השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניסוי טבעי פקטוריאלי× | הפרש-בהפרשים (דיד)× | |
|---|---|---|
| תחום≠ | תכנון ניסויים | אקונומטריקה |
| משפחה≠ | Process / pipeline | Regression model |
| שנת המקור≠ | 1920s (factorial origins, Fisher); natural experiment formalization 1990s–2000s; factorial natural experiment usage widespread 2000s–present | 1994 |
| הוגה השיטה≠ | Extension of natural experiment tradition (Dunning, Angrist & Pischke) combined with factorial design logic (Fisher) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| סוג≠ | Quasi-experimental research design | Causal inference / panel regression |
| מקור מכונן≠ | Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press. ISBN: 978-1107698000 | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| כינויים | factorial quasi-experiment, multi-factor natural experiment, factorial exogenous variation design | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| קשורות≠ | 4 | 5 |
| תקציר≠ | A factorial natural experiment exploits naturally occurring exogenous variation across two or more factors simultaneously, allowing researchers to estimate main effects and interactions without random assignment. Natural events, policy changes, or institutional rules create treatment conditions that approximate a factorial structure, enabling causal inference in observational settings where controlled experimentation is infeasible or unethical. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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