Relationship between Spatial Price Transmission and Geographical Distance in Brazil

Selected Paper prepared for presentation at the Agricultural & Applied Economics Association’s 2011 AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania, July 24-26, 2011. (Poster Presentation)cointegration, price transmission, geographical distance, structural breaks, principal component regression, rice, Brazil., Agricultural and Food Policy, Demand and Price Analysis, C32, Q11, Q13,

Bibliometric trends of health economic evaluation in Sub-Saharan Africa

Background: Collaboration between Sub-Saharan African researchers is important for the generation and transfer of health technology assessment (HTA) evidence, in order to support priority-setting in health. The objective of this analysis was to evaluate collaboration patterns between countries. Methods: We conducted a rapid evidence assessment that included a random sample of health economic evaluations carried out in 20 countries (Angola, Botswana, Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, Zimbabwe, Ghana, Kenya, Nigeria, Ethiopia, Uganda). We conducted bibliometric network analysis based on all first authors with a Sub-Saharan African academic affiliation and their co-authored publications (“network-articles”). Then we produced a connection map of collaboration patterns among Sub-Saharan African researchers, reflecting the number of network-articles and the country of affiliation of the main co-authors. Results: The sample of 119 economic evaluations mostly related to treatments of communicable diseases, in particular HIV/AIDS (42/119, 35.29 %) and malaria (26/119, 21.85 %). The 39 first authors from Sub-Saharan African institutions together co-authored 729 network-articles. The network analysis showed weak collaboration between health economic researchers in Sub-Saharan Africa, with researchers being more likely to collaborate with Europe and North America than with other African countries. South Africa stood out as producing the highest number of health economic evaluations and collaborations. Conclusions: The development and evaluation of HTA research networks in Sub-Saharan Africa should be supported, with South Africa central to any such efforts. Organizations and institutions from high income countries interested in supporting priority setting in Sub-Saharan Africa should include promoting collaboration as part of their agendas, in order to take advantage of the potential transferability of results and methods of the available health economic analyses in Africa and internationally

Estimation of the stage-wise costs of breast cancer in Germany using a modeling approach

Breast cancer (BC) is a heterogeneous disease representing a substantial economic burden. In order to develop policies that successfully decrease this burden, the factors affecting costs need to be fully understood. Evidence suggests that early-stage BC has a lower cost than a late stage BC. We aim to provide conservative estimates of BC's stage-wise medical costs from German healthcare and the payer's perspective. To this end, we conducted a literature review of articles evaluating stage-wise costs of BC in Germany through PubMed, Web of Science, and Econ Lit databases supplemented by Google Scholar. We developed a decision tree model to estimate BC-related medical costs in Germany using available treatment and cost information. The review generated seven studies; none estimated the stage-wise costs of BC. The studies were classified into two groups: case scenarios (five studies) and two studies based on administrative data. The first sickness funds data study (Gruber et al., 2012) used information from the year 1999 to approach BC attributable cost; their results suggest a range between €3,929 and €11,787 depending on age. The second study (Kreis, Plöthner et al., 2020) used 2011–2014 data and suggested an initial phase incremental cost of €21,499, an intermediate phase cost of €2,620, and a terminal phase cost of €34,513 per incident case. Our decision tree model-based BC stage-wise cost estimates were €21,523 for stage I, €25,679 for stage II, €30,156 for stage III, and €42,086 for stage IV. Alternatively, the modeled cost estimates are €20,284 for the initial phase of care, €851 for the intermediate phase of care, and €34,963 for the terminal phase of care. Our estimates for phases of care are consistent with recent German estimates provided by Kreis et al. Furthermore, the data collected by sickness funds are collected primarily for reimbursement purposes, where the German ICD-10 classification system defines a cancer diagnosis. As a result, claims data lack the clinical information necessary to understand stage-wise BC costs. Our model-based estimates fill the gap and inform future economic evaluations of BC interventions

