Essays on Bayesian Inference for Social Networks

This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time. A social network is conceived as being a structure consisting of actors and their social interaction with each other. A common conceptualisation of social networks is to let the actors be represented by nodes in a graph with edges between pairs of nodes that are relationally tied to each other according to some definition. Statistical analysis of social networks is to a large extent concerned with modelling of these relational ties, which lends itself to empirical evaluation. The first paper deals with a family of statistical models for social networks called exponential random graphs that takes various structural features of the network into account. In general, the likelihood functions of exponential random graphs are only known up to a constant of proportionality. A procedure for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods is presented. The algorithm consists of two basic steps, one in which an ordinary Metropolis-Hastings up-dating step is used, and another in which an importance sampling scheme is used to calculate the acceptance probability of the Metropolis-Hastings step. In paper number two a method for modelling reports given by actors (or other informants) on their social interaction with others is investigated in a Bayesian framework. The model contains two basic ingredients: the unknown network structure and functions that link this unknown network structure to the reports given by the actors. These functions take the form of probit link functions. An intrinsic problem is that the model is not identified, meaning that there are combinations of values on the unknown structure and the parameters in the probit link functions that are observationally equivalent. Instead of using restrictions for achieving identification, it is proposed that the different observationally equivalent combinations of parameters and unknown structure be investigated a posteriori. Estimation of parameters is carried out using Gibbs sampling with a switching devise that enables transitions between posterior modal regions. The main goal of the procedures is to provide tools for comparisons of different model specifications. Papers 3 and 4, propose Bayesian methods for longitudinal social networks. The premise of the models investigated is that overall change in social networks occurs as a consequence of sequences of incremental changes. Models for the evolution of social networks using continuos-time Markov chains are meant to capture these dynamics. Paper 3 presents an MCMC algorithm for exploring the posteriors of parameters for such Markov chains. More specifically, the unobserved evolution of the network in-between observations is explicitly modelled thereby avoiding the need to deal with explicit formulas for the transition probabilities. This enables likelihood based parameter inference in a wider class of network evolution models than has been available before. Paper 4 builds on the proposed inference procedure of Paper 3 and demonstrates how to perform model selection for a class of network evolution models.

Modelli non lineari statici e dinamici su dati microeconomici: analisi delle condizioni finanziarie delle famiglie italiane

The thesis studies the economic and financial conditions of Italian households, by using microeconomic data of the Survey on Household Income and Wealth (SHIW) over the period 1998-2006. It develops along two lines of enquiry. First it studies the determinants of households holdings of assets and liabilities and estimates their correlation degree. After a review of the literature, it estimates two non-linear multivariate models on the interactions between assets and liabilities with repeated cross-sections. Second, it analyses households financial difficulties. It defines a quantitative measure of financial distress and tests, by means of non-linear dynamic probit models, whether the probability of experiencing financial difficulties is persistent over time. Chapter 1 provides a critical review of the theoretical and empirical literature on the estimation of assets and liabilities holdings, on their interactions and on households net wealth. The review stresses the fact that a large part of the literature explain households debt holdings as a function, among others, of net wealth, an assumption that runs into possible endogeneity problems. Chapter 2 defines two non-linear multivariate models to study the interactions between assets and liabilities held by Italian households. Estimation refers to a pooling of cross-sections of SHIW. The first model is a bivariate tobit that estimates factors affecting assets and liabilities and their degree of correlation with results coherent with theoretical expectations. To tackle the presence of non normality and heteroskedasticity in the error term, generating non consistent tobit estimators, semi-parametric estimates are provided that confirm the results of the tobit model. The second model is a quadrivariate probit on three different assets (safe, risky and real) and total liabilities; the results show the expected patterns of interdependence suggested by theoretical considerations. Chapter 3 reviews the methodologies for estimating non-linear dynamic panel data models, drawing attention to the problems to be dealt with to obtain consistent estimators. Specific attention is given to the initial condition problem raised by the inclusion of the lagged dependent variable in the set of explanatory variables. The advantage of using dynamic panel data models lies in the fact that they allow to simultaneously account for true state dependence, via the lagged variable, and unobserved heterogeneity via individual effects specification. Chapter 4 applies the models reviewed in Chapter 3 to analyse financial difficulties of Italian households, by using information on net wealth as provided in the panel component of the SHIW. The aim is to test whether households persistently experience financial difficulties over time. A thorough discussion is provided of the alternative approaches proposed by the literature (subjective/qualitative indicators versus quantitative indexes) to identify households in financial distress. Households in financial difficulties are identified as those holding amounts of net wealth lower than the value corresponding to the first quartile of net wealth distribution. Estimation is conducted via four different methods: the pooled probit model, the random effects probit model with exogenous initial conditions, the Heckman model and the recently developed Wooldridge model. Results obtained from all estimators accept the null hypothesis of true state dependence and show that, according with the literature, less sophisticated models, namely the pooled and exogenous models, over-estimate such persistence.

