Open access peer-reviewed chapter

Economic Performance, Greenhouse Gas Emissions, Environmental Management, and Supply Chains in India: A Comparison with Japan

By Hitoshi Hayami, Masao Nakamura and Kazushige Shimpo

Submitted: October 26th 2015Reviewed: February 16th 2016Published: June 30th 2016

DOI: 10.5772/62535

Downloaded: 892


Using input–output tables and data on wastes from the Japanese industrial sectors, we have provided empirical evidence that, in Japan environmental performance of their upstream suppliers contributes positively to the performance of their final product assembly firms or economic sectors. In this paper, we propose to investigate the same hypothesis for firms and other establishments in manufacturing and other sectors in India. Indian supplier firms that sell goods and services to their client assembler firms are not generally structured in the form of efficient supply chains as in advanced economies. So, the environmental performance of these suppliers may not have positive impacts on the performance of their assembler firms or economic sectors, but this is yet to be verified empirically.


  • greenhouse gas emissions
  • supply chains
  • environmental management
  • firm performance
  • India

1. Introduction

Limiting the amounts of industrial wastes generated in firms’ manufacturing processes has been of policy interest in recent years. A type of waste of our interest in this paper is greenhouse gases (represented by the carbon dioxide equivalent below). Even though it is not harmful to human health, CO2 is being regulated like toxic industrial wastes in many developed countries including Japan. More recently, the importance of limiting CO2 emissions globally has been recognized by both developed and developing nations, and an international treaty to strengthen the former Kyoto protocol was signed in Paris.[1] -

One of the topics of research interest, which has not received much empirical attention, is the extent to which CO2 emissions, as an industrial waste, are generated along firms’ supply chains. Although we see large corporations (e.g., 3M, Sony) promoting green procurement policies and claiming to use environment-friendly suppliers, we have little empirical evidence yet to suggest how such environmental management methods based on supply chains might benefit large downstream firms economically. We do not have much empirical evidence either about the impacts on final products of environmental management policies conducted by firms in their supply chains emerging in developing countries like India.

In this paper we present empirical estimates for the amounts of greenhouse gas (GHG) emissions generated by Indian manufacturing and other economic sectors, and their supply chains. (GHG emissions are measured in carbon dioxide (CO2) equivalent in this paper.) We then estimate their contributions to firm performance measured in terms of value added. Figures 1 and 2 show CO2 emissions per person and per income, respectively, in India and Japan over time. We see from these figures that while Japan emits more CO2 than India per capita, Japan generates less CO2 emissions per dollar than India does.

Figure 1.

CO2 emissions per capita: India and Japan, 1990–2011. Source: Prepared by the authors using figures in [2–5].

Figure 2.

CO2 emissions per GNI (gross national income): India and Japan, 1990–2011. Source: Prepared by the authors using figures in [2–5].

The rest of the paper is organized as follows. After a brief review of earlier studies in Section 2, we discuss our method and approach toward the analysis of the generation of industrial waste (CO2 emissions here) by supply chains in Section 3. Our data are briefly introduced in Section 4. We show and analyze certain patterns that are found in the generation of CO2 emissions in Indian and Japanese industries in Sections 5 and 6. Section 6 presents our empirical results that relate the value added to the generation of wastes by downstream and upstream firms. Section 7 concludes.

2. Literature

There are relatively few research studies that use nations’ input–output (I–O) tables as the data source for analyzing the relationships between supply chains and firms’ environmental performance. Hayami et al. [6] present a framework in which I–O tables can be used for analyzing the effects, at the sector level, of the environmental management performance of firms in supply chains on their downstream assembly firms’ performance. They present references on the literature that discusses many aspects of environmental management at upstream supply chains as related to their downstream customer firms [7,8]. Discussions on supply chains in India are also found [911]. Details of I–O analysis and applications to the Indian economy and environmental management are found in papers contained in [12].

3. Our approach to estimating output and waste along the stages of a supply chain

As noted earlier, certain downstream producers in developed countries are beginning to practice “green procurement,” by which upstream suppliers with greener production processes become the preferred suppliers of their downstream customer firms. For example, Cisco, NEC, Sony, and Toshiba discuss their corporate green procurement guidelines in [1316]. We apply this notion to India and investigate empirically the extent to which the same notion holds in India.

In order for the government to evaluate the potential benefits (i.e., the greening) of upstream firm production processes resulting from promoting downstream instruments, it is essential that we estimate relationships that describe the generation of waste materials at both upstream and downstream firms in a national economy. However, to our knowledge, only Hayami et al. present an empirical framework to achieve this objective using available data [6]. They also present an empirical model that allows us to estimate downstream firms’ benefits of reduction of their suppliers’ environmental wastes.

We apply the above model to India and derive some preliminary empirical estimates that evaluate the relative importance of the waste materials generated along the supply chain. Our findings in this chapter provide complementary evidence to the importance of environmental management in supply chains reported, for example, for individual firms, obtained using survey data and methodologies different from ours [8,17].[1] -,[1] -

3.1. Estimation of output along a supply chain

Our methodology is based on the input–output (I–O) analysis originally developed by Leontief [19,20]. (Applications of the I–O analysis to waste management and other environmental issues are found, for example, in [12,2123]. Additional uses of input–output analysis in environmental management are found in [24]. We divide an economy into industrial and other economic sectors where production of goods and services takes place. We define I–O technical coefficients aij (i,j = 1,2,…,n) to be the amount of input from sector i per unit amount of output from sector j. To ensure positive output values, it is customary to assume the Hawkins–Simon condition [25] that aij lie between 0 and 1 and their column sums are less than 1.

