Sources Of Unobserved Heterogeneity Research Articles

HANDLING OF OVERDISPERSION CASES IN MORBIDITY DATA IN SELUMA REGENCY

The problem of overdispersion as a violation of the assumption of equidispersion in Poisson regression is generally caused by sources of unobserved heterogeneity, missing observations on predictor variables, outliers in the data, errors in the specification of the bridging function, and many observed values that are zero. The purpose of this study is to find out the right model and the variables that affect data that occurs overdispersion and excess zero in the case of the number of days of disruption at work, school, or other daily activities due to health complaints. The methods used were Poisson Regression, Negative Binomial Regression, Hurdle Poisson Regression, Zero Inflated Poisson Regression, Zero Inflated Negative Binomial Regression, and Hurdle Negative Binomial Regression. The data used were morbidity taken from data on the number of days of disruption at work, school or other daily activities due to health complaints in Seluma district, Bengkulu Province. It was found that the best model is Zero Inflated Negative Poisson with the smallest Akaike Information Criterion (AIC) value of 1620.609 and the variables that have a significant effect on the log model and the logit model are marital status and work variables.

Estimating separable matching models

SummaryMost recent empirical applications of matching with transferable utility have imposed a natural restriction: that the joint surplus be separable in the sources of unobserved heterogeneity. We propose here two simple methods to estimate models in this class. The first method is a minimum distance estimator that relies on the generalized entropy of matching. The second applies to the more special but popular Choo and Siow model, which reformulates as a generalized linear model with two‐way fixed effects. Neither method requires solving for the stable matching. Both methods are easy to apply and perform very well.

Measuring skin color inequality in women's health in Northeast Brazil: Evidence from the PCSVDFMulher survey.

In this paper, we investigate whether skin color is a source of inequality in women's health by exploring the longitudinal framework of the PCSVDFMulher survey in Northeast Brazil. Specifically, we measure the skin color gradient in women's general and mental health, as well as in showing health risk behavior. We find that darker-skinned women show poorer mental health outcomes and a higher likelihood of drinking and smoking more frequently than their lighter-skinned counterparts. The skin color gradient is persistent and systematic, even when modeling different sources of unobserved heterogeneity and accounting for the existing socioeconomic inequalities and racial identity. We also find that racial identity is an important source of heterogeneous responses of women's health to skin tone.

New needs to consider during accident analysis: Implications of autonomous vehicles with collision reconfiguration systems

Autonomous vehicles are equipped with advanced vehicle technology (AVT) that will improve road traffic safety and reduce accidents. However, due to the uncertain behavior of other road users, collisions can never be completely eliminated. Collision reconfiguration systems offer a solution by, for instance, changing where vehicles are hit and how the impact force is directed towards them. Unfortunately, the logic behind the decision-making of collision reconfiguration systems is fundamentally different from that of other AVTs. Fundamentally different feedback might thus be required from accident analyses to ensure the successful design of collision reconfiguration systems. Through simulations, this study explores decision-making strategies of collision reconfiguration systems to ascertain the implications of which feedback is required from accident analyses. Results show that different strategies can be statistically significantly different from each other in the way they affect severity; and that a new source of unobserved heterogeneity could easily be small variations in the algorithms used by collision reconfiguration systems. Based on this, three new needs to consider during accident analysis are put forth: firstly, new safety surrogate measures (SSMs) that consider severity are required; one such SSM is proposed; secondly, to identify new unobserved heterogeneity as a result of collision reconfiguration systems, the trajectories of traffic near-collisions should be recorded, and statistical tools to identify comparable scenarios developed. Thirdly, new collision patterns will make it difficult to analyze the implications of reconfigured collisions, which suggests that collision configurations must be carefully recorded to provide early feedback.

