Forecasting Aggregate Productivity Using Information from Firm-Level Data
The Review of Economics and Statistics
2014
In this paper, we explore whether information from firm-level data can improve forecasts of aggregate productivity growth. We generate firm-level productivity measures and aggregate them into time-series components that capture within-firm productivity and the productivity contribution of reallocation. We show that these components improve aggregate total factor productivity forecasts in a simple univariate setting, even when firm-level data are available with a time lag. Lagged firm-level information also improves aggregate productivity forecasts when we combine results from a variety of different multivariate forecasting models using Bayesian model averaging techniques.
- DOI
- 10.1162/rest_a_00395
- Volume
- 96 (4)
- Pages
- 745-755
- Language
- en
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- Sources
- openalex crossref