Suppose xj denotes the output from sector j. Then aij are estimated as follows:

aij= (Xij/xj),E1

where Xij denotes the amount of input from sector i that is required for the production of xj. Using supply chain terms, we say aij connect downstream output from sector j to its immediate predecessor upstream input from sector i.

We denote by A an n × n matrix with elements aij, and by x an n × 1 vector in which each component xj represents domestic production (output) of sector j (j = 1,2,..,n). We also denote by fi the final downstream demand for sector i. We denote by f the corresponding n × 1 final downstream demand vector. For example, fi = 1 means a unit final downstream demand for output from sector i. (For simplicity, we ignore the impacts of international trade.)

In order to produce the final downstream demand f, the total amount of input required from sector i in the immediate predecessor stage (denoted by k = 1) is given by


x(1) is also interpreted to be the indirect demand for the previous stage (k = 1) production process, which is induced by final demand f, because without the production of x(1), the final demand cannot be met. In order to produce x(1), the total amount of input required from sector i in the immediate predecessor stage (denoted by k = 2) in the supply chain is given by the ith element of the following vector:


Generally, we can trace production activities along the supply chain backward, starting from the final demand, and we get

x(k)=Ax(k1)=Akf,k= 1,2,....E4

We call x(k) the kth stage indirect effect of final demand f (k = 1,2,…) in the supply chain.

In order to be able to produce final demand f, the following total indirect output must be produced:

x(indirect)=Af+A2f+...... +Akf+ .... =A(IA)1f,E5

where (IA)-1 is the Leontief inverse matrix which exists provided that the aij satisfy the Hawkins–Simon condition given above.

We have shown that our input–output analysis identifies the successive upstream production processes that are followed by the average supply chain for the final demand vector f. This is summarized as follows. The input–output analysis describes all economic activities of the average supply chain in a national economy by following input–output transactions for all goods and services. The analysis typically starts from the final stage of downstream demand as shown above and moves backward by backtracking all predecessor upstream stages of production.

In this paper, we consider CO2 (defined here to be the combined greenhouse gases measured in CO2 equivalent) as a waste material associated with industrial production activities.

3.2. Graphical representation of connectedness of I–O sectors

Different sectors tend to be more connected in modern developed economies than in developing economies. This is because, in a modern economy, unproductive sectors will become more productive, with inputs from more productive sectors to survive. In addition, primary sectors and supplier sectors of manufacturing are connected to assembly sectors of manufacturing in a functional and efficient manner in supply chains. These functional connections are often missing in developing economies. Figures 35 show the degrees of 35 I–O sectors’ connectedness to each other in India and Japan. These 35 sectors are as follows:

1Agriculture, Hunting, Forestry, and Fishing
2Mining and Quarrying
3Food, Beverages, and Tobacco
4Textiles and Textile Products
5Leather and Footwear
6Wood, and Products of Wood and Cork
7Pulp, Paper, Printing, and Publishing
8Coke, Refined Petroleum, and Nuclear Fuel
9Chemicals and Chemical Products
10Rubber and Plastics
11Other Nonmetallic Minerals
12Basic Metals and Fabricated Metals
13Machinery, NEC
14Electrical and Optical Equipment
15Transport Equipment
16Manufacturing, NEC; Recycling
17Electricity, Gas, and Water Supply
19Sales, Maintenance, and Repair of Motor Vehicles and Motorcycles; Retail Sale of Fuel
20Wholesale Trade and Commission Trade, Except of Motor Vehicles and Motorcycles
21Retail Trade, Except of Motor Vehicles and Motorcycles; Repair of Household Goods
22Hotels and Restaurants
23Inland Transport
24Water Transport
25Air Transport
26Other Supporting and Auxiliary Transport Activities; Activities of Travel Agencies
27Posts and Telecommunications
28Financial Intermediation
29Real Estate Activities
30Renting of m&eq and Other Business Activities
31Public Administration and Defense; Compulsory Social Security
33Health and Social Work
34Other Community, Social, and Personal Services
35Private Households with Employed Persons

List of 35 aggregate I–O sectors used in Figures 35

Source: [5,32].

Figure 3.

Degrees of connectedness of 35 I–O sectors: India, 1995. Note: The size of each square represents the amount of relevant input for the cell measured in terms of US $million dollars at current price. Numbers on vertical and horizontal axes represent 35 I–O sectors for India and Japan defined in the text.

Figure 4.

Degrees of connectedness of 35 I–O sectors: India, 2003. Note: The size of each square represents the amount of relevant input for the cell measured in terms of US $million dollars at current price. Numbers on vertical and horizontal axes represent 35 I–O sectors for India and Japan defined in the text.

Figure 5.

Degrees of connectedness of 35 I–O sectors: Japan, 2003. Note: The size of each square represents the amount of relevant input for the cell measured in terms of US $million dollars at current price. Numbers on vertical and horizontal axes represent 35 I–O sectors for India and Japan defined in the text.

Intuitively speaking, Figures 35 show the degrees of connectedness between sectors in terms of economic transactions. For example, sectors whose transactions are mostly within themselves are depicted as single dots. On the other hand, if two different sectors have more transactions with each other, then those two sectors are connected by a box. Multiple sectors with transactions, such as sectors that define supply chains, are shown with larger boxes containing them. As expected, Figures 3 and 4 show that sectors of the Indian economy are not much connected to each other, though there are considerably more connectedness observed during 2003 than during 1995. This implies that there are increasingly more supply chain type relationships emerging in the Indian economy in recent years. The Japanese economy has developed well-defined supply chain based relationships among sectors in many industries [6]. This is clearly observed in Figure 5. We speculate from these figures, for example, that environmental management performance of upstream suppliers affect the performance of downstream firms much more in Japan than in India.

