Fetching the paper…
Reading the bibliography…
Kernel maximum moment restriction (KMMR) recently emerges as a popular framework for instrumental variable (IV) based conditional moment restriction (CMR) models with important applications in conditional moment (CM) testing and parameter estimation for IV regression and proximal causal learning.
Functions of positive and negative type, and their connection with the theory of integral equations
J. Mercer · 1909
Earlier work this paper cites.
Sur les opérations fonctionnelles linéaires, 1909
F. Riesz · 1909
Earlier work this paper cites.
Theory of reproducing kernels
N. Aronszajn · 1950
Earlier work this paper cites.
The bias and moment matrix of the general k-class estimators of the parameters in simultaneous equations
A. L. Nagar · 1959
Earlier work this paper cites.
Rational expectations and the theory of price movements
J. F. Muth · 1961
Earlier work this paper cites.
A new look at the statistical model identification
H. Akaike · 1974
Earlier work this paper cites.
The numerical treatment of integral equations
C. T. Baker · 1977
Earlier work this paper cites.
Estimating the dimension of a model
G. Schwarz et al · 1978
Earlier work this paper cites.
Large sample properties of generalized method of moments estimators
L. P. Hansen · 1982
Earlier work this paper cites.
Generalized instrumental variables estimation of nonlinear rational expectations models
L. P. Hansen and K. J. Singleton · 1982
Earlier work this paper cites.
Approximate distributions of k-class estimators when the degree of overidentifiability is large compared with the sample size
K. Morimune · 1983
Earlier work this paper cites.
Density estimation for statistics and data analysis
B. W. Silverman · 1986
Earlier work this paper cites.
Likelihood ratio tests for model selection and non-nested hypotheses
Q. H. Vuong · 1989
Earlier work this paper cites.
On optimal data-based bandwidth selection in kernel density estimation
P. Hall, S. J. Sheather, M. Jones, and J. S. Marron · 1991
Earlier work this paper cites.
Efficient estimation of models with conditional moment restrictions
W. Newey · 1993
Earlier work this paper cites.
Higher order asymptotics
J. K. Ghosh · 1994
Earlier work this paper cites.
Chapter 36 large sample estimation and hypothesis testing
W. K. Newey and D. McFadden · 1994
Earlier work this paper cites.
GMM estimation of a stochastic volatility model: A monte carlo study
T. G. Andersen and B. E. Sorensen · 1996
Earlier work this paper cites.
The bierens test under data dependence
R. M. de Jong · 1996
Earlier work this paper cites.
Consistent Moment Selection Procedures for Generalized Method of Moments Estimation
D. W. K. Andrews · 1999
Earlier work this paper cites.
Redundancy of moment conditions
T. Breusch, H. Qian, P. Schmidt, and D. Wyhowski · 1999
Earlier work this paper cites.
Generalization of gmm to a continuum of moment conditions
M. Carrasco and J.-P. Florens · 2000
Earlier work this paper cites.
Tests of rank
J.-M. Robin and R. J. Smith · 2000
Earlier work this paper cites.
Asymptotic Statistics
A. Van der Vaart · 2000
Earlier work this paper cites.
Choosing the number of instruments
S. G. Donald and W. K. Newey · 2001
Cited alongside, same era.
Finite sample inference for gmm estimators in linear panel data models
S. R. Bond and F. Windmeijer · 2002
Cited alongside, same era.
Theory of Linear Ill-posed Problems and Its Applications
V. K. Ivanov, V. V. Vasin, and V. Tanana · 2002
Cited alongside, same era.
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
B. Schölkopf and A. Smola · 2002
Cited alongside, same era.
Efficient estimation of models with conditional moment restrictions containing unknown functions
C. Ai and X. Chen · 2003
Cited alongside, same era.
‘mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?
G. Davey Smith and S. Ebrahim · 2003
Select the valid and relevant moments: An information-based lasso for gmm with many moments
X. Cheng and Z. Liao · 2015
Later among the works it cites.
Econometricians have their moments: Gmm at 32
A. R. Hall · 2015
Later among the works it cites.
A kernelized stein discrepancy for goodness-of-fit tests
Q. Liu, J. Lee, and M. Jordan · 2016
Later among the works it cites.
