Samira Hellou
email: hellou.samira@u-paris10.fr

Michel Boutillier
email: michel.boutillier@u-paris10.fr

The impact of regulatory requirements on the banking flows to emerging countries *

Keywords: banking flows, emerging countries, pull and push factors, regulatory requirements

The strengthening of regulatory requirements, along with evolution in banking regulations, can have a negative impact on the external bank financing of emerging countries heavily dependent on this type of financing. Indeed, several studies have aroused fears about the potential effects of significant regulatory adjustments on bank lending to emerging markets. This paper presents a trial to estimate the sensitivity of the banking flows to increased regulatory requirements. We adopt a macroeconomic approach based on the determinants of cross-border banking claims flows from banks located in 19 developed countries to 37 emerging countries. The results of the GMM estimation confirm the negative impact of regulatory requirements on the banking flows to emerging countries, the significant impact of business openness and the negative effect of bank financialization on banking flows to these countries. The results also show that countries rated as speculative grade are influenced by the regulatory requirements, unlike countries rated in investment grade category.

Résumé :

Le renforcement des exigences réglementaires, avec l'évolution de la réglementation bancaire, peut avoir un effet négatif sur le financement extérieur bancaire des pays émergents fortement dépendants à ce type de financement. En effet, plusieurs études ont fait naître des craintes sur les effets potentiels des ajustements réglementaires importants sur les prêts bancaires vers les marchés émergents. Ce papier présente un essai pour estimer la sensibilité des flux bancaires à l'augmentation des exigences réglementaires, dans un cadre macroéconomique basé sur les déterminants des flux des crédits des banques de 19 pays développés vers 37 pays émergents. Les résultats des estimations en GMM confirment l'impact négatif des exigences réglementaires sur les flux bancaires vers les pays émergents, l'impact significatif de l'ouverture commerciale et l'effet négatif de la financiarisation des banques sur les flux bancaires vers ces pays. Les résultats montrent aussi que les pays notés en catégorie spéculative sont influencé par les exigences réglementaires, contrairement aux pays notés en catégorie investissement.

Mots clés : flux bancaires, pays émergents, facteurs pull et push, exigences réglementaires. JEL classifications : F21, F34, G18.

Introduction

Given the importance of capital flows in the financing of emerging countries and the increasing regulatory requirements, several studies have aroused fears about the potential effects of significant regulatory adjustments on bank lending to emerging markets. Indeed, the reduction of regulatory arbitrage opportunities can change the structure of banking flows to emerging countries. This structure has been greatly influenced by evolutions in prudential regulation. Basel I was characterized by simple categorization based on OECD membership countries which gave a wide margin of arbitration. Banks could hold risky assets without regulatory coverage such as short-term assets of OECD emerging countries [START_REF] Bisignano | Qui ont été les privilégiés de Cooke ? Perdants et gagnants de la réglementation des fonds propres[END_REF]. These arbitrages have fueled massive banking flows to emerging countries before the 1997 crisis. Indeed, 64% of bank flows to five countries in crisis were short-term in 1997 [START_REF] Figuet | Basel II and its Implications for Foreign Banks Financing Emerging Countries[END_REF]. In 1999, after publishing the first proposal of Basel II, the Basel Committee received several concerns about its negative effects on lending to risky entities in lower rating category ex: SMEs and emerging countries. The last financial shock has highlighted the weaknesses of this legislation. Therefore, the Basel Committee has proposed a new regulatory framework, Basel III, to strengthen the solvency and liquidity of banks in case of shocks (Basel Committee on Banking Supervision, 2010). Due to capital requirements even higher under Basel III, banking flows might know a tightening due to increased costs and limited risk-taking.

As financing conditions become increasingly restricted with new regulatory reforms, these countries, in need of financing, offset the decline in banking flows in financial markets, which remain volatile and depend on market cycles. Indeed, the tightening of bank financing is part of the current debate around the change in the external financing structure of emerging countries, with the increase of financing in the bonds market to the detriment of bank financing. On the other hand, access to this type of financing requires a fairly developed market, which is not the case for all emerging countries. In this context, this paper attempts to provide some answers to the question of the new prudential regulations effects on the banking flows to emerging countries. We use a macroeconomic approach in order to test the regulatory requirements as a determinant of banking flows to emerging countries under the push and pull factors.

In the best of our knowledge, no paper discusses this question in such way. Firstly, as no specific data is yet available for capital requirements we integrate variables reflecting regulation ratio to consider the effect of the regulation through the effect of these criteria.

Secondly, based to [START_REF] Weder | Will Basel II affect international capital flows to emerging markets?[END_REF] paper who attempted to evaluate ex-ante the impact of Basel II requirements over the period 1993-2001, we evaluate ex-post the capital requirements changes. This method permits the association of risk with regulatory requirements. So, this allows for a detailed analysis of sensitivity to regulatory requirements based on the level of risk. To conduct our empirical assessment, we use cross border data of international banking claims from 19 developed countries to 37 emerging countries, provided by the Bank for international settlements, and ratings to estimate risk, provided by Standard & Poor's, used in the evaluation of regulatory requirements.

Comparing the results of the two estimates with GMM for both periods 1990-2006 and 2007-2014 confirms the significant effect of banking regulations on the banking flows to emerging markets through the significance weighting criteria, the OECD membership for Basel I period and the rating for the Basel II period. The results confirm also the negative impact of regulatory requirements on the banking flows to emerging countries, the significant impact of business openness and the negative effect of bank financialization on banking flows to these countries. Moreover, the results show that countries rated in the speculative grade category are influenced by the regulatory requirements, contrary to countries rated in investment grade category.

The paper is structured as follows. Section 2 present the structure of capital flows to emerging countries and their relation with banking regulation evolution. Section 3 presents the literature review of the banking regulation as an important push or pull factor of these flows. Sections 4 and 5 discuss the empirical model and results. Section 6 concludes.

Banking flows to emerging countries and banking regulation. What link?

Despite the current crisis, the emerging economies still know exceptional growth levels and significant capital flows. Several factors played a positive role in improving the financial situation of these countries. Indeed, after the 1997 crisis, emerging countries try to stabilize and increase the level of confidence in their markets. They are increasing foreign exchange reserves, improving economic fundamentals and the risk-return relationship to be more competitive in terms of capital flows attractiveness. This is through the intervention of elements which reduce the risk such as: the stabilization of inflation or other elements that increase yields as institutional reforms for more open markets. Consequently, the overall situation appears strengthened. Nevertheless, when taken separately, several countries are still ensuring financial stability. These too simple principles seem unable to correctly measure the banking risks.

Therefore, the overhaul of prudential regulation focuses on more sophisticated methods of calculating risks. The Basel II agreement adopts a menu of options to differentiate more finely borrower's level of risk and capital requirements, to cover always a rate of 8%. However, some economists call into question the effectiveness of Basel II agreement because of its procyclical effect and too stringent regulatory requirements for risky entities (SMEs and lowerrated countries). Indeed, the increased requirements for capital strengthening economic cycles may have a destabilizing macroeconomic impact if the decline of credit is not substitutable by other funding sources.

