empirical-methods.bib

@article{abadie2003economic,
  title={The economic costs of conflict: A case study of the Basque Country},
  author={Abadie, Alberto and Gardeazabal, Javier},
  journal={American economic review},
  volume={93},
  number={1},
  pages={113--132},
  year={2003}
}

@article{abadie2010synthetic,
  title={Synthetic control methods for comparative case studies: Estimating the effect of California's tobacco control program},
  author={Abadie, Alberto and Diamond, Alexis and Hainmueller, Jens},
  journal={Journal of the American statistical Association},
  volume={105},
  number={490},
  pages={493--505},
  year={2010},
  publisher={Taylor \& Francis}
}

@article{athey2017state,
  title={The state of applied econometrics: Causality and policy evaluation},
  author={Athey, Susan and Imbens, Guido W},
  journal={Journal of Economic Perspectives},
  volume={31},
  number={2},
  pages={3--32},
  year={2017}
}

@techreport{athey2016efficient,
  title={Efficient inference of average treatment effects in high dimensions via approximate residual balancing},
  author={Athey, Susan and Imbens, Guido W and Wager, Stefan and others},
  year={2016}
}


@article{AtheyImbensJEP2017,
Author = {Athey, Susan and Imbens, Guido W.},
Title = {The State of Applied Econometrics: Causality and Policy Evaluation},
Journal = {Journal of Economic Perspectives},
Volume = {31},
Number = {2},
Year = {2017},
Month = {May},
Pages = {3-32},
DOI = {10.1257/jep.31.2.3},
URL = {http://www.aeaweb.org/articles?id=10.1257/jep.31.2.3}
}


@techreport{belloni2015program,
  title={Program evaluation with high-dimensional data},
  author={Belloni, Alexandre and Chernozhukov, Victor and Fern{\'a}ndez-Val, Ivan and Hansen, Christian},
  year={2015},
  institution={cemmap working paper, Centre for Microdata Methods and Practice}
}


@article{belloni2012sparse,
  title={Sparse models and methods for optimal instruments with an application to eminent domain},
  author={Belloni, Alexandre and Chen, Daniel and Chernozhukov, Victor and Hansen, Christian},
  journal={Econometrica},
  volume={80},
  number={6},
  pages={2369--2429},
  year={2012},
  publisher={Wiley Online Library}
}

@article{carneiro2011estimating,
  title={Estimating marginal returns to education},
  author={Carneiro, Pedro and Heckman, James J and Vytlacil, Edward J},
  journal={American Economic Review},
  volume={101},
  number={6},
  pages={2754--81},
  year={2011}
}

@article{cornelissen2016late,
  title={From LATE to MTE: Alternative methods for the evaluation of policy interventions},
  author={Cornelissen, Thomas and Dustmann, Christian and Raute, Anna and Sch{\"o}nberg, Uta},
  journal={Labour Economics},
  volume={41},
  pages={47--60},
  year={2016},
  publisher={Elsevier}
}

@article{DobbieGoldinYangBail,
Author = {Dobbie, Will and Goldin, Jacob and Yang, Crystal S.},
Title = {The Effects of Pretrial Detention on Conviction, Future Crime, and Employment: Evidence from Randomly Assigned Judges},
Journal = {American Economic Review},
Volume = {108},
Number = {2},
Year = {2018},
Month = {February},
Pages = {201-40},
DOI = {10.1257/aer.20161503},
URL = {http://www.aeaweb.org/articles?id=10.1257/aer.20161503}
}

@techreport{DoudchenkoImbensSynth,
 title = "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis",
 author = "Doudchenko, Nikolay and Imbens, Guido W",
 institution = "National Bureau of Economic Research",
 type = "Working Paper",
 series = "Working Paper Series",
 number = "22791",
 year = "2016",
 month = "October",
 doi = {10.3386/w22791},
 URL = "http://www.nber.org/papers/w22791",
 abstract = {In a seminal paper Abadie et al (2010) develop the synthetic control procedure for estimating the effect of a treatment, in the presence of a single treated unit and a number of control units, with pre-treatment outcomes observed for all units. The method constructs a set of weights such that covariates and  pre-treatment outcomes of the treated unit are approximately matched by a weighted average of control units. The weights are  restricted to be nonnegative and sum to one, which allows the procedure to obtain the weights even when the number of lagged outcomes is modest relative to the number of control units, a setting that is not uncommon in applications.  In the current paper we propose a more general class of synthetic control estimators that allows researchers to relax some of the restrictions in the ADH method. We allow the weights to be negative, do not necessarily restrict the sum of the weights, and allow for a permanent additive difference between the treated unit and the controls, similar to difference-in-difference procedures. The weights directly minimize the distance between the lagged outcomes for the treated and the control units, using regularization methods to deal with a potentially large number of possible control units.},
}

@article{heckman2005structural,
  title={Structural equations, treatment effects, and econometric policy evaluation 1},
  author={Heckman, James J and Vytlacil, Edward},
  journal={Econometrica},
  volume={73},
  number={3},
  pages={669--738},
  year={2005},
  publisher={Wiley Online Library}
}

