| Summary: | 博士 === 臺灣大學 === 經濟學研究所 === 98 === Macroeconomists carry the duty of providing insights and creating application value for practitioners based on studying macroeconomic time series data. However, compared with empirical studies in other areas, application of the business cycle concept on investment portfolios, the interplay between the Kitchin, Juglar and Kuznets cycles, the measurement of inflation rates, and the predictability of Fed Funds futures on U.S. monetary policy are all relatively underrepresented in literature. To bridge the gap in literature, this dissertation aims to study these practically important issues with a formal statistical procedure.
The first chapter applies the spectral analysis to discuss the cyclical patterns of business cycles and asset prices. Section 1 briefly introduces the application of spectral analysis on the study of business cycles. Section 2 uses spectral analysis to discuss the implication of the business cycle concept on the investment of multiple asset classes. In this section, Canova’s (1996) test is applied to test whether if the bonds market, stock market and commodities market have similar cyclical features as the business cycle. Moreover, the test in Fuller (1996) is applied to verify if lead or lag relationships exist between asset prices of the three markets, respectively, and the business cycle with cross spectrum analysis. Empirical results indicate that (1) Bond, stock and commodity markets all have similar cyclical patterns as the business cycles, which are about 3.5~7.5 years in length. (2) There are four statistically significant pairs of lead or lag relationships among the bonds, stocks and commodities market, respectively, and the business cycle, they are: the business cycle leads the commodities market, and lags both the bonds market and stock market, respectively, and the bonds market leads the commodities market. In addition, we have verified through actual data that applying such lead or lag relationship to hold the relative stronger asset class in each corresponding phase of the business cycle can help improve the returns of a portfolio.
Then, section 3 analyzes whether 9 types of mutual funds also possess similar connections in their cyclical patterns. Empirical results indicate that (1) These mutual fund types exhibit similar cyclical patterns. (2) Among them, there are three types of lead or lag relationships, in which bond funds lead stock market funds, stock market funds lead energy funds; bond funds lead technology funds, technology funds lead energy funds; and money market funds lead real estate funds.
Section 4 uses data from 15 OECD countries from 1870 thru 2008 and apply Canova’s (1996) test to prove that, other than the well recognized 3~5 year Kitchin cycle, most OECD countries have experienced regular 7~11 year Juglar cycles and 15~25 year Kuznets cycles as well during the same period. In addition, as we compare the business cycle peaks and troughs dates recognized by the OECD with the Juglar cycle and Kuznets cycle patterns identified in our model, we found that when the economy is in the upswing of Juglar and Kuznets cycles, the expansions of the short cycle identified by the OECD are usually longer. Also, when the economy is in the downswing of Juglar and Kuznets cycles, the contractions of the short cycle identified by the OECD are usually longer. This section further points out that the joint downswing of the Kitchin, Juglar and Kuznets cycle is one of the common causes of the 1930 Great Depression and the 2008 global financial crisis.
Inflation has always been a core issue in macroeconomics. Recent media highlighted the issue that the official inflation rates may not match public experience. Therefore in Chapter II, we shall discuss the measurement of the reliability of CPI. Here we try to construct a new regression model that can measure the reliability of CPI, which model is an extension of the stochastic approach to index numbers. Therefore, the mechanism of systematic change in relative prices in the literature of stochastic approach to index numbers is allowed to vary with time in this chapter. Then we included inflation rate and phases of business cycle dummies in our model to allow for time varying. Such an extension can answer the Keynes’s critic on stochastic approach to index numbers. Moreover, we used US and Australian data, and compared the results from our setting with those from the traditional setting, and further confirmed that our setting was more appropriate than the conventional.
Whether the Fed Funds rate futures have the ability to predict future Fed Funds rates is a significant issue in literature. However, most past research evaluates predictive ability with quantitative measurements, while its qualitative (directional) accuracy was less emphasized. Since changes in Fed Funds rates were in multiples of 0.25% since 1989, therefore the quantitative evaluation used in traditional literature may not be adequate. Hence in Chapter III, the non-parametric generalized Henriksson-Merton (H-M) test proposed by Pesaran and Timmermann (1992, 1994) is applied to verify the directional predictive ability of FF futures on FF rates. The major empirical results are (1) predicting the tightening, easing, or maintaining of monetary policy (2) when the monetary policy reaches a probable turning point, the futures based predictors are reliable for at least one week. In this chapter, we also investigate the effects of practice changes of the US monetary policy process made in February 1994. The results show that the reliability of futures based predictors have improved since then, which was marked a time when the FOMC decisions were made more open and transparent.
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