# Alberto Abadie's research while affiliated with Massachusetts Institute of Technology and other places

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## Publications (63)

In this article we propose a set of simple principles to guide empirical practice in synthetic control studies. The proposed principles follow from formal properties of synthetic control estimators, and pertain to the nature, implications, and prevention of over-fitting biases within a synthetic control framework, to the interpretability of the res...

Synthetic control methods are commonly applied in empirical research to estimate the effects of treatments or interventions on aggregate outcomes. A synthetic control estimator compares the outcome of a treated unit to the outcome of a weighted average of untreated units that best resembles the characteristics of the treated unit before the interve...

This article studies experimental design in settings where the experimental units are large aggregate entities (e.g., markets), and only one or a small number of units can be exposed to the treatment. In such settings, randomization of the treatment may induce large estimation biases under many or all possible treatment assignments. We propose a va...

Probably because of their interpretability and transparent nature, synthetic controls have become widely applied in empirical research in economics and the social sciences. This article aims to provide practical guidance to researchers employing synthetic control methods. The article starts with an overview and an introduction to synthetic control...

Nearest-neighbor matching is a popular nonparametric tool to create balance between treatment and control groups in observational studies. As a preprocessing step before regression, matching reduces the dependence on parametric modeling assumptions. In current empirical practice, however, the matching step is often ignored in the calculation of sta...

Many settings in empirical economics involve estimation of a large number of parameters. In such settings, methods that combine regularized estimation and data-driven choices of regularization parameters are useful. We provide guidance to applied researchers on the choice between regularized estimators and data-driven selection of regularization pa...

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 re...

Policymakers are often interested in estimating how policy interventions affect the outcomes of those most in need of help. This concern has motivated the practice of disaggregating experimental results by groups constructed on the basis of an index of baseline characteristics that predicts the values of individual outcomes without the treatment. T...

Significance tests are probably the most extended form of inference in empirical research, and significance is often interpreted as providing greater informational content than non-significance. In this article we show, however, that rejection of a point null often carries very little information, while failure to reject may be highly informative....

In empirical work in economics it is common to report standard errors that account for clustering of units. Typically, the motivation given for the clustering adjustments is that unobserved components in outcomes for units within clusters are correlated. However, because correlation may occur across more than one dimension, this motivation makes it...

Consider a researcher estimating the parameters of a regression function based on data for all 50 states in the United States or on data for all visits to a website. What is the interpretation of the estimated parameters and the standard errors? In practice, researchers typically assume that the sample is randomly drawn from a large population of i...

Many applied settings in empirical economics involve simultaneous estimation of a large number of parameters. In particular, applied economists are often interested in estimating the effects of many-valued treatments (like teacher effects or location effects), treatment effects for many groups, and prediction models with many regressors. In these s...

Following the work by Eicker, Huber, and White it is common in empirical work to report standard errors that are robust against general misspecification. In a regression setting, these standard errors are valid for the parameter that minimizes the squared difference between the conditional expectation and a linear approximation, averaged over the p...

In recent years a widespread consensus has emerged about the necessity of establishing bridges between the quantitative and the qualitative approaches to empirical research in political science. In this article, we discuss the use of the synthetic control method (Abadie and Gardeazabal, 2003; Abadie, Diamond, and Hainmueller, 2010) as a way to brid...

Matching methods for causal inference selectively prune observations from the data in order to reduce model dependence. They are successful when simultaneously maximizing balance (between the treated and control groups on the pre-treatment covariates) and the number of observations remaining in the data set. However, ex-isting matching methods eith...

Following the work by White (1980ab; 1982) it is common in empirical work in economics to report standard errors that are robust against general misspecification. In a regression setting these standard errors are valid for the parameter that in the population minimizes the squared difference between the conditional expectation and the linear approx...

The R package Synth implements synthetic control methods for comparative case studies designed to estimate the causal e ects of policy interventions and other events of interest (Abadie and Gardeazabal 2003; Abadie, Diamond, and Hainmueller 2010). These techniques are particularly well-suited to investigate events occurring at an aggregate level (i...

synth implements the synthetic control method for causal inference in comparative case studies as described in "Synthetic Control Methods for Comparative Case Studies of Aggregate Interventions: Estimating the Effect of California's Tobacco Control Programm. Journal of the American Statistical Association. 105(490): 493-505. 2010.

