DE LOS CONTRATOS PARA LA ADQUISICION DE BIENES Y/O CONTRATACIÓN DE SERVICIOS

A nation's health is often measured by the value and growth of its gross domestic product

(GDP). Given this method, consider one (admittedly biased) way to improve GDP. A

lumber company can increase GDP by cutting down as many trees as possible and selling

them. An oil company can empty a supertanker of oil along a coastline requiring millions

of dollars in cleanup costs. Both results would add to GDP. However, increased GDP

says nothing about whether the nation or economy will be better off as a result of the

transaction. In the long run, logging without associated replanting or polluting

waterways is obviously detrimental to future economic growth; a nation with depleted or

damaged natural resources will be less able to sustain a viable economy. The current

bottom line is that any economic activity - be it for the good of society or not - increases

GDP.

The root of this problem is that economic success is measured by economic growth. And

for many years, the success of growth came largely at the expense of the environment. It

is because of disregard for the environment that economists have suggested "greening"

national accounts to capture environmental damage. This change requires some notion of

sustainability. Sustainability is defined by the World Commission on Environment and

Development as "meeting the needs of the present without compromising the ability of

future generations to meet their own needs" [Brundtland 87]. This finding implies that

economies need to be designed with long-term ecological concerns in mind. Such an

effort would reward prudent management of natural resources.

One such mechanism would be full cost pricing, introduced earlier. These "green taxes"

could be used to pay for environmental protection, or could replace existing taxes. But

such taxes could also be so high as to completely eliminate production of certain

commodities. An alternative would adjust gross domestic product by subtracting the

environmental costs of production, an idea furthered by Daly and Cobb [88] and others to

capture net national welfare. Their index of sustainable economic welfare (ISEW) shows

capita ISEW increased only 0.7% in the 1970s and decreased by 0.8 percent in the 1980s.

Such an indicator implies substantial environmental deterioration, and sheds light on a

completely different view of progress-- one that comes at great environmental cost.

Indicators such as these will be crucial to future progress in serving the needs of

environmental protection. For example, Hall and Kerr [92] produced an array of

environmental indicators for the 50 states.

A Green Price Indicator

Tables 3-6 and 3-7 of the previous chapter report average external costs per sector of

4%, but provide little indication of how such external costs would affect consumers and

producers. To examine these effects, existing indicators could be environmentally

adjusted. The external cost results of the previous chapter were incorporated into the

frameworks of the U.S. Consumer Price Index (CPI) and Producer Price Index (PPI), two

widely recognized economic indicators collected by the Bureau of Labor Statistics. Each

of these indices relies upon a "market basket" of goods and services that are purchased by

consumers and producers. One of the values used in the determination of the price index

values is the relative importance, or weighting, of purchases from individual sectors. We

add the air pollution external cost to each item in the market basket to get the full cost.

The result is a weighted average of the external costs generated by consumers and

producers.

Using this framework, the external cost values found in the previous chapter were

incorporated into the CPI and 2 versions of the PPI - crude materials and finished goods.

Table 4-1 shows a summary of the results for the CPI, using both the CPI-U and CPI-W

subindices representing urban and non-urban consumer purchasing patterns and

disaggregated into subcategories. The original relative importance values are shown in

the base columns, the "green" results found by incorporating external costs into the base

weightings, and the percentage increases of respective categories. The effect on either

index is about 3%, thus a full cost pricing system would increase consumer prices by 3%.

A detailed presentation of the results is shown in Appendix D.

Category

Base

CPI-U

Green

CPI-U

Percent

Increase

Base

CPI-W

Green

CPI-W

Percent

Increase

Total

100

103.20

3.20

100

103.35

3.35

Food and beverages

16.31

16.77

2.79

17.90

18.41

2.81

Housing

39.56

41.16

4.05

36.45

38.05

4.38

Apparel

4.94

5.09

2.95

5.30

5.46

2.93

Transportation

17.58

18.30

4.12

19.85

20.68

4.19

Medical care

5.61

5.67

1.00

4.59

4.64

0.98

Recreation

6.15

6.25

1.71

5.97

6.07

1.71

Education and

Communication

5.53

5.58

1.00

5.40

5.45

0.99

Other goods and

Services

4.32

4.38

1.41

4.54

4.61

1.41

Table 4-1: Summary of Results from Incorporating External Costs into the Consumer Price Index

[Note: totals may not add due to rounding]

We note that reductions resulting from implementing some sort of policy to reduce

external costs would have an effect on medical care costs. As medical costs decrease,

their external cost contribution would further decrease. However, it is possible that

reductions in medical care expenses would be offset by larger consumer purchases in

"dirty" categories, actually increasing damages.

