Using Panel Data Analysis to Estimate DEA Confidence Intervals Adjusted for the Environment
This paper illustrates three concepts new to the data envelopment analysis (DEA) literature, and applies them to data from Canadian paratransit agencies. First, it predicts valid confidence intervals and trends for each agency's true efficiency. Second, it uses panel data analysis methodology, a set of statistical procedures that are more likely to produce valid estimates than those commonly used in DEA studies. Third, it uses a new method of identifying and adjusting for environmental effects that has more power than conventional procedures.
R&D budget has been recently increased rapidly by our government's direction under the recognition that strong R&D policy lead to the wealth of the nation. The methodologies for effective evaluation have received great attention was increased. We had established the laws to evaluate and man age the performance of national R&D programs in 2005. The previous and current R&D evaluation programs were conducted in the middle of progress. Recently, the importance of evaluation of follow up control conducted after finishing the program in national level is increasing. The purposes of this study are to evaluate national R&D programs in terms of economic impacts and to develop the efficient methodologies by considering follow-up evaluation. This study will be effective to demonstrate the efficiency of the methodologies based on follow-up evaluation and the necessity of the evaluation of R&D programs after wrapping the programs up.