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on Discrete Choice Models |
| By: | Bruno Lanz; Allan Provins |
| Abstract: | Discrete choice experiments (DCE) are increasingly used to quantify the demand for improvements to services provided by regulated utility companies and inform price controls. This form of preference elicitation, however, often reveals a high frequency of status quo (SQ) choices. This may signal an unwillingness of respondents to evaluate the proposed trade-offs in service levels, questioning the welfare theoretic interpretation of observed choices and the validity of the approach for regulatory purposes. Using the methodology for DCE in the regulation of water and sewerage services in England and Wales, our paper contributes to the understanding of SQ choices in several novel dimensions. First, we control for the perception of the SQ and the importance of attributes in day-to-day activities. Second, we use a split sample design to vary both the description of the SQ and the survey administration mode (online vs. in-person). Third, the service attributes can both improve or deteriorate, so that the SQ is not necessarily the least-cost option. Fourth, we examine SQ choices in individual choice tasks and across all tasks so as to identify the determinants of serial SQ choices. Our results suggest that individual SQ choices mostly reflect preferences and thus represent important information for the regulator. However, serial SQ choices are mainly driven by cognitive and/or contextual factors, and these responses should be analysed as part of standard validity tests. |
| Keywords: | Cost-benefit analysis; Regulated utilities; Economic valuation; Discrete choice experiments; Individual decision making; Status quo effect. |
| JEL: | C25 L43 L95 Q25 Q51 Q58 |
| Date: | 2015–02–26 |
| URL: | http://d.repec.org/n?u=RePEc:gii:ciesrp:cies_rp_35&r=dcm |
| By: | Usman Mustafa (Pakistan Institute of Development Economics, Islamabad); Iftikhar Ahmad (Pakistan Institute of Development Economics, Islamabad); Miraj ul Haq (Azad Jammu and Kashmir University, AJK, Pakistan) |
| Abstract: | A dignified and healthy life remains a distant nightmare to the large majority of population in developing countries including Pakistan. Large masses living in this world particularly South Asian country (that is home to over one fifth of the world’s population) is still striving for it. Pakistan, being a developing country, is no exclusion to that state. The condition of sanitation and solid waste management (SWM) in the country carriages a grave challenge to health and hygiene. This study was carried out to show at the household’s HHs) demand for improved environmental settings over valuing their willingness to pay (WTP) for better SWM facilities. The study follows contingent valuation method for assessing the HHs preferences for better living standards. Primary data used in the research was gathered with the application of tailor made questionnaire from both rural and urban regions of district Abbottabad, Pakistan at HHs premises. The objective was to discover the determinants of HH’s WTP for improved environment through better SWM services; the binomial logit regression method was used. Education, income, awareness, location and HH size were found to be influencing HH’s WTP. The study concluded that HHs were WTP, if adequate services were delivered to them. |
| Keywords: | Contingent Valuation Method, Binomial Logit Regression, Willingness to Pay, Solid Waste Management, Environment, Pakistan |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:pid:wpaper:2014:110&r=dcm |
| By: | Pedro Albarrán; Raquel Carrasco; Jesús M. Carro |
| Abstract: | This paper presents and evaluates estimation methods for dynamic nonlinear correlated random effects (CRE) models with unbalanced panels. Accounting for the unbalancedness is crucial in dynamic non-linear models and it cannot be ignored even if the process that produces it is completely at random. Available approaches to estimate dynamic CRE models accounting for the initial conditions problem were developed for balanced panels and they do not work with unbalanced panels. In this type of dynamic models, just ignoring the unbalancedness produces inconsistent estimates of the parameters. Another potential "solution", used by some practitioners, is to take the sub-sample that constitutes a balanced panel and then to estimate the model using the available methods. Nonetheless, this approach is not feasible in some cases because the constructed balanced panel might not contain enough number of common periods across individuals. Moreover, when feasible, it discards useful information, which, as we show, leads to important efficiency losses. In this paper we consider several scenarios in which the sample selection process can be arbitrarily correlated with the permanent unobserved heterogeneity. The approaches we propose exploit all the observations available, can be implemented using standard solutions to the initial conditions problem, and can be easily applied in the context of commonly used models, such as dynamic binary choice models. |
| Keywords: | unbalanced panels, correlated random effects, dynamic non-linear models |
| JEL: | C23 C25 |
| Date: | 2015–02 |
| URL: | http://d.repec.org/n?u=RePEc:cte:werepe:we1503&r=dcm |
| By: | Igor Sarman (Istituto di ricerche economiche (IRE), Facoltà di scienze economiche, Università della Svizzera italiana, Switzerland) |
| Abstract: | Second-homes represent a very peculiar reality for the tourism market, particularly in Switzerland in which this segment has a long tradition and represents an important share in the accommodation sector. Very few studies took into account the intention of second-home owners to permanently move to the place (typically representing the destination of leisure trips) where they own their dwelling. The purpose of the research is to investigate how the intention to relocate is determined by a set of factors; among these, we include socio-economic covariates characterizing the second-home owners and the extent and habits of usage of the second-home. We apply an ordered logit model in which the dependent variable is the self-assessed probability to relocate; we extend the classical framework of ordered logit models including a latent variable, described by a series of indicators such as the attraction of the owners towards the region of relocation, the desire to spend time at destination and owners’ relationship with neighbors. The rationale behind the use of unobservable factors is the idea that the decision to permanently relocate in the second-home destination is not only affected by observable variables but also by different attitudinal and psychological aspects which are not directly observable. Data used to pursue the research objectives refer to a structured survey submitted to individuals owning a second-home in the Lake Maggiore region in Canton Ticino (Switzerland) and the subsample of Swiss respondents was analyzed. About one fifth of the eligible sample declared a very high probability to relocate in a permanent way in the vacation home while more or less 40% declared a very low likelihood. Results indicate that the attitudinal and psychological traits expressed by the second-home owners represent a fundamental source of explanation of their intention to permanently relocate. |
| Keywords: | second-home destinations, intention to move, latent variables, destination engagement, ordered variables modeling |
| Date: | 2015–02 |
| URL: | http://d.repec.org/n?u=RePEc:lug:wpidep:1502&r=dcm |