3.3. Estimation of wastes along a supply chain[1] -

In the I–O analysis presented in Section 3.1, it is customary to include output which has economic value.[1] - It is also customary to assume that industrial waste has no economic value in the form it is generated. For these reasons, industrial wastes are not included in our analysis in Section 3.1.[1] - We treat waste materials separately here. Suppose we have estimated E1j , the amount of waste generated per unit of output produced in sector j (j = 1,2,..,n). We denote by E the corresponding n × n diagonal matrix with E1j in the jth diagonal position. Then the amounts of waste produced by the output of sector j along the successive stages of a supply chain are given as follows:

Denote by wj the amount of waste generated in sector j, and denote by w an n × 1 vector consisting of wj (j = 1,2,..,n).

Then in the final stage, stage 0 (k = 0), of a supply chain, the demand is f, and the waste generated is

w(0) = EA0f = Ef, which is the waste generated from assembly operations of final output f.

In the immediate predecessor upstream stage, stage 1 (k = 1), of the supply chain, the amount of waste generated (called indirect output for stage 1) is


Similarly, we can derive the amount of waste generated along the upstream stages (k = 2, 3,…,) of the supply chain as follows:

w(k)=EAx(k1)=Akf, k= 2,3, ...E7

This is shown in the last row of Table 1.

UpstreamStages of a supply chain (→ → → closer to the final demand → → →)Downstream: final stage of a supply chain (final demand)
and waste
in upstream
(k = 1,2,…)
← ← ←Indirect
output for
the m-th
stage in
(k = m)
← ← ←Indirect
output for
the second
stage in
(k = 2)

output for
the first
stage in
(k = 1)
Production output along the stages of a supply chain
x(indirect) =
Af + A2f +
… + Akf
+ … = A
← ← ←x(n) = Ax(n-1)
= Anf
← ← ←x(2) = Ax(1) = A2fx(1) = Aff (direct
Waste output generated along the stages of a supply chain
w(indirect) =
AEf + A2Ef
+ .... + AkEf
+ … = A(I
← ← ←w(n) =
← ← ←w(2) =
w(1) = AEfEf (direct

Table 1.

Production and waste output along the stages of a supply chain.

3.4. Output along a firm-specific supply chain and statistically obtained average output along the average supply chain

We do not have data on individual firm-specific supply chains that expand from downstream to upstream stages of production. However, element aij of input–output matrix A = {aij, i, j = 1,2,..,n} is in fact the statistically estimated average fraction of output of sector i that goes to sector j. This statistical method of obtaining matrix A (called the commodity flow method) thus allocates input Xij from the data of total output xj [27], that is, aij connects downstream sector j to its immediate upstream sector i statistically. We have used this property of matrix A to obtain the average production and waste output along the stages of the average supply chain, x(k) and w(k), k = 1,2,…, given downstream demand vector f. If we had data on production and waste output for the stages of all firm-specific supply chains for given f, then our I–O based estimates give the first-order approximation to the average output of the quantities for all such firm-specific supply chains. (The first-order approximation arises because of the linearity of aij which defines the I–O matrix A.)

4. Data

4.1. Input–output matrix

As we have noted in Section 3.1, our estimation methodology uses an n × n matrix A consisting of

I–O technical coefficients aij (i,j = 1,2,…,n), where n is the number of economic sectors being considered. Since 1973, estimated values for aij (i,j = 1,2,…,n) are published every 5 years as I–O tables by the Government of India [9,28]. In this paper, we primarily use the Indian I–O tables for the years 1998–1999 and 2003–2004, with 130 sectors (n = 130). The I–O sectors consist of 37 primary sectors, 68 secondary (manufacturing) sectors, and 25 service sectors.

In addition to the I–O matrix A = {aij (i,j = 1,2,…,n)}, the Indian I–O table includes additional information on relevant economic quantities for each of the 130 sectors including final demand f for the Indian economy (see Appendix A1).

4.2. Waste and y-products surveys, and I–O matrix A

The environmental input–output table that we use here, based on greenhouse gas emission estimates (GOI, 2010), I–O table, material table, calorific table, combustion ratio table, and other data, was constructed by [9,12,29,30].

4.3. Calculating the amounts of waste materials

Using application of the input-output analysis described above, we used the estimated quantities of CO2 for each of the 130 Indian I–O sectors, which we use in our regression analyses. We also used value-added estimations for each of these I–O sectors.

Using I–O analysis, we estimated the amounts of CO2 generated per unit output for each of the 130 I–O sectors.

We are interested in studying the behavior of CO2 emissions in firms’ decision processes. In this paper, we denote by CO2 emissions the total emissions in carbon dioxide equivalents of all greenhouse gases. CO2 has certain characteristics in common in terms of their implications for firms’ own economic incentives and government regulations.[1] - For example, CO2 emissions, like some other nontoxic wastes, are harmless to human health. On the other hand, CO2 emissions, like some other waste materials, may also mean firms’ excessive use of costly inputs (fossil fuels in case of CO2). (Note that CO2 emissions and fossil energy use are highly correlated [32, 33].

5. Waste output along supply chains: example of an auto industry

One topic of research interest is to evaluate the relationships that might exist between downstream and upstream firms in terms of their waste behavior. Input–output analysis identifies statistically average economic relationships that exist between upstream and downstream firms. It is then possible to use input–output analysis also to find the average amounts of wastes that are generated by upstream firms in supply chains in response to production activities for the final products of downstream firms.

