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Економетрика II (англійською мовою)
Викладач: доц. Семко Р.Б.
3 кредит. ЄКТS, 2 год./тижд., 7 семестр, залік (забезпечує кафедра фінансів)
Limited Dependent Variable (LDV) models are very popular in modelling and forecasting different real-life outcomes, such as in constructing credit scoring models by commercial banks, predicting company bankruptcies, determining the probability of winning elections or sports matches, weather forecasters calculating the probability of rain, or SMM attempting to determine whether customers will click on Google ads. What factors influence respondent answers? How do people decide what car color to select? How many patents can Apple receive with an additional one billion US dollars of R&D expenditures or What determines the number of banking outlets in the Ukrainian regions? What factors impact the amount of issued bank credits in foreign currency? These and many other questions can be answered and problems solved using LDV models. In addition, some of the models examined in the course are frequently used in many other areas, e.g. Regularized Logistic Regression is a workhouse in personalized recommender systems to suggest new friends in social networks. All LDV regression models will be estimated using the Maximum Likelihood Method, and for each empirical model, underlying latent models will be provided.
To estimate and analyze LDV models, R package will be used.
Students will be able to construct limited dependent variable models, estimate and interpret their coefficients, and set the corresponding underlying latent models. In addition, they will practice applying these regression models to real-life financial and economic cases and academic research.
