The Impact of Corruption and Accountability on refuse collection costs

Graziano Abrate, Federico Boffa, Fabrizio Erbetta, Davide Vannoni

Abstract
This paper explores the link between accountability, corruption and efficiency in the context of the provision of a local public service. Using data on solid waste management services provided by a large sample of Italian municipalities, we estimate a stochastic cost frontier model and  provide robust evidence that high corruption levels and low degrees of accountability substantially increase cost inefficiency. Finally, we show that the negative impact of corruption is weaker for municipalities ruled by left-wing parties, while the positive impact of accountability is stronger if the refuse collection service is managed by limited liability companies.
Keywords: corruption, accountability efficiency, solid waste.
1	INTRODUCTION
In Western countries, many local public services, including water provision, gas distribution and waste collection and disposal, are managed as local monopolies. They are typically operated by firms with tight political connections, if not directly by the local government (in-house provision), usually under soft budget constraints.
Local public utilities may be particularly inefficient, due to the interplay of two factors, managerial slack and corruption. Firms with market power are particularly exposed to managerial slack, especially in the absence of effective monitoring devices or appropriate incentive schemes (Nickell, 1996). Markets with an extensive degree of interaction between politicians and firms tend to be associated to higher levels of corruption and patronage (Shleifer and Vishny, 1994). This is empirically documented by Menozzi et al. (2012), in their analysis of the effects of political connections on utilities' performances.
The main goal of this paper is to measure the impact of corruption and accountability on the efficiency of the provision of refuse collection services. To be more specific, our research hypotheses are that inefficiency is greater for waste operators located in more corrupt regions, and in regions where voters are less informed.
The relationship between observability and the performance of local public governments has rarely been investigated empirically. An exception is Giordano and Tommasino (2013), who identify the determinants of public sector efficiency of the Italian local governments. They show that measures of citizens' political engagement (electoral turnout for referenda and number of newspapers sold) have a positive and significant impact on the efficiency of the provision of local public services such as education, civil justice, healthcare and waste disposal, while measures of social capital do not have any discernible effect.
The negative incidence of corruption on efficiency is well documented. Most of the empirical literature relies on cross-country comparisons and makes use of country level measures of corruption such as the Transparency International index or the Corruption Perception index, while very few papers use disaggregated data at the firm or at the local government level.
For instance, Dal Bò and Rossi (2007) estimate a labour requirement function on a set of 80 electricity distribution firms active in 13 Latin America countries, and show that firms operating in more corrupt environments tend to be less efficient in terms of labour use. Yan and Oum (2014) provide a single country-firm level study. They investigate the effect of corruption on the cost efficiency of a sample of 55 US commercial airports observed from 2001 to 2009, and found a detrimental effect of corruption on efficiency.
Waste collection is a particularly suitable sector to study the effects of political accountability and corruption on efficiency. In Italy, waste collection and disposal are mainly carried out by publicly-owned firms under the control of local governments. Although citizens have an interest in the efficient management of the MSW activity, due to the impact on the tax burden, it is reasonable to assume that they do not have complete information about technology and are unable to perfectly assess its economic performance. This is especially true in contexts plagued by widespread corruption and entrenched presence of criminal organizations. As discussed in D'Amato et al. (2011), entry of organized crime in the waste cycle is mainly aimed at creating shadow circuits for illegal transport and disposal. In this context, the diffusion of collusive relationships among managers and suppliers aimed at overcharging the firms and at seeking illegal sources of profits is an undisputed matter of fact. Also, in more corrupt environments, managers are more likely to engage in negotiating activities with local governments in order to establish more favorable tariffs and service obligations, diverting the managerial efforts away from cost monitoring and productive tasks.
In order to test our predictions about the impact of corruption and accountability on efficiency we  use a rich unique micro dataset on the solid waste collection and disposal activity in Italy, which includes more than five hundred municipalities observed in the years 2004-2006. We use a stochastic cost frontier approach to analyze the effects of accountability and corruption on the costs of providing municipal solid waste (MSW) services throughout Italy.
