A tool for scrutinizing bank bailouts based on multi-period peer benchmarking

Pacific-Basin Finance Journal 19 (2011) 447–469

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Pacific-Basin Finance Journal j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p a c f i n

A tool for scrutinizing bank bailouts based on multi-period peer benchmarking Necmi K. Avkiran a,⁎, Mika Goto b a b

UQ Business School, The University of Queensland, Australia Central Research Institute of Electric Power Industry, Japan

a r t i c l e

i n f o

Article history: Received 2 November 2010 Accepted 8 June 2011 Available online 15 June 2011 JEL classification: G21 L25 Keywords: Banking Financial performance Multi-period peer benchmarking

a b s t r a c t In the wake of the recent global financial crisis central banks and regulators are concerned about re-direction of bailout funds into dividends. Yet, we do not know much about the extent banks follow dividend policies and funding decisions optimal to generating shareholders' wealth because banks have been mostly absent from an otherwise expansive literature on dividend policy. A relative, multi-period analysis of the troubled Japanese regional banks for the period 1998–2007 identifies inefficiencies in the levels of dividends, retained earnings, external funding and shareholder returns. The study unfolds further by investigating associations between inefficiencies and non-performing loans, followed by a comparison of efficient versus inefficient banks across good and bad economic times. The methodology captures linkages among yearly financial decisions over multiple periods, thus summarizing long-term performance. The new approach can guide continuous benchmarking of bank financial performance, as well as help policy-makers monitoring potential misappropriation of bailout funds during financial crises. The findings indicate a potential to adjust levels of debt and equity funding, and substantial room for improvement in shareholder returns. Associations between non-performing loans and technical inefficiencies are generally statistically significant. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved.

1. Introduction This study illustrates a method of peer comparison where observed performances of best-practice banks are used to evaluate a bank's dividend policy and associated financing decisions. Understanding ⁎ Corresponding author at: UQ Business School, The University of Queensland, Brisbane QLD4072, Australia. Tel.: + 61 7 334 63282; fax: + 61 7 334 68166. E-mail address: [email protected] (N.K. Avkiran). 0927-538X/$ – see front matter. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.pacfin.2011.06.001

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which banks are more efficient in the long-run in their key financial decisions while maximizing shareholder returns can guide policy-makers monitoring potential misappropriation of bailout funds. Approach illustrated in the paper's multi-period relative financial performance analysis is timely in the wake of the recent global financial crisis (GFC) when central banks are concerned about re-direction of bailout funds that rely on taxpayers' monies into dividends. The current study provides insight to inefficiencies in allocation of dividends, retained earnings and external funding of operations, as well as potential improvements in shareholder returns, where the latter is defined as annual percent change in total return index (TRI) (includes capital gains and dividends as defined in the DataStream data base). We apply such insight to identify inefficient banks that may be less deserving of financial assistance using taxpayers' monies. In the spirit of productivity or relative efficiency estimation, the objective function of bank production minimizes the inputs of dividends, retained earnings, debt and equity funding, whereas the same function simultaneously maximizes the key output of shareholder returns. To the best of our knowledge, this multi-period study of bank dividend policy from a relative efficiency perspective is the first of its kind. The paper investigates the financial performance of the Japanese regional banks (JRB), which carry high impaired assets, for the period 1998–2007 using a balanced panel data set. The study period includes years of recession (1998–2003), as well as economic recovery (2004–2007). How do observed dividend policies, particularly in times of high non-performing loans (NPL) when shareholder value creation is under threat, compare with benchmark dividend policies found in a peer sample? Study of such a period is significant given that high NPL impair banks' capital, and thus, lower risk-taking capacity for revenue generation. Unable to lend to growing firms, banks' predicament also has a negative impact on economic activity. Even if capital adequacy levels are maintained, this often comes at additional cost to the bank, usually via expensive new equity issues. This has been one of the most fervently argued points in the lead up to the recently accepted Basel III Accord that promises to introduce tighter capital adequacy requirements across the global banking sector. Another motivation is the Japanese corporate governance system of main bank that involves firms whose operations are monitored by their lending bank (often the same bank) (Nakatani, 1984). The main bank system was accepted practice until mid-1990s (see Kang and Shivdasani, 1995), but it has since been recognized as a source of inefficiency. Thus, current corporate leaders are under more pressure to improve efficiency with a view to maximizing shareholder wealth. A large body of literature addresses various aspects of dividend policy in an assortment of industries. According to some authors, dividend policy matters because of various factors such as taxation, transaction costs, imperfect markets, indivisible investment opportunities and irrational behavior (Wilkes, 1977). Banks appear to have escaped the same level of scrutiny directed at non-banking firms, possibly due to their stable dividends, and because they operate in a tightly regulated industry. The current paper focuses on the troubled Japanese regional banking sector, which represents an increasingly deregulated industry operating in a country where firms are gradually shifting toward paying dividends commensurate with company profits. In this study, the non-parametric efficient frontier technique, multi-period range-adjusted measure (MP-RAM), evaluates the relative performance of a bank's dividend policy against that of its peers. MPRAM generates a single technical efficiency score that captures the intertemporal associations among annual operational decisions, where a firm optimizes its behavior across multiple periods. In particular, the measured inefficiencies reflect the impact of a period's dividend policy on the following period's funding decisions. This approach is different from traditional static models based on mathematically independent production frontiers that assume single-period optimization of a firm's behavior. The analysis with the multi-period RAM is also different from that of a traditional lagged regression model. Regression models can identify a relationship between today's dividends and tomorrow's funding needs using lagged variables in a static framework. However, such a static relationship is examined under the assumption that those variables are already determined in optimal levels for each period. On the other hand, the multiperiod RAM iteration optimally allocates dividends and retained earnings over time to maximize shareholder returns across the complete study period before it summarizes the analysis in a scalar value.1 That is, the current paper's method produces a long-term overall efficiency score for each bank. 1 Naceur et al. (2006) also use a panel data set but dynamic regressions to investigate dividend policies of firms listed on the Tunisian Stock Exchange. However, Naceur et al. (2006) are interested in identifying factors influencing firms' dividend policy decisions, while the current paper's principal interest lies in evaluating the comparative financial performance of peer banks conditional on their observed dividend policies.

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In Section 2, the conceptual framework begins with a discussion of the scope of the study, continuing with an overview of dividend policy in practice as evidenced in the extant literature, and the variables in the bank performance model. Section 3 outlines the study setting and the data before discussing MP-RAM. Section 4 reports various analyses of inefficiency, including across banks and across time, and discusses the findings. Concluding remarks in Section 5 summarize the paper, as well as provide some additional discussion, and offer future directions for research in this field. 2. Conceptual framework 2.1. Scope of the study The academic debate on relevance of dividend policy to shareholder wealth can be traced to Modigliani and Miller (1958), and Miller and Modigliani (1961). There are also various motivational theories on dividend policy decision-making such as bird-in-the-hand theory, tax clientele theory, residual dividend theory, agency costs of free cash flow hypothesis, signaling theory, and so on (see Elton and Gruber, 1970; Fama, 1974; Bhattacharya, 1979; Easterbrook, 1984; Miller and Rock, 1985; John and Williams, 1985; Jensen, 1986; Ambarish et al., 1987; Allen et al., 2000; Gillet et al., 2008, and many others). Dhanani (2005) maintains that testing such theories has produced inconclusive results. The current paper accepts the actual dividend policies of banks regardless of managerial motivations, and provides insight to inefficiencies that could be targeted by emulating observed benchmark policies among peers. As in the seminal paper by Lintner (1956), we adopt the view that managers deliberately plan for and implement dividend policies — something that is also acknowledged in La Porta et al. (2000) almost half a century later. Therefore, it is compelling for bank managers, regulators and market analysts to find out how effective dividend policies can be in maximizing shareholder returns, particularly under different economic conditions experienced over time. In the bank management behavior modeled in this study, endogenous and exogenous inputs entering a bank's production processes exit as exogenous outputs. The word endogenous indicates decisions within direct managerial discretion, and the word exogenous suggests decisions outside direct managerial discretion. The parsimonious performance model in this study goes beyond a superficial treatment of dividends versus retained earnings by capturing related key financing decisions such as debt and equity funding of a bank's operations. That is, dividend policy and its concomitant decisions on external funding generate shareholder returns. 2.2. Overview of dividend policy in practice A principal financial axiom dictates that management divide net profits into dividends paid to shareholders and retained earnings. According to Dhanani (2005, p.1627), “…the issue of earnings distribution (and/or retention) … represents an important aspect of financial management…” Most firms that pay dividends maintain a stable dividend payout which they recognize as a source of return for shareholders, as well as a signal to the markets that the firm is doing well. Similarly, retained earnings are internal sources of funds for investments that can generate new cash flows in future periods and a source of capital. Thus, dividend policy reflects the judgment of board of directors on the trade-off between dividends that will add to current shareholder returns, and retained earnings that can be re-invested to generate more dividends and capital gains later, or used to bolster bank capital thus improving soundness and cost of borrowing. 2 At the same time, investors would expect more of the firm's profits to be paid to them in dividends if management is unable to identify investments that will return at least what is expected by the investors. The literature on dividend policy is expansive. For brevity, the rest of the discussion is limited to publications that motivate the study. Partington (1985) discusses three major types of dividend policy based on the priority assigned to dividends: (a) A residual dividend policy where management determines dividends subject to surplus funds after investment and financing decisions (i.e., dividends have the lowest priority). 2

Other possible applications of retained earnings include cash bonuses to executives and funding of stock options.

