Automatic Change versus Induced Policy Response in the Environmental Kuznets Curve: The Case of U.S. Water Pollution Irene Lai C.C. Yang Institute of Economics, Academia Sinica, Nankang, Taipei 115, Taiwan Department of Public Finance, National Chengchi University, Wenshan, Taipei 116, Taiwan October 2006

1. Introduction Kuznets (1955) Grossman and Krueger (1993) the “environmental Kuznets curve” (EKC)

The EKC hypothesis implies that economic growth may be a remedy to environmental problems since it will level off pollution and bring about environmental improvement eventually. Andreoni and Levinson (2001) provided a case for this possibility. They argued for increasing returns in pollution abatement technology (doubling the environmental efforts more than doubles the abatement of pollution) and showed that the scale effect alone is sufficient to generate the EKC. By contrast, Grossman and Krueger (1995) emphasized that the eventual decline in pollution as income rises is not automatic or inevitable; instead, they suggested: “the strongest link between income and pollution in fact is via an induced policy response” (p. 372).

In this paper we incorporate the two contrary views above into a model and allow the link between income and pollution to be through two channels: (i) “automatic change,” which includes the scale effect in abatement technology as emphasized by Andreoni and Levinson (2001), and (ii) “induced policy response,” which, following the suggestion of Grossman and Krueger (1995), is via a collective-decision process by which citizen demands for a cleaner environment drive environmental policy.

2. Model Our model is built on Andreoni and Levinson (2001, hereafter A&L), but with two main modifications. First, instead of being a constant, we allow a person’s willingness-to-pay for environmental improvement (wtp) to positively depend on her own income. As noted in the Introduction, the extant evidence shows that wtp is an increasing function of income. This dependence will play an important role in our analysis. Second, environmental effort to clean up pollution is assumed to be a private action in A&L. We replace the private action with the collective action. This replacement will facilitate us to study the link between income and pollution via an induced policy response. Pearce and Palmer (2001) documented the OECD data on pollution abatement and control expenditures. A large part of environmental effort is channeled through collective action (as public expenditures directly or private expenditures indirectly via regulation).

(1) where is consumption (a private good), P is pollution (a public bad), and is the marginal disutility of pollution with, where is a common function. Note that represents individual i’s willingness-to-pay for environmental improvement (wtp) since. Assumption 1. for all i’s, where. (2) Assumption 2. and.

3. Preliminary analysis (3) (4) with (4-1) (5)

Let (see Eq. (4-2)). The function has several properties:(i) because, (ii) and under Assumption 2, and (iii) (<0) if ( ), and if and only if. From (4), we obtain: (6) where is the inverse function of.

(7) whose sign is negative since under Assumption 1 and. Thus, given M, the preferred share of income devoted to pollution abatement and control is strictly decreasing with respect to individual income: the higher the, the lower the. Two opposing forces govern the sign of. A higher implies a higher. This indirect effect (via the term in (6)) leads to a higher. However, given M, a higher also means that the person bears a higher share of “tax burden” than others, even though she does not enjoy a higher quality of the environment. This direct effect (via the term in (6)) results in a lower. As long as Assumption 1 holds, the direct effect will dominate the indirect effect.

Kahn and Matsusaka (1997) and Kahn (2002) 4. Environmental policy (8) where m is the median income of the economy and According to (8), three factors drive the economy’s share of income devoted to pollution abatement and control (remember that ): (i) (i) Individual preferences ( ). Given, an increase in the aggregate or mean income of the economy will raise the median-income voter’s wtp and hence a higher.

(i) (ii) Abatement technology ( ). From the property of, the effect induced by preferences in (i) will be strengthened by increasing returns to abatement ( ) if, but it will be weakened if. (iii) Income inequality ( ). The income distributions of almost all economies are found skewed to the right and hence.. The ratio can be regarded as a metaphor of income inequality in the economy: the lower the ratio, the higher the income inequality. Eq. (8) tells us that the higher the income inequality in the economy, all else equal, the higher the share of the economy’s income will be devoted to pollution abatement.

(9) (9-3) (10) with (10-1) (10-2) If, (2) becomes: (11)

6. Quantitative evaluation of automatic change versus induced policy response Step 1. Specifying a value for (the median-income voter’s income elasticity of wtp). To estimate in (8), we let. Note that by this specification. The U.S. public’s income elasticity of willingness to pay for quality water is between 0.1 to 0.16 according to Jordan and Elnagheeb (1993), between 0.2 to 0.3 according to Carson et al. (1993), but it equals according to Carson and Mitchell (1993). Step 2. Choosing a value for (abatement technology). Hayes (1987) studied the scale economy of the U.S. water factories and found supportive evidence for increasing returns to scale, which are estimated to be between and

Step 3. Estimating a and. Step 4. Simulating the evolution of and. Step 5. Picking the right value for. Grossman and Krueger (1995) studied the EKC hypothesis for the U.S. river pollution, finding that the turning point incomes for various water quality indicators are around per capita GDP $7600 to $7900.

Scenario 1:,,,, turning point income=$7781, at the turning point; Scenario 2:,,,, turning point income=$7792, at the turning point; Scenario 3:,,,, turning point income=$7764, at the turning point; Scenario 4:,,,, turning point income=$7771, at the turning point.

Table 1. Data on per capita GDP (M), ratio of median to mean income (m/M), and share of income devoted to pollution abatement and control ( ) year M m/M year M m/M year M m/M year M m/M

Table 2. Sensitivity of varying values for m/M =0.2=0.959 m/M=0.72 m/M=0.75 =1.301 = =7779 = =1.205 = = = a= a= =1.305 a= = =7792 = =1.205 a= = =7771 = m/M=0.9 =1.323 a= = = =1.205 a= = =7760 =

Table 3. What if ? =0.1 =0.2 =0.3 =0.959 = = = = =37,124,080 = =1,017,069 = =31,8936 = =73,053 = =53,606,148 = =1,197,473 = = = =73,180 = =276,595,954 = =2,483,081 = = = =73,753 = a= a= a= a= m/M =0.72 m/M =0.75 m/M =0.9 Note: denotes the turning point income Note:

Figure 1-1 estimated against actual s m

Figure 1-2 estimated against actual s m

Figure 2-2 Automatic change versus induced policy response when and and

Figure 3-1

Figure 3-2

Figure 4-1

Figure 4-2