Checklist for data validation
Feb 22nd 2018
I created a list of data validation tasks and procedures to help with the data cleaning and updating process. These tips come from
my experience in producing and cleaning datasets. It is a work in progress so feel free to add your comments. The Google Doc is
My new working paper-July. 18th
The Effects of Demand Shocks on the Growth of Small firms
In this paper I estimate the causal effects of demand shocks on the growth of small firms. I use data from several new sources and, as identification strategy, exploit a governmental procurement process that allocates public contracts through a randomized contest. I find that demand shocks have a positive and significant impact on short-term measures of growth and no impact on long-term measures. On average, an increase in demand of 10% will increase wage expense by 2% and current assets by 5% during the year of the shock. Firms that won during consecutive years show an increase in their levels of fixed assets. Available here
A quick JS scrap tutorial
April 4th, 2017
Happy New Year!
This year taught me the importance to question the assumptions we make when predicting outcomes. As they say, It's Difficult to Make Predictions, Especially About the Future.
How to create maps with Stata
Sept. 3rd, 2016
Stata allows you to create a wide gamut of maps. I write this guide with two main goals in mind: to supplement the resources found online and to highlight functionalities that I find helpful. Stata is not the best software to create maps. Nonetheless knowing how to do so is a convenient way to avoid having to use multiple programss. We are going to use the package SPMAP created by Mauro Pisati and shp2dta by by Kevin Crow.
Analyzing traffic tickets using Ipython
May 5th, 2016
I recently switched to Ipython for my data analysis and exploratory work. Although, I prefer
Stata or R for any serious data analysis, Ipython has an incredible competitive advantage
when it comes to sharing, publishing, and visualizing results. First, you can see the
results below your code which makes it a very convenient way to learn about your data.
from how programmers have dealt with version control, or GIT as it is known in that field.