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Abstract
This paper employs the smooth transition autoregressive model to evaluate the persistence of oil price changes, and chooses monetary policy variables as transition variables of the model to assess their roles in the persistence effects. The empirical results show that oil price changes displayed asymmetric adjustments within different regimes and were more sensitive to the movement of interest rates than inflation rate. In addition, high inflation rate would give rise to low oil price persistence, and expansionary monetary policy would bring about higher oil price persistence. Moreover, when the short- and long-term interest rates were over their threshold values, the persistence effects of oil price changes were opposite. In the present relatively low US interest rates, adopting either an inflation-targeting policy or/and a debt-financing policy to stimulate economic growth, the timing is appropriate and the effect will be positive and expected because of low persistence of oil price changes.
Notes
1. World economic activity has expanded at about 5% per year since 2004, marking the strongest performance in two decades. During 2004–2010, global oil consumption grew by 4.2%, driven largely by rising demand in emerging markets that are both growing rapidly and shifting toward oil-intensive activities. In addition, some of the fastest growing nations also rely on price subsidies, which further boost oil consumption.
2. For a more detailed explanation of the impact of monetary policy on oil prices, see Brown and Yücel Citation(2002).
3. For a more detailed explanation, see Teräsvirta Citation(1994).
4. Some previous studies verified that oil prices linearly Granger-cause monetary policy variables (Cologni and Manera Citation2008; Rahman and Serletis Citation2010). Thus, the smooth transition vector error-correction model seems to be an ideal method to evaluate the causality between oil prices and monetary policy variables. However, our main aim is to estimate the nonlinear impacts of monetary policy variables on oil prices, and most importantly, employing STAR models we can endogenously decide the lag length for monetary policy to influence oil prices.
5. Teräsvirta Citation(1994) indicated that when most of the observations are larger than the threshold value and are located at the right side of transition function, the exponential STAR (ESTAR) model is similar to the logistic STAR (LSTAR) model. Similarly, as most of the observations neighbor upon the threshold value and the transition function increases gradually, the LSTAR model will approach the ESTAR model.
6. For an extensive discussion of (SE)TAR models, see Tong Citation(1990).
7. A detailed explanation is provided by Taylor and Peel Citation(2000).
8. Actually, money supply is a leading indicator of interest rates because by employing some monetary instruments, the central bank can highly influence money supply, and by combining money demand with money supply, interest rates can be decided. However, in the (nonlinear) Granger causality test between oil prices and money supply, money supply does not Granger-cause oil prices. Therefore, we give up this monetary policy variable as a transition variable in the STAR model.
9. Since New Zealand first adopted the inflation-targeting regime in 1990, over 20 countries have adopted this regime. Even the Federal Reserve has suggested introducing inflation targeting in the USA, and academics have proposed that the Bank of Japan adopt inflation targeting in an effort to promote the Japanese economy. Although the European Central Bank has adopted a two-pillar system, based on both inflation and monetary targets, many observers have argued that, in practice, it is very close to a pure inflation-targeting regime.
10. Under the assumption of rational expectation, the actual inflation rate differs from expected inflation rate by a stationary zero-mean forecast error. Thus, we replace expected inflation rate with actual inflation rate as the third proxy of monetary policy variable.
11. Because the West Texas Intermediate spot oil price cannot satisfy the stationarity condition, we use its change rate.
12. In fact, this paper also employs the Brock, Dechert, and Scheinkman (BDS) statistic proposed by Baek and Brock Citation(1992) to test whether the residuals in the VAR models of P and CPI, P and SIR, and P and LIR, respectively, reject the null hypothesis of independent and identical distribution. The tests results of nonlinear Granger causality also support the conclusion that there are nonlinear relationships between oil price change and the CPI, the short-term interest rate, and the long-term interest rate. The test results are available upon request.
13. The digit in parenthesis in the estimated equation is the t-statistic.
14. On 25 November 2008, the FOMC announced it would purchase $500 billion of mortgage-backed securities and $100 billion of debt directly issued by the housing-related, government-sponsored enterprises. In addition, on 18 March 2009, the Federal Open Market Committee (FOMC) announced that it would purchase an additional $750 billion of mortgage-backed securities, an additional $100 billion of Government-Sponsored Enterprise (GSE) debt, and $300 billion of longer term Treasury securities. In late 2010, in response to continuing weakness in the US economy and the zero lower bound, the FOMC embarked on a second round of quantitative policies, announcing its intention to purchase a further $600 billion of longer term Treasury securities by the end of the second quarter of 2011.