AN ECONOMIC ASSESSMENT OF THE EMERGING RENEWABLE CHEMICAL AND POLYMER CLUSTER IN OHIO WITH ESTIMATED ECONOMIC IMPACT ON THE STATE’S ECONOMY
THESIS
Presented in Partial Fulfillment of the Requirements for the Degree of Master of Science
in the Graduate School of The Ohio State University
By
Kathryn S. Ellis, B.S.
The Ohio State University 2009
Master’s Examination Committee: Approved by
Dr. Thomas L. Sporleder, Advisor
Dr. Neal Hooker ______Dr. Stephen C. Myers Advisor
Agricultural, Environmental, and Development Economics Graduate Program
ABSTRACT
The economic impact of the chemical and polymer cluster in Ohio in terms of output, gross state product, income and employment is analyzed in this research. The chemical and polymer cluster positively affects the state’s economy, representing 5.5 percent of Ohio’s gross state product, 9 percent of its output, over 6 percent of its income and 3 percent of the state’s employment. The chemical and polymer cluster represents
2,729 establishments in Ohio. This research employs the methods of input-output analysis to determine the chemical and polymer cluster state impact.
The emerging renewable polymer industry, which provides benefits such as reducing environmental impacts and employing biomass as opposed to crude oil feedstock, is important to Ohio’s future. This industry has the potential to increase output, income, gross state product, and most importantly employment in Ohio. This research utilizes growth rates in three scenarios to determine renewable polymer industry’s affect in Ohio. The renewable polymer industry is estimated at representing over a 12 percent share of Ohio’s polymer sector in the year 2020 in terms of gross state product and employment.
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DEDICATION
Dedicated to my nieces and nephews: Carlie, Marci, Nathan, and Mitchell
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ACKNOWLEDGEMENTS
I wish to thank my advisor, Dr. Thomas Sporleder, for his support and encouragement which has made this degree possible. I appreciate his guidance and intellectual discussion that has contributed greatly to my knowledge and understanding of agricultural economics. His leadership and patience throughout the construction of this thesis is immeasurable.
I would also like to thank Florian Diekmann for his devotion to this project and his many hours of help in creating this thesis. He is a wealth of knowledge that I greatly appreciate. His direction throughout the assembly of this thesis is something I am very thankful for.
Many thanks go to my classmates Daniel Sanders, Ryan Kirwin, Jenny Lau, Matt
Woerman, Lauren Jones, Chris Reece and John Gober. Without them, getting through our Master’s courses would have been impossible! I thank them for their continued friendship. I also wish to thank the rest of the AEDE faculty for their insightful conversation and faith in me over the past six years.
Finally, I wish to thank my mother and father, my sister Sarah and my boyfriend
Patrick for their encouragement and patience over the past two years.
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VITA
April 1, 1985………………………………Born in Wilmington, Ohio
March 2006-March 2009……………….....Research Assistant
The Ohio State University
June 2007………………………………….B.S. in Agribusiness and Applied Economics
The Ohio State University
September 2007-March 2009……………..Graduate Studies, Agricultural Economics
The Ohio State University
FIELDS OF STUDY
Major Field: Agriculture Applied Economics
Area of Emphasis: Finance and Agribusiness
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TABLE OF CONTENTS
Abstract ...... ii
Dedication ...... iii
Acknowledgements ...... iv
Vita ...... v
List of Tables ...... ix
List of Figures ...... xi
CHAPTER 1 ...... 1
INTRODUCTION ...... 1 1.1 Research Need ...... 3 1.2 Research Objectives ...... 8 1.3 Research Methods ...... 9 1.4 Research Justification...... 11 1.5 Overview of Research ...... 12
CHAPTER 2 ...... 14
LITERATURE AND RESEARCH REVIEW ...... 14 2.1 Industry Clusters ...... 14 2.2 Input-Output Analysis ...... 18 2.3 The Polymer Industry ...... 21 2.3.1 Terms Defined ...... 21 2.3.2 Historical Development of the Chemical and Polymer Industry ...... 26 2.3.3 Ohio’s Chemical and Polymer Industry ...... 27 2.4 Renewable Polymer Industry ...... 29 2.4.1 Current Renewable Polymer Market ...... 29 2.4.2 Renewable Polymer Pricing ...... 32 2.4.3 Stimuli for a Renewable Polymer Industry ...... 33 2.5 Industrial Activity in Ohio ...... 35 2.5.1 Agriculture Industry in Ohio ...... 39
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CHAPTER 3 ...... 40
METHODS AND DATA ...... 40 3.1 Overview ...... 40 3.2 I-O Modeling Fundamentals ...... 42 3.3 I-O Modeling Characteristics ...... 44 3.4 Limitations of the I-O Model ...... 45 3.5 Data Collection, Organization ...... 46 3.5.1 IMPLAN Database ...... 46 3.5.2 Number of Establishments ...... 48 3.5.3 Growth Estimates ...... 49 3.6 Modeling with IMPLAN ...... 49
CHAPTER 4 ...... 51
RESULTS 1: THE IMPACT OF THE CHEMICAL AND POLYMER INDUSTRY ON OHIO’S ECONOMY ...... 51 4.1 The Ohio Chemical and Polymer Cluster Model Definition ...... 51 4.2 Results ...... 54 4.2.1 Overview of the Chemical and Polymer Industry in Ohio: Output, GSP, Income and Employment ...... 54 4.2.2 Exports of Ohio’s Chemical and Polymer Cluster ...... 60 4.2.3 Impact Multipliers of Ohio’s Chemical and Polymer Cluster ...... 61 4.2.4 Regional Purchase Coefficients of the Ohio Chemical and Polymer Cluster 62 4.2.5 Number of Establishments of Ohio’s Chemical and Polymer Cluster ...... 63
CHAPTER 5 ...... 65
RESULTS 2: THE IMPACT OF A RENEWABLE POLYMER INDUSTRY ON OHIO’S ECONOMY ...... 65 5.1 Trends in the Renewable Chemical and Polymer Industry ...... 66 5.1.1 The BREW Project ...... 69 5.2 Objectives for Determining the Impact of a Renewable Chemical and Polymer Cluster in Ohio ...... 70 5.3 Methodology and Data ...... 71 5.3.1 Scenarios ...... 71 5.3.2 Technical Substitution ...... 74 5.4 Results of Scenario Analysis ...... 76
CHAPTER 6 ...... 80
Conclusions ...... 80
APPENDIX: ...... 83
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TABLES DESCRIBING THE ECONOMIC IMPACT OF A RENEWABLE POLYMER INDUSTRY IN OHIO ...... 83
BIBLIOGRAPHY ...... 117
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LIST OF TABLES
Table 1: Global Consumption of Biodegradable Polymers (tons), (Platt, 2006, page 42). 5
Table 2: Most Important Types of Bio-based Polymer Groups, (Source: Crank et. al., 2005, page 34) ...... 25
Table 3: Global Consumption of Biodegradable Polymers by End Use, Percent Share, 2005 (Source: Platt, 2006, page 9) ...... 31
Table 4: U.S. Renewable Polymer Producing Companies and Market Share, 2005 (Source: GIA, 2006, page III-3) ...... 31
Table 5: Annual Sales of Biodegradable Polymers for 2006 and Projections for 2007- 2013, thousand pounds (Source: GIA, 2006, III-3) ...... 32
Table 6: Growth in polymer industry by product (various references, various years) ..... 68
Table 7: Projected volumes of GSP for the Paint and Coating Manufacturing industry in the OCPCM in three scenarios. (Computed) ...... 73
Table 8: Projected volumes of PET and technical substitution ratios for its bio-based counterpart, PLA under three scenarios (percentages represent the amount of the market that is biobased). (Computed) ...... 75
Table 9: Projected impact of the bio-based portion of the paint, coating, and adhesive sector based on technical substitution potentials under the Most Likely scenario. Ratios are from PET in Table 8 above. PET is a polymer used in paint, coating, and adhesive manufacturing. Underlying assumptions include keeping costs, revenues, et cetera constant from year to year. (Computed) ...... 76
Table 10: Ohio: Output, Gross State Product, Income, and Employment, Disaggregated Sectors, 2007 (Computed)...... 84
Table 11: Ohio: Output, Gross State Product, Income, and Employment, Aggregated, 2007 (Computed)...... 86
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Table 12: U.S.: Output, Gross Domestic Product, Income and Employment, Aggregated, 2007 (Computed)...... 88
Table 13: Contributions of the Polymer, Chemical, and Petroleum Cluster to Ohio Exports, Domestic and Foreign, Disaggregated, 2007 (Computed)...... 90
Table 14: Contributions of the Polymer, Chemical, and Petroleum Cluster to Ohio Exports, Domestic and Foreign, Aggregated, 2007 (Computed)...... 92
Table 15: Ohio Economic Multipliers: Output, GSP, Income, and Employment, Disaggregated, 2007(Computed)...... 93
Table 16: Ohio Economic Multipliers: Output, GSP, Income, and Employment, Aggregated, 2007 (Computed)...... 95
Table 17: Regional Purchase Coefficients Disaggregated, OCPCM 2007 (Computed) . 97
Table 18: Regional Purchase Coefficients, Aggregated, OCPCM 2007 (Computed). .... 99
Table 19: Number of Establishments for Ohio’s Chemical and Polymer Cluster, 2007 (Source: US Census Bureau, County Business Patterns, 2006) ...... 100
Table 20: NAICS – IMPLAN Concordance related to OCPCM Sectoring Scheme ..... 102
Table 21: Ohio: Scenario Projections of Growth in the Chemical and Polymer Cluster using GSP to year 2020. (Computed) ...... 111
Table 22: Ohio: Scenario Projections of Growth in the Chemical and Polymer Cluster using Employment to Year 2020. (Computed) ...... 112
Table 23: Year 2020 Technical Substitution Ratios for Bio-based Chemicals, matched to NAICS codes under the Polymer Sector of the OCPCM. (Compiled from: (Crank, et.al., 2005; Patel, et. al., 2006)) ...... 113
Table 24: Renewable Polymer Sector Impact on Ohio’s GSP, last column is the bio- based share of the polymer sector industries in 2020 (Computed) ...... 115
Table 25: Renewable Polymer Sector Impact on Ohio’s Employment, last column is the bio-based share of the polymer sector industries in 2020 (Computed) ...... 116
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LIST OF FIGURES
Figure 1: Percent Share of Biodegradable Polymers Consumption by Region, 2005, (Platt, 2005, page 42) ...... 5
Figure 2: Distribution of GSP among the various industries comprising the chemical sector of the OCPCM (Computed) ...... 57
Figure 3: Distribution of GSP among the various industries comprising the polymer sector of the OCPCM (Computed) ...... 58
Figure 4: Share of jobs among the polymer sector of the OCPCM (Computed) ...... 59
Figure 5: Regional Purchase Coefficients for the industries representing the Chemicals Sector of the OCPCM (Computed) ...... 63
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CHAPTER 1
INTRODUCTION
When asked to describe a ‘polymer,’ many people may be baffled and find it difficult to define. Although polymers are something people learn about in an early chemistry class and are often associated with some difficult chemistry concept, people encounter polymers every day. A simple definition of a polymer is something made up of many (poly) units. These many units are called monomers and are constructed of a small number of atoms, commonly carbon and hydrogen. These linked monomers
(polymers) are found in humans, animals, plants, minerals, and many manufactured products. Such familiar polymers in the world are DNA, protein, hair, paint, nylon, plastics, and tires. Polymers are associated with many of the benefits people enjoy in the modern world such as shelter, communication, safety, sports, health and so on.
Many of the manufactured polymers used today are derived from crude oil, a characteristically volatile feedstock in both economic and political terms in regard to crude oil dependence and fluctuating prices. However, the first polymers were developed from renewable materials prior to crude oil gaining share due to its lower costs.
Nonetheless, interest in renewable material sources for polymers has reemerged in recent 1
years due to rising real petroleum prices, concerns regarding environmental impacts, and national security issues related to petroleum resources (Crank et al., 2005; Chemical
Market Resources, 2008). Because of advances in biotechnology, biobased chemicals and renewable polymers 1 are becoming competitive with petroleum-based polymers in
cost, performance, and other additional advantages such as helping to reduce greenhouse
gas emissions (Paster, et. al., 2003). Additional drivers for the biobased chemical and
renewable polymer market include the desire for sustainability through renewable
sourcing, reduction of dependency on fossil fuels, and the decreasing available landfill
space (Chemical Market Resources, 2008). Although there are many reasons for
advocating the adoption of biobased production, there are also market barriers such as
relatively higher production costs and depreciated capital investments in conventional
technology (Dornburg, et. al., 2008). In addition, retailer skepticism about performance,
switching costs, and lack of consumer awareness of benefits of this industry all serve as
barriers (Chemical Market Resources, 2008).
Although polymer manufacturing is already a major part of Ohio’s economy,
renewable polymers made from biomass have the potential to change Ohio’s economic
base and promote economic growth, for example, in job creation (TFR, 2008). A recent
research study noted that the chemical and polymer industry in Ohio is known as a
“hidden gem” or an industry considered as ‘world-class’, but that is not marketed
effectively to outside industry players (Deloitte, 2005). Although this is so, presently no
research has been conducted to estimate the potential benefits or costs of a renewable
1 See Chapter 2 for an explanation of the use of the term “renewable”.
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polymer industry to Ohio’s economy (TFR, 2008). A closer look at the cost-performance ratio of biopolymers must be estimated to make sound economic decisions about the future (Swift, 1998). This study attempts to fill this void and aims to define and quantify selected economic factors of the emerging renewable polymer cluster in Ohio. Within this chapter the research need, objectives of the research, research methods, and justification of the research are presented to better understand the goal of this research.
1.1 Research Need
A critical driver in the push to incorporate biobased chemicals and renewable polymers into the polymer market is the industry’s dependence on crude oil. Traditional, petroleum-based chemicals and polymers utilize oil as a raw material, as a source of energy for production and also in its transportation. Crude oil has become an increasingly scarce resource in high global demand, which causes its price to fluctuate.
Renewable materials are noted as having the ability to lessen the effects of the demand for crude oil and its uncertain supply and price (Conway & Duncan, 2006; Paster et al.,
2003), as well as limiting the environmental impact of using plastics products, which are produced from chemicals and polymers (Chemical Market Resources, 2008). The United
States Department of Energy projects worldwide demand for renewable materials to double by 2050, while crude oil demand will stay stable (United States Department of
Energy, 1999).
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With the adoption of environmentally friendly practices in the United States and the wish for more sustainable products 2, renewable polymers are desirable because of
their potential to reduce greenhouse gas emissions, lessen the carbon footprint, improve
waste disposal methods, and reduce landfill use (Crank et. al., 2005). U.S. businesses are
also adopting policies to promote environmental and social responsibility such as
initiating more sustainable materials, for example, in product packaging (Brody, 2006).
Businesses do this mainly to enhance their market position as they try to conform to what
their consumers want (FPA, 2006).
There are already a number of renewable polymers available in the world market.
Examples can be found in applications including adhesives, bottles, coatings, fiber,
textiles, medicine, film and food packaging and utensils (Chemical Market Resources,
2008). One particular example of a product that utilizes bioplastic is the tractor hood and
side panels of the John Deere Series 9000 four-wheel drive tractor (Society of Plastics
Industry, 2008). Other examples of renewable polymers on the market include polylactic
acid by NatureWorks and copolyester by DuPont (Society of Plastics Industry, 2008).
Europe is ahead of the United States in production and consumption of renewable
polymers, primarily due to more government regulation for things such as diverting
packaging waste towards recycling and composting (Platt, 2006). Europe also benefits in
that many of the world’s leading biodegradable producers are located within the country,
such as BASF and Novamont (Platt, 2006). Western Europe holds 59% of the share of
2Sustainable is defined as meeting the needs of the present without compromising the ability of future generations to meet their own needs (Society of Plastics Industry, 2008).
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polymer consumption, followed by North America with 22% of the share and Asia
Pacific countries with 19%. Even so, United States’ consumption of renewable polymers is predicted to rise by an annual rate of 22 percent. (TFR, 2008) Table 1 shows a comparison of the expected growth of renewable polymers in each region while Figure 1 shows a graphical representation of the percentage share of consumption of biodegradable polymers by region in 2005.
Region 2000 2005 2010 % CAGR '05-'10 Western 15.5 55.7 129.4 18.4 Europe North America 6.7 21.3 46.5 16.9 Asia Pacific 5.8 17.8 38.5 16.7 Total 28 94.8 214.4 17.7
Table 1: Global Consumption of Biodegradable Polymers (tons), (Platt, 2006, page 42).
Asia Pacific 19% North America 22% Western Europe 59%
Figure 1: Percent Share of Biodegradable Polymers Consumption by Region, 2005, (Platt, 2005, page 42) 5
Ohio provides great prospects for a renewable-based polymer market. The polymer industry in Ohio is its largest manufacturing industry and is expected to grow
(TFR, 2008). Among the various advantages Ohio has in regards to adopting renewable polymers is its geographic location and established infrastructure. Ohio has the supply chain and logistics presently in place. Polymer companies in Ohio have access to the I-
71 corridor as well as Lake Erie and the Ohio River, which are all conducive to polymer production. According to a cluster analysis conducted by Deloitte, many customers and suppliers for the chemical and polymer industry are located in Ohio, meaning that Ohio is positioned well for the emerging renewable sector (Deloitte, 2005). Because of this, the concept of industry clusters will be used in this analysis to define what industries are included in the chemical and polymer definition. An industry cluster consists of a group of local industries that are closely linked by and benefit from local supply networks, local customer networks, common labor markets, and access to technical expertise (Shields,
2003).
Additional benefits include that Ohio has a history of innovation, business leadership, an available workforce, and education and research capabilities in order to make the adoption of renewable polymers successful (OBIC, 2008). Ohio is also home to an abundance of natural and agricultural resources that could help the state capitalize on opportunities in renewable polymers (TFR, 2008).
Development of a market for renewable polymers would be advantageous for
Ohio because there is the potential to link the state’s two top industries, polymers and agriculture, which alone represents $98.2 billion in annual revenue (Sporleder, 2007a).
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Essentially, the motive to link the two industries lies in the desire to find alternative feedstocks to petroleum, which has a high cost and uncertain supply. An example of linking the two industries would be growing corn on Ohio farmland and using the starch from this corn to produce polylactic acid through fermentation (Dale, 2003). Battelle believes Ohio’s economic future lies in linking the two industries in order to create novel biotechnologies in the polymer sector and thus new business opportunities (TFR, 2008).
The aforesaid is all significant testimony to the economic opportunity available to
Ohio in the emerging renewable polymer industry. For Ohio’s economy to capitalize on this opportunity, priority must be placed on additional economic analysis that will define and evaluate the industry’s current status and future potential in a renewable polymer industry. Such items as job creation and revenue generation for the state could be measured. Because of the expected advantages of a renewable polymer cluster, there is a need to discover the current size of this industry and its growth potential in Ohio.
Growth potential of the renewable polymer industry has not yet been estimated quantitatively for the state, even though many of the drivers for this industry suggest growth is inevitable. The results of this analysis will not necessarily claim that a renewable polymer industry should be constructed, but it gives industry stakeholders quantifiable information on which to base decisions about its approval. When completed, this model may have the ability to be expanded to serve larger regions and other renewable clusters.
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1.2 Research Objectives
With the advancement of technologies related to the renewable polymer sector,
Ohio has been introduced to an array of economic opportunities. Although Battelle conducted a very significant study of the polymer industry’s economic impact in
Northeast Ohio (Battelle, 2004b), what is not known is the magnitude of the emerging renewable polymer cluster and the future potential of it to all of Ohio. Because this information is not known, it makes it difficult to encourage private sector firms to both make the investment necessary to evolve into leading producers of renewable products in
Ohio and to take advantage of the renewable feedstocks grown in-state, as stated in section 1.1. This work will be valuable for policy making decisions in the state. This research will define the economic impact of an emerging renewable polymer cluster to
Ohio and provide an economic assessment of the market opportunity for renewable polymers in Ohio. Four more precise objectives have been established in order to accomplish this goal:
Objective 1: To determine economic size and markets of the emerging renewable
polymer cluster in Ohio
Objective 2: To evaluate the market growth potential for renewable polymer
production in Ohio
Objective 3: To evaluate the impact on Ohio’s economy of feedstock production
for production of renewable polymers in Ohio
Objective 4: To estimate economic multipliers for the renewable polymer cluster
in Ohio
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1.3 Research Methods
Because development of the chemical and polymer industry into a resulting renewable polymer industry will not solely affect its own industry, it is important to analyze its economic impacts in a supply chain context. Describing the chemical and polymer supply chain in this research will allow for a better design of the research model and allow supply chain managers to apply more effectively in the real world the knowledge gained from this research (Kadipasaoglu, et. al., 2008). Polymers are part of the chemical industry and constitute about 80% of the chemical industry’s output
(Kadipasaoglu et. al., 2008). For this reason, in this analysis the manufactured polymer supply chain is defined as petroleum and natural gas at the beginning of the supply chain, then chemicals, polymers, related mold and equipment manufacturing, and chemical and polymer wholesale. In order to ensure that all industries under these sectors are covered, the Department of Energy report “Top Value Added Chemicals from Biomass, Volume
1” Figure 3 will be used as a starting point, which identifies chemicals used in the renewable realm (United States Department of Energy, 2004). Interviews with polymer engineers and consultants will be conducted to make certain all industries, in terms of a representation of NAICS codes in the chemical and polymer supply chain, are represented in the model.
The concept of an industry cluster provides the framework for which the Ohio
polymer and chemical industry will be defined in this analysis. The state’s polymer
industry definition will be constructed with the use of top-down analysis, where
petroleum, chemical and polymer NAICS industry codes will be used to outline Ohio’s
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polymer cluster. Also, the fact that most of the current polymer companies in Ohio are located in the northeastern corner of the state will help determine the industry cluster in this analysis by identifying the chemical and polymer industries in that location. The polymer cluster definition is a tool used in the execution of the methodology applied in this research, input-output analysis.
The economic theory base for this research is the observation that goods and
services are produced because there is a demand for them. Input-output modeling is a
method for examining changes in final demand. Input-output (I-O) analysis is the
technique of tabulating and describing the linkages or interdependencies between various
industries within an economy (Blair and Miller, 1985). I-O modeling captures what each
sector purchases from every other sector to produce a dollar’s worth of output. The
input-output modeling and the modeling software IMPLAN Professional will be used in
this analysis.
To obtain information on market growth potential for renewable polymer
production, estimates will be gathered from secondary literature available in the public
domain from such resources as past market research reports and American Chemistry
Council reports. This method of gathering growth estimates is preferred as opposed to
meeting with company personnel (i.e. Goodyear staff) where information can be
confidential or a meeting hard to obtain.
When gathering growth estimates for the chemical and polymer industry, a
scenario analysis will be used; the scenario analysis of growth estimates will be a vital
part to the output of the model in this analysis. Because growth rates for future years are
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usually estimates, three scenarios will be constructed to reflect a low growth rate, a high growth rate, and a most likely growth rate (see example in Dornburg, et. al., 2008). The most likely growth rate will be the estimate collected from secondary literature. The low and high growth rate scenarios will be deviations below and above the most likely figure.
To gain knowledge of the polymer industry more generally, use of existing
secondary economic data will be used. Such items as key trends and macro-
environmental drivers of the renewable polymer industry in Ohio will be studied. This
information is available in the public domain, open literature, and from plastics and
polymer trade associations.
Interindustry data on sales, output, employment, et cetera will be obtained from
IMPLAN databases with the use of the software package IMPLAN Professional Version
2.0. IMPLAN is a well-documented input-output model that is widely in use today.
IMPLAN uses secondary data based on the national economy. Estimates of sectoral
activity for final demand, final payments, industry output, and employment for the Ohio
economy will be calculated based on 2007 data through aggregating the detail of
IMPLAN’s 440 industries of the state’s economy. The input-output model created in this
research is known as the Ohio Chemical and Polymer Cluster Model (OCPCM).
1.4 Research Justification
The information provided as a result of this research will generate insight into the current status and potential future market opportunities of the renewable chemical and polymer industry in Ohio. This newly discovered information can be used to encourage
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private sector firms, who were previously hesitant to adopt new practices without valid proof of its potential success, to make the investment necessary to become leading producers of novel polymer products within the state and country. This will, in turn, help to maintain and enhance the competitive position of the polymer industry in Ohio. This analysis will provide important information into the feasibility of the development of a renewable polymer market. Research into this field would inform the industry of the potential opportunities and risks of a renewables market in the state; this information will improve Ohio’s ability to be “first to market” with new products from this sector (TFR,
2008). This research and the OCPCM will have the ability to be expanded to serve larger regions, such as the United States, and other renewable clusters.