Difference-in-differences (DID) estimators are often used in empirical research in economics to evaluate the effects of public interventions and other treatments of interest in the absence of purely experimental data.

Propensity score matching estimators (Rosenbaum and Rubin, 1983) are widely used in evaluation research to estimate average treatment effects. In this article, we derive the large sample distribution of propensity score matching estimators. Our derivations take into account that the propensity score is itself estimated in a first step, prior to mat...

Matching estimators are widely used in statistical data analysis. However, the distribution of matching estimators has been derived only for particular cases (Abadie and Imbens, 2006). This article establishes a martingale representation for matching estimators. This representation allows the use of martingale limit theorems to derive the asymptoti...

Deliberative theorists emphasize that citizensÕ capacity to be-come informed when given a motive and the opportunity to participate in politics is important for democratic citizenship. We assess this capacity among citizens using a deliberative field experiment. In the summer of 2006, we conducted a field experiment in which we recruited twelve cur...

If ignored, non-compliance with a treatment and nonresponse on outcome measures can bias estimates of treatment effects in a randomized experiment. To identify treatment effects in the case where compliance and response are conditioned on unobservables, we propose the parametric generalized endoge-nous treatment (GET) model. As a multilevel random...

The attacks of September 11, 2001, and more recently the Madrid and London downtown train bombings, have raised concerns over both the safety of downtowns and the continuous efforts by terrorists to attack areas of such high density and significance. This article employs building-level data on vacancy rates to investigate the impact of an increased...

Matching estimators are widely used in empirical economics for the evaluation of programs or treatments. Researchers using matching methods often apply the bootstrap to calculate the standard errors. However, no formal justification has been provided for the use of the bootstrap in this setting. In this article, we show that the standard bootstrap...

In paired randomized experiments units are grouped in pairs, often based on covariate information, with random assignment within the pairs. Average treatment effects are then estimated by averaging the within-pair differences in outcomes. Typically the variance of the average treatment effect estimator is estimated using the sample variance of the...

This article discusses difference-in-differences (DID) estimators, which are commonly applied in evaluation research. In particular, the discussion focuses on (a) motivation, definition and interpretation of DID estimators, (b) conditions under which DID estimators are valid, (c) data requirements to compute DID estimators, (d) representative appli...

Building on an idea in Abadie and Gardeazabal (2003), this article investigates the application of synthetic control methods to comparative case studies. We discuss the advantages of these methods and apply them to study the effects of Proposition 99, a large-scale tobacco control program that California implemented in 1988. We demonstrate that fol...

In the U.S., Great Britain and in many other countries, the gap between the demand and the supply of human organs for transplantation is on the rise, despite the efforts of governments and health agencies to promote donor registration. In some countries of continental Europe, however, cadaveric organ procurement is based on the principle of presume...

For many years experimental observations have raised questions about the rationality of economic agents--for example, the Allais Paradox or the Equity Premium Puzzle. The problem is a narrow notion of rationality that disregards fear. This article extends the notion of rationality with new axioms of choice under uncertainty and the decision criteri...

Matching estimators for average treatment effects are widely used in evaluation research despite the fact that their large sample properties have not been established in many cases. The absence of formal results in this area may be partly due to the fact that standard asymptotic expansions do not apply to matching estimators with a fixed number of...

It has been argued that terrorism should not have a large effect on economic activity, because terrorist attacks destroy only a small fraction of the stock of capital of a country (see, e.g., Becker, G., Murphy, K., 2001. Prosperity will rise out of the ashes. Wall Street Journal October 29, 2001). In contrast, empirical estimates of the consequenc...

The difference-in-differences (DID) estimator is one of the most popular tools for applied research in economics to evaluate
the effects of public interventions and other treatments of interest on some relevant outcome variables. However, it is well
known that the DID estimator is based on strong identifying assumptions. In particular, the conventi...

Large male-female disparities in human capital outcomes are found in many developing countries, and are thought to arise from differential allocation of resources to sons and daughters within households. In this paper, we explore the role of fertility behavior as an alternative mechanism generating sex inequality. In particular, if couples have a s...

nnmatch estimates the average treatment effect on depvar by comparing outcomes between treated and control observations (as defined by treatvar), using nearest neighbor matching across the variables defined in varlist_nnmatch. nnmatch can estimate either the treatment effect for the treated observations, for the controls, or for the sample as a who...