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(b) An independent dividend policy where management sets dividends usually in response to a desire to maintain payout stability, followed by adjustments to investment and/or financing decisions (i.e., dividends receive top priority). (c) A simultaneous dividend policy where the dividend policy is neither residual nor independent but some mixture of the first two approaches. Based on a survey of large Australian companies, Partington's (1985) empirical study concludes that managers do not follow a residual dividend policy. The most common pattern of behavior identified by Partington is one where investment and dividend payout decisions are primarily independent of each other and at instances when retained earnings are not sufficient to fund investments, the firm resorts to debt financing. Another survey targeting large UK firms (Dhanani, 2005) also reports empirical evidence against the residual dividend policy. More specifically, Dhanani finds that UK firms exercise a higher level of integration between investment and dividend decisions compared to US firms. UK firms often make dividend decisions after investment decisions but with an eye on maximizing dividends. In general, dividend policy appears to maximize firm's market value. Given that the sample in the current study consists of Japanese regional banks, the following paragraphs continue to outline the evidence on dividend policy from Japan. Mizuno (2007) surveys corporate managers in firms listed on the Tokyo Stock Exchange from two manufacturing and two non-manufacturing industries. Consistent with the empirical evidence reported from other countries (see above), the author finds no evidence to support a practice of residual dividend policy. Japanese firms place higher significance on stable dividends and usually target a dividend payout ratio. Nevertheless, about two-thirds of the firms surveyed believe that dividends should be paid after investment decisions and strengthening of the balance sheet. Japanese managers also acknowledge the link between dividend policy and firm's value. A further interesting finding by Mizuno (2007) is the observation that an increasing number of Japanese firms are setting dividend payments that reflect financial performance, which is a departure from the more traditional practice of stable dividends. This observation provides additional justification for the current study. That is, the case of Japanese firms increasingly paying dividends commensurate with profits presents a more compelling reason to examine the association between dividend policies and shareholder returns. Other studies that have investigated various aspects of dividend decisions among Japanese non-financial firms include Harada and Nguyen (2005), Kato et al. (1997, 2002), Fukuda (2000), and Gul (1999); all of these studies report some degree of information content associated with dividend decisions. 2.3. Dividend policy of banks We were unable to locate any publications on dividend policies of Japanese banks. One exception is what we were able to glimpse on the web sites of three JRBs, namely, Hiroshima Bank, Bank of Yokohama, and Hokkoku Bank, where they refer to dividends having stable and performance-linked components. 3 Similarly, publications on dividend policies of banks from the rest of the world are not as abundant as studies on non-banking firms. Existing studies on bank dividend policy normally examine changes in share prices in response to an announcement of a significant change in dividends to be paid (see Keen, 1978, 1983; Bessler and Nohel, 1996). On the other hand, Casey and Dickens (2000) investigate the impact of taxes on bank dividend policy. Bessler and Nohel (1996) contend that financial institutions have been left out of regular studies on dividend policy because being highly regulated and highly leveraged sets them apart from non-financial institutions. A number of studies have focused on US bank holding companies (BHCs). Filbeck and Mullineaux (1999) find support for the contention that abnormal returns associated with dividend announcements by BHCs are not related to external funding activity. This observation is supported by the argument that bank regulators' monitoring activities, particularly in relation to agency costs, make monitoring efforts of capital market institutions mostly redundant. An earlier study by Filbeck and Chadwell (1993) maintains that due to various enforcement tools at the disposal of regulators such as withdrawal of deposit insurance and monitoring penalties, BHCs are less likely to signal falsely. They find evidence supporting the hypothesis 3

More details are available from the authors.

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that the concentration of insider ownership does not explain differences in share prices following dividend change announcements. Boldin and Leggett (1995) who have also studied US BHCs report evidence supporting the signaling theory, where there is a positive relationship between bank dividends per share and bank quality rating. The authors conclude that bank management use dividends to signal financial soundness to investors. Nevertheless, the assumption that banks are less likely to send false signals to markets does not always hold. Neither does the assumption held about competent and omnipresent regulators as evidenced in the period leading up to the recent GFC; for example, the reader may recall the low interest rate policies adopted by various central banks including the US Federal Reserve (see Allen and Carletti, 2010) and the low level scrutiny of securitization. Asymmetric information between bank executives and other stakeholders can be a key factor underlining the importance of dividends in signaling a bank's financial status to investors, regulators, and customers. For example, evidence from the US banks of 1980s (a time of large losses) indicates that the banks continued to pay dividends, thus attempting to send out positive signals. Such dividend payments were often financed by new equity issues (Bessler and Nohel, 1996) — a practice that would normally be frowned upon or be illegal. In short, banks appear to prefer stable dividends unless forced to act otherwise, although more recent studies on Japanese non-bank firms suggest increasingly performance-based dividends (see Mizuno, 2007; Aoki, 2007). Our assertion is also supported by the deregulation of the Japanese banking sector that has been unfolding since 1998 — characterized by lifting of the blanket guarantee on deposits, diversification of products and services, and establishment of new alliances with non-bank firms. Therefore, given these wider internal and external pressures, we are interested in exploring the following research questions: RQ 1: Do Japanese regional banks (JRBs) prefer stable dividends? RQ 2: Are JRBs' dividends associated with inefficient (excessive) use of equity? In recognition of the high levels of non-performing loans on the books of JRBs, we extend the investigation to explore the potential relationships between non-performing loans (NPL) and various types of inefficiencies on the modeled discretionary variables (i.e., inputs): RQ 3: RQ 4: RQ 5: RQ 6:

Are JRBs' Are JRBs' Are JRBs' Are JRBs'

NPL associated with inefficient (excessive) use of dividends? NPL associated with inefficient (excessive) use of retained earnings? NPL associated with inefficient (excessive) use of debt funding? NPL associated with inefficient (excessive) use of equity funding?

Finally, research question 7 re-visits the question raised in the introduction regarding NPL and bank capital: RQ 7: Are JRBs' NPL associated with their capital adequacy ratios (CAR)? 4 2.4. Variables in the bank financial performance model Literature review in the preceding sections identifies a practice among non-bank firms where investment decisions are taken first, followed by setting of dividends designed to maximize payout, and finally, financing decisions. That is, empirical evidence does not support a residual dividend policy but points to residual funding decisions instead. This is not unusual given that managerial decisions normally focus on value creation where dividends enhance current return to shareholders, and investments enhance future returns. Two other insights gained from the preceding literature review are, (i) the firms' tendency to raise external debt when retained earnings are inadequate, and (ii) an acknowledgment that value of the firm is linked to dividend policy. There is no consensus in literature on banking inputs and outputs. The static performance model outlined in Fig. 1 lays the foundation for the multi-period production assumed later in this study and treats a bank's production (Pt ) as a black box (a phrase coined by Färe and Grosskopf, 1996). That is, the current study does not probe the network of various bank divisions or profit centers and their corresponding 4 CAR is a ratio closely monitored by regulatory authorities. It is normally defined as the ratio of core capital to risk-weighted assets. In the data base used, this ratio is known as the total capital ratio.

