Journal articles on the topic 'Spatial price theory'
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1
McNew, Kevin. "Spatial Market Integration: Definition, Theory, and Evidence." Agricultural and Resource Economics Review 25, no. 1 (April 1996): 1–11. http://dx.doi.org/10.1017/s1068280500000010.
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A point-space model of interregional trade is used to define market integration and to explore its implications for modeling spatial price relationships. This analysis indicates that spatial prices are related nonlinearly, contrary to much of the work on spatial price analysis which uses linear models. As an empirical example, corn market integration along the Mississippi River is examined during the Midwest flood of 1993. Higher transport costs during this period significantly reduced the extent of integration and thereby decreased excess demand shock transference across regions.
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Faminow, Merle D., and Hiroshi Ohta. "Spatial Price Theory of Imperfect Competition." Southern Economic Journal 55, no. 4 (April 1989): 1065. http://dx.doi.org/10.2307/1059495.
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STEVENS, BENJAMIN H., and C. PETER RYDELL. "SPATIAL DEMAND THEORY AND MONOPOLY PRICE POLICY." Papers in Regional Science 17, no. 1 (January 14, 2005): 195–204. http://dx.doi.org/10.1111/j.1435-5597.1966.tb01349.x.
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Guo, Yan, Xiaonan Hu, Zepeng Wang, Wei Tang, Deyu Liu, Yunzhong Luo, and Hongxiang Xu. "The butterfly effect in the price of agricultural products: A multidimensional spatial-temporal association mining." Agricultural Economics (Zemědělská ekonomika) 67, No. 11 (November 12, 2021): 457–67. http://dx.doi.org/10.17221/128/2021-agricecon.
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With the advent of the era of big data, data mining methods show their powerful information mining ability in various fields, seeking the association information hidden in the data, which is convenient for people to make scientific decisions. This paper analyses the butterfly effect in the agricultural product industry chain from the perspective of producer and consumer by using multidimensional time and space theory and proposes a new price forecasting method. We consider that the price change of agricultural products is not only affected by the balance of market supply and demand but also by the factors of time and space. Taking the pig industry chain of Sichuan Province as an example, this paper explores and excavates the data from 2010 to 2020 in the time dimension. Interestingly, we found that the price changes in pork in the market are generally highly correlated with the prices of slaughtered pigs, piglets a few weeks ago and the prices of multiple feed a few months ago. Based on the precise time-space factors, we improved the price forecasting model, greatly improved the accuracy of price prediction, and proved the effectiveness of multidimensional spatiotemporal association mining. The research in this paper is helpful to establish a brand-new agricultural product price prediction theory, which is of great significance to the development of the agricultural economy and global poverty alleviation.
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DING, Chengri, and Yi NIU. "Which is Driver? Land Price or Housing Price: Examining the Urban Spatial Structure of Beijing." Chinese Journal of Urban and Environmental Studies 04, no. 03 (September 2016): 1650026. http://dx.doi.org/10.1142/s2345748116500263.
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This paper examines the spatial structure of Beijing to determine the relationship between land price and housing price. The purposes of the paper are two-fold. One is to help to better understand the roles in which land markets play in urban development and the other is to explain skyrocketing land prices, particularly in the first decade of the 21st century. It has been debated whether land supply is the main cause for skyrocketing land prices. This paper, however, concludes that it is housing price that drives up skyrocketing land prices. The analytical framework to draw the conclusion is to investigate urban spatial development patterns to see if they are consistent with the outcomes of urban model/theory in which land is treated as a production factor for housing and land demand is a derived demand. If the answer is yes, we can conclude the driving role of housing prices on land prices, even though we recognize the effect of land supply restrictions on land prices. So the paper first examines the urban spatial pattern of Beijing, with reference to urban economic model. And then the paper estimates the parameters of a CES-type housing production function. The paper conducts numerical simulation to illustrate how a small increase in housing prices will lead to big increases in land prices. The paper concludes (1) effective roles of price mechanism in land and urban development as manifested by relatively fast decay of land prices compared to housing prices, as expected according to urban theory; and (2) a 25% increase in housing price can lead to 50–125% increases in land prices, depending on the distance to city center. We believe that our finding has substantial policy implications in China.
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CHEN, Jieh-Haur, Chuan Fan ONG, Linzi ZHENG, and Shu-Chien HSU. "FORECASTING SPATIAL DYNAMICS OF THE HOUSING MARKET USING SUPPORT VECTOR MACHINE." International Journal of Strategic Property Management 21, no. 3 (July 11, 2017): 273–83. http://dx.doi.org/10.3846/1648715x.2016.1259190.
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This paper adopts a novel approach of Support Vector Machine (SVM) to forecast residential housing prices. as one type of machine learning algorithm, the proposed SVM encompasses a larger set of variables that are recognized as price-influencing and meanwhile enables recognizing the geographical pattern of housing price dynamics. The analytical framework consists of two steps. The first step is to identify the supporting vectors (SVs) to price variances using the stepwise multi-regression approach; and then it is to forecast the housing price variances by employing the SVs identified by the first step as well as other variables postulated by the hedonic price theory, where the housing prices in Taipei City are empirically examined to verify the designed framework. Results computed by nonparametric estimation confirm that the prediction power of using SVM in housing price forecasting is of high accuracy. Further studies are suggested to extract the geographical weights using kernel density estimates to reflect price responses to local quantiles of hedonic attributes.
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Hsu, Song-ken. "Simple monopoly price theory in a spatial market." Annals of Regional Science 40, no. 3 (May 24, 2006): 531–44. http://dx.doi.org/10.1007/s00168-006-0075-5.
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Lan, Feng, and Ying Tian. "Study on Commodity Residential House Price Volatility of the Guanzhong Urban Agglomeration Using Spatial Econometric Analysis." Applied Mechanics and Materials 638-640 (September 2014): 2436–41. http://dx.doi.org/10.4028/www.scientific.net/amm.638-640.2436.
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This paper was based on the theory of spatial econometric model. It selected the panel datas of the guanzhong urban agglomeration of five core cities from 1998 to 2012, and inspected the commodity residential house price if there is a space dependency relationship between the two cities. On the basis to analyze the main factors influencing the commodity residential house price volatility and research on the influence of the housing price direction. Results show that the sample is significant spatial correlation between urban housing prices. Xi 'an have great influence on regional cities housing price. The urban population, household disposable income, land acquisition costs, sales area are the main influence factors affecting housing price volatility.
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Muhammad Mohsin, Hasan, and Scott Gilbert. "The Relative City Price Convergence in Pakistan: Empirical Evidence from Spatial GLS." Pakistan Development Review 49, no. 4II (December 1, 2010): 439–48. http://dx.doi.org/10.30541/v49i4iipp.439-448.
