Coproduction and Equity in Public Service Delivery

Q 1 Figure 2 Theoretical Model and Its Operationalization

societal perspective, one should compare the costs of increasing pub- lic sector input with the costs of the program and the costs imposed

S 2 S 1 Service user input

on service users by their increase in input.

Figure 1 Mix of Regular Producer and Service User Input

Th e question, then, is how to design a program that counteracts the inequities that may arise from coproduction processes. Figure 2

the horizontal axis displays the amount of illustrates this article’s discussion of that service user input (S), and the vertical axis the

Th e question, then, is how to

question. Th e upper part of fi gure 2 dis-

amount of regular producer input (R). Th e design a program that counter- plays the theoretical model, including the

isoquant lines (Q) show quantities of output

assumed causal eff ects. Th acts the inequities that may arise e lower part displays

for diff erent combinations of inputs. If the the operationalization and empirical test inputs from public employees and service

from coproduction processes.

(addressed in the next section). users are complementary, the isoquant lines are curved, as illustrated in fi gure 1. If the two inputs are perfect

Th eoretically, the starting point is the eff ect of service user input on substitutes, the isoquant lines will be straight. Th e optimal mix of

outcomes: the fundamental idea in coproduction is that the produc- inputs depends on the cost of regular producer input compared to

tive eff orts of service users have an eff ect on the outcome of services citizens’ costs of coproducing.

(Parks et al. 1981). Th is is illustrated by the causal arrow between service user input to coproduction and service outcome in fi gure 2.

In relation to service outcome, the general assumption is made that S 1 , the output will be Q 1 . However, disadvantaged service users who service users prefer an increased and better service outcome over a

In fi gure 1, with regular producer input at R 1 and service user input

are constrained and thus only deliver input corresponding to S 2 will

diminished service outcome.

only obtain output Q 2 , even if regular producer input is still R 1 . So

even when service users are off ered the same public service, inequi- Second, it is assumed that the level of service user input to copro- ties may exist because of diff erent service user input to the copro-

duction is dependent on, among other things, the knowledge and duction of these services.

other resources of the service users (see fi gure 2). Th ere are several reasons for this. Some types of coproductive eff orts require service

Th ere are at least two ways to counteract this. One is to increase users to have certain knowledge on how to coproduce. For instance, regular producer input and target it at disadvantaged service users,

a patient may do physical training after surgery to recover faster

who contribute a low amount of input themselves. However, assum- and better. Yet if the patient does not know the right exercises and ing complementary inputs and that we are situated on the steep side how to perform them, he or she is not able to eff ectively coproduce. of the isoquant (which would often be the case for low service user

Furthermore, the eff ort that service users are willing to invest in

coproduction is likely to depend on the benefi t they expect from regular producer input. In fi gure 1, that would be an increase from

input), moving from Q 2 to Q 1 requires a relatively high increase in

that eff ort. For example, the better the patient’s understanding of R 1 to R 2 .

how to contribute to the recovery process—and the better his or her understanding of the relevance of self-contribution—the more

Th e second option would be to lift the constraints that prevent serv- the patient is willing to provide a high level of input. Additionally,

many kinds of coproduction are more eff ective if service users have program with that aim, if eff ective, would reduce inequities of serv-

ice users from increasing their input from S 2 to S 1 . A coproduction

specifi c, tangible resources. For example, a patient may need specifi c ice outcomes by helping disadvantaged service users increase their

training instruments in order to coproduce eff ectively and obtain productive eff orts and thereby increase their outcomes. Th is may

the best possible outcome. (Similar points about the importance of also be a more economically effi cient strategy compared to directly

abilities to coproduce have been made by Alford 2002; Percy 1984; increasing regular producer input (i.e., increasing R in fi gure 1).

Rosentraub and Sharp 1981.)

