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Oracle inequalities for high-dimensional panel data models

Kock, Anders Bredahl - School of Economics and Management, University of Aarhus - 2013

the estimation error of the Lasso under two different sets of conditions on the covariates as well as the error terms … constants. These results are then used to show that the Lasso can be consistent in even very large models where the number of … regressors increases at an exponential rate in the sample size. Conditions under which the Lasso does not discard any relevant …

Persistent link: https://www.econbiz.de/10010851282

Estimating High-Dimensional Time Series Models

Medeiros, Marcelo C.; Mendes, Eduardo F. - School of Economics and Management, University of Aarhus - 2012

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time …

Persistent link: https://www.econbiz.de/10010851219

Oracle Inequalities for High Dimensional Vector Autoregressions

Kock, Anders Bredahl; Callot, Laurent A.F. - School of Economics and Management, University of Aarhus - 2012

This paper establishes non-asymptotic oracle inequalities for the prediction error and estimation accuracy of the LASSO … in stationary vector autoregressive models. These inequalities are used to establish consistency of the LASSO even when … excluded. Next, non-asymptotic probabilities are given for the Adaptive LASSO to select the correct sign pattern (and hence the …

Persistent link: https://www.econbiz.de/10010851258

Oracle Inequalities for Convex Loss Functions with Non-Linear Targets

Caner, Mehmet; Kock, Anders Bredahl - School of Economics and Management, University of Aarhus - 2013

This paper consider penalized empirical loss minimization of convex loss functions with unknown non-linear target functions. Using the elastic net penalty we establish a finite sample oracle inequality which bounds the loss of our estimator from above with high probability. If the unknown target...

Persistent link: https://www.econbiz.de/10010851265

On the Selection of Common Factors for Macroeconomic Forecasting

Giovannelli, Alessandro; Proietti, Tommaso - School of Economics and Management, University of Aarhus - 2014

We address the problem of selecting the common factors that are relevant for forecasting macroeconomic variables. In economic forecasting using diffusion indexes the factors are ordered, according to their importance, in terms of relative variability, and are the same for each variable to...

Persistent link: https://www.econbiz.de/10011084734

Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

Kock, Anders Bredahl - School of Economics and Management, University of Aarhus - 2010

This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular, we show that the Bridge estimator is oracle efficient. It can correctly distinguish between...

Persistent link: https://www.econbiz.de/10008525438

Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search

Grassi, Stefano; Proietti, Tommaso - School of Economics and Management, University of Aarhus - 2011

An important issue in modelling economic time series is whether key unobserved components representing trends, seasonality and calendar components, are deterministic or evolutive. We address it by applying a recently proposed Bayesian variable selection methodology to an encompassing linear...

Persistent link: https://www.econbiz.de/10009293967

Bayesian stochastic model specification search for seasonal and calendar effects

Grassi, Stefano; Proietti, Tommaso - School of Economics and Management, University of Aarhus - 2011

We extend a recent methodology, Bayesian stochastic model specification search (SMSS), for the selection of the unobserved components (level, slope, seasonal cycles, trading days effects) that are stochastically evolving over time. SMSS hinges on two basic ingredients: the non-centered...

Persistent link: https://www.econbiz.de/10008854104

Characterizing economic trends by Bayesian stochastic model specification search

Grassi, Stefano; Proietti, Tommaso - School of Economics and Management, University of Aarhus - 2011

We extend a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. In particular, we focus on autoregressive models with possibly time-varying intercept and slope and decide on...

Persistent link: https://www.econbiz.de/10009020199

Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice

Callot, Laurent A. F.; Kock, Anders B.; Medeiros, Marcelo C. - School of Economics and Management, University of Aarhus - 2014

autoregressive models. We propose using Lasso-type estimators to reduce the dimensionality to a manageable one and provide strong …

Persistent link: https://www.econbiz.de/10011079278