1. Final lecture Development issues Conservation vs development in a CBA framework The Kuznets curves paradigm Waste Prevention and policy Structural change and innovation: sectors and geography

2. Conservation vs development

3. Adapting CBA to uncertainty and irreversibility: the QUASI OPTION VALUE APPROACH

4. Krutilla, 1967

8. Simple example… A model was developed to cope with CBA under uncertainty and Irreversibility Arrow, K. J., and A. C. Fisher (1974) ‘Environmental preservation, uncertainty, and irreversibility.’ Quarterly Journal of Economics 88, 312–319 Conrad, J. M. (1980) ‘Quasi-option value and the expected value of information.’ Quarterly Journal of Economics 95, 813– 820 Dixit, A.K., and R.S. Pindyck (1994) Investment Under Uncertainty (Princeton University Press)

9. ‘to economists, the important question about irreversibility is this: what are the implications for resource allocation?’ (Fisher. A.C.)

10. V0 – NPV of preservation 0-10 years, Period 1 V0=10 V1 – NPV 10 + years, period 2 But we are uncertain α, V1= Vhigh = 400 1-α, V1= Vlow = 20 Say α=0.2

11. Expected value (V1)= α400 + (1-α)20 = 96 Value of preservation V0 + Expected value (V1)= 106

12. development D0 – value period 1 D1 value period 2 D0+D1 =40+80=120 With V0=10

13. Standard rule We develop if D0+D1 > V0+E(V1) Here 120>106

14. Arrow Fisher Rule But….the logic is flawed

15. D0D1 V0 D1 V1 Flexibility of conserving With Irreversibility V1 HIGH!

16. Arrow Fisher Rule V0 + αVhigh + (1-α)D1

17. 154-120: value of waiting/flexibility V0 + αVhigh + (1-α)D1 10+80+64=154!

18. Is conservation better? (with uncertainty and irreversibility) The value of waiting or quasi option value depends on D0 level Here D0 must be < 74 D1 vs Vl/Vh D0>V0 The interesting case is >0 but not excessive…. Vl < D1 < Vh Even D could be subject to uncertainty

19. Development in the long run. The environmental Kuznets curve hypothesis

20. The IPAT identity A simple but useful way to start thinking about what drives the sizes of the economy’s impacts on the environment. It can be formalised as the IPAT identity: (2.6) I: impact, measured as mass or volume P: population size A: per capita affluence, in currency units T: technology, amount of the resource used or waste generated per unit production

21. The IPAT identity Measure impact in terms of mass Use GDP for national income. Then T is resource or waste per unit GDP. Then for the resource extraction case, we have: (2.6) A T

22. Affluence and technology: the Environmental Kuznets Curve (EKC) World Development Report 1992, subtitled ‘Development and the environment’, noted that: ‘The view that greater economic activity inevitably hurts the environment is based on static assumptions about technology, tastes and environmental investments’.

23. The EKC hypothesis EKC – Environmental Kuznets Curve

24. Figure 2.8 Environmental impact and income e =  y (b) e (a) e y y e =  0 y -  1 y 2

25. Panayotou (1993) “At low levels of development both the quantity and intensity of environmental degradation is limited to the impacts of subsistence economic activity on the resource base and to limited quantities of biodegradable wastes. As economic development accelerates with the intensification of agriculture and other resource extraction and the takeoff of industrialisation, the rates of resource depletion begin to exceed the rates of resource regeneration, and waste generation increases in quantity and toxicity. At higher levels of development, structural change towards information-intensive industries and services, coupled with increased environmental awareness, enforcement of environmental regulations, better technology and higher environmental expenditures, result in levelling off and gradual decline of environmental degradation.”

26. The EKC hypothesis is shortly that for many environmental impacts, an inverted U-shaped relationships between per capita income and pollution is documented. The concentration of a certain pollutant first increases with income/production, reflecting a scale effect, more or less proportional, then eventually starts to decrease, de-linking from income even on an absolute basis. More specifically, the hypothesis predicts that the “environmental income elasticity” decreases monotonically with income, and that it eventually changes its sign from positive to negative, thus defining a turning point for the inverted U-shaped relationship. It does not derive from a theoretical model, it is an intuitive conceptual approach, inductive in nature..though some theoretical explanations have emerged…

27. EKC and delinking Delinking may occur on a relative basis (the elasticity of the environmental impact indicator with respect to an economic driver is positive, but less than unity) or on an absolute basis (negative elasticity). The assessment of both de-linking processes can be referred to the mostly applied research field concerning Environmental Kuznets Curves (EKC). The hypothesis derives from the original analysis of Kuznets on the relationship between income level and income distribution

