To define expenditure rigidity, we use a mapping based on a conceptual framework from the literature. There is surprisingly limited treatment in the literature of mapping the fiscal rigidity of expenditures.<sup>15</sup> The framework in Cetrangolo et al (2010) provides a useful balance of specificity and intuition, and has been applied by the authors to a group of five Latin American countries. Their paper defines fiscal rigidities as “ _the institutional constraints that limit the ability to change the level or structure of public budgets in a specified period of time._ ” This definition emphasizes two key aspects in understanding fiscal rigidities. The first is that rigidity is time sensitive. In the very short term the vast majority of budget components are rigid, whereas in the medium and long term, the entire budget becomes more flexible. Secondly, the institutional constraints to the budget arise out of a desire to ensure compliance with a specific policy objective when it is feared that this will not be handled properly by the authorities. In this sense, rigidities stem from the distrust of some public policy makers by others. As argued by Crispi and others (2004), the existence of increasingly rigid expenditures is not an evil in and of itself. In many cases it reflects the progressive widening of economic and social benefits, while in others it is the product of the gradual implementation of major social reforms.

The adopted framework identifies seven areas of spending rigidities. The specificity of these areas fits well to the level of detail in the BOOST datasets. Table 8 from Cetrangolo et al (2010) lists the main characteristics of each rigid spending area and specific examples of qualifying expenditures. From piloting the approach with several BOOSTs, the best mapping seems to be against the economic classification. Elements of the economic breakdown of the BOOST (Econ 1 or Econ 2) are reviewed to see if they match one of the seven rigid spending categories, and coded appropriately. Expenditures that do not fit one of the categories are considered discretionary. For our exercise, we selected Moldova, Bulgaria, Armenia and Paraguay for applied examples. These countries were selected due to the relatively long time period covered, and the completeness of expenditures at national and local levels of government. The detail and structure of the data provide a rich source of information to analyze fiscal rigidities presented at the aggregate level of government, but also in the interaction of the different levels of government.

Application of the classification to map expenditures is straightforward for most categories. There are several spending categories from Table 1 that are easy to map to the detail in country BOOST data, including social security spending and wages. Debt servicing is well defined in the BOOST and easily mapped as a rigid item given the contractual nature of the obligation and negative consequences of unilaterally adjusting or ceasing these expenditures.

> 15 In addition to the approach of Centragolo  et al (2010) used in this paper, other treatments of fiscal rigidity include the interpretation by Crispi et al (2004) of increased rigidity as a symptom of increased social reforms, and the application to effectiveness of social spending in Slovenia by Mattina and Gunnarsson (2007).