English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The synthetic control method is a an econometric tool to evaluate causaleffects when only one unit is treated. While initially aimed at evaluating theeffect of large-scale macroeconomic changes with very few available controlunits, it has increasingly been used in place of more well-knownmicroeconometric tools in a broad range of applications, but its properties inthis context are unknown. This paper introduces an alternative to the syntheticcontrol method, which is developed both in the usual asymptotic framework andin the high-dimensional scenario. We propose an estimator of average treatmenteffect that is doubly robust, consistent and asymptotically normal. It is alsoimmunized against first-step selection mistakes. We illustrate these propertiesusing Monte Carlo simulations and applications to both standard and potentiallyhigh-dimensional settings, and offer a comparison with the synthetic controlmethod.

An alternative to synthetic control for models with many covariates under sparsity