American, British economists get Nobel for study of timing

STOCKHOLM, Sweden — American Robert F. Engle and Briton Clive W.J. Granger won the Nobel Memorial Prize in Economic Sciences on Wednesday for their use of statistical methods for studying the timing behind economic developments.

Their research is used to gather data for "time series," such as chronological observations or for estimating relationships and testing hypotheses in economic theory, the Royal Swedish Academy of Sciences said.

"Such time series show the development of (gross domestic product), prices, interest rates, stock prices, etc.," the citation said.

Their findings are important because on financial markets, random fluctuations and volatility can affect share prices and value, along with other financial instruments.

Engle is on the faculty of New York University and Granger retired June 30 from the University of California, San Diego, where Engle had previously worked. They will share the prize worth 10 million kronor — about $1.3 million.

Engle told The Associated Press he was surprised by the award, but grateful.

"It's the treat of a lifetime," he said from Annecy, France, where he is on sabbatical. "I'm getting e-mails and messages from friends all over the world."

He said is work is a statistical approach to measuring volatility.

"That's why it's so interesting in financial applications because volatility is such a fundamental concept," he said. "It's important for measuring risk, for valuing derivatives and other financial instruments."

Granger is on sabbatical in New Zealand and was not immediately available for comment.

Engle is the fourth consecutive American to receive the award since 2000.

Peter Englund, a banking and insurance professor at the Stockholm Institute for Financial Research, said their research has helped experts estimate volatility.

"This has most of its applications in financial markets, for instance how the volatility of stock returns and investment returns in general vary over time," he said. "Granger has developed methods that help us model variables that follow trends over time and in particular to estimate relationships between such variables. One example would be exchange rates and relative price levels."