Political economy of pollution in China

Transcription

1 Political economy of pollution in China Jessica Leight Williams Department of Economics April 21, 2016

2 Introduction Over the last three decades, China has experienced phenomenal growth - but this growth has been largely driven by fossil fuels. Air pollution in China is now among the worst in the world; only 1% of Chinese urban residents breathe air that would be considered safe by the European Union. Water pollution, desertification, and loss of biodiversity are also major challenges.

3 Introduction Over the last three decades, China has experienced phenomenal growth - but this growth has been largely driven by fossil fuels. Air pollution in China is now among the worst in the world; only 1% of Chinese urban residents breathe air that would be considered safe by the European Union. Water pollution, desertification, and loss of biodiversity are also major challenges.

4 Introduction Over the last three decades, China has experienced phenomenal growth - but this growth has been largely driven by fossil fuels. Air pollution in China is now among the worst in the world; only 1% of Chinese urban residents breathe air that would be considered safe by the European Union. Water pollution, desertification, and loss of biodiversity are also major challenges.

5 Today s papers The first paper today will document the negative impact of this pollution on human health. The second paper evaluates how high levels of pollution may emerge from skewed promotion incentives faced by regional Chinese politician. But first, I will briefly summarize some of the environmental problems China faces.

6 Today s papers The first paper today will document the negative impact of this pollution on human health. The second paper evaluates how high levels of pollution may emerge from skewed promotion incentives faced by regional Chinese politician. But first, I will briefly summarize some of the environmental problems China faces.

7 Today s papers The first paper today will document the negative impact of this pollution on human health. The second paper evaluates how high levels of pollution may emerge from skewed promotion incentives faced by regional Chinese politician. But first, I will briefly summarize some of the environmental problems China faces.

8 Air pollution Urban air quality has improved due to reduction in (urban) household use of coal; while in rural areas, indoor air pollution due to use of unimproved stoves has remained high. As a result, respiratory disease is the leading cause of death in rural areas, and the third-leading cause in cities. Industrial use of coal has increased; on the positive side, sulfur dioxide emissions remained constant due to changes in the way coal is exploited. The biggest negative impact on air quality has come from the dramatic increase in trucks and automobiles, from 5.5 million in 1990 to 43 million in 2005.

9 Air pollution Urban air quality has improved due to reduction in (urban) household use of coal; while in rural areas, indoor air pollution due to use of unimproved stoves has remained high. As a result, respiratory disease is the leading cause of death in rural areas, and the third-leading cause in cities. Industrial use of coal has increased; on the positive side, sulfur dioxide emissions remained constant due to changes in the way coal is exploited. The biggest negative impact on air quality has come from the dramatic increase in trucks and automobiles, from 5.5 million in 1990 to 43 million in 2005.

10 Air pollution Urban air quality has improved due to reduction in (urban) household use of coal; while in rural areas, indoor air pollution due to use of unimproved stoves has remained high. As a result, respiratory disease is the leading cause of death in rural areas, and the third-leading cause in cities. Industrial use of coal has increased; on the positive side, sulfur dioxide emissions remained constant due to changes in the way coal is exploited. The biggest negative impact on air quality has come from the dramatic increase in trucks and automobiles, from 5.5 million in 1990 to 43 million in 2005.

11 Air pollution Urban air quality has improved due to reduction in (urban) household use of coal; while in rural areas, indoor air pollution due to use of unimproved stoves has remained high. As a result, respiratory disease is the leading cause of death in rural areas, and the third-leading cause in cities. Industrial use of coal has increased; on the positive side, sulfur dioxide emissions remained constant due to changes in the way coal is exploited. The biggest negative impact on air quality has come from the dramatic increase in trucks and automobiles, from 5.5 million in 1990 to 43 million in 2005.

12 Water pollution Water pollution in China is also a major problem for both urban and rural households. Industrial waste and agricultural runoff have led to severely polluted waterways. In northern China, the water in only a third of the river length meets the standard for direct human contact; in the Yellow River, a third of the water is literally toxic (unsafe for human contact, unsuitable for irrigation, and cannot be safely purified). Water shortages in the north compound the pollution problem.

13 Water pollution Water pollution in China is also a major problem for both urban and rural households. Industrial waste and agricultural runoff have led to severely polluted waterways. In northern China, the water in only a third of the river length meets the standard for direct human contact; in the Yellow River, a third of the water is literally toxic (unsafe for human contact, unsuitable for irrigation, and cannot be safely purified). Water shortages in the north compound the pollution problem.

14 Water pollution Water pollution in China is also a major problem for both urban and rural households. Industrial waste and agricultural runoff have led to severely polluted waterways. In northern China, the water in only a third of the river length meets the standard for direct human contact; in the Yellow River, a third of the water is literally toxic (unsafe for human contact, unsuitable for irrigation, and cannot be safely purified). Water shortages in the north compound the pollution problem.

15 Water pollution Water pollution in China is also a major problem for both urban and rural households. Industrial waste and agricultural runoff have led to severely polluted waterways. In northern China, the water in only a third of the river length meets the standard for direct human contact; in the Yellow River, a third of the water is literally toxic (unsafe for human contact, unsuitable for irrigation, and cannot be safely purified). Water shortages in the north compound the pollution problem.