From the perspective of the public sector budget (or a nonprofi t organization that fi nances the coproduction program), this would

Empirical studies have found that low-SES service users coproduce

be the case when the costs of increasing the regular producer input less than high-SES service users (see, e.g., Guryan, Hurst, and are high relative to the costs of the coproduction program. From a

Kearney 2008; Percy 1987). Th is can hardly be explained by lack

706 Public Administration Review • September | October 2013 706 Public Administration Review • September | October 2013

that a program must provide to enhance service user input must be eff orts eff ective. Th e lack of economic resources among low-SES

tailored to each specifi c case.

service users reduces their opportunities to buy materials that would help them coproduce their own or their family’s health, education,

In collaboration with a local government in Denmark, a fi eld experi- and so on (Jakobsen 2013; Warren, Rosentraub, and Harlow 1984). ment was conducted to examine coproduction and equity in rela- Lower levels of education may reduce service users’ understanding

tion to education. Specifi cally, the experiment focused on publicly of the relationship between their own contributions and ultimate

provided language support for immigrant preschool children. As

outcomes. Th is variance in service user knowledge and resources and illustrated in the lower part of fi gure 2, the coproduction program its relationship with service user input (see fi gure 2) is expected to

was operationalized as a suitcase program (described further later), explain much of the inequity in outcomes found empirically.

providing parents with information and basic knowledge about second-language development and materials for their coproduction

Th ird, following the foregoing arguments, this article argues that of this skill. Th e program was aimed at reaching disadvantaged par- in order to increase equity and service outcomes simultaneously,

ticipant families and lifting potential constraints on their coproduc- coproduction programs should aim to lift the constraints on low-

tion of their children’s language development in order to increase SES service users’ input by providing knowledge and materials

educational outcomes.

relevant for their coproduction. Obviously, coproduction strategies that aim to increase and improve service users’ coproductive eff orts

Examining the causal eff ect of coproduction programs empirically, depend on the ability of public organizations to eff ect such eff orts.

and how the eff ect varies for high- and low-SES service users, entails

a number of methodological challenges. Th e fi rst issue is the prob- users’ coproduction indicate that this is in fact possible. For exam-

A number of studies outlining various ways to infl uence service

lem of endogeneity. Service users are almost never selected randomly ple, Marschall (2006) and Ostrom (1996) show that schools’ eff orts

into programs, which produces bias in comparisons of service users to involve parents have a positive eff ect on parents’ input to school

who have been exposed to an intervention and those who have not. services. Other examples can be found in John et al. (2011).

Second, a government’s decision to initiate such programs is often aff ected by the existing level of coproduction, which produces two-

Against this backdrop, a fi eld experiment was conducted to inves- way causation. Additionally, an empirical examination requires a tigate the distributional consequenses of coproduction—and more

relatively large study population that varies with regard to SES and specifi cally, whether improving both effi ciency and equity in service

includes solid measures of the service outcome and SES. To meet outcomes is possible through a coproduction program targeted at

these challenges, a randomized fi eld experiment was used, which increasing service user participation in coproduction.

enables circumvention of the endogeneity problems but also use of fi eld data. Th e next sections describe the coproduction program, the

The Field Experiment

experimental design, and the data.

Coproduction of education is an illustrative example of the impor-

tance of service user input for service outcomes. 1 Family input—

The Coproduction Program

especially the early family environment—plays a crucial role in Th e coproduction program was rather simple. Each family in the

a child’s education (Cunha et al. 2006; Esping-Andersen 2002; program was off ered a suitcase containing various children’s books, Rowe and Goldin-Meadow 2009). Th erefore, parents are important

games, and a tutorial DVD about language development tech- coproducers of their children’s educational outcomes (as are the

niques. Even when parents speak very little Danish themselves, children themselves), and there are good reasons to consider parents’ they can contribute substantially to their children’s second-language coproduction eff orts in educational services as a form of service user

learning by improving their children’s language profi ciency in input (for discussions of coproduction of education, see Davis and

general (Collier and Th omas 1989). Th e content of the suitcase was Ostrom 1991; Ostrom 1996).

developed by experts in second-language learning. Education is also a good example of coproduction that features a

Th e suitcase was introduced to the families in April 2009 by the great diff erence between low- and high-SES service users in terms

employees at the child care centers, and the employees used it in of the amount and quality of service user input. Existing research

their ongoing communication with the families. Th e program did shows that low-SES parents spend less time and communicate less

not include investments or strategies aimed at increasing child care with their children than high-SES parents

employee input, but it did aim to facilitate a (Bonke and Esping-Andersen 2011; Guryan,

better mixing and linking of employee and Hurst, and Kearney 2008; Rowe and Goldin-

service user inputs. Th e program was gener- Meadow 2009). Th is diff erence can partly

Th us, education is an area in

which public organizations

ally well received by children, parents, and

be explained by low-SES families having

might adopt constraint-lifting

employees.

