A cost efficiency analysis of the insurance industry in Mexico

In Mexico, the low participation of insurance activity in national production, in contrast to similar Latin American economies, is a concern. Industry’s regulator promoted more intense competition at the dawn of the century. Was deregulation followed by improvements in the financial and economic performance of Mexican insurance firms? The purpose of this paper is to answer this question through a comprehensive analysis of cost variations in an intertemporal manner, by breaking them down into the economic sources that produce them, including productivity. Cost frontier estimation was grounded in a joint production technology of desirable and undesirable outputs, modeled in an input-oriented fashion. Our results demonstrate that even though some companies achieved cost reductions from technological progress or improvements in efficiency, the Mexican insurance market does not show signs of significant productivity gains.     

Individual Transferable Quota Markets under Illegal Fishing

The use of individual transferable quotas in fisheries has been considered an opportunity to achieve a given total allowable catch with a maximum social benefit. One of the assumptions used in obtaining that result is that the system is in perfect compliance. The presence of violations and the need for enforcement of tradable property rights systems in fisheries has not received much attention in the literature. The incidents of non-compliance, however, may affect the performance of transferable property rights-based fisheries in unexplored ways. In this paper, we adapt previous literature on enforcing emissions trading programs to analyze a positive model of fisherman behavior that operates under a perfectly competitive individual transferable quota system, while recognizing the opportunities for violations of quota holdings, given incomplete enforcement. Considering a poorly enforced, individual transferable quota system we are able to obtain a number of implications for the current and future equilibrium of the quota market, the time paths of the fishery, and the proper design of a policy rule on total allowable catch (TAC).     

An alternative procedure for taking a random sample

Summary The procedure proposed consists in going through the population to be sampled item by item deciding each time with probability p whether the item at hand shall be incorporated in the sample. The "distances" between successive items in the sample will then form a random sample from a geometric distribution. A series of these random distances can easily be produced on a computer and can be conveniently used for taking the sample required. In some cases this method may have its advantages over the conventional use of a table of random numbers.     

Surrogate modelling of a detailed farm-level model using deep learning

Technological change co-determines agri-environmental performance and farm structural transformation. Meaningful impact assessment of related policies can be derived from farm-level models that are rich in technology details and environmental indicators, integrated with agent-based models capturing dynamic farm interaction. However, such integration faces considerable challenges affecting model development, debugging and computational demands in application. Surrogate modelling using deep learning techniques can facilitate such integration for simulations with broad regional coverage. We develop surrogates of the farm model FarmDyn using different architectures of neural networks. Our specifically designed evaluation metrics allow practitioners to assess trade-offs among model fit, inference time and data requirements. All tested neural networks achieve a high fit but differ substantially in inference time. The Multilayer Perceptron shows almost top performance in all criteria but saves strongly on inference time compared to a Bi-directional Long Short Term Memory.     

Does access to improved grain storage technology increase farmers' welfare? Experimental evidence from maize farming in Ethiopia

Seasonal price variability for cereals is two to three times higher in Africa than on the international reference market. Seasonality is even more pronounced when access to appropriate storage and opportunities for price arbitrage are limited. As smallholder farmers typically sell their production after harvest, when prices are low, this leads to lower incomes as well as higher food insecurity during the lean season, when prices are high. One solution to reduce seasonal stress is the use of improved storage technologies. Using data from a randomised controlled trial, in a major maize-growing region of Western Ethiopia, we study the impact of hermetic bags, a technology that protects stored grain against insect pests, so that the grain can be stored longer. Despite considerable price seasonality—maize prices in the lean season are 36% higher than after harvesting—we find no evidence that hermetic bags improve welfare, except that access to these bags allowed for a marginally longer storage period of maize intended for sale by 2 weeks. But this did not translate into measurable welfare gains as we found no changes in any of our welfare outcome indicators. This ‘near-null’ effect is due to the fact that maize storage losses in our study region are relatively lower than previous studies suggested—around 10% of the quantity stored—likely because of the widespread use of an alternative to protect maize during storage, for example a cheap but highly toxic fumigant. These findings are important for policies that seek to promote improved storage technologies in these settings.     

Agriculture and climate change in global scenarios: why don't the models agree

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.     

To Whom,When, and How Much to Discount? A Constrained Optimization of Customized Temporal Discounts

Customized temporal discounts are price cuts or coupons that are tailored by size, timing, and household to maximize profits to a retailer or manufacturer. The authors show how such discounts allow companies to optimize to whom, when, and how much to discount. Such a scheme allows firms to send just enough discounts just prior to the individual's purchase of a rival brand. To do so, the authors model household purchase timing and brand choice in response to discounts and use Bayesian estimation to obtain individual household parameters. They illustrate the model on a Japanese data set having price cuts, a US data set having coupons, and another US data set having discounts. They formulate the optimization task of customized temporal coupons as a constrained multiple-knapsack problem under a given budget. They use simulations of the empirical contexts to obtain optimal solutions and to assess improvement in profits relative to existing practice and alternate models in the literature. The proposed model yields increase in profits of 18–40 percent relative to a standard model that optimizes the value but not timing of discounts.