Using Path Analysis to Integrate Accounting and Non-Financial Information: The Case for Revenue Drivers of Internet Stocks

Anthony Kozberg

Chapter 130 in Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning:(In 4 Volumes), 2020, pp 4441-4472 from World Scientific Publishing Co. Pte. Ltd.

Abstract: This chapter utilizes path analysis, an approach common in behavioral and natural science literatures but relatively unseen in finance and accounting, to improve inferences drawn from a combined database of financial and non-financial information. Focusing on the revenue generating activities of internet firms, this paper extends the literature on internet valuation while addressing the potentially endogenous and multicollinear nature of the internet activity measures applied in their tests. Results suggest that both SG&A and R&D have significant explanatory power over the web activity measures, suggestive that these expenditures represent investments in product quality. Evidence from the path analysis also indicates that both accounting and non-financial measures, in particular SG&A and pageviews, are significantly associated with firm revenues. Finally, this paper suggests other areas of accounting research which could benefit from a path analysis approach.

Keywords: Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data (search for similar items in EconPapers)
JEL-codes: C01 C1 G32 (search for similar items in EconPapers)
Date: 2020
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