The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Endogeneity in survey research
Open accessAbstract
Abstract Endogeneity is a crucial problem in survey-based empirical research on marketing strategy (MS) and inter-organizational relationships (IORs); if not addressed, it can cause researchers to arrive at flawed conclusions and to offer poor advice to practitioners. Although the field is increasingly cognizant of endogeneity-related issues, many authors fail to properly address it, particularly in survey-based research. Emphasizing the role of essential heterogeneity, this article develops an overarching framework to help improve the understanding of endogeneity problems and how to tackle them when researchers use cross-sectional survey-based data. The authors provide explanations of and advice for how MS and IOR researchers can address six “painful” and sometimes hidden decisions: 1) Do you have an endogeneity problem? 2) What technique/estimator is appropriate? 3) What instrumental variables (IVs) should be chosen? 4) How should IVs be evaluated empirically? 5) How should the results be interpreted and evaluated? and 6) What results should you report? The authors provide a practical flowchart to guide researchers in their efforts to address endogeneity-related concerns.
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Cites
Specification Tests in Econometrics
Hausman, J. A. (1978) · Econometrica · doi:10.2307/1913827 · Cited by 18,820
Identification and estimation of local average treatment effects
Imbens, G. W., & Angrist, J. D. (1994) · Econometrica · doi:10.2307/2951620 · Cited by 4,101
On making causal claims: A review and recommendations
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010) · The Leadership Quarterly · doi:10.1016/j.leaqua.2010.10.010 · Cited by 2,441
Angrist, J. D., & Krueger, A. B. (2001) · Journal of Economic Perspectives · doi:10.1257/jep.15.4.69 · Cited by 2,355
Shadow Prices, Market Wages, and Labor Supply
Heckman, J. (1974) · Econometrica · doi:10.2307/1913937 · Cited by 1,852
Counterfactuals and Causal Inference: Methods and Principles for Social Research
Morgan, S. L., & Winship, C. (2007) · doi:10.1017/cbo9780511804564 · Cited by 1,146
Estimating Marginal Returns to Education
Carneiro, P., Heckman, J. J., & Vytlacil, E. J. (2011) · American Economic Review · doi:10.1257/aer.101.6.2754 · Cited by 612
Cited by
Uysal, E., Alavi, S., & Bezençon, V. (2022) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-022-00856-9 · Cited by 182
Metadata
- Authors
- Sande, J. B., & Ghosh, M.
- Venue
- International Journal of Research in Marketing
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 35
- Issue
- 2
- Pages
- 185-204
- ISSN
- 0167-8116 (ISSN-L)
- OpenAlex
- W2793560204
- Cited by
- 264
- References
- 7
- FWCI
- 14.11
- Type
- journal article
- Language
- en
- Open access
- green
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