Model selection in factor-augmented regressions with estimated factors
نویسندگان
چکیده
منابع مشابه
Variable Selection in Predictive Regressions
This chapter reviews methods for selecting empirically relevant predictors from a set of N potentially relevant ones for the purpose of forecasting a scalar time series. I first discuss criterion based procedures in the conventional case when N is small relative to the sample size, T . I then turn to the large N case. Regularization and dimension reduction methods are then discussed. Irrespecti...
متن کاملBayesian variable selection for finite mixture model of linear regressions
We propose a Bayesian method for variable selection in the finite mixture model of linear regressions. The model assumes that the observations come from a heterogeneous population which is a mixture of a finite number of sub-populations. Within each sub-population, the response variable can be explained by a linear regression on the predictor variables. So the whole data set can be modeled by a...
متن کاملUnexpected Banking Loan Losses in an Estimated DSGE Model
In spite of realizing more loss than expected and reserved provision in loaning process, some of our banks avoid recognizing the losses, through extension of the loan contracts and consequently do not shift the realized losses to their capital. With this in mind, the major objective of this study is to design a frame-work, through which we can explain the differences between the results of t...
متن کاملA Generalized Factor Model with Local Factors∗
I extend the theory on factor models by incorporating “local” factors into the model. Local factors affect a decreasing fraction of the observed variables. This implies a continuum of eigenvalues of the covariance matrix, as is commonly observed in applications. I derive conditions under which local factors will be estimated consistently using the common principal component estimator. I further...
متن کاملModel Uncertainty in Cross-country Growth Regressions
We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is very spread among many models suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results support this claim. In contrast with Levine and Renelt (1992), our results broadly support the more “optim...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Econometric Reviews
سال: 2020
ISSN: 0747-4938,1532-4168
DOI: 10.1080/07474938.2020.1808371