16 Costs of pollution A World Bank study in 1997 estimated that total air and water pollution costs amounted to 8% of GDP, with the largest losses attributed to health losses associated with urban air pollution; health losses associated with indoor air pollution; chronic disease from water pollution; crop and forestry damage from acid rain; and nervous system damage and reduced intelligence among children exposed to high levels of lead. The same study estimated that 178,000 premature deaths could be avoided each year if China met its own class II air pollution standards.

17 Costs of pollution A World Bank study in 1997 estimated that total air and water pollution costs amounted to 8% of GDP, with the largest losses attributed to health losses associated with urban air pollution; health losses associated with indoor air pollution; chronic disease from water pollution; crop and forestry damage from acid rain; and nervous system damage and reduced intelligence among children exposed to high levels of lead. The same study estimated that 178,000 premature deaths could be avoided each year if China met its own class II air pollution standards.

18 Global warming China is the second-largest source of greenhouse gases (after the U.S.), and its carbon emissions are growing rapidly. Estimates suggest China will become the largest single contributor of carbon dioxide emissions between 2015 and While many contend that China s participation in the Kyoto Treaty is essential to control emissions, the Chinese government has argued that development should be the primary priority, and they will not restrict emissions during this period of growth. Moreover, even when Chinese carbon emissions match U.S. emissions in total, per-capita emissions will be only one-quarter of U.S. per-capita emissions.

19 Global warming China is the second-largest source of greenhouse gases (after the U.S.), and its carbon emissions are growing rapidly. Estimates suggest China will become the largest single contributor of carbon dioxide emissions between 2015 and While many contend that China s participation in the Kyoto Treaty is essential to control emissions, the Chinese government has argued that development should be the primary priority, and they will not restrict emissions during this period of growth. Moreover, even when Chinese carbon emissions match U.S. emissions in total, per-capita emissions will be only one-quarter of U.S. per-capita emissions.

20 Global warming China is the second-largest source of greenhouse gases (after the U.S.), and its carbon emissions are growing rapidly. Estimates suggest China will become the largest single contributor of carbon dioxide emissions between 2015 and While many contend that China s participation in the Kyoto Treaty is essential to control emissions, the Chinese government has argued that development should be the primary priority, and they will not restrict emissions during this period of growth. Moreover, even when Chinese carbon emissions match U.S. emissions in total, per-capita emissions will be only one-quarter of U.S. per-capita emissions.

21 Global warming China is the second-largest source of greenhouse gases (after the U.S.), and its carbon emissions are growing rapidly. Estimates suggest China will become the largest single contributor of carbon dioxide emissions between 2015 and While many contend that China s participation in the Kyoto Treaty is essential to control emissions, the Chinese government has argued that development should be the primary priority, and they will not restrict emissions during this period of growth. Moreover, even when Chinese carbon emissions match U.S. emissions in total, per-capita emissions will be only one-quarter of U.S. per-capita emissions.

22 Sustainability of land and water resources Rapid depletion of water resources has led to widespread land degradation; problems of desertification and erosion are particularly acute in northern China. Overgrazing in grasslands in the region has aggravated desertification. On the other hand, massive tree planting campaigns have increased forest cover (up from 8.9% in the first national survey in 1962 to 18.2% in ).

23 Sustainability of land and water resources Rapid depletion of water resources has led to widespread land degradation; problems of desertification and erosion are particularly acute in northern China. Overgrazing in grasslands in the region has aggravated desertification. On the other hand, massive tree planting campaigns have increased forest cover (up from 8.9% in the first national survey in 1962 to 18.2% in ).

24 Sustainability of land and water resources Rapid depletion of water resources has led to widespread land degradation; problems of desertification and erosion are particularly acute in northern China. Overgrazing in grasslands in the region has aggravated desertification. On the other hand, massive tree planting campaigns have increased forest cover (up from 8.9% in the first national survey in 1962 to 18.2% in ).

25 Water availability Overexploitation of ground water is a serious challenge in northern China; the water table under Beijing, for example, fell from 5 meters underground in 1950 to 50 meters underground in Private entrepreneurs exacerbate the problem by digging deep wills and selling the water - increasing the threat to long-run sustainability. Cities have also been extracting increasing amounts of water, leading to major subsidence (sinking) in Shanghai and Tianjin. One initiative planned to address these challenges is to pump southern water northward to alleviate stress in the North China basin; ultimately, however, this may be less important than increasing the efficiency of water use, improving water delivery systems, and enhancing incentives for conservation.

26 Water availability Overexploitation of ground water is a serious challenge in northern China; the water table under Beijing, for example, fell from 5 meters underground in 1950 to 50 meters underground in Private entrepreneurs exacerbate the problem by digging deep wills and selling the water - increasing the threat to long-run sustainability. Cities have also been extracting increasing amounts of water, leading to major subsidence (sinking) in Shanghai and Tianjin. One initiative planned to address these challenges is to pump southern water northward to alleviate stress in the North China basin; ultimately, however, this may be less important than increasing the efficiency of water use, improving water delivery systems, and enhancing incentives for conservation.

