The question, "Why use a mathematical programming model at the sectoral level?" is addressed. To address this question, discussion is presented mathematically and verbally upon mathematical programming sector models in which both price and quantity are eŸ variables. The discussion covers both the theoretical properties and the empirical concerns which must be faced in applying such models. Discussion is also presented upon the usefulness of the modeling approach for policy analysis. Selected bibliograpic citations' use of the approach in policy analysis are given.
If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this study is to determine French consumer perceptions and preferences for fresh fruit from different countries. French consumer willingness to pay (WTP) for citrus fruit and the factors affecting WTP are also determined. Design/methodology/approach -An online consumer survey was conducted in France to collect data on consumer perceptions and preferences for fresh fruits from different countries. The contingent valuation method is used to estimate consumer WTP for fresh citrus fruit. A double hurdle model is used to determine the factors that have substantial impact on consumer preferences. Findings -Results show that fresh fruit from China was perceived as the lowest quality, the least safe, and the cheapest among the fruit from various countries. French consumers had the highest stated WTP for fresh fruit from France, followed by fruit from Spain. In addition, consumer WTP for country of origin varies by type of fruit.Research limitations/implications -The contingent valuation method does not require consumers to purchase the product being evaluated, which may overestimate consumer stated WTP. Practical implications -More domestically produced fresh fruit may be provided to satisfy consumer demand for fruit produced in their own countries. As second in consumer stated WTP, Spain should take advantage of the lower price high quality perceptions of their fresh fruit to gain a larger market share in France. Lower rated countries, such as China, Brazil, and Israel, need to improve consumer perception of the fruit from their countries to gain a better position in the fresh fruit market of France. Originality/value -This is the first paper to present French consumer perception of fresh fruit and WTP for citrus fruit from different countries.
Pasture dry matter (DM) {TOTAL, LIVE [total ‐ dead], GRASS, RP [rhizoma peanut {Arachis glabrata Benth)], and DEAD}, and relative growth rate (RGR), as well as steer (Bos spp.) average‐daily gain (ADG) and plasma urea N (PUN) were measured for continuously grazed grass‐RP or bahiagrass (BG) (Paspalum notatum Flugge) in the summers of 1986 and 1987. Crude protein (CP) and in vitro organic matter digestibility (IVOMD) was determined for GRASS and RP. The LIVE DM of the grass‐RP sward was higher than the BG sward (P = 0.06 and P = 0.001 in 1986 and 1987, respectively) due to the additive effect of the RP. Above average spring rainfall in 1987 almost doubled forage availability on both sward types. Rhizoma peanut was responsible for most of the increase on the grass‐RP sward (GRASS component—508 and 569 lb/acre, RP component—437 and 1433 lb/acre seasonal average in 1986 and 1987, respectively). The GRASS CP and IVOMD of either sward was similar and exhibited a similar pattern of decline during the grazing season (18.6‐6.3% CP and 67.4‐45.2% IVOMD from April‐September). The RP CP and IVOMD was higher throughout the grazing season (28.6‐13.9% CP and 78.0‐63.6% IVOMD). There was a significant treatment × year interaction for ADG and PUN (BG‐1.15 and 1.11 lb ADG and 97 and 85 ppm PUN; grass‐RP‐1.50 and 1.99 lb ADG and 166 and 235 ppm PUN in 1986 and 1987, respectively). This was due to increased RP in the sward (26% in 1986 and 45% in 1987).
Dynamic programming to solve the Markov decision process problem of optimal insemination and replacement decisions was adapted to address large dairy herd management decision problems in the US. Expected net present values of cow states (151,200) were used to determine the optimal policy. States were specified by class of parity (n = 12), production level (n = 15), month of calving (n = 12), month of lactation (n = 16), and days open (n = 7). Methodology optimized decisions based on net present value of an individual cow and all replacements over a 20-yr decision horizon. Length of decision horizon was chosen to ensure that optimal policies were determined for an infinite planning horizon. Optimization took 286 s of central processing unit time. The final probability transition matrix was determined, in part, by the optimal policy. It was estimated iteratively to determine post-optimization steady state herd structure, milk production, replacement, feed inputs and costs, and resulting cash flow on a calendar month and annual basis if optimal policies were implemented. Implementation of the model included seasonal effects on lactation curve shapes, estrus detection rates, pregnancy rates, milk prices, replacement costs, cull prices, and genetic progress. Other inputs included calf values, values of dietary TDN and CP per kilogram, and discount rate. Stochastic elements included conception (and, thus, subsequent freshening), cow milk production level within herd, and survival. Validation of optimized solutions was by separate simulation model, which implemented policies on a simulated herd and also described herd dynamics during transition to optimized structure.
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