Abstract

This paper provides substantive rationale and empirical arguments both for and against functional regulation of the banking industry. It examines the cross-sectional and time-serial relationships of two types of international banks' response variables -- capital cushion and return performance signaling behavior -- and their explanatory variables based on functional and prudential regulatory determinants. Contrary to conventional wisdom that prudential regulation is effective in preventing banks from being undercapitalized thereby susceptible to bank runs, the study finds that functional regulation is more relevant to capital signaling than is prudential regulation. Based upon twelve groups of seventy international banks classified by countries spanning over a decade from 1988 to 1997, most functional parameters are statistically significant in terms of cross-sectional OLS with both types of signaling behavior, while there is a statistical significance between the time-series prudential parameters and capital signaling behavior. It can be concluded that, as international banks are faced with increasing competitive pressures to shift their functional emphases from traditional liquidity provisions and payments transfer to innovative financial services and risk management, prudential regulation is less likely to be an efficient and effective means to motivate them to convey hidden information to the markets. The corollary is true that functional regulation could be used instead to induce international banks to maintain safe and sound capital level. However, it is found that international banks' risk-adjusted performance signaling behavior can still be effectively promoted through prudential regulation.

Introduction

Research Problems

The research problems for this paper are centered on the recent episodic financial meltdown in Southeast Asia, which triggered a series of global currency and financial crises during the second half of 1997 starting from the devaluation of the baht in Thailand until the recent turn for the real in Brazil in early 1999. The major cause of these crises had been ascribed to the systemic instability in domestic financial markets whereby commercial banks encountered substantial losses from defaults on foreign currency-denominated loans creating an abrupt shortage of foreign exchange reserves as well as liquidity in the domestic economy. Failure of such financial intermediaries not only transmitted a cross-border contagion effect to the rest of the world among various money and capital markets, but also spilled negative externalities to undermine the real sectors of the economy.

The fragility of banks operating domestically and internationally can be predicated on either mismanagement or misfortune in their increasingly opaque and illiquid asset-liability profiles based on sophisticated risk management strategies and financial engineering techniques. Mismanagement in the banks' asset and liability portfolios involves imprudent lending and investment decisions and excessive risk-taking without adequate internal risk control. Most banks have functional motives and regulatory incentives to conceal their risk management activities from outsiders because of the existence of asymmetric and imperfect information. Economics of differential information is thus one of the prime concerns of international banking regulators to optimize the trade-off between global financial stability and the promotion of efficient and competitive systems of financial innovation. The domain of systemic crisis prevention is in a better understanding of signaling behavior of commercial banks, which allows the markets and general depositors to differentiate between well- and ill-managed banks.

Current and Alternative Solutions

Following the collapse of banks in the various countries during the last two decades, many questions have been raised as to how effective the current regulatory systems are in reducing the banking industry’s fragility and in preventing systemic instability. In the past until recently, many regulatory agencies at both national and international levels have resorted to prudential regulation which mandates banks to maintain a minimum level of capital to cushion their inherent risks of loan defaults and market price volatility. The implications of prudential regulation are on the "fiduciary" relationships between the banks' shareholders and the general depositors in terms of potential problems of conflict of interest within the banking industry. Yet, prudential regulation has become more costly and less effective than regulation through market forces, which focus on the "agency" relationships between the banks' management and the shareholders. Some market-based (private regulation) and model-based (functional regulation) frameworks, which will be discussed later in detail, have been proposed as the alternatives to prudential regulation. These alternative frameworks, while yielding much merit, are relatively difficult to practice and possess several shortcomings.

The motivation for this research is based on an empirical puzzle that banks in both industrialized and emerging countries with seemingly strong capital base become more fragile and vulnerable to systemic instability despite they are all subject to very strict prudential regulation and close supervisory scrutiny. The research questions that follow are why such is the case and how should the alternative regulatory frameworks be implemented in light of the fundamental changes in the global financial systems. From the theoretical perspective, differential information structure in the banking industry is attributed as being an underlying cause of financial fragility and a potential threat to systemic stability. Unfortunately, there has never been a formal study to date that focuses on the causal or correlational relationships between the banks' information signaling behavior and their functional motivation and prudential incentive.

Research Objectives and Scope

The prime objective of this research is to examine and uncover certain flaws in the current prudential regulatory systems. Its secondary objective complements the primary one in terms of the usefulness and viability of the alternative system of functional regulation. Although not directly underscored, the scope of this research also covers the implicit aspects of market-based disciplinary regulation when deriving the proxy variables for signaling behavior of the banks. These layers of objectives and scope will become the grounds for the development of research hypotheses and empirical methodology, which are central to this paper.

The structure of the paper is divided into five parts. The first part lays conceptual and theoretical foundations for the understanding of and development in the economics of banking to date. Under this part, theories of financial intermediation, information, and regulation are discussed and reviewed in light of current literature. The second part involves the establishment of research hypotheses that address the impending empirical puzzle of banking regulation. The quantitative methodology used in empirical study and testing of research hypotheses is given in part three. It constitutes three sub-sections, namely theoretical method, analytical method, and statistical method. The fourth part provides important empirical findings in the tables of test statistics, which include the test of goodness of fit, test of significant relationships, test of significant parameters, and test of multicollinearity. And finally, the interpretation of empirical findings, policy implications, research limitations, and future research directions are given in the summary and conclusions part.

Research Contributions

It is expected that this research will provide additional insights to the advances in both financial economic and political economy disciplines with respect to the ongoing issues in international banks' risk management and financial engineering activities. Specifically, it utilizes a positive approach, rather than a normative argument, to refute conventional wisdom that prudential regulation is most effective in lessening bank fragility and thereby systemic instability. More importantly, its results will shade light on how policy makers in industrialized and emerging countries can modify their current systems of bank regulation and supervision to improve both performance of and safety in their domestic banking industries.

The research will also pave way for further investigation into the area of regulatory replications whereby banking regulations are internalized for all parties concerned, including banks' management, shareholders, and depositors, to make financial services systems function more efficiently and effectively without unnecessary and costly government intervention. The contribution of this research will enhance not only the theoretical concepts of financial intermediation, information, and regulation and their empirical implications in the academic sphere, but also the practicality in policy-making and professional worlds.

Acknowledgement

The author wishes to express his deepest gratitude to all academic advisors, colleagues, and institutional providers of primary data as well as personal inspiration without whom this research will not accomplish its intended objectives. Despite best efforts, all unintentional errors and omissions shall be the sole responsibility of the author.

Theoretical Foundations and Literature Review

Three building blocks pertaining to this research consist of 1) the economics of financial intermediation, 2) the economics of financial information, and 3) the economics of financial regulation. The first deals with economic rationales for financial intermediation in terms of provision and improvement of valuation and operation efficiencies in the real and financial markets. It also covers, in particular, the dynamics within the banking industry in terms of institutional changes and functional transitions from traditional commercial banking services to universal financial products innovation. In the second block, the importance and impacts of differential information structure are reviewed in light of agency theory. More specifically, the existence of hidden knowledge and hidden action in the banking industry which engenders the problems of non-contractual adverse selection and contractual moral hazard will be underscored. And finally, with the combined effects of structural and functional dynamism and the persistence of agency problems, three schools of regulatory economic thought will be discussed and analyzed in the third block, namely the mandate-based, the market-based, and the model-based frameworks of banking regulation.

Economics of Financial Intermediation

In this first theoretical section, the necessary and sufficient conditions for the existence of the banking industry as an important economic agent in the financial markets are reviewed and discussed. Furthermore, the dynamics of technological advancement as well as the fluidity in the global marketplace, which substantially affects geopolitical balances, are emphasized as being the pivotal impetuses for institutional and functional changes within the banking industry.

Necessity of Conventional Banking Operations

Central issue in the theory of banking is why real and financial markets need intermediary even if the markets are relatively efficient and frictionless. The rationale for financial intermediation is that markets are generally not complete in terms of risk sharing and not perfect in terms of information sharing. Traditional theory of banking postulates that markets are altogether inefficient, incomplete, and imperfect. The existence of financial intermediaries is necessary to reduce first and foremost various types of market inefficiencies. The efficiency characteristics in which banks play the vital role to improve are 1) allocative efficiency, 2) distributional efficiency, 3) transactional efficiency, and 4) informational efficiency. Conventionally, banks serve to increase these efficiencies through several functions as follows.

Resource Pooling Function

This function involves the allocative efficiency and resource pooling function of the banks. Myers and Rajan (1995) conceptualize that the ability of a firm with highly liquid core assets to incur debt without jeopardizing its creditworthiness or increasing its bankruptcy costs is a desirable property of good financial intermediary. Based on this presumption, a firm that is able to pool the funds from many small investors has an "absolute advantage" over those that are not, and will eventually become a bank. Economies of scale in the banking industry not only make their resource pooling function more efficient than other non-bank firms, but also provide them with greater influence over the decisions and actions of the borrowers.

Debt capacity of the bank depends primarily on the liquidity of their core assets. As a result, the liquidation value of the loans becomes the main indicator of the bank's debt capacity. If there is no secondary market for loans, then it will be more difficult for the bank to transform their loans, thereby facing with depressed liquidation value. The liquidation value of bank loans depends on how much value individual depositors can recoup from the borrowers' projects. The banks' debt capacity, or resource pooling efficiency, can be increased by two conditions: 1) when they make loans instead of undertaking the projects in-house; and 2) when their bargaining power over the projects' cash flow is high. The first condition is the prime reason why banks should transform their liquid assets into non-committal loans rather than committing to specific projects, thus the liquidity transformation model. The second condition substantiates the banks' role in monitoring the projects on behalf of the depositors and investors, and thus the monitoring delegation model.