A similar analysis was undertaken for the PPI for crude materials and finished goods.

The result is 9% for crude materials and 5% for finished goods, also reflecting the

increased costs to producers that would result from a full cost pricing system. Tables 4-2

and 4-3 show summaries of these findings, and Appendix D shows the detailed results.

Category

Base

PPI

Green

PPI

Percent

Increase

Total

100

108.940

8.94

Farm products

43.912

46.108

5.00

Processed foods and feeds

0.917

0.943

2.84

Hides, skins, leather, and

Related products

0.7

0.729

4.19

Fuels and related products

And power

36.173

40.989

13.31

Chemicals and allied

Products

0.402

0.434

8.07

Rubber and rubber

Products - crude rubber

0.01

0.011

5.87

Lumber and wood

Products

2.911

2.953

1.43

Pulp, paper, and allied

Products

1.161

1.255

8.07

Metals and metal products

10.349

11.423

10.44

Nonmetallic mineral

Products

3.465

4.089

18.00

Table 4-2: Summary of Results from Incorporating External Costs into the

Producer Price Index - Crude Materials

Category

Base

PPI

Green

PPI

Percent

Increase

Total

100

105.444

5.44

Farm products

1.501

1.568

4.45

Processed foods and feeds

24.253

24.998

3.07

Textile products and

Apparel

4.752

4.895

3.00

Hides, skins, leather, and

Related products

0.507

0.520

2.50

Fuels and related products

And power

13.575

16.784

23.64

Chemicals and allied

Products

5.426

5.545

2.19

Rubber and plastic

products

1.65

1.713

3.83

Lumber and wood

products

0.148

0.152

2.36

Pulp, paper, and allied

products

4.528

4.630

2.25

Metals and metal products

1.01

1.045

3.48

Machinery and equipment

13.68

13.957

2.02

Furniture and household

durables

5.934

6.067

2.24

Nonmetallic mineral

products

0.154

0.162

5.25

Transportation equipment

16.566

16.992

2.57

Miscellaneous products

6.317

6.417

1.58

Table 4-3: Summary of Results from Incorporating External Costs into the Producer Price

Index - Finished Goods

The results in Tables 4-1 through 4-3 show the disparity between the effects from

consumers and producers. Namely, the external cost to consumers would be only about

3%. However, producers would be affected by between 5 and 9 percent. The main

reason for this difference is made clear by looking at the category-specific percent

changes in the tables. Producers on average spend much more on fuels, electricity, and

extracted materials, which were shown in the previous chapter as having high external

costs.

As an analogue to the estimated external costs shown above, the price indices could

instead be adjusted downward to represent the damage associated with purchases, in a

way similar to Daly and Cobb's suggestion. Such a green CPI would be adjusted

downward by about 3%. This type of adjustment would be straightforward and quick to

implement, and the Bureau of Labor Statistics could periodically release such results.

Environmental Impacts of the American Consumer

Focusing on the consumer side, we can extract even more detail from our model linking

external costs and the structure of the CPI. Specifically, it is possible to step back from

the dollar-valued air pollution damages that have been the focus of this chapter so far,

and reconsider the range of impacts individually that would result from the purchase of a

$100 basket of consumer goods. Assuming that the CPI is really indicating the typical

spending outlets of each $100 of consumer spending, we can also determine the

environmental impacts of such spending. This result would also then dictate the

environmental footprint of the American consumer. Using the CPI model summarized

above, we can use the sector-by-sector air pollution impact data set (summarized in

Appendix A) to show the impacts of each of the major categories. The results of such a

method are shown in Table 4-4 for CPI-U.

