expanding biodegradable polymer resin use: assessing the aggregate impact on the us economy

ELSEVIER

Expanding biodegradable polymer resin use: Assessing the aggregate impact on the US economy

E. Douglas Beach

Ohio Department of Aging, Columbus, OH, US4

Roy Boyd

Department of Economics, Ohio University, Athens, OH, USA

Noel D. Uri *

Natural Resources and Environment Division, Economic Research Service, U.S. Department of Agriculture, Washington, DC, USA

This paper assesses the aggregate impact of the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins on the US economy. The analytical approach used consists of a computable general equilibrium model composed of 14 producing sectors, 14 consuming sectors, 6 household categories classified by income, and a government. The results suggest that for a $l.OO/lb of resin subsidy, the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins will result in an increase in output by all producing sectors of 0.067% or about $542 million, a rise in the consumption of goods and services of about 0.003% or $110 million, a rise in total utility of 0.004% or $168 million, and a net increase in government expenditures of 0.047% or $369 million. The agricultural sectors would be affected. For example, with a subsidy to promote the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins, output in the program crops sector (primarily corn) will expand (by about $431 million), output in the livestock sector will increase (by about $27 million), and output in all other agriculture commodities sectors will be increased (by about $192 million). When a larger subsidy of a $3.50 /lb for the production of cornstarch-based biodegradable polymer resins is considered, the effects are comparable to the $l.OO/lb subsidy case. The differences between the impacts of the two subsidies are primarily with regard to the order of magnitude of the changes in the equilibrium values of the prices and quantities.

Keywords: biodegradable, polymer resins, computable general equilibrium model, environmental degradation, U.S. economy

1. Introduction

Address reprint requests to Dr. N. D. Uri at ERS/NRED/PMTB, Room 428, United States Department of Agriculture, 1301 New York Avenue,

NW, Washington, DC 20005-4788, USA.

Received 16 January 1995; revised 2 October 1995; accepted 11 October

1995.

* The views expressed are those of the authors and do not necessarily

represent the policies of the organizations with which they are affiliated.

Senior authorship is not assigned. The authors would like to thank the anonymous referees for suggestions.

Mounting environmental concerns have focused attention on designing materials that are recyclable and/or degradable while retaining their performance characteristics. Biodegradable polymers provide an appealing approach to material design because their use in place of petroleum- based plastic materials and resins slows the introduction of fossil fuel-derived carbon dioxide into the atmosphere.‘,’ This is because incineration and biological digestion of renewable biomass simply recycles carbon dioxide and leaves it at its preexisting level. Note that the American Society for Testing and Materials is finalizing a technical

Appl. Math. Modelling 1996, Vol. 20, May 0 1996 by Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010

0307-904X/96/$15.00 SSDI 0307-904X(95)00158-1

Expanding biodegradable polymer resin use: E. D. Beach et al.

definition of a biodegradable polymer and it is their definition that will be used. Biodegradable polymers are those polymers that degrade primarily through the action of microorganisms such as bacteria, fungi, algae, and/or yeasts.

Two essential steps occur in the biodegradation process including depolymerization which occurs outside the mi- croorganism due to the size of the polymer chain and the insoluble nature of many of the polymers and mineralization whereby the cell derives metabolic energy from the mineralization process leaving behind carbon dioxide, methane, nitrogen, water, salts, minerals, and biomass.3 Thus biodegradation relies on microbes and their enzymes to convert organic matter into water, carbon dioxide, cellu- lar material, and mineral salts. Also note that recycling is an alternative way of achieving similar environmental goals. In fact many believe that integrated waste management practices, including recycling and composting of biodegradable wastes, may bring waste disposal in the United States under control4 Recycling is not evaluated here. The subsequent analysis is focused on cornstarch- based biodegradable polymer resins and their potential effects on agricultural sector output and prices.

The main uses of biodegradable polymer resins are for items where disintegration after use is a direct benefit. Examples include agricultural mulch films, planting containers and protectors, hay twine, surgical stitching, medicine capsules, and composting bags.5*6

Biodegradable polymer research has developed plastic resins that can include up to 50% cornstarch.‘,’ Wide-scale adoption of biodegradable polymer resins has the potential of increasing industrial cornstarch demand which would have impacts carrying back into the agricultural sector if cornstarch technologies capture the major portion of this market. Such an assumption is employed here. This simpli- fies the analysis while recognizing that the various biodegradable polymer technologies could use corn, wheat, or potato starch for production. Furthermore since many of the inputs used to produce biodegradable polymers are highly substitutable, there would be positive feedback effects in each related market. Consequently the choice of substrate is not crucial.

2. Background

As noted previously, biodegradable polymer resins com- pete in the plastic materials and resins market in the form of mulch films, planting containers, hay twine, surgical stitching, medicine capsules, and composting bags. The output from this market includes commodity resins such as high, low, and linear-low density polyethylene, polypropylene, polystyrene, polyvinyl chloride, and polyethylene terephthalate. Between 1987 and 1992, the value of ship- ments for the overall industry grew from $26.2 billion to approximately $31.3 billion. Based on constant 1987 dollars, this translates into a 4.6% annual increase.’

