Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Modelagem de dados de entrada para simulação estocástica de lavra

Mine simulation depends on data that is both coherent and representative of the mining operation. This paper describes a methodology for modeling operational data which has been developed for mine simulation. The methodology has been applied to a case study of an open-pit mine, where the cycle times of the truck fleet have been modeled for mine simulation purposes. The results obtained have shown that once the operational data has been treated using the proposed methodology, the system variables have proven to be adherent to theoretical distributions. The research indicated the need jar tracking the origin of data inconsistencies through the development of a process to manage inconsistent data from the mining operation.

Incorporating demand-side aspects into regional policy: variations in the importance of private investment decision factors across regions

Most regional programs focus on the supply side of regions, emphasizing the attraction conditions offered, such as infrastructure, labor skills, tax incentives, etc. This study analyzes one aspect of the demand side, that is, how investment decisions of private firms are made by asking the question: ""Do corporations decide the same way on investments in different parts of the territory?"" The paper analyzes the investments of 373 large Brazilian firms during 1996-2004. Based on the investment decisions of these firms, the role of sales, cash-flow, external financing, and working capital is investigated through regression analysis. The regional influence is captured by explanatory variables representing regional and firm characteristics, and by interaction dummies between the region and the main investment determinants. The results indicate significant differences across regions in the importance of investment determinants. This information is important for regional development policy, because different mechanisms should be used in different regions to foster private investments.

Corruption and the size of government: causality tests for OECD and Latin American countries

The purpose of this article is to examine the causality between government size and corruption, and to verify if there is a different pattern of causality between developed Organization for Economic Co-operation and Development (OECD) countries (excluding Mexico) and developing countries (Latin American countries) during the period 1996 to 2003. Applying Granger and Huang`s (1997) methodology we find evidence that size of government Granger causes corruption in both samples. Since a larger government involvement in private markets today will be followed in future by a higher level of corruption a policy advice would be to enhance governance. The promotion of good governance helps to combat corruption given that it complements efforts to reduce corruption more directly, and it is strongly recommended by the International Monetary Fund, other multilateral institutions, and all worried with the negative impacts of corruption on economic activity.

Opportunistic and partisan election cycles in Brazil: new evidence at the municipal level

This article tests the hypothesis of opportunistic and partisan cycle models using a new large data set of Brazilian municipalities over the 1989-2005 period. The results show an increase in total and current expenditures and a decrease in municipal investments, local tax revenues, and budget surplus in election years. They also show that partisan ideology exerts a relative influence on the performance of the local public accounts. These results confirm that both opportunistic and partisan cycles have occurred in the management of the budgets of Brazilian municipalities after the end of the military government.

Fiscal policy and reelection in Brazilian municipalities

This paper uses a new panel of more than 2,000 Brazilian municipalities over 13 years to analyze the influence of public expenditures on the probability of mayors` reelection. We examine Brazilian municipal elections from 1988 to 2000 using a logit fixed-effects model. The results suggest that mayors who spend more during their terms of office increase the probability of their own reelection or of a successor of the same political party. In particular, higher capital spending over the years preceding elections and current expenditures in election years are beneficial to Brazilian incumbent mayors.

Demand elasticities for food products in Brazil: a two-stage budgeting system

The object of this article is to estimate demand elasticities for a basket of staple food important for providing the caloric needs of Brazilian households. These elasticities are useful in the measurement of the impact of structural reforms on poverty. A two-stage demand system was constructed, based on data from Household Expenditure Surveys (POF) produced by IBGE (The Brazilian Bureau of Statistics) in 1987/88 and 1995/96. We have used panel data to estimate the model, and have calculated income, own-price, and cross-price elasticities for eight groups of goods and services and, in the second stage, for 11 sub groups of staple food products. We estimated those elasticities for the whole sample of consumers and for two income groups.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Body Mass Index, Cigarette Smoking, and Alcohol Consumption and Cancers of the Oral Cavity, Pharynx, and Larynx: Modeling Odds Ratios in Pooled Case-Control Data

study-specific results, their findings should be interpreted with caution

Experimental data and modeling of the thermodynamic properties of bread dough at refrigeration and freezing temperatures

Thermodynamic properties of bread dough (fusion enthalpy, apparent specific heat, initial freezing point and unfreezable water) were measured at temperatures from -40 degrees C to 35 degrees C using differential scanning calorimetry. The initial freezing point was also calculated based on the water activity of dough. The apparent specific heat varied as a function of temperature: specific heat in the freezing region varied from (1.7-23.1) J g(-1) degrees C(-1), and was constant at temperatures above freezing (2.7 J g(-1) degrees C(-1)). Unfreezable water content varied from (0.174-0.182) g/g of total product. Values of heat capacity as a function of temperature were correlated using thermodynamic models. A modification for low-moisture foodstuffs (such as bread dough) was successfully applied to the experimental data. (C) 2010 Elsevier Ltd. All rights reserved.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.

Scavenging processes of atmospheric particulate matter: a numerical modeling of case studies

Below cloud scavenging processes have been investigated considering a numerical simulation, local atmospheric conditions and particulate matter (PM) concentrations, at different sites in Germany. The below cloud scavenging model has been coupled with bulk particulate matter counter TSI (Trust Portacounter dataset, consisting of the variability prediction of the particulate air concentrations during chosen rain events. The TSI samples and meteorological parameters were obtained during three winter Campaigns: at Deuselbach, March 1994, consisting in three different events; Sylt, April 1994 and; Freiburg, March 1995. The results show a good agreement between modeled and observed air concentrations, emphasizing the quality of the conceptual model used in the below cloud scavenging numerical modeling. The results between modeled and observed data have also presented high square Pearson coefficient correlations over 0.7 and significant, except the Freiburg Campaign event. The differences between numerical simulations and observed dataset are explained by the wind direction changes and, perhaps, the absence of advection mass terms inside the modeling. These results validate previous works based on the same conceptual model.

Modeling the risk of malaria for travelers to areas with stable malaria transmission

Background: Malaria is an important threat to travelers visiting endemic regions. The risk of acquiring malaria is complex and a number of factors including transmission intensity, duration of exposure, season of the year and use of chemoprophylaxis have to be taken into account estimating risk. Materials and methods: A mathematical model was developed to estimate the risk of non-immune individual acquiring falciparum malaria when traveling to the Amazon region of Brazil. The risk of malaria infection to travelers was calculated as a function of duration of exposure and season of arrival. Results: The results suggest significant variation of risk for non-immune travelers depending on arrival season, duration of the visit and transmission intensity. The calculated risk for visitors staying longer than 4 months during peak transmission was 0.5% per visit. Conclusions: Risk estimates based on mathematical modeling based on accurate data can be a valuable tool in assessing risk/benefits and cost/benefits when deciding on the value of interventions for travelers to malaria endemic regions.