- Email: [email protected]
A household level environmental Kuznets curve? Some recent evidence on transport emissions and income
Economics Letters 115 (2012) 187–189
Contents lists available at SciVerse ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
A household level environmental Kuznets curve? Some recent evidence on transport emissions and income Adam Cox a,∗ , Alan Collins a , Lee Woods b , Neil Ferguson c a
Department of Economics, University of Portsmouth, UK
b
School of Civil Engineering and Surveying, University of Portsmouth, UK
c
Department of Civil Engineering, University of Strathclyde, UK
article
info
Article history: Received 6 September 2010 Received in revised form 4 December 2011 Accepted 5 December 2011 Available online 16 December 2011
abstract This paper uses detailed survey data to show no evidence of an Environmental Kuznets Curve (EKC) for household transport emissions. The evidence shows that richer households still do not choose to internalize the social cost of polluting by vehicle emissions. © 2011 Elsevier B.V. All rights reserved.
JEL classification: D10 Q50 R40 Keywords: Air quality Environmental Kuznets curve EKC Household transport Survey Vehicle emissions
1. Introduction and background In a study testing the presence of an Environmental Kuznets Curve (EKC) for household transport emissions, Kahn (1998) uses an indirect method of calculation to show a non-monotonic relationship between estimated household vehicle emissions (if all vehicles drove the same distance) and income. Kahn (1998) uses data from roadside emissions tests in California in 1993. The problem here was, whilst obtaining accurate figures for vehicle emissions, mileage itself was not observed. Further, household income had been found using the vehicle owner’s zip code at the time of the roadside survey. Thus total emissions, as a function of emissions per km multiplied by distance, is also not observed. This paper builds on the evidence provided by (Kahn, 1998) by using the 2006 survey data to identify the presence of an EKC type relationship at the household level. The survey contains not only
∗ Correspondence to: Department of Economics, University of Portsmouth, Portsmouth Business School, Richmond Building, Portland Street, Portsmouth, Hampshire, PO1 3DE, UK. Tel.: +44 (0)23 9284 4732; fax: +44 (0)23 9284 4037. E-mail address: [email protected] (A. Cox). 0165-1765/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.econlet.2011.12.014
more recent data but important variables such as annual mileage, household income and the number of vehicles per household. More generally, the EKC hypothesis suggests an inverted U-shaped relationship between income and environmental quality. This implies that initial economic growth is seemingly detrimental to the environment, but the effects are ameliorated and reversed at some greater levels of income. Empirical evidence is still a matter of contention. Surveying empirical EKC studies, Dinda (2004) notes a number of papers that support the evidence of an inverted U shape relationship between income and measures of environmental degradation such as carbon monoxide or nitrous oxide, albeit with no real consensus as to what income level the turning point arises. Dinda (2004) also notes however, a monotonic relationship between income and more harmful environmental measures such as carbon dioxide. In a critical review, Stern (2004) comments that the EKC empirical evidence is not robust and no common inverted U-shaped path is supported. The ambiguity in the empirical evidence continues when specifically exploring a possible EKC relationship between household transport emissions and income. Assuming that technological gains can cut vehicle emissions, newer cars will produce less harmful emissions. Richer households are more likely to own a greater
188
A. Cox et al. / Economics Letters 115 (2012) 187–189 Table 1 Vehicle emissions by income. Household annual income
Number of vehicles per household
Annual household mileage
Household emissions per km (g of CO2 )
Household annual vehicle emissions (kg of CO2 )
Up to £15,599 £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
0.65 0.88 1.06 1.53
6,026 8,102 10,258 12,368
166 171 172 184
1,713 2,343 2,842 3,353
Table 2 OLS regressions summary of log household emissions on income bracket dummy variables. Household annual income dummy
Coefficient estimate
Heteroskedasticconsistent standard errors
t-test probability (Null = 0)
Constant £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
7.40 0.23 0.31 0.92
0.16 0.19 0.20 0.19
0.00 0.24 0.12 0.00
