Latent Agents in Networks: Estimation and Targeting

References

• Angelucci M, De Giorgi G, Rasul I (2018) Consumption and investment in resource pooling family networks. Econom. J. (London) 128(615):2613–2651.Google Scholar
• Ata B, Belloni A, Candogan O (2020) Estimating influence structure in networks with latent agents. Working paper, University of Chicago, Chicago.Google Scholar
• Ballester C, Calvó-Armengol A, Zenou Y (2006) Who’s who in networks. Wanted: The key player. Econometrica 74(5):1403–1417.Crossref, Google Scholar
• Bastani H (2021) Predicting with proxies: Transfer learning in high dimension. Management Sci. 67(5):2964–2984.Link, Google Scholar
• Bellec PC, Lecué G, Tsybakov AB (2018) Slope meets LASSO: Improved oracle bounds and optimality. Ann. Statist. 46(6B):3603–3642.Crossref, Google Scholar
• Belloni A, Oliveira RI (2018) A high dimensional Central Limit Theorem for martingales, with applications to context tree models. Preprint, submitted September 8, https://arxiv.org/abs/1809.02741.Google Scholar
• Belloni A, Chernozhukov V, Hansen C (2014a) Inference on treatment effects after selection amongst high-dimensional controls. Rev. Econom. Stud. 81(2):608–650.Crossref, Google Scholar
• Belloni A, Chernozhukov V, Kato K (2015) Uniform post model selection inference for LAD regression models. Biometrika 102(1):77–94.Crossref, Google Scholar
• Belloni A, Chernozhukov V, Wang L (2014b) Pivotal estimation via square-root LASSO in nonparametric regression. Ann. Statist. 42(2):757–788.Crossref, Google Scholar
• Belloni A, Deng C, Pekec S (2016) Mechanism and network design with private negative externalities. Oper. Res. 65(3):577–594.Link, Google Scholar
• Belloni A, Chen D, Chernozhukov V, Hansen C (2012) Sparse models and methods for optimal instruments with an application to eminent domain. Econometrica 80(6):2369–2429.Crossref, Google Scholar
• Belloni A, Chernuzhukov V, Hansen C, Newey W (2022) High-dimensional linear models with many endogenous variables. J. Econometrics 228(1):4–26.Google Scholar
• Belloni A, Chernozhukov V, Kaul A, Rosenbaum M, Tsybakov AB (2017) Pivotal estimation via self-normalization for high-dimensional linear models with error in variables. Preprint, submitted August 28, https://arxiv.org/abs/1708.08353.Google Scholar
• Benedetto J, Powell A (2006) A (p, q) version of Bourgain’s theorem. Trans. Amer. Math. Soc. 358(6):2489–2505.Crossref, Google Scholar
• Benzi M, Razouk N (2007) Decay bounds and o (n) algorithms for approximating functions of sparse matrices. Electronic Trans. Numerical Anal. 28:16–39.Google Scholar
• Besbes O, Zeevi A (2015) On the (surprising) sufficiency of linear models for dynamic pricing with demand learning. Management Sci. 61(4):723–739.Link, Google Scholar
• Bickel PJ, Ritov Y, Tsybakov AB (2009) Simultaneous analysis of LASSO and Dantzig selector. Ann. Statist. 37(4):1705–1732.Crossref, Google Scholar
• Bifulco R, Fletcher JM, Ross SL (2011) The effect of classmate characteristics on post-secondary outcomes: Evidence from the add health. Amer. Econom. J. Econom. Policy 3(1):25–53.Crossref, Google Scholar
• Bimpikis K, Ozdaglar A, Yildiz E (2016) Competitive targeted advertising over networks. Oper. Res. 64(3):705–720.Link, Google Scholar
• Bisin A, Moro A, Topa G (2011) The empirical content of models with multiple equilibria in economies with social interactions. Technical report, National Bureau of Economic Research, Cambridge, MA.Google Scholar
• Blume LE, Brock WA, Durlauf SN, Jayaraman R (2015) Linear social interactions models. J. Political Econom. 123(2):444–496.Crossref, Google Scholar
