I am Priscila de Oliveira. I am an Assistant Professor of Economics at Nova School of Business and Economics. I work on topics in development and behavioral economics.
I received a Ph.D. in Economics from the University of California, Berkeley in 2023. I also received a Masters in Economics in 2016 from the Sao Paulo School of Economics (FGV) and a B.A. in Economics in 2013 from the University of Sao Paulo (USP), Brazil.
You can contact me at priscila [dot] oliveira [at] novasbe [dot] pt
Click here for my CV
Research
Working Papers
Why Businesses Fail: Underadoption of Improved Practices by Brazilian Micro-Enterprises [Link]
Micro-firms in low and middle income countries often have low profitability and do not grow over time. Several business training programs have tried to increase their productivity through improved management and business practices, with limited success. We run a field experiment with micro-entrepreneurs in Brazil (N = 742) to shed light on the constraints that lead to the under-adoption of improved business practices. We randomly offer entrepreneurs micro-incentives, which include reminders, deadlines and small monetary payments, to implement record keeping or marketing for three consecutive months, following a business training program. Our intervention is designed to have a significant impact on firms' decisions only in the presence of behavioral biases. Compared to traditional business training, micro-incentives significantly increase adoption of marketing (13.2 p.p.) and record keeping (19.2 p.p.), with positive effects on firm survival and investment over four months. Additional survey evidence is consistent with biases, such as inattention, time inconsistency and information avoidance, inhibiting the adoption of improved practices. Taken together, our results show that behavioral biases have a significant impact on firms' managerial decisions.
Failures of Contingent Reasoning in Annuitization Decisions (with Erzo F. P. Luttmer and Dmitry Taubinsky) [Link]
This paper studies psychological biases in take-up of annuities, using an incentivized experiment with a probability-based sample (N = 3,038). Choosing an annuity was payoff-maximizing in the experiment at all prices, but take-up was incomplete and price elastic. Reformulating decisions as insurance against a “bad” outcome rather than insurance against “longevity risk” did not increase take-up. Instead, we find substantial failures of contingent reasoning: participants underappreciated how annuitization mitigated the need for less-efficient means of saving for retirement. Increasing the salience of the interaction with savings decisions, or eliminating the need to think through this interaction altogether, substantially increased annuity take-up.
Selected Work in Progress
Does the Structure of the Hiring Process Impact Gender and Race Gaps? Evidence from Brazil (with Pedro Pires)
We explore how the structure of the screening and hiring process can influence the gender and race wage gaps. We use proprietary data from a HR Tech company that assists large companies with worker recruitment in Brazil. Our dataset contains detailed information on candidates' performance at all stages of the screening process. The first question that we aim to address is: at which stages of the process do gender and race gaps emerge, and when are they the largest? The next step is to compare screening strategies across firms and how they affect the gender and race gaps. For instance, does requiring group interviews result in larger or smaller gaps in job offers? Are hiring decisions affected by the number of people involved? We will also compare firms where HR plays a larger role in recruitment with firms where area managers make the majority of decisions. Finally, we will study whether interviewers might be biased towards candidates more similar to themselves, and whether gender and race gaps vary depending on the recruiters' identities.
Finding the Perfect Hire: Screening Strategies and Job Match Quality (with Pedro Pires)
This paper examines how different screening criteria affect work performance. We use proprietary data from a HR Tech company that assists large companies with worker recruitment in Brazil. We will combine this dataset with post-hiring job performance data. Our goal will be to estimate the implicit weights that firms apply to different worker characteristics when they make hiring decisions. We analyze the consequences of these choices in terms of productivity and diversity. The next step is to identify screening strategies that can maximize the quality of the employer-employee match. Relative to this benchmark, firms may focus too much on certain applicant characteristics that are not very predictive of performance. If this hypothesis is confirmed, it may motivate changes to screening strategies. Finally, we will study when suitable matches are unlikely to be selected during the recruitment process.
Occupational Choices of Micro-Entrepreneurs: Evidence from Mozambique (with Catia Batista)