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Essays on improving the econometric ...

Chen, Ding-Rong.

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Essays on improving the econometric estimation of wetlands values via meta-analysis.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Essays on improving the econometric estimation of wetlands values via meta-analysis./
作者:	Chen, Ding-Rong.
面頁冊數:	116 p.
附註:	Source: Dissertation Abstracts International, Volume: 71-11, Section: A, page: 4117.
Contained By:	Dissertation Abstracts International71-11A.
標題:	Economics, Environmental. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3424603
ISBN:	9781124238449

Essays on improving the econometric estimation of wetlands values via meta-analysis.
Chen, Ding-Rong.

Essays on improving the econometric estimation of wetlands values via meta-analysis. - 116 p.

Source: Dissertation Abstracts International, Volume: 71-11, Section: A, page: 4117.

Thesis (Ph.D.)--The Ohio State University, 2010.

Historically, wetlands have been considered wastelands and can only be improved by drainage and then converted into production lands. This situation has changed since the 1970's due to the public becoming aware of the contributions of wetlands through the provision of various functions, which include habitats for species, protection against floods, water purification, amenities, recreational opportunities, and etc.

ISBN: 9781124238449Subjects--Topical Terms:

1669564
Economics, Environmental.

Essays on improving the econometric estimation of wetlands values via meta-analysis.
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245 1 0 $a Essays on improving the econometric estimation of wetlands values via meta-analysis.
300 $a 116 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-11, Section: A, page: 4117.
500 $a Adviser: Alan Randall.
502 $a Thesis (Ph.D.)--The Ohio State University, 2010.
520 $a Historically, wetlands have been considered wastelands and can only be improved by drainage and then converted into production lands. This situation has changed since the 1970's due to the public becoming aware of the contributions of wetlands through the provision of various functions, which include habitats for species, protection against floods, water purification, amenities, recreational opportunities, and etc.
520 $a In the past few decades, a large number of original site-specific wetland studies were conducted to provide value estimates of wetlands for policy makers' reference to balance the benefits and costs of wetlands conservation so that they can determine an efficient allocation of scarce public resources to wetlands projects. However, given the increasing costs of the original site-specific benefit studies, public agencies have expressed a strong interest in generalizing the findings already in the literature. This idea has stimulated the use of meta-analysis for benefit transfer (BT).
520 $a Meta-analysis is a popular tool for wetland valuation since it can synthesize empirical results across a number of studies that address related research questions. In this study, we focus our goal on improving the econometric estimation of BT through solving several issues we encountered while dealing with our wetland meta-dataset. The potential issues are raised in the following three essays and the corresponding solutions are also proposed in each essay.
520 $a In essay 1, we conduct a meta-analysis for U.S. wetlands by analyzing 72 observations collected in Borisova-Kidder (2006) to identify the important determinants of wetland values. Since the 72 observations in Borisova-Kidder (2006) are stemmed from a number of published studies that applied different methodologies to elicit wetland values, whether pooling these multi-source observations will undermine the consistency and efficiency of model parameters is also examined in this essay.
520 $a The major findings in essay 1 can be summarized as follows. First, an increase in household income will lead to higher wetland values. Second, saltwater marsh and prairie pothole, compared to freshwater marsh, were shown to have a negative relationship with wetland value. Third, most of the wetland services except water quality and amenity were shown to have no significant influence on wetland value. Fourth, among valuation methods only energy analysis was shown to have a significant effect on wetland value. Last, we cannot find any evidence for wetland value being significantly affected by its region. Other geographical factors, e.g. distance from population center, may have impact.
520 $a In essay 2, we aim to improve the efficiencies of both the model parameter estimation and the BT predictions in our wetland meta-equation by overcoming several issues in our wetland meta-dataset. In fact, the dataset used in essay 1 confronts us with the following two difficulties. First, the number of observations may be smaller than ideal for estimating effects on valuation methodology, wetland type, services, and etc. Second, this dataset is relatively noisy. In order to tackle the difficulties, we propose to augment our study with information from a second dataset in a published wetland meta-analysis conducted by Brander et al. (2006) for introducing additional information to our thin dataset.
520 $a The results of essay 2 showed that models with the added information borrowed from Brander et al. score higher logged marginal likelihood values than their respective counterparts. This suggests that such added information can effectively improve our model performance by increasing the probability to observe the sample points in our dataset. Besides, our results also showed that the accuracy of model forecasting is improved by 5% in MAPEs when the added information has been introduced into our model. Moreover, it is also noted that the 90% confidence intervals for models with the added information from Brander et al. have been narrowed down by 54%.
520 $a In essay 3, we apply Bayesian modeling averaging (BMA) to mitigate the model uncertainty issue in the derivation of estimated coefficients as well as the calculation of BT predictions.
520 $a The results of essays 3 showed that for variables receiving higher posterior effect probabilities, the size of their estimated coefficients will be close to those in the FULL model (with a full set of variables) estimated by OLS. For variables with lower probabilities, their estimated coefficients are smaller compared to their respective counterparts. (Abstract shortened by UMI.)
590 $a School code: 0168.
650 4 $a Economics, Environmental. $3 1669564
690 $a 0438
710 2 $a The Ohio State University. $b Agricultural, Environmental and Developmental Economics. $3 1675077
773 0 $t Dissertation Abstracts International $g 71-11A.
790 1 0 $a Randall, Alan, $e advisor
790 $a 0168
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3424603