Trade Preferences and the United States: do they support development?

image: http://mattbrain.blogspot.com/2007/12/african-poverty-and-debt.html

“We believe that those who live in the most extreme poverty deserve this country’s help…the strategy to defeat extreme poverty begins with trade.”
-US President George W. Bush

...in search of evidence of the utility of trade preference programs as measured by their usefulness to world's poorest economies

Prepared for Emily Alpert, Trade Policy Advisor, Oxfam America
By Justin Velez-Greenhalgh (2008)

U.S. Trade Preference Programs: How Well do they work?
(Written Testimony by Katrin Kuhlmann, Senior Vice President, Global Trade Program,

Women’s Edge Coalition – Before the U.S. Senate Finance Committee – May 16, 2007)

This testimony, given by the above referenced source, details the importance of maintaining and improving US trade preference programs. Kuhlmann’s point of view is that the Generalized System of Preferences (GSP) and the myriad of regional preference programs help to bolster the socioeconomic position of women, and to address development concerns in least developed countries (LDCs). She cites one study that found that countries benefitting from GSP preferences increased exports of products eligible for GSP treatment by 8% annually. She also cites other sources, claiming that the Caribbean Basin Economic Recovery Act (CBERA) has led to increased investment, income growth, and export diversification in Central America. Another regional program, the African Growth and Opportunity Act (AGOA), according to the testimony, is said to have generated 45,000 jobs in Swaziland, 26,000 in Lesotho, and 30,000 in Kenya. Additionally, Kuhlmann claims the jewelry industry in India has added 325,000 jobs since the extension of the GSP in 2001.

The testimony also cites the passage of trade bill (HR 6406) in December 2006 as an important step in the proliferation/continuation of trade preferences for poorer countries. Kuhlmann argues that another important component of making trade preferences as useful for beneficiary countries as possible is the continuation of competitive need limit (CNL) waivers. CNLs are used when exports rise above a certain dollar limit. The waivers allow countries to continue the duty free exportation of products even when the CNL has been surpassed.

Katrin Kuhlmann’s testimony addresses the need to make trade preference programs less restrictive in order to maximize economic opportunities for beneficiary countries. One important issue is coverage. Approximately half of the GSP-eligible countries have fewer than 33% of their exports covered. Another problem faced by poorer countries is that many of their economies are commodity (agricultural) and textile dependent. Clothing and agricultural items tend to be excluded from preference programs, or are subject to complex rules of origin.

Kuhlmann’s testimony leads to 4 major policy recommendations regarding US trade preference programs:

1. 100% duty-free market access for all sub-Saharan countries currently covered under AGOA
2. Special benefits that address unique African needs (AGOA plus) – essentially provide duty-free access for all products for sub-Saharan Africa, with an emphasis on infrastructure development and assistance
3. Consolidation of all US trade preference programs into 1 program with one 1 set of eligibility criteria and rules of use
4. Provisions for trade capacity building assistance – ie. Management training, telecommunications and financial services, and tools designed to help LDCs navigate complicated trade rules.

Quantifying the Value of U.S. Tariff Preferences for Developing Countries
World Bank Policy Research Paper 3977, August 2006 (this paper if a reflection of the work and research of the below referenced authors, and not necessarily a policy declaration on the part of the World Bank)
(Written by Judith M. Dean and John Wainio)

This paper is a strong attempt to provide useful data in the debate over trade preference erosion and the extent to which reduction and/or elimination of preferences for developing countries has an economic/developmental impact. According to its abstract, the primary intent of the paper “is to improve our measures of the size, utilization and value of all US non-reciprocal trade preference programs…” Some facts mentioned in the paper are that US regional programs cover a significant amount of beneficiary countries’ exports, are highly utilized by beneficiaries, and have low tariff preference margins. The margin of preference is the difference between the preferential tariff and the Most Favored Nation Tariff (MFN tariff). Basically, where possible, LDCs use what advantages are available to them. “High utilization of preferences has occurred despite evidence that preference margins are generally low.” Limitations of preference programs like the GSP are tariff-rate quotas (TRQs) imposed on agricultural products (meaning duty-free access is not available on products once they exceed the quota), periodic expiration, loss of eligibility due to reaching the World Bank’s high income country category is reached, and competitive need limitations.

This paper, however objective, does note some obvious advantages of regional preference programs over the GSP, specifically the African Growth and Opportunity Act (AGOA). AGOA allows beneficiary countries duty-free access on a larger number of products than does the GSP, and exempts participating members from the competitive need limit. Also noted is the Caribbean Basin Trade Partnership Act (CBTPA), which is an extension of the Caribbean Basin Economic Recovery Act (CBERA), and allows preferential duty treatment on apparel and petroleum products. CBTPA also allows duty-free access for apparel imports assembled in CBERA countries from fabric made and cut in the United States. Yet another preferential program whose benefits exceed those of the GSP is the Andean Trade Preference Act (ATPA), which covers more products, does not have the GSP competitive need limitations, and does not have provisions that graduate participating countries out of eligibility. ATPA preferential treatment includes import –sensitive items such as petroleum, apparel, footwear, and tuna in foil packages.

Interestingly, in 2003, “the US imported about $19.6 billion of non-agricultural products from CBTPA countries, 50% of which was apparel. The conclusion? There is high utilization of regional preference programs. The GSP tends to be underutilized, mostly because the regional programs provide greater advantages to participating countries. Utilization, of course, is representative of the percentage of eligible imports entering the US under preference programs. “The regional preference programs are particularly important for countries in the Caribbean and Andean region, with almost 50 percent of US agricultural imports from CBERA countries and 40 percent from ATPA countries entering the US under these programs in 2003.”

Finally, the study finds that margins of preference (the extent to which preferential tariffs are below MFN tariffs), are not very large. 5.4% is the average preference margin across 101 countries, according to the report. “Few countries exported a product-mix which faced an average nominal tariff preference greater than the 6.4% average tariff across all products eligible for duty-free treatment.” This information might lead one to conclude that since regional preference programs tend to be more user-friendly than the GSP, it might be beneficial to rework some of the rules that apply to ATPA, AGOA, CBERA, etc. to increase preference margins offered to least developed countries, and thereby aid in their further development of economic infrastructures by helping to support export activity. Overall, the article finds that US preference erosion might not have a large impact on development, but that the economic impact on beneficiary countries could still be significant. Because the value of tariff preferences can comprise anywhere from 5 to 15% of a country’s total dutiable exports, there could be an argument that erosion reduces the competitive advantage of several smaller economies.