We measure accountability by newspapers' readership and electoral participation, and corruption by the number of criminal charges against the State, public governments and social institutions. The empirical evidence supports our predictions.
We find that both accountability and corruption have an impact, in the expected direction, on the costs of MSW services. Moreover, by enriching our cost frontier specification, we obtain some interesting additional insights. In particular, we find that the impact of accountability on reducing inefficiency is smaller or even disappears when municipalities organize the service in-house or join a intermunicipal consortium, while corruption is less of harm to efficiency when municipalities are ruled by left-wing parties.
The remainder of the paper is organized as follows. Section 2 describes the main features of the dataset, presents the econometric model and shows the main results of the estimates. Section 3 contains our concluding remarks.
2	EMPIRICAL ANALYSIS
2.1	The econometric model
We use a stochastic cost frontier approach to model the expenditure for collection and disposal of solid waste at the municipal level. The econometric model can be expressed in general terms as:
	(1)	
Where TCit is the total cost incurred by municipality i at time t, yit is a vector of outputs, pit is a vector of input prices, β is a vector of parameters to be estimated, vit is a standard error term measuring random noise and uit is a non-negative error term, to be interpreted as cost inefficiency. The latter follows a truncated normal distribution whose pre-truncation mean is parameterized on a set of exogenous factors zit -- such as our key variables of interest, accountability and corruption -- and a vector of parameters δ to be estimated.
The two sets of parameters (β and δ) are estimated simultaneously. This is what Wang and Schmidt (2002) refers to as one-step procedure, as opposed to a two-step approach which consists of estimating cost inefficiency without including exogenous factors and subsequently fitting a model in which a set of variables is used to explain the estimated inefficiency.
Kumbhakar et al. (1991) and Battese and Coelli (1995) suggest to adopt a linear specification of the mean value of the inefficiency term:
	(2)	
Given the sign of δ parameters, a variation of z variables changes the mean of the pre-truncated distribution of uit, thus allowing for an increase/decrease of the estimated cost inefficiency, in line with our theoretical model.
Cost inefficiency cannot be simply derived as a residual, since the composite error includes the statistical noise vit term, which is not observable. Jondrow et al. (1982) therefore suggest to estimate uit as its conditional expectation uit, given the fitted value of εit =uit+vit, i.e. =E(uit|εit). The latter can then be transformed into a measure of distance from the optimal frontier following Battese and Coelli (1988), who define the cost inefficiency measure, CIit, as:
	(3)	
(3) yields inefficiency values greater than (or equal to) 1, readily interpretable as percentage deviations from the minimum attainable cost. Given that the expected inefficiency (i.e. the mean of the pre-truncated distribution) is modeled as a function of a set of variables z, the effect of such variables on the estimated cost inefficiency index depends on the features of the truncated normal distribution. In general, their marginal effect on cost efficiency CE (i.e., the inverse of cost inefficiency, ranging from 0 to 1) may be computed as (Olsen and Henningsen, 2011):
	(4)	
where Φ(.) and φ denote the cumulative distribution function and the density function of the standard normal distribution,
  is the estimated value of the standard deviation of the inefficiency term,  is the estimated value of the standard deviation of random noise,  is the estimated value of the composed error term ,  is the estimated expected value of the truncated distribution of the inefficiency term, based on the δ parameters. The marginal effects calculated at the individual observation level measure the (monotonic) variation in the cost efficiency index with respect to a contour change of the z variable.
2.2	Data and variables
The database, which can be considered as fairly representative of the entire population of Italian municipalities, refers to a balanced panel of 529 municipalities (of which 204 are localized in the North, 207 are localized in the South, and the remaining 118 are localized in the Centre of Italy) observed over the period 2004-2006. Table 1 presents the summary statistics of the variables included in the cost frontier specification. For each municipality, we observe:
-	the total cost (TC), which is the sum of labor, capital and fuel costs incurred to provide the MSW service;
-	the tons of MSW disposed (yD);
-	the tons of MSW sent for recycling (yR);
-	the price of labor (pL), given by the ratio of total salary expenses to the number of full-time equivalent employees;
-	the price of diesel fuel (pF);
-	the price of capital (pK), obtained by dividing depreciation costs by the capital stock.
We merged different sources of data. Data on costs and output quantities were obtained from annual MUDs (i.e. annual declarations concerning municipal solid waste collection) and were provided by Ecocerved.
Tab. 1 - Summary statistics.

