I am an Economist in Development Impact Evaluation (DIME) at the World Bank. I completed my PhD in Agricultural and Resource Economics at UC Berkeley in 2019. You can view my CV here.

Contact: jloeser@worldbank.org




Working papers


Modeling selection into unordered treatments: An equivalence result
(2023 Oct) show abstract pdf

When individuals self-select into multiple unordered treatments, additional assumptions are needed to identify treatment effects with instrumental variables. Suppose each treatment is targeted by a single instrument, then the following assumptions enabling identification of treatment effects are effectively equivalent: no defiers, identical compliers, and an additive random utility model of treatment selection. This equivalence extends approaches to identification and falsification derived under each assumption, and suggests new ones: no defiers is equivalent to a set of testable restrictions on choice probabilities, and all treatment effects are identified for individuals indifferent between control and all treatments.


Learning from self and learning from others: Experimental evidence from Bangladesh (w/ Florence Kondylis, Mushfiq Mobarak, Maria Jones, and Dan Stein)
(2023 Aug) show abstract pdf working paper (WPS)

Can decentralizing demonstration accelerate learning about new technologies? We randomize access to a fixed demonstration kit for new flood-saline-resilient seeds across villages in Bangladesh, with demonstration either by a single farmer or spread across many farmers. In the short run, higher learning from self and others under decentralization increases technology adoption. In the long run, the impacts of any demonstration persist, but the additional impacts of decentralization vanish. A Bayesian model of learning the returns to a new technology suggests belief dispersion caused noisy adoption along the learning path, and farmers' expected gains from demonstration are four times higher under decentralization.


Consumer surplus with incomplete markets: Applications to savings and microfinance
(2023 Jun) show abstract pdf working paper (WPS)

The household welfare gains from financial inclusion are empirically elusive. I establish that household welfare gains from a financial technology are equal to the area under dynamically compensated demand in a household model with incomplete financial markets, and general technology, preferences, and choice sets. I then estimate compensated demand for financial technologies leveraging three randomized control trials that introduce experimental variation in interest rates. Welfare gains per dollar lent or saved are small as compensated demand elasticities are large, but still correspond to large aggregate welfare gains from financial inclusion.


A few good masks: Evidence from mask manufacturing in Rwanda during the COVID-19 pandemic (w/ Kieran Byrne, Florence Kondylis, and Denis Mukama)
(2022 Apr) show abstract pdf working paper (WPS)

Did increases in mask supply slow the spread of COVID-19? Rwanda licensed and incentivized textile manufacturers to produce high-quality masks at the start of the COVID-19 pandemic; we exploit spatial variation in exposure to mask manufacturing through textile trade networks within an event-study design using receipt-level tax data. Licensing domestic mask manufacturers conservatively reduced mask prices by 8.8% and reduced monthly growth in COVID-19 infections (proxied by demand for anti-fever medicine) by 12%. The dynamics of our results suggest that increased mask quality explains reduced infections, in a context where there was strict enforcement of mask mandates and informal markets for masks.


Intervention size and persistence (w/ Florence Kondylis)
(2021 Sep) show abstract pdf working paper (WPS)

Do larger interventions improve longer run outcomes more cost effectively? And should poverty traps motivate increasing intervention size? This paper considers two approaches to increasing intervention size in the context of temporary unconditional cash transfers – larger transfers (intensity), and adding complementary graduation program interventions (scope). It does so leveraging 38 experimental estimates of dynamic consumption impacts from 14 developing countries. First, increasing intensity decreases cost effectiveness and does not affect persistence of impacts. This result can be explained by poverty traps or decreasing marginal return on investment in a standard buffer stock model. Second, increasing scope increases impacts and persistence, but reduces cost effectiveness at commonly evaluated time horizons and increases heterogeneity. In summary, larger interventions need not have more persistent impacts, and when they do, this may come at the expense of cost effectiveness, and poverty traps are neither necessary nor sufficient for these results.

Publications


Factor market failures and the adoption of irrigation in Rwanda (w/ Maria Jones, Florence Kondylis, and Jeremy Magruder)
American Economic Review 112(7) pp. 2316-2352
(2022 Jul) show abstract pdf online appendix

Factor market failures can limit adoption of profitable technologies. We leverage a plot-level spatial regression discontinuity design in the context of irrigation use by farmers provided free access to water. Using irrigation boosts profits by 43-62%. Yet, farmers only irrigate 30% of plots because of labor costs. We demonstrate inefficient irrigation use, by showing farmers irrigating one plot reduce their irrigation use on other plots. This inefficiency is largest for smaller households and wealthier households, suggesting labor market frictions constrain use of irrigation.

Other publications


Sectoral heterogeneity in the COVID-19 recovery: Evidence from Rwanda (w/ Kieran Byrne, Saahil Karpe, Florence Kondylis, and Megan Lang) featured in Arezki, R., Djankov, S., and Panizza, U., "Shaping Africa's Post-Covid Recovery" (CEPR/VoxEU, February 2021)
(2021 Feb) show abstract pdf

Following the initial COVID-19 shock, developing countries have begun to transition to a COVID-19 economic recovery characterized by eased lockdowns and fiscal stimulus. We leverage high frequency administrative tax records from Rwanda on firm sales and employment to characterize the impacts of the COVID-19 shock and recovery. We show that the aggregate shock peaked in April 2020, with aggregate turnover and employment recovering to pre-COVID-19 levels by September. The aggregate recovery masks meaningful heterogeneity: while the initial shock impacted sectors in which in-person work was most necessary, the sectors in which face-to-face interactions with consumers are most necessary continue to experience a protracted recovery.