Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Seller reputation and price gouging: Evidence from the COVID-19 pandemic.

ABSTRACT: From mid-January to March 2020, 3M masks sold on Amazon by third party sellers were priced 2.4 times higher than Amazon's 2019 price. However, this price increase was not uniform across sellers. We estimate that when Amazon is stocked out (one of our measures of scarcity) new (entrant) sellers increase price by 178%, whereas the continuing sellers' increase is limited to 56.7%. This is consistent with the idea that seller reputation limits the extent of profitable price gouging. Similar results are obtained for Purell hand sanitizer and for other measures of scarcity. We also explore policy implications of our results.

SUBMITTER: Cabral L

PROVIDER: S-EPMC8251445 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Seller reputation and price gouging: Evidence from the COVID-19 pandemic.

Cabral Luís L Xu Lei L

Economic inquiry 20210405 3

From mid-January to March 2020, 3M masks sold on Amazon by third party sellers were priced 2.4 times higher than Amazon's 2019 price. However, this price increase was not uniform across sellers. We estimate that when Amazon is stocked out (one of our measures of scarcity) new (entrant) sellers increase price by 178%, whereas the continuing sellers' increase is limited to 56.7%. This is consistent with the idea that seller reputation limits the extent of profitable price gouging. Similar results ...[more]

PMID: 34230718

Similar Datasets

Physical activity and mental health during the COVID-19 pandemic among individuals with amputation

Project description: Not available

| S-BSST1055 | biostudies-other

The Russia-Saudi Arabia oil price war during the COVID-19 pandemic.

Project description:The COVID-19 pandemic damaged crude oil markets and amplified the consequences of uncertainty stemming from the Russia-Saudi Arabia oil price war in March-April of 2020. We investigate the impacts of the oil price war on global crude oil markets. By doing so, we use the daily futures and spot prices in three major crude oil markets - West Texas Intermediate, European Brent, and Oman - to perform a systematic analysis of the impacts of the oil price war on them. The event study method, a well-established analytical tool to measure the impacts of a given event on markets, is used in this study. The results indicate that information leakage plays an important role in the impacts of the price war. The outbreak of and truce following the price war have asymmetrical impacts on the markets; negative impacts generated by information leakage during the outbreak are generally more durable than the positive ones it generated during the truce. Furthermore, the magnitude of the impacts on futures markets is negatively correlated with the time-to-maturity of futures. Finally, negative crude oil prices affect West Texas Intermediate crude oil markets the most. Our findings generally show that market participants could perceive and assimilate market changes and adjust their expectations, which restrained the impacts that should have occurred within the oil price war.

| S-EPMC8652835 | biostudies-literature

Delayed Colorectal Cancer Care During Coronavirus Disease (COVID-19) Pandemic (DECOR-19)

Project description:To understand and analyse the global impact of COVID-19 on outpatient services, inpatient care, elective surgery, and perioperative colorectal cancer care, a DElayed COloRectal cancer surgery (DECOR-19) survey was conducted in collaboration with numerous international colorectal societies with the objective of obtaining several learning points from the impact of the COVID-19 outbreak on our colorectal cancer patients which will assist us in the ongoing management of our colorectal cancer patients and to provide us safe oncological pathways for future outbreaks.

| 2346925 | ecrin-mdr-crc

Heterogeneous price adjustments among Airbnb hosts amid COVID-19: Evidence from Barcelona.

Project description:COVID-19-induced travel restrictions have led to a sharp drop in Airbnb bookings. Confronted with a decrease in demand, hosts have implemented heterogeneous price responses. This study evaluates the different price adjustments developed by professional and non-professional hosts. Considering the city of Barcelona as the case study, I exploit monthly longitudinal data for 24,000 different Airbnb listings observed between June 2020 and April 2021. Using hedonic regressions with listing and neighbourhood fixed effects, I show that professional hosts have reduced prices to a greater extent, especially during the worst months of the pandemic. The findings support intertemporal price discrimination among professional hosts, which seem to adjust prices faster to meet demand and better adapt to market conditions.

| S-EPMC8784670 | biostudies-literature

Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic.

