Dependencies in multilevel models at the second level have never been thoroughly examined. For certain designs first-level subjects are independent over time, but the second level subjects may exhibit nonzero covariances over time. Following a review of revelant literature the first study investigated which widely used computer programs adequately take into account these dependencies in their analysis. This was accomplished through a simulation study with SAS, and examples of analyses with Mplus and LISREL. The second study investigated the impact of two different missing data techniques for such designs in the case where data is missing at the first level with a simulation study in SAS. The first study simulated data produced in a multiyear study varying the numbers of subjects in the first and second levels, the number of data waves, the magnitude of effects at both the first and second level, and the magnitude of the second level covariance. Results showed that SAS and the MULTILEV component in LISREL analyze such data well while Mplus does not. The second study compared two missing data techniques in the presence of a second level dependency, multiple imputation (MI) and full information maximum likelihood (FIML). They were compared in a SAS simulation study in which the data was simulated with all the factors of the first study and the addition of missing data varied in amounts and patterns (missing completely at random or missing at random). Results showed that FIML is superior to MI because it produces lower bias and correctly estimates standard errors

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利用小型開放經濟體系下寡佔理論模型的建立，以民國78年到85年台灣中游石化業的實證資料為依據，利用完全訊息最大概似法(Full Information Maximum Likelihood Method)對產業獲利率與產業集中度兩條聯立方程式進行估計，結果本文發現，產業集中度對產業獲利率的影響為正但並不具有顯著性；而加權匯率的影響為負但也不具有顯著性；又關稅與產能利用率對產業獲利率則呈現顯著正面的影響；以及進口比例與出口運輸成本對其的影響則為負向且在統計上呈現顯著性。另一方面，產業獲利率、進口比例與進口運輸成本對產業集中度產生顯著正面的影響；而市場規模則呈現顯著負面的影響。

This dissertation attempts to provide a comprehensive examination on the non-market valuation of the effect of open space amenities and local public infrastructure on the value of urban land and housing with both spatial heterogeneity and project heterogeneity. The demand for raw land is a derived demand for housing built on it. Therefore, we need to examine the land market and the housing market together. On the one hand, we estimate the value of urban land in a market that does not satisfy the usual assumptions of a competitive market structure as well as incentive incompatibility issues for transaction participants, with an application to a Chinese regional wholesale land market. These two violations to the traditional hedonic theory also generate two separate valuations on land with differentiated characteristics. On the other hand, we utilize the relative plane coordinates system, the three-dimensional distances, as well as the aggregate weight matrix, to implement the spatial hedonic estimation on the high-rise residential buildings in the same regional housing retail market in China. After these two steps, this dissertation, therefore, focuses on the profit maximization behavior of the property developer, which is the key role to link the factor market (i.e., the land market) and the commodity market (i.e., the housing market) together. Two methods are then employed to implement the hypothesis test on the hedonic price estimation including both inputs and outputs. First, a set of partial derivatives of the profit function with respect to various characteristics gives us the relationship between the marginal valuations in the land market and in the housing market. Second, we introduce a joint estimation approach that we call the spatial full information maximum likelihood (SFIML), which considers the land market, the housing market, and the property developer's profit maximization behavior all together in the estimation. Finally, we conduct a hypothesis test in both of these two scenarios to examine the validity of our linked markets assumption on the hedonic price estimation.

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