This chapter presents cutting-edge approaches to monitoring and evaluating place-based policies. It shows how monitoring and evaluation can make these policies more effective. The chapter starts with showing why monitoring and evaluation are key to effective place-based policymaking. Second, it identifies the challenges. It then explores the framework conditions that need to be in place to support monitoring and evaluation. Finally, the chapter provides a practical guide for policy makers.
Place‑Based Policies for the Future
Abstract
Monitoring and evaluation are necessary to reveal the impacts of a policy.1 They compare the observed outcome that includes the impact of a policy with the counterfactual – what would have happened without the policy (Figure 5.1). Put differently, they compare the changes in outcomes for places, people or firms as a result of a certain policy with the changes in outcomes for places, people or firms with equivalent characteristics but where such a policy has not been implemented. Monitoring and evaluation can thus answer questions such as: what are the effects of a policy? Why does a policy work better in some places than in others? What made the rollout more or less effective?
Source: Authors’ elaboration based on Nathan, M. (2023[1]), “Things We Don’t Want to Know? Monitoring and Evaluating Place-Based Policies”, Background paper for the OECD-EC High-Level Expert Workshop Series on “Place-Based Policies for the Future”, Workshop 4, 7 July 2023, https://www.oecd.org/cfe/regionaldevelopment/place-based-policies-for-the-future.htm.
Monitoring and evaluation are different but complementary practices. Monitoring is the systematic collection of data and information to assess the progress and achievement of set policy objectives. It can also help identify and lift bottlenecks during the implementation. Evaluation refers to the structured and objective assessment of the design, implementation and results of a policy (OECD, 2020[2]).
Knowing what works best and why it works (relative to a counterfactual) can help expand successful place-based policies, including in other places, or avoid certain pitfalls of unsuccessful policies. Robust monitoring and evaluation to track and test policy impact is key, especially as spending on the rising challenges can be high and the needed rollout rapid.
Progress in monitoring and evaluating place-based policies is particularly timely for several reasons:
Persistent spatial disparities in income, wages, employment as well as in broader wellbeing, such as health and life expectancy, between cities and regions have created social discontent and political unrest as well as resurging interest in place-based interventions.
Evidence that some, but not all, place-based policies have played a role in reversing some cities and regions’ fortunes for the better in recent decades (Nathan, 2023[1]).
Recognition that global environmental challenges require a strong place-based approach (Chapter 4). The same applies to other rising challenges, such as demography or value chain insecurities. For example, in the US, the Inflation Reduction Act, CHIPS Act and Bipartisan Infrastructure Law have increased investment in high-tech, low-carbon manufacturing across the US, especially in historically poorer and Rust-Belt locations (Sullivan, 2023[3]).
Monitoring and evaluation have proved effective in improving place-based policymaking. For example, policy learning has improved the design and impact of EU Cohesion Policy over time. Various analyses of Cohesion Policy’s effectiveness have made it more sensitive to the economic structure of regions, their geographical characteristics and the administrative capacity of their central and local governments to devolve the funds (Berkowitz et al., 2023[4]).
Many place-based policies are not systematically monitored and evaluated, or evaluations are incomplete. Out of thousands of impact evaluations across a range of place-based policies, only few meet minimum standards on the counterfactual. Moreover, while around half of well-evaluated local economic development interventions are effective, the size of the effect is often unknown (Nathan, 2023[1]). It is thus important to understand the magnitude of policy impacts to determine which policies are most effective. But robust evaluation evidence of place-based policies is both hard to generate and to incorporate into policymaking structures.
The practical challenges of monitoring and evaluating place-based policies
Understanding the impacts of place-based policies is difficult because they often target multiple actors and sectors. Moreover, place-based policies are undertaken across central, regional and local government levels as well as across government departments. Several policies may thus overlap in the same place and timeframe. For example, in the UK, local economic development policy is distributed across the planning, business, employment, transport and housing functions of central and local governments, as well as in the Treasury (Nathan, 2023[1]).
The main challenge in identifying place-based policies’ causal effect is building a valid counterfactual. This is because the place where the policy happens and the place selected to provide the counterfactual may have underlying differences (Angrist and Pischke, 2009[5]). For example, EU Cohesion Policy typically targets less developed regions (Nathan, 2023[1]). If they are compared with richer regions, policy effects might be confused with the underlying differences.
