I am a Lecturer (Assistant professor) at the University of Sydney's School of Economics.

My research draws on insights from behavioral economics and employs econometrics, field-, and lab-in-the-field experiments to examine a variety of topics in development economics.

I also think a lot about heterogeneity: how it shapes the success and optimal design of public policy, and how heterogeneous returns affect individual decision-making.
Emilia Tjernström

Emilia Tjernström

Lecturer (Assistant professor)

School of Economics, University of Sydney


  • Development economics
  • Behavioral economics
  • Experimental economics


  • PhD in Agricultural and Resource Economics, 2015

    University of California, Davis

  • BA in Economics, 2006

    Colby College

Some things I am grateful for


If you can’t access a paywalled article, feel free to email me. I can almost always share a pre-print version.
Working papers

Heterogeneous Impact Dynamics of a Rural Business Development Program in Nicaragua

Abstract We study the impacts of a rural development program designed to boost the income of the small-farm sector in Nicaragua. Exploiting the random assignment of treatment, we find statistically and economically significant impacts on gross farm income and investment in productive farm capital. Using continuous treatment estimation techniques, we examine the evolution of program impacts over time and find that the estimated income increase persists and that the impacts on productive capital stock continue to rise even after the program concluded. Additionally, panel quantile methods reveal striking heterogeneity of program impacts on both income and investment. We show that this heterogeneity is not random and that there appear to exist low- performing household types who benefit little from the program, whereas high-performing (upper quantile) households benefit more substantially. Analysis using generalized random forests, a machine learning algorithm, points toward greater program impacts for households who were disadvantaged at baseline. Even after controlling for this source of heterogeneity, we find large and persistent differences in how much different types of households benefited from the program. While the benefit-cost ratio of the program is on average positive, the impact heterogeneity suggests that business development programs aiming to engage farm households as agricultural entrepreneurs have limitations as instruments to eliminate rural poverty.

Money Matters: The Role of Yields and Profits in Agricultural Technology Adoption

Abstract Despite the growing attention to technology adoption in the economics literature, knowledge gaps remain regarding why some valuable technologies are rapidly adopted, while others are not. This paper contributes to our understanding of agricultural technology adoption by showing that a focus on yield gains may, in some contexts, be misguided. We study a technology in Ethiopia that has no impact on yields, but that has nonetheless been widely adopted. Using three waves of panel data, we estimate a correlated random coefficient model and calculate the returns to improved chickpea in terms of yields, costs, and profits. We find that farmers’ comparative advantage does not play a significant role in their adoption decisions and hypothesize that this is due to the overall high economic returns to adoption, despite the limited yield impacts of the technology. Our results suggest economic measures of returns may be more relevant than increases in yields in explaining technology adoption decisions.

Natural Disasters, Social Protection, and Risk Perceptions

Abstract Natural disasters give rise to loss and damage and may affect subjective expectations about the prevalence and severity of future disasters. These expectations might then in turn shape individuals’ investment behaviors, potentially affecting their incomes in subsequent years. As part of an emerging literature on endogenous preferences, economists have begun studying the consequences that exposure to natural disasters have on risk attitudes, perceptions, and behavior. We add to this field by studying the impact of being struck by the December 2012 Cyclone Evan on Fijian households’ risk attitudes and subjective expectations about the likelihood and severity of natural disasters over the next 20 years. The randomness of the cyclone’s path allows us to estimate the causal effects of exposure on both risk attitudes and risk perceptions. Our results show that being struck by an extreme event substantially changes individuals’ risk perceptions as well as their beliefs about the frequency and magnitude of future shocks. However, we find sharply distinct results for the two ethnicities in our sample, indigenous Fijians and Indo-Fijians; the impact of the natural disaster aligns with previous results in the literature on risk attitudes and risk perceptions for Indo-Fijians, whereas they have little to no impact on those same measures for indigenous Fijians.

Fitting and Interpreting Correlated Random Coefficient (CRC) Models Using Stata

Abstract In this article, we introduce the community-contributed command randcoef, which fits the correlated random-effects and correlated random-coefficient models discussed in Suri (2011; Econometrica 79: 159–209). While this approach has been around for a decade, its use has been limited by the computationally intensive nature of the estimation procedure that relies on the optimal minimum distance estimator. randcoef can accommodate up to five rounds of panel data and offers several options, including alternative weight matrices for estimation and inclusion of additional endogenous regressors. We also present postestimation analysis using sample data to facilitate understanding and interpretation of results

Identifying the Impact Dynamics of a Small Farmer Development Scheme in Nicaragua

Do Differences in Attitudes Explain Differences in National Climate Change Policies?

