{"id":4536,"date":"2025-10-31T09:33:15","date_gmt":"2025-10-31T13:33:15","guid":{"rendered":"https:\/\/oge.mit.edu\/msrp\/?post_type=profiles&p=4536"},"modified":"2025-12-09T12:03:03","modified_gmt":"2025-12-09T17:03:03","slug":"han-minh-pham","status":"publish","type":"profiles","link":"https:\/\/oge.mit.edu\/msrp\/profiles\/han-minh-pham\/","title":{"rendered":"Han Minh Pham"},"content":{"rendered":"
\n
\"\"<\/figure>\n<\/div>\n\n\n
\n

MIT Department:<\/strong> Political Science
Faculty Mentor<\/strong>: Prof. F. Daniel Hidalgo
Research Supervisor:<\/strong> Becca Sealy
Undergraduate Institution:<\/strong> Political Science
Website<\/strong>:<\/p>\n<\/div><\/div>\n\n\n\n

<\/div>\n\n\n\n

Biography<\/strong><\/h4>\n\n\n\n

Hanh Minh Pham is a junior at Mount Holyoke College, majoring in Statistics and Computer Science. Their interests center around applying statistics as a tool across domains\u2013 from macroeconomics and political science to business strategy. As a researcher in the Political Methodology Lab at MIT, they work under Professor F. Daniel Hidalgo on MonteCarlo simulations to quantify the causal impact of the MBTA Communities Act (Section 3A).Previously, at Iowa State University, Hanh developed a non-parametric model for small area estimation and evaluated estimator performance using Monte Carlo simulations. Hanh worked at Viettel Group, conducting customer segmentation and implementing recommendational gorithms. Finding ways to give back to their community, Hanh serves as board members for Student Government Association (SGA), Student Conference Committee (SCC) andAssociation for Women in Mathematics (AWM) MHC Chapter. Looking ahead, they plan to pursue a PhD in statistics focusing on sampling theory, regression methods, and design of experiments. In their free time, Hanh can be found powerlifting, adding to their fountain pen collection, or listening to financial podcasts.<\/p>\n\n\n\n

Abstract<\/strong><\/h4>\n\n\n\n

MBTA Communities Act: Evaluation of Municipal Compliance with Monte Carlo Simulation<\/strong><\/p>\n\n\n\n

\n
\n
\n
\n

Hanh Minh Pham1<\/sup>, and F. Daniel Hidalgo2<\/sup><\/strong><\/p>\n\n\n\n

\n
\n

1<\/sup>Department of Mathematics and Statistics, Mount Holyoke College<\/p>\n\n\n\n

2<\/sup>Department of Political Science, Massachusetts Institute of Technology<\/p>\n\n\n\n

<\/p>\n<\/div>\n<\/div><\/div>\n<\/div><\/div>\n<\/div><\/div>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n

Massachusetts’ housing crisis has prompted state intervention through the MBTA Communities Act (Section 3A of MGL c. 40A), which requires 177 municipalities served by the MBTA to establish at least one zoning district where multi-family housing is permitted as of right. However, questions remain about whether municipalities implement these requirements in good faith or merely seek minimal compliance. This research adapts a computational approach to evaluate adopted municipal zoning policies against the universe of all possible plans that meet state requirements. Using sequential Monte Carlo simulations, we generate possible zoning plans that satisfy the Act\u2019s complex constraints and assess each on the potential for housing development. These simulated districts incorporate mandated parameters: minimum multi-family unit capacity, land area, % unit capacity & % land area in proximity to transit stations, and minimum density. Then actual zoning plans can be compared to this distribution. This research offer policymakers a framework to assess compliance with state housing mandates that give municipalities considerable discretion in implementation of land use policies.<\/p>\n","protected":false},"featured_media":4537,"template":"","profile_category":[23],"class_list":["post-4536","profiles","type-profiles","status-publish","has-post-thumbnail","hentry","profile_category-2025-interns"],"acf":[],"_links":{"self":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles\/4536","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles"}],"about":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/types\/profiles"}],"version-history":[{"count":2,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles\/4536\/revisions"}],"predecessor-version":[{"id":4843,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles\/4536\/revisions\/4843"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/media\/4537"}],"wp:attachment":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/media?parent=4536"}],"wp:term":[{"taxonomy":"profile_category","embeddable":true,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profile_category?post=4536"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}