less knowledge about skill formation (Rowe

strategies when employing

2008). Th ey may also be constrained by lack One possible challenge is that families and of materials, for example, children’s books.

service user input in service

child care employees may change their Th us, education is an area in which public

production in order to improve behavior because they know they are being

organizations might adopt constraint-lifting

both educational outcomes and examined (the Hawthorne eff ect). When

strategies when employing service user input

starting the program, the families were noti- in service production in order to improve

equity.

fi ed that the program was conducted by the

Coproduction and Equity in Public Service Delivery 707 Coproduction and Equity in Public Service Delivery 707

Table 1 Summary Statistics of Control and Treatment Groups

emphasis was placed on the research element. Hence, the treat-

Control Coproduction

ment was organized and delivered by the government as a normal

Group Program

government program, which reduces any potential researcher eff ect

Children

52.6 considerably. 52.6

Age (months)

Girl

No. of months in child care

The Experimental Design

No. of days hospitalized

Th e families in the study population were randomly assigned to

Western origin

either a treatment group, which was included in the coproduction 89.1%

Non-Western origin

Lebanon or Syria

program, or a control group, which was not exposed to the pro-

Iraq, Iran, or Kuwait

gram. Th e random assignment prevents selection bias and two-way

Turkey

causation. Furthermore, the study population varied considerably

Somalia

with regard to SES. Th 5.7% is enabled examination of the equity question

Other African countries

Afghanistan, Pakistan, or India

by evaluating the program’s eff ect at diff erent levels of SES.

Th e study population consisted of fi ve-year-old children born in 2004,

Delayed school entry

enrolled in public child care, and learning Danish as their second Families

Single parent

language. In all, 284 children from 61 child care centers were included

Household income (1,000 DKK)

in the study, most of whom spoke Arabic as their fi rst language.

Rented housing

No. of people in household

To avoid experimental contamination (the dilution of the treat- 111.6

No. of days without job in 2006, mother

No. of days without job in 2006, father

ment because control group subjects are exposed to it; see Donner

Education

and Klar 2000), a cluster randomization was used to construct

Mother has no registered education

the experimental groups. Th e child care centers were organized in

Mother went to primary school (grades: 1–9)

clusters of one to fi ve centers. Th 27.5% e study included 27 such clusters,

Mother has education beyond primary school

Father has no registered education

which were stratifi ed and randomly assigned to either the treatment

Father went to primary school (grades: 1–9)

group or the control group. 2 Summary statistics of the experimental

Father has education beyond primary school

groups are presented in table 1, which shows that the assignment

No. of convictions, father and mother

Occupation, procedure generally resulted in a balanced set of experimental father

White collar

groups. No more signifi cant diff erences are observed than would be

Blue collar

expected by chance.

Occupation, Th mother e analysis applies the intention-to-treat principle (see Hollis and

White collar

Campbell 1999). Hence, the children are analyzed in the experi-

Blue collar

mental groups in which they were randomly placed, regardless of

Out of job

any shifting between groups, leaving child care before the tests, or

Other

use of the suitcase. Th Child care centers is is done to estimate the eff ect as it occurs in

No. of children

the actual service delivery setting, including all possible implemen-

Percentage of children with Danish as second

tation issues, and to avoid self-selection bias.

language

Budget for targeted language support (1,000

Th DKK) e theoretically assumed relationships between parental resources

Notes: * p < .05; ** p < .01, two-tailed signifi cance tests of the differences

and input to coproduction were not measured (the dotted boxes in

between the control group and the treatment group. Random effects models are

fi gure 2). What was tested is the observable implication that if the

used to conduct signifi cance tests.

coproduction program has an eff ect on disadvantaged parents’ input, Source: Danish Civil Registration System. we should fi nd that the intervention group performs systematically better than the control group—especially among the disadvantaged children. In other words, the diff erence between the control and

language consultants from the elementary school system and not the intervention groups does not express the absolute gain in language

child care employees who have been providing language instruction, development. Parents in the control group also coproduce, and their

which provides a more objective test measure. Th ree tests are used, children experience progress in their language development. Th e each providing a score indicating language profi ciency. Th e children

diff erence between the treatment and control groups represents the were tested approximately 10 months after the intervention was marginal gain in service outcomes produced by the intervention.

initiated.