An interdisciplinary analysis of obesity: theory and empirical evidence

The dissertation is structured in three parts. The first part compares US and EU agricultural policies since the end of WWII. There is not enough evidence for claiming that agricultural support has a negative impact on obesity trends. I discuss the possibility of an exchange in best practices to fight obesity. There are relevant economic, societal and legal differences between the US and the EU. However, partnerships against obesity are welcomed. The second part presents a socio-ecological model of the determinants of obesity. I employ an interdisciplinary model because it captures the simultaneous influence of several variables. Obesity is an interaction of pre-birth, primary and secondary socialization factors. To test the significance of each factor, I use data from the National Longitudinal Survey of Adolescent Health. I compare the average body mass index across different populations. Differences in means are statistically significant. In the last part I use the National Survey of Children Health. I analyze the effect that family characteristics, built environment, cultural norms and individual factors have on the body mass index (BMI). I use Ordered Probit models and I calculate the marginal effects. I use State and ethnicity fixed effects to control for unobserved heterogeneity. I find that southern US States tend have on average a higher probability of being obese. On the ethnicity side, White Americans have a lower BMI respect to Black Americans, Hispanics and American Indians Native Islanders; being Asian is associated with a lower probability of being obese. In neighborhoods where trust level and safety perception are higher, children are less overweight and obese. Similar results are shown for higher level of parental income and education. Breastfeeding has a negative impact. Higher values of measures of behavioral disorders have a positive and significant impact on obesity, as predicted by the theory.

Rainfall spatial predictions: a two-part model and its assessment

Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

Essays in the Economics of Ageing

In the first paper, I assess if financial incentives may be used as an effective device to induce workers to postpone retirement by evaluating the Italian so called “super bonus” reform. The bonus consisted in economic incentives given for a limited period to private sector workers who had reached the requirements for seniority pension. Crucially for this study, public workers were not entitled to the bonus. Using data from the Bank of Italy Survey on Household Income andWealth, and exploiting the DID-Probit strategy proposed by Blundell et al. (JEEA, 2004), I assess the effect of the bonus on the decision to postpone retirement, by comparing private and public workers before and after the reform. Results suggest a reduction of 12ppt in the proportion of private workers who decided to retire among those qualifying for retirement. Results also suggest, not trivially, that most of the effect of the reform is driven by low-income workers. Finally, I propose an estimate of the extensive margin elasticity of Italian older workers. The second study estimates a structural reduced form of the “option value” model developed by Stock and Wise (1990) using Italian data from the Survey of Health, Ageing and Retirement in Europe (SHARE).Exploiting exogenous changes in social security wealth (SSW) results show a significant effect in the expected direction of SSW and of marginal incentives to retire. Results are robust even after controlling for individual heterogeneity and its correlation with financial incentives. Using detailed information on individuals, the results also highlights the importance of individual and job characteristics, which have been very little explored by this literature, as determinants of retirement. This suggests the potential of “tagging” in the design of social security incentives in order to reduce choice distortions and improve the overall efficiency of the system.

America's Shifting Color Line? Reexamining Determinants of Latino Racial Self-Identification

Objectives. Latinos are the nation's largest minority group and will double in size by 2050. Their size coupled with the fact that Latinos do not constitute a separate race raises questions about Latinos' incorporation into the U. S. racial hierarchy. This article explores patterns of Latino racial identity formation, examining the determinants of racial identity. Methods. Using the 2006 Latino National Survey, I estimate multinomial logit and ordered probit models of identification choices. Results. Latino racial identity is strongly associated with several factors, including socioeconomic status, measures of perceived discrimination and commonality, and measures of acculturation/assimilation. Most Latinos have a broader, more complex understanding of race. Furthermore, some Latinos do believe that they occupy a unique position in the racial hierarchy. Conclusions. The results suggest that the color line W. E. DuBois argued has long divided our nation may eventually shift.

