期刊名称：Federal Reserve Bank of St. Louis - Regional Economist
出版年度：2016
出版社：Federal Reserve Bank of St. Louis
摘要：A : Statistical analysis has evolved. In the past, it was focused on one variable measured across people or one variable measured across time. But with the advent of superfast computers, researchers and analysts can jointly model a large number of variables, each with a large number of observations across time. That is "big data." Although being able to use big data has benefits, such as improving the accuracy of forecasts, collecting the data can be extremely time- consuming. To that end, my co-author, Serena Ng of Columbia University, and I (along with tremendous assistance from staff at the St. Louis Fed's data desk) created FRED-MD, a monthly database of over 130 macro- economic time series that cover categories such as output and income, the labor market and prices. The data series are similar to the ones used by James Stock of Harvard and Mark Watson of Princeton, who created a macroeconomic data set that has become the benchmark for a lot of what people do in economics when they are working with big data. With Stock and Watson's choice of data as a guide, we used series that are available in FRED (Federal Reserve Economic Data), the St. Louis Fed's main economic database. Now, rather than having thousands of economists separately put together their own data set, they can simply download a spreadsheet from our website
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