Analysing interest margin determinants using data panel models: Spanish credit institutions 2004-2012.
Salvador Climent Serrano
Generalitat Valenciana
e-mail:
Jose M. Pavía
Department of Applied Economics, Universitat de Valencia
e-mail:
Fernando Toboso
Department of Applied Economics, Universitat de Valencia
e-mail:
Corresponding author:
Jose Manuel Pavía
Facultad de Economía
Dpto. Economía Aplicada
Area de Métodos Cuantitativos
Universidad de Valencia
Campus ElsTarongers
46022 - Valencia
Spain
e-mail:
Acknowledgements
The authors wish to thank Marie Hodkinson for the English revision of the text of the paper.
ANALYSING interest margin determinants using data panel models: Spanish credit institutions 2004-2012.
Authors: deleted
Abstract
As interest margins of credit institutions affect economic performance of countries, finding out which are the main determinants of their evolution is a research task of great interest at current times. This is the purpose of the present paper as regards to the Spanish case over the period 2004-2012. Based on the work of Ho and Saunders (1981) and some of its extensions, we develop a model that includes as explanatory variables not only the factors usually examined in the literature but also some other singular variables that might be relevant. Besides the traditional factors referring to the internal data of credit institutions, we also test as potential determinants of interest margins in Spanish credit institutions the following three variables: their rate of leverage, the quality of their assets measured according to their risk, and the profit obtained from the selling of assets, including real estate ones. The research also provides an analysis of differences between banks and savings banks.This result may be of particular interest for those countries where entities similar to the Spanish saving banks still have a significant market share, as is the case of Germany for instance.
Keywords
Net interest spread; Diversification; Panel Data; Economic Development; Banks and Savings Banks.
JEL Classification: G21, G28; G34
1.- INTRODUCTION
Among the traditional functions of credit institutions a key one is that of capturing funds from savers to offer them to those in need of funding. Obviously, in a market economy the interests paid to savers are usually lower than those charged to debtors. This provides credit entities with positive interest margins that help them in their permanent attempt to cover costs, including capital costs arising from depreciation, and also pay dividends. As positive interest margins also allow these entities to increase own capital, higher profits as a result of higher interest margins make them in a better position to confront some other risks, such as those derived from the 2007 financial crash. Failures and bailouts in the financial system have, of course, major negative economic and social impacts (Furceri and Zdzienicka, 2012; Kasimati and Veraros, 2013).[1]
There is, nevertheless, a dynamic interaction between financial and economic development (de la Torre, Feyen and Ize, 2013). Too wide interest margins may also have negative consequences upon the intermediation role these entities also play. On one hand, too wide margins at the expense of reducing the interest paid on deposits and/or increasing the interest charged upon loans may negatively affect savings and/or investment, hindering economic growth of the country or fueling bigger recessions(Ariestei and Gallo, 2014). On the other hand, very thin margins can also be indicative of very competitive credit entities, with lower intermediation costs that contribute to boost investment. If these narrow margins are compatible with higher sales, annual net profit may not decrease but grow as a result.
Indeed, there is a dynamic interaction between financial and economic development that contributes to macroeconomic volatility(Mandelman, 2011). Therefore, it seems obvious that interest margins of financial intermediaries play a key role for economic performance, with a difficult balance between wide and narrow margins to be reached. If stability, profitability and solvency of these entities require wide margins, boosting economic competitiveness in a country requires narrow margins. What has happened in Spain regarding interest margins of credit organizations?
Figure 1 shows the evolution of the average interest rate charged and paid by the Spanish credit institutions, as well as the resulting average interest margin over the 2004-2012 period investigated.[2] The average margin appears quite stable over more than half of the years considered (1.51% in 2004 to 1.58% in 2007), then grows over the period 2008-2010 (1.68% in 2008 to 2.63% in 2010), to finally start reducing slowly in 2011 (2.62%) and substantially in 2012 (1.90%). Over the entire period the chart shows some fairly low levels for the average interest rates charged and paid as well as the interest margin itself. Furthermore, it must be noticed also that interest rates shown in Figure 1 are nominal. If inflation was accounted for, real interest rates would appear even lower and even with a negative sign for some years.
Figure 1. Nominal averages of interest rates and interest margins of banks
and savings banks in Spain (2004-2012).
Source: own elaboration using data made public by credit organizations.
So, which are the main determinants of the above mentioned evolution of the average interest margin of Spanish credit institutions? For performing this research task we are going to start from the much cited and already classic work of Ho and Saunders (1981) and some of its extensions. However, we will develop a model that includes as explanatory variables not only those factors usually examined in the literature but also some other singular variables that have not received enough attention. Therefore, besides the traditional factors referring to the internal data of credit institutions and to external variables such as GDP and other, we will also test as potential determinants three additional variables that might be relevant for the Spanish case: the rate of leverage of such entities, the quality of their assets measured according to their risk, and the profit they obtain from the sale of assets, including those real estate properties in which they invested over the boom. We also provide an analysis showing some differences between banks and savings banks. In addition, we will also test separately each of the four sources of income not linked with the interest margin, that is, we will differentiate between incomes obtained from capital investments, from commissions, from financial investments (purchase-sale of financial instruments) and from other income sources.