28. EKC motivations Supply side Technology driven by economic growth (profits and investments..) The share of cleaner activities in GDP increases with the scale of the economy (scale + composition effects) As scarcity increases, market prices should reflect it..self-regulatory mechanism? Environmental policy more likely in a developed economy  economic and political conditions needed Property right enforcement (policy issue) Demand side Environmental quality is a normal luxury good (as culture)..higher incomes mean higher WTP for the environmental services..higher taxes are possible, new markets are profitable.. Preferences change as the society develops..the marginal value of consumption is positive but decreasing Environmental costs are increasing even steeply…growth benefits decreasing….even a simple marginal cost-benefit scheme may explain why delinking may occur

29. Policy relevance The EKC evidence may support the idea that no policy is needed…market forces and market dynamics are self- sufficient in inverting the income-environment link BUT the environmental impact may be higher than what is defined as sustainable…policy efforts are needed to support and correct markets..affecting the shape of the EKC

30. Empirical evidence, which has mainly concerned air emissions, is still ambiguous. Some pollutants show a turning point, though it shared view that some critical externalities, like CO2 and waste flows, are monotonically rising with income. At best, relative de-linking may be occurring (Stern, 2004).

31. Air quality indicators Local air quality (CO, sulfur, PM) seem to show an inverted U-shape with income. Global pollutants either rise monotonically with income or eventually present very high turning point (not reached if not by US) * private/public goods as far as countries are concerned..free riding on global commons  policy needed Water indicators The turning point is generally higher EKC for some indicators (local issues) N shape? (Borghesi, 1999)

32. waste Empirical evidence on Delinking concerning environmental waste indicators is probably the scarcest. Contributions providing results for waste are rare. Cole et al. (1997) find no evidence for an inverted U-shape EKC curve concerning municipal waste See the Mazzanti-Zoboli paper (2005) on waste and delinking…

33. There is currently no evidence concerning de-linking with respect to primary sources of waste in Europe (i.e. municipal and packaging waste), which have been targeted by waste- oriented European Directives aimed at reducing diverse environmental externalities associated to waste production and disposal

34. Empirical status of the EKC hypothesis If economic growth is generally good for the environment, then it would seem that there is no need to curtail growth in the world economy in order to protect the global environment. In recent years there have been a number of studies using econometric techniques to test the EKC hypothesis. Two key questions: 1.Are the data generally consistent with the EKC hypothesis? 2.If the EKC hypothesis holds, does the implication that growth is good for the global environment follow?

35. Some evidence Turning points 2003$/per capita (international studies) CO2: 37000-57000 CO16000 Nitrates25-41000 Nitrogen oxide25-29000 Sulfur dioxide10000 Sulfur dioxide (trans)12-13000 Suspended particulates12-13000

36. Lack of clean waterDecline uniformly with increasing income Lack of urban sanitationDecline uniformly with increasing income Ambient levels of suspended particulate matter in urban areas Conform to EKC Urban concentrations of sulphur dioxideConform to EKC Change in forest area between 1961 and 1986, Do not depend on income. Change in rate of deforestation between 1961 and 1986, Do not depend on income. Dissolved oxygen in riversRiver quality tends to worsen with increasing income Faecal coliforms in riversRiver quality tends to worsen with increasing income Municipal waste per capitaRise with income Carbon dioxide emissions per capitaRise with income

37. Evidence. Shafik and Bandyopadhyay summarise the implications of their results by stating: “It is possible to ‘grow out of’ some environmental problems, but there is nothing automatic about doing so. Action tends to be taken where there are generalised local costs and substantial private and social benefits. ”

39. Implications of the EKC Confirming an inverted U in per capita terms does not necessarily imply that future growth means lower environmental impact. Stern et al (1996) projected economic growth and population growth for every country with a population in excess of 1 million. They then used the relationship in Figure 2.10 to compute each country’s SO 2 emissions from 1990 to 2025, and added across countries – global emissions grew from 383 million tonnes in 1990 to 1181 million tonnes in 2025. Arrow et al (1995) concluded that ‘Economic growth is not a panacea for environmental quality.....policies that promote gross national product growth are not substitutes for environmental policy’

40. Carbon dioxide

41. We already tried to focus on specific homogeneous areas rather than OECD or full sample Source: Mazzanti, Musolesi and Zoboli, 2010, Applied Economics

42. EKC, CO2 diversity in long run trends, while most studies focus on average coefficient estimations (e.g. OECD)

43. Figure 3. EU-NORTH countries (scatter : real values. Line : robust locally weighted scatterplot smoothing) EU North

44. EU South

45. Structural breaks Environmental Policy shocks Oil shocks Those can be captured by the time related component of the income- environmental relationship.. Disentangle income and time effects… Further look at separated effects by country Back to the heterogeneity issue Mazzanti, M. & Musolesi, A., 2013. The heterogeneity of carbon Kuznets curves for advanced countries: comparing homogeneous, heterogeneous and shrinkage/Bayesian estimators. Applied Economics, 45, pp.3827–3842. Musolesi, A. & Mazzanti, M., 2014. Nonlinearity, heterogeneity and unobserved effects in the carbon dioxide emissions-economic development relation for advanced countries. Studies in Nonlinear Dynamics & Econometrics, 18(5), p.21.

