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Air quality regulations

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1 to 10 of 36 Results

Replication Data for: Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs Dec 5, 2017 - Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs Dataverse Papadogeorgou, Georgia, 2017, "Replication Data for: Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs", https://doi.org/10.7910/DVN/1YBDV6, Harvard Dataverse, V1, UNF:6:KNnfm8wpSiM/li+qZJ/WbA== [fileUNF] This data set consists the analysis data set for the paper titled "Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs". It includes key power plant covariates, area level characteristics and ambient ozone concentrations with 100 km of the power plant.
Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs Dataverse(Harvard University) Dec 5, 2017 This dataverse contains the data for the paper "Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs", by Papadogeorgou, Mealli, and Zigler. The current version of the paper is available at: https://arxiv.org/abs/1711.01280. The code to replicate the results using these data can be found at https://...
Ozone, Temperature and Census Raw Data Dec 5, 2017 - Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching Dataverse Papadogeorgou, Georgia, 2016, "Ozone, Temperature and Census Raw Data", https://doi.org/10.7910/DVN/LKUDHA, Harvard Dataverse, V3, UNF:6:2LFuJrfGBsxsLBRb26umeg== [fileUNF] This is the raw data file for ozone, and temperature derived from the EPA Air Quality System, and data from Census 2000.
Power Plant Emissions Data Dec 5, 2017 - Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching Dataverse Papadogeorgou, Georgia, 2016, "Power Plant Emissions Data", https://doi.org/10.7910/DVN/M3D2NR, Harvard Dataverse, V2, UNF:6:P//YH0SkeKRgT1CdbNSgvw== [fileUNF] This data set contains data on emissions (and other characteristics) at the level of Electricity Generating Unit (EGU). These data were derived from the EPA Air Markets Program Data (AMPD).
Replication Data for: Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching Dec 5, 2017 - Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching Dataverse Papadogeorgou, Georgia, 2016, "Replication Data for: Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching", https://doi.org/10.7910/DVN/DKXXSN, Harvard Dataverse, V2, UNF:6:s1ohKMuxPzF0XetwktZzdw== [fileUNF] This data set consists the analysis data set for the paper titled "Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching". It includes key power plant covariates and area level characteristics. Power plants are linked to ozone and temperature information.
(Partial) Replication Data for: An empirical evaluation of the causal impact of NAAQS nonattainment designations on particulate pollution and health Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health Zigler, Cory, 2017, "(Partial) Replication Data for: An empirical evaluation of the causal impact of NAAQS nonattainment designations on particulate pollution and health", https://doi.org/10.7910/DVN/ZAYLFA, Harvard Dataverse, V1, UNF:6:w5afM9qjNg6BGRlSwQ+LNw== [fileUNF] This is the analysis data file used for the paper, complete with propensity score estimates but with all Medicare variables set to zero. This file can be used to reconstruct basic data summaries reported in the paper.
County-Level Smoking Data Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health Zigler, Cory, 2017, "County-Level Smoking Data", https://doi.org/10.7910/DVN/VZ21KD, Harvard Dataverse, V1, UNF:6:L7kVxoDhAmjyTwP0BzYVkQ== [fileUNF] County-level smoking data originating from the CDC and produced by Dwyer-Lindgren, Laura and Mokdad, Ali H. and Srebotnjak, Tanja and Flaxman, Abraham D. and Hansen, Gillian M. and Murray, Christopher JL— (2014), “Cigarette smoking prevalence in US counties: 1996-2012,” Population Health Metrics, 12, 5. Original file provided by the above authors a...
Census data Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health Zigler, Cory, 2017, "Census data", https://doi.org/10.7910/DVN/9FS3KI, Harvard Dataverse, V1, UNF:6:CQGKEdSV70TgEQuT1/9N5A== [fileUNF] Census data (year 2000) at the zip code level, originating from the US Census and extracted using the Missouri Census Data Center (http://mcdc.missouri.edu/).
Weather monitoring data Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health Zigler, Cory, 2017, "Weather monitoring data", https://doi.org/10.7910/DVN/N0SFKO, Harvard Dataverse, V1, UNF:6:JFbkDKSoX4tQ9JKsjL625A== [fileUNF] Data from weather monitors in the Automated Surface Observing System, originally provided by the National Oceanic and Atmospheric Administration and available at: http://www.nws.noaa.gov/asos/
Fake (simulated) Medicare Data Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health Zigler, Cory, 2017, "Fake (simulated) Medicare Data", https://doi.org/10.7910/DVN/PR35NS, Harvard Dataverse, V1, UNF:6:94xH7xkCvbvDtLWuPW/t8A== [fileUNF] This file is of the same format of zip-code-level annual Medicare data used for the analysis, but all variables have been simulated to contain fake data. This data file can be used to reconstruct the analog to the analysis data set (but with fake Medicare data)

Replication Data for: Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs

Dec 5, 2017 - Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs Dataverse

Papadogeorgou, Georgia, 2017, "Replication Data for: Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs", https://doi.org/10.7910/DVN/1YBDV6, Harvard Dataverse, V1, UNF:6:KNnfm8wpSiM/li+qZJ/WbA== [fileUNF]

This data set consists the analysis data set for the paper titled "Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs". It includes key power plant covariates, area level characteristics and ambient ozone concentrations with 100 km of the power plant.

Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs Dataverse(Harvard University)

Dec 5, 2017

This dataverse contains the data for the paper "Causal Inference for Interfering Units With Cluster and Population Level Treatment Allocation Programs", by Papadogeorgou, Mealli, and Zigler. The current version of the paper is available at: https://arxiv.org/abs/1711.01280. The code to replicate the results using these data can be found at https://...

Ozone, Temperature and Census Raw Data

Dec 5, 2017 - Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching Dataverse

Papadogeorgou, Georgia, 2016, "Ozone, Temperature and Census Raw Data", https://doi.org/10.7910/DVN/LKUDHA, Harvard Dataverse, V3, UNF:6:2LFuJrfGBsxsLBRb26umeg== [fileUNF]

This is the raw data file for ozone, and temperature derived from the EPA Air Quality System, and data from Census 2000.

Power Plant Emissions Data

Dec 5, 2017 - Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching Dataverse

Papadogeorgou, Georgia, 2016, "Power Plant Emissions Data", https://doi.org/10.7910/DVN/M3D2NR, Harvard Dataverse, V2, UNF:6:P//YH0SkeKRgT1CdbNSgvw== [fileUNF]

This data set contains data on emissions (and other characteristics) at the level of Electricity Generating Unit (EGU). These data were derived from the EPA Air Markets Program Data (AMPD).

Replication Data for: Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching

Dec 5, 2017 - Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching Dataverse

Papadogeorgou, Georgia, 2016, "Replication Data for: Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching", https://doi.org/10.7910/DVN/DKXXSN, Harvard Dataverse, V2, UNF:6:s1ohKMuxPzF0XetwktZzdw== [fileUNF]

This data set consists the analysis data set for the paper titled "Adjusting for Unmeasured Spatial Confounding with Distance Adjusted Propensity Score Matching". It includes key power plant covariates and area level characteristics. Power plants are linked to ozone and temperature information.

(Partial) Replication Data for: An empirical evaluation of the causal impact of NAAQS nonattainment designations on particulate pollution and health

Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health

Zigler, Cory, 2017, "(Partial) Replication Data for: An empirical evaluation of the causal impact of NAAQS nonattainment designations on particulate pollution and health", https://doi.org/10.7910/DVN/ZAYLFA, Harvard Dataverse, V1, UNF:6:w5afM9qjNg6BGRlSwQ+LNw== [fileUNF]

This is the analysis data file used for the paper, complete with propensity score estimates but with all Medicare variables set to zero. This file can be used to reconstruct basic data summaries reported in the paper.

County-Level Smoking Data

Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health

Zigler, Cory, 2017, "County-Level Smoking Data", https://doi.org/10.7910/DVN/VZ21KD, Harvard Dataverse, V1, UNF:6:L7kVxoDhAmjyTwP0BzYVkQ== [fileUNF]

County-level smoking data originating from the CDC and produced by Dwyer-Lindgren, Laura and Mokdad, Ali H. and Srebotnjak, Tanja and Flaxman, Abraham D. and Hansen, Gillian M. and Murray, Christopher JL— (2014), “Cigarette smoking prevalence in US counties: 1996-2012,” Population Health Metrics, 12, 5. Original file provided by the above authors a...

Census data

Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health

Zigler, Cory, 2017, "Census data", https://doi.org/10.7910/DVN/9FS3KI, Harvard Dataverse, V1, UNF:6:CQGKEdSV70TgEQuT1/9N5A== [fileUNF]

Census data (year 2000) at the zip code level, originating from the US Census and extracted using the Missouri Census Data Center (http://mcdc.missouri.edu/).

Weather monitoring data

Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health

Zigler, Cory, 2017, "Weather monitoring data", https://doi.org/10.7910/DVN/N0SFKO, Harvard Dataverse, V1, UNF:6:JFbkDKSoX4tQ9JKsjL625A== [fileUNF]

Data from weather monitors in the Automated Surface Observing System, originally provided by the National Oceanic and Atmospheric Administration and available at: http://www.nws.noaa.gov/asos/

Fake (simulated) Medicare Data

Jan 3, 2017 - Impact of National Ambient Air Quality Standards nonattainment designations on particulate pollution and health

Zigler, Cory, 2017, "Fake (simulated) Medicare Data", https://doi.org/10.7910/DVN/PR35NS, Harvard Dataverse, V1, UNF:6:94xH7xkCvbvDtLWuPW/t8A== [fileUNF]

This file is of the same format of zip-code-level annual Medicare data used for the analysis, but all variables have been simulated to contain fake data. This data file can be used to reconstruct the analog to the analysis data set (but with fake Medicare data)

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