Essays on Machine Learning and Hedonic Models

Thesis (Ph.D.)--University of Washington, 2016-08

Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.

Consumer valuation of energy-saving features of residential air conditioners with hedonic and choice models

The promotion of energy-efficient appliances is necessary to reduce the energetic and environmental burden of the household sector. However, many studies have reported that a typical consumer underestimates the benefits of energy-saving investment on the purchase of household electric appliances. To analyze this energy-efficiency gap problem, many scholars have estimated implicit discount rates that consumers use for energy-consuming durables. Although both hedonic and choice models have been used in previous studies, a comparison between two models has not yet been done. This study uses point of sale data about Japanese residential air conditioners and estimates implicit discounts rates with both hedonic and choice models. Both models demonstrate that a typical consumer underinvests in energy efficiency. Although choice models estimate a lower implicit discount rate than hedonic models, the latter models estimate the values of other product characteristics more consistently than choice models.

The wine hedonic price models in the "Old and New World": : state of the art

The basic hedonic hypothesis is that goods are valued for their utility-bearing characteristics and not for the good itself. Each attribute can be evaluated by consumers when making a purchasing decision and an implicit price can be identified for each of them. Thus, the observed price of a certain good can be analyzed as the sum of the implicit prices paid for each quality attribute. Literature has reported hedonic models estimates in the case of wines, which are excellent examples of differentiated goods worldwide.The impact of different wine attributes (intrinsic or extrinsic) on consumers’ willingness to pay has been analyzed with dissimilar results. Wines coming from "New World" producers seem to be appreciated for different attributes than wines produced in the "Old World". Moreover, "Old and New World" consumers seem to value differently the wine’s characteristics. To our knowledge, no cross country analysis has been done dealing with "New World" wines in "Old World" countries, leaving an important gap in understanding underlying attributes influencing buying decisions.

The effects of cultural heritage on residential property values: Evidence from Lisbon, Portugal

This paper examines the impact of historic amenities on residential housing prices in the city of Lisbon, Portugal. Our study is directed towards identifying the spatial variation of amenity values for churches, palaces, lithic (stone) architecture and other historic amenities via the housing market, making use of both global and local spatial hedonic models. Our empirical evidence reveals that different types of historic and landmark amenities provide different housing premiums. While having a local non-landmark church within 100 meters increases housing prices by approximately 4.2%, higher concentrations of non-landmark churches within 1000 meters yield negative effects in the order of 0.1% of prices with landmark churches having a greater negative impact around 3.4%. In contrast, higher concentration of both landmark and non-landmark lithic structures positively influence housing prices in the order of 2.9% and 0.7% respectively. Global estimates indicate a negative effect of protected zones, however this significance is lost when accounting for heterogeneity within these areas. We see that the designation of historic zones may counteract negative effects on property values of nearby neglected buildings in historic neighborhoods by setting additional regulations ensuring that dilapidated buildings do not damage the city’s beauty or erode its historic heritage. Further, our results from a geographically weighted regression specification indicate the presence of spatial non-stationarity in the effects of different historic amenities across the city of Lisbon with variation between historic and more modern areas.

Spatial housing economics: a survey

This introduction to the Virtual Special Issue surveys the development of spatial housing economics from its roots in neo-classical theory, through more recent developments in social interactions modelling, and touching on the role of institutions, path dependence and economic history. The survey also points to some of the more promising future directions for the subject that are beginning to appear in the literature. The survey covers elements hedonic models, spatial econometrics, neighbourhood models, housing market areas, housing supply, models of segregation, migration, housing tenure, sub-national house price modelling including the so-called ripple effect, and agent-based models. Possible future directions are set in the context of a selection of recent papers that have appeared in Urban Studies. Nevertheless, there are still important gaps in the literature that merit further attention, arising at least partly from emerging policy problems. These include more research on housing and biodiversity, the relationship between housing and civil unrest, the effects of changing age distributions - notably housing for the elderly - and the impact of different international institutional structures. Methodologically, developments in Big Data provide an exciting framework for future work.

Analysis of house prices to assess economic impacts of new public transport infrastructure: Madrid metro line 12.

Transportation infrastructure is known to affect the value of real estate property by virtue of changes in accessibility. The impact of transportation facilities is highly localized as well, and it is possible that spillover effects result from the capitalization of accessibility. The objective of this study was to review the theoretical background related to spatial hedonic models and the opportunities that they provided to evaluate the effect of new transportation infrastructure. An empirical case study is presented: the Madrid Metro Line 12, known as Metrosur, in the region of Madrid, Spain. The effect of proximity to metro stations on housing prices was evaluated. The analysis took into account a host of variables, including structure, location, and neighborhood and made use of three modeling approaches: linear regression estimation with ordinary least squares, spatial error, and spatial lag. The results indicated that better accessibility to Metrosur stations had a positive impact on real estate values and that the effect was marked in cases in which a house was for sale. The results also showed the presence of submarkets, which were well defined by geographic boundaries, and transport fares, which implied that the economic benefits differed across municipalities.

Hedonic analysis of cell phones sold with post-paid service plans in Brazil

The aim of this paper is to analyze the determining factors for the pricing of handsets sold with service plans, using the hedonic price method. This was undertaken by building a database comprising 48 handset models, under nine different service plans, over a period of 53 weeks in 2008, and resulted in 27 different attributes and a total number of nearly 300,000 data registers. The results suggest that the value of monthly subscriptions and calling minutes are important to explain the prices of handsets. Furthermore, both the physical volume and number of megapixels of a camera had an effect on the prices. The bigger the handset, the cheaper it becomes, and the more megapixels a camera phone has, the more expensive it becomes. Additionally, it was found that in 2008 Brazilian phone companies were subsidizing enabled data connection handsets.

