A distributional synthetic control method for policy evaluation

Chen, Yi‐Ting

doi:10.1002/jae.2778

Cited by 6 publications

(2 citation statements)

References 29 publications

(31 reference statements)

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“…Thus far, a comprehensive evaluation method based on empirical analysis has been formed, such as text data mining [ 47 , 48 ], social network analysis [ 49 ], fuzzy comprehensive evaluation [ 50 ], etc. The commonly used empirical analysis tools are PSM-DID model analysis [ 51 ], tool variables [ 52 ] and synthesis control [ 53 ]. The evaluation content is diverse, involving the agricultural economy, finance, science and technology, medical treatment, environment and sustainable development.…”

Section: Literature Reviewmentioning

confidence: 99%

Quantitative Evaluation of China’s Ecological Protection Compensation Policy Based on PMC Index Model

Dai

Zhang

Lan

2022

IJERPH

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As a comprehensive benefit coordination mechanism, ecological protection compensation has received increasing attention internationally. China has also introduced a series of policies to promote ecological protection compensation mechanism improvement. The evaluation of ecological protection compensation policies is the main basis for the formulation, adjustment and improvement of the policy. Based on the front-end perspective of policy formulation, this paper selects 10 ecological protection compensation policies issued by the State Council and various ministries in China from 2006 to 2021. A text mining-based PMC index evaluation system using the ROSTCM tool is constructed to quantitatively evaluate these 10 typical policies, and four representative policies are selected for comparative analysis. The overall design of China’s ecological protection compensation policies is reasonable, and 5 out of 10 policies have good PMC index scores, which are: P1, P2, P5, P7 and P9; and 5 are at acceptable levels, which are: P3, P4, P6, P8 and P10. However, the PMC surface and the concavity index indicate that there are still some limitations that need to be improved, including the obvious internal differentiation of the policies, the single effectiveness of the policies, and the insufficient incentive and guarantee measures. Finally, this paper provides suggestions for the optimization of ecological protection compensation policies accordingly.

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Section: Literature Reviewmentioning

confidence: 99%

Quantitative Evaluation of China’s Ecological Protection Compensation Policy Based on PMC Index Model

Dai

Zhang

Lan

2022

IJERPH

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“…The goal is to identify the shape of the counterfactual distribution, not treatment effects for individuals within an aggregate unit. By contrast, linear point‐wise approaches like Chen (2020), or approaches that (i) decompose distributions into bins and (ii) match these bins between the different distributions, are local: they obtain different weights for each quantile and hence obtain weight functions for each individual unit instead of one set of weights at the aggregate level. As a result, these synthetic controls methods are sensitive to the choice of quantiles or bins; in particular, they require the assumption that the optimal weights for each point on the quantile curve or in each bin are the same or at least similar within a given state (e.g., Assumption 1(ii) in Chen (2020)), something that can be difficult to satisfy in practice.…”

Section: Introductionmentioning

confidence: 99%

Distributional Synthetic Controls

Gunsilius

2023

ECTA

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The method of synthetic controls is a fundamental tool for evaluating causal effects of policy changes in settings with observational data. In many settings where it is applicable, researchers want to identify causal effects of policy changes on a treated unit at an aggregate level while having access to data at a finer granularity. This article proposes an extension of the synthetic controls estimator that takes advantage of this additional structure and provides nonparametric estimates of the heterogeneity within the aggregate unit. The idea is to replicate the quantile function associated with the treated unit by a weighted average of quantile functions of the control units. This estimator relies on the same mathematical theory as the changes‐in‐changes estimator and can be applied in both repeated cross‐sections and panel data with as little as a single pre‐treatment period. It also provides a unique counterfactual quantile function for any type of distribution.

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Did carbon emission trading system reduce emissions in China? An integrated approach to support policy modeling and implementation

2021

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As the highest carbon emission country in the world, it is particularly important to investigate the implementation effect of China’s carbon emission trading (CET) system. Because of the complexity to figure out the counterfactual effect when a single unit is treated, the counterfactual and causal effects of the CET system on the carbon emissions are seldom identified. In order to overcome the weakness that counterfactual effect is difficult to be verified and policy persistence is difficult to be estimated, Synthetic Control Method (SCM) and Regression Discontinuity (RD) are combined to better understand and evaluate the impact of CET system in China. Through the analysis, it is found that CET system is effective in China, but the effect is driven by economic development, energy consumption, FDI and other variables. Because of the differences in economic, geographical, technological and environmental conditions in various areas, each Chinese provincial government should formulate a targeted policy according to local conditions, ensuring an economic and environmentally sustainable growth in the future.

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A distributional synthetic control method for policy evaluation

Cited by 6 publications

References 29 publications

Quantitative Evaluation of China’s Ecological Protection Compensation Policy Based on PMC Index Model

Quantitative Evaluation of China’s Ecological Protection Compensation Policy Based on PMC Index Model

Distributional Synthetic Controls

Did carbon emission trading system reduce emissions in China? An integrated approach to support policy modeling and implementation

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