Project description:Recently, there has been much attention in the use of machine learning methods, particularly deep learning for stock price prediction. A major limitation of conventional deep learning is uncertainty quantification in predictions which affect investor confidence. Bayesian neural networks feature Bayesian inference for providing inference (training) of model parameters that provides a rigorous methodology for uncertainty quantification in predictions. Markov Chain Monte Carlo (MCMC) sampling methods have been prominent in implementing inference of Bayesian neural networks; however certain limitations existed due to a large number of parameters and the need for better computational resources. Recently, there has been much progress in the area of Bayesian neural networks given the use of Langevin gradients with parallel tempering MCMC that can be implemented in a parallel computing environment. The COVID-19 pandemic had a drastic impact in the world economy and stock markets given different levels of lockdowns due to rise and fall of daily infections. It is important to investigate the performance of related forecasting models during the COVID-19 pandemic given the volatility in stock markets. In this paper, we use novel Bayesian neural networks for multi-step-ahead stock price forecasting before and during COVID-19. We also investigate if the pre-COVID-19 datasets are useful of modelling stock price forecasting during COVID-19. Our results indicate due to high volatility in the stock-price during COVID-19, it is more challenging to provide forecasting. However, we found that Bayesian neural networks could provide reasonable predictions with uncertainty quantification despite high market volatility during the first peak of the COVID-19 pandemic.

| S-EPMC8248663 | biostudies-literature

The impact of COVID-19 pandemic on colorectal cancer therapy

Project description:Primary outcome(s): The incidence of obstructive colorectal cancer

| 2656898 | ecrin-mdr-crc

How price-gouging regulation undermined COVID-19 mitigation: county-level evidence of unintended consequences.

Project description:Despite long-standing criticisms, restrictions on price increases during emergencies remain widespread in the US. Criticisms most often cite the social costs of the shortages, but, we have found another, as yet unknown, cost: price-gouging regulations increased social contact during the onset of the COVID-19 pandemic. During the pandemic, thirty-four US states declared emergencies, which activated their preexisting price-gouging regulations, and eight others introduced new regulation along with their emergency declarations. Because these states border eight others that also declared emergencies, but had no price-gouging regulations, this created a unique natural experiment. Exploiting the pandemic-induced variation in regulation, and cellphone mobility data, we find that price controls increased visits to, and social contact in, commercial spaces, presumably because the regulation-induced shortages forced consumers to visit more stores and come in contact with more people as they struggled to find what they needed. This, of course, undermines social distancing efforts.Supplementary informationThe online version contains supplementary material available at 10.1007/s11127-023-01054-z.

| S-EPMC10111309 | biostudies-literature

Impact of COVID-19 on stock price crash risk: Evidence from Chinese energy firms.

Project description:This paper studies the impact of the outbreak of coronavirus disease 2019 (COVID-19) on the stock price crash risk of energy firms in China. We find that the stock price crash risk of energy firms significantly decreases in the post-COVID-19 period. We also find that firms that engage in more corporate social responsibility (CSR) activities are less exposed to stock price crash risk in the post-COVID-19 period than those that engage in less CSR activities. Finally, we show that the effect of COVID-19 on stock price crash risk is less severe for state-owned enterprises (SOEs) than for non-SOEs in the post-COVID-19 period. Our findings demonstrate China's economic recovery in the post-COVID-19 period and have policy implications for firms to improve their resilience to exogenous shocks.

| S-EPMC8641492 | biostudies-literature

Effects of COVID-19 Pandemic on the Outcomes of Colorectal Cancer

Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been identified as the cause of the Coronavirus disease 19 (COVID-19), which was initially reported in December 2019 in China and has since rapidly spread worldwide. Since then, the COVID-19 pandemic has caused a detrimental effect of the national health care system, causing a drastic reduction of the screening programs for colorectal cancer and requiring the redistribution of the hospital resources from elective surgery to the care of patients with SARS-Cov_2 infection requiring admission.

| 2364120 | ecrin-mdr-crc

Placental Privilege: Evidence of Organ Resilience in severe COVID-19

Project description:The blood of pregnant women affected by severe COVD-19 shows profound changes in immune cells. On the contrary, their placentas are relatively protected from severe perturbations.

2025-03-28 | GSE249139 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data