On the effect of fiscal zoning on land and housing values

Institute of University of I ' Business and California at I Economic Research Berkeley FISHER CENTER FOR REAL ESTATE AND URBAN ECONOMICS WORKING PAPER SERIES WORKING PAPER NO. 84-83 THE INTERJURISDICTIONAL EFFECTS OF GROWTH CONTROLS ON HOUSING PRICES L By These papers are preliminary in nature: their purpose is to - stimulate discussion and LAWRENCE KATZ comment. Therefore, they . KENNETH T_ ROSEN are not to be cited or quoted in any publication without the ex- press permission of the author. WALTER A. HAAS SCHOOL OF BUSINESS _

Valuing Urban Land with Land Residual and Option Value Methods: Applications to House Price Dynamics and Volatility

This paper presents a study of the possibilities of using statistical indicators of the functioning of the agricultural sector of the region’s economy to estimate the value of agricultural land resources. The emerging market of agricultural land in the Russian Federation is characterized by a small number of annual transactions; therefore, the assessment of the value of land at the territorial and regional level based on the mechanisms of supply and demand is extremely difficult. To substantiate the tax base of land tax and (in some cases) the rent amount, the cadastral value of land plots is used, which is determined by the results of the state cadastral valuation of agricultural land. The methodology for cadastral valuation is debatable, since it does not provide for surveys of specific land plots; at the same time, it relies on indicators of soil quality. Therefore, its results may not be relevant, because they do not take into account important elements of economic fertility. The purpose of this study is to develop a methodological approach for estimating the value of land, which makes it possible to reflect the real economic potential of agricultural land in the region. This approach is based on the method of direct capitalization of the specific conditional net income calculated on the basis of statistical reports of agricultural producers. The methodology was tested on data from the Voronezh region, as a result of which the authors’ differentiation of municipal districts was formed according to the estimated value of agricultural land. According to the results of a comparative analysis, it is recommended to consider the issue of the advisability of changing the current methodology for assessing the value of agricultural land.

As evidenced by the ubiquitous practice of zoning, many Americans feel that neighboring land uses strongly affect property values, especially those of single-family homes. It is somewhat surprising then that there exist only a few empirical studies designed to test for the existence and strength of negative externalities of neighboring land uses, and that the results of these studies are contradictory. William Stull' found that the median value of owner-occupied single-family homes was significantly affected by the amount of nonsingle-family land use within forty suburban towns in the Boston metropolitan area. But a study of Monroe County, New York2 and two studies of Pittsburgh3 concluded that no significant externalities exist. This study partially rectifies the discrepancy in these results by demonstrating that externalities caused by land use cannot be properly described by the simple definitions of "neighborhood" used in the previous studies.

Community Environment, Zoning, and the Market Value of Single-Family Homes

GIVEN the growing urbanization of our society, it appears likely that the urban property market will command increased scholarly attention. Aside from the fact of the mere importance of this market in our modern economy, it deserves such increased attention because it seems to be so poorly understood. Of course, it is true that many of the statements defining perfect markets are applicable to this one. There are many small independent buyers and sellers, none of whom usually control the market. Participants can easily obtain good information about prices from real estate agents and classified advertising. On the other hand, the product is far from homogeneous. More important for the present purpose, this market is supposedly characterized by interdependence. Externalities are said to abound. Introspective evidence as well as informal discussions with those persons in the act of selecting housing lend support to the view that "neighborhood effects" indeed exert important influences in this market. The existence of zoning ordinances tends to indicate that society has accepted this view. Consider the following statement of Haig:

Abstract. Evaluating residential property prices or land values is quite important for urban planning and government taxation as well. But it is generally difficult to predict land values accurately due to the dynamics of land prices, particularly in urban areas. Urban land values are mostly affected by natural environmental changes and various social and economic factors (Colwell & Munneke, 1997). Also, such socio economic factors are influencing both temporal and spatial aspects of land value, and therefore spatio-temporal clusters of land price changes will show local variations of land values very well. Specifically, the spatio-temporal hot spots might indicate highly increasing demand of lands in the urban area. In those areas, regulation against real estate speculation must be needed from the public perspective because such areas might impact on other area land prices and ultimately national economic status. Therefore, analyzing spatio-temporal aspects of the land price is essential for efficient urban planning and policy making. In this study, we attempt to detect spatio-temporal hot spots which are constantly increasing the value of residential property among real estate. Although there are many types of differently designated lands including such as commercial, agricultural, and lands for other usage, we focus on the residential lands to estimate land values in this research. The reason for this is because residential house price is substantially increasing and becoming one of sensitive issues of Seoul house market. Therefore, poor people or younger generation cannot afford such high housing expenses in Seoul. Also, house transaction data is much larger than other land usage data, and therefore it can be utilized for estimating land values more precisely. From 2011 to 2016, over 1.8 million housing transactions of lease and sale happened in Seoul. This big data on housing lease and sale transactions indicates the value of each location where the transaction occurred. Specifically, we utilize spatial interpolation method including Kriging and differential local Moran’s I approach based on housing transaction data in Seoul. Housing transaction data includes every transaction for sales and leases of the house for the particular period. By applying these methodologies, we can visualize spatio-temporal clusters of highly increasing land prices and interpret significant clusters in terms of social factors. In fact, land price distribution has been widely discussed associated with smart growth and urban development (American Planning Association, 2002; Kaiser et al., 1995). However, most studies have focused on urban development and expansion, rather than the changes in the land price. Moreover, many studies have applied remote sensing approach to analyze urban land expansion (Xiao et al., 2006; Magigi & Drescher, 2010). Notably, Hu et al., (2013) applied IDW to interpolate and estimating land prices with land samples. However, IDW has a shortcoming to interpolate the value which is distant from the sample points. In addition, even studies focusing on the land price have dealt with only one temporal period. From this research gap, we use the ordinary Kriging and differential local Moran’s I to detect and forecast local hot spots of land price changes. This research has conducted the following steps. At the first step, several transactions for the residential area are consolidated into a single land value indicator. Suppose that the residential rent consists of three factors that are housing price (P), deposit (D), and monthly rent (R). Each factor can be transformed into the value index (V) by the transformation formula below. After calculating the land value index from the transformation, the global trend of the value index is overlaid on each period. Figure 1. Shows the mean value index increased from 2011 to 2016. Then, square cells regularly spaced by 100 meters are generated over study area to perform the ordinary Kriging. After the ordinary Kriging, the land value index is assigned to each grid cell. Finally, differential local Moran’s I index is calculated based on the difference that value index change between each year. V = 0.75 * 0.005 * P + 0.005 * D + R As a result, the global trend of land value changes from 2011 to 2016 in Seoul is shown in Figure. 1. The mean value index is increasing constantly. The spatio-temporal hot spots of land price change are found where the value index increment exceeds the average value index increasing over Seoul. As a result, seven clusters are detected (Figure. 2).

Discussion

Spatial landscape indices in a hedonic framework: an ecological economics analysis using GIS

The Valuation of Urban Land: Comparison and Critique of Three CAMA Methods

In recent years, land value capture has attracted increasing attention because of its potential for funding transport infrastructure. It is well acknowledged that transport infrastructure can improve accessibility to employment and amenities; thus one might expect that it is the improved accessibility that adds value to land. Therefore, the issues in the relationship between transport accessibility and land value rise in connection with the concept of land value capture. A study looked at the relationship between transport accessibility and land value with the implication of a local model, geographically weighted regression (GWR). Traditional techniques, such as hedonic models, used to understand the attributes of land value, are global models that could be misleading in examining the spatially varying relationships, such as transport accessibility and land value. By using the Tyne and Wear region in the United Kingdom as a case study, the study revealed that nonstationarity existing in the relationship between transport accessibility and land value indicates that transport accessibility may have a positive effect on land value in some areas but a negative or no effect in others; this suggests that a uniform land value capture would be inappropriate. The use of GWR allows such spatially varying relationships to be revealed, leading to a better understanding of the factors determining positive land value uplift and the implications of spatially dependent transport access premiums in housing values in the context of value capture policies.