Liquidity Transformation Function

This function is concerned with the distributional efficiency and resource transfer function of the banks both spatially across different real assets and intertemporally over different time horizons. A bank is seen as transforming its liquid core asset base into the less liquid ones. Diamond and Dybvig (1983) argue that financial intermediary exists because individual depositors who faced with uncertain consumption needs want to be able to withdraw their savings on demand. By diversifying the idiosyncratic consumption demands of individuals over a large number of such individual depositors, financial intermediaries can finance long-term project investments with short-term demand and time deposits. In relation to the debt capacity model discussed earlier, a firm whose core assets are overly liquid has a "comparative advantage" over less liquid firms in intermediating credits because it can borrow more of the amount needed to make non-committal loans.

However, the choice between making loans to projects and investing directly in the projects does affect the bank's debt capacity. Their differences lie in the fact that lending transactions expose the bank to less cash-flow uncertainty than investing, since loan agreements not only provide the bank with fixed interest-income streams but also the first-priority claim, i.e., forced liquidation, on the project assets in the event of bankruptcy. Moreover, the loan agreements always stipulate strict financial covenants that allow the bank to closely monitor the borrowers' activities and to influence the projects' performance. Thus, the quality of loans made indicates not only how much debt capacity the bank can have but also how flexible and powerful the bank is over the projects' cash flows.

Exchange Facilitation Function

This function focuses on the transactional efficiency of and payments system maintained by the banks. Perold (1995) argues that the function of the payments system is to transform a small number of large payments to a large number of small payment spread over time. There are costs associated with the clearing (processing of payment instruction) and settlement (discharge of obligations) of financial transactions, e.g., processing fees, collateral financing and maintenance, brokerage commissions, bid-ask spread, and taxation. Since most transactions are executed on the basis of oral or other soft commitments among traders, the function of clearing is necessary in order to formalize these unstipulated commitments to resolve discrepancies and misunderstandings and to allow counterparties to track their settlement obligations and exposures. Clearing, therefore, involves the operational tasks of trade-matching, trade confirmation, and determination of settlement commitments. The efficiency and reliability of clearing depend highly on fast and accurate communications and computing technology as well as on standardization of communications protocols.

The organization and management of systems for clearing and settlement is largely dictated by the types of security being settled, by the institutional structures of the banking system, and by the regulations governing transfers of funds and securities. Some operational and structural features common to most payments system include: 1) immobilization of physical securities, 2) netting, 3) delivery-versus-payment, 4) finality of settlement, 5) provision of performance guarantees, and 6) extension of credits. These features generally depend on particular aspects of the system to influence efficiency. The FedWire and the Swiss Interbank Clearing System (SIC) provide very good examples. FedWire transfers can clear and settle without delay because of the Federal Reserve's ability and willingness to extend credit to its prime banking members. However, the FedWire system is prone to deterioration in the creditworthiness of the bank. The SIC, on the other hand, also offers continuous intraday transfers with finality, but without the extension of credit. Transfers through SIC must be queued until they can be fully funded. The SIC system is more prone to gridlock resulting from delays in unwinding the queues.

Monitoring Delegation Function

This function deals with the informational efficiency and financial contracts system of the banks. Diamond (1984) relates the banks' comparative advantage to their greater ability to monitor and control the borrowers' project cash flows. If the banks can extract higher repayments from the projects than individual investors can, then intermediation always dominates direct project financing. The rationale behind this argument is that since monitoring costs for each depositor are high individually, there is an incentive for them to free-ride on the depositors who have a higher stake in the projects. Banks can eliminate this free-riding incentive by pooling the depositors' financial resource and monitoring costs thereby effectively increasing the overall bargaining power over the projects' cash flows.

The bank's greater bargaining power over the project ensures that the repayments it can extract from the project exceed the repayments individual investors can obtain by lending directly to the project. Unfortunately, individual depositors cannot extract this money entirely from the bank if the loan is the only asset the bank possesses. Although depositors can threaten to withdraw their deposits and force the bank to liquidate its assets, it is only when these assets are overly liquid that they have high liquidation value. The bank's bargaining power increases the amount it can lend to the project, but does not change how much it can borrow from the depositors. Thus, the bank whose core assets are overly liquid also has a "comparative advantage" over less liquid banks because it will have relatively higher debt capacity to borrow the amount it requires to finance its loans.

Impetuses for Institutional and Functional Changes

Over the past three decades, there have been strong impetuses both from within and outside the banking industry influencing banks to change structurally. Fast-pacing development in information and communication technologies has made debt capacity, liquidity transformation, and exchange facilitation functions of the banks less important as market participants can perform these functions as efficient on their own. The resultant structural changes have become known as financial disintermediation, spurred by the effects of financial liberalization whereby exchange and payment transactions are less regulated but subject more to market discipline. Geopolitically, fragmented local and domestic markets have become more globalized and closely integrated. Competitive pressures have forced inefficient market participants out while retaining the most efficient ones who can meet the high expectations of demanding market discipline. As a result, banks have relentlessly evolved to offer the markets with new and innovative financial products and services which ever alter their functional orientations almost completely. The new terrain for functional competition in the banking industry now includes 1) credit enhancement, 2) liquidity securitization, 3) risk unbundling, and 4) financial engineering.

Credit Enhancement Function

This model involves the reduction of credit and default risk through financial markets. As information and communication technologies enhance transactional and informational efficiency in the markets, creditworthy firms find that they can borrow funds directly from the markets at lower costs than they could borrow from the banks. Some of the more popular innovative products devised to increase creditworthiness of the borrowers are: 1) commercial papers; 2) credit-enhanced issues, e.g., note issuance facility (NIF) and revolving underwriting facility (RUF); and 3) credit-derivative issues, e.g., credit-linked notes, default swap, total return swap, transfer-risk notes.

The increasing trend in credit disintermediation can be explained by the fact that the improved technology of public monitoring and control has allowed individual investors to monitor borrowing firms directly at low transaction and agency costs. But disintermediation seems to be episodic rather than secular because banks can also gain similar benefits from such improved technology and reduce their monitoring costs even lower. The role of bank in making illiquid loans depends on this profitable franchise servicing demand deposits. If this franchise value dissipates, the bank's comparative advantage in making loans will also decline. In many developing countries, deposit rates are set by a government regulatory cartel. This creates substantial franchise value and rent-generating privilege in deposit taking, and consequently a strong incentive to make loans. Liberalization of deposit rates will, therefore, decrease this franchise value which, in turn, increases the value of credit disintermediation process.

Liquidity Securitization Function

Today, many non-financial firms discover that their liquidity position is improved by the ability to securitize their assets through a special-purpose vehicle, and repackage them in a manner that they can be sold in the markets more easily at fair prices. Securitized products also allow individual investors to realize higher returns while reducing their liquidity risks. To be engaged in securitization activities, banks have to narrow the tradeoff between asset liquidity and investment flexibility. If flexibility is not an issue, the bank can place liquid assets into a separate corporate entity called a "special-purpose vehicle," and, as a result, set its investment flexibility to zero. This, in essence, is the process of securitization; because it holds liquidity as more important than investment flexibility. A substantial regulatory and monitoring mechamism is required to induce banks to forego their investment flexibility and allow securitization to take place.

Securitization can take on two forms: 1) mortgage-backed, and 2) asset-backed. Mortgage-backed securitization involves the pooling of mortgages and the issuing of securities that are collateralized by these mortgages. The basic form of mortgage-backed securities is the mortgage pass-through. The derivatives of this basic form include collateralized mortgage obligations (CMOs) and stripped mortgage-backed securities. Asset-backed securities, on the other hand, are originated from the pooling and repackaging of non-real estate loans such as automobile loans and trade receivables.

Another important aspect of liquidity securitization is the development of the secondary markets for the mortgage pass-through securities. In the United States, a special-purpose vehicle called the Federal National Mortgage Association (FNMA or "Fannie Mae") is responsible for creating a liquid secondary market for uninsured mortgages originated from the Federal Housing Administration (FHA) and the Veterans Administration (VA). In 1968, another special-purpose vehicle called the Government National Mortgage Association (GNMA or "Ginnie Mae") was created to guarantee the uninsured FHA/VA mortgages. For insured FHA/VA mortgages, the Federal Home Loan Mortgage Corporation (FHLMC or "Freddie Mac") was established in 1970 for that purpose. For asset-backed securities, similar special-purpose vehicles or private conduits can be established to purchase loans or receivables, pool them, and sell them as pass-through securities whose collateral is the underlying pool of loans/receivables, which can be either fixed- or floating-rate contracts. They differ from most mortgage pass-throughs in that they are supported by credit enhancements so that they can obtain a high credit rating, which adds value to their marketability and liquidity.

Risk Unbundling Function

Not only do firms want to reduce their cost of funds, they also aim at reducing risk exposures that are associated with disintermediation and securitization activities. In effect, they search for the most effective ways to manage their risk profiles through taking certain hedged positions in their assets in-house, e.g., swaps, or purchasing market-oriented derivative products, e.g., synthetic securities. This model is based on financial innovation and contingent claims to transform market risk. Banks play a central role in the provision of risk management services, to both individual investors and corporate clients. They are also active in the derivative markets and in the trading and underwriting of actuarial insurance, diversification, and guarantees. The essence of creditworthiness in the provision of all of these services gives risk management within banks a distinctive line of business.

However, banks sometime experience certain difficulties communicating their creditworthiness to customers and regulators. Their actions are difficult to monitor or observe, i.e., they are relatively opaque. To preserve their competitive advantage, banks must carefully manage the amount and types of information that they share with other parties. But this works against keeping customers and regulators fully informed. Another important factor is that banks can move into an out of these risk-management activities more quickly than non-financial firms, which has direct consequences for the size and composition of their balance sheets. While this flexibility is a competitive necessity, it further aggravates the monitoring problem for depositors, customers, and regulators.

