The author systematically examines one of the important issues of information — establishing the market price. He introduces the concept of «search» — where a buyer wanting to get a better price, is forced to question sellers. The article deals with various aspects of finding the necessary information.

Economics of Information

Publisher Summary This chapter reviews the supply chain coordination with contracts. Numerous supply chain models are discussed. In each model, the supply chain optimal actions are identified. The chapter extends the newsvendor model by allowing the retailer to choose the retail price in addition to the stocking quantity. Coordination is more complex in this setting because the incentives provided to align one action might cause distortions with the other action. The newsvendor model is also extended by allowing the retailer to exert costly effort to increase demand. Coordination is challenging because the retailer's effort is noncontractible—that is, the firms cannot write contracts based on the effort chosen. The chapter also discusses an infinite horizon stochastic demand model in which the retailer receives replenishments from a supplier after a constant lead time. Coordination requires that the retailer chooses a large basestock level.

Supply Chain Coordination with Contracts

Persistent racial inequality in employment, housing, and a wide range of other social domains has renewed interest in the possible role of discrimination. And yet, unlike in the pre–civil rights era, when racial prejudice and discrimination were overt and widespread, today discrimination is less readily identifiable, posing problems for social scientific conceptualization and measurement. This article reviews the relevant literature on discrimination, with an emphasis on racial discrimination in employment, housing, credit markets, and consumer interactions. We begin by defining discrimination and discussing relevant methods of measurement. We then provide an overview of major findings from studies of discrimination in each of the four domains; and, finally, we turn to a discussion of the individual, organizational, and structural mechanisms that may underlie contemporary forms of discrimination. This discussion seeks to orient readers to some of the key debates in the study of discrimination and to provide a roadmap for those interested in building upon this long and important line of research.

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The Sociology of Discrimination: Racial Discrimination in Employment, Housing, Credit, and Consumer Markets

Financial literacy (or financial knowledge) is typically an input to model the need for financial education and explain variation in financial outcomes. Defining and appropriately measuring financial literacy is essential to understand educational impact as well as barriers to effective financial choice. This article summarizes the broad range of financial literacy measures used in research over the last decade. An overview of the meaning and measurement of financial literacy is presented to highlight current limitations and assist researchers in establishing standardized, commonly accepted financial literacy instruments.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1945216_code425144.pdf?abstractid=1945216&mirid=3

Measuring Financial Literacy

Policy makers have embraced financial education as a necessary antidote to the increasing complexity of consumers' financial decisions over the last generation. We conduct a meta-analysis of the relationship of financial literacy and of financial education to financial behaviors in 168 papers covering 201 prior studies. We find that interventions to improve financial literacy explain only 0.1% of the variance in financial behaviors studied, with weaker effects in low-income samples. Like other education, financial education decays over time; even large interventions with many hours of instruction have negligible effects on behavior 20 months or more from the time of intervention. Correlational studies that measure financial literacy find stronger associations with financial behaviors. We conduct three empirical studies, and we find that the partial effects of financial literacy diminish dramatically when one controls for psychological traits that have been omitted in prior research or when one uses an instrument for financial literacy to control for omitted variables. Financial education as studied to date has serious limitations that have been masked by the apparently larger effects in correlational studies. We envisage a reduced role for financial education that is not elaborated or acted upon soon afterward. We suggest a real but narrower role for “just-in-time” financial education tied to specific behaviors it intends to help. We conclude with a discussion of the characteristics of behaviors that might affect the policy maker's mix of financial education, choice architecture, and regulation as tools to help consumer financial behavior.

This paper was accepted by Uri Gneezy, behavioral economics.

https://pubsonline.informs.org/doi/pdf/10.1287/mnsc.2013.1849

Financial Literacy, Financial Education, and Downstream Financial Behaviors

The current research examines the relationship between consumer financial knowledge, income, and locus of control on financial behavior. Ethnicity is included as a potential moderator of the effects of these three variables on financial behavior. Findings suggest that consumers’ propensity to save, budget, and control spending depends partly on their level of perceived control over outcomes as well as knowledge and financial resources. Evidence of race and ethnicity as moderators is mixed.

Who Is in Control? The Role of Self‐Perception, Knowledge, and Income in Explaining Consumer Financial Behavior

Retailer power and supplier welfare

There is considerable evidence to suggest that consumers are often misinformed about basic financial and economic principles. The purpose of this study was to examine the accuracy of consumers’ self-assessments of their credit ratings. Findings suggest that approximately 32 percent of consumers overestimate their credit ratings, while only 4 percent underestimate their credit ratings. Those who overestimate their credit quality are less knowledgeable about financial matters in general and are more likely to have acquired their financial knowledge from difficult past experiences. In addition, consumers who overestimate their credit ratings are less likely to budget, save, or invest regularly. There is considerable evidence to suggest that in general, consumers are unaware or misinformed about basic financial and economic principles— information they need in order to make important decisions such as buying a home and planning for retirement (Chen and Volpe 1998; Hogarth and Hilgert 2002; Lee and Hogarth 1999; Mandell 2006). This issue has gained more attention recently as a result of concerns about borrowers in the subprime market obtaining mortgages that they cannot afford. There is little known about the specific nature of this lack of awareness and misinformation. Credit scores are designed to measure credit risk at a particular point in time and are based on models that use information in consumer credit reportsmaintainedat thecredit reportingagencies topredictfuturepayment behavior(Fair Isaacs16). Lendersusecredit scores tohelp them makelending decisions, although each lender may differ in terms of the level of risk it finds acceptable, and this may even vary for different types of loans. Higher scores indicatelowercredit risks orhigher credit quality, althoughnosingle cutoff score is used by all lenders. Previous research on biases in judgment and decision making has shown that individuals tend to display overconfidence about their knowledge and

Is Ignorance Bliss? Consumer Accuracy in Judgments about Credit Ratings

Automated underwriting (AU) systems have become the tool of choice in mortgage lending decisions. While these systems provide significant benefits to mortgage originators and investors, questions have been raised about their impact on underserved populations. The questions focus on the relative accuracy of AU compared with manual underwriting and whether AU has increased the flow of mortgage credit to underserved consumers. Using information from Freddie Mac's Loan Prospector AU service, we provide statistics useful in examining these issues. The data strongly support our view that AU provides substantial benefits to consumers, particularly those at the margin of the underwriting decision. We find evidence that AU systems more accurately predict default than manual underwriters do. We also find evidence that this increased accuracy results in higher borrower approval rates, especially for underserved applicants.

Vanessa Gail Perry

Papers

Who Is in Control? The Role of Self‐Perception, Knowledge, and Income in Explaining Consumer Financial Behavior

Retailer power and supplier welfare

Is Ignorance Bliss? Consumer Accuracy in Judgments about Credit Ratings

Automated underwriting in mortgage lending: Good news for the underserved?

Survival of the fittest: Technical assistance, survival and growth of small businesses and implications for public policy