The Cointegration Analysis of the Long-term Bond Rates in Japan under the Zero Lower Bound Problems
Department of Commercial Science, Osaka Sangyo University, Nakagaito, Daito, Osaka, Japan
Keywords: Zero interest rate policy, Quantitative and qualitative easing, Cointegraton analysis, Carlson Parkin method, Dynamic OLS, Error correction model.
In April of 2013, Bank of Japan introduced Qualitative and Quantitative Easing (QQE). And the unexpected announcement of additional QQE in October of 2014 surprised many market participants. Just after both announcements stock prices of Japanese market rose rapidly. BOJ had introduced non-traditional monetary policies not only QQE, but Zero Interest Rate Policy (ZIRP) and Quantitative Easing (QE) for about 15 years. Not only Japan but U.S. Federal Reserve, Bank of England of U.K. (BOE) and Sveriges Riksbank of Sweden have also introduced QE. Especially, Federal Reserve Board of U.S. had executed the non-traditional monetary policies of QE1, QE2 and QE3 since November of 2008 till October of 2014 by the chairmen, Bernanke and Yellen. It continues another non-traditional monetary policy, ZIRP under the slowly recovering economy. Meanwhile ECB announced their introduction of QE on January 22 of 2015 and began buying government bonds on March 9, when Europe’s fragile recovery is lagging the rest of the world and a drop in prices is threatening to make things worse. However none of them had not brought adequate result by the non-traditional monetary policies yet. In this thesis we analyze the relationship between Japanese long-term interest rates and its non-traditional monetary policies under persistent and serious deflation. We investigate the extent to which change rates of monetary base and amounts of loan outstanding of banks and other proxy variables affect both the nominal and real interest rates of 10 year JGBs. We used a fundamental bond rate model based on Sargent (1969) and test the cointegrating relationship among the variables. Then we estimate the model with cointegrating relationship by Dynamic OLS and Error Correction model by GMM.