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Plastic recycling can help improving the environment quality by reducing waste discharge as well as keeping the surrounding clean. This study examines the perception of individual solid-waste generators about plastic recycling and their willingness to pay (WTP) an extra fee in addition to monthly waste collection charges at their current resident places.
RESEARCHES & DISCUSSIONS Plastic recycling can help improving the environment quality by reducing waste discharge as well as keeping the surrounding clean This study examines the perception of individual solid-waste generators about plastic recycling and their willingness to pay (WTP) an extra fee in addition to monthly waste collection charges at their current resident places A survey-based, contingent valuation, approach with an anchored payment card technique was used to interview 487 individuals in Hochiminh city The findings show that the mean expected WTP is VND43,200 per year from ordered probit model Marital status, education level, employment and income are significant socioeconomic determinants of consumers’ WTP Other important behavioral factors are concerns towards the current ambient environment quality and the threats to human health caused by plastic wastes and the benefit of plastic wastes recycling Keyword: willingness to pay, plastic waste recycling, contingent valuation method Introduction Dangers from solid wastes generation to the global environment as well as human health have been remarked and received a great concern of societies recently Plastic is one of the central concerns because most plastics are non-degradable and leads to a growing concern about space at sanitary landfill sites According to Vietnam Environment Situation 2004 – Solid Waste Report, solid wastes mostly originated from households (60% – 70%) in urban areas Statistics (2009) of HCMC Department of Natural Resource and Environment shows that the solid waste system collects approximately about 5,600 to 6,000 tonnes of wastes daily, in which plastics account for the second largest proportion, about 10.8% in households and 19% in schools (The Saigon Times) (1) A large volume of plastic wastes is not collected for re-use or recycling but goes directly to landfills and this causes a great problem for the current ambient en- 52 vironment quality in the city Recycling is widely considered as a common method to deal with such wastes Recycling plastics can, in many cases, help reducing negative effects on the environment and keeping the surrounding clean Although several global environmental programs have been implemented to improve the country’s environmental status in recent years, solid waste management, especially regarding plastic recycling, seems to have lower priority than the other issues such as climate change and water pollution Despite the fact that the country has its own Environmental Law and also follows the global framework of environmental enhancement in some aspects, well-structured policies and regulations regarding waste recycling (i.e plastic waste) have not been enacted This shows the need of further research of consumers’ or public perception on plastic recycling to support policy makers Recycling would result in cost for the local gov* University of Economics - HCMC Economic Development Review - June 2011 RESEARCHES & DISCUSSIONS ernment and the program could succeed only with the contribution from the public This study aims to examine the individual’s perception on plastic recycling program at a more practical aspect And a hypothesized scenario is used to elicit the financial contribution of individuals or, in other words, their WTP for plastic recycling The policy context is consumers’ preferences for an extra payment in addition to monthly waste collection charges at their current living places Because HCMC is considered as the biggest commercial city and the most populated in Vietnam, and since such environmental issue is more serious in urban area, the research scope is limited to HCMC residents only Theoretical consideration a Contingent Valuation Method (CVM): CVM is a survey-based method of eliciting WTP for an improvement in environmental quality through direct questions Owing to its advantage in measuring passive value of public goods where market price does not exist, the CV method is considered a capable measure for evaluating non-marketed goods The specific eliciting WTP technique plays an important role in CV research because each type of question format may bring different results and associated biasness The payment card method (PC) does not suffer a starting point bias associated with iterative bidding and dichotomous choice This method presents respondents with a range of ordered threshold values and requires them to pick a single amount they are