Estimation of Average Treatment Effects Using Panel Data when Treatment Effect Heterogeneity Depends on Unobserved Fixed Effects

Sakaguchi, Shosei

doi:10.2139/ssrn.3447406

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Referring to methodological issues, the heterogeneity of the treated municipalities under consideration here, that is, the differences that they present in terms of socioeconomic characteristics and, also, with respect to their territorial peculiarities, is of major concern for the further development of the analysis. For example, very recently, new methods arose allowing to consider in the estimation of the ATT the treatment heterogeneity due to both observable and unobservable factors (Sakaguchi, 2020). Moreover, it is envisaged an extension of the analysis to the whole set of PAs, including the other IUCN categories to see whether the effect depends on the IUCN categories (Nelson & Chomitz, 2011), for example, by means of a “multiple‐treatment” approach (Callaway & Sant'Anna, 2020; Lopez & Gutman, 2017).…”

Section: Discussionmentioning

confidence: 99%

A socioeconomic impact assessment of three Italian national parks

D’Alberto

Pagliacci

Zavalloni

2022

Journal of Regional Science

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The expansion of protected areas (PAs) is feared to negatively affect the local economy, as every PA, albeit to different degrees, entails restriction to the economic activities. The literature on the topic has started assessing what is the socioeconomic impact of PAs, mostly focusing on the Global South. The objective of this article is the analysis of the socioeconomic impact of three Italian national parks (NPs), established in the 2000s, using a counterfactual approach based on both the outcome regression diff-in-diff and the doubly robust diff-in-diff combined with different propensity score-based and Mahalanobis distance matching procedures. We find that the three Italian NPs have a robust and statistically significant impact on average income of residents in municipalities hosting them. Conversely, there is weak evidence that population and local establishments are positively affected, and touristic local establishments and employment are negatively affected by the three NPs. All together the results indicate that the three NPs have no negative effect on the socioeconomic dynamics of the territories impacted, although additional investigations are required to shed lights to the impact mechanisms.

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Section: Discussionmentioning

confidence: 99%

A socioeconomic impact assessment of three Italian national parks

D’Alberto

Pagliacci

Zavalloni

2022

Journal of Regional Science

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“…But, such a simple approach can yield the true treatment effect only if the two groups are perfectly homogeneous in every possible aspect, which is often not the case in practice (not even in many planned randomized experiments if the sample sizes are not large enough). As put forward by Sakaguchi [26], evaluation of policy (treatment) effects from non-randomized studies generally assumes that, given observed covariates, treatment assignments are independent of possible outcomes, which is often violated due to unobserved confounding variables. The main challenge to get correct treatment effect from such real-life (non-randomized) data, in fact, lies in estimating the counterfactual, the hypothetical outcome of the treated unit in the absence of treatment, with utmost accuracy via a proper adjustment for the confounding effects.…”

Section: Introductionmentioning

confidence: 99%

Robust Estimation of Average Treatment Effects from Panel Data

Roychowdhury¹,

Indrila²,

Ghosh³

2021

Preprint

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In order to evaluate the impact of a policy intervention on a group of units over time, it is important to correctly estimate the average treatment effect (ATE) measure. Due to lack of robustness of the existing procedures of estimating ATE from panel data, in this paper, we introduce a robust estimator of the ATE and the subsequent inference procedures using the popular approach of minimum density power divergence inference. Asymptotic properties of the proposed ATE estimator are derived and used to construct robust test statistics for testing parametric hypotheses related to the ATE. Besides asymptotic analyses of efficiency and powers, extensive simulation studies are conducted to study the finite-sample performances of our proposed estimation and testing procedures under both pure and contaminated data. The robustness of the ATE estimator is further investigated theoretically through the influence functions analyses. Finally our proposal is applied to study the long-term economic effects of the 2004 Indian Ocean earthquake and tsunami on the (per-capita) gross domestic products (GDP) of five mostly affected countries, namely Indonesia,

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Estimation of Average Treatment Effects Using Panel Data when Treatment Effect Heterogeneity Depends on Unobserved Fixed Effects

Cited by 2 publications

References 18 publications

A socioeconomic impact assessment of three Italian national parks

A socioeconomic impact assessment of three Italian national parks

Robust Estimation of Average Treatment Effects from Panel Data

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