Sebastian Calonico
Biographic Data
| ID | 6163698 |
|---|---|
| NAME | Sebastian Calonico |
| GIVEN NAMES | Sebastian |
| FAMILY NAME | Calonico |
| SIGNATURE | CALONICO S |
| AFFILIATIONS | University of Miami |
| ORCID | 0000-0002-9736-8949 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Risk factors for Covid-19 in-hospital mortality in Argentina: A competing risk survival analysis
COVID-19 poses dire threats for low and middle-income countries (LMICs). Yet, there remains limited rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs, and often the evidence was based on small samples and/or unicentric. The objective of this study was to examine risk factors of COVID-19 mortality in Argentina, a hard-hit middle-income Latin American country. We analyze data on 5,146 COVID-19 patients…
Multivalued Treatments and Decomposition Analysis: An Application to the WIA Program
This article provides a general estimation and inference framework to study how different levels of program participation affect participants’ outcomes. We decompose differences in the outcome distribution into (i) a structure effect, arising due to the conditional outcome distributions given covariates associated with different levels of participation; and (ii) a composition effect, arising due to differences in the distributions of observable c…
Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs
Modern empirical work in regression discontinuity (RD) designs often employs local polynomial estimation and inference with a mean square error (MSE) optimal bandwidth choice. This bandwidth yields an MSE-optimal RD treatment effect estimator, but is by construction invalid for inference. Robust bias-corrected (RBC) inference methods are valid when using the MSE-optimal bandwidth, but we show that they yield suboptimal confidence intervals in ter…
Association of negative financial shocks during the Great Recession with depressive symptoms and substance use in the USA: The Cardia study
Background The Great Recession of 2008 was marked by large increases in unemployment and decreases in the household wealth of many Americans. In the 21st century, there have also been increases in depressive symptoms, alcohol use and drug use among some groups in the USA. The objective of this analysis is to evaluate the influence of negative financial shocks incurred during the Great Recession on depressive symptoms, alcohol and drug use. Method…
Regression Discontinuity Designs Using Covariates
We study regression discontinuity designs when covariates are included in the estimation. We examine local polynomial estimators that include discrete or continuous covariates in an additive separable way, but without imposing any parametric restrictions on the underlying population regression functions. We recommend a covariate-adjustment approach that retains consistency under intuitive conditions and characterize the potential for estimation a…
On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference
Nonparametric methods play a central role in modern empirical work. While they provide inference procedures that are more robust to parametric misspecification bias, they may be quite sensitive to tuning parameter choices. We study the effects of bias correction on confidence interval coverage in the context of kernel density and local polynomial regression estimation, and prove that bias correction can be preferred to undersmoothing for minimizi…
Rdrobust: Software for Regression-discontinuity Designs
We describe a major upgrade to the Stata (and R) rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regression-discontinuity designs. The main new features of this upgraded version are as follows: i) covariate-adjusted bandwidth selection, point estimation, and robust bias-corrected inference, ii) cluster–robust bandwidth selection, point estimation, and robust …
Optimal Data-Driven Regression Discontinuity Plots
Exploratory data analysis plays a central role in applied statistics and econometrics. In the popular regression-discontinuity (RD) design, the use of graphical analysis has been strongly advocated because it provides both easy presentation and transparent validation of the design. RD plots are nowadays widely used in applications, despite its formal properties being unknown: these plots are typically presented employing ad hoc choices of tuning …
Rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs
This article describes the R package rdrobust, which provides data-driven graphical and inference procedures for RD designs. The package includes three main functions: rdrobust, rdbwselect and rdplot. The first function (rdrobust) implements conventional local-polynomial RD treatment effect point estimators and confidence intervals, as well as robust bias-corrected confidence intervals, for average treatment effects at the cutoff. This function c…
Robust Data-Driven Inference in the Regression-Discontinuity Design
In this article, we introduce three commands to conduct robust data-driven statistical inference in regression-discontinuity (RD) designs. First, we present rdrobust, a command that implements the robust bias-corrected confidence intervals proposed in Calonico, Cattaneo, and Titiunik (2014d, Econometrica 82: 2295–2326) for average treatment effects at the cutoff in sharp RD, sharp kink RD, fuzzy RD, and fuzzy kink RD designs. This command also im…
Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs: Robust Nonparametric Confidence Intervals
In the regression-discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In this design, local polynomial estimators are now routinely employed to construct confidence intervals for treatment effects. The performance of these confidence intervals in applications, however, may be seriously hampered by their sensitivity to the specific bandwidth employed. Available ba…
Outsiders?: The Changing Patterns of Exclusion in Latin America and the Caribbean. Economic and Social Progress in Latin America. 2008 Report
This report raises a number of fundamental questions about the multidimensional and interrelated nature of social exclusion and moves beyond the traditional emphasis on outcomes and groups to view exclusion as a process that results from societal traits that limit the functionings of the excluded. Using the tools of experimental economics, the report shows the enormous economic and welfare costs of exclusion, suggesting that inclusion policies sh…
Association of negative financial shocks during the Great Recession with depressive symptoms and substance use in the USA: The Cardia study
