由於環境品質改變之成本或效益沒有一個直接的市場可以衡量，為了 克服此一問題，Rosen 於1974年提出特徵價格法完整的理論架構。其利用 差異性財貨之價值受其所具有之不同屬性數量影響，於是可用計量方法將 個別屬性之價值導引出來。本文即是利用Rosen 所提之二階段過程，分別 估計台北、台中、高雄三地區之特徵價格函數，然後利用第一階段所獲得 之價格資料進行第二階段逆需求函數的估計。本研究除了進行上述二階段 之估計，另外以高雄地區為例，計算該地區因水泥廠存在，PM10濃度增加 對當地房地產價格之影響，此一影響也就是水泥廠存在PM10濃度增加所造 成的社會外部成本。 / The measurement of the benefit of environmental improve-ments is difficult because typically there are no markets for environmental guality. However, one can observe behavior in markets that are related to environmental guality , and it is sometimes possible to measure people’s willingness to pay for the environmental goods by using data from these markets. Hedonic methods is one of several techniques for doing this. Hedonic methods are based on the realization that some goods or factors of production are not homogeneous and can differ in numerous characteristics. My study follows the theoretical model that provided by Sherwin Rosen in 1974.According to Rosen’s model, estimation requires a two-step procedure. First, estimate the hedonic price function. Second, estimate the demand function for air guality(PM10’s density). At last , I try to estimate how much the cement plant decreases houses price. In fact , the estima-tion is equal to measure the external cost caused by the ce-ment plant around Kaushang area.

The aim of this thesis is to develop efficient and practically useful Bayesian methods for statistical inference in structural second-price auctions. The models are applied to a carefully collected coin auction dataset with bids and auction-specific characteristics from one thousand Internet auctions on eBay. Bidders are assumed to be risk-neutral and symmetric, and compete for a single object using the same game-theoretic strategy. A key contribution in the thesis is the derivation of very accurate approximations of the otherwise intractable equilibrium bid functions under different model assumptions. These easily computed and numerically stable approximations are shown to be crucial for statistical inference, where the inverse bid functions typically needs to be evaluated several million times. In the first paper, the approximate bid is a linear function of a bidder's signal and a Gaussian common value model is estimated. We find that the publicly available book value and the condition of the auctioned object are important determinants of bidders' valuations, while eBay's detailed seller information is essentially ignored by the bidders. In the second paper, the Gaussian model in the first paper is contrasted to a Gamma model that allows intrinsically non-negative common values. The Gaussian model performs slightly better than the Gamma model on the eBay data, which we attribute to an almost normal or at least symmetrical distribution of valuations. The third paper compares the model in the first paper to a directly comparable model for private values. We find many interesting empirical regularities between the models, but no strong and consistent evidence in favor of one model over the other. In the last paper, we consider auctions with both private-value and common-value bidders. The equilibrium bid function is given as the solution to an ordinary differential equation, from which we derive an approximate inverse bid as an explicit function of a given bid. The paper proposes an elaborate model where the probability of being a common value bidder is a function of covariates at the auction level. The model is estimated by a Metropolis-within-Gibbs algorithm and the results point strongly to an active influx of both private-value and common-value bidders. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Epub ahead of print. Paper 2: Manuscript. Paper 3: Manuscript. Paper 4: Manuscript.</p>