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Review of Quantitative Finance and Accounting

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08.11.2018 | Original Research

The determinants of net interest margin during transition

verfasst von: Maria-Eleni K. Agoraki, Georgios P. Kouretas

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 4/2019

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Abstract

In this paper we examine the banking sector of the Central and Eastern European (CEE) countries during the transition period 1998–2016 in a number of critical dimensions. We place particular importance on the effect that the regulatory framework along with a group of bank-specific, industry-specific and macroeconomic factors have on the net interest margin (NIM) in the banking sectors of the Central and Eastern European countries over the period 1998–2016. In addition to the standard determinants employed in the literature, the present study provides a unique natural experiment to examine the effect of the extensive banking sector reform that took place during the examined period in the CEE countries. We employ both static and dynamic frameworks as well as advanced market structure measures and we argue that net interest margin is determined by bank-specific characteristics such as equity capital, risk and operational inefficiency. Furthermore, it is shown that the regulatory framework as well as the presence of foreign-owned institutions in the CEE countries play an important role in determining NIM. However, as financial systems develop and the reform process ends, both the current and future rates of economic growth are likely to have an enhanced impact on bank margins.

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The CEE countries under consideration are: Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, FYROM, Hungary, Latvia, Lithuania, Poland, Romania, Serbia-Montenegro, Slovakia and Slovenia.

However, during the second half of the 1990s banking reform efforts were impeded, either by internal setbacks or by external causes.

See Demirgüç-Kunt and Huizinga (1999), Nys (2003), Maudos and Fernández de Guevara (2004), Claeys and Vander Vennet (2007). Furthermore, Ziaei (2017) provides a recent analysis to evaluate the effects of financial soudness indicators, financial openness and bank liquidity on financial development across 40 countries.

For robustness we also employ the important research output of the European Bank of Reconstruction and Development (EBRD) of bank and enterprise reform to quantify the reform process in CEE banking, and it identifies all the relevant banking laws that facilitated the transition. Since the EBRD performs a yearly assessment of regulatory reform we are able to exploit the time-series aspect of these indices (see also Agoraki 2009).

However, the relations between bank’s characteristics or external factors and margins are not constant across countries or different periods within the same country.

The pure spread factors, indicate the difference between loan and deposit rates, and reflect the compensation of bank inventory risk arising from uncertainty about loan and deposit transactions.

However, these will not fully account for the changes that occurred during the 1990 s.

Changes in the banking sectors of all countries examined are gradual (if any). This is quite expected as the transformation of income structure is usually subject to exogenous rigidities that may require time to be smoothed out, even when the transition is rapid.

Estimation of Eq. (1) is carried out using simple static methods. Estimation of Eq. (2) is conducted using the GMM methodology for dynamic panel data put forward by Arellano and Bond (1991), Arellano and Bover (1995) and Blundell and Bond (1998). The validity of the instruments applied is tested with the Sargan test. This estimator has two important properties. First, as Binder et al. (2003) show it does not break down in the presence of unit roots. Second it accommodates for potential presence of endogeneity with the use of appropriate instruments. The instruments that are often proposed are taken to be the first differences of the independent variables of the model as well as the lagged value of the dependent variable (Athanasoglou et al. 2006; Agoraki et al. 2011; Delis and Kouretas, 2011; Drakos, et al. 2016).

Chen et al. (2018) provide a new insight on the effects of liquidity on bank risk and performance.

As a check on the robustness of the results, we use the share of total deposits held by the three largest banks in the industry as an alternative concentration measure in our analysis. Both measures yield very similar and consistent results.

Agoraki (2009) provides a comprehensive analysis of market structure in the European banking sector. Recently, Lian (2018) employs the HHI to study the effect of bank competition on the cost of bank loans using U.S. bank loan data. He finds that lenders give favorable loan terms to borrowers in competitive loan markets.

Agoraki et al. (2011) using data for the CEE countries for the period 1998–2005 show that banks with market power tend to take on lower credit risk and have a lower probability of default.

Kouretas and Tsoumas (2016) fully analyze the impact of foreign banks on business regulations in a large sample of countries.

Regarding banks having majority foreign ownership, we distinguish between those that have a single majority owner or a single controlling owner (which are defined as strategic foreign ownership), and those that the foreign owners together hold more than 50 per cent of the shares, although no one of these has a controlling stake (which are defined as other foreign majority ownership).

These indices are constructed on the basis of information obtained in four points in time that correspond to updates in the Barth et al. (2001a, b) database (see also Agoraki 2009; Agoraki et al. 2011; Delis and Kouretas 2011; Kouretas and Tsoumas 2013; Drakos et al. 2016).

See Santos (2001) and VanHoose (2007) for review of the literature.

Demirgüç-Kunt and Detragiache (2002) show that several countries have established a system of national deposit insurance over the last 25 years, this being viewed as a way of avoiding bank runs. However, when deposit insurance is in effect, depositors may have no incentives to monitor banks, which may result in a decrease in market discipline (see e.g., Demirgüç-Kunt and Huizinga 1999).

