방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 패널 기반 관찰 양적 연구× | 고정 효과 모형 (Fixed Effects Model)× | |
|---|---|---|
| 분야≠ | 연구설계 | 계량경제학 |
| 계열≠ | Process / pipeline | Regression model |
| 기원 연도≠ | 1960s–1980s (formalized in econometrics); widely adopted in social sciences by 1990s | 1971–1978 |
| 창시자≠ | Established through econometrics literature; foundational contributions by Cheng Hsiao, Zvi Griliches, and Marc Nerlove | Mundlak (1978); Nerlove (1971); classical panel econometrics |
| 유형≠ | Quantitative observational longitudinal design | Panel regression estimator |
| 원전≠ | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030538002 |
| 별칭 | panel observational study, longitudinal observational panel design, panel survey research, repeated-measures observational design | FE model, within estimator, least squares dummy variable, LSDV regression |
| 관련≠ | 4 | 5 |
| 요약≠ | Panel-based observational quantitative research follows the same individuals, organizations, or units across two or more time points without experimentally manipulating any condition. By combining the within-unit depth of longitudinal tracking with the numerical precision of quantitative measurement, it enables researchers to study change over time, detect lagged effects, and control for stable unobserved characteristics — all while maintaining the ethical simplicity of pure observation. | The fixed effects (FE) model is the workhorse estimator for panel data when unobserved unit-specific characteristics are suspected to correlate with the regressors. By absorbing each entity's time-invariant heterogeneity into a separate intercept, FE isolates the causal effect of within-unit variation and eliminates omitted-variable bias from time-constant confounders. |
| ScholarGate데이터셋 ↗ |
|
|