@article{heckman2007econometric,
  title={Econometric evaluation of social programs, part II: Using the marginal treatment effect to organize alternative econometric estimators to evaluate social programs, and to forecast their effects in new environments},
  author={Heckman, James J and Vytlacil, Edward J},
  journal={Handbook of econometrics},
  volume={6},
  pages={4875--5143},
  year={2007},
  publisher={Elsevier}
}

@article {KingNielsonPSM,
	title = {Why Propensity Scores Should Not Be Used for Matching},
	journal = {Political Analysis},
	year = {Forthcoming},
	abstract = {We show that propensity score matching (PSM), an enormously popular method of preprocessing data for causal inference, often accomplishes the opposite of its intended goal --- thus increasing imbalance, inefficiency, model dependence, and bias. The weakness of PSM comes from its attempts to approximate a completely randomized experiment, rather than, as with other matching methods, a more efficient fully blocked randomized experiment. PSM is thus uniquely blind to the often large portion of imbalance that can be eliminated by approximating full blocking with other matching methods. Moreover, in data balanced enough to approximate complete randomization, either to begin with or after pruning some observations, PSM approximates random matching which, we show, increases imbalance even relative to the original data. Although these results suggest researchers replace PSM with one of the other available matching methods, propensity scores have other productive uses.},
	author = {Gary King and Richard Nielsen}
}

@article{imbens2015matching,
  title={Matching methods in practice: Three examples},
  author={Imbens, Guido W},
  journal={Journal of Human Resources},
  volume={50},
  number={2},
  pages={373--419},
  year={2015},
  publisher={University of Wisconsin Press}
}

@article{AbadieCattaneoAnRev2018,
author = {Abadie, Alberto and Cattaneo, Matias D.},
title = {Econometric Methods for Program Evaluation},
journal = {Annual Review of Economics},
volume = {10},
number = {1},
pages = {465-503},
year = {2018},
doi = {10.1146/annurev-economics-080217-053402},

URL = { 
        https://doi.org/10.1146/annurev-economics-080217-053402
    
},
eprint = { 
        https://doi.org/10.1146/annurev-economics-080217-053402
    
}
,
    abstract = { Program evaluation methods are widely applied in economics to assess the effects of policy interventions and other treatments of interest. In this article, we describe the main methodological frameworks of the econometrics of program evaluation. In the process, we delineate some of the directions along which this literature is expanding, discuss recent developments, and highlight specific areas where new research may be particularly fruitful. }
}


@techreport{baxter2017robust,
  title={Robust Determinants of Bilateral Trade},
  author={Baxter, Marianne},
  year={2017},
  institution={Society for Economic Dynamics}
}

@article{belloniJEP,
Author = {Belloni, Alexandre and Chernozhukov, Victor and Hansen, Christian},
Title = {High-Dimensional Methods and Inference on Structural and Treatment Effects},
Journal = {Journal of Economic Perspectives},
Volume = {28},
Number = {2},
Year = {2014},
Month = {May},
Pages = {29-50},
DOI = {10.1257/jep.28.2.29},
URL = {http://www.aeaweb.org/articles?id=10.1257/jep.28.2.29}}

@book{friedman2001elements,
  title={The elements of statistical learning},
  author={Friedman, Jerome and Hastie, Trevor and Tibshirani, Robert},
  volume={1},
  number={10},
  year={2001},
  publisher={Springer series in statistics New York, NY, USA:}
}

@article{hansen1982generalized,
  title={Generalized instrumental variables estimation of nonlinear rational expectations models},
  author={Hansen, Lars Peter and Singleton, Kenneth J},
  journal={Econometrica: Journal of the Econometric Society},
  pages={1269--1286},
  year={1982},
  publisher={JSTOR}
}

@article{robinson_root-n-consistent_1988,
  title = {Root-{{N}}-{{Consistent Semiparametric Regression}}},
  volume = {56},
  issn = {0012-9682},
  doi = {10.2307/1912705},
  abstract = {[One type of semiparametric regression on an $<$tex-math$>$\$$\backslash$scr\{R\}\^\{p\}$\backslash$times $\backslash$scr\{R\}\^\{q\}$\backslash$text\{-valued\}\$$<$/tex-math$>$ random variable (X, Z) is $\beta{'}$X + \texttheta{}(Z), where $\beta$ and \texttheta{}(Z) are an unknown slope coefficient vector and function, and X is neither wholly dependent on Z nor necessarily independent of it. Estimators of $\beta$ based on incorrect parameterization of \texttheta{} are generally inconsistent, whereas consistent nonparametric estimators deviate from $\beta$ by a larger probability order than N\textsuperscript{-1/2}, where N is sample size. An estimator generalizing the ordinary least squares estimator of $\beta$ is constructed by inserting nonparametric regression estimators in the nonlinear orthogonal projection on Z. Under regularity conditions $\beta$\^ is shown to be $<$tex-math$>$\$N\^\{1/2\}$\backslash$text\{-consistent\}\$$<$/tex-math$>$ for $\beta$ and asymptotically normal, and a consistent estimator of its limiting covariance matrix is given, affording statistical inference that is not only asymptotically valid but has nonzero asymptotic first-order efficiency relative to estimators based on a correctly parameterized \texttheta. We discuss the identification problem and $\beta$\^'s efficiency, and report results of a Monte Carlo study of finite-sample performance. While the paper focuses on the simplest interesting setting of multiple regression with independent observations, extensions to other econometric models are described, in particular seemingly unrelated and nonlinear regressions, simultaneous equations, distributed lags, and sample selectivity models.]},
  number = {4},
  journal = {Econometrica},
  author = {Robinson, P. M.},
  year = {1988},
  pages = {931-954}
}

