The Experts below are selected from a list of 20628 Experts worldwide ranked by ideXlab platform
Anh Pham - One of the best experts on this subject based on the ideXlab platform.
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racial and ethnic price differentials in a small Urban Housing Market
Housing Policy Debate, 2012Co-Authors: Sanjaya Desilva, Anh Pham, Michael SmithAbstract:This article examines whether the presence of blacks and Hispanics has a negative impact on prices in a small Urban Housing Market in the US. To alleviate estimation biases associated with unobserved neighborhood heterogeneity, we focus on Housing price differences across micro-neighborhoods in the small and relatively homogeneous city of Kingston, New York, introduce GIS-based spatial amenity variables as controls, and account for clustered errors, neighborhood fixed effects, spatial errors and spatial lags. Our results, with the exception of the spatial error model, conform with the consensus reached primarily from studies of large cities that the presence of blacks in a neighborhood is associated with lower Housing prices and that the impact of the presence of Hispanics is considerably weaker. The spatial error model yields weaker and statistically insignificant results for blacks, providing some evidence that price discounts in relatively black neighborhoods may be caused not by preferences for segregation but by the correlation of race and the quality of neighborhood amenities.
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racial and ethnic price differentials in a small Urban Housing Market
Housing Policy Debate, 2012Co-Authors: Sanjaya Desilva, Anh Pham, Michael SmithAbstract:This article examines whether the presence of blacks and Hispanics has a negative impact on prices in a small Urban Housing Market in the US. To alleviate estimation biases associated with unobserved neighborhood heterogeneity, we focus on Housing price differences across micro-neighborhoods in the small and relatively homogeneous city of Kingston, New York, introduce GIS-based spatial amenity variables as controls, and account for clustered errors, neighborhood fixed effects, spatial errors and spatial lags. Our results, with the exception of the spatial error model, conform with the consensus reached primarily from studies of large cities that the presence of blacks in a neighborhood is associated with lower Housing prices and that the impact of the presence of Hispanics is considerably weaker. The spatial error model yields weaker and statistically insignificant results for blacks, providing some evidence that price discounts in relatively black neighborhoods may be caused not by preferences for segreg...
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racial preferences in a small Urban Housing Market a spatial econometric analysis of microneighborhoods in kingston new york
2010Co-Authors: Sanjaya Desilva, Anh Pham, Michael SmithAbstract:This paper use spatial econometric models to test for racial preferences in a small Urban Housing Market. Identifying racial preferences is difficult when unobserved neighborhood amenities vary systematically with racial composition. We adopt three strategies to redress this problem: (1) we focus on Housing price differences across microneighborhoods in the small and relatively homogenous city of Kingston, New York; (2) we introduce GIS-based spatial amenity variables as controls in the hedonic regressions; and (3) we use spatial error and lag models to explicitly account for the spatial dependence of unobserved neighborhood amenities. Our simple OLS estimates agree with the consensus in the literature that black neighborhoods have lower Housing prices. However, racial price discounts are no longer significant when we account for the spatial dependence of errors. Our results suggest that price discounts in black neighborhoods are caused not by racial preferences but by the demand for amenities that are typically not found in black neighborhoods.
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racial preferences in a small Urban Housing Market a spatial econometric analysis of microneighborhoods in kingston new york 1
Social Science Research Network, 2010Co-Authors: Sanjaya Desilva, Anh PhamAbstract:This paper use spatial econometric models to test for racial preferences in a small Urban Housing Market. Identifying racial preferences is difficult when unobserved neighborhood amenities vary systematically with racial composition. We adopt three strategies to redress this problem: (1) we focus on Housing price differences across microneighborhoods in the small and relatively homogenous city of Kingston, New York; (2) we introduce GIS-based spatial amenity variables as controls in the hedonic regressions; and (3) we use spatial error and lag models to explicitly account for the spatial dependence of unobserved neighborhood amenities. Our simple OLS estimates agree with the consensus in the literature that black neighborhoods have lower Housing prices. However, racial price discounts are no longer significant when we account for the spatial dependence of errors. Our results suggest that price discounts in black neighborhoods are caused not by racial preferences but by the demand for amenities that are typically not found in black neighborhoods.
