Regression discontinuity designs in agricultural and environmental economics

Wuepper, David; Finger, Robert

doi:10.1093/erae/jbac023

Cited by 24 publications

(11 citation statements)

References 87 publications

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“…For this, we zoom into international border areas and analyze whether there are discontinuities in the risk of pesticide pollution across international borders. In section c below, we discuss the necessary assumptions that must be fulfilled such that this approach identifies countries' causal effect (Wuepper and Finger, 2022). The main idea is that countries' influence is sharply delineated by their borders whereas the influence of environmental and geographic confounders changes either smoothly or randomly across them (Hahn et al, 2001, Lee and Lemieux, 2010, Turner et al, 2014.…”

Section: Spatial Regression Discontinuity Design: Quantifying and Exp...mentioning

confidence: 99%

“…The second part of the equation defines exactly how identification is achieved. We fit two separate regression lines on each border side and their vertical distance close to c identifies τ ij , under the assumption that without τ ij , the pesticide pollution risk would be distributed spatially continuously across the border (Wuepper and Finger, 2022). To estimate the average border discontinuity in pesticide pollution risk globally, we estimate the following regression:…”

Section: Spatial Regression Discontinuity Design: Quantifying and Exp...mentioning

confidence: 99%

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National leverage points to reduce global pesticide pollution

Wuepper

Tang

Finger

2023

Global Environmental Change

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Section: Spatial Regression Discontinuity Design: Quantifying and Exp...mentioning

confidence: 99%

Section: Spatial Regression Discontinuity Design: Quantifying and Exp...mentioning

confidence: 99%

National leverage points to reduce global pesticide pollution

Wuepper

Tang

Finger

2023

Global Environmental Change

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“…For each equation,

{italicCRP}_{i}

Y_{i}^{L}

can alternatively represent changes in CRP or land cover proportions from before to after the 2016 Signup. This constitutes an RD of the first differences for land covers, similar to the estimator described in Lemieux and Milligan (2008) or the difference in discontinuities model described in Wuepper and Finger (2023). The first differences approach better accounts for any baseline differences between accepted and rejected offers that exist before CRP applications are made.…”

Section: Rd Estimates Of Crp Land Use Impactsmentioning

confidence: 99%

Land use impacts of the Conservation Reserve Program: An analysis of rejected offers

Rosenberg

Pratt

2023

American J Agri Economics

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The Conservation Reserve Program is the largest agricultural land retirement program in the United States, with more enrolled acreage entering the program through a competitive auction called the General Signup than any other component. In this study, we assess the land use impacts of the Conservation Reserve Program by observing the land use decisions of parcels following the 2016 General Signup. We estimate land use impacts using a regression discontinuity design based on the Environmental Benefits Index, the program's selection and ranking mechanism. Our estimates largely rely on the auction design of the General Signup, such that we observe the land use decisions of rejected offers. We also use information on the rental rates of these offers to understand what the program pays to retire land in different uses. We estimate that a marginal acre of land enrolled in the Conservation Reserve Program replaces 0.30 acres in cropland, 0.25 acres in mixed forage, 0.32 acres in grassland, 0.12 acres in idle or fallow land, and 0.01 acres in timberland. We also find that enrollments from newly offered fields are more likely to displace cropland and less likely to displace grassland than returning fields. Consequently, we estimate that new enrollments lead to 47% greater reductions in water‐driven erosion and 12% greater reductions in wind‐driven erosion, compared to fields with prior enrollment.

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“…Lalive et al analyzed the joint retirement decisions of couples in Switzerland, finding that men and women are 28% and 12% less likely to be in the labor market around the full retirement age, respectively (Lalive & Parrotta, 2017). Recently, researchers have increasingly used RDD in environmental economics and agriculture to identify causal effects (Asher & Novosad, 2020;Ayres et al, 2019;Jones et al, 2022;Wuepper & Finger, 2022). In many real-world cases, various thresholds such as population level, poverty level, pay line, or farm size exist, making RDD a highly valuable tool in the empirical toolkit.…”

Section: Introductionmentioning

confidence: 99%

Regression discontinuity design and its applications to Science of Science: A survey

Zhang

Wang

2023

Journal of Data and Information Science

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Purpose With the availability of large-scale scholarly datasets, scientists from various domains hope to understand the underlying mechanisms behind science, forming a vibrant area of inquiry in the emerging “science of science” field. As the results from the science of science often has strong policy implications, understanding the causal relationships between variables becomes prominent. However, the most credible quasi-experimental method among all causal inference methods, and a highly valuable tool in the empirical toolkit, Regression Discontinuity Design (RDD) has not been fully exploited in the field of science of science. In this paper, we provide a systematic survey of the RDD method, and its practical applications in the science of science. Design/methodology/approach First, we introduce the basic assumptions, mathematical notations, and two types of RDD, i.e., sharp and fuzzy RDD. Second, we use the Web of Science and the Microsoft Academic Graph datasets to study the evolution and citation patterns of RDD papers. Moreover, we provide a systematic survey of the applications of RDD methodologies in various scientific domains, as well as in the science of science. Finally, we demonstrate a case study to estimate the effect of Head Start Funding Proposals on child mortality. Findings RDD was almost neglected for 30 years after it was first introduced in 1960. Afterward, scientists used mathematical and economic tools to develop the RDD methodology. After 2010, RDD methods showed strong applications in various domains, including medicine, psychology, political science and environmental science. However, we also notice that the RDD method has not been well developed in science of science research. Research Limitations This work uses a keyword search to obtain RDD papers, which may neglect some related work. Additionally, our work does not aim to develop rigorous mathematical and technical details of RDD but rather focuses on its intuitions and applications. Practical implications This work proposes how to use the RDD method in science of science research. Originality/value This work systematically introduces the RDD, and calls for the awareness of using such a method in the field of science of science.

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Regression discontinuity designs in agricultural and environmental economics

Cited by 24 publications

References 87 publications

National leverage points to reduce global pesticide pollution

National leverage points to reduce global pesticide pollution

Land use impacts of the Conservation Reserve Program: An analysis of rejected offers

Regression discontinuity design and its applications to Science of Science: A survey

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