Moritz Poll

PhD Candidate in Economics at Brown University

Welcome to my website. I am a PhD student at the Economics Department of Brown University. My interests are in development, labor, and urban economics. Previously, I was a research assistant at Princeton University with Johannes Haushofer and the Busara Center. I received my MPhil in Economics from the University of Oxford and a BSc Economics from Maastricht University. Below you can find my CV and published research, as well as ongoing projects and papers I have contributed to as a research assistant. I am also a landscape and wildlife photographer.

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Curriculum Vitae

Last updated June 2023
CV Moritz Poll.pdf

Publications

Stress, Ethnicity, and Prosocial Behavior (2023) Journal of Political Economy Microeconomics, 1(2)

With Sara Lowes, Johannes Haushofer, Abednego Musau, David Ndetei, Nathan Nunn, and Nancy Qian

Abstract: While observational evidence suggests that people behave more prosocially towards members of their own ethnic group, many laboratory studies fail to find this effect. One possible explanation is that coethnic preference only emerges during times of stress. To test this hypothesis, we pharmacologically increase levels of the stress hormone cortisol, after which participants complete laboratory experiments with coethnics and noncoethnics. We find mixed evidence that increased cortisol decreases prosocial behavior. Coethnic preferences do not vary with cortisol. However, in contrast to previous studies, we find strong and robust evidence of coethnic preference.

Journal article

w30363.pdf

Research Spotlight

Rural Market Day Coordination

Abstract: Market days are the pulse of rural economic and social life in many parts of the world. They are a way of spatially and temporally aggregating thin market demand and supply to ameliorate food security and price volatility in poor regions. Market days are also a complex coordination game of assortative coordination (everybody trying to be in the same place at the same time) and non-assortative coordination (every village trying to have a different market day to its neighbors in order not to compete for participants). Fundamentally, coordination of markets determines who participates where and when in market exchange. If neighboring cities compete over buyers and sellers on the same day of the week, the resulting dispersed market exchanges will suffer price volatility and unsteady product variety. This can hamper growth in the best of times, but in the worst of times it will deepen food insecurity and economic crisis. Understanding how the coordination works and where it fails can guide the way to making profound changes in poor people's lives. Despite the fact that market days are an age-old feature of economic activity and human civilization, their coordination has not systematically been investigated. The coordination of these markets has an important social impact as it determines who meets on a regular basis, how social cliques and clusters form, within which groups/circles information diffuses or epidemics spread. Coordinated markets are a blueprint for the human networks that are likely to form through market participation and that facilitate knowledge diffusion and social learning. They also form the environment in which consumers and producers engage in costly search for one another.

Work in Progress

Robust results in the presence of treatment interactions: The case of unconditional cash transfers

With Johannes Haushofer

Abstract: Recent contributions to the analysis of randomized experiments have shown that cross-randomizing several treatments can lead to small cell sizes, which can result in distorted treatment effect estimates. In addition, it has been suggested that failure to include interaction terms in regressions may also bias results. In light of these concerns, we re-evaluate a large study of unconditional cash transfers in Kenya with three cross-randomizations (recipient gender, transfer magnitude and timing). To circumvent the failure of asymptotic results in small cells, we first re-estimate the treatment effects of the study using randomization inference,bootstrapping, and a jackknife method. The results are very similar to those obtained with conventional asymptotic methods. Second, we show that in the class of experiments which assign multiple versions of the same treatment, rather than several independent treatments, inclusion of interaction terms does not yield “pure” treatment effects, but rather treatment effects for particular subgroups,which are not generally estimands of interest. Finally, we quantify the possible bias introduced by slight imbalances in cell sizes generated by randomization,and suggest a simple re-weighting to correct for it.

Displacement in the Lab

With Reshmaan Hussam

Abstract: Among the well-documentedmajor consequences of forced displacement are injury and loss of life, disruption of social and economic networks and skill erosion through idleness. But there might a less tangible consequence stemming from the disruption of habits and perturbations in the habitual environment. This study simulates the experience of involuntary displacement in the context of a laboratory to understand how one’s environment impacts seemingly orthogonal dimensions of decision-making. In particular, we ask: how do unanticipated changes in strategically irrelevant dimensions of an environment affect behavior? 

Research Assistance

Efficiency of Informal Transit Networks

For Daniel Björkegren, Alice Duhaut, Geetika Nagpal, and Nick Tsivanidis

Included and excluded instruments in structural estimation

For Isaiah Andrews, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro

Abstract: We consider the choice of instrumental variables when a researcher’s structural model may be misspecified. We contrast included instruments, which have a direct causal effect on the outcome holding constant the endogenous variable of interest, with excluded instruments, which do not. We show conditions under which the researcher’s estimand maintains an interpretation in terms of causal effects of the endogenous variable under excluded instruments but not under included instruments. We apply our framework to estimation of a linear instrumental variables model, and of differentiated goods demand models under price endogeneity. We show that the distinction between included and excluded instruments is quantitatively important in simulations based on an application. We extend our results to a dynamic setting by studying estimation of production function parameters under input endogeneity.