Recipients' Satisfaction with Locally Procured Food Aid Rations: Comparative Evidence from a Three Country Matched Survey

Using survey data from natural experiments in three countries that simultaneously received food aid sourced locally and from the United States, we test the hypothesis that locally-sourced commodities are more culturally appropriate and thus preferred over traditional food aid commodities sourced from the donor country. We use a semi-nonparametric regression method to estimate recipients' satisfaction with these commodities across a range of criteria. We establish that recipients of locally procured rations are generally more satisfied with the commodities they receive than are recipients of US-sourced foods. This pattern is especially pronounced among less-well-off recipients. (C) 2013 Elsevier Ltd. All rights reserved.

Comparative Study of Informal Health Care Networks and Elderly Health Status in Argentina and Cuba

The objective of this study is to evaluate the impact of informal care support networks on the health status, life satisfaction, happiness and anxiety of elderly individuals in Argentina and Cuba. Recent economic changes, demographic changes, the structure of families and changes in women?s labor participation have affected the availability of informal care. Additionally, the growing number of elderly as a percentage of total population has significant implications for both formal and informal care in Argentina and Cuba. Methods: The SABE - Survey on Health, Well-Being, and Aging in Latin America and the Caribbean, 2000 was used as the data source. The survey has a sample of 10,656 individuals aged 60 years and older residing in private households occupied by permanent dwellers in 7 cities in the Latin American and Caribbean region. My study will focus on the Buenos Aires and Havana samples in which there were 1043 individuals and 1905 individuals respectively. General sampling design was used to establish comparability between countries. Individuals requiring assistance are surveyed on their source of help and the relative impact of informal versus paid help is measured for this group. Other measures of social support (number of living children, companionship and number of individuals living in the same dwelling) are used to measure networks for the full sample. Multivariate probit regression analyses were run separately for Cuba and for Argentina to evaluate the marginal impacts of the types of social support on health status, life satisfaction, happiness and anxiety. Results: For Argentina, almost all of the family help variables positively impact good health. Getting help from most other members of the family negatively impacts satisfaction with life. Happiness is affected differently by each of the family help variables but community support increases the likelihood of being happy. Although none of the family or community help variables show statistical significance, most negatively affect anxiety levels. In Cuba, all of the social support variables have a positive marginal impact on the health status of the elderly. In this case, some of the family and community help variables have a negative marginal impact on life satisfaction; however, it appears that having those closest to the elderly, children, spouse, or other family, positively impacts life satisfaction. Most of the support variables negatively impact happiness. Receiving help from a child, spouse or parent is associated with a marginal increase in anxiety, whereas receiving help from a grandchild, another family member or a friend actually reduces anxiety. Discussion: The study highlights the necessity for enhancing the coordination of various care networks in order to provide adequate care and reduce the burdens of old age on the individual, family and society and the need for consistent support for the caregivers. More qualitative work should be done to identify how support is given and what comprises the support. The constant change and advancement of the world, and the growth of the Latin American and Caribbean region, suggests that more updates studies need to be done.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

Using contingent valuation to estimate willingness to pay for improved water source in rural Uganda

This research was conducted in August of 2011 in the villages of Kigisu and Rubona in rural Uganda while the author was serving as a community health volunteer with the U.S. Peace Corps. The study used the contingent valuation method (CVM) to estimate the populations’ willingness to pay (WTP) for the operation and maintenance of an improved water source. The survey was administered to 122 households out of 400 in the community, gathering demographic information, health and water behaviors, and using an iterative bidding process to estimate WTP. Households indicated a mean WTP of 286 Ugandan Shillings (UGX) per 20 liters for a public tap and 202 UGX per 20 liters from a private tap. The data were also analyzed using an ordered probit model. It was determined that the number of children in the home, and the distance from the existing source were the primary variables influencing households’ WTP.