This paper presents an implementation of matching estimators for average treatment effects in Stata. The nnmatch command allows you to estimate the average effect for all units or only for the treated or control units; to choose the number of matches; to specify the distance metric; to select a bias adjustment; and to use heteroskedastic-robust var...

This paper presents an implementation of matching estimators for average treatment eects in Stata. The nnmatch command allows you to estimate the average eect for all units or only for the treated or control units; to choose the number of matches; to specify the distance metric; to select a bias adjustment; and to use heteroskedastic-robust varianc...

In this paper I examine the empirical importance of accounting for heterogeneity (and selection) in the estimation of the returns to schooling and in the evaluation of education policy. I study white males and females in the National Longitudinal Survey of Youth and High School and Beyond, and white males in the Panel Study of Income Dynamics. I fi...

This article introduces a new class of instrumental variable (IV) estimators for linear and nonlinear treatment response models with covariates. The rationale for focusing on nonlinear models is that, if the dependent variable is binary or limited, or if the effect of the treatment varies with covariates, a nonlinear model is appropriate. In the sp...

This article investigates the economic effects of conflict, using the terrorist conflict in the Basque Country as a case study. We find that, after the outbreak of terrorism in the late 1960's, per capita GDP in the Basque Country declined about 10 percentage points relative to a synthetic control region without terrorism. In addition, we use the 1...

Matching estimators for average treatment effects are widely used in evaluation research despite the fact that their large sample properties have not been established in many cases. In this article, we develop a new framework to analyze the properties of matching estimators and establish a number of new results. First, we show that matching estimat...

The Maxwell School's Government Performance Project rated the management successes of the 50 states in several areas, such as capital management, human resources and information technology in 1998 and 2000. Variability among the states was significant. Viewing the Maxwell School data as something to be explained, we focus on political institutions,...

This paper reports estimates of the effects of JTPA training programs on the distribution of earnings. The estimation uses a new instrumental variable (IV) method that measures program impacts on quantiles. The quantile treatment effects (QTE) estimator reduces to quantile regression when selection for treatment is exogenously determined. QTE can b...

This article considers the problem of assessing the distributional consequences of a treatment on some outcome variable of interest when treatment intake is (possibly) nonrandomized, but there is a binary instrument available for the researcher. Such a scenario is common in observational studies and in randomized experiments with imperfect complian...

In this paper we analyze large sample properties of matching estimators, which have foundwide applicability in evaluation research despite that fact that their large sample propertieshave not been established in many cases. We show that standard matching estimatorshave biases in large samples that do not vanish in the standard asymptotic distributi...

This paper investigates the economic effects of conflict, using the terrorist conflict in the Basque Country as a case study. Our analysis rests on two different strategies. First, we use a combination of other regions to construct a ``synthetic'' control region which resembles many relevant economic characteristics of the Basque Country before the...

This paper considers the problem of assessing the distributional consequences of a treatment on some outcome variable of interest when treatment intake is (possibly) non-randomized but there is a binary instrument available for the researcher. Such scenario is common in observational studies and in randomized experiments with imperfect compliance....

This article introduces a new class of instrumental variable (IV) estimators of causal treatment effects for linear and nonlinear models with covariates. The rationale for focusing on nonlinear models is to improve the approximation to the causal response function of interest. For example, if the dependent variable is binary or limited, or if the e...

This paper introduces an instrumental variables estimator for the effect of a binary treatment on the quantiles of potential outcomes. The quantile treatment effects (QTE) estimator accommodates exogenous covariates and reduces to quantile regression as a special case when treatment status is exogenous. Asymptotic distribution theory and computatio...

In this paper I analyze how changes in firm boundaries affect economic outcomes in the movie industry. In this industry, a movie distributor contracts with different exhibitors to show its movie on their screens. Due to incompleteness in these contracts, specifying ownership of decision and control rights over screen use is important. Using cross-s...

This paper reviews the methods for measuring the economic cost of conflict. Estimat- ing the economic costs of conflict require a counterfactual c alculation, which makes this task very difficult. Social researchers have resorted to dif ferent estimation methods de- pending on the particular effect being estimated. The method used in each case depe...

In October of 1998 Nicaragua was hit by Hurricane Mitch, the third most powerful hurricane formed in the Tropical Atlantic basin in the 20 th century. We exploit this exogenous variation and the trajectory of the hurricane in a quasi-experimental design to evaluate the medium-term effects of a large negative shock on children's welfare. While we fi...

