INTERVIEW-BOJ looks to big data for clues on pandemic-driven economic changes
By Leika Kihara and Takahiko Wada
TOKYO, July 16 (Reuters) - The coronavirus pandemic may have caused structural changes in Japan's economy and the way it affects inflation, requiring the Bank of Japan to tap more deeply into big data in making policy decisions, the central bank's top economist said on Thursday.
High-frequency and other unconventional data offer crucial, real-time information on rapid changes that a big shock like COVID-19 causes in the economy, said Kazushige Kamiyama, who heads the BOJ's research and statistics department.
While official consumer inflation data will remain the BOJ's key price gauge, the bank will look more carefully at a broader range of high-frequency and non-traditional data as the pandemic brings unpredictable shifts in the economy, he said.
"Extremely big shocks like COVID-19 could trigger structural changes in the economy," Kamiyama told Reuters.
"We need to avoid being too simplistic, and try to look at the economy with a more sophisticated approach," he said.
The world's third-largest economy is bracing for its worst postwar recession, hurt by coronavirus lockdown measures at home and overseas that have upended supply chains, kept businesses shut and depressed consumer spending.
Major central banks are increasingly tapping non-traditional data, such as credit card spending, foot and vehicle traffic, smartphone usage and even air pollution levels to capture real-time changes in their economies, in contrast to government data that come with months of delay.
The BOJ is seeking to catch up. Last year, Kamiyama set up a task force within his department to better incorporate findings from high-frequency data into the bank's economic analysis.
For example, global movements of car-loaded cargo ships and movement of people around factories offer clues on how much the pandemic hit Japanese exports and output, he said.
"In times of shock, uncertainty over the state of the economy and its outlook heightens. It's like driving without your lights on," Kamiyama said.
"That's when non-traditional data that gives us quick information, including high-frequency data, become really valuable," he said.
Big data may also help policymakers better understand how the pandemic could affect inflation and companies' price-setting behaviour, Kamiyama said.
"The pandemic has caused not just a slump in demand but changes in the supply side" such as social distancing policies that force some retailers to raise prices to make up for higher costs, he said.
That means COVID-19 may not necessarily be deflationary, Kamiyama said.
"There's uncertainty on how the balance of demand and supply could change when economic activity picks up," he said. "We need to use various data to check whether our hypothesis is valid."
(Reporting by Leika Kihara; Editing by Kim Coghill)
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