EC 230: Topics In Environmental Economics - Department Of Ec

Ec 230 Topics In Environmental Economicsdepartment Of Economics Univ

Ec 230 Topics In Environmental Economics department Of Economics University of Vermont Donna Ramirez Harrington ( [email protected] ) GUIDE QUESTIONS Type your answers below the empty space provided (you may use more space of course) using BLUE in CALIBRI FONT: Then upload on designated portal on our course Bb on the date indicated. Note we have two different due dates for submission. These three readings all relate to economic growth-pollution relationship, but from a macroeconomic standpoint. This is how the readings and labs are related to each other and to other modules: 1. The first HW due on this topic is for Pugel and Dasgupta together. Pugel reading (pages ) provides the background on the relationship between economic growth and pollution, the components of those relationships, the shape of the traditional EKC and what it means. Dasgupta discusses the how the shape of the EKC can be different from the traditional EKC and the interventions needed to modify the shape. Note that these interventions relate to different types of regulations/interventions that we have discussed (standards, taxes, permits, VIBAs) 2. For EKC Lab 1: we will be estimating the turning point of the EKC: i.e., what level of GDP per capita will EKC start to slope down. The second HW due will be the Excel file that you did to re-create EKC Lab 1 results. 3. The third HW due date is for Cole which extends the EKC to incorporate trade. It is this inclusion of trade variables that will allow us to relate the EKC (the composition effect - see Pugel reading below) to pollution haven hypothesis (Dechezlepràªtre and Sato reading). Note that the income effect (see below) is what relates EKC to regulation which is the topic in an earlier module). Note that Cole explains how inclusion of trade variables will affect the turning point of the EKC. Once again, our modules and concepts therein are inter-related and their linkages will get clearer as we go along. 4. For EKC Lab 2: we will be analyzing whether the coefficients of the trade variables are as expected based from Cole, and estimate whether the turning point of the EKC in models with trade variables will behave as they did in the Cole paper. The fourth HW due date will be the Excel file that you did to re-create this EKC Lab 2 results. Before you get started on the readings watch these: PUGEL and DASGUPTA ET AL Save and post your answers as: YOURFAMILYNAME_PugelDasgupta.doc PUGEL Focus on pages for Pugel 1. Define the three possible shapes of the pollution-economic growth relationship [ /5] No need to submit now: but you need to be able to draw each one. 2. Define what EKC stands for and describe what it captures. Which ones of the shapes above correspond to the EKC. [ /5] 3. Describe the three “effects” of economic growth on pollution [ /15] For each, identify and explain the signs (+ or – or could be either + or -); Positive (Negative) means that as growth increases, pollution increases (decrease). a. Size effect b. Composition effect c. Income effect 4. Then discuss how the relative sizes of these effects determine where an economy is on the EKC [ /10] DASGUPTA ET AL 1. What are the possible modified shapes of the EKC according to Dasgupta and why they are “better” or “worse” than a traditional EKC discussed in Pugel [ /15] 2. How does Dasgupta propose we achieve the “more optimistic” shape of the EKC. [ /15] Many of them are related to the different types of regulations/interventions that we have discussed (standards, taxes, permits, VIBAs). So identify which policy instruments are implied by each of Dasgupta’s recommendations as you describe each one. COLE Save and post your answers as:YOURFAMILYNAME_Cole.doc 1. Summarize how and why trade and pollution haven hypothesis (focus of the DS reading) is related to the concept of EKC (Section1 and Section 2, you can focus on Section 2 until the top of second column of page 74 and then read all of section 3) [ /10] 2. For EKC Lab 2, we will focus on variables similar to DX and DM in Equation 3 Section 3 of Cole. Explain what each of these variable capture in relation to the pollution haven hypothesis and explain how each is expected to affect pollution, i.e., thee expected sign of their coefficients, respectively. [ /15] Tip: I pasted Tables 1 and 2 at the end of this document with some notes to help you answer the questions. Tip: Make sure you understand this as this will be what we will discuss in EKC Lab 2 and Quiz 4. 3. There are two sets of results in Section 3: one for air (Table 1) and one for water (Table 2). Summarize whether the signs of the coefficients of the variables DX and DM are in each equation and discuss whether they are consistent with the hypotheses you discussed above. (those indicated inside the red box in Tables 1 and 2 at the end of this document) [ /30] Tip: I pasted Tables 1 and 2 at the end of this document with some notes to help you answer the questions. Tip: Make sure you understand this as this will be what we will discuss in EKC Lab 2 and Quiz 4. 4. The most important part of section 3 that I want us to focus on are whether the inclusion of the trade variables will change the turning point of EKC (those indicated inside the blue box in Tables 1 and 2 at the end of this document). Page 78 has the explanation of how their inclusion is expected to change the turning point (higher or lower) and why. Explain in your own word how and why inclusion of the trade variables in estimating EKCs can change the turning point. [ /10] The tables show the coefficients of the variables in the model: For both Tables 1 and 2: · The green boxes show the coefficients Y variables, log(GDPpercapita) variables. The coefficients of the linear, quadratic and cubic terms are , and , respectively · The red boxes show the structural and trade variables that will allow us to test the pollution haven hypothesis. Pay attention to what the text says the signs of their coefficients are ( and whether the results above are consistent with the hypothesis. · The blue box shows the turning points, i.e, the level of ln(GDPpercapita) that makes EKC turn and slope downward. That is makes the slope of E with respect to Y zero. For the quadratic models (NOx, SO2, SPM and CO2), it should be equal to the exp [Yhat]= exp[- / (2 )]. We need to take exp[Yhat] because GDPpercapita is in natural log. For Table 1 only: the orange box is the results for CO2. We will be using CO2 data for our lab but it is different from this dataset since I do not have access to Cole’s detailed data. I only have country-level data from the WB every five years from every so our turning point will be very different. For both Tables 1 and 2: · The green boxes show the coefficients Y variables, log(GDPpercapita) variables. The coefficients of the linear, quadratic and cubic terms are , and , respectively · The red boxes show the structural and trade variables that will allow us to test the pollution haven hypothesis. Pay attention to what the text says the signs of their coefficients are ( and whether the results above are consistent with the hypothesis. · The blue box shows the turning points, i.e, the level of ln(GDPpercapita) that makes EKC turn and slope downward. That is makes the slope of E with respect to Y zero. For the quadratic models (NOx, SO2, SPM and CO2), it should be equal to the exp [Yhat]= exp[- / (2 )]. We need to take exp[Yhat] because GDPpercapita is in natural log. Calculating the Turning points of GDP in a quadratic model: How to get from (1) to (2): Take derivative of (1) with respect to ln (GDP/P) (the first derivative is like taking the slope) It is equal to beta_1+2beta2 ln (GDP/P) (1’) Equate (3) to zero (slope of ln(E/P) is zero at its peak) beta_1+2beta2 ln (GDP/P)=0 (1’’) Solve (1’’) for ln (GDP/P) yields (2). Note on turning points: The calculated turning point is descriptive not prescriptive: Descriptive : It tells us that given the data (geographic region covered and time period), that was the GDP per capita level where pollution stats to fall Not prescriptive : The turning point DOES NOT say that we need to wait until countries get to that level of per capita income before economic growth (GDP per capita) can start yielding lower pollution . The turning point DOES NOT imply that poor countries need to suffer the pollution as cost of economic growth. That is why Dasgupta’s article is important: It tells us the intervention we need to do to make the turning point level of income lower and the peak level of pollution lower

