cp2015_nafta: Data for NAFTA's tariff reductions simulation in Caliendo and...
In paulofelipe/cp2015: Caliendo and Parro (2015) Quantitative Trade Model
cp2015_nafta R Documentation
Data for NAFTA's tariff reductions simulation in Caliendo and Parro (2015)
Description
This data is used to replicate the results of Caliendo and Parro (2015) for
(only) NAFTA's tariff reductions. In addition, it shows the data structure
needed to use this package.
The data structure has been modified for compatibility with the package.
Therefore, the data are not in the original format provided by Caliendo and Parro (2015).
The original data is available at: https://academic.oup.com/restud/article/82/1/1/1547758#supplementary-data.
Usage
cp2015_nafta
Format
A named list of 7 elements: sets, intermediate_consumption, final_consumption,
trade, deficit, and theta.
sets. A named list of vectors containing all regions and all sectors in data.
intermediate_consumption. A data.frame with 4 columns containing intermediate consumption data:
input. The input sector.
sector. The user sector.
sector. The user region.
value. The intermediate consumption value (tariffs-inclusive).
final_consumption. A data.frame with 3 columns containing final consumption data:
sector. The sector.
region. The consumer region.
value. The final consumption value (tariffs-inclusive).
value_added. A data.frame with 3 column containing value added ("labor") data:
sector. The user sector.
region. The user region.
value. The value added.
trade. A data.frame with 5 columns containing the bilateral trade and tariff data:
sector. The sector.
exporter. The exporter region.
importer. The importer region.
value. The trade value (net of tariffs).
tariff. The original tariffs in the database.
tariff_bln. The tariffs in the baseline scenario. Usually the same
original tariffs are used, but this is not mandatory.
tariff_cfl. The tariffs in the counterfactual scenario.
d_bln. The relative change in iceberg trade costs in the baseline scenario (1 = no change).
d_cfl. The relative change in iceberg trade costs in the counterfactual scenario (1 = no change).
As the model solution is in exact changes, the initial value can be set
to 1 and changes can be set proportionally.
deficit. A data.frame with 4 columns containing the deficit data?
region. The region.
D. The original deficit in the database.
theta. A data.frame with 2 columns containing the trade elasticities:
sector. The sector.
value. The theta (trade elasticity) parameter value.
References
Lorenzo Caliendo, Fernando Parro, Estimates of the Trade and Welfare Effects of NAFTA,
The Review of Economic Studies, Volume 82, Issue 1, January 2015, Pages 1–44, https://doi.org/10.1093/restud/rdu035
paulofelipe/cp2015 documentation built on Nov. 24, 2024, 11:46 p.m.
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| cp2015_nafta | R Documentation |
Data for NAFTA's tariff reductions simulation in Caliendo and Parro (2015)
Description
This data is used to replicate the results of Caliendo and Parro (2015) for (only) NAFTA's tariff reductions. In addition, it shows the data structure needed to use this package.
The data structure has been modified for compatibility with the package. Therefore, the data are not in the original format provided by Caliendo and Parro (2015). The original data is available at: https://academic.oup.com/restud/article/82/1/1/1547758#supplementary-data.
Usage
cp2015_nafta
Format
A named list of 7 elements: sets, intermediate_consumption, final_consumption, trade, deficit, and theta.
sets. A named list of vectors containing all regions and all sectors in data.
intermediate_consumption. A data.frame with 4 columns containing intermediate consumption data:
input. The input sector.
sector. The user sector.
sector. The user region.
value. The intermediate consumption value (tariffs-inclusive).
final_consumption. A data.frame with 3 columns containing final consumption data:
sector. The sector.
region. The consumer region.
value. The final consumption value (tariffs-inclusive).
value_added. A data.frame with 3 column containing value added ("labor") data:
sector. The user sector.
region. The user region.
value. The value added.
trade. A data.frame with 5 columns containing the bilateral trade and tariff data:
sector. The sector.
exporter. The exporter region.
importer. The importer region.
value. The trade value (net of tariffs).
tariff. The original tariffs in the database.
tariff_bln. The tariffs in the baseline scenario. Usually the same original tariffs are used, but this is not mandatory.
tariff_cfl. The tariffs in the counterfactual scenario.
d_bln. The relative change in iceberg trade costs in the baseline scenario (1 = no change).
d_cfl. The relative change in iceberg trade costs in the counterfactual scenario (1 = no change). As the model solution is in exact changes, the initial value can be set to 1 and changes can be set proportionally.
deficit. A data.frame with 4 columns containing the deficit data?
region. The region.
D. The original deficit in the database.
theta. A data.frame with 2 columns containing the trade elasticities:
sector. The sector.
value. The theta (trade elasticity) parameter value.
References
Lorenzo Caliendo, Fernando Parro, Estimates of the Trade and Welfare Effects of NAFTA, The Review of Economic Studies, Volume 82, Issue 1, January 2015, Pages 1–44, https://doi.org/10.1093/restud/rdu035
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