Reducing the state space dimension in a large TVP-VAR

Chan, Joshua C. C.; Eisenstat, Eric; Strachan, Rodney W.

doi:10.1016/j.jeconom.2019.11.006

Cited by 59 publications

(55 citation statements)

References 36 publications

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“…Sankaran et al [ 119 ], Rana and Sharma [ 120 , 121 ], and Wang and Ngene [ 122 ] suggested to overcome this problem by using the Wald or modified Wald (MWald) tests, but Hayashi et al [ 123 ] and Lemonte [ 124 ] demonstrated that, in small samples when used empirically to search for unimportant parameters, the Wald test procedure could be misleading. In furtherance of Zhang et al [ 125 ], Mao et al [ 126 ], Adebayo [ 97 ], and Chan et al [ 127 ], we used variance decomposition instead of the Wald test to explore the strengths of inter-variables causal interactions and to reveal potential causality impacts. The method was applied for nine consecutive periods from July 2020 till March 2021.…”

Section: Methodsmentioning

confidence: 99%

Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries

Erokhin

Tianming

2020

IJERPH

246

173

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The stability of food supply chains is crucial to the food security of people around the world. Since the beginning of 2020, this stability has been undergoing one of the most vigorous pressure tests ever due to the COVID-19 outbreak. From a mere health issue, the pandemic has turned into an economic threat to food security globally in the forms of lockdowns, economic decline, food trade restrictions, and rising food inflation. It is safe to assume that the novel health crisis has badly struck the least developed and developing economies, where people are particularly vulnerable to hunger and malnutrition. However, due to the recency of the COVID-19 problem, the impacts of macroeconomic fluctuations on food insecurity have remained scantily explored. In this study, the authors attempted to bridge this gap by revealing interactions between the food security status of people and the dynamics of COVID-19 cases, food trade, food inflation, and currency volatilities. The study was performed in the cases of 45 developing economies distributed to three groups by the level of income. The consecutive application of the autoregressive distributed lag method, Yamamoto’s causality test, and variance decomposition analysis allowed the authors to find the food insecurity effects of COVID-19 to be more perceptible in upper-middle-income economies than in the least developed countries. In the latter, food security risks attributed to the emergence of the health crisis were mainly related to economic access to adequate food supply (food inflation), whereas in higher-income developing economies, availability-sided food security risks (food trade restrictions and currency depreciation) were more prevalent. The approach presented in this paper contributes to the establishment of a methodology framework that may equip decision-makers with up-to-date estimations of health crisis effects on economic parameters of food availability and access to staples in food-insecure communities.

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Section: Methodsmentioning

confidence: 99%

Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries

Erokhin

Tianming

2020

IJERPH

246

173

View full text Add to dashboard Cite

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“…Chan (2018), for example, uses this speci…cation with the Savage-Dickey density ratio to compute the Bayes factor for the restriction to time-invariance of parameters in various models of in ‡ation. Towards the end of this section we discuss an extension and generalization of the speci…cation in Frühwirth-Schnatter and Wagner (2010) by Chan, Eisenstat and Strachan (2020).…”

Section: Approaches To Overparameterizationmentioning

confidence: 99%

“…For example, simple measures of un-certainty are the highest posterior density or the percentile range (e.g., inter-quartile range) for objects of interest. Chan, Eisenstat and Strachan (2020) present an approach that provides a full MCMC exploration of the posterior for a high-dimensional TVP-VAR with stochastic volatility (TVP-VAR-SV). This approach also imposes a change in the model speci…cation but one that is suggested by the data.…”

Section: Approaches To Overparameterizationmentioning

confidence: 99%

“…This simple and empirically supported restriction results in a reduction of the dimension of the model by around 90% to 99%, thereby making the model computable. Chan et al (2020) improve computation by implementing a number of techniques: the rank restriction, they estimate the VAR in structural rather than reduced form, generalize the non-centered parameterization of Frühwirth-Schnatter and Wagner (2010) to the matrix case, employ parameter expansions and use the precision sampling approach of Chan and Jeliazkov (2009).…”

Section: Approaches To Overparameterizationmentioning

confidence: 99%

“…The approach in Chan et al (2020) works by reducing the dimension of the parameter space by reducing the sources of variation in the states. Koop, Korobilis and Pettenuzzo (2019) achieve a reduction in the dimension of the parameter space by using compressed regression to reduce the dimension of the data.…”

Section: Approaches To Overparameterizationmentioning

confidence: 99%

See 2 more Smart Citations

Bayesian State Space Models in Macroeconometrics

Chan

Strachan

2020

SSRN Journal

Self Cite

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State space models play an important role in macroeconometric analysis and the Bayesian approach has been shown to have many advantages. This paper outlines recent developments in state space modelling applied to macroeconomics using Bayesian methods. We outline the directions of recent research, specifically the problems being addressed and the solutions proposed. After presenting a general form for the linear Gaussian model, we discuss the interpretations and virtues of alternative estimation routines and their outputs. This discussion includes the Kalman filter and smoother, and precision based algorithms. As the advantages of using large models have become better understood, a focus has developed on dimension reduction and computational advances to cope with high-dimensional parameter spaces. We give an overview of a number of recent advances in these directions. Many models suggested by economic theory are either non-linear or non-Gaussian, or both. We discuss work on the particle filtering approach to such models as well as other techniques that use various approximations -to either the time t state and measurement equations or to the full posterior for the states -to obtain draws.

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Time‐varying pure contagion effect between energy and nonenergy commodity markets

Gong

Jin

Sun

2022

Journal of Futures Markets

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This paper combines the Kalman filtering technique and the time‐varying parameter vector autoregression model with stochastic volatility model to explore pure contagion effects between energy and nonenergy (i.e., industrial metals, precious metals, and agricultural) commodity markets. Empirical results show the significant pure contagion effects between energy and industrial metals markets in most periods, while pure contagion effects between energy and precious metals and agricultural markets occur only in a few specific periods. Comparing the level of pure contagion effects between different commodity markets, energy is still the main price transmitter. In addition, with the acceleration of the global commodity market financialization process, the frequency and harm of pure contagion effects are gradually increasing. Notably, the COVID‐19 pandemic is emerging as another major crisis after the global financial crisis, exacerbating the pure contagion effects between energy and precious metals and agricultural markets.

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Reducing the state space dimension in a large TVP-VAR

Cited by 59 publications

References 36 publications

Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries

Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries

Bayesian State Space Models in Macroeconometrics

Time‐varying pure contagion effect between energy and nonenergy commodity markets

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