Ellen M Bassett - One of the best experts on this subject based on the ideXlab platform.
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a sharing economy unpacking demand and living conditions in the Urban Housing Market in kenya
World Development, 2018Co-Authors: Sumila Gulyani, Debabrata Talukdar, Ellen M BassettAbstract:With Africa’s Urban transition underway, Housing is a formidable challenge. Housing shortfalls and continued slum growth are consistently forecast. But what kinds of Housing do current residents occupy? Do owners have better quality Housing than tenants? How much do tenants pay and what features do they value? This study builds a demand-side understanding of Housing using survey data from over 14,000 households in 15 Kenyan cities.
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a sharing economy unpacking demand and living conditions in the Urban Housing Market in kenya
World Development, 2018Co-Authors: Sumila Gulyani, Debabrata Talukdar, Ellen M BassettAbstract:Abstract With Africa’s Urban transition underway, Housing is a formidable challenge. Housing shortfalls and continued slum growth are consistently forecast. But what kinds of Housing do current residents occupy? Do owners have better quality Housing than tenants? How much do tenants pay and what features do they value? This study builds a demand-side understanding of Housing using survey data from over 14,000 households in 15 Kenyan cities. Kenya’s Urban Housing Market is characterized by renting and sharing. Approximately 86 percent of residents are tenants; they outnumber owners in 14 of 15 cities. Sharing is ubiquitous—households share houses, rooms, and/or facilities such as toilets and taps. In contrast to standard notions of an “acceptable” Housing unit, only 18 percent of Urban Kenyans live in a self-contained unit with a toilet, kitchen, electricity, and private water connection. The Market is delivering two under-studied Housing categories—compounds and dormitories—explicitly designed for sharing. These house 40 percent of Urban households in individual rooms, but require sharing of toilets and water connections. Rents represent a significant share of household income, but indicate low ability to achieve ownership, if viewed as monthly mortgage payments. Hedonic regression analyses reveal the relative value of house features with electricity, kitchens and number of rooms emerging as important drivers of rent. Neighborhood conditions, such as lack of flooding and perceived safety, and neighborhood level infrastructure and services, such as garbage collection and access to transport, also have positive impacts upon rents. Our analysis urges a rethinking of Housing policies, including reevaluation of what type of Housing is deemed acceptable and affordable for very low income Urban residents. It underscores the need to develop more and better-quality rental Housing and calls for a reassessment of Housing and infrastructure investment programs, as well as more creative approaches for expanding home ownership.
Sanjaya Desilva - One of the best experts on this subject based on the ideXlab platform.
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racial and ethnic price differentials in a small Urban Housing Market
Housing Policy Debate, 2012Co-Authors: Sanjaya Desilva, Anh Pham, Michael SmithAbstract:This article examines whether the presence of blacks and Hispanics has a negative impact on prices in a small Urban Housing Market in the US. To alleviate estimation biases associated with unobserved neighborhood heterogeneity, we focus on Housing price differences across micro-neighborhoods in the small and relatively homogeneous city of Kingston, New York, introduce GIS-based spatial amenity variables as controls, and account for clustered errors, neighborhood fixed effects, spatial errors and spatial lags. Our results, with the exception of the spatial error model, conform with the consensus reached primarily from studies of large cities that the presence of blacks in a neighborhood is associated with lower Housing prices and that the impact of the presence of Hispanics is considerably weaker. The spatial error model yields weaker and statistically insignificant results for blacks, providing some evidence that price discounts in relatively black neighborhoods may be caused not by preferences for segregation but by the correlation of race and the quality of neighborhood amenities.
