Determining(Estimating) Ratios for Enhancing Publicness Through Analysis of Changes in Land Prices Influenced by Upzoning

2016 ◽  
Vol 19 (4) ◽  
pp. 157-168
Author(s):  
Heung-Kwan KIM
Keyword(s):  
Land Prices

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

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.

Big-Box Stores and Urban Land Prices: Friend or Foe?

2017 ◽  
Vol 46 (1) ◽  
pp. 7-58 ◽  
Author(s):  
Barrett A. Slade
Keyword(s):  
Urban Land ◽  
Land Prices ◽  
Big Box

scholarly journals Uncovering inequality through multifractality of land prices: 1912 and contemporary Kyoto

PLoS ONE ◽  
2018 ◽  
Vol 13 (4) ◽  
pp. e0196737 ◽  
Author(s):  
Hadrien Salat ◽  
Roberto Murcio ◽  
Keiji Yano ◽  
Elsa Arcaute
Keyword(s):  
Land Prices

A meta-analysis of the capitalisation of CAP direct payments into land prices

2021 ◽  
Author(s):  
Alessandro Varacca ◽  
Giovanni Guastella ◽  
Stefano Pareglio ◽  
Paolo Sckokai
Keyword(s):  
Agricultural Policy ◽  
Meta Analysis ◽  
Extensive Review ◽  
The European Union ◽  
Decoupled Payments ◽  
Land Prices ◽  
Implementation Scheme ◽  
Direct Payments ◽  
Meta Regression ◽  
The Impact

Abstract The impact of the European Union common agricultural policy direct payments on land prices has received substantial attention in recent years, leading to heterogeneous evidence of capitalisation for both coupled and decoupled payments. In this paper, we provide an extensive review of the empirical works addressing this issue econometrically and compare their results through a Bayesian meta-regression model, focussing on the impact of decoupling and its implementation schemes. We find that the introduction of decoupled payments increased the capitalisation rate, although the extent of this increment hinges on the implementation scheme adopted by the member state.

Learning from House Prices: Amplification and Business Fluctuations

2020 ◽  
Author(s):  
Ryan Chahrour ◽  
Gaetano Gaballo
Keyword(s):  
House Prices ◽  
House Price ◽  
Price Increase ◽  
Land Prices ◽  
Business Fluctuations ◽  
Nominal Rigidity ◽  
Supply Shocks ◽  
Residential Investment ◽  
Amplification Loop ◽  
Initial Price

Abstract We formalize the idea that house price changes may drive rational waves of optimism and pessimism in the economy. In our model, a house price increase caused by aggregate disturbances may be misinterpreted as a sign of higher local permanent income, leading households to demand more consumption and housing. Higher demand reinforces the initial price increase in an amplification loop that drives comovement in output, labor, residential investment, land prices, and house prices even in response to aggregate supply shocks. The qualitative implications of our otherwise frictionless model are consistent with observed business cycles and it can explain the economic impact of apparently autonomous changes in sentiment without resorting to non-fundamental shocks or nominal rigidity.

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