Welcome to this MOOC on Enjoyable Econometrics. In this first lecture, I will explain what we will do now and in the lectures to come. Did you know that you can use econometric methods and techniques to analyze all kinds of situations from your everyday life? You could think of the relation between dates of birth and the achievement of soccer players, but you could also predict the color of next year. This MOOC deals with the application of econometric methods and techniques to a variety of questions, often and on purpose outside the realm of economics. Usually, economic matters are considered for questions and macroeconomics, labor economics or finance, amongst others. At this MOOC however, we will encounter many alternative illustrations concerning football, postage stamps, colors, and what have you. All data that we will use can be found on the following website. An important motivation for me to make this MOOC is to emphasize that econometric models and methods can also be applied to more unconventional settings, which are typically settings where the practitioner has to collect his or her own data first. Such collection can be done by carefully combining existing databases but also by holding surveys or running experiments. Sometimes these data are available in a clean and nice format, but it can also be available only in a messy and noisy format. But quite often, they are not readily available at all, so you often need to collect data yourselves. Not to worry. I will show you that data are everywhere. Conventional econometrics lectures usually introduce a method and then they apply it. I know however that in real life, it does not work that way. In real life, first there is a question, then there is the collection of hopefully relevant data, and finally, there is the method. That brings me to the main idea of this MOOC, and also the associated book with the same title that appeared with Cambridge University Press in 2018. As a consequence, and you will see, the lectures in this MOOC therefore have a format opposite to what is typically done. The main content of each lecture discusses empirical questions like, do home teams get more penalty kicks than away teams? Are there less goals when away supporters cannot come? Can we predict the color of next year? On separate slides, I will collect the relevant methods and techniques for these questions. Of course, this MOOC does not claim to be a general introduction to econometric methods and techniques. My main claim however, is that it hopes to arouse enthusiasm for the application of those methods and techniques, and in fact to illuminate a little bit how econometricians work. New methods have always been designed and developed just because a question or the data required that new method. The title of this MOOC, Enjoyable Econometrics, may sound like an oxymoron. How can something like this be enjoyable? One cause for this doubt may be a cursory look into an introductory textbook on econometrics, where one may bump into text like this. Now, what could that possibly mean? Most textbooks on econometrics typically focus on economic relations in the macroeconomic world or in finance. So the focus often is on gross domestic product, unemployment, and inflation or on the New York Stock Exchange or the Nikkei index. In the present MOOC however, I address other questions. Of course, there is no econometrics without mathematics, but for this MOOC I promise I will try to keep the mathematics to a minimum. Doesn't that sound enjoyable? In the first videos, I will use some of such notation too. In later lectures, the discussion of matters is relegated to separate slides that you can study if you're interested. This MOOC intends to do a couple of things. First, I will outline a few very basic tools of economics. That is, the mean, the median, standard deviation, covariance, and correlation. We do need those tools as almost everything is taken up from there. I have one more closing note. Another important motivation for making this MOOC is that I hope that after this you will embark on a truly introductory course on Econometric Methods. My hope is that I attract new comers by showing that econometrics also can involve smart ways of formulating research questions and smart ways of data collection. So when people maybe shied away from the mainstream applications of econometrics, it is hoped that this MOOC full with alternative research questions and innovative datasets will provide a motivation to embark on a primer cause of economics. But first for now, let's get started.