As stated above, this paper focuses on the working of Spanish banks and savings banks over the period 2004-2012: a period studied of special interest as it includes both years registering high economic growth and years characterized by a deep recession, with several saving banks being bailed-out. Indeed, the singularities our study finds as regards to saving banks in the Spanish case might be of some interest too for those countries in which similar entities still share a significant quota of the intermediation market, as is the case of Germany, for example.[3]
The rest of the paper is organized as follows. Section 2 gives a brief review of key publications on these issues. In section 3 we explain the model and the variables to be tested, as well as the expected sign of the coefficient in each case. In section 4 we explain the results obtained and think about the consequences. Finally, section 5 provides some concluding remarks.
2.- BACKGROUND
If we look at the econometric papers published on the factors influencing the evolution of interest margins, Ho and Saunders (1981) deserves special attention. On a sample of the American banks, these authors developed a model in which the interest margin depends on four factors: the degree of risk aversion, the structure of the market, the average size of banking transactions and the variation of the interest rate applied to loans and deposits. Several authors have made extensions of this model by incorporating new variables and testing them with samples from several countries and regions.
As some other features and results are synthetically presented in Table 1, we briefly mention that some of these contributions over the 1990s were Wong (1997), which contains an extended theoretical model, Angbazo (1997), which focuses on the American banks during the period 1989-1993, and Demirgüç-Kuntand Huizinga (1999), which is an international study using a large amount of variables and a sample of 80 financial institutions worldwide.
Over the 2000s, several other contributions following the line of Ho and Saunders must be mentioned. Saunders and Schmacher (2000) contains a study about several countries, including Spain, covering the period 1988-1995. Abreu and Mendes (2003) is yet another example focusing on what happened in five European countries over the period 1989-1999. Martinez Peric and Mody (2004) give special emphasis to highlighting differences regarding national and foreign banks in Latin American countries. As regards to the European financial institutions, Maudos and Fernandez de Guevara (2004) is another prominent example. In this study, the authors attempt to find out which were the main determinants of the interest margin of European banks for the period 1993-2000. CarboValverde and Rodriguez Fernandez (2007) do so for the period 1994-2001. Kasman, Tunc, Vardar and Okan (2010) also studied the case of European countries during the period 1995-2006 making several classifications and groupings of the data.
More recently, Williams (2007) has emphasized the differences between domestic and foreign banks as regards to the Australian banks over the period 1989-2001. Hawtrey and Liang (2008) investigate the case in fourteen OECD countries during the period 1987-2001. Claeys and Vennet (2008) focuses on European banks over the period 1994-2001, distinguishing between the first fifteen countries that formed part of the EU prior to the 2004 enlargement and the ten new countries that entered on that date and some others like Croatia, Russia and Ukraine. Zhou and Wong (2008) test the determinants for Chinese banks over the period 1996-2003. Also, Maudos and Solis (2009) do the same in the case of Mexico for the period 1993-2005, and Horvath (2009) examines the case of the Czech banks.
The case of credit institutions in Eastern Europe is progressively gaining more and more attention, with new variables being tested as indicated in Table 1. Schwaiger and Liebeg (2008) and Poghosyan (2010) are examples of this. Fungacova and Poghosyan (2011) focus on the Russian banks during the period 1999-2007, paying special attention to the existing property structure (relative weight of public property, private national property and foreign property). And, Tarus, Chekol and Mutwol (2012) contain another study of interest margin determinants for Russian banks over the period 2000-2009.
Finally, Nguyen (2012) examines the case for 28 countries that experience financial liberalization reforms over the period 1997-2004; Lin, Chung, Hsieh, and Wu (2012) examined the period 1997-2005 in the case of the Asian banks; and Hussain (2013) focuses on the case of the Pakistan banks over the period 2001-2010.
Table 1 summarizes the variables tested in all of these articles also indicating the signs of regression coefficients obtained in each case, the R2 obtained for each of them, the period investigated, the area, and the econometric regression approach performed.
1
Table 1.Summary of the main characteristics of contributions reviewed.
1
The above revision literature also allows us to extract some other general conclusions. On the one hand, we find that the weight interest margin has on total income has consistently diminished throughout the years in all the countries and regions examined in these contributions and, on the other hand, they also reveal that differences among countries are fewer and fewer regarding the several commercial activities they perform and the way they manage their balance sheets. If the income obtained through the interest margin represented around 80% of total incomes in the early 1990s (Wong, 1996), over the 2000s this source has represented only about half of total income on average. Obviously, some other sources of income have seen their share increased in all developed countries. Some outstanding examples of these other sources are: commissions, dividends, capital gains obtained from the selling of financial assets, income obtained from the selling of non-financial services (such as insurance, consulting or travel agencies) and income coming from real estate speculative transactions, from investment in fixed and variable income securities, and from shares in companies.
