We propose a different methodology to assess the financial performance of banks: Multiple Indicator, Multiple Cause (MIMIC) Variable model. We also consider other existing methodologies in the literature for estimation of bank performance. The result shows that the influence of funds in affecting the performance of banks, which have been considered a latent construct here, has been increasing over the years. The latent performance score of the public-sector banks is always higher than the private-sector banks. The same is obtained even if we use the semi-parametric stochastic frontier model: The public-sector (nationalised) banks perform better than the Indian private banks (domestic) in terms of advancing loans only. We justify the use of MIMIC model as an alternative by comparing rank correlation between the MIMIC and semi-parametric stochastic frontier model. Our results demonstrate that financial market development through deregulation creates a competitive and efficient banking sector.
AdamsR.M.BergerA.N.SicklesR.C. (1999), ‘Semiparametric Approaches to Stochastic Panel Frontiers with Applications in the Banking Industry’, Journal of Business and Economic Statistics, 17(3): 349–58.
2.
AignerD.J.LovellC.A.K.SchmidtP. (1977), ‘Formulation and Estima-tion of Stochastic Frontier Production Function Models’, Journal of Econometrics, 6(1): 21–37.
3.
BajarasA.SteinerR.SalazarN. (2000), ‘The Impact of Liberalization and Foreign Investment on Columbia’s Financial Sector’, Journal of Development Economics, 63(1): 157–96.
4.
BankerR.D.CharnesA.CooperW.W. (1984), ‘Some Models for Estimating Technical and Scaled Inefficiencies in Data Envelopment Analysis’, Management Science, 32(9): 1078–92.
5.
BatteseG.E.CoelliT.J. (1992), ‘Frontier Production Functions, Technical Efficiency and Panel Data: With Application to Paddy Farmers in India’, Journal of Productivity Analysis, 3(1–2): 153–69.
6.
BaumolW.J.PanzarJ.C.WilligR.D. (1982), Contestable Markets and the Theory of Industry Structure. San Diego, USA: Harcourt Brace Jovanovich.
7.
BergS.A.ForsundR.F.JansenS.E. (1992), ‘Malmquist Indices of Productivity Growth during the Deregulation of Norwegian Banking, 1980–89’, Scandinavian Journal of Economics, 94(Suppl.): S211–28.
8.
BergerA.N.HumphreyD.B. (1991), ‘The Dominance of Inefficiencies over Scale and Product Mix Economies in Banking’, Journal of Monetary Economics, 28(1): 117–48.
9.
BergerA.N.HancockD.HumphreyD.B. (1993), ‘Bank Efficiency Derived from the Profit Function’, Journal of Banking and Finance, 17(2–3): 317–47.
10.
BergerA.N.HunterW.C.TimmeS.G. (1993), ‘The Efficiency of Financial Institutions: A Review and Preview of Research Past, Present and Future’, Journal of Banking and Finance, 17(2–3): 221–49.
11.
BhattacharyyaA.BhattacharyyaA.KumbhakarS.C. (1997), ‘Changes in Economic Regime and Productivity Growth: A Study of Indian Public Sector Banks’, Journal of Comparative Economics, 25(2): 196–219.
12.
BhaumikS.DimovaR. (2004), ‘How Important is Ownership in a Market with a Level Playing Field: The Indian Banking Sector Revisited’, Journal of Comparative Economics, 32(1): 165–80.
13.
BurgessR.PandeR. (2005), ‘Do Rural Banks Matter? Evidence from the Indian Social Banking Experiment’, American Economic Review, 95(3): 780–95.
14.
CharnesA.CooperW.W.RhodesE.L. (1978), ‘Measuring the Efficiency of Decision Making Units’, European Journal of Operational Research, 2(6): 429–44.
15.
ClaessensS.LaevenL. (2004), ‘What Drives Bank Competition? Some International Evidence’, Journal of Money, Credit, and Banking, 36(2): 563–84.
16.
CornwellC.SchmidtP.SicklesR.C. (1990), ‘Production Frontiers with Cross-sectional and Time-series Variation in Efficiency Levels’, Journal of Econometrics, 46(1–2): 185–200.
17.
DasA. (1997), ‘Technical, Allocative and Scale Efficiency of Public Sector Banks in India’, Reserve Bank of India Occasional Papers, 18(June–September), Special Issue: 279–301.
18.
DemsetzH. (1973), ‘Industry Structure, Market Rivalry and Public Policy’, Journal of Law and Economics, 16(2): 1–10.
19.
European Commission (2005), White Paper on Financial Services Policy(2005–2010), SEC(2005)1574.
20.
FareR.GrosskopfS.LovellC.A.K. (1985), The Measurement of the Efficiency of Production. Boston: Kluwer Academic Publishers.
