Working Paper: CEPR ID: DP14227
Authors: David Atkin; Amit Khandelwal; Adam Osman
Abstract: We use tailored surveys and benchmarking in the flat-weave rug industry to better understand the shortcomings of standard productivity measures. TFPQ performs poorly because of variation in product specifications across firms. Controlling for specifications aligns TFPQ with lab benchmarks. We also collect quality metrics to construct quality productivity (the ability to produce quality given inputs) and find substantial dispersion across firms. This motivates interest in multi-dimensional productivity, or capability. As quality productivityis negatively correlated with TFPQ, TFPR may perform better at capturing capabilities in settings where better firms make products with more demanding specifications that have greater input requirements.
Keywords: productivity
JEL Codes: No JEL codes provided
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| tailored surveys (C83) | productivity measures (E23) |
| product specification adjustments (L15) | improved productivity estimates (O49) |
| tfpq (Y60) | quality productivity (L15) |
| quality productivity (L15) | quantity productivity (E23) |
| tfpr (Y20) | firm capabilities (L10) |