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Inference on causal and structural parameters using many moment inequalities

Victor Chernozhukov, Denis Chetverikov, Kengo Kato

arXiv 30 Dec 2013 · Mathematics — Statistics Theory · publishedThe Review of Economic Studies (2018) · 87 citations (OpenAlex)

arXiv:1312.7614 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by $p$, is possibly much larger than the sample size $n$. There is a variety of economic applications where solving this problem allows to carry out inference on causal and structural parameters, a notable example is the market structure model of Ciliberto and Tamer (2009) where $p=2^{m+1}$ with $m$ being the number of firms that could possibly enter the market. We consider the test statistic given by the maximum of $p$ Studentized (or $t$-type) inequality-specific statistics, and analyze various ways to compute critical values for the test statistic. Specifically, we consider critical values based upon (i) the union bound combined with a moderate deviation inequality for self-normalized sums, (ii) the multiplier and empirical bootstraps, and (iii) two-step and three-step variants of (i) and (ii) by incorporating the selection of uninformative inequalities that are far from being binding and a novel selection of weakly informative inequalities that are potentially binding but do not provide first order information. We prove validity of these methods, showing that under mild conditions, they lead to tests with the error in size decreasing polynomially in $n$ while allowing for $p$ being much larger than $n$, indeed $p$ can be of order $\exp (n^{c})$ for some $c > 0$. Importantly, all these results hold without any restriction on the correlation structure between $p$ Studentized statistics, and also hold uniformly with respect to suitably large classes of underlying distributions. Moreover, in the online supplement, we show validity of a test based on the block multiplier bootstrap in the case of dependent data under some general mixing conditions.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Chetverikov, D (2017) Adaptive test of conditional moment inequalities self1.000114100%
2Ciliberto, F. and Tamer, E (2009) Market structure and multiple equilibria in airline markets1.00084100%
3Galichon, A. and Henry, M (2011) Set identification in models with multiple equilibria1.00063100%
4Andrews, D.W.K. and Shi, X (2013) Inference based on conditional moment inequalities1.00054100%
5Armstrong, T.B. and Chan, H.P (2016) Multiscale adaptive inference on conditional moment inequalities0.92843100%
6Bajari, P., Benkard, C.L., and Levin, J (2007) Estimating dynamic models of imperfect competition0.87482100%
7White, H (2000) A reality check for data snooping0.87482100%
8Chernozhukov, V., Lee, S., and Rosen, A (2013) Intersection bounds: estimation and inference self0.84333100%
9Chesher, A., Rosen, A., and Smolinski, K (2013) An instrumental variable model of multiple discrete choice0.81142100%
10Romano, J.P., Shaikh, A.M., and Wolf, M (2014) A practical two-step method for testing moment inequalities with an application to inference in partially identified models0.73732100%

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