The new Basel agreement further strengthens the regulatory capital requirements in quantity and quality. The minimum requirements for common equity increased from 2% to 4.5% with the introduction of a conservation buffer of 2.5% of active funds, the establishment of countercyclical capital reserves of 2.5% -to contain the excessive accumulation of leverageand the introduction of threshold leverage. This significant cost could push banks to increase the credit rate and reduce their loan allocation levels, which can create a drag on economic activity and the level of investment. An effect that highly disrupts dependent markets such as banking flows to emerging markets especially those have not an alternative financing.

Literature review

The literature review consists in three main parts; the first one focuses on the general framework on the determinants of the banking flows to emerging countries. The second part, discuss the role of banking regulation as pull or push factor of the banking flows. The third part deals with the effects of regulatory requirements on bank flows to emerging countries.

3.1.Determinants of banking flows to emerging countries

The emerging countries have experienced a great return of capital flows after 2003, a return explained by changes in economic fundamentals of these countries as well as the abundance of international liquidity. The level of favorable performance in emerging economies is one of the determinants of banking flows that are classified into two categories: Pull and Push determinants [START_REF] Calvo | Capital inflows and the real exchange rate appreciation in Latin America -The role of external factors[END_REF][START_REF] Fernandez-Arias | The new wave of private capital inflows: Push or pull[END_REF]. The external factors (push)

represent the disadvantage to investing in developed countries with low yields pushing liquidity to emerging countries. The internal factors (pull) are the favorable economic situation in emerging countries that attract liquidity to these markets. But the relationship between these factors and capital flows remain ambiguous because of the complex interaction between them.

External or push factors are the unfavorable situation in countries originating of banking flows pushing these capitals to emerging countries. The origin of these flows is mainly developed countries that have excess liquidity, low yields and low interest rates. Several studies, as [START_REF] Calvo | Capital inflows and the real exchange rate appreciation in Latin America -The role of external factors[END_REF], [START_REF] Montiel | Do capital controls and macroeconomic policies influence the volume and composition of capital flows? Evidence from the 1990s[END_REF], [START_REF] Kim | Causes of capital flows in developing countries[END_REF], [START_REF] Ying | An empirical analysis on capital flows: The case of Korea and Mexico[END_REF], [START_REF] Ferrucci | Understanding capital flows to emerging market economies[END_REF], confirm the influence of these factors on the direction of financial flows. Research on push factors of bank flows focus on developed countries GDP as [START_REF] Jeanneau | Determinants of international bank lending to emerging markets countries[END_REF] and S&P 500 as [START_REF] Broto | Measuring and explaining the volatility of capital flows toward emerging countries[END_REF]. Other factors are recently discussed as push factor such as the cost of bank flows and contagion.

Internal or pull factors are the internal factors reflect the economic performance of a country which makes it more attractive in terms of investment as the economic fundamentals, growth rate, interest rate, inflation, …etc. Several studies such as -Fernandez-Aria (1996), [START_REF] Bohn | Determinants of capital flows and exchange rates: US portfolio investment in Asian capital markets in R Glick[END_REF] showed the importance of these factors as determinants of capital flows to developing countries. The stability of exchange rates, political stability and trade openness also are factors that may favor some countries in terms of attractiveness of flows. Few studies, on determinants of foreign bank lending, focused on risk aversion, interest rate and economic growth [START_REF] Jeanneau | Determinants of international bank lending to emerging markets countries[END_REF]. After the last crisis, several studies have highlighted the disruptive effects of fluctuations in capital flows by identifying the episodes of sudden stops and surges as; [START_REF] Ghosh | Surges[END_REF]; [START_REF] Forbes | Capital flow waves: surges, stops, flight, and retrenchment[END_REF]; [START_REF] Reinhart | Capital flow bonanzas: An encompassing view of the past and present[END_REF].

Therefore, several studies have been conducted within this context. Nevertheless, the literature, on the determinants of banking flows under the pull and push factors to emerging countries, remains limited and focus mainly on traditional variables: interest rate and economic growth [START_REF] Figuet | Cross-border banking claims on emerging countries: The Basel III banking reforms in a push and pull framework[END_REF]. Other studies, [START_REF] Jeanneau | Determinants of international bank lending to emerging markets countries[END_REF], [START_REF] Heid | German bank lending during emerging market crises: A bank level analysis[END_REF]; [START_REF] Forbes | Capital flow waves: surges, stops, flight, and retrenchment[END_REF]; [START_REF] Bruno | Capital flows, cross-border banking and global liquidity[END_REF], concentrate on risk aversion variable such as yield spread and VIX. They show the strong correlation between capital flows and the level of risk. [START_REF] Ghosh | Bank flows and Basel III -Determinants and regional differences in emerging markets[END_REF] discuss the factors that determine banking flows from advanced economies to emerging markets in the context of global factors push and pull. The results show that the impact varies considerably depending on the region. [START_REF] Bruno | Capital Flows and the Risk-Taking Channel of Monetary Policy[END_REF] and [START_REF] Rey | Dilemma not trilemma: the global cycle and monetary policy independence[END_REF] show that banking sector capital flows are strictly associated with US monetary policy.

Banking regulation: push or pull factor?

Basel III is the result of improvements experienced by prudential regulation based on Basel II imperfections revealed by the 2007 crisis. These reforms are supposed reduce the frequency or intensity of financial crises, covering both; micro-prudential measures that strengthen banks' resilience to shocks and macro-prudential measures to strengthen the banking system.

These measures limit the pro-cyclicality and risk interdependence between institutions. So, this bank regulation should have a positive impact on the stability of banking systems.

However, the implementation of this new agreement gives rise to concerns about the effects on the costs of its application. This can lead banks to reduce their credit offers by increasing capital cost. Therefore, it may cause a slowdown in economic activity and a reduction in the level of liquidity in the country which adopts this regulation and flows of this country to emerging countries. It is '' the financial flows channel '' through direct and indirect effects on banking flows [START_REF] Ghosh | Bank flows and Basel III -Determinants and regional differences in emerging markets[END_REF].

Banking regulation is an important factor in banking flows at national or international level through its influence on the banks behavior. Regulatory requirements are an additional cost and can influence the volume of loans and their costs. Capital level change effects can create shocks in the banking market; the regulator has taken into account this change through the gradual establishment by 2019 to allow time for banks to accumulate more capital with the retained earnings. Nevertheless, on the capital market this can cause a significant increase in capital costs: the IIF report (2012) estimate that financial markets would be less elastic with this new agreement. Therefore, the emerging economic equity markets may be affected through several channels, even excluding the application of Basel III by the emerging countries. The first channel is the ''trade flows channel'' due to the economic activity decrease in developed countries. Indeed, the implementation of Basel III in developed countries affects the supply of credit and slowing economic activity, imports and trade. This is the effect of Basel III on the developed countries to emerging countries transmitted through the foreign trade channel. The second is the financial channel [START_REF] Ghosh | Bank flows and Basel III -Determinants and regional differences in emerging markets[END_REF]) which results of lower banking flows to emerging countries through increased capital costs and the decline in interest rate spreads. This channel is composed of two small channels; the first is the effect of the reduction in direct bank loans from developed countries to non-banking institutions in emerging countries. This has a direct effect on investment in these countries. The second channel represents indirect effects on these markets through lower lending to banks in emerging countries. These effects can be enhanced by asymmetric information and problems of country risk assessment by the rating agencies. Moreover, the impact of the decrease in banking flows to emerging countries on the financing of these markets depends on the level of diversification of funding sources and access to capital markets. Small and medium companies can find themselves in trouble compared to large companies that can offset the lack of funding by access to financial markets that has evolved after the 1990s. In these countries, effects may be different from one country to another, depending on their level of independence on banking flows.