willing to pay However, the PC technique can still have some drawbacks associated with the provision of bids, anchoring effects and the size of intervals (Cameron and Huppert, 1989) b Econometric model: For PC method, the monetary value of WTP that respondents choose is treated as an ordinal variable and analyzed with an ordered regression model The ordered probit model builds around a latent regression in the same manner as the binominal probit model with attitudinal, behavioral and demographic information as explanatory variables of WTP (Cameron and Huppert, 1989) We assume a standard normal distribution with linearity in WTP as follows: (1) where and denotes the unobserved latent variable of willingness to pay for ob- servation i which lies between cut-points tUi and tLi in the distribution of Let Y be the observed ordinal variable, that is: Y = j if or (j = 0,1, J) where both tUi and tLi are unknown parameters to be estimated with b (Greene, 2003) Respondents have their own WTP intensity but cannot express these given the limited number of possible answers and will choose the answer that most closely represents their own WTP intensity Then the probability of WTP that lies within the interval is: (2) With the assumption that the error term is normally distributed between zero and standard deviation s, equation (2) can be re-written as (Cameron and Huppert, 1989; Haab and McConnell, 2002): (3) where the function is the cumulative standard normal density function and equation (3) is called the ordered probit model (Greene, 2003) With number of observation n, the log-likelihood function for the responses can be written as: (4) The parameters of coefficients b are estimated using maximum likelihood estimation of the ordered probit model Then, the interval bounds i.e tL and tU are derived (these are the “cuts” values in STATA) Since both parameters b and standard deviation s need to be estimated, the log-likelihood function (4) will not result in a unique solution to fit the data well (Jackman, 2000) Because the intercept term is dropped from the maximum likelihood estimation, it is necessary to assume the constant, and standard deviation s The coefficients derived from an ordered probit regression have the form b/s and constant 1/s and the variance of error term is fixed at from ordered probit model in most of the standard computer programs (Winship and Mare, 1984) Thus, it is required to recalculate the original b by rescaling the estimated coefficients with standard deviation s This process is called re-calibrating the b terms once we set the thresholds to cut Economic Development Review - June 2011 53 RESEARCHES & DISCUSSIONS points in monetary amounts Hence, it is possible to interpret the effects of explanatory variables in dollar metric, rather than in probit metric (Jackman, 2000) We obtain a rescaling constant (or standard deviation s) from a linear transformation as: z* = mz + c (5) where z is a location estimate from the probit model, z* is the midpoints of thresholds in dollar amount given as bid levels in the payment card determined by (tL + tU)/2 , m is the re-scaling constant (called the standard deviation s), and c is the location shift It is also assumed that the location shift c is the intercept term which was dropped from the ordered probit model (Jackman, 2000) The re-calibrating process results in a new set of b, denoted as brescaled Given a set of brescaled, the expected willingness to pay (EWTP) is derived by reconstructing the original form of WTP from equation (1) EWTPoprobit = Xibrescaled (6) Then, the mean of expected willingness to pay from the population are estimated by: (7) The marginal effects of changes in the regressors of the ordered probit model can be evaluated at sample means or at other relevant values of the regressors The marginal effect is calculated as: (8) where k denotes a single explanatory variable and change in probabilities for the WTP categories must sum to zero (Cranfield and Magnusson, 2003) Methodology a Value to be measured: consumers’ willingness to pay for plastic recycling: Depending on available collection scheme, consumers will have different choices In general, there are three main schemes of plastics waste collection in Vietnam: vehicles used for collection and residents paying for a monthly waste collection charge; the plastics waste re-purchase scheme in which household would receive an amount for a quantity of solid waste from a collector; and the environmental promotion programs of some institutions going ‘green’ The basic difference in the 54 Economic Development Review - June 2011 three schemes above is the consumer utility optimization problem With the first scheme where consumers are asked for their WTP, they will try to minimize their pay-out consistently with their utility, so the bid level would be distributed