5.1. Example of an auto industry example

Table 1 illustrates how our production of output and waste takes place along a supply chain starting from the final downstream demand. By tracing backward, final assembly plant receives inputs from suppliers in upstream stage 1, who in turn receive their inputs from suppliers in upstream stage 2. As we have shown, I–O analysis allows us to estimate inputs between two successive stages of production along a supply chain.

5.2. A numerical example, India and Japan

This example illustrates the supply chain effects in the propagation of waste (CO2) generation along supply chains in India and Japan.

Amounts generated (tons)Cumulative amounts (tons)Ratio to total
Indirect (first stage)0.7065680.8141930.15462
Indirect (second stage)1.2058882.0200810.383625
Indirect (third stage)1.1518943.1719740.602376
Indirect (fourth stage)0.8969744.0689480.772717
Total (all stages)5.265775.2657701

Table 2.

Supply chain effects, auto industry in Japan: CO2 emissions generated by production of one passenger car with a 2000 cc engine.

Source: Authors’ calculations.

Amounts generated (tons)Cumulative amounts (tons)Ratio to total
Indirect (first stage)1.9198792.0545390.4580298
Indirect (second stage)1.2387333.2932720.7341874
Indirect (third stage)0.64061563.9338880.8770033
Indirect (fourth stage)0.30346874.2373570.9446573
Total (all stages)4.4856024.4856021

Table 3.

Supply chain effects, auto industry in India: CO2 emissions generated by production of one passenger car with a 2000 cc equivalent engine.

Source: Authors’ calculations.

Tables 2 and 3 show how much CO2 emissions occur along the auto supply chains in producing passenger cars with certain characteristics: median size cars in India and cars with 2000 cc engines in Japan.

We see from Table 2 that firms along the auto supply chain in Japan generate 5.26577 tons of CO2 emissions, but only 2% of this amount is generated by the final assembler firms. The remaining 98% of CO2 emissions are generated by suppliers and other upstream firms in the supply chain. In comparison, the corresponding figures for India are: 4.485602 tons of total CO2 emissions per car are generated in total, of which 3% is generated by the final assembler firms and the rest (97%) of the emissions are generated by suppliers (Table 3). This similarity in the patterns of CO2 emissions along auto supply chains between India and Japan suggests that production technology of autos is reasonably standardized, perhaps due to the fact that many auto plants in India are owned and operated to a large extent by Western automakers. Another noteworthy point is that total CO2 emissions per car produced is somewhat lower in India than in Japan. This difference occurs in part because of the sizes of passenger cars considered here that are different between India and Japan, and also in part because of the difference between India and Japan in the amounts of CO2 emissions induced by imported car parts. The use of more imported parts implies lower levels of domestic CO2 emissions, which is the case for India. For passenger car production, this ratio is 0.05846 for India and 0.02316 for Japan.

Based on the results given in Tables 2 and 3, we conclude that government environmental regulations about greenhouse gas emissions need to include not only the final auto producers but also many upstream suppliers, in order to be effective.

We noted that our results in Tables 2 and 3 are consistent with the possibility that downstream firms might be able to upload the processing of CO2 in particular to their upstream suppliers, while processing relatively large amounts of nonenergy-intensive tasks themselves in-house. This could easily happen in practice, since processing energy-intensive tasks is generally expensive.

We also note that this hierarchical structure of processing of the waste materials emitted by firms in assembly-based industries is likely to be typical. This is because of the nature of the types of assembly-based industries, which are most efficiently done by streamlining their supply chains so that assembly operations come last. In addition, assembly firms are generally more powerful than suppliers in their supply chains and hence have the most bargaining power.

Detailed processes of generation of CO2 emissions by upstream and downstream firms are presented in Tables 4 and 5.

Auto: CO2Tons per passenger car (2000 cc equivalent)
DirectFirst indirectSecond indirect3rd indirect4th indirectTotal Generation
Passenger motor cars0.1076Electricity0.1722Electricity0.5514Electricity0.3349Pig iron0.3230Electricity1.2982
Motor vehicle parts and accessories0.1013Cast and forged materials (iron)0.1115Pig iron0.1840Electricity0.1315Pig iron1.0449
Internal combustion engines for motor vehicles and parts0.0663Road freight transport0.0474Private power generation0.1040Private power generation0.1290Private power generation0.4804
Private power generation0.0601Miscellaneous ceramic, stone, and clay products0.0372Coal products0.0927Coal products0.0831Coal products0.3476
Road freight transport0.0599Private power generation0.0349Self-transport by private cars (passengers) P0.0393Crude steel (converters)0.0319Road freight transport0.1471
Sheet glass and safety glass0.0598Nonferrous metal castings and forgings0.0345Crude steel (converters)0.0287Self-transport by private cars (passengers) P0.0185Cast and forged materials (iron)0.1211
Research and development (intra-enterprise)0.0282Self-transport by private cars (passengers) P0.0268Miscellaneous ceramic, stone and clay products0.0268Petroleum refinery products (inc. greases)0.0162Self-transport by private cars (passengers) P0.1082
Motor vehicle bodies0.0209Research and development (intra-enterprise)0.0260Hot rolled steel0.0244Paper0.0144Motor vehicle parts and accessories0.1080
Coastal and inland water transport0.0165Synthetic rubber0.0225Self-transport by private cars (freight) P0.0225Petrochemical basic products0.0132Passenger motor cars0.1076
Tires and inner tubes0.0158Hot rolled steel0.0212Road freight transport0.0209Hot rolled steel0.0120Crude steel (converters)0.0910
Plastic products0.0114Coated steel0.0207Cold-finished steel0.0202Self-transport by private cars (freight) P0.0107Miscellaneous ceramic, stone and clay products0.0895
Waste management services (private)0.0106Thermoplastics resins0.0190Paper0.0193Road freight transport0.0095Petroleum refinery products (inc. greases)0.0695
Self-transport by private cars (passengers) P0.0093Cold-finished steel0.0158Synthetic rubber0.0166Aliphatic intermediates0.0089Hot rolled steel0.0689
Cold-finished steel0.0093Petroleumrefinery products (inc. greases)0.0154Thermoplastics resins0.0161Miscellaneous ceramic, stone and clay products0.0087Internal combustion engines for motor vehicles and parts0.0687
Hot rolled steel0.0076Plastic products0.0153Petroleum refinery products (inc. greases)0.0148Coastal and inland water transport0.0055Research and development (intra-enterprise)0.0638
Miscellaneous ceramic, stone, and clay products0.0071Other rubber products0.0131Aliphatic intermediates0.0135Pulp0.0051Sheet glass and safety glass0.0605
Self-transport by private cars (freight) P0.0049Coastal and inland water transport0.0129Petrochemical basic products0.0124Cyclic intermediates0.0048Self-transport by private cars (freight) P0.0597