The importance of capital flows in the convergence of emerging countries incomes and the importance of financial channel in the transmission of shocks leads us to study the effects of this channel on the capital markets. In this context, the role of banking regulation remains ambiguous to classify it as pull or push factor. It influences the arbitration of international investors in two ways: it can push banking flows through the increase in capital costs, thus decreasing profitability flows to emerging countries, or attract these flows by improving the ratings of these countries.

Empirical studies

Regarding the literature on regulatory requirements, few works have treated its effects on the stability of emerging funding. Van Hoose (2007) shows that it is generally accepted in the theoretical academic literature that the immediate effects of the capital requirements can reduce total loans and increase loan rates. It was not until the 2000s that the subject began to attract economist studies despite the important role played by Basel I in amplifying the 1997 crisis. [START_REF] Bisignano | Qui ont été les privilégiés de Cooke ? Perdants et gagnants de la réglementation des fonds propres[END_REF]; [START_REF] Buch | Determinants of short-term debt: a note[END_REF] show that Basel I favored the short-term financing to emerging countries. As for Basel II, few studies reported negative effects on banking flows to emerging countries such as [START_REF] Reisen | Will Basel II contribute to convergence in international capital flows[END_REF]. He argued that borrowers speculative grade of most emerging and developing countries, would suffer a dramatic rise in debt costs and increased cyclicality of the global banking credit due to Basel II. Griffith-Jones & Spratt (2001) also confirm that Basel II will have a likely negative effect on developing countries.

Other economists confirm that Basel II will have a negligible effect on the financing of emerging countries. [START_REF] Weder | Will Basel II affect international capital flows to emerging markets?[END_REF] address this issue by calculating a measure of the economic capital variation and test its influence on the banking flows of BIS reporting banks. [START_REF] Liebig | Basel II and bank lending to emerging markets: Evidence from the german-banking sector[END_REF], by adopting a micro perspective, calculate the level of bank regulatory capital and the unexpected loss using a value to risk model. This measurement is then tested in a dynamic panel model on the determinants of claims to emerging markets. The results show that there will be a negligible effect on lending by German banks to emerging markets. [START_REF] Liebig | Basel II and bank lending to emerging markets: Evidence from the german-banking sector[END_REF], [START_REF] Claessens | The political economy of Basel II: The costs for poor countries[END_REF], estimate that the Basel II effect on the financing of emerging countries is negligible. About the new Basel III, literature remains limited in some authors', which seems to confirm the negative impact of this agreement on the levels of bank lending in the world. [START_REF] Elliot | Quantifying the effects on lending of increased capital requirements[END_REF] shows that it is likely to be relatively small changes on the lending volumes of US banks due to higher capital requirements. As well Frenkel & Rudolph (2010) examine the macroeconomic and financial effects of the leverage ratio and prove that it will have a significant economic impact. This is likely to lead to a reduction of loans and thus a slowdown in economic activity. They also offer an extensive transition period to avoid these side effects. Others find different results that depend on the characteristics of each economy as [START_REF] Cosimano | Bank behavior in response to Basel III: A cross-country analysis[END_REF]. They confirm that the increase in regulatory requirements under Basel III will push banks to increase their lending rates and reduce the level of credit supply. However, this varies considerably from an advanced economy to another according to equity and elasticity of demand for loans in relation to changes in loan rates. On the other hand, Solvik (2011) shows that more stringent capital requirements on the basis of risk-weighted assets are intended to increase the capacity of the banking system to absorb losses, but also increase banks' incentives to circumvent regulations. [START_REF] Houston | Regulatory arbitrage and international bank flows[END_REF] confirm that differences in banking regulation may be important push or pull factors for cross-border bank claims. The introduction of a leverage ratio based on the unweighted total assets helps to harmonize the activities of banks with their main economic functions and to maximize capital -allocation-efficiency, even if the common argument against a strict leverage ratio is that it increases the cost of bank loans and hurts the economy. [START_REF] Figuet | Cross-border banking claims on emerging countries: The Basel III banking reforms in a push and pull framework[END_REF] show the significant effect of different components of Basel III on the level of banking flows to emerging countries. They use statistics of capital requirement of 500 international banks. This method separates the level of risk from regulatory requirements, which does not allow the detection of categories of countries that will not be affected by the strengthening of regulatory requirements.

This literature review has been prepared in order to present reflection elements concerning the issue of banking flows vulnerability to emerging countries. A deductive reading literature about, on one side, the banking flows determinants to emerging countries, and on the other side, the banking regulation role in the supply of bank financing to these countries confirm '' theoretically '' the role of banking regulation as banking flows determinant to emerging countries without providing a unanimous empirical answer to the question. In this paper we intend to assess the impact of regulatory requirements as push factors on cross border banking claims to 37 emerging markets.

Measurements and estimation procedure

Our estimation of the prudential regulations impact on bank lending to emerging markets use modeling of banks' lending decisions through the push and pulls factors, which constitute the general framework of our empirical test. With this aim, we must develop a model of international bank lending. Most of the existing literatures on international capital flows have adopted a macroeconomic approach, focusing on the push and pull factors determinants of banking flows. However, these studies use data aggregated by creditor countries which does not allow a detailed analysis of the behavior of individual banks. Thus, to test the sensitivity of banking flows to regulatory requirements, we are adopting a macroeconomic approach. On the basis of the push and pull models of banking flows, we are trying to integrate regulatory requirements as a determining factor of these flows. We try to assess these regulation requirements as a quantitative variable.

Regulatory requirements related to credit risk still represent 8% of the risk-weighted assets under Basel I and Basel II. The difference between these two regulations lies in the weights which are primarily related to the OECD membership under Basel I and related to risks under Basel II. Thus, we try firstly to see the effects of these two criteria on the banking flows to emerging countries before and after the implementation of Basel II. Subsequently, we try to estimate the sensitivity of these flows with regulatory requirements through the weights applied under Basel II. These weights represent risk-weighted assets as a percentage of outstanding capital and represents 12.5 of the level of minimum capital requirements.

Concerning the date of the Basel II implementation, according to the Basel Committee, its implementation was scheduled for early January 2007. In our study, the year 2007 is considered as the beginning of the Basel II implementation period. We have known since that date that all developed countries have already begun at least the application of the standard method under Basel II, excepting USA which began its implementation in 20094 . Moreover, the USA was already using another form of regulation as sophisticated and stringent than the Basel II regulations.

Regulatory requirements under Basel I are based on the only criterion of OECD membership.

So, we included a dummy variable that takes the value 0 if the country is not OECD member and the value 1 otherwise (Appendix 3). The estimation is performed for Basel I implementation period (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)

Calculation of interest variable: the risk weights with the IRB approach under Basel II

Under the IRB approach, four risk indicators are defined: 1. PD is the default probability: the risk weights are calculated5 using the default probabilities associated with sovereign ratings of

Standard & Poor's as a proxy to internal ratings. Since the study focuses on annual changes in international bank claims, we take the default probabilities on one year out forecast in order to avoid the multicollinearity problem. 2. M is the credit maturity, which is fixed at 1 year for the same reasons. 3. EAD is the exposure to default which represents the amount due credit.

