方法对比

	自然实验	双重差分法 (Diff-in-Diff)	现场实验
领域	实验设计	计量经济学	实验设计
方法族	Process / pipeline	Regression model	Process / pipeline
起源年份	1990s (formal methodological articulation); earlier in epidemiology (John Snow, 1854)	1994	1920s–1930s (agriculture); 1990s–2000s (social sciences)
提出者	Varied; systematized in econometrics and political science (e.g., Meyer 1995; Angrist & Krueger 1991)	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)	Formalized by R. A. Fisher (1935); systematized in social sciences by Harrison & List (2004)
类型	Quasi-experimental research design	Causal inference / panel regression	Experimental design
开创性文献	Meyer, B. D. (1995). Natural and quasi-experiments in economics. Journal of Business and Economic Statistics, 13(2), 151–161.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355	Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055.
别名	natural quasi-experiment, naturally occurring experiment, exogenous shock design, as-if randomization	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)	field trial, natural field experiment, randomized field experiment, field RCT
相关	3	5	5
摘要	A natural experiment exploits a real-world event, policy, or circumstance that assigns individuals to treatment and control conditions in a way that is plausibly random — or at least exogenous to the outcome of interest. Because the researcher does not control assignment, it occupies a middle ground between a true randomized controlled trial and purely observational research, offering stronger causal leverage than conventional observational designs when the as-if randomization assumption holds.	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.	A field experiment applies the logic of a randomized controlled trial in a naturally occurring, real-world environment rather than an artificial laboratory. Participants are randomly assigned to treatment and control conditions while going about everyday activities, allowing researchers to estimate causal effects with high internal validity while preserving a level of ecological realism that laboratory settings cannot offer. The design is especially prominent in economics, public health, political science, and development research.