Applied Econometric model building
We narrate econometrics using illustrations from your subject(s)! Our hands-on approach in Econometric model building is based upon the following considerations:
Conceptualization:
We start by differentiating between theory, statistics, and mathematics and how their integration makes econometrics a new great science.
Unlike typical parametric or non-parametric tools of data analysis, we learn how to incorporate both quantitative and qualitative variables in the specification of econometric models.
Then we proceed towards presentations of assumptions of the ‘Ordinary Least Squares’ (OLS), using graphs, to learn how the assumptions of the ‘Ordinary least squares’ ensure the best, linear and unbiased estimators.
The functionality of econometric model building:
It is also being narrated with due diligence on how econometrics helps in ‘theory construction’, ‘theory testing’, ‘policy appraisal’, and in the domain of ‘forecasting and prediction’.
Use of visual tools and algebraic manipulations:
For quite some time, Econometrics uses matrices and advanced calculus, which makes this great science somewhat mechanical in nature.
In addition to the use of algebraic manipulations, we prioritize using graphical and visual tools as the basis of structuring equations and econometric expressions.
Data mining, empiricism, and emphasis on the applied model building:
Data mining and exploration are being considered as key strengths of quality econometric models. Using different tools of parametric and nonparametric statistics, key attributes and characteristics of the data are explored.
From the initial specification of econometric models to the consolidation of econometric models, it requires critical assessment and critical judgment about the significance and insignificance of potential regressors. This not only requires good econometrician thinking but a grasp on empirics as well.
How desirable properties of estimators are affected, if assumptions of OLS are violated :
It is imperative for us to learn about the implications of the violation of assumptions such as the presence of specification biases, measurement biases, heteroscedasticity, high multicollinearity, serial correlation, etc. on the desired properties of estimators.
Model specification and estimation choices are primarily based on apprehensions in this regard. Accordingly, we discuss specialized econometric methods on how to deal with each of the violations.
Relevance and applicability:
In addition to our considerations for dealing with violations of OLS assumptions, we emphasize the relevance of econometric models for different types of data. Econometric modeling choices can change considerably for time series, survey, and panel data formats.
Specialized models for binary, ordinal, categorical, and count data are discussed in due detail to avoid any criticism at the stage of the defense.
Domains of applications of econometric modeling:
Econometric tools may effectively be applied in the domains of business administration, economics, sociology, psychology, political science, media studies, education, and medical sciences.
Different applications of econometrics are termed ‘Sociometrics’ and ‘Psychometrics’. It is important to learn that for quite some time, the emphasis of international literature and research has tilted towards the application of model building.
Students and researchers who have a full career ahead, need to gain expertise in quantitative model buildings so as to avoid bounded rationality.
Supplementing digitalization resources:
We supplement the model-building experience with some useful packages such as Stata, Minitab, and SPSS.
To further facilitate digitized learning in online tutoring, graphical/digital tablets, the Microsoft Whiteboard, and screen sharing options are used, so that students get the feel of a live classroom.
Model evaluation and interpreting results:
Once econometric models are furnished, we urge the extraction of findings, so as to validate the research hypothesis. For that matter, we give high value to technical underpinnings such as rationalizing regression coefficients, measuring model utility, testing the reliability of the estimated model, and testing the estimated models for potential violations of OLS assumptions: specification biases.
About the Econometrics Supervisor:
Our faculty in Econometrics has over 15 years of experience in teaching Theory of Econometrics, Applied Econometrics, and Time-Series Econometrics, at the Bachelor’s and Master’s levels.
In addition to that, the faculty person developed a series of econometrics courses for students of different social and behavioral sciences.
An author of journal articles and a thesis supervisor.
Reviews and recommendations
Kyla
The inspirational and supportive tutor goes the extra mile using examples and illustrations, to ensure I understood difficult and complex topics. Articulate personality and precision in interpersonal communication. I am glad to have learned from him.
Kari
He has excellent command over applied econometric modeling and a commendable ability to evaluate and engage with technical matters such as model interpretation and testing the fitted model for specification biases. A dedicated professional!
Smith
Professionally sound, technically competent, and has good pedagogic abilities! He helped me a lot with the theory of econometrics and topics in financial econometrics. A resourceful person!
Mark
To anyone struggling with Applied Econometrics, I would highly recommend seeking guidance from ‘Profess’ faculty, as he explains things clearly and prepared the lessons carefully.
Michael
While preparing for my master’s dissertation, I was looking for someone who can help me with ARIMA and SARIMA modeling. He has excellent command and strong foresight in furnishing research designs, in assessing the academic worth of methodological choices, and how to advance a rather naive research notion into a well-structured hypothesis, and the model specification.
Sasha
What a coherent and effective platform providing customized learning and knowledge for students all across, through such an extensive array of technical and conceptual areas of study! The subjects offered are highly useful for college/university students.
I got Profess services for my post-graduate research thesis, and the way I was guided and taught on both basic and advanced levels such as Applied Econometrics, Data Analysis tools, Questionnaire design, Research Methodology, and Inferential Statistics is what has built my trust in their services and faculty.
Using the same learning skills I have been able to present research papers at several International Conferences. Must say this forum is ideal for social sciences and research students…
Thanks to Profess for your thorough, easy-to-access, and exceptional services!
Gard
I am more than happy with the teaching. He helped me a great deal with Research and Econometrics. Efficient and very easy to communicate with; which reflects upon his skills as a teacher. Highly recommended for research and econometric modeling.
Dr. Haider
As a teacher and researcher, I found him very hardworking, efficient, diligent, resourceful, and full of energy. He has earned his respect among his teachers, peers, colleagues, students, friends, and family due to his cooperative behavior, thought-provoking arguments, and resilience to embrace tough situations, good judgment, and decision making. He always digs deep into the concepts and makes them comprehensible to his students.
He is a good listener and an extraordinary speaker. He has researched and supervised very diverse topics of Economics and Business which shows his untiring work and commitment to his students and institution. His analytical and quantitative skills are at par excellent. He has the great ability to motivate and inspire students and fellow researchers. His ability to lead a team is exceptional. His teammates and students consider him a tough workmaster but still gravitate around him.