Chapter 3 – Design, Data, and Methods



2. Design, Data, and Methods

2.1 Introduction

This study will measure the relative importance of several theoretical factors purported to drive industry change. The primary dependent variables in this study are the diversity observed in the structure of agricultural production across U.S. states, the varying paces of change, and the resultant changes in industry location. The question of whether or not this diversity should be expected is an important underpinning of the study. It may be expected that producers would relocate to locations where business costs are lower, where health and environment regulations are lower or more loosely enforced, or where workers face higher barriers to unionization efforts. To this end, the study incorporates economic and historical factors most relevant to the industries under investigation as well as a goal of explaining change, rather than absolute measures.

This study argues that this diversity across U.S. states indicates the inability of industry-wide developments or exogenous shifts in domestic and global markets to sufficiently explain the process of industry change. As outlined in the previous chapter, multiple factors are relevant to the survival of an industry at a particular location, and these factors may impact actors in different ways. To assess the potentially complimentary explanations advanced, I implement a comparative study of two agricultural industries in the United States and selected U.S. states. I construct a detailed description of the structure and operation of each industry and focus on the causal relationships that lie behind change at both the national and state levels. These industry changes are juxtaposed against changes in the size of end markets and to the greatest extent possible, I focus on the timing of these events to pinpoint causality, a key issue for an assessment of the explanations advanced.

The study will utilize within case comparisons (Mahoney 2003:360-361) to construct the range of state level differences that exist over time in each industry. These differences are theoretically derived and encompass the industry roles played by producers in the case states, the differences in economic factors of production, and differences in state intervention. In a separate case study, I will further detail the role of state intervention as it pertains to agriculture broadly and these two industries specifically. The objective will be an initial assessment of how state intervention is related to the operation of industries, put bluntly as cause or effect. This will allow for an initial assessment of the institutional approach advanced.

The second stage of the analysis will utilize time series analysis at both the level of the United States and at the level of the case states to assess the relative importance of measures of the factors identified in the case studies. In this respect, the case studies serve as detailed elaborations of the variables in play for formal test. The remainder of this chapter specifically addresses two aspects of methodology: case selection and data scope and compilation. While model specification and discussion of the specific variables employed are reserved for that chapter, a broader description of the dependent and independent variables is included at this point for two reasons. First, the case studies utilize much of the information collected for their descriptions. Second, compilation difficulties arose during the study. The decisions made to address these difficulties will thus affect results reported in the remainder of the study.

2.2 Case Selection

Agriculture from 1959 through 2005 represents an ideal research site for several reasons. First, agriculture remains arguably the most mediated sector of the economy by the state, despite the decline in the proportion of the population directly employed in farming activities that started in the 1920s (Dimitri, Effland, and Conklin 2005). However, broad differences in mediation are present throughout the study period and across specific products. Second, while coordination between farmers and manufacturers, the two critical types of actors in this sector, increased during the twentieth century (Harris, Kaufman, Martinez, and Price 2002; Effland 2000), these actors represent fundamentally different types of productive activities, and little formal command through ownership exists. This lack of overlap allows the study to more clearly disaggregate the often different interests of these two sets of actors during a period of incredible change in the relationship between farming and agro-business. Finally, agriculture contains a substantial role for global markets and substantial variation in this role across products. The impact of global markets on domestic producers, both immediate and as producers adjust, allow for a comparison between farmers and manufacturers with respect to competitiveness and causality of resultant industry change.

Pork and tobacco were chosen as the industry cases for several reasons. With respect to Federal policy, substantial differences exist between these two industries. The beginning of the relatively active role for the Federal government in agriculture policy was the enactment of the Agricultural Adjustment Act of 1933 (Dimitri, Effland, and Conklin 2005; Dixon and Hapke 2003). Some objectives, such as rural development and conservation, were captured by programs that applied to all farms. However, the goal of stabilization of farm income was pursued largely through commodity-specific price support through production restriction. Acreage allotments and marketing quotas limited the farm production that was protected by price supports, and thereby provided a disincentive to produce beyond the allocation or quota (Green 1990; USDA-ERS 1984). Importantly, tobacco generally fell under supply restrictions while hog farming did not. This provides the study with a contrast between industries in both the significance of Federal interventions as related to industry changes and the latitude states possessed with respect to significant interventions.