1.5 Overview of Research
This chapter outlines the research need, objectives, methodology, and justification of this research on the economic assessment of an emerging renewable chemical and polymer cluster in Ohio. A review of literature related to defining a cluster, the input- output model, Ohio’s current chemical and polymer market, and industry potential in
Ohio is discussed in Chapter 2. An explanation of the use of the term “renewable polymer” versus other popular names is defined in Chapter 2 as well. The discussions of
Chapter 2 provide the conceptual basis for the outset of this research. Chapter 3 consists of an in-depth explanation of the methods used in the research, the input-output model and IMPLAN; the chapter also exhibits the data collected and used in this analysis.
Chapter 4 explains the chemical and polymer industry definition as developed in this work as well as demonstrates the analysis and results of the chemical and polymer input-
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output analysis. Chapter 4 also includes a discussion on the Regional Purchase
Coefficients for Ohio in addition to an explanation of the economic multipliers generated by the cluster. Chapter 5 gives details and methodology on the scenario analysis applied to the input-output model, which is used to estimate growth rates for the renewable portion of the polymer industry in Ohio in the year 2020. Chapter 6 draws conclusions derived from the results of this research, such as the impact of the renewable polymer industry in Ohio.
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CHAPTER 2
LITERATURE AND RESEARCH REVIEW
This chapter discusses the literature and reviews research focused on the chemical and polymer industry and renewable polymer industry prospects in Ohio. The chapter also reviews literature on the drivers of the emerging renewable chemical and polymer industry in Ohio, as well as the benefits and drawbacks of a renewable polymer industry positioned in Ohio. To begin the chapter, literature is reviewed in regards to industry clusters, which will be used in defining the chemical and polymer industry in Ohio. The material in this chapter is aimed at providing a conceptual foundation for the arrangement and use of the input-output model utilized in this analysis.
2.1 Industry Clusters
Ohio ranked second in the nation in 2003 for output in the chemical and polymer
industry (Deloitte, 2005). The proximity and number of suppliers and consumers in the
state (Deloitte, 2005) provides an ideal method to analyze Ohio’s chemical and polymer
industry through what is known as industry clusters. An industry cluster is a group of
firms, related economic agents and institutions that are located near one another
(Cortright, 2006; Shields, 2003). These closely located firms often enjoy a production
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advantage because of their proximity to one another (Cortright, 2006). The potential to improve regional economies is a major advantage to industry clusters. Firms in an industry cluster have the advantage of local supply networks, local customer networks, common labor markets, and access to technical expertise in the region (Shields, 2003).
An industry cluster can help highlight the strengths and challenges of the local economy and then focus on the strengths to promote growth in the region (Shields, 2003).
Michael Porter of the Harvard Business School is credited with popularizing the term “cluster” in this context. Porter (1990) defines clusters as geographic groups of interconnected companies in a particular field. A cluster includes linked industries like suppliers of inputs and machinery services, distribution channels and customers, manufacturers of complementary products, companies related by skills or common inputs, and related institutions such as research organizations and universities (Porter,
1990). Other theorists disagree on what constitutes a cluster, so it is difficult to find a single, universal definition (Cortright, 2006). This disagreement lies in how the concept is used: as a way to organize local economic development efforts, develop empirical analyses of local economies, or as a way of theorizing about economic growth (Robinson,
2002.)
There are many dimensions to clusters such as geography, social distance,
technology, and production flow, but not all clusters operate in all dimensions. Porter
(1990) describes his idea of the “diamond of competitive advantage”, which illustrates
the idea of an industry cluster and how a company’s location affects its strategy and
performance. The four parts of the diamond explain why industry clusters are more
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competitive than isolated firms. The four parts of the diamond include factor conditions, demand conditions, related and supporting industries, and firm strategy, structure and rivalry (Porter, 1990). Factor conditions are factors of production from which all firms in the cluster draw, such as the labor force. Demand conditions encompasses the presence of demand that local customers have that cause firms in the cluster to continuously innovate, helping the firms to compete more successfully in global markets. The third part of the diamond, related and supporting industries, is locally based suppliers and related industries that form a support network for providers of firms. The forth portion of the diamond involves the strategy to upgrade and invest continuously to remain competitive. Because firms will compete with others within the cluster, they will differentiate themselves. Firm strategy and rivalry contribute to regional competitiveness.
The cluster is the diamond at work—proximity of firms, customers and suppliers to one another increases the pressure to innovate and upgrade (Porter, 1990). Several drivers cause clusters to exist. Because of the proximity of firms, the advantages include labor market pooling, supplier specialization, knowledge spillovers, entrepreneurs, culture, and local demand (Cortright, 2006).
Cortright outlines several ways to identify clusters (Cortright, 2006). One way is top-down analysis which relies on quantitative data to deduce the industrial structure of a regional economy (e.g., industry classification systems, input-output tables, location quotients). Location quotients measure the concentration of a single industry and the extent to which a region is more specialized in an industry than the nation as a whole.
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Location quotients could be used to measure the concentration of the chemical and polymer cluster in Ohio, for example. Although location quotients are important, clusters involve a number of firms in different industries. Input-output tables are used to discern localized connections between industries. They use sales data among firms in different industries to estimate the fraction of inputs used by one industry to purchase from all other industries in the economy. The results of the input-output tables only provide an approximation of likely flow, not a definitive link.
Another way to classify a cluster is to examine geographic variations in
employment among different industrial sectors through the use of the North American
Industrial Classification System (NAICS). If firms are in the same classification, then
they are assumed to be related (Cortright, 2006). Another way of identifying clusters is
bottom-up analysis which examines the inner workings and interfirm connections of a
particular cluster in a particular location (e.g., genealogies, case studies, commentary)
(Cortright, 2006).
Braunerhjelm and Carlsson (1999) deduced through literature two criteria for defining clusters: economic activities should be spatially concentrated and there should be a certain degree of interaction among these economic agents (Braunerhjelm &
Carlsson, 1999). Agglomeration of these firms is caused by supply and demand pulls
(market proximity provides access to suppliers and customers) and knowledge spillover
(Braunerhjelm & Carlsson, 1999). In Braunerhjelm and Carlsson’s cluster analysis, the location quotient was used to identify core industries, because a certain concentration of activity is required to form a cluster.
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The concept of an industry cluster provides the framework for which the Ohio
chemical and polymer industry will be defined in this analysis. The state’s chemical and
polymer industry definition will be constructed with the use of top–down analysis, where
chemical, polymer, and petroleum NAICS industry codes will be used to outline Ohio’s
chemical and polymer cluster. Also, the fact that most of the current chemical and
polymer companies in Ohio are located in the northeastern corner of the state, mainly due
to the of the range of markets in the area such as automotive, biomedical and construction
(Battelle, 2004b), will help determine the industry cluster in this analysis. The chemical
and polymer cluster definition is an implement used in the execution of the methodology
applied in this research, input-output analysis.
A cluster analysis conducted by Deloitte (2005) indicates that Ohio is positioned
well for the chemical and polymer industry due to its proximity to suppliers and
consumers. The study created a cluster by first identifying the “driver industries” (those
industries in the region which have the greatest competitive advantage) and then
identifying the competitive industry clusters related to each driver (the firms in the same
industry which have close buy-sell relationships, share similar labor, or use common
technologies) (Deloitte, 2005).
2.2 Input-Output Analysis
There are several methods available for estimating economic impacts that include
economic base approach, econometric estimation based on time-series or cross-sectional
data, and the method chosen for this analysis, input-output analysis (Coon & Leistritz,
2001; Pagoulatos, et. al., 1986). An input-output (I-O) model basically consists of a set 18
of linear equations where each equation explains the distribution of an industry’s production throughout other industries representing the rest of the economy (Blair &
Miller, 1985). Input-output analysis is based on data collected from industries and is a method of assessing relationships among businesses and between businesses and consumers (IMPLAN, 2004). Input-output allows one to examine the effects of a change in one industry on industries comprising the rest of the economy (IMPLAN, 2004).
Measuring the linkages between industries can exhibit how much of each industry’s output is consumed by other industries and how much is left for final consumption
(Sporleder, 2007a). Measures obtained through this modeling technique are estimates of the amount of direct purchases per dollar of output, total employment, income, contribution to gross state product, and the total dollar value of output.
The I-O model was developed by Wassily Leontief in the late 1930s and has been widely used to analyze changes in interindustry activity (Blair & Miller, 1985). The
United States’ Benchmark Study of Input-Output accounts is a popularly known use of the I-O model and provides detailed information of the structure of the U.S. economy in five-year intervals (Bureau of Economic Analysis, 2009). The I-O model has been used by development economists in the World Bank as a means to examine the elements of structural change and make sense of how these elements are related to each other (Lee and Schluter, 1993). I-O modeling was used by Deloitte, an Ohio-based consulting firm, along with Cleveland State University to assess Ohio’s economic position in several industries such as automobiles and pharmaceuticals (Deloitte, 2005). I-O modeling, as well as the IMPLAN software, as is employed in this analysis, was also used by Battelle in its economic assessment of the polymer industry in northeast Ohio (Battelle, 2004b). 19
The OHFood input-output model of the agri-food cluster uses a comparable framework and analysis that will be used in this work. The OHFood model is an input- output model aimed at describing the interindustry linkages of the food and agriculture- related cluster of Ohio (Sporleder, 2007a). The OHFood model is constructed of 19 sectors related to food and agriculture and 19 sectors related to the general manufacturing and service sectors of the economy (the result of the aggregation of individual sectors into large composite sectors). Also provided by the OHFood model are multipliers and regional purchase coefficients (RPC). RPCs represent the proportion of the total supply of a good or service used to fulfill the demands of a region that is supplied by the region to itself (Sporleder, 2007a).
Multipliers are provided by input-output analysis. Multipliers are used to show how important an industry is to a region or community (Beutler, 1992). In a basic example, multipliers are used to measure the direct or indirect effects a certain amount of production in a sector has on a region’s economy (Beutler, 1992). Multipliers have been used widely in the past for economic impact analysis purposes. For example, economic multipliers have been used to assess the potential economic impacts of recreation spending in Georgia, North Carolina, and South Carolina (Bergstrom, et. al., 1990).
Another example of past use of multipliers is estimating the economic impact of Florida’s citrus industry on the state’s economy (Hodges, et. al., 2001). Economic multipliers have also been used to estimate the impacts of tourism in a particular area (Wagner, 1997).
There are many applications of economic multipliers in the literature pertaining to all types of industries.
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2.3 The Polymer Industry
2.3.1 Terms Defined
Because an impact on Ohio’s polymer industry affects more than its own industry, a supply chain context will be used in this analysis. The supply chain discussed in this work is defined as a sequence of events in a good’s flow, which adds to the value of a specific good (Eye For Transport, 2008). This industry’s supply chain is therefore defined as beginning with petroleum feedstock, then to chemicals, polymers, machinery related to this industry, and ending with distribution. This context will allow for a complete impact analysis of this industry on this state. Polymers are actually a large subset of the chemical industry; the basic chemicals industry supplies the specialized chemicals (i.e. polymers) industry (Deloitte, 2005). Polymers constitute about 80% of the chemical industry’s production output (Kadipasaoglu, et. al., 2008). A polymer’s feedstock 3 is a by-product of petroleum or natural gas production (Kadipasaoglu, et. al., 2008).
There are other “definitions” of the U.S. polymer industry in the literature.
Deloitte performed a study on Ohio’s chemical and polymer industry using ten 4-digit
NAICS codes encompassing the chemicals industry, plastics products industry, rubber industry, pesticide and fertilizer industry, paint and coatings industry, clay products industry and the soap and cleaning compounds industry (Deloitte, 2005). Battelle conducted a study of Northeast Ohio’s polymer industry defining the industry using thirty-one 6-digit NAICS codes aggregated into ten subsectors encompassing tire manufacturing, paint and coating manufacturing, custom compounding of purchased
3 A feedstock is known as the raw material from which the good is made (Kadipasaoglu, et. al., 2008).
21
resins, foam products manufacturing, plastic bag manufacturing, and plastics and rubber products manufacturing (Battelle, 2004b). The Society of the Plastics Industry (SPI) also has a definition, but for the plastics industry alone. This definition uses seventeen 6-digit
NAICS codes covering plastics materials and resins manufacturing, plastics profile shape and fitting manufacturing, foam product manufacturing, plastic bottle manufacturing, and industrial injection-type molds made of plastics (Society of Plastics Industry, 2008). The methodology of defining the chemical and polymer industry that is employed in this analysis has been previously used, as noted by the studies mentioned earlier; however, none of these past works have used a supply chain approach to define the polymer cluster. This is one of the unique contributions of this research.
To facilitate a discussion about the chemical and polymer industry, it is first helpful to define the term “polymer”. Polymers are substances consisting of molecules made of repeating structural units, also called monomers, and connected by covalent chemical bonds (Cowie, 1991; Merriam-Webster Online Dictionary, 2008). There are four classes of polymers, which describe the physical state of the good. These classes are thermoplastics (when heated they flow), thermosets (solids), fibers, and films and coatings (Carlsson, 2002). Some well-known examples of polymers include rubber, starch, plastics, DNA, and proteins (Chemical Heritage Foundation, 2001). The
American Heritage Science Dictionary (2002) describes a polymer as made up of various chemical compounds composed of monomers linked together. Some polymers occur naturally while others are artificially created, but polymers are used widely in industry for the creation of plastic, glass, concrete, and rubber (American Heritage Science
22
Dictionary, 2002). Synthetic compounds are used in everyday items, such as in cars, computers, planes, houses, eyeglasses, paints, appliances, and the list goes on.
Polymers are the newest addition to the bulk materials arena, having only been used for five to seven decades, but in substantial amounts (Crank et. al., 2005). There are several different types of polymers (different chemical compounds) used: polyester, polysaccharides, polyurethanes, and polyamides (Crank et. al., 2005). The majority of feedstocks used to make polymers are derived from crude oil, a finite resource. With the unstable prices that the petroleum market has become well-known for, having a sharp increase in crude oil prices in 2005 (Martin, 2006), a slight decrease after, and then most recently another drastic increase in 2008, it is important to note that polymers utilize oil in three ways: as raw material, as a source of energy for their production, and as a fuel source in their transport (TFR, 2008).
Renewable polymers (sometimes referred to as “biopolymers”) are substances derived from a living plant, animal, or ecosystem, known as biomass, which has the ability to regenerate itself (GIA, 2006). Biomass is renewable, meaning, for example, more plants or animals can be grown to replace those that are used. Renewable polymers are derived from biomass feedstocks such as corn, potatoes, wheat and soybeans. The
American Heritage Dictionary (2006) explains a biopolymer as a macromolecule that is formed in a living organism such as starch or proteins. Renewable resources for polymers can be produced indefinitely and promise environmental benefits such as reducing national dependency on fossil fuels from foreign nations (GIA, 2006). Bio- based types of polymers include co-polyester-based, polylactic acid, starch-based,
23
soybean-based, lignin-based (from wood), water-soluble and polycaprolactone (GIA,
2006; Platt, 2006). Table 2 exhibits the different groups of renewable polymers and the polymer types.
There are three broad methods of production in which polymers can be derived from renewable resources; this provides the means of classification for a renewable polymer (Petersen et. al., 1999). The first classification is polymers directly extracted from natural materials such as polysaccharides in starch and cellulose. The next is polymers produced by chemical synthesis from renewable bio-derived monomers such as polylactate. The last classification is polymers produced by microorganisms or genetically transformed bacteria such as polyhydroxyalkanoates (Petersen, et. al., 1999).
To avoid the confusion of associating the terms “bioplastics”, “biopolymers”, and
“bioproducts” with the definition of “biodegradable”, this analysis will use the term
“renewable polymers”. These terms can be confusing since petroleum-based polymers can be biodegradable and plant-derived (renewable) polymers can be non-degradable
(National Non-Food Crops Centre, 2008). Biodegradable refers to a material that will be
broken down by microorganisms found in the environment and will break down
completely into carbon dioxide or water. The American Society for Testing and Materials
standard ASTM-6400-04 specifies the criteria for biodegradability of plastic, which
requires 60% biodegradation within 180 days (ASTM, 2008). Degradable refers to
substances that will break, but not naturally in the soil or completely into carbon dioxide
or water. Polymers can be either biodegradable or not. Also, biodegradable polymers
can be manufactured completely from petroleum-based resources (Crank, et.al., 2005).
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Bio-based polymer group Type of polymer Structure/Production method
Starch polymers Polysaccharides Modified natural polymer
Bio-based monomer (lactic acid) by Polylactic acid (PLA) Polyester fermentation, followed by polymerization
1. Bio-based 1,3-propanediol by fermentation plus Other polyesters from bio-based petrochemical terephthalic acid intermediates (or DMT)
Polytrimethyleneterphthalate (PTT) 2. Bio-based 1,4-butanediol by Polyester fermentation plus Olybutyleneterephthalate (PBT) petrochemical terephthalic acid
Polybutylene succinate (PBS) 3. Bio-based succinic acid by fermentation plus petrochemical terephthalic acid
Direct production of polymer by Polyhydroxyalkanoates (PHAs) Polyester fermentation or in a crop
Bio-based polyol by fermentation Polyurethanes (PURs) Polyurethanes or chemical purification plus petrochemical isocyanate
1. Bio-based caprolactam by fermentation Nylon 2. Bio-based adipic acid by 1 Nylon 6 fermentation Polyamide 2 Nylon 66 3. Bio-based monomer obtained from a conventional chemical 3 Nylon 69 transformation from oleic acid via azelaic acid
a)Modified natural polymer
Cellulose polymers Polysaccharides b)Bacterial cellulose by fermentation
Table 2: Most Important Types of Bio-based Polymer Groups, (Source: Crank et. al., 2005, page 34)
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Preference is given to the term “renewable” because it more clearly represents the polymers not made from crude oil. This is because in this research, a renewable polymer is defined as being a substance derived from a living organism, which has the ability to regenerate itself at a rate faster than it is consumed and is either biodegradable or non-degradable; in contrast, the term “biopolymer” can have the connotation of including only biodegradable polymers. In essence, each of these terms represent the same meaning to most audiences, but in this research “renewable polymer” is preferred and used. Due to the use of the supply chain methodology, it is important to remember the topic of this work is not solely about polymers, but renewable chemicals and renewable polymers.
2.3.2 Historical Development of the Chemical and Polymer Industry
Blockades preventing the U.S. importing chemicals from German manufacturers during World War I was what motivated this nation into the chemical industry (Deloitte,
2005). The first man-made polymers were made from renewable resources, like animal bones and hooves, but petroleum-based polymers became cheaper in price and better in performance and currently dominate the market as a result (Stevens, 2002). Since the
1930s more and more of these renewable resources were replaced by petrochemical- based resources, mainly because of the growth of the petrochemical industry (Crank et. al., 2005). Ohio’s plastics industry flourished out of an increase in demand created by the shortages of rubber and other natural materials World War II created (Deloitte, 2005).
With the crude oil price shock of the 1970s, interest in non-petrochemical feedstocks grew, but did not last. Since the 1980s and early 1990s attention has focused more on renewable resources for certain applications driven by the goal to make polymers 26
biodegradable. Biodegradable polymers were desired because of the limited space of landfills and consumers’ aspiration for environmentally friendly products (Crank, et.al.,
2005).
Since the 1980s, more types of starch-based polymers, an important group of renewable resources (see Table 2.1), have been introduced. Throughout the 1990s research and development was conducted to make polyhydroxyalkanoates (PHA) production simpler and cheaper. However, in 1999 Monsanto pulled-out of the initiative because their vision for PHA used in crop production was not realized. This withdrawal cast some doubt on the feasibility of renewable-based polymers at the time. In 2001,
Cargill and Dow joined to manufacture PLA, which is one of the most promising polymers and can be used to produce a variety of chemicals and polymers. Dow later withdrew from this relationship and Cargill founded NatureWorks to further develop
PLA. NatureWorks is now part of a joint venture between Cargill and Teijin Limited of
Japan and its renewable polymer uses 65% less fossil fuel resource in its production
(NatureWorks, 2009). In 2006, the United States plastics industry, a large user of polymer compounds, had a value of goods shipped of $379 billion, employed about 1.1 million people, and operated 18,585 facilities in every state (Society of the Plastics
Industry, 2008). The plastics industry is the third largest manufacturing sector in the
United States (Carteaux, 2008).
2.3.3 Ohio’s Chemical and Polymer Industry
Ohio is not considered to be a place that produces basic chemicals, but a place that utilizes chemicals and polymers to create products (Deloitte, 2005). Ohio was made
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to be the national leader in the chemicals and polymer industry due to its location in relation to coal and natural gas resources and the fact that it is home to an array of automotive manufacturing and agricultural activities that are major consumers of rubber and plastics (Deloitte, 2005). The polymer industry, which includes rubber, plastics, coatings, adhesives, and more, is the largest and most important industry to Ohio in terms of employment and revenue (TFR, 2008). The chemicals, polymers, and advanced materials industry in Ohio contributes over $13.8 billion in revenue and $5.3 billion in exports (Ohio DOD, 2008). According to a 2001 study conducted by Bo Carlsson of
Case Western Reserve University, the polymer industry in Ohio consisted of more than
2,800 firms (Carlsson, 2002). 4 Ohio’s polymer industry began as a support to the
automotive industry, producing parts and the like (PolymerOhio, 2008). Today, Ohio’s
polymer industry produces many of today’s products such as medical devices, computers,
and paints.
Polymer production in Ohio increased over fifteen percent from 1999 to 2005,
while other manufacturing industries were known to decline in production (Ohio
Department of Development, 2008). The polymer industry is accounted for growing at
annual rates of five to ten percent (TFR, 2008). According to the American Chemistry
Council (2009), 47,170 jobs are created by Ohio’s chemical industry and an additional
245,659 jobs are generated
4 It is important to note that there are different classifications of the polymer cluster among literature (i.e. what particular industries make up the polymer cluster). In this research, a polymer cluster definition for Ohio will be created, using NAICS codes, so the number of firms, employees, revenue, et cetera may vary from other literature.
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indirectly from this industry’s activity in Ohio and other states. Ohio’s chemical industry ranks third in productivity among other goods producing industries (American Chemistry
Council, 2009).
Ohio’s chemical and polymer companies are located mainly in northeast Ohio,
with fifty percent of the polymer companies concentrated there. The top ten counties in
Ohio for polymer production are as follows, from most concentrated: Cuyahoga, Summit,
Hamilton, Franklin, Montgomery, Lake, Lucas, Stark, Portage, and Butler (County
Business Patterns, 2008). A region in Ohio between Akron and Cleveland has been
nicknamed “Polymer Valley” because of its high number of polymer firms in the location
(Carlsson, 2002).
One of the most well-known polymers is plastic. As for Ohio’s plastics industry,
in 2006 the value of goods shipped amounted to $25.9 billion, employing about 90,000
workers (Society of the Plastics Industry, 2008). Ohio ranked third in the country in
plastics shipments and ranked second in the country in plastics employment in 2006
(Society of the Plastics Industry, 2008).
2.4 Renewable Polymer Industry
2.4.1 Current Renewable Polymer Market
Western Europe is the world leader in biodegradable polymer consumption with a
59% share followed by North America with a 22% share and Asia Pacific countries with a 19% share (Platt, 2006). U.S. annual sales of biodegradable polymers were 20 million pounds in 2000 and increased to 42 million pounds in 2005 (GIA, 2006). Consumption
29
of renewable polymers is expected to grow by 22% annually in the United States (GIA,
2006). Also, worldwide chemical and material demand for products supplied from renewable materials is expected to double by the year 2050 (U.S. Department of Energy,
1999). This exhibits a strategic growth opportunity from the emerging linkages between the polymer processing sector and the agriculture sector. The Department of Energy and
United States Department of Agriculture states that production of chemicals and materials from renewable resources will increase from 5% of the production of U.S. chemical commodities in 2001 to 12% in 2010, 18% in 2020 and 25% in 2030 (Perlack, et. al., 2005).
