colombia: Vendor data from an RCT conducted in Bogota, Colombia.
In grantmcdermott/ritest: Randomisation Inference Testing
Description
Usage
Format
Details
References
Description
This dataset is a preliminary version of the data described in
Iacovone and McKenzie (forthcoming). It conforms to an earlier blog post
written by one of the authors (McKenzie, 2017) and contains data collected
during a randomized controlled trial on supply chains among fresh produce
vendors in Bogota, Colombia.
Usage
1
Format
A data frame with 3336 rows and 8 variables:
- b_block
business block (geographic identifier)
- b_pair
randomly assigned treatment pairs (plus one triplet)
- b_treat
treatment status (1 = yes, 2 = no)
- dayscorab
number of days that week requiring visits to Corabastos central market
- b_dayscorab
baseline of the previous variable
- miss_b_dayscorab
dummy for missing baseline information (1 = yes, 2 = no)
- round2, round3
survey round dummies
Details
The RCT studies the impact of purchase aggregation by many
microenterprises (here: fruit and vegetable vendors), which enables a
reduction in costly individual visits to a large central market. My thanks to
David McKenzie for sharing the data.
References
McKenzie, D. (2017) "Finally, a way to do easy randomization inference in Stata!", Development Impact (World Bank blog). https://blogs.worldbank.org/impactevaluations/finally-way-do-easy-randomization-inference-stata.
Iacovone, L. and McKenzie, D. (forthcoming) "Shortening Supply Chains: Experimental Evidence from Fruit and Vegetable Vendors in Bogota", Economic Development and Cultural Change. https://doi.org/10.1086/714050.
grantmcdermott/ritest documentation built on Jan. 8, 2022, 12:07 a.m.
R Package Documentation
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Description Usage Format Details References
Description
This dataset is a preliminary version of the data described in Iacovone and McKenzie (forthcoming). It conforms to an earlier blog post written by one of the authors (McKenzie, 2017) and contains data collected during a randomized controlled trial on supply chains among fresh produce vendors in Bogota, Colombia.
Usage
1 |
Format
A data frame with 3336 rows and 8 variables:
- b_block
business block (geographic identifier)
- b_pair
randomly assigned treatment pairs (plus one triplet)
- b_treat
treatment status (1 = yes, 2 = no)
- dayscorab
number of days that week requiring visits to Corabastos central market
- b_dayscorab
baseline of the previous variable
- miss_b_dayscorab
dummy for missing baseline information (1 = yes, 2 = no)
- round2, round3
survey round dummies
Details
The RCT studies the impact of purchase aggregation by many microenterprises (here: fruit and vegetable vendors), which enables a reduction in costly individual visits to a large central market. My thanks to David McKenzie for sharing the data.
References
McKenzie, D. (2017) "Finally, a way to do easy randomization inference in Stata!", Development Impact (World Bank blog). https://blogs.worldbank.org/impactevaluations/finally-way-do-easy-randomization-inference-stata.
Iacovone, L. and McKenzie, D. (forthcoming) "Shortening Supply Chains: Experimental Evidence from Fruit and Vegetable Vendors in Bogota", Economic Development and Cultural Change. https://doi.org/10.1086/714050.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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