Information, Misallocation, and Aggregate Productivity

S-Tier
Journal: Quarterly Journal of Economics
Year: 2016
Volume: 131
Issue: 2
Pages: 943-1005

Authors (3)

Joel M. David (not in RePEc) Hugo A. Hopenhayn (not in RePEc) Venky Venkateswaran (New York University (NYU))

Score contribution per author:

2.681 = (α=2.01 / 3 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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 United States, China, and India reveals substantial losses in productivity and output due to the informational friction. Our estimates for these losses range from 7% to 10% for productivity and 10% to 14% for output in China and India, and are smaller, though still significant, in the United States. 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 United States. JEL Codes: O11, O16, O47, E44.

Technical Details

RePEc Handle
repec:oup:qjecon:v:131:y:2016:i:2:p:943-1005.
Journal Field
General
Author Count
3
Added to Database
2026-01-25