Approximately 65.4 billion lb of resins were produced in 1992. Low density polyethylene accounted for 19% of the 1992 market; high density polyethylene, 16%; polyvinyl

chloride, 15%; polypropylene, 13%; polystyrene, 8%; and more than 18 other materials account for the remainder of the resins market.’

The single use items that can be replaced by biodegradable polymer resins are manufactured from a few classes of commodity resins. These include high and low density polyethylene, polypropylene, polystyrene, terephthalate, and polyvinyl chloride. Of the 16.5 billion pounds of plastics used in packaging in 1992, various forms of polyethylene and polystyrene accounted for 62.4% or 10.3 billion lb.9

In 1992 biodegradable polymer resins captured less than 5 million lb or roughly 0.08% of the plastic materials and resins market. The market potential, however, is substantial. The total nonfood packaging market for low density polyethylene in 1992 was 2.68 billion lb.3 Note that degradable food packaging will not be addressed here because the Food and Drug Administration has not estab- lished guidelines for its use. Consequently nonfood packaging is taken as the key market. Additionally note that low density polyethylene is used in the manufacture of trash bags, diaper backing, and agricultural mulch films.

In terms of material characteristics, biodegradable polymer resins are an excellent substitute for these petroleum- based resins.“, ’ By comparison, total 1992 sales of high density polyethylene were 10.4 billion lb. These resins are used to produce durable products and consequently are not as amenable to biodegradable polymer resins substitution as are low density polyethylene resins. There are, however, some potential applications including nonfood bottles, films and sheeting, and consumer packaging.”

The technology exists for biodegradable polymer resins to significantly replace petroleum-based plastic materials and resins in the nonfood packaging market.5,12 The reason that biodegradable polymer resins are not making greater inroads into this market currently is because of relative costs.i3 In 1992, the most recent period for which reliable data are available, petroleum-based resins cost an average of $0.50/lb while cornstarch-based biodegradable polymer resins cost between $1.50 and $4.00/lb.” Given the pre- vailing situation and short of a legislative mandate (there is currently no discussion of such an initiative) to increase the use of biodegradable polymer resins, an increase will require some sort of active government intervention in the market for plastic materials and resins. There are a number of ways the government can intervene to accomplish this including subsidies to producers of biodegradable polymer resins and taxes on consumers of petroleum-based plastic materials and resins. To determine what is required and the extent of the benefits and costs of such intervention, an objective assessment will be made in what follows.

Before doing this, however, it is important to realize that there are interrelationships that must be captured in any such analysis. For example the feedstock used in the manufacture of petroleum-based plastic materials and resins

a Note that there is also inherent value in biodegradability. This value,

however, is difficult to quantify and hence not explicitly included in the

analysis.

Appl. Math. Modelling, 1996, Vol. 20, May 389


by the chemicals and plastics sector is produced by the petroleum refining sector which in turn gets its primary input from the crude oil sector. The feedstock used in the manufacture of cornstarch-based biodegradable polymer resins by the chemicals and plastics sector comes from the agricultural sector. Thus an increase in the manufacture of cornstarch-based biodegradable polymer resins at the ex- pense of petroleum-based plastic materials and resins will directly affect a number of sectors including crude oil, petroleum refining, agriculture, and chemicals and plastics. Moreover there will be a number of indirect effects as the demand for factor inputs and processed inputs by the directly affected sector changes in response to changes in the composition of the output. To accurately measure the benefits and costs associated with the increased production of biodegradable polymer resins and the reduced production of petroleum-based plastic materials and resins in response to the government intervention, these indirect effects as well as the direct effects must be computed. To do so requires the use of a computable general equilibrium model.

3. The modelling approach

Given the interrelationships between the sectors directly involved in producing plastic materials and resins and the rest of the US economy, to analyze properly the replace- ment of petroleum-based plastic materials and resins with cornstarch-based biodegradable polymer resins, a comprehensive analysis must be employed, one where the link- ages between sectors of the economy are explicitly taken into account and one where the price responsiveness of producers and consumers both to absolute and relative changes in the prices of the various goods and services is considered. The analytical approach used will be a computable general equilibrium model that has been disaggregated into 14 producing sectors, 14 consuming sectors, 6 household (income) categories, and the government. This level of disaggregation allows for an assessment of the

direct effects as well as the indirect effects of substituting cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins. By measuring these effects, it is possible to identify the extent to which the agricultural sector (e.g., corn producers) and the other producing and consuming sectors and household groups stand to gain or lose. Hence equity considerations as well as efficiency considerations can be addressed. Thus the incidence of substituting cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins is endogenous to the analysis with no prior assumptions being made. Before conducting the analysis, a brief overview of the model will be provided.

4. The general equilibrium model

The use of a general equilibrium approach to analyze the effects of substituting cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins is reasonable given the interactions between partici- pants within the plastic materials and resins market as well as other interrelated markets.14-” Note that the adoption of a general equilibrium model approach to assess the effects of substituting cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins on the economy is unique to this study. There are no previous efforts using this methodology.

The model used follows in the tradition of the Shoven and Whalley ‘* tax analysis research and incorporates some of the methodological enhancements of the general equilibrium work of Hudson and Jorgenson.‘g,20 For example it recognizes the differences in preferences of consumers as a function of their incomes and specifies a distinct demand system for each group of households. Additionally a neo- classical microeconomic model of producer behavior is employed. The model of consumer behavior is integrated with the model of producer behavior (which contains a price-responsive input-output component) to provide a comprehensive framework for policy simulations.

