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Episodes of compulsive eating may lead to addiction. Changing relative prices does not always work for many food addicts turned overweight or obese individuals. This paper points to when such situations may arise and how they can be remedied.

We modify the standard neoclassical economics model assumption of indifference curves being convex to the origin. It becomes violated in situations when compulsive eaters become food addicts. As a result of that, the assumption of the concave (quasi-concave) utility function is violated too. We also introduce the possibility that compulsive eaters may have stable but nonconstant preferences.

Most important finding of our model is that a smooth dynamic path to addiction, caused by habit, disappears. Hence, the ability for smooth adjustment to relative price changes due to policies targeting obesity may not be applicable for a compulsive addict. We postulate the existence of thresholds past in which irreversible harm to addicted overeaters may occur. Reaching such states implies that no economic tools at our disposal could reverse the harm, which, in turn, deem that many policies directed at altering relative prices are ineffective in correcting overeating addiction and its consequences.

Even if we believe in consumer sovereignty, it is possible to shape consumer behavior via policy actions, including the behavior of extremum seekers turned addicts. The public policy of obesity should consider, in this case, its social cost.

No prior research has considered food addiction in light of compulsive eating caused by extremum-seeking behavior. Addiction correcting food policies always relied on either rational or myopic addiction models.

Equilibrium is an important problem in mathematical economics. The paper deals with the problem by establishing pansystems models of equilibrium and introducing ε‐equilibrium solutions. Under the framework of these models, we discuss the existence of equilibrium solution and the ranges where prices, demand and supply commodities vary, respectively.

Like many industrial nations over the last four decades, the Japanese economy has undergone a number of regime shifts, making parameter estimations difficult. One of the most significant shifts occurred in inflation in the mid 1970s as OPEC suddenly raised oil prices. This abrupt change likely caused consumers' expectations of future inflation to deviate significantly from realized (ex‐post) inflation. Using a Markov chain model, inflation forecasts that take into consideration changing regimes are employed to derive a unique set of real stationary variables that are likely to better represent consumers' expectations and are an alternative to the standard approach of adjusting nominal variables with ex‐post inflation. We employ these real variables in the consumption‐based capital asset pricing model (CCAPM). Estimates of the representative investor's coefficient of relative risk aversion (CRRA) are derived within the framework typically used to examine the equity premium puzzle. Our tests confirm that the equity premium puzzle, if it exists in Japan, is not as significant as previously thought.

In-work transfers are often seen as a good trade-off between redistribution and efficiency as they alleviate poverty among low-wage households, while increasing financial incentives to work. In the context of the recent economic downturn, they have been advocated to offset the disincentive effect of wage cuts and to cushion the negative redistributive impact of earnings losses and cuts in the minimum wage. We study this double effect for Ireland, a country deeply affected by the economic crisis, and for which existing in-work support policies are of limited scope. The employment and poverty effects of alternative policies are analysed thanks to counterfactual simulations built using a micro-simulation model, the Living in Ireland Survey 2001 and labour supply estimations. We focus on an extension of the existing scheme, the Family Income Supplement and its replacement by the refundable tax credit in force in the United Kingdom.

The purpose of the paper is to empirically examine the impact of environmental factors and perceived behavioral control (PBC) in addition to the intention on modified littering behavior.

The present study followed a quantitative approach. The empirical data for the present study were drawn from 750 individuals across the states of Delhi and Punjab in India. The predictors of the antecedents of the modified behavior have been examined using confirmatory factor analysis in AMOS 21.0. The hypothesized relationships were tested using structural equation modeling.

The results of the current research found that the modified littering behavior was significantly influenced by intention, PBC and environmental factors. Among these predictor variables, environmental factors have been found influencing the modified littering behavior to the highest extent.

Considering the highest influence of environmental factors, social marketing interventions need to focus on cleaning the already littered areas, convenient placement of trash bins, regular cleanliness, sanitization and emptying of trash bins.

