About

Dalia Ghanem is an Associate Professor at the Department of Agricultural and Resource Economics at UC Davis. Her research focuses on panel data econometrics, causal inference, nonlinear models, and environmental economics. She has contributed to the development and application of econometric methods for business decisions and environmental policy analysis, as evidenced by her teaching of courses such as NEW-Econometrics for Business Decisions and Applied Econometrics II. Her work integrates advanced econometric techniques to address complex issues in environmental and resource economics, supporting policy-making and economic analysis in these fields.

Research topics

• Computer Science
• Political Science
• Mathematics
• Econometrics
• Statistics
• Machine Learning
• Environmental science
• Economics
• Psychology
• Meteorology
• Medicine
• Engineering
• Geography

Selected publications

• Replication package for: Comment on Suri (2011) "Selection and Comparative Advantage in Technology Adoption"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-10

  datasetOpen access

  Replication package (using synthetic data) for Comment on Suri (2011) "Selection and Comparative Advantage in Technology Adoption" by Emilia Tjernström, Dalia Ghanem, Aleksandr Michuda, Oscar Barriga-Cabanillas, Travis J. Lybbert, and Jeffrey D. Michler.

  PublisherDOI

• When Should Pre-trends Be Parallel?

  AEA Papers and Proceedings · 2026-05-01

  article1st authorCorresponding

  We analyze pre-trends tests through the lens of how units select into treatment. We derive necessary and sufficient conditions for pre-trends and trends to be parallel with and without covariates. These conditions show that even in the absence of structural breaks, pre-trends tests can be uninformative about parallel trends, except under specific restrictions on selection. Thus, correctly interpreting pre-trends tests requires an understanding of the units’ selection behavior, and pre-trends tests cannot replace economic arguments for parallel trends. We document additional issues with pre-trends tests when researchers control for pre-treatment values of time-varying covariates.

  PublisherDOI

• Replication package for: Comment on Suri (2011) "Selection and Comparative Advantage in Technology Adoption"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-10

  datasetOpen access

  Replication package (using synthetic data) for Comment on Suri (2011) "Selection and Comparative Advantage in Technology Adoption" by Emilia Tjernström, Dalia Ghanem, Aleksandr Michuda, Oscar Barriga-Cabanillas, Travis J. Lybbert, and Jeffrey D. Michler.

  PublisherDOI

• Quantifying Threshold Manipulation in the Presence of Rounding: The Case of Lead Monitoring in US Drinking Water

  American Economic Review Insights · 2025-08-27 · 1 citations

  article

  Many laws and economic actions depend on thresholds. As a consequence, threshold manipulation is a common concern in a variety of settings. Existing methods for detecting and quantifying threshold manipulation assume a continuous counterfactual distribution absent manipulation. This assumption is violated in the presence of rounding, which is prevalent in many applications and distinct from manipulation. This paper develops methods for testing and quantifying threshold manipulation when rounding is a prominent feature of the data. We demonstrate the usefulness of our approach in an empirical application examining threshold manipulation in lead monitoring under the U.S. Safe Drinking Water Act.

  PublisherDOI

• Correcting attrition bias using changes-in-changes

  Journal of Econometrics · 2024-04-01 · 2 citations

  article1st authorCorresponding
  PublisherDOI

• Testing Attrition Bias in Field Experiments

  The Journal of Human Resources · 2023 · 36 citations

  1st authorCorresponding
  • Computer Science
  • Econometrics
  • Computer Science

  <h3>Abstract</h3> We approach attrition in field experiments with baseline data as an identification problem in a panel model. A systematic review of the literature indicates that there is no consensus on how to test for attrition bias. We establish identifying assumptions for treatment effects for both the respondents and the study population, and propose procedures to test their sharp implications. We then relate our proposed tests to current empirical practice, and demonstrate that the most commonly used test in the literature is not a test of internal validity in general. We illustrate the relevance of our analysis using several empirical applications.

  PublisherDOI

• Smuggling and State Formation: A Match Made in Algeria

  2023-01-01

  book-chapter1st authorCorresponding
  PublisherDOI

• On model selection criteria for climate change impact studies

  Journal of Econometrics · 2023 · 13 citations

  • Computer Science
  • Econometrics
  • Computer Science

  Climate change impact studies inform policymakers on the estimated damages of future climate change on economic, health and other outcomes. In most studies, an annual outcome variable is observed, e.g. agricultural yield, along with a higher-frequency regressor, e.g. daily temperature. Applied researchers then face a problem of selecting a model to characterize the nonlinear relationship between the outcome and the high-frequency regressor to make a policy recommendation based on the model-implied damage function. We show that existing model selection criteria are only suitable for the policy objective if one of the models under consideration nests the true model. If all models are seen as imperfect approximations of the true nonlinear relationship, the model that performs well in the historical climate conditions is not guaranteed to perform well at the projected climate. We therefore propose a new criterion, the proximity-weighted mean squared error (PWMSE) that directly targets precision of the damage function at the projected future climate. To make this criterion feasible, we assign higher weights to historical years that can serve as “weather analogs” to the projected future climate when evaluating competing models using the PWMSE. We show that our approach selects the best approximate regression model that has the smallest weighted squared error of predicted impacts for a projected future climate. A simulation study and an application revisiting the impact of climate change on agricultural production illustrate the empirical relevance of our theoretical analysis.

  PublisherDOI

• Evaluating the Impact of Regulatory Policies on Social Welfare in Difference-in-Difference Settings

  arXiv (Cornell University) · 2023-06-07 · 1 citations

  preprintOpen access1st authorCorresponding

  Quantifying the impact of regulatory policies on social welfare generally requires the identification of counterfactual distributions. Many of these policies (e.g. minimum wages or minimum working time) generate mass points and/or discontinuities in the outcome distribution. Existing approaches in the difference-in-difference literature cannot accommodate these discontinuities while accounting for selection on unobservables and non-stationary outcome distributions. We provide a unifying partial identification result that can account for these features. Our main identifying assumption is the stability of the dependence (copula) between the distribution of the untreated potential outcome and group membership (treatment assignment) across time. Exploiting this copula stability assumption allows us to provide an identification result that is invariant to monotonic transformations. We provide sharp bounds on the counterfactual distribution of the treatment group suitable for any outcome, whether discrete, continuous, or mixed. Our bounds collapse to the point-identification result in Athey and Imbens (2006) for continuous outcomes with strictly increasing distribution functions. We illustrate our approach and the informativeness of our bounds by analyzing the impact of an increase in the legal minimum wage using data from a recent minimum wage study (Cengiz et al 2019).

  PublisherOA PDFDOI

• Understanding the Persistence of Competitive Authoritarianism in Algeria

  Middle East Today · 2022-01-01 · 7 citations

  book1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Junjie Zhang

  State Grid Corporation of China (China)

  47 shared

• Shu Shen

  45 shared

• Aaron Smith

  8 shared

• Sarojini Hirshleifer

  7 shared

• Karen Ortiz‐Becerra

  7 shared

• Xiaomeng Cui

  Institute for Social and Economic Research

  4 shared

• Désiré Kédagni

  3 shared

• Pedro H. C. Sant’Anna

  Emory University

  3 shared

Education

• B.A., Economics and Political Science

  American University in Cairo, Egypt

  2003

• M.S., Econometrics and Mathematical Economics

  London School of Economics and Political Science, UK

  2007

• Ph.D., Economics

  University of California, San Diego

  2013