Table 1. Classification of producing sectors and consumer goods and services.

Industries Consumer goods

1. Manufacturing 2. Coal mining 3. Other mining 4. Service 5. Chemicals and plastics 6. Food and tobacco products 7. Petroleum refining 8. Financial 9. Forestry

10. Wood products 11. Crude oil and natural gas 12. Agriculture 1 - Program crops 13. Agriculture 2 - Livestock 14. Agriculture 3 - All other

Agriculture

1. Food 2. Alcohol and tobacco 3. Utilities 4. Furnishings and appliances 5. Housing 6. Clothing and jewelry 7. Transportation 8. Financial services 9. Other services

10. Motor vehicles 11. Gasoline and other fuels 12. Reading and recreation 13. Nondurable household items 14. Savings

390 Appl. Math. Modelling, 1996, Vol. 20, May


4.1. The producing sectors

The production sector of the model consists of an input- output matrix with some flexibility with regard to the substitution of the factor inputs (capital, labor, and land). Technologies are represented by production functions that exhibit constant elasticities of substitution. Technological progress (both embodied and disembodied’l) is assumed not to occur over the period of investigation. Each sector as defined in Table 1 is assumed to have a constant elasticity of substitution (CES) production function22 where the value added by the specific sector is a function of labor and capital. Note that there is a transformation matrix whereby raw inputs in the producing sectors are trans- formed into consumption goods and services. Thus the fact that agricultural goods are combined with, say, manufactured goods, chemicals and plastics, and transportation to produce plastic materials and resins is reflected via this transformation matrix.

For four sectors (the three agricultural sectors and the forestry sector), however, a third factor of production - land - is included. This is done because of the special importance of this input to these sectors.23 The incorpora- tion into the production function of this factor is accom- plished by nesting the CES production function. In particular an input is defined that is solely a function (in CES form) of land and capital, which in turn takes the place of capital in the original production function specification. Note that while it would be possible to simply add land as an explicit input in the production function, this would implicitly assume that the elasticity of substitution between all pairs of inputs are the same. By nesting, however, the substitution elasticities are permitted to be different between different inputs.

4.2. The consuming sectors

On the demand side, the model reflects the behavior of consumers (who can also serve as investors), the government, and foreigners. Consumers are grouped according to income (indicated in Table 2) and a demand system is specified for each group. Each income group has an endowment of labor and capital and, given the vector of prices, decides the amount to save and invest and the amount of each good and service to consume (purchase). Investment consequently is determined by savings.

The output of the 14 producing sectors accrues to the owners of the factors of production (i.e., land, labor, and capital) which they sell. With the receipts from sales, these individuals either consume domestic or foreign goods and services, save, or pay taxes to the government. The savings

Table 2. Household categories based on income.

Category Income range

I $O-9,999 II $10,000-19,999 Ill $20,000-29,999 IV $30,000-39,999 V $40,000-49,999 VI $50,000 and over

are used for investment and the taxes are ultimately re- turned to these individuals. The demand for final goods and services comes from three primary sources: (1) final goods and services which are directly consumed by individuals, (2) investment (which is equal to savings), and (3) foreign demand.

A review of Table 1 will show that the composition of the consumer goods and services sectors does not match that of the producing sectors because the final goods and services produced by the producing sectors must go through various channels (i.e., transportation and distribution) before they can be consumed. To address this problem, a transformation matrix is introduced that defines the contri- bution of each producing sector to the composition of each of the final (consumer) goods and services.

For each category of households (Table 2), utility is assumed to be a weighted CES function of the 14 consumer goods and services. The weights on these goods and services (which are household category specific) are computed as the share of total purchases going to a specific consumer good or service. The nature of the CES utility function implies that the elasticity of substitution is the same between any pair of goods and/or services. Because reliable estimates of the respective substitution elasticities across pairs of goods and/or services is difficult to obtain, they are assumed to equal one for all of the combinations. Finally consumers obtain utility from the consumption of all goods and services including leisure (consumer good and service sector number 12). Hence it is necessary to determine a weight for this factor in the utility function. For the purpose of the current analysis, this value is assumed to be 0.5 times labor income. The net effect of adding leisure is to incorporate explicitly the fact that consumers not only derive utility from the act of consuming goods and services (which comes through owning the factors of production) but that they also derive utility from leisure. Thus an increase in leisure can lead to an enhance- ment of individual well being in the model.

A household’s budget constraint is defined such that expenditures on goods and services must be less than or equal to its income, which is defined to equal its portion of the returns to labor plus the returns to capital plus the returns to land. That is expenditure by a household must be less than or equal to the total factor payments it receives. Maximizing utility subject to this expenditure constraint gives the demand for the various goods and services by household categories (see, e.g., Mixon and Uriz4 for a discussion of this). Observe that since savings are considered as one of the items in an individual’s utility function, the choice between consumption and savings is made explicit. That is intertemporal tradeoffs are an integral part of the model.