between zero and a relative low upper value In contrast, the consumer may seek to maximize the amount to be paid by the collectors then the willingness to accept (WTA) would be relative high in the second scheme or they would even have zero WTP or WTA in the third scheme This study is focused to the first scheme only as people will be asked for their WTP The proposed payment vehicle would be an addition to the monthly waste collection charge b Determinants of consumers’ willingness to pay for recycling: The empirical model regresses consumers’ willingness to pay for recycling on a number of socioeconomic factors and behavioral explanatory variables - Socioeconomic variables: Socioeconomic determinants are factors that reflect demographic characteristics of a consumer such as sex, age, marital status, income, employment, education level, and household size These factors are widely used in most CV studies Except household size and age which are continuous values, all the socioeconomic variables are defined as either dummies (i.e sex, marital status, and employment) or as categories (i.e income, and educational level) Income is categorized into six segments rather than as continuous numbers (Haab and McConnell, 2002) For WTP measurement, both income and education are employed in the regression model with their ordinal values - Attitudinal variables: Behavioral factors included in the model are based on consumers’ moral norm in plastic recycling and represent consumers’ perception regarding environmental problem (Hage et al 2009) In this study, we hypothesize that behavioral factors might affect WTP for recycling, which are: (i) Perception of the costs/threats of plastic wastes; (ii) Perception of the benefit of plastic recycling; (iii) Perception of the needs for recycling; and (iv) The habits of dealing with waste There were 10 factors measured in terms of a Likert score value ranging from to in the questionnaire Regarding those answers regarding the consumers’ habit RESEARCHES & DISCUSSIONS in dealing with plastic wastes which have values ranging from 1-4, Likert scores and are converted to “Good habit” and scores and are converted to “Bad habit” The remaining answers regarding the consumers’ consideration towards the agreement of recycling benefits and towards the need, the costs of plastic wastes were converted to “High level of agreement” or “High concern” for scores and and “Neutral to low level of agreement” or “Neutral to low concern” for scores 1, and 3, respectively c Survey administration and data collection: A survey of residents currently living in HCMC in the 18-60 age bracket and having ability to access internet and respond to the online questionnaire was conducted in August 2010 via web-mail A total of 48cores and 5) = Low level of agreement (Likert scores 1,2, and 3) Empirical results It is remarkable that there are only 36 no-responses which account for the smallest percentage 56 Economic Development Review - June 2011 in total responses This means that most people are willing to pay an additional charge Meanwhile, 30.53% of the respondents voted for the highest bid level (VND72,000 per year) and thus RESEARCHES & DISCUSSIONS the distribution of stated values is skewed towards the highest bid a Interpretation of ordered probit regression estimates: The parameter estimates are presented in Table for both the full (unrestricted) model with all independent variables and the final (restricted) model with only significant explanatory factors The results from the full model reveal that there are seven significant variables: four socioeconomic factors (MARRIED, EDU, EMPLOY, and INC) and three behavioral factors (ENVQUAL, ENVTHREAT and BEN3) The Likelihood Ratio (LR) Chi square goodness of fit statistics of the two models are 50.82 and 43.81, respectively, and significant at 1% level These test results indicate that the H0 hypothesis of all estimated parameters equal to zero is rejected, and that the model specification is appropriate and has a power to explain for the variation of WTP choice b Mean of expected willingness to pay: To eliciting the WTP in monetary values, it is necessary to rescale coefficients as indicated in the previous section The re-calibrating process is described in Table (see next page) Table shows that the coefficient m has a positive sign and is significant at 1% level and the intercept term derived from this regression is also significant at 5% The model has a well fit at Rsquared = 0.96 Then, the expected WTP and mean WTP for plastics recycling from the final WTP model are calculated by using equations (5) and (6) as follows: = 43.193 or VND 43,190 per year Since there are no previous studies on WTP for plastics recycling in HCMC, it is impossible to compare the empirical findings with others and Table 3: Ordered probit model estimates