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비선형 하우즈만 모형 적합성 검정×인과 추론을 위한 도구 변수(IV) 방법×
분야계량경제학보건경제학
계열Regression modelProcess / pipeline
기원 연도1978 (nonlinear extension developed through 1980s–1990s)1990s (modern applications)
창시자Jerry A. HausmanAngrist & Pischke (applied econometrics); rooted in econometric theory
유형Specification / endogeneity testMethod
원전Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. DOI ↗Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗
별칭Hausman specification test (nonlinear), nonlinear endogeneity test, Wu-Hausman test (nonlinear), NL-Hausman testIV, two-stage least squares, TSLS, causal estimation
관련33
요약The Nonlinear Hausman test extends Hausman's (1978) endogeneity specification test to nonlinear models such as probit, logit, Tobit, and count-data regressions. It tests whether suspected regressors are endogenous — i.e., correlated with the error term — in a model where the outcome or the relationship is inherently nonlinear, ensuring that IV-corrected estimates are necessary.Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes.
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ScholarGate방법 비교: Nonlinear Hausman test · Instrumental Variables in Health Research. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare