laura Unger, acting chair of the US Securities & Exchange Commission, « The blurring can be seen in a number of ways. First an analyst's salary and bonus may be linked to the profitability of the firm's investment banking business, motivating analysts to attract and retain investment banking clients for the firm. Second, at some firms, analysts are accountable to investment banking for their ratings. Third, analysts sometimes own apiece of the company they analyze, mostly through pre-IPO share acquisitions », Laura Unger, « Testimony concerning conflicts of interest faced by brokerage firms and their research analysts », Testimony before the US House of Representatives Subcommittee on Capital Markets, Insurance and Government Sponsored Enterprises, Committee on Financial Services, July 31 2001, available at http://www.sec.gov/news/testimony/073101tslu.htm and http://www.house.gov/financialservices/080201lu.pdf

The impact of investment banking relationships on analysts' stocks recommendations in the context of initial public offerings (IPO) has been also analyzed by Roni Michaely and Kenk Womack, « Conflict of interest and the credibility of underwriter analyst recommendations, » Review of FinancialStudies, 12, 1999, pp. 653-686.

See Securities Industry Association, Best practices for research, New York and Washington, SIA, 2001.

See « Credit Suisse limits holdings of its analysts », Wall Street Journal, July 25 2001, at C14 ; « Merrill alters a policy on analysts », Wall Street Journal, July 11 2001, at C2.

See BradBarber, Reuven Lehavy, Maureen McNichols and Brett Trueman, « Can investors profit from the prophets ? Security analyst recommendations and stock returns », The Journal ofFinance, vol. 56, n° 2, April 2001, pp. 531-563.

See Brad Barber, Reuven Lehavy, Maureen McNichols and Brett Trueman, « Prophets and losses: reassessing the returns to analysts' stock recommendations », Stanford University, Graduate School of Business Research Paper Series, n° 1692, May 2001 (unpublished).

In fact, for the period July 1997 -December 1999 we only have information from Citibank.

Most of these publications are realized on a monthly basis (see Annex 1). In order to compare the recommendations provided by investment banks, we have defined a specific month From the 20 of each month (not included) to the 20 of the next month (included). For example July is from 21 June until 20 July.

See Bloomberg Markets (2006) for a detail of the relevance for the market of the information provided in that database.

For Ecuador and Panama, we have information only from February 2005 and for Dominican Republic and Uruguay there is no information for equity flows.

For Dominican Republic the information provided for bond flows only starts in July 2004.

For the case of interest rate, for instance, for Argentina we have used Prime rate 30 dias, For Brazil Selic rate, for Chile Tasa de Politica Monetaria, for Colombia DTF, for Mexico Cetes 28 dias, for Peru Interbank Interest Rate for Venezuela TAN.

This sample is less than this one used for total recommendations (149 vs. 160) because in some bond issues (mostly at the beginning of the period) we obtained only the recommendation of the underwriter and not those of other investment banks.

The U.S. Department of Justice considers a market with a result of less than 0.1 to be a competitive marketplace; a result of 0.1-0.18 to be a moderately concentrated marketplace; and a result of 1.8 or greater to be a highly concentrated marketplace. See http://www.usdoj.gov/atr/public/testimony/hhi.htm

This database is jointly developed by the Bank for International Settlements (BIS), the International Monetary Fund (IMF), the Organization for Economic Cooperation and Development (OECD) and the World Bank (WB). See: http://devdata.worldbank.org/sdmx/jedh/jedh_dbase.html

In order to calculate country credit risk, we have taken the spread of the EMBI-Global (JP Morgan), that it is in fact a proxy of the perception of the market about country credit risk.

As noted before, overweight recommendations take the value of 1, neutral outlook the value of 0 and underweight recommendations the value of -1.


A Vaona
email: drea.vaona@economia.univr.it

S Schiavo
email: sschiavo@economia.unitn.it

Nonparametric and Semiparametric Evidence on the Long-Run E¤ects of In ‡ation on Growth

Keywords: E31, O49, C14 In ‡ation, Growth

In this paper we adopt both a nonparametric and a semiparametric IV estimator to show that the relationship between in ‡ation and output growth is non-linear and that there exists a threshold level below which in ‡ation has no e¤ects on growth.

Aim of the Paper and Literature Review

The aim of this paper is to reassess by means of both a nonparametric estimator and a semiparametric instrumental variable (IV) estimator the issue of the long-run relationship between in ‡ation and economic growth.