Data on Outcomes and Parental Background

Th e municipality combines the tests into a single categorization Th e service outcome is operationalized by language tests conducted

that determines the children’s school process. Th is is an important at preschool exit, before the children enter primary school (see

outcome measure: children with critically low language profi ciency fi gure 2). Th is is standard procedure in the municipality. Th us, the

are enrolled in special classes before entering the regular school study did not introduce any tests for research purposes, which also

system. Only 2.8 percent of children from the child care pro- reduces a potential Hawthorne eff ect. Th e tests are conducted by

grams enter this track (post-treatment statistic). We examined the

708 Public Administration Review • September | October 2013

Table 2 Descriptive Statistics of the Individual Language Tests (test score

their past education). Data on household income were also obtained

points)

from the Civil Registration System.

Individual Tests

Mean of

Standard

Observed

Test Score

Deviation of Test

Test Score

Findings

Points

Score Points

Range

Table 3 shows the eff ect of the coproduction program on the three

Test I

(language comprehension,

language tests. All models are estimated by random-eff ects regres-

semistructured dialogue)

sions using the child care center as the grouping variable (see rec-

Test II

ommendations of Green and Vavreck 2008). Th e fi rst two models

(sentence construction and infl ectional forms)

include test I as the dependent variable. Test II is the dependent

Test III

variable in models III–IV and test III is the dependent variable in

(vocabulary sophistication)

models V–IV. Models I, III, and V only include the experimental

Note: Post-treatment statistics including both the control and treatment

group as independent variable (1 = treatment, 0 = control) to test

group.

the overall eff ects. As models I, III, and V show, the coproduction program has no signifi cant average eff ect on any of the tests.

program eff ects on (1) each of the three tests and (2) the propor- However, in accordance with the purpose of facilitating coproduc- tion of children subsequently enrolled in special classes. Table 2

tion that decreases inequity, the program was primarily designed to summarizes the tests.

reach disadvantaged families. Th erefore, it is likely that the program aff ected this group of families but not the more advantaged families.

Th e educational levels of the children’s mothers were used to deter- Hence, models II, IV, and VI examine the eff ect for diff erent levels mine whether the children belonged to an advantaged or disad-

of maternal education by including interaction terms for the experi- vantaged family. Parents’ education is generally a very important

mental group and mother’s education. Th e constitutive term of the predictor of children’s educational chances (Cunha et al. 2006),

experimental group estimates the eff ect of the coproduction pro- including among children learning Danish as their second language

gram for families in which the mother has no registered education. (Egelund, Nielsen, and Rangvid 2011). Additionally, an analysis was conducted using household income as an alternative indica-

In model II, the program has a statistically signifi cant eff ect of 0.86 tor of SES. Th is produced similar results to the maternal education

( p < .01) for children whose mothers have no registered education. 3 measurement.

Th e overall standard deviation of test I is 1.38, and the treatment eff ect therefore corresponds to about 0.6 standard deviation of the

Data on maternal education was obtained through the Danish Civil dependent variable. Th is eff ect is substantial in size. Th e eff ect is Registration System and coded as a three-category variable (sum-

about as large as the diff erence between having a mother with lower mary statistics of education are shown in table 1). Th e highest level

secondary education and a mother with no registered education of education consists of those who have education beyond lower sec- (this diff erence is 0.83 in the control group). Furthermore, the ondary school (i.e., beyond the ninth grade). In the middle category eff ect is larger than the diff erence between having a mother with are mothers with a lower secondary education (fi rst to ninth grade).

higher education levels and a mother with lower education (0.51 for Th e lowest category consists of mothers without registered educa-

e group of children whose mother tion. Mothers in this category have no formal education from the

children in the control group). Th

has no education constitutes one-quarter of the study popula- Danish education system, and it was not possible to establish their

tion. Hence, the reason that a signifi cant eff ect is observed among formal education through surveys of immigrants (every second year, low-SES children but not for the entire population is that all of the the Civil Registration System surveys immigrants in order to register positive treatment eff ect is located in the low SES-group.

Table 3 Effect of Coproduction Program on Educational Outcomes

Test I

Test II

Test III

(Language comprehension,

(Sentence construction and

(Vocabulary sophistication)

semistructured dialogue)

infl ectional forms)

Model V Model VI Experimental group

Model I

Model II

Model III

Model IV

Control (reference) 0 0 0 0 0 0 Coproduction program

–.98 (1.50) .74 (1.78) Mother’s education None registered (reference)

0 0 0 Lower education

2.46 (.99)* Higher education

4.03 (1.13)** Coproduction program × Lower education

–1.40 (1.32) Coproduction program × Higher education

284 284 Number of centers

61 61 61 61 61 61 Notes: *p < .05, **p < .01. P-values test the one-sided hypothesis. Standard errors are shown in parentheses. Dummy variables on eight twin pairs are included but not

shown in the table. Random effects regressions are used to estimate the models (grouping variable: child care center). Dependent variables: Language profi ciency test scores.

