This page was made with the intent to share some articles and/or links that, in one way or another, shaped my academic career.

• SciSpace - This webpage uses AI to help in the literature review by providing the sources for all results. It is remarkably better than other AIs because in addition to having only real studies, you can filter results for articles that are highly cited in a given field, or published in top-notch journals.

• Guess the Correlation - This game is very intuitive, you observe a scatterplot and try to guess the correct correlation of the variables. Warning: you may spend more time than you should on this game.

• The Evolution of Trust - This game shows how game theory can be though and provide an interesting - and more importantly, visual - aspect of agents relating in an economy. You can change agents' type and economy composition to check if the economy thrives.

• Writing Tips for PhD Students - Cochrane (2005) - Cochrane presents many hints on how to write a paper in finance/economics, and more importantly (in my humble view) on how to present (and sell) a paper.

• How to Write Applied Papers in Economics - Bellemare (2020) - Bellemare presents what is most commonly seen in applied papers. He suggests not only the way to make tables and report statistics but also how to write convincingly. Further, I particularly liked it when he explains how to write a good estimation and identification strategy section.

• Writing scientific articles like a native English speaker: top ten tips for Portuguese speakers - Marlow (2014) - Professor Marlow provides useful insights for academic writing by showing the common mistakes Portuguese speakers make when writing in English.

• How to Build an Economic Model in Your Spare Time - Varian (1997) - One of the first papers I read in my master's. Varian presents lightly the process of conducting theoretical research. The main piece of advice I take from him is to look for real-life problems to assess if it is worth pursuing to answer.

• Base dos Dados - Brazil is well-known for having numerous interesting datasets. However, not always they are well-prepared or agree with each other in terms of identifiers. This website provides access to several cleaned datasets and tables with "from/to" in terms of identifiers. In this link, I provide the municipality codes for several sources. Consider donating to this non-profit institute.

• Econometrics Academy - Any Katchova (2013) - This website shows a short theory, an example, and the example's code in different software (SAS, R, Stata, SPSS) of several econometric models. I strongly advise consulting this page to "see" what is happening, especially if you are doing more theoretical statistics or econometrics classes.

• Masayuki Kudamatsu's Webpage - In "Tips 4 Economists" mister Masayuki presents an extensive catalog of texts elaborated by renowned professors from all parts of the world. The texts provide important suggestions for all steps of economic researchers' careers. His website inspired me to produce this page. Check his other pages, he also compiled extensive material about the Stata programming language.

• Paul Goldsmith-Pinkham Presentation  - The scholar provides insightful suggestions for effective presentations. His hints are particularly important for those using Beamer in LaTeX.

• Guia Brasileiro de Análise de Dados (Brazilian Data Analysis Guide) - This book describes the main Brazilian datasets used in studies all over the globe. It also provides a brief introduction to the causal methods used in studies relying on secondary data with little mathematics, being useful for researchers in several areas.

• Endogeneity in Empirical Corporate Finance - Roberts & Whited (2013) - Another source of systematized econometric review with applied examples. Despite focusing on finance, the methods are the same and the examples might provide insights into researchers of other fields of study.

• Applied Tips for Applied Micro RAs - Alfonsi (2021) - A very useful piece of advice for those starting to code and work as Research Assistants, and also for those who code for a long time and can be surprised by how non-transparent their work can be.