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Research研究

My research asks whether market-based environmental regulation and housing policy actually deliver on their promises — and how the gains and burdens are distributed across firms, households, and communities. Two commitments run through the work: I weigh who gains and who loses as heavily as aggregate efficiency, and I bring new, large-scale evidence to bear — linking satellite remote-sensing with administrative microdata through causal-inference and machine-learning methods — to measure outcomes, from facility-level emissions to city-wide rent discounts, that conventional evaluations cannot observe. The agenda is organized around three connected pillars. 我的研究关注:市场化的环境监管与住房政策是否真正兑现了承诺,以及由此产生的收益与负担如何在企业、家庭与社区之间分配。两条主线贯穿始终:我将"谁受益、谁承担"与总体效率置于同等重要的地位;并以大规模的新证据回答这些问题——将卫星遥感与行政微观数据相结合,运用因果推断与机器学习方法,衡量传统评估难以观测的结果,从企业层面的排放到城市范围的租金折价。整个研究议程围绕三条相互关联的支柱展开。

Methods研究方法

Causal inference因果推断 Machine learning机器学习 Policy evaluation政策评估 Applied microeconometrics应用微观计量

Satellite & Spatial Data卫星与空间数据

NASA Aura ESA TROPOMI NASA OCO-2 / OCO-3 NASA Black Marble NYC Housing & Vacancy Survey纽约市住房与空置调查

Pillar 01支柱 01

Market-Based Environmental Regulation & Energy Transition市场化环境监管与能源转型

This pillar examines how incentive-based environmental regulation — rather than conventional command-and-control — influences firms' carbon emissions, air pollution, and the transition to cleaner energy.这一支柱考察基于激励的环境监管(相对于传统的"命令—控制"式监管)如何影响企业的碳排放、空气污染,以及向清洁能源的转型。

A central question is whether market-based instruments — emissions trading and tradable-performance-standard programs — actually deliver the reductions they promise, and how their burdens fall across firms and the communities around them. I use satellite remote-sensing to measure facility-level emissions that sparse or self-reported data often miss, and extend the same lens to carbon pricing in other jurisdictions and to the environmental spillovers of cross-border energy investment.一个核心问题是:诸如排放权交易与"可交易绩效标准"等市场化工具,是否真正实现了其承诺的减排,以及其负担如何在企业与周边社区之间分布。我借助卫星遥感来衡量稀疏或自报数据往往遗漏的企业层面排放,并将同样的视角延伸至其他司法辖区的碳定价,以及跨境能源投资的环境溢出效应。

A parallel strand studies the clean-energy transition — the pace of energy-efficiency improvements and learning-by-doing in renewable power — always pairing the question of aggregate efficiency with attention to who ultimately benefits.与之并行的一条线索研究清洁能源转型——能效改善的速度,以及可再生能源发电中的"干中学"效应——并始终将总体效率的问题与"谁最终受益"的关切结合在一起。

Pillar 02支柱 02

Housing Affordability, Rent Regulation & Inequality住房可负担性、租金管制与不平等

This pillar investigates the distributional consequences of housing regulation — asking not just whether policies such as rent stabilization improve affordability, but for whom, and tracing how their benefits and costs are distributed across income, race, immigration status, and age.这一支柱研究住房监管的分配后果——不仅追问租金稳定等政策是否改善了住房可负担性,更追问"为谁改善",并梳理其收益与成本如何在收入、种族、移民身份与年龄之间分配。

Drawing on rich, long-run administrative microdata and machine-learning methods, I ask who actually gains from rent regulation, whether such policies are progressive, and how they interact with racial and demographic inequality — measuring the size and incidence of the discounts these policies create.依托丰富的长期行政微观数据与机器学习方法,我考察究竟谁真正从租金管制中受益、这类政策是否具有累进性,以及它们如何与种族与人口结构上的不平等相互作用——并衡量这些政策所产生折扣的规模与归宿。

Related questions extend the framework to particular groups and behaviours — how affordability and compliance differ across renters, how faithfully landlords adhere to regulation, how the supply of affordable housing filters over time, and how short-term-rental rules reshape local housing markets and neighbourhood quality of life. Although much of this work is grounded in the United States, the questions it answers apply directly to fast-growing cities elsewhere.相关问题将这一框架延伸至特定人群与行为——可负担性与合规状况在不同租户之间如何差异、业主对监管的遵守程度、可负担住房供给如何随时间"过滤",以及短期租赁规则如何重塑本地住房市场与社区生活质量。尽管这些工作多以美国为背景,但其所回答的问题同样直接适用于其他快速城市化地区。

Pillar 03支柱 03

Climate Change, Adaptation & Sustainable Urban Development气候变化、适应与城市可持续发展

Building on my expertise with satellite data and causal inference, I study how climate change and environmental shocks affect local housing markets and vulnerable populations. A new project examines how climate change interacts with historical housing discrimination — such as redlining — to shape household adaptation outcomes. A further project studies how urban greenery and forestation reshape local housing and labour markets.依托在卫星数据与因果推断方面的专长,我研究气候变化与环境冲击如何影响本地住房市场与脆弱人群。一个新项目考察气候变化如何与历史性的住房歧视(如"红线政策")交互,塑造家庭的适应结果。另一个项目则研究城市绿化与植树造林如何重塑本地住房与劳动力市场。

I combine environmental-policy evaluation with urban economic analysis to learn when market-based regulations and housing policies achieve both efficiency and equity — and when they fall short, and for whom. 我将环境政策评估与城市经济分析相结合,以厘清市场化监管与住房政策何时能够同时实现效率与公平,又在何处、对哪些群体未能奏效。