Employing a Data Envelopment Analysis (DEA) approach, we investigate the technological progress, efficiency, and productivity of the US securities industry between 1980 and 2000. Our results indicate that the US securities industry in general is less efficient than the existing technology allows. The relative productivity of the US securities industry in general declined. The failure of most firms to catch up with the production frontier pushed forward by a few large investment banks is the major reason behind the declines of relative productivity. Smaller regional firms, due to their inability to respond to technological innovation, experienced especially large decreases in both efficiency and productivity.
All financial transactions in the US are essentially conducted by three industries: banking, securities, and insurance. The securities industry performs key services such as investment banking, brokerage activity, corporate strategy development, and portfolio management. With annual global revenue reaching $450 billion (see, e.g., Securities Industry Association (SIA) Research Report, Vol. II, No. 6), the US securities industry plays a vital part in providing financial services both in the United States and abroad.
However, while there has been a critical stream of studies that examines the efficiency performance of the banking industry (e.g., Alam, 2001 and Wheelock and Wilson, 1999; see Berger and Humphrey, 1997 for an excellent review of 130 studies of efficiency performance of financial institutions), there is virtually no academic study that examines the securities industry in spite of its magnitude and importance. The main reason for the lack of research in this industry is that, unlike other financial industries, such as banking, regulators do not collect and make publicly available the type of information necessary to analyze the industry.
To address the gap, this study, in an exploratory nature, examines the US securities industry in a dynamic setting. Measuring productivity change can employ either parametric or non-parametric methods. Parametric methods employ stochastic models that necessitate a large sample size to make a reliable estimation. The non-parametric approach of data envelopment analysis (DEA) is less data demanding. It works well with small sample size and does not require knowledge of the proper functional forms (Grifell-Tatje and Lovell, 1997 and Wheelock and Wilson, 1999). In this study, we adopt DEA to measure the performance of US securities firms and decompose the Malmquist productivity index into its mutually exclusive and exhaustive components. Our results indicate that the US securities industry in general is quite inefficient with respect to the leading firms. The relative productivity of the US securities industry in general declined during the period of study. Our study indicates that in a world of technological innovation, the differential ability of different firms to respond to changes has enormous implications. The failure of most firms to catch up with the production frontier pushed forward by a few large investment banks is the major reason behind the declines in relative productivity. Smaller regional firms, due to their inability to respond to changing technology, experienced especially large decreases in both efficiency and productivity.
The contributions of this paper are as follows: First, this study focuses on efficiency changes and productivity in the US securities industry; our quarterly data cover the period from the first quarter of 1980 to the last quarter of 2000, resulting in an unprecedented long chain of ex post performance indices. Second, our study is the first to employ a DEA-type Malmquist index to examine managerial efficiency and total factor productivity change in the US securities industry. Third, we identify the driving force behind these productivity changes by decomposing total factor productivity change into its exclusive and exhaustive components–change in efficiency (catching-up or falling behind) and change in technology (innovation or shock).
The paper is structured as follows: Following a review of the securities industry in Section 2, we describe the methodology in Section 3. In Section 4, we present the data and analyze the managerial efficiency and productivity change of US broker–dealer firms. Section 5 concludes.
Employing a Data Envelopment Analysis approach, we investigate the technological progress, efficiency, and productivity of the US securities industry between 1980 and 2000. Our results indicate that the US securities industry in general is quite cross-sectionally inefficient. The relative productivity of the US securities industry in general declined. The failure of most firms to catch up with the production frontier pushed forward by a few large investment banks is the major reason behind the declines in relative productivity. Smaller regional firms, due to their inability to respond to technological innovation, experienced especially large decreases in both efficiency and productivity.
The patterns of productivity change we find are consistent with that of the banking industry in a time of rapid change (Wheelock and Wilson, 1999). In response to new technology and opportunities, a few pioneering firms such as large investment banks may, due to their size and resources, adapt quickly while others respond slowly and fall behind.