As to input prices, we relied on balance sheets of the firms (or internal organizational structures of the municipalities, in case of in-house provision) managing the service in the municipalities. As an exception, the price of diesel fuel was drawn from data released by the local Chambers of Commerce.
Table 1 highlights that the average municipality produces almost 21,000 tons of waste, around 20 per cent of which is sent to recycling, with an average cost per ton in the neighborhood of 250 Euros.
Our database contains information concerning the organizational structure of the MSW service as well as the political orientation of the municipality. The limited liability company is by far the most popular legal form (chosen by 82 percent of the entire sample), followed by in-house provision (10 percent) and inter-municipal partnership (8 percent). The political environment is captured by data on the political majorities ruling the municipalities. Data indicate that left-wing parties are governing around 29 percent of municipalities, right-wing parties around 18 percent, and "civic or municipal lists", that is independent local political groups which are not affiliated to major nation-wide left-wing or right-wing parties, the remaining 53 percent.
Finally, the cornerstone of the analysis is related to the measurement of accountability and corruption. Accountability can be defined as the citizens' ability to identify the responsibilities of institutional, economic and social operators and to assess their behaviors and performance. Accountability is in strict relation with diffusion of newspapers (Snyder and Stromberg, 2010). Cartocci (2007) provides the geographical map of social capital in Italy, presenting among the others two indicators describing the citizens' attitude to search for information and participate to the community life:
-	the number of newspapers readers (NEWS) for every 1,000 inhabitants (excluding sport newspapers), defined as an "invisible" form of participation;
-	the average voters' turnout during the period 1999-2001 (VOTE), described as a "visible" form of participation.
Both indicators are available only at the province-level of disaggregation, thus we associated each municipality to its provincial value.
This seems a reasonable degree of approximation given that the average dimension of an Italian province is quite small (around 2700 km² and 500,000 inhabitants). Moreover, in our dataset, there are a total of 101 provinces (out of 110), thus a suitable cross-section variability is ensured.
Giordano and Tommasino (2013) construct an index of political interest taking into account both newspaper diffusion and electoral participation. We follow a similar approach, defining a unique accountability index (ACCOUNT) as the average between NEWS and VOTE.
A crucial point of the analysis clearly concerns the complex assessment of corruption. As argued by Golden and Picci (2005), directly measuring corruption is "an enterprise that is not possible since corruption is a complex set of variable interactions, processes and phenomena with no single metric" (p. 37). Moreover, as suggested by Olken (2009), the most commonly used measures are based on corruption perceptions, while more effort should be put in constructing more objective corruption indices, which could produce more reliable results: "Perceptions data should be used for empirical research on the determinants of corruption with considerable caution, and there is little alternative to continuing to collect more objective measures of corruption, difficult though that may be" (p. 962). Our preferred measure uses publicly available data from the National Institute of Statistics (ISTAT). In particular, CORRUPT indicates the number of criminal charges against the State, public governments and social institutions (per 100,000 inhabitants), and consists of an aggregate indicator that includes crimes such as embezzlement, extortion, conspiracy and other crimes against the faith and public order. CORRUPT is available at provincial level and it is time-invariant, since we consider the average number of crimes during the period 2004-2006. This measure, which has been used by Del Monte and Papagni (2007), does not reflect actual corruption crimes, but only the crimes reported to the police, and hence it has the drawback of underestimating the true phenomenon.
As a robustness check, we use also the corruption index proposed by Golden and Picci (2005), which is based on the difference between the cumulative amount of resources devoted to public works in each province and the physical quantities of infrastructures actually realized.
2.3	The cost frontier specification
In order to identify the relationship between cost efficiency in the collection of solid waste and corruption, we need to parameterize the stochastic cost frontier. A popular functional form in this type of studies is the translog function, that is a second degree Taylor approximation of an arbitrary cost function. In our case, we specify a two output, three input cost frontier, taking the following form:
	(5)	

