景氣循環、通貨膨脹衡量及聯邦資金利率期貨三論

Three Essays on Business Cycles,Inflation Measurement and Fed Funds Rate Futures

顏承暉(Chen-Hui Yen)

指導教授 ： 梁國源

國立臺灣大學/社會科學院/經濟學研究所/博士(2010年)

https://doi.org/10.6342/NTU.2010.01086

摘要

研究總體時間序列資料並據以提供其實務上的應用及意涵是總體經濟學家的重要工作。然而，和其他領域實證研究相較，景氣循環在投資組合上的應用、Kitchin、Juglar以及Kuznets循環間的交互作用、通貨膨脹衡量以及聯邦資金利率期貨對美國貨幣政策的預測能力等方面的研究在文獻中屬於相對少數。基於此原因，本論文將針對這些實務上重要的總體經濟議題從實證的角度分析，並據此提出其意涵。
本論文第一章應用頻譜分析（spectral analysis）來探討景氣循環以及資產價格的循環現象。第一節將介紹頻譜分析如何應用在景氣循環研究上。第二節則探討景氣循環對不同類別資產價格的意涵。首先，本節將利用Canova (1996)所提出的檢定方法驗證債券市場、股票市場、商品市場是不是具有相似的循環現象。其次，本節還應用Fuller (1996)的檢定方法，透過交叉頻譜分析驗證各資產價格與景氣循環的領先落後關係。研究顯示：(1) 債券、股票以及商品市場具有和景氣循環相似的循環週期，週期介在3.5~7.5年間；(2)債券、股票、景氣循環以及商品市場間存在四個具統計上顯著的領先或落後的關係：分別是景氣循環領先商品市場，然而卻同時落後債券市場以及股票市場，又債券市場領先商品市場。此外，本節還透過實際的資料指出，應用這樣的領先落後關係，在不同景氣循環階段持有相對強勢的資產類別，有助於增加投資組合的獲利。
第三節則更進一步分析九大類的共同基金報酬是否也具備有循環上的關連性。研究結果指出：(1) 不同種類的基金類別的確也存在類似的循環現象；(2) 其中存在三種領先或落後的關係，分別是債券型基金領先股票型基金、股票型基金領先能源型基金；債券型基金領先科技型基金、科技型基金領先能源型基金；貨幣型基金領先地產型基金。
第四節將利用1870至2008年15個OECD國家的資料，並應用Canova (1996)所提出的檢定方法證明，除了大家所熟悉的3~5年Kitchin循環外，這段期間大多數的OECD國家同時也經歷具有規律性的7~11年之Juglar循環，以及15~25年的Kuznets循環。除此之外，本節還比對歷次OECD所認定的景氣循環高峰與谷底日期以及其所處Juglar循環以及Kuznets循環的該當階段發現，當經濟同時處於Juglar及Kuznets循環的上升階段時，OECD所認定的循環擴張期通常會比較長。而當經濟同時處於Juglar及Kuznets循環的下降階段時，OECD所認定的短循環景氣收縮期通常會較長。值得注意的是，這一節還指出Kitchin、Juglar及Kuznets循環同時進入收縮期是造成1930年經濟大蕭條以及2008年全球金融海嘯的共同原因之一。
鑑於通貨膨脹是總體經濟學的重要議題，而近年來各電子及平面媒體經常出現官方公布之通貨膨脹與一般民眾生活經驗顯不相當的輿論。因此本論文的第二章將探討如何衡量消費者物價指數（CPI）的可靠度。本章試圖建構一個新的迴歸模型，透過模型的估計結果來衡量CPI的可靠性。更進一步來說，該模型是文獻上指數隨機方法（the stochastic approach to index numbers）的擴充。本文認為，傳統上的指數隨機方法中關於相對價格間系統性改變的機制應該要隨時間作改變。因此，在這一章的模型中，將加入一般通貨膨脹率以及景氣循環階段等虛擬變數來解決文獻上的不足。而這樣的延伸也更能夠回答凱因斯對於指數隨機方法的批判。此外，本章還應用澳洲以及美國的資料，比對本論文與傳統設定方法的實證差別，結果顯示，這一章的設定較傳統的方法更合適用來衡量CPI的可靠度。
聯邦資金利率期貨是否具有未來聯邦資金利率走勢的預測能力是文獻上重要的議題之一，然而過去的研究對於這個議題大多以量化的預測能力來衡量，對於質化（方向性）預測能力的討論則相對有限。但從1989年起聯邦資金利率的變動即以0.25%及其倍數的幅度調整，因此傳統文獻上的量化預測能力評估並不適當。有鑑於此，本論文第三章將應用Pesaran及Timmermann (1992, 1994)所提出的無母數一般化Henriksson-Merton (H-M)檢定驗證聯邦資金利率期貨對未來聯邦資金利率走向是否具有方向性預測能力。主要實證結果表明，聯邦資金利率期貨對於 (1)貨幣政策緊縮、寬鬆或中立，或(2)目前貨幣政策升息或降息循環的轉折點至少在1週之前就具有預測能力。此外，本章亦驗證，隨著1994年2月美國貨幣政策制定過程更趨透明化，聯邦資金利率期貨的預測能力是否有所改善。結果顯示，利率期貨的預測能力的確隨著聯準會政策制定過程的更為透明化而有所增進。

關鍵字

景氣循環 ； 投資組合管理 ； 頻譜分析 ； 指數隨機方法 ； 聯邦資金利率期貨 ； 方向性預測準確性

並列摘要

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.

並列關鍵字

Business cycles ； portfolio management ； spectral analysis ； stochastic approach to index numbers ； Fed Funds futures ； directional forecasting accuracy

參考文獻

A’Hearn, B. and U. Woitek (2001), “More International Evidence on the Historical Properties of Business Cycles”, Journal of Monetary Economics, 47, 321-326.

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Ayres, L. P. (1939), Turning Points in Business Cycles, New York: Macmillan.