Specific Objectives of the Project
To obtain data on payments made to US farmers over the period from 2006–2021 under a variety of federal programs, including during the the Covid-19 pandemic. This data collection effort is meant to complement a project which uses ARMS data to construct a pseudopanel of farm-households, with longitudinal data on farm income and farm-household expenditures. The overall goal then is to relate various federal payments to the farm income and expenditures at a highly disaggregate level.

Summary of Results
We were able to obtain a complete record of all federal payments to U.S. producers under all of the programs administered by the USDA over the last two decades via the Freedom of Information Act. We were subsequently able to link these payments to producer characteristics, aggregated to the zip-code level, available in the Agricultural Resource Management Survey (ARMS) through 2019.

Specific Objectives of the Project
To summarize payments under a variety of federal programs to US farmers, and to relate the incidence of these payments to different farm-household characteristics, including county, acreage, crops, and need, as measured by county-level estimates of the distribution of farm-households' incomes, expenditures, and marginal utility of expenditures.

Summary of Results
We were able to obtain a complete record of all federal payments to US producers under all of the programs administered by the USDA over the last two decades via the Freedom of Information Act. We were subsequently able to link these payments to producer characteristics, aggregated to the zip-code level, available in the Agricultural Resource Management Survey (ARMS) through 2019.

Our project then foundered, as the USDA switched from using the NORC Data Enclave for managing confidential data to a new platform (the ADRF). The new platform is technically superior, but we have had to re-apply for permission to get ARMS data identified at the zip code level.

We remain excited by this project, and pending approval for data access from NASS we hope to return to it.

Specific Objectives of the Project
The principal objective of the project is to measure the value of crop insurance to agricultural producers in the US and in California. A secondary (and supporting) objective involves the construction of a ’quasi-panel’ dataset of farm-households, with longitudinal data on farm income and farm-household expenditures.

Project Report/Summary of Results
We’ve worked with the Sacramento offices of the USDA/NASS to construct a quasi-panel of farm-households, aggregated to the level of a year-county (except that contiguous counties with too few farms are aggregated to “super-counties” to comply with policies regarding confidentiality). We have preliminary results that relate aggregated farm-household expenditures to consumption needs (an index of marginal utilities of expenditures, or MUEs); relate MUEs to farm income net of crop insurance indemnities; and relate indemnities received to MUEs. These preliminary results suggest that crop insurance is more like a lottery than like insurance, in that households are better off than usual in the states of the world in which indemnities are received.

Specific Objectives
As part of the Cap and Trade Program supporting Assembly Bill 32 (AB32), the California Air Resources Board addresses the potential greenhouse gas (GHG) emission leakage created by changes in competitive advantage between California and out-of-state entities. To the extent that industries with high emissions intensity per dollar of value-added lose market share to out-of-state rivals in response to a rise in energy input prices, the market transfer of production to unregulated regions undermines the effectiveness of AB32 in reducing global GHGs. The primary objective of the proposed research is to assess the likely extent of market transfer in California's food processing industries.

Project Report/Summary of Results
This project calculates the extent of market transfer and emissions leakage resulting from greenhouse gas (GHG) regulations on California tomato, sugar, wet corn and cheese processing industries. GHG regulations that raise energy input prices at food processing plants in California have the effect of selectively raising the marginal cost of food processing for California plants, resulting in a cost advantage for unregulated plants in other production regions. Our analysis indicates that selective GHG regulation in Californias AB32 policy will result in significant market transfer from California food processing industries to food processors that produce in unregulated regions.

Market transfer effects are a serious hindrance to well-functioning greenhouse gas (GHG) regulations for at least two reasons. First, selective regulations on California plants reduce regional manufacturing activity in the state, decreasing both tax revenue and employment. Second, the transfer of production from California to other region results in leakage of GHG emissions across state (and national) without improving global climate outcomes. Indeed, global emissions can rise as a result of AB 32 regulations in the event that the displaced California production is produced from natural gas inputs while manufacturers receiving the transferred output rely on coal-fired plants for energy.

