השוואת שיטות

	הפרש-בהפרשים (דיד)	שיטת המשתנים המתערבים (IV) להסקה סיבתית	מודל האפקטים הקבועים לנתוני פאנל
תחום	אקונומטריקה	כלכלת בריאות	אקונומטריקה
משפחה	Regression model	Process / pipeline	Regression model
שנת המקור	1994	1990s (modern applications)	2014
הוגה השיטה	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)	Angrist & Pischke (applied econometrics); rooted in econometric theory	Hsiao (textbook treatment); within transformation of panel data
סוג	Causal inference / panel regression	Method	Panel data regression
מקור מכונן	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.	Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press.
כינויים	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)	IV, two-stage least squares, TSLS, causal estimation	fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
קשורות	5	3	5
תקציר	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.	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.	The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).