Doctoral Programs in Finance: Academic Content and Research Productivity

Article excerpt

The research productivity of doctoral degree holders in finance has attracted interest for several years. The connection between the publication records of graduates and the academic content of the doctoral programs remains largely unexplored. An examination of this connection indicates that the academic content of doctoral programs in finance impacts the publication records of graduates. The number of courses in Continuous Time Finance, Macroeconomics, Investments, Microeconomics, and Stochastic Calculus has a positive influence on measures of research productivity. The number of courses in Financial Institutions, International Finance, and Empirical Research in Finance has a negative influence on the publication records of the graduates. The number of courses in Financial Theory, Corporate Finance, Options and Futures, and Quantitative Analysis has no significant impact on measures of research productivity. [10, 12, 122]

Academic research productivity has long been of interest. Examples of research in the area include Brown (1996) in accounting; Long, Bowers, Barnett, and White (1998) in management; Collins, Cox, and Stango (2000) in economics, and Polonsky, Juric, and Mankelow (2003) in marketing.

Henry and Burch (1974) and Klemkosky and Turtle (1977a and 1977b) were among the first to investigate the degree of institutional concentration in finance research. Since then, Chung and Cox ( 1990) have used a bibliometric approach to examine the patterns of research productivity in finance. Zivney and Berlin (1992) and Fishe (1998) investigate research standards in finance, while Borokhovich, Bricker, Brunarski, and Simkins (1995, 1998) examine differences in finance research productivity and influence across academic institutions. Chan, Chen, and Steiner (2002) analyze the relationship between research productivity in finance and labor mobility. Most recently, Griffiths and Winters (2005) examine promotion and tenure research hurdle rates for finance professors, while Cooley and Heck (2005) report evidence on the research productivity of the most prolific authors in finance.

One characteristic not investigated so far is the relation between the academic content of institutions granting doctoral degrees in finance and the research productivity of their graduates. Our examination of this question seeks to: 1 ) identify the academic content of (courses required) the different doctoral programs in finance and 2) determine what academic content may influence research productivity.

In academia, these results could be useful for directors of doctoral programs, future doctoral students, and administrators in charge of recruitment, promotion, and tenure. In industry, the results could provide valuable information to human resource managers in recruitment and selection of employees.

Business and academe are seeking innovative solutions to increasingly complex problems in investment, banking, and corporate finance. Academic institutions are called upon to provide more advanced financial tools and more useful research, not to mention graduates with more sophisticated financial expertise. In response, more than 100 universities now offer finance doctoral programs in the United States. The rising number of offerings has motivated investigators to examine the characteristics of these programs. For example, Shin and Hubbard (1988) investigate admission procedures and residency and dissertation requirements, while Chung and Cox (1990) and Cooley and Heck (2005) have analyzed the research contributions of doctoral degree holders.

To explore the impact of finance doctoral programs academic content, we first examine the coursework required by 56 doctoral programs. The coursework of practically all the programs can be categorized in three main areas: Finance, Economics, and Mathematics/ Statistics. All the programs require courses or seminars in corporate finance, investments, macroeconomics, microeconomics, econometrics, statistics, and mathematics. …