Rational Foolishness Would Destroy a Public Service Broadcasting System

Working papers

  • Learning by (Virtually) Doing: Experimentation and Belief Updating in Smallholder Agriculture with Travis Lybbert, Rachel Hernández Frattarola, and Juan Sebastian Correa
    Revised and resubmitted 🤞
    Abstract In much of sub-Saharan Africa, soil quality heterogeneity hampers farmer learning about the returns to different inputs. This can partly explain why we observe limited adoption of improved inputs in the region. We study how Kenyan farmers respond to an interactive app that enables them to discover agricultural input returns on a virtual plot that is calibrated to resemble their own. Farmers update both their beliefs and behaviors after engaging with the virtual learning app. Additionally, farmers revise their beliefs upwards after using the app. In an incentive-compatible experiment, farmers receive an input budget from the research team, which they can allocate across farm inputs. After they play several virtual seasons on the app, they have the opportunity to update these allocations. Farmers revise their input allocations along several dimensions after the virtual learning experience. As evidence that these adjustments emerge from real learning, we show that farmers with the highest predicted returns to lime-- -an unfamiliar input in this region---increase their lime orders more than others. Our results suggest that engagement with a personalized virtual platform can induce real learning and enhance farmers' beliefs and technology choices.

  • Can Smallholder Extension Transform African Agriculture? with Joshua Deutschmann, Maya Duru and Kim Siegal
    NBER Working Paper No. 26054
    Abstract Agricultural productivity in Sub-Saharan Africa lags behind all other regions of the world. Decades of investment in agricultural research and extension have yielded more evidence on what fails than on what works---especially for the small-scale producers who dominate the sector. We study a program that targets multiple constraints to productivity at once, similar to anti-poverty "graduation" interventions. Analyzing a randomized controlled trial in western Kenya, we find that participation causes statistically and economically significant gains in output, yields, and profits. In our preferred specification, the program increases maize production by 26% and profits by 16%. The program increases yields uniformly across the sample, while treatment effects on total output and profit impacts are slightly attenuated at the top end of the distribution.

  • Media and Motivation: the Effect of Performance Pay on Writers and Content with Ivan Balbuzanov and Jared Gars
    Abstract We study how incentives for journalists affect the quantity, quality, and composition of online media content. We report results from a field experiment within an online news firm in Kenya. Writers were randomly allocated to earn a piece-rate per article published or to a pay-per-view (PPV) contract. The PPV contract induced writers to produce more "popular" articles, but writers chose to submit fewer articles. Specifically, the PPV contract resulted in a 120% increase in total pageviews, a 180% increase in pageviews per article, and a 40% reduction in the number of articles produced. In line with our theoretical predictions, the effect on article quantity is concentrated among risk averse writers. Further, when given a choice, risk-averse writers tend to select out of the output-based contract. We also document changes along multiple non-incentivized dimensions of news production: writers shift away from producing local news towards national-level news. We see limited changes in article quality or in the prevalence of clickbait. Our study suggests that output-based incentive contracts have substantial implications for journalists' effort and content choices, and more broadly for selection into risky "gig work."

  • A Group Random Coefficient Approach to Modeling Heterogeneity in Technology Adoption with Oscar Barriga Cabanillas, Dalia Ghanem, Travis Lybbert, Jeffrey D. Michler, and Aleksander Michuda
    Abstract Our paper revisits the econometric model that Suri (2011) (S2011) used in her study of heterogeneous returns to agricultural technology adoption. We propose an alternative group random coefficient (GRC) estimation strategy and revisit the empirical puzzle of why relatively few sub-Saharan farmers adopt modern technologies. Drawing on recent developments in the nonparametric panel identification literature, we start with an unrestricted GRC model that nonparametrically identifies the returns to adoption under time homogeneity. We show that the parameters of the S2011 correlated random coefficient model (CRC) can be identified from a restricted version of the GRC method. Specifically, the model in S2011 implies a key restriction that we call linearity in comparative advantage (LCA). Our unrestricted GRC model can be used to detect identification concerns for key structural parameters from the CRC model. We illustrate our method using the same data set as the original study and nd that the motivating empirical puzzle remains unsolved.

  • Learning from Others in Heterogeneous Environments
    (being revised; draft available upon request)

  • Seeds of Uncertainty: Information, Subjective Expectations, and Technology Adoption with Jared Gars
    draft available upon request

  • Filling a Niche: the Impacts of a Local Seed Company on Maize Productivity in Kenya with Samuel Bird, Michael Carter, Travis Lybbert, Mary Mathenge and Tim Njagi
    draft available upon request

Work in progress

  • Market-Level Effects of Competition in Agricultural Input Markets: Prices, Quality, and Mechanisms
    with Maya Duru and Laura Schechter

  • When Intentions Matter—Identifying the Prevalence and Source of Poor-quality Inputs in Kenya
    with Jose Clavijo and Travis Lybbert

  • Nonlinear Pricing Complexity and Consumer Behavior with Joshua Deutschmann and Jeff Michler

  • Arrested Development: the Inefficiencies of Electoral Cycles in Infrastructure Projects with Evan Morier

  • The Dirt on Dirt: Soil Characteristics and Variable Fertilizer Returns in Kenyan Maize Systems with Michael Carter and Travis Lybbert

  • Income Volatility and Technology Choice with Rachel Hernández Frattarola

  • Selection and Heterogeneity in the Returns to Migratio with Eduardo Cenci and Marieke Kleemans


Sometimes I am bad at email…
Please feel free to nudge me if I have not replied within a week
(and sooner if it is important!)