Bryan S. Graham

Research

Working papers

1. “Scenario Sampling for Large Supermodular Games”, 2023 (w/ Andrin Pelican)
   
   
2. “Minimax risk and uniform convergence rates for nonparametric dyadic regression” revision requested by Econometric Theory, 2021 (w/ Fengshi Niu and James L. Powell)
   • arXiv version
   • cemmap version
     
     
3. “Homophily and transitivity in dynamic network formation,” revision requested by the Review of Economic Studies, 2016, also available as a CEMMAP Working paper
   • iPython Notebook to replicate figures and Monte Carlos
     
     

     Publications

     (Note: documents made available for personal study/use only)
     
     

4. “An optimal test for strategic interaction in network formation games” conditonally accepted by the Review of Economic Studies, 2024 (w/ Andrin Pelican)
   • Supplemental Web Appendix
   • arXiv version
   • cemmap version
   • nber version
   • Python uniform graph draw module at GitHub and PyPi
   • Tutorial and replication Python Jupyter Notebook
     
     
5. “Measuring the effects of segregation in the presence of social spillovers: a nonparametric approach” accepted by the Journal of Econometrics, 2024 (w/ Guido Imbens and Geert Ridder)
   • Matlab code archive for replication of empirical illustration ( Warning: This code is 15 years old!).
   • Matlab mat data file. Data are also available in Stata and text formats.
     
     
6. “Sparse network asymptotics for logistic regression under possible misspecification” Econometrica 92 (6): 1837 - 1868, 2024
   • arXiv version
   • cemmap version
   • nber version
   • Python Jupyter Notebook #1 with application and calibrated Monte Carlo results.
   • Python Jupyter Notebook #2 with additional Monte Carlo results.
     
     
7. “Kernel density estimation for undirected dyadic data” _Journal of Econometrics_240 (2): Article 105336, 2024 (w/ Fengshi Niu and James L. Powell)
   • arXiv version
   • Monte Carlo Code
     
     
8. “Identification in a binary choice panel data model with a predetermined covariate” SERIEs: Journal of the Spanish Economic Association 14 (3-4): 315 - 351, 2023 (with Stephane Bonhomme and Kevin Dano) Special Issue in honor of Manuel Arellano
   • arXiv version
   • cemmap version
   • GitHub repository with replication code for numerical examples.
     
     
9. “Foreward from the editors” for “Identification in dynamic binary choice models” by Gary Chamberlain in SERIEs: Journal of the Spanish Economic Association 14 (3-4): 247 - 251, 2023 (with Stephane Bonhomme and Laura Hospido) Special Issue in honor of Manuel Arellano
   
   
10. “Teacher-to-classroom assignment and student achievement” Journal of Business and Economic Statistics 41 (4): 1328 - 1340, 2023 (w/ Geert Ridder, Petra Thiemann and Gema Zamarro)
    • arXiv version
    • cemmap version
    • nber version
      
      
11. “ET Interview: Professor Gary Chamberlain” Econometric Theory 39: 1 - 26, 2023 (w/ Keisuke Hirano and Guido W. Imbens)
    • A few photos of Gary are are here: photo_1, photo_2, photo_3, photo_4, photo_5 and photo_6
      
      
12. “Introduction to the Annals Issue in Honor of Gary Chamberlain” Journal of Econometrics 226 (1): 1 - 3, 2022 (w/ Keisuke Hirano)
    
    
13. “Semiparametrically efficient estimation of the average linear regression function,” Journal of Econometrics 226 (1): 115 - 138, 2022 (w/ Cristine Pinto)
    • Supplemental Web Appendix
    • Monte Carlo Code
      
      
14. “Network data”, Handbook of Econometrics 7A: 111 - 218 (S. Durlauf, L. Hansen, J. Heckman & R. Matzkin, Eds.). Amsterdam: North-Holland, 2020
    • Cemmap Version
    • arXiv version
    • Note: Link to Volume 7A of the Handbook of Econometrics
      
      
15. The Econometric Analysis of Network Data (B. Graham & A. de Paula, Eds.). Amsterdam: Academic Press, 2020
    • Note: This is an edited volume with contributions from an outstanding group of researchers.
      
      
16. “Dyadic regression”, The Econometric Analysis of Network Data: 23 - 40 (B. Graham & A. de Paula, Eds.). Amsterdam: Academic Press, 2020
    • arXiv version
    • Code for Empirical Example
      
      
17. “Testing for externalities in network formation using simulation”, The Econometric Analysis of Network Data: 63 - 82 (B. Graham & A. de Paula, Eds.). Amsterdam: Academic Press, 2020 (w/ Andrin Pelican)
    • arXiv version
    • Code for Empirical Example
      
      
18. “Identification and efficiency bounds for the average match function under conditionally exogenous matching,” Journal of Business and Economic Statistics 38 (2): 303 - 316, 2020 (w/ Guido W. Imbens and Geert Ridder)
    • Also available as a CEMMAP and NBER Working Paper.
      
