Land prices, construction costs, and the affordability of housing in Lucknow City

2019 ◽  
pp. 231-262
Author(s):  
Amitabh Kundu
Keyword(s):  
Construction Costs ◽  
Land Prices

Analysis of Influencing Factors of Housing Price in Xiangtan City

2014 ◽  
Vol 934 ◽  
pp. 263-268 ◽  
Author(s):  
Rong Fang Chen ◽  
Jun Tang
Keyword(s):  
Influencing Factors ◽  
Housing Price ◽  
Evaluation Index ◽  
Housing Supply ◽  
Construction Costs ◽  
Land Prices ◽  
Main Factors

On the basis of rationality evaluation index of housing price, the main influencing factors of housing price were proposed. Through the analysis of 2004-2013 Xiangtan land prices, housing price, construction costs and taxes and other factors, it is concluded that the four main factors that affect Xiangtan City’s housing price are land prices, housing supply, construction costs and taxes.

A Case Study of Reinforced Self-Supported Retaining Wall (RSW)

2013 ◽  
Vol 353-356 ◽  
pp. 2799-2802
Author(s):  
Gwang Hee Kim ◽  
Hyun Woo Joh ◽  
Young Do Lee ◽  
Yoon Seok Shin
Keyword(s):  
Urban Areas ◽  
Retaining Wall ◽  
Construction Sites ◽  
Soil Pressure ◽  
Construction Costs ◽  
Land Prices ◽  
Structural Frame ◽  
Wall System

With increasing land prices and a lack of space in urban areas, urban construction sites are requiring deeper and larger excavations. For this reason, excavation is becoming more important. With deeper excavation, the retaining wall system needs to be adjusted, and a support system for retaining walls needs to be established so that the construction can resist the soil pressure. This can have potential problems depending on construction costs, the duration of construction, and the quality of structural frame. Therefore, the purpose of this study was to compare the conventional retaining wall system with the use of a Reinforcement Self-Supported Retaining Wall (RSW). This study revealed that the construction costs of RSW are 4 percent lower than those for the conventional retaining wall system.

A STUDY ON THE CONSTRUCTION COSTS AND THE LARGE-SCALE RENOVATION COSTS FOR SOCIAL WELFARE FACILITIES

2020 ◽  
Vol 85 (778) ◽  
pp. 2563-2572
Author(s):  
Soichiro YANAGISAWA ◽  
Yuji MATSUDA ◽  
Yukiko INOUE ◽  
Kazuhiko NISHIDE
Keyword(s):  
Social Welfare ◽  
Large Scale ◽  
Construction Costs

Equilibrium Land Prices of Japanese Prefectures: A Panel Cointegration Analysis

2004 ◽  
Author(s):  
Takashi Nagahata ◽  
Yumi Saita ◽  
Towa Tachibana ◽  
Toshitaka Sekine
Keyword(s):  
Panel Cointegration ◽  
Cointegration Analysis ◽  
Land Prices

Sewer System for Improving Flood Control in Tokyo: A Step towards a Return Period of 70 Years

1994 ◽  
Vol 29 (1-2) ◽  
pp. 303-310 ◽  
Author(s):  
Kazuyuki Higuchi ◽  
Masahiro Maeda ◽  
Yasuyuki Shintani
Keyword(s):  
Return Period ◽  
Flood Control ◽  
Rainfall Intensity ◽  
Runoff Coefficient ◽  
Large Drop ◽  
Construction Costs ◽  
Sewer System ◽  
Construction Period ◽  
Metropolitan Government ◽  
Under Construction

The Tokyo Metropolitan Government has planned future flood control for a rainfall intensity of 100 mm/hr, which corresponds to a return period of 70 years, and a runoff coefficient of 0.8. Considering that the realization of this plan requires a long construction period and high construction costs, the decision was made to proceed by stages. In the first stage, the improvement of the facilities will be based on a rainfall intensity of 75 mm/hr (presently 50 mm/hr), corresponding to a return period of 17 years, and a runoff coefficient of 0.8. In the next stage the facilities will be improved to accommodate a rainfall intensity of 100 mm/hr. In the Nakano and Suginami regions, which suffer frequently from flooding, the plan of improvement based on a rainfall intensity of 75 mm/hr is being implemented before other areas. This facility will be used as a storage sewer for the time being. The Wada-Yayoi Trunk Sewer, as a project of this plan, will have a diameter of 8 m and a 50 m earth cover. This trunk sewer will be constructed considering several constraints. To resolve these problems, hydraulic experiments as well as an inventory study have been carried out. A large drop shaft for the trunk sewer is under construction.

Real Estate

2017 ◽  
Author(s):  
Stefan Homburg
Keyword(s):  
Real Estate ◽  
Great Recession ◽  
House Prices ◽  
Borrowing Constraints ◽  
Macroeconomic Models ◽  
Land Prices ◽  
The Great Recession ◽  
Quantitative Importance

Chapter 6 examines real estate as a neglected feature of actual economies. It begins with an empirical overview demonstrating the preeminent role of land as a part of nonfinancial wealth. Whereas many macroeconomic models represent nonfinancial wealth by a symbol K that is interpreted as machines and equipment (if not robots), the text makes clear that such items are of minor quantitative importance. In contemporary economies, nonfinancial wealth consists chiefly of real estate. This is the proper reason so many analysts conjecture a link between house prices and the Great Recession. Changes in house prices (primarily changes in land prices) operate on the economy through their influence on nonfinancial wealth. Nonfinancial wealth affects consumption directly and investment indirectly since it relaxes or tightens borrowing constraints. Building on the results obtained in previous chapters, the text studies housing manias and leverage cycles and relates its main findings to US data.

scholarly journals Effect of water features proximity on farmland prices in a landlocked country: the consequences for planning

2017 ◽  
Vol 12 (No. 1) ◽  
pp. 18-28 ◽  
Author(s):  
P. Sekáč ◽  
M. Šálek ◽  
A. Wranová ◽  
P. Kumble ◽  
P. Sklenička
Keyword(s):  
Water Resources Planning ◽  
The Czech Republic ◽  
Explanatory Variables ◽  
Land Prices ◽  
Five Factors ◽  
Real Estate Brokers ◽  
Farmland Prices ◽  
Agricultural Use ◽  
Resources Planning ◽  
Significant Factors

Conversion of farmland to non-farm uses significantly influences the spatial variability of farmland prices. We tested 12 factors of land prices that experienced real estate brokers indicated to be the most important determinants for the conversion of farmland to non-agricultural use. Five factors can be described as landscape, four as geographic, and three as climatic explanatory variables influencing farmland prices. Our results indicate that the two most powerful factors in explaining the sales price per square metre were proximity to a river and proximity to a lake. In both cases, the price of land diminished significantly with the increasing distance from the edge of water bodies, so the prices in their immediate vicinity are 3.5 to 3.7 times higher than the prices of similar lands more than 5 km from the edge of a water body. The other significant factors were population size of the nearest municipality and percentage representation of forest. The fact that the two most powerful factors indicate the distance to a river, brook, lake or pond shows how important are these freshwater features as determinants of farmland prices in a landlocked country such as the Czech Republic, where this study was performed. The consequences of this finding for water resources planning and management are discussed.

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