{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/121438"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/121438","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Essays on spatial, health, and socioeconomic interactions","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","abstract_has_math":false,"creators":["Lee, Jieun"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Bera, Anil","Li, Bo","Shao, Xiaofeng","Chung, EunYi"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-08","date_published":"2023-08","updated_at":"2026-07-22T22:24:57Z","subjects":["Spatial Dynamic Panel Data Model","Stochastic/non-predetermined Trigger","Endogenous Spatial Weight Matrix","Score Test","Lagrange Multiplier Test","Incidental Parameters Problem","Local Parametric Misspecifications","Weak Identification","Health Capital","Human Capital","Knowledge Spillover","Neoclassical Growth Model","Social Capital","Networks","Baby-boomers","Ageing","Mixture Model Of Group-based Developmental Trajectories"],"languages":["en","eng"],"rights":["Copyright 2023 Jieun Lee"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/121438","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bera, Anil","Li, Bo","Shao, Xiaofeng","Chung, EunYi"]},{"key":"dc:creator","label":"Author","values":["Lee, Jieun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-08","2023-07-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Spatial Dynamic Panel Data Model","Stochastic/non-predetermined Trigger","Endogenous Spatial Weight Matrix","Score Test","Lagrange Multiplier Test","Incidental Parameters Problem","Local Parametric Misspecifications","Weak Identification","Health Capital","Human Capital","Knowledge Spillover","Neoclassical Growth Model","Social Capital","Networks","Baby-boomers","Ageing","Mixture Model Of Group-based Developmental Trajectories"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Jieun Lee"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/121438"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","The student, Jieun Lee, accepted the attached license on 2023-06-29 at 08:07.","The student, Jieun Lee, submitted this Dissertation for approval on 2023-06-29 at 08:07.","This Dissertation was approved for publication on 2023-07-05 at 16:53.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19474 on 2023-12-04 at 17:00:16","This is a series of studies regarding various types of spillover effects via spatial, health, and socioeconomic interactions. Chapter 1 A stochastic or non-predetermined spillover framework is very general and broadly applicable to account for the effects of economic interactions. However, in this case, a spatial weight matrix might be endogenous and thus needs to be tested since a valid and optimal spatial model depends on its endogeneity. To this end, I develop the robust score test (or equivalently Lagrange multiplier test) to determine the endogeneity of a spatial weight matrix in a “weak” spatial dynamic panel data (SDPD) model (Qu, Lee, and Yu 2017) in the sense that parameters associated with the stability condition are weakly identified from zero. First, I analytically correct the score function biases to resolve the incidental parameters problem. Second, I orthogonalize the score functions so that the score test statistic is robust to local parametric misspecification in the weakly identified parameters. A Monte Carlo simulation performs in favor of the theory and shows nice finite sample properties in terms of size and power. Finally, an empirical illustration using the Penn World Table version 7.1 describes how this testing helps researchers select the valid and optimal spatial model at their early research stage. Chapter 2 Health capital has been studied as an alternative form of human capital that affects productivity and, consequently, a country’s aggregate technology or knowledge. This paper examines the presence of knowledge spillovers triggered by health capital as a representative non-economic factor. Following the spatially augmented neoclassical growth model (Ertur and Koch 2007), countries are exposed to externalities in knowledge. Since countries observe each other’s levels of health capital and are partially aware that health capital signals a boost in one’s knowledge, they are expected to actively interact and be matched with different weights depending on the proximity of their health capital levels. The model is empirically tested with the country-level economic and health dataset provided by the Penn World Table (version 7.1) and World Bank data. The key finding is the presence of a significant positive externality in knowledge triggered by health capital. Discussions and policy implications follow. Chapter 3 Social capital (SC) is both an input and an output of individuals’ economic choices, but relatively little is known about SC investment, particularly in individuals’ old age. With a premise that SC is an individual-level concept in which individuals purposely invest, we estimate elderly individuals’ stock and investment in SC using principal component analysis of their social engagement, networks, and trust in social institutions. We describe the distribution of the SC stock and investment across various demographic groups. Based on a capital-accumulation model, and using linear regressions and mixture models, we test hypotheses about the drivers – expected benefits, costs, depreciation, preexisting SC, and social-capital in one’s community – and trajectories of elderly individuals’ SC investment. Implications for their life satisfaction are also assessed. Using four waves of the Korean Longitudinal Study of Ageing, we find that the elderly exhibit gradual attrition of SC, but women retain more SC on account of better mental health and higher returns on investment from lower starting points. Expected returns on SC are associated positively with individuals’ investment, while the opportunity cost of one’s time and SC depreciation are associated weakly negatively with it. Physical and human capital are complementary to SC, encouraging investment. Community-level stock and investment in SC lead to higher investment by individuals themselves."