Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India
30 Pages Posted: 4 Sep 2020 Last revised: 24 Feb 2021
Date Written: January 1, 2021
Do agglomeration-based spillovers impact firms more than the technical know-how obtained through inter-firm collaboration? Quantifying the effect of these treatments on firm performance can be valuable for policy-makers as well as managers/entrepreneurs. I observe the universe of Indian MSMEs inside an industrial cluster but with no collaboration (Treatment Group 1), those in collaboration with other firms for technical know-how but outside a cluster (Treatment Group 2) and those outside cluster with no collaboration (Control Group). Selection of firms into these treatments and subsequent performance of the firm may be simultaneously driven by observable factors. To address selection bias and overcome model misspecification, I use two data-driven, model-selection methods, developed in Belloni et al. (2013) and Chernozhukov et al. (2015), to estimate causal impact of the treatments on GVA of firms. The results suggest that ATE of cluster and collaboration is nearly equal at 30%. I conclude by offering policy implications of the results.
Keywords: Clusters, Collaboration, MSMEs, Model Selection
JEL Classification: L24, L25, L26
Suggested Citation: Suggested Citation