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The high levels of operating efficiency, profits, and market values for banks in the years before the financial crisis raise reasonable doubts about the accuracy of the assessments of the efficiency of banking intermediation. We examine the productivity growth in Spanish banks in the pre-crisis period by separating out the contributions to productivity growth from business practices and from industry-wide technological progress. We find that more than two thirds of the estimated productivity growth in the years 2000–2007 is attributed to banks’ practices, such as the expansion of credit in the housing market, the high recourse to securitization and short-term finance, the reduction in liquidity holdings, and the leveraging process of banks’ balance sheets, that the literature claims are the ultimate causes of the crisis. We estimate that the remaining cumulative annual growth rate is 2.8% for the industry’s technical progress, which is similar to that in the period of 1992–2000.

Banks and other financial intermediaries perform the economic functions of providing liquidity, transferring funds from savers to investors, and collecting and diffusing information (Diamond, 1984, Diamond and Dybvig, 1983, Gorton and Winton, 2003 and Merton, 1995). These functions involve value-added activities that facilitate payments and manage cash, select and monitor borrowers, and provide advice and consultation services. Banks use labor, capital, and other inputs to perform these activities and earn revenues from interest-rate differentials and fees. The level of efficiency when performing banking intermediation activities is a key factor in economic development (Buera et al., 2011, Greenwood et al., 2010 and Mehra et al., 2011). Further, the changes in the costs of intermediation have important macroeconomic consequences for investment and growth (Bernanke et al., 1999, Christiano and Ikeda, 2011 and Hall, 2011). In conventional competitive markets, profits are the reward for providing services demanded by costumers at the lowest cost. The expansion of banks’ balance sheets around the world and the record-high growth rates of profits and productivity up to 2007 should have been an indicator of substantial efficiency gains in financial intermediation. However, the outburst of the severe financial crisis in 2007 showed that at least in the case of banks, the usual indicators of performance might have failed to disclose the “true” economic results. Potential explanations for this paradox might be as follows. Managerial incentives can exist that distort reported profits (Rajan, 1994). Also, financial innovations for regulatory arbitrage (Achayra et al., 2011) and the measurements of profits and output not adjusted for risk can exist (Haldane et al., 2010). Further, innovations of business models that change the nature of the banks’ output over time (Philippon, 2012) can occur, such as the “originate to distribute” model and the market-based intermediation or shadow banking. In this paper, we rely on bank-level productivity estimations to quantify the productivity growth of the Spanish banking industry in the years before the financial crisis (1992–2007) and examine its determinants. The Spanish example is a good case study for a better understanding of why the usual measures of efficiency and profitability for banks might not be informative about the true efficiency gains in financial intermediation. First, the estimated productivity growth of the country’s banking industry before the crisis was one of the highest among developed countries. Second, Diamond and Rajan (2009a) consider what occurred in Spain as representative of the proximate causes of the crisis: (i) investors perceived a permanent reduction in interest rates when Spain joined the Euro zone, (ii) there was an unprecedented expansion of the housing industry, and (iii) banks financed a good portion of the loans with wholesale financing and short-term debt. However, Spain also has different features from the United States and other countries in two main aspects. First, securitized loans remained on the balance sheets of banks, and they were subject to capital requirements; and, second, savings banks compete on an equal basis with commercial banks. We derive the estimates of the bank-level total factor productivity (from now on productivity) from the estimation of the banks’ production function. We model the production and sales of bank services at the branch level assuming a Leontief technology (Martín-Oliver and Salas-Fumás, 2008) with two variable inputs: labor and services from information technology assets (IT capital) and a quasi-fixed input (the physical capacity of the branch). Then, we aggregate the branch-level production function to obtain the bank-level production function, which is the function that we empirically estimate with the Spanish banks’ data. The estimation of the technology parameters follows the methodology developed in Olley and Pakes (1996) and extended by Levinsohn and Petrin (2003) to control for the potential simultaneity bias between the unobserved productivity shock and the management decisions on input quantities in response to the shocks. Next, we explore what is behind the estimated productivity. For this purpose, we isolate the factors that can determine the estimated productivity values because of reasons different from “true” economic efficiency. These factors comprise, on the one hand, differences in the operating characteristics of the banks in the sample (Berger and Mester, 1997 and Frei et al., 2000); on the other hand, they comprise factors related with the proximate causes of the crisis, which is the focus of this paper. In other words, we aim to explore whether certain business decisions by banks improve the short-term private performance of banks but incur the social cost of future financial instability. Examples of these business decisions are the concentration of loans in the housing market, the issuance of securities and short-term debt to finance loans, or the reduction of liquidity holdings and the increase of leverage. Our empirical results show that the growth rate of productivity in the Spanish banking industry more than doubled during the years after the Euro, a result that is consistent with other productivity estimates obtained with other methodologies and with aggregate industry data (O’Mahony and