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The cost of recycling in municipal solid waste service: size and diversificationGraziano ABRATEUniversity of Piemonte OrientaleFabrizio ERBETTAUniversity of Piemonte OrientaleGiovanni FRAQUELLIUniversity of Piemonte OrientaleDavide VANNONIUniversity of TorinoXII European Workshop on Efficiency and Productivity Analysis Verona
Contents • 1. Motivation of the Study • 2. Dataset • 3. Cost Function Models • 4. Regression Results and Discussion
Motivation of the study • The practice of recycling is increasingly encouraged in the planning of Municipal Solid Waste (MSW) services (its enhancement is grounded on both European and national legislation) Q1: Are there scale/scope improvements in the provision of recycling and disposal services? • Strategies of introducing recycling are different across municipalities (from 0 to 76.4%) independently from municipality size (average share of recycling = 18.1% in small municipalities; = 23.6% in medium municipalities; = 17.2% in large municipalities) • Q2: How do costs change with the increase of the share of recycling for different levels of municipal size?
Motivation of the study: the literature framework The existing literature provides evidence of scope/scale economies in MSW industry based on: • Rather simplified cost functions (with the exception of Antonioli and Filippini, 2002) • Use of one-output single cost equation, system of separate output-specific cost equations with cross-output interaction terms (Bohm, Folz, Kinnaman and Podolsky, 2010; Callan and Thomas; 2001), control through a percentage of recycling volumes (Bel and Faged, 2010) Our paper aims at contributing with respect to: • Use of a well-behaved Composite Specification (CS) other than the more classical Translog Specification (TS) • Use of a multi-output framework
Dataset description • 529 Italian municipalities • Period: 2004-2006 • Balanced panel with 1,587 observations • Equally distributed along the Country: 39% in Northern and Southern Italy, respectively, and 22% in central regions • Prevalence (82%) of limited responsibility companies (especially in the North, 94%) and low incidence of in-house organizational form (10%) • Costs and output quantities obtained from annual MUDs (i.e. annual declarations concerning MSW) • COST: labor + capital + energy costs of the municipalities • Tons of MSW disposed (YD) • Tons of MSW recycled (YR) • Share of recycling differs along Country: 37% in the North, 13% in the Center, 7% in the South (average national value = 23%), • Input prices inferred from questionnaires sent to firms (or inter-municipal consortia) managing the service in the municipalities • Labor price (PL): ratio of total salary expenses to number of employees • Capital price (PK): depreciation costs divided by capital stock • Fuel price (PE): assumed to be the same for all municipalities in the sample (Antonioli and Filippini, 2002)
Cost Function Models Translog cost function specification (TS) Composite cost function specification (CS) i, j = Disposal (D) and Recycling (R); r, l = Labor (L), Capital (K) and Energy (E)
Cost Function Models • Cost elasticity Output and factor price cost elasticities in CS:
SCOPE= Cost Function Models • Scale and scope measures
Regression results NLSUR estimation: Translog (TS) and Composite (CS) cost function models
Regression results Estimated costs (CS model) for disposal and recycling at different output levels
Discussion • Constant returns to scale and scope economies of the order of 2% for the average municipality (YD= 17,122 tons, YR = 3,770 tons, population = 42,500 inhabitants) incentive to jointly provide both services (Callan and Thomas (2001)) • Constant output-specific returns to scale up to =1 (i.e. up to YD = 17,122 tons) and decreasing returns to scale hereafter for both disposal and recycling services. Diseconomies of scale are found to be slightly larger for recycling than for disposal (i.e. for from 1 to 8, C increases by a factor of 9 for disposal and 10.9 for recycling) • Scope economies at all simulated output levels, thus justifying the choice to assign the two services through a single tender. However, SCOPE rather limited up to =1, and higher for larger output levels (7% for = 4 and 14% for = 8) • Constant overall SE up to = 1 (average municipality) and overall diseconomies of scale hereafter. Scope economies counterbalance the effect of decreasing returns to scale for both recycling and disposal activities. Therefore, the resulting estimates of aggregate scale diseconomies are found to be not very large.
Regression results Cost estimate for different shares of recycling Municipalities below/on sample mean 50,000 inhabitants Cost estimate for different shares of recycling Municipalities above sample mean 50,000 inhabitants
Discussion • It is not very costly to increase the percentage of recycling up to 30%-35% at all municipality sizes. For example, increasing recycling shares from 10% to 20% would imply that total costs increase by about 4% ( ranging from 0.25 to 8) • It is not very costly to increase even further the percentage of recycling for relatively small municipalities • It is very costly to increase the ratio ShareR beyond certain levels for large municipalities (but: very few large municipalities with high ShareR). For example, when = 8, costs increase by 32.5% if ShareR increases from 20% to 40% • Keeping constant the total amount of waste collected, it is worth to expand recycling programs where the recycling shares are very low (as in the case of Southern Italian regions) irrespective of the size of the municipality, and, in the case of higher starting levels of ShareR, where the population size is below 150,000-200,000 inhabitants (we only look at costs and we don’t consider eventual revenues deriving from recycled materials!)
Discussion • Lower costs for: • Small/medium sized municipalities and Northern/Central regions • Lower costs for in-house organizational forms as compared to the omitted category (Corporation) • some cost category may be under-reported in the case of direct management • it might be the case that municipalities that have decided to keep a direct management of the waste collection service are relatively more virtuous • DENSITY (= population/municipal surface) is a proxy of the degree of urbanization • High-density municipalities may incur higher costs due to the increased difficulty to operate the service (it may be more difficult to have nearby disposal sites, it may be more difficult to organize efficient separate collection) • We also split DENSITY in two variables indicating, respectively: • VERTICAL DENSITY (URBVER)= Population / number of buildings • HORIZONTAL DENSITY (URBHOR)= Number of buildings /municipal surface • Both indicators show a positive and significant impact on costs.
