1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

We present a qualitative and quantitative analysis of the standard growth model modified to include precautionary saving motives and liquidity constraints. We address the impact on the aggregate saving rate, the importance of asset trading to individuals, and the relative inequality of wealth and income distributions.

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Uninsured Idiosyncratic Risk and Aggregate Saving

This paper provides a review of the theory of the determinants of individual and national thrift that has come to be known as the Life Cycle Hypothesis (LCH) of saving. Applications to some current policy issues are also discussed. Part I deals with the state of the art on the eve of the formulation of the LCH some 30 years ago. Part II sets forth the theoretical foundations of the model in its original formulation and later amendment, calling attention to various implications, distinctive to it and, sometimes, counter-intuitive. It also includes a review of a number of crucial empirical tests, both at the individual and the aggregate level. Part III reviews some applications of LCH to current policy issues, though only in sketchy fashion, as space constraints prevent fuller discussion.(This abstract was borrowed from another version of this item.)

Life Cycle, Individual Thrift and the Wealth of Nations

Microdata studies of household saving often find a significant group in the population with virtually no wealth, raising concerns about heterogeneity in motives for saving. In particular, this heterogeneity has been interpreted as evidence against the life-cycle model of saving. This paper argues that a life-cycle model can replicate observed patterns in household wealth accumulation after accounting explicitly for precautionary saving and asset-based means- tested social insurance. We demonstrate theoretically that social insurance programs with means tests based on assets discourage saving by households with low expected lifetime income. In addition, we evaluate the model using a dynamic programming model with four state variables. Assuming common preference parameters across lifetime- income groups, we are able to replicate the empirical pattern that low-income households are more likely than high-income households to hold virtually no wealth. Low wealth accumulation can be explained as a utility-maximizing response to asset-based means-tested welfare programs.

Precautionary Saving and Social Insurance

The staff members of the Board of Governors of the Federal Reserve System and of the Federal Reserve Banks undertake studies that cover a wide range of economic and financial subjects. From time to time the studies that are of general interest are published in the Staff Studies series and summarized in the Federal Reserve Bulletin.

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165 The Demand for Trade Credit: An Investigation of Motives for Trade Credit Use by Small Businesses

A longstanding and contentious problem in the antitrust analysis of proposed bank mergers has been the definition of the geographic area and services that constitute a particular market for financial services. The issues involved can be illustrated by two questions that arise in the following example. A commercial bank wants to acquire another located in the same metropolitan area. If one considers only the banks in that area, the acquisition would apparently reduce competition for banking services in that locality. The first question is, Does the presence of commercial banks outside the area mitigate the anticompetitive effects? The second is, Would the anticompetitive effects be lessened if nonbank institutions in the area offered some (but not all) of the services offered by the two banks? Any definition of a banking market implies answers to these questions regarding the geographic extent of that market and the scope of services to be included. Although buttressed by recent general empirical evidence and market surveys conducted in specific cases, the definition of banking markets has generally relied on Supreme Court decisions from the 1960s and early 1970s. Given the deregulation and financial

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Banking Markets and the Use of Financial Services by Small and Medium-Sized Businesses

Because wealth estimates from survey data have usually fallen substantially short of independent aggregate estimates, survey data have not been seen as adequate for assessing questions dependent on a good representation of the entire distribution of wealth, such as estimates of wealth concentration. The 1983 Survey of Consumer Finances (SCF), which contains a supplementary sample of very high income households drawn from a tax-file sample frame, is the first U.S. survey since the 1963 Survey of Financial Characteristics of Consumers that offers hope of accurately measuring the entire wealth distribution. In this paper, we discuss the design of the survey, the critical issue of proper weighting to merge the supplementary sample with an area probability sample, and the role of imputation. We show that the use of ordinary area probability samples alone leads to probable bias in the measurement of highly concentrated assets such as stocks and bonds. We compare the SCF data with aggregates derived from the flow-of-funds accounts of the Federal Reserve Board. While methodological issues cloud exact comparisons, it appears overall that the SCF estimates are at least as credible as other aggregate measurements. Finally, we use the data to assess the change in concentration of wealth from 1963 to 1983. We estimate that the concentration of wealth in terms of households did not change significantly over this period.

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Measuring wealth with survey data: an evaluation of the 1983 survey of consumer finances

Survey of consumer finances, 1983

Consumer Finance in 1969. During its 3-year existence the Commission coordinated a massive research program to study the operation of consumer credit markets in the United States. Delivered to Congress in 1972, the Commission's multi-volume report established the value of academic research for guiding public policy towards markets for financial services. With a combination of foundation and corporate grants, Dr. Johnson established the Credit Research Center at Purdue to provide an ongoing means of directing academic research expertise toward practical problems in consumer and mortgage credit markets. Over the past quarter-century the Center has gained a national reputation for its work in evaluating public policy toward credit markets. The Center's operations have been sustained by generous grants from both the public and private sectors. Over one hundred articles and monographs by distinguished scholars document its research product. The Center's senior research staff have frequently testified before Congress and state legislatures on such topics as Truth-in-Lending disclosures, the impact of interest rate ceilings on credit availability, equal credit opportunity regulations, personal bankruptcy, credit insurance, credit scoring, credit card usage, and the impact of privacy regulations. The value of these contributions to rational discourse stems from CRC's academic affiliation, rigorous external review of its research, and the years of research experience of its principal researchers and authors. In July of 1997 the Center relocated its offices to Georgetown University in Washington, D.C. The Center is a non-profit unit of the McDonough School of Business where it continues its tradition of non-partisan research and education on economic issues relating to consumer credit and markets for retail financial services. For more information about the Center and its publications visit its website at www.msb.edu/prog/crc. ACKNOWLEDGMENTS We are deeply grateful to Trans Union, LLC, for providing the credit report data at the core of this empirical study. We also thank the members of the Creditor Relations Committee of the National Foundation for Credit Counseling, especially Chairman Bob Runke, who provided the inspiration and creative direction to launch the project. Special thanks also go to Cecelia Diehl and all the NFCC national staff who have provided guidance and comments throughout the project. Stephanie Wilshusen at the Credit Research Center provided expert statistical support in the construction of the empirical models. Credit Research Center Advisory Council members provided many helpful comments that improved the analysis. Last, but certainly not least, we thank the five participating agencies for sharing …

Gregory E. Elliehausen

Papers

165 The Demand for Trade Credit: An Investigation of Motives for Trade Credit Use by Small Businesses

Banking Markets and the Use of Financial Services by Small and Medium-Sized Businesses

Measuring wealth with survey data: an evaluation of the 1983 survey of consumer finances

Survey of consumer finances, 1983

The impact of credit counseling on subsequent borrower credit usage and payment behavior