Authorship：Lead author,　Corresponding author   Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)  

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Publishing type：Research paper (scientific journal)  

This study evaluates the effects of climate change on the net revenue of farmers in Japan. We adopted the Ricardian model, which implicitly accounts for farmers' full adaptation. The main findings of this study are as follows. First, the Ricardian regression shows that changes in temperature significantly impact farmers' net revenue. In contrast, changes in precipitation have limited effects on farmers' net revenue. The results of future predictions showed that the effects of climate change are positive across the country, with varying degrees between north and south. These results are more optimistic than those in the existing literature, which frequently reveal negative climate change impacts in southern Japan. However, it should be noted that this model assumes full adaptation and does not consider the transition costs of farmers, and understanding the actual adaptive measures is an important remaining issue.

DOI： 10.1142/S2010007823500227

Scopus

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Language：Japanese   Publisher：SOCIETY OF ENVIRONMENTAL SCIENCE, JAPAN  

As the impacts of climate change on agriculture are becoming more apparent, adopting immediate and effective adaptation measures to reduce climate change effects is essential. Despite the importance of adaptation, there is little evidence on studies about farmer adaptation and adoption factors. Hence, this paper aims to explore the characteristics and issues related to farmers’ adaptation and quantitatively examine the factors influencing adaptation measures. The main results of this study, based on a web questionnaire survey and meteorological data, are as follows. The questionnaire results show that more than half of the farmers adopt adaptation measures, of which the majority are adopted voluntarily. On the other hand, we found problems such as a limited number of farmers adopting multiple adaptations and maladaptation due to set-up costs and lack of information. The results of the econometric analysis on adaptation factors revealed that age, farm size, and perception of adverse effects of climate change are associated with the adoption of adaptation measures. Moreover, this study shows that risk and time preferences, as well as climate conditions, also affect adaptation. These results suggest that measures to reduce farmers’ risks, such as lowering set-up costs, can effectively promote adaptation.

DOI： 10.11353/sesj.35.328

CiNii Research

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Language：Japanese   Publisher：The Association for Regional Agricultural and Forestry Economics  

The objective of this paper is to shed empirical light on spatial characteristics of land fragmentation (LF) and the nexus between LF and the geographical or social conditions of farmers. We collected data from the “Agricultural Land Information System,” cadastral data from three cities in Hyogo Prefecture, and “Plot Polygon” data from MAFF. We then processed these data and calculated LF indices that contain the average plot size, Simpson index, maximum distance between plots, and standard distance between plots. Using LF indices, we firstly examined the spatial autocorrelation of LF using Moran’s I. In addition, we applied the spatial autoregressive model to investigate the correlation between LF and rural community conditions. The main results of our analysis are as follows. Firstly, the calculated Moran’s I showed that all LF indices have spatial autocorrelation. This implies that there were strategic interactions between farmers at the time of farmland accumulation. Secondly, spatial econometric analysis considering autocorrelation of LF has revealed that geographical conditions such as the steepness of land and average plot size significantly correlated to LF. On the other hand, we could find little evidence of correlations between LF and social conditions such as the number of farmers or the number of meetings in rural communities.

DOI： 10.7310/arfe.57.95

CiNii Research

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Language：Japanese   Publisher：The Association of Rural Planning  

Land fragmentation is a major obstacle to agricultural productivity improvement in Japan. Land Consolidation Banks (LCBs), which were established in each prefecture of Japan in 2014, aim to facilitate land consolidation and reduce land fragmentation. Many qualitative studies have been conducted to evaluate the performance of LCBs. However, few papers shed empirical light on the relationship between land fragmentation and LCBs due to the lack of adequate data. In this paper, we have created data from a large sample of farm plots in Hyogo Prefecture, processing these data using GIS software to calculate the degree of land fragmentation and quantitatively clarify the effects of the LCB in the prefecture on the improvement of land consolidation. The farmland plot data was created in the following manner : Data from the “Agricultural Land Information System” was collected using the web scraping method, these data then being attached to cadaster data in the targeted areas. The large sample of farmersʼ plots revealed that farmers who cultivate relatively large areas of farmland in the targeted areas had succeeded in enlarging their average plot size but had not succeeded in reducing the distance between plots. In addition, we applied propensity score matching to evaluate the impacts of the LCB in Hyogo Prefecture on the enlargement of farm size and on the reduction of land fragmentation. The econometric analysis based on community level data showed that the LCB has contributed to the transfer of farmland but has not contributed to the consolidation of spatially dispersed plots.

DOI： 10.2750/jrps.1.1_29

CiNii Research

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Language：Japanese   Presentation type：Oral presentation (general)  

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Language：Japanese   Presentation type：Oral presentation (general)  

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Language：Japanese   Presentation type：Oral presentation (general)  

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Language：Japanese   Presentation type：Oral presentation (general)  

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Language：Japanese   Presentation type：Poster presentation  

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Faculty of Collaborative Regional Innovation / Specialized Subjects

Faculty of Collaborative Regional Innovation / Specialized Subjects

Faculty of Collaborative Regional Innovation / Specialized Subjects

Faculty of Collaborative Regional Innovation / Specialized Subjects

Faculty of Collaborative Regional Innovation / Specialized Subjects