Erosion of trade preferences in the post-Hong Kong framework: from TRADE IS BETTER THAN AID to AID FOR TRADE

United Nations Conference on Trade and Development
A study carried out under the supervision of Habib Ouane, Director, Division for Africa, Least Developed Countries and Special Programmes (ALDC) and prepared by Stefano Inama, with inputs from Marcel Namfua, Interregional Adviser to ALDC, Craig Van Grastek, and Simon Evenett, University of Saint Gallen
United Nations, New York and Geneva, 2007

This study attempts, as have other recent, similar studies, to address the issue of trade preference erosion, and elucidate the applicable impacts for both developed and least developed countries. The study also hones in on how preference erosion might cause export reduction on the part of LDCs that have successfully utilized favorable agreements with developed countries. Aid for Trade, as a relatively new initiative, is discussed as one possible method of compensating LDCs for losses incurred by preference erosion. The paper acknowledges that such erosion does have significant poverty implications for some countries, and can deeply affect household income, especially the monetary intake of those working in industries that benefit from special trade arrangements.

The study explains how preference erosions might be quantified. For example, if the Most Favored Nation (MFN) duty is 10%, and by special agreement an LDC is allowed entry of certain goods tariff free, then the preference margin is 10%. If that LDC rate remains at zero, but the MFN rate is lowered (liberalized) to 6%, then a preference erosion of 4% has occurred. Additionally, the paper argues that when different countries compete in the same product market, the importer has an incentive to favor the country receiving preference since imports originating there face duties that are less than the MFN rate. Erosion reduces the incentive to source from beneficiary LDCs in certain cases. Why does this incentive become reduced? The paper states that “field experience” teaches us that is the importer that pockets the tariff revenue forgone. Some developing country exporters, after having developed a working relationship with an importer, negotiate a share of that tariff revenue forgone.

The paper details many of the concerns addressed and developments of the World Trade Organization’s (WTO) Sixth Ministerial Conference, held in Hong Kong. It was there that the old paradigm, “trade is better than aid,” was, for all intents and purposes, reversed in favor of new thinking, “aid for trade.” According to the report, preference erosion, most especially for LDCs, is an issue that has been recognized both by the LDC duty-free, quota-free (DFQF) and Aid for Trade Initiatives. MFN trade liberalization and trade preference erosion are opposing concepts because a reduction in MFN rates comes at the expense of preference margins enjoyed by poorer economies. Some developing countries, evidently, are expressing concern because they feel an expansion of competitive opportunity afforded to LDCs will weaken their trading positions.

As an example of how trade preference erosion might be harmful to a poorer country, Lesotho is cited as an example where trading under AGOA has attracted “foreign direct investment (FDI) by some Asian companies in garment factories to develop supply capacity and exploit a substantial preferential margin.” Without the exploitation of such preferential treatment, a country like Lesotho could suffer developmentally in an era of preference erosion. It is, however, noted that in the majority of cases trade preferences alone do not attract FDI and create export diversification.

The study “has examined the issue of preference erosion on a tariff-line basis to identify the countries and product pairs most likely to be affected. It has suggested that although relatively small in absolute terms, the trade volumes affected by erosion may have a significant impact on small-scale industries and agricultural and fishery communities, with poverty implications.” To address the issue of preference erosion and market liberalizations, two main courses of action were identified in the paper:

1 Addressing preference erosion through the EIF and Aid for Trade Initiative – “The integrated Framework (IF) was launched in October 1997 at the WTO High Level Meeting on Integrated Initiatives for LDCs’ Trade Development, as a follow-up of the Plan of Action in favour of the least-developed countries (LDCs), adopted at the First WTO Ministerial Conference in Singapore in 1996. Its objective was to coordinate the existing trade-related capacity-building programmes of the following six international organizations: the IMF, ITC, UNCTAD, UNDP, the World Bank and WTO to assist LDC governments in integrating their trade-related policies into their national development strategies and thus to be more active in the multilateral trading system.”[1] Members voted to endorse an enhanced version of the IF at the Hong Kong Ministerial Conference in December 2005. In June 2006, the task force on the EIF submitted proposals on securing additional funding, strengthening in-country management capacities, and implementing/monitoring EIF processes. Of course, in terms of Aid for Trade, countries certainly need help addressing supply-side constraints (ie – natural disasters, insufficient production capacity, and outrageous costs of transportation) that prevent them from participating effectively in international markets, and to help them contend with the effects of trade liberalization.

2 Extending true market access and reform rules of origin – “WTO member should provide meaningful and comprehensive trade preferences to LDCs, as well as the reform of existing rules of origin. More advanced developing countries should also be part of this effort. The multilateral legal framework of trade preferences needs to be revisited to impart transparency and stability to trade preferences.”

Nickel and Diming the Poor
U.S. Implementation of the LDC Initiative
By Viji Rangaswami
Carnegie Endowment for International Peace, Policy Outlook, Trade Equity & Development Project – July 2006

This article is critical of the apparent double standard involved when the US, one hand, expresses a greater desire for more open access for its farm and manufactured exports, while not, at the same time, doing more to open its markets to the word’s poorest countries. The article sets the parameters, based on UN guidelines, in terms of what qualifies a nation as a least developed country. First, it must have a very low per capita income (probably below 750.00 USD). Second, its human resources must be substandard in that its education system is weak or underdeveloped and the health of its people is not well provided for by some king of strong hospital/medical system. Thirdly, an LDC is economically vulnerable by virtue of its absence of export diversification, inability to contend with natural disasters, as well as a lack of modern services. According to the article, the 50 LDCs combined account for around just 1.1% of total United States imports.

One interesting prediction cited in the article is that, based on information from the International Food Policy Research Institute, the LDCs as well as 8 lower income countries (LICs) would see real income increase by 7.01 billion USD if all rich countries fully opened their markets to LDC exports as part of the Doha Round. Additionally, the 2001 Doha Ministerial Declaration is cited as evidence of the recognition that instability and lack of economic development in the poorest countries (especially as there is a link between instability and terror activity) must be addressed:

“We recognize that the integration of LDCs into the multilateral trading system requires meaningful

market access, support for diversification of their production and export base, and trade-related

technical assistance and capacity building…We commit ourselves to the objective of duty-free, quota-

free market access for products origination in LDCs.”