Some outcomes, in particular wellbeing, are difficult to measure. Wellbeing outcomes are important to evaluate for instance because many of the policies needed to address climate change and biodiversity loss have local wellbeing benefits, notably health, that may not be included in GDP.
Many place-based policies also have long timeframes, which complicates their evaluation. For example, capital investments in transport infrastructure have timeframes for wider economic impacts of over 50 years (Nathan, 2023[1]). Data may also be limited at regional and local levels or not comparable, as place-based policy evidence draws on multiple fields with different terminologies and methods (Nathan, 2023[1]).
The institutional challenges of monitoring and evaluating place-based policies
Policy makers may lack incentives to conduct monitoring and evaluation (Nathan, 2023[1]). They may have an incentive to start new projects rather than figuring out whether past projects worked and may focus on making the ex-ante case for policies in order to get funding (Bravo-Biosca, 2019[6]). Moreover, there may be a political downside to discovering that a policy did not work (Mason, Nathan and Overman, 2023[7]). And even if policies work, evaluation results are difficult to communicate and promote. They are often technical and may not be timely, spanning beyond political terms. In Italy for example, Faggian and Urso (2023[8]) argue that three major reports (the 2009 Barca Report, the 2012 National Strategy for Inner Areas and the 2021 National Recovery and Resilience Plan) have reduced the scope of monitoring and evaluation over the years (Box 5.1).
In the 2009 Barca Report, monitoring and evaluation are interpreted as a collective effort towards more pluralistic, informed and democratic policy choices and solutions, based on experimentation and mutual ‘control’ among actors.
In the 2012 National Strategy for Inner Areas (SNAI), monitoring and evaluation are interpreted as an adherence to the planned timeline and outcomes. They focus on debate and assistance on critical issues, the access to a database of practices, sharing of progress in the set of chosen indicators and on the comparison with ‘ordinary’ policy actions.
In the 2021 National Recovery and Resilience Plan (PNRR), monitoring and evaluation seem to be conceived merely as a technical operation mostly aimed at financial reporting and accountability. Subnational levels of government do not appear among the most frequent entities involved in monitoring and evaluation and neither do their citizens and their needs.
Source:. Faggian, A. and G. Urso. (2023[8]), “Cohesion and Place-Based Policies Post-Emergency in the EU: Why Monitoring is More Important than Ever”, Background paper for the OECD-EC High-Level Expert Workshop Series on “Place-Based Policies for the Future”, Workshop 4, 7 July 2023, https://www.oecd.org/cfe/regionaldevelopment/placebased-policies-for-the-future.htm.
Governments, especially at the subnational level, often do not have the skills and resources to carry out robust monitoring and evaluation. Even commissioning policy monitoring and evaluation requires some capacity, including for contracting and oversight (Mason, Nathan and Overman, 2023[7]). The monitoring and evaluation of place-based policies is often underfunded.
National and local governments could mandate the creation of robust monitoring processes and the use of evaluation results for place-based policymaking, especially for large projects. For example, grant-giving bodies can set minimum standards for monitoring and evaluation as a requirement for receiving funding. Indeed, EU Cohesion Funds have such requirements (Nathan, 2023[1]). ‘Policy labs’ can also be an effective way to encourage monitoring and the use of evaluation evidence to improve policymaking, as highlighted by two examples from Spain and Washington, D.C. (Box 5.2).
A Policy Lab for monitoring and evaluating social inclusion policy in Spain
The Spanish Ministry of Inclusion, Social Security and Migration partnered with the Abdul Latif Jameel Poverty Action Lab (J-PAL) Europe - a research centre -to build a Policy Lab bringing rigorous evidence to social policymaking in Spain. The Policy Lab was created in 2020 to understand the effectiveness of 34 pilot social inclusion programmes, ranging from job search support to online tutoring, or childcare, launched under the Covid-19 NextGenerationEU Recovery plan. The government has committed to piloting and evaluating each programme through randomised control trials (RCTs) run in the new Policy Lab. The results will provide insights for social policy in Spain at the national and regional level prior to scaling up the most effective pilots.
