FIFO and LIFO Methods for Inventory Expensing

Inventory

Inventory refers to the short-term assets on a company’s balance sheet; example – a retail clothier’s stock of shirts, pants, etc.

FIFO

First-in, first-out accounting method, where the costs of the oldest items in inventory are used to compute the cost of goods sold (COGS) expense on a company’s income statement.

FIFO ending inventory for the balance sheet is calculated based on values of the most recent inventory goods purchased.

LIFO

Last-in, first-out accounting method, where the costs of the newest inventory items are used to compute the COGS expense on the income statement.

LIFO ending inventory for the balance sheet is calculated based on values of the first inventory goods purchased.

Average Cost

Weighted average cost method applied to a company’s purchases in determining COGS and the value of beginning and ending inventory.

COGS Expense Calculation

Beginning Inventory (BI) + Purchases = Goods Available for Sale (GAS)

GAS – Ending Inventory (EI) = COGS

COGS is used in calculating a company’s gross profit and gross profit margin (the decimal is typically converted to a percentage)

Gross Profit = Net Revenue - COGS

Gross Margin % = ((Net Revenue – COGS)/Net Revenue)*100

In some instances, the choice of LIFO or FIFO makes intuitive sense for a specific company.  A farmer’s market shop would conceptually be a FIFO business, as the oldest produce should be sold first, given that it will spoil the soonest compared to younger produce.

In reality a company’s management is usually allowed some degree of flexibility in determining its inventory accounting method.  If an analyst is comparing firms in a shared industry structure or market capitalization size, then differences in inventory accounting methods need to be reconciled through the financial statement adjustment process, so the analyst can be sure that the financial ratios for the firms are truly comparable.

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Data Science in Finance: 9-Book Bundle

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Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.