Deivy Houeix Profile Picture

My name is pronounced: Day-vee Wex

Welcome! I received my Ph.D. in Economics from MIT in May 2025. I am currently a Prize Fellow at the Center for History and Economics at Harvard University. In 2027, I will join Columbia Business School as an Assistant Professor of Economics.

My primary field is Development Economics, with secondary interests in Organizational Economics.

My research focuses on technology and firms in lower-income countries, particularly in West Africa. I explore how digital technologies reshape economic relationships and contract structures within and between firms, uncovering some key drivers and barriers to their adoption.

Over the past eight years, I have conducted research projects in Côte d'Ivoire, Ethiopia, Senegal, and Togo.

[Access my CV here] – deivyhoueix@fas.harvard.edu

Working Papers

  • Asymmetric Information and Digital Technology Adoption: Evidence from Senegal, [2025 Daniel Cohen Award], Media Coverage: RFI, World Bank Blog, Jeune Afrique
    Abstract

    Digital technologies promise large productivity gains, but generate data that can be made observable to others at low cost. I show that this embedded observability can be a double-edged sword: while it reduces information frictions and raises efficiency, it also threatens agents' informational rents and deters adoption. Two field experiments in Senegal's taxi industry illustrate this trade-off. When transactions are observable, owners monitor effectively and driver effort rises, but adoption falls---especially among poorer, low-performing drivers. Removing observability nearly doubles adoption and, in a relational contract framework, increases total welfare. The findings highlight how the very feature that enhances the efficiency of digital tools can also hinder their diffusion.

  • Relational Frictions Along the Supply Chain: Evidence from Senegalese Traders (with Edward Wiles), Media Coverage: World Bank Blog
    Abstract

    Search and trust frictions have historically made it hard for small firms in lower-income countries to buy inputs from foreign markets. The growth in smartphone ownership and social media usage has the potential to alleviate these barriers. Informed by a dynamic model of relational contracting, we run a field experiment leveraging these technological tools to provide exogenous variation in (1) search frictions and (2) trust frictions (adverse selection and moral hazard) in a large international import market. In the search treatment, we connect a randomly selected 80\% of 1,862 small garment firms in Senegal to new suppliers in Türkiye. We then cross-randomize two trust treatments that provide additional information about the types (adverse selection) and incentives (moral hazard) of these new suppliers. Reducing search frictions is sufficient to increase access to foreign markets: in all treated groups, firms are 26% more likely to have the varieties a mystery shopper requests, and the goods sold are 30% more likely to be high quality. However, the trust treatments are necessary for longer-term effects: using both transaction-level mobile payments data and a follow-up survey, we show that these groups are significantly more likely to develop the connections into relationships that persist beyond the endline survey. These new relationships lead to increases in medium-run profit and sales. Finally, we use the treatment effects to estimate the model and counterfactually lower the trust frictions among the whole supplier pool for a given firm, finding that the largest gains come from alleviating adverse selection.

  • Nationwide Diffusion of Technology Within Firms’ Social Networks [New version coming soon!], Media Coverage: Liberation
    Abstract

    I conduct a randomized experiment to study the nationwide technology diffusion of a new digital payment technology in Senegal. By leveraging two novel sources of network data—mobile money transactions and anonymized phone contact directories covering the near universe of the adult population in Senegal—I causally identify three sets of adoption spillovers from taxi firms randomized to receive early access to the technology: intra-industry among taxi firms; inter-industry between taxi drivers and other small businesses; and inter-regional spillovers from the capital city to businesses in other urban centers. I show that spillovers go beyond strategic complementarities, reflecting social learning within firms' social networks, driven by social ties and remote interactions.

  • Financial Inclusion and Rural Electrification: Evidence from Togo (with Paul Brimble, Axel Eizmendi Larrinaga, and Toni Oki)
    Abstract

    Most people in sub-Saharan Africa still lack access to electricity, despite rural electrification being a policy priority. We provide evidence that high transaction costs, particularly transportation expenses to access mobile money agents for bill payments, are a key friction for rural households. In rural Togo, these costs account for 28% of solar electricity-related expenditures, rising to 43% in more remote areas. To assess the impact of transaction costs on policy outcomes, we analyze the staggered rollout of two nationwide policies in Togo in 2019: a solar home system subsidy and an expansion of mobile money agents. The subsidy, which nearly halves electricity prices, more than doubles adoption rates. However, the effects vary significantly: households with lower transaction costs—those with direct access to mobile money agents—adopt at much higher rates and decrease the number of payments they make in response to the price reduction. The mobile money agent expansion led to nearly a threefold increase in adoption, an effect similar to that of the subsidy. By reducing transaction costs, these policies enable bulk purchases and lessen the need for frequent payments. Our findings highlight the complementary roles of subsidies and financial inclusion in improving rural electrification and access to essential services.

  • Aggregating Partial Rankings from Neighbors: Methodology and Empirical Evidence (with Pascaline Dupas and Marcel Fafchamps), R&R Quantitative Economics, [New version!]
    Abstract

    Many decisions require ordering alternatives: for example, the selection of top candidates for a competitive academic program or the selection of the poorest individuals for a cash transfer program. One common approach consists in aggregating orderings reported by different observers (e.g., committee or community members), but those orderings are typically partial: not all observers rank all applicants. We introduce a novel type of approach, based on pairwise rankings, to (i) aggregate partial orderings reported by multiple observers and (ii) construct confidence intervals for the resulting aggregate ordering. We identify, both theoretically and using simulations, the conditions under which a pairwise approach dominates rank averaging: when reporting error is low, reported orderings are partial, and observers rank alternatives that are close to each other in their true latent ordering. We introduce improvements to rank averaging and pairwise methods and illustrate them using several datasets. We find that, with partial reported orderings, Borda counts (i.e., simple rank averages) are dominated by the averaging of normalized ranks and should never be used in practice.

Reports