27 Water availability Overexploitation of ground water is a serious challenge in northern China; the water table under Beijing, for example, fell from 5 meters underground in 1950 to 50 meters underground in Private entrepreneurs exacerbate the problem by digging deep wills and selling the water - increasing the threat to long-run sustainability. Cities have also been extracting increasing amounts of water, leading to major subsidence (sinking) in Shanghai and Tianjin. One initiative planned to address these challenges is to pump southern water northward to alleviate stress in the North China basin; ultimately, however, this may be less important than increasing the efficiency of water use, improving water delivery systems, and enhancing incentives for conservation.

28 Water availability Overexploitation of ground water is a serious challenge in northern China; the water table under Beijing, for example, fell from 5 meters underground in 1950 to 50 meters underground in Private entrepreneurs exacerbate the problem by digging deep wills and selling the water - increasing the threat to long-run sustainability. Cities have also been extracting increasing amounts of water, leading to major subsidence (sinking) in Shanghai and Tianjin. One initiative planned to address these challenges is to pump southern water northward to alleviate stress in the North China basin; ultimately, however, this may be less important than increasing the efficiency of water use, improving water delivery systems, and enhancing incentives for conservation.

29 Water transfer: Update Three routes were planned to transfer water from south to north: eastern, central, and western. To date, $60 billion has been spent! Water began flowing in the central leg in October 2014; the western leg, the most challenging and expensive, has yet to come on line. This has already raised fears about drought in the center-south region of China.

30 Water transfer: Update Three routes were planned to transfer water from south to north: eastern, central, and western. To date, $60 billion has been spent! Water began flowing in the central leg in October 2014; the western leg, the most challenging and expensive, has yet to come on line. This has already raised fears about drought in the center-south region of China.

31 Water transfer: Update Three routes were planned to transfer water from south to north: eastern, central, and western. To date, $60 billion has been spent! Water began flowing in the central leg in October 2014; the western leg, the most challenging and expensive, has yet to come on line. This has already raised fears about drought in the center-south region of China.

32 Water transfer: Update Three routes were planned to transfer water from south to north: eastern, central, and western. To date, $60 billion has been spent! Water began flowing in the central leg in October 2014; the western leg, the most challenging and expensive, has yet to come on line. This has already raised fears about drought in the center-south region of China.

33 Greenstone, Impact of air pollution on life expectancy Based on biological evidence, it s clear that air pollution is negative for life expectancy; however, it s challenging to estimate this relationship directly in the data. Why? Where is pollution likely to be higher? This article nicely exploits an unusual feature of China s institutional history to estimate the impact of air pollution on life expectancy.

34 Greenstone, Impact of air pollution on life expectancy Based on biological evidence, it s clear that air pollution is negative for life expectancy; however, it s challenging to estimate this relationship directly in the data. Why? Where is pollution likely to be higher? This article nicely exploits an unusual feature of China s institutional history to estimate the impact of air pollution on life expectancy.

35 Greenstone, Impact of air pollution on life expectancy Based on biological evidence, it s clear that air pollution is negative for life expectancy; however, it s challenging to estimate this relationship directly in the data. Why? Where is pollution likely to be higher? This article nicely exploits an unusual feature of China s institutional history to estimate the impact of air pollution on life expectancy.

36 Heat north and south of the Huai river During the period of central planning, the Chinese government established free winter heating for homes and workplaces as a right - coal was provided for boilers free of cost. However, this right was limited to areas in northern China, defined by two geographic boundaries: the Huai river and the Qinling mountain range. These boiler systems last many years: even today, central heating is more common north of this line.

37 Heat north and south of the Huai river During the period of central planning, the Chinese government established free winter heating for homes and workplaces as a right - coal was provided for boilers free of cost. However, this right was limited to areas in northern China, defined by two geographic boundaries: the Huai river and the Qinling mountain range. These boiler systems last many years: even today, central heating is more common north of this line.

38 Heat north and south of the Huai river During the period of central planning, the Chinese government established free winter heating for homes and workplaces as a right - coal was provided for boilers free of cost. However, this right was limited to areas in northern China, defined by two geographic boundaries: the Huai river and the Qinling mountain range. These boiler systems last many years: even today, central heating is more common north of this line.

39 Heat and human health The potential negative impact of this policy was not lost on even Chinese observers. Premier Zhu Rongji, who worked in Shanghai most of his career before his promotion to the central government in Beijing, reportedly quipped: If I work in your Beijing, I would shorten my life at least five years. To quantify the impact of this policy, Greenstone and colleagues use a regression discontinuity strategy.

40 Heat and human health The potential negative impact of this policy was not lost on even Chinese observers. Premier Zhu Rongji, who worked in Shanghai most of his career before his promotion to the central government in Beijing, reportedly quipped: If I work in your Beijing, I would shorten my life at least five years. To quantify the impact of this policy, Greenstone and colleagues use a regression discontinuity strategy.

41 Heat and human health The potential negative impact of this policy was not lost on even Chinese observers. Premier Zhu Rongji, who worked in Shanghai most of his career before his promotion to the central government in Beijing, reportedly quipped: If I work in your Beijing, I would shorten my life at least five years. To quantify the impact of this policy, Greenstone and colleagues use a regression discontinuity strategy.