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It is evident from general experience that price of same good may differ considerably among countries, regions, cities in same country and even adjacent shopping malls and outlets. It is also common knowledge that stronger competitive forces and information about market price tend to ensure convergence of prices. In the presence of these forces price differentials cannot be persistent and are hence short lived. The recent literature on price convergence has focused on country studies using regional commodity prices and Consumer Price Index (CPI) data.1 The analysis of relative prices or real exchange rates between regions or cities in a country has certain advantages in estimating Purchasing Power Parity (PPP) puzzle. There are no trade barriers and non tradable goods in a single country. Krugman and Obstfeld (2007) consider transportation costs, trade barriers and goods market segmentations as obstacles to hold international Ppp.Furthermore they mention that countries have different endowments, baskets of goods and consumption weights in their inflation index. So PPP may not hold even if there are no non tradable goods and barriers. The PPP theory is related to the law of one price through arbitrage of international goods. The estimation of real exchange rates among countries shows that the convergence towards PPP is very slow.2 This study attempts to use overall Consumer Price Index (CPI) data on 35 Pakistani cities from July 2001 to June 2008 to estimate relative city price convergence with Karachi and Lahore, two numeraire cities. The case of Pakistan is interesting primarily due to the following reasons.
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Huffaker, Ray, Garry Griffith, Charles Dambui, and Maurizio Canavari. "Empirical Detection and Quantification of Price Transmission in Endogenously Unstable Markets: The Case of the Global–Domestic Coffee Supply Chain in Papua New Guinea." Sustainability 13, no. 16 (August 16, 2021): 9172. http://dx.doi.org/10.3390/su13169172.
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Price transmission through global–domestic agricultural supply chains is a fundamental indicator of domestic market efficiency and producer welfare. Conventional price-transmission econometrics test for a theory-based spatial-arbitrage restriction that long-run equilibrium prices in spatially distinct markets differ by no more than transaction costs. The conventional approach is ill-equipped to test for price transmission when endogenously unstable markets do not equilibrate due to systematic arbitrage-frustrating frictions including financial and institutional transaction costs and biophysical constraints. We propose a novel empirical framework using price data to test for market stability and price transmission along international-domestic supply chains incorporating nonlinear time series analysis and recently emerging causal-detection methods from empirical nonlinear dynamics. We apply the framework to map-out and quantify price transmission through the global-exporter–processor–producer coffee supply chain in Papua, New Guinea. We find empirical evidence of upstream price transmission from the global market to domestic exporters and processors, but not through to producers.
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Tan, Zheng-xun. "Spatial Advertisement Competition: Based on Game Theory." Journal of Applied Mathematics 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/216193.
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Since advertisement is an important strategy of firms to improve market share, this paper highlights duopoly advertisement under the Hotelling model. A model of advertisement under spatial duopoly is established, and corresponding effects of brand values and transportation costs are all captured. This study presents the proportion of sales revenue spending on advertisement. The condition for free-rider in advertisement investment is discussed. Under firms with the identical brand values, if firms' advertisement points to corresponding consumers, price and advertisement investment are all reduced. Therefore, advertisement is discussed under spatial competition in this work.
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Hardi, Ode Sofyan. "ANALISIS MODEL HAROLD HOTELLING DALAM PENENTUAN LOKASI BIMBINGAN BELAJAR." Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi 13, no. 1 (March 30, 2015): 1–13. http://dx.doi.org/10.21009/spatial.131.01.
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ABSTRACTThe purpose of this study 1) analyze the application of Harold Hotelling models in determining the location of tutoring (bimbingan belajar), 2) determine whether the theory is still relevant for today and for the type of service industry. Descriptive research is one of the types of research methods that seek to describe and interpret the object in accordance with what it is. By the time the research done on the Moon in March 2014 until December 2014, the unit of analysis in this study is tutoring available the Rawamangun ward, as well as some students from each of the learning guidance. Samples were taken using random samples with system lottery with the intention that each class has an equal chance of being sampled in the study. Samples taken as many as 4 tutoring. As well as students from each sample Bimbel 300 students. Analysis of the data in this study using descriptive statistical analysis.The results of the study explained that for the indicator in accordance with the theory of Harold Hotteling for determining the location of tutoring is spread evenly in the consumer market. In this indicator, the transportation cost rate per unit fixed cost of production of the same product and the difference in profit or loss of the company is only based on the position and location of the source material as well as all costs incurred depending on the situation and location of manufacturers serving the needs of the market. There is no differentiation ability of sellers to conduct market price levels except the only factor in the cost of transportation and every company has complete freedom to operate in the market without incurring the costs and demand is inelastic product is perfect, while the less fit is the indicator of the selling price per unit and the distance is fixed and the qualification level of the buyers and sellers comparable.Keywords: Learning; Guidance; Hotelling; Location
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Yi, Tao, Tan, and Zhu. "Avian Influenza, Public Opinion and Risk Spillover: Measurement, Theory and Evidence from China’s Broiler Market." Sustainability 11, no. 8 (April 19, 2019): 2358. http://dx.doi.org/10.3390/su11082358.
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Animal disease is a major threat to the sustainability of the global livestock market. We explore the price risk spillover of avian influenza to the broiler market, from the perspective of public opinion. Unlike in previous work, where avian influenza is measured as a whole, we decompose an avian influenza epidemic into avian influenza outbreak and public opinion, measured by infection cases and Baidu and Google search volume. Theoretically, by introducing the theory of limited attention and two-step flow of communication, we develop an analytical framework to capture the causal mechanism of avian influenza outbreak, public opinion and broiler price risk spillover, arguing that it is actually public opinion, not avian influenza outbreak alone, that directly causes broiler price risk. Empirically, using a long panel from China spanning from November 2004-November 2017, we examine the causal mechanism and analyse the nonlinear spatial spillover of public opinion to broiler price risk. We find that: (i) neither poultry nor human infection with avian influenza outbreak has a significant spillover to broiler price; (ii) on average, public opinion has a negative spillover to broiler price; in general, spillover of public opinion to broiler price is inverse U-shaped; (iii) on average, public opinion has a negative direct effect on local broiler price and a three times larger negative spatial spillover effect on nearby broiler price; in general, direct and spatial spillover effects are inverse U-shaped. Our research highlights the importance of studying public opinion in amplifying price risk when analysing spillover of animal disease to the global livestock market.
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Jing, Nan, Qi Liu, and Hefei Wang. "Stock price prediction based on stock price synchronicity and deep learning." International Journal of Financial Engineering 08, no. 02 (June 2021): 2141010. http://dx.doi.org/10.1142/s2424786321410103.
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Deep learning technology has been widely used in the financial industry, primarily for improving financial time series prediction based on stock prices. To solve the problem of low fitting and poor accuracy in traditional stock price prediction models, this paper proposes a stock price prediction model based on stock price synchronicity and deep learning methods, which applied the stock price synchronicity theory in stock price trend analysis. This paper first uses the affinity propagation algorithm to build stock clusters, and then, based on convolution neural network (CNN), and feature weight to construct the stock price synchronicity factor. At last, the long short-term memory (LSTM) network with multifactor is built for stock price trend analysis. According to the theory of stock price synchronicity, the affinity propagation algorithm can find the potential related stocks of the target stock. The spatial data analysis ability of the CNN model provides a guarantee for the application in stock price synchronicity factor analysis. The LSTM model can better analyze the information contained in the stock price time series and predict the future price. The experimental results show that, compared with the traditional multilayer neural network model, the LSTM model has better accuracy in the trend prediction of the stock price. Simultaneously, the application of stock price synchronicity effectively improves the performance of the multifactor LSTM network.
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Hu, Jin, Xuelei Xiong, Yuanyuan Cai, and Feng Yuan. "The Ripple Effect and Spatiotemporal Dynamics of Intra-Urban Housing Prices at the Submarket Level in Shanghai, China." Sustainability 12, no. 12 (June 22, 2020): 5073. http://dx.doi.org/10.3390/su12125073.