4.

LGD is the loss given default that fixed at 50%.

The risk weights (RWA / EAD) represent risk-weighted assets as a percentage of the amount due:

12.5 Or 8%

Under this method, K regulatory requirements can take two following values that the counterparty may in default (equation 2) or not (equation 1):

Model specification

We opt for push and pull factors models which consider the key factors that determine the level and direction of banking flows. The choice of empirical modeling is conform to empirical studies on these factors. The model is represented as follows:

, , , ,

, the cross-border banking claims from 19 developed countries to the emerging country i in each period t, , the dependent lagged variable with the corresponding coefficient, , represents all push variables with the vector of corresponding coefficients, represents all pull variables with the vector of corresponding coefficients; the fixed effect, the time fixed effect and , the term error.

As part of the dynamic panel, the generalized method of moments (GMM) appears to be the most appropriate choice for three reasons; the explanatory variable endogeneity, the low temporal dimension in the model and the individual effects resulting from the heterogeneity in the emerging countries group. All tests with the GMM method are validated like so: the pvalue of the Hansen test is above the 10% level (accepting the hypothesis of non-correlation instrumental variables with the error term) and the p-value of the test AR2 is above the 10% threshold (accepting the null hypothesis of no-autocorrelation of errors in order 2). For robustness tests (Appendix 8), we use Static and Dynamic Feasible Generalized Least Squares model, which allows to correct autocorrelation of errors.

Sample

We attempt to provide empirical evidence by focusing on a specific spatiotemporal field. It covers the period of the application of a uniform banking regulation recorded during the years 1990. Thus, two major waves help defining the temporal scope of our study: Basel I in 1988

and Basel II in 2007. The spatial field of the study is identified by defining a list of 37 emerging countries. To date, there is no universal definition for emerging markets. Therefore, the selection of emerging countries is not unanimous among the different academic or professional sources. To select a list of emerging countries, we based our study on databases provided by the IFC (International Finance Corporation) in emerging markets and the list of countries available in the database of the basic variables, i.e. the default probability, which allows us to evaluate changes in regulatory requirements for these countries and cross-border international banking claims. The excluded countries are not retained for non-compliance in the period, or data unavailability. In total, a sample of 37 countries is retained (Appendix 2) representing all geographic regions of emerging countries over 1990-2014.

Variables

After selecting the countries included in the study and the temporal dimension, we consider the problem of the variables selection that best fits with the objective of our test, specifically the variables that influence banking flows to these countries. We hold variables widely used in the literature on the subject. Data used in the model are defined in appendix 16 . The dependent variable is provided by the cross-border international claims from BIS reporting banks7 to all sectors in emerging country i by the end of year. Those are referred as a locational banking statistics and include international transactions between parent banks to their affiliates. The explanatory variables are grouped into two categories according to the literature on the determinants of bank credit flows to emerging economies, pull factors and push factors.

Pull factors:

GDP is the first indicator of country development. We use GDP per capita to remove the effect of the country size [START_REF] Ghosh | Bank flows and Basel III -Determinants and regional differences in emerging markets[END_REF][START_REF] Figuet | Cross-border banking claims on emerging countries: The Basel III banking reforms in a push and pull framework[END_REF]. The competitiveness in terms of profitability as measured by the differential in real interest rates between emerging countries and the United States [START_REF] Jeanneau | Determinants of international bank lending to emerging markets countries[END_REF][START_REF] Figuet | Cross-border banking claims on emerging countries: The Basel III banking reforms in a push and pull framework[END_REF]. The degree of trade openness measured as the sum of imports and exports of goods and services as a percentage of GDP and variables reflecting the weighting criteria in the regulations, OECD membership and rating. These criteria are indicators of the country solvability. OECD membership and good credit rating score are an attractive factor for capital flows.

Push factors:

GDP per capita in developed countries to indicate prosperity pushing these countries to offer more funds [START_REF] Jeanneau | Determinants of international bank lending to emerging markets countries[END_REF][START_REF] Ghosh | Bank flows and Basel III -Determinants and regional differences in emerging markets[END_REF][START_REF] Figuet | Cross-border banking claims on emerging countries: The Basel III banking reforms in a push and pull framework[END_REF]. We include the attractiveness of financial markets as a proxy of profitability in the financial markets through the Standard & Poor's 500 index [START_REF] Broto | Measuring and explaining the volatility of capital flows toward emerging countries[END_REF][START_REF] Figuet | Cross-border banking claims on emerging countries: The Basel III banking reforms in a push and pull framework[END_REF] and VIX (Volatility Index) to measures market expectation of volatility. Finally, we consider the weights related to bank claims that reflect the bank credit cost.

Result analysis

We conduct the empirical test in four steps in two periods and by groups of variables. We begin with the baseline model with traditional push and pull variables (column 1) and then, one by one with variable representing criteria of bank regulation under Basel I (column 2) and

Basel II (column 3). Then, we combine these two variables (column 4). Finally, as a robustness test we change variables control (column 5). All estimates show that the lagged variable is very significant with a positive coefficient sign (table 1). This strong significance reflects the continuity in the behavior of the supply of credit, which can be explained by pattern and familiarity of the borrower.

As for macroeconomic factors, the pull factors determine the banking flows to emerging countries with a highly significant GDP per capita (with a positive and significant coefficient at 1% and 5%), unlike the per capita GDP of developed countries which doesn't seem to play a role in the behavior of lending to emerging countries. The differential in interest rate does not seem have a significant role, which consist with the literature (Weder & Wedew, 2002;[START_REF] Liebig | Basel II and bank lending to emerging markets: Evidence from the german-banking sector[END_REF][START_REF] Broto | Measuring and explaining the volatility of capital flows toward emerging countries[END_REF][START_REF] Figuet | Cross-border banking claims on emerging countries: The Basel III banking reforms in a push and pull framework[END_REF]. The role of financial markets depends on the estimate period. Profitability in the financial markets, represented by the SP500, does not seem influencing the behavior of the credit supply for the period 1990-2006.

For the 2007-2014 period, the role of profitability in the financial markets appears significantly negative (1%) which, highlights the impact of the banks' financialization and the banking evolution with financial innovations related to credit. These results are confirmed with the VIX coefficient, which is not significant for the period 1990-2006 and significant at 1% for 2007-2014 period. Finally, the role of trade openness as a determinant of banking flows is more significant and negative for the 2007-2014 period.

Concerning the two variables that reflect the weighting criteria in bank regulation, the estimate for the period 1990-2006 confirm the significant positive effect (5%) of the OECD membership in the supply of credit which highlights the effect of the easing of regulatory requirements to the OECD member countries. For the same period, the risk level appears insignificant.

