 Bouba Housseini |
 Suman Seth |
|
Audio
Video (with guide)
Guide to the video
Introduction
Part 1 Robustness analysis
1:04 Sources for the lecture
3:28 Policy areas requiring robustness analysis
4:34 Importance of robustness analyses illustrated using Global MPI data
6:15 Implications of conclusions based on a sample
8:04 Parameters of M0 for robustness analysis: poverty cutoff, weighting vector and deprivation cutoffs
9:48 Rank robustness analysis
11:03 First Order unidimensional dominance
13:15 Dominance for H and M0 in AF
16:24 Calculation using two deprivation count vectors
21:10 Discussion of the M0 curve
23:24 Stochastic dominance conditions
26:42 Methods for comparing robustness of ranking
28:38 Kendall’s Tau
32:43 Spearman’s Rho
34:00 Some illustrations using the MPI: Robustness to weights
37:18 Robustness to poverty cutoff (k)
Part 2 Statistical inference
46:30 Estimation from samples about population level characteristics
47:18 Common concerns
49:20 Standard error (SE) and construction of confidence intervals (CI)
54:40 How to obtain the standard error
58:06 How to use a confidence interval
1:00:00 Difference between analytical SE and bootstrap methods
1:08:10 Concerns with sampling
1:11:38 Example using analytical method for SE using data from India
1:13:55 Hypothesis tests and equivalent procedures
1:19:50 Statistical inference in MPI comparisons
1:34:35 Conclusions
