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Huayi Yu

Biographic Data

ID6009262
NAMEHuayi Yu
GIVEN NAMESHuayi
FAMILY NAMEYu
SIGNATUREYU H
AFFILIATIONSRenmin University of China
ORCID0000-0003-4762-4980
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS5
WORKS AS AUTHOR6
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2025
H-INDEX2
  • Does city-county consolidation lead to regional integration of the housing market? Evidence from China

    Open Access•Liyuan Cui, Yujuan Hou et al.•ARTICLE•Land Use Policy•2025•Cited by: 1•References: 54

  • Estimation and Inference of Special Types of the Coefficients in Geographically and Temporally Weighted Regression Models

    Zhi Zhang, Chang-Lin Mei et al.•ARTICLE•Annals of the American…•2023•Cited by: 2•References: 33

    Geographically and temporally weighted regression (GTWR) models have been widely used to explore spatiotemporal nonstationarity where all the regression coefficients are assumed to be varying over both space and time. In reality, however, constant, only temporally varying, and only spatially varying coefficients might also be possible depending on the underlying effects of the explanatory variables on the response variable. Therefore, the develop…

  • A tale of two districts

    Open Access•Huayi Yu, Yujuan Hou•ARTICLE•Regional Science and Urban…•2021

  • Pricing the value of the chance to gain admission to an elite senior high school in Beijing

    Open Access•Jun Han, Liyuan Cui et al.•ARTICLE•Cities•2021•Cited by: 2•References: 37

  • Regional heterogeneity and the trans-regional interaction of housing prices and inflation

    Open Access•Huayi Yu, Yanfen Huang•ARTICLE•Urban Studies•2016•References: 20

    This paper proposes a theoretical framework to analyse the regionally heterogeneous responses of housing prices and inflation to the monetary aggregates shock and the trans-regional interaction of housing prices and inflation, which has seldom been discussed in previous literature. Using a GVAR (Globe Vector Autoregression) model, evidence based on China’s 35 major cities for this framework is provided. The results show that (1) the housing price…

  • The spillovers and heterogeneous responses of housing prices

    Huayi Yu•ARTICLE•Journal of the Asia Pacific Economy•2015•References: 6

    Previous literature seldom discusses city-level housing price spillovers and city-level heterogeneous responses of housing prices to interest rate shocks. This paper adopts the recently developed globe vector autoregression (GVAR) model to empirically study not only the spillovers of housing prices and real income per capita among China's 35 major cities but also the impacts of interest rate shocks on housing prices among these cities. The empiri…

  • Estimation and Inference of Special Types of the Coefficients in Geographically and Temporally Weighted Regression Models

    Zhi Zhang, Chang-Lin Mei et al.•ARTICLE•Annals of the American…•2023•Cited by: 2•References: 33

    Geographically and temporally weighted regression (GTWR) models have been widely used to explore spatiotemporal nonstationarity where all the regression coefficients are assumed to be varying over both space and time. In reality, however, constant, only temporally varying, and only spatially varying coefficients might also be possible depending on the underlying effects of the explanatory variables on the response variable. Therefore, the develop…

  • Pricing the value of the chance to gain admission to an elite senior high school in Beijing

    Open Access•Jun Han, Liyuan Cui et al.•ARTICLE•Cities•2021•Cited by: 2•References: 37

  • Does city-county consolidation lead to regional integration of the housing market? Evidence from China

    Open Access•Liyuan Cui, Yujuan Hou et al.•ARTICLE•Land Use Policy•2025•Cited by: 1•References: 54

  • The spillovers and heterogeneous responses of housing prices

    Huayi Yu•ARTICLE•Journal of the Asia Pacific Economy•2015•References: 6

    Previous literature seldom discusses city-level housing price spillovers and city-level heterogeneous responses of housing prices to interest rate shocks. This paper adopts the recently developed globe vector autoregression (GVAR) model to empirically study not only the spillovers of housing prices and real income per capita among China's 35 major cities but also the impacts of interest rate shocks on housing prices among these cities. The empiri…

  • Regional heterogeneity and the trans-regional interaction of housing prices and inflation

    Open Access•Huayi Yu, Yanfen Huang•ARTICLE•Urban Studies•2016•References: 20

    This paper proposes a theoretical framework to analyse the regionally heterogeneous responses of housing prices and inflation to the monetary aggregates shock and the trans-regional interaction of housing prices and inflation, which has seldom been discussed in previous literature. Using a GVAR (Globe Vector Autoregression) model, evidence based on China’s 35 major cities for this framework is provided. The results show that (1) the housing price…

  • A tale of two districts

    Open Access•Huayi Yu, Yujuan Hou•ARTICLE•Regional Science and Urban…•2021

  • Pricing the value of the chance to gain admission to an elite senior high school in Beijing

    Open Access•Jun Han, Liyuan Cui et al.•ARTICLE•Cities•2021•Cited by: 2•References: 37

  • Estimation and Inference of Special Types of the Coefficients in Geographically and Temporally Weighted Regression Models

    Zhi Zhang, Chang-Lin Mei et al.•ARTICLE•Annals of the American…•2023•Cited by: 2•References: 33

    Geographically and temporally weighted regression (GTWR) models have been widely used to explore spatiotemporal nonstationarity where all the regression coefficients are assumed to be varying over both space and time. In reality, however, constant, only temporally varying, and only spatially varying coefficients might also be possible depending on the underlying effects of the explanatory variables on the response variable. Therefore, the develop…

  • Does city-county consolidation lead to regional integration of the housing market? Evidence from China

    Open Access•Liyuan Cui, Yujuan Hou et al.•ARTICLE•Land Use Policy•2025•Cited by: 1•References: 54

Housing Market and Economics (6 works) · Spatial and Panel Data Analysis (5 works) · China (4 works) · Geography (4 works) · Business (3 works) · Economics (3 works) · Finance (3 works) · Beijing (2 works) · Computer Science (2 works) · Database transaction (2 works)

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