In Equation (5) the residual is composed of a one-sided (uit) term, which follows a truncated normal distribution with mean μit, and a symmetric random noise vit. We further assume that vit and uit are homoskedastic and independent of each other and uncorrelated with the output and input price vectors, yr and ps.
The outputs yr are represented by the volume of MSW disposed (r = D) and the volume of MSW recycled (r = R). On the side of productive factors, prices refers to labor (s = L), capital (s = K) and fuel (s = F).
Cost and input prices are divided by the price of fuel (pF) to ensure homogeneity of degree one in input prices while βsr = βrs and βsm=βms impose symmetry. Other non imposed properties, in particular concerning the concavity of the cost function in input prices, are checked ex post.
We model the expected value of the pre-truncation normal distribution of cost inefficiency as follows:

MODEL 1:
μit=δ₀+δACClnACCOUNTit	(6)	
MODEL 2:
μit=δ₀+δACClnACCOUNTit+δCORRlnCORRUPTit	(7)	
MODEL 3:
μit=δ₀+lnACCOUNTit(δACC+δACC_CORPCORPit)+lnCORRUPTit(δCORR+δCORR_LWLWPOLit) 
+ δCORPCORPit+δLWLWPOLit	(8)	
In Model 1, we consider only the accountability index as a determinant of municipality inefficiency. In Model 2, a corruption index is added as a separate variable in the mean inefficiency ancillary equation. Model 3 enriches the analysis using additional variables that can impact on the way accountability or corruption are affecting the efficient provision of MSW services.
More specifically, Model 3 emphasizes the potential interactions between accountability and the organizational form of service supply, on the one hand, and corruption and political orientation on the other. First, we control for the type of service organization. The type of ownership may directly impact on efficiency, even though empirical evidence in this sense is rather mixed (Bel et al., 2010). Furthermore, if the potential impact of accountability varies across different types of service organizations, we may observe a second indirect effect through the parameter δACC_CORP. The underlying assumption is that, by providing the service by means of organizational forms different than the limited liability company (the only one subject to the private law administrative and accounting rules), municipalities might cushion the benefits of a higher accountability in terms of cost efficiency. In the case of in-house provision a key feature would be the confluence of service costs in the broader municipal budget, thus leaving room for cross-subsidization within the operational autonomy of single municipalities: as a result publicly available information may be distorted. In a similar vein, for associative consortia it is more difficult to disentangle the responsibilities of each municipality in case of poor performance in the management of the service.
The second control concerns the type of political leadership in the local councils, measured by the dummy variable LWPOL. In this case, as well, the political variable is included by itself and in terms of interaction with the level of corruption. The underlying ideas is that local administrations animated by a left-wing political orientation might be more spending-oriented, but at the same time they may be less affected by distorting corruption effects (δCORR_LW is expected to exhibit a negative sign). To that regard, Hessami (2011) finds cross-country evidence that corruption in the public sector is more likely to prevail when right-wing parties are in power. She interprets her results by considering that:"members of right-wing parties are more likely to originate from an entrepreneurial background and their party platforms more strongly represent the interests of businessmen" (p. 2), so that they often (more often than left-wing politicians) end up in a trustful, reciprocal relationship with representatives of the private sector, a link that can also be used to foster illegal activities such as corruption. Moreover, Jimenez and Garcia (2012) find, in a large sample of Spanish municipalities that, after a politician is charged in a local corruption case, the voting share of left-wing parties is reduced by 2-3 percentage points, while right-wing coalitions even increase their share in subsequent elections. Therefore, right-wing voters appear to be much more loyal than left-wing voters, so that left-wing parties have much more to lose if caught involved in corruption activities.
2.4	Results
The one-step total cost frontier (5), combined either with the inefficiency model (6) or (7) or (8), is estimated using maximum likelihood technique. As a normalization strategy, we have divided all continuous variables (cost, output, input price, accountability and corruption measures) by their sample geometric mean.
 This allows directly interpreting first order parameters as cost elasticities at the local approximation point. Table 2 displays the estimated parameters. All first orders parameters of the cost frontier are strongly significant and have the expected positive sign. Output parameters βD and βR indicate that a 1% increase in MSW disposed or MSW sent to recycling results, ceteris paribus, in a 0.753 to 0.767% or 0.243 to 0.253% increase in costs respectively. Scale economies at the sample mean can be computed as the inverse of the sum of output elasticities. In this case, the adopted two-output cost frontier specification yields values around unity in all the models, thus suggesting that the average municipality exhibits constant returns to scale. The estimates of labor and capital price elasticities are given by parameters βL and βK. According to Shephard's lemma they equal the optimal labor and capital cost shares at the local approximation point. The share of the factor (i.e., fuel) used as numeraire in (5) can then be obtained residually.
All the three models estimate a labor cost share (about 45%) higher than the capital cost share (between 10% and 14%) and about the same as the fuel cost share (between 41% and 45%). This seems reasonable and in line with the typical cost structure in this service. Second-order parameters give flexibility to the functional form, allowing to estimate pointwise output and input price elasticities. In particular, the parameter βDR is negative and significant, suggesting cost complementarities in the joint provision of disposal and recycling services.
Turning to cost inefficiency, Table 2 shows that the coefficient of the accountability index (δACC) in Model 1 is negative and highly statistically significant. Greater propensity to participation by citizens -- and therefore less opacity in the relationship between citizens and decision-makers -- can substantially reduce cost inefficiency. This is in line with Besley and Burgess (2002), as well as with a large anecdotal evidence pointing at the notion that a greater pressure by public opinion is able to route managers and policy-makers towards more efficient decisions.
Tab. 2 - Cost frontier estimates.

