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2022 | OriginalPaper | Chapter

15. A Computable General Equilibrium Analysis of the Impact of Climate Change on Regional Economies Through Japan’s Fruit Tree Production Changes: Evidence from Panel Data and Spatial CGE Models

Authors : Suminori Tokunaga, Mitsuru Okiyama, Maria Ikegawa

Published in: Theory and History in Regional Perspective

Publisher: Springer Nature Singapore

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Abstract

According to a report of Japan’s Ministry of the Environment (2015), the severity and significance of climate change are “very high,” and the urgency is “high” for paddy rice and fruit trees among crop cultivation. In this study, we focused on Japan’s fruit tree production, assessing the impacts of climate change, particularly global warming, on regional economies through changes in Japan’s fruit tree cultivation using a panel data model and a nine regional computable general equilibrium (9SCGE) model and the effects of adaptation technology and tariff reduction as recovery policies to mitigate the influence of climate change using this model. Our study revealed three findings: First, we estimated the panel data model of fruit tree production with climate change variables and demonstrated that the impact of high temperature became larger and production decreased when temperature exceeded a certain point, except in Hokkaido. Second, we constructed the 9SCGE model by combining the nine interregional social accounting matrix and the estimation results of the panel data model and conducted three simulated scenarios of global warming without adaptation technology, including the future temperature reaching the predicted maximum, mean, and minimum values. These simulation results revealed that global warming has different impacts on each region and results in regional economic disparities. For example, global warming has a positive impact on regional economies in Hokkaido, Tohoku, and Okinawa. Moreover, through the changes in producer prices for fruit trees and other agricultural products, farmers’ sales will increase to differing degrees among regions. Third, we conducted simulated scenarios of global warming with adaptation technology under the assumption that the development of high-temperature-tolerant fruit trees results in curbing global warming-induced productivity decline (with adaptation technology) as a recovery policy. This simulation revealed that the negative impact on fruit tree production to the west of Kanto will be lower than the range of decline and the equivalent variation gaps between Tohoku and Shikoku will decrease.

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The Japanese Ministry of the Environment (2015) report projected the impact of climate change on fruit trees. (1) For satsuma mandarin oranges, the climate in the 2060s is projected to be more difficult than today for growing in many of today’s prime production areas, and growing will become possible in areas that are currently not suited, including inland areas in the warm southwestern region (relatively warmer areas such as southern Kyushu) and coastal areas along the Sea of Japan and southern Tohoku region. (2) For apples, by the 2060s, the climate is projected to be more difficult than today for growing in the central Tohoku plains, and many of today’s prime production areas, such as the northern Tohoku plains, will reach temperatures similar to areas that produce warm-climate apple varieties today. (3) For grapes, peaches, and cherries, high temperature is expected to cause challenges for cultivation in major-producer prefectures.

Fruit tree production is calculated by multiplying five kinds of production (unit: tons) of mandarin orange (Citrus unshiu), apple, grape, persimmon, and Japanese pear using the 2005 annual wholesale price (amount per ton) for each fruit-producing region. In other words, the production in 2005 is the nominal amount of money, but fruit tree production in each other year is the amount of money fixed at the 2005 wholesale price. There are two reasons for constructing such data. One is that it was not possible to simply add up the production of the four kinds of fruits and it was necessary to multiply the weights in some way. Another is to make the same concept as the amount of fruit trees in 2005 SAM, which is a database of CGE models. The fruit trees are a nominal amount of money in 2005 SAM, but this amount of money is regarded as the production amount with the price set to 1. The monetary value is also displayed in the simulation result, but it is treated as the production amount.

We used prefectural data processed by Dr. Nishimori, who belongs to the National Institute for Agro-Environment Sciences, according to specific observatory data of AMeDAS. We are grateful to him for his cooperation.

Figures from 2010 to 2017 are provided by regional data on the difference between each annual mean temperature from 2010 to 2017 and the 1981–2010 average temperature calculated by regional data on the difference at 2009 using the meteorological observation database by JMA.

For the panel data model, see Greene (2012), Tokunaga et al. (2015, 2016), and Tokunaga et al. (2017).

For the spatial CGE model, see Tokunaga et al. (2003), Ban (2007), Hosoe et al. (2010), EcoMod Modeling School (2012), Okiyama and Tokunaga (2016), and Tokunaga et al. (2017).