The second component of the demand for goods and services is investment. Like the final demand by individuals, total investment is disaggregated (though a transformation matrix) by the sector of the economy that produces it. For the purpose of constructing the general equilibrium model and calibrating it, investment is taken directly from the national income and product accounts (as compiled by the Bureau of Economic Analysis of the US Department of Commerce) and, since savings are assumed to exactly



equal investment, personal savings are scaled to equal the gross investment observed (measured) for each of the 14 producing sectors.

The final component of demand for goods and services is the demand by foreign consumers. The foreign sector produces imports and consumes exports. Trade balance is assumed (that is the nominal value of exports is assumed to equal the nominal value of imports in equilibrium) but the exchange rate is not explicitly incorporated into the model specification. Exports are scaled to match imports. As a result, foreigners can be regarded as consumers who purchase United States exports with income from the sale of imports to the United States.

In the model exports (i.e., foreign demand) are delin- eated by producing sector. In other words a transformation matrix analogous to that used for the consumption of final goods and services is employed. A similar delineation is utilized for imports (i.e., foreign supply). The exports and imports are then scaled so that the total foreign account is balanced. By employing elasticity estimates (both demand and supply) found in the literature, export and import demand relationships are constructed for each producing sector.

4.3. The government sector

The government levies taxes on both production and consumption. That is there are taxes on factors of production, on output, on income, and on consumption. Revenues are used to distribute income back to consumers and to purchase goods and services as well as capital and labor.

There is a question of how to treat the government in a general equilibrium model. For the purpose at hand, it is treated as a separate sector with a constant elasticity of substitution utility function. The elasticity of substitution is assumed to be one. This means that the CES production function collapses to a Cobb-Douglas-type production function. The government collects tax revenue in various forms. The explicitly considered taxes include personal income tax, labor taxes (e.g., a social security tax), capital taxes (e.g., a corporate income tax), property taxes, and sales and excise taxes. All these are treated as ad valorem taxes, and a marginal rate is used for each household category, consumer good and service sector, producing sector and factor input. In this respect, the model is a distinct improvement over earlier general equilibrium mod- els” which simply employed lump sum transfer schemes or used average tax rates.

4.4. A mathematical statement of the model

Given these foregoing considerations, it is useful to state precisely the conditions that the model being used here must satisfy for a general equilibrium to exist. First there cannot be positive excess quantities demanded. That is,

m C aijMj - Ei(p, Y) 2 0 for pi 2 0 (1)

j=I

and where i(i = 1, 2,. . . , n) denotes the consumer goods and services, Mj(j = 1, 2,. . . , m) denotes the activity lev-


els, aij denotes the ijth element in the activity analysis matrix, Y denotes a vector of incomes for the k consumers, p denotes a vector of prices for the n consumer goods and services, and Ei denotes the excess demand for a good or service i.

The second requirement for general equilibrium is that the profits associated with a given activity are not positive. That is,

- i aijpi 2 0 for Mj 2 0 i=l

(2)

Finally, all prices and activity levels must be nonnega- tive. That is,

~~20, i=1,2 ,..., n (3a)

and

Mj20, j=1,2 ,.,., m (3b)

The model is solved for a general equilibrium using the iterative algorithm nominally referred to as the sequence of linear complementary problems (SLCP) developed by Mathiesen.2 ,26 This algorithm is based on the fixed point theorem proved by Scarfz7 A complete listing of the equilibrium conditions together with relevant definitions is found in the Appendix.

5. Data for the 1988 base year

The general equilibrium model is calibrated for 1988. For each of the 14 producing sectors, data on capital receipts and taxes are computed from reports of the Bureau of Economic Analysis of the US Department of Commerce, the US Department of Agriculture, the US Department of Energy, and from Hertel and Tsigas.28 The various elasticities of substitution employed in the analysis were obtained from Boyd.29

Capital income (earnings) and labor income were obtained from the Bureau of Economic Analysis of the US Department of Commerce. Land income was estimated using factor shares obtained from the Economic Research Service of the US Department of Agriculture and applied to the capital income component noted above.

Data on expenditures on each of the 14 goods and services by each of the 6 household categories were obtained from the Consumer Expenditure Survey: Interview Survey, 1984.30 By combining this information with the number of households in each household (income) category (these data come from the Bureau of Economic Analysis), the aggregate expenditures on each category of consumer goods and services by each household category were computed.

The various tax rates used in the analysis were obtained from a variety of sources including the Internal Revenue Service, the Economic Research Service of the Department of Agriculture, Hertel and Tsigas2’ and Ballard, et a1.14 These rates, as noted previously, are marginal rates.

The value of exports and imports in 1988 were taken from the Survey of Current Business (various issues) with the exception of the energy data which were obtained from


Table 3. Equilibrium prices (normalized) and quantities fin hundreds of billions of dollars) for the producing sectors.