THE ROLE OF ASYMMETRIC PRICE TRANSMISSION AND STRUCTURAL BREAKS IN THE RELATIONSHIP BETWEEN COSTA RICAN MARKETS OF LIVESTOCK CATTLE, BEEF AND MILK

The research analyzes the price transmission among the Costa Rican markets of cattle, beef and milk, accounting for asymmetric behavior and structural breaks. Monthly price data covering the first month of 1998 to the fourth month of 2008 were used. Price transmission between each market pair was found. The Price adjustment is consistent at 1% of significant with the behaviour expected. Cattle prices adjust in the milk - cattle relationship, beef meat prices adjust in the cattle - beef meat relation and in the milk - beef meat relation. This finding supports the statement regarding the leading position of “Dos Pinos” as the main player in the market. The results of the asymmetric analysis are not as expected. The coefficients of both adjustments (positive and negative) are not significantly different. The equations allowing for structural break affects the estimates: first after the break the elasticities became higher than 1, second there is more evidence of cointegration and third the adjustment coefficients are significant only when a change in the long run is allowed

The relationship between spatial price transmission and geographical distance: the case of Brazil

The objectives of this research are to investigate the influence of geographical distance on the cointegration relationship in order to increase knowledge on the issue, and to indentify its role in Brazilian agricultural markets. With this intention, the cointegration framework is applied allowing for the presence of multiple structural breaks in the long run equation. The inclusion of breaks is in response to the multiple changes of the agricultural system during the period of investigation. The spatial integration is calculated between each market pair. The cointegration coefficient and geographical distance relationship is calculated by means of an OLS regression, taking into account the quality of roads and the proximity to a border or port. The effect of the distance depends on the product. In the case of rice markets, there is a weak, negative and significant relation. Concerning soybeans, the relationship is not significant. After allowing for the inclusion of breaks in the long run, the results remain unvaried. In addition, the region and a better access to export points are the main variables in the definition of the prices

Zeitschrift für Rechtssoziologie

The price transmission between markets is often interpreted as providing insights into the market’s infrastructure efficiency and transaction costs. Thus, finding a possible explanation for the degree of integration has become an issue of special interest. Recent researchers have pointed out the distance between markets as one of the possible factors. However, the distance is closely related with other elements, such as road quality and the proximity to an export point, which affect transport costs, opportunity costs and thus the integration. Therefore, what the most important factor is when determining the relationship among markets remains unclear. The cointegration framework, OLS and principal component regressions are applied in order to investigate the influence of geographical distance on the cointegration relationship between Brazil`s rice markets. In response to changes of the agricultural policies during the period of investigation, the presence of multiple structural breaks in the long run equation is allowed. The results point out a weak, negative and significant relation between distance and the elasticity of cointegration. Moreover, the region in which the market is located and a better access to export points are the main variables which defined the strength of the price transmission

The relationship between spatial price transmission and geographical distance: the case of Brazil

The objectives of this research are to investigate the influence of geographical distance on the cointegration relationship in order to increase knowledge on the issue, and to indentify its role in Brazilian agricultural markets. With this intention, the cointegration framework is applied allowing for the presence of multiple structural breaks in the long run equation. The inclusion of breaks is in response to the multiple changes of the agricultural system during the period of investigation. The spatial integration is calculated between each market pair. The cointegration coefficient and geographical distance relationship is calculated by means of an OLS regression, taking into account the quality of roads and the proximity to a border or port. The effect of the distance depends on the product. In the case of rice markets, there is a weak, negative and significant relation. Concerning soybeans, the relationship is not significant. After allowing for the inclusion of breaks in the long run, the results remain unvaried. In addition, the region and a better access to export points are the main variables in the definition of the prices.cointegration, price transmission, geographical distance, structural breaks, rice, soybeans, Brazil., Agribusiness, Agricultural and Food Policy, Community/Rural/Urban Development, Food Consumption/Nutrition/Food Safety, Labor and Human Capital,