Corner Solutions Research Articles

Think twice before attacking: Effort, restraint, and sanctions in war conflicts

There are contrasting empirical findings about how third parties mitigate conflict and few theoretical results about war efforts and restraint. Applying a new approach that distinguishes between quantity and effectiveness of effort, we explain countries’ restraint incentives. In our setting, restraint is manifested in reducing the effectiveness of military efforts when third parties impose costs (sanctions) on unrestrained behavior. We show that intermediate sanctions may lead to a mixed-strategy equilibrium or pure strategy equilibria in which only one country reduces its effectiveness. We present the conditions that yield pure-strategy (in which, surprisingly, restraint is a corner solution) and mixed-strategy (MS) equilibria in our multi-stage model. Interestingly, a country's effort decreases with its or its rival's self-restraint, allowing a third party to reduce efforts by sanctioning only one country. Our analysis enriches the classical results, particularly those obtained in the context of war conflicts, which focus on the extent of effort expended and on means of mitigating the conflict. The theoretical study lays the groundwork for future research into war contests and suggests various avenues for further exploration.

Improving decomposition-based MOEAs for combinatorial optimisation by intensifying corner weights

In the real world, a class of common problems such as supply chain management, project scheduling, portfolio optimisation and facility location design are multi-objective combinatorial optimisation problems (MOCOPs), where there are multiple objectives and the set of feasible solutions is discrete. In MOCOPs, corner solutions are solutions in which at least one objective reaches the optimal value. Corner solutions are important as they are likely to be preferred by the decision maker and are able to help improve algorithm performance. In this paper, we first reveal that in decomposition-based MOEAs, improving the corner weights (as opposed to improving the middle weights) significantly enhances the generation of corner solutions, thereby enhancing the overall performance of algorithms. Based on this, we propose a method to enhance the search for corner solutions in MOCOPs. We act on a class of popular MOEAs, decomposition-based MOEAs, and in their evolutionary mechanism we intensify the weights in the corner areas. To verify the proposed method, we conduct experiments by incorporating the method into three decomposition-based MOEAs, MOEA/D, MOEA/D-DRA-UT and MOEA/D-LdEA (the latter two were designed specifically for enhancing the search of corner solutions). The experimental results demonstrate that the proposed method can improve the spread of solution sets found, without compromising the quality of internal solutions.

The extended Grossman human capital model with endogenous demand for knowledge

This paper extends the Grossman human capital model by including endogenous demand for knowledge capital. Human capital investment behavior is modeled from the start of a person's life rather than only after she has acquired the optimal stock of knowledge capital or reached the mandatory schooling age. The general condition for the optimal knowledge capital stock and the optimal health capital stock is derived, and the conditions for an individual's choices of interior and corner solutions for learning time that increases knowledge capital stock are presented. The extended Grossman human capital model provides a theoretical basis for explaining and predicting the effects of economic conditions on educational attainment from a distinctive perspective based on the joint determination of health capital and knowledge capital.

R&D financing and production: A new Ricardian specific factor model

AbstractThis paper contributes to the literature on finance, production, and Research and Development (R&D) by investigating the unique possibilities of polarized decisions of entrepreneurs to yield “extreme” points rather than an “interior solution.” Financiers provide credits for employing sector‐specific skilled and unskilled workers as well as for R&D. With the objective of maximizing returns, financiers' interest lies in financing R&D only in the skilled sector while the unskilled sector—without innovation—collapses. Such corner solution occurs due to much higher skilled‐augmenting technical change guaranteeing maximum prospective return than that in the unskilled. This offers a novel interpretation of a declining share of production workers.