A review of instrumental variable estimators for mendelian randomization
S. Burgess, D. S. Small, and S. G. Thompson · 2017
Later among the works it cites.
Deep IV: A flexible approach for counterfactual prediction
J. Hartford, G. Lewis, K. Leyton-Brown, and M. Taddy · 2017
Later among the works it cites.
Kernel mean embedding of distributions: A review and beyond
K. Muandet, K. Fukumizu, B. Sriperumbudur, and B. Schölkopf · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Empirical likelihood estimation and consistent tests with conditional moment restrictions
S. G. Donald, G. W. Imbens, and W. K. Newey · 2003
Cited alongside, same era.
On the performance of kernel classes
S. Mendelson, T. Graepel, and R. Herbrich · 2003
Cited alongside, same era.
Effective dimension and generalization of kernel learning
T. Zhang · 2003
Cited alongside, same era.
Reproducing Kernel Hilbert Spaces in Probability and Statistics
A. Berlinet and C. Thomas-Agnan · 2004
Cited alongside, same era.
Consistent estimation of models defined by conditional moment restrictions
M. Dominguez and I. Lobato · 2004
Cited alongside, same era.
Higher order properties of gmm and generalized empirical likelihood estimators
W. K. Newey and R. J. Smith · 2004
Cited alongside, same era.
Double/debiased machine learning for treatment and structural parameters, 2018
V. Chernozhukov, D. Chetverikov, M. Demirer, E. Duflo, C. Hansen, W. Newey, and J. Robins · 2018
Later among the works it cites.
Adversarial generalized method of moments
G. Lewis and V. Syrgkanis · 2018
Later among the works it cites.
Breaking the curse of horizon: Infinite-horizon off-policy estimation
Q. Liu, L. Li, Z. Tang, and D. Zhou · 2018
Later among the works it cites.
Generalized random forests
S. Athey, J. Tibshirani, S. Wager, et al · 2019
Later among the works it cites.
Deep generalized method of moments for instrumental variable analysis
A. Bennett, N. Kallus, and T. Schnabel · 2019
Later among the works it cites.
A kernel loss for solving the bellman equation
Y. Feng, L. Li, and Q. Liu · 2019
Later among the works it cites.
Kernel instrumental variable regression
R. Singh, M. Sahani, and A. Gretton · 2019
Later among the works it cites.
A robust and efficient method for Mendelian randomization with hundreds of genetic variants
S. Burgess, C. N. Foley, E. Allara, J. R. Staley, and J. M. M. Howson · 2020
Later among the works it cites.
Minimax estimation of conditional moment models
N. Dikkala, G. Lewis, L. Mackey, and V. Syrgkanis · 2020
Later among the works it cites.
Valid causal inference with (some) invalid instruments
J. S. Hartford, V. Veitch, D. Sridhar, and K. Leyton-Brown · 2020
Later among the works it cites.
Generalized optimal matching methods for causal inference
N. Kallus · 2020
Later among the works it cites.
Ivy: Instrumental variable synthesis for causal inference
Z. Kuang, F. Sala, N. Sohoni, S. Wu, A. Córdova-Palomera, J. Dunnmon, J. Priest, and C. Re · 2020
Later among the works it cites.
Provably efficient neural estimation of structural equation model: An adversarial approach
L. Liao, Y. Chen, Z. Yang, B. Dai, Z. Wang, and M. Kolar · 2020
Later among the works it cites.
Minimax weight and q-function learning for off-policy evaluation
M. Uehara, J. Huang, and N. Jiang · 2020
Later among the works it cites.
Maximum moment restriction for instrumental variable regression
R. Zhang, M. Imaizumi, B. Schölkopf, and K. Muandet · 2020
Later among the works it cites.
Instrumental variable value iteration for causal offline reinforcement learning
L. Liao, Z. Fu, Z. Yang, M. Kolar, and Z. Wang · 2021
Closest in time.
Proximal causal learning with kernels: Two-stage estimation and moment restriction
A. Mastouri, Y. Zhu, L. Gultchin, A. Korba, R. Silva, M. Kusner, A. Gretton, and K. Muandet · 2021
Closest in time.