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Exogenous outputs (non-discretionary)

Endogenous inputs (discretionary)

xt

Fixed exogenous inputs (non-discretionary)

Pt

yt

vt

Fig. 1. Static model of bank performance. Dividends, retained earnings, debt and equity funding comprise the endogenous inputs controlled by management. The model assumes that exogenous inputs such as the cash rate set by the central bank of Japan, regulatory conditions, or the state of the global economy are fixed. Finally, shareholder returns, the only exogenous output, are measured by the annual percent change in total return index.

variables that comprise the underlying sub-technologies (see Avkiran, 2009 for a network analysis in banking). Furthermore, in the absence of clear empirical evidence on whether funding decisions in banking are residual, total annual dividends (Div), and the balance sheet stock levels for retained earnings (Re), debt (D) and equity (E) funding are regarded as endogenous inputs (xt) controlled by management. For example, for most commercial banks customer deposits comprise a major source of external retail-priced debt and therefore, the terms of deposits are actively managed and new deposits solicited, rather than debt becoming a residual decision in implementation of dividend policy. While wholesale funds are also an important source of external debt carefully managed to minimize the overall cost of borrowing, the recent GFC highlights the significance of managing the mix of debt when capital markets are not liquid. Such mix inefficiencies are not addressed in the current study. The model assumes that exogenous inputs (vt) such as the cash rate set by the central bank of Japan, regulatory conditions, or the state of the global economy influence the banks in this study's homogeneous sample in a similar manner (i.e., fixed). Finally, the model measures shareholder returns, the only exogenous output (yt), by the annual percent change in total return index (TRI) (includes capital gains and dividends as defined in the DataStream data base). We note that TRI was also used in a recent data envelopment analysis (DEA) based study of Japanese banks as a measure of shareholder returns (see Avkiran and Morita, 2010b). Thus, the mathematical objective is to identify to what extent observed multiple endogenous inputs can fall while simultaneously maximizing the level of the exogenous output by benchmarking the best performers (i.e., those on the efficient frontier) in the sample of peer banks. Fig. 2 shows the multi-period bank financial performance model used in empirical testing in this study, which is an extension of Fig. 1. Looking at production P in time t, dividend policy and the related external funding decisions lead to shareholder returns measured by the annual percent change in total return index, where the study assumes a time period of 12 months. To capture some of the multi-period linkages in managerial decision-making, we treat dividends and retained earnings as endogenous intermediate products (k). That is, dividends and retained earnings act as outputs in a given period and inputs in the following period. For instance, dividends and retained earnings in period t − 1 (outputs) become inputs to period t because they impact on external funding decisions required for a firm's investments and thus shareholder returns in period t. Similarly, decisions on dividends and retained earnings in period t (outputs) become inputs to period t + 1 in determining debt and equity for period t + 1, and so on. 3. Methodology 3.1. Study setting After the bubble economy period of the late 1980s to early 1990s, Japan fell into a long-term depression, known as the lost decade (Hayashi and Prescott, 2002). During the lost decade, Japanese economy had

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y t-1

Exogenous output: TRI

Endogenous output/input intermediate kt-2 products: Div, Re Endogenous inputs: D, E

Exogenous inputs (fixed)

yt

output/input

output/input

kt

Pt-1

k t+1

Pt+1

Pt xt

vt-1

y t+1

output/input

k t-1

x t-1

453

x t+1

vt

vt+1

Fig. 2. Multi-period model of bank financial performance used in the current study. The above figure shows the multi-period model of bank financial performance (an extension of Figure 1). Focusing on production P in time t, dividend policy and the related external funding decisions manifest themselves as shareholder returns. Dividends and retained earnings are treated as endogenous intermediate products in order to capture multi-period linkages. That is, dividends and retained earnings act as outputs in a given period and inputs in the following period. TRI, annual percent change in total return index measuring shareholder returns; Div, dividends; Re, retained earnings; D, debt; E, equity; P, bank production in a given period.

excess production capacity, higher unemployment and higher company debt. The excessive use of resources was mainly due to the Japanese corporate leaders' belief that expanding corporate size would create corporate value. During the lost decade, such practices resulted in over-investment and inefficient use of resources. 5 Until recently, the Japanese corporate governance system was traditionally characterized by stable shareholders. Stable shareholders imply a concentration of shareholders with strategic ties, rather than a fragmented share holding composed of short-term investors. Stable shareholders focus on enhancing longterm relationships with each other rather than return on equity (Hu and Izumida, 2008). Besides the existence of stable shareholders or cross shareholders, the Japanese corporate governance was also characterized by the unique features of a main bank system. That is, firms belonged to a group with a bank at its center and the bank monitored operations of firms in the group (Nakatani, 1984). Such a corporate governance system appeared to work up to the end of the bubble economy (see Kang and Shivdasani, 1995), but it is now a source of inefficiency. Consequently, the shareholders are directing the current corporate leaders with increasing persistence toward improving efficiency and maximizing the corporate value of their firms. To overcome the economic depression, the government under the Koizumi cabinet (2001–2006) reformed the Japanese economic and financial systems. The corporate governance system has also been a target for reform. Consequently, the Japanese firms have started adopting more of an Anglo-American style of management that includes accepting outside board members and rewarding executives on a performance-based system. Under restructuring, traditional cross shareholdings between firms and financial institutions gradually disappeared. The Japanese firms are increasingly realizing the importance of rewarding shareholders with dividend payouts linked to profits (Aoki, 2007). Japanese regional banks have traditionally built their long-term business relationships with local firms, often limiting their presence to the prefecture where the head office is located, while maintaining a branch in the major cities such as Tokyo and Osaka. According to the Regional Banks Association of Japan, regional banks' main activities consist of retail banking, with approximately 81% of their borrowing customers comprised of small and medium-sized enterprises, and individual consumers; on the other hand, about 71% of their depositing customers are consumers (RBAJ, 2006). Twenty-three percent of deposits collected 5 The phenomenon of managers allowing their firms to grow beyond the optimal size is well covered in literature on ‘empire building’. See Jensen (1986).

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Table 1 Descriptive statistics on variable levels (N = 52), 1998–2007.

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Mean Median Maximum Minimum S.D.c C.V.d Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D. C.V. Mean Median Maximum Minimum S.D.

ΔTRIa

Dividendsb (×000,000)

Retained earnings (×000,000)

Debt funding (×000,000)

Equity funding (×000,000)

− 0.0528 − 0.0463 0.3631 − 0.3865 0.1435 − 2.7191 − 0.0559 − 0.0340 0.2381 − 0.2951 0.1069 − 1.9127 − 0.0862 − 0.0945 1.2952 − 0.4100 0.2500 − 2.8995 0.0135 0.0171 0.5668 − 0.4972 0.1470 10.9203 0.0172 0.0171 0.4051 − 0.3018 0.1362 7.9404 0.0066 0.0007 0.6653 − 0.3125 0.1440 21.6794 0.1933 0.1229 0.8263 − 0.1403 0.2384 1.2331 0.2016 0.1817 0.9189 − 0.1676 0.2224 1.1029 0.2510 0.2445 0.7707 − 0.1013 0.1808 0.7202 − 0.1528 − 0.1512 0.0287 − 0.2995 0.0656

703 569 2654 95 533 0.7580 715 581 2711 97 545 0.7628 743 586 3416 195 599 0.8062 774 589 3435 196 644 0.8325 865 604 7144 201 1009 1.1661 868 614 7266 205 1049 1.2083 960 669 7411 206 1099 1.1451 1100 709 12,148 202 1713 1.5573 1178 746 12,534 199 1776 1.5071 1211 760 8826 151 1478

− 4170 1990 12,415 − 115,337 20,955 − 5.0252 10,621 8859 61,578 − 16,944 11,319 1.0658 6895 5319 52,602 − 22,642 9841 1.4273 3612 3435 27,971 − 21,297 8143 2.2541 − 2380 2516 26,664 − 40,449 11,915 − 5.0063 1277 3224 21,798 − 33,362 10,177 7.9683 8699 7153 55,374 − 16,365 9881 1.1358 10,925 8402 68,230 − 11,844 12,414 1.1363 12,356 10,445 60,085 − 13,927 12,158 0.9839 12,886 9589 67,076 − 889 12,161

2,662,305 2,199,984 9,262,802 427,610 1,674,553 0.6290 2,758,843 2,290,011 9,290,173 446,442 1,724,654 0.6251 2,850,642 2,373,894 9,293,656 456,344 1,781,940 0.6251 2,915,634 2,415,163 9,438,456 465,396 1,807,581 0.6200 3,004,553 2,489,603 9,822,673 481,972 1,876,686 0.6246 3,082,916 2,620,229 9,662,221 502,985 1,897,319 0.6154 3,177,345 2,704,863 9,879,750 522,549 1,972,556 0.6208 3,181,158 2,739,987 9,668,433 520,128 2,006,646 0.6308 3,166,369 2,703,362 10,005,841 521,805 2,004,664 0.6331 3,147,399 2,673,302 10,215,604 516,423 2,024,280

45,230 30,374 313,221 6824 50,443 1.1153 47,163 32,677 318,638 11,522 51,070 1.0828 49,288 32,938 323,129 13,468 53,323 1.0819 50,429 33,123 324,953 13,544 53,500 1.0609 52,692 37,330 333,154 13,886 54,577 1.0358 53,979 37,967 345,898 14,122 56,225 1.0416 55,358 38,185 402,848 14,204 62,362 1.1265 56,460 40,493 396,828 13,970 64,288 1.1386 55,421 39,744 390,528 13,687 63,272 1.1416 54,467 38,969 383,136 13,420 62,062

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Table 1 (continued) ΔTRIa C.V.

