Perhaps, a solid grounding in the theory of probability, classical inference and linear algebra followed by some standard econometrics textbook (e.g. Johnston/ Wooldridge) and also some computational stats theory (e.g. James Gentle) followed by Python/ R (e.g. the Posit RStudio IDE that runs both scripts), assuming none of these steps are complete yet. Should be good for starters!!
Imo, Emmanuel Owusu , most important is learning to match the fit of a mathematical method with the economic subject researched, i.e. to find the right intersection between math and economics.
_________
I think that it is a relatively good approximation to truth — which is much too complicated to allow anything but approximations — that mathematical ideas originate in empirics. But, once they are conceived, the subject begins to live a peculiar life of its own and is … governed by almost entirely aesthetical motivations. In other words, at a great distance from its empirical source, or after much "abstract" inbreeding, a mathematical subject is in danger of degeneration. Whenever this stage is reached the only remedy seems to me to be the rejuvenating return to the source: the reinjection of more or less directly empirical ideas.
Jv Neumann
quoted in:
The Mathematician: in The Works of the Mind (1947) edited by R. B. Heywood, University of Chicago Press, Chicago
Besides supporting the recommendation by Niloy, start by writing its name correctly: econometricS.
A good understanding of theoretical, practical application, and continuous learning.
- Understand the Basics: Start with a solid grounding in the theory of probability, classical inference, and linear algebra.
- Learn Econometrics Models:
- Master the Tools: Familiarize yourself with econometrics software packages like R or Python.
- Stay Current: Keep up to date with the latest developments in the field.
With my little experience, I would advise aspiring students to begin their journey by focusing on building a solid foundation in mathematics, statistics, and economics during their undergraduate studies. This entails taking courses in microeconomics, macroeconomics, calculus, linear algebra, probability, and statistics, which provide the necessary theoretical groundwork for understanding econometric techniques. Additionally, students should actively seek out opportunities for hands-on experience through research projects or internships that involve econometric analysis, as practical application is integral to mastering the discipline.
Furthermore, I would encourage students to consider pursuing advanced degrees, such as master's or doctoral programs, to deepen their understanding of econometrics and enhance their career prospects. These programs often offer specialized coursework and research opportunities tailored to econometric analysis, allowing students to develop expertise in advanced statistical methods and quantitative modeling. Throughout their academic journey, students should also focus on building strong analytical, programming, and communication skills, as these are essential for conducting rigorous research and effectively communicating findings in both academic and professional settings. By diligently following these steps and remaining dedicated to their studies, aspiring econometrics students can position themselves for success in this dynamic and intellectually rewarding field.
To be good enough in linear algebra and Statistics and to use different econometrics softwares.
I think the starting point is not the mathematics or statistics involved in econometrics. Identify questions and issues about topics that you value and how econometrics is used to evaluate these topics. This is a fundamental step. This could be labor economics/econometrics, public policy assessments, economic growth/development, macrodynamic models, finance, econometric theory, etc. Talk to your teacher about topics that interest you. Ask about the applied and theoretical books most focused on your interests and start with the most basic and intermediate ones. Only then read the more advanced books. The level of mathematics/mathematical statistics largely depends on your objectives and the models in your area of interest. For example, knowing measurement and integration may not be very important. Knowing when the answer to your problem depends on predictions and causal effects (whether causal effects must consider the entire specification of detailed structural models or quasi-experimental and experimental techniques) can be much more important than mathematics. Ask questions and take them to your teacher. He won't know the answers to all of them but he will be able to guide you through some of them. In my case, I learned microeconometrics and evaluation of public policies in the area of poverty, inequality and development. But I started with the econometrics of the labor market. Of course I read mathematics and statistics books and even liked them. But my motivation was in the themes and the various questions about them.
Master your mathematics and statistics. Learn various techniques employed to estimate different data types (time series, cross-sectional data and panel data). Practice the codes and be inquisitive to find new ways of doing the things you have learned
Econometrics is an applied subject. We can learn it only by practising it. Mathematics and statistics come later. You Must first know your problem. Then the quantitative aspect of it.
You should now the variables that are needed to address your problem. And also the expected relationship. Economic Theory might help you. But also sociology, political science, anthropology, history or even common sense.
Then you turn to the nature of relationship by simple bivariate charts.
After all comes the econometrics theory.
You may see that often your first guess is wrong.
You may get unexpected relationship and/or insignificant relationship.
Now you need to reformulate your result.
The process goes on.
Read time series and learn more about statistics and econometric tests using software and programmes: EVIEWS , SPSS ,R , .
Try to master linear algebra and statistics and use softwares of econometrics