The existing empirical literature uses spline models in the belief that a threshold level of in ‡ation exists below which increasing in ‡ation fosters output growth and above which more in ‡ation hampers it. However, …rst, the theoretical literature had considerable di¢ culties in matching this stylized fact [START_REF] Temple | In ‡ation and Growth: Stories Short and Tall[END_REF] and, second, di¤erent empirical contributions have assumed di¤erent threshold levels without being able to test their assumptions (with the exception of [START_REF] Khan | Threshold E¤ects in the Relationship Between In ‡ation and Growth[END_REF]. For instance [START_REF] Fischer | The Role of Macroeconomic Factors in Growth[END_REF] imposes a spline model with two breaks, one at 15% annual in ‡ation rate and the other at 40%. [START_REF] Gylfason | Does In ‡ation Matter for Growth?[END_REF] …nd that the relationship between in ‡ation and growth is non-linear and the threshold in ‡ation rate to be around 10%. Ghosh and Phillips (1998) assume the kink of the spline to be at 2.5%, whereas Judson and Orphanides (1999) choose 10%.

A threshold e¤ect is found also by [START_REF] Thirlwall | In ‡ation and Growth: The International Evidence[END_REF] at an annual in ‡ation rate ranging from 8% to 10%. A similar value is suggested also by [START_REF] Sarel | Nonlinear E¤ects of In ‡ation on Economic Growth[END_REF]. One notable contribution is [START_REF] Khan | Threshold E¤ects in the Relationship Between In ‡ation and Growth[END_REF] who …nd the threshold to be around 1% for industrialized countries and 11% for developing ones. However, the result for the industrialized countries is not completely convincing because the number of observations for which in ‡ation is below 1% is rather small and in most cases they represent rare and temporary occurrences with little chance to impact on long-term growth. Hence, the paucity of observations, together with the assumption of the spline model, may drive the result.

In order to take better care of these issues, we think that nonparametric and semiparametric estimators allow to let as much as possible the data speak shedding further light on both the threshold level of in- ‡ation and its non-linear relationship with output growth. Furthermore, by adopting a semiparametric IV estimator it is possible to tackle the issue of the endogeneity of in ‡ation, a problem that most of the above contributions neglect.

Model Speci…cation and Data Issues

We focus on two model speci…cations both of which builds on [START_REF] Khan | Threshold E¤ects in the Relationship Between In ‡ation and Growth[END_REF]. The dependent variable is the growth rate of GDP in constant local currency units. In Speci…cation I controls include the level of in ‡ation, gross …xed capital formation (or gross capital formation when the former is not available) as a share of GDP, the log of initial per capita GDP in PPP adjusted dollars, population growth, a measure of education and the share of government expenditures over GDP. In addition, robustness checks are performed controlling for in ‡ation volatility and …nancial development. In Speci…cation II, the growth rate of the terms of trade and their 5-year standard deviation are also included.

In ‡ation is instrumented by its …rst lag 1 . Data come from di¤erent sources: whenever possible we refer to the World Bank's World Development Indicators (WDI). For per capita GDP and the share of government consumption we revert to Penn World Tables (PWT), while our education measure (average schooling years in the total population aged 15 or more) comes from the Barro and Lee dataset on educational attainment. Terms of trade data are built from export and import unit value series taken from the IMF's International Financial Statistics (IFS), while …nancial development indicators are taken from [START_REF] Beck | A New Database on Financial Development and Structure[END_REF].

The dataset covers the period 1960-1999, which is the maximum length common to all data sources, and 167 countries. Terms of trade data are available for a smaller set of (mainly developed) countries and they are therefore not included in our baseline speci…cation, but only used as a robustness check.

As customary when focusing on long-term growth [START_REF] Temple | In ‡ation and Growth: Stories Short and Tall[END_REF], we divide all series into 8 equal periods of 5 years each and we consider 5-years means (or medians), although we experiment with di¤erent frequencies as well.

The actual number of available observations is reduced due to the presence of missing data, especially for developing countries (whose IFS code is 200 or above). Moreover, we drop from the sample all observations for which the rate of in ‡ation is above 40%: the semiparametric estimator is extremely sensitive to outliers, therefore we adopt the leave-one-out estimator (Pagan and Ullah, 1999) which brings us to trim observations for which in ‡ation is above a certain threshold. We are not the …rst to recognize this problem: [START_REF] Temple | In ‡ation and Growth: Stories Short and Tall[END_REF] warns against the risk of pooling together countries with very di¤erent in ‡ation dynamics, as few extremely high values may well drive the overall results. The 40% cuto¤ point is also employed in [START_REF] Khan | Threshold E¤ects in the Relationship Between In ‡ation and Growth[END_REF], while Gillman et al. (2004) show that using di¤erent truncation points generates negligible di¤erences in the results.

