Quantifying the coherence of development policy priorities

Abstract

Over the last 30 years, the concept of policy coherence for development has received especial attention among academics, practitioners and international organizations. However, its quantification and measurement remain elusive. To address this challenge, we develop a theoretical and empirical framework to measure the coherence of policy priorities for development. Our procedure takes into account the country-specific constraints that governments face when trying to reach specific development goals. Hence, we put forward a new definition of policy coherence where context-specific efficient resource allocations are employed as the baseline to construct an index. To demonstrate the usefulness and validity of our index, we analyze the cases of Mexico, Korea and Estonia, three developing countries that, arguably, joined the OECD with the aim of coherently establishing policies that could enable a catch-up process. We find that Korea shows significant signs of policy coherence, Estonia seems to be in the process of achieving it, and Mexico has unequivocally failed.Furthermore, our results highlight the limitations of assessing coherence in terms of naive benchmark comparisons using development-indicator data. Altogether, our framework sheds new light in a promising direction to develop bespoke analytic tools to meet the 2030 agenda.

Estimating Networks of Sustainable Development Goals

“…Some progress has been made in this vein of research through policy priority inference [67,68]. Starting with a set of exogenous objectives, indicators' initial values, and an estimated network of structural-dependencies, the model generates endogenous policy priorities that can be used to make causal inference in a variety of topics such as policy resilience [69], ex-ante policy evaluation [70], policy coherence [71], and corruption [74]. 44 In this framework, the purpose of the network is only to specify how the SDG indicators co-evolve once certain variations are induced by the adaptation of the budgetary allocations.…”

Policy priority inference: A computational framework to analyze the allocation of resources for the sustainable development goals

“…PPI builds on a model previously developed by Castañeda et al (2018) (referred to as "the CCG model" from here onward), consisting of a central authority allocating resources across a multidimensional and interlinked policy space. The CCG model has been previously applied to the study of policy resilience , ex-ante policy evaluation (Castañeda and Guerrero, 2019), policy coherence (Guerrero and Castañeda, 2020), and corruption (Guerrero and Castañeda, 2019). However, its ability to provide detailed policy advice is limited by not being able to account for negative interlinkages between indicators (so environmental issues cannot be considered) and by the need to build international datasets for calibration purposes.…”

“…Fourth, we compare the budgetary data with fluid priorities. This allows us to measure the level of policy coherence through an index created by Guerrero and Castañeda (2020). Fifth, we explore rigid priorities by fixing P according to coarse-grained budgetary data and evaluate their feasibility.…”

“…This is so because the prospective priorities are, effectively, a counterfactual of what the government would do under the NDP. Comparing this counterfactual to the fiscal data allows measuring the level of coherence of the budget through an index developed by Guerrero and Castañeda (2020). Figure 9 shows the result of this exercise.…”

“…An index with value 1 suggests full coherence, meaning that all the dots in the left panel would lie on the dotted line because both the budget and the prospective allocation are identical. The right panel shows the distribution of the coherence index (see Guerrero and Castañeda (2020) for details on the estimation procedure). Clearly, the budget is incoherent with the government's aspirations (at least at the level of the SDGs).…”