Auto: CO2Tons per passenger car (2000 cc equivalent)
DirectFirst indirectSecond indirectThird indirectFourth indirectTotal generation
Electrical equipment for internal combustion engines0.0046Self-transport by private cars (freight) P0.0128Coastal and inland water transport0.0091Paperboard0.0042Paper0.0537
Electric bulbs0.0044Coal products0.0124Cast and forged materials (iron)0.0080Waste management services (private)0.0041Cold-finished steel0.0509
Petroleum refinery products (inc. greases)0.0037Cast and forged steel0.0115Air transport0.0071Cold-finished steel0.0039Coastal and inland water transport0.0499
Air transport0.0032Other final chemical products0.0104Waste management services (private)0.0069Industrial soda chemicals0.0036Synthetic rubber0.0424
Abrasive0.0030Wholesale trade0.0100Research and development (intra-enterprise)0.0065Crude steel (electric furnaces)0.0035Thermoplastics resins0.0392
Advertising services0.0029Crude steel (converters)0.0099Cyclic intermediates0.0063Air transport0.0031Nonferrous metal castings and forgings0.0385
Other rubber products0.0024Paper0.0073Aluminum (inc. regenerated aluminum)0.0062Ferro alloys0.0031Petrochemical basic products0.0327
Coated steel0.0024Air transport0.0066Other industrial organic chemicals0.0050Cement0.0029Aliphatic intermediates0.0307
Wholesale trade0.0023Motor vehicle parts and accessories0.0061Other resins0.0044Thermoplastics resins0.0028Plastic products0.0305
Harbor transport service0.0023Steel pipes and tubes0.0056Hired car and taxi transport0.0038Petrochemical aromatic products (except synthetic resin)0.0024Waste management services (private)0.0300
Sewage disposal0.0020Inorganic pigment0.0053Coated steel0.0037Synthetic rubber0.0022Coated steel0.0282
Hired car and taxi transport0.0019Waste management services (private)0.0050Industrial soda chemicals0.0037Research and development (intra-enterprise)0.0019Air transport0.0226
Coal products0.0018Electrical equipment for internal combustion engines0.0050Crude steel (electric furnaces)0.0036Other industrial organic chemicals0.0018Motor vehicle bodies0.0219
30 sectors Subtotal0.69831.13381.13381.06560.86554.8061
Cumulative/Grand total0.02040.15460.38360.60240.77271.0000

Table 4.

Generation of CO2 by supply chains per production of a passenger car with a 2000 cc engine: Japan.