The estimation for 2007-2014 shows that the ratings influence the supply of credit, which can be explained by the weight given by regulations to risk. The effect of the OECD membership does not play a significant role. Comparing the results of the two estimates for both periods confirms the significant effect of banking regulations on the banking flows to emerging markets through the significance weighting criteria, the OECD membership for Basel I period and the rating for the Basel II period. Our results on the effects of ratings before and after the implementation of Basel II are consistent with the results of [START_REF] Iftekhar | The effects of ratings-contingent regulation on international bank lending behavior: Evidence from the Basel II accord[END_REF], confirming the weight of ratings after the implementation of Basel II in the credits flows to emerging countries. Concerning the exchange rate variable, the effect is tested but not reported, it is not significant for both periods. Indeed, bank loans may be more sensitive to exchange rate expectations than the real exchange rate. To estimate the sensitivity of the banking flows to the changes of regulatory requirements, we integrate the weightings applied in banking regulation Basel II. The results show a negative and significant effect at 5% in order of 0.039 to risk-weighted assets as a percentage of the amount due (the credit level) on the banking flows to emerging countries (table 2). As credit risk assessment remains unchanged (BCBS, 2010) still calculated with IRB model and given the adjustments required for credit risk under Basel III 8 , the level of minimum regulatory requirements increase from 8% to 10.5% or even 13% if we consider the countercyclical buffer (Table 3). This corresponds to an increase of 2.5% to 5% regulatory requirements, inducing an increase of 31.25% to 62.5% of the weighted assets credit risk percentage. Considering the coefficient (-0.0391) of the last estimate (Table 2), this increase induces a decrease of 1.22% to 2.44% of bank claims to emerging countries. Moreover, these countries will not be affected on the same level by this increase of regulatory requirements. A priori, countries with lower ratings will be more affected. 8 We adopt the implicit hypothesis that banks will not change their behavior with the introduction of Basel III. Besides, regulatory requirements do not only dependent on the solvency ratio; rating has a negative or positive effect in determining the level of regulatory requirements. The deterioration or improvement, such as: the deterioration of the rating B to -B causes an increase of 33.5264% of risk weighted assets which, in our estimation, and considering the same level of regulatory requirements, can induce a fall in banking flows of 1.31%.

Conversely, the improved rating, from -B to B, increases the banking flows by 1.31%.

Table 4 also shows that changes in risk-weighted assets are more important for the ratings that represent a high degree of risk. Therefore, we try, in table 5, to test the effect of regulatory requirements on bank flows to countries rated in speculative grade category compared to countries in investment grade category. The results confirm that countries with lower ratings are influenced by regulatory requirements unlike the well-rated countries. This increase of 2.5% to 5% regulatory requirements with Basel III, induce an increase of 31.25% to 62.5% of the weighted assets credit risk percentage. Considering the coefficient (-0.181) of the last estimate (Table 5), this increase induces a decrease of 5.65% to 11.31% of bank claims to speculative grade emerging countries. However, this can have a positive effect by encouraging these countries to develop alternative financing on capital markets and to stabilize their external financing.

Results in table 5 show that, for investment grade countries, regulatory requirements do not seem play a significant role in the determination of banking flows. This reflects the low level of regulatory requirements for this category. For control variables, lagged variable and GDP for emerging countries seem influence positively and significantly banking flows. Financial markets, through SP500 and VIX, seem have a significant and negative effect on the volume of banking flows and this is the same for trade openness. For countries rated in the speculative category, regulatory requirements are the only variable that seems to play a role in determining bank flows with the lagged variable. This shows the importance of these requirements so high that the other control variables no longer have any effect. As a final point, for both categories, differential interest rate and GDP for developed countries do not affect banking flows to emerging market.

As a robustness test for all estimations and with the same steps, we use static and dynamic feasible generalized least squares model (appendix 8). All tests confirm the significances and signs of each variable and period with the GMM model. These results provide an overall estimate of the effects of regulatory requirements under Basel III on bank claims to emerging countries, but their analysis must be cautious because firstly, they do not take into account the impact of the liquidity and the leverage ratio. Secondly, they will depend on the level of regulatory requirements actually applied by the banks. However, other studies have dealt with the effect of these ratios that joins our results such as [START_REF] Houston | Regulatory arbitrage and international bank flows[END_REF]. They confirm that the introduction of a leverage ratio based on the unweighted total assets harmonize the activities of banks with their main economic functions and to maximize capital -allocation-efficiency, but a strict leverage ratio increases the cost of bank loans and hurts the economy. Otherwise, the paper does not take into account the dependence on the wholesale market to control the drying up of interbank dollar markets, which appear to have played an important role in the dynamics of international bank lending (McGuire &Peter, 2012 and[START_REF] Mccauley | Dollar credit to emerging market economies[END_REF]al., 2015).

Conclusion

The high-level growth in emerging countries promises of higher equity returns. Nevertheless, these expectations will not be full filed without the large capital flows from rich countries in capital to the developed economies. While strengthening regulatory requirements, changes in banking regulation affect the structure of external financing of emerging countries. Indeed, the results of the GMM estimation confirm the negative and significant effect of the regulatory requirements levels on the banking flows towards emerging countries. Therefore, adjustments of regulatory requirements under Basel III result in restrainment of banking flows to emerging countries. However, this decline may be offset by an improvement in the level of risk in these countries or be strengthened by a drop in ratings. On the other hand, given that the banking flows to lower rated countries are more sensitive to this increase in regulatory requirements, emerging countries are encouraged to improve their ratings. The results confirm also, the significant impact of business openness and the negative effect of bank financialization on banking flows to these countries.

Consequently, emerging countries offset this decline in banking flows by financing on the financial markets, which remain highly volatile. Nevertheless, for less developed countries that do not have access to financial markets, decline in banking flows will have an impact on the financing of investment and growth. period (1990-2006) and the value of 1 for the Basel II period (2007[START_REF] Ghosh | Surges[END_REF]. SGDUM is a dummy variable that takes the values of 1 if country is rated speculative grade and 0 if country is rated investment grade. _diff is the interaction between BASELDUM and SGDUM.

  Figure 1

  and Basel II implementation period (2007[START_REF] Ghosh | Surges[END_REF] to test the effect of OECD membership on the banking flows before and after Basel II. The Diff in Diff estimate confirms the structural change of bank flows between the two periods (Appendix 7). In the same way, the fact that regulatory requirements under Basel II depend mainly on risk, we include a variable that reflects the risk -which takes a value between 1 and 26 from the AAA to SD rating (Appendix 6) -in the model to compare the risk effect on the credit flows before and after the implementation of Basel II. In a last step, and to measure the credit flows sensitivity to the regulatory requirements under Basel II, we include a variable that reflects the weights applied under Basel II. For the regulatory requirements calculation given that we don't have any information indicating the requirements level applied by each bank. The calculation of these weights is based on the IRB method (Internal Ratings Based) that represents the method used by most large international banks to calculate capital requirements under Basel II (Bank for International Settlements, June 2006. p78) and Basel III (Bank for International Settlements, December 2010 revised June 2011. p43).