In the end our sample contains 85 countries and 421 observations, 119 of which pertain to 19 industrial countries. Adding the terms of trade variables substantially reduces the sample size: while developed countries are almost una¤ected, the number of developing countries in the sample falls from 66 to 25.

Estimation Method, Results and Conclusions

A nonparametric estimator is one of the tools that it is possible to use when the relationship between two variables is thought to be non-linear. Furthermore, in order to control for the e¤ect of other covariates, it is possible to use a semiparametric estimator. In this contribution, we follow [START_REF] Park | Semiparametric Instrumental Variable Estimation[END_REF] and we implement a semiparametric IV estimator that accounts for the potential endogeneity of in ‡ation.

The main assumption of [START_REF] Park | Semiparametric Instrumental Variable Estimation[END_REF] is that in the following model

y i = x 0 1i + (x 2i ) + u i (1)
E [u i jx 2i ] is not null, where y is the dependent variable, x ji for j = 1; 2 are two sets of independent variables, ( ) is a non-linear function of unspeci…ed form and i is the subscript for the i-th observation. Let z i be the set of instrumental variables: one …rst …lters out the exogenous part of (x 2i ) by computing g(z 1i ) = E [ (x 2i ) jz 1i ] and then obtains the model:

y i = x 0 1i + g(z 1i ) + v i (2)
where E [v i jz 1i ] = 0: At this stage, supposing x 1i to be exogenous, following [START_REF] Robinson | Root-N-consistent Semiparametric Regression[END_REF] it is possible to obtain estimates of beta as follows:

^ = " n X i=1 (x 1i m12i ) (x 1i m12i ) 0 # 1 " n X i=1 (x 1i m12i ) (y i m2i ) 0 # (3)
where m12i and m2i are the non-parametric estimators of m 12i = E (x 1i jz i ) and m 2i = E (y i jz i ) : More in detail, the nonparametric estimator of m 2 is:

m2 = P n i=1 K z i z h y i P n i=1 K z i z h ( 4
)
where h is the bandwidth and K ( ) is the kernel function. Once having ^ in hand it is easy to …nd ĝ (z i ) :

ĝ (z i ) = m2i m12i ^ (5)
In this contribution, we use a Gaussian kernel and Silverman's optimal bandwidth (Pagan and Ullah, 1999).

Table 1 shows the parameter estimates for the control variables. Figure 1 shows the result for a nonparametric estimation of the relationship between in ‡ation and real GDP growth: the threshold in ‡ation level is around 12 percent. Below it in ‡ation does not appear to be particularly harmful to growth, while above it their relationship becomes markedly negative and steeper. Figure 2 shows the results for the semiparametric IV estimator. The continuous line traces ĝ (z i ) ; whereas the dotted lines mark the 95% con…dence interval. Overall, in ‡ation does not appear to a¤ect growth in a substantial way. The …rst box of Figure 3 shows that the same result would appear using 5 years medians instead of 5 years means, as suggested by [START_REF] Temple | In ‡ation and Growth: Stories Short and Tall[END_REF]. However, splitting the sample between developed and developing countries, as usual in the literature above [START_REF] Khan | Threshold E¤ects in the Relationship Between In ‡ation and Growth[END_REF], provides fruitful insights. The threshold level sticks to around 12% for developed countries, whereas no clear cut result emerges for the group of developing ones. This is probably the results of the very di¤erent experiences undergone by the economies grouped under this label: the relationship between in ‡ation and growth goes up and down for di¤erent in ‡ation levels. Adding terms of trade data (Speci…cation II) does not alter the results in any signi…cant way. Similarly, results are robust to the introduction of in ‡ation volatility and di¤erent measures of …nancial development among control variables 2 .

The last exercise implemented in the paper deals with the frequency of the data. One aspect of the growth-in ‡ation nexus that standard regression analysis has addressed poorly concerns the possibility that the relationship varies by frequency. While we …nd no major change for developing countries, an interesting e¤ect appears for the group of industrialized economies. Figure 4 shows that moving from 3 to 5 to 8 years averages lets a positive relationship between in ‡ation and real growth emerge at low in ‡ation levels. In particular, as displayed in the right panel of Figure 4, below 4% in ‡ation exerts a positive e¤ect on long-run growth, while the relationship becomes markedly negative for rates above 5-6%