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Essays on spatial, health, and socioeconomic interactions"]}]}],"canonical_facts":{"dc:contributor":["Bera, Anil","Li, Bo","Shao, Xiaofeng","Chung, EunYi"],"dc:creator":["Lee, Jieun"],"dc:date":["2023-08","2023-07-05"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","The student, Jieun Lee, accepted the attached license on 2023-06-29 at 08:07.","The student, Jieun Lee, submitted this Dissertation for approval on 2023-06-29 at 08:07.","This Dissertation was approved for publication on 2023-07-05 at 16:53.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19474 on 2023-12-04 at 17:00:16","This is a series of studies regarding various types of spillover effects via spatial, health, and socioeconomic interactions. Chapter 1 A stochastic or non-predetermined spillover framework is very general and broadly applicable to account for the effects of economic interactions. However, in this case, a spatial weight matrix might be endogenous and thus needs to be tested since a valid and optimal spatial model depends on its endogeneity. To this end, I develop the robust score test (or equivalently Lagrange multiplier test) to determine the endogeneity of a spatial weight matrix in a “weak” spatial dynamic panel data (SDPD) model (Qu, Lee, and Yu 2017) in the sense that parameters associated with the stability condition are weakly identified from zero. First, I analytically correct the score function biases to resolve the incidental parameters problem. Second, I orthogonalize the score functions so that the score test statistic is robust to local parametric misspecification in the weakly identified parameters. A Monte Carlo simulation performs in favor of the theory and shows nice finite sample properties in terms of size and power. Finally, an empirical illustration using the Penn World Table version 7.1 describes how this testing helps researchers select the valid and optimal spatial model at their early research stage. Chapter 2 Health capital has been studied as an alternative form of human capital that affects productivity and, consequently, a country’s aggregate technology or knowledge. This paper examines the presence of knowledge spillovers triggered by health capital as a representative non-economic factor. Following the spatially augmented neoclassical growth model (Ertur and Koch 2007), countries are exposed to externalities in knowledge. Since countries observe each other’s levels of health capital and are partially aware that health capital signals a boost in one’s knowledge, they are expected to actively interact and be matched with different weights depending on the proximity of their health capital levels. The model is empirically tested with the country-level economic and health dataset provided by the Penn World Table (version 7.1) and World Bank data. The key finding is the presence of a significant positive externality in knowledge triggered by health capital. Discussions and policy implications follow. Chapter 3 Social capital (SC) is both an input and an output of individuals’ economic choices, but relatively little is known about SC investment, particularly in individuals’ old age. With a premise that SC is an individual-level concept in which individuals purposely invest, we estimate elderly individuals’ stock and investment in SC using principal component analysis of their social engagement, networks, and trust in social institutions. We describe the distribution of the SC stock and investment across various demographic groups. Based on a capital-accumulation model, and using linear regressions and mixture models, we test hypotheses about the drivers – expected benefits, costs, depreciation, preexisting SC, and social-capital in one’s community – and trajectories of elderly individuals’ SC investment. Implications for their life satisfaction are also assessed. Using four waves of the Korean Longitudinal Study of Ageing, we find that the elderly exhibit gradual attrition of SC, but women retain more SC on account of better mental health and higher returns on investment from lower starting points. Expected returns on SC are associated positively with individuals’ investment, while the opportunity cost of one’s time and SC depreciation are associated weakly negatively with it. Physical and human capital are complementary to SC, encouraging investment. Community-level stock and investment in SC lead to higher investment by individuals themselves."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/121438"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Jieun Lee"],"dc:subject":["Spatial Dynamic Panel Data Model","Stochastic/non-predetermined Trigger","Endogenous Spatial Weight Matrix","Score Test","Lagrange Multiplier Test","Incidental Parameters Problem","Local Parametric Misspecifications","Weak Identification","Health Capital","Human Capital","Knowledge Spillover","Neoclassical Growth Model","Social Capital","Networks","Baby-boomers","Ageing","Mixture Model Of Group-based Developmental Trajectories"],"dc:title":["Essays on spatial, health, and socioeconomic interactions"],"dc:type":["text"],"thesis:degree_discipline":["Economics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}