$1000 Cash Back: Asymmetric Information in Auto Manufaturer Promotions

Automobile manufacturers make frequent use of promotions that give cash-back payments. Two common types of cash-back promotions are rebates to customers, which are widely publicized to potential customers, and discounts to dealers, which are not publicized. While the payments nominally go entirely to one party or the other, the real division of the manufacturer-supplied surplus between dealer and customer depends on what price the two parties negotiate. These two types of promotions thus form a natural experiment of the effect of information asymmetry on bargaining outcomes: in the customer rebate case, the parties are symmetrically informed about the availability of the manufacturer-supplied surplus, while in the dealer discount case, the dealer will generally have an informational advantage. The aim of this paper is to compare, in appropriate settings and with appropriate controls, the price outcomes of transactions conducted under these two types of promotions in order to empirically quantify the effect of this information asymmetry. We show that customers obtain approximately 80% of the surplus in cases when they are likely to be well-informed about the promotion (customer rebate), and approximately 35% when they are likely to be uninformed (dealer discount). For a promotion of average size, this difference translates to customers being worse off by $500 when they do not know that the promotion is being offered.

Scarcity Rents in Car Retailing: Evidence from Inventory Fluctuations at Dealerships

Price variation for identical cars at the same dealership is commonly assumed to arise because dealers with market power are able to price discriminate among their customers. In this paper we show that while price discrimination may be one element of price variation, price variation also arises from inventory fluctuations. Inventory fluctuations create scarcity rents for cars that are in short supply. The price variation due to inventory fluctuations thus functions to efficiently allocate particular cars that are in restricted supply to those customers who value them most highly. Our empirical results show that a dealership moving from a situation of inventory shortage to an average inventory level lowers transaction prices by about 1% ceteris paribus, corresponding to 15% of dealers' average per vehicle profit margin or $250 on the average car. Shorter resupply times also decrease transaction prices for cars in high demand. For traditional dealerships, inventory explains 49% of the combined inventory and demographic components of the predicted price. For so-called 'no-haggle' dealerships, the percentage explained by inventory increases to 74%.

Consumer Information and Price Discrimination: Does the Internet Affect the Pricing of New Cars to Women and Minorities?

Mediating transactions through the Internet removes important cues that salespeople can use to assess a consumer's willingness to pay. We analyze whether dealers' difficulty in identifying consumer characteristics on the Internet and consumers' ease in finding information affects equilibrium prices in car retailing. Using a large dataset of transaction prices for new automobiles, the first part of the paper an- alyzes the relationship between car prices and demographics. We find that offline African-American and Hispanic consumers pay approximately 2% more than other consumers, however, we can explain 65% of this price premium with differences in income, education,a nd search costs; we find no evidence of statistical race discrimination. The second part of the paper turns to the role of the Internet. Online minority buyers who use the Internet Referral Service we study, Autobytel.com, pay nearly the same prices as do whites, irrespective of their income, education, and search costs. Since members of minority groups who use the Internet may not be representative, we control for selection. We conclude that the Internet is disproportionately beneficial to those who have personal characteristics that put them at a disadvantage in negotiating. African-American and Hispanic individuals, who are least likely to use the Internet, are the ones who benefit the most from it.

Cowboys or Cowards: Why are Internet Car Prices Lower?

This paper addresses the question of how much the Internet lowers prices for new cars and why. Using a large dataset of transaction prices for new automobiles and referral data from Autobytel.com, we find that online consumers pay on average 1.2% less than do offline consumers. After controlling for selection, we find that using Autobytel.com reduces the price a consumer pays by approximately 2.2%. This suggests that consumers who use an Internet referral service are not those who would have obtained a low price even in the absence of the Internet. Instead, our finding is consistent with consumers choosing to use Autobytel.com because they know that they would do poorly in the traditional channel, perhaps because they have a high personal cost to collecting information and bargaining. This group disproportionately uses Autobytel.com because its members are the ones with the most to gain. We estimate that savings to consumers who use Autobytel.com alone are at least $240 million per year. Since there are other referral and informational sites that may also help consumers bargain more effectively with dealers, we conclude that the Internet is facilitating a large transfer of surplus to Internet consumers in the retail auto industry.

How the Internet Lowers Prices: Evidence from Matched Survey and Auto Transaction Data

There is convincing evidence that the Internet has lowered the prices paid by some consumers in established industries, for example, term life insurance and car retailing. However, current research does not reveal much about how using the Internet lowers prices. This paper answers this question for the auto retailing industry. We use direct measures of search behavior and consumer characteristics to investigate how the Internet affects negotiated prices. We show that the Internet lowers prices for two distinct reasons. First, the Internet helps consumers learn the invoice price of dealers. Second, the referral process of online buying services, a novel institution made possible by the Internet, also helps consumers obtain lower prices. The combined information and referral price effects are -1.5%, corresponding to 22% of dealers' average gross profit margin per vehicle. We also find that buyers with a high disutility of bargaining benefit from information on the specific car they eventually purchased while buyers who like the bargaining process do not. The results suggest that the decisions consumers make to use the Internet to gather information and to use the negotiating clout of an online buying service have a real effect on the prices paid by these consumers.

