Estimating the inverse demand function for transferring agricultural water in Taiwan

Abstract

Changing climate has increasingly exacerbated droughts and floods in Taiwan; therefore, it is important to understand the actual demand of transferring Taiwan's agricultural water. This estimation model could help the water resource agencies to develop appropriate mechanisms for transferring agricultural water, as well as bargaining tools for water-related negotiations. In this study, an inverse demand function estimation model for transferring agricultural water was established, and the water usage statistics derived from the water charge agreements, covering the period from January 1989 to December 2006 and including drought and non-drought periods, regarding the charging of water management fees and water usage fees, was applied to the estimation model in our empirical research. The agreements were made between irrigation associations and water companies, industrial water users, and science and industrial parks, for the purposes of strengthening irrigation management, building usage, and disposal of remaining water. The empirical research was conducted to estimate the demand for transferring agricultural water using double-log regression model for panel data, and analyzed with random effects models for regular conditions and drought periods. The results showed that the inverse demand function developed in this study was able to pass Largrange multiplier test, and adjusted R 2 for the regression were high, fitting the random effects model showing good compatibility with the sample selection.From the results, we can verify the estimation models to forecasting models. The significant results not only prove that the model could provide important market information for the commercialization of water resources, but water resource agencies could also make use of this important information to develop suitable mechanisms for transferring agricultural water, as well as bargaining tools for negotiation of water transactions.

The price elasticity of transferring agricultural water to industrial water during non-drought period in Taiwan

“…This could provide a pragmatic look at the real situation in the Taiwan water market to help understanding the market situation. The difference between Huang and Chiueh (2010) and this study are (1) this article focuses on the black water market 1 during non-drought period, and the data range is different. This study corrected data from January 1998 to December 2008 during non-drought periods, while Huang and Chiueh (2010) corrected data from January 1989 to December 2006 and including drought and non-drought periods, (2)This study corrected more detailed data than Huang and Chiueh (2010).…”

“…This study gathers the water transfer data from the 17 farm irrigation associations in Taiwan. Following Huang and Chiueh (2010), this study collected transaction data of agricultural water from the black markets, including the collection of statistical data of water usage from the shortterm water charge agreements made between farm irrigation associations and industrial water users, or science and industrial parks, for the purposes of strengthening irrigation management, building usage, and disposal of remaining water.…”

“…Therefore, this study adopted Huang and Chiueh (2010) to use the random effects model for panel data to extract useful information for transferring agricultural water to non-agricultural sectors. The random effects model of the transferring agricultural water demand function can be expressed as follows:…”

“…Dalhuisen et al (2003) estimated the daily, monthly, and quarterly water demand functions by the regression method based on respective periodical (daily, monthly, and quarterly) data of transaction prices and water quantities. Huang and Chiueh (2010) established the inverse demand function estimation model for transferring agricultural water in Taiwan, covering from January 1989 to December 2006 and including drought and non-drought periods. Huang and Chiueh (2010) found that the factors influencing the transaction water prices are different between drought and non-drought periods in Taiwan.…”

“…Huang and Chiueh (2010) established the inverse demand function estimation model for transferring agricultural water in Taiwan, covering from January 1989 to December 2006 and including drought and non-drought periods. Huang and Chiueh (2010) found that the factors influencing the transaction water prices are different between drought and non-drought periods in Taiwan. Almost all the transfers of agricultural water in Taiwan are mediated and compensated by the government during the drought season.…”