VALUATION OF MARKET RENTAL VALUE OF A PLANNED DORMITORY USING HEDONIC PRICING METHOD: A CASE STUDY OF POLYTECHNIQUE OF STATE FINANCE STAN, INDONESIA

This study determines the attributes that affect the market rental value of dormitories using the Hedonic Pricing Model. The proportional stratified random sampling technique was used to obtain data from 1,292 PKN STAN students in levels 1 to 3, which was analyzed using the SPSS statistical application. Based on the calculation, the dormitory value varies between IDR11,719,521 (RM3,424.82) to IDR15,482,242 (RM4524,41). The determinants that have a significant positive effect on dormitory value are bathroom location, average remittances per month, earnings per month, room size, gender, and origin, while the type of residence attribute has a negative correlation effect. The results of this study will be beneficial inputs for the PKN STAN in determining the market rental value, the quality of buildings and facilities are in accordance with the market preference.

Identifying the effect of retail brands on private residential rental prices in Great Britain

This study extends our understanding of the influence of proximity to retail grocery provision on housing rental prices. To achieve this, extensive data on the size and location of retail outlets are combined with neighbourhood rental values for small areas across a two year period, together with varied contextual data for each area. In order to control the influence of many confounding variables in the determination of housing rentals, the technique of propensity score matching is applied. This provides a sophisticated means for the comparison between areas where there is substantial natural variation, rather than manageable controls. For a variety of types of retail brands, only a significant relationship is found between the proximity of a Premium retail outlet and the housing rental value. The findings of this research allow local planning officers to further understand the impact of planning applications on the potential for gentrification and the affordability of neighbouring housing.

An Economic Analysis of French Bean(Phaseolus vulgaris L.) Production in Bishnupur District of Manipur

The study was conducted in Bishnupur district of Manipur with an objective to work out the cost and return of French bean production. The primary data on various costs and returns were collected at random from 100 respondent farmers. Production is normally considered as the function of area and yield. Results of the cost of cultivation analysis revealed that human labour, rental value of owned land, hired machinery charges, fertilizers and plant protection chemicals were important contributors to the total cost of cultivation. The average cost of cultivation was found to be Rs. 238894 per hectare.The hired human labour charges as the major cost item, it accounted for about 41.14 per cent of the total cost of cultivation. The imputed value of family labour and rental value of owned land were the next important cost components contributing about 11.56 and 11.30 per cent of the total cost of cultivation. The net farm income per hectare was estimated at Rs.230962 and benefit cost ratios per hectare was found to be 1.96. The government and related departments should arrange training programs to upgrade the knowledge on recommended package of practices on cultivation of vegetable crops and educating the farmers to develop social consciousness by strengthening local security service through proper initiatives. The farmers also need to encourage forming farmer groups or farmer producer organization (FPOs) in order to improve the production and marketing efficiency of French beans in Bishnupur district of Manipur.

THE IMPACT OF INSTITUTIONAL LANDUSES ON RENTAL VALUE OF RESIDENTIAL PROPERTIES IN AGBANI, ENUGU, NIGERIA

Agbani, Enugu Nigeria was a rural community until three very important institutions were moved by the governor to that location. This study therefore investigates the impact of Institutional Landuses on rental values of residential properties in Agbani. The study tried to determine the trends in rental values of residential accommodations in Agbani before and after the institutions came. It also compared the rent in Agbani with that of surrounding communities of Amuri, Amodu, Ugbawka and Akpugo. The study adopted the survey research methodology and covered tenement rooms, self contained rooms, one bedroom flats, two bedrooms flats and threebedroom flats. Rental survey was carried out between 1999 and 2014. A one way ANOVA was used to test the hypothesis. It was discovered that there was a statistically significant difference between rental values before and after the institutions came. Also the survey shows a significant difference between rental values of residential accommodations in Agbani and that of surroundingcommunities. The study therefore recommended among other things that institutional landuses should be used as a fulcrum that drives development in under-developed and developing countries of the world.

Effects of Noise Pollution on Residential Property Value in Enugu Urban, Nigeria

One of the persistent environmental issues today is high noise levels in residential areas especially in the developing countries. There are several unorganized informal sector activities such as recreational, road traffic, household and religious activities, operation of power generating sets, incompatible uses in space among others that are the sources of noise pollution in residential areas. A number of empirical studies have been carried out on the impact of noise on residential property values. However, one finds it very difficult to ascertain whether noise pollution affects residential property value in Enugu Urban. The aim of this study is to ascertain whether noise pollution has significant influence on residential rental values in the study area. The study has discovered that residential properties affected by noise pollution have lower rental value compared to those unaffected by 3.1% of its rental value. The study has provided some insight to guide property buyers or users, investors, property managers, and valuers as regards property transactions. The study has suggested that property value spatial index of noise pollution in the study area can be built and use as a guide for urban management strategy to achieve sustainable development.