• Boucher V, Bramoullé Y, Djebbari H, Fortin B (2014) Do peers affect student achievement? Evidence from Canada using group size variation. J. Appl. Econometrics 29(1):91–109.Crossref, Google Scholar
• Bramoullé Y, Djebbari H, Fortin B (2009) Identification of peer effects through social networks. J. Econometrics 150(1):41–55.Crossref, Google Scholar
• Calvó-Armengol A, Patacchini E, Zenou Y (2009) Peer effects and social networks in education. Rev. Econom. Stud. 76(4):1239–1267.Crossref, Google Scholar
• Campbell A (2013) Word-of-mouth communication and percolation in social networks. Amer. Econom. Rev. 103(6):2466–2498.Crossref, Google Scholar
• Candès E, Tao T (2007) The Dantzig selector: Statistical estimation when p is much larger than n. Ann. Statist. 35(6):2313–2351.Crossref, Google Scholar
• Candogan O, Bimpikis K, Ozdaglar A (2012) Optimal pricing in networks with externalities. Oper. Res. 60(4):883–905.Link, Google Scholar
• Chen X, Shao Q-M, Wei BW, Xu L (2016) Self-normalized Cramér-type moderate deviations under dependence. Ann. Statist. 44(4):1593–1617.Crossref, Google Scholar
• Chernozhukov V, Chetverikov D, Kato K (2013) Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors. Ann. Statist. 41(6):2786–2819.Crossref, Google Scholar
• Chernozhukov V, Chetverikov D, Kato K (2019) Inference on Causal and Structural Parameters using Many Moment Inequalities. R. Econom. Stud. 86(5):1867–1900.Google Scholar
• Chernozhukov V, Chetverikov D, Kato K (2014b) Gaussian approximation of suprema of empirical processes. Ann. Statist. 42(4):1564–1597.Crossref, Google Scholar
• De Giorgi G, Frederiksen A, Pistaferri L (2020) Consumption network effects. Rev. Econom. Stud. 87(1):130–163.Crossref, Google Scholar
• De Giorgi G, Pellizzari M, Redaelli S (2010) Identification of social interactions through partially overlapping peer groups. Amer. Econom. J. Appl. Econom. 2(2):241–275.Crossref, Google Scholar
• De Paula A (2015) Econometrics of network models. Unpublished manuscript, University College London, London.Google Scholar
• De Paula A (2017) Econometrics of network models. Honoré B, Pakes A, Piazzesi M, Samuelson L, eds. Adv. Econom. Econometrics Theory Appl. 11th World Congress (Cambridge University Press, Cambridge, UK), 268–323.Google Scholar
• De Paula Á, Rasul I, Souza P (2019) Identifying network ties from panel data: Theory and an application to tax competition. Preprint, submitted October 16, https://arxiv.org/abs/1910.07452.Google Scholar
• Demko S, Moss WF, Smith PW (1984) Decay rates for inverses of band matrices. Math. Comput. 43(168):491–499.Crossref, Google Scholar
• Dubé J-P, Manchanda P (2005) Differences in dynamic brand competition across markets: An empirical analysis. Marketing Sci. 24(1):81–95.Link, Google Scholar
• Epple D, Romano R (2011) Peer effects in education: A survey of the theory and evidence. Handbook Social Econom. 1(11):1053–1163.Crossref, Google Scholar
• Facebook for Business (2020a) About custom audiences from customer lists. Accessed December 7, 2020, https://www.facebook.com/business/help/341425252616329.Google Scholar
• Facebook for Business (2020b) About offer ads. Accessed December 7, 2020, https://www.facebook.com/business/help/374943579189527.Google Scholar
• Facebook for Business (2020c) Upload unique promo codes and barcodes to your offer ad. Accessed December 7, 2020, https://www.facebook.com/business/help/1181893525262443.Google Scholar
• Fainmesser IP, Galeotti A (2015) Pricing network effects. Rev. Econom. Stud. 83(1):165–198.Crossref, Google Scholar
• Fletcher JM (2010) Social interactions and smoking: Evidence using multiple student cohorts, instrumental variables, and school fixed effects. Health Econom. 19(4):466–484.Crossref, Google Scholar