@article{guerre_optimal_2000,
  title = {Optimal {{Nonparametric Estimation}} of {{First}}-Price {{Auctions}}},
  volume = {68},
  copyright = {Econometric Society 2000},
  issn = {1468-0262},
  doi = {10.1111/1468-0262.00123},
  abstract = {This paper proposes a general approach and a computationally convenient estimation procedure for the structural analysis of auction data. Considering first-price sealed-bid auction models within the independent private value paradigm, we show that the underlying distribution of bidders' private values is identified from observed bids and the number of actual bidders without any parametric assumptions. Using the theory of minimax, we establish the best rate of uniform convergence at which the latent density of private values can be estimated nonparametrically from available data. We then propose a two-step kernel-based estimator that converges at the optimal rate.},
  language = {en},
  number = {3},
  journal = {Econometrica},
  author = {Guerre, Emmanuel and Perrigne, Isabelle and Vuong, Quang},
  year = {2000},
  keywords = {First-price auctions,independent private value,kernel estimation,minimax theory.,nonparametric identification,two-stage nonparametric estimation},
  pages = {525-574},
  file = {C:\\Users\\sweeneri\\Zotero\\storage\\4JKN7HXA\\Guerre et al_2000_Optimal Nonparametric Estimation of First-price Auctions.pdf;C:\\Users\\sweeneri\\Zotero\\storage\\GFSNFC2G\\1468-0262.html}
}

@incollection{powell_chapter_1994,
  title = {Chapter 41 {{Estimation}} of Semiparametric Models},
  volume = {4},
  abstract = {A semiparametric model for observational data combines a parametric form for some component of the data generating process (usually the behavioral relation between the dependent and explanatory variables) with weak nonparametric restrictions on the remainder of the model (usually the distribution of the unobservable errors). This chapter surveys some of the recent literature on semiparametric methods, emphasizing microeconometric applications using limited dependent variable models. An introductory section defines semiparametric models more precisely and reviews the techniques used to derive the large-sample properties of the corresponding estimation methods. The next section describes a number of weak restrictions on error distributions \textemdash{} conditional mean, conditional quantile, conditional symmetry, independence, and index restrictions \textemdash{} and show how they can be used to derive identifying restrictions on the distributions of observables. This general discussion is followed by a survey of a number of specific estimators proposed for particular econometric models, and the chapter concludes with a brief account of applications of these methods in practice.},
  booktitle = {Handbook of {{Econometrics}}},
  publisher = {{Elsevier}},
  author = {Powell, James L.},
  month = jan,
  year = {1994},
  pages = {2443-2521},
  file = {C:\\Users\\sweeneri\\Zotero\\storage\\WBWGL496\\Powell_1994_Chapter 41 Estimation of semiparametric models.pdf;C:\\Users\\sweeneri\\Zotero\\storage\\H9S5A6FW\\S1573441205800108.html},
  doi = {10.1016/S1573-4412(05)80010-8}
}

@misc{noauthor_semiparametric_nodate,
  title = {Semiparametric Regression Applied Econometrician | {{Econometrics}}, Statistics and Mathematical Economics},
  language = {en},
  journal = {Cambridge University Press},
  howpublished = {https://www.cambridge.org/us/academic/subjects/economics/econometrics-statistics-and-mathematical-economics/semiparametric-regression-applied-econometrician, https://www.cambridge.org/us/academic/subjects/economics/econometrics-statistics-and-mathematical-economics/semiparametric-regression-applied-econometrician},
  file = {C:\\Users\\sweeneri\\Zotero\\storage\\YYRAAYS4\\semiparametric-regression-applied-econometrician.html}
}

@article{lewbel2012comparing,
  title={Comparing features of convenient estimators for binary choice models with endogenous regressors},
  author={Lewbel, Arthur and Dong, Yingying and Yang, Thomas Tao},
  journal={Canadian Journal of Economics/Revue canadienne d'{\'e}conomique},
  volume={45},
  number={3},
  pages={809--829},
  year={2012},
  publisher={Wiley Online Library}
}

@article{dong2015simple,
  title={A simple estimator for binary choice models with endogenous regressors},
  author={Dong, Yingying and Lewbel, Arthur},
  journal={Econometric Reviews},
  volume={34},
  number={1-2},
  pages={82--105},
  year={2015},
  publisher={Taylor \& Francis}
}

@article{ai2003interaction,
  title={Interaction terms in logit and probit models},
  author={Ai, Chunrong and Norton, Edward C},
  journal={Economics letters},
  volume={80},
  number={1},
  pages={123--129},
  year={2003},
  publisher={Elsevier}
}