Advertising for attention in a consumer search model

We model the idea that when consumers search for products, they first visit the firm whose advertising is more salient. The gains a firm derives from being visited early increase in search costs, so equilibrium advertising increases as search costs rise. This may result in lower firm profits when search costs increase. We extend the basic model by allowing for firm heterogeneity in advertising costs. Firms whose advertising is more salient and therefore raise attention more easily charge lower prices in equilibrium and obtain higher profits. As advertising cost asymmetries increase, aggregate profits increase, advertising falls and welfare increases.Advertising; attention; consumer search; saliency;

Strategic Wage Setting and Coordination Frictions with Multiple Applications

We examine wage competition in a model where identical workers choose the number of jobs to apply for and identical firms simultaneously post a wage. The Nash equilibrium of this game exhibits the following properties: (i) an equilibrium where workers apply for just one job exhibits unemployment and absence of wage dispersion; (ii) an equilibrium where workers apply for two or for more (but not for all) jobs always exhibits wage dispersion and, typically, unemployment; (iii) the equilibrium wage distribution with a higher vacancy-to-unemployment ratio first-order stochastically dominates the wage distribution with a lower level of labor market tightness; (iv) the average wage is non-monotonic in the number of applications; (v) the equilibrium number of applications is non-monotonic in the vacancy-to-unemployment ratio; (vi) a minimum wage increase can be welfare improving because it compresses the wage distribution and reduces the congestion effects caused by the socially excessive number of applications; and (vii) the only way to obtain efficiency is to impose a mandatory wage that eliminates wage dispersion altogether.wage setting, unemployment, minimum wage, Nash equilibrium

Hybrid R&D

We develop a model of R&D competition and collaborationin which individual firms carry out independent in-house researchand also undertake joint research projects with other firms. Weexamine the impact of collaboration on in-house research andexplore the circumstances under which a hybrid organization ofR&D which combines the two is optimal for firms andsociety. We find that investments in independent research and injoint research are complementary: an increase in the number ofjoint projects also increases in-house research. Firm profits arehighest under a hybrid organization if the number of firms issmall (less than 5) while they are highest with pure in-houseresearch if the number of firms is large (5 or more). However,social welfare is maximized under a hybrid organization of R&D inall cases. Our analysis also yields new results on the role ofcooperative R&D. We find that non-cooperative decision making byfirms leads to larger R&D investments and higher social welfarethan fully cooperative decision making. However, a hybrid form ofdecision making where there is bilateral cooperation in jointprojects and non-cooperative decision making in in-house researchyields the highest level of welfare in concentrated industries.

Urban Renewal

The following conditions, as stipulated in the program, will be of primary importance 1. That this area become a delightful, highly utilized heart of the city . 2. That it provide all major facilities and appropriate environment tor living, working, culture and recreation in balanced quantities, for the people who will reside within its boundaries, and in addition, provide a variety of activities which will benefit people throughout the region as a whole. 3. That it create permanent values; human, social, and economic. to the city. 4. The following minimum facilities are to be provided a. Residence for at least 5,000 families. b. Offices. c. Local and area wide shopping. d. A community college. e. 100% expansion of existing hospital. f. Parks, playground, and other outdoor recreation

Prevalence of Geographic Tongue in Chilean Children between 7 and 10 Years of Age