Quantile Mixed Hidden Markov Models for Multivariate Longitudinal Data: An Application to Children's Strengths and Difficulties Questionnaire Scores

AbstractThe identification of factors associated with mental and behavioural disorders in early childhood is critical both for psychopathology research and the support of primary health care practices. Motivated by the Millennium Cohort Study, in this paper we study the effect of a comprehensive set of covariates on children's emotional and behavioural trajectories in England. To this end, we develop a quantile mixed hidden Markov model for joint estimation of multiple quantiles in a linear regression setting for multivariate longitudinal data. The novelty of the proposed approach is based on the multivariate asymmetric Laplace distribution which allows to jointly estimate the quantiles of the univariate conditional distributions of a multivariate response, accounting for possible correlation between the outcomes. Sources of unobserved heterogeneity and serial dependency due to repeated measures are modelled through the introduction of individual-specific, time-constant random coefficients and time-varying parameters evolving over time with a Markovian structure respectively. The inferential approach is carried out through the construction of a suitable expectation–maximization algorithm without parametric assumptions on the random effects distribution.

Interrelationships Among Fertility, Internal Migration,and Proximity to Nonresident Family:A Multilevel Multiprocess Analysis.

Past research has found that relations to nonresident family can influence individual fertility and migration behaviors separately. However, fertility and migration outcomes may also be interrelated, suggesting potential links across all three demographic processes. With this in mind, we track a cohort of women in Norway from age 18 to 31, recording the emergence of birth and migration events as well as their proximity to nonresident family networks (siblings and parents). Using a multilevel multiprocess statistical framework, with observations nested within women and equations for births, migrations, and proximity to nonresident family estimated simultaneously, our results support the notion that linked lives matter. Even in early adulthood, proximity to nonresident family has a positive effect on transitions to motherhood, whereas the presence of children (itself an outcome of past fertility) is associated with lower propensities to migrate. Mothers also have higher propensities to be living near family than women without children. The presence of local nonresident family reduces propensities for second and third migrations. However, after accounting for unobserved heterogeneity and selection, we observe a small positive effect of proximity to family on first migrations undertaken after age 18. Significant cross-process residual correlations exist across all three outcomes, suggesting that separately estimated model estimates may be vulnerable to bias emerging from unobserved sources of heterogeneity and selection. Our analysis therefore suggests that decisions about fertility, migration, and proximity to family are jointly determined and endogenous, and they should be analyzed simultaneously when possible.

A Correlated Random Parameters Model with Heterogeneity in Means to Account for Unobserved Heterogeneity in Crash Frequency Analysis

Unobserved heterogeneity induced by omitted variables is a major challenge in developing reliable road safety models. In recent years, the random parameters negative binomial (RPNB) model has been used frequently in crash frequency analysis to account for unobserved heterogeneity. However, the majority of past studies of the RPNB model assumed that there was no correlation between different sources of unobserved heterogeneity, which is not always true given the complex interactions of safety factors. Compared with the RPNB model, a more flexible random parameters model that is the correlated random parameters negative binomial with heterogeneity in means (CRPNBHM) model was proposed in this study. Results indicate that the CRPNBHM model could not only capture the otherwise unobserved heterogeneity, but also track the underlying correlation among different sources of unobserved heterogeneity, thus outperforming the RPNB model. In addition, new insights into the interactions of safety factors (e.g., the joint safety effects of heavy trucks and pavement rutting depth) were obtained from the CRPNBHM model and these are expected to be beneficial in developing effective safety countermeasures. Results from this study demonstrated the CRPNBHM model to be a good alternative for crash frequency analysis, particularly when unobserved heterogeneity was detected.

An exploratory investigation of public perceptions towards safety and security from the future use of flying cars in the United States

This study aims at investigating public perceptions towards the safety and security implications that will arise after the future introduction of flying cars in the traffic fleet. In this context, we focus on individuals’ opinions about possible safety benefits and concerns as well as about policy measures that can potentially enhance the security of flying car. Due to the emergent nature and lack of public exposure of this technology, individuals’ perceptions and opinions regarding flying cars might be subject to several layers of unobserved heterogeneity, such as shared unobserved variations across interrelated perceptions, grouped effects, and interactive effects between various sources of unobserved heterogeneity. To explore individuals’ perceptions accounting, at the same time, for such heterogeneity patterns, grouped random parameters bivariate probit and correlated grouped random parameters binary probit models with heterogeneity in means are estimated. In this context, data collected from an online survey of 584 individuals from the United States are statistically analyzed. The estimation results revealed that a number of individual-specific socio-demographic, behavioral and driving attributes affect the perceptions towards the safety aspects of flying cars, along with the attitudes towards potential security interventions. Despite the exploratory nature of the analysis, the findings of this study can provide manufacturers, policy-makers and regulating agencies with valuable information regarding the integration and acceptance challenges that may arise with the introduction of flying cars.

