My simple thoughts

The US has aggressively proposed the enactment of worldwide minimum tax for corporations in the last months. In the early of July, Joe Biden was able to get 130 countries around the world to set a minimum tax rate of 15 percent that all companies pay, which is known as Global Minimum Tax (GMT). For the US, GMT is a tool to stop multinational enterprises from shifting their money from US to countries with lower tax rates. The Organization for Economic Cooperation and Development (OECD) estimated the GMT would generate extra $150 billion of tax revenue for the US each year. GMT is a scheme to reduce tax competition between countries which is expected to reduce tax avoidance of multinational enterprises. When it is implemented, the home country would be able to charge income tax at the GMT's rate when the corporation's effective tax rate is lower than the GMT rate. Effective tax rate is different with statutory tax rate, which can be seen in the domestic tax regulations. Effective...

  This part covers basic syntaxes in the Python programming language using Jupyter Notebook. However, you can also use another Integrated Development Environment (IDE), such as Pycharm, VS Code, Idle, or any other IDE. The syntaxes are still the same no matter what IDE you are using. If you are looking to install Python or navigate Jupyter Notebook, you should check my previous articles   here   and   here . Basically, all programming languages can be divided into sequential, branching, and looping. We will discuss the basic syntaxes in Python from there. Sequential Sequential programming is when our code consists of operations one over the other, which will be run in a sequence, just like counting from 1 to 10. Sequential is the basic logic on how computers run our instructions. Computers always execute our code in order, unless you tell them otherwise, from the very top to the very bottom. For example, let’s make our previous “hello world” code to take the user’s n...

  Okay, as promised, we are going to cover using Jupyter Notebook as our IDE to work on our Python code. Assuming you have read the first part, which you can find   here , you should have your Anaconda ready by now. To start, click the Anaconda-Navigator icon. It’s the one that looks like a green ring. Then, launch Jupyter Notebook. On the picture below, it’s on the top right corner. After launching Jupyter, the program will start running on your terminal or command prompt, and subsequently open Jupyter Notebook on your browser. On the Jupyter interface, you can load an existing notebook if you have any. Assuming that you don’t, let’s make a new one by clicking “ New ”, then choose “ Python 3(ipkernel)” . This action will open a new tab on your browser. Below is the new tab. See the green box below? We call it a “cell”. That is where we write our code in. Now, let’s write the ‘Hello world’ code just like in the previous part, by typing   print(‘Hello world’) . To execute ...

  Maybe you have just browsed the internet, social media, or talked with Siri on your iPhone, and suddenly a question popped up in your mind, “How do they create all of these?” Well, the answer is Data Science. You have probably known the answer and looked for more technical answers on how exactly someone does data science. Then, you will stumble upon Python, the most popular data science tool (a programming language, to be specific) to date. But, how to get started? That is why you googled up and decided to open this article. There are numerous ways to get your Python ready to go. However, my favorite one is using Jupyter Notebook as the Integrated Development Environment (IDE). What is IDE, you asked? Just think of it as your workshop where you write your code and showcase what can your code do. You can write your code without IDE, but it will be more difficult. IDEs provide you with all the tools you need, check your syntax, and analyze what goes wrong on your code. Jupyter Note...