There are several renewable polymer products available in the world market
today. Such polymers include polylactic acid (PLA), which is made from corn, wheat or
potatoes, and are used in films and moldings. Consumer products made from renewable
polymers that are available today include compostable trash bags, biodegradable mulch
film, food and beverage bottles, disposable service ware, textiles, adhesives, paints, cell
phones, medical supplies, computer parts and so on (NNFCC, 2007; GIA, 2006; Platt,
2006). Table 3 lists the share of global biodegradable polymer consumption by end-use
market in 2005.
Many companies have initiatives in bio-based materials. NatureWorks, a Cargill
subsidiary, produces a PLA-based renewable polymer from sources such as corn; this
represents the largest selling product category in the U.S. (GIA, 2006). The leading
players in the U.S. renewable polymer market in 2005 are listed in Table 4. In terms of
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the world market, Novamont is the lead player holding 50.48% market share in 2005 followed by NatureWorks/Cargill with 18.12% share (GIA, 2006).
End Use Percent Share Packaging 39 Loosefill 24 Bags & 21 Sacks Fiber 9 Other 7
Table 3: Global Consumption of Biodegradable Polymers by End Use, Percent Share, 2005 (Source: Platt, 2006, page 9)
Company Market Share Cargill/Nature Works 40.46 BASF 14.41 Novamont 13.73 Eastman Chemicals 10.89 National Starch 7.54 Dupont 5.09 Solvay 4.97 Polycaprolactones Others 2.91
Table 4: U.S. Renewable Polymer Producing Companies and Market Share, 2005 (Source: GIA, 2006, page III-3)
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2.4.2 Renewable Polymer Pricing
Because of better production techniques, better material sourcing and higher
production volumes, renewable polymer prices have decreased recently (Platt, 2006).
The production cost for renewable polymers has been historically higher compared to
traditional polymers (GIA, 2006), but the gap is narrowing (Platt, 2006). In 2005, the
prices of renewable polymers ranged from $0.95/lb. to $2.81/lb., but are estimated to
decline to a range of $0.68/lb. to $1.06/lb. by 2010 (GIA, 2006). The decline in price is
estimated to occur because of a decrease in processing and production costs and an
increase in production and consumption of renewable polymers (GIA, 2006). A 2006
market research report conducted by Global Industry Analysts, Inc. projects sales to
increase in the renewable polymer market as seen in Table 5.
Year Sales (thousand pounds) 2006 47,571.06 2007 52,982.93 2008 58,121.95 2009 62,844.39 2010 67,423.64 2011 72,828.60 2012 78,863.44 2013 84,747.02
Table 5: Annual Sales of Biodegradable Polymers for 2006 and Projections for 2007- 2013, thousand pounds (Source: GIA, 2006, III-3)
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2.4.3 Stimuli for a Renewable Polymer Industry
The chemicals industry continues to consolidate, a challenge of the industry
which is the result of its maturity and commoditization of its products (Deloitte, 2005).
Because price is often how companies in this industry compete, it is important for
chemical manufacturers to distinguish themselves through product innovation or
customization, which could allow them to improve profits (Deloitte, 2005). Renewable
polymers may be one method to accomplish this (Deloitte, 2005).
An interest in renewable polymers has risen out of concern for increased
petroleum prices, petroleum’s potential environmental impacts and national security
issues related to crude oil dependence. Renewable polymers compete closely with
petroleum-based polymers in terms of cost and performance; renewable polymers can
also be biodegradable and non-toxic to produce (Paster, et. al., 2003). Renewable
resources have the potential to satisfy future material demand of crude oil for chemical
and polymer production. With an increasing global demand of crude oil and its uncertain
supply and volatile price, a reduction in economic risk associated with reliance on crude
oil is desirable. Also, a decrease in dependence of oil imported from unstable regions is
sought-after. With the price differential between renewable polymers and petroleum-
based polymers having narrowed within the last several years, interest in renewable
resources has increased (Platt, 2006).
Aside from the fact that renewable polymers may be able to satisfy future material
demand (away from oil), there are several other drivers for its adoption. Implementation
of renewable polymers has the potential to reduce greenhouse gas emissions, lessen the
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carbon footprint, improve waste disposal methods through the use of composting, and reduce landfill use (Crank, et.al., 2005). Consumer preferences are changing, leading to different consumer demands. Environmentally-friendly, “green” products are increasingly being demanded by the consumer. Some U.S. businesses are adopting policies to promote environmental and social responsibility. For example, Wal-Mart has been working with suppliers to introduce sustainable materials to product packaging
(TFR, 2008) and making reusable bags available in lieu of plastic bags. Also, Del Monte
Fresh Produce uses NatureWorks PLA in packaging fruit (GIA, 2006). The strategies
U.S. businesses are taking to integrate renewable materials into products can enhance market position. Thus there is a desire for environmentally-friendly products in the marketplace.
Renewable polymers have the potential to create new alternatives. For example,
renewable polymers could be a new source of income in the agriculture sector with new
markets for feedstocks. Replacement of traditional packaging materials could be a use
for renewable polymers. Source options could be enhanced in that feedstocks may be
grown specifically for use as renewable materials. An example would be biotechnology
and plant breeding to produce crops with higher yield and desirable plant composition for
bioproduct application (TFR, 2008). An illustration of this would be growing a new crop
in Ohio for use in rubber production. In addition, there is wide-scale availability of
naturally occurring, cheaper (in relation to the alternative, petroleum) feedstock around
the world that could be used in renewable polymer production (GIA, 2006).
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An additional driver of the incorporation of renewable resources for chemicals
and polymers lies in the concept of white biotechnology. White biotechnology refers to
using living cells or enzymes (from plants or bacteria) in fermentation or enzymatic
processes to manufacture products that are easily degradable, require less energy, and
create less waste during their production (Dornburg, et. al., 2008). The previously
mentioned drivers for the renewable polymer industry are only a small section of a long
list of the potential opportunities this emerging sector can provide.
2.5 Industrial Activity in Ohio
There are several characteristics Ohio encompasses that aid its economy in
capitalizing on business opportunities that have the potential to help in an emerging
renewable polymer industry. With a workforce of over 6 million people, Ohio is the
nation’s third largest manufacturing economy (National Association of Manufacturers,
2008). This is amplified by the fact that industries that are large consumers of
manufactured rubber products, such as motor vehicles and industrial machinery, are
concentrated in Ohio (Policy Research and Strategic Planning, 2008). This available
workforce and established polymer industry could benefit a promising renewable
polymer industry in the state. Ohio has an established industry infrastructure with supply
chain and logistics in place as well as the advantage of being located near Lake Erie, the
Ohio River, and the I-70 and I-71 corridors making distribution of renewable polymer
products possible. Approximately half of rubber and plastic resins are transported by
truck while the other half is shipped by rail and water (O’Reilly, 2009). Ohio’s central
location and established transportation system give the state a competitive edge with
35
access to customers and vendors (TFR, 2008). Ohio is within a one day’s drive of 63% of
U.S. manufacturing facilities and 80% of U.S. corporate headquarters (Bio Ohio, 2008).
Ohio’s proximity to particular industries, such as automobiles and agriculture, is a strength of the state to the chemical and polymer industry (Deloitte, 2005).
Ohio also has a history of innovation and business leadership, and access to education and research institutions, which could benefit the renewable industry in terms of access to innovation and research and development initiatives. Akron, Ohio claims itself to be the “rubber capital of the world” and is home to Goodyear and Goodrich
(Mandel, 2004). Research and development is typically done near company headquarters
(Shanahan, et.al., 1985) and Ohio is home to numerous headquarters including Cooper
Tire and Rubber, Goodyear Tire and Rubber, Owens-Illinois, and PolyOne (Ohio
Department of Development, 2008). An advantage of this is that regions where industrial research and development occur have a comparative advantage over other regions for future technological change, new products, and new industries (Malecki, 1981). Major companies (mainly in the tire and rubber industry) have kept their headquarters in Ohio in large part because of their proximity to high quality universities and infrastructure that provide highly skilled people, suppliers, and firms with developed financial and legal services (Carlsson, 2002).
Ohio is home to leading research institutions. The University of Akron’s College of Polymer Science and Polymer Engineering is ranked second in the country in polymer science programs (University of Akron, 2008). Battelle is also located in Ohio and is one of the leading contract research institutions in the world. The University of Dayton
36
Research Institute is one of the largest research institutions that conduct research and development in composites and advanced polymer technologies (University of Dayton,
2008). Other schools with polymer research programs in Ohio include Case Western
Reserve’s Macromolecular Institute, University of Cincinnati, Shawnee State University,
Kent State University’s Liquid Crystal Institute, and University of Toledo. Total academic polymer research in Ohio is estimated at about $20 million annually (Carlsson,
2002).
PolymerOhio (2008), a polymer trade organization located in Ohio, envisions
Ohio utilizing its assets to build new industry and enhance the economy while providing new jobs. With an abundance of natural and agricultural resources and the chance to link the polymer and agriculture industries of the state, Ohio provides opportunities in the emerging renewable polymer sector.
Ohio also has the advantage of being home to the Ohio Bioproducts Innovation
Center (OBIC). OBIC was established in June of 2005 with the aim of targeting investments to enhance research capabilities and linking innovative research and industry needs. OBIC was funded by an $11.5 million Wright Center of Innovation award (Third
Frontier project), along with matching funds from other external partners (OBIC, 2008) .
Other goals of OBIC are to increase job opportunities in the state, grow and stabilize the state’s economy, catalyze investments in renewable feedstocks and work with industry to create new value chains for renewable materials. OBIC has partners at each point of the supply chain. Such partners include Battelle, the Ohio State University, USDA
Agriculture Research Service, Ohio Corn Growers Association, Ohio Department of
37
Agriculture, Ohio Polymer Strategy Council, PolymerOhio, Inc., ADM, Cargill, Sherwin
Williams, Cooper Tire, and many more. The vast array of industry representatives that partner with OBIC shows how the organization’s initiative is widely supported (OBIC,
2008).
Another positive feature to Ohio business, especially in the renewable materials realm, is the Ohio Agriculture to Chemicals, Polymers, and Advanced Materials Task
Force (Task Force hereafter). This governmental task force was created to provide insight to governmental decision makers on Ohio’s agriculture industry and specialty chemicals and polymer industry, highlight the trends and current conditions of these industries, identify how the two industries could align, and finally to provide recommendations for expanding these industries and their alignment in the state (TFR,
2008). Task Force members included representatives from the Ohio Department of
Agriculture, Ohio Senate, Ohio House of Representatives, Ohio Farm Bureau Federation,
Ohio Department of Development, Polymer Ohio trade organization, OBIC and others.
On the contrary, Ohio does harbor weaknesses that may be a burden to gaining or sustaining new business. It is perceived that Ohio has a burdensome tax system, a complex regulatory system and has a union presence with high labor costs (Deloitte,
2005). Because of the 2001 recession, Ohio has been home to declining output in some sectors (Deloitte, 2005). In terms of the chemical and polymer industry, other states do not know how advanced Ohio’s industry is or the scale and sophistication of this industry in Ohio (Deloitte, 2005).
38
2.5.1 Agriculture Industry in Ohio
Ohio’s agriculture industry provides benefits to the state’s economy. Ohio is one of the top ten states in agriculture commodities including corn, soybeans, winter wheat, eggs, chickens, hogs and so on (ERS-USDA, 2008). Ohio’s food and agriculture related sector accounted for $98 billion in output in 2006 and accounted for 924,000 jobs
(Sporleder, 2007a). The state has diverse agriculture production opportunities due to its varied growing regions and natural resources. Ohio is home to a variety of biomass feedstocks such as crop residues, like corn stover and wheat straw, and wood biomass. In
2005, Ohio had available crop residues of about 3.5 million dry tons, available wood biomass of about 3.7 million tons, and over 555,000 tons of livestock manure (Jeanty, et.al., 2004). Ohio has 14.6 million acres of land available to farming and had a total of
75,861 farms in 2007 (Census of Agriculture, 2007). The Task Force Report states that because of Ohio’s diverse agriculture, foundation in polymers, and research capabilities, the state has an opportunity to be a leader in the renewable polymer sector (TFR, 2008).
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CHAPTER 3
METHODS AND DATA
3.1 Overview
The means of obtaining information on Ohio’s chemical and polymer industry as well as an emerging renewable polymer industry's effect on the state’s economy is through the use of the input-output model (I-O model hereafter). The first literature about the input-output model and economic impact analysis dates back to when Francois
Quency in 1758 published “Tableau Economique”, which traces expenditures through an economy (Blair and Miller, 1985; Kurz and Neri, 2000). The I-O model was later developed by Wassily Leontief in the late 1930s and is a well-established model that has been widely used to analyze changes in interindustry activity (Blair & Miller, 1985).
Leontief was awarded the Nobel Prize in Economics in 1973 for his development of the input-output model (Blair and Miller, 1985).
The I-O model captures what each business or sector purchases from every other sector to produce a dollar’s worth of goods or services (Sporleder, 2007a). An economic impact analysis is a technique for estimating the indirect and induced effects one industry’s expenditures will have on an economy’s output, employment, and income.
Indirect effects are impacts caused by the repetition of industries purchasing from other 40
industries as a result of final demand changes. Induced effects are the influences on all local industries caused by the expenditures of new household income generated by the direct and indirect effects of final demand changes (IMPLAN, 2004). The input-output model consists of several sectors, each representing some industry or related industries, for a particular period of time.
The I-O model is used to capture the economy-wide environment so as to analyze
demand changes (Lee & Schluter, 1993). The model captures the interdependencies among industries. This happens because each industry employs the outputs of other industries as its raw materials or as a factor of production; thus buying goods affects demand in other industries Uncovering these interdependencies can show how much of each industry’s output is used by other industries in the economy, which can then reveal how much is left for final consumption. Economic measures the I-O model provides are total employment, estimates of the direct purchases per dollar of output, income, contribution to gross state product and the total dollar value of output. I-O can be used to study the structure of the national economy, regional economies, and as a tool for national and economic planning (Lee and Schluter, 1993).
For an illustration of how the I-O model operates, consider crude oil production
where some output from this production activity is input into polymer manufacturing.
Polymer output serves as inputs in several different industries, such as molded parts in
automobile manufacturing. This example shows how the output of one industry may be
41
used as an input in other industries, such as a raw material. Measuring the linkages between sectors allows one to see how much of one industry’s output is used as inputs in other industries and to also see what is left over for final consumption.
3.2 I-O Modeling Fundamentals
The basic form an input-output model takes is a transactions table where the rows
explain the distribution of a producer’s output through the economy while the columns
represent the mix of inputs required by one certain industry in the production of its output
(Blair and Miller, 1985). The foundations of input-output analysis lie in matrix algebra.
To get a matrix of technical coefficients, divide the input purchases of a sector by its total
output. This matrix of technical coefficients (also known as the inputs and outputs of
each industry) represents the A matrix—it is the production function of all industries in
the economy. The I-O model is derived through algebraic manipulation of these matrix
functions (Blair and Miller, 1985). The derivation is as follows:
(1) Xi = a i1X1 + ai2X2 + … + a ii Xi + … a inXn + Y i . . .
Xn = a n1X1 + an2X2 + … + a niXi + … a nn Xn + Y n
Where X i…n represents industries’output, a in are technical coefficients representing
industry i purchases by industry n (input) and industry i output to industry n, and Y i…n represents final consumption of these industries. A simply way to exhibit these equations is X=A*X+Y. Equation (2) defines this in matrix terms:
42
(2) (I-A)*X=Y
a11 a12 . . . a 1i . . . a 1n X1 Y1 a21 a22 . . . a 2i . . . a 2n X2 Y2 . . . A= . , X= . , Y= . . . . an1 an2 . . . a ni . . . a nn Xn Yn
Where A is the matrix of technical coefficients, I is the identity matrix (which A is subtracted from to get a negative), X is a vector of industries’ output, and Y is a vector of final consumption of these industries. In this research, matrix A is what is focused on.
The next step is to divide both sides of the equation by (I-A), to get equation (3):
(3) X=((I-A) ⁻1)*Y
(4) (∆X)=((I-A) ⁻1)*( ∆Y)
Equation (1) states that output supply (X) equals intermediate demand (AX) plus
final demand (Y); this is the fundamental I-O model. Equation (2) is a transitional step to
get to Equation (3), which states that output (X) is a function of final demand (Y) through
what is known as the Leontief Inverse (I-A) -1. Equation (4) exhibits that total industry output (X) will change with change in final demand (Y) (Blair and Miller, 1985). By using this model as the conceptual basis, a prediction of, for example, how changes in final demand of renewable polymer products change total output for all industries (X).
43
3.3 I-O Modeling Characteristics
There are two types of I-O models, open and closed. An open model treats
households as exogenous, where final demand in households depend on income they
receive from other sectors in the economy. Closed models treat households as
endogenous, where labor services are used as an input for other sectors and the model
shows consumption of households from other sectors. I-O modeling is generally short-
term, within a year; any longer and accuracy suffers (Blair & Miller, 1985).
Multipliers are a useful facet of the I-O model. Multipliers represent a predictive
model in that they describe the response of the economy to a stimulus (Pagoulatos, et. al.,
1986). Output multipliers represent the total value of production in all sectors of the
economy needed to satisfy a dollars worth of a particular sector’s output. For example, if
the output multiplier for a certain sector reads 1.54, it would mean that for every $1
million change in final demand for that sector, an increase of $1.54 million in economy-
wide output would be realized. Income multipliers signify the impact of changes in final
demand spending on changes in income received by households. Employment multipliers
represent the value of a sector’s output as it relates to that sector’s number of employees.
The employment multiplier is represented in person-years needed given the change in
output. In essence, a multiplier represents how a one unit change, for example positive,
in one sector will cause a positive change in all other sectors in the economy. Type II
multipliers will be used in this analysis, which incorporates all information about the
44
institutions or households into the model, direct effects, indirect effects, and induced effects (IMPLAN, 2004). The Type II framework allows for the analysis of inter- institutional transfer in a region.
There are several assumptions of the input-output model that must be noted. To estimate flows of goods and services from a region to the rest of the world, regional purchase coefficients will be used. RPCs represent the proportion of total demand from the study area purchased from local producers in that study area (MIG, 2009). This method is based on the characteristics of the region and describes actual trade flows for the region mathematically. RPCs are generated by a set of econometrically based equations in the IMPLAN program. For example, an RPC of 0.25 for a particular commodity means that for each dollar of local demand, 25% will be purchased from local producers (IMPLAN, 2004). RPCs can be adjusted in the model. This assumption maximizes local economic activity while minimizing imports. Other assumptions of the I-
O model include constant returns to scale, no supply constraints, a fixed commodity input structure (prices changes do not cause a firm to substitute goods), and homogeneous sector output (proportions of all commodities produced by an industry remain the same).
In other words, technology is held constant (same share of inputs and outputs are used from year to year) (IMPLAN, 2004).
3.4 Limitations of the I-O Model
In addition to the assumptions, there are a few limitations to the I-O model such
as the fact that the models are static, so no price adjustments or substitution of inputs can
be made, thus making long-term structural estimations of the economy being modeled 45
difficult (Faber, et. al., 2007). Also I-O models can only respond to shifts in demand, not movements along the demand curve because inputs are used as a fixed set (production functions are fixed) (Hughes, 2003). Another limitation related to multipliers is the tendency to overstate the impacts; the economy may already be operating near or at full capacity (Kay, 2002). Although econometric analysis can solve these problems, the I-O model is preferred because it allows for analysis of relationships among businesses and between businesses and consumers. I-O allows for examination of the effects of a change in one or several economic activities on the entire economy.
3.5 Data Collection, Organization
3.5.1 IMPLAN Database
Interindustry data on sales, output, employment, et cetera will be obtained from the 2007 IMPLAN database for Ohio and the U.S. with the use of the software package
IMPLAN Professional Version 2.0. IMPLAN, an acronym for IMPact Analysis for
PLANning, is a computer software modeling system used to create input-output models to measure regional economic impact (IMPLAN, 2004). IMPLAN was developed by the
USDA Forest Service to aid the Forest Service in land and resource management planning (IMPLAN, 2004). IMPLAN is now housed by the Minnesota IMPLAN Group,
Inc. (MIG, 2009). The IMPLAN software, along with its database, allows for the construction of transactions tables representing the detail of the 440 sectors of the U.S. economy. IMPLAN's real advantage comes in that it provides flexibility in the methods and assumptions used to generate social accounts and input-output multipliers (IMPLAN,
2004).
46
IMPLAN uses secondary data based on the national economy. Estimates of sectoral activity for final demand, final payments, industry output, and employment for the Ohio economy will be calculated based on 2007 data (the latest available) through aggregating the detail for IMPLAN’s 440 industries of the state’s economy. The secondary database IMPLAN uses to compile its data include the following sources: U.S.
Bureau of Economic Analysis Benchmark I/O Accounts of the U.S., US Bureau of
Economic Analysis Output Estimates, U.S. Bureau of Economic Analysis REIS Program,
U.S. Bureau of Labor Statistics ES202 Program, U.S. Bureau of Labor Statistics
Consumer Expenditure Survey, U.S. Census Bureau County Business Patterns, U.S.
Census Bureau Decennial Census and Population Surveys, U.S. Census Bureau
Economic Censuses and Surveys, U.S. Department of Agriculture and U.S. Geological
Survey (IMPLAN, 2004).
The Minnesota IMPLAN Group collects new data each year at the national level, which is converted into the IMPLAN data format where new national I-O matrices, tables for deflators, margins and RPCs are formed. State level data is gathered and controlled to the national levels. An IMPLAN data file for a state includes the components of employment, value-added, output, final institutional demand, inter-institutional transfers, and national structural matrices. The data is collected based on a sectoring scheme, in this case the North American Industrial Classification System (NAICS) (IMPLAN, 2004;
US Census Bureau, 2007). The IMPLAN database comprises 440 industries bridged to
NAICS codes.
47
The factor of employment includes total wage and salary employees including
self-employed jobs in a region. Both full-time and part-time workers are included and
the metric is annual average jobs (full-time equivalents). IMPLAN uses three data sets to
construct its employment figure: Covered Employment and Wages, County Business
Patterns, and Regional Economic Information Systems. The value-added figure of the
IMPLAN system represents four components: employee compensation, proprietor
income, other property income, and indirect business tax. Employee compensation is all
income paid to workers by employees including benefits such as health insurance, while
propriety income is all payments received by self-employed individuals representing
income. Other property income includes such items as interest, rents, royalties, dividends
and profits. Indirect business taxes do not include taxes on income, but sales taxes paid
to businesses by individuals. The income measure of IMPLAN is simply the sum of
employee compensation, proprietor income, and other property income. Output in the
IMPLAN model represents the value of production by industry for an annual calendar
year (IMPLAN, 2004). The IMPLAN database goes through a validation process before
it is released (MIG, 2009).
3.5.2 Number of Establishments
The data on the number of establishments is obtained by use of the U.S. Census
Bureau’s County Business Patterns (US Census Bureau, 2006). Once the definition of
the chemical and polymer cluster is defined using NAICS codes, County Business
Patterns will be used to locate the number of establishments per NAICS code in Ohio.
The most current year of this data is 2006.
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3.5.3 Growth Estimates
To obtain information on market growth potential for renewable polymer
production a literature review of data found in the public domain is conducted. The
American Chemistry Council and National Petroleum and Refiners Association are a few
organizations that provide useful, relevant information on trends in the chemical and
polymer market. Market industry reports such as those conducted by Global Industry
Analysts and Fredonia also provide valuable information on past growth trends as well as
forecast growth rates for the U.S. Interviews with consultants of Polymer Ohio, a
polymer trade organization in Ohio, are utilized to establish the accuracy of the growth
rates gathered by the literature review. These individuals work directly with companies
in the chemical and polymer industry, thus they are likely to know current trends about
growth in this market.
To gain knowledge of the polymer industry more generally, use of existing
secondary economic data will be used. Such items as key trends and macro-
environmental drivers of the renewable polymer industry in Ohio will be studied. This
information is available in the public domain, open literature, and from chemical and
plastics/polymer trade associations. This information will also be validated when
interviewing with the polymer industry consultants.
3.6 Modeling with IMPLAN
To use IMPLAN in order to gain insight on output, gross state product, income
and employment, first the user must choose the study area in question. This can be
49
the entire U.S., a particular state, or a cluster of several states or counties. Aggregation of the 440 sectors can then take place, but is optional. The model can then be calculated.