42 Introduction to regression discontinuity Let s consider an example close to the heart of students: the legal drinking age in the U.S. is 21 years. Imagine (a stretch, I know) that this limit was perfectly enforced. If you had a population of young people nearing their 21st birthday, no one would be drinking the day before their birthday; the day after, some proportion of the population would be consuming alcohol. If you were interested in estimating the impact of alcohol on car accidents, you could compare the frequency of accidents among individuals one day after their 21st birthday to the frequency among individuals one day before their 21st birthday.

43 Introduction to regression discontinuity Let s consider an example close to the heart of students: the legal drinking age in the U.S. is 21 years. Imagine (a stretch, I know) that this limit was perfectly enforced. If you had a population of young people nearing their 21st birthday, no one would be drinking the day before their birthday; the day after, some proportion of the population would be consuming alcohol. If you were interested in estimating the impact of alcohol on car accidents, you could compare the frequency of accidents among individuals one day after their 21st birthday to the frequency among individuals one day before their 21st birthday.

44 Introduction to regression discontinuity Let s consider an example close to the heart of students: the legal drinking age in the U.S. is 21 years. Imagine (a stretch, I know) that this limit was perfectly enforced. If you had a population of young people nearing their 21st birthday, no one would be drinking the day before their birthday; the day after, some proportion of the population would be consuming alcohol. If you were interested in estimating the impact of alcohol on car accidents, you could compare the frequency of accidents among individuals one day after their 21st birthday to the frequency among individuals one day before their 21st birthday.

45 Introduction to regression discontinuity Let s consider an example close to the heart of students: the legal drinking age in the U.S. is 21 years. Imagine (a stretch, I know) that this limit was perfectly enforced. If you had a population of young people nearing their 21st birthday, no one would be drinking the day before their birthday; the day after, some proportion of the population would be consuming alcohol. If you were interested in estimating the impact of alcohol on car accidents, you could compare the frequency of accidents among individuals one day after their 21st birthday to the frequency among individuals one day before their 21st birthday.

46 An intuitive example, continued Why does this make sense? Are there significant differences between people one day after their 21st birthday and one day before that birthday, other than their legal drinking status? Unlikely; if we do observe a difference in accident rates between people slightly younger than 21 and people slightly older than 21, it seems reasonable to attribute this to the impact of alcohol. This is the intuition of regression discontinuity design.

47 An intuitive example, continued Why does this make sense? Are there significant differences between people one day after their 21st birthday and one day before that birthday, other than their legal drinking status? Unlikely; if we do observe a difference in accident rates between people slightly younger than 21 and people slightly older than 21, it seems reasonable to attribute this to the impact of alcohol. This is the intuition of regression discontinuity design.

48 An intuitive example, continued Why does this make sense? Are there significant differences between people one day after their 21st birthday and one day before that birthday, other than their legal drinking status? Unlikely; if we do observe a difference in accident rates between people slightly younger than 21 and people slightly older than 21, it seems reasonable to attribute this to the impact of alcohol. This is the intuition of regression discontinuity design.

49 An intuitive example, continued Why does this make sense? Are there significant differences between people one day after their 21st birthday and one day before that birthday, other than their legal drinking status? Unlikely; if we do observe a difference in accident rates between people slightly younger than 21 and people slightly older than 21, it seems reasonable to attribute this to the impact of alcohol. This is the intuition of regression discontinuity design.

50 Notational framework Assignment to the treatment is going to be determined fully or partially by the value of a predictor (the covariate X i ); in the preceding example, this was age. D i denotes treatment status. { 1 if X i X 0 D i = 0 if X i < X 0 The crucial point is that X 0 is a threshold; no matter how close X i gets to the threshold, treatment status does not change until it has crossed the threshold.

51 Notational framework Assignment to the treatment is going to be determined fully or partially by the value of a predictor (the covariate X i ); in the preceding example, this was age. D i denotes treatment status. { 1 if X i X 0 D i = 0 if X i < X 0 The crucial point is that X 0 is a threshold; no matter how close X i gets to the threshold, treatment status does not change until it has crossed the threshold.

52 Notational framework Assignment to the treatment is going to be determined fully or partially by the value of a predictor (the covariate X i ); in the preceding example, this was age. D i denotes treatment status. { 1 if X i X 0 D i = 0 if X i < X 0 The crucial point is that X 0 is a threshold; no matter how close X i gets to the threshold, treatment status does not change until it has crossed the threshold.

