Figure 12-15 shows the application of the expenditure rigidity mapping to the BOOST data for Armenia, Moldova, Bulgaria and Paraguay. In most of the countries, there is an apparent increase in the share of rigid spending over time. The exception is Paraguay, where discretionary spending now makes up more than half the budget for the first time in more than a decade. On the contrary, for Moldova and Bulgaria the discretionary component of spending has fallen to alarmingly low levels (14 and 18 percent, respectively). This suggests the authorities in these countries have limited ability to easily adjust spending, or in other words, they will have a more difficult time in applying negative expenditure force in the near term.

It is important to mention some of the limitations of this methodology. First, mapping at more aggregate levels such as “Econ 1” in the BOOST leaves open the possibility that some subcomponents may not be rigid. For example, wages and remuneration of the civil service are generally seen as straightforward examples of rigid expenditure. However, there may be certain aspects of non-monetary compensation (e.g., year-end bonuses) that are at the discretion of ministry management and more easily adjusted than salaries. Second, and relatedly, to properly consider all fiscal rigidities, a full understanding of the legal and institutional country context is needed. The better the understanding of line items in the budget, the more detailed the mapping can be. Third, the interpretation of rigid spending areas is subjective and can fundamentally differ from country to country, depending on the specific classification and BOOST structure. Each BOOST database is different in its internal structure, which makes standardization difficult. Yet overall, we feel the mapping framework provides sufficient guidance to give country teams a solid basis for classifying rigid expenditures that can make expenditure adjustment difficult.

**Case Study: A closer look at tagging Moldova’s expenditures**

Table 9 below provides a more detailed look at the application of the tagging framework to the BOOST data for Moldova. After the BOOST data is parsed by economic classification (Econ 2), each line item is analyzed to see if there is a match with one of the seven categories of rigid expenditures from Cetrangolo et al 2010. Any remaining expenditures that do not fit into any of the seven categories are deemed discretionary. The results below show the significant increase in rigid spending, and that between 50-65 percent of rigid expenditures come from three main categories – benefit principle funding, resource disputes within government and intergovernmental relations. For the benefit principle funding category, the main components are the pension fund and healthcare spending. Combined, these spending items increased substantially between 2008 and 2009, especially as a share of remaining spending as the authorities sought to cut discretionary spending while also providing a safety net to the population. Resource disputes within government refers to politically inflexible expenditures such as wages and other operating expenditures. The majority of spending included in intergovernmental relations is the current transfers to sub-national tiers of government.