Coproduction and Equity in Public Service Delivery 709

Th e eff ects of the program on tests II and III (see models IV and VI)

are positive for children whose mothers have no registered education, .18 as expected, but not statistically signifi cant. Finding a signifi cant

eff ect when examining test I but not when examining tests II and III .16 is not surprising. Th e reason is that the suitcase treatment is, in many .14

regards, aimed at improving language comprehension, which is cap-

tured by test I, while other elements are captured by tests II and III.

Th e eff ect of the program on the children’s school process was also examined. Th .06 e municipality categorizes the children according to

an overall assessment of their language test results, as described

earlier. Th is categorization has signifi cant consequences for children’s .02 school process. Children with critically low language profi ciency are

enrolled in special classes before entering the regular school system. Coproduction

Coproduction Control

program group program

No education

Lower

Higher

Table 4 examines whether the program reduced the proportion of

children sent to special classes. Model I examines the average eff ect

using a random-eff ects logistic regression. As shown in model I, the

Figure 3 Effect of Coproduction Program on Proportion of

coproduction strategy did reduce the group of children enrolled in

4 special classes ( Children Sent to Special Classes Contingent on Mother’s p = .01). When calculating the predicted probabili-

Education

ties (not shown), the eff ect of the program corresponds to reducing the special class category from 6.7 percent to 0.7 percent, which is a reduction of about 89 percent.

this group is compared to the treatment group of children whose mothers have no education (treatment, no education), a treatment

Th e strong treatment eff ect on the proportion of children enrolled eff ect of –2.85 ( p = .014) is observed. Th ere are no signifi cant treat- in special classes also proves that the coproduction program mainly

ment eff ects when examining children whose mothers have either aff ected children from disadvantaged families, as the risk of being

lower secondary or higher education (not shown). enrolled in special classes is negatively associated with mother’s education. To examine this further, model II in table 4 includes the

In order to provide a more intuitive presentation of the interaction interaction between the treatment and mother’s education. To avoid

between mother’s education and the treatment, fi gure 3 portrays interaction terms in the logistic regression, dummy variables are

the eff ect on the proportion of children enrolled in special classes included for the diff erent combinations of mother’s education and

contingent on maternal education. For children whose mothers the treatment.

have no reported education, the treatment substantially reduced the proportion enrolled in special classes (from about 17 percent to 0

Control group children whose mothers have no reported education percent). For children whose mothers have either lower secondary or (no treatment, no education) are used as a reference group. When

higher education, no substantial treatment eff ect is found. In sum, the results show a positive eff ect from the coproduction program

Table 4 Effect of Coproduction Program on Proportion of Children Sent to

on educational outcomes for children from disadvantaged families.

Special Classes

Sim ilar results were found in an analysis (not shown) in which

Model I

Model II household income was used as an indicator of advantaged/disadvan-

Experimental group

taged families.

Control (reference)

Coproduction program

Short-Term Return on Government Investment

Experimental group and mother’s education

Control, no education

0 a Th e coproduction program’s reduction in the proportion of children

Coproduction program, no education

requiring special classes also entails a reduction in the municipal-

Control, lower education

ity’s costs of education (which should be contrasted with the costs

Coproduction program, lower education

of the program). Table 5 shows the annual costs (in Danish kroner,

Control, higher education

Coproduction program, higher education

DKK) and returns of the coproduction program in a scenario where

the program is applied to the whole study population (all 284

children). 5 Th e calculation is based on the program eff ects found in

Number of centers

the previous analysis (model I in table 4)—that is, the eff ect on the number of children entering special classes.