Second, as with farms generally (Dimitri, Effland, and Conklin 2005), both tobacco and hog farms grew in size, capitalization, and specialization. However, these producers vary with respect to the ability to relocate production and the degree to which coordination takes place between farming and manufacturing. Tobacco is more closely tied to specific land characteristics than hog farming, though it was produced in a number of states outside the core regions of the Appalachian Mountains and Eastern Seaboard. In 1992 for example, 19 states as far west as Kansas and as far south as Florida produced tobacco (Grise 1995:2). By contrast, hog production takes place in every state and requires relatively little land. While hogs were traditionally produced in states where feed prices were low, the increasing size and specialization of these operations raises in importance both environmental and labor cost factors for production (Key and McBride 2007:9-10).

Raw tobacco can be stored to facilitate year-round production, but year-round slaughter hog production must exist for year-round pork production. For several reasons, including assurance of quality (Martinez and Zering 2004), increasing cost associated with hog farm growth (Key and McBride 2007; Martinez 2000), and growing meat packer concentration (MacDonald 1999), coordination through production and marketing contracts more closely ties farms and manufacturers in the pork industry than in the tobacco industry.

Finally, these industries exhibit important differences with respect to consumption and the role of global markets. Figure 1 displays domestic tobacco leaf production, imports, and exports from 1959 through 2005. Tobacco production peaked in 1963 at over 2.3 billion pounds. As late as 1981, tobacco production surpassed 2 billion pounds intermittently, but sharply fell to 645 million pounds by 2005. While export markets are a vital component of this industry, they do not offset the decline brought by falling cigarette production and rising imports of tobacco leaf. By contrast, Figure 2 shows a relative absence of global markets from domestic hog production. The contrast in the role of global markets creates a difference in the relationship between farmers and processors.

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Figure 1: U.S. Tobacco Production, Imports, and Exports

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Figure 2: U.S. Hog Production and Import and Export Share of Production

This study utilizes within-case comparisons at the level of U.S. states. A subset of states involved in each industry was chosen based in part on the patterns of change visible in the dependent variable. In the tobacco industry, additional factors include the importance of the state to national tobacco production, the specific varieties of tobacco produced, and the applicability of the national price support system to the variety of tobacco produced in the state. All 6 states, North Carolina, South Carolina, Virginia, Kentucky, Tennessee, and Maryland, produce cigarette tobaccos. However, Virginia, Kentucky, and Tennessee also produce tobacco for use in snuff and chew, which is not substitutable for tobaccos destined for other products. Maryland was included because the Federal price support system was not applied to its tobacco after 1959. Importantly, this selection does not represent production of cigar tobacco, and the relative sizes of these end markets are provided in the next section. Finally, North Carolina, Kentucky, and Tennessee represent the core farming states for this industry, while the other states are relatively peripheral.

With respect to hog production, additional factors include the relative importance of the livestock industry to the state, the presence or absence of corporate farming restrictions in the state, and other state-level interventions that impact the industry. An important region component to the case selection was also a factor for case selection. Iowa, Illinois, and Minnesota represent three of the traditional centers of the industry. North Carolina’s prominence as a center in the industry developed over the study period and in the institutional context of the Confederate South. Texas both represents the rapidly-developing Southwest region and is a state to which the livestock industry is important. Additionally, Minnesota, Iowa, and Texas contain or contained limited restrictions on corporate farming (Edmonson and Krause 1978), an important factor for this industry. The development of CAFOs of increasing size results in various efforts to reduce the associated environmental problems, from regulation of farming methods to moratoria on CAFO development, exist throughout the sample.

2.3 Data Compilation

This chapter concludes with a brief description of the data sources and compilation methods used to generate appropriate statistical and case study information. At the level of industries, farm producers, manufacturers, consumption, and the relationships between these concepts are involved in the explanations advanced. Additionally, the within case comparisons require information at both the national and state levels. Consequently, consistent and reliable measures of the concepts in play are difficult to generate.

Most of this section details primary statistical information, though additional primary and secondary information is utilized in the case studies. While the breadth of measures available and the caveats to their employ are the primary focuses of this section, not all specific measures are utilized in each stage of analysis. For instance, the specific variables employed in the model analysis will be discussed briefly in that chapter. Extended documentation of specific conversion practices are located in Appendix A, and for annual time series data, linear interpolation is used unless otherwise noted.

