Dr. Howell's research in this area examines how firms, industries, and economies generate, absorb, and benefit from innovation and technological change. His work traces how policy environments, market structure, and the geography of knowledge shape firm-level innovation outcomes, from early-stage R&D investment through commercialization, productivity growth, and international competitiveness. A central focus is how structural economic reforms, particularly the transition from state-directed to market-oriented enterprise systems and the liberalization of foreign direct investment, reshape the conditions under which indigenous innovation occurs and knowledge spillovers diffuse across firms and regions. He also examines how different policy instruments, including tax reform, industrial cluster policy, and R&D subsidies, produce heterogeneous effects depending on firm type, ownership structure, absorptive capacity, and technological position. His most recent work in this area extends the innovation agenda to the economics of artificial intelligence, developing computational tools to measure how AI reshapes the task and skill content of inventive activity, and examining the distributional consequences of AI-driven technological change for workers, firms, and local labor markets.

Dr. Howell's research in this area examines how labor markets and social institutions distribute economic opportunities and hardships unevenly across geography, ethnicity, and socioeconomic groups. Grounded in nearly two decades of fieldwork and empirical research in China, this work began by documenting the nature and scale of ethnic and spatial disparities in wages, self-employment, labor mobility, and access to capital, establishing foundational evidence on dimensions of inequality that prior research had largely overlooked. It then turned to policy evaluation, asking whether and how targeted interventions narrow those gaps and improve household welfare. His research spans minimum wages, cash transfer programs, rural infrastructure investment, energy policy, and social protection programs, consistently attending to distributional effects across household type, ethnic group, and geographic setting. A recurring insight across this body of work is that the welfare consequences of both market forces and policy interventions are deeply uneven, and that the institutional conditions shaping who benefits, including land rights, labor market access, mobility, and local governance capacity, matter as much as policy design itself.

Dr. Howell's research in this area examines how places grow, stagnate, and respond to economic and environmental disruption, and how policy shapes those trajectories. His work on place-based policy traces the effects of economic development zones, infrastructure investment, and industrial policy on regional productivity, firm competitiveness, and community welfare, using natural experiments and quasi-experimental designs to separate policy effects from underlying geographic advantages. A parallel strand examines environmental and climate policy, studying how conservation programs, carbon pricing, and environmental shocks affect household welfare, land use, and regional development trajectories, with particular attention to how costs and benefits are distributed across ethnic groups and geographic settings. His most recent work in this area applies multimodal large language models and geospatial AI to urban measurement challenges, demonstrating that frontier computational tools can recover neighborhood-level poverty and document the persistent spatial legacy of historical policy decisions in settings where traditional data sources are absent, delayed, or prohibitively expensive. Together, this research program asks how places and communities can develop sustainably and equitably in the face of policy change, environmental pressure, and technological disruption.

entitymatch is a Python package for semantic entity matching with geographic blocking and LLM validation. It links entity records across messy datasets using sentence-transformer embeddings, two-tier geographic blocking, and optional LLM-based validation. Designed for researchers and analysts who need to match organizations, firms, or institutions across administrative datasets where names are inconsistent, misspelled, or abbreviated, the package supports semantic similarity matching that goes beyond exact string comparison, with configurable geographic blocking to reduce the search space and improve precision at scale.

PyPI  |  GitHub

The capstone course Dr. Howell teaches, PAF 516 | Community Analytics (Course Website), trains students to build fully open-source community analytics dashboards for any location in the United States. Students construct their own composite indices for economic hardship, housing vulnerability, environmental risk, and other policy-relevant dimensions, integrating census data, spatial analysis, and interactive visualizations into stakeholder-ready tools deployed via GitHub Pages. The interactive dashboard below demonstrates the final product.