Auto: CO2Tons per passenger car (2000 cc equivalent)
DirectFirst stage indirectSecond stage indirectThird stage indirectFourth stage indirectTotal generation
VehiclesIron steel and ferroalloys0.8470Iron steel and ferroalloys0.2832Iron steel and ferroalloys0.0799Iron steel and ferroalloys0.0266Iron steel and ferroalloys1.2545
Iron and steel casting and forging0.0405Petroleum products0.0456Petroleum products0.0296Petroleum products0.0152Motor vehicles0.1489
Land transport including pipelines0.0388Nonferrous basic metals0.0384Nonferrous basic metals0.0152Cement0.0063Petroleum products0.1239
Petroleum products0.0205Iron and steel casting and forging0.0305Land transport including pipelines0.0126Land transport including pipelines0.0057Iron and steel casting and forging0.0872
Synthetic fibers and resin0.0146Land transport including pipelines0.0254Cement0.0113Nonferrous basic metals0.0051Land transport including pipelines0.0872
Nonferrous basic metals0.0141Synthetic fibers and resin0.0174Iron and steel casting and forging0.0109Iron and steel casting and forging0.0034Nonferrous basic metals0.0759
Motor vehicles0.0125Coal and lignite0.0090Synthetic fibers and resin0.0072Synthetic fibers and resin0.0029Synthetic fibers and resin0.0442
Air transport0.0119Cement0.0077Coal and lignite0.0050Paper, paper products, and newsprint0.0022Cement0.0313
Other nonmetallic mineral products0.0071Paper, paper products, and newsprint0.0060Paper, paper products, and newsprint0.0041Coal and lignite0.0021Paper, paper products, and newsprint0.0186
Trade0.0055Railway transport services0.0055Inorganic heavy chemicals0.0031Inorganic heavy chemicals0.0016Coal and lignite0.0182
Insurance0.0046Other nonmetallic mineral products0.0052Railway transport services0.0031Railway transport services0.0014Air transport0.0180
Paper, paper products, and newsprint0.0043Inorganic heavy chemicals0.0049Natural gas0.0025Other nonmetallic mineral products0.0012Other nonmetallic mineral products0.0169
Hand tools and hardware0.0041Natural gas0.0045Other nonmetallic mineral products0.0024Natural gas0.0012Railway transport services0.0150
Railway transport services0.0040Trade0.0037Trade0.0018Other chemicals0.0009Inorganic heavy chemicals0.0128
Rubber products0.0040Air transport0.0036Other chemicals0.0017Trade0.0008Trade0.0123
Plastic products0.0038Coal products0.0023Air transport0.0015Fertilizers0.0007Natural gas0.0092
Other chemicals0.0034Other chemicals0.0021Coal products0.0013Crude oil0.0006Other chemicals0.0087
Banking0.0033Plastic products0.0019Crude oil0.0010Air transport0.0006Plastic products0.0070
Inorganic heavy chemicals0.0020Motor vehicles0.0014Fertilizers0.0009Coal products0.0005Insurance0.0066
Other transport equipment0.0018Banking0.0013Plastic products0.0008Plastic products0.0003Banking0.0057
Other nonelectrical machinery0.0017Insurance0.0013Construction0.0006Construction0.0003Rubber products0.0053
Miscellaneous metal products0.0007Construction0.0010Banking0.0006Banking0.0002Hand tools and hardware0.0048
Art silk and synthetic fiber textiles0.0006Iron ore0.0009Insurance0.0004Structural clay products0.0002Coal products0.0045
Communication0.0006Rubber products0.0008Structural clay products0.0004Insurance0.0002Fertilizers0.0028
Coal and lignite0.0005Communication0.0007Water transport0.0004Water transport0.0002Crude oil0.0027
Construction0.0004Hand tools and hardware0.0006Iron ore0.0003Other oil seeds0.0002Construction0.0025
Electronic equipments including TV0.0004Water transport0.0006Communication0.0003Communication0.0001Other nonelectrical machinery0.0022
Jute hemp and mesta textiles0.0004Miscellaneous manufacturing0.0006Storage and warehousing0.0003Storage and warehousing0.0001Other transport equipment0.0021
Community, social, and personal services0.0003Miscellaneous metal products0.0005Rubber products0.0003Jute hemp and mesta textiles0.0001Communication0.0018
30 sectors subtotal0.13471.91671.23330.63760.30204.4656
Cumulative/Grand total0.03000.45800.73420.87700.94471.0000

Table 5.

Generation of CO2 by supply chains per production of a passenger car with a medium size engine: India.

Source: Authors’ calculations.

Tables 4 and 5 show the amounts of CO2 emissions generated by the final auto producers, as well as their suppliers and other upstream firms, in producing a passenger car with a 2000 cc engine. These tables provide details on the amounts of waste materials generated by each of the industrial sectors, based on which figures reported in Tables 2 and 3 were obtained.

6. Estimating the contributions of direct and indirect CO2 emissions

6.1. Relative contributions of direct and indirect CO2 emissions to the total sectorial emissions

It is intuitively clear that final output (called output from downstream sectors), whether assembled manufactured products, or output from primary sectors such as mining and agriculture, uses much output produced in their predecessor sectors including suppliers (upstream sectors). It is then likely that the total emissions attributable to any final product (e.g., a passenger car) consist of significant amounts of indirect emissions from upstream sectors and direct emissions which are emitted from the final car assembly stage in the downstream part of the supply chains. Figures 6 and 7 show the breakdown of direct and indirect emissions for 16 sectors. Industries 9–13 with asterisks are thought to be assembly-based manufacturing industries.

We see in these figures that CO2 emissions are skewed toward upstream firms in manufacturing supply chains. This is particularly evident for Japan (Figure 7). Figure 7 also shows that proportions of toxic wastes show a similar pattern.

Figure 6.

CO2 emissions by industry: proportions of indirect emissions for India.

Figure 7.

CO2 emissions by industry: proportions of indirect emissions for Japan. Notes: In this graph for Japan, proportions of indirectly generated amounts of toxic waste (solid and liquid) materials other than CO2 are also shown.

2Food production
6Petrol/Coal production
7Basic metals
8Nonferrous metals production
9*General machinery
10*Electric machinery
12*Transportation machinery
13*Precision machinery
14Electric power
15Public utility

List of industries used in Figures 6 and 7

*Assembly-based manufacturing industries.

Are the patterns of CO2 emissions across upstream and downstream economic sectors that we observed in Figures 6 and 7 consistent with downstream firms’ profit maximization behavior? We are interested in testing the following hypothesis:

H1: Downstream firms’ performance (measured by their value added) is affected by their upstream firms’ CO2 emissions as well as their own.

In general, we expect upstream firms’ generation of toxic wastes such as CO2 to be a negative factor in firms’ value added, but generation of nontoxic wastes may not be, since most nontoxic wastes have commercial value. We first focus on the impacts of downstream firms’ immediate predecessor upstream firms on downstream firm performance, because the impacts, if any, of downstream firms’ environmental management policies such as green procurement can extend most effectively to their immediate predecessor upstream suppliers.

Dependent variableValue addedValue addedValue addedValue added
Direct CO2 waste (downstream)−0.0043
Indirect CO2 waste (upstream total, all stages)−0.1266***
Indirect CO2 waste (upstream, first stage)−0.0107***
Adjusted R20.018460.272580.043730.12097
No. of observations130130396396

Table 6.

Determinants of downstream firms’ value added: effects of direct and indirect CO2 emissions by upstream firms, India and Japan.

*Significance level at 10%.

**Significance level at 5%.

***Significance level 1%.

Notes: The dependent variable (value-added) is measured per sector output.

