The Dynamics of the Australian Short-Term Interest Rate

Brailsford, Tim; Maheswaran, Krishnan

doi:10.2139/ssrn.104668

Cited by 9 publications

(18 citation statements)

References 38 publications

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“…A growing strand of literature has attempted to analyse international financial spillovers 12 but has largely ignored the slope of the yield curve. To this level the yield curve in the euro area can be expected to have some predictive content for growth in Tunisian economy.…”

Section: The Linear Regression Estimatesmentioning

confidence: 99%

“…Against this background, we investigate the usefulness of the French slope of the yield curve as a predictor of domestic growth over k months ahead. To compare the explanatory power of foreign spread and domestic spread and test for the existence of international financial linkages 13 , we estimate the following system of equation: 12 For example, Plosser and Rouwenhorst (1994), using time series techniques, find evidence that the US slope of the yield curve helps predict growth in both Germany and the U.K. (and vice versa) significantly. Bernard and Gerlach (1998), using probit estimation, find that the slope of the yield curve in the US and Germany helps predict recessions in other G7 countries, the UK and Japan, in particular, significantly.…”

Section: The Linear Regression Estimatesmentioning

confidence: 99%

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Yield spread as a leading indicator of Tunisian industrial production

Tarek¹

2013

International Journal of Management Excellence

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Section: The Linear Regression Estimatesmentioning

confidence: 99%

Section: The Linear Regression Estimatesmentioning

confidence: 99%

Yield spread as a leading indicator of Tunisian industrial production

Tarek¹

2013

International Journal of Management Excellence

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“…Both economic intuition and casual empiricism suggest that interest rates mean revert, yet clear statistical support for the hypothesis that b is non-zero remains elusive. Working in a GMM framework, no evidence of mean reversion is found in US rates (CKLS, 1992), UK rates (Dahlquist, 1996) or Australian rates (Brailsford and Maheswaran, 1998;Treepongkaruna and Gray, 2003). Dahlquist (1996) does, however, report statistical evidence of mean reversion for Sweden and Denmark.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Brenner et al (1996) confirm the magnitude of the CKLS estimate for US rates. 3 Brailsford and Maheswaran (1998), Treepongkaruna and Gray (2003) and Gray (2005) estimate c's ranging from 1.19 to 1.70 for various Australian short-rate series. Dahlquist (1996) reports an unusually low c of 0.16 for the UK, but estimates for Germany, Denmark and Sweden range from 0.39 to 1.15.…”

Section: Introductionmentioning

confidence: 99%

On the estimation and comparison of short-rate models using the generalised method of moments

Faff¹,

Gray²

2006

Journal of Banking & Finance

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“…Of particular interest to this study, Gray (1996b) found evidence of regime switching in the Australian 90 day Bank accepted bill rates using weekly observations from 1978 to 1995. However, the regime switching analysis in each of these papers uses a classical framework whereas this study applies a Bayesian analysis in estimating the parameters of the regime switching process.In addition, several authors have conducted studies of Australian short-term interest ratesincluding Brailsford and Maheswaran (1998) and Gray and Treepongkaruna (2002).Other researchers have studied the nature of the term structure of interest rates (see Bhar ( ), Heaney (1994 and Alles (1995)). However, a separate analysis of either holding period returns or the spread of such returns has not been conducted using Australian data.…”

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confidence: 99%

Bond Term Premium Analysis in the Presence of Multiple Regimes

Guido

Walsh²

2005

Int Rev Finance

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This papers addresses whether observed violations in the Liquidity Preference Hypothesis (LPH) can be explained by the presence of multiple regimes in the term premia. The investigation proceeds by directly testing the LPH via a series of inequality tests which allow the moments to be conditioned on observable information using an instrumental variables approach. The apparent rejection of the LPH is then investigated by modelling the term premia over time using a simple Bayesian Markov mixture model. The results suggest the presence of time varying term premia and multiple regimes which may explain the violations of the LPH. The Liquidity Preference Hypothesis (LPH) states that the ex ante return on government bonds is a monotonically increasing function of time to maturity. In other words, conditional on all available information, the expected holding period return on a 10 year bond should be greater than that of a 7 year bond which is greater than that of a 5 year bond and so on. The intuition underpinning the LPH is that longer maturity bonds are more risky than shorter maturity and therefore a risk premium is included in the expected holding period return (see Hicks (1946) and Kessel (1965)). Therefore tests of the LPH amount to testing a series of inequality restrictions on the set of risk premiums. Tests of the LPH have fallen into two broad categories. Firstly, unconditional tests of the LPH have been conducted by Fama (1984), McCulloch (1987) and Richardson, Page 2 Richardson and Smith (1992) with mixed results. Moreover, the power of these tests is questionable as the econometrician is discarding information available to the economic agents. The LPH makes inferences about the monotonicity of conditional expected returns; so unconditional tests lack the power to fully test the theory. Secondly, the theory relates ex ante returns, which are unobservable. Many econometricians have attempted to address this issue by forming expectations models and testing the fitted values of the expected returns (see Fama (1986), Fama and Bliss (1987), Stambaugh (1988), Fama and French (1989) and Klemkosky and Pilotte (1992)). However, when the tests of the LPH are complicated with an expectations model it is difficult to decipher the true implications. That is, it is necessary to consider the joint statistical properties of both the LPH test and the expectations model. This complication makes the test results difficult to interpret. More recently, statistical methods for testing inequality constraints have been developed. Boudoukh, Richardson, Smith and Whitelaw (1999) (hereafter BRSW) developed a test of inequality constraints allowing moments to be conditioned on observable information using an instrumental variables approach consistent with Hansen and Singleton (1982). This procedure overcomes the problem of unobservable ex ante risk premia and allows the econometrician to condition the returns on available information. This procedure was particularly applicable to tests of the LPH as it accounts for cross correlation ...

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The Dynamics of the Australian Short-Term Interest Rate

Cited by 9 publications

References 38 publications

Yield spread as a leading indicator of Tunisian industrial production

Yield spread as a leading indicator of Tunisian industrial production

On the estimation and comparison of short-rate models using the generalised method of moments

Bond Term Premium Analysis in the Presence of Multiple Regimes

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