Building Resilient Health Systems: Experimental Evidence from Sierra Leone and the 2014 Ebola Outbreak (2021, QJE)

For Oeindrila Dube, Johannes Haushofer, Bilal Siddiqi, Darin Christensen, and Maarten Voors

Developing countries are characterized by high rates of mortality and morbidity. A potential contributing factor is the low utilization of health systems, stemming from the low perceived quality of care delivered by health personnel. This factor may be especially critical during crises, when individuals choose whether to cooperate with response efforts and frontline health personnel. We experimentally examine efforts aimed at improving health worker performance in the context of the 2014–15 West African Ebola crisis. Roughly two years before the outbreak in Sierra Leone, we randomly assigned two accountability interventions to government-run health clinics – one focused on community monitoring and the other gave status awards to clinic staff. We find that over the medium run, prior to the Ebola crisis, both interventions led to improvements in utilization of clinics and patient satisfaction with the health system. In addition, child health outcomes improved substantially in the catchment areas of community monitoring clinics. During the crisis, the interventions also led to higher reported Ebola cases, as well as lower mortality from Ebola – particularly in areas with community monitoring clinics.  We explore three potential mechanisms: the interventions (1) increased the likelihood that patients reported Ebola symptoms and sought care; (2) unintentionally increased Ebola incidence; or (3) improved surveillance efforts.  We find evidence consistent with the first: by building trust and confidence in health workers, and improving the perceived quality of care provided by clinics prior to the outbreak, the interventions encouraged patients to report and receive treatment. Our results suggest that accountability interventions not only have the power to improve health systems during normal times, but can additionally make health systems resilient to crises that may emerge over the longer run.

Main paper, Companion Paper (AEA P&P), Non-technical summary

Media Coverage: New York Times, IPA, CBS

Multi-Country Economic Opportunity Assessment – Jobs Make The Difference

With Jason Pronyk, Daniel Egel, Susan Razzaz, and Shelly Culbertson

We analyze the employment opportunities for Syrian IDPs and refugees in Syria, Jordan, Lebanon, Iraq, Turkey and Egypt. Full report under https://www.jobsmakethedifference.org/

Put to rest

The Non-Monetary Value of Work

With Reshmaan Hussam and Ingvild Skarpeid

Abstract: Communities with significant proportions of young unemployed men are often regarded as breeding grounds for crime and violence. This project seeks to understand the elementary mechanisms driving this association. What makes idleness so dangerous? Beyond serving as a source of income, how do individuals in impoverished, high-unemployment communities experience employment? We run a randomized control trial in the Kibera slum of Nairobi. We set up an employment program, in which we vary and measure employees’ relative valuations for three non-monetary dimensions of work: busyness (as opposed to idleness), agency (as opposed to subjugation) and purpose (as opposed to meaninglessness). Our experiment further allows us to estimate how these non-monetary valuations evolve with the experience of the newly employed. We then conduct a second randomized experiment that probes the role of idleness in exacerbating past trauma and motivating future risk-taking behavior. 

The Timing of Return Migration after Conflict (Master's Thesis)

Abstract: Who returns after fleeing a conflict and how do forced migrants decide when to return? Return migration is selective whenever the choice between staying and returning is deliberate. Such selection may introduce bias when estimating the impact of return migration on refugees’ welfare, their destination country or country of origin. This paper recognizes the agency of forced migrants when it comes to their decision to return, despite their involuntary displacement. It constructs a model of return timing choice capable of producing plausible return patterns. A key motive of both return and non-return is individual-specific locational preference. The paper proposes a GMM-estimator for the preference distribution across the population which is vital to understanding return migration flows and to undertaking counterfactual analysis. It can be used to gauge how likely someone is to return or what impact a policy intervention might have on return decisions. 

The Timing of Return Migration after Conflict

Dichotomous Effects of Positive and Negative Growth on the Income of the Poor (Bachelor's Thesis)

Abstract: Who returns after fleeing a conflict and how do forced migrants decide when to return? Return migration is selective whenever the choice between staying and returning is deliberate. Such selection may introduce bias when estimating the impact of return migration on refugees’ welfare, their destination country or country of origin. This paper recognizes the agency of forced migrants when it comes to their decision to return, despite their involuntary displacement. It constructs a model of return timing choice capable of producing plausible return patterns. A key motive of both return and non-return is individual-specific locational preference. The paper proposes a GMM-estimator for the preference distribution across the population which is vital to understanding return migration flows and to undertaking counterfactual analysis. It can be used to gauge how likely someone is to return or what impact a policy intervention might have on return decisions. 

Dichotomous Effects of Positive and Negative Growth on the Income of the Poor