Estimating demand systems with corner solutions: the performance of Tobit-based approaches

ABSTRACT Since the introduction of the Tobit framework to perform estimation involving censored dependent variables, practitioners have been facing a clear trade-off between flexibility and theoretical plausibility in modelling consumers’ preferences in the presence of zero consumptions; the Kuhn-Tucker (or virtual price) approach is rigorously based on the economic choice theory but cannot be applied to complex and flexible demand systems, whereas the Tobit-based approach can be applied to any class of demand systems but is deficient in the theoretical foundations on the underlying preferences behind the observed choices. Hence, we assess the performance of three Tobit-based approaches (simple, correlated, and Amemiya-Tobin) and explore the extent of possible biases in elasticity estimates to provide reasonable criteria for model selection. Our analysis concludes that theoretical restrictions implied by the choice theory are essential to the Tobit model and improve its ability to capture the true underlying elasticities and mitigate overrejections. However, the performance of the Tobit models gradually deteriorates as the number of zero consumptions increases; the average rejection rate against the true elasticity values increases substantially as we have more zero consumptions. We illustrate the performance differences among the three Tobit models by applying them to the estimation of demand for fruits and vegetables.

Discrete-continuous models of residential energy demand: A comprehensive review

This paper reviews forty years of research applying econometric models of discrete-continuous choice to analyze residential demand for energy. The review is primarily from the perspective of economic theory. We examine how well the utility-theoretic models developed in the literature match data that is commonly available on residential energy use, and we highlight the modeling challenges that have arisen through efforts to match theory with data. The literature contains two different formalizations of a corner solution. The first, by Dubin and McFadden (1984) and Hanemann (1984), models an extreme corner solution, in which only one of the discrete choice alternatives is chosen. While those papers share similarities, they also have some differences which have not been noticed or exposited in the literature. Subsequently, a formulation first implemented by Wales and Woodland (1983) and extended by Kim et al. (2002) and Bhat (2008) models a general corner solution, where several but not all of the discrete choice alternatives are chosen. Seventeen papers have employed one or another of these models to analyze residential demand for fuels and/or energy end uses in a variety of countries. We review issues that arose in these applications and identify some alternative model formulations that can be used in future work on residential energy demand.

Correcting for Endogeneity in Models with Bunching

We develop a novel control function approach in models where the treatment variable has bunching at one corner of its support. This situation typically arises when the treatment variable is a constrained choice and some observations choose the corner solution. The method exploits distributional shape restrictions but makes no exclusion restrictions. We provide estimators and establish their asymptotic behavior, prove the convergence of the bootstrap, and develop tests of the identification assumptions. An application reveals that watching television has no effect on cognitive skills and a negative effect on noncognitive skills in children.

Is there a liability of foreignness or foreign privilege in developing nation compliance monitoring?

PurposeDrawing on the international business and game theory literature, this study assesses foreign firm treatment in the early stages of regulatory enforcement.Design/methodology/approachTreating regulation intensity as an exposure variable, negative binomial regression models were applied to firm-level data from 32 emerging markets (n = 15,331) to identify the determinants of inspection interactions. Robustness checks also were performed via variable substitutions for several predictors and an alternative form of statistical testing (i.e. Tobit regression, since it arguably better addresses dependent variables with corner solution responses).FindingsControlling for multiple organizational, regulatory and national characteristics, the findings are consistent with a foreign privilege, manifesting in reduced vulnerability to multiple encounters with labor inspection officials. Moreover, inward FDI stock was negatively related to the general probability of repeat interactions regardless of locus of ownership, an effect that was not moderated by stage of development or the regulatory influence of host interest groups. This collectively suggests that foreign firms not only are favored in compliance monitoring but also work post-entry to influence agencies to generally benefit business.Research limitations/implicationsMore comprehensive assessments were precluded given the lack of information on reasons for contact, citations and fines, and inspectorate reactions to company responses. Second, enforcement-risk management was measured indirectly since investors' internal dealings and actions toward officials are unavailable in secondary sources.Practical implicationsThese findings have important implications for social responsibility, suggesting CSR stakeholders need to track enforcement more closely and exert pressure where needed so rights are not sacrificed for economic development.Originality/valueThis study provides the most rigorous assessment to date of the role that firm, government and economic factors play in national inspection targeting. It also examined whether foreign owners pool and leverage their political influence to impact general inspection activity, a previously untested prospect.