Internet Car Retailing

This paper investigates the effect of Internet car referral services on dealer pricing of automobiles in California. Combining data from J.D. Power and Associates and Autobytel.com, a major online auto referral service, we compare online transaction prices to regular street' prices. We find that the average customer of this online service pays approximately 2% less for her car, which corresponds to about $450 for the average car. Fifteen percent of the savings comes from making the purchase at a low-price dealership affiliated with the web service. The remaining 85$300 than an equivalent offline sale. However, because online consumers are cheaper to serve and online sales may be new business for the dealerships, web-affiliated dealers are likely to be better off. Consumers who use the web do better than at least 61% of offline consumers.

Why New Car Dealers Sell Used Cars: A Structural Analysis of the Impact of Used Car Markets on the Automobile Distribution Channel

Most new car dealers also sell used cars from the same physical location. Used cars sold by these dealers are relatively good substitutes for new cars and thus, could compete with the new cars sold by the dealers. Previous empirical research on the automobile market has mostly ignored the presence of the used car market while the analytical literature provides ambivalent suggestions. In this paper, we study how the availability of used cars at new car dealers affects the substitution between new and used cars as well as how it affects the margins and profits obtained by the dealer and manufacturer. Using a transaction level dataset which contains both new and used car transactions, we perform a detailed empirical analysis to understand how the existence of the used car markets affect the new car market as well as the channel members. We build a full equilibrium structural model of new and used car competition with profit maximizing manufacturers and dealers. Using the estimated model we quantify the substitutability between new and used cars and compare it with a more conventional demand model which considers new cars only. We then proceed to analyze whether dealers consider the substitutability between new and used cars to shed light on how dealers price their cars. We then contrast the distribution of profits between the manufacturer and dealer to understand how the used markets affect the distribution of power in the channel. Our results indicate that the new car prices have a higher impact on used car demand than used car prices have on new car demand. We also find that the ability to price and sell used cars gives the dealer higher margins on new cars and increases their power in the channel

Preeclampsia and COVID-19: results from the INTERCOVID prospective longitudinal study

Background: It is unclear whether the suggested link between COVID-19 during pregnancy and preeclampsia is an independent association or if these are caused by common risk factors. Objective: This study aimed to quantify any independent association between COVID-19 during pregnancy and preeclampsia and to determine the effect of these variables on maternal and neonatal morbidity and mortality. Study Design: This was a large, longitudinal, prospective, unmatched diagnosed and not-diagnosed observational study assessing the effect of COVID-19 during pregnancy on mothers and neonates. Two consecutive not-diagnosed women were concomitantly enrolled immediately after each diagnosed woman was identified, at any stage during pregnancy or delivery, and at the same level of care to minimize bias. Women and neonates were followed until hospital discharge using the standardized INTERGROWTH-21st protocols and electronic data management system. A total of 43 institutions in 18 countries contributed to the study sample. The independent association between the 2 entities was quantified with the risk factors known to be associated with preeclampsia analyzed in each group. The outcomes were compared among women with COVID-19 alone, preeclampsia alone, both conditions, and those without either of the 2 conditions. Results: We enrolled 2184 pregnant women; of these, 725 (33.2%) were enrolled in the COVID-19 diagnosed and 1459 (66.8%) in the COVID-19 not-diagnosed groups. Of these women, 123 had preeclampsia of which 59 of 725 (8.1%) were in the COVID-19 diagnosed group and 64 of 1459 (4.4%) were in the not-diagnosed group (risk ratio, 1.86; 95% confidence interval, 1.32–2.61). After adjustment for sociodemographic factors and conditions associated with both COVID-19 and preeclampsia, the risk ratio for preeclampsia remained significant among all women (risk ratio, 1.77; 95% confidence interval, 1.25–2.52) and nulliparous women specifically (risk ratio, 1.89; 95% confidence interval, 1.17–3.05). There was a trend but no statistical significance among parous women (risk ratio, 1.64; 95% confidence interval, 0.99–2.73). The risk ratio for preterm birth for all women diagnosed with COVID-19 and preeclampsia was 4.05 (95% confidence interval, 2.99–5.49) and 6.26 (95% confidence interval, 4.35–9.00) for nulliparous women. Compared with women with neither condition diagnosed, the composite adverse perinatal outcome showed a stepwise increase in the risk ratio for COVID-19 without preeclampsia, preeclampsia without COVID-19, and COVID-19 with preeclampsia (risk ratio, 2.16; 95% confidence interval, 1.63–2.86; risk ratio, 2.53; 95% confidence interval, 1.44–4.45; and risk ratio, 2.84; 95% confidence interval, 1.67–4.82, respectively). Similar findings were found for the composite adverse maternal outcome with risk ratios of 1.76 (95% confidence interval, 1.32–2.35), 2.07 (95% confidence interval, 1.20–3.57), and 2.77 (95% confidence interval, 1.66–4.63). The association between COVID-19 and gestational hypertension and the direction of the effects on preterm birth and adverse perinatal and maternal outcomes, were similar to preeclampsia, but confined to nulliparous women with lower risk ratios. Conclusion: COVID-19 during pregnancy is strongly associated with preeclampsia, especially among nulliparous women. This association is independent of any risk factors and preexisting conditions. COVID-19 severity does not seem to be a factor in this association. Both conditions are associated independently of and in an additive fashion with preterm birth, severe perinatal morbidity and mortality, and adverse maternal outcomes. Women with preeclampsia should be considered a particularly vulnerable group with regard to the risks posed by COVID-19

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe