Data access is often a nightmare. Especially with irregular data shapes or multiple data types. APIs, or application programming interfaces, offer a simple access gates to the information resources in their native structures, and therefore they offer a powerful tool to quickly boost many research projects. In a nutshell, an API is a gate through which a user may access the resources or data located on a server in a quick and friendly way. APIs have a generic address, typically in the form of http address, and endpoints. Endpoints direct the user to specific parts of of the database (like tables), the user may need to access. APIs require an authentication key, called a token, which offers the server the access control mechanism. Sometimes you need to pay for a token, but oftentimes some limited functionality is offered for free. To demonstrate the performance of the API, I will access the trading database of R programming
I recently came across a problem of testing if the expectations of one variable, call it $Y$, vary alongside the distribution of another variable, say $X$. The problem can be approached through several angles, including parametric quantile approach, however, it was decided to use one of the most flexible methods, and actually one of my favorites, i.e. the bootstrap. The idea is quite simple. Imagine two random variables $Y$ and $X$. (For more information about the exact definitions of what a random variable is, the Wikipedia page has a lot of useful information.) Given their observed realisations $\{(Y_i,X_i):i=1,...,n\}$, the goal is to test if the conditional average of $Y$ is statistically different from its unconditional average. We can approximate the former by estimating the mean of $Y$ for different parts of $X$ distribution. For instance, we can test if expectations of $Y$ d...
Marcin Wolski, PhD
Climate Economist
European Investment Bank
E-mail: M.Wolski (at) eib.org
Phone: +352 43 79 88708
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IDEAS/RePEc