50
CHAPTER 4
RESULTS 1: THE IMPACT OF THE CHEMICAL AND POLYMER INDUSTRY
ON OHIO’S ECONOMY
This chapter presents the definition of the chemical and polymer industry as established in this research, which is organized by NAICS codes and that can be applied to Ohio’s economy as well as the United States’. This chapter assesses the impact of the chemical and polymer industry on Ohio’s economy in terms of the dollar of output, gross state product, income, and employment and compares the state’s impact to the United
States’ in this cluster. Multipliers are expressed in this chapter for the same measures.
This chapter discusses regional purchase coefficients calculated in this work. In addition, the chapter concludes with a discussion of the number of establishments in Ohio comprising this industry.
4.1 The Ohio Chemical and Polymer Cluster Model Definition
The Ohio Chemical and Polymer Cluster Model (OCPCM) is organized so as to define the supply chain of the chemical and polymer cluster of the economy. The model consists of five broad sectors, which are all in a supply-chain context, vertically-linked 51
and interdependent. The five major components comprising the cluster are petroleum and natural gas extraction, chemicals, polymers, mold and equipment manufacturing related to chemical and polymer production and, lastly, chemical and polymer distribution.
An excellent representation of the supply chain vertical linkages of the chemical
and polymer industry composed by the U.S. Department of Energy (United States
Department of Energy, 1999) was used to begin the construction of the chemical and
polymer cluster definition in this study. The chemicals listed on Figure 3 of this USDOE
report were matched with NAICS codes and the codes were then included in this cluster
definition. In addition, past definitions of the polymer industry were used as a starting
point to derive the NAICS codes that would be included under the “polymer” sector of
this cluster. Once the definition was complete, an interview with an industry expert
(Hattery, 2009) was conducted to ensure the representation of the polymer supply chain
was correct and not lacking any sector. As a result, this study uses 6-digit NAICS codes
to define the cluster using codes beginning in 21, 324, 325, 326, and 333. Once the
NAICS codes to be included in the definition were identified, the codes were then
matched to an IMPLAN 440-industries bridge. The concordance between IMPLAN and
NAICS codes of the OCPCM can be viewed in Table 20 of the appendix.
The OCPCM is composed of 66 disaggregated sectors representing the petroleum
feedstock, chemicals, polymers, and related equipment production. Table 10 5 in the
5 All tables in the appendix are supporting information in this work. The tables are crucial elements to the understanding of this research.
52
appendix lists the disaggregated organization of the 66 industries included in the definition of the OCPCM model. Table 10 also exhibits the results of the disaggregation of the OCPCM model. The disaggregated model is presented to show the scope and substantial detail of the cluster definition and how each component contributes to the overall chemical and polymer impact on the economy. Table 10 would be of most use to industry personnel or polymer association officials who wish to study the significant detail of this industry’s impact. However, most audiences (i.e. the general public) interested in the results of this analysis would prefer a more aggregated version of this table. For this reason, an aggregated version was constructed (please see Table 11 in the appendix). Many of the 39 sectors that are included in the aggregated version of the cluster are defined based upon the aggregation of similar industries from the disaggregated model. For example, the “Rubber Product Manufacturing” sector of
OCPCM Table 11 is defined to include tire manufacturing, rubber and plastics hose and belting manufacturing, and other rubber product manufacturing.
The specific definition of sectors within OCPCM was accomplished by maintaining significant detail among the chemical and polymer cluster, but aggregating non-chemical and polymer related sectors of the rest of the economy into large composites (the general manufacturing and services sectors). In the aggregated version
(see Table 11), which will be used in the discussion from this point forward, the specific chemical and polymer related sub-sectors of OCPCM are oil and gas extraction; support activities for mining; natural gas distribution; petroleum and coal products manufacturing; basic chemical manufacturing; soap, cleaning compound, and toilet preparation manufacturing; other chemical product and preparation manufacturing; 53
coating and laminated packaging paper and plastic film manufacturing; plastic material and resin, synthetic rubber and organic fiber manufacturing; paint, coating, and adhesive manufacturing; plastics products manufacturing; rubber products manufacturing; plastics and rubber industry machinery; industrial mold manufacturing; boat building; and chemical and polymer distribution (wholesale). The Ohio Chemical and Polymer Cluster
Model in its aggregated form is comprised of 16 sectors related to chemicals and polymers and 23 sectors that are based on the general manufacturing and services sectors of the rest of the economy.
4.2 Results
4.2.1 Overview of the Chemical and Polymer Industry in Ohio: Output, GSP, Income and Employment
A summary of the entire Ohio economy can be shown by the output, gross state product, income and employment of each of the 39 sectors of the state’s economy as defined in this study exhibited in the aggregated style, Table 11 of the appendix. The total economic output for the entire economy of Ohio in 2007 was $959 billion, with total employment of almost 6.8 million people. Ohio’s economy generated $466.3 billion in gross state product (GSP) in 2007, with the chemical and polymer cluster share of $25.5 billion. This translates into the chemical and polymer cluster of the Ohio economy generating about $5.47 of each $100 in the state’s GSP. Ohio’s chemical and polymer sector contributed about 4 percent to the gross domestic product of the chemical and polymer cluster of the United States (see Table 12 in the appendix for a U.S. comparison).
54
In terms of the chemical and polymer cluster in Ohio, the related sectors generated $89 billion in output, which represents about 9 percent of the total state’s output. The chemical and polymer cluster output corresponds to about $1 of every $9 in total output of Ohio’s economy. The cluster output of $89 billion can be divided among its five components. The largest component of the cluster’s output comes from the chemical sector representing over $40 billion of the $89 billion in output, a share of 45 percent. The chemical sector’s $40 billion output is made up of over $14 billion from both the petroleum and coal products manufacturing and basic chemical manufacturing subsectors, followed by over $8.7 billion from the soap, cleaning compounds, and toilet preparation manufacturing and over $3 billion from other chemical product and preparation manufacturing.
The polymer sector adds about 37 percent of the total output of the chemical and polymer cluster, or $33.2 billion. This sector is largely composed of the plastics product manufacturing subsector, representing $13.2 billion in output, followed by over $8 billion in output from the plastics material and resin, synthetic rubber, and organic fiber manufacturing subsector. Ohio’s polymer sector adds about 8 percent to the overall U.S. polymer sector output.
The petroleum and natural gas extraction subsector represents over 9.5% of this cluster’s output, which corresponds to $8.5 billion in output. Oil and gas extraction is the largest component of this sector with about $4 billion in output, followed closely by the natural gas distribution subsector with over $3.4 billion in output; support activities for mining complete this sector, contributing $1.2 billion in output. Chemical and polymer
55
distribution represents almost 7 percent of the chemical and polymer cluster output in
Ohio while the mold and equipment manufacturing sector represents 1.7 percent.
The measure of gross state product is important in gauging the relative importance of one sector compared to another. In this calculation, it represents the value-added measure as calculated in IMPLAN, which is defined as the sum of employee compensation, proprietors’ income, other property income and indirect business taxes.
GSP for the total state economy is similar in concept to the measure called gross domestic product for a nation (Bureau of Economic Analysis, 2008). According to the
U.S. Census Bureau (2003), gross domestic product is the most important measure of the nation’s economic importance in that it calculates the total market value of all final goods and services produced in a country during a specific period of time. The Ohio economy in 2007 generated $466.3 billion in GSP with the chemical and polymer cluster share representing $ 25.5 billion (please reference Table 11). This translates into the chemical and polymer cluster contributing $5.47 of every $100 in Ohio GSP. Ohio’s chemical and polymer cluster contributed about 4 percent to the overall U.S. chemical and polymer cluster gross domestic product.
Of the $25.5 billion in GSP from the chemical and polymer cluster, about 35 percent and 33 percent are attributable to the chemical sector and the polymer sector, respectively. Petroleum and natural gas extraction and chemical and polymer distribution each contribute about 15 percent to this cluster’s GSP or about $3.7 billion and $3.9 billion, respectively. Mold and equipment manufacturing related to polymer production adds 2 percent to the chemical and polymer cluster GSP. Figure 2 exhibits the
56
distribution of GSP among the various industries that make up the chemical sector.
Figure 3 does the same for the polymer sector.
The chemical and polymer cluster contributes 202,034 person-years to Ohio’s economy. The polymer sector of this cluster represents the largest share contributing
80,481 person-years or 40 percent of the jobs in the cluster. This translates into the polymer sectors accounting for every 4 in 10 jobs in the cluster. The chemical and polymer distribution sector largely affects the cluster’s employment, adding 66,036 person-years or 3 in 10 jobs to the cluster’s employment. The chemical sector adds
29,951 person-years or about 15 percent of the total chemical and polymer cluster employment. The petroleum and natural gas extraction sectors adds another 17,501 jobs
Petroleum and Coal Products, 28%
Total Polymers, Basic Chemical, 27% Chemicals, and Chemicals, 35% Petroleum Cluster, Soap, Cleaning 65% Compound, and Toilet Preparation, 35%
Other Chemical Product and Preparation, 10%
Figure 2: Distribution of GSP among the various industries comprising the chemical sector of the OCPCM (Computed)
57
Coated and Laminated Packaging Paper and Plastics Film, 5% Plastics Material and Resin, Synthetic Rubber, and Organic Fiber, 14%
Paint, Coating, and Total Polymers, Adhesive, 12% Chemicals, and Polymers, 33% Petroleum Cluster, Plastics Product, 48% 67%
Rubber Product, 21%
Figure 3: Distribution of GSP among the various industries comprising the polymer sector of the OCPCM (Computed)
to the Ohio economy, while mold and equipment manufacturing related to polymer production adds over 8 thousand jobs. Figure 4 exhibits the breakdown of the share of jobs among the polymer sector, the largest contributing sector in terms of employment of the chemical and polymer cluster. The polymer sector employment of Ohio’s chemical and polymer cluster contributes about 8 percent to the overall U.S. polymer sector (see
Table 12).
Income in this calculation is the sum of employee compensation, proprietors’ income and other property income. In terms of income generated by the chemical and polymer cluster, it accounts for 5.5 percent of the total income in the entire state or $23.7
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Coated and Laminated Packaging Paper and Plastics Plastics Material and Film, 6% Resin, Synthetic Rubber, and Organic Fiber, 7%
Paint, Coating, and Total Polymers, Adhesive, 9% Chemicals, and Petroleum Cluster, Polymers, 40% Plastics Product, 57% 60%
Rubber Product, 21%
Figure 4: Share of jobs among the polymer sector of the OCPCM (Computed)
billion (please reference Table 11 in the appendix). The largest contributing sector of this cluster is chemicals, accounting for $8.6 billion in income, followed closely by the polymers sector with over $8.1 billion in income. Petroleum and natural gas extraction represents about 14 percent of the cluster with $3.4 billion in income, while chemical and polymer distribution represents 13 percent of the cluster’s income with $3.1 billion in income. Mold and equipment manufacturing slightly add to the cluster’s income with a 2 percent share. Ohio’s chemical and polymer cluster contributes about 4 percent to U.S. chemical and polymer cluster income. It is important to note that the results of this analysis should be regarded as the “lower bound” because the figures do not include retail impacts.
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4.2.2 Exports of Ohio’s Chemical and Polymer Cluster
One interesting aspect of the chemical and polymer cluster is its contribution to exports. Another feature of the OCPCM is the ability to track exports to other states as well as foreign exports. See the aggregated Table 14 in the appendix for a summary of the contributions of the chemical and polymer cluster in Ohio to exports, both domestic and foreign. Total chemical and polymer cluster exports from Ohio to other states were over $30 billion in 2007. This also translates into the chemical and polymer cluster contributing about 9 cents of every dollar of domestic exports from the entire Ohio economy. Foreign exports from Ohio, or exports outside the U.S., totaled over $11 billion for a total export figure of over $41 billion coming from Ohio. About 73 cents of every dollar exported outside Ohio by its chemical and polymer cluster was explained by domestic exports to other states within the U.S.
The polymer sector of the chemical and polymer cluster represents the most domestic exports of any other sector within the cluster, representing $19 billion or 63 percent of total domestic exports from the cluster. Combined with its foreign exports of over $5 billion, the polymer sector of this cluster accounted for $24 billion in exports to
Ohio economy in 2007.
The chemical sector of the chemical and polymer cluster represented a total of
$12 billion in exports to the Ohio economy, with $6.5 billion being domestic exports and
$5.6 billion being foreign exports. The chemical sector contributes about 22 percent to the state’s total domestic exports.
The chemical and polymer distribution sector exports $2.4 billion to domestic sources and $230 thousand to foreign sources. The petroleum and natural gas extraction
60
sector mainly contribute to domestic exports with over $1 billion, while adding $80 thousand to foreign exports for the state. Mold and equipment manufacturing related to polymer production represent only about 2 percent to total cluster exports, exporting
$701 thousand domestically and $297 through foreign sources.
4.2.3 Impact Multipliers of Ohio’s Chemical and Polymer Cluster
Impact multipliers are quantitative measures of the total effects that a change in
the final demand for a sector of the Ohio economy has on output, GSP, income, and
employment. Each industry in the OCPCM produces goods and services which generate
demands for other goods and services and multipliers describe this repeating process
(IMPLAN, 2004). The multipliers calculated in this study, shown in both the
disaggregated and aggregated form in Tables 15 and 16, respectively, of the appendix are
Type II multipliers. Type II multipliers measure the direct, indirect and induced (changes
in spending from households as income fluctuates due to changes in production, also
known as a change in the value added component) effects.
In its simplest explanation, an output multiplier of a particular sector measures the
total change in output generated by a one dollar change in final demand for the product of
a particular sector. In referring to Table 16 of the appendix, the output multiplier for
plastics products manufacturing is 1.4777. This multiplier means that a one dollar
change in final demand for the plastics products manufacturing sector generates a total
economy-wide output of $1.48. Other multipliers are calculated for GSP, income and
employment. Similar to output, the plastics products manufacturing employment
multiplier of 1.8999 means that for a $1 million change in final demand, the effect is
61
about 1.9 person-years. The plastics products manufacturing sector’s income multiplier of
1.7466 means that for every $1 million change in final demand, income the result is $1.75 million in income. Likewise, the GSP multiplier of 1.7679 represents that a $1 change in final demand will generate a $1.77 effect on GSP. Each multiplier expressed in Tables
15 and 16 can be interpreted in this same way. Multipliers are beneficial in a predictive model in that they describe the response of an economy to a stimulus or change in demand (IMPLAN, 2004). Multipliers are beneficial to industry personnel in that they can predict how a change in final demand in a particular sector will change economy- wide output.
4.2.4 Regional Purchase Coefficients of the Ohio Chemical and Polymer Cluster
The regional purchase coefficient (RPC) is the proportion of local demand purchased from local producers (IMPLAN, 2004), the remaining proportion is imported.
Using the IMPLAN software, all industries are treated equally in that each will take an equal proportion of its need from local sources (IMPLAN, 2004). Table 17 and Table 18 in the appendix exhibit the disaggregated and aggregated forms, respectively, of the
RPCs in the OCPCM.
According to Table 18 of the aggregated OCPCM, each of the industries in the chemical sector purchases over fifty percent of its demand from local producers. The soap, cleaning compound and toilet preparation industries and those industries under the other chemical product and preparation manufacturing subsector each purchase 80 cents of every $1 from local producers. The following graph represents the RPCs of the industries under the chemicals sector:
62
Other Chemical Product and 0.8064 Preparation
Soap, Cleaning Compound, and Toilet 0.8037 ry Preparation st u d n I Basic Chemical 0.6231
Petroleum and Coal Products 0.5419
0.00 0.20 0.40 0.60 0.80 1.00 RPC
Figure 5: Regional Purchase Coefficients for the industries representing the Chemicals Sector of the OCPCM (Computed)
The industry of the OCPCM which purchases the most from local producers is the plastics products manufacturing industry under the polymer sector. This industry purchases 85 percent of every dollar from local producers. Other industries that purchase over 50 percent of every dollar from local producers include natural gas distribution, plastics and rubber industry machinery, and chemical and polymer distribution. Please refer to Tables 17 and 18 in the appendix for RPCs of each sub-sector in the OCPCM.
4.2.5 Number of Establishments of Ohio’s Chemical and Polymer Cluster
The number of establishments for the chemical and polymer cluster were collected using the U.S. Census Bureau’s County Business Patterns database for the most recent year, 2006. The number of establishments was collected per NAICS code for Ohio 63
and organized into Table 19 in the appendix. The total number of establishments for the whole chemical and polymer cluster in 2006 was 2,729 establishments. The polymers sector of the chemical and polymer cluster contributed the most with 1,290 establishments, followed by the chemical sector with 592 establishments, the petroleum and natural gas sector with 540 establishments, and mold and equipment manufacturing with 307 establishments. This overall figure of 2,729 establishments corresponds to
PolymerOhio estimates of 2,800 establishments in Ohio (PolymerOhio, 2008).
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CHAPTER 5
RESULTS 2: THE IMPACT OF A RENEWABLE POLYMER INDUSTRY ON
OHIO’S ECONOMY
Polymers made from renewable feedstocks are important for the future in that they allow for cleaner production of chemicals, can contribute to reducing environmental impacts of chemical use, and allow for use of biomass feedstocks (Dornburg, et. al,
2008), which are readily available in Ohio, as a replacement for crude oil. Ohio having ranked second in the nation in chemical and polymer industry output in 2003 (Deloitte,
2005) is positioned well to foster the development of a renewable polymer sector. With the growth of a renewable polymer sector in Ohio, the potential to increase state income, output and, most importantly, jobs is very attractive and must be determined.
This chapter examines the potential economic influence on Ohio’s economy of an emerging renewable chemical and polymer industry. To begin the chapter, growth estimates of selected biopolymer compounds for the United States and Ohio are established through extensive reviews from credible sources throughout the world. The primary analysis involves calculating the renewable portion of Ohio’s chemical and
65
polymer cluster and estimating the influence of this emerging situation on Ohio’s overall economy. The methodology for achieving a calculation of the growth estimate for a renewable industry is explained.
5.1 Trends in the Renewable Chemical and Polymer Industry
Biobased products are slowly penetrating the United States’ market having
increased from about 5% of the market in 2002 to about 8% of the market in 2005
(Biomass Research and Development Technical Advisory Committee, 2008). Trends in
the U.S. chemical and polymer industries coincide with this estimate.
To begin, the American Chemistry Council (2009) forecasted that in 2005 the
U.S. chemical industry would increase 5% to $700 billion. However, the American
Chemistry Council (2009) estimated that overall chemical industry production would fall
1.5% in 2008 and this trend would continue into 2009, falling again 1.5% compared with
a growth in the industry in 2007. The National Petroleum and Refiners Association
estimated that the U.S. chemical industry output declined by 3.2% in 2008 from 2007
(Storck, 2006) predicting that production of virtually all major petrochemicals would
decline in 2008 after a rise in 2007 (O’Reilly, 2009). Industry sales rose by 2.4% CAGR
and production increased by 2.6% CAGR during the 1998-2007 period; however, the
American Chemistry Council estimates that output for the chemical industry will fall by
3.6% in 2009 (American Chemistry Council, 2009). Other studies suggest that the real
dramatic renewable chemical and polymer growth happens from 2020-2050 (Patel, et. al.,
2006).
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Total output of all basic chemical manufacturing dropped in 2008 by 8.7% from
2007 (Storck, 2006). Total U.S. production of organic chemicals declined by 9.2% in
2005 with basic inorganic output expected to grow by 3.6% from 2007 to 2008 and basic organic chemical output expected to drop 13.4% from 2007 (Storck, 2006; American
Chemistry Council, 2009). Soap, cleaning compound, and toilet preparations were expected to grow by 1.7% in 2008 compared to 2007 (Storck, 2006).
In terms of the renewable portion of the chemical industry globally, the market for specialty chemicals from biomass is expected to grow at 10-20% per year (Dale, 2003).
An important note is that only about 10% of the 100 million metric tons of organic chemicals marketed annually in the U.S. are produced from biomass (Dale, 2003). In addition, the rate biotechnology penetrates the chemical industry is 5%, but will increase to 10-20% by 2010 (MIP, 2007).
For the renewable polymer industry, trends indicate growth. The biodegradable polymer market in the U.S. is estimated to grow 8.6% CAGR from 48 million pounds in
2006 to reach 85 million pounds by 2013 (GIA, 2006). Total North American biodegradable polymer consumption is expected to grow by 16.9% from 2005-2010
(Platt, 2006). Global production of polymers from biomass was about 13 million metric tons in 2007, but only a mere 250,000 metric tons of that were newer polymers like PLA and biobased polyurethanes (Tullo, 2008).
For end-use segments of the U.S. polymer industry, the resins, synthetic rubber, and fibers output declined 9.4% in 2008 from 2007 (Storck, 2006; O’Reilly, 2009).
Biodegradable polymers in packaging sales is expected to grow 7.96% CAGR to 2013 from 30 million pounds in 2006, while compost bags are expected to grow 8.74% CAGR
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to 2013 starting with 16 million pounds in 2006 (GIA, 2006). Other end-use products using biodegradable polymers, such as agricultural (i.e. mulch films) and medical, will grow 8.84% CAGR to 2013 from 2 million pounds in 2006 (GIA, 2006). Worldwide, 5% of the polymers used in packaging will be made from petrochemicals, the rest being made from biobased resources (Patel & Crank, 2007). Table 6 shows the growth of polymer products from several references:
Product Growth Rate Reference Co-polyester 7.31% CAGR over 2006-2013 to reach 28 million by 2013 GIA Starch 6.44% CAGR over 2006-2013 to reach 17 million by 2013 GIA Starch 11.9% GAGR from 2005-2010 starting with 8 tonnes in 2005 Platt
Others (Lignin, soybean, water- soluble, polycaprolactone) 5.62% CAGR over 2006-2013 to reach 3 million by 2013 GIA PLA 11.06% CAGR over 2006-2013 starting with 18 million pounds in 2006 GIA PLA 18.7% CAGR over 2005-2010 starting with 9.6 tonnes in 2005 Platt PHA 71% CAGR from 2005-2010 starting with 0.1 tonnes in 2005 Platt Synthetics 18.4% CAGR from 2005-2010 starting with 3.6 tonnes in 2005 Platt Chlorine -8.9% drop in output in 2008 from 2007 Stork Sulfuric Acid -1.8% drop in 2008 from 2007 Stork Ammonia -6.9% drop in 2008 from 2007 Stork Propylene -7.7% decline in output in 2008 from 2007 Stork Ethylene -8.4% drop in output in 2008 from 2007 Stork
Table 6: Growth in polymer industry by product (various references, various years)
For Ohio, in 2001 the polymer industry was noted as being the second largest in the state, with annual sales of $22 billion (Proenza, 2001). In terms of the state of Ohio, the average annual growth rate of the chemicals and polymer industry output fell 2.3% annually between 1998 and 2003 while employment in this industry fell by 2.7% during
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that same time (Deloitte, 2005). Ohio’s chemical industry was expected to grow annually by 3.6% through 2008, while nationwide the industry was predicted to grow by 4.5% annually (Deloitte, 2005).
5.1.1 The BREW Project
In 2006, several universities and research institutions in the EU collaborated to
produce the “BREW Project”, in which one portion of the research aims to estimate the
growth opportunities for biobased chemicals in Europe. This research identifies three
scenarios for the growth of the biobased chemicals industry in Europe applied to a
specific set of biobased chemicals and their petrochemical counterparts. Growth rates for
the biobased chemicals industry are applied to volumes of tonnage of each biobased
chemical (Patel, et. al., 2006). The growth rates used in the “BREW Project” are a result
of primary data collection in which expert opinion was employed. The use of expert
opinion is an invaluable method for which this report pertaining to Ohio’s chemical and
polymer cluster could not duplicate for reasons of time and funding. Because the
“BREW Project” employed expert opinion, was published in 2006, and utilized a solid
methodology, it is considered important and worthy enough to reference in the
development of the methodology used in this analysis.
To take full advantage of the unique opportunities the growing industry of
renewable chemicals and polymers provide, high priority needs to be placed on additional
economic analysis. Such an economic analysis is needed to define and evaluate the
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current and estimate the potential future impact of the emerging renewable polymer cluster on Ohio’s economy. For example, the potential for creating jobs in Ohio resulting from renewable feedstock sources needs to be quantified.
