麻豆村

A team of students from 麻豆村鈥檚 helped the (GAO) build the first known comprehensive inventory of state and local semiconductor incentives in the post-CHIPS and Science Act era. Their work follows a $50 billion federal investment to revitalize the U.S. semiconductor industry.聽

Found in most electronic devices, semiconductors serve as the 鈥渂rains鈥� for phones, cars, medical devices and computers. Master鈥檚 students Henry Albright, Shawn Lu, Ana Rowley, Isabella Veneris and Albert Yang worked with the nonpartisan GAO on a project spanning policy analysis, data engineering and spatial mapping. Their work gives federal analysts a clearer foundation for evaluating how public investments are shaping advanced manufacturing, workforce development and regional economic growth across the country.

A national question without a clear answer

The requires the GAO to assess how federal investments are unfolding over time. To do that effectively, analysts first needed a clearer understanding of the policy landscape beyond Washington, particularly the incentives states and local governments were offering alongside federal funding.

For the GAO, the challenge included both scope and lens. 鈥淲hile we鈥檝e been charged to look at the federal angle, we were also aware that there were some non-federal elements,鈥� explained聽, the GAO鈥檚 director for science, technology assessment and analytics. 鈥淩ecognizing that the states can play a really important role here, we wanted to get that perspective.鈥�

鈥淔or the GAO to have a better understanding of how the federal legislation is working, the analysts need to understand how state and local policies are impacting the industry,鈥� said Albright, a second-year student in the聽 master鈥檚 program at Heinz College.

That information exists, but not all in one place. Data related to incentives is scattered across legislation, economic development agencies and public records that vary widely by state. Some programs are highly targeted, while others are embedded in broader economic policy. Comparing approaches to understand how they interact with or are influenced by federal investment is difficult without a consolidated baseline.

The GAO asked the student team to help close that gap.

Building a foundation for federal oversight

Rather than producing a one-time report, the team focused on creating a tool the GAO could continue to use.

鈥淲hat we built was essentially a database that could serve as a baseline for the GAO,鈥� said Rowley. 鈥淚t鈥檚 a structured database that they can continue to add to and then analyze that data in different ways.鈥� The database included 133 state and local incentives across 37 states; the students coded each policy using consistent categories that allow for future analysis.

To do that, students translated dense legislative language into standardized variables. This approach allows analysts to test different questions over time, using employment data, investment patterns or other outcomes without rebuilding the dataset from scratch.

For GAO analysts, the value wasn鈥檛 just the data itself, but what it made possible. 鈥淭he final deliverable provides us a really great resource,鈥� Wright said. 鈥淚f we have questions from congressional staff down the road about state legislation, we can go to the tools the team provided rather than starting from scratch.鈥�

Faculty adviser聽Jordan Pallitto, a Heinz College adjunct professor, emphasized that the project mirrored the kind of work in which professional analysts often engage.聽

鈥淭his project sits right in Heinz College鈥檚 wheelhouse,鈥� he said. 鈥淚t鈥檚 a blend of qualitative and quantitative thinking applied to a real-world problem.鈥�

When the data complicates the story

As the team began analyzing the data, some findings challenged common assumptions. One example came from case studies they created to compare states with different incentive strategies. Arizona, for instance, attracted significant semiconductor investment despite having relatively few state-specific incentives, while other states with more targeted programs saw different results.

鈥淭he amount of money that states spend on incentives doesn鈥檛 necessarily impact the number of semiconductor facilities in their state,鈥� Albright said.聽

Rather than pointing to a single explanatory factor, the data suggested a more complex picture shaped by existing industry presence, federal investment timing, workforce capacity and historical development patterns. Importantly, the team avoided drawing causal conclusions that the data could not yet support.

鈥淭hat complexity is an example of how capstone projects help students transition from classroom theory to real-world application,鈥� Pallitto said. 鈥淭he team had to decide what mattered and whether something would actually be useful to GAO. They had to think like policy analysts.鈥�

In some cases, the students鈥� analysis revealed gaps the GAO hadn鈥檛 yet identified. 鈥淲e had a lot of unknown unknowns,鈥� said Kelsey Kennedy, senior analyst at the GAO. 鈥淭his project helped surface things that weren鈥檛 on my radar before. If I had just reviewed the database quickly, I may not have come away with those conclusions. The case studies helped pull out what mattered and why it mattered to policymakers.鈥�

Learning to work with imperfect information and uncertainty

The project required skills that went beyond technical analysis. Unlike most classroom coursework, there was no predefined dataset and no guarantee that the information they needed would be available or consistent across states.

鈥淲e had to decide what data and which variables we should include,鈥� said Yang. 鈥淭he experience helped me a lot.鈥�

Students also had to learn when to stop searching for data that simply wasn鈥檛 accessible. 鈥淲ith school assignments, you鈥檙e used to knowing there鈥檚 an answer,鈥� Albright said. 鈥淗ere, knowing when to stop researching was part of the job.鈥�

The experience reshaped how several students think about public policy analysis 鈥� particularly the need to balance rigor with practicality when working under real-world constraints.

Midway through the project, a federal government shutdown limited communication with GAO project sponsors, forcing the team to continue their work with minimal client feedback. The experience mirrored conditions analysts often face in professional settings.

鈥淚t was weird working on a project when nobody could legally respond to us,鈥� said Veneris. 鈥淏ut we still had deliverables due.鈥�

Their initiative did not go unnoticed by the project鈥檚 federal partners.

鈥淚t was incredibly impressive the amount of work the students did, especially given the government shutdown. The fact that they stayed resilient, focused and on track was really impressive,鈥� Wright said.