CAMCR: Computer-Assisted Mixture model analysis for Capture–Recapture count data

Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.

Identified consumers: an experiment on the informativeness of cross-demand price effects

Often, firms have no information on the specification of the true demand model they are faced with. It is, however, a well established fact that trial-and-error algorithms may be used by them in order to learn how to make optimal decisions. Using experimental methods, we identify a property of the information on past actions which helps the seller of two asymmetric demand substitutes to reach the optimal prices more precisely and faster. The property concerns the possibility of disaggregating changes in each product’s demand into client exit/entry and shift from one product to the other.

Towards diversification of the tourism sector: A recreational demand study of yachting and marina services in the Caribbean

Includes bibliography.

Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors

Consider a nonparametric regression model Y=mu*(X) + e, where the explanatory variables X are endogenous and e satisfies the conditional moment restriction E[e|W]=0 w.p.1 for instrumental variables W. It is well known that in these models the structural parameter mu* is 'ill-posed' in the sense that the function mapping the data to mu* is not continuous. In this paper, we derive the efficiency bounds for estimating linear functionals E[p(X)mu*(X)] and int_{supp(X)}p(x)mu*(x)dx, where p is a known weight function and supp(X) the support of X, without assuming mu* to be well-posed or even identified.

A comparison of sales response predictions from demand models applied to store-level versus panel data

In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate different forms of consumer heterogeneity depending on the level of data aggregation. This study shows via simulation that demand models with various heterogeneity specifications do not produce more accurate sales response predictions than a homogeneous demand model applied to store-level data, with one major exception: a random coefficients model designed to capture within-store heterogeneity using store-level data produced significantly more accurate sales response predictions (as well as better fit) compared to other model specifications. An empirical application to the paper towel product category adds additional insights. This article has supplementary material online.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

The food business environment and the role of China and Brazil building a ""food bridge""

Purpose - The purpose of this paper is to discuss the economic crisis of 2008/2009 and the major impacts on developing nations and food-producing countries Within this macro-environment of food chains, there is concern that food inflation might come back sooner than expected The role of China as one of the major food consumers in the future, and Brazil, as the major food producer, is described as the food bridge, and an agenda of common development of these countries suggested. Design/methodology/approach - This paper reviews literature on muses of food inflation, production shortages, and investigation of programs to solve the problem in the future, it is also based on author`s personal insights and experience of working on this field in the last 15 years, and recent discussions in forums and interviews Findings - The major factors that jointly caused food prices increase in 2007/2008 were population growth, Income distribution, urbanization, dollar devaluations, commodity funds, social programs, production shortages, and bionic`s A list of ten policies is suggested. horizontal expansion of food production, vertical expansion, reduction in transaction costs, in protectionism and other taxes, investment in logistics, technology and better coordination, contracts, new generation of fertilizers and to use the best sources of biofuels. Originality/value - Two major outputs from this paper are the ""food demand model"" that inserts in one model the trends and muses of food inflation and the solutions, and the ""food bridge concept"" that also aligns in one box the imminent major food chain cooperation between China and Brazil

THE TEMPO AND MODE OF EVOLUTION OF TRANSPOSABLE ELEMENTS AS REVEALED BY MOLECULAR PHYLOGENIES RECONSTRUCTED FROM MOSQUITO GENOMES

Although many mathematical models exist predicting the dynamics of transposable elements (TEs), there is a lack of available empirical data to validate these models and inherent assumptions. Genomes can provide a snapshot of several TE families in a single organism, and these could have their demographics inferred by coalescent analysis, allowing for the testing of theories on TE amplification dynamics. Using the available genomes of the mosquitoes Aedes aegypti and Anopheles gambiae, we indicate that such an approach is feasible. Our analysis follows four steps: (1) mining the two mosquito genomes currently available in search of TE families; (2) fitting, to selected families found in (1), a phylogeny tree under the general time-reversible (GTR) nucleotide substitution model with an uncorrelated lognormal (UCLN) relaxed clock and a nonparametric demographic model; (3) fitting a nonparametric coalescent model to the tree generated in (2); and (4) fitting parametric models motivated by ecological theories to the curve generated in (3).

What if there was a stronger pharmaceutical price competition in Spain? When regulation has a similar effect to collusion

This paper examines statins competition in the Spanish pharmaceutical market, where prices are highly regulated, and simulates a situation in which there is unrestricted price competition. A nested logit demand model is estimated with a panel of monthly data for pharmaceuticals prescribed from 1997 to 2005. The simulation indicates that the regulation of prices is similar in its effects to cooperation among producers, since the regulated prices are close to those that would be observed in a scenario of perfect collusion. Freedom to set prices and a regulatory framework with appropriate incentives would result in a general reduction in prices and may make the current veiled competition in the form of discounts to pharmacists become more visible. The decrease in prices would be partially offset by an increase in consumption but the net effect would be an overall decrease in expenditure. The counterfactual set-up would also lead to important changes in the market shares of both manufacturers and active ingredients, and a reversal of generic drugs. Therefore, pro-competitive regulation would be welfare-enhancing but would imply winners and losers.