Interestingly, the author of this article also claims that the US has erred by tying the completion of the Doha Round to its obligations under the poor country/LDC initiative. It’s felt that such linkage would shorten the period of time during which poor countries would enjoy preferential access. The reason is that when the Doha Round concludes, tariffs will be substantially reduced for all countries in the WTO. At that point, the margin of preference enjoyed by developing and least developed countries will also be reduced considerably. This period of time where LDCs are supposed to be afforded preferential access to developed countries markets is thought to be sufficient to improve their methods of competitiveness. Secondly, the author argues the lack of fairness involved when disagreements between highly powerful entities like the United States and the European Union cause stalls in Doha implementation and further complicate problems for LDCs.

Yet another avenue of interest explored in this article is the US claim that new preferences for poorer countries not already included in the system of preferences “will require careful evaluation of its impact on and relationship to current tariff preference programs, such as the African Growth and Opportunity Act (AGOA) and the Caribbean Basin Initiative (CBI).” To combat this though process, an IFPRI study is cited, which shows that sub-Saharan LDCs would still benefit if all LDCs received 100% duty-free, quota-free (DFQF) trade treatment. Malawi, for example, would be expected to increase exports by five times with full implementation of the LDC initiative.

As far as development is concerned, there is strong concern with regard to a loophole in the Hong Kong commitment. Evidently, the US has interpreted the commitment such that they may exclude up to 3% of potential exports from poor countries. That exclusion could amount to as much as 300 tariff lines, or practically all LDC exports. Again, accordingly to IFPRI, that’s about a 6 billion USD difference in real income gains between what could occur with 100% duty free treatment as opposed to 97% duty free treatment for LDCs.

Finally, the paper is concluded with 5 major recommendations:

1. Early Implementation – it is argued that a show of good-faith effort to implement the poor countries initiative could garner good will, and make other countries more willing to negotiate to our favor regarding other matters.
2. Allow 100% Access – the author maintains that the United States ought to provide complete duty-free, quota-free excess to all LDC exports. An exclusion of 3% of products (approximately 330 tariff lines) could drastically reduce potential economic benefits to those who need it most.
3. Allow 100% Access Plus for Sub-Saharan Africa – for one, as noted earlier, an IFPRI study concludes that improved market access for all LDCs does not come at the expense of sub-Saharan Africa. Furthermore, it is argued that disincentives under current trade preference programs are more problematic than previously thought. For example, limitation on the amount of sub-Saharan apparel that can be shipped into the US diminishes the incentive of outside businesses to invest in the productive capacity of African exports. Additionally, requiring that African producers utilize either US or African fabrics makes the situation difficult lower-priced and/or higher quality fabrics may be available from Asia. Non-tariff barriers, such as US sanitary and phytosanitary standards. It is suggested that USDA’s Animal and Plant Health Inspection Service (APHIS) be tasked with attacking the problems African farmers face in terms of acquiring approval for US markets.
4. Ensure Simple ROOs – the rule of origin as dictated by the existing US Generalized System of Preferences, which requires that products “be substantially transformed in a beneficiary country, and that at least 35 percent of the value of the product originate a beneficiary country, is one example of a good, straightforward, easy to meet rule of origin that facilitates trade.” More flexible cumulation rules are called for in the article – cumulation allows inputs from different countries whose eligibility falls under the same program to be counted in the value-added threshold. In terms of an African plus type initiative, it might be beneficial something like a 25% value added rule for sub-Saharan countries.
5. Expand the List to Include Other Low Income Countries – Kenya, Pakistan, Sri Lanka, and Papua New Guinea are just a few countries not classified as LDCs, but still plagued by epidemics like HIV/AIDS, natural disaster, and lack of export diversification.

[1] Agency for international trade information and cooperation – AITIC’s EIF page – http://www.acici.org/aitic/eif/Intro.htm

Federal Crop Insurance,etc. from the Farm Bill debate...

Federal Crop Insurance Act, Farm Safety Net Improvement Act, and various RCCP Proposals

an abbreviated analysis prepared for Emily Alpert of OxfamAmerica

(for the entire document, please email: velez_greenhalgh@msn.com)

prepared in August 2007

The Federal Crop Insurance Act (7 U.S.C. 1501 et seq.) (FCIA) states as its purpose the promotion of “national welfare by improving the economic stability of agriculture through a sound system of crop insurance and providing the means for the research and experience helpful in devising and establishing such insurance.” In section 503 of the FCIA, the Federal Crop Insurance Corporation is created as part of the United States Department of Agriculture as the agency responsible for carrying out the title. Additionally, the FCIA states under section 508 that “if sufficient actuarial data are available…the Corporation may insure, or provide reinsurance for insurers of, producers of agricultural commodities grown in the United States under 1 or more plans of insurance determined by the Corporation to be adapted to the agricultural commodity concerned. To qualify for coverage under a plan of insurance, the losses of the insured commodity must be due to drought, flood, or other natural disaster (as determined by the Secretary).”

With regard to pricing, the Federal Crop Insurance Corporation “shall establish or approve the price level…of each agricultural commodity for which insurance is offered.” As set forth under the FCIA, the expected market price is not to be less than the projected market price of the commodity. Authorized pricing approaches under the law include but are not limited to the following: expected market price may be the actual market price at the time of harvest; or expected market price, specifically for revenue and similar plans, may be the actual price of the commodity.

The Farm Safety Net Improvement Act of 2007 (S 1872 IS) proposes to incorporate processes established under the FCIA in the creation of a new revenue counter-cyclical program (RCCP). Under the proposed legislation, RCCPs would be triggered if “the State revenue from the crop year for the covered commodity in the State…is less than the revenue counter-cyclical program guarantee for the crop year for the covered commodity in the State…” Furthermore, the Farm Safety Net Improvement Act calls for State revenue to be determined by taking the actual State yield for each planted acre for the crop year, and multiplying that number against the RCCP harvest price for the crop year. Each state’s yield would be determined by taking the amount of the covered commodity produced in the State, and dividing that number of acres in the State planted to the covered commodity. Based on those underlying parameters, the RCCP guarantee will be 90% of the expected State yield multiplied against the RCCP pre-planting price. The legislation specifically calls for the pre-planting price to be the harvest prices established under the Federal Crop Insurance Act. According to Senator Durbin’s proposed legislation, “the revenue counter-cyclical program pre-planting price for a crop year for a covered commodity shall equal the average price that is used to determine crop insurance guarantees for the crop for the covered commodity under the Federal Crop Insurance Act…” RCCP pre-planting prices would be prevented by law from decreasing or increasing more than 15% from the previous year.
According to the American Farmland Trust, the “RCCP replaces existing counter-cyclical payments (CCPs) and loan-deficiency payments (LDPs) with a state-level revenue protection program. Congressional Budget Office (CBO) estimates indicate the cost saving from integrating crop insurance and replacing LDP’s, and CCP’s fully offset the cost of the RCCP making it effectively cost neutral.”[1] A search of the CBO cost estimates search engine, however, did not reveal any publicly-available assessments of taxpayer cost for Sen. Durbin’s amendment (S. 1872). RCCP payments, if they are required to be made for crop years 2008 through 2012 under the Farm Safety Act, would be calculated as the product derived from multiplying the following 4 elements:

The difference between the RCCP guarantee for the commodity in the State and the actual State revenue for the crop year
The acreage planted to the covered crop for harvest
The quotient derived by taking the farm’s production history and dividing that number by the anticipated State yield
90%

As far as how the WTO might view RCCPs, there is still question, largely depending on how Congress acts, as to whether they will be rated Green or Blue Box. The green box, of course, allows disaster payments and income safety nets – but the WTO might still find them more Blue Box appropriate. The Institute for Agriculture and Trade Policy, when reviewing RCCP as national yield-based program, stated that “[w]here the RCCP Green Box notification could be challenged as WTO illegal is at the juncture of payments claimed as relief from officially declared natural disasters…and income support payments to mitigate an income collapse resulting from policy decisions…WTO members are allowed to subsidize crop risk insurance premiums for producers “for relief from natural disasters”…and to make payments for “income safety nets” …But it would be difficult to verify, and hence to notify, to the WTO what part of RCCPs corresponded to natural disaster relief payment and what corresponded to an income loss that could result from a policy or neglect to administer a policy.”[2] Of course, the WTO is naturally concerned about US subsidies and the extent to which USDA programs distort trade and/or encourage export dumping. Interestingly enough, the CBO, in its most recent budget outlook, stated, “the sharp rise in some commodity prices (especially for corn) is expected to reduce spending for agricultural subsidies by $8 billion in 2007.”[3] Also notable is a CBO report that estimates, “the static welfare effect on the United States of a global 33 percent reduction in all tariffs and subsidies in the agricultural sector would be a loss of $11.1 billion, or 0.122 percent.” The study concluded, however, the negative welfare effect involved zero harm to the US agricultural industry, but implied shrinkage in the manufacturing sector caused by agricultural expansion drawing away capital, labor, and resources.[4]

Originally, the National Corn Growers’ Association proposed an RCCP plan that was based on county, not state yields. Their intent, of course was to propose the creation of a program that more adequately reflected local agricultural climates. Under their plan, the RCCP target revenue would have been the product obtained by multiplying a county’s trend yield by the pre-planting harvest price by 95%. Interestingly, the county trend yield would have been based on a regression formula, represented by the following (utilizing USDA county per acre yield data from 1980 through 2005):
yield/planted acre = Ac + Bc X year + error (Ac and Bc represent estimated parameters)
In the instance of corn, the NCGA proposal bounded the RCCP price between $2.40 and $3.20/bushel. “The RCCP cup (or floor) price of $2.40 per bushel is based on setting marketing loans rates equal to 95% of the 2000-04 Olympic average of season average price ($2.01 per bushel for corn) and a price basis of $0.39 per bushel to account for historical differences between seasonal-average and pre-planting revenue insurance prices.” The RCCP cap price was achieved by performing simulations to estimate RCCP program costs when the cap is set as a ratio of the cup prices. “The simulations showed that when the RCCP cap prices are set as 1.333 times the RCCP cup prices, the projected aggregate costs for RCCP are approximately $500 million per year above the Congressional Budget Office’s March 2007 farm bill spending baseline.”[5] Basically, the NCGA has argued revenue based countercyclical payments – based on county-level triggers – would be more cost effective than the Farm Bill’s current commodity support programs because the government makes, or can make, subsidy payment to farmers even in a crop year when their revenue is stable. Additionally, their argument is that revenue is a better target than yield because farmers still need financial protection when prices are high and yields are low. Still yet, there are some concerns about the NCGA proposal that have been expressed by others. To some, it’s not abundantly clear whether the Individual Revenue Insurance (IRI) component, which represents 1 tier of the NCGA’s 2 tier plan, would be required and whether producers would be able to choose crop insurance policies available other than crop revenue insurance-like IRI. Some researchers have argued that “[w]hile the concept provides a greater safety net, insuring revenue would likely create higher federal budget expenditures and increase the uncertainty associated with budget exposure for commodity program costs compared to existing CCPs. It is possible that some of this increase could be offset as the design of the two-tier program could relieve some of the usage and, therefore, cost of federally subsidized crop insurance.”[6]

Of course, the National Corn Growers Association wasn’t the only source of a type of revenue-protecting safety net in advance of this year’s Farm Bill debate. The US Agriculture Secretary proposed a Counter-cyclical Revenue Program (CCR), which also would have served as a replacement for the current counter-cyclical payment program. The Secretary’s proposal, unlike that of the NCGA’s and that of Sens. Brown and Durbin, envisioned CCR payments that would be triggered when national actual revenue falls below national target revenue. Also unlike the Brown/Durbin amendment, the Secretary’s program would be based on 85% of CCP payment yields multiplied against a base acres calculation, as opposed to the Farm Safety Net Improvement Act’s revenue guarantee, which would be 90% of the expected State yield for the covered commodity multiplied against the RCCP-defined pre-planting harvest price. The national target revenue would be given by the following formula:
NTR = {2007 target price – 2007 direct payment rate} X 2002-2006 Olympic National Average (note: the 02 through 06 average used in the NTR formula would be fixed for the entire life of the new Farm Bill)
The national actual revenue would be given by the following formula:
NAR = National Average Yield X Maximum of Season Average Market Price of Loan Rate
Furthermore, a CCR payment (triggered when national actual revenue falls below national target revenue), would be calculated by completing the following formula:
CCR Payment = NPR (national payment rate) X CCP Payment Yield X Base Acres x 0.85
(note: the NPR would be national target revenue minus national actual revenue, then divided by CCP payment yield)
According to some researchers on the subject, “[i]n their comparison of the CCR to the CCP, Richardson and Outlaw (200) showed that the CCR would pay about $1.5 billion less than the CCP over 2008-2016, with all of the savings by CCR coming in 2013-2016.” The same researchers found that crops with higher projected prices (wheat, corn, sorghum, barley, oats, and soybeans) were less protected by CCRs than by CCPs. They also noted that CCPs have built-in maximum payment rates, whereas such is not the case with CCRs.[7]
Risk Reduction, Crop Insurance Policies, Yield/Market Trending, and Production Impact
As is known, the USDA’s Risk Management Agency (RMA) provides management services and actuarial data for crop policies that fall under the following categories: Multiple Peril Crop Insurance (MPCI), Crop Revenue Coverage (CRC), Group Risk Plan (GRP), Income Protection (IP), Group Risk Income Protection (GRIP), or any other Federal Crop Insurance Corporation reinsured product providing indemnity for farmers against revenue and income risk factors. It should also be known that Revenue Assurance (RA) policies do serve as an alternative to MPCI, CRC, GRP, IP, and GRIP policies. “RA offers coverage levels of 65% through 85% for basic and optional units…80-85% coverage levels are available only in counties and on crops where MPCI allows 80-85% coverage levels and are not available on basic or optional units for cotton. The crop per-acre revenue guarantee may vary; however, the coverage level percent will be the same for each crop unit. For an enterprise unit, the crop per-acre revenue guarantee will be the same for all acres in the enterprise unit. The coverage level will be 65% through 85%...For the whole farm unit, the per-acre revenue guarantee will be the same for all insured acres. The level of coverage will be from 65% through 85%...”[8] As the proposed safety net introduced for Senate deliberation by Senators Durbin and Brown bears striking similarities to the current revenue assurance framework, it should be noted that current RA policies protect farmers from low price and low yield market circumstances, or perhaps, a combination of both factors. Major factors in RA policies as they are currently structured are yield history/average production history, revenue percentage coverage levels elected by individual farmers, projected harvest prices, and fall harvest prices.

