This paper aims to construct a regional macro-econometric model to quantitatively analyze factors that contribute to the correction of regional disparities by province in China.

　According to the National Bureau of Statistics of China, the urbanization rate in China increased from 10.64% in the year 1949 to 25.84% in the year 1990.　Furthermore, it exceeded 50% for the first time in the year 2011 and reached 65.22% in the year 2022.　In the year 1962 household registration system strictly distinguished urban and rural areas and restricted population migration.　This one factor contributes to regional disparities in China.　Therefore, when we analyze the Chinese economy, regional economies, such as urban and rural areas, and coastal and inland areas need to be considered.

　This paper examines regional disparities between coastal areas and inland areas in China;（1） focusing on the period from 1990 to 2020 （31 years）, （2） targeting Shanghai （coastal are）, Jiangxi （central area） and Gansu （inland area）, （3） using official statistics from National Bureau of Statistics of China, （4） examining factors for reducing regional disparities in the three regions.　By analyzing these factors, we explored the potential for reducing regional disparities in the Chinese economy.

　The model developed is a macro-econometric model that adjusts the supply side and demand side.　The core structure of the model is an adjustment of the aggregate demand side and aggregate supply side to develop a practical model that enables long-term forecasts, but also analyses short-term economic and fiscal developments. Other features of the model are as follows;

　　（1）　Urban and rural areas population factors are important issues in China, so it is important to take a supply （production） side approach that includes population factors.

　　（2）　“The capacity utilization rate” （demand-supply gap） is defined as the ratio between （a） aggregate demand （real GDP）, determined endogenously by the sum of demand variables, and （b） aggregate supply （potential real GDP）, determined by the value of the production function.

　　（3）　Furthermore, “the capacity utilization rate” affects investments, various deflators and other variables.

　　（4）　This model is a two-area （urban and rural） and two-sector （economic and fiscal） model.

JEL Classifications:C50, J31, O11, R15

　This study investigated the willingness-to-pay （WTP） for disaster reduction measures using immersive virtual reality equipment, and examined its usefulness and potential for future use.　Conventionally, contingent valuation method （CVM） has used photographs and illustrations as aids in explaining questions. Attempts have also been made to use short videos and computer graphic techniques with the aim of obtaining more accurate results by providing the evaluator with a large amount of information.　In this study, immersive virtual reality equipment, which has become increasingly popular in recent years, was used to provide more realistic information and to confirm its impact on the results of willingness-to-pay measurements.

　In the empirical survey, a flood scenario was created as a specific disaster prevention measure, and CVM was conducted using immersive virtual reality equipment.　The following three effects were expected from the use of immersive virtual reality equipment to simulate the experience of encountering a flood.　（1） it would boost respondent WTP for disaster reduction measures, （2） it would stabilize variation in WTP among respondents for disaster reduction measures, and （3） it would improve the reliability of the analysis for disaster reduction measures.

　The results of the empirical study comparing the flood prevention scenario with the environmental protection scenario did not confirm the above three effects as a statistically significance.　On the other hand, a simple comparison of average indicators confirmed the superiority of immersive virtual reality equipment in measuring willingness-to-pay for several indicators.

JEL classification:L96

　　National and local governments implement economic policies based on their judgments of economic trends and direction.　Understanding and analyzing these policies are essential, but economic trends are not uniform across the country and differ from region to region.　To implement economic measures tailored to regional economic conditions, it is necessary to grasp economic trends and the reasons for their fluctuations quickly and appropriately at the regional level.　Comprehensive economic sentiment and measurement of economic turning points at the national and regional levels are based on the Composite Index （CI）, but CI at the prefecture level should appropriately reflect regional characteristics.　The problem lies in the fact that constituent series from different fields are combined at the same ratio.　Therefore, in this paper, we focus on methods for creating the current CI and prefectural CI as a composite ratio of statistics that can reflect regional economic and industrial characteristics, and estimate the CI based on these characteristics.　The results show that CI can be more closely linked to other economic indicators and business surveys and are useful as indicators for understanding recent economic trends.

JEL classifications:E32, R11, R15

　The purpose of this study was to show that prices of Kyoto Vegetables determined by not only brand power but also nutritional components.　Procedures of the analysis were as follows.　First, branding promotion activities conducted for Kyoto Vegetables to enhance their value are discussed.　Two types of branding exist for Kyoto Vegetables:“Brand Kyoto Vegetables,” to increase the market value of the vegetables;and “Kyoto Traditional Vegetables,” to preserve traditional vegetables in the Kyoto Region.　We mainly focused on “Brand Kyoto Vegetables,” as a pioneer in the branding of agricultural products.　Next, we created panel data to clarify the differences between the nutritional components of nine kinds of Kyoto Vegetables, such as Kujo leek and Manganji capsicum, and the corresponding common vegetables. Using Hedonic methods, the panel data showed the brand power and nutritional components determine the price of Kyoto Vegetables.　Our analysis revealed the following two results.　First, Kyoto Vegetables brand power increased the price.　Second, in addition to this brand power, Kyoto Vegetables being richer in nutrients than other vegetables contributed to an increase in prices.　In particular, protein and dietary fiber showed a significant effect on price. Together the nutritional components and brand power add value to Kyoto Vegetables.　These results indicate that the branding of Kyoto Vegetables involves not only efforts that are visible to consumers, such as “Brand Kyoto Vegetables” and “Kyoto Traditional Vegetables,” but also improvements in the Kyoto Vegetables themselves, including technical improvements and guidance on production and distribution.　Therefore, the high prices of Kyoto vegetables can be attributed to these efforts.　This analysis reveals that Kyoto vegetables are broadly accepted by consumers based on their image as well as their nutrition and quality.

JEL Classifications:R15, N55, Q13, Z10