Handling constrained many-objective optimization problems via determinantal point processes

Although various research studies have been performed to solve constrained multi-objective optimization and many-objective optimization problems, more attention should be paid to the widely existing constrained many-objective optimization problems (CMaOPs). Balancing convergence, diversity and feasibility is an essential issue for CMaOPs. To this end, traditional methods tend to adopt one-by-one selection or deletion strategies. However, these strategies rarely consider the quality of the entirety. Consequently, some poorly performed yet promising solutions might be discarded, finally degrading the performance. To overcome this drawback, this article first introduces the determinantal point processes (DPPs) in Machine Learning to handle CMaOPs. A new algorithm is proposed by applying the DPPs rather than traditional selection strategies for selecting population and archive. To effectively utilize DPPs, two novel Kernel Matrices are designed to represent convergence, diversity, and feasibility qualities of solutions in population and archive, respectively. Besides, a new ε-constrained technique is tailored for the update strategies of archive and corner solution set to handle CMaOPs, especially those with complex constraints. Experiments on 16 different CMaOPs of 77 instances with up to 15 objectives demonstrated the superiority of the proposed method to the state-of-the-art algorithms.

The predictive power of risk elicitation tasks

This work reports the results of two online experiments with a general-population sample examining the performance of different tasks for the elicitation of risk attitudes. First, I compare the investment task of Gneezy and Potters (1997), the standard choice-list method of Holt and Laury (2002), and the multi-alternative procedure of Eckel and Grossman (2002) and evaluate their performance in terms of the number of correctly-predicted binary decisions in a set of out-of-sample lottery choices. There are limited differences between the tasks in this sense, and performance is modest. Second, I included three additional budget-choice tasks (selection of a lottery from a linear budget set) where optimal decisions should have been corner solutions, and find that a large majority of participants provided interior solutions instead, casting doubts on people’s understanding of tasks of this type. Finally, I investigate whether these two results depend on cognitive ability, numerical literacy, and education. While optimal choices in budget-choice tasks are related to numerical literacy and cognitive ability, the predictive performance of the risk-elicitation tasks is unaffected.

Методика отбора регионов для исследования адаптации сельского хозяйства к изменению климата

The impact of climate change on the social and institutional conditions of agriculture (as opposed to technological ones) in Russia has hardly been studied. With a limited budget, such research should examine a small sample of regions. To reduce the subjectivity, a formalised methodology for creating and ranking small samples of regions was developed. While occupying the largest possible share in the country’s gross agricultural production, the regions included in the sample should significantly differ in natural and agricultural zones, agricultural production efficiency, contribution of peasant farms to agricultural output. Unlike other methods, the proposed technique uses a linear programming problem, where all corner solutions are integer. Data envelopment analysis (DEA) was utilised to ensure the inclusion of both efficient and inefficient regions in the sample. In accordance with these requirements, Altai, Krasnoyarsk, Krasnodar krais and Moscow oblast were selected for analysis. For the regions included in at least one of the five best samples (such as Volgograd, Saratov and Leningrad oblasts), a model of partial equilibrium on the wholesale markets of agricultural products of the constituent entities of the Russian Federation (VIAPI model) was applied to assess the impact of scenario climate change on the output and wholesale prices of ten types of agricultural products. The research revealed that while the production in the selected regions is resistant to this influence, except for Altai and Krasnoyarsk krais, regional market prices are still rising due to the impact of world prices for milk products and grain.

Оптимальное распределение материальных и нематериальных благ: вмененные цены семейных и религиозных обязанностей

This study develops the economic approach to human relations and applicates the results of the equilibrium analysis on commodity and in marriage markets to the tangibles-intangibles trade-off. The paper examines the optimization between gifts and parental concern in large families, where children attractiveness is different. The model of parental concern confirms optimal equilibrium proportions on commodity and in marriage markets, derived from the golden ratio. The measurement of intangibles is based on the opportunity costs of tangibles to be given up. Shakespeare gives a literal illustration for the general gifts-concern equilibrium, when the corner solution of Cordelia to give up the heritage is equilibrated by the opposite corner solution of both Goneril and Regan to deprive King Lear of shelter. But the empirical confirmation of optimal proportions of general equilibrium can be got from primary source of tangibles-intangibles trade-off, the Old Testament, where one fifth of income on donations and five-times payback for the stolen ox had been prescribed. The model presented here derives these proportions from the golden ratio. It also describes the demonstrative tangibles-intangibles trade-off; golden ratio follows the continuity between Testaments and exhibits at the equilibrium the negative attractiveness of Pharisees, produced by their demonstrative righteousness.

