Synthetic Difference in Differences

Synthetic Difference in Differences PDF Author: Dmitry Arkhangelsky
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
We present a new perspective on the Synthetic Control (SC) method as a weighted least squares regression estimator with time fixed effects and unit weights. This perspective suggests a generalization with two way (both unit and time) fixed effects, and both unit and time weights, which can be interpreted as a unit and time weighted version of the standard Difference In Differences (DID) estimator. We find that this new Synthetic Difference In Differences (SDID) estimator has attractive properties compared to the SC and DID estimators. Formally we show that our approach has double robustness properties: the SDID estimator is consistent under a wide variety of weighting schemes given a well-specified fixed effects model, and SDID is consistent with appropriately penalized SC weights when the basic fixed effects model is misspecified and instead the true data generating process involves a more general low-rank structure (e.g., a latent factor model). We also present results that justify standard inference based on weighted DID regression. Further generalizations include unit and time weighted factor models.

Synthetic Difference in Differences

Synthetic Difference in Differences PDF Author: Dmitry Arkhangelsky
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
We present a new perspective on the Synthetic Control (SC) method as a weighted least squares regression estimator with time fixed effects and unit weights. This perspective suggests a generalization with two way (both unit and time) fixed effects, and both unit and time weights, which can be interpreted as a unit and time weighted version of the standard Difference In Differences (DID) estimator. We find that this new Synthetic Difference In Differences (SDID) estimator has attractive properties compared to the SC and DID estimators. Formally we show that our approach has double robustness properties: the SDID estimator is consistent under a wide variety of weighting schemes given a well-specified fixed effects model, and SDID is consistent with appropriately penalized SC weights when the basic fixed effects model is misspecified and instead the true data generating process involves a more general low-rank structure (e.g., a latent factor model). We also present results that justify standard inference based on weighted DID regression. Further generalizations include unit and time weighted factor models.

Synthetic Difference In Differences

Synthetic Difference In Differences PDF Author: Dmitry Arkhangelsky
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 61

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Book Description
We present a new perspective on the Synthetic Control (SC) method as a weighted least squares regression estimator with time fixed effects and unit weights. This perspective suggests a generalization with two way (both unit and time) fixed effects, and both unit and time weights, which can be interpreted as a unit and time weighted version of the standard Difference In Differences (DID) estimator. We find that this new Synthetic Difference In Differences (SDID) estimator has attractive properties compared to the SC and DID estimators. Formally we show that our approach has double robustness properties: the SDID estimator is consistent under a wide variety of weighting schemes given a well-specified fixed effects model, and SDID is consistent with appropriately penalized SC weights when the basic fixed effects model is misspecified and instead the true data generating process involves a more general low-rank structure (e.g., a latent factor model). We also present results that justify standard inference based on weighted DID regression. Further generalizations include unit and time weighted factor models.

Synthetic Difference-in-differences Estimation

Synthetic Difference-in-differences Estimation PDF Author: Damian Clarke
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
In this paper, we describe a computational implementation of the Synthetic difference-in-differences (SDID) estimator of Arkhangelsky et al. (2021) for Stata. Synthetic difference-in-differences can be used in a wide class of circumstances where treatment effects on some particular policy or event are desired, and repeated observations on treated and untreated units are available over time. We lay out the theory underlying SDID, both when there is a single treatment adoption date and when adoption is staggered over time, and discuss estimation and inference in each of these cases. We introduce the sdid command which implements these methods in Stata, and provide a number of examples of use, discussing estimation, inference, and visualization of results.

Causal Inference in Statistics, Social, and Biomedical Sciences

Causal Inference in Statistics, Social, and Biomedical Sciences PDF Author: Guido W. Imbens
Publisher: Cambridge University Press
ISBN: 0521885884
Category : Business & Economics
Languages : en
Pages : 647

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Book Description
This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Causal Inference

Causal Inference PDF Author: Scott Cunningham
Publisher: Yale University Press
ISBN: 0300255888
Category : Business & Economics
Languages : en
Pages : 585

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Book Description
An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the basis of arguments—economic and otherwise—since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It’s rare that a book prompts readers to expand their outlook; this one did for me.”—Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied—for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.

The Estimation of Causal Effects by Difference-in-difference Methods

The Estimation of Causal Effects by Difference-in-difference Methods PDF Author: Michael Lechner
Publisher: Foundations and Trends(r) in E
ISBN: 9781601984982
Category : Business & Economics
Languages : en
Pages : 72

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Book Description
This monograph presents a brief overview of the literature on the difference-in-difference estimation strategy and discusses major issues mainly using a treatment effect perspective that allows more general considerations than the classical regression formulation that still dominates the applied work.

Balancing, Regression, Difference-In-Differences and Synthetic Control Methods

Balancing, Regression, Difference-In-Differences and Synthetic Control Methods PDF Author: Nikolay Doudchenko
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 33

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Book Description
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

Econometric Evaluation of Socio-Economic Programs

Econometric Evaluation of Socio-Economic Programs PDF Author: Giovanni Cerulli
Publisher: Springer
ISBN: 3662464055
Category : Business & Economics
Languages : en
Pages : 319

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Book Description
This book provides advanced theoretical and applied tools for the implementation of modern micro-econometric techniques in evidence-based program evaluation for the social sciences. The author presents a comprehensive toolbox for designing rigorous and effective ex-post program evaluation using the statistical software package Stata. For each method, a statistical presentation is developed, followed by a practical estimation of the treatment effects. By using both real and simulated data, readers will become familiar with evaluation techniques, such as regression-adjustment, matching, difference-in-differences, instrumental-variables and regression-discontinuity-design and are given practical guidelines for selecting and applying suitable methods for specific policy contexts.

Biodefense in the Age of Synthetic Biology

Biodefense in the Age of Synthetic Biology PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309465184
Category : Technology & Engineering
Languages : en
Pages : 189

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Book Description
Scientific advances over the past several decades have accelerated the ability to engineer existing organisms and to potentially create novel ones not found in nature. Synthetic biology, which collectively refers to concepts, approaches, and tools that enable the modification or creation of biological organisms, is being pursued overwhelmingly for beneficial purposes ranging from reducing the burden of disease to improving agricultural yields to remediating pollution. Although the contributions synthetic biology can make in these and other areas hold great promise, it is also possible to imagine malicious uses that could threaten U.S. citizens and military personnel. Making informed decisions about how to address such concerns requires a realistic assessment of the capabilities that could be misused. Biodefense in the Age of Synthetic Biology explores and envisions potential misuses of synthetic biology. This report develops a framework to guide an assessment of the security concerns related to advances in synthetic biology, assesses the levels of concern warranted for such advances, and identifies options that could help mitigate those concerns.

Conflict and child mortality in Mali: A synthetic control analysis

Conflict and child mortality in Mali: A synthetic control analysis PDF Author: Masset, Edoardo
Publisher: Intl Food Policy Res Inst
ISBN:
Category : Political Science
Languages : en
Pages : 37

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Book Description
A civil conflict broke out in northern Mali in 2012, which is continuing to the present day. Very little is known about its impact on civilians. In this paper we show how to use birth history data to build long time series of mortality rates, and we use novel synthetic control methods to estimate the impact of the Malian civil conflict on child mortality. We find that conflict produced a significant increase in under-5 mortality, and that the impact was negligible on infant mortality but large on child mortality. We analyse trends of key mortality determinants, and conclude that a reduction in vaccination rates and in access to health care in childhood were the most likely mediators of impact. Northern Mali is today one of the poorest and most neglected areas of the world where humanitarian assistance is urgently needed.