More Data Can Mean Less Guessing About the Economy
By STEVE LOHR
DAVID TABOR, 37 and a civil engineer, runs an eight-person home-inspection company in Hurricane, W.Va.
Other than their owners, most small businesses have no employees. His is one of the 4.3 million that do have them, and that employ fewer than 20 people each. And while these companies collectively produce roughly 15 percent of the nation’s economic output, their activities aren’t captured by the official numbers in a timely or detailed way.
Yet this measurement shortfall in the small-business sector, and a series of other information gaps in the economy, may be overcome by what experts say is an emerging data revolution — Big Data, in the current catchphrase. The ever-expanding universe of digital signals of behavior, from browsing and buying on the Web to cellphone location data, is grist for potential breakthroughs in economic measurement. It could produce more accurate forecasting and more informed policy-making — more science and less guesswork.
“We’re seeing the emergence of new sets of data and knowledge that we’ve never had before,” says James Poterba, president of the National Bureau of Economic Research and a professor at the Massachusetts Institute of Technology. “It’s a real opportunity for policy makers.”
In the small-business case, Mr. Tabor’s company, American Home Inspectors and Engineering Assessments Inc., is one of more than 200,000 that have allowed Intuit, the software maker, to gather data on their use of Intuit’s online payroll or online accounting products for research on employment and sales trends. The data are stripped of identifying information, and, in asking permission, Intuit also emphasizes that it uses the data to improve its products.
Mr. Tabor said he had no qualms about contributing his anonymized data. “I’m happy they use the data for research and to make their services better,” he says.
Intuit began its research in 2004 on small businesses and has expanded its scope, including many more companies and becoming more fine-grained in its data tracking as it has added products, services and customers.
Researchers at the Bureau of Economic Analysis, the government’s statistical scorekeeper of economic activity, are now experimenting with the Intuit data, seeking to tap it to improve the official estimates.
“The promise of new data sources, like Intuit and others, is more accurate, more timely and cheaper data for monitoring the economy,” says Steve Landefeld, director of the bureau. “That could be a really big step forward.”
National income accounting emerged in the Great Depression, in an effort to bridge the economic information gap of its day. In June 1930, based on scattered reports available to him, President Herbert Hoover declared, “The Depression is over,” when in reality conditions were quickly worsening.
The main tool for government statistics remains telephone and in-person surveys of households and businesses — surveys that are costly and time-consuming.
Tracking behavior online can pull in far more data, more quickly — so that governments should be able to see signs of inflation, deflation and employment trends sooner and adjust policy faster.
For example, the Intuit monthly employment data, based on online monitoring, is current. That is eight months to a year ahead of the government’s best statistical look at the health of small business, which is culled from quarterly surveys, state unemployment records and tax returns. The monthly Intuit survey data have also proved accurate, almost mirroring the government results when they are finally reported, according to Susan Woodward, a consulting economist for Intuit.
“Whatever is happening, it is better to know sooner,” Ms. Woodward says.
Yet whether more data, collected faster, will improve economic forecasting is uncertain. So far, the results are mixed. An encouraging study, begun in 2009 and repeatedly updated, has used Google searches to predict home sales and prices three months into the future. In the study, the higher the frequency of search terms like “house prices,” “real estate agent” and “mortgage rates,” the more likely the national housing market would heat up.
The results of the study, “The Future of Prediction,” by Lynn Wu, an assistant professor at the Wharton School of the University of Pennsylvania, and Erik Brynjolfsson, a professor at the M.I.T. Sloan School of Management, have held up over time. In the most recent version, their model using search data predicted future home sales 24 percent more accurately than the forecasts by experts from the National Association of Realtors.
But another major project using Google search terms points to the limits of such techniques: Google Flu Trends uses the same methods as Big Data-style economic prediction, although it focuses on public health.
The service monitors flu-related search terms and seeks to predict the incidence of flu, ahead of official statistics based on doctors’ reports to the Centers for Disease Control and Prevention. In 2009, with the outbreak of H1N1 flu, Google Flu Trends was prescient.
Yet this past flu season, Google’s algorithms stumbled. As an article in the science journal Nature noted in February, Google Flu Trends estimated that nearly 11 percent of Americans were ill at the January peak — nearly double the 6 percent reported later by the C.D.C. Apparently, the Google algorithms were unable to sift out news reports and social media messages warning of a harsh flu season, which sent flu-related searches spiking.
Google is tweaking its algorithms accordingly. But experts say the episode underlines why the new technology will most likely supplement official economic statistics rather than replace them for the foreseeable future.
“The potential is extraordinarily exciting, but I worry that the expectations are way ahead of the likely reality for the next several years,” says Mr. Landefeld of the Bureau of Economic Analysis.
THE economics profession is gearing up to exploit new sources of digital data. In a recent paper, “The Data Revolution and Economic Analysis,” two Stanford economists, Liran Einav and Jonathan Levin, concluded that “there is little doubt, at least in our minds, that over the next decades ‘big data’ will change the landscape of economic policy and economic research.”
At Intuit, the small-business data portray a sector that was “hurt much more than big business by the recession and its recovery has been far worse,” says Ms. Woodward, the economic consultant. Over the last three and a half years, payroll employment for all companies has increased 6.9 percent, while small-business employment has risen far less, just 1.9 percent. Hiring among the small companies, though still sluggish, has inched ahead in the last three months.
In West Virginia, Mr. Tabor’s company did better than many, but his story echoes the national trend. He bought his home-inspection business in 2007, when times were good. But later, when the economy slowed, hours would go by without the phone ringing. “I thought, ‘Oh dear, what have I done,’ ” he recalls.
Mr. Tabor modernized the business, shifting from paper to laptops and smartphones, and expanded into doing valuations for insurance companies and serving as an engineering expert in litigation. Revenue, he said, is up 15 percent this year.
“We are going to be looking to hire, probably next year,” he says.
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