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The ripple effect of housing price movements between cities has been extensively investigated, but there are relatively few studies on this topic within a metropolitan context, especially at the submarket level. This paper describes the use of ripple effect theory to examine the diffusion process and convergence of intra-urban housing prices at the submarket level in Shanghai, an emerging global city in China. The analysis is based on directed acyclic graphs, local indicators of spatial association time-paths, and a recently developed convergence test. The empirical results of grouping analysis identify 25 submarkets in Shanghai, and the diffusion of housing prices between these submarkets is found to be caused by both geographical and economic proximities. There is also a complex recursive process of price spillovers from high- to low-priced submarkets, and vice versa, which contributes to the spiraling local housing prices. Housing prices diverge across all submarkets, and the whole market can be divided into three convergence clubs. Finally, these convergence clubs have a circular structure with a degree of continuity. This study broadens our knowledge of the price interrelationship among housing submarkets at the intra-urban level. These findings have profound implications for urban planners, policy makers, and local residents.
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Chu, Luhong, and Haizhen Wen. "Temporal and Spatial Effects of Urban Center on Housing Price — A Case Study on Hangzhou, China." World Journal of Social Science Research 5, no. 1 (February 28, 2018): 89. http://dx.doi.org/10.22158/wjssr.v5n1p89.
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<em>With the acceleration of urbanization and the rapid development of real estate, people pay more and more attention to the change of urban housing prices. Over time, the change of city center will inevitably affect the urban land or housing prices, which is reflected in the spatial distribution of urban land or housing prices. Therefore, this article attempts to explore the impact of urban center on housing prices from the perspective of multi-center city and study separately from two aspects of time and space. This paper takes the six main urban districts of Hangzhou as the research scope. At the time level, we select the residential data from 2007 to 2015 to construct models respectively based on the hedonic price theory and find that the influence of different urban center on housing price shows a certain change with time. On the spatial level, this paper choses the residential data in 2012 to construct geographic weighted regression model and the result shows that the impact of three centers on housing prices shows a certain degree of spatial heterogeneity.</em>
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LÖFGREN, KARL GUSTAF. "The pricing of pulpwood and spatial price discrimination: Theory and practice." European Review of Agricultural Economics 12, no. 2 (1985): 283–93. http://dx.doi.org/10.1093/erae/12.2.283.
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LOFGREN, K. G. "The pricing of pulpwood and spatial price discrimination: Theory and practice." European Review of Agricultural Economics 12, no. 3 (January 1, 1985): 283–93. http://dx.doi.org/10.1093/erae/12.3.283.
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Hu, Shuyun, Dazhuan Ge, Guojian Hu, Jingwen Sun, Yingyi Ma, Mengqiu Lu, and Yuqi Lu. "The Patterns and Mechanisms of Land Price Divergence in Multiple Industries from the Perspective of Element Flows: The Case of the Yangtze River Delta, China." Land 11, no. 2 (January 25, 2022): 188. http://dx.doi.org/10.3390/land11020188.
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An in-depth exploration of the inner mechanisms of the spatio-temporal evolution of land prices in multiple industries (residential, commercial service and industrial) is of great significance for improving the overall economic development efficiency and resource allocation capacity of the region. Based on urban land price transaction data provided by the China Land Market Network, 307 county-level units in the Yangtze River Delta were used as the study area and spatial auto-correlation and spatio-temporal hotspot analysis were used to explore the spatial variation and temporal changes of land prices in multiple industries in the Yangtze River Delta from 2008 to 2018. The three-dimensional driving theory of land “demand + supply + market” was used as the basis to construct the index system of influential factors and the Spatial Durbin Model was used to explore the mechanism of the spatio-temporal variation of land prices in multiple industries. The results show that the land prices of multiple industries in the Yangtze River Delta are generally high in the east and low in the west and high in the south and low in the north, which is spatially consistent with the level of regional economic development. Due to the disparity in economic development between the regions, factors such as population, capital, technology and information are redistributed and fed into each other’s cycles between cities. The resulting spatial differences in land market supply and demand are intrinsic to the spatial differentiation of urban land prices. It is further proposed that land prices are a monetized expression of the abundance of resources in a city and that land prices are determined by the combined ability of regional resource factors to be allocated. Thus, land price differentiation reflects differences in the level of comprehensive regional development. Finally, the dynamic interaction of various factors on land values is used to promote the division of urban functions and regional economic development, which is an effective way to promote high-quality integrated regional development.
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Panasolo, Alessandro, Franklin Galvão, Hermes Yukio Higachi, Edilson Batista de Oliveira, Fernando Campos de Oliveira, Carlos Augusto Wroblewski, Tatiana Maria Cecy Gadda, and Camila Fossa Balbinot. "Urban green areas and real estate prices in Curitiba, Brazil." Revista Ibero-Americana de Ciências Ambientais 11, no. 6 (July 6, 2020): 86–102. http://dx.doi.org/10.6008/cbpc2179-6858.2020.006.0008.
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We attempted to identify to which extent the implicit ecosystem service values of urban green areas impact real estate values in the city of Curitiba, Brazil. The study is based on spatial econometrics techniques and hedonic price theory applied to 43 urban green areas, highlighting three units: the Airumã Private Natural Heritage Reserve, the Teresa Urban Ecological Station, and the President Getulio Vargas Refinery. Information was obtained on the structural characteristics of more than 5,300 apartments and houses. The results of exploratory spatial data analysis (ESDA) and estimates from hedonic regression model parameters show that the presence of urban green areas contribute to the final property prices. The effects of proximity to urban green areas on the price of urban residential property are not homogeneous and stationary throughout urban spaces and can generate distinct spatial clusters of real estate prices: high-high and low-low. The used methodology proved to be efficient to assess the value of urban green areas with regard to the use of information, processing, data analysis, and results generated. Furthermore, it measured the impact of these areas on property prices and provided easily interpretable data that can be relevant for payments for ecosystem services policies at the local level.
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Liu, Qing. "Analysis of Urban Residents' Sports Consumption Demand Based on Intercepted Regression Model." Journal of Mathematics 2021 (December 6, 2021): 1–10. http://dx.doi.org/10.1155/2021/1085549.
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At this stage, broadening the consumer market, upgrading the consumption system and gradually establishing a consumption-led development concept are key factors in promoting high-quality economic development. At the same time, China's macro economy is also experiencing another test. The rapid development of China's real estate market in recent years has attracted a large number of investors, and real estate prices have produced irrational and substantial increases. Behind the boom of the real estate market is a social system crisis driven by profiteering and the growing seriousness of real estate financial bubble. So exploring the mechanism of the influence of real estate prices on the upgrading of residents' consumption is important for the current stage of China. Therefore, it is important to investigate the mechanism of real estate price impact on consumer upgrading for the coordinated development of real estate industry and national economy. In this paper, we analyze and examine the theory on the consumption improvement by the literature survey method. We also summarize the present research on the correlation and the influence mechanism of the real estate price and the consumption improvement and choose the index which reflects the present state of the real estate industry and the consumption of the inhabitant. Besides the input indicators that qualitatively manage the impact of housing prices on the improvement of residents' consumption, we first use the descriptive statistics method to understand the level of the Chinese real estate market and improve consumer spending. Based on this, the descriptive statistical method is applied to define the current state of China's real estate market and the level of improvement in consumption, and to define the standard for improving consumption in China. On the other hand, based on the spatial and spatial spillover points of view, we use spatial analysis framework combined with exploratory spatial data analysis and GIS to investigate spatial correlation between consumption structure and housing price, and accurately reflect the spatial clustering status of the index by drawing. Moran dispersion plot and Lisa cluster plot, then the spatial Darwinian model, are used to investigate the impact of real estate prices on the increase in occupant consumption from a macro perspective.
