My replication code and data can be accessed on Harvard Dataverse.
My other code can be accessed on GitHub, including the packages I’ve written (described below).
get_files automates downloading files from a website using web scraping when you provide it with a url and the file extensions to scrape.
word2pdf automates Microsoft Word document to pdf conversion.
crop_eps crops .eps files; useful when you can’t get the cropping of a graph just right in your statistical software.
tabulator efficiently tabulates and produces Stata
tabulator directly through R:
tabulator includes the following functions:
tab()efficiently tabulates based on a categorical variable, sorts from most common to least common, and displays the proportion of observations with each value, as well as the cumulative proportion.
tabcount()counts the unique number of categories of a categorical variable or formed by a combination of categorical variables.
quantiles()produces quantiles of a variable. It is a wrapper for base R
quantile()but is easier to use within
quo_to_chr()works under the hood, converting a quosure to a character string.
To install directly through Stata:
ssc install <package_name>, replace
exampleobs prints (randomly selected) example observations and optionally stores the values in a local macro. This is useful to explore possible values of a variable in your data set without being biased by the ordering of the data.
fiscal_impoverishment includes commands to estimate fiscal impoverishment (FI) and fiscal gains to the poor (FGP), which are measures of how much the poor benefit from or are hurt by the tax and transfer system from Higgins and Lustig (2016). Additional commands graph FI and FGP curves.
head prints the head observations (first observations in data set) and mimics the
head() function in R and
head command in Linux.
randomselect randomly selects observations and marks them with a dummy variable. It differs from sample in that it does not drop the non-selected observations from the data set, and that either individual observations or other units, defined by a variable in the data set, can be randomly selected.
tail prints the tail observations (last observations in data set) and mimics the
tail() function in R and
tail command in Linux.