Title,Citation,Topic_area,Study_type,Study_evidence_rating,Outcome_effectiveness,Findings,Intervention_program,Topics,Target_population,Firm_characteristics,Geographic_setting,Original_publication_date,Original_publication_link,"Review Protocol"
"Would people behave differently if they better understood Social Security? Evidence from a field experiment","Liebman, J., & Luttmer, E. (2011). Would people behave differently if they better understood Social Security? Evidence from a field experiment. National Bureau of Economic Research working paper no. 17287. Cambridge, MA: NBER.","Behavioral Finance: Retirement, Behavioral Insights","Study Type: Causal Impact Analysis","Causal Evidence Rating: Moderate Causal Evidence",,"Summary:

	
	
		The study’s objective was to examine the impact of providing information about Social Security rules and benefits on labor force participation, knowledge of Social Security, and claiming of Social Security benefits.
		Workers nearing retirement age were randomly assigned into either the treatment group, which was sent an informational brochure about Social Security and invited to a 15-minute web tutorial on Social Security provisions, or to the control group, which was not offered this information but could seek other publicly available information about Social Security. The authors measured outcomes through a follow-up survey conducted 13 months after random assignment.
		The study found that, on average, members of the treatment group were more likely to work for pay in the last month and were more likely to be aware that Social Security benefits were based on the number of years with the highest earnings, compared with the control group. However, there were no statistically significant differences between the two groups on any other outcomes related to earnings and employment, Social Security benefit receipt, or understanding Social Security rules.
		The quality of causal evidence presented in this report is moderate because it was based on a well-conducted randomized controlled trial with high attrition and adequate control variables. This means we are somewhat confident that the estimated effects are attributable to providing information about Social Security provisions, but other factors might also have contributed.",,,Employed,,,2011,http://www.nber.org/papers/w17287.pdf,"Behavioral Finance: Retirement, Behavioral Insights Review Protocol"
"Details matter: The impact of presentation and information on the take-up of financial incentives for retirement saving","Saez, E. (2009). Details matter: The impact of presentation and information on the take-up of financial incentives for retirement saving. American Economic Journal: Economic Policy, 1(1), 204-228.","Behavioral Finance: Retirement, Behavioral Insights","Study Type: Causal Impact Analysis","Causal Evidence Rating: High Causal Evidence",,"Summary:

	
	
		The study’s objective was to examine the impact of contribution matches, credit rebates, and advance notification on tax filers’ decisions about opening an individual retirement account (IRA) during the tax preparation process and the amount they contributed to the IRA.
		The authors randomly assigned tax filers at 60 H&R Block locations in St. Louis, Missouri, to treatment conditions, defined by whether the filers were offered a 50 percent one-time match on IRA contributions, a 33 percent credit rebate on IRA contributions, or a 50 percent match on one-time and monthly IRA contributions. H&R Block provided tax filing information from the 2005 and 2006 tax years as well as background information on the filers.
		The study found that offering a 50 percent match on one-time IRA contributions and offering a 33 percent credit rebate increased the likelihood of opening an IRA and the amount contributed, but the effect on the likelihood of opening an IRA was larger for the 50 percent match treatment group.
		The quality of causal evidence is high for some outcomes because they were based on a well-implemented randomized controlled trial. This means we are confident that the estimated effects are attributable to the treatment under study, and not to other factors. However, the quality of causal evidence for other outcomes is low because the analyses were based on a nonrandom subset of the randomized sample, and the author did not use sufficient controls when estimating impacts.",,,Adult,,,2009,,"Behavioral Finance: Retirement, Behavioral Insights Review Protocol"