5.2 Objectives for Determining the Impact of a Renewable Chemical and Polymer Cluster in Ohio
Ohio’s chemical and polymer industry already is important to the state’s
economy. Emerging technologies related to renewable polymer production from natural
sources, such as plants, animals, and microorganisms, have opened substantial economic
opportunities and potentials within the chemical, agricultural, and polymer clusters of the
state over the past few years. What is currently not known is the magnitude of the
economic impact of this emerging renewable chemical and polymer cluster and the
promise of future market opportunities for renewable polymers in Ohio. The lack of such
knowledge is a critical problem: stakeholders of the renewable polymer cluster currently
do not have the necessary information base to encourage private sector firms (1) to make
the investment necessary to become leading producers of innovative renewable products
and materials in Ohio; and (2) to utilize greater amounts of locally-produced renewable
materials.
A portion of this research is based on defining and quantifying selected economic scenarios that may emerge for the renewable polymer cluster in Ohio to 2020. Since forecasting of future years is difficult to do accurately due to uncertain events in the future, the current structure of 2007 will be used to the year 2020 where structural changes are predicted to not vary much from the 2007 base. The goal of the applied research is two-fold: first, to determine the economic impact of the emerging renewable 70
chemical and polymer production in Ohio and, second, to provide an economic assessment of the market opportunity for renewable chemicals and polymers in Ohio.
Meeting these goals involves these specific objectives 1) evaluate the impact on Ohio’s economy of feedstock production for production of renewable polymers in Ohio and 2) estimate economic multipliers for the various industry segments of the renewable polymer cluster in Ohio.
5.3 Methodology and Data
The objectives can best be achieved through the use of economic scenarios that help quantify the influence that renewable polymers may have on the future economy of
Ohio. Growth rates and technical substitution potentials for the renewable chemical and polymer industry for Ohio and the U.S. depend on several factors. These factors may include fossil fuel prices, technological advancement, and production costs (Patel, et. al.,
2006). Because the exact future structure of the market is uncertain and it is likely the market conditions for biobased chemicals and polymers may differ from today, scenario analysis permits orderly analysis to encompass several outcomes for the future based on today’s predictions. Assumptions that are necessary in order to use this methodology include keeping costs, revenues, technology and the like constant from year to year. The economic analysis here is based on a most likely scenario and the boundary scenarios
(best and worst) concerning renewable polymer growth in the industry.
5.3.1 Scenarios
In this analysis, forecasts for growth potential of the polymer sector are examined
to the year 2020 (this analysis focuses only on the polymer sector of the chemical and 71
polymer cluster). The year 2020 is most appropriate for this study because the figures in the OCPCM Tables 10 and 11 (output, gross state product, income, and employment) provided by use of IMPLAN are from the year 2007. The analysis of the possibilities of the renewable chemical and polymer market to 2020 are based on three straightforward scenarios. The BREW study conducted in Europe (Patel, et. al., 2006) and which is based on expert opinion uses scenarios to analyze future industry growth in the renewable polymer sector. The report used an annual growth rate range of 1-3% to construct its scenarios. Considering additional references for the growth rate of the United States, such as GIA cited previously in section 5.1, the scenarios of 1-3% annual growth rate are used here. Although the actual growth rate of the renewable polymer industry is likely to be higher, the conservative range of 1-3% annual growth is used. The following are the scenarios generated for this analysis:
• Worst Circumstances for Future Growth : Low growth, 1% compounded annually 6.
Expected market potentials are low.
• Most Likely Circumstances for Future Growth: Most likely growth, 2%
compounded annually. Market potentials are attractive and it is anticipated that from
now to 2020 this will be the most likely growth rate.
• Best Circumstances for Future Growth: High growth, 3% compounded annually.
Market potentials are highly favorable, for example production costs are low and
there are government policies in place requiring the use of biobased substitutes, et
cetera. It is anticipated, though, that this will not be the most likely situation.
6 Compound annual growth rate refers to how the market would grow if it grew at a steady rate over the time horizon. It is the geometric mean growth rate on an annualized basis (Investopedia, 2009).
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Market potentials of the renewable chemical and polymer sector depend on factors such as crude oil prices, alternative feedstock prices, and biotechnology development. For example, in the “Worst” scenario, crude oil prices are relatively low, alternative feedstock prices are higher than crude oil prices, and not much as developed in terms of biotechnology related to renewable polymer advancement. The scenario growth rates will be applied to the GSP and employment figures of Table 10, using 2007 figures as the base volume. GSP is used because it does not double count for usage. The following Table 7 illustrates this approach using GSP:
Scenario Gross State Product Worst Most Likely Best Base 1% CAGR 2% CAGR 3% CAGR
Year 2007 2010 2020 2010 2020 2010 2020 Paint and Coating 782.5 806.3 890.6 830.4 1,012.3 855.1 1,149.2 Manu.
Table 7: Projected volumes of GSP for the Paint and Coating Manufacturing industry in the OCPCM in three scenarios. (Computed)
An alternative ‘base case’ approach to using the 2007 GSP and employment volumes of Table 10 of the OCPCM would be to use the current volume (either in pounds or dollars) of renewable polymers consumed in Ohio today; the growth rates would then be applied to this current volume of renewable polymers in Ohio. Although conceptually
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this may provide a better estimate when calculating the future growth in the renewables industry, this ‘base case’ volume is very hard to estimate and is currently not in the literature.
The difficultly of estimating the current renewables figure in Ohio lies in the complexity of the question. If the question is how many renewable polymers are actually made within Ohio, then the number may be very small. If the question is asking how many renewable polymers are used in a compound that is blended in Ohio (i.e. several
Ohio companies use PLA in a compound, for example, in making paper or plastic cups), then there are approximately 30 million pounds consumption in Ohio of PLA (Hattery,
2009). There is also the fact that products are not necessarily considered 100 percent biobased if one component of it is bio-based. So are these products included in the measurement for the share of renewable polymers in Ohio? Gary Hattery (2009), an engineer and a consultant to the trade organization PolymerOhio, estimates that 1-5 percent of the polymer materials market in Ohio is bio-based today. However, he defends that this figure will change with the change in the definition of the question pertaining to the renewable polymer market (Hattery, 2009). For this reason, the ‘base case’ used in this analysis will be the 2007 GSP and employment volumes of the chemical and polymer cluster of Table 10, which the growth rates will be applied to in scenarios and sequentially the technical substitution of bio-based chemical counterparts incorporated to these figures to get the bio-based portion in year 2020.
5.3.2 Technical Substitution
Technical substitution in this situation is the potential to substitute a particular petrochemical with its bio-based chemical counterpart (in terms of replacement in its use 74
in the manufacturing process, not end-use products), or in other words, the ratio of how much of the polymer sub-sector will be bio-based. A list of bio-based chemicals will be matched to its petrochemical counterpart under each NAICS code in this chemical and polymer cluster definition. Because a complete list of both petrochemicals and bio-based chemical counterparts for each sub-sector is not likely to be found, literature and expert opinion will be used to highlight and focus on the most important (most influential to the market in terms of gaining market share) chemicals per NAICS code. If there are several chemicals per NAICS code, the percentages will simply be averaged. The technical substitution ratios (acquired from a literature review) will then be applied to the projected volumes of gross state product and employment in the ‘Most Likely’ scenario, which have been adjusted by the growth rate of 2 percent. By manipulating the projected volumes of 2020 GSP and employment in OCPCM Table 10 with the technical substitution figures, the result is the impact of the bio-based proportion on the economy.
Table 8 and Table 9 illustrate this approach:
Worst Most Likely Best Petrochemical Bio-Based 2010 2020 2010 2020 2010 2020 PET PLA 10% 40% 15% 60% 25% 100%
Table 8: Projected volumes of PET and technical substitution ratios for its bio-based counterpart, PLA under three scenarios (percentages represent the amount of the market that is biobased). (Computed)
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GSP Employment Paint, Coating & $1,017 7,097 Adhesive Manu. Million person-years
2010: 15 % Bio-based $153 M 1,065 2020: 60% Bio-based $610 M 4,258
Table 9: Projected impact of the bio-based portion of the paint, coating, and adhesive sector based on technical substitution potentials under the Most Likely scenario. Ratios are from PET in Table 8 above. PET is a polymer used in paint, coating, and adhesive manufacturing. Underlying assumptions include keeping costs, revenues, et cetera constant from year to year. (Computed)
5.4 Results of Scenario Analysis
A summary of the application of the growth rate scenarios of 1-3 percent can be viewed in Table 21 (GSP) and Table 22 (employment) of the appendix. Table 21 exhibits the gross state product volumes to 2020 for the industries comprising the polymer sector.
Under the ‘Worst’ scenario of 1 percent CAGR, GSP in the polymer sector in 2020 will be $9.6 billion, while under the ‘Most Likely’ scenario (2 percent CAGR) GSP will be
$10.9 billion in 2020 and under the ‘Best’ scenario (3 percent CAGR), GSP will be $12.3 billion in 2020 in the polymer sector of Ohio economy. In terms of employment, it is estimated that in 2020 under the ‘Worst’ scenario the number of jobs will be 91,597 in the polymer sector or 104,113 jobs under the ‘Most Likely’ scenario, or 118,192 under the ‘Best scenario’. These figures simply exhibit the growth in the polymer industry to the year 2020.
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The ‘Most Likely’ scenario is used to estimate the portion of the polymer industry that will be renewable in 2020. This scenario is only used because it is likely that this is the outcome in 2020 of the polymer sector; the other scenarios are less likely to occur.
The technical substitutions ratios for petrochemicals and their bio-based counterpart gathered through a literature search are exhibited in Table 23 of the appendix and were gathered for the year 2020. For example, the bio-based chemical PLA was found to replace its petrochemical counterpart PET by 41 percent in 2020 (Crank, et. al., 2005).
PET is a chemical used in polystyrene foam product manufacturing, plastics material resin manufacturing, artificial and synthetic fibers and filaments manufacturing; therefore this was one of the technical substitution ratios used in the calculation of the overall technical substitution ratio for that sub-sector (all chemical ratios under a particular sub- sector were averaged to get the overall ratio for the sub-sector).
There were several sub-sectors such as tire manufacturing, paint and coating manufacturing, and adhesive manufacturing where chemical technical substitution ratios could not be found. For these sub-sectors, the overall most conservative ratio of the ratios for the chemicals that were found was used as that sub-sector’s technical substitution ratio. The most conservative ratio that still allows for some bio-based share in the sub-sector (not zero) was 10 percent. Although it is likely that the actual ratio is different, it is probable that there will be a bio-based share in most of the sub-sectors defined under the polymer sector of the OCPCM. For this reason, 10 percent bio-based share was used in these sub-sectors. The shaded cells in Table 23 are those sub-sectors where the most conservative ratio was used. For this kind of analysis the most conservative ratio should be used until a better estimate is made available, whether that is 77
through additional literature or through use of an expert panel. A more definitive measure of the chemical technical substitution ratios would be to make use of expert opinion, for which this study has neither the time nor funding for.
Applying the technical substitution ratios to the ‘Most Likely’ scenario produces
GSP and employment estimates of the renewable polymer industry in 2020, as exhibited in Tables 24 and 25 of the appendix. As a result, the polymer sector of the OCPCM will represent $1.8 billion in GSP in 2020. In other words, in 2020 the polymer sector of
Ohio’s economy will be 13 percent bio-based (from renewable resources). The plastics products manufacturing sub-sector of the polymer sector represents the largest share of renewable polymers in 2020 with GSP of $765 million, or 44 percent share of the bio- based portion of polymers. The bio-based plastics material and resin, synthetic rubber and organic fiber sub-sector represents almost a 26 percent share of GSP of the polymer sector.
In terms of employment in the renewable polymer realm in 2020, the bio-based portion of the polymer sector of OCPCM is estimated to represent 12,065 person-years in
2020. In other words, the bio-based portion will employ 12 percent of the polymer sector employment in 2020. The plastics product manufacturing sector comprises the most bio- based jobs of the polymer sector in 2020 employing 6,683 person-years, or 55 percent of the bio-based portion of polymer employment. Overall, the renewable portion of the polymer industry is over 12 percent. This corresponds with the estimate provided by literature mentioned earlier that biotechnology will enter the chemical and polymer
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industry at a rate of 10-20 percent in 2010 and beyond (MIG, 2007). Please see Tables
24 and 25 for a sub-sector break-down of renewable polymers share of the polymer sector in 2020.
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CHAPTER 6
CONCLUSIONS
The Ohio Chemical and Polymer Cluster Model (OCPCM) is an input-output model that captures inter-industry linkages among various sector and industries that form
Ohio’s economy. The OCPCM maintains significant detail in the chemical and polymer cluster, which is designed to provide estimates of economic importance of this cluster, along with the industries of the general manufacturing and services sectors that complete
Ohio’s economy. The economic measures of importance that this input-output model provides are output, gross state product, income, and employment.
OCPCM also provides multipliers for these same economic measures. These multipliers can be useful in investigating a statewide influence of the induced changes in output, gross state product, income and employment in a particular sector. The impact of the chemical and polymer industry on Ohio’s economy can easily be exhibited through these economic multipliers.
Based on the chemical and polymer sector input-output model created in this analysis, examination of the importance of the chemical and polymer cluster to Ohio’s economy is made possible. This analysis indicated that in 2007 the chemical and polymer cluster output accounted for over 9 percent of Ohio’s output, about 5.5 percent 80
of both the state’s gross state product and income, as well as 3 percent of Ohio’s employment. Ohio’s gross state product was $466.3 billion while the chemical and polymer cluster contributed $25.5 billion of that figure. This means that the chemical and polymer cluster contributes $5.47 of each $100 of Ohio GSP.
Of the five components of the chemical and polymer cluster as defined in this study, the chemicals sector contributes the most in terms of output, contributing $8.9 billion in GSP to Ohio’s economy in 2007. The polymer sector is notable as closely following the chemical sector in output contributing $8.4 billion in GSP. The polymer sector contributes the most to the cluster in terms of employment with 80,481 person- years, followed by chemical and polymer distribution adding 66,036 person-years and the chemical sector with almost 30 thousand jobs. The entire chemical and polymer cluster accounted for 202,034 of Ohio jobs in 2007. The number of establishments making up the chemical and polymer cluster, as defined in this study, is 2,729 establishments.
When comparing Ohio’s chemical and polymer cluster impact to the entire United
State’s impact in this cluster, Ohio contributes about 4 percent to the impact of the U.S. chemical and polymer cluster in output, gross domestic product and income. In terms of employment, however, Ohio adds 5.4 percent to the national employment effect in the chemical and polymer cluster. Focusing on the polymer sector alone, Ohio supplies about 8 percent of the national impact in all measures, output, gross domestic product, income, and employment.
To estimate the potential impact of a renewable polymer industry on Ohio’s economy, a scenario analysis was conducted. Focusing on the ‘Most Likely’ scenario, where the polymer industry grows at a compound annual rate of 2 percent to the year
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2020 and for which chemical technical substitution ratios were applied, the impact of a renewable polymer sector on Ohio’s GSP is $1.8 billion in 2020. This means that in
2020 the polymer sector will be comprised 13 percent of renewable polymers. The plastics products manufacturing sub-sectors makes up most of the renewable polymers market with a 44 percent share of GSP followed by the plastics material and resin, synthetic rubber and organic fiber sub-sector with a 26 percent share of the renewable polymer GSP. It was also estimated that the bio-based portion of the polymer sector will employ 12,065 persons in 2020, a 12 percent share. The plastics products manufacturing sub-sector will employ 55 percent of the 12,065 people in 2020.
This research provides knowledge on key economic trends and impacts, in the form of dollars and multipliers, of the renewable chemical and polymer cluster in Ohio that previously was not available. The chemical and polymer cluster as defined in this supply chain context contributes positively to Ohio’s employment, as well as output,
GSP, and income, and is a large contributor to the U.S.’ chemical and polymer cluster overall. The renewable polymer sector’s impact on Ohio’s GSP and employment, although seemingly small, is positive to the state’s economy. Because the cluster definition was constructed with the U.S. economy in mind, the Ohio Chemical and
Polymer Cluster Model can easily be used at the national level, for other states, or even at regional levels, say for a several county or several state cluster. This model is valuable in that it is a clear representation of inter-industry relationships among all industries in
Ohio’s economy, only with a focus on the chemical and polymer cluster.
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APPENDIX:
TABLES DESCRIBING THE ECONOMIC IMPACT OF A RENEWABLE
POLYMER INDUSTRY IN OHIO
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Gross State Product Total Output (GSP) Income Employment $ Millions $ Millions $ Millions Person Years Polymers, Chemicals, and Petroleum Cluster Petroleum and Natural Gas Extraction 8,534.9 3,719.2 3,350.3 17,501 Oil and Gas Extraction 3,952.4 2,374.2 2,141.5 10,839 Support Activities for Mining 1,193.4 509.5 498.7 3,143 Drilling Oil and Gas Wells 549.1 272.4 267.0 953 Support Activities for Oil and Gas Operations 366.5 136.6 132.6 1,576 Support Activities for Other Mining 277.8 100.5 99.0 614 Natural Gas Distribution 3,389.2 835.6 710.2 3,519
Chemicals 40,113.5 8,888.3 8,616.9 29,952 Petroleum and Coal Products Manufacturing 14,075.0 2,473.1 2,421.3 4,434 Petroleum Refineries 11,960.7 1,438.6 1,395.3 1,535 Asphalt Paving Mixture and Block Manufacturing 768.1 336.9 334.4 1,235 Asphalt Shingle and Coating Materials Manufacturing 652.9 423.4 420.9 945 Petroleum Lubricating Oil and Grease Manufacturing 577.9 232.4 229.4 597 All Other Petroleum and Coal Product Manufacturing 115.4 41.7 41.2 122 Basic Chemical Manufacturing 13,919.1 2,455.1 2,279.9 10,510 Petrochemical Manufacturing 1,097.6 123.8 116.8 487 Industrial gas Manufacturing 952.7 285.4 271.5 815 Synthetic Dye and Pigment Manufacturing 1,795.5 390.9 374.0 2,522 Alkalies and Chlorine Manufacturing 343.1 49.0 43.9 330 Carbon Black Manufacturing 27.5 4.5 4.4 28 Other Basic Inorganic Chemical Manufacturing 1,397.5 358.4 342.8 2,589 Other Basic Organic Chemical Manufacturing 8,305.3 1,243.0 1,126.6 3,739 Soap, Cleaning Compound, and Toilet Preparation Manufacturing 8,696.2 3,107.5 3,083.0 8,533 Soap and Cleaning Compound Manufacturing 5,588.7 1,958.9 1,944.8 4,954 Toilet Preparation Manufacturing 3,107.4 1,148.6 1,138.2 3,579 Other Chemical Product and Preparation Manufacturing 3,423.3 852.6 832.7 6,475 Printing Ink Manufacturing 515.6 93.6 91.3 950 All Other Chemical Product and Preparation Manufacturing 2,907.7 758.9 741.4 5,525
Polymers 33,181.7 8,391.7 8,135.9 80,483 Coated and Laminated Packaging Paper and Plastics Film Manu. 1,836.7 439.8 432.8 4,341 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manu. 8,232.0 1,163.9 1,088.2 5,988 Plastics Material and Resin Manufacturing 6,851.0 910.1 843.1 4,195 Synthetic Rubber Manufacturing 1,154.0 219.8 212.2 1,479 Artificial and Synthetic Fibers and Filaments Manufacturing 227.1 34.0 32.9 314 Paint, Coating, and Adhesive Manufacturing 4,514.3 1,047.9 1,026.6 7,097 Paint and Coating Manufacturing 3,419.4 805.5 790.5 5,047 Adhesive Manufacturing 1,094.9 242.4 236.1 2,050 Plastics Product Manufacturing 13,159.3 3,999.7 3,934.8 46,160 Rubber and Plastics Footwear Manufacturing 3.5 0.9 0.8 25 Plastics Packaging Materials, Film and Sheet Manufacturing 1,959.9 589.5 579.9 4,965 Unlaminated Plastics Profile Shape Manufacturing 763.0 260.9 258.4 2,616 Plastics Pipe and Pipe Fitting Manufactu ring 1,454.7 341.3 336.4 2,859 Laminated Plastics Plate, Sheet, and Shapes Manufacturing 477.4 136.7 134.8 1,828
Table 10: Ohio: Output, Gross State Product, Income, and Employment, Disaggregated Sectors, 2007 (Computed).
