Identification of ‘wasteful commuting’ using search theory

In this paper, we employ search theory as a micro-economic foundation for the wasteful commuting hypothesis. In the empirical analysis, the extent of the ‘wasteful commuting’ is identified by comparing the commute of employees and self-employed individuals who do not work from home. It is argued that the commute of the self-employed is the result of a search process for vacant workplaces, whereas employees search for vacant jobs. Because the arrival rate of workplaces exceeds the arrival rate of jobs, the self-employed have a shorter commute. We find that 35% of the commuting time may be considered ‘wasteful’ and reject alternative hypotheses why the self-employed have a shorter commute.

Open Space in Cities The costs and benefits of providing open space in cities

Abstract Although many researchers have investigated the value of open space in cities, few of them have compared them to the costs of providing this amenity. In this paper, we use the monocentric model of a city to derive a simple cost-benefit rule for the optimal provision of open space. The rule is essentially the Samuelson-condition for the optimal provision of a public good, with the price of land as the appropriate indicator for its cost. The condition is made operational by computing the willingness to pay for public and private space on the basis of empirical hedonic price functions for three Dutch cities. The conclusions with respect to the optimal provision of open space differ between the three cities. Further investigation reveals that willingness to pay for parks and public gardens increases with income, although not as fast as that for private residential space. Key words: spatial planning, provision of public goods, cost-benefit analysis JEL code: R52, H41, D61 The authors would like to thank Paul Cheshire, Carel Eijgenraam, Martin Koning, Piet Rietveld and Wouter Vermeulen for very useful comments and Jelte Haagsma for research assistance. The authors would also like to thank the Dutch Association of Real Estate Agents (NVM) for using their data. Introduction It is generally recognized that market failures and external effects abound in urban economics (see, for instance, Anas, Arnott and Small, 1998), but it is often not completely clear how effective various possible measures are in improving resource allocation. A specific example is the evaluation of spatial planning policy, which is an almost universally an important part of urban policy. Although economists have paid attention to various aspects of spatial planning (see, for instance, Fischel (1985) on zoning) much remains to be learned. This paper focuses on one aspect of spatial planning within cities: the provision of open space in the form of parks and public gardens. These are generally considered to be important amenities and many studies have confirmed their significance for the well being of urban residents, usually on the basis of hedonic price studies. A glance at the literature suggests that most studies stop after having established that statistically significant benefits are present. However, for a complete cost-benefit analysis we also need to assess the costs of these amenities. In this paper we make an attempt to introduce the cost side into the analysis by deriving a cost-benefit rule that can be made operational by means of hedonic analysis. We apply this result to the provision of open space in three large cities of the Netherlands. In the densely populated Netherlands, spatial planning imposes tight restrictions on land use throughout the country, but especially on the western part, which is the economic centre. Probably the best known feature of Dutch physical planning is the prolonged attempt to preserve the polder landscape in the so-called Green Heart of the country's economic core region, the Randstad. As a consequence, the cities in that part of the country are more compact than they would otherwise probably have been. A framework for cost-benefit analysis In this section, we develop a model for a monocentric city in which a benevolent planner provides open space by means of spatial planning policy. The model is outlined in 2.1 and the policy evaluation question is considered in 2.2. Section 2.3 discusses the suggested cost-benefit rule and its operationalization and applicability in real world circumstances. The model We consider the demand for open space in a monocentric city, which is the workhorse of urban The utility function of the household is: (2.1) and the budget restriction: with y denoting household income, p i the price of land in neighbourhood i, t the commuting cost per unit t of distance, and x i the distance between neighbourhood i and the city centre. We have normalized the price of the composite good to 1. Households maximize their utility by choosing a neighbourhood i and thereby determining their optimal consumption of housing and the composite good. The price for land in the neighbourhoods adjusts in such a way that in every neighbourhood the same level of utility is reached. It is well known that the equilibrium rent level in the city can be described by a bid rent function. A bid rent function gives the maximum amount of money a household is willing to pay for one unit of land when it has to reach utility level u* and income, unit commuting cost and the available amount of open space are given. Formally, the bid rent function ψ is defined for each neighbourhood i as: where ( ) ⋅ C denotes the amount of the composite good that a household must consume in order to reach utility u* conditional on housing consumption h i and open space i S . 