I study the unprecedented exodus westward of highly-skilled scientists after the end of the USSR and examine both the selection of emigrants and the impact of emigration on their subsequent productivity. Using a unique panel dataset of over 15,000 Russian scien-tists across many fields of science, I argue that the end of the USSR provides condition...

This paper explores the relationship between nonseparable models and treatment effect models when the causal variable of interest is endogenous. Like the treatment effect liter-ature, our aim is to place no structure on the outcome equation, and establish necessary and sufficient conditions on the first stage equation for point identification of th...

It is often asserted that consumers purchasing automobiles and other durable goods un-derweight gasoline or other future add-on costs. We test this hypothesis in the US automobile market by examining the equilibrium e¤ects of time series variation in gasoline price expectations on the market shares and relative prices of vehicles with di¤erent fuel...

## Citations

... Another alternative is the sampling framework in which the number of untreated observations N 0 grows at a faster rate than the number of treated observations N 1 . For example, Abadie & Imbens [4], Ferman [15] assume that N 0 N d/2 ...

... For inference, Chernozhukov et al. (2021) introduced an exact and robust conformal inference method based on permutation, and Li (2020) derived the distribution theory for SC estimator using projection theory with a sub-sampling method to conduct hypothesis testing and construct confidence intervals. Most recently, the SC methods have also found applications in settings with multiple treated units (Dube & Zipperer 2015, Robbins et al. 2017, Abadie & L'Hour 2021, which however are still restricted to the estimation of ATE. ...

... The weakness of this approach lies in the fact that it entails some degree of arbitrariness in the selection of the control unit. To solve this problem, Abadie (2021) offered an ingenious solution. Information would be collected on several different potential control units or peers, which taken together go to make up the donor pool. ...

... The risk difference in acute PSP with a 95% confidence interval was estimated as the difference between the probability of receiving morphine titration of TPVB patients and that of ESPB patients in the matched sample. The standard errors were estimated using cluster-robust standard errors to account for pair membership [30]. ...

... Liquidity of the foreign exchange market is significantly higher than other markets. Abadie and Gardeazabal (2007) attempt to measure the impact of terrorism on the foreign direct investment in an open economy. They made use of the data set on net stock of FDI obtained from the UNCTAD (United Nation Conference on Trade and Development) for 98 countries and GTI (Global Terrorism Index) for measuring data on terror activities which have the advantage over other measures by being popular among the international investors' who use it to evaluate specific country's risk. ...

... In this situation, it is also possible to put their beliefs ahead of the decision of the person they represent. In case of a lack of previous donor intention, the possible family choice is to object to donation (Delgado, 2019;Abadie, 2006). ...

... Altogether, the machine learning algorithm has an advantage over the traditional regression methods (Gowin et al., 2019). In the area of business and economics linear, ridge, lasso, and elastic net through machine learning perform better for prediction with dimensional data (Abadie and Kasy, 2019;Emmert-Streib and Dehmer, 2019;Hofmarcher, Cuaresma, Grun and Hornik, 2011;Sapra, 2016). The research by Christos and Georgios (2018) used the regularization of parameters, penalizing data, and artificial neural network through machine learning for predicting Boston housing prices, in a result, they found that the elastic-net model performed better compared to the other linear models. ...

... We adopt the potential outcomes framework-see Imbens and Rubin (2015) for an introduction to potential outcomes and causality, and Abadie and Cattaneo (2018) for a review 1 INTRODUCTION of program evaluation methodology. We assume that each unit has two potential outcomes, Y i (1) and Y i (0), which correspond, respectively, to the outcomes that would be observed under treatment or control. ...

... Hence, the result will have large positive outcome errors that introduce positive bias into the average outcome for the matched controls. For an almost-identical example in the context of prognostic score estimation with additional discussion and simulation results, see Hansen (2008), and for a discussion of similar pitfalls arising in adjustments for randomized trials see Abadie, Chingos and West (2018). ...

... Moreover, our high-powered meta-analyses across the different sports and competitions cannot reject the hypothesis of no effect of marginally trailing on winning, and the confidence intervals suggest that the true effect, if existent at all, is likely relatively small. This absence of supportive evidence is particularly informative in the light of BP's prior finding of a large positive effect and our sizable datasets (Abadie, 2020). ...