2.3.1 Agriculture and Agricultural Production

Specific measures of agriculture operations and farm production, the specific measures of the dependent variable, are listed in Table 1. Raw numbers were collected for use in the case studies; proportions generally will be utilized in the modeling analysis and will be discussed in that chapter. Relevant data are industry-specific, and only the total number of farm operations and the value of production are universal measures across agricultural industries. To this end, I briefly discuss specific aspects of these two industries that warrant the collection of different types of data.

Hog farming ultimately produces hogs marketed for slaughter. However, the division of the hog farming process into discrete stages of the hog lifecycle entails the creation of markets for pigs not ready for slaughter. The broad measures of production utilized are marketings, pig crop, and value of production. In addition, I also assess the suitability of hog inventories and production as measured by live weight as alternative measures. To assess specialization within these discrete stages of hog farming at the state level, this study also includes an assessment of inshipments, which are sales of hogs not ready for slaughter from an operation to another in a different state. Where possible, the study also incorporates information with respect to the proportion of farms that possess inventory only used for breeding and inventory other than hogs to be used for breeding. This will allow for some assessment of the relation between specialized state roles and economic factors.

Table 1: Agriculture and Production Variables Collected

|Variable |Description |Source Type |

| |

|Hog Farming Variables |

|Inventory |Hog inventory, BOY |Annual survey |

|Pig Crop |Total pigs farrowed |Annual survey |

|Inshipments |Hogs/pigs received by state, not for slaughter |Annual survey |

|Marketings |Marketed for slaughter or sale to other states |Annual survey |

|Production |Total meat produced, live weight |Annual survey |

|Price/Value |Average price received/total value of production, either for slaughter or |Annual survey |

| |from inshipments | |

|Operations, by inventory |Total number of operations/distribution by size group based on sales and |Total: 1965- annual survey;|

|and by sales |inventory |Total and distribution: |

| | |Census years |

| | | |

|Tobacco Farming Variables |

|Acreage |Harvested acreage, all varieties and by variety |Annual survey |

|Production |Tobacco production, all varieties and by variety |Annual survey |

|Value |Value of production, all varieties and by variety |Annual survey |

|Operations, by acreage |Total number of operations/distribution by acreage harvested |Census years |

| | | |

|General Farming Variables |

|Operations |Total number of farms |Census years and annual |

| | |survey |

|Acreage |Land in farms, all types |Census years and annual |

| | |survey |

|Cropland |Harvested cropland |Census years |

|Pastureland |All land for pasture, whether cropland, woodland, or other land |Census years |

|Value |Total value of production, all products |Census years |

The tobacco industry is also disaggregated, but by the type of tobacco produced, each of which is most suited to a particular application. The two primary types of tobacco produced in the United States, flue-cured and burley (light air-cured) are utilized primarily by the cigarette industry. Fire-cured and dark air-cured tobaccos are utilized by the tobacco products industry (snuff and chewing tobacco). Cigar filler, binder, and wrapper are primarily used to produce cigars (Grise 1995:4). As each of these types possesses a distinct geography, the effects of consumption changes on specific states will depend on the product in question. For this reason, I collect production information for all production and for specific classes of tobacco. Table 2 identifies the key classification groups and primary locations of production discussed in this study.

Table 2: Tobacco Classes, Geographies, and Proportions of Total Production

|Tobacco Type |Tobacco Classes |Major Producing Locations, 1998 |Proportion Total Tobacco, 2005 |

|Cigarette Types |

|Flue-cured types |Types 11-14 |North Carolina, Virginia, South Carolina, |59% of production, 53% of value |

| | |Georgia, Florida | |

|Burley (light air-cured) |Type 31 |Kentucky, Tennessee, Virginia, North Carolina, |32% of production, 30% of value |

| | |Indiana, Ohio, West Virginia, Missouri | |

|Maryland (light |Type 32 |Maryland, Pennsylvania |0.5% of production, 0.4% of |

|air-cured) | | |value |

| | | | |

|Other Tobacco Product (Chew, Snuff) Types |

|Dark air-cured and |Types 35-37 (dark |Kentucky and Tennessee (both); Virginia |8% of production, 11% of value |

|Fire-cured |air-cured) and Types |(fire-cured) | |

| |21-24 (fire-cured) | | |

|All cigar fillers, |Types 41-65 |Pennsylvania and Puerto Rico (filler); |2% of production, 6% of value |

|binders, wrappers | |Connecticut and Massachusetts (binder and | |

| | |wrapper); Wisconsin (binder) | |

Source: Gale, Foreman and Capehart 2000:3; USDA-NASS 2007.

