Retailing and the period leading up to the Great Recession: a model and a 25-year financial ratio analysis of US retailing

Abstract

Today, more than ever, retailers need to analyze the key solvency (liquidity) and efficiency financial ratio measures that affect how well their firms perform and to engage in long-term activities that will lead to improved results. Clearly, the recent ‘Great Recession’ has had a significant negative impact on retailers worldwide. Yet, an important question remains largely answered: Was the retail industry a major contributor to the events leading up to the economic crisis or was it an affected bystander shaken by the recession? This paper addresses the question for US retailing, the largest retail economy in the world. Although there has been considerable research on some aspects of the performance of the industry and individual firms, no prior studies exist that comprehensively examine the financial ratio performance of the totality of US retailing over time. Here, the financial performance of US retailers in 54 different sectors is analyzed for the 1982–2007 period using a model and data derived from Dun & Bradstreet's annual Industry Norms & Key Business Ratios. Results show that for many financial measures – such as the current ratio, liabilities to net worth, return on sales (profit margin), return on assets, financial leverage, and return on net worth – US retailing's financial performance has been in a steady decline for decades. The model introduced here is largely validated.

Keywords::

• ratio analysis
• retail performance
• financial ratio model
• Great Recession
• long-term trends
• tracking retail industry results
• overall averages versus trends

Notes

^2. The limitations of the D&B database are noted later in the article.

^3. Note: These measurement criteria (decision rules) represent a generalized view across all of retailing as derived from D&B reports; thus, other interpretations are possible – especially by industry sector. We have set out to provide some guidelines. They may be modified as appropriate for the particular retailing scenario.

^4. Note: In doing the data analysis, the ‘decision rules’ represent a generalized view across all of retailing as derived from the D&B reports; thus, other interpretations are possible – especially by industry sector.

^5. For return on sales (profit margin) and return on assets, the sectors' medians were used to determine good trend performance.

^6. Regression analysis with profitability indicators as dependent variables and solvency and efficiency ratios as independent variables was not appropriate here due to the anticipated high degree of multicollinearity (with some efficiency and solvency ratios correlated). Also, factor analysis of efficiency and solvency ratios did not produce a factor structure that could be properly interpreted or used for further analysis.

^7. Many thanks to the referees for their constructive comments that were addressed in strengthening both this section and the overall article.