The changing geography of banking – Ancona, Sept. 23 rd 2006 Discussion of: “Cross border M&As in the financial sector: is banking different from insurance?” by D. Focarelli, A. F. Pozzolo Gregorio De Felice Research Department

1 Background and motivations of the paper Empirical evidence There is an “asymmetry” in the degree of internationalization between banking and insurance, as measured by the number of cross-border transactions.  Higher (absolute) number of cross-border M&As in the banking sector than in the insurance sector, but  significantly lower percentage (of total M&As) of cross-border banking M&As. Objective The authors’ main aim is to explain such asymmetry by comparing the determinants of cross-border M&As in the banking and in the insurance sectors.

2 Add new empirical evidence on the determinants of the internationalization of both the banking and insurance sectors, by testing three major hypotheses:  “Follow the client” hp.: the internationalization of financial firms is a by-product of the international expansion of manufacturing firms, as banks simply follow their home clients where they operate abroad.  “Risk diversification” (or “Profit exploiting”) hp.: “financial firms located in small and less developed countries have stronger incentives to expand their activities abroad”, in order to benefit from risk diversification. Furthermore, as profit-maximizing firms, banks and insurance companies tend to expand towards fast growing and high profitable markets. Objectives and testable hypotheses

3 Objectives and testable hypotheses (cont.)  “Financial market development” hp.: banks and insurance companies operating in larger and more developed financial markets are more likely to be efficient and, thus, more capable of exploiting profit opportunities abroad, especially in high-potential growth markets. OTHER CONTROL VARIABLES  Institutional characteristics and demographic structure are as well expected to affect the pattern of internationalization of financial sector.

4 Main findings Bilateral relationships between origin and destination countries are positively and significantly related with the number of cross-border M&As (consistently with the follow the client hp.). Results hold for both banks and insurance companies. Risk diversification is more important for insurance companies, because supply factors are less relevant in determining the market equilibrium. Stock exchange market development positively affects the propensity of banks and insurance companies to expand internationally. Insurance companies are more likely to engage in cross-border acquisitions if they are based in countries with a larger banking sector and a lower insurance penetration. Banks are more likely to enter less developed financial markets, while insurance companies are more likely to expand towards countries with a more developed insurance market.

5 Comments: methodology and data The percentage of cross-border M&As is probably not the only (... and best) measure of internationalization: an alternative proxy is the ratio of international assets/domestic or total assets. The dependent variable is the number of cross-border transactions: what about their (relative) value? All explanatory variables are mean values over the sample period (1990 or 1995 – 2003?!) By neglecting the time series dimension, the authors are implicitly assuming a static world: this might be a very strong limit, especially for developing countries: e.g., Latin America or CEECs’ attractiveness for foreign investors has changed a lot over the Nineties! How is the sample selected? Is there a cut-off threshold to extract sample deals? Why are all cross-border M&As occurred in CEECs excluded from the sample?

6 1.“Follow the client” hypothesis test The three measures of economic integration (i.e., BILATERAL TRADE, COMMON LANGUAGE and COMMON COLONIZATION) have a positive and statistically significant effect on the internationalization pattern of banks and insurance companies. Major comments But: The proxies do certainly capture the tightness and “proximity” between two countries, not necessarily the presence of firms/clients in the destination country. What about using FDI in manufacturing or service sectors? How does the hypothesis apply to retail-oriented insurance companies? Regression results highlight that the stronger the level of commercial trade intensity and cultural proximity between two countries, the higher the number of cross-border deals, but do not provide evidence that banks and insurance companies follow their (corporate) clients.

7 Major comments (cont.) 2. “Risk diversification/profit exploiting” hypothesis test Explanatory variables: BanksInsurance companies Origin countries Destination countries (-) development ** (-) development *** (-) size ** Development = GDP per capita Size = Population ---

8 Major comments (cont.) 2. “Risk diversification/profit exploiting” hypothesis test Why financial firms located in small/less developed countries may have a stronger incentive to internationalize? Is there any empirical evidence on this? From your tables 4-5, such countries are primarily destination targets in M&As deals... As far as the measures, the authors use GDP/pc to proxy for both economic development and growth potential. Therefore their conclusions are less clear; why don’t they also include the level of GDP/GNI and an explicit measure of growth potential? The signs of size and GDP in table 7 contrast the authors’ hypothesis: the results suggest that smaller and less developed countries are more likely to attract foreign financial investors, and there is no evidence supporting the diversification argument.

9 Major comments (cont.) 3. “Financial market development” hypothesis test Explanatory variables: BanksInsurance companies Origin countries Destination countries (+) Stock market *** (+) Stock market * (-) Credit developm.*** (+) Stock market ** (+) Credit development *** (-) Insurance penetration ** (-) Credit development * (+) Insurance penetration *

10 Major comments (cont.) 3. “Financial market development” hypothesis test Is this an alternative or complementary hypothesis?  From par , page 12, it seems an alternative one. But the authors claim that for the insurance sector results are “consistent with the diversification hypothesis” (page 13) by looking at the coefficient and elasticity of the INSURANCE PENETRATION...  Some results might be driven by the (positive) correlation between “size and economic development” and “financial development”, but no data are provided. How do you argument the hypothesis that “more developed domestic industries might also provide... higher prospects of economic growth, thus reducing the incentives to internationalize” (page 12)? Empirical evidence suggest the opposite... Highly developed financial markets tend to be more efficient and concentrated, and therefore more likely to be origin countries in international deals: how do you explain the negative and significant coefficient of industry concentration for banks? Need to control for efficiency of both origin and destination countries.

11 Conclusions... By drawing on a wide and updated data set, this paper contributes with new interesting evidence to the empirical literature on the determinants of cross-border M&As of financial institutions. On the whole, the analysis is much more useful in order to assess the determinants of cross-border deals, than the asymmetries in the degree of internalization of banks and insurance companies. However, authors’ conclusions on the effect of size and economic development (proxies for risk diversification) should be taken carefully, due to variables and measure specifications. Some variables might have a different economic interpretation:  the number of M&As may as well measure the attractiveness of a destination market, and not only its contestability; in such a case, it may be interesting to look at the interaction of M&As and banking development.

12... and some suggestions State testable hypotheses more clearly, and discuss their theoretical underpinnings more in details to improve the paper reading. Provide a detailed description of some control variable: e.g., how do you exactly measure regulatory restrictions/barriers? Address more extensively some counterintuitive results, e.g. the negative effect of origin market concentration on bank internationalization: it contrasts with both previous empirical evidence and practitioners’ experience.