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racial and ethnic price differentials in a small Urban Housing Market
Housing Policy Debate, 2012Co-Authors: Sanjaya Desilva, Anh Pham, Michael SmithAbstract:This article examines whether the presence of blacks and Hispanics has a negative impact on prices in a small Urban Housing Market in the US. To alleviate estimation biases associated with unobserved neighborhood heterogeneity, we focus on Housing price differences across micro-neighborhoods in the small and relatively homogeneous city of Kingston, New York, introduce GIS-based spatial amenity variables as controls, and account for clustered errors, neighborhood fixed effects, spatial errors and spatial lags. Our results, with the exception of the spatial error model, conform with the consensus reached primarily from studies of large cities that the presence of blacks in a neighborhood is associated with lower Housing prices and that the impact of the presence of Hispanics is considerably weaker. The spatial error model yields weaker and statistically insignificant results for blacks, providing some evidence that price discounts in relatively black neighborhoods may be caused not by preferences for segreg...
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racial preferences in a small Urban Housing Market a spatial econometric analysis of microneighborhoods in kingston new york
2010Co-Authors: Sanjaya Desilva, Anh Pham, Michael SmithAbstract:This paper use spatial econometric models to test for racial preferences in a small Urban Housing Market. Identifying racial preferences is difficult when unobserved neighborhood amenities vary systematically with racial composition. We adopt three strategies to redress this problem: (1) we focus on Housing price differences across microneighborhoods in the small and relatively homogenous city of Kingston, New York; (2) we introduce GIS-based spatial amenity variables as controls in the hedonic regressions; and (3) we use spatial error and lag models to explicitly account for the spatial dependence of unobserved neighborhood amenities. Our simple OLS estimates agree with the consensus in the literature that black neighborhoods have lower Housing prices. However, racial price discounts are no longer significant when we account for the spatial dependence of errors. Our results suggest that price discounts in black neighborhoods are caused not by racial preferences but by the demand for amenities that are typically not found in black neighborhoods.
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racial preferences in a small Urban Housing Market a spatial econometric analysis of microneighborhoods in kingston new york 1
Social Science Research Network, 2010Co-Authors: Sanjaya Desilva, Anh PhamAbstract:This paper use spatial econometric models to test for racial preferences in a small Urban Housing Market. Identifying racial preferences is difficult when unobserved neighborhood amenities vary systematically with racial composition. We adopt three strategies to redress this problem: (1) we focus on Housing price differences across microneighborhoods in the small and relatively homogenous city of Kingston, New York; (2) we introduce GIS-based spatial amenity variables as controls in the hedonic regressions; and (3) we use spatial error and lag models to explicitly account for the spatial dependence of unobserved neighborhood amenities. Our simple OLS estimates agree with the consensus in the literature that black neighborhoods have lower Housing prices. However, racial price discounts are no longer significant when we account for the spatial dependence of errors. Our results suggest that price discounts in black neighborhoods are caused not by racial preferences but by the demand for amenities that are typically not found in black neighborhoods.
Sumila Gulyani - One of the best experts on this subject based on the ideXlab platform.
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a sharing economy unpacking demand and living conditions in the Urban Housing Market in kenya
World Development, 2018Co-Authors: Sumila Gulyani, Debabrata Talukdar, Ellen M BassettAbstract:With Africa’s Urban transition underway, Housing is a formidable challenge. Housing shortfalls and continued slum growth are consistently forecast. But what kinds of Housing do current residents occupy? Do owners have better quality Housing than tenants? How much do tenants pay and what features do they value? This study builds a demand-side understanding of Housing using survey data from over 14,000 households in 15 Kenyan cities.
