16,037 research outputs found

    Interactive learning aided by JavaScript

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    This paper presents a case study in which some of the features of JavaScript have been employed to support the learning environment of students. Students have access to notes, self‐assessment tests, and revision crossword puzzles. JavaScript is sufficiently advanced to permit the writing of a simple nutritional analysis program. However, there are some problems caused by slight incompatibilities between browsers, but this complication is of no importance when students have access only to one browser on the network

    09-08 "Agricultural Dumping Under NAFTA: Estimating the Costs of U.S. Agricultural Policies to Mexican Producers"

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    With the opening of the Mexican economy under the North American Free Trade Agreement (NAFTA), Mexican agriculture came under new competitive pressures from U.S. exports. It was widely recognized at the beginning of NAFTA that Mexico had geographically-based comparative advantages in supplying off-season fruits and vegetables to a hungry U.S. market. NAFTA’s liberalization of agricultural trade produced the expected results, with more staple crops and meats flowing south and more seasonal fruits and vegetables flowing north. In agriculture, tariffs and quotas have now mostly been eliminated. Not so agricultural subsidies, which were left largely undisciplined by NAFTA. High U.S. farm subsidies for exported crops, which compete with Mexican products, have prompted charges that the level playing field NAFTA was supposed to create is in fact tilted heavily in favor of the United States. This paper assesses the costs of U.S. agricultural policies to Mexican producers by examining the extent to which the United States exported agricultural products to Mexico at prices below their costs of production, one of the definitions of “dumping” in the WTO. We study eight agricultural goods – corn, soybeans, wheat, rice, cotton, beef, pork, and poultry – all of which are heavily supported by the U.S. government, were produced in Mexico in significant volumes before NAFTA, and experienced dramatic increases in U.S. exports to Mexico after the agreement. We look at the years 1997-2005 because the beginning year follows both the implementation of NAFTA and the enactment of the 1996 U.S. Farm Bill, which significantly changed the nature of U.S. farm support. We estimate “dumping margins” and the costs to Mexican producers of prices driven below production costs by U.S. policies. We estimate Mexican losses for the eight products at 12.8billionoverthenine−yearperiod,morethanthevalueofMexicantomatoexportstotheUnitedStates.Cornfarmersexperiencedthegreatestlosses:12.8 billion over the nine-year period, more than the value of Mexican tomato exports to the United States. Corn farmers experienced the greatest losses: 6.6 billion, an average of $99 per hectare per year.

    04-02 "The Paradox of Agricultural Subsidies: Measurement Issues, Agricultural Dumping, and Policy Reform"

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    World trade talks have foundered recently, in part due to developing country demands that industrialized countries reduce their large farm support programs to allow poor farmers in the global South to compete more fairly. Claiming that Northern farm subsidies amount to over $1 billion a day, and that the average European cow receives more in subsidies than the nearly three billion people who live on less than two dollars a day, Southern governments, farmer groups, and international aid groups have demanded steep cuts in Northern agricultural subsidies. This paper examines the economic and policy aspects of the subsidy debate. We begin with an examination of the most widely used measure of agricultural support, the OECD’s Producer Support Estimate. We identify several important flaws in its application and interpretation as a reliable subsidy measure, highlighting the particular problems this can cause in measuring the levels of farm support in developing countries whose economies may not be fully integrated with the world economy. We then review the results of economic modeling of trade liberalization and subsidy reduction, finding that overall such measures are unlikely to raise producer prices to a sufficient degree to bring relief from alleged agricultural dumping to Southern farmers by bringing export prices above production costs. We briefly examine one alternative explanation for low commodity prices, the oligopolistic nature of agricultural trade. We conclude with an outline for policy reforms at the global and national levels to address measurement flaws, raise commodity prices, and reduce the undercutting of developing country farmers by below-cost agricultural exports from the North. Throughout, we draw on US-Mexico trade in maize as an illustrative case study. We conclude that subsidy reduction is unlikely to reduce economic pressures on Mexican maize producers from below-cost US exports, nor are such measures likely to improve the economic prospects for similar small-scale farmers growing food primarily for subsistence and the internal market. Instead, policy reforms should focus on ending agricultural dumping, reducing global commodity overproduction in key crops, and reducing the market power of agribusiness conglomerates.

