Demand Preference of Consumers as a Catalyst for Local Rice Supply in Niger State

The research looked at Demand preference as it affects local rice supply in Niger State, Nigeria. Multi – stage sampling method was employed to obtain 125 household consumers of local Rice. The sampling of respondents cut across Agricultural zones 1, 2 and 3 of Niger State. Primary and Secondary data were used. Descriptive statistics like mean, frequency tables and percentages were employed to describe the socio – economic characteristics of the respondents. Vector Autoregressive model (VAR) was used to estimate production variables that granger caused local Rice supply. . Hedonic model was used to determine the effect of local Rice characteristics on the preference and willingness to pay by consumers. The result indicated the mean age of 45 for Niger. The household size has mean of 6 and years spent in school stood at 17 for Niger. The annual income mean were 414 thousand naira for Niger State. The granger causality equations show that, all variables granger caused production of local, Rice in Niger States except dlnarea. The dlnarea in Niger State was not significant. This means that it does not granger caused local Rice production. The result of hedonic model revealed that free from stone, whiteness, aroma, cohesion and taste were all significant. This means that all these attributes have great effect on price, preference and willingness to pay higher price for local Rice. These will encourage the producers to produce more and will lead to higher supply in the market.

Applying Property Pricing Models to Estimate a Foreclosure Discount in the Hotel Real Estate Sector

This study investigates the magnitude of the foreclosure sale discount in the hotel sector. The foreclosure sales discount is captured using three different models: hedonic, hybrid, and repeat sales. Controlling for various hotel attributes and time, the hedonic model shows a foreclosure discount of 40%, followed by the repeat sales model at 42% and the hybrid model at 45%, all relative to non-distressed market prices. The results of the study provide novel empirical evidence of cross-sectional variation in foreclosure discounts between independent hotels and branded hotel segments and by location. In particular, variation in the foreclosure discount is driven by independent and upscale hotels and hotels located in resorts, small metro towns, and urban locations. In addition, the study results reveal the influence of occupancy, deferred maintenance, renovation, and holding period on transaction prices.

Impact of Truck Parking Facilities on Commercial and Industrial Land Values: A Spatial Hedonic Model

Strategic locations for truck parking capacity expansion should be selected to maximize benefits to drivers and industry while minimizing negative externalities to communities. To select strategic locations, local governments, developers, state transportation agencies, and private truck stop operators need to understand how parking facilities affect local economies. Although sufficient parking capacity allows drivers to adhere to federally mandated rest requirements, demand for safe parking is outpacing supply. Truck parking demand is likely to grow as freight tonnage is estimated to increase 1.2% per year between 2018 and 2045 and mandates for electronic logging devices go into effect. However, truck parking facilities can be viewed by local communities and real-estate developers as producing pollution, noise, and congestion. Yet, they may also represent economic opportunities for tax revenues for the local economy and agglomeration benefits for surrounding trucking-related industries. To address these concerns, a systematic, data-driven review of the economic impacts of truck parking facilities is critical. This paper applied a spatial-autoregressive model with autoregressive disturbances to estimate the impact on commercial and industrial land values attributed to proximity to truck parking facilities. Significant benefits to local land values were found: every 1% increase in distance from a parking facility was associated with a 0.284% decrease in land values, which corresponds to a $2,465/acre reduction in value for an average parcel. The findings of the study could help transportation agencies and truck stop operators strategically locate truck parking facilities to harness the economic benefits to local communities.

THE DEVELOPMENT OF PENANG SHOP PRICE INDEX (PSPI) USING LASPEYRES HEDONIC PRICE MODEL

The index is considered an important benchmark and is a decision-making tool in the financial and capital markets, as well as in the property market. In Malaysia, continuous monitoring of property price movements is important as almost half of banking exposure is on property. Further, NAPIC has published indicators displaying the performance of property such as MHPI and PBO-RI. However, indicators regarding the price of commercial property are still less widely published in Malaysia. This study was conducted to develop indicators related to the price of commercial property, especially to shop property. This study has focused on the state of Penang as a study area. The literature review methodology is used to identify existing methods and practices used in developing the index of commercial property both in Malaysia and internationally. In determining the appropriate form of hedonic functions for the development of PSPI, analysis of dependent and independent variables was performed. Meanwhile, the development of the index is based on the Laspeyres hedonic model which is the same as the development of MHPI and PBO-RI. The development of PSPI will be able to help the industry and investors to make decisions and benchmark the performance of shop. This is also one of the pilot studies in Malaysia to form an indicator of commercial property.

