Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018
Abstract This article investigates the causal effect of farm participation in two Austrian agri‐environmental schemes (AES), Immergrün ( ground cover ) and Zwischenfrucht ( catch cropping ), on fertilizer and plant protection expenditures in the 2014 programming period. Combining European Farm Accou...
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ftsubgoettingen:oai:publications.goettingen-research-online.de:2/139177 2024-01-07T09:42:55+01:00 Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018 Uehleke, Reinhard Leonhardt, Heidi Hüttel, Silke Uehleke, Reinhard Leonhardt, Heidi Hüttel, Silke 2023 https://resolver.sub.uni-goettingen.de/purl?gro-2/139177 https://doi.org/10.1111/agec.12805 en eng https://resolver.sub.uni-goettingen.de/purl?gro-2/139177 doi:10.1111/agec.12805 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/article journal_article yes 2023 ftsubgoettingen https://doi.org/10.1111/agec.12805 2023-12-10T23:12:09Z Abstract This article investigates the causal effect of farm participation in two Austrian agri‐environmental schemes (AES), Immergrün ( ground cover ) and Zwischenfrucht ( catch cropping ), on fertilizer and plant protection expenditures in the 2014 programming period. Combining European Farm Accountancy Data Network data with information on scheme participation from administrative control data offers identifying farm participation in specific schemes targeted at reducing input intensity. Given the overall small sample, we maximized the utilizable sample size by combining difference‐in‐difference and kernel matching with automated bandwidth selection. To address the remaining post‐matching covariate imbalances, we used double machine learning (DML) techniques for a guided selection of potential confounding covariates. Our results suggest that, given the available sample, we cannot substantiate moderate effects of AES participation, and that guided covariate selection by DML offers no gain over non‐guided covariate selection for the small sample. Our results underline the need to increase the number of farms and the duration in available farm panels to substantiate future counterfactual‐based evaluations of policy. Article in Journal/Newspaper DML GRO.publications (Göttingen Research Online Publications - Göttingen University) Agricultural Economics |
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Open Polar |
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GRO.publications (Göttingen Research Online Publications - Göttingen University) |
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ftsubgoettingen |
language |
English |
description |
Abstract This article investigates the causal effect of farm participation in two Austrian agri‐environmental schemes (AES), Immergrün ( ground cover ) and Zwischenfrucht ( catch cropping ), on fertilizer and plant protection expenditures in the 2014 programming period. Combining European Farm Accountancy Data Network data with information on scheme participation from administrative control data offers identifying farm participation in specific schemes targeted at reducing input intensity. Given the overall small sample, we maximized the utilizable sample size by combining difference‐in‐difference and kernel matching with automated bandwidth selection. To address the remaining post‐matching covariate imbalances, we used double machine learning (DML) techniques for a guided selection of potential confounding covariates. Our results suggest that, given the available sample, we cannot substantiate moderate effects of AES participation, and that guided covariate selection by DML offers no gain over non‐guided covariate selection for the small sample. Our results underline the need to increase the number of farms and the duration in available farm panels to substantiate future counterfactual‐based evaluations of policy. |
author2 |
Uehleke, Reinhard Leonhardt, Heidi Hüttel, Silke |
format |
Article in Journal/Newspaper |
author |
Uehleke, Reinhard Leonhardt, Heidi Hüttel, Silke |
spellingShingle |
Uehleke, Reinhard Leonhardt, Heidi Hüttel, Silke Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018 |
author_facet |
Uehleke, Reinhard Leonhardt, Heidi Hüttel, Silke |
author_sort |
Uehleke, Reinhard |
title |
Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018 |
title_short |
Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018 |
title_full |
Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018 |
title_fullStr |
Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018 |
title_full_unstemmed |
Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018 |
title_sort |
counterfactual evaluation of two austrian agri‐environmental schemes in 2014–2018 |
publishDate |
2023 |
url |
https://resolver.sub.uni-goettingen.de/purl?gro-2/139177 https://doi.org/10.1111/agec.12805 |
genre |
DML |
genre_facet |
DML |
op_relation |
https://resolver.sub.uni-goettingen.de/purl?gro-2/139177 doi:10.1111/agec.12805 |
op_rights |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1111/agec.12805 |
container_title |
Agricultural Economics |
_version_ |
1787424167328481280 |