Reference case $1.00 resin subsidy Percent

Sector Price Quantity Price Quantity change '

1 Manufacturing 1 .ooooo 22.39780 1 .ooooo 22.39631 - 0.0067 2 Coal Mining 1 .ooooo 0.28022 1.00001 0.28022 0.0000 3 Other Mining 1 .ooooo 0.23889 0.99983 0.23892 0.0142 4 Service 1 .ooooo 34.07910 0.99999 34.07990 0.0023 5 Chemicals 1 .ooooo 3.37973 1.00001 3.38017 0.0130 6FoodandTobacco 1 .ooooo 3.85858 0.99985 3.85905 0.0122 7 Petroleum Refining 1 .ooooo 1.64365 1.00003 1.64390 0.0152 8 Financial 1 .ooooo 8.60249 1.00003 8.60285 0.0042 9 Forestry 1 .ooooo 0.15030 1.00147 0.15018 - 0.0838

10 Wood Products 7 .ooooo 2.28792 1.00006 2.28780 - 0.0052 11 Crude Oil 1 .ooooo 1.15147 1.00005 1.15151 0.0034 12 Agriculture - PC * 1 .ooooo 0.72850 0.99294 0.73281 0.5919 13 Agriculture - L 1 .ooooo 1.41446 1.00024 1.41473 0.0191 14 Agriculture - 0 1 .ooooo 0.69644 1.00106 0.69663 0.0275

Total 1 .ooooo 80.90956 0.99995 80.91498 0.0067

’ The percent change represents the percentage change in the equilibrium quantities between a $1.00 subsidy for the production of cornstarch-based biodegradable polymer resins and the reference case. * For the agriculture sectors, PC denotes program crops, L denotes livestock, and 0 denotes all other agricultural activities. Also some of the other titles have been abbreviated. The complete titles are given in Table 7.

the Energy Information Administration ment of Energy and the agriculture obtained from the Economic Research Department of Agriculture.

of the US Depart- data which were Service of the US

6. Results and discussion

As noted previously, there are a number of ways that biodegradable polymer resin use can be expanded through government intervention in the plastic materials and resins market. In the current analysis, it will be assumed that the government provides a subsidy to plastic materials and resin producers sufficient to make the cost of comstarch- based biodegradable polymer resins comparable to the cost

of petroleum-based resins so that the former can be eco- nomically substituted for the latter. As noted above, cornstarch-based resins currently cost between $1.00 and $3.50 more that petroleum-based resins. This being the case, two separate scenarios will be investigated, one using the lower bound estimate and the other using the upper bound estimate.

What does such a subsidy imply for the use of corn? Wet corn milling yields between 33 and 35 lb of starch per 56 lb bushel of corn. Multiplying the number of pounds of resin by the percentage of cornstarch used in a particular technology gives an estimate of the number of pounds of cornstarch needed for the given amount of resin. Dividing the number of pounds of cornstarch needed by 34 (the pounds of cornstarch per bushel of corn) gives the number

Table 4. Equilibrium prices (normalized) and quantities fin hundreds of billions of dollars) for the consuming sectors.

Reference case $1.00 resin subsidy Percent

Sector Price Quantity Price Quantity change ’

1 Food * 2 Alcohol and tobacco 3 Utilities 4 Furnishings 5 Housing 6 Clothing 7 Transportation 8 Financial services 9 Other services

10 Motor vehicles 11 Gasoline 12RandR 13 Nondurable goods 14 Savings

Total

1 .ooooo 5.49502 0.99988 5.49578 0.0138 1 .ooooo 1.10121 0.99993 1.10131 0.0091 1 .ooooo 1.97800 0.99999 1.97805 0.0025 1 .ooooo 1.26292 1 .ooooo 1.26293 0.0008 1 .ooooo 5.52584 1.00002 5.52584 0.0000 1 .ooooo 2.64025 1 .ooooo 2.64030 0.0019 1 .ooooo 0.39274 0.99999 0.39275 0.0020 1 .ooooo 1.78548 1.00003 1.78545 -0.0017 1 .ooooo 7.64462 1 .ooooo 7.64472 0.0013 1 .ooooo 3.03739 1 .ooooo 3.03744 0.0016 1 .ooooo 0.85038 1.00002 0.85038 0.0007 1 .ooooo 2.69636 1.00002 2.69634 -0.0007 1 .ooooo 1.21342 1 .ooooo 1.21344 0.0016 1 .ooooo 2.66049 0.99999 2.66049 0.0000 1 .ooooo 38.28412 0.99999 38.28522 0.0029

’ The percent change represents the percentage change in the equilibrium quantities between a $1.00 subsidy for the production of cornstarch-based biodegradable polymer resins and the reference case. * Note that some of the sector titles in the table have been abbreviated. The complete designations are given in Table 7.


Expanding biodegradable polymer resin use: E. 0. Beach et al.

of bushels of corn required to produce the given quantity of resin.3

6.1. Reference case

The reference case results (both quantities and normalized prices) for the computable general equilibrium model are presented in Tables 3, 4, and 5 for the producing sector, the consuming sector, and households (income categories), respectively. Note that the nominal values of the quantities are in hundreds of billions of 1988 dollars. The sector numbers and category numbers correspond to those used in Tables 1 and 2. By themselves, the values found in Tables 3, 4, and 5 provide little useful information beyond show- ing how the model is calibrated. Rather the significance of the general equilibrium model and of the equilibrium values is in how these values change in response to the policy initiative that perturbs the general equilibrium.