By including the corruption variable (Model 2), the magnitude of δACC is reduced, although it remains negative and highly statistically significant. As expected, the corruption index parameter (δCORR) is instead positive, suggesting that more widespread bribing practices negatively affect the efficiency performance of MSW services. On the whole, this leads support both to the baseline version of our theoretical model, and to its enriched version that includes corruption.
Model 3 explores in greater details the effects of accountability and corruption. In this case, the parameter δACC measures the impact of the degree of accountability in the base case in which waste is collected directly by individual municipalities or through inter-municipal consortia, while the parameter of the interacted term (δACC_CORP) should be interpreted as the incremental effect due to the presence of limited liability companies. By itself, the corporatization of waste collection generally reduces cost inefficiency (δCORP = -0.127). This result is in line with the empirical evidence about the positive effects of corporatization on the performance of local public services provision (Cambini et al., 2011)  The marginal impact of accountability in the case of service supply through distinct business organizations is very significant (δACC_CORP = -0.469) while δACC is not statistically significant. The effect of accountability if corporatization occurs may be computed as δACC + δACC_CORP, yielding a coefficient equal to -0.508 (s.e. = 0.165), which is statistically significant at 1%. This means that accountability reduces cost inefficiency only if the service is managed through the establishment of independent companies, while the presence of associations of municipalities or of direct in-house management blur the potential benefits of a higher transparency.
Similarly, we analyze the differential prevalence of corruption across different political majorities. The parameter δCORR_LW represents the incremental cost inefficiency due to corruption under left-wing political guidance. In Model 3 δCORR still remains positive and highly statistically significant, while the interaction term δCORRLW is inefficiency-reducing. The resulting effect of corruption in municipalities led by left-wing local councils is equal to 0.201 (s.e. = 0.091) and is statistically significantly different from zero at 5% level (p-value = 0.027). This implies that in municipalities ruled by right-wing parties and by independent parties ("civic lists") waste collection services suffer more from cost inefficiency due to corruption. The impact of corruption is twice as large as that recorded for municipalities ruled by left-wing parties. The behavior of left-wing municipal councils is, however, more spending-oriented (δLW = 0.136).
The last rows in Table 2 show the statistics for λ coefficient, which is defined as the ratio between the standard deviation of the inefficiency term (σu) and the standard deviation of random noise. The values are statistically significant at 1% level, indicating that the inefficiency term has a significant contribution on total variation of the composed error. Then, the likelihood ratio tests of the unrestricted Model 3 (U) against the restricted (R) Models 1 and 2 indicate that including a large set of explanatory variables of expected inefficiency would be preferable.
Using equation (4), we compute the marginal effects on estimated cost efficiency for our preferred specification (Model 3). Results are displayed in Table 3, which provides a measure of the marginal improvement in the efficiency level that can be achieved by reducing corruption or increasing accountability.
Tab. 3 - Marginal effects on estimated cost efficiency.

The theoretical maximum cost efficiency (frontier level) is equal to 1: therefore, the efficiency level can be also interpreted as the percentage of efficiency achieved with respect to the maximum. Since the explanatory variables are in logarithm, the magnitude of the values in Table 3 can be interpreted as follows. In the cases where the services are provided by limited liability companies, increasing accountability by 10% would move the efficiency level towards the frontier by approximately 0.8%. Furthermore, decreasing corruption by 10% would increase the efficiency level, on average, by 0.64%, with a more remarkable impact for not left-governed municipalities (0.76%).
Figures 1 and 2 depict the relationship, based on Model 3, between marginal effects of accountability and corruption and the conditional expectation of cost efficiency. Figure 1 shows that the effect due to a marginal improvement in accountability is enhanced when estimated efficiency decreases. This means that the effort to induce less opacity in the relationship between citizens and decision-makers would be more advantageous if the level of efficiency is lower. In a specular way, Figure 2 shows a general tendency of corruption to worsen cost efficiency, especially for those municipalities not leaded by left-wing parties and already suffering from higher inefficiency (i.e low levels of cost efficiency, particularly if below 0.7).