A model of factors determining levels of public support for health care policy in the United States

Public preferences for policy are formed in a little-understood process that is not adequately described by traditional economic theory of choice. In this paper I suggest that U.S. aggregate support for health reform can be modeled as tradeoffs among a small number of behavioral values and the stage of policy development. The theory underlying the model is based on Samuelson, et al.'s (1986) work and Wilke's (1991) elaboration of it as the Greed/Efficiency/Fairness (GEF) hypothesis of motivation in the management of resource dilemmas, and behavioral economics informed by Kahneman and Thaler's prospect theory. ^ The model developed in this paper employs ordered probit econometric techniques applied to data derived from U.S. polls taken from 1990 to mid-2003 that measured support for health reform proposals. Outcome data are four-tiered Likert counts; independent variables are dummies representing the presence or absence of operationalizations of each behavioral variable, along with an integer representing policy process stage. Marginal effects of each independent variable predict how support levels change on triggering that variable. Model estimation results indicate a vanishingly small likelihood that all coefficients are zero and all variables have signs expected from model theory. ^ Three hypotheses were tested: support will drain from health reform policy as it becomes increasingly well-articulated and approaches enactment; reforms appealing to fairness through universal health coverage will enjoy a higher degree of support than those targeted more narrowly; health reforms calling for government operation of the health finance system will achieve lower support than those that do not. Model results support the first and last hypotheses. Contrary to expectations, universal health care proposals did not provide incremental support beyond those targeted to “deserving” populations—children, elderly, working families. In addition, loss of autonomy (e.g. restrictions on choice of care giver) is found to be the “third rail” of health reform with significantly-reduced support. When applied to a hypothetical health reform in which an employer-mandated Medical Savings Account policy is the centerpiece, the model predicts support that may be insufficient to enactment. These results indicate that the method developed in the paper may prove valuable to health policy designers. ^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

Actividad insecticida de Ricinus Communis L. sobre Plodia Interpunctella Hbn. (Lepidoptera: Phycitinae).

La aplicación de insecticidas sintéticos como principal sistema de control de plagas de granos y productos almacenados ha originado el desarrollo de poblaciones de insectos resistentes a dichos químicos, la contaminación del medio ambiente y la acumulación de sustancias tóxicas en los alimentos. En este trabajo se evaluaron los efectos de la aplicación de molido de hojas de ricino sobre larvas de la «polilla de las harinas» (Lepidoptera: Phycitinae). Los molidos vegetales se obtuvieron a partir de hojas de Ricinus communis L. secadas en estufa a 40 ± 2 °C durante 48 horas y posteriormente molidas hasta lograr un polvo de textura similar a la harina de maíz, material con el que se mezcló a fin de lograr concentraciones de 5, 10 y 15 % y un testigo sin ricino. Las unidades experimentales consistieron en cajas de Petri con seis larvas de primer y segundo estadio y se efectuaron cinco repeticiones por tratamiento (n=120). Se registró el número de larvas, pupas y adultos vivos, cada cuatro días, hasta que las larvas sobrevivientes llegaron al estado adulto. Se calcularon los porcentajes de eficacia mediante la fórmula de Abbott. Los resultados se evaluaron por ANVA y test de Tukey. Se determinaron el tiempo efectivo medio (TE50) y concentración efectiva media (CE50) por el método Probit. Los resultados de mortalidad indicaron que la concentración al 15 % superó significativamente al resto de los tratamientos y al testigo.

Factores que influyen en la adopción de tecnologías de conservación de suelos en el secano interior de Chile Central

El desarrollo de sistemas agrícolas sustentables es un desafío en el contexto de políticas e incentivos tendientes a la conservación de los recursos naturales, especialmente en zonas de secano. El presente estudio examina variables demográficas y productivas que influyen en la adopción de tecnologías de conservación de suelos en 90 pequeños productores del secano interior de Chile Central, en las comunas de Pencahue y Curepto. Se utilizó un modelo de regresión Probit, el cual asocia la adopción de las tecnologías con las variables: edad del agricultor, tamaño familiar, superficie predial y forma de tenencia de la tierra; presencia de: plantaciones forestales, invernaderos, aboneras, animales mayores en el predio; experiencia en comercialización del productor y participación en actividades de capacitación. El modelo seleccionado tiene un alto poder de predicción, llegando a clasificar correctamente un 92,2% de las observaciones. Los resultados econométricos muestran que la participación en actividades de extensión, la superficie predial, la presencia de plantaciones forestales y el uso de aboneras, influyen de manera positiva y significativa sobre la adopción de tecnologías conservacionistas. Resulta relevante el impacto de la capacitación sobre la adopción de tecnologías de alto grado de inversión, así como la incorporación de prácticas de conservación de bajo nivel de inversión como las aboneras.