Within the framework of industry-specific analysis, there are two basic methodological approaches that can be employed: large-n analysis (statistical examination of a large number of cases) or small-n analysis (indepth studies of a small number of cases). While possible in the abstract, large-n analysis is not an especially good candidate for addressing the research agenda pursued in this book. First, the number of well-recorded case studies involving individual Chinese industries is quite small at present. Consequently, large-n analysis would require primary data collection for many industries. While basic information about many industries is supplied in national, provincial, and ministerial yearbooks, the available data varies widely on several counts: degree of detail, consistency of reporting practices, and the number of possible sources. While data on China's economy has been improving steadily, information remains incomplete in one respect or another for many industries. This was especially true for the 1980s, when reports on Chinese industries were still often superficial, haphazardly documented from year to year, and nearly impossible to verify even by the most rudimentary methods (e.g., comparing different sources). Simply put, there is not enough wellrecorded data about a sufficient number of industries in order to conduct large-n analysis consistent with my research agenda.
Second, it can be argued that case-study analysis is simply better-suited for the task at hand. Even if the limitations of large-n analysis did not exist for the study of Chinese industries, small-n analysis would still provide greater opportunity to trace the process by which independent variables affect dependent variables. Put another way, the decisive evidence necessary to establish the causal relationship between degrees of