Financial Engineering Function

This function differs from risk unbundling function in that it deals more deeply with the transformation of the firms' idiosyncratic (internal operations) risks through investment-financing advisory services rather than dealing with the market risks through trading derivatives contracts. According to Merton (1992), financial engineering is the means for implementing financial innovation. It is a systematic approach used by banks and financial service firms to seek better solution to specific financial problems of their clients. The changes in finance theory and computer technology and the transaction-cost-reducing effect of the financial-innovation spiral have had their greatest impact on the production aspects of banks' financial engineering process. There are two models for financial engineering: 1) the underwriting model and 2) the synthesizing model. The underwriting model emphasizes marketing or distribution skills of the bank. The bank is positioned more like an agent than a principal to the transaction. The unit trust used as the intermediation vehicle is a transparent institution. No sophisticated valuation or trading skills are needed. The synthesizing model focuses more on a strong dynamic-trading skill than a strong distribution system, and relies on the power of modern computer technology and highly-skilled personnel, trained in advanced methods of estimation and contingent-claims pricing. With its reliance on dynamic trading, the synthesizing model benefits disproportionately from the financial-innovation spiral, which is supported by the creation of and the continuous feedbacks from the secondary markets for those synthetic products when they gain more popularity, higher credit-rating, and higher liquidity.

Compared with the underwriting model, the synthesizing model appears to have several advantages. It makes the part of the transactions perceived by the customer much simpler because the bank issues the contract without requiring the intervening element of the trust as another institution involved in the transaction. The synthesizing model is considerably more efficient for a bank that specializes in unique or boutique financial contracts. Essentially, any contract with payoffs that depend on the price of an underlying security can be produced by the same type of the dynamic-trading process. This model offers the opportunity to create custom-made financial products at a standard-product level of cost. Another advantage to the bank as a principal is the opportunity to net its transactions. Thus, a bank that offers a wide variety of custom contracts, each contingent in different ways on the price path of the underlying security, can run a single replicating portfolio in the security and hedges the net contingent payouts.

These seemingly irreversible structural and functional changes are necessary to make the markets more dynamically complete in terms of Arrow-Debreu optimal risk sharing. After the issues of efficiency and completeness have been successfully addressed, what still remains is the issue of perfect information to be discussed in the next section.

Economics of Financial Information

The ultimate test of markets efficiency is in the area of information. Two strands of economics of information are divided between the domain of capital markets (macro-level) and of the firms (micro-level). Informational efficiency in the markets domain is theorized by Fama (1965). The economics of information that deals with the firms is grouped into game theory (inter-firm conflicts) and agency theory (intra-firm conflicts). Both domains of information efficiency are relevant to the banking industry, but only the latter one will be addressed in view of the banks’ signaling behavior. Two types of differential information in the context of agency theory are 1) hidden knowledge of the banks' shareholders from general depositors and 2) hidden action of the banks' management from their shareholders. Hidden knowledge can be thought of as a non-contractual adverse selection issue in which the general depositors or potential debtholders have less knowledge of whether the banks' shareholders Pareto sub-optimize their self-interest by overinvestment or underinvestment. Hidden action, on the other hand, is a contractual moral hazard issue where banks' management over-expose their asset portfolios to higher risk without adequate internal control systems in order to exploit the deposit insurance and implicit put options the banks have for their incumbent shareholders and depositors.

Two frameworks that are currently used to explain and tackle hidden knowledge and hidden action problems are: 1) incentive compatible models and 2) incomplete contract models.

Incentive Compatible Models for Hidden-Knowledge Problems

Three incentive compatible models that can be used to endogenously create incentive for banks to signal their hidden knowledge are as follows:

1)  Incentive-Signaling Model
2)  Financing-Signaling Model
3)  Issue-Invest Model

Incentive-Signaling Model

Ross (1977) conceptualizes the so-called "incentive-signaling model" based on the firms offering to guarantee their products and services to signal customers their inside information. The rationale for such a behavior is that the performance of the firm is affected by the actions of its management and serves as a measure of how well the members have performed. Compensation scheme that is anchored to the firm performance serves as an incentive for managerial performance. Thus, they will have a strong self-interest incentive to disclose relevant information to the markets. Such disclosure will raise the value of the firm and the manager's compensation. If managers are assumed not to disseminate misleading information, then only managers with bad news will say nothing. Outsiders will observe some managers spreading good news and others staying quite, and they will not draw the inference that no news is good news. In contrast, no news will be regarded as bad news. As a consequence, those managers with no news will suffer by being lumped in with those suppressing bad news. Those with bad news will in turn gain if outsiders cannot distinguish between firms with nothing to say and those suppressing bad news. Therefore, all managers without bad news will have an incentive to disclose relevant information to avoid adverse selection problem.

The way in which the managers can signal the validity of their inside information is to provide a guarantee. By explicitly altering and announcing their new compensation schedule, they signal the market that they have an incentive to tell the truth. Moreover, all managers with good news have an incentive to validate their information with such guarantees in order to distinguish themselves from others with no news or bad news. The forms of performance guarantees can be both simple and complex. The whole financial structure of the firm can be used as a means of signaling. For instance, the failure to pay dividends or the announcement to issue new shares are taken as a sign of bad news. On the contrary, a simple announcement of a dividend increase can be used to signal the market that earnings are rising.

The incentive-signaling model provides a structure that banks use to disclose their information in such a way that potential depositors believe it. Banks with the best news distinguish themselves from those with the next best. At the bottom of the hierarchy are the banks with the worst news who would like to suppress it. But since it is not in the interest to offer the kinds of guarantees provided by those with better news, the worst news will also be effectively signaled. The model also provides a new format with which to discuss disclosure regulation and the role of information in the markets. The complex arrangements and interactions between the bank and the market provide a continuing mode for the communication of information about the bank to outsiders in the market. The role of regulation is that privately agree-upon contracts are honored. No need exists for regulation that information must be disclosed, since managers already have incentives to signal relevant information. There is a need to enforce the contracts which depositors and banks would arrive at. This matter is the primary concern of contractual efficiency that requires regulatory and supervisory involvement from the government.

Financing-Signaling Model

Giammarino and Neave (1982) consider the signaling behavior of the firms through financial structure when they possess inside information about the riskiness of their new investment opportunities. They present a "financing-signaling model" in which the firm and investors have different perceptions of the risk of the return on an investment opportunity, but agree on the mean return. They, in essence, assume that the manager's objective is to act in the current and passive shareholders' interest and that imperfect information is about the firm's risk of return on an investment opportunity. They also concentrate on the choice among financing instruments, and develop a rational for convertible debts. In their argument, equity is preferred to debt so long as the investors overestimate the risk of the return on the firm's investment opportunity. A decision by the well-managed firm to issue equity, therefore, serves as a signal to the market that its new project's risk is lower than that of its competitors.

The financing-signaling model has a profound implication on the setting up of capital adequacy ratios of the banks. When banks have hidden knowledge about the risk of their new lending activities and know that such a risk is not as high as it is otherwise perceived by the market, their willingness to raise capital base unilaterally signals their confidence on their asset portfolios. The resultant capital level may well exceed the risk-based capital ratios required by the regulators. However, the ability to reduce the risk level of the banks' loan and investment portfolios depends greatly on their risk management and financial engineering activities, which unfortunately are opaque. Outside prospective depositors and investors have the benefit that they can observe the banks' ability directly and screen their hidden knowledge through their capital structures, but at the expense of losing their ability to observe the banks' hidden action. Therefore, other revealing mechanisms are required to allow the markets to have better control over the banks' risk management activities or to induce the banks to voluntarily disclose them to the public. This matter is to be taken up in the revealing models discussed later.

Issue-Invest Model

Myers and Majluf (1984) suggest an "issue-invest model" which looks similar to that of Giammarino and Neave (1982) but differs in that the imperfect information is about the firm's expected returns on the new investment opportunities rather than the risks. Their assumptions are that the objective of the firm's manager is to act in current and passive shareholders' interest and that financial slack, i.e., the firm's high level of liquidity and its ability to issue risk-free debt, induces the manager to use internal funds before external financing. The rationale for holding financial slack is that the firm does not want to have to issue stock on short notice in order to pursue a valuable investment opportunity. Financial slack has value because, without it, the firm is sometimes unwilling to issue stock and, therefore, passes up a good investment opportunity, thus the underinvestment problem. Slack does not allow the firm to take advantage of investors by issuing only when stock is overvalued. If investors know that the firm does not have to issue stocks in order to invest, then an attempt to issue would signal a bad news to the market.

The value of slack disappears if the firm can costlessly convey its hidden knowledge to all investors. One way to justify this argument is to think of cases in which values depend on proprietary information which, if released to the market, would be released to competitors also, and would consequently reduce either the value of its asset-in-place, the net present value (NPV) of its investment opportunity, or both. The firm has the incentive not only to signal the availability of its financial slack to the market, but also to supply verifiable detail sufficient to indicate the true state of its slack. The costs of verification may be significant; making it public will tell the firm's competitors all they want to know.

In this issue-invest model, firms would prefer debt to equity if they do not have enough financial slack. This seems to contradict the financing-signaling model of Giammarino and Neave that firms prefer equity to debt. But, if we consider the situation more closely, we would find that the firms with low-risk investment opportunities also possess high financial slack. Such does not require them to use external financing of any form at all. As a matter of fact, financial slack will be reflected as retained earnings in the firms' increased equity level. Therefore, from the bank's capital ratio perspective, it is expected that the well-managed banks which do not forego positive NPV projects or low-risk loans will have higher capital ratios than those that do not. And the signaling behavior of the banks will be concentrated on demonstrating their superior financial slack on the asset-side liquidity composition rather than on the liability-side capital structure.