The predicted market transfer effect in each food processing industry depends on supply and demand conditions facing California producers. Some combination of three things must occur in response to an increase in the marginal cost of production: (i) the cost increase can be passed forward to consumers in the form of higher prices for manufactured food; (ii) the cost increase can be passed backward to farmers in the form of lower farm prices; or (iii) the cost increase can result in narrower margins for food processors. In this report, we subsume the latter two effects into our calculation of backward shifting, as our data is not sufficiently rich to distinguish how cost increases predicted to be absorbed in each industry are likely to be shared between California farmers and food processors. Backward shifting of costs as a result of AB 32 regulations results in lower value for farm products procured by California food processors, which would be shared in some fashion between food processors and agricultural producers through lower prices for farm products, and our results are expressed in terms of this lower combined value in the California supply chain.

Market transfer from California food processors to food processors in other, unregulated production regions is mediated through forward shifting effects of the regulation into consumer prices. Cost increases passed forward into consumer prices provide food processors in other regions with the economic incentive to increase production. As a result, the forward shifting effect of an increase in marginal cost among California producers leads to both decreased demand for the processed food product as well as a loss in market share for California plants. We measure the market transfer effect in each industry as the share of the decrease in processed food output by California producers that is acquired by out-of-state producers.

The primary objective of this research project is to test for and measure changes in the domestic competitiveness of wholesale markets for fruits and vegetables over time and across regions and commodities. Do vegetables get more expensive when transportation is costly? America's vegetable markets rely on a massive shipping network, and with rising gas prices and efficient new vehicles, this question will remain important in the coming years. This issue speaks to the availability of affordable produce to consumers living far from farming communities. It is of special interest to California agriculture, which is a major exporter of all of the commodities in our data.

This project is using a rich dataset on the prices of a number of agricultural commodities in a range of wholesale markets around the United States. This data is being collected and combined from several formats, including microfilm an d paper in the Giannini Library, scanned records in USDA archives, and for recent years, a publicly available digital database. Combining these sources for final analysis is an ongoing detailed process.

Analysis is ongoing as new data sources are integrated into the existing dataset. Thus far, the analysis shows that transport costs are important in vegetable markets, accounting for as much as 20% of wholesale prices for perishable items like tomatoes and lettuce in importing markets. Adjusting for inflation, these price differences have actually been quite stable over time. Increases in gas prices don't seem to translate into higher vegetable prices on average, in part because our measures thus far are very noisy. For a dollar increase in the price of gasoline, we measure the price of celery going up 15% on average in distant markets. The price of potatoes only goes up by 1.6% on average. So while importing markets do face higher vegetable prices, the changing cost of shipping may not be changing this relationship in a significant way.

What effect do rising levels of unemployment have on grocery purchasing patterns? More specifically, how does the level of unemployment in a neighborhood affect the probability of households buying certain products at the grocery store? In order to address this question, a large data set combining retail scanner data, demographic and unemployment data was analyzed. Preliminary reduced form results indicate there exists an economically and statistically relationship between neighborhood unemployment and changes in the pattern of grocery purchases (both within and between grocery category). For example, quantities sold of nearly all packaged meat have a positive relationship with unemployment (the largest coefficient is estimated on the "Franks" packaged meat sub-category) and both cold and hot cereal sales increase with unemployment. These results are suggestive, however, a more complete analysis is forthcoming. Next steps include further economic modeling and the application of the multivariate logit approach to incomplete demand systems.

The federal government has developed a large number of programs To insure various “specialty crops”' over the last two decades, particularly in California. If these new insurance programs have affected either producer or consumer welfare, then we would expect to see this reflected in output and prices. We find that the supply of and demand for insurance for tree crops is much larger than for non-tree crops. Crop insurance has a small but significant negative effect on prices of insured crops. This last finding is consistent with the view that demand for such highly disaggregated commodities is likely to be highly elastic. A consequence is that crop insurance for these specialty crops has little benefit for consumers, even when it generates a large supply response.

Publications: Ligon, E. 2011. "Supply and Effects of Specialty Crop Insurance", NBER Working Paper 16709.