Adis IsrangkuraTiparpa Ratisurakarn2020-08-112020-08-112019b208803https://repository.nida.ac.th/handle/662723737/5073Thesis (Ph.D. (Economics))--National Institute of Development AdminForests have significant functions for the global ecosystem. Despite its immense contribution to our wellbeing, deforestation is continuing to be one of the world’s biggest problem leading to degradation of environmental and human welfare. In developing countries, there has been ongoing controversy in balancing economic development on the one hand and the need to conserve forests on the other. A key to balancing development and conservation is an accurate estimation of the economic value of forests and use it in decision making.  In this regard, innovation in economic valuation of the benefits of forests through environmental valuation techniques will not only enhance the accuracy of the estimation of the forest value but also accurately gear national development towards its sustainable path.   The purpose of the study is to adopt the Meta-analysis to estimate the economic value of forests. Meta-analysis is a statistical tool for synthesizing and integrating outcomes of previous studies into a more general form. The Meta-analysis developed in this study is based on the ordinary least square estimation of Meta-equations that contain various features of forest valuation, they are, types of forest ecosystem services, methodologies, forest types by latitude, forest types by biome, percentage of forest area, population density, and country’s GDP per capita. In this study, 301 forest values were gathered from 81 past research articles and studies. After eliminated some outliers, 288 observations of forest values were used to perform the Meta-analysis.   The Meta-regression result shows that methodologies, forest types, the scale of research, protected level of the forests, and population density have a significant impact on forest values. The result of the Meta-analysis shows the mean economic value of forests to be $US8.95 per hectare per 1000 person per year (in 2017).   The Meta-regression result of the third model is selected to predict the value of forests in Thailand. After adjusting the equation to the Thai socioeconomic status, population density, and forest areas in 2017, the predicted value for Thai forests at a country level is between 935 and 9,453 international dollars per hectare in 2017. This is comparable with the actual range of Thai forest values from original studies which range between 194.56 and 28,412.72 international dollars per hectare in 2017.137 leavesapplication/pdfengThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.e-ThesisForests and forestry -- Economic aspectsEcosystem servicesForest ecosystemsValuationtext--thesis--doctoral thesis10.14457/NIDA.the.2019.38