53 Simple model Suppose that potential outcomes can be described by this simple model: Y is linear in X, and the effect of treatment is constant. E[Y 0i X i ] = α + βx i Y 1i = Y 0i + ρ This leads to a simple regression equation: Y i = α + βx i + ρd i + ɛ i

54 Simple model Suppose that potential outcomes can be described by this simple model: Y is linear in X, and the effect of treatment is constant. E[Y 0i X i ] = α + βx i Y 1i = Y 0i + ρ This leads to a simple regression equation: Y i = α + βx i + ρd i + ɛ i

55 Simple model, Part II RD captures causal effects by distinguishing the nonlinear and discontinuous function, 1(X i X 0 ), from the smooth function x i. If the trend relationship is nonlinear, i.e. E[Y 0i X i ] = f (X i ), then we can construct RD estimates by fitting the following equation: Y i = f (X i ) + ρd i + ɛ i

56 Simple model, Part II RD captures causal effects by distinguishing the nonlinear and discontinuous function, 1(X i X 0 ), from the smooth function x i. If the trend relationship is nonlinear, i.e. E[Y 0i X i ] = f (X i ), then we can construct RD estimates by fitting the following equation: Y i = f (X i ) + ρd i + ɛ i

57 Identifying assumption 1 The first identifying assumption is that conditional on X i, D i is uncorrelated with Y 1i and Y 0i (potential outcomes with and without treatment). In the sharp RD case, this is true by assumption: Xi fully determines D i, thus there is no residual variation in D i after conditioning on X i. Given your age, there is no variation in whether or not you are legally 21; you are or are not! This assumption could be violated if individuals can manipulate their status vis-a-vis their threshold: i.e., if some individuals misrepresent their age in order to drink. In that case, Xi (true age) does not fully determine D i (legal drinking status), because some individuals are cheating.

58 Identifying assumption 1 The first identifying assumption is that conditional on X i, D i is uncorrelated with Y 1i and Y 0i (potential outcomes with and without treatment). In the sharp RD case, this is true by assumption: Xi fully determines D i, thus there is no residual variation in D i after conditioning on X i. Given your age, there is no variation in whether or not you are legally 21; you are or are not! This assumption could be violated if individuals can manipulate their status vis-a-vis their threshold: i.e., if some individuals misrepresent their age in order to drink. In that case, Xi (true age) does not fully determine D i (legal drinking status), because some individuals are cheating.

59 Identifying assumption 1 The first identifying assumption is that conditional on X i, D i is uncorrelated with Y 1i and Y 0i (potential outcomes with and without treatment). In the sharp RD case, this is true by assumption: Xi fully determines D i, thus there is no residual variation in D i after conditioning on X i. Given your age, there is no variation in whether or not you are legally 21; you are or are not! This assumption could be violated if individuals can manipulate their status vis-a-vis their threshold: i.e., if some individuals misrepresent their age in order to drink. In that case, Xi (true age) does not fully determine D i (legal drinking status), because some individuals are cheating.

60 Identifying assumption 1 The first identifying assumption is that conditional on X i, D i is uncorrelated with Y 1i and Y 0i (potential outcomes with and without treatment). In the sharp RD case, this is true by assumption: Xi fully determines D i, thus there is no residual variation in D i after conditioning on X i. Given your age, there is no variation in whether or not you are legally 21; you are or are not! This assumption could be violated if individuals can manipulate their status vis-a-vis their threshold: i.e., if some individuals misrepresent their age in order to drink. In that case, Xi (true age) does not fully determine D i (legal drinking status), because some individuals are cheating.

61 Identifying assumption 1 The first identifying assumption is that conditional on X i, D i is uncorrelated with Y 1i and Y 0i (potential outcomes with and without treatment). In the sharp RD case, this is true by assumption: Xi fully determines D i, thus there is no residual variation in D i after conditioning on X i. Given your age, there is no variation in whether or not you are legally 21; you are or are not! This assumption could be violated if individuals can manipulate their status vis-a-vis their threshold: i.e., if some individuals misrepresent their age in order to drink. In that case, Xi (true age) does not fully determine D i (legal drinking status), because some individuals are cheating.

62 Identifying assumption 2 The second identifying assumption is that the functions E[Y 1i X i ] and E[Y 0i X i ] are continuous at the threshold X 0. Intuitively? Y i may change with X i. In our example, the number of accidents generally declines with age, both for drinkers and not-drinkers. Key assumption: the probability of an accident for a drinker does not jump discontinuously at the 21st birthday, and neither does the probability of an accident for a non-drinker.

63 Identifying assumption 2 The second identifying assumption is that the functions E[Y 1i X i ] and E[Y 0i X i ] are continuous at the threshold X 0. Intuitively? Y i may change with X i. In our example, the number of accidents generally declines with age, both for drinkers and not-drinkers. Key assumption: the probability of an accident for a drinker does not jump discontinuously at the 21st birthday, and neither does the probability of an accident for a non-drinker.

64 Identifying assumption 2 The second identifying assumption is that the functions E[Y 1i X i ] and E[Y 0i X i ] are continuous at the threshold X 0. Intuitively? Y i may change with X i. In our example, the number of accidents generally declines with age, both for drinkers and not-drinkers. Key assumption: the probability of an accident for a drinker does not jump discontinuously at the 21st birthday, and neither does the probability of an accident for a non-drinker.

65 Identifying assumption 2 The second identifying assumption is that the functions E[Y 1i X i ] and E[Y 0i X i ] are continuous at the threshold X 0. Intuitively? Y i may change with X i. In our example, the number of accidents generally declines with age, both for drinkers and not-drinkers. Key assumption: the probability of an accident for a drinker does not jump discontinuously at the 21st birthday, and neither does the probability of an accident for a non-drinker.

