Data availability and baselines

Insufficient up-to-date macroeconomic data on government websites, which could hinder timely and effective planning especially during crisis periods, needs to be rectified. The State Statistical Committee (SSC) has numerous macroeconomic indicators on its website. However, in most cases, very recent data are missing. International organizations such as ADB, the IMF and the World Bank release forecasts of macroeconomic indicators for upcoming years, and SSC should consider following the same approach.

Accessibility of healthcare data in Azerbaijan needs to be improved. Reports from the Ministry of Health Care are not publicly available on its website. In addition, the State Agency for Mandatory Health Insurance considers healthcare information to be highly sensitive. Accordingly, this information is not contained on its website. Information related to daily coronavirus infections and vaccinations was released publicly. It would be useful for the agency to disseminate gender, age, and region-disaggregated information to the public.

Sex-disaggregated data need to be accurate and usable for in-depth analyses to support policy development and program planning and implementation. The government has increased its focus on gender equality and has made significant progress on gender data tracking and transparency. Although there are a few publicly available national resources, they lack qualitative information.

Inavailability of data could hinder the achievement of a project's intended results. While gender data was available in major programs like the Emergency Subsidy Program, such data was unavailable for others. Of the six outputs in the gender monitoring matrix, two were not achieved as the following data were unavailable: (i) the number of micro, small, and medium enterprise beneficiaries under the small business wage subsidy program and those registered to women; and (ii) thenumber of micro, small, and medium enterprises that benefited from tax relief and those registered to women

Data collection, which took longer than anticipated under the CARES program, need to be expedited in future emergency responses. Data collection challenges experienced under CARES included (i) competing priorities, (ii) need to cover many different agencies, and (iii) need to collect data remotely. In some cases, the same dataset was collected from multiple sources and agencies, necessitating cross checking and verification and requiring considerable time and resources.

Difficulties with data accentuated problems that included health targets, such as the vaccine rollout. Although testing rates had reached World Health Organization targets by August 2021, it was not clear that the national average testing rate applied uniformly at the provincial level.

Comprehensive and disaggregated enterprise-level data are needed to effectively support micro, small, and medium-sized enterprises (MSMEs) in times of crisis. The absence of a real-time disaggregated financial data collection system at the beneficiary level made it difficult to timely track the status of business recovery of affected MSMEs. The dataset collected and used in reports on MSME lending did not include comprehensive disaggregated enterprise-level data from the start, making it impossible to assess the inclusiveness of the concessional lending.

Data interoperability facilitates beneficiary targetting in times of crisis. Difficulty in consolidating data between federal, provincial, and local-level governments and between sectors affected program implementation and progress monitoring. While Nepal’s social security programs each identify and register beneficiaries, there is no central register for poor and vulnerable populations. Hence, the ward officials identified food support beneficiaries, which led to implementation challenges.

Lack of readily available and measurable social and economic data can limit the scope of the design and monitoring framework (DMF). The CPRO loan supported 12 schemes of the PMGKY program, which extended insurance cover for health workers, cash transfers, food and fuel transfers, and employment guarantees.. However, the DMF included only eight schemes for monitoring as part of the CPRO loan because specific results and performance Indicators could not be devised during appraisal considering the urgency of the requirement for assistance.

Limited baseline data could lead to unrealistic performance Indicators and targets. Because this was ADB’s first TVET grant project in Timor-Leste, which introduced a new area of formalized skills development, baseline data for the targets were limited. This led to some unrealistic performance Indicators and targets. For example, the number of students and trainers to be trained appeared to be modest, whereas the target of 65% of graduates to find employment within 3 months of graduation was overambitious.