What are new techniques are current nowadays in Econometrics, especially for PREDICTION AND FORECASTING
Zulfiqar Ali Mir , Probabilistic/Bayesian forecasting for sure is trending right now, see for example this fresh-out-of-the-oven paper:
Article Probabilistic forecasting of heterogeneous consumer transact...
and also:
Article Bayesian Forecasting of Many Count-Valued Time Series
You can find a new topic at the link below :
file:///C:/Users/Administrator/Downloads/wpiea2020045-print-pdf.pdf
Sigma F.Y , indeed there are many, but which ones are the interesting ones? I believe probabilistic/Bayesian forecasting in my opinion :)
Dear Zulfiqar,
Relatively new techniques: Choice models (eg. conditional logit, multinomial probit, mixed logit, rank-ordered probit, etc); Nonlinear Dynamic Stochastic General Equilibrium (DSGE) model; Nonlinear models with AR and SAR specifications (eg. Threshold Autoregressive (TAR) models, Smooth Transition Regression (STR – logistic vs. exponential) models; Fractionally Integrated GARCH models (FIGARCH); etc.
Prediction/forecasting: Bayesian predictions (check model fit and predict out-of-sample observations); etc.
https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwiOh5LTlaXuAhUHyxoKHdkhCzcQFjAAegQIARAC&url=https%3A%2F%2Fwww.springer.com%2Fgp%2Fbook%2F9783030542511&usg=AOvVaw3GD-H9npYZzR4wwfjxub_p
The technique that you will use vary depending on your prediction purpose. Generally, techniques involving nonlinear structures are at the forefront. Nonparametric and semiparametric approaches, Bayesian estimation, Ridge and Lasso estimation, methods that including Machine Learning produce the most appropriate results for current issues.