Farm Subsidies - Magnitudes and Comparisons

Continuing the discussion of the paper I wrote entitled "The Evolving Role of the USDA in
the Food and Agricultural Economy", today I'll discuss some USDA farm support programs (in another post, I'll discuss the academic research on effects of these and other USDA programs). 

In 2012 (the last date of the Census of Ag), the average government payment per farm receiving payments was $9,925. However, a large percentage of farms receive no government payments . In particular, farms that sell less than $50,000 worth of products tend not to receive payments, while the opposite is true for farms with sales greater than $50,000. For the 3.9 percent of farms with sales of $1 million or more, 71.2 percent receive payments averaging $40,559. Whereas the smallest farms receive the smallest average payments in total dollars, they receive the largest payments when expressed relative to value of production. Farms with sales of less than $1,000 that receive payments tend to get 9.36 cents for every dollar of output produced, but farms with sales of more than $1 million that receive payments tend to get only about 2 cents for every dollar of output produced.

Although government payments represent a small fraction of the value of output (i.e., gross revenue), they are certain to represent a much higher fraction of farmers’ net income. In fact, USDA Census of Agriculture data show that in 2012, the average net cash income for each category of farm with sales of less than $24,999 was negative. Those farms operate at a loss; because of this, whatever government payment they receive is infinitely greater than what they
make from farming. The average payment as a percentage of net income (for those receiving payments) is 31 percent, 18 percent, 13 percent, and 7 percent for farms with total sales in the categories $100,000 to $249,999, $250,000 to $499,999, $500,000 to $999,999, and $1 million or more, respectively.

It is interesting to compare all this with SNAP payments.  As indicated, of the farms receiving payments in 2012, the average payment was $9,925. By contrast, USDA data indicate that the average payment per individual receiving SNAP in 2012 was $133 per month, which amounts to $1,596 annually. SNAP payments increase at a decreasing rate with the size of the household. For a four-person household receiving SNAP benefits, the average payment was $440 per month, or $5,280 per year, in 2012. Food assistance programs represent a larger share of the USDA budget than do farm support programs because SNAP recipients far outnumber the recipients of farm program payments, not because each SNAP recipient receives a higher payout than does each recipient of farm supports.

It is also useful to compare US farm support payments with those in other countries.  For this, we can turn to data from a World Bank project led by the Kym Anderson and colleagues. 

The nominal rate of assistance (NRA) is defined as the percentage increase or decrease in gross returns to farmers caused by government policies. A positive number means a country’s
policies are pushing up agricultural prices and returns, and a negative number implies the opposite. The gross rate of assistance (GRA) is the NRA expressed in absolute dollar terms (in the year 2000) instead of in percentage terms. The GRA is the NRA multiplied by the value of agricultural production in a country divided by the number of farmers.

Figure 14 shows the average NRA, and figure 15 shows the average GRA of 53 different countries from 2000 to 2010. The figures contain a selection of developed and developing countries to provide insight into the diversity of agricultural policies around the world. The United States had an average NRA of 11.2 percent and a GRA of $3,576 per farmer over this period. That means that the gross returns of US farmers are 11.2 percent (or $3,576 per farmer) higher than would have been the case were it not for various government policies. Some countries, such as Norway, Iceland, Switzerland, and the Republic of Korea, have NRAs higher than 100 percent. Thus, US agricultural policies push farmer prices and returns higher than would be the case in the absence of such policies, but by an amount far less than is the case in some other countries and far more than in others.

Whereas figure 15 shows a snapshot of the GRA at a point in time, figure 16 shows changes in the GRA per farmer over time in eight selected locations (all in 2000 dollars). The GRA per farmer in the United States increased sharply from the 1970s to the 1980s and has subsequently stayed around $3,000 per farmer per year. The GRA per farmer in Japan has risen over the entire period considered from only $536 per farmer per year in the 1960s to $8,653 per farmer per year from 2000 to 2009. New Zealand dramatically lowered the GRA per farmer from the 1980s to the 1990s. Brazil and China have policies that are relatively neutral with regard to farmer gross returns. Until recently, countries in the European Union had highly distorting policies equivalent to taxes in excess of 100 percent.

In most locations (except eastern Europe and central Asia), agricultural policies have distorted the overall economy less since the 1980s. From 2000 to 2010, the United States had a welfare reduction index (WRI) of 17; the only locations that had less distorting policies were Australia and New Zealand, which had an average index of only 3.8 over this period (figure 17).

The welfare reduction index (WRI)  accounts not only for transfers but also for trade policies that affect the food and agricultural economy. According to Anderson, Rausser, and Swinnen, the WRI is calculated as “the percentage uniform trade tax which, if applied equally to all agricultural tradables, would generate the same reduction in national economic welfare as the actual intrasectoral structure of distortions to domestic prices of these tradable goods.”