      
19. “A quantile correlated random coefficients panel data model,” Journal of Econometrics 206 (2): 305 - 335, 2018 (w/ Jinyong Hahn, Alex Poirier and Jim Powell)
    • Web appendix
    • Stata Do and Data files
      
      
20. “Identifying and estimating neighborhood effects,” Journal of Economic Literature 56 (2): 450 - 500, 2018
    
    
21. “An econometric model of network formation with degree heterogeneity,” Econometrica 85 (4): 1033 - 1063, 2017
    • CEMMAP and NBER working paper versions
    • Supplemental web appendix
    • Detailed calculations
    • Python 2.7 Monte Carlo script
    • Note: To run the Monte Carlo you will need to install the netrics package. More information about this package is available here. Links: pypi, GitHub
      
      
22. “Efficient estimation of data combination models by the method of auxiliary-to-study tilting (AST),” Journal of Business and Economic Statistics 31 (2): 288 - 301, 2016 (w/ Cristine Pinto and Daniel Egel)
    • Web appendix
    • Stata DCT and Do files, Matlab code, dataset (tab delimited, mat)
      
      
23. “Methods of identification in social networks,” Annual Review of Economics 7: 465 - 485, 2015
    
    
24. “Complementarity and aggregate implications of assortative matching: a nonparametric analysis,” Quantitative Economics 5 (1): 29 - 66, 2014 (w/ Guido W. Imbens and Geert Ridder)
    • Web appendix
      
      
25. Mobility and the Metropolis: How Communities Factor into Economic Mobility, A Report from the Pew Charitable Trusts. Washington D.C.: The Pew Charitable Trusts, 2013 (w/ Patrick Sharkey)
    • Pew web page for report
    • Additional information
      
      
26. “Comparative static and computational methods for an empirical one-to-one transferable utility matching model,” Advances in Econometrics 31: 153 - 181, 2013
    • Web appendix
    • Matlab code
      
      
27. “Comment on “Social networks and the identification of peer effects” by Paul Goldsmith-Pinkham and Guido W. Imbens,” Journal of Business and Economic Statistics 31 (3): 266 - 270, 2013
    
    
28. “Identification and estimation of average partial effects in `irregular’ correlated random coefficient panel data models,” Econometrica 80 (5): 2105 - 2152, 2012 (w/ James Powell)
    • Web appendix
    • Data archive (Readme)
    • Estimation sample (comma delimited)
    • Matlab code archive
      
      
29. “Inverse probability tilting for moment condition models with missing data,” Review of Economic Studies 79 (3): 1053 - 1079, 2012 (w/ Cristine Pinto and Dan Egel)
    • Web appendix
    • Additional calculations
    • Replication instructions
    • MATLAB code documentation
    • Stata DCT file, Stata Do file, Matlab Code, Dataset (tab delimited), (MAT file)
    • Code for comparison Monte Carlos (Readme)
    • Code for higher order Monte Carlos (Readme)
    • Code for Average Treatment Effect (ATE) estimation (Readme)
      
      
30. “Econometric methods for the analysis of assignment problems in the presence of complementarity and social spillovers,” Handbook of Social Economics 1B: 965 - 1052 (J. Benhabib, A. Bisin, & M. Jackson, Eds.). Amsterdam: North-Holland, 2011
    • Last pre-publication version (typeset version has numerous typos)
    • Matlab code for Monte Carlo
    • Mathematica code for figures
    • Errata (correction of proof of Theorem 4.1)
      
      
31. “Efficiency bounds for missing data models with semiparametric restrictions,” Econometrica 79 (2): 437 - 452, 2011
    • Web appendix
    • Additional calculations
    • Earlier version (Appendix)
      
      
32. “Robustness to parametric assumptions in missing data models,” American Economic Review: Papers and Proceedings 101 (3): 538 - 543, 2011 (w/ Keisuke Hirano)
    • Matlab code
      
      
33. “The incidental parameter problem in a non-differentiable panel data model,” Economics Letters 105 (2): 181 - 182, 2009 (w/ Jinyong Hahn and Jim Powell)
    
    
34. “Identifying social interactions through conditional variance restrictions,” Econometrica 76 (3): 643 - 660, 2008
    • Web appendix
    • Stata file #1, #2, #3, #4; Matlab file #1, #2, #3
    • Dissertation version (May 2005)
      
      
35. “Rich nations, poor nations: how much can multiple equilibria explain,” Journal of Economic Growth 11 (1): 5 - 41, 2006 (w/ Jon Temple)
    • Data
    • Mathematica code for calibration results
    • Mathematica code for phase diagrams
      
      
36. “Identification and estimation of the linear-in-means model of social interactions,” Economics Letters 88 (1): 1 - 6, 2005 (w/ Jinyong Hahn)
    
    
37. “Longevity and life-cycle savings,” Scandinavian Journal of Economics 105 (3): 319 - 338, 2003 (w/ David Bloom and David Canning)