Generic drugs in Spain: price competition vs. moral hazard

This paper examines competition between generic and brand-name drugs in the regulated Spanish pharmaceutical market. A nested logit demand model is specified for the three most consumed therapeutic subgroups in Spain: statins (anticholesterol), selective serotonin reuptake inhibitors (antidepressants) and proton pump inhibitors (antiulcers). The model is estimated with instrumental variables from a panel of monthly prescription data from 1999 to 2005. The dataset distinguishes between three different levels of patients’ copayments within the prescriptions and the results show that the greater the level of insurance that the patient has (and therefore the lower the patient’s copayment), the lower the proportion of generic prescriptions made by physicians. It seems that the low level of copayment has delayed the penetration of generics into the Spanish market. Additionally, the estimation of the demand model suggests that the substitution rules and promotional efforts associated with the reference pricing system have increased generic market share, and that being among the first generic entrants has an additional positive effect.

Why Have Aggregate Skilled Hours Become So Cyclical Since the Mid-1980's?

This paper documents and discusses a dramatic change in the cyclical behavior of aggregate hours worked by individuals with a college degree (skilled workers) since the mid-1980’s. Using the CPS outgoing rotation data set for the period 1979:1-2003:4, we find that the volatility of aggregate skilled hours relative to the volatility of GDP has nearly tripled since 1984. In contrast, the cyclical properties of unskilled hours have remained essentially unchanged. We evaluate the extent to which a simple supply/demand model for skilled and unskilled labor with capital-skill complementarity in production can help explain this stylized fact. Within this framework, we identify three effects which would lead to an increase in the relative volatility of skilled hours: (i) a reduction in the degree of capital-skill complementarity, (ii) a reduction in the absolute volatility of GDP (and unskilled hours), and (iii) an increase in the level of capital equipment relative to skilled labor. We provide empirical evidence in support of each of these effects. Our conclusion is that these three mechanisms can jointly explain about sixty percent of the observed increase in the relative volatility of skilled labor. The reduction in the degree of capital-skill complementarity contributes the most to this result.

Revisiting youden’s index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden’s index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel–Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden’s index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.

Consumer welfare and the loss induced by withholding information: The case of BSE in Italy

The paper develops a measure of consumer welfare losses associated with withholding it formation about a possible link between BSE and vCJD. The Cost of Ignorance (COI) is measured by comparing the utility of the informed choice with the utility of the uninformed choice, under conditions of improved information. Unlike previous work that is largely based on a single equation demand model, the measure is obtained retrieving a cost,function from a dynamic Almost Ideal Demand System. The estimated perceived loss for Italian consumers due to delayed information ranges from 12 percent to 54 percent of total meat expenditure, depending on the month assumed to embody correct beliefs about the safety level of beef.

Meta-analysis: a unifying meta-likelihood approach framing unobserved heterogeneity, study covariates, publication bias, and study quality

OBJECTIVES: This contribution provides a unifying concept for meta-analysis integrating the handling of unobserved heterogeneity, study covariates, publication bias and study quality. It is important to consider these issues simultaneously to avoid the occurrence of artifacts, and a method for doing so is suggested here. METHODS: The approach is based upon the meta-likelihood in combination with a general linear nonparametric mixed model, which lays the ground for all inferential conclusions suggested here. RESULTS: The concept is illustrated at hand of a meta-analysis investigating the relationship of hormone replacement therapy and breast cancer. The phenomenon of interest has been investigated in many studies for a considerable time and different results were reported. In 1992 a meta-analysis by Sillero-Arenas et al. concluded a small, but significant overall effect of 1.06 on the relative risk scale. Using the meta-likelihood approach it is demonstrated here that this meta-analysis is due to considerable unobserved heterogeneity. Furthermore, it is shown that new methods are available to model this heterogeneity successfully. It is argued further to include available study covariates to explain this heterogeneity in the meta-analysis at hand. CONCLUSIONS: The topic of HRT and breast cancer has again very recently become an issue of public debate, when results of a large trial investigating the health effects of hormone replacement therapy were published indicating an increased risk for breast cancer (risk ratio of 1.26). Using an adequate regression model in the previously published meta-analysis an adjusted estimate of effect of 1.14 can be given which is considerably higher than the one published in the meta-analysis of Sillero-Arenas et al. In summary, it is hoped that the method suggested here contributes further to a good meta-analytic practice in public health and clinical disciplines.

Revisiting Youden's index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

The paper considers meta-analysis of diagnostic studies that use a continuous Score for classification of study participants into healthy, or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between Studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might he confounded by a potentially unknown variation of the cut-off Value. To cope with this phenomena it is suggested to use, instead an overall estimate of the misclassification error previously suggested and used as Youden's index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel-Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden's index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.