Log likelihood

Note: *p < .05; **p < .01. P-values test the one-sided hypothesis. Standard er- rors are shown in parentheses. Dummy variables for each of eight twin pairs are included but not shown in the table. A random effects logistic regression is used

Th e mean costs per child in special classes (97,700 DKK) are much

to estimate model I (grouping variable: child care center). The penalized maxi-

higher than the mean costs per child in regular classes (62,484

mum likelihood estimation (Firth 1993) is used in model II to deal with the prob-

DKK). Th erefore, from a public sector investment perspective, there

lem of separation. To avoid interaction terms in the logistic regression in model II, we include dummy variables for the different combinations of SES and treatment

are good reasons to ensure that children’s language skills are devel-

groups (there are six combinations, so fi ve dummy variables are included).

oped to a level that enables them to enter the regular school system.

a Reference group.

Th e costs of the program are 1,340 DKK per child (380,560 DKK

710 Public Administration Review • September | October 2013

Table 5 Annual Short-Term Return-on-Investment Ratio

engaged in parent involvement activities, it may be more diffi cult

Cost of one child in the school system

for new coproduction programs to create a marginal eff ect in educa-

Mean costs of one child in special class (comprehensive

tion. In areas in which service user involvement is less pronounced,

language support)

the potential for eff ective coproduction programs may be greater.

Mean costs of one child in regular class

Th e theoretical model advanced in this study may provide guide-

Costs if no coproduction program was applied

Costs of special classes for the study population if no program

lines for the design of coproduction programs in other areas that

was applied

increase both effi ciency and equity, namely, by focusing on the

Costs of regular classes for the study population if no program

(lack of ) resources that may constrain low-SES service users from

was applied Total costs for school costs if no program was applied

coproducing.

Costs if the program was applied to the whole study population Costs of special classes if the whole study population was

Th is article does not contend that direct investments in service users’

exposed to the program

coproduction resources, rather than increasing regular producer

Costs of regular classes if the whole study population was

input, is always the best solution. Th is determination should be

exposed to the program

Total costs for school costs if the program was applied to the

based on an evaluation of the specifi c case, and a number of factors

whole study population

should be considered when assessing the generalizability of these

Total returns of the program

results to a given case. When regular producer and service user

Costs of the program Program costs per child

inputs are complementary and the service user input is low (i.e., a

Costs of the program if the whole study population received

scenario at the steep side of the isoquant in fi gure 1), the likelihood

program

that coproduction programs are the most effi cient strategy increases.

Net returns

Furthermore, the likelihood that coproduction programs are the

Return-on-investment ratio

1.57 most effi cient strategy increases when the costs of regular producer

Note: Amounts are in DKK. The calculation is based on two scenarios: (1) no

input are high relative to the costs of programs aimed at increasing

children from the study population were exposed to the program; (2) all children from the study population included in the analysis were exposed to the program.

service user input. Additionally, managers should consider whether

An annual return rate of 5% is added to the program costs to take opportunity

it is possible to aff ect service users’ coproduction resources and

costs into account.

whether managers have suffi cient knowledge about the kinds of resources that should be provided.

if the whole study population received the intervention), and the Finally, this study does not directly measure parental knowledge and estimated return-on-investment ratio is no less than 1.57.

resources or their eff ect on parental time spending. Parents were provided with both information and materials that support their

Th is study did not collect data on the cost of parental input, so the communicative interaction with their children, and it is therefore societal cost–benefi t analysis cannot be made. However, long-run

not possible to separate the eff ect of the two. However, the observ- cost–benefi t analyses of other child care programs, such as the Perry

able outcomes of this study correspond to the empirical implications Preschool Program (see, e.g., Heckman 2006), indicate that there

of the theoretical model, which lends support to the notion that may be substantial long-run gains from the examined program as

knowledge and material resources are important constraints on low- well. Th e present economic analysis is restricted to the short-run

SES service users’ coproductive eff orts.

eff ects.

Conclusion

Discussion of the Results

Despite the recently revived interest in service user coproduction Th e experimental design of the fi eld study avoids the methodo-

in public service delivery, less attention has been devoted to the logical challenges associated with investigating causal eff ects using

potential trade-off between governments’ reliance on it and equity fi eld data in citizen participation research. Consequently, it can

in service outcomes. Th is arises because disadvantaged service users

be stated rather confi dently that the coproduction program had a tend to coproduce less—partly because of resource constraints— causal eff ect on low-SES children. In the control group, a strong

than advantaged service users. To the extent that service user copro- relationship between maternal education and children’s educational

duction increases the quantity and quality of service, making service achievements was observed (see fi gure 3), which underscores the risk user coproduction an important part of public service delivery may of inequity in services such as education that rely on service user

increase inequity in service outcomes. For example, with respect coproduction. Th e coproduction program was able to break that

to education, recent research on parental investments in children’s relationship, thereby reducing inequities while effi ciently increasing

education demonstrates large diff erences between parents with high outcomes.

versus low SES.

