Has tourism driven house prices in Germany? Time-varying evidence since 1870

2021 ◽  
pp. 135481662110088
Author(s):  
Sefa Awaworyi Churchill ◽  
John Inekwe ◽  
Kris Ivanovski
Keyword(s):  
World War Ii ◽  
Historical Data ◽  
House Prices ◽  
Housing Prices ◽  
Time Varying ◽  
Data Set ◽  
Time Series Modelling ◽  
The Impact ◽  
Tourism Flows ◽  
Non Parametric

Using a historical data set and recent advances in non-parametric time series modelling, we investigate the nexus between tourism flows and house prices in Germany over nearly 150 years. We use time-varying non-parametric techniques given that historical data tend to exhibit abrupt changes and other forms of non-linearities. Our findings show evidence of a time-varying effect of tourism flows on house prices, although with mixed effects. The pre-World War II time-varying estimates of tourism show both positive and negative effects on house prices. While changes in tourism flows contribute to increasing housing prices over the post-1950 period, this is short-lived, and the effect declines until the mid-1990s. However, we find a positive and significant relationship after 2000, where the impact of tourism on house prices becomes more pronounced in recent years.

scholarly journals Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China

2022 ◽  
Vol 11 (1) ◽  
pp. 57
Author(s):  
Lingbo Liu ◽  
Hanchen Yu ◽  
Jie Zhao ◽  
Hao Wu ◽  
Zhenghong Peng ◽  
...  
Keyword(s):  
Public Service ◽  
House Prices ◽  
Housing Prices ◽  
Positive Influence ◽  
Policy Formulation ◽  
Public Facility ◽  
Factors Affecting ◽  
Public Facilities ◽  
Geographically Weighted Regression Model ◽  
The Impact

The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities accessibility of schools, hospitals, green space, and public transit stations with four kinds of accessibility models such as the nearest distance, real time travel cost, kernel density, and two step floating catchment area (2SFCA), and explores the multiscale effect of public services accessibility on house prices with multiscale geographically weighted regression model. The results show that the differentiated scale effect not only exists among different public facility accessibilities, but also exists in different accessibility models of the same sort of facility. The article also suggests that different facilities should adopt its appropriate accessibility model. This study provides insights into spatial heterogeneity of urban public service facilities accessibility, which will benefit decision making in equal accessibility planning and policy formulation for the layout of urban service facilities.

The Impact of US Monetary Growth on Bitcoin Trading Volume in the Current Economic Uncertainty

2020 ◽  
pp. 493-509
Author(s):  
İsmail Canöz
Keyword(s):  
Causal Relationship ◽  
Trading Volume ◽  
Causal Effect ◽  
Study Data ◽  
Time Interval ◽  
Time Varying ◽  
Economic Uncertainty ◽  
Causality Test ◽  
Data Set ◽  
The Impact

This study examines the effect of US monetary growth on Bitcoin trading volume. To achieve this purpose, firstly, the symmetric causality test is used. Following this test, another symmetric causality test is used to reveal a time-varying causal effect between variables. The data set covers the period from July 2010 to July 2019. The results of the first symmetric causality test, which considers the time interval of the study data as a whole, show that there is no causal relationship between variables. According to the results of the second causality test, these support the previous results substantially. However, an interesting detail is the causal relationship between variables for the period between April 2019 and July 2019. The reason for this relationship could be that investors who are indecisive during the current economic uncertainty add Bitcoin to their portfolios in response to the Federal Reserve's decisions.

The Effect of Home-Sharing on House Prices and Rents: Evidence from Airbnb

2020 ◽  
Author(s):  
Kyle Barron ◽  
Edward Kung ◽  
Davide Proserpio
Keyword(s):  
United States ◽  
Instrumental Variables ◽  
Positive Impact ◽  
House Prices ◽  
Data Set ◽  
Estimation Strategy ◽  
Instrumental Variables Estimation ◽  
Residential House ◽  
The Impact

We assess the impact of Airbnb on residential house prices and rents: using a data set of Airbnb listings from the entire United States and an instrumental variables estimation strategy, we show that Airbnb has a positive impact on house prices and rents.

Autarky and the Rise and Fall of Piracy in Ming China

2014 ◽  
Vol 74 (2) ◽  
pp. 509-534 ◽  
Author(s):  
James Kai-sing Kung ◽  
Chicheng Ma
Keyword(s):  
Historical Data ◽  
Sharp Rise ◽  
Data Set ◽  
Trade Potential ◽  
The Impact

We examine the impact of rigorous trade suppression during 1550–1567 on the sharp rise of piracy in this period of Ming China. By analyzing a uniquely constructed historical data set, we find that the enforcement of a “sea (trade) ban” policy led to a rise in pirate attacks that was 1.3 times greater among the coastal prefectures more suitable for silk manufactures—our proxy for greater trade potential. Our study illuminates the conflicts in which China subsequently engaged with the Western powers, conflicts that eventually resulted in the forced abandonment of its long upheld autarkic principle.

