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THE GOODYEAR TIRE & RUBBER COMPANY: interest expense

Interest expense for THE GOODYEAR TIRE & RUBBER COMPANY. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All THE GOODYEAR TIRE & RUBBER COMPANY financial histories

What this measure means

Borrowing costs recognized as interest expense. This is distinct from cash interest paid and may not include every capitalized borrowing cost.

Exact concept: us-gaap:InterestExpense. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2008-01-01 to 2024-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Interest expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2024-01-012024-12-31522,000,000USD2025-02-1410-K · 0000950170-25-020763
2023-01-012023-12-31532,000,000USD2025-02-1410-K · 0000950170-25-020763
2022-01-012022-12-31451,000,000USD2025-02-1410-K · 0000950170-25-020763
2021-01-012021-12-31387,000,000USD2024-02-1310-K · 0000950170-24-014240
2020-01-012020-12-31324,000,000USD2023-02-1310-K · 0000950170-23-002558
2019-01-012019-12-31340,000,000USD2022-02-1410-K · 0000950170-22-001201
2018-01-012018-12-31321,000,000USD2021-02-0910-K · 0001564590-21-004857
2017-01-012017-12-31335,000,000USD2020-02-1110-K · 0000950123-20-001393
2016-01-012016-12-31372,000,000USD2019-02-0810-K · 0000950123-19-000989
2015-01-012015-12-31438,000,000USD2018-02-0810-K · 0000950123-18-001052
2014-01-012014-12-31444,000,000USD2017-02-0810-K · 0001564590-17-001142
2013-01-012013-12-31392,000,000USD2016-02-0910-K · 0000950123-16-013733
2012-01-012012-12-31357,000,000USD2015-02-1710-K · 0000950123-15-002527
2011-01-012011-12-31330,000,000USD2014-02-1310-K · 0000950123-14-002054
2010-12-312011-12-31330,000,000USD2013-02-1210-K · 0000950123-13-000902
2010-01-012010-12-31316,000,000USD2011-02-1010-K · 0000950123-11-011714
2009-12-312010-12-31316,000,000USD2013-02-1210-K · 0000950123-13-000902
2009-01-012009-12-31311,000,000USD2011-02-1010-K · 0000950123-11-011714
2008-12-312009-12-31311,000,000USD2012-02-1410-K · 0000950123-12-002512
2008-01-012008-12-31320,000,000USD2011-02-1010-K · 0000950123-11-011714

Related financial histories

Inspect the source

Entity
THE GOODYEAR TIRE & RUBBER COMPANY / CIK 0000042582
Captured
2026-09-19T14:47:30.957Z
SEC response SHA-256
6bca54fff4017cd1c4be443218963c4c9c1341a32bbcaa52b72f6a0f546d29b6

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000042582.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))