Data and Code for: "Consumer Credit and the Incidence of Tariffs: Evidence from the Auto Industry"

Principal Investigator(s): View help for Principal Investigator(s) Kristine Hankins, University of Kentucky; Morteza Momeni, Tennessee Tech University; David Sovich, University of Kentucky

Version: View help for Version V1

Name	File Type	Size	Last Modified
Consumer_Credit_Data			11/07/2025 07:37:AM
Texas_Data			11/08/2025 06:14:AM
AALA.dta	application/x-stata-dta	1.6 MB	07/24/2025 04:34:AM
HHI_Equifax.dta	application/x-stata-dta	14.5 KB	07/20/2025 05:55:PM
SalesData_GoodCarBadCar.dta	application/x-stata-dta	1.1 MB	07/20/2025 05:55:PM
agg_default.dta	application/x-stata-dta	2.5 KB	07/20/2025 05:55:PM
cost_of_debt.dta	application/x-stata-dta	18 KB	07/20/2025 05:55:PM
issuing_entity_table.dta	application/x-stata-dta	30.9 KB	07/20/2025 05:55:PM
make_model_linktable.dta	application/x-stata-dta	2.6 GB	07/24/2025 09:33:AM
make_parent_lender_map.csv	text/csv	970 bytes	07/20/2025 06:05:PM

Project Description

Summary: Data and code for replicating the results in "Consumer Credit and the Incidence of Tariffs: Evidence from the Auto Industry".

Paper Abstract:

"Captive finance subsidiaries create a channel for trade policy to affect consumer credit. Examining the impact of the Trump administration's metal tariffs on captive automobile lenders, we find that consumers received higher interest rates from captive lenders after the tariffs relative to unaffected non-captive lenders. Further, we document a disparate impact on low-income borrowers and in areas with less lending competition. Our results suggest that tariffs may impact not only the price of goods but also the financing terms of purchases. Thus, focusing solely on directly affected product prices may underestimate tariff pass-through significantly."

Scope of Project

Subject Terms: auto loans; new vehicles; tariff pass-through; cost pass-through; captive finance

JEL Classification:
      F13 Trade Policy; International Trade Organizations
      G23 Pension Funds; Non-bank Financial Institutions; Financial Instruments; Institutional Investors
      H22 Taxation and Subsidies: Incidence

Geographic Coverage: United States

Universe: Auto loans originated between 2017 and 2018.

New vehicle sales between 2017 and 2018.

Data Type(s): observational data

Methodology

Response Rate: The final auto loan sample consists of roughly 2 million securitized auto loans from 127 distinct asset-backed securities and 14 lenders.

The final vehicle sales sample consists of roughly 2 million new vehicles sold and registered in the state of Texas.

Sampling: The auto loan sample comes from public auto loan ABS.

The new vehicle sales sample comes from the State of Texas Department of Motor Vehicles.

Data Source: The paper uses three types of data:

1. Publicly available data.
2. Confidential vehicle sales price data from the Texas Department of Motor Vehicles.
3. Confidential consumer credit data from Equifax.

Collection Mode(s): other

Weights: Unweighted.

Unit(s) of Observation: Vehicle purchases., Auto loans.

Geographic Unit: State.

Related Publications

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Published Versions

V1 [2025-12-22]

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Dublin Core

DDI 2.5

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