Analyzing Spatial Heterogeneity of Housing Prices Using Large Datasets

Wu, Yangyi; Wei, Yehua Dennis; Li, Han

doi:10.1007/s12061-019-09301-x

Cited by 44 publications

(17 citation statements)

References 74 publications

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“…This is in agreement with the extant literature as well as our a priori expectation [9,27,36,43]. Although the perception of how much risk is mitigated by insurance may vary among individual herders, however, LHI remains a holistic risk management framework that can improve the resilience of vulnerable herders, promote ecological sustainability, and contribute to agricultural modernization [5,11,18,[45][46][47]. To this end, there is a need for further research in the study areas to determine the range of premiums herders are willing to pay for insuring their livestock and the type of insurance products they are likely to patronize.…”

Section: Discussionsupporting

confidence: 88%

Willingness to Pay for Livestock Husbandry Insurance: An Empirical Analysis of Grassland Farms in Inner Mongolia, China

Dong

Jimoh²,

Hou

et al. 2020

Sustainability

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Livestock husbandry insurance (LHI) is increasingly gaining acceptance in developing countries, relative to its efficacy in mitigating the covariate risks faced by households in vulnerable agrarian communities. However, this risk-mitigating tool has received little research attention in the context of Chinese herders. The current study focused on the status, and determinants of herders’ willingness to purchase LHI. We used a contingent valuation approach to collect data from 450 households across three grassland types in Inner Mongolia. Descriptive statistics and binary logistic regression models were used to analyze the collected data. We show that herders’ level of awareness and acceptance of LHI are below expectations. Our results further indicated that herders with higher education level, livestock number, risk perception level, awareness, and contracted grassland area are more likely to purchase LHI. Policymakers and insurers should design programs that will educate herders on LHI while taking cognizance of other critical factors that influence households to purchase insurance. This will go a long way in scaling-up the attractiveness of LHI to herders and the agrarian community at large.

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Section: Discussionsupporting

confidence: 88%

Willingness to Pay for Livestock Husbandry Insurance: An Empirical Analysis of Grassland Farms in Inner Mongolia, China

Dong

Jimoh²,

Hou

et al. 2020

Sustainability

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“…The main reason is that the natural conditions and economic foundations of various regions in Gansu Province are very different, which has caused the imbalance in the level of agricultural production and development speed between eastern and western regions, mountainous and Sichuan regions, and agricultural and pastoral areas [36]. According to the difference in agricultural TFP among different regions, the government should formulate and implement region-specific measures, rationally construct the distribution of agricultural productivity, promote specialized production, improve economic efficiency, and promote agricultural transformation and upgrading [39,[49][50][51].…”

Section: Discussionmentioning

confidence: 99%

Identification of Transformation Stages and Evolution of Agricultural Development Types Based on Total Factor Productivity Analysis: A Case Study of Gansu Province, China

Chen

Che

et al. 2020

Agriculture

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Agricultural transformation is a transition process of agriculture from the low development stage to the high development stage. Identifying the agricultural transformation stage and analyzing the evolution of agricultural development types based on Total Factor Productivity (TFP) are of great significance for the rational formulation of agricultural development policies. Based on the total factor productivity analysis framework, the DEA-Malmquist index model was used to measure the agricultural TFP of the 87 counties in Gansu Province from 1988 to 2017. The cumulative anomaly method was used to help identify agricultural transformation stages. Agricultural development types of counties in different stages and their evolution process were analyzed. Results show that (1) the agricultural transformation of Gansu Province can be divided into three stages: Traditional agriculture in 1988–1998; low-capacity technology agriculture in 1999–2011; and high-capacity technology agriculture in 2012–2017. (2) From 1988 to 2017, the agricultural TFP showed periodic U-shaped fluctuations, and the areas with high TFP value expanded from the central region to the western region and then to the entire region of the province. (3) Gansu Province presented a significant spatiotemporal variation of agricultural development types. From 1988 to 1998, type-I (low technological efficiency and slow technological progress) and type-VI (high technological efficiency and fast technological progress) agricultural development was mainly observed, and these two kinds of counties accounted for 55.17% of all evaluation units. From 1999 to 2011, the number of counties with type-I agricultural development increased significantly, reaching 35, followed by the number of counties with type IV (low technological efficiency) agricultural development, reaching 18. They together accounted for 60.92% of all evaluation units. From 2012 to 2017, the number of counties with type-IV and type-VI agricultural development was the largest, reaching 29 and 25, respectively. They together accounted for 62.07% of all evaluation units. (4) Types of agricultural development frequently change—from 1988 to 2017, the influencing factors of agricultural development had undergone a transition from both technological efficiency and technological improvement to technological efficiency or technological improvement alone.