    05-02 "Understanding the Farm Problem: Six Common Errors in Presenting Farm Statistics"

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    Farm statistics are regularly quoted in the press and in policy circles, often in misleading ways. This, in turn, can easily lead to mistaken policies. Two examples of misleading statistical presentation include the common refrain that farm incomes are now higher than non-farm incomes, so there is little justification, from either an equity or a social justice perspective, for funding farm programs. Another is the oft-quoted statement that 60% of farmers and ranchers never get any government support at all (Environmental Working Group 2004). It is not just the press and advocacy organizations that present data in misleading ways. Noted agricultural economist Bruce Gardner, in a recent New York Times article, argued that small family farms were thriving. He cited the slowed rates of farm loss and the growth of “non-traditional” small farms sustained by off-farm income. As he noted, 90% of farm household income is from off-farm sources, and as a result farmers now enjoy living standards above the national average (Gardner 2005). All of the above statements are true – and truly misleading. The same data present a very different story when treated more carefully. Small and mid-sized full-time family farms have incomes at or below the national average, and less than half of that income is from their full-time-farming activities. A large majority of this group, which accounts for over three-quarters of full-time farmers, receives government farm-support payments of some sort, and many depend on them to stay above the poverty line and to stay in farming. The largest group of farms in the United States today are so-called “rural residence farms,” which are indeed thriving as Gardner points out, but are doing so primarily because they are part-time operations with ample outside sources of income, from retirement or from full-time non-farm careers. This paper is intended to both highlight some of the common errors in depicting the farm sector and present a more accurate image of family farming in the United States. Based on readily available data from the U.S. Department of Agriculture’s Economic Research Service, I identify six common errors: 1. Including “Rural Residence Farms,” which represent two-thirds of all U.S. farms but do not farm for a living, in the totals for the farm sector. This leads to the misleading statement that a minority of farms get farm payments. A minority of part-time farmers gets payments, but a significant majority of full-time commercial and family farmers receives farm payments. 1 Comments and other correspondence may be directed to [email protected]. 2 GDAE Working Paper No. 05-02: Understanding the Farm Problem 2. Using averages for the farm sector as a whole when presenting income data. The accurate but misleading statement that average farm household income is 18% higher than that of the non-farm population is rooted in this error. Some 56% of full-time farmers sell less than 100,000ayearandhaveaverageincomesonly86100,000 a year and have average incomes only 86% of the U.S. average. 3. Including non-farm income in analyses of farm programs. Family farm households rely heavily on off-farm income to keep their households solvent, getting more than half their incomes from off-farm activities. On the farm they are squeezed between low prices for their products and rising prices for their inputs. 4. Ignoring the impact of land ownership. Farm payments are presented as going to the farmers themselves, but some go to landowners who do not farm the land. Roughly 45% of U.S. farm land is cultivated by operators who do not own the land. 5. Viewing the skewed distribution of farm payments in isolation from the structure of the farm sector itself. Farm payments historically have been based on production, and some still are. Others are based on acreage. Payments are mainly skewed because land and production are highly skewed. To the extent payments remain tied to either production or land ownership, they will continue to go disproportionately to the wealthiest farmers. 6. Presenting farm subsidies as going unfairly to the top 10%-20% of farmers, who don’t need it. Payments are highly concentrated, but the average full-time family farmer, with income around the national average, finds herself in the top 13 percent of payment recipients with modest payments of under 18,000. The most widely used data on individual recipients is misleading: Nearly half of the top 20 subsidy recipients in 2003 went to cooperatives, Indian tribes, and conservation trusts, and the rest went to corporations, not family-owned farms. Again, the data presented here are readily available. Hopefully, this paper will contribute to a more accurate depiction of the family farm sector and the problems it faces, and to a more grounded discussion of the policy reforms that are desperately needed in U.S. farm programs.

    05-07 "Identifying the Real Winners from U.S. Agricultural Policies"

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    In this paper, we argue that advocates for new U.S. agricultural trade policies should consider refocusing their campaigns on the corporate livestock sector rather than farmers. There is little evidence that farmers as a group are reaping significant gains from current U.S. agricultural subsidy programs, even though they are the direct recipients. Low prices and high costs have left farmers with stagnant or declining net farm incomes. Furthermore, there is little conclusive evidence that the removal of U.S. subsidy payments would significantly reduce production or raise prices, though there is significant disagreement on this point. There is wider agreement that U.S. farm policies contribute significantly to depressed prices for agricultural commodities. Among the beneficiaries of those low prices are the consumers of U.S. grains and oilseeds, notably the concentrated animal feeding operations that now dominate the U.S. livestock industry. These industrial operations get feed that is generally sold at below farmers’ costs of production. We raise two questions for future research, and provide tentative answers. First, would U.S. policies that ensure higher feed prices reduce the incentives toward concentrated feeding operations and tip the economic balance back toward diversified family farmers? Initial research suggests that the economic benefits of current policies to corporate livestock operators are significant and that their reform could contribute to structural change in the farm sector in favor of family farmers. Second, since subsidies to feed are not now treated as highly disciplined input subsidies for livestock operations under World Trade Organization rules, would a more accurate accounting bring U.S. subsidies above the maximum levels allowed in the prevailing Agreement on Agriculture? We present initial calculations that suggest such an accounting change would put the United States over is limit for 2000 and nearly over for 2001.
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