The reaction of consumer spending and debt to tax rebates – evidence from consumer credit data

We use a new panel dataset of credit card accounts to analyze how consumers responded to the 2001 federal income tax rebates. We estimate the monthly response of credit card payments, spending, and debt, exploiting the unique, randomized timing of the rebate disbursement. We find that on average consumers initially saved some of the rebate, by increasing their credit card payments and thereby paying down debt. But soon afterwards spending increased, counter to the canonical Permanent-Income model. For people whose most intensively used credit card account is in the sample, spending on that account rose by over $200 cumulatively over the nine months after rebate receipt, which represents over 40% of the average household rebate. Because these results relied exclusively on exogenous, randomized variation, they represent compelling evidence of a causal link from the rebate to spending. ; Further, we found significant heterogeneity in the response to the rebate across different types of consumers. Notably, spending rose most for consumers who were initially most likely to be liquidity constrained according to various criteria, for example consumers who appeared to be initially constrained by their credit limits (before making additional payments). By contrast, debt declined most (so saving rose most) for unconstrained consumers. These results suggest that liquidity constraints are important. More generally, we found that there can be important dynamics in consumers’ response to ‘lumpy’ increases in income like tax rebates, working in part through balance sheet (liquidity) mechanisms.Consumer behavior ; Consumer credit ; Credit cards

The Reaction of Consumer Spending and Debt to Tax Rebates -- Evidence from Consumer Credit Data

We use a new panel dataset of credit card accounts to analyze how consumers responded to the 2001 Federal income tax rebates. We estimate the monthly response of credit card payments, spending, and debt, exploiting the unique, randomized timing of the rebate disbursement. We find that, on average, consumers initially saved some of the rebate, by increasing their credit card payments and thereby paying down debt. But soon afterwards their spending increased, counter to the canonical Permanent-Income model. Spending rose most for consumers who were initially most likely to be liquidity constrained, whereas debt declined most (so saving rose most) for unconstrained consumers. More generally, the results suggest that there can be important dynamics in consumers' response to "lumpy" increases in income like tax rebates, working in part through balance sheet (liquidity) mechanisms.

Do consumers choose the right credit contracts?

We find that on average consumers chose the contract that ex post minimized their net costs. A substantial fraction of consumers (about 40%) still chose the ex post sub-optimal contract, with some incurring hundreds of dollars of avoidable interest costs. Nonetheless, the probability of choosing the sub-optimal contract declines with the dollar magnitude of the potential error, and consumers with larger errors were more likely to subsequently switch to the optimal contract. Thus most of the errors appear not to have been very costly, with the exception that a small minority of consumers persists in holding substantially sub-optimal contracts without switching. Klassifikation: G11, G21, E21, E5

Benefits of relationship banking: evidence from consumer credit markets

This paper empirically examines the benefits of relationship banking to banks, in the context of consumer credit markets. Using a unique panel dataset that contains comprehensive information about the relationships between a large bank and its credit card customers, we estimate the effects of relationship banking on the customers' default, attrition, and utilization behavior. We find that relationship accounts exhibit lower probabilities of default and attrition, and have higher utilization rates, compared to non-relationship accounts, ceteris paribus. Such effects become more pronounced with increases in various measures of the strength of the relationships, such as relationship breadth, depth, length, and proximity. Moreover, dynamic information about changes in the behavior of a customer’s other accounts at the bank, such as changes in checking and savings balances, helps predict and thus monitor the behavior of the credit card account over time. These results imply significant potential benefits of relationship banking to banks in the retail credit market.Consumer credit ; Credit cards

Do consumers choose the right credit contracts?

A number of studies have pointed to various mistakes that consumers might make in their consumption-saving and financial decisions. We utilize a unique market experiment conducted by a large U.S. bank to assess how systematic and costly such mistakes are in practice. The bank offered consumers a choice between two credit card contracts, one with an annual fee but a lower interest rate and one with no annual fee but a higher interest rate. To minimize their total interest costs net of the fee, consumers expecting to borrow a sufficiently large amount should choose the contract with the fee, and vice-versa. ; We find that on average consumers chose the contract that ex post minimized their net costs. A substantial fraction of consumers (about 40%) still chose the ex post sub-optimal contract, with some incurring hundreds of dollars of avoidable interest costs. Nonetheless, the probability of choosing the sub-optimal contract declines with the dollar magnitude of the potential error, and consumers with larger errors were more likely to subsequently switch to the optimal contract. Thus most of the errors appear not to have been very costly, with the exception that a small minority of consumers persists in holding substantially sub- optimal contracts without switching.Consumer credit ; Contracts