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KABOUDAN, MAK. "GP VERSUS GLS SPATIAL INDEX MODELS TO FORECAST SINGLE-FAMILY HOME PRICES." New Mathematics and Natural Computation 04, no. 02 (July 2008): 143–63. http://dx.doi.org/10.1142/s1793005708001021.
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This paper investigates use of genetic programming regression models to forecast home values. Neighborhood prices in a city are represented by a quarterly index. Index values are ratios of each local neighborhood to the global city average real price of homes sold. Relative average neighborhood home attributes, local socioeconomic characteristics, spatial measures, and real mortgage rates explain spatiotemporal variations in the index. To examine efficacy of model estimation, forecasts obtained using genetic programming are compared with those obtained using generalized least squares. Out-of-sample genetic programming predictions of home prices obtained using spatial index models deliver reasonable forecasts of home prices.
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Zhang, Min Li, and Guo Chao Han. "Application of Spatial Decision Support System in Real Estate Appraisal." Applied Mechanics and Materials 174-177 (May 2012): 3286–90. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.3286.
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After the economic crisis in 2009, the real estate market has gone through a temporary prosperity, but now it is undergoing the country’s another round of macro control. In order to comply with the national’s implementation of "one-room, one- price" policy and make second-hand housing market standardized. A comprehensive analysis of our country’s real estate prices and the latest development trends is made in this paper, besides; the analysis is based on the real estate evaluation theory. This paper presents a novel real estate estimation method based on spatial decision support system, theoretical analysis and the application of computer technology, this approach is an integration of decision support systems (DSS) and Geographic Information Systems (GIS). Meanwhile, it can make our country’s real estate evaluation more regular and scientifically.
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Costello, Greg. "Land price dynamics in a large Australian urban housing market." International Journal of Housing Markets and Analysis 7, no. 1 (February 25, 2014): 42–60. http://dx.doi.org/10.1108/ijhma-11-2012-0059.
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Purpose – Housing is a composite asset comprising land and improved components varying as proportions of total value over space and time. Theory suggests land and improvements (structures) are unique goods responding differently to economic stimuli. This paper aims to test the expectation of different overall house price changes in response to variation in land and improved components. Design/methodology/approach – House price dynamics are decomposed to analyse the influence of land and structure components for the city of Perth, Australia both at aggregate level and for spatially defined housing sub-regions, sample period 1995-2010. Findings – Values of land and improvements on that land evolve differently over time and are significantly influenced by the magnitude of land leverage. The study extends previous research through extensive spatial disaggregation of a larger more detailed data set than previously used in studies of this type confirming significant variation in land leverage ratios, overall price change and growth rates for land and improvements in sub-regional markets defined by spatial criteria. Research limitations/implications – The results suggest an important role for policy development with respect to housing affordability and supply side regulation of land in large urban housing markets. Practical implications – The results suggest important implications for hedonic price analysis of housing markets. The inclusion of land leverage variables in hedonic regression could remove coefficient bias associated with omitted location amenity variables. Originality/value – The paper adapts methodology from previous studies but extends previous literature through detailed analysis of a large Australian housing market (Perth) enabling extensive spatial disaggregation of the sample and providing greater insight to spatial variation of land leverage than in previous studies.
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Xi, Hao, Lin Tang, and Changchun Feng. "Research on the Measurement Method of Benchmark Price of Rental Housing." Land 11, no. 5 (May 22, 2022): 759. http://dx.doi.org/10.3390/land11050759.
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China’s rental housing market has just started to develop in recent years. It is relatively imperfect and lacks a clear reference for the pricing of rents, which is not fully transparent. A study on the rent formation mechanism of rental housing has policy implications for the construction of a guiding price for the rental housing market and the establishment of a reference basis for the pricing of subsidized housing. Referring to the definition of a benchmark land price, we use data from Beijing to innovatively introduce the concept of benchmark rent. Based on hedonic price theory and the driving factors of benchmark rent, a system of indicators is constructed to explore the mechanism of influencing factors at meso and micro levels on the benchmark rent of market-based rental housing. After LaGrange and robustness tests, it is found that the spatial error model (SEM) is more suitable for benchmark rent determination. We conclude that benchmark rents are affected by spatial relationships caused by spatial heterogeneity and dependency, and that there is significant spatial variation in the factors affecting market-based rental housing benchmark rents. The determination of the benchmark rent can be used as a guiding signal for the market, as a clear signal expectation for the market, government, and tenants.
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Herath, Shanaka. "Elevating the Value of Urban Location: A Consumer Preference-Based Approach to Valuing Local Amenity Provision." Land 10, no. 11 (November 11, 2021): 1226. http://dx.doi.org/10.3390/land10111226.
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Estimating the non-market monetary values of urban amenities has become commonplace in urban planning research, particularly following Rosen’s seminal article on hedonic theory in 1974. As a revealed preference method, the hedonic approach decouples the market price of a house into price components that are attributable to housing characteristics. Despite the potential contribution of this theory in a planning context, three main limitations exist in the conventional applications: (1) variable measurement issues, (2) model misspecification, and (3) the problematic common use of global regression. These flaws problematically skew our understanding of the urban structure and spatial distribution of amenities, leading to misinformed policy interventions and poor amenity planning decisions. In this article, we propose a coherent conceptual framework that addresses measurement, specification, and scale challenges to generate consistent economic estimates of local amenities. Finally, we argue that, by paying greater attention to the spatial equity of amenity values, governments can provide greater equality of opportunities in cities.
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ZWIRNER, FABIO. "THE HIGGS PUZZLE: EXPERIMENT AND THEORY." International Journal of Modern Physics A 17, no. 23 (September 20, 2002): 3300–3317. http://dx.doi.org/10.1142/s0217751x02012740.
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The present experimental and theoretical knowledge of the physics of electroweak symmetry breaking is reviewed. Data still favor a light Higgs boson, of a kind that can be comfortably accommodated in the Standard Model or in its Minimal Supersymmetric extension, but exhibit a non-trivial structure that leaves some open questions. The available experimental information may still be reconciled with the absence of a light Higgs boson, but the price to pay looks excessive. Recent theoretical ideas, linking the weak scale with the size of possible extra spatial dimensions, are briefly mentioned. It is stressed once more that experiments at high-energy colliders, such as the Tevatron and the LHC, are the crucial tool for eventually solving the Higgs puzzle.
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Karlsson , Vifill. "A Recent Development of the Spatial Disparity of Housing Prices in Iceland and Its Underlying Economic Causes." International Journal of Regional Development 2, no. 2 (October 27, 2015): 44. http://dx.doi.org/10.5296/ijrd.v2i2.8102.
