Results 131 to 140 of about 23,659 (294)
Robust estimation of the vector autoregressive model by a trimmed least squares procedure. [PDF]
The vector autoregressive model is very popular for modeling multiple time series. Estimation of its parameters is done by a least squares procedure. However, this estimation method is unreliable when outliers are present in the data, and there is a need
Croux, Christophe, Joossens, Kristel
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The Impact of Uncertainty on Forecasting the US Economy
Journal of Forecasting, EarlyView.ABSTRACT This paper examines the predictive value of uncertainty measures for key macroeconomic indicators across multiple forecast horizons. We evaluate how different uncertainty proxies—economic policy uncertainty (EPU), VIX, geopolitical risk, and measures of macroeconomic and financial uncertainty—enhance forecast accuracy for industrial production,
Angelica Ghiselli
wiley +1 more source
CONDITIONAL FORECASTING FOR THE U.S. DAIRY PRICE COMPLEX WITH A BAYESIAN VECTOR AUTOREGRESSIVE MODEL
A dynamic Bayesian Vector Autoregressive model of the U.S. dairy price complex is estimated based on the Normal-Wishart distribution. The Gibbs sample technique is use with the Normal-Wishart distribution to provide conditional forecasts on the future ...
Thompson, Stanley R. +2 more
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Using DSGE and Machine Learning to Forecast Public Debt for France
Journal of Forecasting, EarlyView.ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
wiley +1 more source
Stock Prices and Economic Fluctuations: A Markov Switching Structural Vector Autoregressive Analysis [PDF]
The role of expectations for economic fluctuations has received considerable attention in recent business cycle analysis. We exploit Markov regime switching models to identify shocks in cointegrated structural vector autoregressions and investigate ...
Markku Lanne, Helmut Luetkepohl
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Journal of Forecasting, EarlyView.ABSTRACT This paper adopts a bivariate Markov‐switching multifractal (BMSM) model to reexamine comovement in SV between commodity, foreign exchange (FX), and stock markets. After the 2007–2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio
Ruipeng Liu +3 more
wiley +1 more source
General-to-Specific Model Selection Procedures for Structural Vector Autoregressions [PDF]
Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse ...
Hans-Martin Krolzig
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Evaluating Forecasts at Multiple Horizons: An Extension of the Diebold–Mariano Approach
Journal of Forecasting, EarlyView.ABSTRACT Forecast accuracy tests are fundamental tools for comparing competing predictive models. The widely used Diebold–Mariano (DM) test assesses whether differences in forecast errors are statistically significant. However, its standard form is limited to pairwise comparisons at a single forecast horizon.
Andrew Grant +2 more
wiley +1 more source
The Influence of South East Asia Forest Fires on Ambient Particulate Matter Concentrations in Singapore: An Ecological Study Using Random Forest and Vector Autoregressive Models. [PDF]
Int J Environ Res Public Health, 2020 Rajarethinam J, Aik J, Tian J.
europepmc +1 more source
This paper examines the effects of monetary policy in Pakistan economy using a data rich environment. We used the Factor Augmented Vector Autoregressive (FAVAR) methodology, which contains 115 monthly variables for the period 1992:01 to 2010:12.
Munir, Kashif, Qayyum, Abdul
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