scholarly journals HOUSING PRICE CYCLES IN POLAND – THE CASE OF 18 PROVINCIAL CAPITAL CITIES IN 2000–2020

2021 ◽  
Vol 25 (4) ◽  
pp. 332-345
Author(s):  
Radoslaw Trojanek
Keyword(s):  
Financial Crisis ◽  
Average Duration ◽  
Housing Price ◽  
Housing Markets ◽  
Real Term ◽  
Spatial Diversity ◽  
Capital Cities ◽  
Before And After ◽  
Provincial Capital ◽  
Unique Dataset

Using a unique dataset of 4,5 million offers, the housing cycles in 18 Polish provincial capitals were identified between 2000 and 2020 before and after the financial crisis. Differences in the course of the cycles depending on spatial diversity are presented, as well as differences in the strength of decreases and increases in individual phases. The examined housing markets in Poland have experienced significant variability in the extent of their cycles. One complete cycle was found in each of the analysed cities. Its average duration was approximately 12 years. In this cycle, residential prices (in real terms) increased by 88% on average, in the upward phase by 158%, while in the downward phase, they decreased by 27% in the cities under study. A correlation was found that implies that the higher the price rises in the upward period, the higher the price correction ensues in the cycle’s downward phase. Moreover, the similarity in fluctuations was present in the metropolitan markets in local housing markets, especially before the financial crisis. Apartment prices continued to grow by 2.9% on average in the real term during the COVID-19 pandemic in 2020.

Study on the Influencing Factors of the Western Provincial Capital Cities’ Housing Price Differences

2014 ◽  
Vol 1079-1080 ◽  
pp. 1093-1097
Author(s):  
Xi Lu Liu ◽  
Jian Ping Yang
Keyword(s):  
Real Estate ◽  
Supply And Demand ◽  
Housing Price ◽  
Real Estate Market ◽  
Capital Cities ◽  
The Real Estate ◽  
Western Area ◽  
Property Price ◽  
Provincial Capital ◽  
Price Differences

In recent years, the regional difference of the real estate price in western area gradually increases, making the effects of macroeconomic regulation and control is different among regions. In this paper, based on the theory of market supply and demand, first of all, the indicators are selected that can reflect the conditions of real estate market, then western provincial capital cities’ real estate markets are divided into three regions through cluster analysis. Secondly, the natural logarithmic model is established concerning the commercial housing price and the factors. Multiple regression analysis is performed for each area, in order to analyze the reasons of property price differences in three regions.

Dynamic Relationship between Crude Oil and Stock Prices in India: Before And After the Subprime Financial Crisis 2008

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 96-104
Author(s):  
P. Sakthivel ◽  
S. Rajaswaminathan ◽  
R. Renuka ◽  
N. R.Vembu
Keyword(s):  
Financial Crisis ◽  
Crude Oil ◽  
Stock Prices ◽  
Oil Prices ◽  
Energy Index ◽  
Data Set ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Long Run ◽  
Before And After

This paper empirically discovered the inter-linkages between stock and crude oil prices before and after the subprime financial crisis 2008 by using Johansan co-integration and Granger causality techniques to explore both long and short- run relationships.  The whole data set of Nifty index, Nifty energy index, BSE Sensex, BSE energy index and oil prices are divided into two periods; before crisis (from February 15, 2005 to December31, 2007) and after crisis (from January 1, 2008 to December 31, 2018) are collected and analyzed. The results discovered that there is one-way causal relationship from crude oil prices to Nifty index, Nifty energy index, BSE Sensex and BSE energy index but not other way around in both periods. However, a bidirectional causality relationship between BSE Energy index and crude oil prices during post subprime financial crisis 2008. The co-integration results suggested that the absence of long run relationship between crude oil prices and market indices of BSE Sensex, BSE energy index, Nifty index and Nifty energy index before and after subprime financial crisis 2008.

A multifractal detrended fluctuation analysis of housing market: a role of financial crises in developed economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Ali Raza ◽  
Nida Shah ◽  
Muhammad Tahir Suleman ◽  
Md Al Mamun
Keyword(s):  
Financial Crisis ◽  
Housing Market ◽  
Market Efficiency ◽  
House Price ◽  
Fluctuation Analysis ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Run ◽  
Before And After

Purpose This study aims to examine the house price fluctuations in G7 countries by using the multifractal detrended fluctuation analysis (MF-DFA) for the years 1970–2019. The study examined the market efficiency between the short-term and long-term in the full sample period, before and after the global financial crisis period. Design/methodology/approach This study uses the MF-DFA to analyze house price fluctuations. Findings The findings confirmed that the housing market series are multifractal. Furthermore, all the markets showed long-term persistence in both the short and long-term. The USA is identified as the most persistent house market in the short run and Japan in the long run. Moreover, in terms of efficiency, Canada is identified as the most efficient house market in the long run and the UK in the short run. Finally, the result of before and after the financial crisis period is consistent with the full sample result. Originality/value The contribution of this study in the literature is fourfold. This is the first study that has examined the house prices efficiency by using the MF-DFA technique given by Kantelhardt et al. (2002). Previously, the house market prices and efficiency has been investigated using generalized Hurst exponent (Liu et al., 2019), Quantile Regression Approach (Chae and Bera, 2019; Tiwari et al., 2019) but no study to the best of the knowledge has been done that has used the MF-DFA technique on the housing market. Second, this is the first study that has focused on the house markets of G7 countries. Third, this study explores the house market efficiency by dividing the market into two periods i.e. before and after the financial crisis. The study strives to investigate if the financial crisis determines the change in the degree of market efficiency or not. Finally, the study gives valuable insights to the investors that will help them in their investment decisions.

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