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

See all articles by Samarth Gupta

Samarth Gupta

National Council of Applied Economic Research

Date Written: January 1, 2021

Abstract

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

Gupta, Samarth, Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India (January 1, 2021). Available at SSRN: https://ssrn.com/abstract=3660898 or http://dx.doi.org/10.2139/ssrn.3660898

Samarth Gupta (Contact Author)

National Council of Applied Economic Research ( email )

Parisila Bhawan
11 - Indraprastha Estate
New Delhi, 110002
India

HOME PAGE: http://blogs.bu.edu/samarth/

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