Alliance One Tobacco (Malawi)
Academic Research Repository at the Institute of Developing EconomiesNot a member yet
52305 research outputs found
Sort by
Institutional Guardianship and Opposition Fragmentation in Egypt’s Post-2011 Transition
No full textapplication/pdfIDP000994_001This paper examines why Egypt’s revolutionary coalition rapidly fractured after 2011, despite sustained mass mobilization and evident regime vulnerability. Instead of attributing fragmentation to repression, organizational weakness, or elite manipulation, the paper advances an institutional argument centered on the opposition’s engagement with state bodies perceived as relatively autonomous and authoritative. Focusing on the military, the judiciary, and Al-Azhar, the analysis shows how inherited legacies of autonomy, public trust, and symbolic authority encouraged opposition actors to redirect political conflict toward institutional arbitration. Under conditions of uncertainty, engagement with these institutions offered stability and protection to or constraints on rivals. However, the reliance on guardianship displaced horizontal coordination, reduced incentives for compromise, and produced patterned forms of fragmentation as actors aligned with different institutional pathways. Nevertheless, institutions that appeared capable of mediating conflict during moments of crisis remained embedded within the authoritarian order and insulated decisive authority from electoral competition through their interventions. This paper argues that authoritarian reconstitution in Egypt was enabled by coercion and interactional dynamics in which opposition strategies of institutional appeal and the autonomy of state institutions reinforced one another.technical repor
A New Perspective on China-Africa Relations: Interactions between Chinese Companies and Traditional Kingdoms in Uganda
No full textPJa/3/Af4application/pdfZAF202600_102中国アフリカ関係をめぐる研究は、中国とアフリカ諸国の国家間関係や、中国による対アフリカ援助や中国国営企業の活動がアフリカ諸国の政治経済に及ぼす影響を考察するという限られた視座から捉えられてきた。中国アフリカ関係を重層的に捉えているとは言い切れない従来の研究に対し、本稿では、多くのアフリカ諸国の地方統治に欠かせないアクターである伝統的権威に着目し、ウガンダ中部のブガンダ王国および同国西部のブニョロキタラ王国が、どのように中国アフリカ関係の構築において主体的な役割を果たしているのかを検討する。そして、主に2024 年から2025 年にかけて実施したフィールドワークから得られた一次資料の考察をもとに、伝統的権威が中国ウガンダ関係の輪郭を形成するうえで不可欠な役割を担っていることを示す。journal articl
Finding Beauty in Pain: working through pigment and blood in the works of Hervé Guibert, Léon-Gontran Damas, and Caio Fernando Abreu
No full textThis study focuses on issues of race and AIDS. I bring these issues together to think about how
they have both been understood through similar processes of stigmatization and shaming, and to
analyze the narrative responses created by writers in order to handle the grief associated with the
weight of such stereotyping, and to create beauty out of ugliness. The literature of AIDS and the
long history of racial stigma emerge in response to such grief,and the act of writing becomes an
act of mourning for the writers I study (Léon-Gontran Damas [France], Caio Fernando Abreu
[Brazil)] and Hervé Guibert [France]). All three write from an acute state of bereavement which
propels them to push against marginalization. They embrace their minoritized selves, and
reconstruct their diseased and racialized or outcasted bodies along terms that help them honor
their differences rather than reject them. My two objectives with this dissertation are: first, to
show how Damas, Abreu, and Guibert reject the external gaze and push against monolithic ideas
of what it means to exist in a corporeal and spiritual sense; and second, to focus on questions of
reception and appreciation, and on the impact the writing has on their readers.Romance Languages and Literature
Understanding the factors controlling ozone pollution in East Asia
No full textEast Asia is one of the most severely polluted regions in the world. A key component of this pollution is tropospheric ozone, which poses a threat to both human and ecosystem health. Despite targeted efforts to reduce emissions, tropospheric ozone has continued to rise steadily in the region over the past twenty years. This dissertation investigates the factors controlling ozone pollution in East Asia using integrated data analysis from satellites, aircraft campaigns, and in-situ measurements, as well as chemical transport modeling. Specific topics addressed in my dissertation include the following:
Infer the spatial distribution of surface ozone concentrations in Asia using multispectral satellite ozone retrievals (Chapter 1):
Over the past two decades, satellite instruments have provided unprecedented information on global air quality, but direct inference of surface ozone from space remains challenging. Here, we develop a novel approach that combines multispectral ozone retrievals from the thermal infrared Tropospheric Emission Spectrometer (TES) and the ultraviolet-visible Ozone Monitoring Instrument (OMI) with a chemical reanalysis. Our results show the potential of combining satellite measurements and chemical reanalyses to augment air quality assessments in regions lacking robust surface monitoring networks.
