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 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, Media Coverage: RFI, World Bank Blog, Jeune Afrique
    Abstract

    Digital technologies have the potential to increase firm productivity. However, they often come bundled with data observability, which can be a double-edged sword. Observability reduces information frictions and can increase efficiency, but some agents may lose their informational rent and thus resist adoption. I explore this trade-off between observability and adoption through two field experiments conducted over nearly two years. These experiments, guided by contract theory, introduce digital payments to the Senegalese taxi industry in partnership with the country's largest payment company. In the first experiment, I randomize access to digital payments for drivers (employees) and transaction observability to taxi owners (employers). I find that digital payments reduce drivers' cash-related costs by about half but also serve as effective monitoring tools for taxi owners. Transaction observability substantially increases driver effort, contract efficiency, and the duration of owner-driver relationships. However, 50% of drivers—primarily the worst-performing and poorest—decline to adopt digital payments when transactions are observable. The second experiment shows that the adoption rate doubles when drivers are assured that owners will not be able to observe their transactions. I develop a theoretical framework and use the experimental variations to estimate the welfare impacts of policy counterfactuals. I show that removing transaction observability would maintain moral hazard problems but broaden adoption and thus increase overall welfare—an approach ultimately implemented by the payment company. These findings highlight the crucial role of information embedded in digital technologies, as it magnifies gains for adopting firms but can deter initial adoption.

  • Nationwide Diffusion of Technology Within Firms’ Social Networks, 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.

  • 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 our search treatment, we connect a randomly selected 80% of 1,862 small garment firms in Senegal to new suppliers in Turkey. We then cross-randomize two trust treatments that provide additional information about the types (adverse selection) and incentives (moral hazard) of these new suppliers. Alleviating 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 impact: 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 study. These new relationships lead to increases in medium-run profit and sales. Finally, we use the treatment effects to estimate the model and evaluate counterfactuals where we set various combinations of the frictions to zero, finding that the largest gains come from eliminating adverse selection.

  • 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.

  • Eliciting Poverty Rankings from Urban or Rural Neighbors: Methodology and Empirical Evidence (with Pascaline Dupas and Marcel Fafchamps), Revised August 2024 for Quantitative Economics
    Abstract

    We introduce a novel approach for eliciting relative poverty rankings that aggregates partial orderings reported independently by multiple neighbors. We first identify the conditions under which the method recovers more accurate rankings than the commonly used Borda count method. We then apply the method to secondary data from rural Indonesia and to original data from urban Cote d’Ivoire. We find that the aggregation method works as well as Borda count in the rural setting but, in the urban setting, reconstructed rankings from both the pairwise and Borda count methods are often incomplete and sometimes contain ties. This disparity suggests that eliciting poverty rankings by aggregating rankings from neighbors may be more difficult in urban settings. We also confirm earlier research showing that poverty rankings elicited from neighbors are correlated with measures of poverty obtained from survey data, albeit not strongly. Our original methodology can be applied to many situations in which individuals with incomplete information can only produce a partial ranking of alternatives.

Reports