Alfredo Sosa
Economist specializing in trade policy, supply chains, and applied econometrics
https://asosa513.github.io/alfredo-sosa-economics/
🌐 https://alfredo-sosa-economics.com/
https://www.linkedin.com/in/alfredososa513/
✉️ alfredosos@gmail.com ✉️ alfredosos@goutlook.com
📍 Ann Arbor, Michigan
About
Economist with more than 20 years of experience applying econometrics, data science, and business analytics to real-world economic and operational problems. My work focuses on international trade policy, supply chains, and industrial organization, with particular emphasis on the effects of tariffs on the U.S. automotive and commercial vehicle industries.
Current research examines how tariff shocks propagate through global production networks, using detailed trade data, industrial production indicators, and supply-chain measures to analyze impacts on prices, output, and cost structures.
This website presents a portfolio of research papers, data products, and applied analytics tools focused on the economic effects of trade policy and supply chain dynamics.
Current Research
1. The Impact of Section 301 Tariffs on U.S. Vehicle Production and Sales: Evidence from HS6-Level Exposure and Dynamic Difference-in-Differences
This paper estimates the causal effects of the 2018–2019 Section 301 tariffs on U.S. commercial vehicle production using a difference-in-differences and event-study framework. The analysis combines trade data, industrial production indicators, and tariff exposure measures to quantify how tariff increases affected production, input costs, and supply chain dynamics. SSRN Link
2. The 2025–2026 Tariff Expansions and the U.S. Vehicle Supply Chain (Policy Documentation and Data Infrastructure)
This paper documents the 2025–2026 expansion of U.S. tariff policy and constructs a product-level dataset measuring tariff exposure across the vehicle supply chain. The project integrates policy data from Federal Register notices with trade and supply-chain information and presents stylized evidence on production, prices, employment, and logistics costs. SSRN Link
3. Firm-Level Evidence on Tariff Exposure and U.S. Manufacturing Outcomes (Research Agenda)
This project will extend the analysis to the firm level by constructing detailed firm-level datasets to examine how tariff exposure affects production, sales, and performance across U.S. manufacturers. Leveraging documented policy variation, the study will implement causal inference strategies, including difference-in-differences designs, to estimate the effects of tariffs within industrial supply chains.
Applied Analytics Projects
Interactive Supply Chain Dashboards
Developed interactive dashboards analyzing trade flows, tariff exposure, production indicators, and supply chain dynamics in the U.S. vehicle sector. These tools integrate data from USITC, FRED, and internal processing pipelines to support real-time analysis of policy and market conditions.
Machine Learning Applications
Developed machine learning models to support forecasting and policy analysis in supply chains and logistics. Applications include demand forecasting, pricing dynamics, and counterfactual analysis of tariff exposure and input costs.