Scale-appropriate mechanization impacts on productivity among smallholders: Evidence from rice systems in the mid-hills of Nepal

Smallholder farmers in the mid-hills of Nepal are facing an acute labor shortage due to out-migration which, in general, has affected the capacity to achieve timely crop establishment, harvest, and inter-cultural operations. These effects are more visible in the case of labor-intensive crops such as rice and promoting higher levels of rural mechanization has emerged as the primary policy response option. Nevertheless, quantitative evidence for the ability of mechanization to offset the adverse effects of shortages increasing labor prices in these systems is largely absent. This study investigates the impacts associated with adoption of mini-tillers (5 to 9 horsepower) for land preparation on smallholder rice productivity in the mid-hills of Nepal. We use an endogenous switching regression that accounts for both observed and unobserved sources of heterogeneity between mini-tiller adopters and non-adopters. Findings demonstrate that rising on-farm rural wage rates and an emerging decline in draft animal availability are driving adoption of the mini-tiller. Among users, the mini-tiller increased rice productivity by 1,110 kg/ha (27%). Further, regression results suggest that mini-tiller non-adopters would be able to increase their rice productivity by 1,250 kg/ha (26%) if they adopt. Moreover, our analysis revealed that very small farms (≤0.25 ha) that adopt mini-tillers are benefited the most in terms of gains in rice productivity. These findings support policies that favor the expansion of small-scale mechanization in the hill production ecologies of South Asia and highlight the need to foster the emergence of an associated service economy that will permit smallholders access to capital-intensive machinery such as the mini-tiller.

Investigating people’s preferences for car-free city centers: A discrete choice experiment

In the face of climate change and growing health hazards due to air pollution in urban centers, private car use is being increasingly criticized. At the same time, research suggests that there is an unsatisfied demand for modes of transportation other than private cars. In fact, many cities all over Europe have already established car-restricted or car-free areas. This paper uses a discrete choice experiment to learn more about people’s preferences regarding a car-free city center in Berlin, Germany. We find that, given the current infrastructure, around 60% of our respondents are willing to accept a car-free city center. By improving infrastructure for cyclists, willingness to accept a car-free city center strongly increases. Similarly, improving the network of bus stops and train stations as well as rededicating released streets to recreational uses would contribute to a higher acceptance of a car-free city center. Using a random parameters logit model, we have also identified observed and unobserved sources of heterogeneity.

Impacts of improved maize varieties in Nigeria: ex-post assessment of productivity and welfare outcomes

Investment in agricultural research and development is an important intervention for improving crop productivity and household welfare in most developing countries where agriculture is the main source of livelihoods. This paper uses nationally representative plot- and household-level data from the major maize producing regions of Nigeria to assess the impacts of adoption of improved maize varieties on maize yield and household welfare outcomes. The paper employed an endogenous switching regression approach to control for both observed and unobserved sources of heterogeneity between adopters and non-adopters. Adoption of improved maize varieties increased maize grain yield by 574 kg/ha and per-capita total expenditure by US$ 77 (US$ 0.21/day). We found that the incidence of poverty among adopters would have been higher by 6% without adoption of the improved varieties. These findings underscore that investments and policy measures to increase and sustain the adoption of improved maize cultivars are critical for improving the productivity of maize in Nigeria and reducing poverty.