One interesting note regarding revenue assurance policies under their current structure is that according to underwriting guidelines indemnities may not be paid to producers as a result of high price/low yield and/or low price/high yield environments. Now there is some logic in this rule – farmers, in many cases, can survive a crop year marked by low prices and high yields with their revenues intact. However, high price/low yield is a problem for farmers – national and regional market circumstances can be drifting in their favor, but with low yield, revenue drops markedly. As an example, current revenue assurance underwriting guidelines state, “[w]hole-farm units may not receive a payment if your corn revenue is low and your soybean or spring wheat revenue is high or vice versa.”

Senator Durbin, for his part, has made an attempt to address gaps where the current crop insurance environment performs incongruently with America’s subsidy framework for covered commodities. The American Farmland Trust, for example, is behind the crop insurance/RCCP integration strongly. Their position is that as a result of RCCP promulgation, “[p]rivate revenue insurance would operate much like it does currently. However, it would only cover a farmer’s individual revenue loss – for example from localized flooding or drought – if it were greater than the national loss. Because crop insurance only takes on individual risk, higher levels of protection would be available to farmers at a lower premium. Integration means a more efficient system, allowing the government to capture savings from crop insurance and use taxpayer money more wisely.”[9]

To read the proposed Farm Net Safety Improvement Act, one will find that there is reliance on the pre-planting or projected harvest price method. The Act calls for the RCCP guarantee for a crop year to be the expected State Yield for each planted acre of the covered commodity multiplied against the RCCP pre-planting price for the crop year for the covered commodity. One study on integrated production and price risk management, with specific regard to corn and soybean futures contracts, found that over the course of the 22-year period ending in the 1996-1997 crop year, pre-planting prices exceeded harvest prices in about 67% of the years for corn and 75% of the years for soybeans. Although that pattern suggests the pre-harvest pricing methods might ultimately prove beneficial to farmers, there are some interesting caveats. According to the study just mentioned, “where a high price/yield correlation exists, producers who price before harvest with fixed-price commitments may have greater exposure to production risk than with harvest sales. Increased risk occurs because short hedges work effectively as a risk-management tool only when value changes in the short futures position are offset by approximately equal and opposite value changes in the long cash position, i.e., the grain being produced.” To that end, the study suggests, “[t]he crop insurance needed for maximum effectiveness in managing production risk with pre-harvest pricing would be a type valuing lost production as its replacement cost.”[10] Keep in mind, short hedge positions are financial instruments that protect farmers from potential decreases in their cash positions at the time of harvest – if the cash price for a commodity for which a farmer has short hedge position is significantly higher than the agreed-upon hedge price, the farmer has then incurred potentially significant opportunity costs. For that reason, short hedges for farmers work if long hedge positions for commodities purchasers decline in the same marketing season, meaning that prices decline below the long position and decrease or eliminate any potential savings the holder of the long hedge might have.

The integrated production and price risk study previously mentioned also produced some interesting results when it came to mean net return over total economic cost and mean net cash flow regarding corn and soybean farms in Ohio between 1985 and 1997. The study evaluated farmers under three categories: cash renter, buyer/renter, and owner. If one were to take this study as one small snapshot of the virtues of pre-harvest risk management strategies, coupled with crop insurance instruments, the conclusion would be that pre-harvest pricing holds sound economic benefits for farmers. Multiple peril crop insurance (insures yield per acre) and crop revenue coverage (similar to revenue assurance policies in that protection is provided against low price or low yield, or a combination of both factors) added some benefit either as independent strategies, or coupled with pre-harvest pricing.

