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

https://link.springer.com/content/pdf/10.1057/jors.1979.126.pdf

Forecasting Economic Time Series

The R package partykit provides a flexible toolkit for learning, representing, summarizing, and visualizing a wide range of tree-structured regression and classification models. The functionality encompasses: (a) basic infrastructure for representing trees (inferred by any algorithm) so that unified print/plot/predict methods are available; (b) dedicated methods for trees with constant fits in the leaves (or terminal nodes) along with suitable coercion functions to create such trees (e.g., by rpart, RWeka, PMML); (c) a reimplementation of conditional inference trees (ctree, originally provided in the party package); (d) an extended reimplementation of model-based recursive partitioning (mob, also originally in party) along with dedicated methods for trees with parametric models in the leaves. Here, a brief overview of the package and its design is given while more detailed discussions of items (a)-(d) are available in vignettes accompanying the package.

/pdf/partykit-a-modular-toolkit-for-recursive-partytioning-in-r-24qoeyflxj.pdf

Partykit: a modular toolkit for recursive partytioning in R

What manner of organization is the National Bureau of Economic Research? How does it select research topics? Who does the work and what kind of tasks do they perform? Where do the funds come from? How does the National Bureau safeguard the scientific quality of its findings? How are the results disseminated? Visitors to the National Bureau often ask these and similar questions; perhaps the answers will be of interest to readers of the American Statistician. The National Bureau of Economic Research is a private non-profit corporation, formed, according to its charter, "to conduct, or assist in the making of exact and impartial investigations in the field of economic, social and industrial science, and to this end to cooperate with governments, universities, learned societies, and individuals." Hence it is not a government agency, nor an adjunct of a university, nor does it sell research services. The revenue from the only products it does sell, publications, barely covers the printing costs. Its funds are contributed by philanthropic foundations, by trade and professional organizations, by business concerns, trade unions, and individuals. Contributions are usually on a yearly basis, but some grants cover several years. Some of the funds are earmarked for specific studies; the balance goes to support a general program of research. The National Bureau is governed by a Board of Directors numbering about thirty, selected to represent various institutions and diverse points of view on economic problems. Over the years since the Bureau was founded in 1920 this body of men has made a significant contribution to the development of scientific inquiry in economics, both within the National Bureau and outside. Such outstanding economists as Wesley C. Mitchell, George E. Roberts, Allyn A. Young, Edwin F. Gay, Thomas S. Adams, and John R. Commons have been among its members. At the present time professors from a dozen universities are on the Board. Also, Directors from each of the following organizations are elected: American Statistical Association, American Economic Association, American Farm Economic Association, Economic History Association, American Institute of Accountants, American Management Association, Congress of Industrial Organizations, and American Federation of Labor. Finally, there is a group of Directors at Large, men from varied walks of life with an abiding interest in economic research. The Board serves an important function not only in shaping the broad lines of the research program but also in safeguarding the quality of the results. Matters of policy requiring prompt action are handled by an Executive Committee of eleven, elected by the Board from its membership. Arthur F. Burns, the Director of Research, is the member of the Committee who is directly responsible for the research program. The members of the research staff, numbering about twenty-five, direct the individual studies, and are aided in their work by upwards of forty-five research assistants. A staff of typists, bookkeepers, mimeograph operators, etc., brings the total payroll of the National Bureau to roughly a hundred persons. William J. Carson, the Executive Director, handles the Bureau's finances, accounts, and other administrative matters. Not all the employees of the National Bureau work at the main office at 1819 Broadway, New York City. DuLr Financial Research Program is housed at "Hillside," an estate about 10 miles north of Manhattan overlooking the HuLdson River. Other National BureauL investigators are to be fotund at various universities throughout the United States, since cooperative arrangements are maintained with a number of universities that permit their facultv members to engage in National Butreau studies. Government agencies, too, cooperate in similar ways. Such cooperative relationships are a vital feature of our work, and we try to foster them in many ways. The growing acceptance on the part of universities of the view that research is part of the job of a faculty member has helped to make these efforts productive. For example, for a number of years we have appointed promising young men or women holding university positions as Research Associates for one year. The objective is to enable scholars to pursue their research interests in fields in which the National Bureau also has an interest. Since 1930 twenty-six Research Associates, coming from eighteen American colleges or universities and two foreign universities, have been appointed under the plan. The work of several committees is another example of cooperation for the purpose of advancing research. Two committees, one on financial and the other on fiscal research, help to guide our studies in these areas. They are composed of experts from universities, government agencies, and private business. In 1935 the Universities-National Bureau Committee was established for the express purpose of promoting contact