Th e experimental study design, however, provides less evidence Th e identifi cation of such a potential trade-off should give rise to about the external validity of the fi ndings. Th e study was conducted

interest in the equity issue as it relates to research on coproduction within the area of education and child care in which service user

and to citizen participation in public service delivery in general. input is known to be of great importance and in which there is great Most of the recent wave of research on coproduction has focused variation between high- and low-SES service users. Th e potential

primarily on the potential of harnessing citizens’ coproductive for eff ective coproduction programs may be smaller in other areas

eff orts. Less attention has been paid to the potential eff ects (both in which service user input is less important for outcomes. On the

positive and negative) on equity that may result from an increased other hand, because most schools and child care centers are already

focus on coproduction.

Coproduction and Equity in Public Service Delivery 711

Th is study contributes a theoretical understanding of how copro- resources. Th is study tested a low-cost program providing parents duction of public services—in spite of the potential trade-off

with information and basic materials, and it had a great impact on mentioned earlier—could instead increase equity. Based on the

the most disadvantaged group of children and a high immediate argument that disadvantaged service users’ input to the coproduc-

return-to-investment ratio.

tion of services may be constrained by lack of knowledge and other resources needed to coproduce, this article argues that if coproduc-

Acknowledgments

tion programs are designed to lift such constraints, coproduction We would like to thank Aarhus municipality, especially Catharina strategies may increase both effi ciency and equity in public service

Damsgaard and Anette D. Knudsen, for excellent collaboration on delivery.

this project. We are also grateful to Søren Serritzlew for his numer- ous comments and suggestions. Furthermore, the project has ben-

Th e fi eld experiment presented here supports this claim. Th e pro- efi ted signifi cantly from comments provided by participants of the gram was aimed at lifting knowledge and resource constraints faced

European Group for Public Administration Study Group on Public by disadvantaged families. Th e results show

Governance of Societal Sectors (Toulouse, that the program signifi cantly reduced the

France, 2010), the Public Management group of children enrolled in special classes

Th e results show that the pro-

Research Association Conference (Syracuse by no less than 89 percent, with the largest

gram signifi cantly reduced the

University, 2011), the European Consortium eff ects found among children from low-

for Political Research Workshop on Citizens SES families. In other words, the inequities

group of children enrolled in

special classes by no less than 89 and Public Service Performance, and col-

leagues at the Department of Political Science reducing the costs devoted to special classes,

in educational outcomes were reduced. By

percent, with the largest eff ects

and Government, Aarhus University. We the strategy has an immediate return-to-

found among children from

also thank Dr. Michael McGuire and three investment ratio of about 1.57. Hence, from a

low-SES families.

anonymous reviewers for their comments and public sector perspective, the program is more

suggestions. Finally, we would like to thank effi cient than providing remedial or compensatory services for low-

the Danish Institute for Local and Regional Government Research performing children after the fact.

for funding this project’s data collection.

Th ese fi ndings have several implications for the literature on citizen

Notes

participation in service delivery and on coproduction in particu-

1. Th

e production functions commonly used in education research fi t very well

lar. First, they underscore the importance of the equity issue. In

with the subdivision of input to public sector and citizen inputs (see Hanushek

the control group, maternal education is highly predictive of child

educational achievements, even though all children were off ered the

2. Stratifi cation variables: (1) the children’s statistically predicted language profi -

same level of public child care service.

ciency at school start, (2) the child care employees’ attitudes toward language support, and (3) the centers’ share of immigrant children.

Second, the results clearly show that a coproduction program

3. Robustness analyses show results similar to table 3 if the unbalanced covariates

specifi cally targeted at lifting constraints in terms of knowledge and

are included in the model or an alternative cluster variable or diff erent estima-

tangible resources eff ectively benefi ts the most disadvantaged group

tion approaches are used.

of children. Th e results show that a coproduction program can

4. Robustness analyses confi rm the results.

improve equity in service delivery while, at the same time, improv-

5. 1 U.S. dollar equaled about 5.2 DKK, and 1 euro equaled about 7.5 DKK at the

ing outcomes. As discussed, however, the extent to which these

time of estimation.

results can be generalized to other service areas or other countries cannot be determined from these data.

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