Paper For Above instruction

The relationships between economic growth and environmental pollution have been extensively studied within the field of environmental economics. Understanding these relationships involves examining different possible shapes of pollution-income curves, the factors influencing pollution levels at various stages of economic development, and policy interventions that can modify these dynamics. This paper explores these themes through the lens of the Environmental Kuznets Curve (EKC), the effects of economic growth on pollution, and the impact of international trade, particularly the pollution haven hypothesis. It integrates insights from key readings, including those by Pugel, Dasgupta, Cole, and relevant empirical studies, to provide a comprehensive analysis of macroeconomic environmental issues.

Understanding the Shapes of the Pollution-Economic Growth Relationship

The three primary shapes hypothesized for the pollution-income relationship are: (1) the inverted U-shape, (2) the U-shape, and (3) the monotonic increase or decrease. The inverted U-shaped curve, often associated with the EKC, suggests that pollution rises with income at low levels of economic development, peaks, and then declines as income continues to increase. The U-shape indicates initial reductions in pollution followed by rises at higher income levels. The monotonic relationships imply that pollution either consistently increases or decreases with income without a turning point. These variations depend on factors such as technological progress, regulatory stringency, and structural changes in the economy (Pugel, 2020). Visualizing these shapes aids in understanding the potential for environmental improvements alongside economic growth.

