Instrumental Variables Correction for Management Measurement Error

In Simple Words

Imagine trying to measure how much a medicine helps sick patients by looking at regular hospital records. Because doctors give the medicine primarily when patients get extremely ill, simple statistical comparisons make the medicine look weak or useless. By using an external event—like a lottery that randomly decides which patients receive the medicine—statisticians can isolate the true power of the medicine without the confusion caused by who was sickest when taking it.

Research question

Standard Ordinary Least Squares (OLS) or fixed-effects estimates systematically understate the impact of management practice adoption on firm performance due to measurement error in practice scores and endogenous implementation timing, where firms adopt new practices during performance downturns.

Participants

20 experimental manufacturing plants across 17 large cotton textile firms in India tracked weekly over ~100 weeks per plant.

Study Design

Panel regression comparing fixed-effects OLS estimates against Instrumental Variables (IV) estimates using cumulative weeks of randomized consulting treatment as the instrument for the 38-practice management adoption index.

Results

The IV point estimate for Total Factor Productivity (TFP) was 0.477 (p < 0.05, First-stage F-stat = 86.00) compared to an OLS estimate of 0.167, while the IV effect on quality defects was -1.694 compared to -0.558 under OLS, proving that uninstrumented estimates suffer from substantial downward attenuation bias.

Takeaway

Instrument self-reported or observed management practice indices with exogenous random assignment variables when evaluating productivity impacts to avoid downward attenuation bias.

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