66 When, and why, is regression discontinuity useful? Regression discontinuity is useful when an outcome of interest changes discretely at a specified threshold. In addition to the previous example, consider test score thresholds for admission; eligibility for government programs defined by age; physical boundaries of towns defining eligibility for schools; etc.

67 When, and why, is regression discontinuity useful? Regression discontinuity is useful when an outcome of interest changes discretely at a specified threshold. In addition to the previous example, consider test score thresholds for admission; eligibility for government programs defined by age; physical boundaries of towns defining eligibility for schools; etc.

68 Quasi-random assignment around the threshold If the assumptions of an RD design are satisfied, then essentially you have a RCT around the threshold: all those close to the threshold (e.g., all those close to the age of 21) are similar in unobservable and observable characteristics; it is a matter of chance (quasi-random) that some pass their 21st birthday a few days earlier. As econometricians, we can then exploit this quasi-randomness of assignment relative to the threshold.

69 Quasi-random assignment around the threshold If the assumptions of an RD design are satisfied, then essentially you have a RCT around the threshold: all those close to the threshold (e.g., all those close to the age of 21) are similar in unobservable and observable characteristics; it is a matter of chance (quasi-random) that some pass their 21st birthday a few days earlier. As econometricians, we can then exploit this quasi-randomness of assignment relative to the threshold.

70 Identification strategy The identification strategy is relatively simple: the authors exploit a regression discontinuity, regressing pollution and life expectancy on a dummy for being north of the line, along with a flexible control for distance from the line. TSP j = α 0 + α 1 N j + α 2 f (L i ) + X i κ + ν j Y j = δ 0 + δ 1 N j + δ 2 f (L i ) + X i φ + µ j Why should this control variable be included? TSP is total suspended particulates; it s a commonly used measure of ambient air quality.

71 Identification strategy The identification strategy is relatively simple: the authors exploit a regression discontinuity, regressing pollution and life expectancy on a dummy for being north of the line, along with a flexible control for distance from the line. TSP j = α 0 + α 1 N j + α 2 f (L i ) + X i κ + ν j Y j = δ 0 + δ 1 N j + δ 2 f (L i ) + X i φ + µ j Why should this control variable be included? TSP is total suspended particulates; it s a commonly used measure of ambient air quality.

72 Identification strategy The identification strategy is relatively simple: the authors exploit a regression discontinuity, regressing pollution and life expectancy on a dummy for being north of the line, along with a flexible control for distance from the line. TSP j = α 0 + α 1 N j + α 2 f (L i ) + X i κ + ν j Y j = δ 0 + δ 1 N j + δ 2 f (L i ) + X i φ + µ j Why should this control variable be included? TSP is total suspended particulates; it s a commonly used measure of ambient air quality.

73 Two-stage least squares The authors also estimate a 2SLS specification, regressing life expectancy on TSP where TSP is instrumented by a dummy for north. What is the identification strategy needed for this specification? The results are most striking when presented graphically, though regressions are also useful.

74 Two-stage least squares The authors also estimate a 2SLS specification, regressing life expectancy on TSP where TSP is instrumented by a dummy for north. What is the identification strategy needed for this specification? The results are most striking when presented graphically, though regressions are also useful.

75 Two-stage least squares The authors also estimate a 2SLS specification, regressing life expectancy on TSP where TSP is instrumented by a dummy for north. What is the identification strategy needed for this specification? The results are most striking when presented graphically, though regressions are also useful.

76 Visualizing the RD

77 Regression discontinuity results: TSP

78 Regression discontinuity results: Life expectancy

79 Regression discontinuity results: Predicted life expectancy

80 Ordinary Least Squares

81 Regression discontinuity results: Tables

82 Interpreting the results First, the authors compare the 2SLS results to OLS results that I did not present; they find that the 2SLS results are significantly more negative than the OLS estimates, consistent with the intuition that pollution is positively correlated with other covariates (e.g., income) that increase life expectancy. They find that TSP concentrations are 55% higher in the north, leading to life expectancies that are 5 years shorter. The population in northern China between 1990 and 2000 is over 500 million; this implies around 2.5 billion life-years lost. The authors suggest these high levels of pollution might be one reason that rapid economic growth in China has not led to comparably rapid growth in life expectancy.

83 Interpreting the results First, the authors compare the 2SLS results to OLS results that I did not present; they find that the 2SLS results are significantly more negative than the OLS estimates, consistent with the intuition that pollution is positively correlated with other covariates (e.g., income) that increase life expectancy. They find that TSP concentrations are 55% higher in the north, leading to life expectancies that are 5 years shorter. The population in northern China between 1990 and 2000 is over 500 million; this implies around 2.5 billion life-years lost. The authors suggest these high levels of pollution might be one reason that rapid economic growth in China has not led to comparably rapid growth in life expectancy.

84 Interpreting the results First, the authors compare the 2SLS results to OLS results that I did not present; they find that the 2SLS results are significantly more negative than the OLS estimates, consistent with the intuition that pollution is positively correlated with other covariates (e.g., income) that increase life expectancy. They find that TSP concentrations are 55% higher in the north, leading to life expectancies that are 5 years shorter. The population in northern China between 1990 and 2000 is over 500 million; this implies around 2.5 billion life-years lost. The authors suggest these high levels of pollution might be one reason that rapid economic growth in China has not led to comparably rapid growth in life expectancy.

