The Within-household Schooling Decision: A Study of Children in Rural Andhra Pradesh

Using microdata from a field survey of children in rural Andhra Pradesh, India, we estimate econometric models which aim to identify the key explanatory factors in the school versus out-of-school dichotomy. The approach differs from that of many other previous studies of child schooling, by focusing on the effects of sibling competition within the household. The value of this approach is confirmed by our findings that the schooling decision depends as much on the child's characteristics and position within the household, as on the circumstances of the household taken as a unit.

The econometric modeling of social Preferences

Experimental data on social preferences present a number of features that need to be incorporated in econometric modelling. We explore a variety of econometric modelling approaches to the analysis of such data. The approaches under consideration are: the random utility approach (in which it is assumed that each possible action yields a utility with a deterministic and a stochastic component, and that the individual selects the action yielding the highest utility); the random behavioural approach (which assumes that the individual computes the maximum of a deterministic utility function, and that computational error causes their observed behaviour to depart stochastically from this optimum); and the random preference approach (in which all variation in behaviour is attributed to stochastic variation in the parameters of the deterministic component of utility). These approaches are applied in various ways to an experiment on fairness conducted by Cappelen et al. (2007). At least two of the models that we estimate succeed in capturing the key features of the data set.Econometric modelling and estimation, model evaluation, individual behaviour, fairness

Overbidding and Heterogeneous Behavior in Contest Experiments: A Comment on the Endowment Effect

We revisit the meta-analysis of Sheremeta (2013) on overbidding in contest experiments and focus on the effect of endowment on overbidding. Whereas Sheremeta (2013) assumes, and finds evidence of, an increasing linear relationship between endowment and overbidding in his meta-analysis, Quantal Response Equilibrium (QRE) predicts an increasing concave relationship, and Baik et al. (2016) find an inverted-U shaped relationship in their analysis of a single experiment. We use the same data as in Sheremeta (2013), but employ a different econometric model which leads to support for both QRE and the inverted-U shaped relationship. Following Baik et al. (2016) we posit that the inverted-U relationship may be interpreted in terms of a wealth effect

Experimetrics: A Survey

This monograph aims to survey a range of econometric techniques that are currently being used by experimental economists. It is likely to be of interest both to experimental economists who are keen to expand their skill sets, and also the wider econometrics community who may be interested to learn the sort of econometric techniques that are currently being used by Experimentalists. Techniques covered range from the simple to the fairly advanced. The monograph starts with an overview of treatment testing. A range of treatment tests will be illustrated using the example of a dictator-game giving experiment in which there is a communication treatment. Standard parametric and non-parametric treatment tests, tests comparing entire distributions, and bootstrap tests will all be covered. It will then be demonstrated that treatment tests can be performed in a regression framework, and the important concept of clustering will be explained. The multilevel modelling framework will also be covered, as a means of dealing with more than one level of clustering. Power analysis will be covered from both theoretical and practical perspectives, as a means of determining the sample size required to attain a given power, and also as a means of computing ex-post power for a reported test. We then progress to a discussion of different data types arising in Experimental Economics (binary, ordinal, interval, etc.), and how to deal with them. We then consider the estimation of fully structural models, with particular attention paid to the estimation of social preference parameters from dictator game data, and risky choice models with between-subject heterogeneity in risk aversion. The method maximum simulated likelihood (MSL) is promoted as the most suitable method for estimating models with continuous heterogeneity. We then consider finite mixture models as a way of capturing discrete heterogeneity; that is, when the population of subjects divides into a small number of distinct types. The application used as an example will be the level-k model, in which subject types are defined by their levels of reasoning. We then consider other models of behaviour in games, including the Quantal Response Equilibrium (QRE) Model. The final area covered is models of learning in games

A Test of the Rational Expectations Hypothesis using data from a Natural Experiment

Data on contestants' choices in Italian Game Show Affari Tuoi are analysed in a way that separates the effect of risk attitude (preferences) from that of beliefs concerning the amount of money that will be offered to contestants in future rounds. The most important issue addressed in the paper is what belief function is actually being used by contestants. The parameters of this function are estimated freely along with the parameters of a choice model. Separate identification of the belief function and preferences is possible by virtue of the fact that at a certain stage of the game, beliefs are not relevant, and risk attitude is the sole determinant of choice. The rational expectations hypothesis is tested by comparing the estimated belief function with the "true" offer function which is estimated using data on offers actually made to contestants. We find that there is a significant difference between these two functions, and hence we reject the rational expectations hypothesis. However, when a simpler "rule-of-thumb" structure is as- sumed for the belief function, we find a correspondence to the function obtained from data on actual offers. Our overall conclusion is that contestants are rational to the extent that they make use of all available relevant information, but are not fully rational because they are not processing the information in an optimal way. The importance of belief-formation is confirmed by the estimation of a mixture model which establishes that the vast majority of contestants are forward-looking as opposed to myopic.Beliefs, Discrete choice models, Method of simulated likelihood, Natural Experiments, rational expectations, risky choice

A Kuhn–Tucker model for behaviour in dictator games

We consider a dictator game experiment in which dictators perform a sequence of giving tasks and taking tasks. The data is used to estimate the parameters of a Stone-Geary utility function over own-payoff and other’s payoff. The econometric model incorporates zero observations (e.g. zero-giving or zero-taking) by applying the Kuhn-Tucker theorem and treating zeros as corner solutions in the dictator’s constrained optimisation problem. The method of maximum simulated likelihood (MSL) is used for estimation. We find that selfishness is significantly lower in taking tasks than in giving tasks, and we attribute this difference to the “cold prickle of taking”