number of vehicles and use them more, but are also more likely to own newer vehicles that produce less harmful emissions. While there are household-level EKC studies in a developing country context (Pfaff et al., 2004) looking at inter alia, fuel use, there are even less studies in a developed country context and particularly in the specific context of transport. 2. Data A postal questionnaire survey was undertaken in six case study areas in Scotland1 during 2006.2 It was sent to 2,495 addresses, asking a random adult in the household to complete the questionnaire about themselves, their household and their partner/spouse if also living at that address. Data regarding household income and household emissions used in this paper are taken from the 280 responses from this survey. The 11% response rate to this survey is in line with studies using similar postal survey techniques by (Kitamura et al., 1997; Cervero and Day, 2008) and Kenyon (2009). Further, this sample size appears appropriate. Tabachnick and Fidell (2007) suggest that the sample should be 104 + the number of independent variables and Garson (2010) notes there must be at least 20 times as many cases as independent variables. Further, this survey sample is shown to be representative of the population when compared to larger surveys. The Scottish Household Survey (2007) reports 70% of 13,414 households have access to a car, this paper’s sample shows 74%. The SHS also reports the percentage of households that have access or otherwise to vehicles, this paper’s sample follows in parenthesis, 30% (26%) of households have no car, 45% (52%) have one car and 25% (22%) have two or more cars. The Scottish Transport Statistics (2010) data shows the average age of all vehicles to be 6.1 years old in 2006, similar to the sample used, 6.02 years old. Total household annual income is collected by allowing the respondent to select which income band they best suit. The data can therefore be grouped into income bands covering all survey responses. Vehicle emissions data are calculated by the vehicle CO2 rating (g/km) multiplied by the distance travelled. CO2 ratings per km are taken from the UK Government Vehicle Certification Agency (VCA) using the exact make, model and engine size of vehicle collected in the survey. An assumption has to be made that all driving behaviours are similar across the mileage stated.
1 The survey areas and the corresponding numbers of replies are as follows: Glasgow Central 49, Glasgow Pollokshields 71, Glasgow Darnley 25, Edinburgh Central 46, Edinburgh Restalrig 39, Edinburgh Corstorphine 50. 2 This research was undertaken as part of the Engineering and Physical Sciences Research Council (EPSRC) Sustainable Urban Environments Programme, City Form: The Sustainable Urban Form Consortium (grant no. GR/S20529/01).
3. A household-level environmental Kuznets curve for vehicle emissions? Theoretically the social cost of driving a vehicle is higher than the private cost, that is to say each household fails to fully internalize the cost of contributing to environmental degradation by way of vehicle emissions. The household choice here is twofold: firstly, the choice and number of vehicles, vehicles have a wide range of CO2 ratings. Secondly, the extent to which the car is used essentially corresponds to how much fuel the household chooses to use. From this data the average number of vehicles owned by a household increases from 0.65 vehicles, at incomes up to £15,599, to 1.53 vehicles at incomes £52,000 or more. The continual increase shows that richer households own more vehicles. On average the lowest income households will drive their vehicles for 6,026 miles per year. Annual vehicle mileage increases with income. The highest income households drive their vehicles, on average, 12,368 miles per year. Richer households do drive more miles in total, but may be driving those miles across more than one vehicle. Household transport emissions per km increases with income from 166 g per km to 184 g per km. This evidence suggests that richer households drive more polluting vehicles than poorer households. These results are shown in Table 1, detailing the mean household levels for each corresponding income bracket. The last column in Table 1 is the mean total household annual vehicle emissions. Average transport emissions increase from 1,713 to 3,353 kg of CO2 per year between the poorest and richest households. A summary of results from a simple ordinary least squares regression model are reported in Table 2. The lowest income band, up to £15,000 a year, is the base case thus the coefficient on each subsequent household income band shows the difference in emissions compared to the lowest income households. According to these