(Continued on next page)
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Table 10 Continued
Plastics Bottle Manufacturing 1,487.3 421.0 414.7 3,844 Other Plastics Product Manufacturing 5,957.7 1,944.8 1,916.8 26,821 Polystyrene Foam Product Manufacturing 284.3 94.0 85.2 966 Urethane and Other Foam Product Manufacturing 771.6 210.8 207.7 2,236 Rubber Product Manufacturing 5,439.4 1,740.3 1,653.6 16,897 Tire Manufacturing 1,176.0 398.2 361.2 3,601 Rubber and Plastic Hose and Belting Manufacturing 1,013.6 358.5 354.5 3,947 Other Rubber Product Manufacturing 3,249.8 983.7 937.9 9,349
Mold and Equipment Manufacturing Related to Polymer Production 1,460.9 559.1 544.4 8,065 Plastics and Rubber Industry Machinery 593.2 177.2 171.4 2,293 Industrial Mold Manufacturing 704.1 325.7 319.8 5,014 Boat Building 163.5 56.2 53.2 758
Chemical and Polymer Distribution (Wholesale) 5,839.5 3,897.2 3,068.5 66,036
Total of Polymers, Chemicals, and Petroleum Cluster 89,130.6 25,455.5 23,716.0 202,037
General Manufacturing & Service Sectors Farm Inputs, Equipment & Professional Services 6,487.5 1,687.5 1,627.9 31,099 Farming 8,409.8 3,485.6 3,249.2 102,410 Food Processing 31,052.6 5,579.9 5,146.6 58,604 Wood Processing 15,033.2 4,004.5 3,903.7 60,166 Food Services 22,093.1 9,938.7 8,818.1 430,439 Mining 699.8 373.8 308.0 2,251 Stone, Clay & Glass 9,003.8 3,789.3 3,698.1 32,655 Metal Industries 59,351.4 18,053.3 17,628.7 149,060 Construction 51,366.0 20,130.6 19,802.4 377,747 Textiles, Apparel, Accessories, Yarn & Leath 3,058.4 627.3 605.5 11,952 Machinery, Equipment & General Manufacturing 41,479.8 13,901.3 13,476.4 156,099 Motor Vehicles, Allied Equipment & Services 65,824.1 14,801.6 13,962.5 176,130 Transportation & Communication 36,396.2 17,611.3 16,965.9 215,216 Computer & Electronic Products 18,406.5 8,513.3 8,234.5 110,746 Publishing & Information Technologies 29,142.3 14,627.1 13,443.4 116,972 Wholesale & Retail Trade 86,036.6 57,419.0 45,209.6 962,057 Business, Professional & Personal Services a 115,704.2 69,451.1 64,376.0 843,296 Financial, Legal, & Real Estate 98,367.2 57,589.1 52,855.9 606,479 Leisure Activities & Entertainment 14,408.8 7,244.7 6,544.5 191,451 Health Care & Social Assistance 70,266.2 41,424.2 40,894.3 788,941 Electricity, Gas & Sanitary 19,017.7 11,020.8 9,628.2 56,953 Education Services 26,560.6 23,399.1 23,348.4 449,632 Government, Military, & Non-Profit 41,678.3 36,180.4 36,038.0 631,823
Total of Manufacturing & Service Sectors 869,843.8 440,853.6 409,765.7 6,562,178
Total Economy (P, C, & P Cluster + General Manu. & Service Sectors) 958,974.4 466,309.1 433,481.7 6,764,215
Note: The wholesaling sector is one sector in the input-output model but is disaggregated. County Business Patterns 2006
is used to estimate the percentage of payroll and employment in the polymer, chemical and petroleum cluster. The percentage of payroll (6.54) is used to estimate
the proportion of PCP cluster output, GCP, and income. The percentage of employment (6.42) is used to estimate PCP cluster employment. a Includes diverse service items such as advertising, cleaning, barber and beauty shops, and funerals. Source: Computed
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Gross State Total Product Output (GSP) Income Employment $ Millions $ Millions $ Millions Person Years Polymers, Chemicals, and Petroleum Cluster Petroleum and Natural Gas Extraction 8,534.9 3,719.2 3,350.3 17,501 Oil and Gas Extraction 3,952.4 2,374.2 2,141.5 10,839 Support Activities for Mining 1,193.4 509.5 498.7 3,143 Natural Gas Distribution 3,389.2 835.6 710.2 3,519
Chemicals 40,113.5 8,888.3 8,616.9 29,951 Petroleum and Coal Products Manu. 14,075.0 2,473.1 2,421.3 4,433 Basic Chemical Manu. 13,919.1 2,455.1 2,279.9 10,510 Soap, Cleaning Compound, and Toilet Preparation Manu. 8,696.2 3,107.5 3,083.0 8,533 Other Chemical Product and Preparation Manu. 3,423.3 852.6 832.7 6,475
Polymers 33,181.7 8,391.7 8,135.9 80,481 Coated and Laminated Packaging Paper and Plastics Film Manu. 1,836.7 439.8 432.8 4,341 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manu. 8,232.0 1,163.9 1,088.2 5,988 Paint, Coating, and Adhesive Manu. 4,514.3 1,047.9 1,026.6 7,097 Plastics Product Manu. 13,159.3 3,999.7 3,934.8 46,158 Rubber Product Manu. 5,439.4 1,740.3 1,653.6 16,897
Mold and Equipment Manufacturing Related to Polymer Production 1,460.9 559.1 544.4 8,065 Plastics and Rubber Industry Machinery 593.2 177.2 171.4 2,293 Industrial Mold Manu. 704.1 325.7 319.8 5,014 Boat Building 163.5 56.2 53.2 758
Chemical and Polymer Distribution (Wholesale) 5,839.5 3,897.2 3,068.5 66,036
Total Polymers, Chemicals, and Petroleum Cluster 89,130.6 25,455.5 23,716.0 202,034 General Manufacturing & Service Sectors Farm Inputs, Equipment & Professional Services 6,487.5 1,687.5 1,627.9 31,099 Farming 8,409.8 3,485.6 3,249.2 102,410 Food Processing 31,052.6 5,579.9 5,146.6 58,604 Wood Processing 15,033.2 4,004.5 3,903.7 60,166 Food Services 22,093.1 9,938.7 8,818.1 430,439 Mining 699.8 373.8 308.0 2,251 Stone, Clay & Glass 9,003.8 3,789.3 3,698.1 32,655 Metal Industries 59,351.4 18,053.3 17,628.7 149,060 Construction 51,366.0 20,130.6 19,802.4 377,747 Textiles, Apparel, Accessories, Yarn & Leath 3,058.4 627.3 605.5 11,952 Machinery, Equipment & General Manufacturing 41,479.8 13,901.3 13,476.4 156,099 Motor Vehicles, Allied Equipment & Services 65,824.1 14,801.6 13,962.5 176,130 Transportation & Communication 36,396.2 17,611.3 16,965.9 215,216 Computer & Electronic Products 18,406.5 8,513.3 8,234.5 110,746 Publishing & Information Technologies 29,142.3 14,627.1 13,443.4 116,972 Wholesale & Retail Trade 86,036.6 57,419.0 45,209.6 962,057
Table 11: Ohio: Output, Gross State Product, Income, and Employment, Aggregated, 2007 (Computed). (Continued on next page)
86
Table 11 Continued
Business, Professional & Personal Services a 115,704.2 69,451.1 64,376.0 843,296 Financial, Legal, & Real Estate 98,367.2 57,589.1 52,855.9 606,479 Leisure Activities & Entertainment 14,408.8 7,244.7 6,544.5 191,451 Health Care & Social Assistance 70,266.2 41,424.2 40,894.3 788,941 Electricity, Gas & Sanitary 14,645.7 9,341.1 7,948.4 36,279 Education Services 26,560.6 23,399.1 23,348.4 449,632 Government, Military, & Non-Profit 46,050.3 37,860.1 37,717.8 652,497
Total of Manufacturing & Service Sectors 869,843.8 440,853.6 409,765.7 6,562,178
Total Economy (P, C, & P Cluster + General Manu. & Service Sectors) 958,974.4 466,309.1 433,481.7 6,764,212
Note: The wholesaling sector is one sector in the input-output model but is disaggregated. County Business Patterns 2006
is used to estimate the percentage of payroll and employment in the polymer, chemical and petroleum cluster. The percentage of payroll (6.54) is used to estimate the proportion of PCP cluster output, GCP, and income. The percentage of employment (6.42) is used to estimate PCP cluster employment. a Includes diverse service items such as advertising, cleaning, barber and beauty shops, and funerals. Source: Computed
87
Gross Domestic Total Output Product (GDP) Income Employment
$ Millions $ Millions $ Millions Person Years Polymers, Chemicals, and Petroleum Cluster Petroleum and Natural Gas Extraction 542,595.5 271,523.9 247,448.5 783,594 Oil and Gas Extraction 278,448.1 161,763.3 145,877.9 368,451 Support Activities for Mining 137,401.4 65,944.8 64,425.8 306,243 Natural Gas Distribution 126,746.0 43,815.8 37,144.8 108,900
Chemicals 975,457.9 199,105.0 192,988.7 465,877 Petroleum and Coal Products Manufacturing 598,362.6 106,336.8 103,592.0 111,593 Basic Chemical Manufacturing 220,611.2 41,160.4 38,404.0 148,368 Soap, Cleaning Compound, and Toilet Preparation Manufacturing 105,192.5 38,537.1 38,226.7 106,455 Other Chemical Product and Preparation Manufacturing 51,291.6 13,070.7 12,766.0 99,461
Polymers 409,717.2 103,967.3 100,448.8 981,867 Coated and Laminated Packaging Paper and Plastics Film Manu. 19,713.03 4,780.75 4,705.10 47,746 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manufacturing 133,432.34 22,179.25 20,819.02 105,763 Paint, Coating, and Adhesive Manufacturing 39,164.82 9,258.74 9,066.73 63,507 Plastics Product Manufacturing 171,738.05 53,029.30 52,034.49 618,661 Rubber Product Manfacturing 45,668.97 14,719.23 13,823.41 146,190
Mold and Equipment Manufacturing Related to Polymer Production 21,470.6 7,961.8 7,741.8 111,837 Plastics and Rubber Industry Machinery 4,688.9 1,531.0 1,480.5 17,853 Industrial Mold Manufacturing 5,621.3 2,686.2 2,637.9 39,953 Boat Building 11,160.4 3,744.6 3,623.4 54031
Chemical and Polymer Distribution (Wholesale) 144,491.8 97,325.9 76,327.7 1,405,975.5
Total Polymers, Chemicals, and Petroleum Cluster 2,093,733.0 679,883.8 624,955.5 3,749,151
General Manufacturing & Service Sectors Farm Inputs, Equipment & Professional Services 153,349.6 57,042.1 55,587.6 1,269,932 Farming 412,492.5 168,779.2 150,846.9 3,101,493 Food Processing 761,694.1 132,360.0 119,834.9 1,628,260 Wood Processing 365,450.1 103,025.8 100,408.7 1,400,406 Food Services 579,681.6 281,631.9 250,792.4 10,560,608 Mining 50,004.3 29,300.8 25,240.3 119,279 Stone, Clay & Glass 157,337.2 66,720.3 65,010.8 581,330 Metal Industries 631,549.2 188,779.8 184,160.7 1,754,911 Construction 1,623,849.5 690,847.0 679,584.2 11,364,947 Textiles, Apparel, Accessories, Yarn & Leath 159,544.5 36,039.5 34,962.9 678,758 Machinery, Equipment & General Manufacturing 689,542.7 245,806.1 236,439.9 2,653,416 Motor Vehicles, Allied Equipment & Services 666,379.3 183,218.7 166,888.6 2,814,053 Transportation & Communication 886,622.6 387,687.5 371,750.6 5,193,896 Computer & Electronic Products 769,322.4 341,368.3 331,086.3 3,723,557 Publishing & Information Technologies 1,014,941.2 538,742.7 493,852.2 3,416,372 Wholesale & Retail Trade 2,355,366.0 1,586,513.3 1,244,221.0 24,534,532 Business, Professional & Personal Services 3,206,556.0 1,969,766.5 1,826,581.3 22,892,686 Financial, Legal, & Real Estate 3,636,687.3 2,328,950.3 2,140,582.2 18,167,928 Leisure Activities & Entertainment 810,840.2 428,173.8 390,571.9 6,975,940
Table 12: U.S.: Output, Gross Domestic Product, Income and Employment, Aggregated, 2007 (Computed).
(Continued on next page) 88
Table 12 Continued
Health Care & Social Assistance 1,819,678.9 1,081,789.1 1,068,668.8 18,233,684 Electricity, Gas & Sanitary 484,965.6 313,837.9 268,188.4 1,005,386 Education Services 794,942.1 701,171.9 699,473.5 13,630,840 Government, Military, & Non-Profit 1,478,660.6 1,266,163.8 1,262,410.3 17,456,938
Total of Manufacturing & Service Sectors 23,509,457.4 13,127,716.2 12,167,144.6 173,159,152
Total Economy (P, C, & P Cluster + General Manu. & Service Sectors) 25,603,190.4 13,807,600.1 12,792,100.1 176,908,303
Note: The wholesaling sector is one sector in the input-output model but is disaggregated. County Business Patterns 2006
is used to estimate the percentage of payroll and employment in the polymer, chemical and petroleum cluster. The percentage of payroll (5.78) is used to estimate
the proportion of PCP cluster output, GCP, and income. The percentage of employment (5.42) is used to estimate PCP cluster employment. a Includes diverse service items such as advertising, cleaning, barber and beauty shops, and funerals. Source: Computed
89
Total Exports as Domestic Share of Exports as P,C,P Plus Share of Cluster Polymer, Chemical, and Total Exports Foreign Domestic Total Sector Total Petroleum Cluster = Exports Exports Exports Exports $ Millions $ Millions $ Millions Petroleum and Natural Gas Extraction 1,125.01 80.95 1,044.06 92.8% 2.6% Oil and Gas Extraction 79.85 79.85 0.00 0.0% 0.2% Support Activities for Mining 773.75 0.00 773.75 100.0% 1.8% Drilling Oil and Gas Wells 315.96 0.00 315.96 100.0% 0.7% Support Activities for Oil and Gas Op 208.82 0.00 208.82 100.0% 0.5% Support Activities for Other Mining 248.97 0.00 248.97 100.0% 0.6% Natural Gas Extraction 271.41 1.10 270.31 99.6% 0.6%
Chemicals 14,696.42 5,591.41 9,105.01 62.0% 34.2% Petroleum and Coal Products Manu. 1,392.90 695.68 697.22 50.1% 3.2% Petroleum Refineries 644.83 644.83 0.00 0.0% 1.5% Asphalt Paving Mixture and Block Manu 296.83 4.68 292.15 98.4% 0.7% Asphalt Shingle and Coating Materials 305.98 19.53 286.45 93.6% 0.7% Petroleum Lubricating Oil and Grease 127.15 8.53 118.62 93.3% 0.3% All Other Petroleum and Coal Product 18.11 18.11 0.00 0.0% 0.0% Basic Chemical Manufacturing 6,912.90 3,500.74 3,412.16 49.4% 16.1% Petrochemical Manufacturing 133.02 133.02 0.00 0.0% 0.3% Industrial gas Manufacturing 110.93 13.70 97.23 87.7% 0.3% Synthetic Dye and Pigment Manu. 1,077.21 362.47 714.74 66.4% 2.5% Alkalies and Chlorine Manufacturing 98.13 68.16 29.97 30.5% 0.2% Carbon Black Manufacturing 18.49 18.49 0.00 0.0% 0.0% Other Basic Inorganic Chemical Manu. 998.59 701.62 296.96 29.7% 2.3% Other Basic Organic Chemical Manu. 4,476.54 2,203.28 2,273.26 50.8% 10.4% Soap, Cleaning Compound, and Toilet Preparation Manufacturing 4,990.45 843.14 4,147.32 83.1% 11.6% Soap and Cleaning Compound Manu. 3,330.38 464.85 2,865.53 86.0% 7.7% Toilet Preparation Manufacturing 1,660.07 378.28 1,281.79 77.2% 3.9% Other Chemical Product and Preparation Manufacturing 1,400.17 551.86 848.31 60.6% 3.3% Printing Ink Manufacturing 280.74 68.58 212.16 75.6% 0.7% All Other Chemical Product and Preparation 1,119.43 483.28 636.15 56.8% 2.6%
Polymers 23,532.79 5,039.30 18,493.49 78.6% 54.7% Coated and Laminated Packaging Paper and Plastic Film Manu. 1,569.73 266.38 1,303.34 83.0% 3.6% Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manufacturing 7,368.53 2,349.03 5,019.50 68.1% 17.1% Plastics Material and Resin Manu. 5,823.56 1,880.02 3,943.54 67.7% 13.5% Synthetic Rubber Manu. 1,096.90 453.38 643.52 58.7% 2.6% Artificial and Synthetic Fibers and Filaments 448.07 15.63 432.44 96.5% 1.0%
Table 13: Contributions of the Polymer, Chemical, and Petroleum Cluster to Ohio Exports, Domestic and Foreign, Disaggregated, 2007 (Computed).
(Continued on next page)
90
Table 13 Continued
Paint, Coating, and Adhesive Manu 3,834.56 416.17 3,418.40 89.1% 8.9% Paint and Coating Manu. 3,323.04 264.67 3,058.37 92.0% 7.7% Adhesive Manu. 511.52 151.49 360.03 70.4% 1.2% Plastics Product Manufacturing 5,682.02 1,217.99 4,464.03 78.6% 13.2% Rubber and Plastic Footwear Manu. 0.39 0.39 0.00 0.0% 0.0% Plastics Packaging Materials, Film and Sheet 455.86 253.76 202.10 44.3% 1.1% Unlaminated Plastics Profile Shape Manu. 372.83 40.55 332.28 89.1% 0.9% Plastics Pipe and Pipe Fitting Manu. 721.81 86.17 635.64 88.1% 1.7% Laminated Plastics Plate, Sheet, and Shapes 165.99 1.89 164.10 98.9% 0.4% Plastics Bottle Manu. 800.24 67.06 733.18 91.6% 1.9% Other Plastics Product Manu. 2,902.11 767.36 2,134.75 73.6% 6.7% Polystyrene Foam Product Manu. 0.12 0.12 0.00 0.0% 0.0% Urethane and Other Foam Product Manu. 262.67 0.69 261.98 99.7% 0.6% Rubber Product Manufacturing 5,077.95 789.73 4,288.22 84.4% 11.8% Tire Manu. 1,120.73 236.10 884.64 78.9% 2.6% Rubber and Plastic Hose and Belting Manu. 906.40 249.21 657.19 72.5% 2.1% Other Rubber Product Manu. 3,050.81 304.42 2,746.39 90.0% 7.1%
Mold and Equipment Manufacturing Related To Polymer Production 1,000.68 297.30 703.38 70.3% 2.3%
Plastics and Rubber Industry Machinery 150.45 150.45 0.00 0.0% 0.3% Industrial Mold Manufacturing 698.36 99.86 598.50 85.7% 1.6% Boat Building 151.86 46.99 104.87 69.1% 0.4%
Chemical and Polymer Wholesale 2,654.20 230.72 2,423.48 91.3% 6.2%
Total Ohio Polymer, Chemical, and Petroleum Cluster 43,009.10 11,239.68 31,769.42 73.9% 100.0% Total Ohio Economy 392,962.40 71,133.32 321,829.09 81.9%
Source: Computed
91
Sector Total Exports as Domestic Share of Exports as P,C,P Plus Share of Cluster Polymer, Chemical, and Total Exports Foreign Domestic Total Sector Total Petroleum Cluster = Exports Exports Exports Exports $ Millions $ Millions $ Millions Petroleum and Natural Gas Extraction 1222.00 80.95 1,141.05 93.4% 3.0% Oil and Gas Extraction 79.85 79.85 0.00 0.0% 0.2% Support Activities for Mining 920.38 0.00 920.38 100.0% 2.2% Natural Gas Extraction 221.77 1.10 220.67 99.5% 0.5%
Chemicals 12124.31 5,591.41 6,532.90 53.9% 29.3% Petroleum and Coal Products Manu. 695.68 695.68 0.00 0.0% 1.7% Basic Chemical Manu. 5025.42 3,500.74 1,524.68 30.3% 12.1% Soap, Cleaning Compound, and Toilet Preparation Manu. 5023.81 843.14 4,180.68 83.2% 12.1% Other Chemical Product and Preparation Manu. 1379.41 551.86 827.55 60.0% 3.3%
Polymers 24,415.72 5,039.30 19,376.42 79.4% 59.0% Coated and Laminated Packaging Paper and Plastic Film Manu. 1,575.35 266.38 1,308.97 83.1% 3.8%
Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manu. 8,807.56 2,349.03 6,458.53 73.3% 21.3% Paint, Coating, and Adhesive Manu 4,094.00 416.17 3,677.83 89.8% 9.9% Plastics Product Manu. 4,825.71 1,217.99 3,607.71 74.8% 11.7% Rubber Product Manu. 5,113.11 789.73 4,323.38 84.6% 12.3%
Mold and Equipment Manufacturing Related To Polymer Production 998.74 297.30 701.44 70.2% 2.4%
Plastics and Rubber Industry Machinery 150.45 150.45 0.00 0.0% 0.4% Industrial Mold Manufacturing 696.43 99.86 596.57 85.7% 1.7% Boat Building 151.86 46.99 104.87 69.1% 0.4%
Chemical and Polymer Wholesale 2,654.20 230.72 2,423.48 91.3% 6.4%
Total Ohio Polymer, Chemical, and Petroleum Cluster 41,414.98 11,239.68 30,175.29 72.9% 100.0% Total Ohio Economy 392,155.54 71,134.15 321,021.39 81.9%
Source: Computed
Table 14: Contributions of the Polymer, Chemical, and Petroleum Cluster to Ohio Exports, Domestic and Foreign, Aggregated, 2007 (Computed).
92
Gross State Product Total Output (GSP) Income Employment Polymers, Chemicals, and Petroleum Cluster Petroleum and Natural Gas Extraction Oil and Gas Extraction 1.5392 1.4695 1.6760 2.4107 Support Activities for Mining Drilling Oil and Gas Wells 1.4355 1.4368 2.2616 2.5543 Support Activities for Oil and Gas Operations 1.7023 2.0174 1.7695 2.1808 Support Activities for Other Mining 1.5935 1.8981 2.0161 2.9575 Natural Gas Distribution 1.4940 2.1328 2.3804 3.4920
Chemicals Petroleum and Coal Products Manufacturing Petroleum Refineries 1.4639 3.0459 3.8549 17.7080 Asphalt Paving Mixture and Block Manu. 1.5486 1.5207 1.5848 2.6682 Asphalt Shingle and Coating Materials Manu. 1.4025 1.2956 1.4282 2.7029 Petroleum Lubricating Oil and Grease Manu. 1.5660 1.5583 1.6724 3.4582 All Other Petroleum and Coal Product Manu. 1.5613 1.6336 1.6969 3.4130 Basic Chemical Manufacturing Petrochemical Manu. 1.8444 3.6200 3.7256 8.0821 Industrial gas Manu. 1.7259 2.1739 2.8722 5.5333 Synthetic Dye and Pigment Manu. 1.7736 2.5858 2.2988 3.9619 Alkalies and Chlorine Manu. 1.8249 3.7580 3.4326 5.4352 Carbon Black Manu. 1.7277 2.7492 2.7678 3.8469 Other Basic Inorganic Chemical Manu. 1.7167 2.3796 2.0177 3.3859 Other Basic Organic Chemical Manu. 1.7828 2.9952 3.6186 8.4696 Soap, Cleaning Compound, and Toilet Preparation Manufacturing Soap and Cleaning Compound Manu. 1.7456 1.9588 3.0110 5.4065 Toilet Preparation Manu. 1.6611 1.8580 2.8164 4.5015 Other Chemical Product and Preparation Manufacturing Printing Ink Manu. 1.7817 2.8720 2.1293 3.2174 All Other Chemical Product and Preparation Manu. 1.7331 2.2999 2.0610 3.2490
Polymers Coated and Laminated Packaging Paper and Plastics Film Manu. 1.6053 2.1805 1.9113 2.6267 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manu. Plastics Material and Resin Manu. 1.8028 3.2733 3.5227 6.5349 Synthetic Rubber Manu. 1.7884 2.6643 2.5776 3.9094 Artificial and Synthetic Fibers and Filaments Manu. 1.6251 2.8383 2.4540 3.4110 Paint, Coating, and Adhesive Manufacturing Paint and Coating Manu. 1.6635 2.2558 2.2048 3.4972 Adhesive Manu. 1.7544 2.5228 2.0875 3.2138 Plastics Product Manufacturing Rubber and Plastic Footwear Manu. 1.5995 2.2547 1.7892 1.6011 Plastics Packaging Materials, Film and Sheet Manu. 1.4305 1.6748 1.7265 2.0558 Unlaminated Plastics Profile Shape Manu. 1.4073 1.6049 1.6198 1.8071 Plastics Pipe and Pipe Fitting Manu. 1.2701 1.5785 1.7440 1.9169 Laminated Plastics Plate, Sheet, and Shapes Manu. 1.6717 2.0757 1.9235 2.0473
Table 15: Ohio Economic Multipliers: Output, GSP, Income, and Employment, Disaggregated, 2007(Computed).
(Continued on next page)
93
Table 15 Continued
Plastics Bottle Manu. 1.4103 1.6670 1.7709 1.9153 Other Plastics Product Manu. 1.5531 1.8381 1.7183 1.8234 Polystyrene Foam Product Manu. 1.3797 1.5782 1.6565 1.7766 Urethane and Other Foam Product Manu. 1.6550 2.0239 2.0559 2.2233 Rubber Product Manufacturing Tire Manu. 1.4936 1.7308 1.5902 2.1544 Rubber and Plastic Hose and Belting Manu. 1.4157 1.6046 1.5317 1.7710 Other Rubber Product Manu. 1.4695 1.7702 1.8860 2.1268
Mold and Equipment Manufacturing Related to Polymer Production Plastics and Rubber Industry Machinery 1.5106 1.9228 1.6693 2.0050 Industrial Mold Manufacturing 1.5787 1.6784 1.4367 1.6310 Boat Building 1.4666 1.7428 1.6531 1.7852
Chemical and Polymer Distribution (Wholesale) 1.5663 1.4797 1.4757 1.4107
General Manufacturing & Service Sectors Farm Inputs, Equipment & Professional Services 1.6808 2.2623 2.0486 1.9761 Farming 1.4250 1.4998 2.0000 1.2637 Food Processing 1.7137 2.7569 2.5189 3.6539 Wood Processing 1.5894 2.1014 1.8122 2.0750 Food Services 1.6926 1.7870 1.6721 1.2578 Mining 1.4822 1.4860 1.5115 2.0600 Stone, Clay & Glass 1.5419 1.6730 1.6936 2.0499 Metal Industries 1.4272 1.7426 1.7281 2.2160 Construction 1.5886 1.8055 1.5795 1.6004 Textiles, Apparel, Accessories, Yarn & Leather 1.4618 2.1749 1.8215 1.8565 Machinery, Equipment & General Manufacturing 1.4755 1.7621 1.6579 1.9564 Motor Vehicles, Allied Equipment & Services 1.4476 2.0476 1.7943 2.2367 Transportation & Communication 1.6242 1.6736 1.6192 1.7882 Computer & Electronic Products 1.7083 1.8363 1.5319 1.9246 Publishing & Information Technologies 1.5554 1.6097 1.7745 2.0806 Wholesale & Retail Trade 1.5663 1.4797 1.4757 1.4107 Business, Professional & Personal Services 1.5794 1.5383 1.6250 1.6266 Financial, Legal, & Real Estate 1.5878 1.5694 1.6552 1.7277 Leisure Activities & Entertainment 1.6918 1.7596 1.6309 1.4489 Health Care & Social Assistance 1.7198 1.6775 1.4974 1.5270 Electricity, Gas & Sanitary 1.4916 1.4494 1.6532 2.1586 Education Services 1.5746 1.3619 1.2525 1.2860 Government, Military, & Non-Profit 1.5767 1.3708 1.2610 1.3240
Note: The wholesaling and retailing sector is one sector in the input-output model so the multipliers estimates are the same
for both chemical and polymer and general wholesaling and retailing. N.A. means 'not available.' Source: Computed
94
Gross State Product Total Output (GSP) Income Employment Polymers, Chemicals, and Petroleum Cluster Petroleum and Natural Gas Extraction Oil and Gas Extraction 1.5322 1.4651 1.6700 2.4022 Support Activities for Mining 1.5418 1.6616 1.9339 2.4164 Natural Gas Distribution 1.4681 2.1048 2.3562 3.4548
Chemicals Petroleum and Coal Products Manufacturing 1.4544 2.3574 2.7424 7.8799 Basic Chemical Manufacturing 1.8452 2.9333 3.0943 6.0723 Soap, Cleaning Compound, and Toilet Preparation Manufacturing 1.7124 1.9254 2.9594 5.0825 Other Chemical Product and Preparation Manufacturing 1.7483 2.3652 2.0711 3.2525
Polymers Coated and Laminated Packaging Paper and Plastic Film Manu. 1.5231 2.0794 1.8313 2.5325 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manufacturing 1.8201 3.2808 3.4689 6.0216 Paint, Coating, and Adhesive Manufacturing 1.6896 2.3247 2.1748 3.4248 Plastics Product Manufacturing 1.4777 1.7679 1.7466 1.8999 Rubber Product Manufacturing 1.4740 1.7413 1.7373 2.0744
Mold and Equipment Manufacturing Related to Polymer Production Plastics and Rubber Industry Machinery 1.5103 1.9252 1.6733 2.0105 Industrial Mold Manufacturing 1.5813 1.6824 1.4404 1.6354 Boat Building 1.4664 1.7457 1.6587 1.7922
Chemical and Polymer Distribution (Wholesale) 1.5660 1.4680 1.4591 1.3987
General Manufacturing & Service Sectors Farm Inputs, Equipment & Professional Services 1.6836 2.2745 2.0651 1.9883 Farming 1.4268 1.5051 2.0143 1.2659 Food Processing 1.7105 2.7618 2.5359 3.6778 Wood Processing 1.5791 2.0960 1.8113 2.0765 Food Services 1.6895 1.7888 1.6776 1.2597 Mining 1.4820 1.4908 1.5187 2.0749 Stone, Clay & Glass 1.5405 1.6765 1.7015 2.0613 Metal Industries 1.4248 1.7435 1.7347 2.2269 Construction 1.5839 1.7970 1.5767 1.6008 Textiles, Apparel, Accessories, Yarn & Leather 1.4523 2.1662 1.8196 1.8571 Machinery, Equipment & General Manufacturing 1.4753 1.7642 1.6621 1.9628 Motor Vehicles, Allied Equipment & Services 1.4468 2.0504 1.8000 2.2456 Transportation & Communication 1.6341 1.6854 1.6300 1.7966 Computer & Electronic Products 1.7097 1.8391 1.5354 1.9305 Publishing & Information Technologies 1.5555 1.6121 1.7807 2.0887 Wholesale & Retail Trade 1.5666 1.4814 1.4790 1.4131 Business, Professional & Personal Services 1.5806 1.5403 1.6298 1.6309 Financial, Legal, & Real Estate 1.5875 1.5714 1.6607 1.7334 Leisure Activities & Entertainment 1.6919 1.7642 1.6400 1.4546 Health Care & Social Assistance 1.7210 1.6806 1.5023 1.5315
Table 16: Ohio Economic Multipliers: Output, GSP, Income, and Employment, Aggregated, 2007 (Computed).