Measuring the impacts of adaptation strategies to drought stress: The case of drought tolerant maize varieties

This study measured the impacts of drought tolerant maize varieties (DTMVs) on productivity, welfare, and risk exposure using household and plot-level data from rural Nigeria. The study employed an endogenous switching regression approach to control for both observed and unobserved sources of heterogeneity between adopters and non-adopters. Our results showed that adoption of DTMVs increased maize yields by 13.3% and reduced the level of variance by 53% and downside risk exposure by 81% among adopters. This suggests that adoption had a “win-win” outcome by increasing maize yields and reducing exposure to drought risk. The gains in productivity and risk reduction due to adoption led to a reduction of 12.9% in the incidence of poverty and of 83.8% in the probability of food scarcity among adopters. The paper concluded that adoption of DTMVs was not just a simple coping strategy against drought but also a productivity enhancing and welfare improving strategy. The results point to the need for policies and programs aimed at enhancing adoption as an adaptation strategy to drought stress in Nigeria and beyond.

Identification and estimation of latent group-level-effects in infrastructure performance modeling

As in other panel data analyses, the presence of unobserved heterogeneity is a critical issue in the estimation of infrastructure performance models. In the literature, this issue has been addressed by formulating variable intercept, fixed or random effects models under the assumptions that (1) heterogeneity stems from facility/individual-level effects, and that (2) the coefficients are constant and homogeneous across the population. In contrast, we present mixture regression as a performance modeling framework. The approach relies on the assumption that the underlying population is comprised of a finite set of classes/segments in unknown proportions. The segmentation basis is latent meaning that the criteria to establish the number and type of segments are related to unobserved heterogeneity manifested in facility performance/deterioration. The segments are characterized by a set of commonly specified regression equations, which allows for the identification and estimation of coefficients, i.e., group-level effects, that differ in terms of their level-of-significance, magnitude or sign. We also derive an instance of the Expectation-Maximization Algorithm to estimate the associated parameters, and to assign facilities to the population segments. To illustrate the framework, we analyze the performance of a panel of 131 pavements from the AASHO Road Test. The results suggest both observed and unobserved sources of heterogeneity in the panel. The heterogeneity is captured by differential group-level effects, which we estimate and interpret. We also discuss how these effects can be exploited in the development of resource allocation strategies. We also compare the mixture regression model to established benchmarks.

Do Social Connections Create Trust? An Examination Using New Longitudinal Data

The origins of generalized trust remain unclear despite its importance to social, political, and economic functioning. Social capital theory and previous cross-sectional research suggest that informal social ties may be a source of trust. Using the 2006–2008 General Social Survey panel, we assess the relationship between changes in informal social ties and changes in trust. As the first US longitudinal analysis to address this question, our fixed-effects analysis is not biased by time-invariant factors, such as personality, or other sources of unobserved heterogeneity. We further control for changes in religious attendance, television viewing, family structure, health status, and educational attainment. Our fixed-effects results, as well as results from an auxiliary cross-lagged analysis, yield support for the proposition that informal social ties enhance trust.

The effect of financial incentives on the quality of health care provided by primary care physicians

