Analysis of the residential location choice and household energy consumption behavior by incorporating multiple self-selection effects

Abstract

It is expected that the residential location choice and household energy consumption behavior might correlate with each other. Besides, due to the existence of self-selection effects, the observed inter-relationship between them might be the spurious result of the fact that some unobserved variables are causing both. These concerns motivate us to (1) consider residential location choice and household energy consumption behavior (for both in-home appliances and out-of-home cars) simultaneously and, (2) explicitly control self-selection effects so as to capture a relatively true effect of land-use policy on household energy consumption behavior. An integrated model termed as joint mixed Multinomial Logit-Multiple Discrete-Continuous Extreme Value model is presented here to identify the sensitivity of household energy consumption to land use policy by considering multiple self-selection effects. The model results indicate that land-use policy do play a great role in changing Beijing residents’ energy consumption pattern, while the self-selection effects cannot be ignored when evaluating the effect of land-use policy. Based on the policy scenario design, it is found that increasing recreational facilities and bus lines in the neighborhood can greatly promote household's energy-saving behavior. Additionally, the importance of “soft policy” and package policy is also emphasized in the context of Beijing.

Introduction

Energy problem has gained more and more attention from both developed and developing countries. Recently, apart from the technological development and economic control measures, the role of the behavioral sciences is emphasized in dealing with the energy issue (Armel, 2008, Allcott and Mullainathan, 2010), especially for the problem of household energy consumption (i.e., including both in-home and out-of-home energy usage) which has historically been difficult to address by using traditional economic methods (Yu et al., 2011).

In the behavioral sciences, the importance of relationships between long-term choices, medium-term choices and short-term choices is emphasized (Eliasson and Mattsson, 2000, Waddell, 2001). In the household energy consumption domain (note that household energy consumption here is defined as direct energy used within households and for personal transport, while the indirect energy embedded in goods and services purchased by households is excluded), following the definition given by Ben-Akiva and Lerman (1991), the long-term decision is defined as the residential choice; medium-term decision as the choice of end-use ownership; and short-term decision as the end-use usage (e.g., frequency, duration, distance traveled, etc.). It is plausible that the decision of residential location not only determines the connection between the household with the rest of the urban environment, but also influences the household's activity time allocation (Pinjari et al., 2009) as well as the concomitant energy consumption behavior. Under such kind of consideration, it is reasonable to infer that residential location choice might be influential to household energy consumption behavior. Although the integrated analysis on land-use planning and travel behavior has received a great deal of interest, the land-use and energy consumption by in-home end uses does not gain the same level of attention in both academic and practical sides (Cooper, 2011). According to the CFA (Consumer Federation of America) survey result, it is surprising that in America, since 2009, the energy consumption caused by in-home end uses has taken just as large a bite out of household budgets as does expenditures for gasoline. Therefore, both of the in-home and out-of-home energy consumption deserves to be emphasized, furthermore, due to the total money and time budget constraints, it is necessary to consider these two together (see Yu et al., 2011 for an elaboration).

Essentially, the inter-relationship between residential location and household energy consumption behaviors can be very complicated. However, majority of earlier research assumed that there is a one-way causal effect from the residential environment (RE) characteristics to household energy consumption behavior. Specifically to say, households and individuals locate themselves in neighborhoods, and then based on neighborhood attributes, determine their energy consumption behaviors. In this context, if it is found that accessibility to bus/subway station has a negative influence on household energy consumption, the implication would be that building neighborhoods by configuring a near bus/subway stop could decrease the aggregate energy demand in the population. The problem here is that how individuals/households make residential choice and energy consumption decisions is not comprehensively known. In reality, households and individuals who are environmentally-friendly may self select to settle down in neighborhoods with good accessibility to bus/subway station, hence, they can pursue their energy-saving lifestyles. If this were true, urban land-use policies aimed at increasing the accessibility to public transport would not get the expected result on reducing household energy consumption. Such kind of non-causal association between residential choice and energy consumption behavior derived from intervening variables (e.g., social factors, cultural factors, psychological factors, social-demographics, etc.) which are causing both is termed as “self-selection effect”. Statistically, self-selection arises in any situation in which individuals select themselves into a group. In this sense, interaction between residential choice and household energy consumption behavior should not be simply interpreted by regarding the residential environment indicators as exogenous explanatory variables. The observed inter-relationship between these two might be part causal and part self-selection. That is to say, after controlling for the spurious association due to self-selection effect based on demographics and other unobserved characteristics, we are more confident of assessing the causal impact of RE on household energy consumption, and then more credible and persuasive policies can be developed. Meanwhile, the self-selection effect might vary with end uses. For example, households who do not like cooking may choose to reside in the neighborhood with good catering facilities (e.g., restaurants and/or supermarkets) and use less cooking-related end uses, while households with a preference on driving may prefer to live in suburban area so as to satisfy their desire of driving. Obviously, these two effects are distinct. Thus, it is better to consider multiple self-selection effects which reflect the diverse self-selection effects for different end uses. Additionally, the above-mentioned behavioral aspects might be heterogeneous across households, caused by observed and unobserved factors.

The above-mentioned behavioral mechanisms actually pose some policy issues which have not been highlighted in practice. First, whether is the land-use policy effective on controlling the household energy consumption and to what extend does it work? The “true” effect of land-use policy might be wrongly predicted if the self-selection phenomenon is ignored. Second, whether does the self-selection effect significantly exist and for what types of end uses may households have significant self-selection effects? By answering these two questions, the need for “soft policy” (e.g., enhancing the residents’ environmental awareness, making the residents aware of their excessive energy consumption patterns, and promoting energy-saving behavior) and what kinds of end uses should be emphasized when implementing the “soft policy” could be identified. Third, whether is it necessary to jointly represent the energy consumption behaviors in domestic sector and private transportation sector? This issue might provide unique lens on the necessity of the development of the package policy which could reduce the energy consumption in the above two sectors simultaneously.

In order to develop a robust policy system to reduce the total household energy consumption, this study aims to deal with the aforesaid policy issues by accommodating all the behavioral mechanisms mentioned above in a consistent and unified framework. Specifically, we first build an integrated model, termed mixed Multinomial Logit–Multiple Discrete-Continuous Extreme Value (MNL–MDCEV) model, which covers residential location choice, end-use (including in-home appliances and out-of-home cars) ownership, and usage behavior, and then apply it to examine the sensitivity of household energy consumption to changes in land use policy by considering a comprehensive set of residential environment (RE) variables, socio-demographic variables as well as multiple self-selection effects. For the purposes of this study, a household energy consumption survey was conducted in Beijing in 2010 to collect the information about household energy consumption, ownership/usage of in-home appliances and cars, household and individual attributes, together with the residential environment characteristics. As a result, 775 valid samples were finally collected and the data is utilized to estimate the model.

The remaining part of this paper is organized as follows. The next section gives a brief overview of the existing literature on residential choice and household energy consumption behaviors. Section 3 presents the structure of the integrated model (i.e., mixed MNL–MDCEV model). Section 4 introduces the survey data. Results of model estimation are shown and the policy scenario design based on the model results is interpreted in Section 5. This study is concluded in Section 6 along with a discussion about future research issues.