To measure the relative importance of each industry to state agricultural production, this study also incorporates the proportion of total agricultural production composed by the industry. General information, including total numbers of farms, acreage, sales, and the proportion of total farm sales accounted for by livestock sales and crop sales are collected. Land usage information is also collected and may serve as a more useful control given the vast differences in land usage across U.S. states (Wiebe and Gollehon 2006). In addition, measures of the total number of industry operations and a general distribution based on size were collected. In most cases, annual series of these general characteristics are not available or are not directly comparable with the industry-level operations data. Where annual data is not available, I utilize data from the Census of Agriculture. This limits the statistical modeling portion of the study when these variables are used but does not pose a problem for the case study portions.

Finally, while this study does incorporate some information with respect to farm operations and structure, more detailed data with respect to corporate involvement, farm specialization, and similar items could not be reliably collected or estimated for a significant portion of the period. Where possible, this study will utilize secondary analyses to discuss these more significant measures of farm structure and arguments for reasonable proxy measures will be advanced in the case studies.

2.3.2 Manufacturer Information

Table 3 lists the main independent variables, grouped by general concept. Manufacturer data is used to gauge the degree to which a significant manufacturer role exists within the state in both absolute and relative terms. The presence of a large manufacturing sector in the industry may be highly related to the existence of related agriculture activities in the state in both the past and future as well as related to specific policy developments and state attention to the industry in question. In addition, as with other manufacturing industries, average wages and state law pertaining to unionization and other issues are likely influential on production locations and their change over time. A time series encompassing multiple measures of manufacturing employment, wages, and production value for the case industries is constructed using the Census of Manufactures and the Annual Survey of Manufactures.

Several data difficulties are present in this series and require some elaboration. First, while Census years are generally adequate in terms of a level of detail sufficient to separate the pork industry from the broader meat packing industry with respect to industry value, this level of detail is not available in Survey years, is not present with respect to employment and wage information, and in some cases is not present at the level of some states. Further discussion with respect to specific variables employed and their suitability are available in the modeling chapter. But conceptually, the study will present available information from Census years in the case studies and will estimate the share of meat packing composed of pork production for non-Census years using the Census years as baselines. Second, appropriate characterization of the meatpacking industries in terms of pork-centric, beef-centric, or a combination, will be presented for each case state. The broader meatpacking industry may be utilized at points as a proxy for the pork industry. It should be noted that while pork consumption per capita has remained reasonably stable over the study period at 50 pounds, beef consumption increased from 60 pounds per person in 1959 to a peak of 90 pounds in 1975, before declining to 60 pounds by 1999 (Putnam 2000). Appropriate annual consumption information will also be utilized where necessary for control purposes. Finally, a USDA series consisting of commercial slaughter plants by product type will also be compared with Census information.

Table 3: Independent Variables Employed by Concept

|Variable |Description |Source Type |

| |

|Manufacturer Variables |

|Establishments |Total number of establishments by industry, all manufacturing |Annual survey, Census |

|Employment |Total employment by industry, all manufacturing |Annual survey, Census |

|Wages |Average wages by industry, all manufacturing |Annual survey, Census |

|Value of shipments |Total value of industry production by industry, all manufacturing |Annual survey, Census |

|Value added |Total value of industry minus materials costs by industry, all |Annual survey, Census |

| |manufacturing | |

|Slaughter plants |Total hog slaughtering plants for the pork industry |Annual survey (1967-2005) |

| | | |

|Trade and Consumption Variables |

|Quantity/value |Quantities and values of all industry products |Annual series |

|Domestic consumption |Quantities of final industry products |Annual series |

| | | |

|Policy and Institutional Variables |

|CAFO limits |Presence/absence of CAFO expansion |Annual series |

|Corporate farming limits |Presence/absence of corporate farming restrictions |Annual series |

|Vertical integration |Presence/absence of limits to vertical integration in livestock, pork|Annual series |

|limits |industries | |

|Federal price supports |Applicability and characteristics (support levels) of Federal price |Annual series |

| |supports, tobacco | |

|Quota transfer limits |Classification of quota transfers/leases in tobacco industry |Annual series |

|Large producers, |Relative importance of large operations to farming activities, both |Annual series |

|agriculture |industries | |

|Large manufacturers |Presence/absence of substantial portion of national manufacturer |Annual series |

| |production, industries | |

|Region |Region (hog farming only) |Annual series |

|Importance of agriculture|Agriculture’s importance to the state |Annual series |

