A bioeconomic model for estimating the optimal level of deer and tag sales

This paper presents a dynamic model that determines the optimal number of deer hunting permit sales, subject to the objective of maximizing the discounted economic benefits stream from both the consumptive and nonconsumptive uses of deer. This bioeconomic model integrates economic benefits estimated using the dichotomous choice contingent valuation method with biological growth constraints on deer. Using a hunting zone in California as a case study, the model found that the optimal levels of buck hunting permits sold should change on a rotational basis over time and that the current practice of not selling doe hunting permits for that zone is non optimal.     

A science-driven market-based instrument for determining the cost of environmental services: A comparison of two catchments in Australia

An auction-based approach (or MBI for “market-based instrument”) was used to purchase environmental services from landowners and to establish a long-term economic resource (forest plantations) in two catchments in the state of Victoria (Australia). The policy goal of the MBI was to encourage the conversion of cleared land to forest plantations. It was desired to achieve this while also reducing the amount of land affected by dryland salinity with minimum impact on water available for irrigation. Operationally, interested landowners identified areas on which they would be willing to establish forest plantations, and stated the amount of money they would require from the government to undertake plantation establishment; this constituted a landowner bid. The proposed planting area associated with each bid was processed through a quantitative hydrological model to estimate off-site impacts on dryland salinity and the change in water yield resulting from the conversion of individual non-forested areas to forest plantations. Landowner bids were then accepted or not based on the economic trade-offs among dollars requested by a landowner, reduction in water yield, and decrease in dryland salinity. To enable a comparison of costs, the MBI was independently trialled in two catchments. For both, the cost to government of a hectare of plantation and/or a hectare of salinity benefit was calculated a number of ways. Assuming the existence of a calibrated hydrological model, costs associated with distributing money via such an MBI were publicity, fieldwork, processing the bids through the model, probity, legal, and administration. In the Gippsland catchment, the total cost to establish forest plantations was $5340 per ha whereas it was $1635 per ha in the Corangamite catchment. No salinity benefit was obtained in Gippsland, but in Corangamite, if considered in isolation of the economic forest plantation benefit, the cost per hectare of salinity benefit was $5020.Operational aspects of the MBI are presented and discussed and a comparison is made to the expected costs of a conventional, non-science driven approach to landowner incentives.     

Socioeconomic predictors of forest use values in the Peruvian Amazon: A potential tool for biodiversity conservation

Conservation is a crisis discipline requiring rapid action with limited funds. This study examines the potential of socioeconomic variables to predict forest use values. If natural resource use can be predicted from socioeconomic data, conservation planners could rapidly identify and focus conservation programs on the sectors of local populations that most intensively utilize local flora and fauna. Families in three communities in the northern Peruvian Amazon were surveyed over a 6-month period. Data were collected on use of flora and fauna from six locally determined use categories (food, medicine and poisons, wood, weavings, adornments, and “other”) in forest types of three age classes (fallow fields—very young forests, young secondary forests, and old secondary forests). Forest use values were the dependant variables calculated in $/ha/year. Socioeconomic variables included: age, education, family size, residence time, land worked, land owned, number of fishing nets, chickens, pigs, cows, and/or mules owned (all proxies for productive assets), and level of ecological knowledge (ability of informants to correctly identify forest species and answer basic questions about their biology). Ordinary least square multiple regressions were run independently for each forest type. Regressions were also run separately for the two most valuable use categories, food and wood. Low R² adjusted values (all < 0.3) reflect the difficulty in predicting human behavior due to confounding variables and complex interactions. Residence time and a household's community of residence were the most significant predictors of forest use values. Households in Vista Alegre, the community with the highest density of people and smallest landholdings per household, extracted the highest value of forest products per hectare. The longer a family stayed in any community the higher the value of forest goods they extracted. If families that lived in an area longest are the most intensive extractors of forest products, they should be a major focus for conservation programming. In addition, the higher value of products extracted from forests by some families may make them more open to strategies seeking to protect long-term viability of the resources they utilize. The importance of residence time also indicates that planners need to account for changes in the resource use patterns of stakeholders over time.     

A health economic model to assess the cost-effectiveness of OPTIFAST for the treatment of obesity in the United States

Objectives: Obesity is associated with high direct medical costs and indirect costs resulting from productivity loss. The high prevalence of obesity generates a justified need to identify cost-effective weight loss approaches from a payer’s perspective. Within the variety of weight management techniques, OPTIFAST is a clinically recognized and scientifically proven total meal replacement Low Calorie Diet that provides meaningful results in terms of weight loss and reduction in comorbidities. The objective of this study is assess potential cost-savings of the OPTIFAST program in the US, as compared to “no intervention” and pharmacotherapy.

Methods: An event-driven decision analytic model was used to estimate payer’s cost-savings from reimbursement of the 1-year OPTIFAST program over 3 years in the US. The analysis was performed for the broad population of obese persons (BMI >30?kg/m²) undergoing the OPTIFAST program vs liraglutide 3?mg, naltrexone/bupropion and vs “no intervention”. The model included the risk of complications related to increased BMI. Data sources included published literature, clinical trials, official US price/tariff lists, and national population statistics. The primary perspective was that of a US payer; costs were provided in 2016?US dollars.

Results: OPTIFAST leads over a period of 3 years to cost-savings of USD 9,285 per class I and II obese patient (BMI 30–39.9?kg/m²) as compared to liraglutide and USD 685 as compared to naltrexone/bupropion. In the same time perspective, the OPTIFAST program leads to a reduction of cost of obesity complications of USD 1,951 as compared to “no intervention”, with the incremental cost-effectiveness ratio of USD 6,475 per QALY. Scenario analyses also show substantial cost-savings in patients with class III obesity (BMI?≥?40.0?kg/m²) and patients with obesity (BMI?=?30–39.9?kg/m²) and type 2 diabetes vs all three previous comparators and bariatric surgery.