6.2. A $l.OO/lb subsidy for the production of cornstarch- based biodegradable polymer resins case

The results for a $l.OO/lb subsidy for the production of cornstarch-based biodegradable polymer resins case are presented in Tables 3, 4, and 5. Also indicated in these tables are the percentage changes in the equilibrium quantities in the producing sectors, consuming sectors, and households as a result of the substitution of cornstarch- based biodegradable polymer resins for petroleum-based plastic materials and resins.

In response to the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins, total output in the producing sectors will rise by 0.013% or by about $542 million. Note that these and other effects are in terms of the annual impacts. This increase, however, is somewhat misleading since it is not spread uniformly across producing sectors. For example, the output of the agricultural program crops sector, wherein is contained corn production, will expand by 0.592% ($431 million). The price of corn would fall both in relative and absolute terms. This is the result of the relative shifts in the demand and supply of corn. While the demand for corn increases as cornstarch-based biodegrad-

able polymer resins are substituted for petroleum-based resins, the supply of corn increases relatively more in response to the changing output price relationships among the agricultural sectors and the forestry sector. In fact, as the price of corn increases initially in response to the increased demand for cornstarch and hence corn, factors of production including land are diverted from the production of forestry products (whose output declines by 0.08% [$12 million]) to the production of corn. With the decline in forest product output and a relative increase in its price, output in the wood products sector likewise declines by 0.005% ($12 million).

The other sector adversely affected in terms of reduced output is the manufacturing sector. The fall in the output of this sector by 0.007% ($150 million) is the consequence of a reduction in government expenditures brought about by a decline in its revenues. A substantial portion of government expenditures are directed at the manufacturing sector.

Also, contrary to initial expectations, the output in the petroleum refining sector actually increases by 0.015% (25 million). A priori it is anticipated that as cornstarch-based polymer resins are substituted for petroleum-based plastic materials and resins, the demand for refined petroleum products would decline. As a result of the subsidy for cornstarch-based polymer resins, however, there is a reduction in the price of these resins relative to the price of petroleum-based plastic materials and resins with the consequence that more are exported increasing the available foreign exchange that can be used to acquire imports. Some of these imports come in the form of crude oil which is an input into the petroleum refining sector.

Output in the other producing sectors will, in general, increase although the magnitude of sector-specific effects are somewhat variable. For example, for the service sector, output increases by 0.002% ($80 million) while the food and tobacco sector output increases by 0.012%. These changes are primarily the result of consumers adjusting their consumption of goods and services in response to changes in relative prices. The output in the coal mining sector declines as imported crude oil is substituted for coal as a boiler fuel in the generation of electricity and for some industrial steam applications.

A number of things will happen in the agricultural sectors, some of which have been previously noted. In

Table 5. Equilibrium utility levels fin hundreds of billions of dollars) by household categories.

$1 .OO resin Reference case subsidy Percent

Category utility level utility level change ’

12 2.46324 2.46349 0.0101 II 5.03590 5.03631 0.008 1 Ill 7.73044 7.73077 0.0042 IV 8.03519 8.03546 0.0033 V 6.36474 6.36486 0.0018 VI 16.71871 16.71900 0.0017 Total 46.34821 46.34989 0.0036 Government 7.71151 7.70781 - 0.0470

’ The percent change represents the percentage change in the equilibrium quantities between a $1.00 subsidy for the production of cornstarch-based biodegradable polymer resins and the reference case. * Note that the household categories correspond to those defined in Table 2.



addition to those effects previously noted, output in the livestock sector will increase by 0.019% ($27 million) and output in the all other agriculture commodities sectors will rise by 0.028% ($19 million) because the price of the output in the agriculture-program crops sector falls and this is an input into the other two agricultural sectors.

With regard to the consuming sectors, the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins results in an increase in the consumption of goods and services by about 0.003% ($110 million). The most beneficially affected sector in relative terms is the food sector which experiences a 0.014% ($76 million) increase in consumption. The second most significantly affected sector (in percentage terms) is the alcohol and tobacco sector which realizes a 0.009% ($10 million) rise in consumption. Most other sectors experience minimal changes attributable to the indirect effects of substituting cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins. These indirect effects include a slightly higher real income (brought about by a reduction in the price of corn) and changing relative prices (which leads to substitution of relatively less expensive goods and services for relatively more expensive).

Aggregate utility rises. This increase is equal to 0.004% ($168 million) for all household categories. The increase, however, does not fall evenly across households. Category I and Category II households realize a larger increase in utility than households with relatively higher incomes since the prices of the goods and services for which they spend a relatively larger proportion of their income falls relative to the prices of other goods and services. Thus when all of the effects of the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins are considered (that is both the direct and the indirect effects), the policy option is in general progressive. In other words the substitution of cornstarch- based biodegradable polymer resins for petroleum-based plastic materials and resins benefits most the lowest household (income) categories and progressively fewer households with larger incomes. The effects, however, are extremely modest, almost to the point of insignificance.

The government does realize an increase in expenditures relative to revenue as a result of the subsidy to promote the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins. The aggregate effect is a net increase in government expenditures by 0.047% or about $369 million. The revenue to cover the increased expenditures come from the increase in tax receipts from both the producing and consuming sectors.