Black-Litterman model with copula-based views in mean-CVaR portfolio optimization framework with weight constraints

This study examines the portfolio optimization problem by exploiting daily data of 10 international Exchange Trade Funds (ETF) from 2012 to 2022. We extend the Black-Litterman (BL) approach using ARMA-GARCH-copula-based expected returns as a proxy for investor views and use the CVaR metric as a risk measure in the optimization procedure. The BL approach provides a Bayesian methodology for combining the equilibrium returns and the investor views to produce expected returns. We use Regular Vine (R-vine) copula since it provides a flexible multivariate dependency modeling. The suggested approach is compared against the copula-CVaR portfolio, which likewise a BL copula approach avoids excessive corner solutions that many optimization approaches would generate in case of extreme values of estimated parameters. We compare the performance of these two approaches using out-of-sample back-testing against two benchmarks: Mean–Variance optimizations (MV) and equal weights portfolio (EW). To further reduce the sensitivity of considered strategies to input parameters, we evaluate out-of-sample performance at three levels of maximum weight constraints: 30%, 40%, and 50%. Moreover, in this paper, we consider different levels of view confidence—τ in the Black-Litterman model as it significantly affects the obtained results and inferences. We calculate and report the portfolios’ tail risks, maximum drawdown, turnover, and the break-even point for all optimization approaches. Our empirical analysis indicates better performance for the CBL portfolio regarding lower tail risk and higher risk-adjusted returns, and the copula-CVaR portfolio is better regarding lower turnover and higher break-even point.

A many-objective evolutionary algorithm based on corner solution and cosine distance

A many-objective evolutionary algorithm based on corner solution and cosine distance

The impacts of climate change on cropland allocation, crop production, output prices and social welfare in Israel: A structural econometric framework

We propose a model that simulates climate change impacts on crop production and food prices under partial equilibrium. Our model incorporates a system of Laspeyres price and quantity indices that link structurally estimated community-level produce supply functions to market level demand functions. The supply estimation accounts for corner solutions associated with disaggregate land use observations and is constrained to reproduce aggregate supply data. We use the model to assess climate change impacts in Israel, which protects local agriculture by import tariffs and quotas. The simulation results vary greatly when we allow prices to change as a response to supply changes, highlighting the importance of endogenizing prices in climate change simulations. The results imply that climate changes projected for Israel are expected to be beneficial to farmers, particularly due to the positive impact of the forecasted large temperature rise on field crop production. Fruit outputs are projected to decline, and reduce consumer surplus, but to a lower extent than the increase in total agricultural profits. Nearly 20% of the profit rise is attributed to farmers’ adaptation through land reallocation. Adaptation to the projected reduction in precipitation by increasing irrigation is found to be warranted from the farmers’ perspective; however, it is not beneficial to society as a whole. Abolishing import tariffs effectively transfers surpluses from producers to consumers, but the impact of this policy on social welfare is relatively modest.

Cooperative Multiobjective Evolutionary Algorithm With Propulsive Population for Constrained Multiobjective Optimization

Convergence, diversity and feasibility are three important issues when solving constrained multiobjective optimization problems (CMOPs). To deal with the balance among convergence, diversity and feasibility well, this article proposes a cooperative multiobjective evolutionary algorithm with propulsive population (CMOEA-PP) for solving CMOPs. CMOEA-PP has two populations, including propulsive population and normal population, and these two populations work cooperatively. Specifically, propulsive population focuses on convergence. Normal population gives priority to feasibility and is obligated to maintain diversity. To cross through the infeasible region and reach the Pareto front (PF), propulsive population does not consider constraints in the early stage and only considers constraints in the later stage. To further accelerate the speed of convergence, propulsive population only searches for corner solutions and center solutions, while normal population searches for the whole PF. As a result, propulsive population can cross through the infeasible region because of the lack of attention to feasibility. In addition, propulsive population also can guide and accelerate the convergence of the evolutionary process. Comprehensive experiment results on several sets of benchmark problems demonstrate that CMOEA-PP is better than existing state-of-the-art competitors.

