Economics at your fingertips  

Strengthening Causal Inference through Qualitative Analysis of Regression Residuals: Explaining Forest Governance in the Indian Himalaya

Arun Agrawal and Ashwini Chhatre
Additional contact information
Ashwini Chhatre: Department of Geography, University of Illinois at Urbana-Champaign, 232 Davenport MC-150, 607 S. Mathews Ave., Urbana IL 61801, USA

Environment and Planning A, 2011, vol. 43, issue 2, 328-346

Abstract: This paper contributes to fertile debates in environmental social sciences on the uses of and potential synergies between qualitative and quantitative analytical approaches for theory development and validation. Relying on extensive fieldwork on local forest governance in India, and using a dataset on 205 forest commons, we propose a methodological innovation for combining qualitative and quantitative analyses to improve causal inference. Specifically, we demonstrate that qualitative knowledge of cases that are the least well predicted by quantitative modeling can strengthen causal inference by helping check for possible omitted variables, measurement errors, nonlinearities in posited relationships, and possible interaction effects, and thereby lead to analytical improvements in the quantitative analysis. In the process, the paper also presents a contextually informed and theoretically engaged empirical analysis of forest governance in north India, showing in particular the importance of institutional and historical factors in influencing commons outcomes.

Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link) (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.1068/a42302

Access Statistics for this article

More articles in Environment and Planning A
Bibliographic data for series maintained by SAGE Publications ().

Page updated 2023-11-14
Handle: RePEc:sae:envira:v:43:y:2011:i:2:p:328-346