The purpose of this paper is to propose and evaluate a new matching sample comparison method, the industry size peer matching method.
Based on archival financial data from Compustat and econometric methods, the paper first validates that such a method will result in firms being divided into more homogenous groups, making peer‐performance comparison more meaningful. Then it compares this new peer matching method with previous methods through two resource‐based related studies in the IT valuation context.
The results show that the industry size matching method is a better method because: it is theoretically grounded, addressing industry, size, and random shock effects and, at the same time, avoids the selection bias caused by using a single firm as benchmark; and empirically such a technique results in more homogeneous groups and can explain more firm‐level returns than the industry‐only classification.
Matched sample comparison group analysis is widely used in both academy and industry. The paper's theoretically grounds and empirically validated matching sample comparison method provides researchers and practitioners with a tool for their future research, performance evaluation, earning management detection, or compensation contract design, when selecting the right peers is called for.
