Paul D. McNelisBendheim Chair, Professor of Economics and Financial Policy
Finance and Economics Joined Fordham: 2005 General Information 1790 Broadway, 13th Floor New York, NY 10019 Email: mcnelis@fordham.edu Website: http://www.bnet.fordham.edu/mcnelis/default.htm |
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Paul McNelis holds the Robert Bendheim Chair in Economic and Financial Policy in the Department of Finance, Graduate School of Business Administration, Fordham University, Lincoln Center campus. McNelis was previously a Professor of Economics at Georgetown, joining the faculty in 1977 as an Assistant Professor. He was born in Hazleton, Pa., where his father was an official of the United Mine Workers and his mother worked for the State Unemployment office. After completing his theological studies McNelis was ordained as a Catholic priest for the Maryland Province of the Society of Jesus on June 4, 1977. McNelis has worked with various international development organizations in Washington as well as several central banks, such as the Central Bank of Ireland, the Reserve Bank of Australia, the Reserve Bank of New Zealand, the Bank of Indonesia, the Hong Kong Monetary Authority, and the Bank of Japan. He was also a visiting professor at Trinity College, Dublin in 1986-87, the first Philips visiting professor at the Vargas Foundation in Sao Paulo, Brazil during the 1994-95 academic year, and the Gasson Professor of Economics at Boston College during the 2001-02 academic year. He has taught in multiple languages, offering short courses on Neural Networks and Finance in Portuguese in São Paulo and Brasília, Brazil, and in Spanish in Barcelona, Léon, and Santiago, Chile. His writings are in the field of Computational Macroeconomics, concentrating on problems of adjustment and financial liberalization in Latin America and Asia. His current research is on applications of neural networks and genetic algorithms for predicting exchange rate and asset-price instabilities, for assessing the effects of alternative monetary aggregates on inflation and interest rates in the short run, for evaluating credit risks in emerging markets, and solving real business cycle models. |