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<p>In this paper, the author examines the development of the spatial distribution of housing<br />prices. Due to consumer preferences for access over amenity value, there is a spatial disparity<br />of housing prices. According to Alonso’s extension of von Tünen’s theory, the relationship<br />between housing prices in urban and rural areas tends to follow certain principles. This<br />relationship is more often negative than positive, i.e. the price of a standardized unit of<br />housing declines with increasing distance from a central business district (CBD). It has been<br />documented that this relationship is negative for Iceland, as well as in many regions of other<br />countries. It is argued here that this relationship has become increasingly marked in Iceland,<br />most likely due to the altered household preferences and structural changes. A macro panel<br />data set from Iceland will be used, representing several essential variables of the residential<br />housing market for 79 municipalities in Iceland from 1981 to 2006.</p>
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Xue, Yunqiang, Qifang Kong, Feng Sun, Meng Zhong, Haokai Tu, Caifeng Tan, and Hongzhi Guan. "Shared Parking Decision Behavior of Parking Space Owners and Car Travelers Based on Prospect Theory—A Case Study of Nanchang City, China." Sustainability 14, no. 24 (December 15, 2022): 16877. http://dx.doi.org/10.3390/su142416877.
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Shared parking improves the utilization rate of parking spaces by taking advantage of temporal and spatial differences, which is conducive to alleviating parking problems. From the perspective of bounded rationality, this paper studies the factors that influence the decision behavior of parking space owners and car travelers (non-residential drivers who have parking needs near residential areas) in sharing parking spaces. Prospect theory was used to analyze the bounded rational behavior characteristics of parking space owners and car travelers, and a value function model with rental price as the reference point was established. Combined with the survey data of the Xinhuangcheng district in Nanchang City, China, the shared parking space rental price that satisfied both parties was analyzed in this case study. The results of the study show that factors such as personal characteristics and behavioral habits affect the decision behavior of parking space owners and car travelers, and that rental price is a key factor. When the rental price of parking spaces is close to the maximum price desired by the owner, the owner feels the benefit and is willing to share the private parking space, but when the rental price differs greatly from the maximum price desired by the owner, the owner feels the loss and is not willing to share the parking space. From the survey data, it can be concluded that the ideal rental price of shared parking spaces around the survey area is 5 CNY/h. This paper provides a theoretical basis and guidance for the formulation of shared parking policies, which can help solve parking problems.
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Chen, Xiaofeng, Qiankun Song, Luqing Rong, and Zhenjiang Zhao. "Location-Price Game in a Dual-Circle Market with Different Demand Levels." Mathematical Problems in Engineering 2021 (March 26, 2021): 1–15. http://dx.doi.org/10.1155/2021/8870747.
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This paper researches a location-price game in a dual-circle market system, where two circular markets are interconnected with different demand levels. Based on the Bertrand and Salop models, a double intersecting circle model is established for a dual-circle market system in which two players (firms) develop a spatial game under price competition. By a two-stage (location-then-price) structure and backward induction approach, the existence of price and location equilibrium outcomes is obtained for the location game. Furthermore, by Ferrari method for quartic equation, the location equilibrium is presented by algebraic expression, which directly reflects the relationship between the equilibrium position and the proportion factor of demand levels. Finally, an algorithm is designed to simulate the game process of two players in the dual-circle market and simulation results show that two players almost reach the equilibrium positions obtained by theory, wherever their initial positions are.
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CHEN, WENTING, and SHA LIN. "OPTION PRICING UNDER THE KOBOL MODEL." ANZIAM Journal 60, no. 2 (September 12, 2018): 175–90. http://dx.doi.org/10.1017/s1446181118000196.
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We consider the pricing of European options under a modified Black–Scholes equation having fractional derivatives in the “spatial” (price) variable. To be specific, the underlying price is assumed to follow a geometric Koponen–Boyarchenko–Levendorski process. This pure jump Lévy process could better capture the real behaviour of market data. Despite many difficulties caused by the “globalness” of the fractional derivatives, we derive an explicit closed-form analytical solution by solving the fractional partial differential equation analytically, using the Fourier transform technique. Based on the newly derived formula, we also examine, in theory, many basic properties of the option price under the current model. On the other hand, for practical purposes, we impose a reliable implementation method for the current formula so that it can be easily used in the trading market. With the numerical results, the impact of different parameters on the option price are also investigated.
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Li, Yuxing, Hao Wu, Yu Shi, Hao Li, Xuefeng Gao, and Yeyang Zhu. "Research on Electric-Vehicle Switching Scheduling and Charging Strategy of Charging Stations." E3S Web of Conferences 292 (2021): 01031. http://dx.doi.org/10.1051/e3sconf/202129201031.
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In order to effectively alleviate the congestion of power exchange stations, the game theory was used to discuss the spatial characteristics of electric vehicle power exchange demand, analyze the decision making and game process of electric vehicle users specifically. Moreover, on the basis of the research, the specific way of setting the price of the exchange station was proposed and the game mathematical model was constructed.
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Lu, Bo, and Huipo Wang. "Research on the Competitive Strategy of Cross-Border E-Commerce Comprehensive Pilot Area Based on the Spatial Competition." Scientific Programming 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/6216052.
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By now, 13 cross-border e-commerce comprehensive pilot areas have been approved by the State Council of China; Dalian and Tianjin are two of them. But with the development of the construction of the cross-border e-commerce comprehensive pilot areas, the competition between those pilot areas is inevitable. Dalian and Tianjin are located in the Bohai Sea and the distance between them is only 800 kilometers. For Dalian and Tianjin they are in thus competitive situations: first they have to compete with each other; second since they are located in Bohai Sea (North China), they have to compete with other cross-border e-commerce comprehensive pilot areas (South China). In this paper, our aim is to build models to provide best price strategies for these two cities. Based on the two-sided market theory and the geographical position, this paper builds two competitive theory models. Through the analyzing of the equilibrium, we get two main results: (1) according to different service area, the cities (Dalian and Tianjin) should have different price; (2) the two-sided market characters have an impact on their strategies.
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Wang, Chunyun, Xiaoxi Yu, and Jiang Zhao. "Identifying the Real Income Disparity in Prefecture-Level Cities in China: Measurement of Subnational Purchasing Power Parity Based on the Stochastic Approach." Sustainability 14, no. 16 (August 10, 2022): 9895. http://dx.doi.org/10.3390/su14169895.
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Common prosperity has become the consensus of the times on development. This study aims to establish a generalized framework of the multilateral index number system under the stochastic approach and further derive the Geary–Khamis (GK) system and the Rao system under the stochastic approach to measure subnational Purchasing Power Parities (PPPs) for quantifying the real income disparity, excluding the effect of prices in prefecture-level cities in China, accurately. The results reveal that: (1) The GK system and the Rao system under the stochastic approach have advantages in addressing information loss and reliability measures, and further improve the spatial price index theory; (2) The distribution of price levels in China is in line with the trend of decreasing economic levels from east to west, which may be related to the Penn effect; (3) Compared with nominal income, real income increased significantly, and the ratio of the highest to the lowest real income in China decreased from 2.62 to 2.02. Real income, excluding the effect of prices, shows a new characteristic of moving toward the north for the high-income agglomeration areas and toward the southwest for the low-income agglomeration areas. These findings are conducive to the adoption of regionally differentiated measures to promote the realization of common prosperity, which has significant practical relevance.