for parameters explaining WTP N = 452 Variable SEX WTP Full model Coefficient WTP Final model P>|z| 0.075 (0.108) 0.489 MARRIED -0.202 (0.127) 0.111* AGE -0.010 (0.011) 0.334 EDU 0.230 (0.106) EMPLOY Coefficient P>|z| -0.266 (0.112) 0.017** 0.030** 0.225 (0.103) 0.028** -0.383 0.181) 0.034** -0.415 (0.176) 0.019** INC 0.199 (0.045) 0.000*** 0.173 (0.043) 0.000*** MEM 0.012 (0.021) 0.570 INFO 0.126 (0.106) 0.236 -0.404 (0.156) 0.010*** -0.365 (0.154) 0.018** ENVTHREAT 0.505 (0.242) 0.037** 0.558 (0.215) 0.010*** HEALTH 0.008 (0.146) 0.959 NEED 0.285 (0.284) 0.314 ACT1 -0.016 (0.152) 0.918 ACT2 0.012 (0.112) 0.915 ACT3 0.039 (0.161) 0.808 BEN1 -0.342 (0.269) 0.203 BEN2 -0.289 (0.365) 0.430 BEN3 0.682 (0.292) 0.019** 0.423 (0.227) 0.063* 50.82 LR chi-square (7) 43.81 0.0001 Prob > chi-square 0.000 ENVQUAL LR chi-square (18) Prob > chi2 Note: figures in parentheses are standard errors of the estimates *, **, *** denoted level of significance at 10%, 5% and 1%, respectively Economic Development Review - June 2011 57 RESEARCHES & DISCUSSIONS Table 4: Defining standard deviations and intercept /cut1 = -0.3968087 Midpoints of thresholds in monetary metric z* = (tL + tU)/2 (0 + 12)/2 = /cut2 = 0.3892714 (12 + 24)/2 = 18 z /cut3 = 0.7156811 (24 + 36)/2 = 30 Const /cut4 = 0.9656855 (36 + 50)/2 = 43 Prob > F = 0.0035 /cut5 = 1.624124 (50 + 70)/2 = 60 R-squared = 0.9596 Cut points from STATA oprobit discuss the performance of the analysis overall From 452 observations including true zero bids, we obtain a mean willingness to pay an additional charge in waste collection fee around VND43,200 per year or VND3,600 per month This is a reasonable price in comparison with the average monthly waste collection charge of VND13,000 obtained from the survey c Marginal change of WTP: In order to examine the change in the predicted probability of WTP by a marginal change in one explanatory variable, others remain unchanged, the MEOPROBIT module in STATA was used (Cornelissen, 2006) It is seen that being married decreases the possibility of paying for high bids VND50,000 (1.6%) and VND72,000 (8.9%) The marginal effect of dummy MARRIED is significant at 5% for most Linear regression z* = mz + c (m = s) Coef p-value 27.756 0.003*** 13.093 0.024** bids Unemployed respondents have the negative marginal effects on the last two WTP categories, but positive effects on all the remaining bids However, EMPLOY is insignificant for the bid of VND50,000 Marginal effects on WTP are also stronger for EMPLOY than for the MARRIED (Table 5) For the two categorical variables INCOME and EDU, the pattern is reverse to the socioeconomic dummies Higher education level has the highest positive marginal effect on the highest bid (VND72,000) by 7.8% and decreases the possibility of being willing to pay for the lower yea-saying bid (VND12,000) by 4.1% A marginal increase in income will increase the probability of willingness to pay the highest bid (VND72,000) by 6% INCOME is the only variable having marginal effects significant at 1% for every bid Table 5: Marginal effects of ordered probit model Y=0 Y = 24 Y = 36 Y = 50 0.239 Y = 72 0.080 0.177 0.108 0.091 Prob At mean 0.069 0.174 0.113 0.097 0.253 0.295 MARRIED 0.038 0.048 0.015 0.005 -0.016 -0.089 p-value 0.030 0.019 0.019 0.030 0.061 0.014 EDU 0.305 -0.030 -0.041 -0.013 -0.005 0.012 0.078 p-value 0.032 0.032 0.040 0.061 0.061 0.029 EMPLOY 0.044 0.071 0.028 0.015 -0.005 -0.153 p-value 0.005 0.013 0.040 0.089 0.435 0.024 -0.023 -0.031 -0.010 -0.004 0.009 0.060 p-value 0.000 0.000 0.001 0.009 0.006 0.000 ENVQUAL 0.040 0.063 0.025 0.013 -0.007 -0.134 p-value 0.005 0.014 0.039 0.084 0.211 0.023 -0.104 -0.095 -0.019 0.000 0.055 0.163 0.050 0.004 0.000 1.000 0.067 0.001 -0.073 -0.074 -0.017 -0.002 0.038 0.129 0.139 0.049 0.003 0.555 0.180 0.031 INC ENVTHREAT p-value BEN3 p-value 58 Y = 12 Sample frequency Economic Development Review - June 2011 RESEARCHES & DISCUSSIONS Marginal effects of ‘High concern about the environmental quality’ ENVQUAL dummy indicate that consumers are more likely to pay lower prices (1.3% to 6.3%) and less likely to pay the highest price (13.4%), if they are ‘seriously’ or ‘somewhat seriously’ concerned on the current ambient environmental quality Relative to those who are ‘seriously’ or ‘somewhat seriously’ concerned about the threats from plastic wastes to the environment, the marginal effects of ENVTHREAT are positive on the two highest bids (5.5% to 16.3%) Similarly, ‘High level of agreement’ in the benefit of plastics recycling, i.e ‘help keeping surrounding clean,’ BEN3 dummy variable, has positive effect on the highest bid (12.9%) This implies that consumers who ‘strongly agree’ or ‘somewhat agree’ with this benefit are more likely willing to pay VND72,000 (12.9%) In contrast, those who with ‘neutral to low level of agreement’ are willing to pay