Neither Harisson-McCabe nor Breusch-Pagan tests for heteroskesdasticity detected statistically significant level in the regressions reported above.

We have also run regressions with log of value-added as the dependent variable. We obtained estimation results which are qualitatively the same. Further, we experienced considerable multicollinearity when indirect emissions from both first and all stages entered regressions. Therefore, we only report regressions with either one of the indirect emission variables here.

These regression results were calculated by the authors. Results for Japan in columns E and F are also reported in [6].

We test this hypothesis empirically by estimating the following regressions using a sample of economic sectors corresponding to Indian input–output sectors for which usable data are available. The data used includes value added and the amounts of CO2 emissions generated during direct and indirect stages of production for each of the input–output sectors in the sample. (Descriptive statistics for these variables for India and Japan are presented in Appendix 2.)

In our specification, we regress value added on the amounts of CO2 generated directly by downstream firms as well as the amounts of CO2 generated indirectly by their upstream producers. Our OLS regression results for India are given in columns A and B of Table 6. Columns C and D show the corresponding results for Japan.[1] -

Even though CO2 is not thought to be one of the industrial wastes in a traditional sense, the amounts of CO2 emissions represent the levels of firms’ inputs of fossil fuels. As such, like some other toxic wastes, firms have economic incentives, even without government regulations, to reduce such emissions of CO2, since the cost of energy can be a significant portion of firms’ production costs. Furthermore, from policy perspectives, some policies introduced by the governments of developed countries have been promoting energy-efficient production processes for many years (e.g., beginning in the late 1970s, after the second oil crisis in Japan). And also, in recent years, CO2 emission quota policies of various sorts are being introduced in Japanese, EU, and other nations’ industries.

From Column C of Table 6, we see that 1 ton of direct waste output of CO2 contributes to −0.0018 of firms’ value added per yen of firms’ output. On the other hand, contribution to firms’ value added of the indirect waste output of CO2 from their immediate upstream predecessor suppliers is −0.0115, which is numerically much larger and statistically more significant than our direct waste output. We conclude that firms face significant financial losses, measured by value added, when direct and indirect generation of CO2 occurs in their own production processes. Generation of CO2 emissions by firms’ immediate upstream predecessor suppliers seems to have much larger negative effects on their value added than their own direct waste output. This suggests that downstream firms may have economic incentives to reduce waste output by their immediate predecessor upstream suppliers.

Comparing columns A (India) and C (Japan), we see similar patterns on how CO2 emissions along supply chains affect final sectors’ value added. As far as final sectors’ direct emissions are concerned, direct CO2 emissions have no impact on value added for India, since its coefficient (−0.0043) is statistically not significant. On the other hand, their immediate predecessor CO2 emissions negatively affect final sectors’ value added (with statistically significant coefficient (−0.0107). But direct emission coefficients in Column B are positive and statistically significant (0.0649), suggesting that the more fossil energy is used by the final sector, the more productive (in terms of value added) final sectors become. This might indicate inefficient use of fossil energy, but this is not clear, since the same coefficient in column A is statistically insignificant.[1] - In all cases, indirect emissions from all supplier stages combined are statistically significant and negative. From these results, we tentatively conclude that, for India, environmental management policies encouraging suppliers in supply chains to reduce their CO2 emissions will likely improve final sector firms’ performance measured in terms of value added. These results for India are consistent with but are not as strong as the policy conclusions obtained for Japan [6].

7. Concluding remarks

Recent advances in supply chain based management methods have made it possible for many firms to organize their production and other business activities as part of the supply chains they belong to. Efficiency gains are realized in terms of reduced inventories, reduced lead times for new product development, and shorter delivery lags, among many other benefits. Our results suggest that including certain supply chain level environmental management schemes, such as “how to manage toxic and nontoxic wastes, as well as CO2 emission for a supply chain as a whole,” in such supply chain management methods might improve not only downstream firms’ economic performance but also advanced economies’ environmental performance significantly.

Consideration of such schemes may underlie some firms’ proposals for green procurement policies. In many sectors of an advanced economy, as supply chain management becomes more sophisticated in pursuing economic efficiency, larger downstream firms tend to become more dominant as the primary driver of management decisions associated with their supply chains. (Note, however, that this phenomenon is not limited to assembly-based manufacturing industries. In retail industries, Walmart and the like have become the primary decision makers for their entire global supply chains.) It is possible that, as a national economy develops and increases its sophistication in logistic capabilities, organic connections between upstream and downstream firms become more prevalent, as we see in Japan. This might make it easier for some downstream firms to adopt green procurement policies.

Another factor that might be important to consider in supply chain based environmental policies is firm ownership structures. Ownership structures of firms involved in supply chains are complex but tend to share some systematic patterns. Dominant downstream firms generally influence business decisions of their upstream suppliers via some forms of partial ownership and/or certain guaranteed purchase agreements. Dominant firms do not necessarily extend their partial ownership to all other firms in their supply chains, but, nevertheless, dominant firms often have significant influence over smaller upstream firms through various sorts of business relationships.

Current public policies on waste management in Japan focus on firms and/or establishments. Because of the reasons stated above, this is not appropriate for an advanced economy in which many firm decisions are made at their supply chain levels in interrelated ways. Our empirical results present limited evidence, for both India and Japan, that downstream firms’ economic performance is affected not only by their own environmental policies but also by the environmental behavior of their upstream suppliers. Some profit-maximizing firms may see it to their advantage to implement green procurement policies. As we have shown, improving suppliers’ environmental performance may lead to immediate improvements in downstream firms’ economic performance. We suppose that government environmental policies need to accommodate this supply chain effect as well. As of now, few environmental regulations for downstream firms have serious implications for upstream firms’ environmental behavior.