• Fletcher JM (2012) Peer influences on adolescent alcohol consumption: Evidence using an instrumental variables/fixed effect approach. J. Population Econom. 25(4):1265–1286.Crossref, Google Scholar
• Galeotti A, Goyal S, Jackson MO, Vega-Redondo F, Yariv L (2010) Network games. Rev. Econom. Stud. 77(1):218–244.Crossref, Google Scholar
• Gautier E, Tsybakov A (2014) High-dimensional instrumental variables regression and confidence sets. Technical report, HAL. https://hal.science/hal-00591732v7.Google Scholar
• Golub GH, Van Loan CF (2012) Matrix Computations, vol. 3 (JHU Press).Google Scholar
• Gröchenig K, Klotz A (2010) Noncommutative approximation: Inverse-closed subalgebras and off-diagonal decay of matrices. Constructive Approximation 32(3):429–466.Crossref, Google Scholar
• Gröchenig K, Klotz A (2014) Norm-controlled inversion in smooth banach algebras, ii. Mathematische Nachrichten 287(8-9):917–937.Google Scholar
• Harrison JM, Keskin NB, Zeevi A (2012) Bayesian dynamic pricing policies: Learning and earning under a binary prior distribution. Management Sci. 58(3):570–586.Link, Google Scholar
• Hartline J, Mirrokni V, Sundararajan M (2008) Optimal marketing strategies over social networks. Proc. 17th Internat. Conf. World Wide Web (ACM, New York), 189–198.Google Scholar
• Instagram Business (2016) Reaching your customers on Instagram. Accessed December 7, 2020, https://business.instagram.com/blog/targeting-instagram-ads.Google Scholar
• Jaffard S (1990) Propriétés des matrices <<bien localisées>> près de leur diagonale et quelques applications. Annales de l’Institut Henri Poincare Nonlinear Anal., vol. 7 (Elsevier, Amsterdam), 461–476.Google Scholar
• Javanmard A, Montanari A (2014) Confidence intervals and hypothesis testing for high-dimensional regression. J. Machine Learn. Res. 15(1):2869–2909.Google Scholar
• Keskin NB, Zeevi A (2014) Dynamic pricing with an unknown demand model: Asymptotically optimal semi-myopic policies. Oper. Res. 62(5):1142–1167.Link, Google Scholar
• Kleinberg J (2000) The small-world phenomenon: An algorithmic perspective. Proc. 32nd Annual ACM Sympos. Theory Comput. (ACM, New York), 163–170.Google Scholar
• Koltchinskii V, Lounici K, Tsybakov AB (2011) Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion. Ann. Statist. 39(5):2302–2329.Crossref, Google Scholar
• König MD, Liu X, Zenou Y (2019) R&D networks: Theory, empirics, and policy implications. Rev. Econom. Stat. 101(3):476–491.Crossref, Google Scholar
• Lilien GL, Kotler P, Moorthy KS (1995) Marketing Models (Prentice Hall).Google Scholar
• Lin X (2010) Identifying peer effects in student academic achievement by spatial autoregressive models with group unobservables. J. Labor Econom. 28(4):825–860.Crossref, Google Scholar
• Lindquist MJ, Zenou Y (2014) Key players in co-offending networks. Preprint, submitted March, 15, https://dx.doi.org/10.2139/ssrn.2409534.Google Scholar
• Liu X, Patacchini E, Zenou Y, Lee LF (2012) Criminal networks: Who is the key player? Preprint, submitted June 23, https://dx.doi.org/10.2139/ssrn.2089267.Google Scholar
• Lobel I, Sadler ED, Varshney LR (2016) Customer referral incentives and social media. Management Sci. 63(10):3514–3529.Google Scholar
• Manchanda P, Dubé JP, Goh KY, Chintagunta PK (2006) The effect of banner advertising on internet purchasing. J. Marketing Res. 43(1):98–108.Crossref, Google Scholar
• Manresa E (2013) Estimating the structure of social interactions using panel data. Unpublished manuscript, CEMFI, Madrid.Google Scholar
• Manski CF (1993) Identification of endogenous social effects: The reflection problem. Rev. Econom. Stud. 60(3):531–542.Crossref, Google Scholar