The Policy Lab is for example monitoring and evaluating the impact of an online tutoring programme to improve mathematics learning outcomes and socio-economic inclusion among students with disadvantaged socio-economic backgrounds. To track and test programme impact, 6 000 students are randomly divided in five groups receiving different combinations of intensive online tutoring for mathematics, socio-emotional and mentoring support. These groups also differ in the size of student groups, to assess their optimal size. One group serves as control group, not receiving any type of support.
The Policy Lab’s monitoring and evaluation effort involves working across all levels of government and multiple implementing partners. Most do not have previous experience with randomised evaluation methods. J-PAL Europe staff and a team of Spanish and international researchers provide technical assistance in evaluation design and help translate the results into actionable and scalable policy advice. The Policy Lab’s approach could set a valuable example for how social policy is conducted in the future, in Spain and elsewhere.
The Lab @ DC evaluates and informs policymaking in Washington, D.C., United States
“The Lab @ DC” uses scientific insights and methods to evaluate and improve policies and provides analysis to inform policy decisions by Washington D.C.’s government. The Lab collaborates with government agencies to:
Design policy interventions that fit the local context, based on theory and evidence from academic and business research as well as analyses of administrative data.
Conduct evaluations, including RCTs as well as policy experimentation and monitoring, to assess how well certain policies work and how to improve them.
Promote a community of practice that enables cooperation with experts and stakeholders across government agencies, universities and community groups.
The Lab @ DC is currently running an RCT to assess whether discounted transit fares improve mobility and wellbeing for lower-income residents. More than two thousand lower-income residents were randomly assigned to one of three groups. For nine months, residents in group I pay a half-price transit ticket, residents in group II benefit from unlimited free trips, and residents in group III, the control group, have no discounts. The results will help understand how the discounts affect the number and type of trips to help shape future transit affordability programmes.
Sources: OECD (2023[9]), OECD-EC High-Level Expert Workshop Series on “Place-Based Policies for the Future”, Workshop 4, 7 July 2023. Alzate, D. et al. (2023[10]), “Creating a policy lab for evaluating social inclusion policy in Spain”, J-PAL Blog, https://www.povertyactionlab.org/blog/9-6-22/creating-policy-lab-evaluating-social-inclusion-policy-spain (accessed on 4 March 2024).; Washington, D.C. government (n.d.[11]), The Lab @ DC, https://oca.dc.gov/page/lab-dc (accessed on 4 March 2024).; The Lab @ DC (n.d.[12]), Can discounted transit improve mobility and well-being for lower-income residents?, https://thelabprojects.dc.gov/fare-subsidy (accessed on 4 March 2024).
Combining monitoring and evaluation with experimentation can strengthen their impact on policy effectiveness. Experimenting, testing and adopting a learning-by-doing approach can -if complemented with robust monitoring and evaluation - help adjust policies during implementation (Bravo-Biosca, 2019[6]). For example, Australia’s Latrobe Valley Authority has an industrial strategy to support places affected by forest logging closure, with “project control groups” and a community of practice to check compliance with project milestones, resolve issues and enable learning across projects (OECD, 2023[9]).
Monitoring and evaluation mandates should be combined with adequate resources. For example, local governments may need capacity to safely store, access and work with administrative microdata to evaluate place-based policies (Nathan, 2023[1]). Subnational governments need to hire and train public officials, even if the actual monitoring and evaluation activities are outsourced.
When to start monitoring and evaluating
Monitoring and evaluation should be built into the whole policy cycle, from the initial stages to the end. This is to follow policy steps fully and collect new data for the evaluation that are fit-for-purpose. This is especially important at subnational level where data may be less readily available or, if they are, of worse quality than at national level. Monitoring and evaluating place-based policies thus provides an opportunity to collect new regional and local data. Embedding evaluation thinking into the initial stages of policy design can also contribute to set clear policy objectives.
Where to start
Monitoring and evaluation of place-based policies begins with identifying the intervention logic: how a policy is expected to achieve its objectives for a place or the people or firms in it (Bates and Glennerster, 2017[13]; What Works Centre for Local Economic Growth, 2016[14]). This includes determining the inputs (e.g. the amount of money spent), policy actions (e.g. the consultation of citizens), outputs (e.g. the number of metro stops created), and long-term outcomes (e.g. increased accessibility to public services).