21.
FareR.GrosskopfS.LovellC.A.K. (1994), Production Frontiers. Cambridge: Cambridge University Press.
22.
FarrellM. (1957), ‘The Measurement of Productive Efficiency’, Journal of the Royal Statistical Society, Series A, 120(3): 253–90.
23.
GilbertR.A.WilsonP.W. (1998), ‘Effects of Deregulation on the Productivity of Korean Banks’, Journal of Economics and Business, 50(2): 133–55.
24.
GoldbergerA.S. (1972), ‘Structural Equation Methods in the Social Sciences’, Econometrica, 40(6): 979–1001.
25.
Grifell-TatjeE.LovellC.A.K. (1996), ‘Deregulation and Productivity Decline: The Case of Spanish Savings Banks’, European Economic Review, 40(6): 1281–1303.
26.
HarkerP.T.ZeniosA.S. (2000), ‘What Drives the Performance of Finan-cial Institutions?’, in HarkerP.T.ZeniosA.S. (eds), Performance of Financial Institutions: Efficiency, Innovation, Regulation, pp. 3–31. New York: Cambridge University Press.
27.
HicksJ. (1935), ‘The Theory of Monopoly’, Econometrica, 3(1): 1–20.
28.
HumphreyD.B.PulleyL.B. (1997), ‘Banks’ Responses to Deregulation: Profits, Technology, and Efficiency’, Journal of Money, Credit and Banking, 29(1): 73–93.
29.
JoreskogK.G. (1970), ‘A General Method for Analysis of Covariance Structures’, Biometrika, 57(2): 239–51.
30.
JoreskogK.G.GoldbergerA.S. (1975), ‘Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable’, Journal of the American Statistical Association, 70(351): 631–39.
31.
JoreskogK.SorbomJ. (1993a), LISREL 8: Structural Equation Modelling with the Simplis Command Language. Hillsdale, NJ: Lawrence Erlbaum Associates.
KneipA.SicklesR.C.SongW. (2003), ‘On Estimating the Mixed Effects Model’, Mimeo, Rice University, USA.
34.
KumbhakarS.C.SarkarS. (2003), ‘Deregulation, Ownership, and Productivity Growth in the Banking Industry: Evidence from India’, Journal of Money, Credit, and Banking, 35(3): 403–24.
35.
LeibensteinH. (1966), ‘Allocative Efficiency Versus X-Efficiency’, American Economic Review, 56(3): 392–415.
36.
LeightnerJ.E.LovellC.A.K. (1998), ‘The Impact of Financial Liberalization on the Performance of Thai Banks’, Journal of Economics and Business, 50(2): 115–31.
37.
MeeusenW.van den BroeckJ. (1977), ‘Efficiency Estimation from Cobb–Douglas Production Functions with Composed Error’, International Economic Review, 18(2): 435–44.
38.
Ram MohanT.T.RayS.C. (2004), ‘Comparing Performance of Public and Private Sector Banks: A Revenue Maximization Efficiency Approach’, Economic and Political Weekly, (39): 1271–76.
39.
ParkB.SimarL. (1994), ‘Efficient Semiparametric Estimation in Stochastic Frontier Models’, Journal of the American Statistical Association, 89(429): 929–36.
40.
ParkB.SicklesR.C.SimarL. (1998), ‘Stochastic Panel Frontiers: A Semi-parametric Approach’, Journal of Econometrics, 84(2): 273–301.
41.
RagunathanV. (1999), ‘Financial Deregulation and Integration: An Australian Perspective’, Journal of Economics and Business, 51(6): 505–14.
42.
SchumpeterJ. (1934), The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle. Cambridge: Harvard University Press.
43.
SensarmaR. (2006), ‘Are Foreign Banks Always the Best? Comparison of State-owned, Private and Foreign banks in India’, Economic Modelling, 23(4): 717–35.
44.
ShephardR.W. (1953), Cost and Production Functions. Princeton: Princeton University Press.
45.
SimarL.WilsonP. (1999), ‘Estimating and Bootstrapping Malmquist Indices’, European Journal of Operational Research, 115(3): 459–71.
46.
SimarL.WilsonP. (2000), ‘A General Methodology for Bootstrapping in Nonparametric Frontier Models’, Journal of Applied Statistics, 27(6): 779–802.
47.
ZaimO. (1995), ‘The effect of Financial Liberalization on the Efficiency of Turkish Commercial Banks’, Applied Financial Economics, 5(4): 257–64.
48.
ZellnerA. (1970), ‘Estimation of Regression Relationships Containing Unob-servable Independent Variables’, International Economic Review, 11(3): 441–54.
