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Nowcasting from cross-sectionally dependent panels

Fosten, Jack; Nandi, Shaoni - In: Journal of applied econometrics 38 (2023) 6, pp. 898-919

Persistent link: https://www.econbiz.de/10014432199

Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions

Andersen, Torben G. - 2020

This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all – or a subset – of the variables may be fractionally integrated and the...

Persistent link: https://www.econbiz.de/10012831312

Dynamic Implied Correlation Modeling and Forecasting in Structured Finance

Löhr, Sebastian - 2015

derivatives such as synthetic single-tranche collateralized debt obligation swaps. This paper suggests a dynamic panel regression …-specific effects on implied tranche correlations. The implied-correlation forecasts of tranche spreads are compared to forecasts using … correlation model …

Persistent link: https://www.econbiz.de/10013034784

Least Squares Estimation of Large Dimensional Threshold Factor Models

Massacci, Daniele - 2017

super consistent, with convergence rate that depends on the time and cross-sectional dimensions of the panel, and it does …

Persistent link: https://www.econbiz.de/10012971327

Forecasting inflation in Argentina

Garegnani, María Lorena; Gómez Aguirre, Mauricio - 2018

During the year 2016, the Central Bank of Argentina has begun to announce inflation targets. In this context, providing the authorities of good estimates of relevant macroeconomic variables turns out to be crucial to make the pertinent corrections to reach the desired policy goals. This paper...

Persistent link: https://www.econbiz.de/10011846246

A Machine Learning Approach to Estimating Large Positive Definite Covariance Matrix of High Frequency Data

Cui, Liyuan - 2019

This paper proposes a novel covariance estimator via a machine learning approach when both the sampling frequency and covariance dimension are large. Assuming that a large covariance matrix can be decomposed into low rank and sparse components, our method simultaneously provides a consistent...

Persistent link: https://www.econbiz.de/10012867396

A penalized two-pass regression to predict stock returns with time-varying risk premia

Bakalli, Gaetan; Guerrier, Stéphane; Scaillet, Olivier - 2021

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

Persistent link: https://www.econbiz.de/10012487589

Assessing and relaxing assumptions in quasi-simplex models

Cernat, Alexandru; Lugtig, Peter; Uhrig, S.C. Noah; … - 2014

reliability of survey measures. Using data from the British Household Panel Survey this paper shows how the assumptions of the …

Persistent link: https://www.econbiz.de/10010251137

Forecasting with Panel Data : Estimation Uncertainty Versus Parameter Heterogeneity

Pesaran, M. Hashem; Pick, Andreas; Timmermann, Allan - 2022

We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with …-sectional (N) and time (T) dimensions and varying degrees of parameter heterogeneity. We investigate conditions under which panel …

Persistent link: https://www.econbiz.de/10013292495

Baltagi, Badi H.; Pirotte, Alain - 2011

This paper considers various estimators using panel data seemingly unrelated regressions (SUR) with spatial error … correlation. The true data generating process is assumed to be SUR with spatial error of the autoregressive or moving average type …, and heterogeneous versus homogeneous panel data models …

Persistent link: https://www.econbiz.de/10014183698

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