Clearly, the intent of the Farm Safety Net Improvement Act is to provide a better-functioning system for farmers to protect their revenue, while not, at the same time, drastically increasing cost to the American taxpayer. As already discussed, even without Sen. Durbin’s proposed legislation, farmers have options to reduce a variety of risk types. One study done by the USDA’s Economic Research Service concluded, “the degree to which strategies, such as forward contracting or hedging, reduce income risk depends on yield variability, the correlation between price and yield, and whether or not the crop is insured.” The study looked at four hypothetical corn farms in the following counties in the United States, and estimated risk: Iroquois County, Illinois – low yield variability and strongly negative yield-price correlation (low yields, high prices, or vice versa); Anderson County, Kansas – high yield variability and high yield-price correlation (high yields, high prices or low yields, low prices); Lincoln County, Nebraska – low yield variability and weak yield-price correlation; and Pitt County, North Carolina – high yield variability and low yield-price correlation. The findings for these counties were interesting. For example, farmers in the Corn Belt (ie – Iroquois County) seemed to benefit from the inverse price/yield relationship in a year of low output because of increased prices. Also, bumper crops tended to be additional protection in low price years. As far as hedging expected output, that strategy seemed to work best in Lincoln County, “where the probability of income below 70 percent of expected return is reduced from 8 to 2 percent.” Hedging seemed to be optimal in Lincoln County because of more consistent outputs and relatively uncorrelated prices and yields. As for Anderson and Pitt Counties, the study found there was greater revenue risk present than the other counties when no strategy was in place (ie – cash sales at time of harvest). For one, those two counties have a higher yield variability, so farmers can suffer without protections against weather problems or the benefit of field irrigation. Because Anderson and Pitt Counties are yield variable and have some degree of yield-price correlation, hedging may not offer the best protection. “Crop insurance is generally more effective than hedging in reducing the risks of vey low revenues across the four counties. When crop insurance alone is used by a producer, the probabilities of very low revenue is reduced greatly in all counties except Lincoln County, Nebraska.” In Lincoln County, the widespread use of irrigation actually tends to take the place of insurance policies. Nonetheless, the study, in part, concluded, “[c]rop insurance reduced risk more than forward pricing in most areas, but the greatest risk reductions are obtained by combining insurance and forward pricing.”[12]
Regarding revenue insurance, the same ERS study mentioned above found that revenue insurance (as it was assumed for purposes of the study) provided an intra-seasonal guarantee on the basis of farm yields and futures prices. Another conclusion was the “risks in farming would be substantially less if outputs could be insured and priced forward over periods more nearly matching the expected life of the specialized machines and equipment required for production.” At the same time, crop insurance was determined to be potentially useful because yields change gradually on a farm’s yield history, and it this easier for a producer to anticipate his/her coming season’s output. One final compelling finding of the study was that if one is looking at risk reduction from year to year, not just within the year, forward pricing (forward contracts are similar to short hedges, but reduce basis risk, which occurs when the cash price is less than the commodities futures market price over a series of years[13]) before planting tends to be more stable than harvest prices for crops that can’t be stored between years.[14]

As far as the growth or prevalence of crop insurance in the United States, the number of net acres insured in 2005 was 245.84 million. Total premiums in that year were $3.95 billion. Premium subsidies were $2.3 billion in 2005, and are expected to trend upward to $2.9 billion in 2015. To note, there were no major crop disasters in 2004 or 2005, and one study of loss ratios (which predict or assess the actuarial fairness of insurance premiums) found that “federal crop insurance will meet the loss ratio targets set by Congress.” Total obligations (indemnities paid, delivery expenses, administrative and operating expenses, commissions, etc.) were projected at $3.5 billion for 2006, and expected to reach more than $5 billion by 2008. Other predictions and assessments relating to insurable crops were also made. For cotton, the actual yield is expected to go from around 824 lbs/acre in 2005/2006 to 836 lbs/acre in 2015/2016 (with some up and down variation between the years), with gross market revenue (USD/acre) expected to increase to 544.86 by the 2015/2016 season. For soybeans, the actual yield is expected to go from 43.3 bu/acre in 2005/2006 to 44.0 bu/acre in 2015/2016 (with some up and down variation between the years), with gross market revenue (USD/acre) expected to increase to 243.46 by the 2015/2016 season. For wheat, the actual yield is expected to go from 42.0 bu/acre in 2005/2006 to 44.5 in 2015/2016 (with no up and down variation predicted for the interim years), with gross market revenue (USD/acre) expected to increase to 167.79 by the 2015/2016 growing season. For rice, actual yield is expected to go from around 6636 lbs/acre in 2005/2006 to 7427 lbs/acre in 2015/2016 (with no up and down variation predicted for the interim years), with gross market revenue (USD/acre) expected to increase to 659.64 by the 2015/2016 growing season. And for corn, the actual yield is expected to go from around 147.9 bu/acre in 2005/2006 to 164.3 bu/acre (with little to no variation in the interim), with gross market revenue (USD/acre) expected to grow to 409.39 by the 2015/2016 season.[15]
Another study evaluating the potential impact of crop insurance on US production trends revealed some insight that might be useful in evaluating how an integrated RCCP/crop insurance approach might influence the agricultural industry. The market impacts of crop insurance were analyzed using a POLYSYS-ERS simulation model for an average representative year. With regard to wheat production, “[t]otal…acreage expands about 300,000 to 350,000 on average, roughly a 0.5 percent increase in acreage compared with a scenario of no crop insurance subsidies. Total acreage for all eight crops expands about 900,000 acres, so that wheat accounts for about one the total increase.” The study, however, did not find an increase in wheat acreage in all US regions. “Wheat acreage does not increase in all regions in response to the premium subsidies…While premium subsidies have the direct effect of increasing net returns from wheat production, the resulting higher production reduces market prices, partially offsetting the incentive to expand production in subsequent years. In addition, subsidized insurance products are also available for competing crops, creating incentives to increase their production, with subsequent reductions in prices.”[16] Thus, if subsidized crop insurance premiums add to farming net returns and encourage increased production in some cases but not all, it might be argued that the integrated RCCP/crop insurance approach might have some impact on production incentive for farmers, but with multiple crops considered covered commodities, the market overall will probably ebb and flow, encouraging farmers not so much to overproduce, but to follow educated predictions in making planting decisions.

HARVEST PRICES
Pre-planting and/or projected harvest prices are calculated and used by FCIC/RMA-approved insurance carriers according to certain government guidelines. The following table details accepted methods for calculating projected harvest prices, which are used in determining per-acre revenue:

Ø CORN – cancellation date prior to March 15 – projected harvest is the simple average of the final daily settlement prices for the first ten trading days in February for the Chicago Board of Trade (CBOT) December futures contract
Ø CORN – covered states with a March 15th cancellation date - projected harvest price is the simple average of final daily settlement prices in February for the (CBOT) December corn futures contract
Ø SOYBEANS – cancellation date prior to March 15 – projected harvest price is the simple average of the final daily settlement prices for the first ten trading days in February for the CBOT November futures contract
Ø SOYBEANS – covered states with a March15th cancellation date – projected harvest price is the simple average of the final daily settlement prices in February for the CBOT November futures contract
Ø SPRING WHEAT – projected harvest price is the simple average of the final daily settlement prices in February for the Minneapolis Grain Exchange (MGE) September hard red spring wheat futures contract (durum wheat can be insured as hard red spring wheat under current underwriting guidelines)(spring wheat price may be used both for durum and Khorasan wheat)
Ø WINTER WHEAT - projected harvest price for Idaho, Indiana, Kentucky, Michigan, Ohio, and Tennessee is the simple average of the final daily settlement prices from August 15 to September 14 for the coming year’s CBOT July soft red winter wheat futures contract
Ø WINTER WHEAT – projected harvest price for Arkansas, Colorado, Iowa, Kansas, Missouri, Montana, Nebraska, Oklahoma, and South Dakota is the simple average of the final daily settlement prices from August 15 to September 14 for the coming year Kansas City Board of Trade July hard red winter wheat futures contract
Ø COTTON - projected harvest price is the January 15 through February 14 harvest year’s average daily settlement price per pound for the New York Cotton Exchange December cotton futures contract rounded to the nearest whole cent (RMA, as of 2005, pledged to release the cotton projected harvest price by February 20 of each harvest year)
Ø RICE - projected harvest price for rice in all covered states is the January harvest year’s average daily settlement price per pound for the harvest year’s CBOT November rough rice futures contract, rounded to the nearest 1/10th of 1 US cent