results, households earning £15,600 to £31,199 a year produce 23% more emissions and households earning £31,200 to £51,999 a year produce 31% more emissions. Although the estimated coefficients are positive, the reported t-test probability shows that the increase in emissions for these two income brackets is not statistically greater than that of the lowest income households. However, there is evidence to suggest that the highest income households produce 92% more emissions than the lowest income households. This data displays little evidence of a nonmonotonic relationship between emissions and income and thus is not supportive of the EKC hypothesis at a household level. Looking in more detail at the data, Table 3 shows the annual mileage, the emissions per km and the total emissions of the first
A. Cox et al. / Economics Letters 115 (2012) 187–189
189
Table 3 Vehicle emissions by income: vehicle 1 and vehicle 2. Household annual income
Vehicle 1
Vehicle 2 or more
Annual mileage Up to £15,599 £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
Emissions per km (g)
Annual vehicle emissions (kg of CO2 )
6,026 8,502
166 170
1,713 2,448
10,635
168
12,635
188
Annual mileage
Emissions per km (g)
Annual vehicle emissions (kg of CO2 )
– 5,750
– 174
– 1,669
2,891
8,692
185
2,640
3,679
11,911
184
3,393
Table 4 Vehicle engine size and vintage: vehicle 1 and vehicle 2. Household annual income
Up to £15,599 £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
Vehicle 1
Vehicle 2 or more
Engine size
Vintage
Engine size
Vintage
1544 1622 1552 1969
2000 2003 2003 2004
– 1757 1730 1717
– 1999 1998 1999
vehicle and the second (or more)3 vehicle. Vehicle usage increases with income for both first and second vehicles. The second vehicle in the household is driven less on average than the first at each income level. However, at the £15,600 to £31,199 and £31,200 to £51,999 incomes, households choose to drive vehicles that produce higher levels of CO2 emissions. There is no reduction of annual vehicle emissions as households become richer for either the first or second vehicle. Table 4 shows the engine size and vintage of the first and second vehicles, these two factors contribute towards the CO2 per km rating awarded by the VCA. Although there is not a strict linear pattern of engine size increasing with income, the richest households use vehicles with an average engine size of 1969 cubic capacity (cc) compared to the poorest households using 1544cc engines. The two middle income bands choose to use second vehicles that are much larger in engine size than the first vehicle. The age of the first car does decrease with income. This provides some evidence to suggest that richer households do choose to use newer vehicles for their first vehicle. However, the second vehicle they choose is, on average, markedly older than the first. In essence, the evidence suggests that, on average, richer families do own more and newer vehicles and drive their vehicles more, but they do not own less polluting vehicles. It suggests that
3 Due to a small number of households from the survey that owned a third vehicle, the data has been pooled: ‘‘Two or more vehicles’’.
richer households still do not choose to internalize the social cost of polluting by vehicle emissions. References Cervero, R., Day, J., 2008. Suburbanization and transit oriented development in China. Transport Policy. 15, 315–323. Dinda, S., 2004. Environmental Kuznets curve hypothesis: a survey. Ecological Economics 49, 431–455. Garson, D., 2010. Multiple Regression. Retrieved from http://statpages.org/#Power, March, 2010. Kahn, M.E., 1998. A household level environmental Kuznets curve. Economics Letters 59, 269–273. Kenyon, S., 2009. The impacts of Internet use upon activity participation and travel: Results from a longitudinal diary-based panel study. Transportation Research Part C. 18, 21–35. Kitamura, R, Mokhtarian, P.L, Daidet, L., 1997. A micro-analysis of land use and travel in five neighborhoods in the San Francisco bay area. Transportation 24, 125–158. Pfaff, A., Chaudhuri, S., Nye, H., 2004. Household production and environmental Kuznets curves. Environmental and Resource Economics 27, 187–200. Scottish Transport Statistics,, 2010. No 29: 2010 Edition. Retrieved July 04, 2011 from http://www.scotland.gov.uk/Publications/2010/12/17120002/22. Stern, D., 2004. The rise and fall of the environmental Kuznets curve. World Development 32, 1419–1439. Tabachnick, B.G., Fidell, L.S., 2007. Using Multivariate Statistics, Fifth ed. Pearson, Boston. The Scottish Household Survey,, 2007. Annual Report. Retrieved July 04, 2011 from http://www.scotland.gov.uk/Publications/2008/08/07100738/10.