− 0.4296

Dividendsb (×000,000) 1.2209

Retained earnings (×000,000) 0.9437

Debt funding (×000,000) 0.6432

Equity funding (×000,000) 1.1394

Notes: There is a gradual rise in shareholder returns until the onset of the recent financial crisis in 2007. The large variations in shareholder returns for 2001–2003 correspond to the last three years of the recession which followed the bursting of the Japanese economic bubble in the early 1990s. Overall, retained earnings show more variation (see coefficient of variation in Table 1) than debt and equity funding across the study period of 1998–2007. a ΔTRI: Annual percent change in total return index is the only output variable. b Input figures are in Japanese yen. c S.D., standard deviation. d C.V., coefficient of variation, defined as S.D. over the mean.

by private financial institutions in Japan are with regional banks (a share only second to deposits collected by city banks); a similar relationship exists with loans where regional banks hold a 25.6% share. In addition to dominating banking in regional areas of Japan, these banks hold 53.9% share of the finance extended to local governments (RBAJ, 2006). On a less positive note, regional banks are behind the major Japanese banks in reducing non-performing loans and enhancing profitability (OECD, 2006; Bank of Japan, 2006). In 2007 (the last year in the current study period), the ratios of non-performing loans to total credit for regional banks and major banks had improved to about 4% and 1.5% respectively, whereas in 2001 (about half-way through the current study period) the figures were 8.1% and 8.7% respectively (Bank of Japan, 2007). Such NPL ratios are also substantially higher than those found in other East Asian countries with relatively more robust economies and banking sectors (e.g., Australia at about 0.5%). 3.2. Data Table 1 shows the descriptive statistics using inflation-adjusted data for the variables in the bank financial performance model for the sample of fifty-two Japanese regional banks. 6 During the years of reform referred to above, we notice a gradual rise in shareholder returns until the onset of the recent financial crisis in 2007. The large variations in shareholder returns for 2001–2003 correspond to the last three years of the recession which followed the bursting of the Japanese economic bubble in the early 1990s. The pattern between shareholder returns and dividends in the study period of 1998–2007 appears unclear. That is, while dividends have grown slowly but steadily, some of this growth has occurred during falling shareholder returns. Yet, this happens to be the anticipated relationship based on the literature review that generally suggests a stable payout as common practice where sharp reductions in dividends paid are considered as a matter of last resort. This finding represents the first empirical insight to research question 1, suggesting that JRBs prefer stable dividends. Overall, retained earnings show more variation (see coefficient of variation in Table 1) than debt and equity funding across the study period of 1998–2007. The yearly change in the sample variation for retained earnings and dividends is generally in the same direction, although once again, retained earnings tend to vary more. This observation highlights the accounting relationship among profits, dividends and retained earnings mentioned earlier. That is, if the Japanese regional banks generally follow a stable dividend payout, fluctuations in profits are likely to manifest as greater variation in retained earnings. Regarding debt and equity funding, the regional banks appear to take similar decisions as evidenced with the stable coefficient of variation numbers across the study period that includes both recession (1998–2003) and economic recovery (2004–2007). In the case of the Japanese regional banks, these observations suggest a stable relationship with creditors and shareholders — points already highlighted in Section 3.1. 6 The Regional Banks Directory provided by the Regional Banks Association of Japan (http://www.chiginkyo.or.jp/pdf_data/ 01_gaiyou/chiginpanfu-e2010.pdf) lists 63 JRBs, i.e. 82.54% of the population is captured in our study. Attrition is due to unavailability of some observations as we construct a balanced panel data set using various data bases such as BankScope and DataStream.

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The correlation matrix in Table 2 indicates three high and three moderate level positive associations among input variables. In regression studies, high correlations among independent variables would normally be a concern because the explanation of the variation in the dependent variable can be confounded by correlations among independent variables (i.e., collinearity). On the other hand, in DEA, where the purpose is to benchmark the relative performance based on actual observations rather than treat input variables as explanatory variables, high correlations among inputs is not a problem. In fact, DEA literature regards higher correlations as desirable. According to studies on DEA's robustness and potential for model misspecification, the researcher is advised to be cautious about the findings from an efficiency model where the correlations among inputs are low (Smith, 1997). Chapparo et al. (1999) also report similar findings where low correlations lead to increased dimensionality, and thus, a substantial drop in the performance of DEA estimates; the latter is measured by comparing rank correlations between DEA estimates and the so-called ‘true’ efficiency estimates obtained from large-scale Monte Carlo simulations based on Cobb–Douglas type production functions. Before leaving the section on data, we would like to address another potential concern for those who are more familiar with parametric tests. For example, most regression studies would normally re-scale variables to account for differences that may arise due to size of operations. Re-scaling variables by such methods as dividing with total assets also unifies the dimensions of different measures. Such matters are known in DEA literature under the headings of unit-invariance and translation-invariance. For example, unit-invariance implies freedom to choose variables measured in different dimensions (i.e., optimal solution is not affected by variables measured in different units); translation-invariance implies optimal solution is not affected by data transformations, where variable returns-to-scale (VRS) modeling can handle large variations in data. Similarly, the assumption of VRS means that efficiency estimates are not confounded by the impact of differences in scale of operations. We would like to state upfront that the DEA formulation used is unit- and translation-invariant, and assumes VRS (detailed in the next section), thus allaying any concerns a reader may hold. 3.3. Multi-period range-adjusted measure (MP-RAM) MP-RAM is based on data envelopment analysis (DEA). DEA is a non-parametric efficient frontier technique that computes a comparative ratio of weighted outputs to weighted inputs for the production in each unit, which is reported as the relative technical efficiency score. DEA operates on the condition of Pareto optimality for efficient production, where a bank is not efficient if an output can be raised without raising any of the inputs and without lowering any other output. Similarly, a bank is not efficient if an input can be decreased without decreasing any of the outputs and without increasing any other input (Charnes et al., 1981). DEA helps the decision maker wanting to know whether performance can be improved relative to observed behavior in a peer group. The relative efficiency score (a scalar value) is usually expressed as either a number between 0 and 1, or as a percentage. A bank with a score less than 1 is deemed inefficient. Those units on the efficient frontier determine the potential improvements (projections) for the various inefficient units off the frontier. DEA's ability to capture the interactions among multiple inputs and multiple outputs is its distinct advantage over traditional ratio analysis; because of this characteristic, some researchers refer to DEA as a relative multi-criteria decision-making technique. DEA's appeal as a benchmarking tool is succinctly captured in the words of Sherman and Zhu (2006, p. 302), “…studies of

Table 2 Pearson's r correlation matrix for input variables.

Dividends Retained earnings Debt funding Equity funding

Dividends

Retained earnings

Debt funding

Equity funding

1.00

0.50 1.00

0.78 0.41 1.00

0.86 0.34 0.81 1.00

Notes: In practical applications of data envelopment analysis, higher rather than lower correlations are to be expected between inputs because such variables are related to the scale of operations (Smith, 1997, p. 236).

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benchmarking practices with DEA have identified numerous sources of inefficiency in some of the most profitable firms…”. The reader can refer to Cooper et al. (2007), and Cooper et al. (2011) for a more indepth treatment of DEA. This study extends a model of DEA called RAM (range-adjusted measure) proposed by Cooper et al. (1999) to a multi-period framework. For example, Ward (2009) uses RAM to evaluate non-price competition in the UK mortgage market. Avkiran and Morita (2010a, 2010b) use RAM to benchmark Chinese bank performance from a multiple-stakeholder perspective, and predict Japanese bank stock performance with a composite efficiency metric, respectively. We would like to highlight that use of RAM enables the analysis to capture the potential non-radial reduction in inputs and non-radial increase in outputs. That is, the radial changes assumed in earlier DEA formulations are inappropriate unless proportionality can be justified based on the knowledge of production processes. Let us assume that the two key inputs in a bank profitability analysis are interest expense and noninterest expense and the two key outputs are interest income and non-interest income. This is a common approach and others who have used these variables include Miller and Noulas (1996), Bhattacharyya et al. (1997), Brockett et al. (1997), Leightner and Lovell (1998), Sturm and Williams (2004), and Avkiran and Thoraneenitiyan (2010). A bank that observes a policy of paying higher salaries to retain employees who excel in customer service will incur relatively more non-interest expense, but could compensate for this by paying lower interest rates on its deposit accounts (thus, incurring relatively less interest expense). The same bank may also choose to focus its attention on the sale of those services that generate more fee income than loans (thus, earning relatively more non-interest income). In the above examples, proportional projections assumed in the radial and input- or output-oriented DEA formulations cannot properly reflect the bank's operational decisions. On the other hand, estimating non-proportional projections through non-radial RAM is a more realistic representation of a complex business world. Furthermore, non-oriented RAM facilitates a more comprehensive evaluation where inefficiencies on the input as well as the output side of the modeled production are captured simultaneously. Capturing intertemporal behavior of variables using DEA was illustrated in the dynamic model used by Nemoto and Goto (2003), which is further extended to the RAM model in the current study. A specific bank, say, the j-th bank in a sample of n banks (j = 1, …, n), uses m inputs to produce s outputs. In computation of RAM, xijt and yrjt are the i-th input (i = 1, … , m) and the r-th output (r = 1, … , s) of the j-th bank in period t (t = 1…T), respectively. In addition to these variables, we introduce a special variable, kljt , which can be the l-th output (l = 1, … , p) of the j-th bank (j = 1, … , n) in period t, or the l-th input in period t + 1. That is, these intermediate products exit the corporate production activity as outputs from a given period, only to become inputs to the following period. Such variables are optimized across the study period and produce a multi-period linkage among periodic financial decisions (refer back to Fig. 2). The subscript o stands for a specific bank whose performance is currently examined by RAM. y Inefficiencies (ditx , dl,k t − 1and drt ) belong to the i-th input, l-th intermediate product and r-th output, x k y respectively. Rit, Rl, t − 1 and Rrt represent the ranges for endogenous inputs, intermediate products, and the exogenous output, respectively. The scalar (λjt), often known as a structural or intensity variable, establishes linkages among banks in a data space. The study specifies the multi-period RAM model as follows: T 1 ∑ Max: T ðm + p + sÞ t = 1

