structural, macroeconomic and institutional data, this paper provides an empirical analysis of the determinants of intermediation spreads in all countries in the world for which data are available, representing to the best of our knowledge the most comprehensive attempt to study net interest margin determinants in a large sample of countries since the seminal contribution by Demirgüç-Kunt and Huizinga (1999). Second, and most importantly, this paper uses the results of the empirical analysis to benchmark country-level costs of financial intermediation with a view to highlight the factors that most affect bank intermediation spreads. Our main concern is not to uncover new findings about the drivers of intermediation spreads but rather to provide an easy-to-interpret tool to highlight the most important factors by country. To this end, empirical results are used to decompose the difference between each country’s net interest margins and those of the average banking system in the world as well as of the average banking system of the regional grouping to which the country belongs. Simple bar charts of relative contributing factors are then constructed to sharpen the intuition behind the estimates to show “what determines a country’s net interest margin.” Benchmarking costs of financial intermediation around the world is a useful exercise in detecting deficiencies at the country level; it can also help policy makers identify areas to prioritize through reform. For example, if high intermediation costs are especially driven by high operating costs in the banking system, efforts to reduce the opportunity cost of holding reserves are unlikely to bring down spreads. Improving productivity by, for example, incentivizing an increased use of technology and automation in the production and distribution of banking services would be a more effective strategy. On the other hand, if macroeconomic volatility creates uncertainty that banks need to compensate for by charging higher risk premia, reducing information asymmetries through the promotion of credit bureaus or improving contract enforcement through more effective liquidation procedures will do little to eliminate the underlying drivers of high spreads.

Understanding the main determinants of intermediation costs is also relevant to the agenda of many international financial institutions, especially multilateral development banks, which are increasingly concerned with maximizing the additionality of development finance by crowding in private capital. High costs of financial intermediation represent an important obstacle to leveraging private sector investments for growth and sustainable development. Therefore, understanding the factors driving bank spreads is important for the implementation of this agenda. Along the same lines, analysis of bank intermediation efficiency is an increasingly common component of IMF/World Bank-led Financial Sector Assessment Programs (FSAPs) and other country-level diagnostics, hence developing an international benchmark in this area can help focus the analysis.

The remainder of this paper is organized as follows. The next section presents the methodology and the data used to analyze the drivers of bank intermediation costs around the world. Section 3 presents an accounting decomposition of the intermediation spread in its constituent parts, i.e., cost and profit components. Section 4 presents the results of the econometric model and evaluates the importance of bank-specific, structural, macroeconomic and institutional factors affecting spreads. Section 5 introduces the methodology used to decompose econometric results to build bar-charts of relative contributing factors of financial intermediation costs. The last section concludes.

# **2. Methodology and data**

Bank intermediation costs can be measured using both ex-ante and ex-post spreads. The ex-ante spread is the difference between contractual rates charged on borrowers and those paid on depositors. The expost spread is the difference between banks’ actual interest revenue and their actual interest expense, usually divided by earning assets or total assets. The ex-post spread differs from the ex-ante spread by 4