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“…The assessment of clustering mainly focuses on whether the clustering method has allowed better models to be constructed (e.g. Wu, Wei, & Li, 2019). In order to make such an assessment it is necessary to have information about prices or valuations of real estate.…”

Section: Problem Specificationmentioning

confidence: 99%

Measurement of entropy in the assessment of homogeneity of areas valued with the Szczecin Algorithm of Real Estate Mass Appraisal

Gnat¹

2019

JEM

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Aim/purpose -General real estate taxation is a process regulated, inter alia, by the Real Estate Management Act. It is intended to establish a tax base for real estate in the event of a change in real estate tax base. General taxation is one of several applications of mass valuation of real estate, which enables valuation of many properties at the same time and with a uniform approach. One of the methods of mass valuation of real estate already applied in practice is the Szczecin Algorithm of Real Estate of Mass Appraisal (SAREMA). One of the immanent features of general taxation and the algorithm itself is the division of a selected area into possibly homogeneous areas called taxing zones within the general taxation terminology and, more broadly, elementary areas, according to the nomenclature used in the SAREMA. The paper presents the results of the studies on the measurement of elementary areas homogeneity on the example of land plots located in Szczecin. It is important to assess whether the designated sub-areas of valuation cover properties similar to each other in terms of their specific characteristics. If so, it will help to obtain more accurate mass valuation results. Design/methodology/approach -The paper proposes to use a modified entropy measure to establish whether the designated areas are homogeneous in terms of the specified properties of real estate. The database of real estate includes more than 1.5 thousand urbanised land plots located in Szczecin. The measurement of entropy will be preceded by the specification of elementary areas. The available methods include the application of an expert approach, under which land boundaries will be indicated by property valuers.Findings -The main conclusion of the study is that a modified measure of entropy ensures a better indication of the degree of indefiniteness of valued sub-areas and thus it offers a better way of supporting the delimitation of these sub-areas in comparison to the classical measure of entropy.Research implications/limitations -The delimitation of valuation sub-areas constitutes an important element of mass valuation. Proper execution of this process enables obtaining much more precise valuations. An objective measure of homogeneity gives a chance to compare different approaches to the creation of the above-mentioned subareas and to choose the best of them. Originality/value/contribution -The main achievement of the study is a proposal to modify the classical entropy measure, thanks to which it better reflects the specificity of the assessment of homogeneity of the areas valued in terms of property market analysis.

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Analyzing Spatial Heterogeneity of Housing Prices Using Large Datasets

Cited by 44 publications

References 74 publications

Willingness to Pay for Livestock Husbandry Insurance: An Empirical Analysis of Grassland Farms in Inner Mongolia, China

Willingness to Pay for Livestock Husbandry Insurance: An Empirical Analysis of Grassland Farms in Inner Mongolia, China

Identification of Transformation Stages and Evolution of Agricultural Development Types Based on Total Factor Productivity Analysis: A Case Study of Gansu Province, China

Measurement of entropy in the assessment of homogeneity of areas valued with the Szczecin Algorithm of Real Estate Mass Appraisal

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