3.- METHODOLOGICAL ISSUES
3.1.- Data and Model
The sample used for our study is formed by all savings banks (47) as well as the most representative banks (14) operating in Spain at the beginning of the study (2004) together with all the new entities created as a result of the intense restructuring process implemented in the Spanish financial system over the last years (see, Climent and Pavia, 2013). Credit institutions that make up the sample represent 99.9 % of the total activity of banks and savings banks operating in Spain and 90% of the activity of the financial system as a whole.
In particular, our study is based on the activity of a total of seventy-five credit entities over nine time periods. This allows for building a more informative database than databases just based on sectional information because it presents more variability, less co-linearity and more degrees of freedom, making it possible to take into account both the time and cross-sectional dimensions of the data by means of a non-balanced panel data econometric model. This, no doubt, will result in more efficient regression estimators and, overall, will allow us to better control for endogeneity and/or possible heterogeneity not individually observed. Moreover, in order to control for the possibility that each credit institution might have singular non-measurable, non-observable characteristics that might influence the relationship between interest margin and determinants, we will also introduce in our model individual effects, αi =α + νi. In particular, the model specification is as follows.
3.2 . VARIABLES
As mentioned in the introductory section, despite the model we use being based on the work of Ho and Sanders (1981) and some of its extensions, we have decided to include some more variables that have received little attention in the literature but, as indicated in the following sub-paragraphs, might be relevant.
The dependent variable is, of course, the interest margin which is defined, as usual, as the difference between interests paid and charged. Concerning the explanatory variables, in our model we differentiate between explanatory variables that are internal to the credit entity from those that are external. Let us explain them in more detail.
3.2.1 INTERNAL VARIABLES
As internal variables we have considered the following four groups: 1) structure of property, 2) extraordinary profits, 3) quality of the credit entity itself and 4) determinants obtained from the balance sheet information, both regarding assets and liabilities. Let us specify them in more detail and argue about the expected sign of the coefficient.
A) STRUCTURE OF THE PROPERTY
Type: Saving Bank/Bank. This variable is a dummy variable. For Bank we attribute a value of 1 and for Saving Bank a value of 0. A positive sign for the coefficient would indicate that the interest margin is greater in banks; the opposite when the sign is negative. Usually, we cannot expect any fixed sign ex-ante for this variable, however, the great problems experienced since 2007 by most saving banks in Spain let us expect a positive sign.[4]
B) DETERMINANTS OBTAINED FROM THE BALANCE SHEET INFORMATION
Liquidity (unproductive assets) / Total Assets. This ratio is formed by the most liquid assets (cash and deposits in central banks) as a share of total assets. The sign of this variable allows for both possibilities. First, it could be argued that the opportunity cost of having these liquid assets is the average profitability of productive assets that they do not get as a result. Interest margins might be increased in an attempt to compensate for this lower profitability of liquid assets (Lin et al, 2012). This would lead to a positive coefficient being expected. On a similar direction, it could also be argued that as credit institutions with high liquidity will experience less or no tension regarding this, they will not be forced to pay high interest on deposits. If so, higher liquidity might be associated with higher interest margins, with a positive sign being expected again. Alternatively, as these types of assets do not generate incomes, the expected sign of this coefficient would be negative because the higher the amount of resources tied up in these assets the lower the amount of interests obtained and the interest margin that results (Lin et al, 2012; Fungačova and Poghosyan, 2011). Therefore, the expected sign associated with this variable is undetermined.
Loans /Total Assets. Following Garcia-Herrero et al (2009) and Kasman et al (2010), we can expect higher interest margin of credit institutions the higher its loan portfolio is in relation to their total assets. Higher percentages regarding this variable are often coupled with a decrease in the liquidity ratio. The higher the number of entities with a high proportion of their assets at risk, as credits are, the more likely it is that the interest margins are higher too (Trujillo-Ponce, 2013). On the contrary, we could also argue that higher amounts of credits means higher risk of default and that if this risk materializes the amount of interest gained might be lower too, with lower interest margins as a consequence, ceteris paribus. Therefore the expected sign of the coefficient for this variable is undetermined.
Deposits / Total Assets. This ratio is formed by the amount of deposits owed by credit institutions as a share of their total assets. Over the years prior to the financial crash, Spanish credit institutions have been largely financed through funds coming from wholesale markets, which have had some positive consequences, as Trujillo-Ponce (2013) stresses, but have resulted in higher costs paid by these entities than would have been the case if they had financed more through deposits of customers. As known, deposits represent a cheaper and more stable financial source than the alternatives (Claeys and Bennett, 2008; Garcia-Herrero et al, 2009). Also, the financial crisis that began in 2007 closed these wholesale markets almost completely for the Spanish credit institutions, which led them to compete more heavily for financial resources, which translated into more aggressive policies and an increase in the cost of their external financing (Trujillo-Ponce , 2013). All these arguments lead us to expect no clear sign for the coefficient regarding this variable. It might be positive if the first effect dominates and negative if it is the second which does so.