In sum the effects of a subsidy to promote the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins will be an increase in output by all producing sectors of 0.067% or about $542 million, a rise in the output of agriculture-program crops (corn) sector of 0.592% ($431 million), a rise in the consumption of goods and services by about 0.003% or $110 million, a rise in total utility by 0.004% or $168 million, and a net increase in government expenditures of 0.047% or $369 million.

6.3. A $3SO/lb subsidy for the production of cornstarch- based biodegradable polymer resins case

The qualitative effects of a $3.50/b subsidy for the production of cornstarch-based biodegradable polymer resins are comparable to the $l.OO/lb subsidy case. The differences between the impacts of the two subsidies are primarily with regard to the order of magnitude of the changes in the equilibrium values of the prices and quantities. For this reason, a complete listing of the results are not presented. (They are available upon request.) In the $3.50/b subsidy case, the production of goods and services will increase by 0.021% ($1.703 billion), output in the agriculture-program crops sector (e.g., corn) will increase by 1.859 ($1.354 billion), and output in the chemicals and plastics sector will expand by 0.041% ($138 million).

The consumption of goods and services will increase by 0.009% ($335 million) with consumption increasing most in the food sector (by 0.041% or $226 million) and in the alcohol and tobacco sector (by 0.028% or $31 million).

Utility will increase for each household category with the aggregate increase approximating 0.011% ($504 million). As before, the subsidy is progressive. The govem- ment will see its expenditures increase relative to revenue by 0.149% ($1.152 billion) as it pays for the subsidy.

7. A comparison

The two existing economic studies on the effects of substituting cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins are partial equilibrium in nature. The first by Coble et al.31 uses a nonlinear mathematical programming model of the agricultural sector to examine the potential economic impacts. Assuming that 50% of the petroleum-based resins are replaced by cornstarch-based polymer resins under the existing farm program as detailed in the Food, Agriculture, Conservation, and Trade Act of 1990 (the 1990 Farm Bill) and that the price of cornstarch-based biodegradable polymer resins are 115% of those of petroleum-based plastic materials and resins, corn output will expand by 2.6%, consumer welfare will decline by 0.008% because consumers must pay the increased deficiency payments associated with expanded corn production through higher taxes (an assumption in the model), and government farm program payments expand by 0.52%. Beyond the fact that the relative price assumption associated with the two different types of resins is not accurate based on current cost estimates (see above), the partial equilibrium nature of the model used in the analysis does not capture any beneficial effects of the expansion in corn and cornstarch production on other sectors of the economy and, consequently, the aggregate impact of the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins is understated.

Beach and Price,3 also using a partial equilibrium farm sector model for individual commodities and based on the 1990 Farm Bill, find that with an assumption that 50% of the petroleum-based resins are replaced by cornstarch-based polymer resins, the increase in cornstarch-based biodegrad-



able polymer use is very small (0.076%). Corn production expands minimally by 0.003% (289,000 bushels), and deficiency payments by the government actually fall by 0.265% ($5.628 million). This latter result is somewhat anomalous given that deficiency payments to the other agricultural sectors remained virtually unchanged.

8. Sensitivity analysis

No analysis is complete without an examination of the sensitivity of the results to key assumptions. In the foregoing discussion, many assumptions were made with regard to model structure and parameter estimates. A full examination and discussion of these assumptions would be virtually impossible. Consequently only the results from the sensitivity analysis of one crucial assumption will be discussed. Namely what are the effects on the vector of equilibrium prices and quantities of the assumption concerning the elasticity of substitution between corn and refined petroleum in the production of polymer resins? The original point estimate of this elasticity was 1.0 (i.e., the Cobb-Douglas case). In subsequent simulations, however, it was lowered to 0.5 and then raised to 1.5. In general the effect of raising the elasticity of substitution to magnify the influence of the subsidy while lowering it mitigates its impact. The quantitative effects, however, on the results are minimal. Under both the $l.OO/lb subsidy and the $3.50/lb subsidy, neither output nor consumption nor total utility are affected by more than $50 million and in no case is there any change in the qualitative results discussed previously.

These sensitivity results suggest that the value of the substitution elasticity, while important in the determination of the vectors of general equilibrium prices and quantities and significant in determining the implications of a policy initiative affecting biodegradable polymer resins, is not so pivotal to the model that an error in its value leads to misleading and nonsensical results.

9. Conclusion

The foregoing analysis has examined the effects of the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins on the US economy. The analytical approach used in the study consisted of a computable general equilibrium model composed of 14 producing sectors, 14 consuming sectors, 6 household categories classified by income, and a government. The results suggest that, for example for a $l.OO/lb of resin subsidy, the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins will result in an increase in output by all producing sectors of 0.067% or about $542 million, a rise in the consumption of goods and services by about 0.003% or $110 million, a rise in total utility by 0.004% or $168 million, and a net increase in government expenditures of 0.047% or $369 million.

The agricultural sectors would be affected. For example, with a $l.OO/lb subsidy to promote the substitution of cornstarch-based biodegradable polymer resins for

petroleum-based plastic materials and resins, output in the program crops sector (primarily corn) will expand (by about $431 million), output in the livestock sector will increase (by about $27 million), and output in the all other agriculture commodities sector will be enhanced (by about $192 million).

