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| 푸리에 하우즈만 검정× | 인과 추론을 위한 도구 변수(IV) 방법× | |
|---|---|---|
| 분야≠ | 계량경제학 | 보건경제학 |
| 계열≠ | Regression model | Process / pipeline |
| 기원 연도≠ | 2000s–2010s | 1990s (modern applications) |
| 창시자≠ | Extends Hausman (1978) using Gallant's (1981) Fourier flexible functional form; applied in panel/time-series settings by Christopoulos & Leon-Ledesma (2004) and subsequent literature | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| 유형≠ | Specification / endogeneity test | Method |
| 원전≠ | Christopoulos, D. K., & Leon-Ledesma, M. A. (2004). Current account sustainability in the US: What do we really know about it? Journal of International Money and Finance, 23(5), 821–840. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| 별칭 | Fourier-Hausman endogeneity test, Fourier augmented Hausman test, nonlinear Hausman test, flexible Hausman specification test | IV, two-stage least squares, TSLS, causal estimation |
| 관련≠ | 5 | 3 |
| 요약≠ | The Fourier Hausman test extends the classical Hausman endogeneity test by augmenting the regression with Fourier trigonometric terms — sines and cosines of time — so that the test remains valid even when the data-generating process contains smooth structural breaks or gradual nonlinearities that conventional linear specifications miss. | 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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