The use of blended payment schemes in primary care, including the use of financial incentives to directly reward 'performance' and 'quality' is increasing in a number of countries. There are many examples in the US, and the Quality and Outcomes Framework (QoF) for general practitioners (GPs) in the UK is an example of a major system-wide reform. Despite the popularity of these schemes, there is currently little rigorous evidence of their success in improving the quality of primary health care, or of whether such an approach is cost-effective relative to other ways to improve the quality of care. The aim of this review is to examine the effect of changes in the method and level of payment on the quality of care provided by primary care physicians (PCPs) and to identify:i)the different types of financial incentives that have improved quality;ii)the characteristics of patient populations for whom quality of care has been improved by financial incentives; andiii)the characteristics of PCPs who have responded to financial incentives. We searched the Cochrane Effective Practice and Organisation of Care (EPOC) Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL) and Cochrane Database of Systematic Reviews (CDSR) (The Cochrane Library), MEDLINE, HealthSTAR, EMBASE, CINAHL, PsychLIT, and ECONLIT. Searches of Internet-based economics and health economics working paper collections were also conducted. Finally, studies were identified through the reference lists of retrieved articles, websites of key organisations, and from direct contact with key authors in the field. Articles were included if they were published from 2000 to August 2009. Randomised controlled trials (RCT), controlled before and after studies (CBA), and interrupted time series analyses (ITS) evaluating the impact of different financial interventions on the quality ofcare delivered by primary healthcare physicians (PCPs). Quality of care was defined as patient reported outcome measures, clinical behaviours, and intermediate clinical and physiological measures. Two review authors independently extracted data and assessed study quality, in consultation with two other review authors where there was disagreement. For each included study, we reported the estimated effect sizes and confidence intervals. Seven studies were included in this review. Three of the studies evaluated single-threshold target payments, one examined a fixed fee per patient achieving a specified outcome, one study evaluated payments based on the relative ranking of medical groups' performance (tournament-based pay), one study examined a mix of tournament-based pay and threshold payments, and one study evaluated changing from a blended payments scheme to salaried payment.Three cluster RCTs examined smoking cessation; one CBA examined patients' assessment of the quality of care; one CBA examined cervical screening, mammography screening, and HbA1c; one ITS focused on four outcomes in diabetes; and one controlled ITS (a difference-in-difference design) examined cervical screening, mammography screening, HbA1c, childhood immunisation, chlamydia screening, and appropriate asthma medication. Six of the seven studies showed positive but modest effects on quality of care for some primary outcome measures, but not all. One study found no effect on quality of care. Poor study design led to substantial risk of bias in most studies. In particular, none of the studies addressed issues of selection bias as a result of the ability of primary care physicians to select into or out of the incentive scheme or health plan. The use of financial incentives to reward PCPs for improving the quality of primary healthcare services is growing. However, there is insufficient evidence to support or not support the use of financial incentives to improve the quality of primary health care. Implementation should proceed with caution and incentive schemes should be more carefully designed before implementation. In addition to basing incentive design more on theory, there is a large literature discussing experiences with these schemes that can be used to draw out a number of lessons that can be learned and that could be used to influence or modify the design of incentive schemes. More rigorous study designs need to be used to account for the selection of physicians into incentive schemes. The use of instrumental variable techniques should be considered to assist with the identification of treatment effects in the presence of selection bias and other sources of unobserved heterogeneity. In randomised trials, care must be taken in using the correct unit of analysis and more attention should be paid to blinding. Studies should also examine the potential unintended consequences of incentive schemes by having a stronger theoretical basis, including a broader range of outcomes, and conducting more extensive subgroup analysis. Studies should more consistently describe i) the type of payment scheme at baseline or in the control group, ii) how payments to medical groups were used and distributed within the groups, and iii) the size of the new payments as a percentage of total revenue. Further research comparing the relative costs and effects of financial incentives with other behaviour change interventions is also required.

Siblings and human capital: A comparison between Italy and France

Abstract This paper investigates how family size affects children's human capital, comparing Italy and France. We tested the in these countries, starting with the assumption that the higher the number of siblings, the fewer parental resources are available for each child, and the lower the probability that each child will successfully pursue his/her educational career. We find a negative correlation between the number of siblings and human capital. However, when the analysis is developed with a causal approach, the strength of the weakens in Italy and disappears in France. (ProQuest: ... denotes formulae omitted.) 1. Introduction Studies of the determinants of educational attainment, occupation, and income usually consider the family background as a general effect. Meanwhile, fewer researchers have investigated family size as an independent effect. In this article, we focus our attention on a set of fundamental questions regarding social inequalities that may be linked to family background characteristics, especially family size. Based on the theory, our assumption is that the higher the number of siblings, the lower the likelihood is that an individual will attain the highest levels of education (Blake 1980). Does growing up in large families affect people's educational chances? If so, is the negative on educational attainment of belonging to a large family weakened among the more advantaged social classes? Has the negative of large family size on educational attainment changed over the course of the 20th century? Are there any significant differences in the educational opportunities and life chances of first- and lastborns? When families have large numbers of children, there is often a of the resources available to each individual child. This research seeks to investigate whether, as a result of varying national family policies, the dilution effect differs between countries. In our analysis of this issue, we focus on Italy and France, two European countries where family policies and fertility choices are very different, but for which comparable data are available. The main goal of this article is to describe the statistical association between siblings and human capital, after controlling for other variables (year at birth, social class, etc.). We note, however, that some unobserved factors may also influence both family size and children's outcomes. Previous studies (see, for example, Angrist and Evans 1998) have argued that one possible source of unobserved heterogeneity is the preference among parents to have smaller families, with each child being of higher quality. The level of status anxiety for children may drive both the family size and the education of each child (Dalla Zuanna 2007). Hence, the endogeneity issue should be taken into account when evaluating the true causal of family size on education. In the final section of this article, an instrumental variable approach will be applied, using the sibling sex composition as an exogenous determinant of family size variation (Conley and Glauber 2005). This approach - which was mainly chosen because of the specificity of the data source for Italy and France - is not completely satisfactory. Consequently, this part of the research should be viewed as merely a first step towards the formulation of a more exhaustive causal approach. We intend to contribute to the literature published to date by providing the first international comparison in this area of research. It certainly is a challenge to compare two countries, especially when the surveys are not identical. Fortunately, the variables of interest examined in this paper are quite similar for the two countries, enabling us to compare different behaviors, as well as different policies. The paper is organized as follows. The next section briefly summarizes the current state of the debate about these issues in the literature, and outlines the main hypotheses. …

