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The predictive power of the term structure of interest rates : the case of Jordan

This thesis investigates whether the short end of the term structure has the ability to predict the future movements in short term rates and the inflation rate using data from a developing country: the case of Jordan. A number of econometric techniques are employed to examine the predictability of the term structure and to deal with the low quality data. In order to examine the ability of the term structure to predict the future movements in short term rates, the validity of the Expectations Hypothesis (EH) is tested. The EH implies that the term spread is an optimal predictor of the future changes in short term rates. For the empirical testing, two sets of data are used; the term structure in the Jordanian interbank market and the term structure in the primary market. The information content of the term structure about inflation rate is examined by investigating whether there is a long run equilibrium relationship between the short term rates and the inflation rate; that is, testing the Fisher Hypothesis, and between the domestic term spread and the inflation rate. Moreover, given that the exchange regime in Jordan is pegged to the US Dollar, the information content of the US term spread is also examined. The cointegration analysis is the only technique that provides evidence that the EH holds. In addition, it provides evidence that the domestic and the US term spreads contain some information about the inflation rate. As a result of dealing with low quality data, the Monte Carlo simulation provides evidence that the size distortion of the Dickey Fuller (DF) test becomes larger as the noise increases in the data and faster as the sample size becomes bigger. This evidence supports the literature that discusses the size distortion of the DF test.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:551747
Date January 2010
CreatorsQaqeesh, Sahar Sameeh
ContributorsHall, Stephen G.
PublisherUniversity of Leicester
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://hdl.handle.net/2381/10212

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