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Tuz, Ahmet, and Begum Sertyesilisik. "Investigating Green Marketing Implementation with the Hedonic Price Model in Residential Projects: The Case of Istanbul." Critical Housing Analysis 8, no. 1 (June 2021): 85–100. http://dx.doi.org/10.13060/23362839.2021.8.1.525.
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The strategic importance of green marketing (GM) in value creation for the end customer (VCEC) and the contribution of the spatial and structural characteristics of a residential project (RP) to the final price have been acknowledged in the literature. However, GM features that can lead to price increases have not been evaluated from the VCEC perspective. This study examines the impacts of GM strategies on RPs. This study applies Hedonic Price Modelling to newly built RPs in Istanbul and evaluates the results from the perspective of the Attractive Quality Attributes Theory. The results showed that the total price of the RPs was affected more by design-related sustainable features of RPs and revealed that there is a relationship between GM and sustainable design. The study highlights the importance of GM, which companies can use to operate effectively in a competitive market and increase the satisfaction of end customers through value creation. The study’s findings can be considered useful information for policies on creating a sustainable built environment.
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Yuan, Chenzhe. "Application of GIS in the Analysis of Urban Economic Migration." SHS Web of Conferences 151 (2022): 01022. http://dx.doi.org/10.1051/shsconf/202215101022.
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As an intuitive embodiment of the city’s comprehensive strength, urban competitiveness, combined with the theory of regional gravity center, makes a comparative analysis of the urban economic migration of urban competitiveness in different years, which helps to analyze the spatial and temporal development differences of regional cities, thus providing a new perspective for the analysis and research of urban competitiveness. In the market economy, land price plays an important role in optimizing the allocation and intensive use of urban land resources. Therefore, it is of great practical significance for the government to reasonably allocate urban land resources and standardize the order of land market to master the spatiotemporal change law of urban land price and study the driving mechanism of land price change. This paper analyzes the urban economic migration with the help of GIS technology and carries out research at the same time, analyzes the spatio-temporal change law of the form, analyzes the urban form measurement, expansion intensity and expansion speed, and explores the driving forces and constraints affecting the urban spatial form. From this, we can obtain the spatio-temporal trajectory of GIS in urban economic migration and evolution, and the analysis and research of this trajectory can understand the direction of regional economic development and the balance of development.
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Respondek, G., J. Gröger, J. Floeter, and A. Temming. "Variability of fishing effort for the German brown shrimp (Crangon crangon) fishing fleet: influencing factors, and seasonal and spatial patterns." ICES Journal of Marine Science 71, no. 7 (February 26, 2014): 1805–17. http://dx.doi.org/10.1093/icesjms/fsu016.
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Abstract We examined factors affecting the fishing effort in the German brown shrimp (Crangon crangon) fishery, including shrimp and fuel price, catch per unit effort (cpue), number of days with strong wind, fishing port, and season. Time-series analysis (TS) using rational transfer functions (ARIMAX, an extension of autoregressive integrated moving average (ARIMA) modelling) were applied to model mean monthly boat effort (MBE, in hours), aggregated from the logbook data of five German ports for the years 2000–2008. We addressed two major areas: (i) whether cyclic effort patterns and the effect of external factors such as wind differ regionally, and (ii) whether external factors such as cpue, shrimp and fuel prices have a significant influence on the effort pattern. The estimated ARIMAX models accounted for 52–77% of the variance in MBE if analysed separately for each port, indicating a stable seasonal pattern of fishing effort without major interannual variations or significant trends. In spite of considerable variability in the external factors, none of cpue, shrimp or fuel price had a significant effect on the fishing effort. We interpreted this stability as a lack of alternative target species and discuss the theory that a response of a fishery to these external factors might only occur once certain critical threshold values have been exceeded, which was not the case during the investigated period. The models indicated differences in the seasonal patterns of the different harbours, with shorter trips and an earlier start for the main fishing season in the southwest (SW) regions, whereas in the northeast (NE) harbours, trips were longer, peak effort was shifted by 1–2 months and the spring season was of greater importance. The relationships of these regional patterns to the shrimp life cycle and coast topography, as well as implications for future management, are discussed.
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Wakefield, Lane T., and Kirk L. Wakefield. "An Examination of Construal Effects on Price Perceptions in the Advance Selling of Experience Services." Journal of Service Research 21, no. 2 (November 5, 2017): 235–48. http://dx.doi.org/10.1177/1094670517738367.
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Service research in the advance selling of experience services is limited in regard to how individual and situational differences influence price information processing. Applying construal-level theory in the context of advance selling of tickets for experience services, this research demonstrates that who (near vs. far social distance), when (near vs. far temporal distance), and where (spatial distance) influence price sensitivity and perceived value of the experience service. Study 1 finds that consumers are more price sensitive when they consider the advance purchase of events taking place further in the future, unless they are experienced, as Study 2 finds. Across both studies, buyers perceive greater value when the time and location of the event are psychologically near. Compared to when social distance is near (self-reference), consumers construe other average buyers in the market to be relatively more price sensitive and to perceive relatively higher value for experience services. Since an important factor at work in the minds of buyers is other buyers, the results imply that service providers should frame offers in reference more to others than the self for experiences. The effects of time and distance suggest managers should carefully geo-target offers customized to when and where customers are when buying tickets. As experienced buyers have learned to be price sensitive for tickets, managers should identify these individuals to provide relevant value-added offers.
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Gao, Bingyuan, and Yueping Du. "Equilibrium Further Studied for Combined System of Cournot and Bertrand: A Differential Approach." Complexity 2020 (February 27, 2020): 1–11. http://dx.doi.org/10.1155/2020/3160658.
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In general, quantity competition and price competition exist simultaneously in a dynamic economy system. Whether it is quantity competition or price competition, when there are more than three companies in one market, the equilibrium points will become chaotic and are very difficult to be derived. This paper considers generally dynamic equilibrium points of combination of the Bertrand model and Cournot model. We analyze general equilibrium points of the Bertrand model and Cournot model, respectively. A general equilibrium point of the combination of the Cournot model and Bertrand model is further investigated in two cases. The theory of spatial agglomeration and intermediate value theorem are introduced. In addition, the stability of equilibrium points is further illustrated on celestial bodies motion. The results show that at least a general equilibrium point exists in combination of Cournot and Bertrand. Numerical simulations are given to support the research results.
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Xue, Chao, Yongfeng Ju, Shuguang Li, Qilong Zhou, and Qingqing Liu. "Research on Accurate House Price Analysis by Using GIS Technology and Transport Accessibility: A Case Study of Xi’an, China." Symmetry 12, no. 8 (August 10, 2020): 1329. http://dx.doi.org/10.3390/sym12081329.
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Based on the symmetrical public transportation network data of Xi’an, China obtained by geographic information system (GIS) technology in 2019, three urban public transportation indexes of walking accessibility, bus accessibility, and metro accessibility were established, and a real estate price prediction model was built by using several machine learning algorithms to predict and analysis the housing price in Xi’an, China. Firstly, the symmetrical road network data and real estate property data of Xi’an were collected and preprocessed, secondly, the spatial syntax theory and distance calculation method were applied to establish three indexes of traffic accessibility; finally, taking the house property data and the calculated traffic accessibility indexes as the characteristic index, the real estate price prediction model of Xi’an was constructed by using the random forest algorithm (RF), lightweight gradient lift algorithm (LGBM), and gradient lifting regression tree algorithm (GBDT). The prediction accuracy of the final model is 89.2% and the root-mean-square error is 1761.84. The results show that the accessibility of bus and metro to some extent represent the convenience of public transportation in different areas of urban space. The higher the accessibility index is, the more convenient the traffic is. The real estate price model has high prediction accuracy and can reflect the real situation of urban real estate price. The importance of the three accessibility features to the real estate price prediction model are nearly more than 20%, which indicates that the accessibility of urban public transportation has an important impact on the change of urban real estate price, and the development of urban public transportation plays an important role in the real estate economy.