Fig. 1 - Relation between marginal effect of accountability and estimated cost efficiency.

Fig. 2 - Relation between marginal effect of corruption and estimated cost efficiency.
2.5	Impact of accountability and corruption on costs
In this section we provide evidence on the impact of accountability and corruption changes on cost variation. Based on the cost frontier model, the over-cost measure (g) could be determined as the ratio between the estimated inefficiency term, uit, and the predicted optimal cost, c(yit,pit;β). Since the inefficiency term has been modeled as a function of several exogenous factors, the over-cost rate will also depend on such factors, i.e. g≡g(z). A variation in external factors, therefore, will bring about a change in the rate itself. Such difference can be expressed as:
	(9)	
Where: ∂CE/∂z is the marginal effect computed in (21). In order to evaluate the effect of changes of z-factors in relation to the actual observed cost, we formulated (26) as follows:
	(10)	
Figures 3 and 4 illustrate the potential cost change due to a reduction or expansion of accountability and corruption levels, respectively, up to the maximum/minimum and first/third quartile values observed in the sample.

Fig. 3 - Simulation of % changes of costs associated with changes in accountability (only limited liability companies, CORP = 1).

Fig. 4 - Simulation of % changes of costs associated with changes in corruption.
A reduction in accountability to the minimum level results in a cost increase up to approximately 15% of the observed cost (10% if first quartile level is considered). On the other hand, an expansion of the level of accountability to the maximum (or to third quartile) would allow a cost saving of up to 20%, with a median value slightly less than 5%, corresponding to approximately 300,000 euro in absolute terms. Given the average population of municipalities in our sample, this means an average impact of about 8.5 euro per inhabitant: if extended to the whole Italian population, the total cost savings would be around 500 million euro.
A more widespread corruption (to the maximum level) would increase costs up to 10% (5% when considering the third quartile) in the presence of local governments with left-wing political orientation and up to 17% (7%) in the group of not left-wing observations. By contrast, programs aimed at curbing corruption would allow, in the not left-wing group, cost savings up to 25% (10%) if the first quartile is considered), with a median value of 10%, corresponding to approximately 500,000 euros, i.e. 14 euros per inhabitant. These figures are roughly twice as those for the group of municipalities ruled by left-wing political parties, and corroborate the previous evidence concerning a lower permeability of the latter to the corruption plague.

Fig. 5 - Simulation of % changes of costs associated with changes in accountability and corruption. Breakdown by geographical region.
Figure 5 illustrates cost change simulations for the three main macro regions of the country The results show a greater sensitivity of Southern Italy to policies designed to improve social conditions in terms of corruption and accountability, as well as to a worsening of the level of corruption. For instance, a reduction in corruption up to the lowest observed value would imply a median cost saving of 530,000 (300,000) euros, corresponding to about 13.6 (8.5) euros per inhabitant, for municipalities located in the South (in the North, respectively) However, a deterioration in the accountability level would have a differentially larger impact in Northern and Central Italy, where the level of participation by citizens is, on average, higher.
Finally, in Table 4 we present cost simulations for a set of large municipalities (with more than 300,000 inhabitants). With reference to the two mostly populated Italian cities, Rome and Milan, a large reduction of the degree of corruption is expected to result in a relative cost saving of 10-11%, equivalent to around 18-20 euros per inhabitant. The second largest Southern city, Palermo, looks like the municipality which is mostly affected by changes in the degree of corruption. In the same vein, an improvement in the level of accountability in the two most populous cities is shown to induce a relative cost saving ranging between 2.4 and 2.6%, equivalent to a saving of 4-5 euros per inhabitant. The major benefit would concern, in this case, the Southern municipalities (Palermo and Bari), generally affected by less transparency of the decision making process.
2.6	Robustness checks
In this section we address some identification issues, such as the potential endogeneity of CORRUPT and the omitted variable bias, that could affect the validity of the above reported results. Following Dal Bó and Rossi (2007), we argue that using corruption data at the provincial level and municipal-level data from one particular industry should reduce potential endogeneity problems. In fact, while it is likely that existing corruption in a province has an impact on the cost efficiency of a subset of firms such as our waste management providers, it is less likely that the inefficiency of the latter will affect the province's overall corruption level. Moreover, in order to check whether our results are robust to changes in the modeling of the expected value of the inefficiency term, we estimate several models including additional control variables, such as geographical dummies (DNORTH and DSOUTH), aiming at capturing the extent to which the location in the North or the South of the Country has, in itself, a differential impact with respect to the omitted class represented by Center Italy, a time trend (TIME) and a different corruption index (CORRGP), in order to make sure our results are not an artifact of a particular measure of corruption.
Tab. 4 – Impact of accountability and corruption on costs for some large municipalities.