lower bids, i.e VND12,000 (7.4%) and VND24,000 (1.7%) Among the three behavioral factors, i.e ENVQUAL, ENVTHREAT, and BEN3, all other things being equal, the ENVTHREAT dummy tends to have strongest marginal effects over WTP categories than the other two variables The result suggests that consumers with higher concerns about the threats from plastics waste are willing to pay more than those who are concerned about the environment quality and the surrounding cleanliness as a benefit from plastic wastes recycling makers, the functional environmental agencies and the plastics producers Thus, there should be parallel action programs from all entities so that the environmental quality enhancement plan would be implemented simultaneously According to the individuals’ opinions, the best solutions to handling of plastic wastes were a higher monthly solid waste collection fee and a surcharge/environmental tax imposed on products containing plastics as perceived by 46% and 35% of the respondents, respectively However, in order to implement these two solutions, more consideration and measurements should be carried out so that the charges would be well affordable for both consumers and producers Besides, stopping supply of free plastic bags in supermarkets and improving the deposit-refund system on plastic items were also possible solutions stated by 32% and 24% of the respondents, respectively These two later solutions have a same characteristic in which consumers not have financial responsibility, but environmental awareness instead Hygiene quality and safety standards of recycled products are highly concerned Because the products are indeed made from disposals which Policy implication and recommendation Recycling plastics would result in costs to the waste management agencies and recyclers, yet enhance an eco-friendly environment The extra amount paid by consumers aims to cover the cost of recycling plastics As presented above, the average expected WTP of consumers is of VND43,200 per year Thus, the policy makers should consider whether the charge policy applies on household-based unit or on adult individuals in the coming development plans Moreover, recycling is not only the responsibility of the consumers but also of the Government – policy Economic Development Review - June 2011 59 RESEARCHES & DISCUSSIONS could have been mixed with other wastes, such a low quality treatment process could even endanger human health Thus, in order to implement any plan, one should introduce guarantees in quality standards to ensure that the recycled products would not have negative effects on human health A well-managed process for the collected funds should be considered seriously and efficiently by policy makers This matter in fact was mentioned in most of respondents’ opinions collected from the survey Respondents indicate that a more transparent and efficient program management is strongly necessary It is also the main reason of most protest zero responses of solutions, especially awareness inspiration and education, before taking into account financial responsibilities such as surcharges, taxes or increment in wastes collection charges The same characteristic found in solutions of stopping the supply of free plastic bags and improving the deposit-refund system on plastic items is that consumers not have financial responsibility, but environmental awareness instead, while policies that emphasize the role of Government and functional agencies are highly voted by the respondents and worth implementation Encouraging re-using plastics and finding alternatives to plastics products are possible solution as well Last but not least, because a large proportion of consumers are still new to and not very familiar with environment protection programs, especially those asking for their financial responsibility, it is necessary to ensure a wide propagation about such programs and their necessity via a range of possible approaches Regarding the surveyed respondents’ preferences, telecommunication/ radio programs and conferences, and TV news programs are mostly preferred for information channels The next important channels are websites, while environmental programs run by institutions, functional agencies, and local authorities also play an important role in which people will have more chances to shift from perception to action Conclusion Possible solutions to plastic wastes include: imposing some surcharge/tax on plastic items, stopping the supply of free plastic bags in supermarkets, improving the deposit-refund system on plastic items (e.g plastic bottles), and increasing the monthly solid waste collection fee However, whether consumers have to pay an increment in monthly waste collection charge or they have to pay some surcharge or tax on plastic items together with manufacturers, these policies take into