Looking at the uniqueness of the present study in the Indian context, this paper is the first to empirically examine the predictive ability of environmental factors and PBC in addition to the intention that may help close the intention–behavior gap.

Labor supply data seldom include detailed information on hours and wages in secondary job or overtime work. Based on survey information on hours and wages in overtime work and second job which is merged to administrative register information on income taxes and deductions we estimate a “Hausman labor supply model,” which allows for a detailed treatment of nonconvexities. Including explicit information on overtime pay and second job wages increase the estimated elasticities compared to a standard labor supply model without this information. However, allowing a more flexible treatment of nonconvexities the estimated elasticities are reduced; even below the estimates of the baseline results. In simulations we show that these findings have significant consequences when evaluating the degree of self-financing of various tax reforms.

The aim of this paper is to respond to the call for exploring and empirically testing both antecedents and outcomes of brand addiction and compulsive buying behaviour. The focus of the study is on the food habits of young female consumers.

To test the hypotheses, a survey design gathering cross-sectional primary data from 325 female Italian consumers and a structural equation modelling have been adopted.

Findings show that brand addiction is positively influenced by consumer resilience, leading to increased life happiness and self-esteem, while compulsive buying behaviour is negatively influenced by consumer resilience and positively influenced by impulsivity. Compulsive buying is also associated with brand addiction and emotional overeating. Emotional overeating is additionally influenced by impulsivity and the control variables of enjoyment of food and loneliness. Moreover, loneliness has a negative impact on life happiness and self-esteem.

The study applies the proposed theory by Mrad and Cui (2020) on the relationship between brand addiction and compulsive buying to food consumption. Furthermore, it expands on this research by investigating consumer characteristics as determinants and behavioural outcomes.

By using higher moments, this paper extends the quadratic local risk-minimizing approach in a general discrete incomplete financial market. The local optimization subproblems are convex or nonconvex, depending on the moment variants used in the modeling. Inspired by Lai et al. (2006), the authors propose a new multiobjective approach for the combination of moments that is transformed into a multigoal programming problem.

The authors evaluate financial derivatives with American features using local risk-minimizing strategies. The financial structure is in line with Schweizer (1988): the market is discrete, self-financing is not guaranteed, but deviations are controlled and reduced by minimizing the second moment. As for the quadratic approach, the algorithm proceeds backwardly.

In the context of evaluating American option, a transposition of this multigoal programming leads not only to nonconvex optimization subproblems but also to the undesirable fact that local zero deviations from self-financing are penalized. The analysis shows that issuers should consider some higher moments when evaluating contingent claims because they help reshape the distribution of global cumulative deviations from self-financing.

A detailed numerical analysis that compares all the moments or some combinations of them is performed.

The quadratic approach is extended by exploring other higher moments, positive combinations of moments and variants to enforce asymmetry. This study also investigates the impact of two types of exercise decisions and multiple assets.

In the paper we design a super genetic hybrid algorithm (SuperGHA), an integrated optimization system for simultaneous parametric search and nonlinear optimization. The parametric search machine is implemented as a genetic superstructure, producing tentative parameter vectors that control the ultimate optimization process. The family of parameter vectors evolves through ordinary genetic operators aimed at producing the best possible parameterization for the underlying optimization problem. In comparison to traditional genetic algorithms, the integrated superstructure involves a twofold ordering of the population of parameter vectors. The first sorting key is provided by the objective function of the optimization problem at issue. The second key is given by the total mesh time absorbed by the parametric setting. In consequence, SuperGHA is geared at solving an optimization problem, using the best feasible parameterization in terms of optimality and time absorbance. The algorithm combines features from classical nonlinear optimization methodology and evolutionary computation utilizing a powerful accelerator technique. The constrained problem can be cast into multiple representations, supporting the integration of different mathematical programming environments. We show by extensive Monte Carlo simulations that SuperGHA extracts suitable parameter vectors for fast solution of complicated nonlinear programming problems.