The National Bureau of Economic Research

Credit cycles have been a characteristic of advanced economies for over 100 years On average, a sustained pick-up in the ratio of credit to GDP has been highly correlated with banking crises The boom phases of the cycle are characterised by large deviations in credit from trend A range of mechanisms can generate these effects, each of which has strategic complementarity between banks at its core Macro-prudential policy could curb these credit cycles, both through raising the cost of maintaining risky portfolios and through an expectations channel that operates via banks' perceptions of other banks' actions

http://www3.tcmb.gov.tr/konferanslar/financial_stability/Conference_files/Curbing_the_Credit_Cycle.pdf

Curbing the Credit Cycle

In this paper we provide a review of the literature on the link between stock market volatility and aggregate demand. In particular, we focus on the implications of the so-called uncertainty hypothesis according to which it is primarily the uncertainty associated with stock market fluctuations that influences aggregate demand. Empirical studies find that stock market volatility indeed feeds back into the real economy.

Stock Market Volatility and the Business Cycle

We investigate the risk of holding credit default swaps (CDS) in the trading book and compare the Value at Risk (VaR) of a CDS position to the VaR for investing in the respective firm's equity using a sample of CDS - stock price pairs for 86 actively traded firms over the period from March 2003 to October 2006. We find that the VaR for a stock is usually far larger than the VaR for a position in the same firm's CDS. However, the ratio between CDS and equity VaR is markedly smaller for firms with high credit risk. The ratio also declines for longer holding periods. We also observe a positive correlation between CDS and equity VaR. Panel regressions suggest that our findings are consistent with qualitative predictions of the Merton (1974) model.

https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=2794016

A Value at Risk Analysis of Credit Default Swaps

We study the development of bank lending in the USA after four large jumps in uncertainty using an event study approach. We find that more liquid banks slow down and lend less after a surge in uncertainty. Lending by smaller banks is also less responsive to increases in uncertainty, which points to an increased importance of bank–customer relationships. For capitalization, we find mixed evidence. These heterogeneities across banks suggest that declines in bank lending following increases in uncertainty result at least partly from a reduced supply of bank loans.

/pdf/do-banks-lend-less-in-uncertain-times-4f99lpfpc9.pdf

Do Banks Lend Less in Uncertain Times

This paper uses regression analysis to compare the market pricing of the default risk of banks to that of other firms We study how CDS traders discriminate between banks and other type of firms and how their judgement changes over time, in particular, since the start of the recent financial turmoil We use monthly data on the Credit Default Swaps (CDS) of 41 major banks and 162 non-banks By means of panel analysis, we decompose the CDS premia into the expected loss and the risk premium Our primary result is that market participants indeed viewed banks differently and that they drastically changed their mind during the recent turmoil that started in August 2007

/pdf/are-banks-different-evidence-from-the-cds-market-47497y4dvq.pdf

Are Banks Different? Evidence from the CDS Market

This paper tests whether the results from standard structure-conduct-performance [SCP] models estimated at the industry level are sensitive to the degree of heterogeneity of the firms in the industries. Industries are separated into homogeneous and heterogeneous categories depending on whether the profit rates of firms within an industry converge on a common value or not. In “homogeneous” industries we find that both the long-run projected returns on assets for the industries and Bureau of Census price-cost-margins are well explained by variables usually included in SCP models, as in particular industry concentration. In contrast, few if any of the usual SCP-model variables are statistically significant in the regressions for heterogeneous industries.

Burkhard Raunig

Papers

Stock Market Volatility and the Business Cycle

A Value at Risk Analysis of Credit Default Swaps

Do Banks Lend Less in Uncertain Times

Are Banks Different? Evidence from the CDS Market

Heterogeneities within Industries and Structure-Performance Models