Contents lists available at SciVerse ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
A household level environmental Kuznets curve? Some recent evidence on transport emissions and income Adam Cox a,∗ , Alan Collins a , Lee Woods b , Neil Ferguson c a
Department of Economics, University of Portsmouth, UK
b
School of Civil Engineering and Surveying, University of Portsmouth, UK
c
Department of Civil Engineering, University of Strathclyde, UK
article
info
Article history: Received 6 September 2010 Received in revised form 4 December 2011 Accepted 5 December 2011 Available online 16 December 2011
abstract This paper uses detailed survey data to show no evidence of an Environmental Kuznets Curve (EKC) for household transport emissions. The evidence shows that richer households still do not choose to internalize the social cost of polluting by vehicle emissions. © 2011 Elsevier B.V. All rights reserved.
JEL classification: D10 Q50 R40 Keywords: Air quality Environmental Kuznets curve EKC Household transport Survey Vehicle emissions
1. Introduction and background In a study testing the presence of an Environmental Kuznets Curve (EKC) for household transport emissions, Kahn (1998) uses an indirect method of calculation to show a non-monotonic relationship between estimated household vehicle emissions (if all vehicles drove the same distance) and income. Kahn (1998) uses data from roadside emissions tests in California in 1993. The problem here was, whilst obtaining accurate figures for vehicle emissions, mileage itself was not observed. Further, household income had been found using the vehicle owner’s zip code at the time of the roadside survey. Thus total emissions, as a function of emissions per km multiplied by distance, is also not observed. This paper builds on the evidence provided by (Kahn, 1998) by using the 2006 survey data to identify the presence of an EKC type relationship at the household level. The survey contains not only
∗ Correspondence to: Department of Economics, University of Portsmouth, Portsmouth Business School, Richmond Building, Portland Street, Portsmouth, Hampshire, PO1 3DE, UK. Tel.: +44 (0)23 9284 4732; fax: +44 (0)23 9284 4037. E-mail address: [email protected] (A. Cox). 0165-1765/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.econlet.2011.12.014
more recent data but important variables such as annual mileage, household income and the number of vehicles per household. More generally, the EKC hypothesis suggests an inverted U-shaped relationship between income and environmental quality. This implies that initial economic growth is seemingly detrimental to the environment, but the effects are ameliorated and reversed at some greater levels of income. Empirical evidence is still a matter of contention. Surveying empirical EKC studies, Dinda (2004) notes a number of papers that support the evidence of an inverted U shape relationship between income and measures of environmental degradation such as carbon monoxide or nitrous oxide, albeit with no real consensus as to what income level the turning point arises. Dinda (2004) also notes however, a monotonic relationship between income and more harmful environmental measures such as carbon dioxide. In a critical review, Stern (2004) comments that the EKC empirical evidence is not robust and no common inverted U-shaped path is supported. The ambiguity in the empirical evidence continues when specifically exploring a possible EKC relationship between household transport emissions and income. Assuming that technological gains can cut vehicle emissions, newer cars will produce less harmful emissions. Richer households are more likely to own a greater
188
A. Cox et al. / Economics Letters 115 (2012) 187–189 Table 1 Vehicle emissions by income. Household annual income
Number of vehicles per household
Annual household mileage
Household emissions per km (g of CO2 )
Household annual vehicle emissions (kg of CO2 )
Up to £15,599 £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
0.65 0.88 1.06 1.53
6,026 8,102 10,258 12,368
166 171 172 184
1,713 2,343 2,842 3,353
Table 2 OLS regressions summary of log household emissions on income bracket dummy variables. Household annual income dummy
Coefficient estimate
Heteroskedasticconsistent standard errors
t-test probability (Null = 0)
Constant £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
7.40 0.23 0.31 0.92
0.16 0.19 0.20 0.19
0.00 0.24 0.12 0.00