2 The first order condition of the maximization in (2.3) implies: This equation states that the value of the bid rent function equals the household's marginal willingness to pay for land. In a market equilibrium all households have the same gross income and reach the same utility level and are therefore on the same bid rent curve. The value of this bid rent curve is then equal to the price of land i p . Optimal provision of open space The amount of land available for residential purposes (R i ) and parks or public gardens (S i ) in neighbourhood i is L i . For simplicity we take this amount to be equal in all neighbourhoods. (At the end of the next section we will relax this assumption.) To study the optimal provision of open space in the city, we introduce a planner who maximizes the value of the social surplus generated by the city. This surplus is defined as the difference between the total amount of income earned in the city and the costs that have to be made to enable its inhabitants to reach a given utility level u*. The social planner chooses h i , R i and S i such that the value of the social surplus of each neighbourhood i (SS i ) is maximized, while taking into account the constraint: The social surplus SS of the city is the sum of the social surpluses of all neighbourhoods: In these equations i µ is the Lagrange multiplier associated with constraint (2.6). We can easily remove it by combining the last two conditions as: We assume that a neighbourhood will be developed whenever it contributes to the total surplus of the city, that is, whenever the value of the land in residential use (the provision of the appropriate amount of open space included) exceeds its value in agricultural use. This is similar to the way the boundary of the city is determined in monocentric models where no neighbourhoods are distinguished. A cost-benefit rule The derivations of the previous subsection suggest a relatively straightforward cost-benefit rule for the provision of open space. Open space should be provided until the sum of the marginal willingness to pay of all the inhabitants of a neighbourhood is equal to the market value of residential land in the neighbourhood: It should, of course, immediately be noted that neither the willingness to pay for open space nor the market value of residential land is directly observable. Open space is a public good for which no market price exists and urban residential land is in practice almost always traded jointly with the houses constructed on it. Fortunately, both problems can be solved by the hedonic method. To see this, observe that in a market equilibrium every household must reach the equilibrium utility level u*. This requires that a hedonic price function ( ) emerges that facilitates such an equilibrium. The budget restriction of a household can then be written as , and we can substitute it in the utility function to write the condition for a market equilibrium as: (2.12) Even though this hedonic price function is only defined in our model for a finite number of neighbourhoods, we may reasonably conjecture that a smooth function exists that takes on the same values as the actual hedonic function for all neighbourhoods and is also defined for other possible combinations of h, S, and x. Since small changes in h, S and x should not change utility, this more general smooth hedonic price function must have: It follows immediately from (2.13) that the partial derivative of the hedonic price function with respect to h is the marginal willingness to pay for residential land, and from (2.14) that the partial derivative of the hedonic price function with respect to S is the marginal willingness to pay for open space. Equation (2.15) shows the familiar property that the house price should contain a compensation for commuting cost. The version of the cost-benefit rule (2.11) that will be used in our empirical work is therefore: Existing literature The value of open space has been studied intensively over the past decades. For instance, an early study by Since a recent survey of the international literature on the valuation of open space is available, we will only briefly discuss a few studies for the Netherlands, to which our empirical work refers. Luttik (2000) studied a limited number of relatively small areas and found that a view on open space increases the value of a house with 6 to 12 percent. However, she reported that it was much more difficult to demonstrate any effect of a park or a recreational area bordering the residential area. For only two of the eight areas she examined significant coefficients for these variables were found. Visser and van Dam (2005) for distances well below the 500 m used in the Dutch white paper mentioned in the introduction