account the financial obligation from the users’ side, yet not reflect the attitudinal responsibility of consumers and role of Government Thus, in order to implement these two solutions, more consideration and measurements should be carried out so that the charges would be well affordable for both consumers and producers Also, it is necessary to apply simultaneously a variety 60 Economic Development Review - June 2011 The study presents a CV approach with an anchored payment card technique to measure consumers’ WTP for plastics recycling in HCMC, Vietnam The first significant finding in this study is that most consumers (90%) are highly concerned about the current ambient environment quality and the threats caused by plastics wastes to the environment The results from the ordered probit regression show that the mean expected willingness to pay an additional charge for plastic recycling is VND43,200 per year Secondly, the results show that behavioral factors have more influences on the consumers’ WTP A marginal increase in the consumers’ perception towards the threats from plastic wastes to the environment has the strongest effect on the probability of WTP in comparison to the other two behavioral variables, which are the concerns about the ambient environment quality Notably, income plays an important role in determining consumers’ WTP Higher income and higher educated consumers are likely willing to pay higher bids Marital status and employment are also significant factors but have opposite signs for the marginal effects on the predicted probability of WTP Moreover, a number of possible solutions to plastic wastes problem were also investigated via voting of the respondents in which two solutions suggest financial responsibilities and two others take into account consumers’ awareness of disposing wastes and habit of using plastics Media and telecommunica- RESEARCHES & DISCUSSIONS tion are the most potential channels to propagate and disseminate information among plastics endusers regarding threats from plastic wastes, the need for recycling and any available plans/policies relating to the problemn Notes: (1) The Saigon Times Online, Accessible on Oct 7, 2010; Available at: http://www.thesaigontimes.vn/Home/thoisu/doisong/25510/ dered Probit, available at: http://ideas.repec.org/c/boc/bocode/s456788.html Cranfield, J & E Magnusson (2003) “Canadian Consumer’s Willingness-To-Pay for Pesticide-Free Food Products: An Ordered Probit Analysis”, International Food and Agribusiness Management Association (IAMA) Greene, W (2003), Econometric Analysis, 5th Edition, Prentice Hall Hage, O., P Soderholm & C Berglund (2009) “Norms and Economic Motivation in Household Recy- (2) True zero responses reflect the valueless of cling: Empirical Evidence from Sweden”, Resources, amenity, where as protest zero responses are placed Conservation and Recycling, Vol 53, Issue 3, Pp 155- when respondents provide nay-saying due to some as- 165 pects of the scheme though they find the positive value Hanemann, W (1994) “Valuing the Environment of the amenity The reason of a respondent placing through Contingent Valuation”, Journal of Economic Per- protest vote may be because he/she does not fully trust spectives, Vol 8, No.4, Pp 19-43 the proposed service, or he/she may think that the project is unreliable (Fonta et al., 2010) References Boyle, K J & R.C Bishop (1988) “Welfare Meas- Jackman, S (2000) “Models for Ordered Outcomes”, Political Science 200C, available at: http://www.stanford.edu/class/polisci203/ordered.pdf Winship, C & R Mare (1984) “Regression Models urements Using Contingent Valuation: A Comparison of with Ordinal Variables”, American Sociological Review, Techniques”, American Journals of Agricultural Econom- Vol 49, pp 512-525 ics, Vol 70, No 1, pp 20-28 Cameron, T & D Huppert (1989) “OLS versus ML Estimation of Non-market Resource Value with Payment 10 Wooldridge, J.M (2009), Introductory Econometric: A Modern Approach, 4th Edition, South Western College Card Interval Data”, Journal of Environmental Economics and Management, Vol.17, Issue 3, pp 230-246 Cornelissen, T (2006), MEOPROBIT, Stata Module to Compute Marginal Effects after Estimation of Or- Economic Development Review - June 2011 61 ... (ii) Perception of the benefit of plastic recycling; (iii) Perception of the needs for recycling; and (iv) The habits of dealing with waste There were 10 factors measured in terms of a Likert score... used to elicit the financial contribution of individuals or, in other words, their WTP for plastic recycling The policy context is consumers’ preferences for an extra payment in addition to monthly... variation of WTP choice b Mean of expected willingness to pay: To eliciting the WTP in monetary values, it is necessary to rescale coefficients as indicated in the previous section The re-calibrating