Information, Misallocation and Aggregate Productivity
Hugo Hopenhayn and
No 20340, NBER Working Papers from National Bureau of Economic Research, Inc
We propose a theory linking imperfect information to resource misallocation and hence to aggregate productivity and output. In our setup, firms look to a variety of noisy information sources when making input decisions. We devise a novel empirical strategy that uses a combination of firm-level production and stock market data to pin down the information structure in the economy. Even when only capital is chosen under imperfect information, applying this methodology to data from the US, China, and India reveals substantial losses in productivity and output due to the informational friction. Our estimates for these losses range from 7-10% for productivity and 10-14% for output in China and India, and are smaller, though still significant, in the US. Losses are substantially higher when labor decisions are also made under imperfect information. We find that firms turn primarily to internal sources for information; learning from financial markets contributes little, even in the US.
JEL-codes: E44 O11 O16 O47 (search for similar items in EconPapers)
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Published as Joel M. David & Hugo A. Hopenhayn & Venky Venkateswaran, 2016. "Information, Misallocation, and Aggregate Productivity," The Quarterly Journal of Economics, vol 131(2), pages 943-1005.
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Journal Article: Information, Misallocation, and Aggregate Productivity (2016)
Working Paper: Information, Misallocation and Aggregate Productivity (2014)
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