The dissertation studies the relationship among durable goods, price indexes and monetary policy in two sticky-price models with durable goods. One is a one-sector model with only durable goods and the other is a two-sector model with durable and non-durable goods. In the models with durable goods, the COLI (Cost of Living Index) and the PPI (Producer Price Index) identical to the CPI (Consumer Price Index) measured by the acquisitions approach are distinguished, and the COLI/PPI ratio plays an important rule in monetary policy transmission. The welfare function based on the household utility can be represented by a quadratic function of the quasi-differenced durables-stock gaps and the PPI inflation rates. In the one-sector model, the optimal policy maximizing welfare is to keep the (acquisition) price and the output gap at a constant rate which does not depend on the durability of consumption goods. In the two-sector model with sticky prices, the central bank has only one policy instrument, so it cannot cope with distortions in both sectors. Simulation results show that the PPI is an adequate price index for monetary policy and that a policy of targeting core inflation constructed by putting more weight on prices in the sector producing more durable goods is near optimal.

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This dissertation consists of three essays. Chapter II uses the method of structural factor analysis to study the effects of monetary policy on key macroeconomic variables in a data rich environment. I propose two structural factor models. One is the structural factor augmented vector autoregressive (SFAVAR) model and the other is the structural factor vector autoregressive (SFVAR) model. Compared to the traditional vector autogression (VAR) model, both models incorporate far more information from hundreds of data series, series that can be and are monitored by the Central Bank. Moreover, the factors used are structurally meaningful, a feature that adds to the understanding of the “black box” of the monetary transmission mechanism. Both models generate qualitatively reasonable impulse response functions. Using the SFVAR model, both the “price puzzle” and the “liquidity puzzle” are eliminated. Chapter III employs the method of structural factor analysis to conduct a forecasting exercise in a data rich environment. I simulate out-of-sample real time forecasting using a structural dynamic factor forecasting model and its variations. I use several structural factors to summarize the information from a large set of candidate explanatory variables. Compared to Stock and Watson (2002)’s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor forecasting models compared to alternatives that include univariate autoregression (AR) model, the VAR model and Stock and Watson’s (2002) models, especially when forecasting real variables. In chapter IV, we measure U.S. technology shocks by implementing a dual approach, which is based on more reliable price data instead of aggregate quantity data. By doing so, we find the relative volatility of technology shocks and the correlation between output fluctuation and technology shocks to be much smaller than those revealed in most real-business-cycle (RBC) studies. Our results support the findings of Burnside, Eichenbaum and Rebelo (1996), who showed that the correlation between technology shocks and output is exaggerated in the RBC literature. This suggests that one should examine other sources of fluctuations for a better understanding of the business cycle phenomena.

The primary purpose of this study is to explore whether changes in oil price are exogenous for small open economy and the significance of the financial variables in accordance with empirical results to discuss the role of monetary policies and implications. Considering the factors of monetary policy of the central banks with respect to the SVAR model, that tries to determine whether oil price shocks have disparaged effects on two small market economies, Taiwan and Korea, and trying to compare the difference and effects of their respective policies. In this paper, the empirical analysis, we found that the oil price shocks is a direct result of a major factor in decline in output, and while the impact of monetary policy effects on output is vague that coincide with Kim and Roubini (2000). In addition, Bernanke et al. (1997) analysis of the central bank encounter with the rise in oil prices in response to raise interest rates, the empirical results in this article: (1) policy implementation between the two countries have a significant impact on oil prices will be affected by the increase in oil prices which led to the implementation of central bank tightening of monetary policy , (2) central bank policy changes on behalf of the discount rate shocks, their impact on the real impact of the output is limited, (3) found that the central bank monetary policy to curb the effect of smaller price increases.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 168-172). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 168-172). Also available on the Internet.

Thesis--Jāmiʻat al-Iskandārīyah, 1976. / Includes bibliographical references (p. [511]-535).

Thesis (M.A.)--Guo li zheng zhi da xue. / Cover title. Reproduced from typescript. Includes bibliographical references.

Thesis (Doctoral)--Rijksuniversiteit Groningen, 2001. / In English, with summary in Dutch. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 146-154). Available also in a digital version from Dissertation Abstracts.