This paper uses a nonparametric estimator and a semiparametric IV one to assess the issue of the non-linear relationship between in ‡ation and economic growth and the existence of a threshold e¤ect within it. Our results point to the fact that in ‡ation does not have a substantial e¤ect on economic growth when it is below 12% in developed countries and that the high variability of growth performances in developing countries does not allow to …nd a precise threshold level for in ‡ation. Moving from 3 to 5 to 8 years averages lets a positive relationship between in- ‡ation and economic growth emerge that turns negative above 5-6%. Whilst we do not address the issue of the allocative ine¢ cency generated by in ‡ation, our results also suggest that -from the standpoint of its impact on growth -the importance of low in ‡ation targeting may have been overstated. However, it is also con…rmed that high in ‡ation is detrimental to economic growth. *: significant at the 5% level

Figure 1 -Figure 2 -Figure 3 -Figure 4 -

 1234 Figure 1 -Non-parametric estimation of the effect of inflation on real economic growth

Table 1 -

 1 Coefficient estimates of the control variables

			Specification I			Specification II
		All	Developed	Developing	Median	All	Developed	Developing
	GDP per cap.	-4.40*	-6.02*	-4.26*	-4.01*	-6.53*	-5.66*	-5.93*
	t-statistics	(-7.49)	(-4.56)	(-6.18)	(-6.47)	(-6.92)	(-4.00)	(-4.30)
	Pop. growth	1.53*	0.02	1.73*	0.25	0.35	0.56	0.47
	t-statistics	(9.13)	(0.05)	(8.63)	(0.84)	(1.03)	(1.17)	(0.87)
	Investment/GDP	0.18*	0.16*	0.21*	0.14*	0.28*	0.11	0.37*
	t-statistics	(7.06)	(2.64)	(6.34)	(5.56)	(7.35)	(1.59)	(5.55)
	Gov.Consumption	-0.05	-0.10*	-0.02	-0.09*	-0.06	-0.12*	-0.01
	t-statistics	(-1.77)	(-2.88)	(-0.52)	(-3.35)	(-1.62)	(-2.95)	(-0.11)
	Education	0.10	0.37	0.01	0.08	0.23	0.41	0.22
	t-statistics	(0.54)	(1.81)	(-0.03)	(0.38)	(0.93)	(1.76)	(0.41)
	T. of Trade Growth	-	-	-	-	0.07*	0.11*	0.07
	t-statistics	-	-	-	-	(2.08)	(2.30)	(1.23)
	T. of Trade Stan. Dev.	-	-	-	-	0.78	-6.43	0.86
	t-statistics	-	-	-	-	(1.90)	(-1.66)	(1.43)

Results about the validity of the instrument are available from the authors upon request.

In particular, liquid liabilities to GDP, deposit money bank assets to GDP, and private credit by deposit money banks to GDP. These results are not displayed and are available from the authors upon request.


Stefano Schiavo

Andrea Vaona

Poolability and the finance-growth nexus: a cautionary note

Keywords: C23, O16 poolability, finance, growth

The present contribution tests whether countries can be pooled when studying the financegrowth nexus. Overall, our results point toward a 'pragmatic' positive answer, though considerable heterogeneity is present among developing countries.

The framework of reference

This paper investigates the issue of poolability of different countries to study the connection between finance and growth.

The relationship between financial development and growth is a long-standing issue in economics. Recently, empirical research has moved from cross-country studies to the widespread use of panel regressions in accordance with the direction taken by the growth literature as a whole and in order to avoid simultaneity bias [START_REF] Levine | Finance and growth: Theory and evidence[END_REF]. One issue that is largely overlooked in most panel studies concerns the poolability of individual series. [START_REF] Levine | What we have learned about policy and growth from crosscountry regressions?[END_REF] recognizes the relevance of the problem, but they do not take a stance on it, focusing rather on testing the robustness of the specification of the estimated model.

On the contrary, in the present work we do concentrate specifically on whether series are poolable. In so doing, we follow [START_REF] Baltagi | Pooling: an experimental study of alternative testing and estimation procedures in a two-way error components model[END_REF] who very clearly notes that this question has to be answered before the data are pooled, instruments identified and models estimated. If pooling is in fact rejected, then there will be no scope for a multi-country analysis and policy recommendations will simply be based on wrong premises. Far from being a simple econometric exercise, our contribution highlights the importance of unveiling the priors standing behind econometric estimates, especially when the latter have far reaching policy implications.

Dataset and specification

We exploit the dataset used by [START_REF] Levine | Financial intermediation and growth: causality and causes[END_REF], which is available on-line1 . It contains data on 74 countries spanning the 1960-1995 period. As customary in growth regressions, data are averaged over non-overlapping five years windows to focus on long-run relationships. We opt for a simple linear specification, which is almost standard in this stream of the literature (see [START_REF] Levine | Financial intermediation and growth: causality and causes[END_REF][START_REF] Calderón | The direction of causality between financial development and economic growth[END_REF][START_REF] Beck | Stock markets, banks, and growth: panel evidence[END_REF].

