the quality of the data system. Under the assumption that international guidelines provide the benchmark for ideal data systems, adherence to such standards implies that the quality of data systems meets wellestablished standards. Countries are evaluated against a set of criteria such as use of an updated national accounts base year, use of the latest balance of payments manual, the external debt reporting status, an updated consumer price index, an updated industrial production index, updated import/export prices, an accounting basis for reporting government financial data, vaccine reporting to WHO (discrepancy between WHO and government estimates), subscription to the IMF’s Special Data Dissemination Standard, and enrollment data reporting to UNESCO). Each criterion has equal weight.

The periodicity and timeliness dimension measures the availability and frequency of key socioeconomic indicators, of which nine are indicators of Millennium Development Goals (MDG). This dimension attempts to measure the extent to which data are made accessible to users through transformation of source data into timely statistical outputs. The frequency of the main indicators considered, each receiving equal weight, includes: an income poverty indicator; a child malnutrition indicator; a child mortality indicator; an immunization indicator; an HIV/AIDS indicator; a maternal health indicator; a gender equality in education indicator; a primary-school completion indicator; an access to water indicator; and a GDP growth indicator.

**Table 1. Subcomponents of the Statistical Capacity Indicator**

|**Dimension**|**Definition**|
|---|---|
|**Statistical**<br>**Methodology**<br>**(scale: 0-100)**|Measures a country’s ability to adhere to_internationally recommended standards_<br>_and methods_. This aspect is captured by assessing guidelines and procedures used<br>to compile macroeconomic statistics and social data reporting and estimation<br>practices.|
|**Source Data**<br>**(scale: 0-100)**|Reflects whether a country conducts_micro data collection_activity in line with<br>internationally recommended frequency and whether_data from administrative_<br>_systems_are available and reliable for statistical estimationpurposes.|
|**Periodicity and**<br>**Timeliness**<br>**(scale: 0-100)**|Measures_the availability and periodicity of key socioeconomic indicators_, of which<br>nine are Millennium Development Goals (MDG) indicators.|

Source: Statistical Capacity Indicator Note, World Bank's Development Data Group (2021).

The World Bank’s SCI goes beyond its name by capturing many of the elements of transparency. The availability and regular publication of micro and macro data as well as whether production of such data adheres to international standards goes to the heart of “openness,” the ability of citizens to learn information from the government. The measure goes beyond statistical capacity—the SCI score of highly competent statistical offices can be penalized if they do not publish statistics. The SCI captures transparency by using data-centric, objective, and verifiable measures—and is unique in that it is not dependent on perceptions of transparency by survey respondents, as is typically the case in many transparency indicators. The SCI can be interpreted as a statistical or data transparency index.

Several studies have used the SCI to evaluate the quality of data systems and investigate its relationship with other macroeconomic variables (Devarajan, 2013; Kubota and Zeufack, 2020; Islam and Lederman, 2020). Nevertheless, the SCI has limitations. It covers only developing economies and is available from 2004 to 2020. The availability of data at high frequencies (quarterly and monthly) is largely not considered. For microdata, it does not consider establishment and labor force surveys. It also does not include a measure of openness in terms of online access to data. Its successor, the Statistical Performance Indicators (SPI)—launched in _World Development Report 2021: Data for Better Lives_ — deals with many of 8