The authors thank Keio University for their generous support to conduct research reported in this Chapter. This research was also in part supported by the Social Science and Humanities Research Council of Canada.

Appendix A1. 130 Sectors of the input–output Table: India, 2003

oils other
than vanaspati
2Wheat42Tea and
and cotton
textiles in
8Sugarcane48Woolen textiles
9Groundnut49Silk textiles
10Coconut50Art silk
and synthetic
fiber textiles
11Other oil seeds51Jute hemp
and mesta
12Jute52Carpet weaving
textile products
15Coffee55Furniture and
fixtures (wooden)
16Rubber56Wood and
wood products
17Tobacco57Paper, paper
products, and
and publishing
19Vegetables59Leather footwear
20Other crops60Leather and
leather products
21Milk and
milk products
61Rubber products
62Plastic products
23Poultry and eggs63Petroleum products
64Coal products
and logging
27Coal and
28Natural gas68Pesticides
29Crude oil69Paints,
varnishes, and lacquers
30Iron ore70Drugs and
31Manganese ore71Soaps,
33Copper ore73Other
36Mica76Other nonmetallic
mineral products
77Iron, steel,
and ferroalloys
38Sugar78Iron and steel
casting and forging
and boora
79Iron and steel
basic metals
117Hotels and
120Ownership of dwellings
121Education and research
122Medical and health
123Business services
90Batteries125Legal services
126Real estate
127Renting of machinery
and equipment
128Community, social,
and personal services
129Other services
and boats
130Public administration
and defense
121Education and research
122Medical and health
123Business services
124Computer-related services
125Legal services
126Real estate
127Renting of machinery
and equipment
103Gems and
128Community, social, and
personal services
129Other services
130Public administration
and defense
106Construction121Education and research
107Electricity122Medical and health
108Water supply123Business services
124Computer-related services
125Legal services
126Real estate
127Renting of machinery
and equipment
128Community, social, and
personal services
129Other services
115Communication130Public administration
and defense
Final Demand
PFCEPrivate final
in stocks
VAValue added

Source: [28,31].

Appendix A2. Descriptive statistics for regression variables: India, 2003 and Japan, 2000

VariablesMeanStd. dev.MedianMinimumMaximumNo. obs.
Value added (dep. variable)0.479780.235040.388900.009081130
GHG emissions (CO2 equivalent): India, ton-CO2 per million Rupees
Direct emissions (from current sector)1.46995.47090.18850.000048.1495130
Indirect emissions (emissions from all previous sectors/stages combined)2.46673.22551.98130.000027.4213130
Indirect emissions (emissions from immediate predecessor sector/stage)3.28172.59902.98070.000018.5870130
Japan obs.
Value added (dep. var.)0.4442860.1809050.40806600.929868396
GHG emissions (CO2 equivalent): Japan, ton-CO2 per million Yen
Direct emissions (from current sector)1.814888.023130.248140104.2946396
Indirect emissions (emissions from all previous sectors/stages combined)2.990293.992681.98527052.4515396
Indirect emissions (emissions from immediate predecessor sector/stage)1.423722.995840.71593044.9873396

Source: India—The dataset is compiled by the authors using The Central Statistical Organisation, India at current million Indian Rupees [28]. Japan—The dataset is compiled by the authors using data available from and Ministry of Economy, Trade and Industry.

Notes. Value added and direct waste outputs are measured per sector output. Indirect waste output for each stage is measured per total indirect output (all stages combined).


  • The 2015 United Nations Climate Change Conference, held in Paris, France, from November to December 2015 was the 21st yearly session of the Conference of the Parties (COP) to the 1992 United Nations Framework Convention on Climate Change (UNFCCC) and the 11th session of the Meeting of the Parties to the 1997 Kyoto Protocol. The Paris Agreement, a global agreement on the reduction of climate change, the text of which represented a consensus of the representatives of the 196 parties attending it, was signed. It needs to be ratified to become a world treaty [1].
  • A questionnaire-based survey across 124 companies from eight industrial sectors in Taiwan was used [17] in one study, while survey data on a sample of 122 firms drawn from electronics manufacturers listed on the database of the Taiwan Stock Exchange Corporation (TWSE) market and the Gre Tai Securities Market (GTSM) in Taiwan was used in another study [8].
  • See [18] where Indian manufacturers’ approaches to green supply chain management are explained.
  • Waste here denotes CO2, but our formulation applies to other waste materials as well.
  • In reality, most waste materials have positive or negative economic value. For example, CO2 has economic value in the GHG market currently [26].
  • Actual statistical treatment of industrial waste materials depends on the nature of each waste material, which we will not discuss here.
  • In addition to direct regulations of various types pertinent to toxic wastes and CO2, indirect regulations often dictate firms’ management of some of nontoxic wastes as well. For example, firms’ nontoxic wastes are sometimes indirectly regulated in terms of the amounts of such waste materials that firms are allowed to bring to landfills and other waste processing facilities. Some nontoxic wastes have commercial value as well.
  • Various tests of heteroskedasticity and specification tests that we have done, respectively, show little heteroskedasticity and little specification errors.
  • We speculate that there are multiple channels through which downstream and upstream firms’ environmental policies affect downstream firms’ value added.

© 2016 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Hitoshi Hayami, Masao Nakamura and Kazushige Shimpo (June 30th 2016). Economic Performance, Greenhouse Gas Emissions, Environmental Management, and Supply Chains in India: A Comparison with Japan, Sustainable Supply Chain Management, Evelin Krmac, IntechOpen, DOI: 10.5772/62535. Available from:

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