-
a sharing economy unpacking demand and living conditions in the Urban Housing Market in kenya
World Development, 2018Co-Authors: Sumila Gulyani, Debabrata Talukdar, Ellen M BassettAbstract:Abstract With Africa’s Urban transition underway, Housing is a formidable challenge. Housing shortfalls and continued slum growth are consistently forecast. But what kinds of Housing do current residents occupy? Do owners have better quality Housing than tenants? How much do tenants pay and what features do they value? This study builds a demand-side understanding of Housing using survey data from over 14,000 households in 15 Kenyan cities. Kenya’s Urban Housing Market is characterized by renting and sharing. Approximately 86 percent of residents are tenants; they outnumber owners in 14 of 15 cities. Sharing is ubiquitous—households share houses, rooms, and/or facilities such as toilets and taps. In contrast to standard notions of an “acceptable” Housing unit, only 18 percent of Urban Kenyans live in a self-contained unit with a toilet, kitchen, electricity, and private water connection. The Market is delivering two under-studied Housing categories—compounds and dormitories—explicitly designed for sharing. These house 40 percent of Urban households in individual rooms, but require sharing of toilets and water connections. Rents represent a significant share of household income, but indicate low ability to achieve ownership, if viewed as monthly mortgage payments. Hedonic regression analyses reveal the relative value of house features with electricity, kitchens and number of rooms emerging as important drivers of rent. Neighborhood conditions, such as lack of flooding and perceived safety, and neighborhood level infrastructure and services, such as garbage collection and access to transport, also have positive impacts upon rents. Our analysis urges a rethinking of Housing policies, including reevaluation of what type of Housing is deemed acceptable and affordable for very low income Urban residents. It underscores the need to develop more and better-quality rental Housing and calls for a reassessment of Housing and infrastructure investment programs, as well as more creative approaches for expanding home ownership.
Yiyao He - One of the best experts on this subject based on the ideXlab platform.
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heterogeneous traders house prices and healthy Urban Housing Market a dsge model based on behavioral economics
Habitat International, 2020Co-Authors: Yiyao HeAbstract:Abstract A healthy Urban Housing Market should be characterized by relative stability, which is reflected in reasonable fluctuations in Housing prices. However, house prices in China have experienced rapid and prolonged growth of approximately twice that of people's disposable income since 2004. This growth can be attributed to the heterogeneous trading behaviors of value investors and domestic and foreign speculators. By constructing a Dynamic Stochastic General Equilibrium (DSGE) model based on the theory of behavioral economics, this study explores how fundamental and speculative investments affect Housing prices and economic fluctuations in a Market with heterogeneous traders. The devising of optimal macro-control policy is also discussed. Results show that speculators in the Housing Market explain the rapid rise and slow decline of house prices, which negatively affects a healthy Housing Market and its output. Excessive substitution effect between consumption and Housing purchase resulting from the real estate boom also negatively affects the final output. The simulation experiments of policy intervention show that the combination of exchange rate regulation and property tax contributes to the stability of the Housing Market and macro-economy as a mix of short- and long-term policies. This paper holds that to ensure the economy's sustainable development in the new era, the central bank should implement Market-oriented reforms of the exchange rate and lay out the landing of property tax properly.
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heterogeneous traders house prices and healthy Urban Housing Market a dsge model based on behavioral economics
Habitat International, 2020Co-Authors: Yiyao HeAbstract:Abstract A healthy Urban Housing Market should be characterized by relative stability, which is reflected in reasonable fluctuations in Housing prices. However, house prices in China have experienced rapid and prolonged growth of approximately twice that of people's disposable income since 2004. This growth can be attributed to the heterogeneous trading behaviors of value investors and domestic and foreign speculators. By constructing a Dynamic Stochastic General Equilibrium (DSGE) model based on the theory of behavioral economics, this study explores how fundamental and speculative investments affect Housing prices and economic fluctuations in a Market with heterogeneous traders. The devising of optimal macro-control policy is also discussed. Results show that speculators in the Housing Market explain the rapid rise and slow decline of house prices, which negatively affects a healthy Housing Market and its output. Excessive substitution effect between consumption and Housing purchase resulting from the real estate boom also negatively affects the final output. The simulation experiments of policy intervention show that the combination of exchange rate regulation and property tax contributes to the stability of the Housing Market and macro-economy as a mix of short- and long-term policies. This paper holds that to ensure the economy's sustainable development in the new era, the central bank should implement Market-oriented reforms of the exchange rate and lay out the landing of property tax properly.