Emulating Simulations of Cosmic Dawn for 21cm Power Spectrum Constraints on Cosmology, Reionization, and X-ray Heating

Current and upcoming radio interferometric experiments are aiming to make a statistical characterization of the high-redshift 21cm fluctuation signal spanning the hydrogen reionization and X-ray heating epochs of the universe. However, connecting 21cm statistics to underlying physical parameters is complicated by the theoretical challenge of modeling the relevant physics at computational speeds quick enough to enable exploration of the high dimensional and weakly constrained parameter space. In this work, we use machine learning algorithms to build a fast emulator that mimics expensive simulations of the 21cm signal across a wide parameter space to high precision. We embed our emulator within a Markov-Chain Monte Carlo framework, enabling it to explore the posterior distribution over a large number of model parameters, including those that govern the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a worked example, we use our emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment, showing that its characterization of a fiducial 21cm power spectrum will considerably narrow the allowed parameter space of reionization and heating parameters, and could help strengthen Planck's constraints on $\sigma_8$. We provide both our generalized emulator code and its implementation specifically for 21cm parameter constraints as publicly available software.Comment: 22 pages, 9 figures; accepted to Ap

Do Consumers Choose the Right Credit Contracts?

We analyze an experiment conducted by a large U.S. bank that offered consumers a choice between two credit card contracts, one with an annual fee but a lower interest rate and one with no annual fee but a higher interest rate. We find that on average consumers chose the credit contract that minimized their costs. A substantial fraction of consumers (about 40%) still chose the suboptimal contract. Nonetheless, the probability of choosing the suboptimal contract declines with the dollar magnitude of the potential error, and consumers with larger errors are more likely to subsequently switch to the optimal contract

Polarized Redundant-Baseline Calibration for 21 cm Cosmology Without Adding Spectral Structure

21 cm cosmology is a promising new probe of the evolution of visible matter in our universe, especially during the poorly-constrained Cosmic Dawn and Epoch of Reionization. However, in order to separate the 21 cm signal from bright astrophysical foregrounds, we need an exquisite understanding of our telescopes so as to avoid adding spectral structure to spectrally-smooth foregrounds. One powerful calibration method relies on repeated simultaneous measurements of the same interferometric baseline to solve for the sky signal and for instrumental parameters simultaneously. However, certain degrees of freedom are not constrained by asserting internal consistency between redundant measurements. In this paper, we review the origin of these "degeneracies" of redundant-baseline calibration and demonstrate how they can source unwanted spectral structure in our measurement and show how to eliminate that additional, artificial structure. We also generalize redundant calibration to dual-polarization instruments, derive the degeneracy structure, and explore the unique challenges to calibration and preserving spectral smoothness presented by a polarized measurement.Comment: 12 pages, 3 figures, updated to match the published MNRAS versio

The Faint End Slopes Of Galaxy Luminosity Functions In The COSMOS 2-Square Degree Field

We examine the faint-end slope of the rest-frame V-band luminosity function (LF), with respect to galaxy spectral type, of field galaxies with redshift z<0.5, using a sample of 80,820 galaxies with photometric redshifts in the Cosmic Evolution Survey (COSMOS) field. For all galaxy spectral types combined, the LF slope, alpha, ranges from -1.24 to -1.12, from the lowest redshift bin to the highest. In the lowest redshift bin (0.02<z<0.1), where the magnitude limit is M(V) ~ -13, the slope ranges from ~ -1.1 for galaxies with early-type spectral energy distributions (SEDs), to ~ -1.9 for galaxies with low-extinction starburst SEDs. In each galaxy SED category (Ell, Sbc, Scd/Irr, and starburst), the faint-end slopes grow shallower with increasing redshift; in the highest redshift bin (0.4<z<0.5), the slope is ~ -0.5 and ~ -1.3 for early-types and starbursts respectively. The steepness of alpha at lower redshift could be qualitatively explained by large numbers of faint dwarf galaxies, perhaps of low surface brightness, which are not detected at higher redshifts.Comment: 24 pages including 5 figures, accepted to ApJ