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Essays on Competition in Housing Markets
No full textThis dissertation comprises two essays on competition in housing markets. The first essay investigates the impact of market power in residential real estate. I study this question empirically in the context of the Chicago rental market. To do so, I build a novel dataset that links the universe of market-rate multifamily properties and their owners from 2000 to 2023. Using a staggered event study design, I find that acquisitions of competing properties raise price and reduce occupancy. I then estimate a structural model of rental demand and supply, and use the estimates to calculate welfare under various policy counterfactuals. These results highlight how market power mediates the effectiveness of urban rental policies and shapes housing affordability in the 21st century. The second essay examines imperfect competition and quality degradation in affordable housing markets. In these markets, I hypothesize that landlords choose quality in order to maximize profit. To evaluate this hypothesis, I link all rental housing properties in the city of Chicago to data on building quality, and I explore how and when building acquisitions lead to changes in quality
Budgeted Signaling: Rethinking Post-Cold War EU Member States’ Defense Spending and Militarization
No full textWhat explains European states’ defense spending behavior? This paper seeks to answer this question by first examining the current debates around this topic. While each of these debates has its own merit, it is far from offering comprehensive explanations. Therefore, I developed three hypotheses to evaluate which one holds the most explanatory power. Through testing four different models with controls and country-fixed effects, I find European states want to signal their credibility as security actors through defense spending. This has important implications for what militarization is and how the process of militarization goes beyond security purposes
Investigating neural correlates of attention in relation to the development of executive functions in early childhood
Get PDFMost previous studies investigating early neural predictors of Executive Function (EF) abilities focused on resting-state brain activity in infancy, with mixed findings. Here, we investigated early neural predictors of later-emerging EF abilities by measuring task-related changes in brain activity, which we argue to be more sensitive to detecting individual differences in EF skills. Sixty-six 9-month-old infants participated in an action observation and execution task, while their brain activity was recorded. Two conditions were used, which required different levels of cognitive control and social engagement: one group of infants saw an experimenter performing actions in consecutive trials and then performed similar actions themselves (the Blocked condition), while the other group performed the actions, taking turns with the experimenter (the Interleaved condition). At age five, 45 of the original infants returned for follow-up assessments and completed a battery of well-established EF tasks. Of these 45 participants, 35 infants provided usable neural data at 9 months and behavioral EF data at age 5 and were included in the final analysis. Results revealed a close link between infants’ neural activity and their EF abilities that were specific to frontal theta oscillations, a neural component associated with high-order cognition, and to the Interleaved condition, which was the condition that required greater attentional control and social engagement from infants. The results highlight the importance of selecting appropriate tasks and neural measures to detect longitudinal brain-behavior relations
Scripts, Scholars, and the State: The Role of Empire, Scholarship, and the Census in Shaping Religious Identity in Colonial India
Get PDFThis thesis investigates the emergence of modern Hindu identity during the British colonial period in India through the lens of interconnected intellectual, administrative, and ideological networks. Contrary to deterministic accounts that attribute the creation of Hinduism solely to British colonialism, this study argues that Hindu identity was co-constituted by a diverse array of actors and institutions. These included British Orientalist scholars such as William Jones and Max Müller, colonial bureaucrats who designed and implemented the census and legal reforms, and Indian reformists and nationalists who internalized and reframed these colonial categories. Drawing on a network analysis approach, the study traces the interplay between textual translation, legal codification, census enumeration, and nationalist mobilization. Through close examination of primary sources—including the 1871, 1881, and 1891 Indian census reports—and a wide array of secondary scholarship, this thesis demonstrates that modern Hindu identity was neither wholly imposed from above nor spontaneously arising from within. Rather, it was a contingent, negotiated outcome of overlapping discursive and institutional forces. In emphasizing the relational and contested nature of identity formation, the thesis contributes to a more nuanced understanding of how religion, statecraft, and knowledge production interacted in colonial South Asia
Three Essays on Labor Markets in India
No full textThe first chapter studies the contractual frictions which arise in low wage labor markets due to liquidity constraints and limited commitment on both sides of the market. Using three field experiments I show that these frictions are quantitatively large and lead to significant inefficiencies. The second chapter analyses undercutting behavior of workers in wage negotiations with firms at spot markets. It highlights that despite oversupply of labor and high unemployment, rate of undercutting is fairly low. Using variation in job contract structure, the chapter shows that workers value of leisure hours is a crucial determinant of their undercutting behavior. Unlike the first two chapters which focus on contemporary labor markets, the third chapter looks at labor markets over a long period of time on both sides of the boundary of the princely state of Hyderabad. The chapter shows that outcomes of different caste groups on either side of the boundary were affected by the differences in the ruling order and the labor institutions that arose as a consequence of those orders
Ski Resort Green Marketing in the Rocky Mountain West
No full textIn this dataset, we assess the prevalence of sustainability efforts of all major ski areas across the U.S. Rocky Mountain West (n = 83) and develop a quantitative metric for each ski area’s sustainability marketing. We also include data for seven independent variables at all 83 resorts.
Each resort’s acreage and lift ticket price (on an off-peak Winter Saturday) was found on the resort’s own website. We also found out whether each resort publicized the employment of a sustainability director or another similar position (any dedicated staff member for environmental/sustainability management or education was counted, no matter their title, such as “ecology specialist” or “environmental education manager”). A list of SSC member resorts is kept by the National Ski Areas Association, which we used to determine each resort’s membership status. 2020 Election data, specifically the margin by which Donald Trump won or lost each resort’s home county and state, comes from the MIT Election Data Lab (MIT Election Data and Science Lab, 2018). Climate projections for each resort, specifically the projected proportion of ski days lost by 2050 in an RCP 8.5 warming scenario, come from a recent analysis from the American Meteorological Society (Lackner et al, 2021).