A Bayesian zero-one inflated beta modeling of dairy farmers’ decision to sell nothing or some output through contract farming

AbstractSmallholder farmers’ preferences for participation in contract farming may take the form of proportional data––whereby farmers only sell some proportions or fractions of their output to contractors. We analyze determinants for preferences for zero (potential corner solution) and proportional amounts of milk that farmers sell through contract farming, using dairy farmers’ data from Zambia. Bayesian linear, linear probability, and hurdle models are compared with a Bayesian zero-one inflated beta regression. Monte Carlo simulations show that alternative models are biased. Meanwhile, empirical findings suggest that gender and marital status of the household head, household size, and delayed payment significantly drive preferences for proportional milk sales in contract farming. Additionally, household size, experience selling through milk collection centers, total livestock units, access to dairy marketing information, and a buyer's milk price, among others, tend to affect zero-inflated outcomes. We recommend a Bayesian zero-one inflated beta regression model for proportional data and also provide strategies to overcome farmer-engagement barriers in contract farming.

Conjunctive screening in models of multiple discreteness

Consumer demand for products often result in the purchase of multiple goods at the same time. Corner solutions, or the non-purchase of items, occur when consumers have strong preference for some goods that do not satiate and weak preference for other goods. However, if non-purchase arises because a consumer finds particular brands and attributes unacceptable, leading to the formation of consideration sets, then estimates of preference will be too extreme and biased. In this paper, we extend the work on consideration sets and discrete choices to a wider class of models, and develop a model of multiple discreteness with conjunctive screening of the alternatives that remove offerings from consideration. We propose a method for consideration set formation that does not require one to specify a partitioned space of the augmented variable, and that can be adapted into the class of choice models in which an outcome variable is removed. We explore implications for disentangling non-purchase due to consideration set formation using two data sets of ice cream and frozen pizza purchases. The ice cream data, in which responses are both discrete and volumetric, allow us to compare differences in how screening affect purchase incidence versus volumetric demand per incidence. Screening reduces the estimated number of customers with positive demand but leads to an increase in demand for those not screened. In the frozen pizza data, we find that conjunctive screening accounts for many of the observed corner solutions and leads to estimates of preference and satiation that differs from traditional models of multiple-discreteness without screening.

Determinants of Smallholder Farmer Labor Allocation Decisions in Uganda

ABSTRACT This study provides evidence on factors that influence household labor allocation decisions and demand for farm labor in Uganda. We estimated a monthly panel data to deal with potential heterogeneity or individual effect and tested for violation of the random effects modeling assumption that the explanatory variables are orthogonal to the unit effects. In addition, we estimated a random effects tobit model that involve explained variables with corner solutions. The results show that exogenous income did not affect off-farm labor supply by liquidity constrained households while liquidity unconstrained households increased the amount of labor supplied to off-farm activities and the amount of labor hired in. Farm size and education of household head improved labor productivity on farm and hence the amount of labor hired. Road proximity improved both the hiring in and out of labor. The household being male headed improved the work hours in the nonagricultural off-farm activities. The findings imply that direct payments such as input provision to the poor may not improve labor employment unless backed with policies that remove bottlenecks and improve opportunities in the labor market. Instead, investment in micro credit institutions, road infrastructure, and education suited to smallholder production needs and policies that improve gender balance in terms of access to productive resources could help alleviate bottlenecks in labor markets and improve resource allocation between farm and off-farm sectors.

Unintended Consequences of Environmental Policies: the Case of Set-aside and Agricultural Intensification

The objective of this paper is to evaluate the indirect impacts of a set-aside policy on the environment through crop intensification. We estimate a structural, multi-output model on a panel of French farmers from 2006 to 2010, accounting for multivariate selection (corner solutions) on crops and land use. We use a parametric and a semi-nonparametric (based on sieve estimation) version of a quasi-maximum likelihood (QML) estimator, compare their goodness of fit and parameter efficiency and check for closeness with a test for non-nested models. We then perform a simulation experiment based on elasticity estimates for set-aside area and input demand, to evaluate intensive margin effects of the set-aside policy. Results show that a set-aside subsidy can provide farmers with incentives to intensify their production, leading to potential adverse environmental effects.