In the case of the tobacco industry, very few establishments exist, leading to non-disclosure of information at the state level at the level of specific types of tobacco plants, especially toward the end of the research period. Generally, the number of establishments is available at the state level for the industry as a whole, and when available, will serve as a proxy for manufacturer role in the state. However, the study does separate cigarette manufacture from other types of activities because it is the largest source of employment in the industry.

Finally, the classification system in operation changes during the study period at 1997. Direct comparability between the Standard Industrial Classification System (SIC) and the North American Industrial Classification System (NAICS) does not exist except at the most detailed levels. This is problematic for the annual Survey series, which does not contain this detail. While the study utilizes the published concordances and industry or product descriptions to surmount this gap, caution should be utilized outside Census years. Table 4 presents an assessment for the U.S. pork and tobacco product industries immediately preceding and following this gap as a general assessment of the suitability of the conversion process. The specific definitions for the industries in both time periods are contained in Appendix A.

Table 4: Comparison of Constructed SIC and NAICS Definitions of the Tobacco and Pork Industries

|Industry |Non-Poultry Meatpacking|Pork[1] |Tobacco Products |Cigarettes |

|Industry Shipments Value |

|Average Change, 1992-1996 |1.3% |1.7% |10.7% |10.8% |

|Change, 1996-1997 |12.7% |-2.7% |4.6% |0.9% |

|Average Change, 1997-2001 |1.0% |0.5% |2.9% |4.9% |

| |

|Employment |

|Average Change, 1991-1996 |1.7% |2.0% |4.6% |5.2% |

|Change, 1996-1997 |10.4% |-4.1% |7.0% |3.9% |

|Average Change, 1997-2002 |1.8% |0.8% |-5.9% |-6.4% |

2.3.3 Trade and Consumption

In the cases of swine and tobacco leaf, production is composed of domestic consumption plus net trade over the long run. This study will compare changes in trade against changes in production in order to gauge the impacts of global trade for these intermediate products. For final industry products, the study will compare trade to production for value information and trade to consumption when quantities are available. Quantities and values of relevant products were collected through the study period from the December release of the relevant Bureau of Census trade series for all intermediate and final industry products. To measure the change in relative levels of power in the industry, I collect information with respect to the marketing spread, the proportion of total retail value that accrues to each stage of production.

Table 5: Trade Series and Classification Systems, 1959-2005

|Period |Classification System |Data Series Source |

|Imports | | |

|1959-1963 (June) |Schedule A |FT-110 |

|1963 (July-December), 1965-1970 |TSUSA |FT-246 |

|1964, 1971 |Schedule A (revised) |FT-135 |

|1972-1988 |TSUSA (revised) |UC Davis (FT-246) |

|1989-2005 |Harmonized System |USDA Foreign Agricultural Service |

| | | |

|Exports | | |

|1959-1964 |Schedule B |FT-410 |

|1965-1977 |Schedule E |FT-410 |

|1978-1988 |Schedule B (different from 1959-1964) |UC Davis (FT-410 and FT-446) |

|1989-2005 |Harmonized System |USDA Foreign Agricultural Service |

Two difficulties arise with respect to trade information. First, classification systems and published data series change repeatedly over the study period and, until 1989, were different in detail level and structure between imports and exports. Table 5 identifies the specific series used and the operational classification system for each period of consistency. Second, conversion between systems was not possible for every product. However, at broader levels of aggregation, product codes were successfully grouped such that a reasonably consistent annual series could be generated.