Background The Great Recession of 2008 was marked by large increases in unemployment and decreases in the household wealth of many Americans. In the 21st century, there have also been increases in depressive symptoms, alcohol use and drug use among some groups in the USA. The objective of this analysis is to evaluate the influence of negative financial shocks incurred during the Great Recession on depressive symptoms, alcohol and drug use. Method…
Outsiders?: The Changing Patterns of Exclusion in Latin America and the Caribbean. Economic and Social Progress in Latin America. 2008 Report
This report raises a number of fundamental questions about the multidimensional and interrelated nature of social exclusion and moves beyond the traditional emphasis on outcomes and groups to view exclusion as a process that results from societal traits that limit the functionings of the excluded. Using the tools of experimental economics, the report shows the enormous economic and welfare costs of exclusion, suggesting that inclusion policies sh…
Robust Data-Driven Inference in the Regression-Discontinuity Design
In this article, we introduce three commands to conduct robust data-driven statistical inference in regression-discontinuity (RD) designs. First, we present rdrobust, a command that implements the robust bias-corrected confidence intervals proposed in Calonico, Cattaneo, and Titiunik (2014d, Econometrica 82: 2295–2326) for average treatment effects at the cutoff in sharp RD, sharp kink RD, fuzzy RD, and fuzzy kink RD designs. This command also im…
Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs: Robust Nonparametric Confidence Intervals
In the regression-discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In this design, local polynomial estimators are now routinely employed to construct confidence intervals for treatment effects. The performance of these confidence intervals in applications, however, may be seriously hampered by their sensitivity to the specific bandwidth employed. Available ba…
Optimal Data-Driven Regression Discontinuity Plots
Exploratory data analysis plays a central role in applied statistics and econometrics. In the popular regression-discontinuity (RD) design, the use of graphical analysis has been strongly advocated because it provides both easy presentation and transparent validation of the design. RD plots are nowadays widely used in applications, despite its formal properties being unknown: these plots are typically presented employing ad hoc choices of tuning …
Rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs
This article describes the R package rdrobust, which provides data-driven graphical and inference procedures for RD designs. The package includes three main functions: rdrobust, rdbwselect and rdplot. The first function (rdrobust) implements conventional local-polynomial RD treatment effect point estimators and confidence intervals, as well as robust bias-corrected confidence intervals, for average treatment effects at the cutoff. This function c…
Rdrobust: Software for Regression-discontinuity Designs
We describe a major upgrade to the Stata (and R) rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regression-discontinuity designs. The main new features of this upgraded version are as follows: i) covariate-adjusted bandwidth selection, point estimation, and robust bias-corrected inference, ii) cluster–robust bandwidth selection, point estimation, and robust …
On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference
Nonparametric methods play a central role in modern empirical work. While they provide inference procedures that are more robust to parametric misspecification bias, they may be quite sensitive to tuning parameter choices. We study the effects of bias correction on confidence interval coverage in the context of kernel density and local polynomial regression estimation, and prove that bias correction can be preferred to undersmoothing for minimizi…
Regression Discontinuity Designs Using Covariates
We study regression discontinuity designs when covariates are included in the estimation. We examine local polynomial estimators that include discrete or continuous covariates in an additive separable way, but without imposing any parametric restrictions on the underlying population regression functions. We recommend a covariate-adjustment approach that retains consistency under intuitive conditions and characterize the potential for estimation a…
Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs
Modern empirical work in regression discontinuity (RD) designs often employs local polynomial estimation and inference with a mean square error (MSE) optimal bandwidth choice. This bandwidth yields an MSE-optimal RD treatment effect estimator, but is by construction invalid for inference. Robust bias-corrected (RBC) inference methods are valid when using the MSE-optimal bandwidth, but we show that they yield suboptimal confidence intervals in ter…
Association of negative financial shocks during the Great Recession with depressive symptoms and substance use in the USA: The Cardia study
Background The Great Recession of 2008 was marked by large increases in unemployment and decreases in the household wealth of many Americans. In the 21st century, there have also been increases in depressive symptoms, alcohol use and drug use among some groups in the USA. The objective of this analysis is to evaluate the influence of negative financial shocks incurred during the Great Recession on depressive symptoms, alcohol and drug use. Method…
Multivalued Treatments and Decomposition Analysis: An Application to the WIA Program
This article provides a general estimation and inference framework to study how different levels of program participation affect participants’ outcomes. We decompose differences in the outcome distribution into (i) a structure effect, arising due to the conditional outcome distributions given covariates associated with different levels of participation; and (ii) a composition effect, arising due to differences in the distributions of observable c…
Risk factors for Covid-19 in-hospital mortality in Argentina: A competing risk survival analysis
COVID-19 poses dire threats for low and middle-income countries (LMICs). Yet, there remains limited rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs, and often the evidence was based on small samples and/or unicentric. The objective of this study was to examine risk factors of COVID-19 mortality in Argentina, a hard-hit middle-income Latin American country. We analyze data on 5,146 COVID-19 patients…
Mathematics (9 works) · Statistics (9 works) · Computer Science (8 works) · Statistical Methods and Inference (8 works) · Estimator (7 works) · Inference (7 works) · Statistical Methods and Bayesian Inference (7 works) · Advanced Causal Inference Techniques (6 works) · Artificial Intelligence (6 works) · Regression discontinuity design (6 works)