Diagnose the causes of persistently high surface ozone in South Korea (Chapter 2):
Despite substantial efforts to reduce emissions, South Korea continues to experience widespread exceedances of their ozone standard. I examine trends in ozone and from 2015–2019 across South Korea, identifying volatile organic compounds (VOCs) as a dominant driver of ozone formation under current conditions. Simulations with anthropogenic emissions zeroed out reveal a significant external background contribution, implying that the air quality standard in South Korea is not practically achievable unless this background external to East Asia can be decreased.
Determine the origin of increasingly high background ozone in East Asia (Chapter 3):
From Chapter 2, we find that severe surface ozone pollution in East Asia is due in part to an elevated background subsiding from the free troposphere. We find that increasing background ozone is driven by enhanced stratospheric downwelling in recent years. This growing stratospheric contribution poses a substantial obstacle to achieving air quality standards, suggesting that mitigation strategies must account for both anthropogenic emissions and climate-driven changes in stratosphere–troposphere exchange.Earth and Planetary Science
Spatio-Temporal Methods for Causal Inference in Quasi-Experimental Studies: Applications to Environmental Health
No full textModern environmental health studies often rely on quasi-experimental designs, where policies or external shocks induce localized changes in exposure across geographic regions. When comprehensive panel data are available before and after an intervention, one can, in principle, leverage the observed data to reconstruct counterfactual trends. Yet rare outcomes (e.g., low counts of a disease) and unmeasured confounding that evolves dynamically across regions and periods can undermine standard approaches like difference-in-differences or synthetic control methods. This dissertation develops a unified suite of Bayesian spatio-temporal methods, spatio-temporal matrix completion and Gaussian process models, that explicitly borrow strength across units and time points to stabilize inference and quantify uncertainty. Through extensive simulations and real-data applications, we demonstrate how these methods generalize popular causal tools, yield interpretable weighting schemes, and provide practical guidance on model implementation for environmental health research.
In Chapter 1, we introduce Bayesian spatio-temporal matrix completion models tailored for rare count outcomes in quasi-experimental panel data through an application examining the impacts of traffic-related air pollution (TRAP) on childhood hematologic cancers. Although some pollutants emitted in vehicle exhaust, such as benzene, are known to cause leukemia in adults with high exposure levels, less is known about the relationship between TRAP and childhood hematologic cancer. In the 1990s, the US EPA enacted the reformulated gasoline program in select areas of the US, which drastically reduced ambient TRAP in affected areas. This created an ideal quasi-experiment to study the effects of TRAP on childhood hematologic cancers. However, existing methods for quasi-experimental analyses can perform poorly when outcomes are rare and unstable, as with childhood cancer incidence. We develop Bayesian spatio-temporal matrix completion methods to conduct causal inference in quasi-experimental settings with rare outcomes. Selective information sharing across space and time enables stable estimation, and the Bayesian approach facilitates uncertainty quantification. We evaluate the methods through simulations and apply them to estimate the causal effects of TRAP on childhood leukemia and lymphoma.
In Chapter 2, we expand on Chapter 1 to investigate the potential heterogeneous impacts of the reformulated gasoline program on the incidence of CYA lymphoma across disease type and demographic strata. We employ recently-proposed Bayesian causal Gaussian process (GP) models, applied to population cancer registry data, to estimate effects of the program on CYA lymphoma incidence across strata defined by cancer type, sex, race, Hispanic ethnicity, and age group. Our analytic framework allows for stable estimation of stratum-specific effects via data-driven information sharing across space, time, and strata. Effects are reported on both the absolute and relative scales. We find evidence that the largest program-attributable reductions in lymphoma incidence rates occurred for Hodgkin lymphoma, and among individuals who are male, white, and/or aged 20-29. The finding of larger reductions in Hodgkin lymphoma is notable since prior TRAP studies have primarily focused on non-Hodgkin lymphoma.