Table 6: Comparisons of Change in Trade across Data Series, Pork Industry

|Period |Live Swine |All Pork |Fresh Pork |Processed Pork |

|Imports | | | | |

|Avg. Change, 1959-1963 |7.3% |3.4% |-3.1% |4.4% |

|Change, 1963-1964 |27.9% |-2.5% |2.9% |-3.2% |

|Avg. Change, 1963-1965 |111.2% |11.4% |18.8% |10.5% |

|Avg. Change, 1965-1970 |85.5% |11.6% |5.0% |12.5% |

|Change, 1970-1971 |-2.0% |-3.2% |-5.7% |-3.0% |

|Avg. Change, 1970-1972 |33.8% |5.8% |12.7% |5.1% |

|Avg. Change, 1983-1988 |29.1% |9.9% |22.5% |2.8% |

|Change, 1988-1989 |27.6% |-12.8% |-17.0% |-8.6% |

|Avg. Change, 1989-1994 |-3.3% |-0.5% |3.1% |-4.2% |

| | | | | |

|Exports | | | | |

|Avg. Change, 1959-1964 |39.0% |19.3% |89.7% |-8.3% |

|Change, 1964-1965 |-18.1% |-0.3% |9.1% |-24.5% |

|Avg. Change, 1972-1977 |21.8% |42.5% |46.2% |16.0% |

|Change, 1977-1978 |35.0% |2.7% |-4.8% |114.6% |

|Avg. Change, 1983-1988 |25.5% |16.6% |18.0% |4.4% |

|Change, 1988-1989 |-58.3% |16.4% |17.3% |4.0% |

|Avg. Change, 1989-1994 |88.1% |11.5% |11.0% |22.3% |

For the pork industry, three groups of products were constructed: live swine, fresh pork and pork products, and processed pork products. The distinction between fresh and processed pork is generally the preservation of meat through drying, salting, or canning. Fresh pork products are generally composed of both pork carcasses and pork cuts and parts that are chilled, frozen, or fresh. In some cases, imports and exports were tracked at different levels of aggregation, making the distinction between fresh and processed items difficult to ascertain. However, the vast majority of pork products in terms of value were comparable over time for both imports and exports. Table 6 presents value information for pork trade around these classification and series changes. For the sake of brevity, series changes that occur over multiple sequential years, such as 1963-1965 for imports, are presented as averages across the sequential transitions and as year-over-year changes from the previous series.

Table 7: Comparisons of Change in Trade across Data Series, Tobacco Industry

|Period |Tobacco Leaf |Non-cigar Tobacco |Tobacco Products |Cigarettes |

| | |Leaf | | |

|Imports | | | | |

|Avg. Change, 1959-1963 |-2.8% |-0.9% |-6.7% |-1.2% |

|Change, 1963-1964 |10.9% |6.5% |49.9% |1.2% |

|Avg. Change, 1963-1965 |14.4% |16.6% |22.7% |-6.2% |

|Avg. Change, 1965-1970 |0.0% |-1.3% |26.5% |67.5% |

|Change, 1970-1971 |-30.9% |-35.7% |17.5% |373.5% |

|Avg. Change, 1970-1972 |6.0% |9.2% |23.8% |152.0% |

|Avg. Change, 1983-1988 |7.3% |8.8% |-15.2% |23.7% |

|Change, 1988-1989 |2.1% |0.7% |2.6% |33.6% |

|Avg. Change, 1989-1994 |12.4% |12.7% |32.2% |72.8% |

| | | | | |

|Exports | | | | |

|Avg. Change, 1959-1964 |3.7% |3.5% |7.0% |6.4% |

|Change, 1964-1965 |-7.3% |-8.5% |-6.6% |-8.1% |

|Avg. Change, 1972-1977 |11.6% |11.6% |21.9% |25.2% |

|Change, 1977-1978 |24.1% |22.7% |20.2% |21.9% |

|Avg. Change, 1983-1988 |-2.3% |-2.9% |20.9% |20.4% |

|Change, 1988-1989 |3.5% |4.3% |26.2% |27.3% |

|Avg. Change, 1989-1994 |0.9% |1.5% |9.5% |9.9% |

Manufactured tobacco product classification was similar for both imports and exports at a general level, and three product types are available: cigars and cheroots, cigarettes, and other tobacco products, which include smoking and reconstituted tobacco, chew, and snuff. For tobacco leaf, due to the very dissimilar systems employed to track imports and exports, direct comparability of imported to exported tobacco leaf can only be performed at a broad level. Two broad classifications are generated for the entire study period: non-cigar tobaccos; and cigar tobaccos, which include cigar binders, wrappers, and fillers. However, within the export data, this study will retain a detailed distinction corresponding to the types identified by Table 2. Table 7 details the consistency of the broad groups of tobacco and tobacco products across the classification systems presented in Table 5.