(Continued on next page)
95
Table 16 Continued
Electricity, Gas & Sanitary 1.4156 1.3515 1.5889 2.2135 Education Services 1.5755 1.3641 1.2553 1.2887 Government, Military, & Non-Profit 1.5940 1.4015 1.2858 1.3520
Note: The wholesaling and retailing sector is one sector in the input-output model so the multipliers estimates are the same
for both chemical and polymer and general wholesaling and retailing. N.A. means 'not available.' Source: Computed
96
RPC Polymers, Chemicals, and Petroleum Cluster Petroleum and Natural Gas Extraction Oil and Gas Extraction 0.2733 Support Activities for Mining Drilling Oil and Gas Wells 0.4629 Support Activities for Oil and Gas Operations 0.3755 Support Activities for Other Mining 0.1197 Natural Gas Distribution 0.6173 Chemicals Petroleum and Coal Products Manufacturing Petroleum Refineries 0.4780 Asphalt Paving Mixture and Block Manu. 0.9912 Asphalt Shingle and Coating Materials Manu. 0.9880 Petroleum Lubricating Oil and Grease Manu. 0.9985 All Other Petroleum and Coal Product Manu. 0.4713 Basic Chemical Manufacturing Petrochemical Manu. 0.4717 Industrial gas Manu. 0.7054 Synthetic Dye and Pigment Manu. 0.6953 Alkalies and Chlorine Manu. 0.6425 Carbon Black Manu. 0.1134 Other Basic Inorganic Chemical Manu. 0.5164 Other Basic Organic Chemical Manu. 0.6312 Soap, Cleaning Compound, and Toilet Preparation Manufacturing Soap and Cleaning Compound Manu. 0.8350 Toilet Preparation Manu. 0.7512 Other Chemical Product and Preparation Manufacturing Printing Ink Manu. 0.8955 All Other Chemical Product and Preparation Manu. 0.7908 Polymers Coated and Laminated Packaging Paper and Plastics Film Manu. 0.0020 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manu. Plastics Material and Resin Manu. 0.0005 Synthetic Rubber Manu. 0.0010 Artificial and Synthetic Fibers and Filaments Manu. 0.0005 Paint, Coating, and Adhesive Manufacturing Paint and Coating Manu. 0.0246 Adhesive Manu. 0.9139 Plastics Product Manufacturing Rubber and Plastic Footwear Manu. 0.0043 Plastics Packaging Materials, Film and Sheet Manu. 0.9222 Unlaminated Plastics Profile Shape Manu. 0.9753 Plastics Pipe and Pipe Fitting Manu. 0.9649 Laminated Plastics Plate, Sheet, and Shapes Manu. 1.0000 Plastics Bottle Manu. 0.9498 Other Plastics Product Manu. 0.7137 Polystyrene Foam Product Manu. 0.9627 Urethane and Other Foam Product Manu. 1.0000
Table 17: Regional Purchase Coefficients Disaggregated, OCPCM 2007 (Computed)
(Continued on next page)
97
Table 17 Continued
Rubber Product Manufacturing Tire Manu. 0.0006 Rubber and Plastic Hose and Belting Manu. 0.0016 Other Rubber Product Manu. 0.0024 Mold and Equipment Manufacturing Related to Polymer Production Plastics and Rubber Industry Machinery 0.5722 Industrial Mold Manufacturing 0.0000 Boat Building 0.0119 Chemical and Polymer Distribution (Wholesale) 0.5394 General Manufacturing & Service Sectors Farm Inputs, Equipment & Professional Services 0.1634 Farming 0.4330 Food Processing 0.5252 Wood Processing 0.1514 Food Services 0.8502 Mining 0.1405 Stone, Clay & Glass 0.1418 Metal Industries 0.0694 Construction 0.9550 Textiles, Apparel, Accessories, Yarn & Leather 0.0567 Machinery, Equipment & General Manufacturing 0.0634 Motor Vehicles, Allied Equipment & Services 0.0878 Transportation & Communication 0.5811 Computer & Electronic Products 0.4217 Publishing & Information Technologies 0.2666 Wholesale & Retail Trade 0.5394 Business, Professional & Personal Services 0.8032 Financial, Legal, & Real Estate 0.6264 Leisure Activities & Entertainment 0.5301 Health Care & Social Assistance 0.8439 Electricity, Gas & Sanitary 0.7846 Education Services 0.9460 Government, Military, & Non-Profit 0.9078
Note: The wholesaling and retailing sector is one sector in the input-output model so the multipliers estimates are the same
for both chemical and polymer and general wholesaling and retailing. N.A. means 'not available.'
Source: Computed
98
RPC Polymers, Chemicals, and Petroleum Cluster Petroleum and Natural Gas Extraction Oil and Gas Extraction 0.2625 Support Activities for Mining 0.2516 Natural Gas Distribution 0.6173 Chemicals Petroleum and Coal Products Manufacturing 0.5419 Basic Chemical Manufacturing 0.6231 Soap, Cleaning Compound, and Toilet Preparation Manufacturing 0.8037 Other Chemical Product and Preparation Manufacturing 0.8064 Polymers Coated and Laminated Packaging Paper and Plastic Film Manu. 0.0021 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manufacturing 0.0006 Paint, Coating, and Adhesive Manufacturing 0.1145 Plastics Product Manufacturing 0.8476 Rubber Product Manufacturing 0.0015 Mold and Equipment Manufacturing Related to Polymer Production Plastics and Rubber Industry Machinery 0.5811 Industrial Mold Manufacturing 0.0000 Boat Building 0.0119 Chemical and Polymer Distribution (Wholesale) 0.5394 General Manufacturing & Service Sectors Farm Inputs, Equipment & Professional Services 0.1634 Farming 0.4330 Food Processing 0.5252 Wood Processing 0.1514 Food Services 0.8502 Mining 0.1405 Stone, Clay & Glass 0.1416 Metal Industries 0.0693 Construction 0.9539 Textiles, Apparel, Accessories, Yarn & Leather 0.0568 Machinery, Equipment & General Manufacturing 0.0634 Motor Vehicles, Allied Equipment & Services 0.0878 Transportation & Communication 0.5811 Computer & Electronic Products 0.4217 Publishing & Information Technologies 0.2666 Wholesale & Retail Trade 0.5394 Business, Professional & Personal Services 0.8032 Financial, Legal, & Real Estate 0.6264 Leisure Activities & Entertainment 0.5310 Health Care & Social Assistance 0.8439 Electricity, Gas & Sanitary 0.7244 Education Services 0.9460 Government, Military, & Non-Profit 0.9165
Note: The wholesaling and retailing sector is one sector in the input-output model so the multipliers estimates are the same
for both chemical and polymer and general wholesaling and retailing. N.A. means 'not available.' Source: Computed
Table 18: Regional Purchase Coefficients, Aggregated, OCPCM 2007 (Computed).
99
NAICS CODE NAICS Description Polymer and Related Chemical Cluster # of Estab 06 Petroleum & Natural Gas Extraction Oil and Gas Extraction (211) 21100 Oil and Gas Extraction 201 Support Activities for Mining (2131) 213111 Drilling Oil and Gas Wells 78 213112 Support Activities for Oil and Gas Operations 150 213113, 213114, 213115 Support Activities for Mining 27 Natural Gas Distribution (2212) 2212 Natural Gas Distribution 84 Chemicals Petroleum and Coal Products Manufacturing (3241) 32411 Petroleum Refineries 9 324121 Asphalt Paving Mixture and Block 109 324122 Asphalt Shingle and Coating Materials 16 324191 Petroleum Lubricating Oil and Grease 34 324199 All Other Petroleum and Coal Products 3 Basic Chemical Manufacturing (3251) 32511 Petrochemical Manu. 41 32512 Industrial Gas Manu. 28 325131, 325132 Synthetic Dye and Pigment Manu. 21 325181 Alkalies and Chlorine Manu. 4 325182 Carbon Black Manu. 2 325188 Other Basic Inorganic Chemical Manu. 45 32519 Other Basic Organic Chemcial Manu. 47 Soap, Cleaning Compound, and Toilet Preparation Manufacturing (3256) 325611, 325612, 325613 Soap and Cleaning Compound Manu. 83 32562 Toilet Preparation Manu. 22 Other Chemical Product and Preparation Manufacturing (3259) 32591 Printing Ink Manu. 34 32592, 325991, 325992, 325998 All other Chemical Product and Preparation Manu. 94 Polymers Coated and Laminated Packaging Paper and Plastics Film Manu. 322221 Coated & Laminated Packaging Paper and Plastics Film Manu. 5 Plastics Material and Resin, Synthetic Rubber and Organic Fiber Manufacturing (3252) 325211 Plastics Material and Resin Manu. 65 325212 Synthetic Rubber Manu. 9 325221, 325222 Artificial and Synthetic Fibers and Filaments Manu. 2
Table 19: Number of Establishments for Ohio’s Chemical and Polymer Cluster, 2007 (Source: US Census Bureau, County Business Patterns, 2006)
(Continued on next page) 100
Table 19 Continued
Paint, Coating and Adhesive Manufacturing (3255) 32551 Paint and Coating Manu. 83 32552 Adhesive Manu. 51 Plastics Product Manufacturing (3261) 316211 Rubber and Plastics Footwear Manu. 1 326111, 326112, 326113 Plastics Packaging Materials, Film and Sheet 89 326121 Unlaminated Plastics Profile Shape Manu. 47 326122 Plastics Pipe and Pipe Fitting Manu. 33 32613 Laminated Plastics Plate, Sheet, and Shapes 23 32616 Plastics Bottle Manu. 23 326192, 326191, 326199 Other Plastics Product Manu. 544 326140 Polystyrene Foam Product Manu. 25 326150 Urethane and Other Foam Product Manu. 37 Rubber Product Manufacturing (3262) 326211, 326212 Tire Manu. 38 32622 Rubber and Plastics Hose and Belting Manu. 24 326291, 326299 Other Rubber Product Manu. 191 Mold and Equipment Manufacturing Related to Polymer Production Plastics and Rubber Industry Machinery (3332) 33322 Plastics and Rubber Industry Machinery 72 Industrial Mold Manufacturing 333511 Industrial Mold Manu. 226 Boat Building 336612 Boat Building 9 TOTAL 2,729
Source: County Business Patterns
101
OCPSM IMPLAN IMPLAN Description 2007 NAICS Polymers, Chemicals, and Petroleum Cluster (Disaggregated) 1 20 Oil and gas extraction 211 2 28 Drilling oil and gas wells 213111 3 29 Support activities for oil and gas operations 213112 4 30 Support activities for other mining 213113-5 5 32 Natural Gas Distribution 2212 6 108 Coated and laminated paper, packaging paper and plastics film manu 322221-2 7 115 Petroleum refineries 32411 8 116 Asphalt paving mixture and block manufacturing 324121 9 117 Asphalt shingle and coating materials manufacturing 324122 10 118 Petroleum lubricating oil and grease manufacturing 324191 11 119 All other petroleum and coal products manufacturing 324199 12 120 Petrochemical manufacturing 32511 13 121 Industrial gas manufacturing 32512 14 122 Synthetic dye and pigment manufacturing 32513 15 123 Alkalies and chlorine manufacturing 325181 16 124 Carbon black manufacturing 325182 17 125 All other basic inorganic chemical manufacturing 325188 18 126 Other basic organic chemical manufacturing 32519 19 138 Soap and cleaning compound manufacturing 32561 20 139 Toilet preparation manufacturing 32562 21 140 Printing ink manufacturing 32591 22 141 All other chemical product and preparation manufacturing 32592, 32599 23 93 Footwear manufacturing 3162 24 127 Plastics material and resin manufacturing 325211 25 128 Synthetic rubber manufacturing 325212 26 129 Artificial and synthetic fibers and filaments manufacturing 32522 27 136 Paint and coating manufacturing 32551 28 137 Adhesive manufacturing 32552 29 142 Plastics packaging materials and unlaminated film and sheet manu 32611 30 143 Unlaminated plastics profile shape manufacturing 326121 31 144 Plastics pipe and pipe fitting manufacturing 326122 32 145 Laminated plastics plate, sheet (except packaging), and shape manu 32613 33 146 Polystyrene foam product manufacturing 32614 34 147 Urethane and other foam product (except polystyrene) manufacturing 32615 35 148 Plastics bottle manufacturing 32616 36 149 Other plastics product manufacturing 32619 37 150 Tire manufacturing 32621 38 151 Rubber and plastics hoses and belting manufacturing 32622 39 152 Other rubber product manufacturing 32629 40 208 Plastics and rubber industry machinery manufacturing 33322 41 217 Industrial mold manufacturing 333511 42 291 Boat building 336612
43 Farming 1 Oilseed farming 11111-2 2 Grain farming 11113-6, 11119 3 Vegetable and melon farming 1112 4 Fruit farming 11131-2,111331-4, 111336*, 111339 5 Tree nut farming 111335, 111336* 6 Greenhouse, nursery, and floriculture production 1114 7 Tobacco farming 11191 8 Cotton farming 11192 9 Sugarcane and sugar beet farming 11193, 111991 10 All other crop farming 11194, 111992, 111998 11 Cattle ranching and farming 11211, 11213 12 Dairy cattle and milk production 11212
Table 20: NAICS – IMPLAN Concordance related to OCPCM Sectoring Scheme
(Continued on next page) 102
Table 20 Continued
13 Poultry and egg production 1123 14 Animal production, except cattle and poultry and eggs 1122, 1124-5, 1129 15 Forest nurseries, forest products, and timber tracts 1131-2 16 Logging 1133 17 Fishing 1141 18 Hunting and trapping 1142 74 Tobacco product manufacturing 3122
44 Farm Inputs, Equip, and Prof Services 19 Support activities for agriculture and forestry 115 27 Other nonmetallic mineral mining and quarrying 21239 42 Other animal food manufacturing 311119 130 Fertilizer manufacturing 325311-4 131 Pesticide and other agricultural chemical manufacturing 325320 164 Lime and gypsum product manufacturing 3274 203 Farm machinery and equipment manufacturing 333111 204 Lawn and garden equipment manufacturing 333112 379 Veterinary services 54194
45 Processing 41 Dog and cat food manufacturing 311111 43 Flour milling and malt manufacturing 31121 44 Wet corn milling 311221 45 Soybean and other oilseed processing 311222-3 46 Fats and oils refining and blending 311225 47 Breakfast cereal manufacturing 311230 48 Sugar cane mills and refining 311311-2 49 Beet sugar manufacturing 311313 50 Chocolate and confectionery manufacturing from cacao beans 31132 51 Confectionery manufacturing from purchased chocolate 31133 52 Nonchocolate confectionery manufacturing 31134 53 Frozen food manufacturing 31141 54 Fruit and vegetable canning, pickling, and drying 31142 55 Fluid milk and butter manufacturing 311511-2 56 Cheese manufacturing 311513 57 Dry, condensed, and evaporated dairy product manufacturing 311514 58 Ice cream and frozen dessert manufacturing 311520 59 Animal (except poultry) slaughtering, rendering, and processing 311611-3 60 Poultry processing 311615 61 Seafood product preparation and packaging 3117 62 Bread and bakery product manufacturing 31181 63 Cookie, cracker, and pasta manufacturing 31182 64 Tortilla manufacturing 31183 65 Snack food manufacturing 31191 66 Coffee and tea manufacturing 31192 67 Flavoring syrup and concentrate manufacturing 31193 68 Seasoning and dressing manufacturing 31194 69 All other food manufacturing 31199 70 Soft drink and ice manufacturing 31211 71 Breweries 31212 72 Wineries 31213 73 Distilleries 31214
(Continued on next page)
103
Table 20 Continued
46 Wood Processing 95 Sawmills and wood preservation 3211 96 Veneer and plywood manufacturing 321211-2 97 Engineered wood member and truss manufacturing 321213-4 98 Reconstituted wood product manufacturing 321219 99 Wood windows and doors and millwork 32191 100 Wood container and pallet manufacturing 32192 101 Manufactured home (mobile home) manufacturing 321991 102 Prefabricated wood building manufacturing 321992 103 All other miscellaneous wood product manufacturing 321999 104 Pulp mills 32211 105 Paper mills 32212 106 Paperboard Mills 32213 107 Paperboard container manufacturing 32221 109 All other paper bag and coated and treated paper manufacturing 322223-6 110 Stationery product manufacturing 32223 111 Sanitary paper product manufacturing 322291 112 All other converted paper product manufacturing 322299 207 Other industrial machinery manufacturing 33321, 333291-4, 333298 295 Wood kitchen cabinet and countertop manufacturing 33711 296 Upholstered household furniture manufacturing 337121 297 Nonupholstered wood household furniture manufacturing 337122 300 Wood television, radio, and sewing machine cabinet manufacturing1 337129 301 Office furniture and custom architectural woodwork and millwork manufacturing1337211, 337212, 337214
47 Food Services 413 Food services and drinking places 722
48 Mining 21 Coal mining 2121 22 Iron ore mining 21221 23 Copper, nickel, lead, and zinc mining 21223 24 Gold, silver, and other metal ore mining 21222, 21229
49 Stone, Clay, and Glass 25 Stone mining and quarrying 21231 26 Sand, gravel, clay, ceramic and refractory minerals mining and quarrying 21232 153 Pottery, ceramics, and plumbing fixture manufacturing 32711 154 Brick, tile, and other structural clay product manufacturing 327121-3 156 Flat glass manufacturing 327211 157 Other pressed and blown glass and glassware manufacturing 327212 158 Glass container manufacturing 327213 159 Glass product manufacturing made of purchased glass 327215 160 Cement manufacturing 32731 161 Ready-mix concrete manufacturing 32732 162 Concrete pipe, brick, and block manufacturing 32733 163 Other concrete product manufacturing 32739 164 Lime and gypsum product manufacturing 3274 165 Abrasive product manufacturing 32791 166 Cut stone and stone product manufacturing 327991 167 Ground or treated mineral and earth manufacturing 327992 168 Mineral wool manufacturing 327993 169 Miscellaneous nonmetallic mineral products 327999
50 Metal Industries 170 Iron and steel mills and ferroalloy manufacturing 3311 171 Steel product manufacturing from purchased steel 33121, 33122 172 Alumina refining and primary aluminum production 331311-2 173 Secondary smelting and alloying of aluminum 331314 174 Aluminum product manufacturing from purchased aluminum 331315, 331316, 331319 (Continued on next page) 104
Table 20 Continued
175 Primary smelting and refining of copper 331411 176 Primary smelting and refining of nonferrous metal 331419 177 Copper rolling, drawing, extruding and alloying 33142 178 Nonferrous metal rolling, drawing, extruding and alloying 33149 179 Ferrous metal foundries 33151 180 Nonferrous metal foundries 33152 181 All other forging, stamping, and sintering 332111-2, 332117 182 Custom roll forming 332114 183 Crown and closure manufacturing and metal stamping 332115-6 184 Cutlery, utensil, pot, and pan manufacturing 332211, 332214 185 Handtool manufacturing 332212-3 186 Plate work and fabricated structural product manufacturing 33231 187 Ornamental and architectural metal products manufacturing 33232 188 Power boiler and heat exchanger manufacturing 33241 189 Metal tank (heavy gauge) manufacturing 33242 190 Metal can, box, and other metal container (light gauge) manufacturing 33243 191 Ammunition manufacturing 332992-3 192 Arms, ordnance, and accessories manufacturing 332994-5 193 Hardware manufacturing 3325 194 Spring and wire product manufacturing 3326 195 Machine shops 33271 196 Turned product and screw, nut, and bolt manufacturing 33272 197 Coating, engraving, heat treating and allied activities 3328 198 Valve and fittings other than plumbing 332911-2, 332919 199 Plumbing fixture fitting and trim manufacturing 332913 200 Ball and roller bearing manufacturing 332991 201 Fabricated pipe and pipe fitting manufacturing 332996 202 Other fabricated metal manufacturing 332997-9 298 Metal and other household furniture (except wood) manu. 337124-5
51 Construction 34 Construction of new nonresidential commercial and health care structures 23* 35 Construction of new nonresidential manufacturing structures 23* 36 Construction of other new nonresidential structures 23* 37 Construction of new residential permanent site single- and multi-family structures23* 38 Construction of other new residential structures 23* 39 Maintenance and repair construction of nonresidential maintenance and repair 23* 40 Maintenance and repair construction of residential structures 23* 101 Manufactured home (mobile home) manufacturing 321991
52 Textiles, Apparel, Accessories, Yarn & Leath 75 Fiber, yarn, and thread mills 3131 76 Broadwoven fabric mills 31321 77 Narrow fabric mills and schiffli machine embroidery 31322 78 Nonwoven fabric mills 31323 79 Knit fabric mills 31324 80 Textile and fabric finishing mills 31331 81 Fabric coating mills 31332 82 Carpet and rug mills 31411 83 Curtain and linen mills 31412 84 Textile bag and canvas mills 31491 85 All other textile product mills 31499 86 Apparel knitting mills 31511, 31519 87 Cut and sew apparel contractors 31521 88 Men's and boys' cut and sew apparel manufacturing 31522 89 Women's and girls' cut and sew apparel manufacturing 31523 90 Other cut and sew apparel manufacturing 31529 91 Apparel accessories and other apparel manufacturing 3159 92 Leather and hide tanning and finishing 3161 94 Other leather and allied product manufacturing 3169
(Continued on next page ) 105
Table 20 Continued
303 Mattress manufacturing 33791 304 Blind and shade manufacturing 33792 310 Jewelry and silverware manufacturing 33991
53 Machinery, Equipment, & General Manu. 195 Machine shops 33271 205 Construction machinery manufacturing 33312 206 Mining and oil and gas field machinery manufacturing 33313 209 Semiconductor machinery manufacturing 333295 210 Vending, commercial, industrial, and office machinery manufacturing 333311-3 211 Optical instrument and lens manufacturing 333314 212 Photographic and photocopying equipment manufacturing 333315 213 Other commercial and service industry machinery manufacturing 333319 214 Air purification and ventilation equipment manufacturing 333411-2 215 Heating equipment (except warm air furnaces) manufacturing 333414 216 Air conditioning, refrigeration, and warm air heating equipment manu 333415 217 Industrial mold manufacturing 333511 218 Metal cutting and forming machine tool manufacturing 333512-3 219 Special tool, die, jig, and fixture manufacturing 333514 220 Cutting tool and machine tool accessory manufacturing 333515 221 Rolling mill and other metalworking machinery manufacturing 333516, 333518 222 Turbine and turbine generator set units manufacturing 333611 223 Speed changer, industrial high-speed drive, and gear manufacturing 333612 224 Mechanical power transmission equipment manufacturing 333613 225 Other engine equipment manufacturing 333618 226 Pump and pumping equipment manufacturing 333911, 333913 227 Air and gas compressor manufacturing 333912 228 Material handling equipment manufacturing 333921-4 229 Power-driven handtool manufacturing 333991 230 Other general purpose machinery manufacturing 333992, 333997, 333999 231 Packaging machinery manufacturing 333993 232 Industrial process furnace and oven manufacturing 333994 233 Fluid power process machinery 333995-6 259 Electric lamp bulb and part manufacturing 33511 260 Lighting fixture manufacturing 33512 261 Small electrical appliance manufacturing 33521 262 Household cooking appliance manufacturing 335221 263 Household refrigerator and home freezer manufacturing 335222 264 Household laundry equipment manufacturing 335224 265 Other major household appliance manufacturing 335228 266 Power, distribution, and specialty transformer manufacturing 335311 267 Motor and generator manufacturing 335312 268 Switchgear and switchboard apparatus manufacturing 335313 269 Relay and industrial control manufacturing 335314 270 Storage battery manufacturing 335911 271 Primary battery manufacturing 335912 272 Communication and energy wire and cable manufacturing 33592 273 Wiring device manufacturing 33593 274 Carbon and graphite product manufacturing 335991 275 All other miscellaneous electrical equipment and component manu 335999 299 Institutional furniture manufacturing 337127 302 Showcase, partition, shelving, and locker manufacturing 337215 314 Sign manufacturing 33995 315 Gasket, packing, and sealing device manufacturing 339991 316 Musical instrument manufacturing 339992 317 All other miscellaneous manufacturing 339993, 339995, 339999 318 Broom, brush, and mop manufacturing 339994 416 Electronic and precision equipment repair and maintenance 8112 417 Commercial & industrial machinery & equipment repair&maintenance 8113 (Continued on next page)
106
Table 20 Continued
54 Motor Vehicles, Allied Equipment and Services 276 Automobile manufacturing 336111 277 Light truck and utility vehicle manufacturing 336112 278 Heavy duty truck manufacturing 336120 279 Motor vehicle body manufacturing 336211 280 Truck trailer manufacturing 336212 281 Motor home manufacturing 336213 282 Travel trailer and camper manufacturing 336214 283 Motor vehicle parts manufacturing 3363 362 Automotive equipment rental and leasing 5321 414 Automotive repair and maintenance, except car washes 81111-2, 811191, 811198 415 Car washes 811192
55 Transportation & Communication 284 Aircraft manufacturing 336411 285 Aircraft engine and engine parts manufacturing 336412 286 Other aircraft parts and auxiliary equipment manufacturing 336413 287 Guided missile and space vehicle manufacturing 336414 288 Propulsion units and parts for space vehicles and guided missiles 336415, 336419 289 Railroad rolling stock manufacturing 3365 290 Ship building and repairing 336611 292 Motorcycle, bicycle, and parts manufacturing 336991 294 All other transportation equipment manufacturing 336999 332 Air transportation 481 333 Rail transportation 482 334 Water transportation 483 335 Truck transportation 484 336 Transit and ground passenger transportation 485 339 Couriers and messengers 492 430 State and local government passenger transit n.a.