Timmer, 2009). However, we also find that an important part of this productivity growth in the pre-crisis years is explained by business decisions that, ex-post, have been identified as drivers of the crisis. When removing these and other operational factors from the estimated productivity, the productivity residual grows at a similar rate in the years before and after the introduction of the Euro. Therefore, we show that the high growth rates of raw productivity estimated for the banking industry during the years prior to the crisis cannot be taken as indicators of efficiency gains. The paper is related to the long list of published papers on productivity and the efficiency of banks.1 We are the first to estimate the total factor productivity (TFP) from a Leontief-type production function formulated at the branch level. Most of the productivity estimates in banking are obtained with cost or profit functions (Kumbhakar and Lovell, 2000).2 This paper is also, to the best of our knowledge, the first to consider IT capital as a productive input, which seems essential in one of the most IT-capital intensive industries. This paper is also one of the few (together with Bunch et al., 2009 and Nakane and Weintraub, 2005) that corrects for the simultaneity bias in the estimation of the production function, following the methodology in Olley and Pakes (1996) and Levinsohn and Petrin (2003). Our paper is also related with the growing literature that is interested in measuring the cost efficiency of financial intermediation, either through a more accurate measurement of the output of banks and market-based (shadow banking) intermediaries (Philippon, 2012) or through the calculation of risk-adjusted measures of productivity (Basu et al., 2011 and Haldane et al., 2010). Our contribution regarding this literature is twofold: First, we estimate the production function and the productivity values using bank-level data, whereas the previous papers use aggregate industry data for their estimations. Second, our analysis goes beyond the scope of these papers, obtaining a more accurate estimation of the contribution of technical progress to the productivity growth of the banking industry and provides an empirical test for some of the theories on the causes of the financial crisis. The rest of the paper is organized as follows. Section 2 describes the production technology of banks and the methodology used in the estimation of productivity. Section 3 shows the results of the estimation of the production function and the average productivity from the bank-level data for the Spanish banking industry. Section 4 contains an analysis of the determinants of the observed productivity of Spanish banks in the context of the banking practices that are related with the causes behind the recent financial crisis. The conclusion summarizes the main results of the paper.

Efficient financial intermediation is a key factor for economic development. The high productivity growth in the banking industry around the world, up to 2008, anticipated a period of prosperity and wealth creation. However, the outburst of the financial crisis revealed that these expectations were totally erroneous. Conventional measures of banks’ productivity growth as a proxy for efficiency gains in financial intermediation have been questioned, and new developments are needed to properly assess the “true” efficiency gains in the banking industry over time. This paper contributes to this development in two ways: First, with a new methodology for the measurement of productivity in banks and, second, with the measurement of the component of the industry’s productivity growth attributed to technical progress. From the methodological point of view, the paper introduces a Leontief production function for banks with IT capital as one of the inputs that is then estimated following the procedure posited in Levinsohn and Petrin (2003) and Olley and Pakes (1996) to control for the simultaneity bias between labor and productivity. This estimation method has clear implications for the policy analysis and productivity estimations of banks: First, the results obtained from the estimation of the production function cannot reject the null hypothesis of the constant returns to scale (rejected in the OLS); the return to scale properties of the production function is a key factor in mergers and restructuring decisions. Second, the estimated elasticity of the output of banks from IT capital services is twice the elasticity estimated using an OLS. Because this elasticity enters into the calculation of the contribution of IT to labor productivity growth, the contribution of IT capital is twice what it would have been in the OLS. Using the estimates to control for simultaneity, we find that the cumulative growth in IT capital per employee increases output by 27% during the sample period (1.6% cumulative annual growth) that shows the high contribution of IT capital in the banking industry. Overall, the average annual cumulative growth rate in labor productivity is 4.4% during the sample period (1.6% of IT capital contribution plus 2.8% of technical progress). As for the measurement of the industry’s advances in operating efficiency, we find that Spanish banks participate in many of the causes that led to the financial crisis. More than two thirds of the reported growth in banks’ productivity was at the expense of fuelling a housing and real-estate credit bubble. These activities created a liquidity gap between loans and deposits that were financed with MBS and interbank loans. Thus, the activities reduced the asset liquidity ratios and increased their financial leverage. This occurred at the same time that the industry maintained a steady annual growth rate in operating efficiency of 2.8%, similar to the rate in the pre-Euro period. More research is needed to advance our knowledge on how to reconcile productivity estimates of individual banks with systemic measures of financial stability. We believe that our approach offers a promising start. Haldane et al. (2010) propose using risk-free measures of output for banks in the calculations of the banks’ productivity growth within the KLEMS project. One difficulty to this approach is how to obtain the appropriate price for risk. Our approach relies on quantities and does not require information on prices, a clear advantage when taking into account the market failures that affect the pricing of risk.