INFORMATION, MISALLOCATION, AND AGGREGATE PRODUCTIVITY

• 成果类型: Article
• 署名作者: David, Joel M.; Hopenhayn, Hugo A.; Venkateswaran, Venky
• 署名单位: University of Southern California; University of California System; University of California Los Angeles; New York University
• 刊物名称: QUARTERLY JOURNAL OF ECONOMICS
• ISSN/ISSBN: 0033-5533
• DOI: 10.1093/qje/qjw006
• 发表日期: 2016
• 页码: 943-1005
• 关键词: STOCK-PRICE; MARKETS; GROWTH; INDIA

摘要

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.