Methodological reflexions on non structural modelling: an approach by VAR models and their dynamic extensions

Meuriot, Véronique

doi:10.4000/msh.10423

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…All the variables which were not stationary according to their orders of integration were differentiated in order to make them stationary. Indeed, macroeconomic or macro financial modeling within the context of the VAR (Vector Auto regressive Model) requires that the variables be stationary (Meuriot, 2008). The tables in appendix 1 give an account of the treatments carried out on the variables country by country.…”

Section: Variables and Data Processingmentioning

confidence: 99%

Financial Accelerator and Bank Excess Liquidity in Cemac Zone

Tchounga¹,

M’bakob²

2022

AJEF

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In this paper, we broaden the debate on the determinants of bank excess liquidity by focusing on a new mechanism. Using time series data from six CEMAC countries and using shock simulation in a structural VAR as well as Cointegration analysis in an ARDL model, the empirical analysis shows that the financial rigidity caused by the increase in the information asymmetry premium leads to a fall in investment which weakens economic activity. The fall in economic activity amplifies the increase in information asymmetry premium resulting in an increase of free reserves. Finally when the effect of the financial accelerator is reduced by stretching the information asymmetry premium towards zero, then the refunding policy through calls to tender favors a decrease of interest rates, a profusion of credit and consequently the increase of investments and consumption. We suggest all measures aimed at reducing the asymmetry of information on the credit market, in particular, the creation of credit offices and / or public credit registers, the creation of rating agencies for companies and individuals, improvement of the quality of institutions whose poor quality leads to the camoufl age of information and moral hazards.

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Section: Variables and Data Processingmentioning

confidence: 99%