The dependent variable is the growth rate of real per capita gross domestic product (GDP).

Regressors include the level of financial development, along with a set of conditioning variables:

the level of initial real per capita GDP, educational attainment, government size, openness to trade, inflation, and the black market exchange rate premium. Three alternative measures of financial development are used: (i) liquid liabilities of the financial system divided by GDP; (ii) the ratio of commercial bank assets divided by commercial bank plus central bank assets; (iii) the value of credit extended to the private sector over GDP. The first is a typical index of financial depth; the second measures the degree of involvement of the private sector in providing financial services and hence proxies the maturity of the system; the third excludes credit extended by the central bank and government agencies and also credit issued to public-owned enterprises.

Methods, Results and Conclusions

Suppose that the matrix of the regressors X can be partitioned into two parts, X 1 and X 2 . In our case, X 2 are the financial indicators taken one at a time and X 1 are all the other regressors including a constant. We test the poolability of X 2 only. The restricted model is:

y = β 1 X 1 + β 2 X 2 + u
while the unrestricted one is

y = β 1 X 1 + b 2 X * 2 + e
where y is the dependent variable, β 2 and b 2 are the restricted and the unrestricted vectors of coefficients, u and e are stochastic errors, and X * 2 is the counterpart of X 2 for the unrestricted model. Given that we are interested in testing for poolability in an unbalanced setting, X * 2 is obtained from X 2 in two steps. First, one obtains its rows as follows:

i X * 2 = i X 2 ⊗ i D
where the i subscript marks the i-th row of a matrix and D is a matrix of country dummy variables. Second, one stacks i X * 2 in a single matrix to obtain X * 2 .

A review of existing poolability tests is offered in [START_REF] Baltagi | Econometric Analysis of Panel Data[END_REF]. On the basis of a Monte

Carlo study, [START_REF] Baltagi | Pooling: an experimental study of alternative testing and estimation procedures in a two-way error components model[END_REF] recommends the Roy-Zellner test and the [START_REF] Mcelroy | Weaker MSE criteria and tests for linear restricrions in regression models with non-spherical disturbances[END_REF] criteria.

The latter ones do not test the null hypothesis of poolability, but help to choose 'pragmatically' between the pooled and the un-pooled estimator on the basis of the lower mean squared error (MSE). In this study we stick to these recommendations. Finally, given that we have an unbalanced dataset we estimated the variance-covariance matrix of the errors relying on [START_REF] Davis | Estimating multi-way error components models with unbalanced data structures using instrumental variables[END_REF].

Results are presented in Table 1. At first we study the behavior of the whole sample:

although poolability is always rejected by the Roy-Zellner test, the MSE criteria support it, save in one instance for private credit. The picture is even more robust for the group of developed countries, whilst quite a lot of heterogeneity appears to characterize developing economies.

Therefore, pooling seems to be especially problematic for those countries representing the usual target of policy recommendations.

To conclude, while not supported on a purely statistical ground, pooling may indeed be justified from a 'pragmatic' point of view as the additional information granted by a pooled crosssection analysis outweighs the distortion generated by superimposing an identical coefficient across all countries. At the same time, though, our results highlight that the behavior of developing countries is less homogenous. This may be caused by a number of reasons: first, data for developing countries might be of lesser quality; second, substantial heterogeneity across developing countries might actually exist, but we cannot fully capture it due to the relatively short time dimension of the dataset. Our results appear to suggest a critical attitude toward a 'one-fits-all' approach for growth policies and reassess the importance of a country-specific attitude capable to take into account historical, legal and cultural aspects as well (see for instance [START_REF] Rodrik | Getting the diagnosis right[END_REF].

  Roy-Zellner test has an F distribution with (76,363) degrees of freedom in the case of the whole sample, (21,124) for developed countries, and (54,232) for developing ones. The null hypothesis is poolability, p-values in parentheses b. λNT ≤ 0.5 c. λNT ≤ θNT d. λNT ≤ (N -1)/2

Table 1 :

 1 Poolability tests across countries for different financial indicators

	Developing Countries	liquid commercial-private	liabilities central bank credit	2.30 (0.00) 2.26 (0.00) 1.78 (0.00)
		private	credit	3.56 (0.00)
	Developed Countries	commercial-	central bank	2.15 (0.00)
		liquid	liabilities	2.53 (0.00)
		private	credit	1.85 (0.00)
	Whole sample	commercial-	central bank	2.24 (0.00)
		liquid	liabilities	2.40 (0.00)
			test	Roy-Zellner a	Pooling is better?

http://www.econ.brown.edu/fac/Ross Levine/Publications.htm