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Asia-Pacific Financial Markets

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21.07.2020 | Original Research

Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach

verfasst von: Tai-Hsin Huang, Yi-Huang Chiu, Chih-Ying Mao

Erschienen in: Asia-Pacific Financial Markets | Ausgabe 2/2021

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Abstract

This paper develops a stochastic approach to impose regularity properties on a directional output distance function (DODF) and an output distance function, which can be estimated by maximum likelihood. We use the resulting parameter estimates to evaluate efficiency and total factor productivity (TFP) growth for Taiwan’s commercial banks over the period 2002–2015 and claim that the failure of considering the regularity restrictions and the exclusion of undesirables lead to miscalculated efficiency measures and productivity gains. The outcomes from the regularity-constrained DODF reveal that almost all data-points satisfy the regularity properties, that the managerial abilities of the banks improve after the subprime crisis of 2007, and that the sample banks’ TFP grow at an average rate of 1.93% per annum, whereby technical change is the driving force. However, our estimates show downward trends in the growth rate of TFP and technical change.

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We do not show the relevant results for brevity.

We implicitly impose the assumption of null-joint production and weak disposability of good and bad outputs, and strong disposability of the good output y. Please see, e.g., Färe and Grosskopf (2005), for the related definitions.

Färe et al. (2005) estimate the stochastic DODF without imposing monotonicity, which violates the monotonicity conditions 57 out of 209 times in 1993 and 20 out of 209 times in 1997.

It is noteworthy that if different distributions are assumed, then the resulting parameter estimates and the number of constraint violations may change somewhat.

It can be shown that \(\left| {F_{2} } \right| = \left| {\begin{array}{*{20}c} {\alpha_{22} } & {\alpha_{23} } \\ {\alpha_{23} } & {\alpha_{33} } \\ \end{array} } \right| = \alpha_{22} \alpha_{33} - \alpha_{23}^{2} = \left| {F_{3} } \right| = \left| {\begin{array}{*{20}c} {\alpha_{11} } & {\alpha_{13} } \\ {\alpha_{13} } & {\alpha_{33} } \\ \end{array} } \right| = \left| {F_{1} } \right| \ge 0\).

Since our likelihood function may have multiple local maxima, a change in initial conditions tends to result in distinct parameter estimates.

Note that our simultaneous estimation procedure with respect to (2) and (7)–(12) can still raise the efficiency of the estimators somewhat due to the imposition of cross-equation restrictions on the coefficients under study.

Although the use of ODF allows one to decompose the Malmquist TFP change index into three items, i.e., TC^S, EC^S, and SC (a scale component), DODF is unable to address the term of SC. Since this paper mainly focuses on the use of DODF, we follow Feng and Serletis (2014) who ignore this scale component.

A financial holding company (FHC) is a financial institution engaged in banking-related activities, offering customers a wide range of financial services, such as purchasing insurance products and investment in securities. An FHB is a subsidiary of an FHC, and its scale is usually larger than Non-FHBs, which do not belong to any financial group. Here, a foreign bank is obligated to follow the regulations of both the home and host countries, and its scale is close to Non-FHBs in Taiwan.

Four out of the five foreign banks started their businesses in Taiwan after 2007. Hence, there are no observations for the four banks prior to 2007.

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Titel: Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach
verfasst von: Tai-Hsin Huang
Yi-Huang Chiu
Chih-Ying Mao
Publikationsdatum: 21.07.2020
Verlag: Springer Japan
Erschienen in: Asia-Pacific Financial Markets / Ausgabe 2/2021
Print ISSN: 1387-2834
Elektronische ISSN: 1573-6946
DOI: https://doi.org/10.1007/s10690-020-09319-z

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