Indexación: Web of Science; Scielo.RESUMEN: El objetivo del estudio fue determinar la prevalencia de lengua geográfica y evaluar su asociación con el estrés emocional, irritación crónica, lengua fisurada y tipo de establecimiento educacional, en niños de 7 a 10 años de edad en la ciudad de Viña del Mar, Chile. De un total de 27.234 escolares, cursando 2 a 5 año básico, pertenecientes a colegios de la ciudad de Viña del Mar, Chile, se examinaron 436 niños.Se realizó un estudio descriptivo transversal de alumnos provenientes de tres tipos de establecimientos educacionales diferentes: particular, particular con subvención del estado de Chile y municipalizado. Las variables estudiadas fueron edad, sexo y establecimiento educacional. Adicionalmente, en los alumnos con lengua geográfica y 23 alumnos sin este diagnóstico se evaluó la presencia de lengua fisurada, irritación lingual crónica y estrés emocional. Se determinó la prevalencia mediante el cálculo de una proporción, las variables discretas se analizaron mediante Chi-cuadrado de Pearson o la prueba de Fisher y para determinar medidas de asociación con lengua geográfica se realizó regresión logística binaria, considerándose significativo un p<0,05. De los 436 niños, 23 presentaron lengua geográfica, evidenciando una prevalencia de 5,28%, con un IC 95% de 3,37% a 7,81%. No se evidenciaron diferencias respecto al sexo, edad ni tipo de establecimiento educacional. No se determinaron factores asociados a lengua geográfica. La prevalencia de LG determinada es similar a otros estudios que abarcan la misma población de rangos etarios. Al igual que en otros estudios no se pudo demostrar que el estrés emocional, irritación crónica, lengua fisurada y tipo de establecimiento educacional constituyeron factores asociados a la presencia de lengua geográfica.ABSTRACT: The aim of this study was to determine the prevalence of geographic tongue and evaluate its association with emotional stress, chronic irritation, fissured tongue and type of educational establishment, in children between 7 and 10 years of age, in the city of Viña del Mar, Chile. From a total of 27,234 students attending 2nd through 5th grade, we examined 436 children. A descriptive study of students was carried out from three different educational institutions: private, private with state funding and public schools. The variables studied were age, sex and the educational establishment the children attended. Additionally in the students with geographic tongue and in 23 students without this diagnosis, we evaluated the presence of fissured tongue, tongue irritation and chronic emotional stress. Prevalence was determined by calculating ratio, discrete variables were analyzed using Pearson Chi-square test or Fisher, and in order to determine association measures with geographic tongue, binary logistic regression was considered significant at p <0.05. Of the 436 children, 23 had geographic tongue, showing a prevalence of 5.28% with a 95% CI 3.37% to 7.81%. No differences regarding sex, age and type of educational establishment were found. No factors associated with geographic tongue were determined. The prevalence of the LG is similar to other studies covering the same age ranges. Furthermore, and as in other works, our study did not to show that emotional stress, chronic irritation, fissured tongue and the type of educational establishment constituted factors associated with the presence of geographic tongue.http://ref.scielo.org/y3rcd

On adaptive kernel intensity estimation on linear networks

In the analysis of spatial point patterns on linear networks, a critical statistical objective is estimating the first-order intensity function, representing the expected number of points within specific subsets of the network. Typically, non-parametric approaches employing heating kernels are used for this estimation. However, a significant challenge arises in selecting appropriate bandwidths before conducting the estimation. We study an intensity estimation mechanism that overcomes this limitation using adaptive estimators, where bandwidths adapt to the data points in the pattern. While adaptive estimators have been explored in other contexts, their application in linear networks remains underexplored. We investigate the adaptive intensity estimator within the linear network context and extend a partitioning technique based on bandwidth quantiles to expedite the estimation process significantly. Through simulations, we demonstrate the efficacy of this technique, showing that the partition estimator closely approximates the direct estimator while drastically reducing computation time. As a practical application, we employ our method to estimate the intensity of traffic accidents in a neighbourhood in Medellin, Colombia, showcasing its real-world relevance and efficiency.Comment: 19 pages, 7 figure

Non-Parametric Analysis of Spatial and Spatio-Temporal Point Patterns

The analysis of spatial and spatio-temporal point patterns is becoming increasingly necessary, given the rapid emergence of geographically and temporally indexed data in a wide range of fields. Non-parametric point pattern methods are a highly adaptable approach to answering questions about the real-world using complex data in the form of collections of points. Several methodological advances have been introduced in the last few years. This paper examines the current methodology, including the most recent developments in estimation and computation, and shows how various R packages can be combined to run a set of non-parametric point pattern analyses in a guided and intuitive way. An example of non-specific gastrointestinal disease reports in Hampshire, UK, from 2001 to 2003 is used to illustrate the methods, procedures and interpretations

Variation of allozyme frequencies in Spanish field and cellar populations of D. melanogaster.

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Spatio-temporal modeling of infectious diseases by integrating compartment and point process models

Infectious disease modeling plays an important role in understanding disease spreading dynamics and can be used for prevention and control. The well-known SIR (Susceptible, Infected, and Recovered) compartment model and spatial and spatio-temporal statistical models are common choices for studying problems of this kind. This paper proposes a spatio-temporal modeling framework to characterize infectious disease dynamics by integrating the SIR compartment and log-Gaussian Cox process (LGCP) models. The method’s performance is assessed via simulation using a combination of real and synthetic data for a region in São Paulo, Brazil. We also apply our modeling approach to analyze COVID-19 dynamics in Cali, Colombia. The results show that our modified LGCP model, which takes advantage of information obtained from the previous SIR modeling step, leads to a better forecasting performance than equivalent models that do not do that. Finally, the proposed method also allows the incorporation of age-stratified contact information, which provides valuable decision-making insights