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Born in Los Angeles, Anthony Howell's early life was shaped by poverty, homelessness, foster care, and the effects of parental incarceration and early loss. After living across multiple households in Los Angeles, Jersey City, and Detroit, he moved to Lansing and was adopted at age 10 by working-class relatives. He began working at 14, balancing school with part-time jobs and spending summers at a GM assembly plant. As factories in the region closed, he witnessed firsthand the consequences of regional economic decline, including unemployment, neighborhood disinvestment, crime, and social instability. These early experiences helped shape his long-term interest in opportunity, inequality, local economic development, and the role of public policy.

Anthony began his higher education at a local community college before transferring to Michigan State University. As a first-generation college student navigating an unfamiliar academic world, he struggled early and finished his freshman year with a 2.1 GPA. Over time, mentors, a strong peer community, and a growing sense of purpose helped transform his trajectory. By graduation, his GPA had risen to 3.5. Alongside his studies, he worked in community-based settings including a soup kitchen and the Refugee Development Center in Lansing, experiences that deepened his commitment to public service and his interest in how institutions shape opportunity for vulnerable populations. He later completed a Master's degree in GIScience at Michigan State, where he built a strong foundation in spatial analysis and quantitative research.

Anthony went on to earn a PhD in Geography from UCLA, where he received the Chancellor's Prize, an award given to the top 1% of incoming doctoral students. During his doctoral training, he also completed a Master's degree in Statistics and advanced coursework in quantitative methods in political science, strengthening his expertise in causal inference, econometrics, and computational methods. His language study and China-based fieldwork were supported by nationally competitive fellowships, including FLAS and the U.S. Department of State's Critical Language Scholarship, which provided intensive Mandarin training and helped lay the foundation for a long-term research program on China.

As an undergraduate and graduate student, Anthony pursued various grant and scholarship opportunities to intern and volunteer abroad. These experiences included working at the Western Development Commission, an economic development council in the west of Ireland, volunteering with NGOs in low-income communities in Mexico, and conducting early research visits to China. These international engagements broadened his interest in community development, comparative policy, and the study of how institutions shape economic opportunity across different settings.

Anthony began research in China as an undergraduate at Michigan State, when he received funding to visit the Chinese Academy of Sciences in Beijing and designed his first survey at a migrant skills-training facility. For his Master's thesis, he later carried out extensive fieldwork in Xinjiang, where he developed survey instruments, trained local enumerators, and implemented a mixed-methods sampling design across urban service establishments in Urumqi and Kashgar. This project collected nearly 2,000 surveys from Han, Hui, and Uyghur respondents and contributed some of the earliest evidence on ethnic disparities in wages, self-employment, and mobility in China.

Anthony later returned to China as a Fulbright Scholar to conduct dissertation research on industrial policy, innovation, and entrepreneurship. During this period, he gained access to proprietary firm-level data and developed original measures of local industrial policy by systematically collecting information from Chinese municipal sources. He also participated in the China Household Ethnic Survey project, a major collaborative effort involving Chinese and international researchers to collect and analyze nationally significant data on ethnic minority populations in China.

From 2014 to 2019, Anthony served as Assistant and Associate Professor at Peking University. He was awarded the Early Scientist Award from China's National Natural Science Foundation (equivalent to the Early CAREER Award from the U.S. NSF) to study China's innovation, technological change, and entrepreneurship ecosystems. During this time, he expanded a research agenda on industrial policy, firm innovation, productivity, and internationalization, while building long-term collaborations across China's research universities and policy institutions. Capitalizing on PKU's proximity to Zhongguancun, often referred to as China's "Silicon Valley," Anthony immersed himself in Beijing's tech ecosystem. Through his position at PKU, he secured co-working space in Garage Cafe, a publicly-funded incubator on Innovation Way, witnessing firsthand the transformation of the area into a policy-induced innovation hub. He also served in an advisory role for a student-led start-up company, and collaborated with partners at the Ministry of Science and Technology on international projects that fostered exchanges between start-ups in Silicon Valley and Zhongguancun.