MEASURING WELFARE EFFECTS OF SPATIAL PLANNING

In a densely populated country such as the Netherlands, a restrictive spatial planning policy is generally believed to be necessary to balance the numerous and often contradictory claims on space of households, industries, infrastructure and agriculture, and other functions. Clearly, such a policy is expected to have beneficial effects. However, it should be equally clear, from its restrictiveness, that there are costs associated with such a policy. In this contribution the appropriateness of social cost benefit analysis is considered as a tool for the evaluation of spatial policy in the Netherlands. The paper starts with a brief overview of a major characteristic of this analysis and discusses its potential importance for the evaluation of spatial planning in the Netherlands. The discussion continues with the possibility of assessing the cost and benefits associated with non-market goods, which is perhaps the main controversial aspect of SCBA, by focusing on the relevant example of the value of open space in cities. Copyright (c) 2007 by the Royal Dutch Geographical Society KNAG.

What can hedonic analysis tell us about the value of landscapes?

One of the main tasks of Dutch spatial planning is the preservation of valuable landscapes. Landscapes, in our definition, are considered to be valuable in the sense that significant changes in these landscapes are experienced by many as a loss. For instance the typically Dutch polder landscape has, according to many, a high aesthetic value that justifies costly measures to protect it like the construction of a tunnel for the high-speed railway that crosses the so-called Green Heart of the Randstad which is dominated by this landscape type. There are other important examples of landscapes that are regarded as valuable in other parts of the country, for instance as the typical “bocage” landscape around Ootmarsum in the Twente region (eastern part of the Netherlands), and the heath field in parts of Drenthe (northern part of the Netherlands). These landscapes are closely connected to particular types of land-use (such as cattle farming in the case of the polders). As long as this specific land-use type is the most profitable one, in the conventional economic sense that no other use of the land gives the owner a higher profit, there is no need for special protection measures. However, if other land-use types become more profitable the landscape would disappear or its quality would decline. And hence land-use planning might become necessary

Monetary valuation of aircraft noise: A hedonic analysis around Amsterdam airport

In densely-populated countries and in particular in large metropolitan areas, the presence of so much human activity causes all sorts of negative externalities, for example traffic noise disturbance. These externalities call for corrective measures by the government. Economists have developed a number of procedures that provide reasonable estimates on the monetary value of some amenities and externalities. In this paper we develop a spatially-explicit hedonic pricing model for house prices in order to quantify the social cost of aircraft noise disturbance in monetary terms. While focusing on aircraft noise around Amsterdam airport in the urban fringe of the Amsterdam region, a key point in our analysis is that we account for background noise. We do this by taking multiple sources of traffic noise (i.e. road, railway and aircraft noise) into account simultaneously and by setting threshold values for all three sources of noise above which sound is generally experienced as nuisance. Based on our regression results we conclude that a higher noise level means ceteris paribus a lower house price. Air traffic has the largest price impact, followed by railway traffic and road traffic. These model outcomes can subsequently be used to estimate the marginal and total benefits of aircraft noise reduction in the studied area around Amsterdam airport. We find a marginal benefit of 1 dB noise reduction of 1459 Euro per house, leading to a total benefit of 1 dB noise reduction of 574 million Euros.Aircraft noise GIS Hedonic price theory Noise reduction Valuation

The effect of search imperfections on commuting behaviour: Evidence from employed and self-employed workers

We aim to estimate the effect of search imperfections on the length of the average commute. We start from the assumption that the commute of the self-employed is the result of a search process for vacant workplaces, whereas employees search for vacant jobs. Because the arrival rate of workplaces is much higher than the arrival rate of jobs, the self-employed minimize the commute, whereas employees may have to accept jobs with a longer commute. In the empirical analysis, the extent of the 'wasteful' or 'excess commuting' is identified by estimating the difference in the commute of employees and self-employed individuals. Our estimates indicate that about 40 to 60% of the observed commute may be considered 'excess' due to search imperfections. We reject a range of alternative hypotheses as to why the self-employed have a shorter commute than employees (self-selection of not working from home, preference for residence and workplace locations, characteristics of workers which are difficult to observe).

Monetary valuation of aircraft noise; a hedonic analysis around Amsterdam airport Ecological Economics

In densely-populated countries and in particular in large metropolitan areas, the presence of so much human activity causes all sorts of negative externalities, for example traffic noise disturbance. These externalities call for corrective measures by the government. Economists have developed a number of procedures that provide reasonable estimates on the monetary value of some amenities and externalities. In this paper we develop a spatially-explicit hedonic pricing model for house prices in order to quantify the social cost of aircraft noise disturbance in monetary terms. While focusing on aircraft noise around Amsterdam airport in the urban fringe of the Amsterdam region, a key point in our analysis is that we account for background noise. We do this by taking multiple sources of traffic noise (i.e. road, railway and aircraft noise) into account simultaneously and by setting threshold values for all three sources of noise above which sound is generally experienced as nuisance. Based on our regression results we conclude that a higher noise level means ceteris paribus a lower house price. Air traffic has the largest price impact, followed by railway traffic and road traffic. These model outcomes can subsequently be used to estimate the marginal and total benefits of aircraft noise reduction in the studied area around Amsterdam airport. We find a marginal benefit of 1 dB noise reduction of 1459 Euro per house, leading to a total benefit of 1 dB noise reduction of 574 million Euros. © 2009 Elsevier B.V. All rights reserved