Econometric policy evaluation: A critique

Enclosed is a copy of the Board of Governors’ Semiannual Agenda of Regulations for the period August 1, 1980 through February 1, 1981. The Semiannual Agenda provides you with information on those regulatory matters that the Board now has under consideration or anticipates considering over the next six months, and is divided into three parts: (1) regulatory matters that the Board had considered during the previous six months on which final action has been taken; (2) regulatory matters that have been proposed for public comment and that require further Board consideration; and (3) regulatory matters that the Board may consider over the next six months.

Federal Reserve Bank of New Yorkの制定せる財務諸表様式について

Financial systems are crucial to the allocation of resources in a modern economy. They channel household savings to the corporate sector and allocate investment funds among firms; they allow intertemporal smoothing of consumption by households and expenditures by firms; and they enable households and firms to share risks. These functions are common to the financial systems of most developed economies. Yet the form of these financial systems varies widely. In the United States and the United Kingdom competitive markets dominate the financial landscape, whereas in France, Germany, and Japan banks have traditionally played the most important role. Why do different countries have such different financial systems? Is one system better than all the others? Do different systems merely represent alternative ways of satisfying similar needs? Is the current trend toward market-based systems desirable? Franklin Allen and Douglas Gale argue that the view that market-based systems are best is simplistic. A more nuanced approach is necessary. For example, financial markets may be bad for risk sharing; competition in banking may be inefficient; financial crises can be good as well as bad; and separation of ownership and control can be optimal. Financial institutions are not simply veils, disguising the allocation mechanism without affecting it, but are crucial to overcoming market imperfections. An optimal financial system relies on both financial markets and financial intermediaries.

比较金融系统 = Comparing financial systems

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Likelihood Based Inference In Cointegrated Vector Autoregressive Models

Comparing financial systems.

This paper describes a financial stress index for the United States, the CFSI, which provides a continuous signal of financial stress and broad coverage of the areas that could indicate it. The index is based on daily public market data collected from four sectors of the financial markets – credit markets, foreign exchange markets, equity markets, and interbank markets. A dynamic weighting method is employed to capture changes in the relative importance of these four sectors as they occur. In addition, the design of the index allows the origin of the stress to be identified. We compare the CFSI to alternative indexes using a detailed benchmarking methodology and show how the index can be applied to systemic stress monitoring and early warning system design. To that end, we investigate alternative stress signaling thresholds and frequency regimes and establish optimal frequencies for filtering out market noise and idiosyncratic episodes. Finally, we quantify a powerful CFSI-based rating system that assigns a probability of systemic stress to ranges of CFSI outcomes.

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The Financial Stress Index: Identification of Systemic Risk Conditions

From the financial supervisor’s point of view, an early warning system involves an ex-ante approach to regulation, targeting to predict and prevent crises. An efficient EWS allows timely ex-ante policy action and can reduce the need for ex-post regulation. This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to propose a hybrid class of models for systemic risk incorporating the structural characteristics of the financial system and feedback amplification mechanism. The models explain financial stress using data from five largest bank holding companies, regressing institutional imbalances using an optimal lag method. Z‐scores of institutional data are justified as explanatory imbalances. The models utilize both public and proprietary supervisory data. The SAFE EWS monitors micro-prudential information from systemically important institutions to anticipate build-up of macro-economic stresses in the financial markets at large. To the supervisor, SAFE presents a toolkit of possible institutional supervisory actions that can be used to diffuse the build-up of systemic stress in the financial markets. A hazard inherent for all ex-ante models is that the model uncertainty may lead to wrong policy choices. To mitigate this risk, SAFE develops two modeling perspectives: a set of medium term (six-quarter) forecasting specifications to allow the policymakers sufficient time for ex-ante policy action, and a set of short term (two-quarter) forecasting specifications for verification and adjustment of supervisory actions. Individual financial institutions may utilize public version of SAFE EWS to enhance systemic risk stress testing and scenario analysis. The paper shows econometric results and robustness support for the SAFE set of models. Discussion of results addresses usability and tests of usefulness of supervisory data. In addition, the paper investigates and suggests levels for action thresholds appropriate for this EWS.

/pdf/safe-an-early-warning-system-for-systemic-banking-risk-2xyc67cbbv.pdf

SAFE: An Early Warning System for Systemic Banking Risk

Growing complexity and episodic turmoil in the financial system call for reassessment of existing early warning systems (EWSs) for systemic risk. This paper critically reviews the extensive EWS literature and typology and proposes a new class of supervisory models. The paper also discusses important design implications for an efficient EWS. The new class of supervisory models for systemic risk should be built from an integrated perspective and model EWS according to the users' objectives and competencies. It should incorporate both microprudential and macroprudential perspectives, as well as the structural considerations of the financial system itself. From the financial supervisor's point of view, an EWS involves an ex ante approach to regulation designed to highlight conditions that have in the past been associated with systemic risk. Forward-looking supervisory instruments become more important as they allow ex ante policy action and can reduce the need for ex post regulation.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2246110_code1446362.pdf?abstractid=2244422&mirid=1

Early Warning Systems for Systemic Banking Risk: Critical Review and Modeling Implications

This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk, incorporating the structural characteristics of the financial system and a feedback amplification mechanism. The models explain financial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the financial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifications that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifications for verification and adjustment of supervisory actions. This paper highlights the application of these models to stress testing, scenario analysis, and policy.

/pdf/safe-an-early-warning-system-for-systemic-banking-risk-4phc292hea.pdf

SAFE: An early warning system for systemic banking risk

This study analyses the relationship between corporate sustainability and corporate risk. Different grades of sustainability are constructed from the inclusion of companies into sustainability indices and the number of years included. The grades are measured against variables of expected and unexpected risk and drivers of a sustainable company’s risk (sustainability risk). Based on the assumption that the level of sustainability impacts upon the dimension of risk, a sample of 167 European companies and different subsamples are assessed on available accounting data. However, the findings do not provide any clear evidence, suggesting that companies, once rated as sustainable, display similar patterns of risk and that a high degree of sustainability may be achieved without adverse impacts on risk and risk-adjusted return.

Dieter Gramlich

Papers

The Financial Stress Index: Identification of Systemic Risk Conditions

SAFE: An Early Warning System for Systemic Banking Risk

Early Warning Systems for Systemic Banking Risk: Critical Review and Modeling Implications

SAFE: An early warning system for systemic banking risk

Corporate sustainability and risk