Machine Learning, Architectural Styles and Property Values

This paper couples a traditional hedonic model with architectural style classifications from human experts and machine learning (ML) enabled classifiers to estimate sales price premia over architectural styles, both at the building and the neighborhood-level. We find statistically and economically significant price differences for houses from distinct architectural styles across an array of specifications and modeling assumptions. Comparisons between classifications from ML models and human experts illustrate the conditions under which ML classifiers may perform at least as reliable as human experts in mass appraisal models. Hedonic estimates illustrate that the impact of architectural style on price is attenuated by properties with less well-defined styles and we find no evidence for differential price effects of Revival or Contemporary architecture for new construction.

Pengaruh Implementasi Sertifikasi SVLK, Karakteristik Produk dan Tujuan Ekspor Terhadap Harga Premium Ekspor Kayu Olahan Indonesia

Premium price is an indicator of certification market effectiveness. But its existence depends on the eco-consumers in the markets. Ideally, certification is in line with benefits obtained from the market. This research aims to analyze whether the SVLK certification is capable to generate premium price of Indonesian mouldings exports and see if there is a different effect between EU and Non-EU export destinations. The analysis base on transactional exports data from 2006 to 2017 using the hedonic model approach. The regression results show that the price of SVLK certified products is 7% more expensive than non-certificate products. However, there is no significant influence of the export destination to EU or Non-EU to the prices.

A Priori Spatial Segmentation of Commercial Property Market using Hedonic Price Modelling

The improvement of property price modelling accuracy using property market segmentation approaches is well documented in the housing market. However, that cannot be said of the commercial property market which is adjudged to be volatile, heterogeneous and thinly traded. This study, therefore, determines if the commercial property market in Malaysia is spatially segmented into submarkets and whether accounting for the submarkets improves the accuracy of price modelling. Using a 11,460 shop-offices transaction dataset, the commercial property submarkets are delineated by using submarket binary dummies in the market-wide model and estimating a separate hedonic model for each submarket. The former method improves the model fit and reduces error by 5.6% and 6.5% respectively. The commercial property submarkets are better delineated by estimating a separate hedonic model for each submarket as it improves the model fit by about 7% and reduces models’ error by more than 10%. This study concludes that the Malaysian commercial property market is spatially segmented into submarkets. Modelling the submarkets improves the accuracy and correctness of price modelling.

Urban Structure in Troubled Times: The Evolution of Principal and Secondary Core/Periphery Gaps through the Prism of Residential Land Values

The structure of modern cities is characterized by the uneven spatial distribution of people and activities. Contrary to economic theory, it is neither evenly distributed nor entirely monocentric. The observed reality is the result of various feedbacks in the context of the interactions of attraction and repulsion. Heretofore, there is no agreement concerning the means to measuring the dimensions of these interactions, nor the framework for explaining them. We propose a simple model and an associated method for testing the interactions using residential land values. We claim that land values reflect the attractiveness of each location, including its observable and unobservable characteristics. We extract land values from prices of residences by applying a dedicated hedonic model to extensive residential real estate transaction data at a detailed spatial level. The resulting land values reflect the attractiveness of each urban location and are an ideal candidate to measure the degree of centrality or peripherality of each location. Moreover, assessment of land values over time indicates ongoing centralization and peripheralization processes. Using the urban structure of a small and highly urbanized country as a test case, this paper illustrates how the dynamics of the gap between central and peripheral urban areas can be assessed.

Evaluating the Impact of Urban Blue Space Accessibility on Housing Price: A Spatial Quantile Regression Approach Applied in Changsha, China

Urban nature spaces are increasingly recognized as essential urban features providing crucial amenities to the residents’ health and well-being. While many studies have been conducted focusing on the influence of green spaces on house prices, very few have explored the impact of urban blue spaces. In this study, we analyzed the proximity effects of different types and sizes of urban blue spaces on property value in Changsha metropolis, China, and examined the spatial quantile effect across different housing prices. A two-stage instrumental method (2SLS) hedonic model was employed to evaluate the impact of different types of urban blue space: river (mainstream and tributary), wetland park, and lakes (large, medium, and small). Spatial quantile regression (SQR) was then used to measure the spatial effect of accessibility on various house price ranges. The 2SLS results show that, except for small-sized lakes, proximity to blue spaces significantly increases property value. Analysis of the SQR model reveals that proximity to major blue spaces increases the marginal willingness-to-pay among homebuyers of high-priced properties, while ordinary blue spaces are more attractive to buyers of low- and medium-priced houses. This may be broadly related to the level of education, utility, and sensitivity to ecosystem services across income groups. Based on these findings, we recommend that urban planners adopt different strategies to promote space utilization efficiency. This is one of the few studies that analyze the capitalization of blue space accessibility in house prices across different quantiles. By categorizing blue spaces and employing the SQR model, this study found the effect of blue spaces on housing prices to be heterogeneous, providing new perspectives to the existing literature.