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Citations for "Combining Micro and Macro Data in Microeconometric Models"

by Imbens, G.W. & Lancaster, T.

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  1. del Bono, Emilia & Ermisch, John F & Francesconi, Marco, 2008. "Intrafamily Resource Allocations: A Dynamic Model of Birth Weight," CEPR Discussion Papers 6970, C.E.P.R. Discussion Papers.
  2. Guell, Maia & Hu, Luojia, 2006. "Estimating the probability of leaving unemployment using uncompleted spells from repeated cross-section data," Journal of Econometrics, Elsevier, vol. 133(1), pages 307-341, July.
  3. Judith K. Hellerstein & Guido W. Imbens, 1999. "Imposing Moment Restrictions From Auxiliary Data By Weighting," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 1-14, February.
  4. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
  5. Peter Arcidiacono & Holger Sieg & Frank Sloan, 2007. "Living Rationally Under The Volcano? An Empirical Analysis Of Heavy Drinking And Smoking," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(1), pages 37-65, 02.
  6. Anne-Gisèle Privat, 2005. "L'avenir des retraites en France: Evalutation de l'impact des réformes de 1993 et de 2033 à l'aide du modèle de microsimulation Artémis," Sciences Po publications info:hdl:2441/f4rshpf3v1u, Sciences Po.
  7. van Dijk, Bram & Paap, Richard, 2008. "Explaining individual response using aggregated data," Journal of Econometrics, Elsevier, vol. 146(1), pages 1-9, September.
  8. Ana María Ibañez Londoño & Juan Carlos Muñoz Mora & Philip Verwimp, 2013. "Abandoning Coffee under the Threat of Violence and the Presence of Illicit Crops. Evidence from Colombia," HiCN Working Papers 150, Households in Conflict Network.
  9. V. Smith & Subhrendu Pattanayak, 2002. "Is Meta-Analysis a Noah's Ark for Non-Market Valuation?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(1), pages 271-296, June.
  10. repec:eee:juecon:v:99:y:2017:i:c:p:48-61 is not listed on IDEAS
  11. Arthur Charpentier & Mathieu Pigeon, 2016. "Macro vs. Micro Methods in Non-Life Claims Reserving (an Econometric Perspective)," Risks, MDPI, Open Access Journal, vol. 4(2), pages 1-18, May.
  12. Lee, Seojeong, 2014. "Asymptotic refinements of a misspecification-robust bootstrap for generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 178(P3), pages 398-413.
  13. Anne-Gisèle Privat & Sophie Pennec & Thierry Debrand, 2003. "Un modèle de micro-simulation pour la projection des retraites du régime général," Économie et Prévision, Programme National Persée, vol. 160(4), pages 215-230.
  14. Heinz König & Michael Lechner, 1994. "Some Recent Developments in Microeconometrics - A Survey," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 130(III), pages 299-331, September.
  15. Laura Mayoral, 2013. "Heterogeneous Dynamics, Aggregation, And The Persistence Of Economic Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54, pages 1295-1307, November.
  16. repec:spr:stmapp:v:26:y:2017:i:2:d:10.1007_s10260-016-0367-6 is not listed on IDEAS
  17. Lancaster, Tony & Imbens, Guido, 1996. "Case-control studies with contaminated controls," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 145-160.
  18. Liu, Tianqing & Yuan, Xiaohui, 2012. "Combining quasi and empirical likelihoods in generalized linear models with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 39-58.
  19. Michael Rendall & Ryan Admiraal & Alessandra DeRose & Paola DiGiulio & Mark Handcock & Filomena Racioppi, 2008. "Population constraints on pooled surveys in demographic hazard modeling," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(4), pages 519-539, October.
  20. Amil Petrin, 2001. "Quantifying the Benefits of New Products: The Case of the Minivan," NBER Working Papers 8227, National Bureau of Economic Research, Inc.
  21. Devereux, Paul J. & Tripathi, Gautam, 2009. "Optimally combining censored and uncensored datasets," Journal of Econometrics, Elsevier, vol. 151(1), pages 17-32, July.
  22. Gad Allon & Awi Federgruen & Margaret Pierson, 2011. "How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 489-507, October.
  23. Steven Berry & James Levinsohn & Ariel Pakes, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
  24. Nikolas Mittag, 2013. "A Method Of Correcting For Misreporting Applied To The Food Stamp Program," Working Papers 13-28, Center for Economic Studies, U.S. Census Bureau.
  25. Brannlund, Runar & Nordstrom, Jonas, 2004. "Carbon tax simulations using a household demand model," European Economic Review, Elsevier, vol. 48(1), pages 211-233, February.
  26. Ichino, Andrea & Polo, Michele & Rettore, Enrico, 2003. "Are judges biased by labor market conditions?," European Economic Review, Elsevier, vol. 47(5), pages 913-944, October.
  27. Smith, V. Kerry & Pattanayak, Subhrendu K. & Van Houtven, George L., 2006. "Structural benefit transfer: An example using VSL estimates," Ecological Economics, Elsevier, vol. 60(2), pages 361-371, December.
  28. van den Berg, Gerard J. & van der Klaauw, Bas, 2001. "Combining micro and macro unemployment duration data," Journal of Econometrics, Elsevier, vol. 102(2), pages 271-309, June.
  29. de Roos, Nicolas & McKenzie, Jordi, 2014. "Cheap Tuesdays and the demand for cinema," International Journal of Industrial Organization, Elsevier, vol. 33(C), pages 93-109.
  30. Takahiro Hoshino & Ryosuke Igari, 2017. "Quasi-Bayesian Inference for Latent Variable Models with External Information: Application to generalized linear mixed models for biased data," Keio-IES Discussion Paper Series 2017-014, Institute for Economics Studies, Keio University.