The previous graphs aggregate the effects of agricultural and trade policies across all commodities. Figure 18 shows the average NRA for 11 different commodities in the United States from 2000 to 2010. During that period, sugar, cotton, and milk producers benefited most, with NRAs of 75 percent, 56 percent, and 39 percent, respectively. Barley and wheat had relatively low NRAs. Other commodities like beef and pork (not shown in the graph) had NRAs near zero.

To put these figures in perspective, it is useful to compare them with other distortions in the economy. In a remarkable statement, Anderson, Rausser, and Swinnen write,

“In 2004, existing agricultural and trade policies accounted for an estimated 70 percent of the global welfare cost of all merchandise trade distortions, even though the agricultural sector contributes only 6 percent of global trade and 3 percent of global GDP.”

In short, despite the small contribution of agriculture to global GDP, agricultural policies are responsible for the lion’s share of welfare losses that result from trade distorting policies.

In the paper I also talked about the fact that USDA impacts on the economy likely extend beyond those caused by explicit farm-commodity policies. To get a sense of such impacts, I utilized the RegData database.  You can read the paper for more details on that data set, or look at some of the work by Levi Russel who blogs at FarmerHayek.com.

Zhen et al. on Soda Taxes

Yesterday, I was browsing recent back issues of the American Journal of Agricultural Economics looking for papers on consumer demand (somebody has an AAEA presidential address to write).  

I came across two papers by Chen Zhen and co-authors published in 2014 on effects of sugared sweetened beverage taxes (or "soda taxes") that I'd previously read but not blogged on before.  I thought I'd mention them here given the ongoing policy discussions surrounding the issue (Philadelphia politicians are currently considering a soda tax; Oakland has a ballot measure planned on the issue; and there is much debate about the potential effects of the soda tax already passed in Mexico).

In the first paper, Zhen and colleagues show that the way most of these taxes are designed, on a per ounce of soda basis, is not nearly as effective as would be a tax on a per calorie basis.  The authors write:

“For every 3,500 beverage calories reduced, the estimated consumer surplus loss due to a calorie-based tax is $1.40 lower than the loss induced by an ounce-based tax. A 0.04 cent per kcal SSB tax is predicted to reduce beverage energy from ScanTrack supermarkets by 9.3%, compared with 8.6% from a half-cent per ounce tax. Applying this percentage change to beverages obtained from all sources, we calculated that a 0.04 cent per kcal tax on SSBs will reduce total beverage energy by about 5,800 kcal per capita per year.14 Compared with an ounce-based SSB tax that also achieves a 5,800 kcal reduction in beverage energy, the 0.04 cent per kcal SSB tax is estimated to save $2.35 per capita or $736 million for the U.S. population in consumer surplus per year.”

The "lost consumer surplus" means consumers are worse off with either tax.  This is an issue I've raised several times before: there have been few serious attempts to carefully articulate how a soda tax improves consumer welfare given that consumers don't like paying higher prices (e.g., see here or here).

In the second paper, the authors show how a sugar-sweetened beverage tax might have unintended consequences. 

“The preferred demand specification predicts that almost half of the reduction in SSB calories caused by an increase in SSB prices is compensated for by an increase in calories from other foods. We further found potential unintended consequences of an SSB price increase on sodium and fat intake. Because energy intake is just one of many dimensions of nutrition, the results on sodium and fat highlight the complexity of using targeted food and beverage taxes to improve nutrition outcomes.”

They predict that one half-cent per ounce tax on such beverages would reduce body weight by "0.37 and 0.16 kg/person in 1 year and 0.70 and 0.31 kg/person in 10 years for low- and high-income adults, respectively."

They also write:

“The welfare loss for low-income households is about $5 per household per year more than high-income households because low-income households reported higher SSB purchases in Homescan. This difference in welfare loss between low- and high-income households reinforces the regressive nature of an SSB tax”

Support for GMO Labeling a Left-Wing Phenomenon?

Much has been written about whether aversion to biotechnology and GMOs has ideological dimensions rooted in the left.  I've written about this before, as have many others (this paper in Food Policy extends the discussion to a whole host of food regulations beyond biotechnology).  Most of the studies I've seen (including my own data) suggest only small differences in the left and the right in terms of beliefs about safety of eating GMOs.  However, as I previously argued:

“One distinction, which I think is missing, is the greater willingness of those on the left to regulate on economic issues, such as GMOs, than those on the right. Stated differently, there are questions of science: what are the risks of climate change or eating GMOs. And then there are more normative questions: given said risk, what should we do about it? Even if the left and the right agreed on the level of risk, I don’t think we should expect agreement on political action.”

Perhaps the clearest demonstration of this difference in willingness to regulate comes from a new paper by John Bovay and Julian Alston in the Journal of Agricultural and Resource Economics. They look at precinct-level voting data on the Prop 37 mandatory labeling initiative in California in 2012. One of the best predictors of support for Prop 37?  The share of people in the precinct voting for Obama. Here's a telling graph from their paper.   It's an almost perfect positive, linear relationship. 