2.3.4 State Policies and Institutions

The presence or absence of relevant state and Federal policies and the industry contexts that exist within each state serve as measures of the institutional explanation. While the first set of variables directly impacts the state’s agricultural producers, the second represents a potential for action, not an explicit measure of action. If the markets-as-politics approach is correct, industry context will be directly related to the form resultant state policy takes. The time series approach utilized in the modeling portion of the project will allow for a direct comparison between these two sets of variables, and it is expected that both sets of variables will be highly correlated. However, the inclusion of measures of industry context will serve to capture unobserved state policies.

Relevant policies vary with respect to the two industries. For hog farming, limits on the development or expansion of CAFOs and hog farms more generally, limits on corporate farming, and limits on consolidation or coordination between farmers and manufacturers represent the most significant forms of state intervention. Due to the visibility of environmental problems associated with increasing CAFO size, a number of states passed limitations on the expansion or formation of these types of operations, which affects the geographical distribution of the industry (Sullivan, Vasavada, and Smith 2000). Corporate farming restrictions are especially important to this industry because of the geographical concentration of restrictions to the Midwest (Edmonson and Krause 1978; Matthey and Royer 2001) and because corporate farming is associated with livestock CAFO production because of the relatively coordinated relationship between farmers and processors and because of the relatively high capital needs of these operations (Flora 1998). Finally, high levels of concentration among meatpackers, the captive nature of farming to these packers, and the especially strong drive for coordination leads to an impetus address pricing controversies and the abilities of farmers to exert some control over prices in some cases (Hahn 2002; though see Rhodes 1995 for opposite state reaction based on job losses to other states). As a result, many of the corporate farming restrictions enacted during the twentieth century sought to limit vertical integration and control aspects of contract production in livestock, not just to limit the ownership of land by corporations.

Tobacco’s status as a crop covered by Federal price support greatly reduces the impact that U.S. states may exert. Its geographical concentration in the South further limits state-level institutional variation as it pertains to the structure of the agricultural sector, labor conditions, and state government activism and implementation of policy (James 1986). Two policy differences, the applicability of the Federal price support system to the tobacco produced in the state and the degree to which marketing and production quotas may be transferred by various means are assessed. Quota transfer, which allows the agglomeration of production to where it is most efficient, is a function of both the Federal and state-level decisions (Gale, Foreman, and Capehart 2000:36).

Finally, these direct impacts are coupled with the industry context that exists within the state. Multiple measures are implemented, including substantial importance of the industry to the state, the presence or absence of large producers as the dominant form of industry production in the state, the importance of agriculture in general to the state, and other characteristics of industry production. Similar variables are included for the manufacturing component of the industry. Thresholds and decision rules utilized to generate these variables are discussed in the modeling chapter.

2.4 Conclusion

The following two case studies center on the industries included in this study. The overarching objectives are to describe the structure and operation of each industry, to address the changes present in each industry, to present a preliminary assessment of causality based the actions of industry actors and changes in domestic and global demand, to assess differences from the general industry picture at the state level, and to justify the inclusion of particular variables as valid operationalizations of the concepts of importance in the modeling chapter. Within each industry, farming activities are contextualized by the trends that are evident within agriculture more generally, such as the increasing specialization of production at the farm level and the growing size of farm operations.

The case studies utilize the global value chains conceptualization of the industry to delineate the principal actors and their relationships. Actors will possess different strategic interests and different capacities for action as they attempt to realize their interests (Gereffi 1994). The principal outcome for these chapters will be a determination of causality for industry change during periods of presence or absence of exogenous changes in demand. To this end, a timeline of major industry developments will also be presented.

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[1] The industry shipments value is based on product-level disaggregation of the non-poultry meatpacking industry. By contrast, all other industry groupings are based on industry-level definition. Employment is estimated based on the proportion of non-poultry meatpacking product shipments composed by pork products in each industry segment. Please see Appendix A for more detailed information.

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