Automated Author ProfileArgente, David
Pennsylvania State University
Argente, David
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.1 (sum of 5 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This is the replication package for "The Life Cycle of Products: Evidence and Implications," accepted in 2023 by the Journal of Political Economy.
Authors
- Argente, David ;
- Lee, Munseob ;
- Moreira, Sara
We use a dataset with prices and spending on consumer packaged goods matched at the barcode-level across the US and Mexico to measure the price index in Mexico relative to the US. Mexican prices relative to the US are 23% lower compared to the International Comparisons Project's (ICP) price index. We decompose the 23% gap into the biases from imputation, sampling, quality, and variety. Quality bias increases Mexican prices by 48%. Imputation, sampling, and variety bias lowers Mexican prices by 11%, 13%, and 33%, respectively.
Authors
- Argente, David ;
- Hsieh, Chang-Tai ;
- Lee, Munseob
We use a dataset with prices and spending on consumer packaged goods matched at the barcode-level across the US and Mexico to measure the price index in Mexico relative to the US. Mexican prices relative to the US are 23% lower compared to the International Comparisons Project's (ICP) price index. We decompose the 23% gap into the biases from imputation, sampling, quality, and variety. Quality bias increases Mexican prices by 48%. Imputation, sampling, and variety bias lowers Mexican prices by 11%, 13%, and 33%, respectively.
Authors
- Argente, David ;
- Hsieh, Chang-Tai ;
- Lee, Munseob
The programs replicate tables and figures from "On the Effects of the Availability of Means of Payments: The Case of Uber", by Alvarez and Argente.
Authors
- Alvarez, Fernando ;
- Argente, David
Argente, David, Hsieh, Chang-Tai, and Lee, Munseob, (2022) “The Cost of Privacy: Welfare Effects of the Disclosure of COVID-19 Cases.” Review of Economics and Statistics 104:1, 176–186.
Authors
- Argente, David ;
- Hsieh, Chang-Tai ;
- Lee, Munseob