   : the distribution of a standard normal distribution function. ρ (PD): the correlation is a decreasing function of the default probability. b (PD) : stipulates that adjustment of maturity is a decreasing function of the default probability. EL (Expected Losses) = PD*LGD with 99.

  is a dummy variable that takes the values of 0 for the Basel I

Table 1 :

 1 Estimation results of regulation criteria with GMM system

		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
		DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS
				1990-2006					2007-2014
	L.DlIBCLAIMS	0.215 ***	0.215 ***	0.245 ***	0.246 ***	0.157 **	0.282 ***	0.281 ***	0.277 ***	0.274 ***	0.287 ***
	DlGDP_CEC	(0.0561) 0.652 ***	(0.0602) 0.636 ***	(0.0647) 0.598 ***	(0.0647) 0.592 ***	(0.0762) 0.710 ***	(0.0778) 0.567 **	(0.0794) 0.566 **	(0.0796) 0.573 ***	0.0811 0.568 **	(0.0644) 0.461 **
		(0.117)	(0.113)	(0.124)	(0.119)	(0.104)	(0.210)	(0.209)	(0.208)	(0.207)	(0.178)
	DlGDP_CDC	-0.117	-0.101	-0.0551	-0.0566	-0.166	-0.258	-0.256	-0.262	-0.255	0.106
	DIFF_IR	(0.163) -0.0829	(0.117) -0.0926	(0.0955) -0.140 **	(0.0973) -0.134 *	(0.137)	(0.316) -0.120	(0.314) -0.121	(0.313) -0.122	(0.310) -0.126	(0.262)
	lSP500	(0.103) -0.0199	(0.0960) -0.0283	(0.0685) -0.0312	(0.0667) -0.0358		(0.150) -0.212 ***	(0.150) -0.212 ***	(0.156) -0.213 ***	(0.156) -0.213 ***
		(0.0298)	(0.0294)	(0.0199)	(0.0212)		(0.0520)	(0.0520)	(0.0518)	(0.0518)
	OCDEDUM		0.0704 **		0.0584 **	0.0531 *		-0.0000741		-0.0105	-0.0115
			(0.0336)		(0.0269)	(0.0304)		(0.0229)		(0.0223)	(0.0267)
	lRATING_SP			-0.0408	-0.0344	-0.0463			-0.0380 **	-0.0389 **	-0.0265 **
				(0.0848)	(0.0711)	(0.0891)			(0.0148)	(0.0153)	(0.0130)
	lVIX					-0.0118					-0 . 1 8 3 ***
	DlTRADOPEN					(0.0414) 0.303 *					(0.0393) -0 . 3 0 2 **
	Constant	0.210	0.259	0.392	0.400	(0.155) 0.203	1.528 ***	1.529 ***	1.615 ***	1.617 ***	(0.139) 0.605 ***
		(0.208)	(0.202)	(0.285)	(0.262)	(0.241)	(0.373)	(0.373)	(0.372)	(0.371)	(0.119)
	Observations	419	419	377	377	417	239	239	239	239	294
	AR2	0.321	0.331	0.522	0.500	0.975	0.534	0.534	0.563	0.568	0.371
	Hansen	0.444	0.459	0.497	0.512	0.438	0.435	0.468	0.417	0.494	0.234
	instr	32	33	33	34	34	35	36	36	37	37

Notes: Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01.

Table 2 :

 2 Estimation results of risk weighted assets under Basel II

		GMM system over 2007-2014
		(1)	(2)	(3)	(4)
		DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS
	L.DlIBCLAIMS	0.303 ***	0.274 ***	0.272 **	0.274 ***
	DlGDP_CEC	(0.0940) 0.593 **	(0.0982) 0.601 **	(0.100) 0.596 **	(0.0921) 0.571 ***
		(0.248)	(0.231)	(0.232)	(0.193)
	DlGDP_CDC	-0.387	-0.392	-0.423	-0.113
		(0.425)	(0.390)	(0.400)	(0.341)
	DIFF_IR	-0.112	-0.164	-0.164
	lSP500	(0.158) -0.219 ***	(0.186) -0.217 ***	(0.170) -0.205 ***
		(0.0597)	(0.0704)	(0.0683)
	lRWA_EAD		-0.0391 **	-0.0455 **	-0.0385 *
			(0.0174)	(0.0176)	(0.0207)
	OCDEDUM			-0.0464	-0.0322
	lVIX			(0.0363)	(0.0502) -0.178 ***
					(0.0462)
	DlTRADOPEN				-0.290
	Constant	1.575 ***	1.524 ***	1.434 ***	(0.206) 0.499 ***
		(0.430)	(0.504)	(0.486)	(0.141)
	Observations	223	223	223	222
	AR2	0.562	0.665	0.686	0.680
	Hansen	0.572	0.518	0.562	0.536
	instr	36	36	37	38
	Notes: L.DlIBCLAIMS is the lagged dependent variable (cross-border banking claims).
	Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01.

Table 3 :

 3 Evolution of capital -Basel II to Basel III-

	Components of equity	Basel II	Basel III
	Total Tier 1	Tier 1 :2% RWA	Tier 1
			Core: 4,5% RWA
			+ Conservation Buffer: 2,5% RWA
			+ countercyclical buffer: 0 -2,5% RWA
			+ systemic risk
		Tier 1 complementary	Tier 1 complementary
		: 2% RWA	: 1,5% RWA
	Tier 2	Tier 2 :4% RWA	Tier 2 :4% RWA
	Total funds	8% RWA	10,5% à 13% RWA

Table 4 :

 4 Weights and regulatory requirements related to ratings of S&P under the IRB

					approach of Basel II
	RATING Code RATING PD_1Y	p_PD	b_PD	M MA WCDR LGD	k	RWA/EAD (%) ∆RWA/EAD(%)
	AAA	1	0	0,24		1			0,5	-
	AA+	2	0	0,24		1			0,5	-
	AA	3	0,02	0,238806 0,342333 1	1	0,009991 0,5 0,004895	6.11925	6.11925
	AA-	4	0,03	0,238213 0,316834 1	1	0,013774 0,5 0,006737	8.421375	2.302125
	A+	5	0,06	0,236454 0,27553 1	1	0,023465 0,5 0,011432	14.29037	5.868995
	A	6	0,07	0,235873 0,266737 1	1	0,02633	0,5 0,012815	16.01875	1.72838
	A-	7	0,08	0,235295 0,259234 1	1	0,029062 0,5 0,014131	17.66363	1.64488
	BBB+	8	0,14	0,231887 0,228957 1	1	0,043411 0,5 0,021005	26.25662	8.59299
	BBB	9	0,2	0,228581 0,210641 1	1	0,055379 0,5 0,026689	33.36175	7.10513
	BBB-	10	0,32	0,222257 0,18767 1	1	0,074973 0,5 0,035887	44.85812	11.49637
	BB+	11	0,43	0,216785 0,173909 1	1	0,089601 0,5	0,04265	53.31287	8.45475
	BB	12	0,68	0,205412 0,1536	1	1	0,115634 0,5 0,054417	68.02125	14.70838
	BB-	13	1,13	0,188203 0,132566 1	1	0,148533 0,5 0,068616	85.77038	17.74913
	B+	14	2,31	0,157807 0,105577 1	1	0,201957 0,5 0,089428	111.7855	26.01512
	B	15	4,73	0,131274 0,081606 1	1	0,276855 0,5 0,114778	143.472	31.6865
	B-	16	7,92	0,122288 0,06627 1	1	0,362397 0,5 0,141599	176.9984	33.5264
	CCC/C	17-25	26,87	0,12	0,036294 1	1	0,685696 0,5 0,208498	260.6226	83.6242
	Source: author's calculation. Note: PD-1Y refers to the default probabilities on one year associated with sovereign ratings of
	Standard & Poor's as a proxy to internal ratings

Table 5 :

 5 Estimation results of risk weighted assets under Basel II with system GMM over 2007-2014 Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01.