Leading to Efficient Coordination: Individual Traits, Beliefs and Choices in the Minimum Effort Game

We consider data from an experiment on the minimum-effort game, repeated over many periods. In each play of the game, each player's belief about the minimum-effort of other players in the group is elicited, in addition to the player's chosen effort level. We find that many agents choose effort levels systematically exceeding their beliefs of others' effort levels. We explain this in terms of such subjects taking the role of ``leader'' in an attempt to pull the group towards more efficient outcomes. We find that the propensity for leaders to emerge depends on design features such as conditions relating to the cost of effort, and the amount of information available to players, and also on individual traits such as trustfulness and cognitive ability. The between-subject heterogeneity that we uncover necessarily leads to between-group heterogeneity, and we use this to explain why some groups appear more inclined than others to shift to the superior equilibrium

Heterogeneity in Preferences towards Complexity

We analyze lottery-choice data in a way that separately estimates the effects of risk aversion and complexity aversion. Complexity is represented by the number of different outcomes in the lottery. A finite mixture random effects model is estimated which assumes that a proportion of the population are complexity-neutral. We find that around 33% of the population are complexity-neutral, around 50% complexity-averse, and the remaining 17% are complexity-loving. Subjects who do react to complexity appear to have a bias towards complexity aversion at the start of the experiment, but complexity aversion reduces with experience, to the extent that the average subject is (almost) complexity-neutral by the end of the experiment. Complexity aversion is found to increase with age and to be higher for non-UK students than for UK students. We also find some evidence that, when evaluating complex lotteries, subjects perceive probabilities in accordance with Prospective Reference Theory

Impact of a (poly)phenol-rich extract from the brown algae Ascophyllum nodosum on DNA damage and antioxidant activity in an overweight or obese population: a randomized controlled trial

Background Epidemiologic evidence suggests that a diet rich in (poly)phenols has beneficial effects on many chronic diseases. Brown seaweed is a rich source of (poly)phenols. Objective The aim of this study was to investigate the bioavailability and effect of a brown seaweed (Ascophyllum nodosum) (poly)phenol extract on DNA damage, oxidative stress, and inflammation in vivo. Design A randomized, double-blind, placebo-controlled crossover trial was conducted in 80 participants aged 30–65 y with a body mass index (in kg/m2) ≥25. The participants consumed either a 400-mg capsule containing 100 mg seaweed (poly)phenol and 300 mg maltodextrin or a 400-mg maltodextrin placebo control capsule daily for an 8-wk period. Bioactivity was assessed with a panel of blood-based markers including lymphocyte DNA damage, plasma oxidant capacity, C-reactive protein (CRP), and inflammatory cytokines. To explore the bioavailability of seaweed phenolics, an untargeted metabolomics analysis of urine and plasma samples after seaweed consumption was determined by ultra-high-performance liquid chromatography–high-resolution mass spectrometry. Results Consumption of the seaweed (poly)phenols resulted in a modest decrease in DNA damage but only in a subset of the total population who were obese. There were no significant changes in CRP, antioxidant status, or inflammatory cytokines. We identified phlorotannin metabolites that are considered potential biomarkers of seaweed consumption including pyrogallol/phloroglucinol-sulfate, hydroxytrifurahol A-glucuronide, dioxinodehydroeckol-glucuronide, diphlorethol sulfates, C-O-C dimer of phloroglucinol sulfate, and C-O-C dimer of phloroglucinol. Conclusions To the best of our knowledge, this work represents the first comprehensive study investigating the bioactivity and bioavailability of seaweed (poly)phenolics in human participants. We identified several potential biomarkers of seaweed consumption. Intriguingly, the modest improvements in DNA damage were observed only in the obese subset of the total population. The subgroup analysis should be considered exploratory because it was not preplanned; therefore, it was not powered adequately. Elucidation of the biology underpinning this observation will require participant stratification according to weight in future studies. This trial was registered at clinicaltrials.gov as NCT02295878

Genome-wide protein QTL mapping identifies human plasma kallikrein as a post-translational regulator of serum uPAR levels

The soluble cleaved urokinase plasminogen activator receptor (scuPAR) is a circulating protein detected in multiple diseases, including various cancers, cardiovascular disease, and kidney disease, where elevated levels of scuPAR have been associated with worsening prognosis and increased disease aggressiveness. We aimed to identify novel genetic and biomolecular mechanisms regulating scuPAR levels. Elevated serum scuPAR levels were identified in asthma (n=514) and chronic obstructive pulmonary disease (COPD; n=219) cohorts when compared to controls (n=96). In these cohorts, a genome-wide association study of serum scuPAR levels identified a human plasma kallikrein gene (KLKB1) promoter polymorphism (rs4253238) associated with serum scuPAR levels in a control/asthma population (P=1.17×10−7), which was also observed in a COPD population (combined P=5.04×10−12). Using a fluorescent assay, we demonstrated that serum KLKB1 enzymatic activity was driven by rs4253238 and is inverse to scuPAR levels. Biochemical analysis identified that KLKB1 cleaves scuPAR and negates scuPAR's effects on primary human bronchial epithelial cells (HBECs) in vitro. Chymotrypsin was used as a proproteolytic control, while basal HBECs were used as a control to define scuPAR-driven effects. In summary, we reveal a novel post-translational regulatory mechanism for scuPAR using a hypothesis-free approach with implications for multiple human diseases