Incomplete Contract Models for Hidden-Action Problems

The following are three proposed incomplete contract models that can be utilized to exogenously induce banks to signal or reveal their hidden actions:

1)  Incentive Contracting Model
2)  Debt Contracting Model
3)  Internal Control Model

Incentive Contracting Model

In Myers and Majluf's issue-invest model, there is an implicit consequence that the manager’s investment decision is suboptimal once he knows that his decision to issue stocks is considered bad news and the stock prices will be depressed. As a result, he will forego new investment opportunities even though they produce positive NPV. This behavior is not directly observed by the market because an investment decision is never made. And the investors will be worse off with this underinvestment decision. Dybvig and Zender (1991) propose the "incentive contracting model" to ensure that the manager undertakes new projects without affecting the firm's capital structure. Their main conclusion is that in order for the investment decision to be optimal, financing and management incentive contracts have to be separated. They utilize Modigliani and Miller's capital structure irrelevancy proposition to support their argument that financing does not affect the firm's value even when information is asymmetric, provided that the market does not generate information about the firm's value and that information cost does not depress the market price of the firm's equity.

The separation of financing (i.e., claims on debt and equity) from incentive contract (i.e., control rights) allows the firm to design its management compensation schedule to be contingent only upon the firm's current asset-in-place (current stock prices), value of investment opportunities, and the manager's effort. This model is also consistent with Ross's incentive-signaling model in terms of guarantee offering. Optimal incentive contracts can, therefore, be designed internally once the investment decision is also optimal. This can be achieved only when the manager acts in the interest of all investors, old and new. The financing-signaling model of Giammarino and Neave and the issue-invest model of Myers and Majluf are not consistent with this incentive contracting model because they assume that the manager serves the current shareholders' interest who are passive. This assumption makes financing and incentive contract inseparable and the MM's irrelevancy proposition inapplicable. To apply this model to the banking industry, one would have to ignore the importance of capital adequacy ratios on the liability side and focus more on the liquidity reserve ratios on the asset side, since signaling through capital structure is no longer relevant. In this case, the design of an incentive contract for the banks seems to coincide with Edwards' proposal for collateralized banking (Edwards, 1996) discussed earlier, which emphasizes the direct relationship between demand deposits and liquidity and credit quality of the banks' assets.

Debt Contracting Model

The problems of security design occur when an inappropriate choice of contract features can result in inefficiencies. Historically, corporate finance has been concerned with other possible inefficiencies. For instance, Jensen and Mecklin (1976) emphasize the agency cost of equity finance in terms of overinvestment decision or moral hazard, while Myers (1977) identifies the agency costs of debt by pointing out the underinvestment decision. Security design approach considers how both cash flow claims (i.e., debt and equity) and control rights (i.e., management contract) can be structured so as to minimize contracting inefficiencies. Zender (1991) and Aghion and Bolton (1992) argue that contracts that grant control to one class of agents exclusively may not be efficient because either they fail to give the controlling agent the incentives to make optimal investment decision or because contracts held by outside investors will not be sufficiently valuable to permit raising the required external funds. They contend that contracts with contingent transfer of control rights may minimize inefficiencies thereby providing a rational for optimal debt contracting.

In this model, Anderson and Sundaresan (1996) attempt to use security design approach to design an optimal debt contract that can minimize contractual inefficiencies for the firm in the event of financial distress. Despite increasing bankruptcy cost when faced with uncertain forced liquidation, debt is still chosen because the alternative forms of financial contracting such as equity will incur agency costs which may exceed those of debt. The choice of the terms of the debt contract can be expected to reduce such a costly liquidation. A change in the contract features affects the game model faced by the contracting parties. Those contract features include the specification of coupon rate, maturity, face value, and the amortization schedule. The application of debt contract design model to the banking industry can be quite complicated since contract features may vary with different types of cash flow claims which banks' depositors would like to hold. Nevertheless, some alterations in the banks' certificates of deposit (CD) should increase contractual efficiency. However, the standardization and negotiability of such CDs would be negatively affected because of those built-in flexibilities in debt contracts. It thus depends greatly on future financial technology that can close the gap between contracting efficiency and liquidity of the debt instruments.

Internal Control Model

The relationship between internal control and capital structure is studied and proposed by Berkovitch and Israel (1996) in their internal control design model. They distinguish between two types of financial claims: fixed-claim securities such as debt and preferred stocks, and residual-claim securities such as common stock. Each claim type allocates control to its holders to make managerial replacement decision, i.e., the ability to affect hiring and firing of managers. Since the firm's cash flows are affected by the manager's effort and ability, both types of the claim-holders are said to have indirect control over such cash flows as well. The managerial replacement decision determines the quality of the manager and affects the effort he or she exerts. The replacement rule that maximizes expected managerial quality implies that a manager whose ability is below the average ability of alternative managers is replaced. After the manager exerts effort, security holders observe a signal that reveals the cash flow under that manager. Given that signal, they decide whether to replace or retain the manager.

Because of the uncertain nature of the firm's cash flows, residual-claim holders are more aggressive and likely to replace the manager more often than fixed-claim holders. When an entrepreneur wants to commit the firm to replace some above-average managers, he issues fixed-claim securities and gives absolute control to residual-claim holders. When he wants to commit the firm to retain some below-average managers, he would issue fixed-claim securities and allocate fixed-claim holders enough control right to enable them to affect managerial replacement decision. This allocation of control right is equivalent to giving residual-claim holders control but giving fixed-claim holders veto power over their decision.

Berkovitch and Israel argue that fixed-claim holders obtain control when the firm's cash flow is relatively insensitive to managerial effort because fixed-claim holders are less inclined to replace the managers whose ability is known than residual-claim holders. Moreover, the firm value and debt levels are positively correlated when residual-claim holders have absolute control and are negatively correlated when fixed-claim holders have veto power. Therefore, internal control and capital structure can affect the firm's investment as well as risk management decisions. If it is optimal to commit the firm to be sensitive toward risk in those decisions, then the entrepreneur should issue debt and give fixed-claim holders veto power.

By allocating control rights to residual-claim holders, the banks' management would be more accountable to fixed-claim holders (i.e., depositors) who could benefit from free-riding on the managerial replacement decisions and monitoring effort of the banks' stockholders. This emphasis on residual claims and absolute control right would induce the banks' stockholders to increase their capital contribution as the banks' value and debt level increase. In effect, the capital cushion of the well-managed and accountable banks will endogenously be increased. This, also, could serve as a valid argument against the current deposit insurance program that removes the incentive for monitoring the banks' hidden action from both depositors and stockholders. Increased control right is considered to be a natural mechanism for self-insured financial institutions.

Economics of Financial Regulation

This section provides a review of theory of banking regulation and supervision based upon various economic frameworks of financial regulation as well as to discuss it in relation to the problems of differential information. Financial regulation arises mainly from two reasons: systemic stability and contractual reliability. Systemic stability deals with the issues of institutional safety and soundness in general in which banks are expected to perform prudent and competent economic functions. This regulatory objective is explored more in the sub-section of regulatory theory of public interest. Contractual reliability, on the other hand, is concerned with the relationship between the banks and their clients that they are required to perform intermediation functions with honesty and accountability. Under the sub-section of supervisory theory of private interest, the regulatory objective to monitor and enforce contractual obligations will also be discussed. While the first two sub-sections stress on regulatory objectives, the last sub-section will discuss three alternative regulatory frameworks in connection to the economics of information and the regulatory players.

Regulatory Theory of Public Interest

As banks can incur significant social costs, they are subject to strong scrutiny both from within the financial markets and the public authority. The main objective of public scrutiny and oversight is to maximize welfare and avoid market failure. Economic and social welfare include efficiency in three areas: allocation, transaction, and information that the banks are expected to facilitate. The avoidance of market failure is to ascertain that banks will not operate sub-optimally and be the primary cause of systemic crisis. The criteria for welfare maximization are high performance and considerate prudence while the criteria for market failure minimization are safety (high liquidity) and soundness (adequate solvency).

Systemic Stability Objective

Due to the potential competitive inefficiency in the banking industry resulting from specific rent-seeking behavior or market failure in general, which can lead to a system-wide banking and financial crisis, banks are therefore very tightly regulated. Three kinds of behavioral characteristics are the foci for banking regulation: 1) competence, 2) prudence, and 3) honesty. In order to guarantee a minimum level of banks' competency like a qualifying examination for driver's license, an entry regulation such as bank registration or fit and proper standard is required. However, that minimum competency level does not mean that the banks will execute their best efforts to represent the public and maximize the uninformed depositors' interests. Thus, the prudential regulations such as activity firewalls and geographical restriction are usually mandated. To elicit honest behavior from the banks that they contemplate the institutional safety and soundness as their first priority, many ex ante safeguarding measures (e.g., capital adequacy and required reserve ratios) and ex post safety nets (e.g., discount window, deposit insurance, and lender-of-last-resort) are imperative.

The negative consequences of systemic instability can be put in sequence as follows: 1) depositor runs due to short-run illiquidity of the banks, 2) bank runs and insolvency problems as a result of mismanagement or misfortune, 3) systemic collapse of the overall banking system from herd-like withdrawing panics due to the public inability to distinguish between the healthy banks and the distressed or failed banks, and 4) the contagion effects of systemic crisis that spill over to other financial markets in domestic and other countries and result in negative externalities to the real sectors of the economy. Therefore, it is utmost important that the government intervene to regulate banking industry to prevent a series of undesirable consequences.

Competitive Efficiency Objective

Two perspectives of regulation for competitive efficiency are used to explain why banks are subject to government regulation: 1) the rent-seeking behavior of the banks (i.e., self-interest maximization), and 2) the negative externalities the banks generate toward the economy (i.e., market failure). In the rent-seeking perspective, Stigler (1971) argues that market participants will demand regulation when the expected marginal benefits of such regulation exceed the expected marginal costs. Regulation is demanded as a means by which a bank can raise the costs of its competitors or reduce its costs while leaving the costs of its competitors unchanged. When banks demand regulation that is designed to increase their market share at the expense of their competitors, they are said to be engaged in rent-seeking behavior. Economic rent is the abnormal profit a firm can earn when its market power is increased. Thus, rent seeking is the process by which banks allocate real resources to lobbying and the use of pressure groups to generate rents from regulation.