			Speculative grade versus Investment grade countries
		(1)	(2)	(3)	(4)	(1)	(2)	(3)	(4)
		DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS
		Investment Grade countries			Speculative Grade countries
	L.DlIBCLAIMS	0.139 *	0.156 *	0.176 ***	0.194 **	0.329 **	0.250 *	0.267 **	0.258 *
	DlGDP_CEC	(0.0765) 0.964 ***	(0.0831) 1.001 ***	(0.0462) 0.829 ***	(0.0731) 0.963 ***	(0.123) 0.444	(0.121) 0.339	(0.118) 0.403	(0.130) 0.397
		(0.212)	(0.214)	(0.228)	(0.168)	(0.332)	(0.260)	(0.265)	(0.266)
	DlGDP_CDC	-0.514	-0.587	-0.155	-0.269	0.0407	0.0124	0.0881	-0.0407
		(0.336)	(0.357)	(0.321)	(0.337)	(0.613)	(0.503)	(0.449)	(0.484)
	DIFF_IR	-0.442	-0.319			0.0697	-0.211
	lSP500	(0.267) -0.255 ***	(0.286) -0.284 ***	-0.355 ***		(0.273) -0.277	(0.313) -0.238	-0.253
		(0.0639)	(0.0810)	(0.0729)		(0.188)	(0.200)	(0.166)
	lRWA_EAD		-0.0346	-0.0417	-0.0367		-0.189 **	-0.166 **	-0.181 **
	lVIX		(0.0343)	(0.0281)	(0.0237) -0.199 ***		(0.0705)	(0.0584)	(0.0755) -0.119 *
	DlTRADOPEN				(0.0547) -0.337 *				(0.0556) -0.219
	Constant	1.849 ***	2.003 ***	2.477 ***	(0.177) 0.535 ***	1.962	1.669	1.771	(0.244) 0.314 *
		(0.461)	(0.573)	(0.521)	(0.164)	(1.324)	(1.422)	(1.177)	(0.178)
	Observations	137	122	162	122	82	81	94	80
	AR2	0.386	0.403	0.523	0.246	0.518	0.605	0.651	0.554
	Hansen	0.490	0.564	0.284	0.822	0.610	0.467	0.333	0.728
	instr	28	29	28	30	11	12	11	13
	Notes:

  Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01. Autocorrelation and heteroscedasticity have been corrected 8.3. Robustness tests of the second estimation with Static Feasible Generalized Least Squares model Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01. Autocorrelation and heteroscedasticity have been corrected 8.4. Robustness tests of the second estimation with Dynamic Feasible Generalized Least Squares model Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01. Autocorrelation and heteroscedasticity have been corrected. 8.5. Robustness tests of the third estimation with Static Feasible Generalized Least Squares model Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01. Autocorrelation and heteroscedasticity have been corrected 8.6. Robustness tests of the third estimation with Dynamic Feasible Generalized Least Squares model Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01. Autocorrelation and heteroscedasticity have been corrected.