Previously published climate predictions were only available for 69 resorts out of the 83 examined in the study (Lacker et al, 2021). To generate values for the other resorts, we employed an imputation method, using a k-nearest-neighbors classification, where each resort was grouped with the 5 closest to it in a three-dimensional space with normalized axes of base elevation, summit elevation, and latitude. Then, the average climate prediction values between those 5 resorts were imputed to the missing value
Non-Asymptotic Statistical Analysis of Ensemble Based Filtering Algorithms
Get PDFAt its core, this dissertation aims to formalize and explain—through a statistical lens—the empirical success of popular ensemble-based algorithms in the data assimilation literature. A key component of this effort is the derivation of non-asymptotic, dimension-free bounds for the estimation of covariance operators. To achieve this, we leverage existing techniques from high-dimensional probability while also developing new theoretical tools to analyze the behavior of a certain class of covariance estimators under structural assumptions. This dissertation rigorously establishes fundamental guarantees for these estimators, shedding light on the mechanisms that drive their effectiveness and providing a deeper understanding of their practical success
Introspective access to value-based multi-attribute choice processes
Get PDFPeople routinely choose between options varying on multiple attributes – homes to rent, movies to watch, and so on. Here, we test how much awareness people have of the mental processes underlying these choices. We develop a method to quantify awareness of value-based multi-attribute choice processes that accounts for diverse choice strategies. Across five studies, participants make choices and then report how they believe they made them. We use computational modeling to identify the process revealed in their choices, and compare it to their self-reports to quantify individuals’ accuracy about their choice process. While we observe substantial variation in accuracy, participants are often highly accurate about their choice process – more accurate than predicted by a sample of decision scientists – and more accurate than informed third-party observers, suggesting evidence for introspection. These results challenge notions that we are strangers to ourselves and instead suggest that people often know how they made value-based choices
Genetic and Nongenetic Risk Factors for Breast Cancer Risk Estimation
Get PDFImportance: Most breast cancers in Africa are diagnosed at advanced stages. Improved risk prediction tools to optimize screening and earlier diagnosis are urgently needed. Objective: To build a comprehensive breast cancer risk estimation model by integrating a polygenic risk score (PRS), pathogenic variants (PVs) in high- or moderate-penetrance genes, and a questionnaire-based risk calculator. Design, Setting, and Participants: This multicenter case-control study initially enrolled women in Nigeria in 1998 and expanded to Cameroon and Uganda in 2011; enrollment ended in 2018. Women with breast cancer (hereafter cases) were enrolled through hospital oncology units, whereas women without breast cancer (hereafter controls) were recruited from other outpatient clinics and the community. Participants whose genetic data were used in PRS development were excluded from the development of the comprehensive breast cancer risk estimation model. Analyses were performed from September 2023 to January 2025. Exposures: Lifetime absolute risk estimation models that integrated a PRS only (previously developed using data from women of African ancestry and European ancestry), PRS plus PVs in high- or moderate-penetrance genes (BRCA1, BRCA2, PALB2, ATM, CHEK2, TP53, BARD1, RAD51C, and RAD51D), epidemiologic risk factors only (ascertained from NBCS questionnaires), and a combined model containing these 3 components. Main Outcomes and Measures: Lifetime absolute risk of breast cancer was estimated, accounting for an association between family history and genetic factors. Participants’ lifetime estimated absolute risk was categorized by the following risk thresholds: lower than 3%, 3%, 5%, and 10% or higher. Results: A total of 1686 women, of whom 996 were cases (mean [SD] age at enrollment, 49.5 [12.2] years) and 690 were controls (mean [SD] age at enrollment, 41.5 [13.8] years), were included in the main analyses. The age-adjusted area under the receiver operating characteristic curve (AUROC) was 0.579 (95% CI, 0.549-0.610) for the PRS only model and 0.609 (95% CI, 0.579-0.638) for the PRS plus PV model. In the combined model containing both genetic and nongenetic risk factors, age-adjusted AUROC increased to 0.723 (95% CI, 0.698-0.748). Using a threshold of 10% or higher lifetime absolute risk, the combined model classified 12.0% of cases (120) as high risk compared with 3.7% of cases (37) using the epidemiologic factors only model and 5.0% of cases (50) using the PRS plus PV model. Conclusions and Relevance: In this case-control study, a breast cancer risk estimation model was developed that combines genetic and nongenetic factors and refines a previous model that includes epidemiologic risk factors. Further development and validation of this model are necessary to advance breast cancer risk assessment in sub-Saharan Africa.</p
Explainable differential diagnosis with dual-inference large language models
Get PDFAutomatic differential diagnosis (DDx) involves identifying potential conditions that could explain a patient’s symptoms and its accurate interpretation is of substantial significance. While large language models (LLMs) have demonstrated remarkable diagnostic accuracy, their capability to generate high-quality DDx explanations remains underexplored, largely due to the absence of specialized evaluation datasets and the inherent challenges of complex reasoning in LLMs. Therefore, building a tailored dataset and developing novel methods to elicit LLMs for generating precise DDx explanations are worth exploring. We developed the first publicly available DDx dataset, comprising expert-derived explanations for 570 clinical notes, to evaluate DDx explanations. Meanwhile, we proposed a novel framework, Dual-Inf, that could effectively harness LLMs to generate high-quality DDx explanations. To the best of our knowledge, it is the first study to tailor LLMs for DDx explanation and comprehensively evaluate their explainability. Overall, our study bridges a critical gap in DDx explanation, enhancing clinical decision-making