Dictatorial Peace?

2002 ◽  
Vol 96 (1) ◽  
pp. 15-26 ◽  
Author(s):  
MARK PECENY ◽  
CAROLINE C. BEER ◽  
SHANNON SANCHEZ-TERRY
Keyword(s):  
World War Ii ◽  
Authoritarian Regimes ◽  
Conflict Behavior ◽  
Democratic Peace ◽  
Data Set ◽  
Military Regimes ◽  
Interstate Disputes ◽  
Interesting Variation ◽  
The Impact ◽  
Militarized Interstate Disputes

Is there a dictatorial peace that resembles the democratic peace? This paper uses a new data set compiled by Barbara Geddes to examine the conflict behavior of three types of autocratic regimes—personalist, military, and single-party dictatorships—in the post-World War II era. We find some evidence that specific types of authoritarian regimes are peaceful toward one another. No two personalist dictators or two military regimes have gone to war with each other since 1945. These dyads were not less likely to engage in militarized interstate disputes than were mixed dyads, however. Although single-party regimes were the only homogeneous dyad in this study to have experienced war, multivariate analyses of participation in militarized interstate disputes suggest that single-party states are more peaceful toward one another than are mixed dyads. Thus, while we have found no unambiguous evidence of a dictatorial peace to match the robustness of the democratic peace, there is substantial interesting variation in the conflict behavior of specific types of authoritarian regimes. The analysis presented here demonstrates that studies of the impact of regime type on conflict behavior must work from a more sophisticated conception of authoritarianism.

scholarly journals THE EFFECT OF URBAN GREEN SPACES ON HOUSE PRICES IN WARSAW

2018 ◽  
Vol 22 (5) ◽  
pp. 358-371 ◽  
Author(s):  
Radoslaw Trojanek ◽  
Michal Gluszak ◽  
Justyna Tanas
Keyword(s):  
Least Squares ◽  
Residential Buildings ◽  
House Prices ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Data Set ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Green Area ◽  
The Impact

In the paper, we analysed the impact of proximity to urban green areas on apartment prices in Warsaw. The data-set contained in 43 075 geo-coded apartment transactions for the years 2010 to 2015. In this research, the hedonic method was used in Ordinary Least Squares (OLS), Weighted Least Squares (WLS) and Median Quantile Regression (Median QR) models. We found substantial evidence that proximity to an urban green area is positively linked with apartment prices. On an average presence of a green area within 100 meters from an apartment increases the price of a dwelling by 2,8% to 3,1%. The effect of park/forest proximity on house prices is more significant for newer apartments than those built before 1989. We found that proximity to a park or a forest is particularly important (and has a higher implicit price as a result) in the case of buildings constructed after 1989. The impact of an urban green was particularly high in the case of a post-transformation housing estate. Close vicinity (less than 100 m distance) to an urban green increased the sales prices of apartments in new residential buildings by 8,0–8,6%, depending on a model.

Realistic weather conditions and removal of time-varying sea-surface effects: Application on ocean-bottom-cable data

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. V297-V315
Author(s):  
Elsa Cecconello ◽  
Walter Söllner
Keyword(s):  
Weather Conditions ◽  
Surface Effects ◽  
Sea Surface ◽  
Ocean Bottom ◽  
Time Varying ◽  
Theoretical Derivation ◽  
Data Set ◽  
Wave Heights ◽  
Sea Surface Effects ◽  
The Impact

In marine seismic acquisition, seismic reflections at the sea surface, such as sea-surface ghosts and multiples, affect the accuracy of the retrieved subsurface reflections and reduce the usable frequency bandwidth. These sea-surface effects tend to increase with the increasing roughness of the weather conditions. Consequently, processing techniques that neglect the roughness and time variation of the sea surface induce errors in the data that could compromise the validity of the final images and interpretations. We study the impact of time-varying rough sea surfaces using a modeling method derived from the Rayleigh reciprocity theorem for time-varying surfaces, and we analyze errors in the source-deghosting operation. We show that the source-deghosting limitations are weather dependent for data including sea-surface multiples: For calm sea states (wave heights below 1.25 m), the error made by the source-deghosting process is negligible; however, for rough seas (wave heights above 1.5 m), it becomes significant and blurs the deghosted image at the sea-surface multiple signals. To accurately remove all sea-surface effects from the seismic data, we simultaneously apply source-deghosting and multiple-removal operations to the same up-going wavefield. This procedure is shown to be weather independent based on our theoretical derivation and the synthetic results. Finally, this is tested on a 2D OBC data set. Comparing the proposed inversion to up-down deconvolution, we observe similar features in both wavefields: Source ghosts and sea-surface multiples seem to have been correctly removed from the data, and the inverted result indicates a slightly better resolution for deeper reflections.