In Chapter 3, we delve deeper into Gaussian process approaches for quasi-experiments, addressing diverse confounding structures that may not be fully accommodated by the model presented in Chapter 2. Estimating causal effects in quasi-experiments with spatio-temporal panel data often requires adjusting for unmeasured confounding that varies across space and time. Gaussian processes offer a flexible, nonparametric modeling approach that can account for such complex dependencies through carefully chosen covariance kernels. In this paper, we provide a practical and interpretable framework for applying GPs to causal inference in panel data settings. We demonstrate how GPs generalize popular methods such as synthetic control and vertical regression, and we show that the GP posterior mean can be represented as a weighted average of observed outcomes, where the weights reflect spatial and temporal similarity. To support applied use, we explore how different kernel choices impact both estimation performance and interpretability, offering guidance for selecting between separable and nonseparable kernels. Through simulations and application to Hurricane Katrina mortality data, we illustrate how GP models can be used to estimate counterfactual outcomes and quantify treatment effects. All code and materials are made publicly available to support reproducibility and encourage adoption. Our results suggest that GPs are a promising and interpretable tool for addressing unmeasured spatio-temporal confounding in quasi-experimental studies.Biostatistic
Essays in Behavioral Dynamics
No full textThis thesis consists of three chapters that study behavior when people make correct inferences from observed events but make mistakes when reasoning about hypothetical events. This type of behavior is documented in a growing experimental literature on failures of contingent thinking. The first chapter proposes a theoretical framework for analyzing this behavior in competitive markets, introducing Dynamic Cursed Expectations (DCE) and the corresponding equilibrium concept, Dynamic Cursed Expectations Equilibrium (DCEE). The second chapter studies an asset pricing model and shows that DCEE leads to overvaluation of risky assets and overtrading relative to the Rational Expectations Equilibrium benchmark. The third chapter introduces Sequential Cursed Equilibrium (SCE) for extensive games and shows that multiple experimental results on failures of contingent thinking can be explained by SCE behavior.Economic
Stereotypes that Dumbfound: Comprehensive Investigations Across Content, Methods, and Demography
No full textStereotypes help humans navigate a complex social world by offering heuristics about the characteristics of social groups. Nevertheless, stereotypes can hinder decision-making along two paths. First, even when stereotypes are accurate at the group-level, meaning they reflect statistically significant differences between groups (e.g., height differences between men and women), stereotypes can prevent accurate inferences at the individual-level. Second, when stereotypes are inaccurate at the group-level, all inferences that follow – at the group-level and individual-level – are necessarily inaccurate.
Across five chapters, I examine stereotypes with group-level accuracy and group-level inaccuracy to obtain general insights about their magnitude (how robust is the stereotype?), pervasiveness (which groups or places exhibit the stereotype most strongly or weakly?), mechanisms (what features drive the effect?), and malleability (can even entrenched stereotypes change?). In doing so, I show how both types of stereotypes can dumbfound because they (a) impede accurate inferences, (b) conflict with ground-truth data and/or (c) contradict participants’ own stated beliefs and values.
Chapter I (Morehouse et al., 2022; CRESP) presents 7 experiments (N > 7,000) probing the nature of a stereotype with group-level accuracy: surgeon=male. In particular, I examine the magnitude, prevalence, mechanisms, and malleability of this gender-occupation stereotype, and whether it is sufficiently strong to prevent logical inferences. A Supplemental Chapter (Morehouse, Pan, Contreras, & Banaji, 2024; ICML) extends this work by exploring whether a Large Language Model – GPT-4 – similarly exhibits gender-occupation stereotypes across a set of 1,016 diverse occupations. Additionally, I tested whether systematic changes to the input prompt influence the degree of observed bias.
Chapter II (Morehouse et al., 2025; Scientific Reports) leverages an archival dataset with over 600,000 respondents to interrogate the “American=White” stereotype. Although the US has been historically majority-White, this stereotype lacks group-level accuracy because all Americans, regardless of ethnic ancestry, are American. Beyond benchmarking stereotype strength at the societal-level, I uncover individual-level and regional-level predictors of this American=White effect and use time-series models to examine whether it has changed over the past 17 years (2007-2023).
Chapter III (Morehouse, Maddox & Banaji, PNAS) reports 13 experiments (N > 60,000) to test a stereotype that dumbfounds by defying biological fact and participants’ explicitly held beliefs: “Human=White.” In addition to probing its existence, I examine whether this stereotype is pervasive across U.S. demographic groups (e.g., gender and political ideology) and conduct exploratory analyses to assess its emergence in non-US countries. Finally, Chapter IV (Morehouse, Ueda, Saiki, & Banaji, in prep) investigates whether these findings are unique to dominant groups in Western contexts or represent a more universal “Human=Own (Dominant) Group” effect. Specifically, four samples of Japanese participants (tested in two Japanese writing systems, Katakana and Kanji) were recruited to test the magnitude and prevalence of a “Human=Japanese” effect in Japan.
Together, these five chapters harness data from ~700,000 respondents across 37 experiments to demonstrate that (1) even stereotypes with group-level accuracy prevent simple inferences; (2) implicit stereotypes with group-level inaccuracy are surprisingly robust and pervasive across groups and geography; (3) certain demographic characteristics consistently predict stereotype strength; and (4) even widely held stereotypes are malleable; they are sensitive to targeted interventions and the passage of time. In doing so, this body of work illuminates the features that create, maintain, and change stereotypes that dumbfound.Psycholog