SOURCE: USDA Risk Management Agency
Revenue Assurance
Underwriting Rules: Feed Barley, Malting Barley, Canola/Rapeseed, Corn, Cotton,
Rice, Soybeans, Sunflowers, Spring Wheat, and Winter Wheat
(04-RA-UR (Ed. Rev. 07/25/03) – last revised: 05/16/2007)

Of course, the other end of the harvest pricing schedule is the release of fall harvest prices. According to the RMA, the FCIC releases fall harvest prices for revenue assurance policies based on the following schedule: August 5 for winter wheat, September 5 for feed barley and spring wheat, October 5 for canola and sunflowers, November 5 for soybeans, November 10 for rice, December 5 for corn, and December 10 for cotton. The chart below details government-accepted methods for calculating these fall harvest prices:

Ø CORN – fall harvest price is the simple average of the final daily settlement prices in November for the CBOT December futures contract
Ø SOYBEANS – fall harvest is the simple average of the final daily settlement prices in September for the CBOT October soybean oil futures contract – divided by 2, then minimized by 1
Ø SPRING WHEAT – fall harvest is the simple average of the final daily settlement prices in August for the MGE September hard red spring wheat futures contract
Ø WINTER WHEAT – for Idaho, Kentucky, Michigan, Ohio, and Tennessee fall harvest price is the simple average of the final daily settlement prices from July 1 to July 14 for the CBOT July soft red winter wheat futures contract; for Arkansas, Colorado, Iowa, Kansas, Missouri, Montana, Nebraska, Oklahoma, and South Dakota fall harvest price is the simple average of the final daily settlement prices from July 1 to July 14 for the KCBT July hard red winter wheat futures contract
Ø COTTON – fall harvest price is the simple average of the final daily settlement prices in November for the harvest year’s NYCE December futures contract, rounded to the nearest whole US cent
Ø RICE – fall harvest price is the October harvest year’s average daily settlement price per pound for the harvest year’s CBOT November rough rice futures contract, rounded to the nearest 1/10th of 1 US cent

SOURCE: USDA Risk Management Agency
Revenue Assurance
Underwriting Rules: Feed Barley, Malting Barley, Canola/Rapeseed, Corn, Cotton,
Rice, Soybeans, Sunflowers, Spring Wheat, and Winter Wheat
(04-RA-UR (Ed. Rev. 07/25/03) – last revised: 05/16/2007)




So how does harvest pricing for revenue assurance policies compare to the target prices established under the 2002 Farm Act? First, it’s important to note that harvest pricing is also used for income protection, multiple peril crop insurance, group risk income protection, and crop revenue coverage plans – and that it is possible for some variance to exist in harvest pricing, depending on the type of coverage chosen. Target prices as outlined in the 2002 Farm Bill, of course, are currently used in the calculation of CCPs in the legislation set to expire at the end of this year.


Top 5 States in 2006 in terms of production…
1. Kansas - $1,339,520,000 in wheat production
2. North Dakota - $1,129,014 in wheat production
3. Montana - $703,474,000 in wheat production
4. Washington - $615,593,000 in wheat production
5. Oklahoma - $395,760,000 in wheat production

Top 5 States in 2006 in terms of production…
1. Iowa - $3,187,813,000 in soybean production
2. Illinois - $3,087,360,000 in soybean production
3. Minnesota - $1,898,050,000 in soybean production
4. Indiana - $1,789,200,000 in soybean production
5. Nebraska - $1,477,950,000 in soybean production

Top 5 States in 2006 in terms of production…
1. Texas - $1,554,060,000 in cotton production
2. California - $989,141,000 in cotton production
3. Georgia - $646,626,000 in cotton production
4. Mississippi - $569,900,000 in cotton production
5. Arkansas - $533,982,000 in cotton production

Top 5 States in 206 in terms of production…
1. Arkansas - $892,028,000 in rice production
2. California - $464,464,000 in rice production
3. Louisiana - $200,930,000 in rice production
4. Missouri - $121,894,000 in rice production
5. Mississippi - $121,055,000 in rice production

[1] American Farmland Trust (Farm Safety Net Improvement Act of 2007)
http://www.farmland.org/

[2] Institute for Agriculture and Trade Policy – Revenue-Based Countercyclical Payments: US Disaster Relief? (by Steve Suppan, IATP Trade and Global Governance Program) (April 2007) (p.3)

[3] Congressional Budget Office – The Budget and Economic Outlook (August 2007) (p.7)

[4]Congressional Budget Office – The Effects of Liberalizing World Agricultural Trade: A Review of Modeling Studies (June 2006) (p.18)

[5] RCCP: Explaining the New Approach to Farm Programs
http://www.coloradocorn.com/legislative/2007%20Farm%20Bill/RCCP%20Explaining%20the%20New%20Approach%20to%20Farm%20Programs%200705031.rev.docp

[6] The 2007 Farm Bill: Policy Options and Consequences (Counter-Cyclical Programs and Safety Nets) – by James W. Richardson and Steven L. Klose, Texas A&M University (February 2007) (p.5)

[7] The 2007 Farm Bill: Policy Options and Consequences (Counter-Cyclical Programs and Safety Nets) – by James W. Richardson and Steven L. Klose, Texas A&M University (February 2007) (p.5)

[8] Revenue Assurance – Underwriting Rules: Feed Barley, Malting Barley, Canola/Rapeseed, Corn, Cotton, Rice, Soybeans, Sunflowers, Spring Wheat, and Winter Wheat
(04-RA-UR (Ed. Rev. 07/25/03) – last modified, 05/16/2007 / p.2)


[9] American Farmland Trust: Integrated Farm Revenue Program (Enhancing the long-term viability and competitiveness of American Agriculture)
http://www.farmland.org/

[10] Integrated Production and Price Risk Management: Impacts on Level and Variability of Corn and Soybean Producers’ Net Returns – by Robert N. Wisner, E. Neal Blue, and E. Dean Baldwin (p.2)
http://www.econ.iastate.edu/faculty/wisner/articles/aaee985final.doc