This alternative measure, which has been proposed by Golden and Picci (2005), is available for all Italian provinces and reflects "the difference between the amount of physically existing public infrastructure (roads, schools, hospitals, etc.) and the amount of money cumulatively allocated by government to create this public works" (Golden and Picci, 2005, p. 37).
Tab. 5 - Robustness check of cost inefficiency determinants.

The underlying idea is that corruption raises the costs of building public infrastructures, so that CORRGP is computed as the (logarithm of the) ratio between the building cost and the actual value of public investment. As recognized by Golden and Picci (2005), the measure captures some inefficiencies as well as various illegal activities that comprise genuine corruption. However, the fact that public sector costs were found to vary geographically in ways quite different from private sector costs "offers persuasive, if indirect, confirmation that the measure of corruption we create is valid, reflecting the extensive graft and fraud that are especially common to public sector contracting, rather than mere inefficiencies." (p. 38).
The geographical dummies are not generally significant (with the exception of model A in which DSOUTH assumes a positive value, thus suggesting a higher refuse collection costs for Southern municipalities), while the time trend is negative and significant at the 1% level across all the models, indicating a cost reducing technological progress.
The results confirm the cost-reducing impact of the degree of accountability in the cases where solid waste services are provided by corporations (δACC_CORP) ranges from -0.180 to -0.341 and is always statistically significant at the 1% level). Moreover, in all models, corruption contributes to deteriorate cost efficiency, even when it is measured by CORRGP, either included individually or along with CORRUPT. Models C and D confirm that the index of corruption adopted in the baseline model is still significant even after controlling for a variable, i.e. CORRGP, reflecting cost over-charge ratios. The dampening effect played by the specific left-wing political orientation (i.e. the negative and significant sign of δCORRLW and δGPLW), is confirmed except for Extended Model D, while LWPOL still exhibits a positive and significant coefficient, thereby underpinning the previous evidence that municipalities ruled by left wing local councils have a more marked attitude to increase expenditures. Finally, δCORP holds its negative sign and is statistically significant in all specifications except for Extended Model A.
3	CONCLUSIONS
The aim of this paper is to analyze empirically how accountability of public policy making, on the one hand, and corruption, on the other hand, impact on efficiency in the provision of a typical local public service, such as solid waste collection and disposal.
Our predictions are tested using a rich dataset on solid waste management services provided by Italian municipalities for the years 2004-2006. The results of our cost frontier estimates show that both accountability, measured by newspapers' readership and electoral participation, and corruption, measured using official data about the criminal activity existing in the area where the refuse collection service is provided, matter and exhibit a statistically significant impact (negative for corruption, positive for accountability) on efficiency levels. In addition, we show that the effects of accountability decline or even disappear when municipalities provide the service in-house or by adhering to intermunicipal consortia, which appear to be less efficient ways of organizing the activity, as compared to entrusting it to a limited liability company. Finally, we find that, while municipalities ruled by left-wing parties exhibit higher inefficiency levels, they are also those in which the impact of corruption on inefficiency is lower.
Our results are robust to the introduction of further explanatory variables of the mean value of the inefficiency term and to the measurement of corruption through the missing-expenditure index introduced by Golden and Picci (2005). Overall, our findings suggest that fighting corruption and making the behavior of managers of local public utilities more accountable have non trivial effects on the costs of collecting solid waste, especially for the Southern regions of the country. Our simulations for six Italian major cities show that costs can decrease in the range of 3-14%, if corruption declined to the minimum value observed in the sample, while they can decrease in the range of 2-11%, if accountability increased up to its maximum value.

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Contact information
Graziano Abrate
University of Piemonte Orientale and HERMES
Email: graziano.abrate@eco.unipmn.it

Federico Boffa
University of Macerata and Institut d'Economia de Barcelona
Email: federico.boffa@unimc.it
 
Fabrizio Erbetta
University of Piemonte Orientale and HERMES.
Email: fabrizio.erbetta@eco.unipmn.it

Davide Vannoni
University of Torino and Collegio Carlo Alberto.
Email: davide.vannoni@unito.it