Market failures refer to conditions under which the market-guiding invisible hand of voluntary exchange would fail to direct society's resources to an allocative pattern capable of achieving optimum social welfare. Three types of market failure are: 1) sub-optimal Pareto allocation, 2) natural or informational monopolies, and 3) negative externalities and social costs. A market failure is presumed to occur when market participants do not take into account all the costs of their decisions. A bank's private cost, or the cost that governs its private behavior, is presumed to diverge from the true social cost of the firm's decisions, thus resulting in an externality and a failure of the market to allocate resources most efficiently. Regulation is an appropriate means of correcting this inefficiency and other market failures.

Supervisory Theory of Private Interest

From the standpoint of fiduciary nature of the banking industry and its relation to the markets, efficiency in contractual relationship is the primary concern for banking supervision. Supervisory theory of private interest searches for low-cost mechanisms by which to reconcile conflict between regulators' private and societal goals. Resource costs are associated with the markets' need to control its banking industry. It is desirable for the markets that this control be produced at minimum cost. To achieve this objective, banking supervision, therefore, has to engender contractual efficiency and bank-specific or idiosyncratic transparency.

Idiosyncratic Transparency Objective

One major incentive for the banks to pursue their self-interest and make their financial contracts with outsiders ineffectual is the presence of differential information. Several supervisory options can be used to resolve this idiosyncratic opaqueness of the banks' behavior including internal control, industry oversight, and public oversight. First, internal control refers to resistance to financial failure, abuse of fiduciary responsibilities, and other lapses in management. Management problems should be reflected in the reputation of the bank, which in turn will be reflected in its value. Thus, an important responsibility of bank's management is to maximize its franchise value, and to put in place the necessary safeguards against its erosion. If the bank is subject to a high level of transparency, the pressure on management to enforce safe and sound practices and high standards of conduct may obviate external supervision that could entail greater regulatory burdens. Second, industry oversight refers to supervision by industry association and self-regulatory organizations (SROs) to encourage and enforce high standards on their members and to discipline them for non-compliance. It may be that SROs, together with external audits by public accounting firms and the threat of lawsuits by disgruntled private parties, can alleviate shortcomings in self-regulation without incurring some of the regulatory costs associated with external supervision. Third, public oversight refers to supervision by agencies set up for a specific purpose whose mandates are anchored in regulatory statutes. This requires an infrastructure of qualified, motivated banking examiners who have at their disposal both civil and criminal penalties. Most financial systems have found that a structure of external supervision is necessary no matter how effective internal control and SRO supervision become, since there are always gaps that could lead to instability and breaches of appropriate conduct in financial markets.

Contractual Efficiency Objective

Private and public fiduciary relationships may be viewed as contracts that delegate obligations to the counterparties. Each obligation establishes a principal-agent relationship. Every agent has an objective function that differs from that of the principal. Every agent faces a temptation to evade some of its obligations whenever it can hide self-serving actions or other relevant information from the principal. Contracting efficiency looks past market failures to focus on society's need to monitor and police at minimum resource cost. Jensen (1994) describes the central proposition of agency theory as follows: rational self-interested people involved in cooperative endeavors always have incentive to reduce or control conflicts of interest so as to reduce the losses resulting from them. A reliable outside supervisor can improve the fairness, efficiency, and enforceability of financial agreements by offering to mediate transactions in which the interests of bank's management, shareholders, debtholders, and depositors diverge. Agency theory recognizes the value of incentive-based compensation and ex post settlement as ways for society to constrain the tradeoffs between public and private benefits that are made by banks' management and by the government and private parties that supervise them. Agents are willing to accept tighter control only if they are compensated appropriately for the private benefits that tighter controls take away from them.

Alternative Regulatory Frameworks

Turning away from the focus on regulatory objectives, the emphasis of this sub-section is on the regulatory agencies or players themselves. To alleviate asymmetric information-induced problems in the banking industry, three alternative regulatory frameworks are categorized along the lines of regulatory players’ jurisdiction:

1)  Mandate-based prudential regulation
2)  Market-based private regulation
3)  Model-based functional regulation.

Mandate-Based Regulation

As discussed before in the regulatory theory of public interest, prudential regulation incorporates both preventive (safeguarding) and protective (safety-net) measures in mandating the banking industry to behave in the interest of the public at large according to the safety and soundness doctrine as well as to perform financial intermediation functions in the manner that meet the market expectations for competitive and contractual efficiency. The preventive measures include various activity restrictions, such as the fit and proper entry requirements and the separation between commercial banking and investment banking functions, as well as disclosure requirements and monitoring oversight such as the SEC’s mandate on off-balance-sheet financial reporting and early warning signals relating to liquidity and solvency positions of the banks.

The protective measures, on the other hand, include capital adequacy ratios, deposit insurance, and lending of last resort from the central bank. Capital adequacy standards, such as the Basle’s capital-to-risk-weighted-asset ratio, are imposed on banks as a self-insured cushion against risk of losses from their credit and investment operations. Deposit insurance is used to protect depositors’ funds thereby building strong public confidence in the banking systems in the event that some banks are faced with temporary liquidity problem. Lender-of-last-resort scheme is deployed as the ultimate safety net to rescue the banks that have a serious liquidity problem but still possess a sound solvency position.

Market-Based Regulation

In connection to the supervisory theory of private interest, the agency theory has given rise to various private regulatory applications in both corporate finance and financial institution. Costly monitoring, free-riding, corporate governance, and shareholder activism are among the most prominent areas of research in the field of market-based regulation, which build on the frameworks of securities and incentive systems design. In essence, the theory addresses the two-stage conflictual relationships between principal and agent, namely shareholders as being an agent for debtholders (depositors) in monitoring the bank management’s decisions and activities, and bank management as being an agent for shareholders in monitoring the performance of the bank’s loan, investment, and derivative portfolios. However, since behavioral monitoring is costly the market-based regulation encounters an inevitable free-riding problem whereby debtholders free ride on the shareholders’ effort to monitor the bank’s risk-prone activities. The tensions and interactions between debtholders and shareholders of the banks are manifested in the optimal design of debt contracts and covenants. Despite optimal securities design, the tradeoff between information monitoring and free-riding costs still represent a deadweight burden which the banking industry as a whole has to shoulder.

The inherent conflict of interests between shareholders and the bank management can potentially be resolved through optimal incentive systems design. Theoretically, the effectiveness of incentive systems rests upon how active the incumbent shareholders are in influencing the behavior of the bank management through the board of directors. The so-called "corporate governance" specifically deals with the issues like markets for corporate control, executive compensations, and risk-adjusted performance measurements to allow shareholder activism to play a more important role in less transparent decision-making.

Model-Based Regulation

The concept of model-based regulation stems from an increasing exposure of corporations and banks to credit and market risks. In corporate finance, credit and market risks can be shared or shifted to counterparties through hedging and risk management activities. Dynamic trading of and assuming hedged positions in underlying and derivative financial instruments are not uncommon to corporate risk management practices. In the banking industry, however, the management of credit and market risks entails much more sophistication than a mere hedging activity in that banks, as a prime provider of those financial instruments, have to be engaged in the ongoing financial innovation and opaque engineering activities which involve complex mathematical programming and stochastic models.

Due to the opaqueness of the banks’ financial engineering activities, it is extremely difficulty for the outsiders to observe or measure the risk of their derivative portfolios, let alone measuring their intrinsic values. The only way in which banks can disclose or report their portfolio positions is through the use of option-pricing, or more generally, contingent-claim models. For example, many banks currently incorporate the value-at-risk (VAR) model to measure their portfolios’ daily exposure to market risk. This has made banking regulation even more difficult for public regulators, depositors, and shareholders alike.

The proposed model-based regulation focuses on capital-at-risk (CAR) and risk-adjusted return on capital (RAROC) as the main indicators of banks’ risk and potential fragility. The problem with these indicators is that they are derived internally and specifically by the banks in question, which in turn are based upon the historical profiles of their portfolios in connection with the current asset-liability management and the expected rates of return from those portfolios.

Research Hypotheses

From the theoretical basis of these three regulatory frameworks, it is necessary to justify which of these frameworks would be the most effective candidate for banking regulation. To relate these theoretical perspectives to the testable hypotheses, some linkages among the three frameworks need be established. First, the mandate-based regulatory objectives of systemic stability and competitive efficiency can be translated into the banks’ financial variables such as liquidity and solvency positions in conjunction with the required prudential standards. Second, the market-based incentive compatible models with emphasis on depositors’ delegated monitoring and corporate governance can be exhibited through the banks’ marginal asset-liability gaps and the degrees of asset opaqueness and off-balance-sheet portfolio positions in relation to the banks’ functional performance. And third, the model-based regulatory indicators will be compared against both mandate- and market-based measures to see whether the banks are capable of and willing to signal inside information about their risks to the general public.

For the purpose of this research, the information signaling behavior of the banks is divided into two categories: 1) capital cushion signaling and 2) return performance signaling. Capital cushion can be observed ex ante by bank depositors and the general public, which indicates the level of self-insurance against credit and market risks in the event that losses are realized. Return performance, on the other hand, is an ex post measure which indicates how well the banks managed their on- and off-balance-sheet portfolios given the relevant risk exposures.

In order to test whether prudential regulation of the banking industry is less effective in the area of capital adequacy than functional regulation, two research hypotheses are established.

H1:  Capital signaling behavior is influenced more by functional determinants than prudential ones.