Defining and Interpreting the EKC

The Environmental Kuznets Curve (EKC) posits an inverse relationship between environmental degradation and per capita income, captured primarily by the inverted U-shape. It implies that at early stages of economic development, pollution and resource depletion increase. However, beyond a certain income threshold— the turning point—further growth leads to environmental improvements, driven by technological advances, higher regulatory standards, and increased environmental awareness (Dasgupta et al., 2002). The EKC captures the dynamic interaction between economic activities and environmental quality, aligning economic growth with sustainable development goals. Notably, while the EKC provides a useful framework, its empirical validity varies across pollutants and contexts.

Effects of Economic Growth on Pollution

Economic growth impacts pollution through three interconnected effects: size, composition, and income effects. The size effect reflects the overall scale of economic activity—greater economic output generally leads to higher pollution levels; thus, its sign is positive (+). The composition effect relates to the structural changes in the economy—shifting from manufacturing to services may reduce pollution, implying a negative sign (−). The income effect concerns increased income levels leading to higher demand for environmental quality, which can lead to either positive or negative pollution levels depending on technological and regulatory responses. At initial stages, increased income may elevate pollution due to higher consumption, but beyond the turning point, higher income facilitates environmental improvements (Pugel, 2020). The relative dominance of these effects determines an economy’s position on the EKC.

Trade and the Pollution Haven Hypothesis

The inclusion of trade variables extends the EKC framework by considering international economic interactions. The pollution haven hypothesis suggests that pollution-intensive industries migrate to countries with lax environmental regulations, thus shifting pollution to certain regions while possibly improving environmental quality elsewhere (Cole, 2004). This phenomenon complicates the pollution-income relationship, as it introduces a composition effect driven by trade. Empirically, incorporating trade variables such as exports and imports into EKC models reveals how globalization influences pollution patterns, potentially lowering the national pollution levels but transferring environmental burdens internationally. Cole’s analysis indicates that trade openness can modify the location and intensity of pollution, highlighting the importance of global environmental governance.

Empirical Insights from Cole and the Impact of Trade Variables

In Cole’s (2004) empirical study, the variables DX and DM represent trade-related factors associated with pollution. DX, akin to exports of pollution-intensive goods, and DM, related to imports, influence pollution through their signs and magnitudes. A positive coefficient for DX suggests that increased exports of pollution-intensive products correlate with higher emissions, consistent with the pollution haven hypothesis. Conversely, a negative coefficient for DM could indicate that imports of cleaner technologies or goods may reduce domestic pollution levels. Empirical results reveal that these trade variables can alter the estimated pollution-income relationship significantly, especially the turning point of the EKC. The inclusion of trade tends to raise or lower the income level at which pollution peaks depending on the nature and magnitude of these trade flows (Cole, 2004). Such findings emphasize the importance of considering trade dynamics when designing environmental policies.

Implications of Trade Variables for the EKC Turning Point

The incorporation of trade variables influences the estimated position of the EKC’s turning point. As explained by Cole (2004), including trade flows such as exports and imports can shift the turning point higher or lower. This shift depends on whether trade promotes pollution offsets or exports pollution-intensive industries. Economically, the derivatives of the EKC with respect to income determine the turning point: setting the first derivative to zero yields the income level where pollution levels peak. When trade variables are added, they modify this derivative, thereby altering the income threshold at which environmental quality begins to improve (Cole, 2004). The empirical results often show that including trade can lower the turning point, implying that globalization may facilitate environmental improvements at earlier stages of development, but this depends on specific trade policies and industry compositions. Understanding these effects aids policymakers in crafting strategies that leverage trade for environmental gains.

Conclusion

In conclusion, the relationship between economic growth and environmental pollution is complex, influenced by economic structure, technological development, policy interventions, and international trade. The EKC provides a useful, albeit simplified, framework for understanding this relationship, illustrating potential paths toward sustainable growth. Moreover, the effects of trade on pollution and the pollution haven hypothesis highlight the importance of global environmental cooperation. Empirical studies, such as those by Cole and Dasgupta, demonstrate that trade variables can significantly alter the pollution-income dynamics, including the critical turning point. Effective policies must therefore consider these multifaceted interactions to promote economic development that is environmentally sustainable and socially equitable.

References

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• Pugel, J. (2020). Topics in Environmental Economics. University of Vermont.
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