Thanks to the 211 votes on the papers, here are the selected top ten:

- B. Efron (1979) Bootstrap methods: another look at the jacknife Annals of Statistics
- R. Tibshirani (1996) Regression shrinkage and selection via the lasso J. Royal Statistical Society
- A.P. Dempster, N.M. Laird and D.B. Rubin (1977) Maximum likelihood from incomplete data via the EM algorithm J. Royal Statistical Society
- Y. Benjamini & Y. Hochberg (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Royal Statistical Society
- W.K.Hastings (1970) Monte Carlo sampling methods using Markov chains and their applications, Biometrika
- J. Neyman & E.S. Pearson (1933) On the problem of the most efficient test of statistical hypotheses Philosophical Trans. Royal Statistical Society London
- D.R. Cox (1972) Regression models and life-table J. Royal Statistical Society
- A. Gelfand & A.F.M. Smith (1990) Sampling-based approaches to calculating marginal densities J. American Statistical Assoc.
- C. Stein (1981) Estimation of the mean of a multivariate normal distribution Annals of Statistics
- J.O. Berger & T. Sellke (1987) Testing a point null hypothesis: the irreconciability of p-values and evidence J. American Statistical Assoc

Which ones should I now add? First, Steve Fienberg pointed out to me the reading list he wrote in 2005 for the iSBA Bulletin. Out of which I must select a few ones:

- A. Birnbaum (1962) On the Foundations of Statistical Inference J. American Statistical Assoc.
- D.V. Lindley & A.F.M. Smith (1972) Bayes Estimates for the Linear Model J. Royal Statistical Society
- J.W.Tukey (1962) The future of data analysis. Annals of Mathematical Statistics
- L. Savage (1976) On Rereading R.A. Fisher Annals of Statistics

And then from other readers, including Andrew, I must also pick:

- H. Akaike (1973). Information theory and an extension of the maximum likelihood principle. Proc. Second Intern. Symp. Information Theory, Budapest
- D.B. Rubin (1976). Inference and missing data. Biometrika
- G. Wahba (1978). Improper priors, spline smoothing and the problem of guarding against model errors in regression. J. Royal Statistical Society
- G.W. Imbens and J.D. Angrist (1994). Identification and estimation of local average treatment effects. Econometrica.
- Box, G.E.P. and Lucas, H.L (1959) Design of experiments in nonlinear situations. Biometrika
- S. Fienberg (1972) The multiple recapture census for closed populations and incomplete 2
^{k}contingency tables Biometrika

Of course, there are others that come close to the above, like Besag’s 1975 Series B paper. Or Fisher’s 1922 foundational paper. But the list is already quite long. (In case you wonder, I would not include Bayes’ 1763 paper in the list, as it is just too remote from statistics.)