k

x y p s dl;t−1 d d ∑ itx + ∑ k + ∑ rt y R R R r=1 i=1 l=1 it rt l;t−1 m

! ð1Þ

(The objective function that maximizes average range-adjusted slacks across T periods) n

s:t:

x

∑ xijt λjt + diot = xiot

j=1

i = 1; …; m; t = 1; …; T;

ð1aÞ

(Constraints of endogenous inputs, D and E: observations in these two inputs for each bank are connected with the optimized weight lambda to construct the production frontier) n

k

∑ klj;t−1 λjt + dlo;t−1 = klo;t−1

j=1

l = 1; …; p; t = 1; …; T;

ð1bÞ

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(Constraints of endogenous intermediate products, Div and Re: these variables act as inputs from a bank's production system) n

k

∑ kljt λjt −dlot = klot

l = 1; …; p; t = 1; …; T−1;

j=1

ð1cÞ

(Constraints of endogenous intermediate products, Div and Re: in this instance, these variables act as inputs from a bank's production system) n

y

∑ yrjt λjt −drot = yrot

r = 1; …; s; t = 1; …; T;

j=1

ð1dÞ

(Constraint of the exogenous output, TRI) n

∑ λjt = 1; t = 1; …; T;

λjt ≥ 0; j = 1; …; n; t = 1; …; T;

j=1

ð1eÞ

(Constraint for variable returns-to-scale technology and non-negative constraint for lambda in each bank and period) x

dit ≥ 0; i = 1; …; m;

t = 1; …; T;

ð1fÞ

(Non-negative constraint for each slack in each period) k

dl;t−1 ≥ 0; l = 1; …; p;

t = 1; …; T;

ð1gÞ

(Non-negative constraint for each slack in each period) y

drt ≥ 0;

r = 1; …; s;

t = 1; …; T:

ð1hÞ

(Non-negative constraint for each slack in each period) where, Rxit = xit −x it ði = 1; 2; ⋯; mÞ k

Rl;t−1 = kl;t−1 −k l;t−1 ðl = 1; 2; ⋯; pÞ Ryrt = yrt −y rt ðr = 1; 2; ⋯; sÞ n o n o x it = max xijt ; x it = min xijt ði = 1; 2; ⋯; mÞ; ðt = 1; 2; …; TÞ; j j n o n o k l;t−1 = max klj;t−1 ; k l;t−1 = min klj;t−1 ðl = 1; 2; ⋯; pÞ; ðt = 1; 2; …; T Þ; j

j

y rt

n o n o = max yrjt ; y rt = min yrjt ðr = 1; 2; ⋯; sÞ; ðt = 1; 2; …; TÞ; j

j

and exogenous inputs are omitted because they are fixed. The above is an extension of the conventional RAM to multi-period optimization under variable returns-toscale production. The objective function maximizes average range-adjusted inefficiencies across all periods. Constraints also extend to the multi-period framework. Hence, the objective function is maximized to meet all constraints regarding the endogenous inputs, the endogenous intermediate products and the exogenous output. Eq. (1) assumes a production frontier for each period so that inefficiencies are defined in each year. In summary, Eq. (1) generates a single efficiency score per bank for the entire study period computed as 1 minus the value of the objective function. This setup facilitates an overall multi-period efficiency score that captures the intertemporal linkages among yearly financial decisions. In other words, the study acknowledges that in the real business world management would normally make strategic decisions that cover multiple periods. In measuring inefficiencies, the approach establishes a link between the dividend policy of a given period and the funding decisions in the following period. This makes the current paper's efficiency measurement different from traditional static DEA models that provide unrelated annual

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efficiency scores. The objective function maximizes the average of the accumulated inefficiencies across the study period and reports an efficiency score that reflects a series of consecutive financial decisions. An analyst can also observe the annual changes in inefficiency by measuring each period's deviation of inputs

Table 3 Study sample ranked in descending order of overall efficiency for the period 1998–2007. Bank#

Bank name

Overall efficiency score

12 45 14 46 6 36 15 32 19 9 51 37 25 10 29 26 50 23 47 42 35 1 8 30 22 44 21 3 33 24 48 41 4 11 52 27 16 2 40 20 5 34 13 28 31 17 7 18 49 43 38 39

Bank of Yokohama Shimizu Bank Chikuho Bank Shizuoka Bank Bank of Iwate Minami-Npn.Bk. Chugoku Bank Kagawa Bank Fukui Bank Bank of Okinawa Yamagata Bank Miyazaki Bank Hokkoku Bank Bank of Ryukyus Iyo Bank Hokuetsu Bank Tomato Bank Higo Bank Suruga Bank San-In Godo Bank Michinoku Bank 77 Bank Bank of Nagoya Joyo Bank Higashi Nippon Bank Shikoku Bank Hachijuni Bank Akita Bank Kagoshima Bank Hiroshima Bank Tochigi Bank Oita Bank Aomori Bank Bank of Saga Yamanashi Chuo Bk. Hyakugo Bank Daisan Bank Aichi Bank Ogaki Kyoritsu Bank Gunma Bank Awa Bank Keiyo Bank Chiba Bank Hyakujushi Bank Juroku Bank Daishi Bank Bank of Kyoto Eighteenth Bank Toho Bank Shiga Bank Musashino Bank Nanto Bank

1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 0.99699 0.99621 0.99585 0.99498 0.99413 0.99353 0.99165 0.99119 0.98972 0.98937 0.98920 0.98740 0.98647 0.98520 0.97763 0.97350 0.97317 0.97217 0.97177 0.97145 0.96939 0.96926 0.96738 0.96696 0.96673 0.96596 0.96573 0.96381 0.96380 0.95803 0.95552 0.95151 0.95109 0.95090 0.94595 0.93703 0.93437 0.93234 0.92976 0.92861 0.92755 0.92302 0.90189 0.89382 0.88945

Notes: The small number of seven efficient banks in a sample of fifty-two indicates a discriminating relative performance model. The small range of scores, 1.00000–0.88945, suggests a homogeneous sample as expected with Japanese regional banks. Frequency of emulation by others (available from authors) enables further sorting among the efficient banks whose ranks would otherwise be tied.

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and outputs from the benchmark levels in the sample (i.e., inefficiencies). Next, the multi-period RAM model specified in Eq. (1) based on the performance model outlined in Fig. 2 tests the sample of Japanese regional banks.