	Appendix 8: Robustness tests
	8.1. Robustness tests of the first estimation with Static Feasible Generalized Least Squares model (2) (3) (4) (5) (6) (7) (8) DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS (1) (9) (10) 1990-2006 2007-2014 0.673 *** (0.0647) 0.671 *** (0.0638) 0.732 *** (0.0700) 0.731 *** (0.0690) 0.841 *** (0.0826) 0.699 *** 0.105 0.676 *** 0.107 0.717 *** 0.104 0.703 *** 0.106 0.676 *** 0.0926 -0.146 (0.120) -0.150 (0.118) -0.230 * (0.129) -0.234 * (0.127) -0.333 ** (0.134) -0.253 0.167 -0.238 0.168 -0.247 0.156 -0.242 0.158 0.0400 0.163 -0.118 ** (0.0495) -0.101 ** (0.0491) -0.0478 (0.0546) -0.0294 (0.0541) -0.0513 0.150 -0.0753 0.151 -0.0318 0.151 -0.0474 0.152 0.0120 (0.0173) 0.00416 (0.0171) -0.0207 (0.0215) -0.0284 (0.0212) -0.167 *** 0.0456 -0.165 *** 0.0455 -0.181 *** 0.0432 -0.177 *** 0.0437 0.0896 *** (0.0309) 0.0870 *** (0.0311) 0.0598 ** (0.0263) -0.0235 0.0209 -0.0213 0.0208 -0.0131 0.0188 -0.0127 (0.0187) -0.00831 (0.0181) -0.0204 (0.0175) -0.0251 *** 0.00830 -0.0241 *** 0.00859 -0.0176 ** 0.00745 -0.0113 (0.0295) -0.0440 * 0.0250 0.323 *** (0.112) -0 . 3 9 3 *** 0.0933 -0.00510 (0.117) 0.0388 (0.116) 0.254 * (0.150) 0.286 * (0.148) 0.141 (0.0962) 1.226 *** 0.327 1.222 *** 0.327 1.368 *** 0.311 1.347 *** 0.314 0.189 ** 0.0773 464 464 396 396 437 239 239 239 239 294 140.4 153.5 138.4 150.4 161.7 72.70 74.12 82.42 83.12 108.8 Notes: Dependent variable, for all regressions, is cross-border banking claims. Standard errors in parenthesis: * p < 0.10, ** p < 0.05, *** p < 0.01. DlGDP_CEC DlGDP_CDC DIFF_IR lSP500 OCDEDUM lRATING_SP lVIX DlTRADOPEN Constant Observations chisquared Autocorrelation and heteroscedasticity have been corrected 8.2. Robustness tests of the first estimation with Dynamic Feasible Generalized Least Squares model (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS 1990-2006 2007-2014 L.DlIBCLAIMS 0.394 *** (0.0335) 0.375 *** (0.0345) 0.405 *** (0.0375) 0.384 *** (0.0389) 0.387 *** (0.0368) 0.129 ** (0.0557) 0.123 ** (0.0561) 0.112 ** (0.0552) 0.109 * (0.0556) 0.101 ** (0.0499) DlGDP_CEC 0.611 *** (0.0579) 0.612 *** (0.0575) 0.594 *** (0.0592) 0.596 *** (0.0589) 0.759 *** (0.0704) 0.633 *** (0.108) 0.617 *** (0.109) 0.653 *** (0.106) 0.644 *** (0.108) 0.615 *** (0.0968) DlGDP_CDC -0.0357 (0.106) -0.0430 (0.106) -0.0242 (0.114) -0.0325 (0.113) -0.159 (0.119) -0.365 ** (0.170) -0.348 ** (0.171) -0.334 ** (0.157) -0.327 ** (0.159) -0.0250 (0.172) DIFF_IR -0.0518 (0.0423) -0.0389 (0.0425) -0.0507 (0.0466) -0.0378 (0.0469) -0.0919 (0.154) -0.110 (0.155) -0.0717 (0.154) -0.0833 (0.155) lSP500 0.00636 (0.0174) 0.000803 (0.0174) -0.0177 (0.0196) -0.0229 (0.0196) -0.168 *** (0.0448) -0.168 *** (0.0449) -0.182 *** (0.0423) -0.179 *** (0.0425) OCDEDUM 0.0489 ** (0.0237) 0.0458 * (0.0242) 0.0303 (0.0210) -0.0171 (0.0205) -0.0161 (0.0204) -0.00980 (0.0185) lRATING_SP 0.00561 (0.0133) 0.00670 (0.0130) -0.00126 (0.0125) -0.0242 *** (0.00810) -0.0234 *** (0.00828) -0.0175 ** (0.00772) lVIX 0.00498 (0.0262) -0.0555 ** (0.0262) DlTRADOPEN 0.336 *** (0.0964) -0 . 3 5 6 *** (0.0975) Constant -0.00849 (0.119) 0.0245 (0.119) 0.148 (0.137) 0.176 (0.137) 0.00617 (0.0839) 1.227 *** (0.322) 1.228 *** (0.322) 1.367 *** (0.304) 1.354 *** (0.306) 0.217 *** (0.0804) Observations 443 443 389 389 430 239 239 239 239 294 chi squared 345.6 353.1 317.0 322.3 371.8 79.12 79.68 89.56 90.02 110.2 Notes: (1) (2) (3) (4) DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlGDP_CEC 0.699 *** (0.105) 0.779 *** (0.113) 0.754 *** (0.116) 0.668 *** (0.0997) DlGDP_CDC -0.253 (0.167) -0.319 * (0.186) -0.312 * (0.189) 0.0297 (0.181) DIFF_IR -0.0513 (0.150) 0.00943 (0.153) -0.0358 (0.156) lSP500 -0.167 *** (0.0456) -0.205 *** (0.0518) -0.200 *** (0.0516) lRWA_EAD -0.0353 *** (0.0115) -0.0433 *** (0.0130) -0.0111 (0.0110) OCDEDUM -0.0427 * (0.0245) -0.0119 (0.0211) lVIX -0.0329 (0.0285) DlTRADOPEN -0.412 *** (0.104) Constant 1.226 *** (0.327) 1.446 *** (0.370) 1.418 *** (0.369) 0.104 (0.0863) Observations 239 223 223 278 chi squared 72.70 75.13 79.48 85.68 Notes: (1) (2) (3) (4) DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS L.DlIBCLAIMS 0.0693 (0.0469) 0.0806 * (0.0466) 0.0695 (0.0474) 0.0972 ** (0.0458) DlGDP_CEC 0.707 *** (0.104) 0.765 *** (0.111) 0.756 *** (0.114) 0.697 *** (0.0993) DlGDP_CDC -0.271 (0.168) -0.293 (0.181) -0.312 * (0.186) 0.0274 (0.174) DIFF_IR -0.0491 (0.150) -0.0110 (0.153) -0.0379 (0.156) lSP500 -0.159 *** (0.0459) -0.197 *** (0.0516) -0.193 *** (0.0518) lRWA_EAD -0.0343 *** (0.0108) -0.0392 *** (0.0124) -0.0161 * (0.00859) OCDEDUM -0.0332 (0.0235) -0.0132 (0.0197) lVIX -0.0674 ** (0.0327) DlTRADOPEN -0.365 *** (0.110) Constant 1.157 *** (0.330) 1.383 *** (0.370) 1.354 *** (0.370) 0.191 * (0.0980) Observations 239 223 223 278 chi squared 77.28 80.32 82.78 96.39 (2) (3) (4) (1) (2) (3) (4) DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS Investment Grade countries Speculative Grade countries DlGDP_CEC 0.822 *** (0.115) 0.815 *** (0.129) 0.728 *** (0.118) 0.651 *** (0.103) 0.529 *** (0.197) 0.520 *** (0.188) 0.609 *** (0.173) 0.750 *** (0.176) DlGDP_CDC -0.266 (0.171) -0.236 (0.205) -0.115 (0.166) 0.328 * (0.170) -0.0491 (0.332) -0.169 (0.226) 0.0789 (0.248) -0.320 (0.329) DIFF_IR -0.195 (0.152) -0.111 (0.164) 0.134 (0.278) -0.489 (0.369) lSP500 -0.180 *** (0.0440) -0.176 *** (0.0522) -0.189 *** (0.0457) -0.187 ** (0.0891) -0.259 *** (0.0566) -0.288 *** (0.0512) lRWA_EAD -0.00696 (0.0171) -0.00736 (0.0150) 0.00962 (0.0105) -0.130 *** (0.0438) -0.103 *** (0.0331) -0.0843 ** (0.0371) lVIX -0.0107 (0.0305) -0.0564 (0.0538) DlTRADOPEN -0.631 *** (0.103) -0.000410 (0.203) Constant 1.329 *** (0.317) 1.284 *** (0.378) 1.359 *** (0.326) 0.0576 (0.0963) 1.339 ** (0.642) . 1.839 *** (0.408) 2.046 *** (0.371) 0.160 (0.161) Observations 152 137 179 179 87 86 100 99 chi squared 87.77 71.06 63.89 111.7 15.74 43.98 66.48 27.34 Notes: (1) (2) (3) (4) (1) (2) (3) (4) DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS DlIBCLAIMS Investment Grade countries Speculative Grade countries L.DlIBCLAIMS 0.0883 * (0.0525) 0.104 * (0.0548) 0.0967 * (0.0500) 0.111 ** (0.0504) 0.247 ** (0.0969) 0.217 ** (0.0909) 0.195 ** (0.0834) 0.247 *** (0.0949) DlGDP_CEC 0.849 *** (0.110) 0.839 *** (0.120) 0.721 *** (0.116) 0.655 *** (0.109) 0.443 ** (0.221) 0.543 ** (0.213) 0.598 *** (0.190) 0.802 *** (0.199) DlGDP_CDC -0.461 *** (0.176) -0.493 ** (0.204) -0.208 (0.172) 0.384 ** (0.179) 0.548 (0.344) 0.147 (0.337) 0.256 (0.315) -0.0649 (0.363) DIFF_IR -0.195 (0.126) -0.125 (0.139) 0.360 (0.238) -0.224 (0.350) lSP500 -0.136 *** (0.0456) -0.121 ** (0.0537) -0.157 *** (0.0492) -0.301 *** (0.0927) -0.279 *** (0.0983) -0.281 *** (0.0909) lRWA_EAD -0.0183 (0.0184) -0.0123 (0.0156) -0.00449 (0.0126) -0.139 *** (0.0484) -0.142 *** (0.0397) -0.135 *** (0.0429) lVIX -0.0748 ** (0.0306) -0.106 (0.0677) DlTRADOPEN -0.636 *** (0.127) -0.0226 (0.224) Constant 1.002 *** (0.329) 0.856 ** (0.388) 1.112 *** (0.351) 0.211 ** (0.0870) 2.129 *** (0.671) 1.950 *** (0.707) 1.963 *** (0.653) 0.264 (0.201) Observations 137 122 162 162 79 78 89 88 chi squared 92.82 73.30 61.45 141.5 45.89 46.13 53.13 47.57 Notes: (1) Notes:

Report: European Parliament's Committee on Economic and Monetary Affairs. October 2011. http://www.europarl.europa.eu/activities/committees/studies.do?language=EN

We assume that the default probability for all economic actors in a country (public sector, private sector, banking sector) tend to the country's default probability. For this variable, we use the ratings provided by S&P rating agency.

See appendices 4 and 5 for variables detailed information.

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