The authors went on to use these results to predict what would have happened in other states if they'd had an opportunity to vote on Prop 37 (I should note we did something very similar in a paper on for votes on California's Prop 2 related to animal welfare in 2008).  Bovay and Alston found the following:

“Projections using our estimated model imply that a majority of voters in only three of fifty states (Hawaii, Rhode Island, and Vermont) plus the District of Columbia would have passed Proposition 37 had it been on their ballots in 2012”

Enriched colonies

A couple months ago, I discussed the book chapter I wrote on a different type of hen housing system: the enriched colony . Today, the Wall Street Journal ran a piece I wrote about this hen housing system and the costs of alternative housing systems.   

A few snippets:

“A 2014 California voter initiative and subsequent state legislation ultimately led to a ban on sales of battery-cage eggs in the Golden State. Because eggs have few close substitutes, demand tends to be relatively insensitive to changes in price. When demand is inelastic, a small-percentage change in the quantity supplied causes an even greater increase in price.

Comparing the prices of eggs sold in California before and after the law with the prices of eggs sold in other states reveals that the legislation increased egg prices for Californians by at least 22%—or about 75 cents for a dozen. A related analysis using Agriculture Department wholesale price data indicates the California law increased prices between 33% and 70%. Poor Americans, who spend a larger share of their incomes on food, are disproportionately affected.”

and

“Rather than getting rid of the cages entirely, one answer is to use a relatively new type of housing: the enriched-colony cage system. Unlike the barren environment in the battery cages, the much larger, enriched-colonies have nesting areas for egg laying and a matted area that allows the hens to exercise their natural urge to scratch. Also available are perches that allow the hens to get up off the wire floor.

An enriched colony is not a Ritz-Carlton, and some animal advocates think the systems do not go far enough. However, they represent an innovative compromise that attempts to balance cost and the hens’ well-being.”

Food Demand Survey (FooDS) - April 2016

The latest edition of the Food Demand Survey is now out.

From the regular tracking portion of the survey:

• Willingness-to-pay for all food products was down this month, with the largest drop occurring for hamburger;
• The was a sizable uptick in consumers' anticipation of price increases for beef, pork, and chicken and a slight reduction in planned purchases of these items;
• Expenditures on food away from home were up about 5%; and
• We added "cancer and meat consumption" to the list of, now, 18 times for which we track awareness and concern.

Three new ad hoc questions were added this month.

The first set of questions was meant as follow-up to a survey Politico recently conducted of "food experts" (I was a participant in their survey).  Politico asked the following question to the experts: "Are the presidential candidates doing a sufficient job in the campaign discussing the future of food policy?" A whopping 97% said "no".  

I posed a related question to the respondents of FooDS.  Rather than just asking about the issue as a stand alone question, I put food an agricultural policy in the context of other issues candidates spend their time talking about.  In particular, participants were asked: “Are the presidential candidates spending too much or too little time discussing each of the following issues?”  

A list of nine issues was provided, which included “food policy” and “agricultural policy.”  Only about 6% of respondents thought too much time was being spent on the two issues.  44% and 46% thought about the right amount of time was being spent on agricultural and food policy, and 50% and 47% thought too little time was spent on agriculture and food, respectively.  

Immigration policy was the only issue for which more respondents thought candidates were spending too much vs. too little time.  Except for food and agricultural policy, the largest fraction of respondents thought the candidates were spending the right amount of time on the other issues.  

Secondly, we asked another question - this time exactly as it was asked in the Politico food-expert survey.  In particular, participants were asked “Should the government’s role in regulating the US food system be more active, less active, or the same?”  Here, our respondents lined up closely with Politico's food experts:  

Over half of the participants (59%) believe that the government should become more active in regulating the US food system, while less than 13% of participants believe the government should be less active in regulating the US food system.  This is consistent with other research that suggests consumers tend to be rather "statist" when it comes to food policy.

Finally, based on a suggestion from Jason Winfree at University of Idaho, who passed along an article about the (sometimes unjustified) negative perceptions of frozen food,  respondents were asked whether they agreed or disagreed with a list of nine statements related to the tastiness, affordability, and health of fruits and vegetables that are either fresh, frozen, or canned.  

In terms of taste, fresh rated higher than frozen, which was rated higher than canned.  All three had a mean score above 3, meaning respondents were more likely than not to agree that all three types of fruits and vegetables were tasty.  In terms of affordability, the ranking was exactly reversed with canned being perceived as most affordable and fresh least affordable (although all three were far about the mean of 3, implying most consumers though all three were affordable.  Finally, perceived health lined up almost exactly with perceived tasted: fresh was perceived as healthier than frozen which was perceived healthier than canned.