Search results for "Mixture models"
showing 10 items of 15 documents
The many faces of human sociality: uncovering the distribution and stability of social preferences
2018
There is vast heterogeneity in the human willingness to weigh others' interests in decision making. This heterogeneity concerns the motivational intricacies as well as the strength of other-regarding behaviors, and raises the question how one can parsimoniously model and characterize heterogeneity across several dimensions of social preferences while still being able to predict behavior over time and across situations. We tackle this task with an experiment and a structural model of preferences that allows us to simultaneously estimate outcome-based and reciprocity-based social preferences. We find that non-selfish preferences are the rule rather than the exception. Neither at the level of …
Early life body mass trajectories and mortality in older age: Findings from the Helsinki Birth Cohort Study
2014
Overweight and obesity in childhood have been linked to an increased risk of adult mortality, but evidence is still scarce.We identified trajectories of body mass index (BMI) development in early life and investigated their mortality risk. Data come from the Helsinki Birth Cohort Study, in which 4943 individuals, born 1934-1944, had serial measures of weight and height from birth to 11 years extracted from health care records, weight and height data in adulthood, and register-based mortality data for 2000-2010.Three early BMI trajectories (increasing, average, and average-to-low for men and increasing, average, and low-to-high BMI for women) were identified. Women with an increasing or low-…
A robust aerial image registration method using Gaussian mixture models
2014
Aerial image registration is one of the bases in many aerospace applications, such as aerial reconnaissance and aerial mapping. In this paper, we propose a novel aerial image registration algorithm which is based on Gaussian mixture models. First of all, considering the characters of the aerial images, the work uses a shape feature detector which computes the boundaries of regions with nearly the same gray-value to extract invariant feature. Then, a Gaussian mixture models (GMM) based image registration model is built and solved to estimate the transformation matrix between two aerial images. Furthermore, the proposed method is applied on real aerial images, and the results demonstrate the …
Unbundling technology adoption and tfp at the firm level. Do intangibles matter?
2012
We use a panel of European firms to investigate the relationship between intangible assets and productivity. We distinguish between total factor productivity (tfp) and technology adoption, whereas standard estimations consider only a notion of productivity that conflates the two effects. Although we are unable to address simultaneity, we allow for the existence of multiple technologies within sectors through a mixture model approach. We find that intangible assets have nonnegligible effects that both push firms toward better technologies (technology adoption effects) and allow for more efficient exploitation of a given technology (tfp effects).
Environmental Quality and Entrepreneurial Activity in Rural Tourism in Italy
2012
We estimate the relation between environmental quality and services in rural tourism in Italy. We use the average number of firms per region in 2003-07 to indicate entrepreneurial activity. We suggest that heterogeneity among administrative regions can be tied to environmental quality. Incorporated farms in rural tourism are relatively more common in regions with better environmental quality, and command higher average price from better quality in hospitality. Only 7% of entrepreneurial activity can be attributable to environmental quality. We conclude that rural tourism activity in Italy is not genuinely tied to environmental quality.
Labor productivity and firm-level TFP with technology-specific production functions
2020
Abstract We investigate the technological dimension of productivity, presenting an empirical methodology based on mixture models to disentangle the labor productivity differences associated with the firm's choice of technology (BTFP) and those related to the firm's ability to exploit the adopted technology (WTFP). The estimation endogenously determines the number of technologies (in the sector) and degree of technology sharing across firms (i.e., for each firm, the probability of using a given technology). By using comparable data for about 35,000 firms worldwide distributed across 22 (two-digit) sectors, we show BTFP to be at least as important as WTFP in explaining the labor productivity …
Evolution of the Global Distribution of Carbon Dioxide: A Finite Mixture Analysis
2015
Economists and environmental policymakers have recently begun advocating a bottom-up approach to climate change mitigation, focusing on reduction targets for groups of nations, rather than large scale global policies. We advance this discussion by taking a quantitative perspective, focusing on econometric identification of groups of countries that have statistically similar distributions of carbon emissions using a broad range of finite mixture models. Nearly all of our results yield a consistent pattern: after 1980, there are two distinct emissions distributions, and that these distributions continue to evolve over time. We provide a rigorous analysis of these distributional differences al…
Incentive and Selection Effects of Medigap Insurance on Inpatient Care
2012
The Medicare program, which provides insurance coverage to the elderly in the United States, does not protect them fully against high out-of-pocket costs. For this reason private supplementary insurance, named Medigap, has been available to cover Medicare gaps. This paper studies how Medigap affects the utilization of inpatient care, separating the incentive and selection effects of supplementary insurance. For this purpose, we use two alternative estimation methods: a standard recursive bivariate probit and a discrete multivariate finite mixture model. We find that estimated incentive effects are modest and quite similar across models. On the other hand, there seems to be very significant …
Analysis and modeling of Temporal Dominance of Sensations with stochastic processes
2019
Temporal Dominance of Sensations (TDS) is a technique to measure temporal perception of food product during tasting. For a panelist, it consists in choosing in a list of attributes which one is dominant at any time. This work aims to model TDS data with a stochastic process and proposes to use semi-Markov processes (SMP), a generalization of Markov chains which allows dominance durations to be modeled by any type of distribution. The model can then be used to compare TDS samples based on likelihood ratio. Because probabilities of transition from one attribute to another one can also depend on time, we propose to model TDS by period and we propose a method to select optimally the number of p…
Analysis and modeling of Temporal Dominance of Sensations with stochastic processes
2019
Temporal Dominance of Sensations (TDS) is a technique to measure temporal perception of food product during tasting. For a panelist, it consists in choosing in a list of attributes which one is dominant at any time. This work aims to model TDS data with a stochastic process and proposes to use semi-Markov processes (SMP), a generalization of Markov chains which allows dominance durations to be modeled by any type of distribution. The model can then be used to compare TDS samples based on likelihood ratio. Because probabilities of transition from one attribute to another one can also depend on time, we propose to model TDS by period and we propose a method to select optimally the number of p…