Seth Freedman

Do Social Networks Solve Information Problems for Peer-to-Peer Lending? Evidence from Prosper.Com

This paper studies peer-to-peer (p2p) lending on the Internet. Prosper.com, the first p2p lending website in the US, matches individual lenders and borrowers for unsecured consumer loans. Using transaction data from June 1, 2006 to July 31, 2008, we examine what information problems exist on Prosper and whether social networks help alleviate the information problems. As we expect, data identifies three information problems on Prosper.com. First, Prosper lenders face extra adverse selection because they observe categories of credit grades rather than the actual credit scores. This selection is partially offset when Prosper posts more detailed credit information on the website. Second, many Prosper lenders have made mistakes in loan selection but they learn vigorously over time. Third, as Stiglitz and Weiss (1981) predict, a higher interest rate can imply lower rate of return because higher interest attracts lower quality borrowers. Micro-finance theories argue that social networks may identify good risks either because friends and colleagues observe the intrinsic type of borrowers ex ante or because the monitoring within social networks provides a stronger incentive to pay off loans ex post. We find evidence both for and against this argument. For example, loans with friend endorsements and friend bids have fewer missed payments and yield significantly higher rates of return than other loans. On the other hand, the estimated returns of group loans are significantly lower than those of non-group loans. That being said, the return gap between group and non-group loans is closing over time. This convergence is partially due to lender learning and partially due to Prosper eliminating group leader rewards which motivated leaders to fund lower quality loans in order to earn the rewards.

Effect of the Affordable Care Act Medicaid Expansion on Emergency Department Visits: Evidence From State-Level Emergency Department Databases

Study objective We assess whether the expansion of Medicaid under the Patient Protection and Affordable Care Act (ACA) results in changes in emergency department (ED) visits or ED payer mix. We also test whether the size of the change in ED visits depends on the change in the size of the Medicaid population. Methods Using all‐capture, longitudinal, state data from the Agency for Healthcare Research and Quality’s Fast Stats program, we implemented a difference‐in‐difference analysis, which compared changes in ED visits per capita and the share of ED visits by payer (Medicaid, uninsured, and private insurance) in 14 states that did and 11 states that did not expand Medicaid in 2014. Analyses controlled for state‐level demographic and economic characteristics. Results We found that total ED use per 1,000 population increased by 2.5 visits more in Medicaid expansion states than in nonexpansion states after 2014 (95% confidence interval [CI] 1.1 to 3.9). Among the visit types that could be measured, increases in ED visits were largest for injury‐related visits and for states with the largest changes in Medicaid enrollment. Compared with nonexpansion states, in expansion states the share of ED visits covered by Medicaid increased 8.8 percentage points (95% CI 5.0 to 12.6), whereas the uninsured share decreased by 5.3 percentage points (95% CI –1.7 to –8.9). Conclusion The ACA’s Medicaid expansion has resulted in changes in payer mix. Contrary to other studies of the ACA’s effect on ED visits, our study found that the expansion also increased use of the ED, consistent with polls of emergency physicians.

The information value of online social networks: Lessons from peer-to-peer lending

We examine whether social networks facilitate online markets using data from a leading peer-to-peer lending website. We find that borrowers with social ties are consistently more likely to have their loans funded and receive lower interest rates; however, most borrowers with social ties are more likely to pay late or default. We provide evidence that these findings are driven by lenders not fully understanding the relationship between social ties and unobserved borrower quality. Overall, our findings suggest caution for using online social networks as a signal of quality in anonymous transactions.

Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms

We study the effect of hospital adoption of electronic medical records (EMRs) on health outcomes, particularly patient safety indicators (PSIs). We find evidence of a positive impact of EMRs on PSIs via decision support rather than care coordination. Consistent with this mechanism, we find an EMR with decision support is more effective at reducing PSIs for less complicated cases, using several different metrics for complication. These findings indicate the negligible impacts for EMRs found by previous studies focusing on the Medicare population and/or mortality do not apply in all settings.

Changes in inpatient payer-mix and hospitalizations following Medicaid expansion: Evidence from all-capture hospital discharge data

Context The Affordable Care Act resulted in unprecedented reductions in the uninsured population through subsidized private insurance and an expansion of Medicaid. Early estimates from the beginning of 2014 showed that the Medicaid expansion decreased uninsured discharges and increased Medicaid discharges with no change in total discharges. Objective To provide new estimates of the effect of the ACA on discharges for specific conditions. Design, setting, and participants We compared outcomes between states that did and did not expand Medicaid using state-level all-capture discharge data from 2009–2014 for 42 states from the Healthcare Costs and Utilization Project’s FastStats database; for a subset of states we used data through 2015. We stratified the analysis by baseline uninsured rates and used difference-in-differences and synthetic control methods to select comparison states with similar baseline characteristics that did not expand Medicaid. Main outcome Our main outcomes were total and condition-specific hospital discharges per 1,000 population and the share of total discharges by payer. Conditions reported separately in FastStats included maternal, surgical, mental health, injury, and diabetes. Results The share of uninsured discharges fell in Medicaid expansion states with below (-4.39 percentage points (p.p.), -6.04 –-2.73) or above (-7.66 p.p., -9.07 –-6.24) median baseline uninsured rates. The share of Medicaid discharges increased in both small (6.42 p.p. 4.22–6.62) and large (10.5 p.p., 8.48–12.5) expansion states. Total and most condition-specific discharges per 1,000 residents did not change in Medicaid expansion states with high or low baseline uninsured rates relative to non-expansion states (0.418, p = 0.225), with one exception: diabetes. Discharges for that condition per 1,000 fell in states with high baseline uninsured rates relative to non-expansion states (-0.038 95% p = 0.027). Conclusions Early changes in payer mix identified in the first two quarters of 2014 continued through the Medicaid expansion’s first year and are distributed across all condition types studied. We found no change in total discharges between Medicaid expansion and non-expansion states, however residents of states that should have been most affected by the Medicaid expansion were less likely to be hospitalized for diabetes.

Hospital Ownership Type and Innovation: The Case of Electronic Medical Records Adoption

Nonprofit and for-profit firms coexist in many industries, with the hospital sector being one of the most predominant examples. This article explores whether nonprofit hospitals are more likely to make expensive investments with uncertain returns and potential public good value. Specifically, we estimate differences in the adoption of electronic medical records (EMRs) by ownership structure. We find that nonprofit hospitals are 11 to 18 percentage points more likely to have installed advanced EMR systems than for-profit hospitals by 2012. Although we find little difference in the likelihood of meeting initial government requirements for the “meaningful use” of EMRs, we find that nonprofits are 12 percentage points more likely to reach more stringent meaningful use standards that began in 2014. That being said, nonprofit adoption rates decrease as for-profit market penetration rates increase, suggesting nonprofits are less likely to adopt an uncertain technology when facing more direct competition from for-profit hospitals.

Electronic Medical Records and Medical Procedure Choice: Evidence from Cesarean Sections

This paper examines how hospital adoption of Electronic Medical Records (EMRs) impacts medical procedure choice in the context of Cesarean section deliveries. It provides a unique contribution by tying the literature on EMR diffusion to the literature on the utilization of expensive medical technology and provider practice style. Exploiting within-hospital variation in three types of EMR adoption, we find that Computerized Physician Order Entry, an advanced EMR system that typically incorporates decision support, reduces C-section rates for low-risk mothers by 2.5%. Obstetric specific EMR systems and Physician Documentation have no statistically significant effect on C-section rates. In addition, we find that the CPOE effect occurs predominantly in hospitals that were already performing fewer C-sections, and does not change the behavior of already high-intensity providers.