4. Results and discussion 4.1. Overall efficiencies, annual inefficiencies and banks for closer scrutiny Table 3 lists the study sample of banks ranked in descending order based on the MP-RAM overall efficiency scores. The small number of seven efficient banks, that is, benchmark banks, in a sample of fiftytwo banks indicates a discriminating relative performance model. The small range of scores, 1.00000– 0.88945, suggests a homogeneous sample as one would expect with Japanese regional banks (see Section 3.1). 7 Coefficients of variation on the size proxy, total assets (not shown in tables), fall in the narrow range of 0.6229–0.6465 across the study period, thus lending further support to the contention of a homogenous sample. DEA is particularly suited to discerning the performance of units in a homogeneous sample where each unit is benchmarked against the efficient frontier defined by the best in that peer group. 8 Next, the study reports the observed annual inefficiencies across the study period of 1998–2007. Table 4 shows the annual ranking of inefficient banks in descending order on the sum of range-adjusted inefficiencies from the five variables in the performance model. This study focuses on the sum of inefficiencies for a bank in a given year and compares it against other banks in the same year. As per definition in Eq. (1), the seven overall efficient banks identified in Table 3 are also efficient in every year (not shown in Table 4). A quick inspection of Table 4 reveals more inefficient banks in the earlier and later years of the study period. 2003–2007 represents a period of steadily rising economic activity in Japan; the level of economic activity can be seen in the coincident index from the Cabinet Office of the Government of Japan (http:// www.esri.cao.go.jp/en/stat/di/di-e.html). Table 4 suggests an ostensibly counter-intuitive rise in inefficiency accompanied by a fall in the number of efficient banks for 2003–2007. One possible explanation for this observation is a growing gap between a small group of banks in a better position to take advantage of increased economic activity and the rest that are less well placed. That is, in the recovery period, the group of stronger banks is improving their production processes and thus, putting a greater distance between themselves and the others by pushing out the efficient frontier. Recalling the motivation identified in the very first paragraph in the introduction, the study makes further use of Table 4 to demonstrate how industry watchers can identify those banks less deserving of bailout funds. Here, we show an easy-to-implement approach without prescribing cut-offs. Banks below the dotted lines in Table 4 represent for each year those banks that show above-average sum of inefficiencies (compare with the last row of numbers). From within these sub-groups, we then select those banks that show above-average inefficiencies for at least four years (an arbitrary choice) but not necessarily in consecutive years. Table 5 ranks the eleven inefficient banks thus identified based on the descending order of dividend inefficiencies. The shortlist shown in Table 5 corresponds to Keiyo Bank, that is, bank #34, and all the others below Keiyo Bank first shown in Table 3 of overall efficiency scores. In terms of inefficient allocation (overuse) of dividends, Chiba Bank, Hyakujushi Bank, Daishi Bank and Juroku Bank stand out from the rest with above group average inefficiencies. Regulators intending to extend bailout funds would be advised to target these four banks for much closer scrutiny. In other words, these banks are paying more dividends than they need to in comparison to their efficient peers who are able to generate the same or better shareholder returns on less or same dividends respectively (Pareto optimality). An analyst can also bring to bear other short-listing 7 This small range can also be attributed to the fact that the overall efficiency score is a scalar value that summarizes performance over a ten-year study period covering recessionary as well as recovery periods, thus leading to more subdued overall variations in scores. 8 In response to a suggestion by one of the anonymous reviewers, we replicate Table 3 by averaging static RAM scores across the study period in an effort to expedite a comparison with the dynamic MP-RAM scores (i.e., overall efficiency scores). As anticipated, there is no significant correlation between dynamic RAM and static RAM scores. Details are available from the authors.

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Table 4 Annual inefficiencies for the Japanese regional banks. 199899 B#

SS

38 8 2 43 9 28 5 29 17 41 51 31 44 47 4 40 33 39 35 49 3 21 18 11 7 20 52

3.26 10.40 11.68 13.81 14.69 16.38 20.23 20.77 21.21 22.14 22.60 22.79 29.41 33.32 34.67 42.29 43.30 47.10 49.52 58.16 60.21 60.44 60.44 61.61 67.73 72.62 75.06

Total adjusted inefficiencies 995.8 for the 4 period Annual 36.88 mean SS

200001

199900 B # 27 16 29 35 32 52 8 22 33 40 11 43 41 49 34 2 44 28 17 20 5 13 38 7 21 31 18 39

SS 1.45 3.36 3.78 4.08 13.53 15.46 19.09 22.99 24.17 25.78 30.28 33.09 35.37 35.55 37.43 38.83 41.86 53.57 55.11 58.49 60.06 60.42 64.53 64.56 68.05 70.59 70.65 76.79

1088.9 3 38.89

B # 29 35 49 4 44 26 11 40 27 5 52 16 17 31 28 7 2 43 22 38 34 13 39

SS 3.13 3.54 4.16 6.49 9.64 10.79 12.23 14.03 14.57 16.74 17.28 18.48 25.41 27.01 30.12 34.75 36.62 42.19 45.28 51.80 52.28 53.90 75.49

605.9 5 26.34

200102 B # 5 35 29 27 33 49 2 4 28 40 18 17 7 31 41 38 43 13

SS 5.94 9.45 11.98 22.12 24.35 37.52 45.17 48.57 48.99 55.16 58.98 60.00 63.08 68.45 70.06 81.32 87.23 96.70

895.0 5 49.73

200203 B # 33 9 5 49 27 40 38 8 18 2 17 20 7 43 13

SS 2.88 4.00 16.16 23.19 26.79 30.31 39.22 42.03 42.59 51.27 53.71 56.11 67.56 67.73 72.37

595.9 2 39.73

200304 B # 20 52 5 3 7 17 16 27 18 48 8 39 43 49 34 38

SS 1.98 5.17 16.49 22.64 23.57 23.86 29.91 33.78 36.73 38.51 47.75 54.55 55.21 56.57 76.31 81.15

604.1 6 37.76

200405 B # 33 22 52 5 47 24 17 23 3 48 4 43 31 27 49 28 38 39 16

SS 4.05 7.88 12.82 13.26 16.59 19.98 20.16 21.81 26.19 27.91 30.67 31.03 35.28 36.89 55.24 56.63 59.68 67.79 68.83

612.6 9 32.25

200607

200506 B # 11 52 25 23 3 30 49 22 42 1 27 4 17 34 31 33 5 28 43 16 38 24 39

SS 3.23 6.43 7.72 9.63 10.96 17.88 19.28 19.95 21.13 25.79 27.31 29.54 35.57 35.66 38.84 39.04 42.22 47.36 50.77 51.32 52.60 76.78 80.91

749.9 2 32.61

B # 33 4 47 2 16 19 23 3 17 25 41 37 22 5 52 20 26 10 42 31 34 28 38 44 11 50 24 40 18 49 43 1 48 39 30

SS 0.55 3.24 6.79 16.57 16.96 17.08 17.15 17.73 21.06 21.41 22.16 26.43 29.15 29.85 30.65 30.88 35.50 37.58 39.76 41.50 41.53 42.26 44.24 46.15 46.90 47.82 50.04 50.63 56.66 56.75 60.45 74.88 82.26 94.85 102.86

1360.2 6 38.87

Notes: Table 4 reveals more inefficient banks in the earlier and later years of the study period. Banks below the dotted lines represent for each year those banks that show above-average sum of inefficiencies (compare with the last row of numbers). B#, bank number; SS, sum of range-adjusted inefficiencies across the five variables in the performance model. Table 4 excludes efficient banks.

criteria by observing the inefficiencies in other variables of the performance model shown in Table 5 (e.g., secondary sorting on equity funding).

4.2. Inefficiencies in the performance model variables and their associations with non-performing loans Measurement of technical inefficiencies in the utilization of inputs or production of outputs indicates to management the potential performance improvements. DEA, as a multi-criteria decision-making

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Table 5 Eleven shortlisted inefficient banks ranked on sum of range-adjusted dividend inefficiencies in descending order, 1998–2007.

Inefficient bank and corresponding inefficiencies Chiba Bank Hyakujushi Bank Daishi Bank Juroku Bank Shiga Bank Bank of Kyoto Nanto Bank Keiyo Bank Toho Bank Musashino Bank Eighteenth Bank Group mean

Dividends

Retained earnings

Debt funding

Equity funding

ΔTRIa

21.01 15.12 14.65 12.54 8.79 7.23 5.39 4.92 4.76 4.14 0.00 8.96

11.28 39.39 39.87 36.72 36.29 17.30 38.28 9.68 25.08 52.88 19.15 29.63

71.97 35.06 89.38 57.79 110.70 92.81 130.37 11.03 54.00 32.10 12.58 63.44

119.73 17.58 3.51 16.86 24.85 0.00 7.25 67.50 0.88 50.68 18.59 29.77

59.39 188.17 168.67 180.54 260.87 203.91 316.18 150.09 261.69 337.99 275.74 218.48

Note: Banks listed in Table 5 show above-average inefficiencies for at least four years in Table 4. In terms of inefficient allocation of dividends, that is, overuse, Chiba Bank, Hyakujushi Bank, Daishi Bank and Juroku Bank are above the group mean. Regulators intending to extend bailout funds are encouraged to vet these four banks more closely. a ΔTRI: Annual percent change in total return index.

technique is eminently qualified for the initial exploration that can guide management toward more indepth analysis. In Fig. 3, readers can quickly see considerable room for improvement in the sample in shareholder returns (measured by the change in TRI, total return index), as well as debt and equity funding. More specifically, the total return index shows higher inefficiencies compared to the other variables in the model. In the conceptual framework, TRI is the only exogenous output, which means management does not have direct control over this variable. Ultimately, the capital markets judge the discretionary, intertwined managerial decisions on investments (asset quality), dividends and external funding utilized, and the TRI captures this judgment. Thus, the inefficiencies in the endogenous variables are of more immediate interest to management practicing benchmarking. 9 While the analysis reveals mostly stable inefficiencies for debt and equity funding, one can also see a steep rise in 2006–2007 as the recent financial crisis began (see Fig. 3). This observation partially reflects the varied actions of those banks with troubled balance sheets seeking external funding, and others attempting to exploit an environment of high economic activity that preceded the recent financial crisis. Overall low dividend inefficiencies (except for 2001–2002) observed in Fig. 3, once again suggest a preference for stable dividends among the JRBs (see research question 1 in Section 2.3). Nevertheless, according to the Bank of Japan (2008), the period of 1995–2003, which covers the earlier part of the full study period (1998–2007), coincides with net losses for regional banks, where non-performing loans were also at high levels. Thus, the implication is that the majority of banks were able to manage their dividend policies at a time of limited cash flows. At the outset, we pointed out that one of the motivations for studying Japanese regional banks is their relatively higher proportion of non-performing loans (NPL). We now proceed to investigate with simple linear regression the extent variation in NPL ratio (i.e., non-performing loans standardized by total assets) can be explained by range-adjusted inefficiencies identified through MP-RAM. We allow a twelve-month lag between input and output inefficiencies — essentially arguing that financial decisions flowing from dividend policies shape shareholder returns, as well as give rise to non-performing loans. Table 6 reports the key regression results for the full study period (1998–2007), as well as for the years of recession therein (i.e., 1998–2003).