• Meinardus G (2012) Approximation of Functions: Theory and Numerical Methods, vol. 13 (Springer Science & Business Media, New York).Google Scholar
• Negahban S, Wainwright MJ (2011) Estimation of (near) low-rank matrices with noise and high-dimensional scaling. Ann. Statist. 32(9):1069–1097.Google Scholar
• Neyman J (1979) c(α) tests and their use. Sankhya 41:1–21.Google Scholar
• Neyman J, Scott EL (1965) On the use of C (a) optimal tests of composite hypotheses. Bull. Inst. Internat. Statist. 41:476–495.Google Scholar
• Patacchini E, Zenou Y (2012a) Ethnic networks and employment outcomes. Regional Sci. Urban Econom. 42(6):938–949.Crossref, Google Scholar
• Patacchini E, Zenou Y (2012b) Juvenile delinquency and conformism. J. Law Econom. Organ. 28(1):1–31.Crossref, Google Scholar
• Patacchini E, Rainone E, Zenou Y (2017) Heterogeneous peer effects in education. J. Econom. Behav. Organ. 134:190–227.Crossref, Google Scholar
• Raskutti G, Wainwright MJ, Yu B (2011) Minimax rates of estimation for high-dimensional linear regression over ℓq-balls. IEEE Trans. Inform. Theory 57(10):6976–6994.Crossref, Google Scholar
• Rose CD (2017) Identification of peer effects through social networks using variance restrictions. Econom. J. 20(3):S47–S60.Crossref, Google Scholar
• Sacerdote B (2001) Peer effects with random assignment: Results for Dartmouth roommates. Quart. J. Econom. 116(2):681–704.Crossref, Google Scholar
• Slade ME (1995) Product rivalry with multiple strategic weapons: An analysis of price and advertising competition. J. Econom. Management Strategy 4(3):445–476.Crossref, Google Scholar
• Topa G, Zenou Y (2015) Neighborhood and network effects. Handbook of Regional and Urban Economics, vol. 5 (Elsevier, Amsterdam), 561–624.Google Scholar
• Tudón J (2022) Distilling network effects from steam. Quantitative Marketing Econom. 20:293–312.Crossref, Google Scholar
• Twitter Business (2020) Intro to custom audiences. Accessed December 7, 2020, https://business.twitter.com/en/help/campaign-setup/campaign-targeting/custom-audiences.html.Google Scholar
• Ugander J, Karrer B, Backstrom L, Marlow C (2011) The anatomy of the facebook social graph. Preprint, submitted November 18, https://arxiv.org/abs/1111.4503.Google Scholar
• Van de Geer S, Bühlmann P, Ya’acov R, Dezeure R (2014) On asymptotically optimal confidence regions and tests for high-dimensional models. Ann. Statist. 42(3):1166–1202.Crossref, Google Scholar
• Watts DJ, Strogatz SH (1998) Collective dynamics of “small-world” networks. Nature 393(6684):440–442.Crossref, Google Scholar
• Xu K, Zhao X, Bastani H, Bastani O (2021) Group-sparse matrix factorization for transfer learning of word embeddings. Internat. Conf. Machine Learn. (PMLR), 11603–11612.Google Scholar
• Zhang C-H, Zhang SS (2014) Confidence intervals for low-dimensional parameters with high-dimensional data. J. Roy. Statist. Soc. B 76(1):217–242.Crossref, Google Scholar
• Zhang D, Wu WB (2017) Gaussian approximation for high dimensional time series. Ann. Statist. 45(5):1895–1919.Crossref, Google Scholar
• Zhang X, Cheng G (2014) Bootstrapping high dimensional time series. Unpublished working paper. Texas A&M University, College Station, TX.Google Scholar
• Zhang Y, Chen Y-J (2020) Optimal nonlinear pricing in social networks under asymmetric network information. Oper. Res. 68(3):818–833.Google Scholar
• Zhou J, Chen Y-J (2015) Key leaders in social networks. J. Econom. Theory 157:212–235.Crossref, Google Scholar
• Zhou J, Chen Y-J (2016) Targeted information release in social networks. Oper. Res. 64(3):721–735.Link, Google Scholar
• Zhu Y, Bradic J (2018) Significance testing in non-sparse high-dimensional linear models. Electron. J. Statist. 12(2):3312–3364.Google Scholar