Baumol and others, 1982.
Berger, Allen N., and David B. Humphrey, 1997, “Efficiency of Financial Institutions: International Survey and Directions for Future Research,” European Journal of Operational Research (Vol. 98, No. 2), pp. 175–212.
Besanko and Thakor, 1992.
Bresnahan, T.F., 1989, “Empirical Studies of Industries with Market Power,” in Handbook of Industrial Organization, Volume II, ed. by R. Schmalensee and R. D. Willig (Amsterdam: North-Holland).
Buchs, Thierry, and Johan Mathisen, 2005, “Competition and Efficiency in Banking: Behavioral Evidence from Ghana,” IMF Working Paper No. 05/17 (Washington: International Monetary Fund).
Claessens, Stijn, and Luc Laeven, 2003, ”What Drives Bank Competition? Some International Evidence,” World Bank Policy Research Paper No. 3113 (Washington: World Bank).
Coelli, Tim, 1996, “A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program,” Center for Efficiency and Productivity Analysis Working Paper No. 96/08 (Armidale, New South Wales, Australia: University of New England).
Daumont, Roland, Francoise Le Gall, and Francois Leroux, 2004, “Banking in Sub-Saharan Africa: What Went Wrong?,” International Monetary Fund Working Paper 04/55 (Washington: International Monetary Fund).
Färe, Rolf, Shawna Grosskopf, and C. A. Knox Lovell, 1985, The Measurement of Efficiency of Production (Boston: Kluwer-Nijhoff Publishing).
Gelos, R. Gaston, and Jorge E. Roldos, 2002, “Consolidation and Market Structure in Emerging Market Banking Systems,” IMF Working Paper No. 02/186 (Washington: International Monetary Fund).
Hauner, David, 2004, “Explaining Efficiency Differences Among Large German and Austrian Commercial Banks,” Applied Economics (Vol. 37, No. 9), pp. 969–80.
Koopmans, Tjalling Charles, 1951, “An Analysis of Production as an Efficient Combination of Activities,” in Activity Analysis of Production and Allocation, ed. by Tjalling Charles Koopmans (New York: Wiley).
Levy Yeyati, Eduardo L., and Alejandro Micco, 2003, “Concentration and Foreign Penetration in Latin American Banking Sector: Impact on Competition and Risk,” IDB Working Paper No. 499 (Washington: Inter-American Development Bank).
Lovell, C. A. Knox, 1993, “Production Frontiers and Productive Efficiency,” in The Measurement of ProductiveEfficiency: Techniques and Applications, ed. by Harold O. Fried, C. A. Knox Lovell, and Shelton S. Schmidt (Oxford: Oxford University Press).
Molyneux, Phil, D. M. Lloyd-Williams, and John Thornton, 1994, “Competitive Conditions in European Banking,” Journal of Banking and Finance (Vol. 18), pp. 445–59.
Panzar, John, and James Rosse, 1987, “Testing for Monopoly Equilibrium,” The Journal of Industrial Economics (Vol. 35, No. 4), pp. 443–56.
Peiris, Shanaka J., 2005, “Financial Sector Reforms in Uganda 1999–2004” in Uganda— Selected Issues (Washington: International Monetary Fund).
Petersen and Rajan, 1995.
Sealey, Calvin W., Jr., and James T. Lindley, 1977, “Inputs, Outputs, and a Theory of Production and Cost at Depository Financial Institutions,” Journal of Finance (Vol. 32, No. 4), pp. 1251–66.
Seiford, Lawrence M., and Robert M. Thrall, 1990, “Recent Developments in DEA: The Mathematical Programming Approach to Frontier Analysis,” Journal of Econometrics (Vol. 46, Nos. 1–2), pp. 7–38.
Vives, Xavier, 2001, “Competition in the Changing World of Banking,” Oxford Review of Economic Policy (Vol. 17, No. 4), pp. 535–47.
The authors are, respectively, economists in the IMF’s Fiscal Affairs Department and African Department. This paper draws partly on Hauner (2004) and Peiris (2005). Thanks are due to Leslie Teo, Yuji Yokobori, Martin Cihak, Richard Podpiera, Peter Allum, and Jan Mikkelsen for comments.
Starting in October 2001, the BOU aligned its loan classification criteria with international standards and issued circulars in April and July 2002 to adequately capture NPLs in the system.
The NPL ratio rose through end-2003 because of the default of a large trading company. Changes in NPLs can be relatively large because of the concentration of exposures.
Funds placed abroad largely comprise deposits in the correspondent accounts of the large foreign-owned banks.
Ugandan banks have higher overhead costs than comparable banks in Kenya, partly because they do more outreach and have recently invested in physical infrastructure, such as branches and ATMs. Cross-country comparisons show that smaller banks have higher overhead costs because they find it difficult to exploit economies of scale and scope. This is confirmed by a significant positive correlation between the share of deposits and loans below U Sh 3 million in total deposits and loans and overhead costs, as well as the relatively low ratio of loan and deposit volume per branch in Uganda.
The BOU categorizes banks as small or large based on their asset size as of a particular date, which in this case was 2002. A foreign-owned bank is one with majority foreign ownership.
Note that the H-statistic in the post-privatization period is statistically significantly different from the pre-privatization level at the 5 percent significant level in the first two specifications and at the 10 percent significance level under the interest-revenue specification (Table 3).
Empirical applications necessarily refer to relative efficiency. When outputs are held fixed and inputs are to be minimized, relative efficiency is attained by a production unit if and only if according to the available evidence none of the inputs can be reduced without increasing at least another input.
The most common parametric approaches are the stochastic frontier approach (SFA), the thick frontier approach (TFA), and the distribution-free approach (DFA). The main trade-off between parametric and non-parametric approaches concerns their assumptions on random errors and the functional form of the cost frontier. While DEA fails to distinguish between inefficiency and random errors, it does not presume a particular functional form of the frontier. Parametric approaches, in turn, distinguish between random errors and inefficiency, but do so along the lines of somewhat arbitrary assumptions about their respective distributions, and, in addition, impose a particular functional form, which, if misspecified, risks overstating inefficiency. In practice, bank efficiency studies have used nonparametric and parametric methods similarly frequently (Berger and Humphrey, 1997).
A “radial” reduction cuts all inputs by the highest proportion λ possible for all of them at given output levels. After radial reduction, there could be remaining “slack” in some inputs (Farrell efficiency is necessary but not sufficient for Pareto efficiency). Here, this problem is circumvented by amending the linear program so that it meets Koopman’s efficiency, which also fulfils the Pareto criterion. See Lovell (1993) for a more extensive treatment, and Coelli (1996) on how the software used here solves the problem.
Alternatives for dealing with M&A would have been to delete all banks involved, resulting in a selection bias, or to add up the figures of the merging banks for the years before the merger, counterintuitively implying a decline in the combined assets after consolidation.
When some banks push the frontier inward, and others are left behind, then average efficiency decreases.
Bootstrapping would be one way to check whether this change is statistically robust. Bootstrapping is a way to analyze the sensitivity of efficiency scores relative to the sampling variations of the estimated frontier.
It should, however, be noted that stress testing conducted during the recent FSAP Update mission suggest that even a 50 percent reduction in government securities yield would not severely damage small banks.
In fact, the equilibrium test for periods further away from the privatization period are more robust in accepting the null hypothesis of banking system equilibrium.