Research on Divorce: Continuing Trends and New Developments

Research on divorce during the past decade has focused on a range of topics, including the predictors of divorce, associations between divorce and the well‐being of children and former spouses, and interventions for divorcing couples. Methodological advances during the past decade include a greater reliance on nationally representative longitudinal samples, genetically informed designs, and statistical models that control for time‐invariant sources of unobserved heterogeneity. Emerging perspectives, such as a focus on the number of family transitions rather than on divorce as a single event, are promising. Nevertheless, gaps remain in the research literature, and the review concludes with suggestions for new studies.

The Impact of the Earned Income Tax Credit on Marriage and Divorce: Evidence from Flow Data

While considerable research focuses on the anti-poverty and labor supply effects of the Earned Income Tax Credit (EITC), relatively little is known about the program’s influence on marriage and divorce decisions. Furthermore, nearly all work in this area uses stock measures of marital status derived from survey data. In this paper, I draw upon Vital Statistics data between 1977 and 2004 to construct a transition-based measure of marriage and divorce rates. Flows into and out of marriage are advantageous because they are more likely to capture the immediate impact of policy changes. Controlling for state-level characteristics and sources of unobserved heterogeneity, I find that increases in the EITC are associated with reductions in new marriages, although the estimated effect is economically small. I find no relationship between the EITC and new divorces. These results are robust to alternative estimation strategies, data restrictions, and the inclusion of additional policy and demographic controls.

Reassessing the Link Between Premarital Cohabitation and Marital Instability

Premarital cohabitation has been found to be positively correlated with the likelihood of marital dissolution in the United States. To reassess this link, I estimate proportional hazard models of marital dissolution for first marriages by using pooled data from the 1988, 1995, and 2002 surveys of the National Survey of Family Growth (NSFG). These results suggest that the positive relationship between premarital cohabitation and marital instability has weakened for more recent birth and marriage cohorts. Using multiple marital outcomes for a person to account for one source of unobserved heterogeneity, panel models suggest that cohabitation is not selective of individuals with higher risk of marital dissolution and may be a stabilizing factor for higher-order marriages. Further research with more recent data is needed to assess whether these results are statistical artifacts caused by data weaknesses in the NSFG.

Reassessing the Link Between Premarital Cohabitation and Marital Instability

It has been found that premarital cohabitation is positively correlated with the likelihood of marital dissolution in the U.S. To reassess this link, I estimate proportional hazard models of marital dissolution for first marriages using pooled data from three surveys of the NSFG 1988, 1995, and 2002 and demonstrate that the positive relationship between premarital cohabitation and marital instability has weakened for more recent birth and marriage cohorts. Using multiple marital outcomes for a person to account for one source of unobserved heterogeneity, panel models suggest that cohabitation is not selective of individuals with higher risk of marital dissolution and may be a stabilizing factor for higher parity marriages.