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The robustness of our estimations is supported by the similar results obtained when re-analyzing data with the new stratification that made the study groups comparable in terms of pre- intervention morbitity.
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Elasticities from our estimations are lower for all tertiles in comparison to these estimates; yet both results demonstrate the higher price responsiveness of poorer bidi consumers.
Our estimations are run on three different sub-samples.
Our estimations are based on the following equation, where we cluster by labor market region.
These firm variables used in our estimations are common indicators of innovativeness at the firm level.
We also illustrate that our estimations are conservative because of low resolution of the DEMs used for calculations.
The marginal effects in our estimations are presented for the highest value only, which is "enterprise profits increased".
As the threshold value for when noise is regarded as disturbing is set at 50 dB in Sweden [65], our estimations are based on this value.
This exercise reveals that our estimations are based on a sample in which firms with more than 50 employees are somewhat overrepresented.
Our estimations are displayed together with the initial WHO plan and national Care and Treatment Plan (CTP) targets for ART scale-up in Tanzania during 2004 2009 for comparison.
For the two Hong Kong scenarios we considered, our estimations are quite close to the observed figures.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com