When a larger subsidy of a $3.50/lb for the production of cornstarch-based biodegradable polymer resins is considered, the effects are comparable to the $l.OO/lb subsidy case. The differences between the impacts of the two subsidies are primarily with regard to the order of magnitude of the changes in the equilibrium values of the prices and quantities.

Finally the magnitude of the results from this study differ somewhat from the results of other studies of the issue because the other studies are partial equilibrium in nature and consequently do not capture the indirect effects of substituting cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins on the other producing sectors, including the other agricultural sectors, of the US economy.

As a consequence of this analysis, the implications of the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins are clear. Namely most producing sectors benefit although a few are adversely affected in terms of reduced output. The various consuming sectors would experience a cumulative rise in the consumption of goods and services. These changes, however, are relatively modest.

Beyond these quantifiable effects on production, consumption, and utility, there will be difficult-to-quantify improvements in the environment. (Note that the computable general equilibrium model used in the analysis does not have an environmental component because ele- ments of environmental quality are extremely difficult to quantify let alone interrelate with the various producing and consuming sectors of the US economy.) In the aggregate, there will ostensibly be a general improvement in environmental quality as cornstarch-based polymer resins are substituted for petroleum-based plastic materials and resins although there will be some environmental degradation associated with expanded corn production.32 Finally, while the substitution of cornstarch-based biodegradable polymer resins for petroleum-based plastic materials and resins will retard the buildup of inert substances thereby helping with waste management, the Environmental Pro- tection Agency feels that there are as yet too many unan- swered questions concerning the impact of biodegradable polymers in different environmental settings such as the impact of small pieces of degrading polymers in terrestrial and aquatic ecosystems and the effect of degradable polymers on recycling programs to mandate their increased use.l’

Appendix. Empirical model I. Overall equilibrium by sector

Y)+GEi++Mi

= c RASiL + GDi + CDi + UX, + IWi (1) L



CSL,=CDL~+GDL (2) c j

CSK,=CDK,+GDK (3)

~s~~=~oo,+cDD (4) c j

where

GDL = cTLi

GDK= cTKi (6)

GDD= cTDi (7)

II. Consumer goods and services

Co, = cZ,;[GCEj - TCj] i

CRCS,, = GCE,

CRCS,, =SL,+SK,+SD,+ TRNc-PIT, (10)

GC, = CRCS,, -SAV,

+(l - TAU,)(ZTA,- l)SL, (11)

GC, = SL, +SK, +SDc + TRN,-PIT,

+(1- TAU,)(ZTA,- l)SL, (12)

TE= ~[SL,ZTA,TAU,+SK,TAU, +SD,TAU,

-(@c,+T~)I (13) where Qc,= SL,TAU,+SK,TAU,+SD,TAU,-PIT,

III. Foreign sector balance

C {U~j[ EM,/(l + EM,)] + UM,/(l + EM,)) i

= c(Ux,+FE,)

IV. Consistency

C(SL,+SK,+SD,+TRN~-PIT,-TC,)

= CCC,

(14)

(15)

(Net household income equals household expenditures)

C (GSK, + GE, + TL,+ TK~+ TD~ + TXO,)+ GTL

= CTRN+ C[(GDK, + GDj)+ GD,] (16) c i

(Government income plus endowments equals government outlays)

c@JIWj- ux,) =o (17)

(Net exports equal zero)

C(CD,+GD~+UX,-GE~-UM~)

= C(DL~+DK~+TL,+TK,+TXO~) (18)

(The value of demand equals value added plus taxes)

2D. GE: UiIi C, lL4SjL

Total production in sector j (j = 1, 2,. . . ,14) Consumer demand for product j Government endowment of product j Imports of product j RAS balanced input-output intermediate de- mands

GDj IWj ux,

SL, SK, SD, DL, DKj DDj GDL GDD

TL, TK,

3Ei

‘ji

RCS,,

TC,

TW PIT, TAU,, SAV,

GCc ZTA TE EMj FEj

Government demand for product j Investment in sector j Exports of product j Supply of labor by household c(c = 1, 2,. . . ,6) Supply of capital by household c Supply of land by household c Demand for labor in the industry j Demand for capital in the industry j Demand for land in industry j Government demand for labor Government demand for land Tax on labor in industry j Tax on capital in industry j Tax on land in industry j Consumer demand for consumer product i (i = 1, 2,. . . ) 14) A 14 X 14 transformation matrix RAS balanced matrix of each household’s demand for each consumer good Excise tax on consumer good j Transfer payment to household c Personal income tax payment for household c Marginal income tax rate for household c Savings in household c Gross consumption of household c Consumption plus leisure coefficient Total government endowments Demand elasticity of export demand Endowment/demand sector of adjusted elasticity of export demand

GSKj Government endowment of capital in industry j GDKj Government demand for capital in industry j GTL Government wage taxes on its own employees TXOj Government output tax on industry j

TCc Consumption taxes on household c

CGc Total government consumption by household c

Nomenclature

k ‘ij

Y k

consumer goods and services denotes the activity levels the ijth element in the activity analysis matrix a vector of incomes for the k consumers the number of consumers

APP~. Math. Modelling, 1996, Vol. 20, May 397


P

Li i

the vector of prices for the n consumer goods and services number of goods and services the excess demand for a good or service i a good or service

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