In recent years, land value capture has attracted increasing attention because of its potential for funding transport infrastructure. It is well acknowledged that transport infrastructure can improve accessibility to employment and amenities; thus one might expect that it is the improved accessibility that adds value to land. Therefore, the issues in the relationship between transport accessibility and land value rise in connection with the concept of land value capture. A study looked at the relationship between transport accessibility and land value with the implication of a local model, geographically weighted regression (GWR). Traditional techniques, such as hedonic models, used to understand the attributes of land value, are global models that could be misleading in examining the spatially varying relationships, such as transport accessibility and land value. By using the Tyne and Wear region in the United Kingdom as a case study, the study revealed that nonstationarity existing in the relationship between transport accessibility and land value indicates that transport accessibility may have a positive effect on land value in some areas but a negative or no effect in others; this suggests that a uniform land value capture would be inappropriate. The use of GWR allows such spatially varying relationships to be revealed, leading to a better understanding of the factors determining positive land value uplift and the implications of spatially dependent transport access premiums in housing values in the context of value capture policies.

Exploring the value of cultivated land resources around big cities is an important prerequisite for when realizing the “trinity” of cultivated land protection in terms of quantity, quality, and ecology. At present, the value of cultivated land resources faces the problem of having a low comparative efficiency of economic output, inadequate visualisation of asset value, and serious undervaluation. The manifestation of social, ecological, and cultural values in cultivated land plays an important role in accurately calculating the value of cultivated land. Therefore, this study attempted to clarify the composition and account for the logic of the comprehensive value of cultivated land around big cities. Taking the Hefei metropolitan area as an example, we used mathematical modeling and geostatistical analysis to measure the integrated value of cultivated land around big cities from 2010 to 2020 and analyse the spatial and temporal evolution characteristics and influencing factors. The results revealed a 2:7:1 ratio of economic, social, ecological, and cultural values for cultivated land in the metropolitan area. The comprehensive value of cultivated land was higher in 2020 than in 2010, was approximately 7.7 times the current compensation standard, and was significantly affected by the natural geography, economic development, cultivated land conditions, and protection policies. Furthermore, the comprehensive value showed spatial differentiation characteristics of ‘high in the east and south and low in the west and north’, and a spatial agglomeration effect was evident in some areas. A significant increase was observed in the social value of cultivated land, followed by an increase in the ecological and cultural values, whereas a slow downward trend was observed for the economic value. The economic value of cultivated land around big cities showed a downward trend, whereas the social, ecological, and cultural values showed upward trends. In the future, differentiated policy tools should be adopted based on the spatial heterogeneity of the comprehensive value of cultivated land in the Hefei metropolitan area to enhance their comprehensive value. In addition, scientific and reasonable compensation standards should be established, and high-quality agricultural development with the high-level protection of cultivated land should be promoted in metropolitan areas.

This paper develops an empirical method that uses two separate housing related components to estimate housing value: land and building. The artificial neural network (ANN) technique is used to iteratively solve for two hedonic models simultaneously by minimizing the difference in the observed total value and the sum of the estimated land and building values. This method enables one to objectively separate housing value into land and building components. Using actual sales transaction data from Taipei City, we estimate the land value as a share of the total housing value. The results show that the land value accounts for a higher share with older properties. The share of the land value of low-rise buildings tends to be higher than that of high-rise buildings. The share of the land value can deviate by 20 percentage points between more or less expensive housing communities within Taipei City.

Purpose– Housing is a composite asset comprising land and improved components varying as proportions of total value over space and time. Theory suggests land and improvements (structures) are unique goods responding differently to economic stimuli. This paper aims to test the expectation of different overall house price changes in response to variation in land and improved components.Design/methodology/approach– House price dynamics are decomposed to analyse the influence of land and structure components for the city of Perth, Australia both at aggregate level and for spatially defined housing sub-regions, sample period 1995-2010.Findings– Values of land and improvements on that land evolve differently over time and are significantly influenced by the magnitude of land leverage. The study extends previous research through extensive spatial disaggregation of a larger more detailed data set than previously used in studies of this type confirming significant variation in land leverage ratios, overall price change and growth rates for land and improvements in sub-regional markets defined by spatial criteria.Research limitations/implications– The results suggest an important role for policy development with respect to housing affordability and supply side regulation of land in large urban housing markets.Practical implications– The results suggest important implications for hedonic price analysis of housing markets. The inclusion of land leverage variables in hedonic regression could remove coefficient bias associated with omitted location amenity variables.Originality/value– The paper adapts methodology from previous studies but extends previous literature through detailed analysis of a large Australian housing market (Perth) enabling extensive spatial disaggregation of the sample and providing greater insight to spatial variation of land leverage than in previous studies.