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DE HAAS, MICHIEL. "MOVING BEYOND COLONIAL CONTROL? ECONOMIC FORCES AND SHIFTING MIGRATION FROM RUANDA-URUNDI TO BUGANDA, 1920–60." Journal of African History 60, no. 3 (November 2019): 379–406. http://dx.doi.org/10.1017/s0021853719001038.
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AbstractMigration was a crucial component of the spatially uneven formation of labour markets and export-oriented economies in colonial Africa. Much of this mobility was initiated by migrants themselves rather than by colonial authorities. Building on analytical concepts from economic history and migration theory, this study explains the changing composition and magnitude of one such uncontrolled migration flow, from Ruanda-Urundi to Buganda. Migrants’ mobility choices – when to migrate, for how long, and with whom – proved highly responsive to shifting economic opportunity structures on the sending and receiving ends. Initially, large differences in terms of land and labour endowments, socio-economic structures, and colonial interventions, combined with substantial scope for price arbitrage, created large spatial inequalities of opportunity and strong incentives for circular male labour migration. Over time, however, migration contracted as opportunities in Ruanda-Urundi and Uganda converged, not in the least as a result of large-scale mobility itself.
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Czinkan, Norbert, and Áron Horváth. "Determinants of housing prices from an urban economic point of view: evidence from Hungary." Journal of European Real Estate Research 12, no. 1 (May 7, 2019): 2–31. http://dx.doi.org/10.1108/jerer-10-2017-0041.
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Purpose The purpose of the paper is to investigate a cross section of Hungarian settlement-level unit housing prices with a special emphasis on measuring the effect of population and its growth, along with accessibility to the centre of an aggregated spatial unit such as a micro-region, county or region, for the period of 2001-2011. Design/methodology/approach The analysis uses cross-sectional ordinary least squares techniques with Moulton-corrected standard errors. The estimation is guided by the implications of a simplified monocentric urbanized area framework following the model of DiPasquale and Wheaton (1996), and the econometric model is augmented with population growth rate at the settlement level to bridge the theory explaining rents and data base containing prices instead. Findings The location is a key factor in determining housing prices: living 10 min further from the centre results in 11 per cent cheaper housing. When estimating bid-rent curves, results show that it is crucial to control for city size and the income effect. The elasticity of housing price with respect to city size is 0.09 according to our preferred model. Population growth has an asymmetric impact on housing prices: municipalities with positive expected population growth have higher prices today. Practical implications Estimating the quantitative relationship between commuting time and housing price is crucial for a cautious infrastructure development. The benefits of improved roads and faster access could be capitalized in appreciating the housing stock. Estimating the slope of the bid-rent curve is one possible ex ante quantification of the benefits of a public development. Originality/value One contribution of this research is providing empirical evidence to surprisingly limited applied work in the field of (monocentric) urban models using data from the CEE region. Second, to the best of the authors’ knowledge, this is the first study to investigate Hungarian settlement-level unit prices from an urban economic point of view.
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CASTIGLIONE, FILIPPO. "DIFFUSION AND AGGREGATION IN AN AGENT BASED MODEL OF STOCK MARKET FLUCTUATIONS." International Journal of Modern Physics C 11, no. 05 (July 2000): 865–79. http://dx.doi.org/10.1142/s0129183100000754.
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We describe a new model to simulate the dynamic interactions between market price and the decisions of two different kind of traders. They possess spatial mobility allowing to group together to form coalitions. Each coalition follows a strategy chosen from a proportional voting "dominated" by a leader's decision. The interplay of both kind of agents gives rise to complex price dynamics that is consistent with the main stylized facts of financial time series. The present model incorporates many features of other known models and is meant to be the first step toward the construction of an agent-based model that uses more realistic markets rules, strategies, and information structures.
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Lin, Chien-Wen, Jen-Cheng Wang, Bo-Yan Zhong, Joe-Air Jiang, Ya-Fen Wu, Shao-Wei Leu, and Tzer-En Nee. "Lie symmetry analysis of the effects of urban infrastructures on residential property values." PLOS ONE 16, no. 8 (August 5, 2021): e0255233. http://dx.doi.org/10.1371/journal.pone.0255233.
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Due to the complexity of socio-economic-related issues, people thought of housing market as a chaotic nucleus situated at the intersection of neighboring sciences. It has been known that the dependence of house features on the residential property value can be estimated employing the well-established hedonic regression analysis method in teams of location characteristic, neighborhood characteristic and structure characteristic. However, to further assess the roles of urban infrastructures in housing markets, we proposed a new kind of volatility measure for house prices utilizing the Lie symmetry analysis of quantum theory based on Schrödinger equation, mainly focusing on the effects of transportation systems and public parks on residential property values. Based on the municipal open government data regularly collected for four cities, including Boston, Milwaukee, Taipei and Tokyo, and all spatial sampling sites were featured by United States Geological Survey (USGS) National Map, transportation and park were modelled as perturbations to the quantum states generated by the feature space in response to the environmental amenities with different spatial extents. In an attempt to ascertain the intrinsic impact of the location-dependent price information obtained, the similarity functions associated with the Schrödinger equation were considered to facilitate revealing the city amenities capitalizing into house prices. By examining the spatial spillover phenomena of house prices in the four cities investigated, it was found that the mass transit systems and the public green lands possessed the infinitesimal generators of Lie point symmetries Y2 and Y5, respectively. Compared statistically with the common performance criteria, including mean absolute error (MAE), mean squared error (MSE) and, root mean squared error (RMSE) obtained by hedonic pricing model, the Lie symmetry analysis of the Schrödinger equation approach developed herein was successfully carried out. The invariant-theoretical characterizations of economics-related phenomena are consonant with the observed residential property values of the cities internationally, ultimately leading to develop a new perspective in the global financial architecture.
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Burtnyak, Ivan, and Anna Malytska. "The evaluation of derivatives of double barrier options of the Bessel processes by methods of spectral analysis." Investment Management and Financial Innovations 14, no. 3 (October 11, 2017): 126–34. http://dx.doi.org/10.21511/imfi.14(3).2017.12.
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The paper deals with the spectral methods to calculate the value of the double barrier option generated by the Bessel diffusion process. This technique enables us to calculate the option price in the form of a Fourier-Bessel series with the corresponding ratio. The autors propose a simple method to estimate options using the Green’s expansion function for boundary value problem for a singular parabolic equation. Thus, the accuracy of the estimation coincides with the accuracy of the convergence of the Fourier-Bessel series. In this paper, the authors use the spectral theory to calculate the price of derivatives of financial assets considering that the processes described are by Markov and can be considered in Hilbert spaces. In this work, the authors use the diffusion process to find derivatives prices by introducing them through the Bessel functions of first kind. They also examine the Sturm-Liouville problem where the boundary conditions utilize the Bessel functions and their derivatives. All assumptions lead to analytical formulae that are consistent with the empirical evidence and, when implemented in practice, reflect adequately the passage of processes on stock markets. The authors also focus on the financial flows generated by Bessel diffusion processes which are presented in the system of Bessel functions of the first order under the condition that the linear combination of the flow and its spatial derivative are taken into account. Such a presentation enables us to calculate the market value of a share portfolio, provides the measurement of internal volatility in the market at any given time, and allows us to investigate the dynamics of the stock market. The splitting of Green’s function in the system of Bessel functions is presented by an analytical formula which is convenient for calculating the price level of options.