Conclusions: Reimbursing OPTIFAST leads to meaningful cost-savings for US payers as compared with “no intervention” and liraglutide and naltrexone/bupropion in obese patients. Similar results can be expected in matching healthcare settings of other countries. Moreover, OPTIFAST has additional clinical and economic advantages through very low complication and adverse events rates.     

基于MESS模型的服务业影响因素及空间溢出效应分析——以浙江省69个市县为例

基于矩阵指数空间规范(MESS)模型,文章以浙江省69个市县为例,采用Bayes方法对服务业的影响因素进行了空间计量分析。研究发现,浙江省各市县的服务业存在显著的空间相依性和空间异质性。地区的服务业从业人员比例、人口密度、工业产值以及地方财政支出占GDP的比例不仅对本地区的服务业增长有显著的促进作用,还对邻近地区的服务业有正向溢出效应;而地区的全社会固定资产投资对服务业的发展则是一个抑制性因素。     

A global economic model to assess the cost-effectiveness of new treatments for advanced breast cancer in Canada

Objective Considering the increasing number of treatment options for metastatic breast cancer (MBC), it is important to develop high-quality methods to assess the cost-effectiveness of new anti-cancer drugs. This study aims to develop a global economic model that could be used as a benchmark for the economic evaluation of new therapies for MBC.

Methods The Global Pharmacoeconomics of Metastatic Breast Cancer (GPMBC) model is a Markov model that was constructed to estimate the incremental cost per quality-adjusted life years (QALY) of new treatments for MBC from a Canadian healthcare system perspective over a lifetime horizon. Specific parameters included in the model are cost of drug treatment, survival outcomes, and incidence of treatment-related adverse events (AEs). Global parameters are patient characteristics, health states utilities, disutilities, and costs associated with treatment-related AEs, as well as costs associated with drug administration, medical follow-up, and end-of-life care. The GPMBC model was tested and validated in a specific context, by assessing the cost-effectiveness of lapatinib plus letrozole compared with other widely used first-line therapies for post-menopausal women with hormone receptor-positive (HR+) and epidermal growth factor receptor 2-positive (HER2+) MBC.

Results When tested, the GPMBC model led to incremental cost-utility ratios of CA$131 811 per QALY, CA$56 211 per QALY, and CA$102 477 per QALY for the comparison of lapatinib plus letrozole vs letrozole alone, trastuzumab plus anastrozole, and anastrozole alone, respectively. Results of the model testing were quite similar to those obtained by Delea et al., who also assessed the cost-effectiveness of lapatinib in combination with letrozole in HR+/HER2?+?MBC in Canada, thus suggesting that the GPMBC model can replicate results of well-conducted economic evaluations.

Conclusions The GPMBC model can be very valuable as it allows a quick and valid assessment of the cost-effectiveness of any new treatments for MBC in a Canadian context.     

A modified logit model for time series with an application to the pricing behaviour of manufacturing firms in Australia

The modified logit model (Amemiya and Nold, 1975) is generalised to the case where the error term is autocorrelated. The asymptotic distribution (as n →∞ and T →∞) of a feasible GLS estimator of β is derived. Tests of linear restrictions on β and the significance of ρ are presented. The results of the applied work suggest that the factors which explain the pricing behaviour of manufacturing firms, as reported in the tendency survey conducted by the Australian Chamber of Commerce and Industry and the Westpac Banking Corporation, include historical inflation rates of up to 7 quarters and capacity utilisation. First version received: March 2001/Final version received: July 2002 RID="*" ID="*"  The first draft of this paper was written while the author was on study leave at the Department of Econometrics, University of Sydney, Australia.     

A systematic review of cost-effectiveness modeling of pharmaceutical therapies in neuropathic pain: variation in practice,key challenges,and recommendations for the future

Objectives: Complexities in the neuropathic-pain care pathway make the condition difficult to manage and difficult to capture in cost-effectiveness models. The aim of this study is to understand, through a systematic review of previous cost-effectiveness studies, some of the key strengths and limitations in data and modeling practices in neuropathic pain. Thus, the aim is to guide future research and practice to improve resource allocation decisions and encourage continued investment to find novel and effective treatments for patients with neuropathic pain.

Methods: The search strategy was designed to identify peer-reviewed cost-effectiveness evaluations of non-surgical, pharmaceutical therapies for neuropathic pain published since January 2000, accessing five key databases. All identified publications were reviewed and screened according to pre-defined eligibility criteria. Data extraction was designed to reflect key data challenges and approaches to modeling in neuropathic pain and based on published guidelines.

Results: The search strategy identified 20 cost-effectiveness analyses meeting the inclusion criteria, of which 14 had original model structures. Cost-effectiveness modeling in neuropathic pain is established and increasing across multiple jurisdictions; however, amongst these studies, there is substantial variation in modeling approach, and there are common limitations. Capturing the effect of treatments upon health outcomes, particularly health-related quality-of-life, is challenging, and the health effects of multiple lines of ineffective treatment, common for patients with neuropathic pain, have not been consistently or robustly modeled.

Conclusions: To improve future economic modeling in neuropathic pain, further research is suggested into the effect of multiple lines of treatment and treatment failure upon patient outcomes and subsequent treatment effectiveness; the impact of treatment-emergent adverse events upon patient outcomes; and consistent and appropriate pain measures to inform models. The authors further encourage transparent reporting of inputs used to inform cost-effectiveness models, with robust, comprehensive and clear uncertainty analysis and, where feasible, open-source modeling is encouraged.