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| Fama-MacBeth-Regression× | Lokale Projektionen× | Panel VARX× | |
|---|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model | Regression model |
| Entstehungsjahr≠ | 1973 | 2005 | 2013 |
| Urheber≠ | Eugene Fama and James MacBeth | Oscar Jorda | Canova and Ciccarelli |
| Typ≠ | Cross-sectional regression | Multi-horizon regression | Multi-equation panel model |
| Wegweisende Quelle≠ | Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3), 607-636. DOI ↗ | Jorda, O. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161-182. DOI ↗ | Canova, F., & Ciccarelli, M. (2013). Panel vector autoregressive models: A survey. Advances in Econometrics, 32, 205-246. DOI ↗ |
| Aliasnamen≠ | Two-step cross-sectional regression | LP-IR, Multi-horizon regression | Panel VAR-X |
| Verwandt | 3 | 3 | 3 |
| Zusammenfassung≠ | The Fama-MacBeth procedure is a two-step regression methodology for analyzing cross-sectional relationships while controlling for time-series structure. Introduced by Fama and MacBeth (1973), it first estimates time-series parameters for each cross-sectional unit, then regresses outcomes on those parameters across the cross-section, averaging results over time. This approach elegantly separates within-unit dynamics from cross-sectional heterogeneity and provides standard errors robust to panel structure. | Local Projections (LP) is a semi-parametric method for estimating impulse responses directly via multi-horizon regressions, bypassing VAR-model specification. Introduced by Jorda (2005), it projects outcomes h periods ahead onto current shocks and lags, producing impulse-response functions without assuming a particular lag structure or VAR order. This flexibility has made it the dominant approach in applied macroeconomics for measuring policy effects and shock transmission. | Panel VARX extends vector autoregression to heterogeneous panels with exogenous variables, enabling simultaneous modeling of multiple endogenous variables alongside observed external factors across many units. Introduced by Holtz-Eakin et al. (1988) and advanced by Canova and Ciccarelli (2013), it captures dynamic relationships within units while allowing parameters to vary across units. This framework is essential for macroeconomic panels and understanding cross-unit heterogeneity in responses to common shocks. |
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