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Huang, Qinshi, Weixuan Song, Liyan Liu, Chunhui Liu, Xinyi Zhang, and Ge He. "Exploring Residential Heterogeneity through Multiscalar Lens: A Case Study of Hangzhou, China." Complexity 2021 (February 22, 2021): 1–12. http://dx.doi.org/10.1155/2021/3798183.
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The pattern, process, and mechanism of residential heterogeneity vary significantly with different geographical scales. However, most traditional methods ignore the checkboard and modifiable areal unit problem (MAUP), which may cover up the complexity and hierarchy of social space. Taking Hangzhou city as an example, a multiscalar method was proposed based on the information entropy theory to estimate residential heterogeneity and its scale sensitivity. Based on the sixth population census of Hangzhou and the housing price database of 6,536 residential districts from 2008 to 2018, we explore the scale effect and dynamic characteristics of residential heterogeneity. The results of spatial simulation and geostatistical analysis based on Python Spatial Analysis Library (PySAL) module show that the multiscalar algorithm better presents the real segregation pattern than traditional method, which is one of the new models and technologies in urban geography complex system. Exploring residential heterogeneity through multiscalar lens provides an important basis for the gradual and refined urban renewal.
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Bivand, Roger. "Spatial Data Analysis: Theory and Practice. By ROBERTHAINING(Cambridge: Cambridge University Press, 2003). [Pp. xx+432]. ISBN 0-521-77437-3. Price £29.95 Paperback. ISBN 0-521-77319-9. Price £80. Hardback." International Journal of Geographical Information Science 18, no. 3 (April 2004): 300–301. http://dx.doi.org/10.1080/13658810310001638682.
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Zapototska, V. "PRICING OF REGIONAL HOUSING MARKETS, THEORETICAL AND APPLIED ASPECTS." Bulletin of Taras Shevchenko National University of Kyiv. Geography, no. 66-67 (2017): 138–46. http://dx.doi.org/10.17721/1728-2721.2017.66.23.
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The article covers the theoretical and applied principles of price formation for housing within regional markets. In research process was found that the development of the regional housing market is subordinated to the action of regional development theories and general economic theories (cost and price). Among the spatial theories the influence of theories of agriculture placing and industry, central places, geographical location of economy, the theories of “growth poles”, “diffusion of innovations”, “center-periphery theory”, “city-centrality”. Economic theories are theories which actually are based on market process, formation of free market and theories of market`s processes regulation. It is proved that such theories do joint influence on pricing and the pricing mechanisms. It is proved that such theories do common influence on price formation and the pricing mechanisms. It was found, that pricing is an objective process, for determining and establishing prices within the region, which occurs primarily at regional and local level, touching individual regional market and is subjected to regulation by the state. It was established, that the formation of regional housing markets are too difficult process and are indicated by a large number of factors influencing to the processes of its formation. Through theoretical generalization, we identified six groups of factors that have a direct and indirect impact on supply and demand on the regional housing market. To the first group of factors attributed territorial housing market factors, among which are selected location of the property, infrastructure providing of this territory and ecological situation. The second group of factors includes quality characteristics of housing, among which are: construction materials; working characteristics and wearing out; architectural and planning features of the property. The third group is represented by economic factors, which include income of population, income of developers or property developers; the overall level of development of a region or settlement; investment factor; mortgage factor speculative factor and construction industry development in general. Group of demographic-settlement factors include an assessment of the demographic situation, labor market in the region, migration processes, the system of settlement and security of this area. Legislative and legal factors manifested through the state and regional policy in the housing market, housing programs, taxation processes, lending insurance and in the housing market. Social and psychological factors include behavior and preferences of consumers, price expectations, seasonality, ethnic or religious characteristics of the region. Here are presented the dynamics and confirmed differentiation in housing prices within the largest cities in Ukraine and in the city of Kyiv.
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Cong, Xueping, Xueming Li, and Yilu Gong. "Spatiotemporal Evolution and Driving Forces of Sustainable Development of Urban Human Settlements in China for SDGs." Land 10, no. 9 (September 21, 2021): 993. http://dx.doi.org/10.3390/land10090993.
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As the world’s largest developing country, China has actively implemented the UN Sustainable Development Goals (SDGs). Sustainable development of urban human settlements is the result of localization and the deepening of sustainable development theory in China. This study combines SDGs to construct an evaluation index system for the sustainable development of urban human settlements in China, using optimization methods, such as natural breaks (Jenks), exploratory spatial data analysis, and GeoDetector, to conduct systematic research on the spatiotemporal evolution of the current sustainable development level and analyze the core driving forces of urban human settlements in 285 prefecture-level cities in China from 2000 to 2019. Our study revealed that: (1) The overall sustainable development level of urban human settlements and their subsystems in China has improved steadily, but the levels of subsystems are quite different; (2) the sustainable development level of the urban human settlements in China can be expressed as a spatial pattern of “high in the east and low in the west, high in the south and low in the north” and has relatively significant spatial correlation characteristics; notably, the development level of each subsystem has different spatial characteristics; (3) the sustainable development level of urban human settlements is mainly based on medium sustainability, and the main development model is to progress from a medium-low development level to a medium-high development level; (4) the sustainable development level of urban human settlements is mainly driven by the per capita gross domestic product (GDP), housing price-to-income ratio, investment in education and scientific research, Internet penetration, and PM2.5.
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Combrinck, Zene, Elizelle Juanee Cilliers, Louis Lategan, and Sarel Cilliers. "Revisiting the Proximity Principle with Stakeholder Input: Investigating Property Values and Distance to Urban Green Space in Potchefstroom." Land 9, no. 7 (July 20, 2020): 235. http://dx.doi.org/10.3390/land9070235.
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Nature is essential to urban quality of life, yet green spaces are under pressure. In an attempt to strengthen the case for urban greening and to reclaim nature into cities, this research considered green spaces from an economic spatial perspective. The proximity principle, as part of hedonic price analysis, is employed to determine the impact of green spaces on property value in specifically selected residential areas within Potchefstroom, South Africa. Our statistical analysis indicated a rejection of the proximity principle in some areas, contradicting internationally accepted theory. To investigate local trends and possible reasons for the rejection, supporting quantitative data was gathered through structured questionnaires disseminated to local residents of Potchefstroom and Professional Planners in South Africa. Challenges pertaining to the planning of green spaces were emphasised, despite residents’ willingness to pay more for such green spaces in close proximity to residential areas, according to the cross-tabulations conducted. The research results contributed to the discourse on the economic benefits of green spaces and presented the trends of such benefits within the local context of Potchefstroom. The results emphasised the need to rethink the planning of green spaces within the local context, and provided recommendations on how to reclaim nature into cities from a spatial planning perspective.