The interpretation of 2SLS with a continuous instrument: A weighted LATE representation

被引:0
作者
Alvarez, Luis A. F. [1 ]
Toneto, Rodrigo [2 ]
机构
[1] Univ Sao Paulo, BR-05508010 Sao Paulo, Brazil
[2] Queen Mary Univ London, London E14NS, England
基金
巴西圣保罗研究基金会;
关键词
Instrumental variables; Local average treatment effects; Underlying weights; VARIABLES; MODELS; IDENTIFICATION; EQUATIONS; DEMAND;
D O I
10.1016/j.econlet.2024.111658
中图分类号
F [经济];
学科分类号
02 ;
摘要
This note introduces a novel weighted local average treatment effect representation for the two -stages leastsquares (2SLS) estimand in the continuous instrument with binary treatment case. Under standard conditions, we obtain weights that are nonnegative, integrate to unity, and assign larger values to instrument support points that deviate from their average. Our representation does not require instruments to be discretized nor relies on limiting arguments, such as those used in the definition of the marginal treatment effect (MTE). The pattern of the weights also has a clear interpretation. We believe these features of the representation to be useful for applied researchers when communicating their results. As a direct byproduct of our approach, we also obtain a representation of the 2SLS estimand as a weighted average of treatment effects among "marginal compliance"groups, without having to resort to the threshold -crossing representation underlying the MTE construction. The latter representation has an intuitive interpretation as well.
引用
收藏
页数:4
相关论文
共 23 条
  • [11] From LATE to MTE: Alternative methods for the evaluation of policy interventions
    Cornelissen, Thomas
    Dustmann, Christian
    Raute, Anna
    Schonberg, Uta
    [J]. LABOUR ECONOMICS, 2016, 41 : 47 - 60
  • [12] Coussens S, 2021, Arxiv, DOI arXiv:2108.03726
  • [13] Escanciano J.C., 2023, Robust identification in regression discontinuity designs with covariates
  • [14] Goldsmith-Pinkham P., 2024, Contamination bias in linear regressions
  • [15] Understanding instrumental variables in models with essential heterogeneity
    Heckman, James J.
    Urzua, Sergio
    Vytlacil, Edward
    [J]. REVIEW OF ECONOMICS AND STATISTICS, 2006, 88 (03) : 389 - 432
  • [16] Unordered Monotonicity
    Heckman, James J.
    Pinto, Rodrigo
    [J]. ECONOMETRICA, 2018, 86 (01) : 1 - 35
  • [17] Structural equations, treatment effects, and econometric policy evaluation
    Heckman, JJ
    Vytlacil, E
    [J]. ECONOMETRICA, 2005, 73 (03) : 669 - 738
  • [18] Instrumental Variables: An Econometrician's Perspective
    Imbens, Guido W.
    [J]. STATISTICAL SCIENCE, 2014, 29 (03) : 323 - 358
  • [19] IDENTIFICATION AND ESTIMATION OF LOCAL AVERAGE TREATMENT EFFECTS
    IMBENS, GW
    ANGRIST, JD
    [J]. ECONOMETRICA, 1994, 62 (02) : 467 - 475
  • [20] Michal Kolesar, 2013, ESTIMATION INS UNPUB