9 Following a suggestion by one of the anonymous reviewers, we investigate rank correlations among different inefficiencies. Findings indicate that all inefficiencies are positively correlated with each other at the significance level of 5%. That is, there is preliminary evidence to indicate that inefficient use of one input is generally associated with inefficient use of other inputs, and may subsequently lead to a more inefficient output.

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18.000

Total Return Index

16.000 14.000 12.000 10.000 8.000 6.000 4.000 2.000 0.000

1998- 1999- 2000- 2001- 2002- 2003- 2004- 2005- 20061999 2000 2001 2002 2003 2004 2005 2006 2007

1.600

Retained Earnings

1.400

Dividens

1.200 1.000 0.800 0.600 0.400 0.200 0.000

4.500 4.000 3.500 3.000 2.500 2.000 1.500 1.000 0.500 0.000 1998- 1999- 2000- 2001- 2002- 2003- 2004- 2005- 20061999 2000 2001 2002 2003 2004 2005 2006 2007

7.000

3.500

6.000

3.000

Equity Funding

Debt Funding

1998- 1999- 2000- 2001- 2002- 2003- 2004- 2005- 20061999 2000 2001 2002 2003 2004 2005 2006 2007

5.000 4.000 3.000 2.000

2.500 2.000 1.500 1.000 0.500

1.000

0.000

0.000 1998- 1999- 2000- 2001- 2002- 2003- 2004- 2005- 20061999 2000 2001 2002 2003 2004 2005 2006 2007

1998- 1999- 2000- 2001- 2002- 2003- 2004- 2005- 20061999 2000 2001 2002 2003 2004 2005 2006 2007

Fig. 3. Annual average of banks' inefficiencies for each variable. Inefficiencies are adjusted by the annual variable range in the sample. Measurement of inefficiencies in the employment of inputs or generation of outputs identifies potential performance improvements. There is considerable room for improvement in the sample in shareholder returns (measured by annual percent change in total return index), as well as debt and equity funding.

While the R-squared values are generally low, we offer some comments on the coefficients. The coefficients for TRI inefficiencies are statistically significant and negative in both instances, where the coefficient is less significant for the recession period. At first glance, the negative sign of the coefficients may appear counter-intuitive because it suggests a reduction of TRI inefficiencies as non-performing loans rise. This observation can be explained by acknowledging the troubled period under study when government and regulatory authorities in Japan would have required banks to lend to risky customers in order to stimulate the economy. It can also be seen as part of the main bank system that would have made it difficult for banks to refuse lending. Recalling the section dedicated to the study setting, a third possible explanation is the large proportion of JRBs' loan portfolios tied to financing local governments; such business relationships are bound to impose greater political limitations on operational decision-making. These three external forces would have pushed the JRBs to become even more homogeneous in their operations, thus reducing the observed relative inefficiencies. In short, higher NPL would have been regarded as the cost of doing business when the focus is on the wider economy. This phenomenon can also be seen in China, probably in a more amplified manner, where a 20% plus NPL ratio was not unusual (see KPMG, 2007) because regulators prefer high growth in economic activity, thus maintaining employment levels and social and political cohesion.

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Table 6 Standardized coefficients and significance levels from regressions of NPL ratioa on range-adjusted inefficiencies. Dependent variable: NPL ratio

Independent variables are inefficiencies in

Period

[1998–07 1998–03] [1998–07 1998–03] [1998–07 1998–03] [1998–07 1998–03] [1998–07 1998–03]

Dividends

Coefficient 0.024 Significance 0.611 R2 0.001

Retained earnings

0.049 0.391 0.002

− 0.138 0.003c 0.019

− 0.191 0.001c 0.036

Debt

− 0.126 0.006c 0.016

ΔTRI

Equity

− 0.033 0.567 0.001

0.050 0.280 0.003

0.131 0.021d 0.017

b

− 0.124 0.007c 0.015

− 0.128 0.024d 0.016

Notes: Fuller details on regressions are available from authors upon request. Results are reported for the full study period, as well as the recession period of 1998–2003. a NPL ratio: Ratio of non-performing loans to total assets. b ΔTRI: Annual percent change in total return index. c Significant at 1%. d Significant at 5%.

Regression coefficients for debt funding inefficiencies and NPL ratio are negative (see Table 6) and only significant for the full study period (see research question 5). We suspect the forces explained in the previous paragraph are also at play here. For most regional banks, debt funding represents their efforts in collecting deposits in a country where the biggest competitor vying for family savings was Japan Post for the period under study (handled by Japan Post Bank since privatization in October 2007). Regression analysis suggests an insignificant coefficient for equity inefficiencies across the full study period, but a positive and significant coefficient for the recession years (see research question 6). This observation suggests that when non-performing loans are particularly high, we can expect higher technical inefficiencies in employment of equity to fund operations. Inefficiencies in retained earnings are reasonably stable for the study period (see Fig. 3) and regression coefficients across both periods are significant at the 1% level. In answer to research question 4, Japanese regional banks' non-performing loans appear to be negatively associated with excessive use of retained earnings. Regression analysis with dividends and NPL indicates insignificant positive coefficients for both periods shown in Table 6. This answers research question 3 by highlighting the lack of association between NPL and inefficient or excessive use of dividends. That is, banks are not relying on excessive use of dividends when their non-performing loans are on the rise, instead preferring practices befitting austerity. Before leaving the investigation of possible effects of inefficiencies in various bank performance measures on NPL, we pause to reflect on research question 7 regarding capital adequacy. Regressing CAR on NPL ratio using the available data (2000–2006) reveals a significant standardized coefficient of − 0.421 (.000) and an R-squared value of 17.8%, suggesting capital may suffer when non-performing loans rise (not shown in Table 6). This is an intuitive empirical finding and lends support to one of the key concerns that has led to the recently accepted Basel III Accord. In research question 2 we enquired whether dividends would be associated with inefficient or excessive use of equity; this position was taken based on Bessler and Nohel's (1996) observation that troubled US banks of early 1980s continued to pay dividends often by issuing new equity. Regressing dividends on equity inefficiencies indicates an insignificant association (a standardized coefficient of 0.063 with a significance level of 17.6%). That is, preliminary findings show no clear evidence of Japanese regional banks using equity to maintain stable dividends even when the banks may be navigating troubled economic times with reduced profitability. However, given the mixed economic times in the ten-year study period, we repeat the above regression for the recession years of 1998–2003 when JRBs are more likely to rely on equity to maintain dividend levels. Results now indicate a low but statistically significant positive coefficient (0.117 with a significance level of 4%) and an equally low R-squared value of 1.4%. Thus, we can, at best, claim to have found a weak relationship in seeking an answer to research question 2. 4.3. Comparing efficient versus inefficient banks across the good and bad economic years Table 7 shows the actual levels of output and input variables in the bank financial performance model. The differences between the shareholder returns measured by the total return index for 2006 (a point of

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high economic activity) and 1999 (the point of lowest economic activity in the study period), are in general, positive. This observation confirms that banks are able to generate higher shareholder returns in good economic times. The variation in this behavior is not discernible when the study compares the group of seven benchmark (efficient) banks to the three most inefficient banks in the sample (see group mean % differences). For brevity, the rest of the comparative analysis in Table 7 continues to use the three most inefficient banks, whose scores are very close to each other. Regarding dividends, we observe a similar positive but stronger difference between the best and worst economic years in the study period. This difference is more pronounced among the benchmark banks with an average difference of 107.08%, which appear to be increasing their dividends by a larger proportion, compared to the inefficient banks with an average difference of 28.84%. The latter observation suggests that efficient banks are more likely to share the profits of good economic times with their shareholders. On the

Table 7 Comparing the benchmark and inefficient banks in good and bad economic times on the actual levels of variables in the model. ΔTRI Benchmark banksa Bank of Yokohama (75)

Dividends Retained earnings Debt funding Equity funding (×000,000) (×000,000) (×000,000) (×000,000)