H2:  Return signaling behavior is influenced more by prudential determinants than functional ones.

The distinction between functional and prudential determinants is given by the objectives the banks attach for each determinant. For instance, the banks' asset-liability management and off-balance-sheet activities aim to achieve the optimal levels of banks' asset utilization thereby maximizing returns, whereas management of liquidity and solvency positions are used to serve the banks in times of temporary financial difficulty and prolonged financial distress.

Research Methodology

Research methodology is divided into three phases from theoretical conceptualization of variable proxies and financial data analysis to statistical modeling and inference.

Theoretical Method

The main purpose of theoretical method is to provide reasonable ground and sufficient justification for the proxy variables to be used in statistical modeling. Two types of proxy variables are dependent or response variables and independent or explanatory variables, which can be elicited from the banks' financial statements.

Proxies for Dependent (Response) Variables

Two types of response variables, namely capital signaling behavior and return signaling behavior, are determined as follows.

Capital Signaling Behavior

Capital signaling behavior is represented by the ratio between the Basle mandate-based capital adequacy rate and the model-based rate of internal capital reserves. If the ratio is greater than 1, then the bank was willing to provide capital to cushion its portfolio risks more than it required. This means that the bank intended to signal to the general public about its safety and soundness conditions, which connotes low bank risks. According to the Basle Accord of 1988, the minimum capital adequacy rate is set at 8% of the bank's total net worth to risk-weighted asset classes. Asset classes are rated according to their credit quality starting from 0% for secured assets, 20% for loans to other banks and municipalities within OECD countries, 50% for mortgage-backed loans, and 100% for unsecured loans and investment in securities portfolios as well as holdings in subsidiaries. Notional balances of off-balance-sheet commitments are weighted at 2.5% while contingent claims at 5%. The important pitfall of the Basle capital ratio is that it is subjective and may not reflect the actual risk exposures of the banks using it.

When equity is the risk-based capital with internal models, the various business units of the bank have to meet a target return on this economic capital. This ensures that they actually charge risks, measured as economic capital, to customers. The required reserves diverge from those that would be based on mandate-based capital to the extent that economic capital and regulatory capital are different. The internal capital reserve rate, therefore, is the ratio between the bank's reserves for expected portfolio risks plus its capital-at-risk (CAR) over its total loan and investment portfolios. The amount of reserves plus CAR properly reflects the actual risk exposures and can be used to compare against the total net worth to obtain the bank’s capital signaling behavior.

The measure of economic capital or CAR is derived from the value-at-risk (VAR) methodology. When using this method to value capital, the following assumptions apply:

• Capital is intended to provide a protection against the deviation of losses beyond the average. It does not provide protection to predictable average losses, which should be taken care of through reserves and provision policies.

• The deviations from the average are the unexpected losses. Capital provides a protection against these losses. The deviations of losses are defined subject to a tolerance level. By definition, CAR is associated with the tolerance level.

• The losses that exceed the upper bound set by the tolerance level are exceptional losses By definition, exceptional losses cannot be absorbed by CAR. If they occur, the bank defaults.

• The tolerance level represents the probability that actual losses deviate by more than the upper bound. Therefore, the tolerance level is the default probability of the bank.

• It is not equivalent to measure unexpected loss at the business unit level in terms of VAR and those unexpected losses that put the solvency of the entire bank at stake.

Using a 2.5% confidence level of market risk is acceptable for the purpose of risk monitoring and enforcing limits at the level of a business unit. If the aggregate loss of the bank goes beyond capital, this event does trigger default. CAR requires stricter rules to be defined than VAR used for day-to-day operations.

Return Signaling Behavior

Return signaling behavior, which is associated with the behavior of bank's management in managing its portfolios, is represented by the ratio between the risk adjusted return on capital (RAROC) and the conventional return on capital employed (ROCE). If a bank's RAROC exceeds its benchmark ROCE, then it means that the bank management is able to signal to its shareholders about its internal capability to manage and control portfolio risks while meeting the required return expectations.

Traditionally, the profitability measures include return on assets (ROA), return on equity (ROE), and ROCE. New risk-based performance measures have been induced by regulations. Since banks are committed to obtain mandate-based capital, they have to provide a sufficient return on this capital and to monitor the cost of mandate-based capital used up by transactions and portfolios. However as discussed earlier, mandate-based capital such as the Basle ratio has many drawbacks since it is subjectively determined. The use of CAR allows the bank to adjust profitability with economic measure of risks.

The RAROC adjusts the bank's earnings from portfolios to their risks based on CAR. The earnings can be defined as the net interest margin, excluding fees, plus trading and investment income. They can be calculated both before and after operating costs. The minimum value of the required ratio depends upon the perimeter of the earnings calculation. For the purpose of this research, the earnings are calculated before operating costs, which truly reflect various banks' management and exposures to portfolio risks cross-sectionally without imposing any comparative advantage on operating cost management among them.

The assumptions on which the derivation of RAROC is based are:

• The measures of risks are within a specific time horizon.

• The time profile of earnings over the same horizon.

• The expected and unexpected credit losses are derived from default rates and recoveries.

• The expected and unexpected losses from market risk exposure are derived from VAR measure.

Proxies for Independent (Explanatory) Variables

Two groups of explanatory variables are also derived from the banks' financial statements. The first group is called "functional determinants," the second group "prudential determinants."

Functional Determinants

Functional determinants are predicated on two important banking activities: 1) asset-liability management (ALM) to tackle the risks associated with liquidity gaps, and 2) off-balance-sheet management to address the risk-shifting issues. The measures derived from them will be used to test how well they contribute to the capital signaling and return signaling behavior of the banks.

Liquidity gaps are defined by Bessis (1998) as follow. When assets are greater than resources from operations, a "funding gap" occurs which should be financed externally from deposits and borrowings. On the other hand, when liabilities are greater than assets, an "investment gap" appears, and the excess resources have to be deployed through loans, securities, and derivative investment vehicles. In terms of ALM, banks want to ensure that their funding gaps can be financed under normal conditions without being subject to higher interest rates associated with the emergency funding of unexpected large deficits, while their investment gaps can be narrowed down without imposing higher exposures to credit and market risks on the asset side and interest rate risk on the liability side.

A measure used to represent the banks' ALM function and a proxy for the first explanatory variable in this research is called a "marginal gap." It is calculated as the difference between the annual percentage change of assets and of liabilities. A positive marginal gap means that the variation in assets exceeds that of liabilities, and vice versa for a negative marginal gap. The banks that consistently maintain the positive marginal gaps have experienced more uncertainties in their uses of excess funds than in their sources of deficit funds. Such an instance indicates their vulnerability to asset management and all associated risks. On the contrary, those that have maintained the negative marginal gaps are more susceptible to liability-related risks than to asset-related risks.

Based on the four non-traditional banking functions in terms of credit enhancement, liquidity securitization, risk unbundling, and financial engineering, the banks are intensively engaged in off-balance-sheet activities with the primary purposes to hedge the down-side risks of unfavorable credit and market exposures while gaining on the up-side volatility through dynamic trading of underlying financial assets and derivatives instruments. They also extensively utilize the off-balance-sheet products to manage risk for their clients through risk sharing (futures contracts and commitments) and risk shifting (option contracts and guaranties). Commitment loans and their derivatives are those that have the futures-contract feature such as letters of credit, project-loan drawdowns, and securitized instruments. Contingent claims are options-like contracts that banks originate such as stand-by lines of credit, swap contracts, floating-rate notes, equity derivatives, and structured products.

To measure the degree of the banks' opaque activities, the so-called "opacy ratios" – the ratios between the off-balance-sheet portfolios and the on-balance-sheet portfolios – are used. The higher the opacy ratio, the more intensive the risk management activities in which the banks are engaged. Unless they have the appropriate internal risk control systems in place, high opacy ratios indicate that the banks are likely to be more vulnerable to operational risk than to the external credit and market risks they intend to reduce for themselves and their clients.

Prudential Determinants

Prudential determinants are directly derived from the banks' liquidity and solvency policy. The rationale for using these two measures is that in order to achieve the optimal capital structures and the desirable levels of internal financial cushion, the banks would maintain their liquidity and solvency positions that are commensurate with their expected rates of return.

The measure of the banks' liquidity position is called a "liquidity ratio." The liquidity ratio is simply the ratio between the banks' secured asset portfolios and their total demand and time deposits. As their liquidity ratios increase, the banks are said to have strong and sound collateralized asset classes to cushion or self-insure for unexpected credit and investment losses without jeopardizing their creditworthiness. The liquidity ratio also indicates the degree of short-term vulnerability of the banks in time of massive withdrawals in the event of depositor runs.

The solvency position of the banks is given by the ratio between their total on-balance-sheet portfolios and total obligations. The resultant "solvency ratio" measures both safety of the banks' total indebtedness as being protected by their total asset base and long-term viability to forced liquidation, such as in the event of bank runs. The higher the solvency ratios, the more safety cushions the external depositors and creditors of the banks have. However, no quality distinction is provided for the banks' total asset portfolios in the solvency ratio. Banks that have high solvency ratios may be considered operationally risky if majority of their portfolios consists of unsecured asset classes.

Analytical Method

The analysis phase of research methodology involves data manipulation and transformation after all variable proxies have been identified in the theoretical phase. In this phase, accounting and financial information obtained from the banks' annual reports is thoroughly analyzed using spreadsheet computer program. There are two steps in this analytical method: 1) data manipulation and 2) data transformation.

Data Manipulation

Data manipulation involves the grouping of data inputs into four tables (see illustration below or Appendix III for actual derivation). The first table, labeled "Portfolios Table," is used to derive the bank's total assets, including secured assets, semi-secured (mortgaged) assets, loan and investment portfolios which are unsecured, off-balance-sheet instruments (commitments and contingents), and the Basle Accord's risk-weighted assets (RWA). The second table is called "Obligations Table," consisting of data inputs from the banks' current and long-term obligations and, in connection with the Portfolios Table, serves as a basis for establishing the bank's "Asset-Liability Management Profiles" to be used as the proxies for independent variables.