The Impact of Neighborhood Characteristics on Housing Prices-An Application of Hierarchical Linear Modeling

2012 ◽  
Vol 1 (2) ◽  
pp. 31-44
Author(s):  
Lee Chun Chang ◽  
Hui-Yu Lin
Keyword(s):  
Empirical Study ◽  
Hierarchical Linear Modeling ◽  
House Prices ◽  
Housing Prices ◽  
Neighborhood Characteristics ◽  
Linear Modeling ◽  
Hierarchical Linear Modelling ◽  
Neighborhood Characteristic ◽  
Linear Modelling ◽  
The Impact

Housing data are of a nested nature as houses are nested in a village, a town, or a county. This study thus applies HLM (hierarchical linear modelling) in an empirical study by adding neighborhood characteristic variables into the model for consideration. Using the housing data of 31 neighborhoods in the Taipei area as analysis samples and three HLM sub-models, this study discusses the impact of neighborhood characteristics on house prices. The empirical results indicate that the impact of various neighborhood characteristics on average housing prices is different and that the impact of house characteristics on house prices is also moderated by neighborhood characteristics.

Housing markets’ linkage between China and Taiwan

2019 ◽  
Vol 12 (5) ◽  
pp. 826-848 ◽  
Author(s):  
Mei-Se Chien ◽  
Neng-Huei Lee ◽  
Chih-Yang Cheng
Keyword(s):  
Economic Integration ◽  
House Prices ◽  
Housing Prices ◽  
Housing Markets ◽  
Wealth Effects ◽  
Time Varying ◽  
Consumer Expenditure ◽  
Content Type ◽  
Cross Border ◽  
Cointegration Tests

Purpose This paper aims to examine the linkage of regional housing markets between Taiwan and China as increasing economic integration. Design/methodology/approach Two time-varying estimations of cointegration tests, Gregory and Hansen (1996) cointegration test with structural break and the recursive coefficients of cointegration (Hansen and Johansen, 1993) are applied to trace the possible dynamic linkage of cross-border regional housing prices between Taiwan and China. Findings First, the estimating results of the long-run relationships show that increasing housing prices in Beijing and Shanghai decrease Taipei’s house prices, while Shenzhen and Chengdu have converse effects. The technologies’ levels of Taiwanese industries surrounding the cities in China will affect the direction of the linkage of regional housing prices between the two economies. Second, in light of causalities of these five housing prices’ changes, Beijing and Shanghai lead Taipei and Shanghai leads Chengdu, which, in turn, leads Shenzhen. Finally, the results of time-varying cointegration tests show that some critical economic and political incidents changed the linkages of housing prices between Taipei and the four cities in China. Originality/value Although some empirical works examined the linkages between cross-border house prices in Europe and the USA, study has looked at the linkages of cross-border housing prices between Taiwan and China. This is an interesting topic insofar as house price integration has implications for wealth effects that feed into consumer expenditure in both Taiwan and China. The empirical evidence overall displays the existence of the integration of regional housing markets between Taiwan and China. For the longer-term future, increasing economic integration between China and other Asia countries will result in greater and more diversified cross-border housing markets and pools of investors.

scholarly journals A new Mass Rapid Transit (MRT) line construction and housing wealth: Evidence from the Circle Line

2017 ◽  
Vol 1 (1) ◽  
pp. 64 ◽  
Author(s):  
Mi Diao ◽  
Yi Fan ◽  
Tien Foo Sing
Keyword(s):  
House Prices ◽  
Phase 1 ◽  
Housing Prices ◽  
Wealth Effects ◽  
Housing Wealth ◽  
Rapid Transit ◽  
Treatment Zone ◽  
Housing Wealth Effects ◽  
The Impact ◽  
Mass Rapid Transit

This study uses the opening of the new Mass Rapid Transit (MRT) in stages between 2010 and 2012 in Singapore as the exogenous event to empirically test the impact of the new Circle Line (CL) on housing wealth. Applying a "differences-in-differences" approach to the non-landed private housing transaction data covering the period from 2009 to 2013, we find that the average housing prices increase by 1.6% in the post-opening of the CL. We find significant capitalization of the new CL into housing prices, especially households living within a 400-meter radius (the treatment zone) from the closest MRT stations on the CL. The treatment effects that are measured by the “marginalwillingness to pay” for houses located within the treatment zone is 13.2% relative to houses located outside the treatment zone. The new CL opening creates an estimated S$1.23 billion housing wealth effects for households living in close proximity to the CL MRT stations. However, we do not find significant "anticipative" effects on house prices in the six-month window prior to the opening of CL. The strongest treatment effect is found after the opening of the phase 1 of CL, and the treatment intensity declines in phases 2 and 3 of the CL opening.

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