什么是双重差分模型介绍

来源：蜘蛛抓取(WebSpider) 时间：2017-08-21 05:52 标签： 双重差分模型的应用
如何进行双重差分模型（DID）模型的平行趋势检验-土地公问答
如何进行双重差分模型（DID）模型的平行趋势检验
如何进行双重差分模型（DID）模型的平行趋势检验
答：即不同组间样本在政策实施前可能存在事前差异，继而导致对政策实施效果的有偏估计，难以保证对于政策实施组和对照组在样本分配上的完全随机，非随机分配政策实施组和对照组的试验称为自然试验(natural trial)双重差分模型(difference-in-differe...
即同组间本政策实施前能存事前差异继导致政策实施效偏估计难保证于政策实施组照组本配完全随机非随机配政策实施组照组试验称自试验(natural trial)双重差模型(difference-in-difference类试验存较显著特点通范围公共政策别于普通科研性研究DID)近用于计量经济于公共政策或项目实施效定量评估仅通单前比或横向比析忽略种差异
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双重差分模型幻灯片++difference+in+differences+models.ppt 30页
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Difference in Difference Models Bill Evans Spring 2008 Difference in difference models Maybe the most popular identification strategy in applied work today Attempts to mimic random assignment with treatment and “comparison” sample Application of two-way fixed effects model
Problem set up Cross-sectional and time series data One group is ‘treated’ with intervention Have pre-post data for group receiving intervention Can examine time-series changes but, unsure how much of the change is due to secular changes
Intervention occurs at time period t1 True effect of law Ya – Yb Only have data at t1 and t2 If using time series, estimate Yt1 – Yt2 Solution? Difference in difference models Basic two-way fixed effects model Cross section and time fixed effects Use time series of untreated group to establish what would have occurred in the absence of the intervention Key concept:
can control for the fact that the intervention is more likely in some types of states Three different presentations Tabular Graphical Regression equation Difference in Difference Key Assumption Control group identifies the time path of outcomes that would have happened in the absence of the treatment In this example, Y falls by Yc2-Yc1 even
without the intervention Note that underlying ‘levels’ of outcomes are not important (return to this in the regression equation)
In contrast, what is key is that the time trends in the absence of the intervention are the same in both groups
If the intervention occurs in an area with a different trend, will under/over state the treatment effect In this example, suppose intervention occurs in area with faster falling Y Basic Econometric Model Data varies by
state (i) time (t) Outcome is Yit Only two periods Intervention will occur in a group of observations (e.g. states, firms, etc.) Three key variables Tit =1 if obs i belongs in the state that will eventually be treated Ait =1 in the periods when treatment occurs TitAit
-- interaction term, treatment states a
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双重差分模型介绍及其应用
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