Inflation Behavior in Top Sukuk Issuing Countries: Using a Bayesian Log-linear Model
author
Abstract:
This paper focused on developing a model to study the effect of sukuk issuance on the inflation rate in top sukuk issuing Islamic economies at 2014. For this purpose, as the available sample size is small, a Bayesian approach to regression model is used which contains key supply and demand side factors in addition to the outstanding sukuk volume as potential determinants of inflation rate. In the suggested model, inflation rate variable shows an apparent right skewness and the efficiency of log transformation for this variable is confirmed via Box-Cox approach. To give Bayesian estimators of the regression parameters, we have implemented an MCMC approach including 100,000 iterations in the WinBUGS software. The results show that sukuk volume is a significant determinant of inflation in selected Islamic countries, but only in the well-developed capital market economies its increase could decline the rate of inflation and so sukuk could be used as a policy instrument for controlling inflation. Also the Bayesian estimation of the other parameters shows that increase of money growth and exchange rate growth lead to higher inflation rates.
similar resources
Asymmetric Behavior of Inflation in Iran: New Evidence on Inflation Persistence Using a Smooth Transition Model
T his paper investigates the asymmetric behavior of inflation. We use logistic smooth transition autoregressive (LSTAR) model to characterize the regime-switching behavior of Iran’s monthly inflation during the period May 1990 to December 2013. We find that there is a triple relationship between the inflation level, its fluctuations and persistence. The findings imply that the behavi...
full textBayesian paradigm for analysing count data in longitudina studies using Poisson-generalized log-gamma model
In analyzing longitudinal data with counted responses, normal distribution is usually used for distribution of the random efffects. However, in some applications random effects may not be normally distributed. Misspecification of this distribution may cause reduction of efficiency of estimators. In this paper, a generalized log-gamma distribution is used for the random effects which includes th...
full textA New Method for Improving Computational Cost of Open Information Extraction Systems Using Log-Linear Model
Information extraction (IE) is a process of automatically providing a structured representation from an unstructured or semi-structured text. It is a long-standing challenge in natural language processing (NLP) which has been intensified by the increased volume of information and heterogeneity, and non-structured form of it. One of the core information extraction tasks is relation extraction wh...
full textasymmetric behavior of inflation in iran: new evidence on inflation persistence using a smooth transition model
t his paper investigates the asymmetric behavior of inflation. we use logistic smooth transition autoregressive (lstar) model to characterize the regime-switching behavior of iran’s monthly inflation during the period may 1990 to december 2013. we find that there is a triple relationship between the inflation level, its fluctuations and persistence. the findings imply that the behavior of infla...
full textBayesian Selection of Log-Linear Models
A general methodology is presented for nding suitable Poisson log-linear models with applications to multiway contingency tables. Mixtures of multivariate normal distributions are used to model prior opinion when a subset of the regression vector is believed to be nonzero. This prior distribution is studied for two and three-way contingency tables, in which the regression coe cients are interpr...
full textDyadic Prediction Using a Latent Feature Log-Linear Model
In dyadic prediction, labels must be predicted for pairs (dyads) whose members possess unique identifiers and, sometimes, additional features called side-information. Special cases of this problem include collaborative filtering and link prediction. We present the first model for dyadic prediction that satisfies several important desiderata: (i) labels may be ordinal or nominal, (ii) side-infor...
full textMy Resources
Journal title
volume 6 issue 1
pages 29- 46
publication date 2017-03-16
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023