56 Computer and Electronic Products 234 Electronic computer manufacturing 334111 235 Computer storage device manufacturing 334112 236 Computer terminals and other computer peripheral equipment manu 334113, 334119 237 Telephone apparatus manufacturing 33421 238 Broadcast and wireless communications equipment 33422 239 Other communications equipment manufacturing 33429 240 Audio and video equipment manufacturing 3343 241 Electron tube manufacturing 334411 242 Bare printed circuit board manufacturing 334412 243 Semiconductor and related device manufacturing 334413 Electronic capacitor, resistor, coil, transformer, and other inductor manu 334414-6 244 245 Electronic connector manufacturing 334417 246 Printed circuit assembly (electronic assembly) manufacturing 334418 247 Other electronic component manufacturing 334419 248 Electromedical and electrotherapeutic apparatus manufacturing 334510 249 Search, detection, and navigation instruments manufacturing 334511 250 Automatic environmental control manufacturing 334512 251 Industrial process variable instruments manufacturing 334513 252 Totalizing fluid meters and counting devices manufacturing 334514 253 Electricity and signal testing instruments manufacturing 334515 254 Analytical laboratory instrument manufacturing 334516 255 Irradiation apparatus manufacturing 334517 Watch, clock, and other measuring and controlling device manufacturing 334518-9 256 257 Software, audio, and video media reproducing 334611-2 258 Magnetic and optical recording media manufacturing 334613 (Continued on next page) 107
Table 20 Continued
371 Custom computer programming services 541511 372 Computer systems design services 541512 373 Other computer related services, including facilities management 541513, 541519
57 Publishing and Information Technologies Printing 32311 113 114 Support activities for printing 32312 341 Newspaper publishers 51111 342 Periodical publishers 51112 343 Book publishers 51113 344 Directory, mailing list, and other publishers 51114, 51119 345 Software publishers 51121 350 Internet publishing and broadcasting 51913 351 Telecommunications 517 352 Data processing, hosting, and related services 518 353 Other information services 51911-2
58 Wholesale and Retail Trade 319 Wholesale trade 42 321 Retail - Furniture and home furnishings 442 320 Retail - Motor vehicle and parts 441 322 Retail - Electronics and appliances 443 323 Retail - Building material and garden supply 444 324 Retail - Food and beverage 445 325 Retail - Health and personal care 446 326 Retail - Gasoline stations 447 327 Retail - Clothing and clothing accessories 448 328 Retail - Sporting goods, hobby, book and music 451 329 Retail - General merchandise 452 330 Retail - Miscellaneous 453 331 Retail - Nonstore 454 340 Warehousing and storage 493
59 Business, Professional & Personal Services 313 Office supplies (except paper) manufacturing 33994 361 Imputed rental value for owner-occupied dwellings n.a. 363 General and consumer goods rental except video tapes and discs 53221-2, 53229, 5323 365 Commercial and industrial machinery and equipment rental and leasing 5324 369 Architectural, engineering, and related services 5413 370 Specialized design services 5414 374 Management, scientific, and technical consulting services 54161, 5613* 375 Environmental and other technical consulting services 54162, 54169 376 Scientific research and development services 5417 377 Advertising and related services 5418 378 Photographic services 54192 380 All other miscellaneous professional, scientific, and technical services 54191, 54193, 54199 381 Management of companies and enterprises 55 382 Employment services 5613* 384 Office administrative services 5611 385 Facilities support services 5612 386 Business support services 5614 387 Investigation and security services 5616 388 Services to buildings and dwellings 5617 389 Other support services 5619 418 Personal and household goods repair and maintenance 8114 419 Personal care services 8121 420 Death care services 8122 421 Dry-cleaning and laundry services 8123 422 Other personal services 8129 (Continued on next page) 108
Table 20 Continued
60 Financial, Legal & Real Estate 354 Monetary authorities and depository credit intermediation 521, 5221 355 Nondepository credit intermediation and related activities 5222-3 356 Securities, commodity contracts, investments, and related activities 523 357 Insurance carriers 5241 358 Insurance agencies, brokerages, and related activities 5242 359 Funds, trusts, and other financial vehicles 525 360 Real estate 531 366 Lessors of nonfinancial intangible assets 533 367 Legal services 5411 368 Accounting, tax preparation, bookkeeping, and payroll services 5412
61 Leisure Activities & Entertainment 311 Sporting and athletic goods manufacturing 33992 312 Doll, toy, and game manu 33993 Scenic and sightseeing transportation and support activities for transportation 487, 488 338 346 Motion picture and video industries 5121 347 Sound recording industries 5122 348 Radio and television broadcasting 5151 349 Cable and other subscription programming 5152 364 Video tape and disc rental 53223 383 Travel arrangement and reservation services 5615 402 Performing arts companies 7111 405 Independent artists, writers, and performers 7115 406 Museums, historical sites, zoos, and parks 712 407 Fitness and recreational sports centers 71394 408 Bowling centers 71395 409 Amusement parks, arcades, and gambling industries 7131-2 410 Other amusement and recreation industries 71391-3, 71399 411 Hotels and motels, including casino hotels 72111-2 412 Other accommodations 72119, 7212-3
62 Health Care & Social Assistance 132 Medicinal and botanical manufacturing 325411 133 Pharmaceutical preparation manufacturing 325412 134 In-vitro diagnostic substance manufacturing 325413 135 Biological product (except diagnostic) manufacturing 325414 305 Surgical and medical instrument manufacturing 339112 306 Surgical appliance and supplies manufacturing 339113 307 Dental equipment and supplies manufacturing 339114 308 Ophthalmic goods manufacturing 339115 309 Dental laboratories 339116 394 Offices of physicians, dentists, and other health practitioners 6211-3 395 Home health care services 6216 Medical and diagnostic labs and outpatient and other ambulatory care services 6214-5, 6219 396 397 Hospitals 622 398 Nursing and residential care facilities 623 399 Child day care services 6244 400 Individual and family services 6241 Community food, housing, and other relief services, including rehabilitation 6242-3 401 services (Continued on next page)
109
Table 20 Continued
63 Electricity, Gas, & Sanitary 31 Electric power generation, transmission, and distribution 2211 33 Water, sewage and other systems 2213 337 Pipeline transportation 486 390 Waste management and remediation services 562 431 State and local government electric utilities n.a. 432 Other state and local government enterprises n.a.
64 Education Services 391 Elementary and secondary schools 6111 392 Junior colleges, colleges, universities, and professional schools 6112-3 393 Other educational services 6114-7 438 Employment and payroll for SL Government Education n.a.
65 Government, Military, & Non-Profit 293 Military armored vehicle, tank, and tank component manufacturing 336992 391 Elementary and secondary schools 6111 392 Junior colleges, colleges, universities, and professional schools 6112-3 393 Other educational services 6114-7 423 Religious organizations 8131 424 Grantmaking, giving, and social advocacy organizations 8132, 8133 425 Civic, social, professional, and similar organizations 8134, 8139 427 Postal service 491 429 Other Federal Government enterprises n.a. 432 Other state and local government enterprises n.a. 437 Employment and payroll for SL Government Non-Education n.a. 439 Employment and payroll for Federal Non-Military n.a. 440 Employment and payroll for Federal Military n.a. 425 Civic, social, professional, and similar organizations 8134, 8139 427 Postal service 491
66 Others 433 *Not an industry (Used and secondhand goods) n.a. 434 *Not an industry (Scrap) n.a. 435 *Not an industry (Rest of the world adjustment) n.a. 436 *Not an industry (Noncomparable imports) n.a.
110
Gross State Product Worst Most Likely Best Base 1% CAGR 2% CAGR 3% CAGR 2007 2010 2020 2010 2020 2010 2020 $ millions Polymers 8,391.7 8,645.9 9,550.5 8,905.3 10,855.5 9,169.8 12,323.4 Coated and Laminated Packaging Paper and Plastics Film Manu. 439.8 453.1 500.5 466.7 568.9 480.6 645.8 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manufacturing 1,163.9 1,199.2 1,324.7 1,235.2 1,505.7 1,271.9 1,709.3 Plastics Material and Resin Manufacturing 910.1 937.7 1,035.8 965.9 1,177.4 994.5 1,336.6 Synthetic Rubber Manufacturing 219.8 226.4 250.1 233.2 284.3 240.2 322.7 Artificial and Synthetic Fibers and Filaments Manufacturing 34.0 35.0 38.7 36.1 44.0 37.2 49.9 Paint, Coating, and Adhesive Manufacturing 1,047.9 1,079.7 1,192.6 1,112.1 1,355.6 1,145.1 1,538.9 Paint and Coating Manufacturing 805.5 830.0 916.8 854.9 1,042.1 880.2 1,183.0 Adhesive Manufacturing 242.4 249.7 275.8 257.2 313.5 264.8 355.9 Plastics Product Manufacturing 3,999.7 4,120.9 4,552.0 4,244.5 5,174.0 4,370.6 5,873.7 Rubber and Plastics Footwear Manufacturing 0.9 0.9 1.0 0.9 1.1 0.9 1.3 Plastics Packaging Materials, Film and Sheet Manufacturing 589.5 607.3 670.9 625.5 762.5 644.1 865.6 Unlaminated Plastics Profile Shape Manufacturing 260.9 268.8 296.9 276.8 337.5 285.0 383.1 Plastics Pipe and Pipe Fitting Manufacturing 341.3 351.6 388.4 362.2 441.5 372.9 501.2 Laminated Plastics Plate, Sheet, and Shapes Manufacturing 136.7 140.8 155.5 145.0 176.8 149.3 200.7 Plastics Bottle Manufacturing 421.0 433.8 479.2 446.8 544.6 460.1 618.3 Other Plastics Product Manufacturing 1,944.8 2,003.7 2,213.3 2,063.8 2,515.7 2,125.1 2,855.9 Polystyrene Foam Product Manufacturing 94.0 96.8 106.9 99.7 121.5 102.7 138.0 Urethane and Other Foam Product Manufacturing 210.8 217.2 239.9 223.7 272.7 230.4 309.6 Rubber Product Manufacturing 1,740.3 1,793.1 1,980.7 1,846.9 2,251.3 1,901.7 2,555.8 Tire Manufacturing 398.2 410.3 453.2 422.6 515.1 435.1 584.8 Rubber and Plastic Hose and Belting Manufacturing 358.5 369.3 408.0 380.4 463.7 391.7 526.4 Other Rubber Product Manufacturing 983.7 1,013.5 1,119.5 1,043.9 1,272.5 1,074.9 1,444.6
Table 21: Ohio: Scenario Projections of Growth in the Chemical and Polymer Cluster using GSP to year 2020. (Computed)
111
Employment Worst Most Likely Best Base 1% CAGR 2% CAGR 3% CAGR 2007 2010 2020 2010 2020 2010 2020 person-years Polymers 80,483 82,922 91,597 85,409 104,113 87,946 118,192 Coated and Laminated Packaging Paper and Plastics Film Manu. 4,341 4,473 4,940 4,607 5,616 4,744 6,375 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manu. 5,988 6,169 6,815 6,355 7,746 6,543 8,794 Plastics Material and Resin Manufacturing 4,195 4,322 4,774 4,452 5,427 4,584 6,160 Synthetic Rubber Manufacturing 1,479 1,524 1,683 1,570 1,913 1,616 2,172 Artificial and Synthetic Fibers and Filaments Manufacturing 314 324 357 333 406 343 461 Paint, Coating, and Adhesive Manufacturing 7,097 7,312 8,077 7,531 9,181 7,755 10,422 Paint and Coating Manufacturing 5,047 5,200 5,744 5,356 6,529 5,515 7,412 Adhesive Manufacturing 2,050 2,112 2,333 2,175 2,652 2,240 3,010 Plastics Product Manufacturing 46,160 47,559 52,534 48,985 59,713 50,440 67,788 Rubber and Plastics Footwear Manufacturing 25 26 28 27 32 27 37 Plastics Packaging Materials, Film and Sheet Manufacturing 4,965 5,115 5,651 5,269 6,423 5,425 7,291 Unlaminated Plastics Profile Shape Manufacturing 2,616 2,695 2,977 2,776 3,384 2,859 3,842 Plastics Pipe and Pipe Fitting Manufacturing 2,859 2,946 3,254 3,034 3,698 3,124 4,199 Laminated Plastics Plate, Sheet, and Shapes Manufacturing 1,828 1,883 2,080 1,940 2,365 1,998 2,684 Plastics Bottle Manufacturing 3,844 3,960 4,375 4,079 4,973 4,200 5,645 Other Plastics Product Manufacturing 26,821 27,634 30,525 28,463 34,696 29,308 39,388 Polystyrene Foam Product Manufacturing 966 995 1,099 1,025 1,250 1,056 1,419 Urethane and Other Foam Product Manufacturing 2,236 2,304 2,545 2,373 2,893 2,443 3,284 Rubber Product Manufacturing 16,897 17,409 19,230 17,931 21,858 18,464 24,814 Tire Manufacturing 3,601 3,710 4,098 3,821 4,658 3,935 5,288 Rubber and Plastic Hose and Belting Manufacturing 3,947 4,067 4,492 4,189 5,106 4,313 5,796 Other Rubber Product Manufacturing 9,349 9,632 10,640 9,921 12,094 10,216 13,729
Table 22: Ohio: Scenario Projections of Growth in the Chemical and Polymer Cluster using Employment to Year 2020. (Computed)
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TECHNICAL PETROLEUM-BASED BIO-BASED SUBSTITUTION AVERAGE Polymer Sector CHEMICAL CHEMICAL 2020 PERCENT Coated and Laminated Packaging Paper and Plastics Film Manu. Coated & Laminated Packaging Paper & Plastics Film 10% 10% Plastics Material and Resin, Synthetic Rubber and Organic Fiber Manufacturing 325211 Plastics Material and Resin Manufacturing 27.25% PE (Polyethylene) PHA 14% Ethylene Ethylene 0% PTT PTT 100% Nylon 6 (PA) PTT 100% Nylon 6 (PA) PLA 10% PET PLA 41% PS PLA 31% PP starch polymers 10% PP PLA 10% PP PTT, PBT, PBS 20% PP PHA 20% PVC PHA 10% PUR starch polymers 10% PUR PHA 10% PUR PUR 30% PC (polycarbonate) PTT, PBT, PBS 20% 325212 Synthetic Rubber Manufacturing 7% PE (Polyethylene) PHA 14% Ethylene Ethylene 0% 325221, 325222 Artificial and Synthetic Fibers and Filaments 25.50% PVC PHA 10% PET PLA 41% Paint, Coating and Adhesive Manufacturing (3255) 32551 Paint and Coating Manufacturing 10% 32552 Adhesive Manufacturing 10% Plastics Product Manufacturing (3261) 10% 316211 Rubber and Plastics Footwear 10% 326111, 326112, 326113 Plastics Packaging Materials, Film and Sheet 10% 14% PE (Polyethylene) PHA 14% 326121 Unlaminated Plastics Profile Shape 10% 326122 Plastics Pipe and Pipe Fitting 10% 32613 Laminated Plastics Plate, Sheet, & Shapes 10% 32616 Plastics Bottle Manufacturing 10%
Table 23: Year 2020 Technical Substitution Ratios for Bio-based Chemicals, matched to NAICS codes under the Polymer Sector of the OCPCM. (Compiled from: (Crank, et.al., 2005; Patel, et. al., 2006))
(Continued on next page)
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Table 23 Continued
326192, 326191, 326199 Other Plastics Product Manu 10% 326140 Polystyrene Foam Product Manu 31% PS PLA 31% 326150 Urethane and Other Foam Product 16.67% PUR starch polymers 10% PUR PHA 10% PUR PUR 30% Rubber Product Manufacturing (3262) 326211, 326212 Tire Manufacturing 10% 32622 Rubber and Plastics Hose & Belting 10% 326291, 326299 Other Rubber Product Manu 10%
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Technical Substitution Gross State Most Likely Percent of Bio-based in Bio-based Product Base 2% CAGR 2020 GSP in 2020 2007 2020 $ Millions $ Millions $ Millions Polymers 10,855.5 14,042.8 1,760.8 Coated and Laminated Packaging Paper and Plastics Film Manu. 568.9 735.9 0.1 73.6 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manufacturing1,505.7 1,947.7 455.3 Plastics Material and Resin Manufacturing 1,177.4 1,523.1 0.2725 415.0 Synthetic Rubber Manufacturing 284.3 367.8 0.07 25.7 Artificial and Synthetic Fibers and Filaments Manufacturing 44.0 56.9 0.255 14.5 Paint, Coating, and Adhesive Manufacturing 1,355.6 1,753.6 175.4 Paint and Coating Manufacturing 1,042.1 1,348.0 0.1 134.8 Adhesive Manufacturing 313.5 405.6 0.1 40.6 Plastics Product Manufacturing 5,174.0 6,693.2 765.3 Rubber and Plastics Footwear Manufacturing 1.1 1.4 0.1 0.1 Plastics Packaging Materials, Film and Sheet Manufacturing 762.5 986.4 0.14 138.1 Unlaminated Plastics Profile Shape Manufacturing 337.5 436.5 0.1 43.7 Plastics Pipe and Pipe Fitting Manufacturing 441.5 571.1 0.1 57.1 Laminated Plastics Plate, Sheet, and Shapes Manufacturing 176.8 228.7 0.1 22.9 Plastics Bottle Manufacturing 544.6 704.5 0.1 70.5 Other Plastics Product Manufacturing 2,515.7 3,254.4 0.1 325.4 Polystyrene Foam Product Manufacturing 121.5 157.2 0.31 48.7 Urethane and Other Foam Product Manufacturing 272.7 352.8 0.1667 58.8 Rubber Product Manufacturing 2,251.3 2,912.3 291.2 Tire Manufacturing 515.1 666.4 0.1 66.6 Rubber and Plastic Hose and Belting Manufacturing 463.7 599.9 0.1 60.0 Other Rubber Product Manufacturing 1,272.5 1,646.1 0.1 164.6
Table 24: Renewable Polymer Sector Impact on Ohio’s GSP, last column is the bio- based share of the polymer sector industries in 2020 (Computed)
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Technical Substitution Gross State Most Likely Percent of Bio-based in Bio-based Product Base 2% CAGR 2020 GSP in 2020 2007 2020 Person-Years Person-Years Person-Years Polymers 80,483 104,113 12,065 Coated and Laminated Packaging Paper and Plastics Film Manu. 4,341 5,616 0.1 562 Plastics Material and Resin, Synthetic Rubber, and Organic Fiber Manufacturing5,988 7,746 1,716 Plastics Material and Resin Manufacturing 4,195 5,427 0.2725 1,479 Synthetic Rubber Manufacturing 1,479 1,913 0.07 134 Artificial and Synthetic Fibers and Filaments Manufacturing 314 406 0.255 104 Paint, Coating, and Adhesive Manufacturing 7,097 9,181 918 Paint and Coating Manufacturing 5,047 6,529 0.1 653 Adhesive Manufacturing 2,050 2,652 0.1 265 Plastics Product Manufacturing 46,160 59,713 6,684 Rubber and Plastics Footwear Manufacturing 25 32 0.1 3 Plastics Packaging Materials, Film and Sheet Manufacturing 4,965 6,423 0.14 899 Unlaminated Plastics Profile Shape Manufacturing 2,616 3,384 0.1 338 Plastics Pipe and Pipe Fitting Manufacturing 2,859 3,698 0.1 370 Laminated Plastics Plate, Sheet, and Shapes Manufacturing 1,828 2,365 0.1 236 Plastics Bottle Manufacturing 3,844 4,973 0.1 497 Other Plastics Product Manufacturing 26,821 34,696 0.1 3,470 Polystyrene Foam Product Manufacturing 966 1,250 0.31 387 Urethane and Other Foam Product Manufacturing 2,236 2,893 0.1667 482 Rubber Product Manufacturing 16,897 21,858 2,186 Tire Manufacturing 3,601 4,658 0.1 466 Rubber and Plastic Hose and Belting Manufacturing 3,947 5,106 0.1 511 Other Rubber Product Manufacturing 9,349 12,094 0.1 1,209
Table 25: Renewable Polymer Sector Impact on Ohio’s Employment, last column is the bio-based share of the polymer sector industries in 2020 (Computed)
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