Ex-ante modelling can help choose between different policies. Evaluators refer to the modelling of possible policy effects before a policy is implemented as “ex-ante modelling”, while the assessment of actual policy effects after a policy is implemented is called “ex-post impact evaluation”. Ideally, ex-ante and ex-post evaluation are complements. Nevertheless, robust ex-ante modelling could substitute ex-post evaluation where governments may lack resources for complex evaluations (OECD, 2023[9]). In many OECD-wide reviews of place-based policies, ex-ante modelling appears to be more common than ex-post impact evaluations (Nathan, 2023[1]).
What to monitor and evaluate
Place-based policy monitoring and evaluation should examine broad policy outcomes, such as the reduction of poverty or inequalities, improved access to public services, the increase of competences, etc. Long-term outcomes should be wider in scope than short-term policy outputs, and several indicators may be needed to measure progress towards each single outcome (Faggian and Urso, 2023[8]). Effective monitoring and evaluation is different from reporting for accountability or budgetary purposes. Monitoring and evaluation should also take into account key general future priorities, such as reaching climate neutrality by 2050, protecting and recovering biodiversity and halting the degradation of land, even if the evaluated place-based policies are not designed to address these priorities specifically.
Place-based policy monitoring and evaluation should examine unintended consequences of policies, such as out-of-area negative spillovers. Monitoring and evaluation should also examine potential benefits on people, businesses or workers who are vulnerable, and risk being forgotten in policymaking and evaluation. In India for example, infrastructure investment such as highways has sometimes benefited places with stronger initial financial development, higher initial productivity, better access to finance and higher literacy rates compared to disadvantaged places and evaluation has discovered this bias belatedly (Dasgupta and Grover (2022[15]), Das et al. (2023[16])). Key guiding questions for monitoring and evaluating place-based policies can be:
Are only average effects assessed or also effects on vulnerable groups or individuals?
Are poor neighbourhoods or informal workers given consideration?
Are environmental impacts accounted for?
Does the evaluation use the most relevant data or only the data that is easiest to obtain?
How long to monitor and when to evaluate
Place-based policy monitoring and evaluation should examine outcomes over sufficiently long timeframes to avoid biasing results. For example, labour market policies to improve worker skills may take more time to produce benefits and may produce more long-lasting benefits than labour market policies encouraging workers to apply for more jobs. If the monitoring and evaluation period is too short, the evaluation may result in misguided conclusions. A longer evaluation period may however make the evaluation costlier and delay the availability of results.
Continuous monitoring and evaluation through sequenced feedback systems allow policy makers to track outputs and see provisional outcomes at multiple points in time. This can help build and maintain buy-in (Nathan, 2023[1]) and is especially important in very long-term Big-Push-style policies, like in post-unification Germany (Enenkel, 2021[17]) or New-Deal-era US rural development programmes (Kline and Moretti, 2014[18]).
Choosing between different impact evaluation tools
Randomised control trials (RCTs) are the gold standard of impact evaluation, and other statistical tools can ‘mimic’ them. RCTs are applicable to place-based policies that target specific people or firms. Ethical concerns arising from the random allocation of a policy to people or firms can be mitigated by designs that offer several varieties of a policy or that randomise its timing so that no-one is left untreated (Nathan, 2023[1]). RCTs may however be impracticable for policies that target places, especially infrastructure investment, because it would require randomly allocating infrastructure investment to places. This may be expensive and pose technical challenges. In particular, random sampling of a sufficiently large number of regions is often not possible. If RCTs are not applicable, the next best option is to exploit the ‘quasi-randomness’ in certain place-based policy designs and use statistical techniques to build a valid counterfactual (Box 5.3).
To assess the impact of a policy, it is important to compare it to the counterfactual outcome had the policy not been implemented (Figure 5.1). Since the true counterfactual is usually not known, many estimation strategies have been developed based on outcomes at the same time in other places.
For the evaluation of Cohesion Policy over the 2007-2013 period, for example, the EU Commission relied on two types of statistical techniques. One, called “regression discontinuity design”, compares the performance of regions that received support to the performance of similar regions in terms of economic conditions and trajectories that just failed to qualify for support (Berkowitz et al., 2023[4]). Comparing the performance of similar regions on either side of this ‘cutoff’ - the policy decision of which regions get support, and which do not - provides a reasonably accurate estimate of the Cohesion Policy’s impact.
