WebWith the datasets generated, we can now move on to testing for the presence of weak instruments. The cragg package offers two main functions to do this: cragg_donald(), and stock_yogo_test. cragg_donald() implements the calculation for the Cragg-Donald statistic (1993), which can be thought of as the matrix-analogue of the first stage F-statistic. WebApr 7, 2024 · ivreg2进行弱工具变量检验后的结果怎么看？,各位群友，我通过ivreg2进行了弱工具变量的检验，得到如下结果：Weak identification test (Cragg-Donald Wald F statistic): 12.981Stock-Yogo weak ID test critical values: 10% maximal IV size 16.38 15% maximal IV size 8.96 20% maximal IV size 6.66 25% maximal IV size 5.53,经管之家(原人大经济论坛)
cragg package - RDocumentation
http://mayoral.iae-csic.org/IV_2015/IVGot_lecture3.pdf WebThe cragg package has two main functions cragg_donald(), and stock_yogo_test(). cragg_donald() implements the Cragg-Donald test for weak instruments in R. It can be thought of as the matrix-equivalent of the first-stage F-test for weak instruments, and is used to evaluate models with multiple endogenous variables. hiutaleet
Comparison of conditional F-statistics • OneSampleMR - Dr Tom …
WebCragg-Donald statistic I For notational compactness, let P W = W(W0W)−1W0 and M W = I − P W for any matrix W, and let W⊥ be the residuals from projection on X, so W⊥ = M XW. Define Z = [XZ] to be the matrix of all instruments (included and excluded). I One can construct the Cragg-Donald statistic as follows: G T = (Y 0M ZY) −1/2Y⊥ ... Web（3）在扰动项为iid的假设下（这要求不存在异方差），可以使用“Cragg-Donald Wald F统计量”。 （4）不作iid扰动项的假设（允许存在异方差），可以使用“Kleibergen-Paap Wald rk F统计量”。 解决方法 （1）寻找更强的工具变量。 WebStaiger and Stock （1997）建议只要该值大于10就认为不存在弱IV。这个值用于iid的情况。 （3）Cragg-Donald Wald F统计量，由Cragg and Donald （1993）提出，Stock and Yogo （2005）给出其临界值，Stata在回归时会给出临界值。 hiutaleneule