85 Interpreting the results First, the authors compare the 2SLS results to OLS results that I did not present; they find that the 2SLS results are significantly more negative than the OLS estimates, consistent with the intuition that pollution is positively correlated with other covariates (e.g., income) that increase life expectancy. They find that TSP concentrations are 55% higher in the north, leading to life expectancies that are 5 years shorter. The population in northern China between 1990 and 2000 is over 500 million; this implies around 2.5 billion life-years lost. The authors suggest these high levels of pollution might be one reason that rapid economic growth in China has not led to comparably rapid growth in life expectancy.

86 Discussion questions It s hard to argue that central heating is all bad; what are the policy implications of the results? What should the Chinese government change? How does this dilemma compare to similar environmental challenges faced by the U.S. in earlier stages of its history? How did the U.S. confront those challenges?

87 Discussion questions It s hard to argue that central heating is all bad; what are the policy implications of the results? What should the Chinese government change? How does this dilemma compare to similar environmental challenges faced by the U.S. in earlier stages of its history? How did the U.S. confront those challenges?

88 Jia, Pollution for promotion This paper seeks to understand the political economy underlying high levels of pollution in China: what incentives do politicians face to rein in pollution, or to allow it to increase? Jia seeks to identify a quasi-exogenous source of varying incentives for promotion for provincial governments, exploiting the varying pattern of connections between those governors and officials on central governing bodies. She finds that incentives for promotion seem to have a significant impact on increasing politician - suggesting that part of the fault for China s deteriorating environment conditions may be found in its political system.

89 Jia, Pollution for promotion This paper seeks to understand the political economy underlying high levels of pollution in China: what incentives do politicians face to rein in pollution, or to allow it to increase? Jia seeks to identify a quasi-exogenous source of varying incentives for promotion for provincial governments, exploiting the varying pattern of connections between those governors and officials on central governing bodies. She finds that incentives for promotion seem to have a significant impact on increasing politician - suggesting that part of the fault for China s deteriorating environment conditions may be found in its political system.

90 Jia, Pollution for promotion This paper seeks to understand the political economy underlying high levels of pollution in China: what incentives do politicians face to rein in pollution, or to allow it to increase? Jia seeks to identify a quasi-exogenous source of varying incentives for promotion for provincial governments, exploiting the varying pattern of connections between those governors and officials on central governing bodies. She finds that incentives for promotion seem to have a significant impact on increasing politician - suggesting that part of the fault for China s deteriorating environment conditions may be found in its political system.

91 Measurement of pollution Jia uses several different measures of pollution at the province-year level: chemical oxygen demand (COD) in industrial waste water, and industrial sulfur dioxide emissions (SO 2 ); both are known to be detrimental to health and land productivity. She also uses measures of water quality in provincial rivers, and industrial and non-industrial provincial GDP.

92 Measurement of pollution Jia uses several different measures of pollution at the province-year level: chemical oxygen demand (COD) in industrial waste water, and industrial sulfur dioxide emissions (SO 2 ); both are known to be detrimental to health and land productivity. She also uses measures of water quality in provincial rivers, and industrial and non-industrial provincial GDP.

93 Connections of provincial governors The connection dummy captures relationships between provincial governors and members of the Politburo Standing Committee (PSC), the highest governing body in China. Thus for governor j of province i in year t, C ijt = I (C ij PSC jt > 0), where C ij is a dummy for individuals i and j previously being colleagues, and PSC jt is a dummy for official j being a member of the PSC. Note that the connection dummy varies across provinces and governors, but also for the same governor over time (if someone he was previously connected to, joins the PSC).

94 Connections of provincial governors The connection dummy captures relationships between provincial governors and members of the Politburo Standing Committee (PSC), the highest governing body in China. Thus for governor j of province i in year t, C ijt = I (C ij PSC jt > 0), where C ij is a dummy for individuals i and j previously being colleagues, and PSC jt is a dummy for official j being a member of the PSC. Note that the connection dummy varies across provinces and governors, but also for the same governor over time (if someone he was previously connected to, joins the PSC).

95 Connections of provincial governors The connection dummy captures relationships between provincial governors and members of the Politburo Standing Committee (PSC), the highest governing body in China. Thus for governor j of province i in year t, C ijt = I (C ij PSC jt > 0), where C ij is a dummy for individuals i and j previously being colleagues, and PSC jt is a dummy for official j being a member of the PSC. Note that the connection dummy varies across provinces and governors, but also for the same governor over time (if someone he was previously connected to, joins the PSC).

96 Graphical demonstration of political connections

97 Discussion questions What identification assumption is required for this specification to generate an unbiased estimate of the impact of connections on pollution? What if politicians are elevated to the PSC in response to some prior trend in a province they previously worked? How could this be detected? What test does Jia perform to provide evidence about pre-trends?

98 Discussion questions What identification assumption is required for this specification to generate an unbiased estimate of the impact of connections on pollution? What if politicians are elevated to the PSC in response to some prior trend in a province they previously worked? How could this be detected? What test does Jia perform to provide evidence about pre-trends?