number of vehicles and use them more, but are also more likely to own newer vehicles that produce less harmful emissions. While there are household-level EKC studies in a developing country context (Pfaff et al., 2004) looking at inter alia, fuel use, there are even less studies in a developed country context and particularly in the specific context of transport. 2. Data A postal questionnaire survey was undertaken in six case study areas in Scotland1 during 2006.2 It was sent to 2,495 addresses, asking a random adult in the household to complete the questionnaire about themselves, their household and their partner/spouse if also living at that address. Data regarding household income and household emissions used in this paper are taken from the 280 responses from this survey. The 11% response rate to this survey is in line with studies using similar postal survey techniques by (Kitamura et al., 1997; Cervero and Day, 2008) and Kenyon (2009). Further, this sample size appears appropriate. Tabachnick and Fidell (2007) suggest that the sample should be 104 + the number of independent variables and Garson (2010) notes there must be at least 20 times as many cases as independent variables. Further, this survey sample is shown to be representative of the population when compared to larger surveys. The Scottish Household Survey (2007) reports 70% of 13,414 households have access to a car, this paper’s sample shows 74%. The SHS also reports the percentage of households that have access or otherwise to vehicles, this paper’s sample follows in parenthesis, 30% (26%) of households have no car, 45% (52%) have one car and 25% (22%) have two or more cars. The Scottish Transport Statistics (2010) data shows the average age of all vehicles to be 6.1 years old in 2006, similar to the sample used, 6.02 years old. Total household annual income is collected by allowing the respondent to select which income band they best suit. The data can therefore be grouped into income bands covering all survey responses. Vehicle emissions data are calculated by the vehicle CO2 rating (g/km) multiplied by the distance travelled. CO2 ratings per km are taken from the UK Government Vehicle Certification Agency (VCA) using the exact make, model and engine size of vehicle collected in the survey. An assumption has to be made that all driving behaviours are similar across the mileage stated.
1 The survey areas and the corresponding numbers of replies are as follows: Glasgow Central 49, Glasgow Pollokshields 71, Glasgow Darnley 25, Edinburgh Central 46, Edinburgh Restalrig 39, Edinburgh Corstorphine 50. 2 This research was undertaken as part of the Engineering and Physical Sciences Research Council (EPSRC) Sustainable Urban Environments Programme, City Form: The Sustainable Urban Form Consortium (grant no. GR/S20529/01).
3. A household-level environmental Kuznets curve for vehicle emissions? Theoretically the social cost of driving a vehicle is higher than the private cost, that is to say each household fails to fully internalize the cost of contributing to environmental degradation by way of vehicle emissions. The household choice here is twofold: firstly, the choice and number of vehicles, vehicles have a wide range of CO2 ratings. Secondly, the extent to which the car is used essentially corresponds to how much fuel the household chooses to use. From this data the average number of vehicles owned by a household increases from 0.65 vehicles, at incomes up to £15,599, to 1.53 vehicles at incomes £52,000 or more. The continual increase shows that richer households own more vehicles. On average the lowest income households will drive their vehicles for 6,026 miles per year. Annual vehicle mileage increases with income. The highest income households drive their vehicles, on average, 12,368 miles per year. Richer households do drive more miles in total, but may be driving those miles across more than one vehicle. Household transport emissions per km increases with income from 166 g per km to 184 g per km. This evidence suggests that richer households drive more polluting vehicles than poorer households. These results are shown in Table 1, detailing the mean household levels for each corresponding income bracket. The last column in Table 1 is the mean total household annual vehicle emissions. Average transport emissions increase from 1,713 to 3,353 kg of CO2 per year between the poorest and richest households. A summary of results from a simple ordinary least squares regression model are reported in Table 2. The lowest income band, up to £15,000 a year, is the base case thus the coefficient on each subsequent household income band shows the difference in emissions compared to the lowest income households. According to these results, households earning £15,600 to £31,199 a year produce 