The index actually takes values from 3 to 12. We transform each index to annual series by assigning the index value in the year the survey conducted to all years up to the next survey.

In this study, we introduce the EBRD index of banking system reform in the CEE countries to identify the progress in areas such as: (1) the adoption of regulations according to international standards and practices, (2) the implementation of higher and more efficient supervision, (3) the privatisation of state-owned banks and (4) the write-off of non-performing loans and the closure of insolvent banks (see also Agoraki 2009; Agoraki et al. 2011).

Since the EBRD performs a yearly assessment of regulatory reform we are able to exploit the time-series aspect of these indices. This an advantage of this index compared to the ones constructed based on the World Bank database which does not have fixed frequency. This implies that in the case of EBRD we have 285 country-year regulatory observations which are the ones that really drive the system whereas in the case of the World Bank database we have smaller number of country-year regulatory observations.

If it is assumed that the aggregate demand for dealership services is an increasing function of GDP growth, then one would expect, ceteris paribus, to increase margins. An alternative scenario could be that higher growth is a proxy for higher corporate profits and therefore, more scope for internal funding of investment and hence lower demand for dealership services, which would push interest margins downwards.

We thank an anonymous referee for this clarification.

The HHI is calculated as the sum of the squared market shares in total assets of the individual banks. Note that the index is calculated on a county-specific basis.

The privatization of the CEE countries’ banking system was characterized by the entry of foreign banks. Thus, state-owned banks have been reduced significantly in all countries indicating that the privatization process has been quite effective (EBRD 2004). Consolidation and privatization have resulted in markets fairly concentrated in terms of ownership, dominated by a limited number of mostly foreign-owned banks, while the remainder of the sector is fragmented among a number of smaller players.

We assume that the banking markets of individual countries in the region possess similar characteristics and therefore the region can be treated as a single market.

We estimate our model with a generalized-least-squares (GLS) procedure referred to as the error-components model. Given our pooled time-series, cross-sectional data, a GLS procedure is preferable to ordinary least squares (OLS) because OLS estimates may be biased and inconsistent, while GLS model allows for correction of potential cross-sectional heteroskedasticity and/or serial correlation.

The coefficients of the time and country dummies have been omitted from the regression output but are available upon request.

The economic importance of the EA explanatory variable is calculated as follows: Assume a unit increase of EA then given the value of the coefficient to be equal 0.023 × 1 = 0.023 the percentage change of NIM will be equal to 0.023/3.52 = 0.65%. We apply similar calculations to all other cases for which the magnitude of the coefficient is economically significant.

We observe that for all static models including those that consider the regulatory variables EA, LLP, LIQ and IIP are the variables that besides statistical significance they also have economic importance. In fact, the size of the coefficient varies very little among the alternative models. Furthermore, in models III and IV of Table 3 efficiency appears also to have economic importance when the World Bank regulatory indices are included. A unit increase in efficiency leads to an increase of 2.35% in NIM.

The fact that the two coefficients completely offset each other does not necessarily imply that nominal GDP has no effect on NIM. On the aggregate level, this canceling out could be a straightforward outcome. However, we should underline that the presence of heterogeneity across country and periods imply that the aggregation of GDP and inflation may not be time synchronous and thus nominal GDP has an effect on NIM.

Such explanations may include informational opacity, partisan politics, domestic alliances and institutional capacity.

Our theoretical model displays a dynamic approach in which banks need to match deposit supply and the demand of lending. The maximization of bank wealth considers both initial and end-of-period information. Thus, we consider that previous values of bank margins may affect current values of margins.

In order to ensure robustness, we compared the various consistent GMM estimators (system GMM) to simpler static estimators, which are likely to be biased in opposite directions as regards the lagged dependent variables in panels with a small time dimension. In the first estimates, standard errors are biased, as discussed previously, although the bias is expected to be small. Indeed, the difference in the coefficients between the two estimation methods is found to be significant.

The percentage change of NIM is calculated respectively 0.39% for a unit increase in EA or 14 base points, 0.37% for a unit increase in LLP or 25 base points, 0.70% decline for a unit increase of LIQ or 25 base points, operational efficiency will have a positive impact of 36 base points and 1% increase for a unit increase of IIP or 37 base points.

Martinez Peria and Schmukler (2001) find evidence that market discipline more generally exists in developing countries, even in the presence of deposit insurance. In the CEE, depositors have few alternatives for bank deposits; yet they are regularly confronted with information about bad asset quality in some banks and even outright bank failures. This feature will induce depositors to act prudently and avoid depositing money in badly capitalized banks.

In our study the relationship is linear (the square of bank assets is insignificant in all models).

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Titel: The determinants of net interest margin during transition
verfasst von: Maria-Eleni K. Agoraki
Georgios P. Kouretas
Publikationsdatum: 08.11.2018
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 4/2019
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-018-0773-y

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