  31. Lancaster, Tony, 1997. "Bayes WESML Posterior inference from choice-based samples," Journal of Econometrics, Elsevier, vol. 79(2), pages 291-303, August.
  32. Jayawardhana, Jayani, 2013. "Direct-to-consumer advertising and consumer welfare," International Journal of Industrial Organization, Elsevier, vol. 31(2), pages 164-180.
  33. Mora, Ricardo & Machado, Matilde P. & Carro, Jesús M., 2014. "Transmission of preferences and beliefs about female labor market participation : direct evidence on the role of mothers," UC3M Working papers. Economics we1421, Universidad Carlos III de Madrid. Departamento de Economía.
  34. Xiao, Wei, 2008. "The Competitive and Welfare Effects of New Product Introduction: The Case of Crystal Pepsi," Research Reports 149938, University of Connecticut, Food Marketing Policy Center.
  35. Manolis Galenianos & Alessandro Gavazza, 2017. "A Structural Model of the Retail Market for Illicit Drugs," American Economic Review, American Economic Association, vol. 107(3), pages 858-896, March.
  36. d'Haultfoeuille, Xavier, 2010. "A new instrumental method for dealing with endogenous selection," Journal of Econometrics, Elsevier, vol. 154(1), pages 1-15, January.
  37. Michael S. Rendall & Ryan Admiraal & Alessandra De Rose & Paola Di Giulio & Mark S. Handcock & Filomena Racioppi, 2006. "Population constraints on pooled surveys in demographic hazard modeling," MPIDR Working Papers WP-2006-039, Max Planck Institute for Demographic Research, Rostock, Germany.
  38. Berg, Gerard J. van den & Klaauw, Bas van der, 1998. "Combining micro and macro unemployment data," Serie Research Memoranda 0041, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  39. Ryosuke Igari & Takahiro Hoshino, 2017. "Bayesian Data Combination Approach for Repeated Durations under Unobserved Missing Indicators: Application to Interpurchase-Timing in Marketing," Keio-IES Discussion Paper Series 2017-015, Institute for Economics Studies, Keio University.
  40. Naoki Wakamori, 2011. "Portfolio Considerations in Differentiated Product Purchases: An Application to the Japanese Automobile Market," Staff Working Papers 11-27, Bank of Canada.
  41. Emilia Del Bono & John Ermisch & Marco Francesconi, 2012. "Intrafamily Resource Allocations: A Dynamic Structural Model of Birth Weight," Journal of Labor Economics, University of Chicago Press, vol. 30(3), pages 657-706.
  42. Brännlund, Runar & Nordström, Jonas, 2001. "Modelling Consumer Demand and Household Labour Supply: Welfare Effects of Increasing Carbon Taxes," Umeå Economic Studies 571, Umeå University, Department of Economics.
  43. F Bravo, 2008. "Effcient M-estimators with auxiliary information," Discussion Papers 08/26, Department of Economics, University of York.
  44. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," Review of Economic Studies, Oxford University Press, vol. 79(3), pages 1053-1079.
  45. Nevo, Aviv, 2003. "Using Weights to Adjust for Sample Selection When Auxiliary Information Is Available," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 43-52, January.
  46. Michael S. Rendall & Mark S. Handcock & Stefan H. Jonsson, 2007. "Bayesian Estimation of Hispanic Fertility Hazards from Survey and Population Data," Working Papers 496, RAND Corporation.
  47. Esmeralda A. Ramalho & Richard J. Smith, 2013. "Discrete Choice Non-Response," Review of Economic Studies, Oxford University Press, vol. 80(1), pages 343-364.
  48. Bayram, Deniz & Dayé, Modeste, 2014. "Asymptotic Properties of the Weighted Least Squares Estimator Under Moments Restriction," MPRA Paper 60465, University Library of Munich, Germany.
  49. Paulo Albuquerque & Bart J. Bronnenberg, 2009. "Estimating Demand Heterogeneity Using Aggregated Data: An Application to the Frozen Pizza Category," Marketing Science, INFORMS, vol. 28(2), pages 356-372, 03-04.
  50. Ramalho, Esmeralda A., 2002. "Regression models for choice-based samples with misclassification in the response variable," Journal of Econometrics, Elsevier, vol. 106(1), pages 171-201, January.
  51. Bruce Meyer & Nikolas Mittag, 2013. "Misclassification In Binary Choice Models," Working Papers 13-27, Center for Economic Studies, U.S. Census Bureau.
  52. Qian, Hailong & Schmidt, Peter, 1999. "Improved instrumental variables and generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 91(1), pages 145-169, July.
  53. Davis, Peter, 2000. "Empirical models of demand for differentiated products," European Economic Review, Elsevier, vol. 44(4-6), pages 993-1005, May.
  54. repec:spo:wpecon:info:hdl:2441/f4rshpf3v1umfa09lat214kj4 is not listed on IDEAS
  55. Philipson, Tomas & Malani, Anup, 1999. "Measurement errors: A principal investigator-agent approach," Journal of Econometrics, Elsevier, vol. 91(2), pages 273-298, August.
  56. repec:sbe:breart:v:26:y:2006:i:2:a:1577 is not listed on IDEAS
  57. Yuan, Xiaohui & Liu, Tianqing & Lin, Nan & Zhang, Baoxue, 2010. "Combining conditional and unconditional moment restrictions with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2420-2433, November.
  58. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Multivariate Extreme Value (MEV) models," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 31-52.
  59. d'Haultfoeuille, Xavier, 2010. "A new instrumental method for dealing with endogenous selection," Journal of Econometrics, Elsevier, vol. 154(1), pages 1-15, January.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.