99 Discussion questions What identification assumption is required for this specification to generate an unbiased estimate of the impact of connections on pollution? What if politicians are elevated to the PSC in response to some prior trend in a province they previously worked? How could this be detected? What test does Jia perform to provide evidence about pre-trends?

100 Placebo tests Another concern is that the effect detected could be some regional shock correlated with the elevation of certain politicians to the PSC. For example, growth slows in western China; in response, politicians with experience in the west are prioritized for PSC positions. How does Jia test this hypothesis? Why is this test described as a placebo test?

101 Placebo tests Another concern is that the effect detected could be some regional shock correlated with the elevation of certain politicians to the PSC. For example, growth slows in western China; in response, politicians with experience in the west are prioritized for PSC positions. How does Jia test this hypothesis? Why is this test described as a placebo test?

102 Placebo tests Another concern is that the effect detected could be some regional shock correlated with the elevation of certain politicians to the PSC. For example, growth slows in western China; in response, politicians with experience in the west are prioritized for PSC positions. How does Jia test this hypothesis? Why is this test described as a placebo test?

103 Placebo tests Another concern is that the effect detected could be some regional shock correlated with the elevation of certain politicians to the PSC. For example, growth slows in western China; in response, politicians with experience in the west are prioritized for PSC positions. How does Jia test this hypothesis? Why is this test described as a placebo test?

104 Interpreting connections Jia has a very specific interpretation of the evidence about the impact of connections on pollution: what is her interpretation? What are other potential interpretations? What evidence does she cite to substantiate her interpretation? Do you find it compelling?

105 Interpreting connections Jia has a very specific interpretation of the evidence about the impact of connections on pollution: what is her interpretation? What are other potential interpretations? What evidence does she cite to substantiate her interpretation? Do you find it compelling?

106 Interpreting connections Jia has a very specific interpretation of the evidence about the impact of connections on pollution: what is her interpretation? What are other potential interpretations? What evidence does she cite to substantiate her interpretation? Do you find it compelling?

107 Summing up This paper argues that pollution is the byproduct of a (literal) race to the top by regional Chinese officials: hoping for promotion, they accelerate growth and incur high environmental costs. Do you find this explanation to be compelling? Why does pollution have no significant impact on promotion possibilities? How could this be changed?

108 Summing up This paper argues that pollution is the byproduct of a (literal) race to the top by regional Chinese officials: hoping for promotion, they accelerate growth and incur high environmental costs. Do you find this explanation to be compelling? Why does pollution have no significant impact on promotion possibilities? How could this be changed?

109 Summing up This paper argues that pollution is the byproduct of a (literal) race to the top by regional Chinese officials: hoping for promotion, they accelerate growth and incur high environmental costs. Do you find this explanation to be compelling? Why does pollution have no significant impact on promotion possibilities? How could this be changed?

110 Is FDI the problem It s a commonly told story that foreign firms looking to invest in developing countries use, or prefer to use, highly polluting technologies, and this is an important source of pollution. There s some evidence about this point in China from a recent paper by Judith Dean and colleagues; they evaluate whether location choice in China is responsive to levies for water pollution. If foreign firms prefer provinces with lax pollution standards, that could be a problem.

111 Is FDI the problem It s a commonly told story that foreign firms looking to invest in developing countries use, or prefer to use, highly polluting technologies, and this is an important source of pollution. There s some evidence about this point in China from a recent paper by Judith Dean and colleagues; they evaluate whether location choice in China is responsive to levies for water pollution. If foreign firms prefer provinces with lax pollution standards, that could be a problem.

112 Is FDI the problem It s a commonly told story that foreign firms looking to invest in developing countries use, or prefer to use, highly polluting technologies, and this is an important source of pollution. There s some evidence about this point in China from a recent paper by Judith Dean and colleagues; they evaluate whether location choice in China is responsive to levies for water pollution. If foreign firms prefer provinces with lax pollution standards, that could be a problem.

113 Water pollution levies In theory, this is the most fully developed mechanism of pollution control in China; factories that want to discharge emissions into water pay a fine depending on the pollutant, volume of emissions and concentration. The concentration standards vary at the provincial level. The tax rate for each pollutant is set at the national level. Nothing is said here about enforcement.

114 Water pollution levies In theory, this is the most fully developed mechanism of pollution control in China; factories that want to discharge emissions into water pay a fine depending on the pollutant, volume of emissions and concentration. The concentration standards vary at the provincial level. The tax rate for each pollutant is set at the national level. Nothing is said here about enforcement.

115 Water pollution levies In theory, this is the most fully developed mechanism of pollution control in China; factories that want to discharge emissions into water pay a fine depending on the pollutant, volume of emissions and concentration. The concentration standards vary at the provincial level. The tax rate for each pollutant is set at the national level. Nothing is said here about enforcement.

116 Water pollution levies In theory, this is the most fully developed mechanism of pollution control in China; factories that want to discharge emissions into water pay a fine depending on the pollutant, volume of emissions and concentration. The concentration standards vary at the provincial level. The tax rate for each pollutant is set at the national level. Nothing is said here about enforcement.

117 FDI in China

118 Aggregate results

119 Results decomposed by investment source