The effect on prices of the attributes of holiday hotels: a hedonic prices approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment. The effect on price is estimated under the hedonic function perspective by means of random effect models, known also as mixed or panel models. Some 82,000 prices were gathered between 1991 and 1998 from tour operator catalogues. The study reveals huge price differences between 4-star hotels and the rest, coupled with practically no difference between 1-star and 2-star hotels. Other attributes with a significant effect on price are town, hotel size, distance to the beach and availability of parking place. The results can assist hotel managers in shaping pricing and investment strategies

Two Levels of Motivation and Two Types of Well-Being: Relations Between General and Goal-Specific Motivations, and Eudaimonic and Hedonic Well-Being

In this thesis I assess the individual and joint predictive associations and effects between multiple motivation and well-being concepts. In particular, three pairs of motivation concepts (intrinsic/extrinsic, approach/avoidance, and eudaimonic/hedonic) are assessed simultaneously at two levels of analysis (disposition and goal) and examined in relation to two types of well-being (eudaimonic and hedonic) in two studies, one correlational and the other experimental. Study 1: Using a correlational design, participants (N = 325, M age = 19.10, 87% female) completed self-report measures assessing six motivation and two well-being concepts. Exploratory factor analyses were used to assess patterns of associations among the motivational constructs. Results indicated that constructs displaying conceptual and empirical similarities co-occur, particularly, intrinsic, approach and eudaimonic motivation. Regression models were used to assess predictive relations between the motivational constructs and well-being. Both types of well-being were predicted by approach and avoidance dispositions, and hedonic goals. Additionally, eudaimonic well-being was uniquely predicted by eudaimonic dispositions and goals, and intrinsic dispositions; and hedonic well-being was uniquely predicted by extrinsic dispositions and approach goals. The patterns of associations among motivational constructs, and similarities and differences in the ways they predict each type of well-being, are discussed. Study 2: Using an experimental design, participants (N = 447, M age = 19.30, 88% female) were randomly assigned to one of eight experimental conditions, each involving a manipulation aimed at priming combinations of the three pairs of motivational constructs at the goal level. Participants then completed measures of both types of well-being. ANOVAs were used to assess the main effects and interactions of experimental condition for each of the three pairs of motivational constructs on well-being. Main effects of experimental conditions were non-significant. However, results indicated that focus on each of the three pairs of motivational constructs predicted well-being and that the manipulation impacted well-being indirectly, through experimentally-shifted motivational focus. Few interactions emerged. Implications for future experimental research and the conceptual integration of motivation and well-being constructs are discussed. In conclusion, Studies 1 and 2 inform the motivation and well-being fields in novel ways and provide preliminary steps towards studying these fields from an integrated and comprehensive motivational framework.

HEDONIC ANALYSIS OF CELL PHONES SOLD WITH POST-PAID SERVICE PLANS IN BRAZIL

The aim of this paper is to analyze the determining factors for the pricing of handsets sold with service plans, using the hedonic price method. This was undertaken by building a database comprising 48 handset models, under nine different service plans, over a period of 53 weeks in 2008, and resulted in 27 different attributes and a total number of nearly 300,000 data registers. The results suggest that the value of monthly subscriptions and calling minutes are important to explain the prices of handsets. Furthermore, both the physical volume and number of megapixels of a camera had an effect on the prices. The bigger the handset, the cheaper it becomes, and the more megapixels a camera phone has, the more expensive it becomes. Additionally, it was found that in 2008 Brazilian phone companies were subsidizing enabled data connection handsets.

Hedonic analysis of cell phones sold with post-paid service plans in Brazil

The aim of this paper is to analyze the determining factors for the pricing of handsets sold with service plans, using the hedonic price method. This was undertaken by building a database comprising 48 handset models, under nine different service plans, over a period of 53 weeks in 2008, and resulted in 27 different attributes and a total number of nearly 300,000 data registers. The results suggest that the value of monthly subscriptions and calling minutes are important to explain the prices of handsets. Furthermore, both the physical volume and number of megapixels of a camera had an effect on the prices. The bigger the handset, the cheaper it becomes, and the more megapixels a camera phone has, the more expensive it becomes. Additionally, it was found that in 2008 Brazilian phone companies were subsidizing enabled data connection handsets.

Characterization Of Microsatellite Markers Developed From Prosopis Rubriflora And Prosopis Ruscifolia (leguminosae - Mimosoideae), Legume Species That Are Used As Models For Genetic Diversity Studies In Chaquenian Areas Under Anthropization In South America.

Prosopis rubriflora and Prosopis ruscifolia are important species in the Chaquenian regions of Brazil. Because of the restriction and frequency of their physiognomy, they are excellent models for conservation genetics studies. The use of microsatellite markers (Simple Sequence Repeats, SSRs) has become increasingly important in recent years and has proven to be a powerful tool for both ecological and molecular studies. In this study, we present the development and characterization of 10 new markers for P. rubriflora and 13 new markers for P. ruscifolia. The genotyping was performed using 40 P. rubriflora samples and 48 P. ruscifolia samples from the Chaquenian remnants in Brazil. The polymorphism information content (PIC) of the P. rubriflora markers ranged from 0.073 to 0.791, and no null alleles or deviation from Hardy-Weinberg equilibrium (HW) were detected. The PIC values for the P. ruscifolia markers ranged from 0.289 to 0.883, but a departure from HW and null alleles were detected for certain loci; however, this departure may have resulted from anthropic activities, such as the presence of livestock, which is very common in the remnant areas. In this study, we describe novel SSR polymorphic markers that may be helpful in future genetic studies of P. rubriflora and P. ruscifolia.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.