[11] Integrated Production and Price Risk Management: Impacts on Level and Variability of Corn and Soybean Producers’ Net Returns – by Robert N. Wisner, E. Neal Blue, and E. Dean Baldwin (p.9)
(Mean net return over total economic costs, mean net cash flow, and CVs of net cash flow for alternative risk management strategies for different financially structured corn and soybean farms, Ohio 1985-1997)
[12] How Farmers Can Reduce Risk: Examples Using Hedging, Forward Contracting, Crop Insurance, and Revenue Insurance (p.65, 66, 67)
Economic Research Service, USDA

[13] AgManager.info (Mykel Taylor, et.al. – Department of Agricultural Economics at Kansas State University)
http://www.agmanager.info/marketing/publications/marketing/forwardcontracting.asp

[14] How Farmers Can Reduce Risk: Examples Using Hedging, Forward Contracting, Crop Insurance, and Revenue Insurance (p.68)
Economic Research Service, USDA

[15] Food and Agricultural Policy Institute (FAPRI) (Crop Insurance Outlook Tables)
http://www.fapri.org.models/cropinsurance.aspx

[16] The Effect of the Federal Crop Insurance Program on Wheat Acreage (by Monte L. Vandeveer and C. Edwin Young) (p.27, 29) (Wheat Yearbook/WHS-2001/March 2001)
Economic Research Service/United States Department of Agriculture
[17] The 2002 Farm Act: Provisions and Implications for Commodity Markets/AIB-778 (p.5)
Economic Research Service/USDA

[18]Rain and Hail Agricultural Insurance
http://www.rainhail.com/prices/Price_harvest.htm


[19] United States Department of Agriculture National Agriculture Statistics Service
http://www.nass.usda.gov/QuickStats/index2.jsp

Harvest pricing and the 2007 re-consideration of the Farm Bill...

As is known by many, harvest prices and harvest pricing are extremely important in crop insurance and in potential revenue guarantee programs...

How are Harvest Prices achieved? Do they vary by State?

Harvest Pricing for FCIC-reinsured policies are not derived by political methods. They are not targets designed by members of Congress. They are, however, defined and determined by terminal commodities exchange markets. Pre-harvest prices, which are an important component of the revenue guarantee that would be en force under Sen. Durbin’s proposed legislation, really represent market-driven expectations of the value of commodities futures contracts mostly at the end of each calendar year. As such, pre and post-planting harvest prices come from the following terminal markets: the Chicago Board of Trade (CBOT) for winter wheat, corn, soybeans and rice; the Kansas City Board of Trade (KCBOT) for winter wheat; the Minneapolis Grain Exchange (MGE) for spring wheat; and the New York Cotton Exchange (NYCE) for cotton. Therefore, it isn’t so much the case that harvest prices vary significantly from one state or the other—policy availability, however, is State-dependent. The types of commodities planted to harvest by producers dictate which, if any, harvest prices apply, which markets will be used, and which policies are approved by the FCIC to protect revenue for the farmer’s home state.

WTO Subsidy Boxes

WTO Domestic Subsidy Boxes
...how are subsidies and other agricultural support payments classified by the World Trade Organization?

Below please find a description of these WTO boxes and the ways in which certain types of supports fall into them...

Justin Velez-Greenhalgh (developed in 2007 for Oxfam America)

· Amber Box: all domestic subsidies - such as market price support—that are considered to distort production and trade. Subsidies in this category are expressed in terms of a “Total Aggregate Measurement of Support” (Total AMS) which includes all supports in one single figure. Amber Box subsidies are subject to WTO reduction commitments
· Blue Box: subsidy payments that are directly linked to acreage or animal numbers, but under schemes which also limit production by imposing production quotas or requiring farmers to set-aside part of their land. These are deemed by WTO rules to be ‘partially decoupled’ from production and are not subject to WTO reduction commitments. In the EU, they are commonly known as direct payments
· Green Box: subsidies that are deemed not to distort trade, or at most cause minimal distortion and are not subject to WTO reduction commitments. For the EU and US one of the most important allowable subsidies in this category is decoupled support paid directly to producers. Such support should not relate to current production levels or prices. It can also be given on condition that no production shall be required in order to receive such payments.

(www.actionaid.org)

FARM BILL CONCLUSION - by Justin Velez-Greenhalgh

...thoughts based on an indepth review of the 8 freshmen democrats sitting on the US House Committee on Agriculture in the 110th Congress

...these thoughts were developed as part of research for Oxfam America in 2007 during the Farm Bill debate

As evidenced by the analysis of the 8 freshmen Congressional members with assignments to the House Committee on Agriculture, proclivity toward revolution and/or sweeping reform of the Farm Bill is in short supply. A number of these freshmen represent rural districts with farmers/farms that have been receiving trade distorting subsidy payments for several years. Politically speaking, many of the freshmen are moderate to conservative, especially with regard to their fiscal points of view – which, ironically, translates to acquiescence to rural economic forces that have long relied on regular payments based on past production, payments that provide protection in low price environments based on past acreage, and/or payments that protect farmers when cash prices are at their lowest levels for any given season (based on current production levels – often resulting in excess farm production).
With the exception of NY Rep. Gillibrand, who represents a district with relatively little reliance on subsidy programs (compared to other of the freshmen studied in this memorandum) and whose constituent farmers tend to produce non-program crops, all other Democratic freshmen on the Agriculture Committee are in a tight position. Some of them are former Republicans – others rose to power as part of the 2006 Democratic sweep (after having unsuccessfully run in their districts during elections cycles where the political air was not moving in the Democrat direction) – still others availed themselves of another theme that hit hard last year, Republicans steeped in legal trouble and public controversy. Disappointing as the political reality might be, House Speaker Pelosi is probably right to protect her freshmen by holding off from igniting the light of reform fires if she hopes to continue working with those individuals in Congress in January 2009 – and also if she hopes to remain the House Speaker, as opposed to the Congresswoman from the 8th Congressional district of California.

Unfortunately, Raymond Offenheiser, Oxfam’s President, couldn’t have been more apropos when he said, “It's a sad day when the Democratically led Agriculture Committee is a better friend to wealthy special interests than the Bush administration." Even the Democrats who gained seats promising protection for the small farms and farmers, the average worker, the solidly middle-class American citizens, find themselves unable (perhaps unwilling) to plant the seeds of change when rich, powerful interests (collecting what amounts, in many cases, to rural corporate welfare) can easily shop for a compliant, submissive Congressional candidate across the political aisle.