The other technique, called “propensity score matching”, matches regions that received support with those that did not in terms of their relevant characteristics, such as those that might affect their growth performance and bias the evaluation of policy impact (Berkowitz et al., 2023[4]). Like regression discontinuity, comparing the performance of regions that received support with the performance of similar regions that did not get support provides another estimate of Cohesion Policy’s impact.
For large, one-off place-based interventions for which no counterfactual locations may be available, “synthetic control” designs can be used to build a control region from a weighted average of other locations (Nathan (2022[19]) for a recent example). Models, such as computable general equilibrium (CGE) models, macro-econometric models, or dynamic stochastic general equilibrium (DSGE) models can also be used to simulate a counterfactual on an ex-ante basis (Berkowitz et al., 2023[4]).
Many other tools are available, such as those presented in the UK Government Magenta Book ( (2020[20]), (2020[21])) and by the What Works Centre for Local Economic Growth (2016[14]). In practice, evaluating place-based policies will require using multiple methods depending on the features of policies and constraints on randomisation discussed above (Bates and Glennerster, 2017[13]).
Which data to use for the evaluation
Robust impact evaluation often requires using newly collected data from monitoring (Nathan, 2023[1]). Policy makers thus have an important role to play in setting up effective monitoring systems to collect detailed information on policy inputs, actions, outputs and long-term outcomes. Policy makers also need to ensure that this data is suitably checked and stored and easily accessible. Ideally the data should be freely accessible.
Digital technologies have expanded the potential of datasets that can serve evaluation purposes, subject to adequate privacy protection. First, large administrative microdata provide detailed information on people, households, firms and places over long time periods. Second, Big Data and new internet-based data sources are typically higher frequency and cover more dimensions than conventional administrative sources and can be used as a complement (Nathan, 2023[1]).
Who should monitor and evaluate, and who should be heard
Different types of evaluators are prone to different biases, which risk impairing effectiveness. For researchers and academics, career advancement often depends on publications more than on engagement with policy. Academic evaluations may thus focus on the research design’s validity more than on policy implications, which might limit usefulness to policy makers (Nathan, 2023[1]). On the other hand, policy makers may privilege evidence that applies across places even if it is of lower quality (Vivalt, Coville and Sampada, 2021[22]). Policy makers or researchers or bodies commissioned by the government may also find it difficult to be sufficiently independent (Sanders and Breckon, 2023[23]). Some countries are establishing independent impact evaluation centres, for example Australia’s Office of Impact Analysis. The latter produces evidence-based assessments of policies and supports government departments and agencies in the evaluation process (Australian Government, n.d.[24]).
Evaluators can work with local partners and interview the beneficiaries and implementers of place-based policies to understand the local context. It is also important to hear from ‘disenfranchised’ people as this might help measure to whom the benefits of policies accrue. How-to guides developed by Bates and Glennerster (2017[13]) and the What Works Centre for Local Economic Growth (2022[25]) can help policy makers monitor and evaluate place-based policies effectively, as well as act as proficient commissioners and users of evaluation evidence.
Communicating evaluation results
Evaluation results need to be communicated in a clear and actionable way so that policy makers and practitioners can use them. That is, research findings need to be translated into non-technical messages and policy implications. For example, Figure 5.2 summarises evidence on the effectiveness of business accelerators and incubators in a visual way.
Source: Authors’ elaboration based on Nathan, M (2023[1]), “Things We Don’t Want to Know? Monitoring and Evaluating Place-Based Policies”, Background paper for the OECD-EC High-Level Expert Workshop Series on “Place-Based Policies for the Future”, Workshop 4, 7 July 2023, https://www.oecd.org/cfe/regionaldevelopment/place-based-policies-for-the-future.htm.
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← 1. This chapter was informed by the fourth workshop in the series on Place-Based Policies for the Future that was held on 7 July 2023 with invited experts. Papers for the seminar were prepared by Professor Max Nathan (Things We Don't Want to Know? Monitoring and evaluating place-based policies) and Professor Alessandra Faggian and Professor Giulia Urso (Cohesion and place-based policies post-emergency in the EU).