(Figures in million U.S. dollars unless otherwise specified)

Credit Suisse Group Illustration
Obligations Table

(Figures in million U.S. dollars unless otherwise specified)

Data Transformation

Data transformation is used to derive the comparable measures for the variable. For response variables, the banks' capital signaling and return signaling behavior are transformed in the Capital Profiles Table and Return Profiles Table. For explanatory variables, the banks' dynamic gaps, opacy ratios, liquidity ratios, and solvency ratios are transformed from the Portfolios Table in connection with the Obligations Table.

The derivation of expected loss and unexpected loss (CAR) is obtained using the following formula:

CAR = k (D_max - D_avg) E

where:

k = 1.96 standard deviation associated with the 2.5% tolerance level (a )

D_max = Upper bound of unexpected losses

D_avg = Mean of expected losses

E = Notional amounts exposed to portfolio risks

The formula used to derive RAROC is as follow:

RAROC = (Earnings - Expected Losses)/CAR

The first table is called the bank's "Capital Profile," which is derived from both balance sheet and income statement of the bank. In there, the banks' realized credit and market losses are manipulated as well as their reserves in order to arrived at the CAR measure. The end results of this Capital Profile are the dependent variable proxies for the bank's cushion signaling behavior. The second table is prepared for deriving the bank's "Return Profile" based on the bank's income statement data. This Return Profile will represent the dependent variable proxies for bank performance signaling behavior.

(Figures in million U.S. dollars unless otherwise specified)

(Figures in million U.S. dollars unless otherwise specified)

Statistical Method

Within the statistical phase of research, four important steps are required: 1) sampling and data collection, 2) model specification, 3) statistical estimation and inference.

Sampling and Data Collection

The sampling process adopted by this research is non-random but predetermined from the available name list of 67 largest international banks from 12 countries based upon 1998 Fortune Global500 ranking. The reason for not using randomization is that all large national banks which constitute the population in each country are known. Smaller regional banks are excluded from the research because they are more susceptible to systemic risk than large banks, which might contaminate the robustness of statistical inference. Furthermore, many of small banks do not provide complete and adequate financial data to cover the period of study.

The time span of this research is a 10-year period coverage from 1988 to 1997. This period is most appropriate because it covers the banks' financial data from the 1988 when the Basle capital ratio was first implemented until 1997 when all annual reports were completed and issued.

In terms of data collection, the author relied on two major sources: primary and secondary. The primary data come from the bank's annual reports while the secondary data are retrieved from the Standard & Poors (S&P) Global Vantage database.

Model Specification

Four statistical models are specified according to the stacked multiple regression using dummy variables to represent the country cross-section and explanatory variables to represent the time-series. Ordinary least squares (OLS) econometric assumptions of normality, homoskedasticity, and constant variance in error terms apply.

• Capital signal = S b _i(Country_i) + b ₁₃(Marginal Gap) + b ₁₄(Opacy)

• Capital signal = S b _i(Country_i) + b ₁₃(Liquidity) + b ₁₄(Solvency)

• Return signal = S b _i(Country_i) + b ₁₃(Marginal Gap) + b ₁₄(Opacy)

• Return signal = S b _i(Country_i) + b ₁₃(Liquidity) + b ₁₄(Solvency)

where:  i = 1,…,12

1 = USA;        4 = Australia;     7 = Germany;    10 = Spain
2 = Canada;    5 = France;         8 = Swiss;         11 = Japan
3 = UK;          6 = Benelux;        9 = Italy;           12 = Thailand

Statistical Estimation and Inference

Utilizing the SAS statistical program, parametric estimation can be conducted for 1) the estimation of country cross-sectional differences based on dummy parameters and 2) the estimation of time-series differences based on explanatory parameters. The resultant statistical inference includes:

Test of goodness of fit (R²)

This test provides the magnitude of explanatory power the independent variables specified in each model have in explaining the dependent variable. By using the adjusted R² instead of normal R², such explanatory power magnitudes are normalized the effect of different numbers of parameters and data points in case of unequal cells or missing variables.

Test of significant relationships (F)

Based on the analysis of variance (ANOVA) table, the resultant F-values of each regression indicate how well the set of explanatory variables in the model is related to the response variable at a pre-specified level of significance (a ). If the regression's F-value is greater than the critical F-value with a = 0.05, then there is a significant relationship between the explanatory variables and the response variable.

Test of significant parameters (t)

This test involves the estimation of each explanatory variable's parameter (b -coefficient) and how statistically significant it is in explaining the response variable. Similar to the F-value, the test of significant parameter is based on the t-value measured against the critical t-value with a = 0.05.

Test of multicollinearity (r )

Based on the correlation matrix, the test of multicollinearity is used to supplement model specification to examine whether or not the explanatory variables are not largely correlated with each other. If such is the case, then the statistical model is considered poorly specified.

Empirical Findings

Below are test statistics for hypothesis testing of the estimated parameters from the models which infer that there are significant relationships between response variables and explanatory variables.

Test of Goodness of Fit

* Hypothesis #1
** Hypothesis #2

The R² is the ratio between sum of squared regression (SSR) and sum of squared error (SSE), which measures the effectiveness of each determinant in explaining the banks' signaling behavior. Since the R² and adjusted R² in all cases are quite close to one another, it means that the models are well specified given the total number of sampling observations.

The above table shows that the adjusted R² of the first regression dominates all the rest, which implies that functional determinants are the most relevant factor in determining the signaling behavior of international banks under study. Thus, hypothesis # 1 is confirmed. When each type of signaling behavior is examined separately, it is found that prudential determinants are more relevant to return signaling behavior than to capital signaling behavior, which confirms hypothesis # 2. Still, as their adjusted R² values are very close to each other, they imply that both functional and prudential determinants have relatively equal explanatory power with regard to return signaling.

Test of Significant Relationships *

* Significance Level of 0.05

Because the F-value is derived from the ratio between the mean squared regression (MSR) and the mean squared error (MSE), which takes into account both the number of parameter and of observations in terms of degree of freedom, it provides additional information about the efficiency of each determinant in explaining the banks' signaling behavior beside the effectiveness information given by the R² and adjusted R².

At the significance level of 0.05, the F-values of all four stacked regressions are significant at every corresponding p-value. It can be inferred from the table that there are strong relationships between the determinants and the signaling behavior. However, both functional and prudential determinants exhibit a stronger link to the capital signaling behavior than to the return signaling behavior. This implies that prudential determinants have more precision (efficiency), i.e., with lower random error or disturbance, than functional determinants do in relation with signaling behavior. It is also expected that functional determinants and return signaling behavior are more latent and subject to higher random error than are prudential determinants and capital signal. And since prudential determinants are more directly imposed to banks than are functional ones and capital signaling behavior is more explicit than return signaling behavior, it should not be uncommon to see lower random error in the relationships between prudential determinants and capital signaling behavior.

Cushion Signal vs. Functional Determinants

Performance Signal vs. Functional Determinants

Cushion Signal vs. Prudential Determinants

Performance Signal vs. Prudential Determinants

In terms of individual parameter estimation, more detail information can be uncovered from the test of significant parameters using t-value. At the same level of significance of 0.05, the above tables provide test statistics, including the b coefficients, standard errors of the b coefficients, t-values, and their corresponding p-values, for making inference.

With regard to functional determinants in the first two tables, majority of cross-sectional country parameters is statistically significant with respect to both capital and return signaling behavior. This implies that functional regulation tends to be internationally effective in inducing banks' signaling behavior. Considering the prudential determinants in the last two tables, only one of the time-series parameters is statistically significant, i.e., solvency ratio. The country parameter representing Thailand turns out to be significant in terms of prudential regulation. This is the case because Thai banking industry has been subject to tight prudential restriction than its counterparts in the industrialized countries. Parameter-wise, it can therefore be inferred that functional determinants are more relevant to bank's signaling behavior than prudential determinants.

Test of Multicollinearity

From the correlation matrix outputs, all explanatory variables are properly specified in the models. More specifically, Gap and Solvency tend to correlate 36.8% of a time. Opacy and Liquidity tend to correlate 23.7% of a time. Gap and Opacy are least correlated -3.4% of a time. Liquidity and Solvency are less correlated 14.5% of a time.

Summary and Conclusions

Major Findings

Based on the above empirical results, it can first be concluded from the test of significant relationships that both types of determinants are able to explain the banks' capital and return signaling behavior statistically well. The second conclusion drawn from the test of goodness of fit is that functional determinants can explain capital signaling better than prudential determinants. With the relatively equal explanatory power of both groups of determinants, the third conclusion follows that prudential determinants can explain return signaling as good as functional determinants. In terms of parametric estimation, it can be concluded that both types of behavior are sensitive cross-sectionally to functional determinants, while only capital signaling behavior is sensitive time-serially to prudential determinants, especially the solvency ratio. An explanation as to why only solvency ratio has become the only significant parameter for capital signaling behavior is that it has a direct bearing on how banks adjusted their capital structures over time, while other parameters do not.

Policy Implications

For the purposes of policy formulation and implementation following the major conclusions outlined above, prudential regulation on banks' capital adequacy ratios is likely to be less effective and more costly than employing the model-based incentives. The obvious rationale for this implication is that in the event of systemic crisis after bank runs and depositor runs, the government through the central bank would inevitably intervene to subsidize the banking industry at the expense of taxpayers. This potentially high rescue cost could be avoided if functional regulation is used in place of prudential regulation whereby market discipline will differentiate poorly-managed banks from the well-performed ones which provides early warning signals for an orderly repercussion within the banking industry..