23% more emissions and households earning £31,200 to £51,999 a year produce 31% more emissions. Although the estimated coefficients are positive, the reported t-test probability shows that the increase in emissions for these two income brackets is not statistically greater than that of the lowest income households. However, there is evidence to suggest that the highest income households produce 92% more emissions than the lowest income households. This data displays little evidence of a nonmonotonic relationship between emissions and income and thus is not supportive of the EKC hypothesis at a household level. Looking in more detail at the data, Table 3 shows the annual mileage, the emissions per km and the total emissions of the first
A. Cox et al. / Economics Letters 115 (2012) 187–189
189
Table 3 Vehicle emissions by income: vehicle 1 and vehicle 2. Household annual income
Vehicle 1
Vehicle 2 or more
Annual mileage Up to £15,599 £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
Emissions per km (g)
Annual vehicle emissions (kg of CO2 )
6,026 8,502
166 170
1,713 2,448
10,635
168
12,635
188
Annual mileage
Emissions per km (g)
Annual vehicle emissions (kg of CO2 )
– 5,750
– 174
– 1,669
2,891
8,692
185
2,640
3,679
11,911
184
3,393
Table 4 Vehicle engine size and vintage: vehicle 1 and vehicle 2. Household annual income
Up to £15,599 £15,600 to £31,199 £31,200 to £51,999 £52,000 or more
Vehicle 1
Vehicle 2 or more
Engine size
Vintage
Engine size
Vintage
1544 1622 1552 1969
2000 2003 2003 2004
– 1757 1730 1717
– 1999 1998 1999
vehicle and the second (or more)3 vehicle. Vehicle usage increases with income for both first and second vehicles. The second vehicle in the household is driven less on average than the first at each income level. However, at the £15,600 to £31,199 and £31,200 to £51,999 incomes, households choose to drive vehicles that produce higher levels of CO2 emissions. There is no reduction of annual vehicle emissions as households become richer for either the first or second vehicle. Table 4 shows the engine size and vintage of the first and second vehicles, these two factors contribute towards the CO2 per km rating awarded by the VCA. Although there is not a strict linear pattern of engine size increasing with income, the richest households use vehicles with an average engine size of 1969 cubic capacity (cc) compared to the poorest households using 1544cc engines. The two middle income bands choose to use second vehicles that are much larger in engine size than the first vehicle. The age of the first car does decrease with income. This provides some evidence to suggest that richer households do choose to use newer vehicles for their first vehicle. However, the second vehicle they choose is, on average, markedly older than the first. In essence, the evidence suggests that, on average, richer families do own more and newer vehicles and drive their vehicles more, but they do not own less polluting vehicles. It suggests that
3 Due to a small number of households from the survey that owned a third vehicle, the data has been pooled: ‘‘Two or more vehicles’’.
richer households still do not choose to internalize the social cost of polluting by vehicle emissions. References Cervero, R., Day, J., 2008. Suburbanization and transit oriented development in China. Transport Policy. 15, 315–323. Dinda, S., 2004. Environmental Kuznets curve hypothesis: a survey. Ecological Economics 49, 431–455. Garson, D., 2010. Multiple Regression. Retrieved from http://statpages.org/#Power, March, 2010. Kahn, M.E., 1998. A household level environmental Kuznets curve. Economics Letters 59, 269–273. Kenyon, S., 2009. The impacts of Internet use upon activity participation and travel: Results from a longitudinal diary-based panel study. Transportation Research Part C. 18, 21–35. Kitamura, R, Mokhtarian, P.L, Daidet, L., 1997. A micro-analysis of land use and travel in five neighborhoods in the San Francisco bay area. Transportation 24, 125–158. Pfaff, A., Chaudhuri, S., Nye, H., 2004. Household production and environmental Kuznets curves. Environmental and Resource Economics 27, 187–200. Scottish Transport Statistics,, 2010. No 29: 2010 Edition. Retrieved July 04, 2011 from http://www.scotland.gov.uk/Publications/2010/12/17120002/22. Stern, D., 2004. The rise and fall of the environmental Kuznets curve. World Development 32, 1419–1439. Tabachnick, B.G., Fidell, L.S., 2007. Using Multivariate Statistics, Fifth ed. Pearson, Boston. The Scottish Household Survey,, 2007. Annual Report. Retrieved July 04, 2011 from http://www.scotland.gov.uk/Publications/2008/08/07100738/10.