46. EU south

47. North America and Oceania

48. EU North

49. Waste (prevention)

50. Scenarios: MSW generation and landfilling in the EU-27 Note: Figures from 1980-2004 are data from Eurostat. Figures from 2005-2020 are projections. BMW = biodegradable municipal waste. Source: EEA (2007).

51. Waste: not less important, and related to climate change   Moving away from landfilling

52. Landfilling, incineration and material recovery (EEA, 2009) EEA (2009), Diverting waste from landfill

53. Waste Management composition in EEA countries. Year 2009. Share of total disposal.

54. EU 27: MSW generated (Kg per capita) and major relevant policies

55. Waste generation growth rate between 1995/2009. EEA countries.

56. PoliciesInnovation Waste Performance Direct effect

57. Number of patent application filed at the EPO. Specific waste technologies, 3 year moving average. (1981=100). Material Recycling on the right axe.

58. D’Amato A., Mazzanti M. Montini A., 2013, Waste Management in Spatial Environments, Routledge, London.. Mazzanti M. Montini A., 2009, Waste & Environmental Policy, Routledge, London. Mazzanti M. Montini A. (2014), Clustering waste performances. Spatial and socio economic effects in the Italian environment, in Handbook of Waste Management (edited by Tom Kinnaman) Nicolli F. Mazzanti M. (2011), Diverting waste: the role of innovation, in OECD, Invention and transfer of environmental technologies, Paris: OECD.

59. Mazzanti M. Montini A. (2014), Clustering waste performances. Spatial and socio economic effects in the Italian environment, in Handbook of Waste Management (edited by Tom Kinnaman) Policy, geography, institutions matter…

68. Geography and sectors Composition of the economy, innovation and structural change

69. 69 V.Costantini, M.Mazzanti, A.Montini - Environmental Performance and Regional Innovation Spillovers Table 3–CO 2 and SO X emission intensity (kg x 1M€ of value added, increasing order) Region CO 2 Region SO X Trentino Alto Adige 136 Trentino Alto Adige 39 Campania 141 Valle d’Aosta 45 Valle d’Aosta 153 Abruzzo 69 Piedmonte 185 Campania 78 Lazio 204 Lombardy 99 Marche 206 Lazio 101 Lombardy 209 Marche 108 Abruzzo 258 Piedmonte 108 Veneto 267 Calabria 123 Emilia Romagna 270 Basilicata 224 Tuscany 278 Emilia Romagna 226 ITALY 301 Molise 276 Calabria 307 Veneto 300 Umbria 342 ITALY 315 Friuli Venezia Giulia 353 Tuscany 349 Basilicata 430 Umbria 373 Liguria 472 Friuli Venezia Giulia 539 Sicily 547 Puglia 859 Molise 689 Liguria 886 Sardinia 824 Sicily 1,347 Puglia 971 Sardinia 1,530 Can we say something on the divers?

70. Beyond income – within the EKC again… Environmental performances are driven by structural features (ECONOMIC SPECIALIZATION) Innovation (EFFICIENCY)

71. Brown vs Green economy… Manufacturing is heavier.. But more innovative…. Again the IPAT framework.. EU 20% (now 15%) non binding manufacturing target by 2020 (vs?) GHG Targets 2020-2030 Advanced services oriented economy risk: low innovation, low growth and wages…..(EEA, 2014)

72. Shift-Share: productive specialization (industry mix) component 72 V.Costantini, M.Mazzanti, A.Montini - Environmental Performance and Regional Innovation Spillovers Note: Below zero values indicate positive performances

73. Shift-Share: efficiency component 73 V.Costantini, M.Mazzanti, A.Montini - Environmental Performance and Regional Innovation Spillovers Note: Below zero values indicate positive performances

74. Innovation counter balances growth driven environmental effects Innovation is jointly occuring with structural change (recomposition of the economy + innovation diffusion + skill development) Innovative sectors are often the ‘heavy’ sectors (those subject to env policies) Innovation induced by energy saving actions (even without policy) Innovation induced by policies which bear more on heavy sectors