The benefit of prudential regulation can still be reaped from its focus on competitive efficiency of the banking industry, as the empirical findings suggests that prudential regulation is as relevant to return signaling behavior as functional regulation. In this case, the line of segregation can be established between the two regulatory approaches whereby functional regulation is used as an appropriate framework for capital signaling behavior inducement whereas the prudential regulation is adapted or shifted to promote return signaling behavior and competitive performance of the banks.

For regulatory evaluation purposes, the research has found that functional regulation is more universal across nations even among less developed countries (in the case of Thailand) while the Basle Accord has been quite effective over the last decade in improving banks’ capital base. With the ongoing modification in the capital adequacy directive to include the VAR measure of market risk element in bank capital, it is expected that large international banks will be able to comply with international mandates with less difficulty.

Research Limitations

Four areas of limitation are identified in this research. The first is concerned with the availability of primary data from some banks. Most international banks provided their corporate annual reports from 1991 onwards even though the intended time span of the research is from 1968 to 1997. A few of them were able to provide a complete set of financial data as requested. Therefore, the use of secondary data from Standard & Poors Global Vantage database to supplement the primary source becomes more important from the lack of data and for numerical consistency purposes.

The second limitation deals with the adequacy of less developed countries' representation in the sample. Although the main objective of this research is to study the behavior of top largest international banks in the world, several leading banks in the emerging and less developed countries (LDC) should not be ignored. In order to fix such a deficiency, a sample of banks in Thailand is included as a representative of LDC banks. Using Thai banks' data is very relevant because the dawn of global financial crisis was originated from the collapse of the banking industry in Thailand. The knowledge and familiarity of the author about Thai banks are also of great benefit since follow-up or country-specific research programs can be conducted more conveniently. Still, the inclusion of more representative banks from LDCs would certainly have enhanced the scope of this study.

For technical limitations, inconsistency in financial reporting formats across different countries is deemed to be a crucial concern. Many banks report their reserves for credit and market risks on the asset side, others on the liability side. This affects their relative balance sheets which require further data manipulation and transformation. Another difficulty is on the disclosure and classification of off-balance-sheet items. Most European banks are able to disclose their off-balance-sheet activities better than the rest of the sample banks. In order to normalize these deficiencies, the standard financial statement formats presented by S&P Global Vantage database have been fully utilized.

Despite the use of S&P database, the classification between the types of off-balance-sheet items remains a clear restriction. The database does not differentiate between the commitment type and the contingent type of off-balance-sheet activities as they possess varying degrees of risk exposure. In essence, the commitment transactions involve guarantees and stand-by credits and loans that have the futures contract characteristics whereas the contingent transactions are much like the options contracts in which off-balance-sheet instruments are transacted conditionally. It is, therefore, based on the author' s judgement, not objectivity, that in which types of off-balance-sheet instruments used by banks should fall between the two categories.

Future Research Directions

What have been accomplished so far in this research are the answers to why prudential regulation becomes less effective to induce banks to signal their hidden information about their capital cushion and what should be done to improve or correct the current systems. The tasks that remain are the answers to how prudential regulation can technically be improved to make banks more competitive and how functional regulation can be standardized to make the model-based measures more transparent. The theme for this future research is properly labeled "regulatory replications" whereby banking regulations are internalized for involved market participants to make regulatory and supervisory systems work more efficiently and effectively.

The future research directions can be approached from two perspectives . From a qualitative angle, the impacts of alternative model-based regulations on systemic stability could be studied. Quantitatively, the modeling of prudential regulation that is tied to competitive performance of the banking industry vis-a -vis other non-bank financial services ind ustries, e.g., securities and insurance, should be explored. These entail more elaborately designed empirical research and mathematical modeling both on the intra-industry and inter-industry cross-sectional scales. In addition, more robust non-linear econometric models will be employed to these future studies in terms of time-series analysis.

At present, there has been an increasing trend of advanced research in the areas of financial intermediation and regulation at both domestic and international levels. What have been theoretically conceptualized and empirically proven in the economics of monetary and capital markets as well as the economics of corporate finance can be extended to banking and financial services industries. It is, therefore, optimistically expected that the momentum of this rudimentary research shall continue well into and gain more participation in the twenty-first century.

References

Anderson, Ronald W., and Suresh Sundaresan. "Design and Valuation of Debt Contracts." The Review of Financial Studies 9 (Spring 1996): 37-68.

Berkovitch, Elazar, and Ronen Israel. "The Design of Internal Control and Capital Structure." The Review of Financial Studies 9 (Spring 1996): 209-240.

Bessis, Joël. Risk Management in Banking. New York: John Wiley & Sons, 1998.

Crockett, Andrew. "The Changing Role of Central Banks." The Money Macro and Finance Annual Conference. Durham, 11 Sep. 1997.

Culp, Christopher L. "Functional and Institutional Interaction, Regulatory Uncertainty, and the Economics of Derivatives Regulation." The Financier 2 (1995): 458-487.

Diamond, D. "Financial Intermediation and Delegated Monitoring." Review of Economic Studies 51 (1984): 393-414.

Diamond, D., and Phillip Dybvig. "Bank Runs, Deposit Insurance, and Liquidity." Journal of Political Economy 91 (1983): 401-419.

Dybvig, Phillip H., and Jaime F. Zender. "Capital Structure and Dividend Irrelevance with Asymmetric Information." Review of Financial Studies 4 (1991): 201-219.

Edwards, Franklin R. The New Finance: Regulation and Financial Stability. Washington, D.C.: American Enterprise Institute for Public Policy Research Press, 1996.

Giammarino, R.M., and E.H. Neave. "The Failure of Financial Contracts and the Relavance of Financial Policy." Working paper No. 82-3. Queen's University, Kingston, Ontario, 1982.

Greenspan, Alan. "The Role of Capital in Optimal Banking Supervision and Regulation." The Conference on Capital Regulation in the 21st Century. New York, 26 Feb. 1998.

Jensen, M.C., and W. Meckling. "Theory of the Firm: Managerial Behavior, Agency Costs and Capital Structure." Journal of Financial Economics 3 (1976): 305-360.

Jorion, Philippe. Value at Risk: The New Benchmark for Controlling Derivative Risk. New York: McGraw-Hill, 1997.

Kane, Edward J. "Competitive Financial Reregulation: An International Perspective." Threats to International Financial Stability. Ed. Richard Portes and Alexander K. Swoboda. Cambridge, UK: Cambridge University Press, 1987. 111-149.

__________. "How Market Forces Influence the Structure of Financial Regulation." Restructuring Banking and Financial Services in America. Ed. William S. Haraf and Rose Marie Kushmeider. Washington, D.C.: American Enterprise Institute for Public Policy Research Press, 1988. 343-382.

__________. "Ethical Foundations of Financial Regulation." Journal of Financial Services Research 12 (1997): 51-74.

Merton, Robert C. "On the Application of the Continuous-Time Theory of Finance to Financial Intermediation and Insurance." The Geneva Papers on Risk and Insurance 14, Jul. 1989: 225-262.

__________. "Operation and Regulation in Financial Intermediation: A Functional Perspective." Working paper No. 93-020. Harvard University, Graduate School of Business Administration, Boston, MA, 1992.

Merton, Robert C., and Zvi Bodie. "A Conceptual Framework for Analyzing the Financial Environment." The Global Financial System: A Functional Perspective. By Dwight B. Crane, et al. Boston, MA: Harvard University Press, 1995. 3-31.

__________. "Financial Infrastructure and Public Policy: A Functional Perspective." The Global Financial System: A Functional Perspective. By Dwight B. Crane, et al. Boston, MA: Harvard University Press, 1995. 263-282.

Mishkin, Frederic S. The Economics of Money, Banking, and Financial Markets. Boston, MA: Little, Brown and Co., 1986.

Modigliani, Franco, and Merton H. Miller. "The Cost of Capital, Corporation Finance, and the Theory of Investment." American Economic Review 48 (1958): 261-297.

__________. "Corporate Income Taxes and the Cost of Capital: A Correction." American Economic Review 53 (1963): 433-443.

Muller, Huib. "Supervisory Cooperation: A Condition for Fair Competition in International Banking." Competition and Cooperation in World Banking. London: The Institute of Bankers, 1985. 41-60.

Myers, Stewart C., and Nicholas S. Majluf. "Corporate Financing and Investment Decision When Firms Have Information that Investors Do Not Have." Journal of Financial Economics 13, (1984): 187-221.

Myers, Stewart C., and Raghuram G. Rajan. "The Paradox of Liquidity." Working Paper No.5143. National Bureau of Economic Research, 1995.

Perold, Andre F. "The Payment System and Derivative Instruments." The Global Financial System: A Functional Perspective. By Dwight B. Crane et al. Boston, MA: Harvard University Press, 1995. 33-79.

Ross, Stephen A. "The Determination of Financial Structure: The Incentive-Signalling Approach." Bell Journal of Economics 8 (1977): 23-40.

__________. "Institutional Markets, Financial Marketing, and Financial Innovation." Journal of Finance 44, Jul. 1989: 541-556.

Smith, Roy C., and Ingo Walter. Global Banking. Oxford: Oxford University Press, 1997.

Stigler, George J. "The Theory of Economic Regulation." Bell Journal of Economics and Management Science 2 (1971): 2-19.

Walmsley, Julian. New Financial Instruments. 2^nd Ed. New York: John Wiley & Sons, Inc., 1998.

Back to Top

About the Author

* Worapot Ongkrutaraksa is currently a senior lecturer of finance at Curtin University's School of Economics & Finance, Australia. He used to conduct his post-graduate research in financial economics at Kent State University and international political economy at Harvard University through the Fulbright sponsorship between 1995 and 1998.

E-mail: [email protected]

Home Page