Synthesis of Short-Cut DCF Appraisal and Spreadsheet Iteration of Freehold Rental Growth Rates Across Specific Valuation Epochs

While the use of simple deterministic models to calculate rental value growth (RVGrowth) rate of reversionary freeholds across epochs prior to upward rent review appears illusive, literature evidence of the synthesis between short-cut DCF valuation and Solver tools in a spreadsheet does not constitute an exhaustive list of solutions. This study examined alternative spreadsheet and iteration tools that can determine RVGrowth rate of freehold investment properties across rent review epochs. With recourse to a hypothetical case of a freehold investment property, this experimental study identified the mathematical composition of RVGrowth in an explicit DCF framework, performed short-cut DCF Valuation and equivalent yield calculation at specific epochs prior to and including the full reversion; as well as using Goal Seek to calculate RVGrowth across all epochs prior to- and including the full reversion. Excel® Solver and Goal Seek, as well as the graphing/root-solving tool in Kyplot® were found to feasibly produce identical results for RVGrowth rate. This is among the limited studies that identified and researched the veracity of alternative tools for RVGrowth rate iteration. The value of this study is the awareness of alternative analytical tools avail freehold investors who desire knowledge of RVGrowth rate when making purchase-, hold-, and sales decisions.

Comparative Economics of Wheat Cultivation Establishment Techniques in Haryana

The study was conducted in Karnal and Kaithal districts of Haryana during the year 2017-18. The results of the revealed that the share of variable cost as well as fixed cost in total cost of conventional technique of wheat were estimated to be was higher than the conservation techniques (ZTT and THST). The highest cost was incurred on fertilizer investment in variable cost. On the other side in case of fixed cost, highest share were incurred on rental value of land in conventional as well as conservation techniques of wheat in both the districts. The highest gross as well as net returns were found to be higher in turbo happy seeder technique (THST) over zero tillage technique and conventional technique in Karnal and Kaithal district of Haryana. As far as benefit cost analysis, turbo happy seeder technique was recorded profitable over zero tillage technique and conventional technique in the study area.

Modeling the Commercial Property Value Using Ordinary Least Squared (OLS): A Case Study of Putatan, Sabah and Limbang, Sarawak

Real Estate is an asset that provides profitable investment in return. Commercial property constitutes an important part of the real estate sector. In valuing commercial property, rental value is an essential component for valuers in applying valuation methods. Determining the rental value usually a difficult process as it involves a lot of influence factors. There are various factors that can be used but not the same for every commercial property. Therefore, this paper shows the modeling valuation comparison between two commercial property areas of Putatan and Limbang that represent the outskirts of the city in Sabah and Sarawak respectively. The purpose of this study is to find an effective approach to develop a suitable model for commercial property valuation using OLS and subsequently intends to identify factors that influence the commercial properties for both study areas. The OLS technique was used for this study to develop the property valuation model in Putatan and Limbang. The outcome shows that both study areas can be modeled using OLS for property valuation using similar factors but the Limbang area produced higher accuracy than Putatan based on the adjusted R2 value. However, in terms of the significant of the property value influence factors, both Limbang and Putatan produced different significant factors. Thus, it shows that most of the outskirt city commercial property valuation must be modeled using different influence factors. The model will benefit the local authorities, especially for commercial property valuation. Ultimately, revaluation also can be done easily with low cost, less time and few people needed for this approach.

Predicting the rental value of houses in household surveys in Tanzania, Uganda and Malawi: Evaluations of hedonic pricing and machine learning approaches

Housing value is a major component of the aggregate expenditure used in the analyses of welfare status of households in the development economics literature. Therefore, an accurate estimation of housing services is important to obtain the value of housing in household surveys. Data show that a significant proportion of households in a typical Living Standard Measurement Survey (LSMS), adopted by the Word Bank and others, are self-owned. The standard approach to predict the housing value for such surveys is based on the rental cost of the house. A hedonic pricing applying an Ordinary Least Squares (OLS) method is normally used to predict rental values. The literature shows that Machine Learning (ML) methods, shown to uncover generalizable patterns based on a given data, have better predictive power over OLS applied in other valuation exercises. We examined whether or not a class of ML methods (e.g. Ridge, LASSO, Tree, Bagging, Random Forest, and Boosting) provided superior prediction of rental value of housing over OLS methods accounting for spatial autocorrelations using household level survey data from Uganda, Tanzania, and Malawi, across multiple years. Our results showed that the Machine Learning methods (Boosting, Bagging, Forest, Ridge and LASSO) are the best models in predicting house values using out-of-sample data set for all the countries and all the years. On the other hand, Tree regression underperformed relative to the various OLS models, over the same data sets. With the availability of abundant data and better computing power, ML methods provide viable alternative to predicting housing values in household surveys.