American Journal of Agricultural Economics, Vol. 97, No. 5 (October 2015), pp. 1494-1511 (18 pages) Food commodity price fluctuations have an important impact on poverty and food insecurity across the ...
After computing the sample autocovariance matrices, PROC STATESPACE fits a sequence of vector autoregressive models. These preliminary autoregressive models are used to estimate the autoregressive ...
Abstract: The Kullback information criterion, KIC, and its univariate bias-corrected version, KIC/sub c/, are two recently developed criteria for model selection. A small sample model selection ...
The vector autoregressive model has long been used for portfolio analysis, while a recent extension (VARX) incorporates exogenous factors. Despite its increased forecasting precision, the ...
Abstract: Dynamic multi-objective optimisation (DMO) handles optimisation problems with multiple (often conflicting) objectives in varying environments. This paper proposes vector autoregressive ...
This study examines how trade shocks that start in one large economy ripple through other countries and how long those effects stick around. Using quarterly bilateral-trade data for 2012-2023, the ...
Building a vector autoregressive model with R. My coursework for the course Time Series Analysis II (offered by University of Helsinki's Master's Programme in Mathematics and Statistics), spring 2020.
Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 183, No. 1 (2020), pp. 91-119 (29 pages) Output growth data for the UK regions are available at only annual frequency ...
Multivariate count time series arise in a wide range of applications, including the number of COVID-19 cases recorded each week in different counties of the Republic of Ireland. In this example, it is ...
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