Best economic yearb 1.4819 12,534.20 % difference 58.70% 362.35% Worst economic year 0.9338 2710.99 Shimizu Bank (43) Best economic year 1.0362 298.43 % difference 3.08% 54.12% Worst economic year 1.0052 193.64 Chikuho Bank (40) Best economic year 0.9766 198.96 % difference − 2.33% 105.49% Worst economic year 0.9999 96.82 Shizuoka Bank (32) Best economic year 1.1122 4078.59 % difference 13.41% 75.52% Worst economic year 0.9807 2323.71 Bank of Iwate (31) Best economic year 1.1739 696.34 % difference 48.29% 43.84% Worst economic year 0.7916 484.11 Minami-Nippon Bk. (26) Best economic year 0.9891 198.96 % difference − 2.64% 2.75% Worst economic year 1.0159 193.64 Chugoku Bank (24) Best economic year 1.3508 1392.69 % difference 47.27% 105.49% Worst economic year 0.9172 677.75 Group mean % difference 23.68% 107.08% c Three most inefficient banks Shiga Bank (0.902) Best economic year 1.252 795.82 % difference 21.05% 36.99% Worst economic year 1.0343 580.93 Musashino Bank (0.894) Best economic year 1.3964 994.78 % difference 31.23% 46.78% Worst economic year 1.0641 677.75 Nanto Bank (0.889) Best economic year 1.1585 696.34 % difference 18.60% 2.74% Worst economic year 0.9768 677.75 Group mean % difference 23.63% 28.84%

1754.23 49.34% 1174.68 1104.64 − 9.61% 1222.12 1168.30 0.12% 1166.93 1529.41 2.76% 1488.38 1256.84 0.45% 1251.17 1168.30 − 0.21% 1170.81 1292.65 − 4.38% 1351.86 5.50%

10,005.84 7.70% 9290.17 1219.46 13.51% 1074.33 521.8 16.88% 446.44 7542.47 9.66% 6878.07 2125.62 7.86% 1970.79 611.58 − 0.81% 616.56 5170.75 15.14% 4490.95 9.99%

390.53 22.56% 318.64 13.87 2.36% 13.55 13.69 3.24% 13.26 145.02 2.80% 141.07 16.81 2.75% 16.36 15.44 2.86% 15.01 21.32 2.90% 20.72 5.64%

1267.78 − 4.72% 1330.56 1268.77 2.68% 1235.68 1226.99 1.52% 1208.57 − 0.17%

3759.90 15.96% 3242.44 3066.99 32.72% 2310.83 4329.30 26.15% 3431.92 24.94%

56.74 28.23% 44.25 84.74 84.66% 45.89 47.82 13.80% 42.02 42.23%

Notes: ΔTRI stands for annual percent change in total return index. Differences between the shareholder returns measured by the total return index for 2006 (a point of high economic activity) and 1999 (the point of lowest economic activity in the study period), are in general, positive. Dividends show positive but stronger difference between the best and worst economic years in the study period. Furthermore, this difference is more pronounced among the benchmark banks. a These are the global leaders in the sample (i.e., banks that are efficient in every year) sorted in descending order of how many inefficient banks emulated them in calculation of scores (see the so-called reference set frequencies shown in brackets). b According to the coincident index from the Cabinet Office of the Government of Japan, year 1999 was the worst year (in the study period of 1998–2007) in terms of economic activity, and 2007 was the best year. For the best year we choose the second best year 2006 instead because 2007 is also the start of the recent financial crisis. c Overall efficiency scores are shown in brackets next to the inefficient bank name.

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other hand, retained earnings show a mixture of positive and negative differences among both efficient and inefficient banks. The variation within the benchmark group, that is, the efficient banks in the sample, is greater. With one exception, namely, the efficient Minami Nippon-Bank, all debt and equity funding differences are positive, reflecting the increased funding used during times of high economic activity. The Minami Nippon-Bank, which is showing a small drop in its level of debt funding for the best economic year, also has lower retained earnings and shareholder returns. The bank is able to maintain a small rise in its dividends, underscoring the importance given to paying dividends. Comparing the benchmark banks against the inefficient banks on external funding reveals larger differences within the latter group, suggesting that inefficient banks are more reliant on external funding when they want to take advantage of increased economic activity. The findings in the current sub-section appear to follow common-sense expectations, and thus, highlight the appropriateness of DEA in discerning between efficient and inefficient banks. A quick search in Web of Science data base indicates 162 publications (as at 20 September 2010) that have applied DEA in banking studies, although the current study is the first to bring this multi-criteria decision-making technique to bear on dividend policies and associated financing decisions of banks. 5. Concluding remarks and future directions This paper studies the financial performance of the Japanese regional banks for the period 1998–2007. We undertake a relative evaluation comparing the impact of a bank's dividend policy and associated financing decisions on shareholder returns against the observed performances of the best-practice peer banks. It is demonstrated that the insight thus gained can help identify banks that may be less deserving of bailout funds compared to more efficiently managed banks. The study also investigates the differences in the observed levels of dividends, retained earnings, external funding and shareholder returns across the good and bad economic times. As Japanese firms gradually move toward aligning dividends with profits, the current paper lays the foundation for further studies in bank dividend policies and their associations with shareholder returns. The overall multi-period efficiency score provided by the new approach captures the intertemporal linkages among yearly financial decisions. In other words, the analysis reflects the real-world of business where firms normally optimize their decisions in a multi-period framework. Thus, this paper's efficiency measurement is an improvement over traditional static analyses. Analysis based on the multi-period range-adjusted measure (MP-RAM) of inefficiencies reveals a substantial room for adjusting levels of debt funding and equity funding, and potential to improve shareholder returns. The deployment of dividends even with the otherwise inefficient banks shows little inefficiency, which reinforces the literature-based expectation of stable dividends across the Japanese regional banking sector for 1998–2007. In the past, the Japanese Ministry of Finance and the Financial Services Agency have encouraged a stable dividend policy (as part of stable business relationships) by issuing regulatory edicts designed to rectify unusually high or low dividends, or absence thereof. Banks (efficient or otherwise) are able to generate higher shareholder returns in good economic times. On the other hand, comparing efficient versus inefficient banks indicates that efficient banks are more likely to share the profits of good economic times in the form of dividends. Evidence points to inefficient banks wanting to take advantage of increased economic activity by relying more on external funding because they are more likely to have depleted internal funding sources. Technical inefficiencies revealed through peer benchmarking provide a reason for regulators to proceed with more caution in allocating taxpayers' monies to inefficient banks. An immediate application of the paper's methodology following the recent GFC is in identifying those banks more (less) efficient in financial management, which in turn, could help policy-makers better determine deserving (undeserving) allocation of bailout funds. For example, a bank with a history of efficient operations, whose balance sheet currently carries toxic assets by virtue of exposure to a failed investment bank, could be a candidate for bailout funds. Similarly, the regulators ought to give a bank that has been operating inefficiently for a number of years a much lower priority to receive assistance from taxpayers. We admit that granting of bailout funds can be a complex decision involving politics, and governments may also be tempted to inject capital into inefficient banks that can demonstrate positive net present value

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opportunities. The analysis illustrated in the current study provides a method for monitoring bank financial performance that can become part of the toolkit for central banks that normally undertake a fine balancing act between ensuring economic growth and maintaining soundness of the banking sector. The relative nature of the analysis which relies on multidimensional benchmarking based on actual observations among a homogeneous group of peers is another desirable feature of this tool that can mute arguments by those banks who may seek special consideration. Given the exploratory nature of DEA, findings in this study ought to be treated as starting points for more in-depth investigations. Future directions include re-examining bank dividend policies post-2007 to find out if Japanese banks are in fact moving away from stable dividends to payouts more in line with profits. In a few years, studying the impact of the recent GFC on bank dividend policies would no doubt provide further interesting avenues for research. Should new banking studies clearly demonstrate residual funding decisions similar to that observed in non-banking literature, this would open the way for debt and/ or equity to be treated as non-discretionary endogenous inputs, although such analysis would reduce the scope for benchmarking. The preliminary associations between non-performing loans and various variables reported in this study also warrant more in-depth studies to test such relationships with new data sets — preferably data that are less homogenous. Other possible variations to the current study's research design include analyzing a period shorter than ten years in estimating the MP-RAM overall efficiency score. Extensions of the study may also include: a comprehensive comparison between relative efficiency analysis and more traditional measures of bank efficiency, such as cost-to-income ratio and intermediation ratio, thus building more bridges between different approaches (see Avkiran, 2011 for a recent comparison in the context of Chinese banks); use of multivariate parametric methods to further explore whether the inefficient use of one input generally implies inefficient use of other inputs and subsequently leads to more inefficient output production; use of price changes instead of shareholder returns as the output variable; investigating whether most Japanese regional banks delayed introducing performance-linked dividends until the economic recovery seen around 2006; and, a comparison of inefficiency of Japanese regional banks to those of major banks and other firms from different industries. 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