Agricultural land refers to the total amount of rent. We calculate land rent and owned land rent per cultivated land and owned land rent per farmer based on the “Statistics on Production Cost,” the “Report of Statistics Survey on Farm Management and Economy,” and the “Statistics on Crops” of the Ministry of Agriculture, Forestry, and Fisheries. The total amount of rent is determined by multiplying the rent per cultivated land of the farmer by the total cultivated land or total farmers. Therefore, we can obtain the capital in agriculture sectors by deducting the total amount of rent from the sum of operation surplus and compensation of capital stock in the SAM. In addition, the households in the SAM can provide the total amount of rent as household income.

For map of the nine regions of Japan in 9SCGE model, see Fig. 15.3c.

Although the results of simulations with interregional elasticities changed from 2.0 to 0.5 were different, we adopted the elasticity values that have been commonly used in previous studies because we do not know which elasticity value will be optimal at a future point in time.

This parameter represents the degree to which the output of fruit tree production is affected by global warming. In other words, if the output of fruit tree production calculated by the two efficiency parameters obtained from the calibration is not subjected to global warming, this parameter is set to 1. However, if the output of fruit tree production is reduced by 10% due to global warming, the productivity is reduced by 10% by multiplying the output of fruit tree production by 0.9 of this parameter. This parameter is obtained from the search frame shown in Fig. 15.4.

Although these processes were repeated, the optimal global warming parameters could not be obtained in Chubu and Shikoku in case of the maximum value because we were unable to obtain an optimal solution in the 9SCGE model.

Specifically, the rate of change in production in Hokkaido is calculated using the coefficients in Eq. (15.4). The rate of change in production in the Kanto region of the CGE model is calculated using the coefficients and the temperature in the future obtained by multiplying the coefficients in each production function and each temperature in the future in three regions of Hokuriku, Kanto-Tosan, and Tokai by the weight of the cultivated area of Niigata prefecture, Kanto-Tosan region, and Shizuoka prefecture, respectively. Similarly, the rate of change in production in the Chubu region is calculated based on the coefficients in each production function and each temperature in the future in the two regions of Hokuriku and Tokai, and the weight of the cultivation area of Ishikawa and Toyama prefectures and Tokai region, excluding Shizuoka prefecture, respectively. The rate of change in production in the Kinki region was obtained based on the coefficients in each production function and each temperature in the future in the two regions of Hokuriku and Kinki, and the weight of the cultivated area of Fukui Prefecture and Kinki regions, respectively. However, considering the result of Hokuriku in Table 15.5, the rate of change in Hokuriku’s production was reduced by 100% for the maximum, mean, and minimum values.

In the simulation analysis using the 9SCGE model, the capital stock changes with land and labor, but is not used in the search framework to replicate the output value, because the coefficient of the capital stock was not statistically significant in the estimation results of the production function using panel data.

The Yomiuri Shimbun on May 6, 2015, reported, “the Ministry of Agriculture, Forestry, and Fisheries will strengthen research to make agricultural products strong against heat and water shortage as a measure against global warming from 2015.” Assuming that the annual average temperature rises by 2 °C in that, predicting to what extent crop yield and quality will decline for domestic major agricultural crops, with the aim of suppressing such damage to less than half.

It has been pointed out that Japan’s volume of imported goods has been small. The reason is not a result of a high import tariff rate but because there are nontariff barriers that prohibit importation unless quality standards are met. In response to these indications, the CGE model cannot simulate nontariff barriers per se, but it is possible to analyze by replacing the portion corresponding to the nontariff barrier with a higher import tariff rate than the present import tariff rate. Carrying out such a simulation will be for future study.

The reason why the import amount in the case of without the adaptation technology increases by 76.69 billion yen from the base value is that the producer price is relatively higher than the import price of the imported fruit trees because the domestic fruit tree production decreases due to global warming. If a nontariff barrier exists, the import volume does not change significantly from the base value. Therefore, we determined the import tariff rate corresponding to the nontariff barrier by searching the import tariff rate so that the import volume does not increase through some simulations in the CGE model. Moreover, when the estimated import tariff rate is set to zero, a simulation that removes nontariff barriers is possible.

Ban K (2007) Development of a Multiregional Dynamic Applied General Equilibrium Model for the Japanese Economy; Regional Economic Analysis Based on a Forward-Looking Perspective. RIETI Discussion Paper Series 07-J-043 (in Japanese)

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Title: A Computable General Equilibrium Analysis of the Impact of Climate Change on Regional Economies Through Japan’s Fruit Tree Production Changes: Evidence from Panel Data and Spatial CGE Models
Authors: Suminori Tokunaga
Mitsuru Okiyama
Maria Ikegawa
Publisher: Springer Nature Singapore
Book: Theory and History in Regional Perspective
Print ISBN: 978-981-16-6694-0

Electronic ISBN: 978-981-16-6695-7

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-981-16-6695-7_15

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