Perverse Nudges: Minimum Payments and Debt Paydown in Consumer Credit Cards

Credit card minimum payments can act as an “anchor” that causes consumers to pay less of their debt than they otherwise would, leading to higher balances and interest costs, lower credit card scores, increased bankruptcy risks, and in the aggregate, suboptimally high levels of debt in the macro-economy. Policy “nudges,” which aim to increase the monthly amount that individuals pay on their credit card debt, have had mixed results.https://repository.upenn.edu/pennwhartonppi/1018/thumbnail.jp

Exploring the Determinants of High-Cost Mortgages to Homeowners in Low- and Moderate-Income Neighborhoods

In spite of the recent impetus to reform home mortgage markets, particularly as they affect low- and moderate-income (LMI) households, little systematic evidence is available about how potential abuses in mortgage lending manifest in the mortgages held by those households. While racial discrimination in mortgage markets has a long history in the United States, the role of mortgage brokers in lending has only recently increased and become controversial. In this chapter, we uncover two mechanisms through which differential mortgage pricing occurs among LMI homeowners: black borrowers and borrowers who use mortgage brokers pay more for mortgage loans than other borrowers, after controlling for a wide variety of factors

The labor market consequences of impatience

Standard economic theory suggests that individuals know best how to make themselves happy. Thus, policies designed to encourage more forward-looking behaviors will only reduce people's happiness. Recently, however, economists have explored the role of impatience, especially difficulties with delaying gratification, in several important economic choices. There is strong evidence that some people have trouble following through on investments that best serve their long-term interests. These findings open the door to policies encouraging or requiring more patient behaviors, which would allow people to enjoy the eventual payoff from higher initial investment. &nbsp;</p

Affordability, financial innovation and the start of the housing boom

At their peak in 2005, roughly 60 percent of all purchase mortgage loans originated in the United States contained at least one non-traditional feature. These features, which allowed borrowers easier access to credit through teaser interest rates, interest-only or negative amortization periods, and extended payment terms, have been the subject of much regulatory and popular criticism. In this paper, we construct a novel county-level dataset to analyze the relationship between rising house prices and non-traditional features of mortgage contracts. We apply a break-point methodology and find that in housing markets with breaks in the mid-2000s, a strong rise in the use of non-traditional mortgages preceded the start of the housing boom. Furthermore, their rise was coupled with declining denial rates and a shift from FHA to subprime mortgages. Our findings support the view that a change in mortgage contract availability and a shift toward subprime borrowers helped to fuel the rise of house prices during the last decade

Iterative hard thresholding in genome-wide association studies: Generalized linear models, prior weights, and double sparsity.

BackgroundConsecutive testing of single nucleotide polymorphisms (SNPs) is usually employed to identify genetic variants associated with complex traits. Ideally one should model all covariates in unison, but most existing analysis methods for genome-wide association studies (GWAS) perform only univariate regression.ResultsWe extend and efficiently implement iterative hard thresholding (IHT) for multiple regression, treating all SNPs simultaneously. Our extensions accommodate generalized linear models, prior information on genetic variants, and grouping of variants. In our simulations, IHT recovers up to 30% more true predictors than SNP-by-SNP association testing and exhibits a 2-3 orders of magnitude decrease in false-positive rates compared with lasso regression. We also test IHT on the UK Biobank hypertension phenotypes and the Northern Finland Birth Cohort of 1966 cardiovascular phenotypes. We find that IHT scales to the large datasets of contemporary human genetics and recovers the plausible genetic variants identified by previous studies.ConclusionsOur real data analysis and simulation studies suggest that IHT can (i) recover highly correlated predictors, (ii) avoid over-fitting, (iii) deliver better true-positive and false-positive rates than either marginal testing or lasso regression, (iv) recover unbiased regression coefficients, (v) exploit prior information and group-sparsity, and (vi) be used with biobank-sized datasets. Although these advances are studied for genome-wide association studies inference, our extensions are pertinent to other regression problems with large numbers of predictors

Manager- und transaktionsspezifische Determinanten der Performance von Arbitrage CLOs

Der vorliegende Beitrag untersucht die Determinanten der Performance europäischer Arbitrage Collateralized Loan Obligations für das Jahr 2009. Der Fokus liegt dabei auf der Bedeutung der performanceabhängigen Vergütung des CLO-Managers, den Eigenschaften des CLO-Managers und der Transaktionscharakteristika als mögliche Einflussfaktoren der Rating Performance. Es wird gezeigt, dass Transaktionen, bei denen dem CLO-Manager eine Incentive Management Fee gewährt wird, mit einer höheren Wahrscheinlichkeit herabgestuft werden als Transaktionen ohne Incentive Fee. Dieser Befund bestätigt die Hypothese, dass durch die Incentive Fee Risikoanreize für CLO-Manager geschaffen werden. Des Weiteren wird ein positiver Zusammenhang zwischen der Erfahrung bzw. der Größe eines CLO-Managers und der Rating Performance festgestellt. Der Einfluss des Managers auf die Performance einer CLO-Transaktion wird auch an den weiteren in der Studie herangezogenen managerspezifischen Charakteristika wie Typ und Unternehmenssitz bestätigt. Für die Transaktionscharakteristika wird hingegen im betrachteten Untersuchungszeitraum kein signifikanter Einfluss auf die Rating Performance nachgewiesen

OPENMENDEL: A Cooperative Programming Project for Statistical Genetics

Statistical methods for genomewide association studies (GWAS) continue to improve. However, the increasing volume and variety of genetic and genomic data make computational speed and ease of data manipulation mandatory in future software. In our view, a collaborative effort of statistical geneticists is required to develop open source software targeted to genetic epidemiology. Our attempt to meet this need is called the OPENMENDELproject (https://openmendel.github.io). It aims to (1) enable interactive and reproducible analyses with informative intermediate results, (2) scale to big data analytics, (3) embrace parallel and distributed computing, (4) adapt to rapid hardware evolution, (5) allow cloud computing, (6) allow integration of varied genetic data types, and (7) foster easy communication between clinicians, geneticists, statisticians, and computer scientists. This article reviews and makes recommendations to the genetic epidemiology community in the context of the OPENMENDEL project.Comment: 16 pages, 2 figures, 2 table

Gender Differences in Russian Colour Naming

In the present study we explored Russian colour naming in a web-based psycholinguistic experiment (http://www.colournaming.com). Colour singletons representing the Munsell Color Solid (N=600 in total) were presented on a computer monitor and named using an unconstrained colour-naming method. Respondents were Russian speakers (N=713). For gender-split equal-size samples (NF=333, NM=333) we estimated and compared (i) location of centroids of 12 Russian basic colour terms (BCTs); (ii) the number of words in colour descriptors; (iii) occurrences of BCTs most frequent non-BCTs. We found a close correspondence between females’ and males’ BCT centroids. Among individual BCTs, the highest inter-gender agreement was for seryj ‘grey’ and goluboj ‘light blue’, while the lowest was for sinij ‘dark blue’ and krasnyj ‘red’. Females revealed a significantly richer repertory of distinct colour descriptors, with great variety of monolexemic non-BCTs and “fancy” colour names; in comparison, males offered relatively more BCTs or their compounds. Along with these measures, we gauged denotata of most frequent CTs, reflected by linguistic segmentation of colour space, by employing a synthetic observer trained by gender-specific responses. This psycholinguistic representation revealed females’ more refined linguistic segmentation, compared to males, with higher linguistic density predominantly along the redgreen axis of colour space