Emissions (pounds)

Category

Base

CPI-U

CO

NO2

PM10

SO2

VOC

GWP

Total

100

0.728

0.690

0.085

0.930

0.192

268.595

Food and beverages

16.31

0.171

0.160

0.011

0.106

0.038

33.471

Housing

39.56

0.167

0.312

0.043

0.578

0.044

134.403

Apparel

4.944

0.033

0.031

0.003

0.045

0.013

11.670

Transportation

17.578

0.267

0.129

0.017

0.125

0.070

67.623

Medical care

5.614

0.017

0.012

0.002

0.016

0.005

4.452

Recreation

6.145

0.036

0.021

0.003

0.029

0.010

8.164

Education and

communication

5.528

0.018

0.012

0.004

0.015

0.005

3.880

Other goods and

services

4.321

0.018

0.014

0.002

0.016

0.005

4.932

Table 4-4: Summary of Environmental Impacts for every $100 of consumer purchases, based on

Consumer Price Index weightings

The total in Table 4-4 shows that every $100 of consumer spending causes the release of

0.7 pounds of CO and NO2, about 0.1 pounds of PM10, 0.9 pounds of SO2, 0.2 pounds

of VOC, and about 270 pounds of global warming potential (in carbon dioxide equivalent

releases). Table 4-5 shows the result of scaling the $100 basket effects up by the 1992

average annual U.S. household expenditures of $29,850 [BLS 92].

Emissions (pounds)

Category

CO

NO2

PM10

SO2

VOC

GWP

Total

217.319

205.961

25.228

277.473

57.362

80,175.601

Food and beverages

51.186

47.795

3.273

31.607

11.460

9,991.123

Housing

49.949

93.060

12.856

172.437

13.166

40,119.196

Apparel

9.728

9.158

0.939

13.317

4.028

3,483.601

Transportation

79.744

38.432

4.930

37.462

21.031

20,185.608

Medical care

5.092

3.567

0.514

4.668

1.522

1,328.867

Recreation

10.809

6.350

0.993

8.606

3.097

2,436.950

Education and

communication

5.441

3.538

1.259

4.460

1.431

1,158.129

Other goods and

services

5.369

4.061

0.465

4.917

1.626

1,472.126

Table 4-5: Summary of Environmental Impacts per household, 1992, based on Consumer Price

Index weightings

This result is the first to specifically link the total supply chain environmental impacts

with consumer purchases. It shows that the average American household was responsible

for over 80,000 pounds (40 tons) of carbon dioxide-equivalent releases, as well as 25 to

275 pounds of other conventional pollutants. Other metrics have previously shown per-

capita values found by allocating releases per person (or per household unit), but the

analysis above is a direct link between releases and the consumer purchases that cause

them. In addition, it is a "bottom up" versus "top down" estimate of the impacts of the

consumer. The result was built up from purchases as opposed to dividing by consumers.

As a comparison, we validate our results versus one simple metric for determining per-

household impacts. We assume 95 million households in the U.S. in 1992 [Census 96].

Using this number, we divide the EPA estimates of air pollutants from industrial activity

shown in Table 3-1 by 95 million to generate assumed per-household values. Table 4-6

compares them to our own estimates from Table 4-5.

Emission

Per-household

estimate

Table 4-5

estimate

Carbon Monoxide

0.25

0.1

Nitrogen Oxides

0.18

0.1

Particulate Matter (PM 10)

0.12

0.01

Sulfur Dioxide

0.21

0.13

Volatile Organic Compounds

0.12

0.03

Global Warming Potential

(in CO

2

equivalent)

47

36.5

Table 4-6: A comparison of generated estimates of household impacts versus generated per-

household estimates [in metric tons]

Although some of the values are similar, other differ by an order of magnitude. The

source of this discrepancy is fairly straightforward. Most of the differences can be

explained by non-consumer consumption activity, e.g. energy production, transportation

and construction. Only a portion of these sources are represented in the CPI, although all

of the emissions are represented in the EPA estimates. Finally, since mobile sources are

major contributors to CO, NOx, and VOC, the per-household estimates are affected.

But just generating such values pales in comparison to the importance of making relevant

corporate executives, politicians, and other decision makers aware of them. If CEOs

became aware of "greened" balance sheets, perhaps they would be more inclined to

authorize investments to improve environmental quality. In other words, ecological

indicators need to be used by those who can make a difference.

In document COORDINACIÓN ZONAL 7 DEL MINISTERIO DE RELACIONES EXTERIORES Y MOVILIDAD HUMANA (página 47-50)