Interaction terms in logit and probit models

By Chunrong Ai, E. Norton. 2003

5,587 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Marketing

View Paper: https://www.semanticscholar.org/paper/c9130843be7184cb43f4284371642f65ef845061

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Citations in the corpus

Effects of Federal Policy to Insure Young Adults: Evidence from the 2010 Affordable Care Act Dependent Coverage Mandate (2012, neutral): “As an alternative, we also estimated our main models using a logistic regression specification with standard errors calculated as suggested by Ai and Norton (2003).”
The Choice of Different Types of Subjectivity in CEO Annual Bonus Contracts (2011, neutral): “a procedure based on Ai and Norton (2003). Following our hypotheses, we expect the coefficients”
Measuring Securities Litigation Risk (2012, background): “…Z-statistic of 3.53) but that those for quintiles 3 and 4 are not significantly positive (the mean marginal effect for 33 The analyses suggested by Ai and Norton (2003) result in a distribution of marginal effects with associated distributions of standard errors and Z-statistics (rather than…”
Reward-based crowdfunding of entrepreneurial projects: the effect of local altruism and localized social capital on proponents’ success (2017, neutral): “However, given the non-linear nature of the Tobit model, examining only the coefficients of the interaction terms can lead to misinterpretation of the results (Ai and Norton 2003).”
External Knowledge and Information Technology: Implications for Process Innovation Performance (2017, background): “For example, the sign of the coefficient does not necessarily indicate the sign of the interaction effect (Ai and Norton 2003).”
Materiality Judgments and the Resolution of Detected Misstatements: The Role of Managers, Auditors, and Audit Committees (2012, methodology): “However, Ai and Norton (2003)”
The Geography of Conflicts and Regional Trade Agreements (2012, background): “The interaction between old wars and trade gains, but also with multilateral openness complicates somewhat the computation of the marginal effects with respect to Ai and Norton (2003).”
Safer Ratios, Riskier Portfolios: Banks’ Response to Government Aid (2014, neutral): “…estimates in panel data sets with a short time series and many fixed effects, leading to an incidental parameters problem and inconsistent estimates.14 Second, nonlinear fixed effects models generate biased estimates for interaction terms (Ai and Norton, 2003), the main coefficients of interest.”
Co-opted Boards (2014, neutral): “11 Ai and Norton (2003) note that interpretation of interacted variables in nonlinear models is not straightforward.”