on measures of governance. Hollyer et al, (2011) create a transparency index based on the availability of country-level data – 172 variables in total categorized under Economic Policy and Debt in the World Bank’s World Development Indicators – to show that democratic countries are more transparent. Similarly, Williams (2009) constructs a transparency index based on the quantity of data released by governments through the availability of socio-economic data contained in the World Development Indicators and the International Finance Statistics databases. Choi and Hashimoto (2018) proxy for data transparency policy reforms using subscriptions to the IMF’s Data Standards Initiatives and find that such reforms lead to falls in sovereign bond spreads. The study finds that the larger quantity of data produced, as measured by the index, is positively correlated to the quality of bureaucracy, investment and financial sector development.

Finally, there is the question of whether data transparency can contribute to long term growth. The role of data transparency in facilitating economic growth is closely tied to institutions in the literature. The quality of institutions is largely dependent on their degree of accountability and corruption. Institutions operating in secrecy – lack of transparency - tend to be poor in quality as public officials can seek personal gain with little accountability. A large body of literature documented the detrimental effects of corruption on economic growth (Mauro 1995; Ehrlich and Lui, 1999). The secretive nature of corruption makes it distortionary, thereby discouraging investment and slowing growth (Shleifer and Vishny, 1993). Corruption can discourage foreign direct investment, entry of new firms, and misallocate public expenditures (De Soto, 1989; Mauro, 1998; Wei, 2000; Brada et al., 2019). Furthermore, institutions or even corruption that is “unpredictable” discourages investment and lowers growth (Campos et al., 1999). Corruption may also reduce parental investments in human capital (Varvarigos and Arsenis, 2015; Brunetti et al., 1998). Islam and Lederman (2020) find a statistically significant impact on transitional growth to a higher potential level of gross domestic product per capita. The estimates indicate an elasticity of the magnitude of 0.03 percent per year, which is much larger than the elasticity of trade openness and schooling in their estimation sample. Thus, there is some evidence that better data ecosystems can have far-reaching economic benefits.

# **Measuring the Performance of Data Systems**

The ideal data transparency measure covers the capacity of the data system to produce timely and good quality data that is widely accessible. Additional elements include the legal framework surrounding data and the features or services data systems provide. There are three main measures that are widely used: (i) the Statistical Capacity Indicator (SCI) from the World Bank (that is to be discontinued), (ii) the Statistical Performance Indicator (SPI) also from the World Bank released as part of WDR 2021, and (iii) the Open Data Inventory (ODIN) from the Open Data Network.<sup>2</sup> The SCI is a composite score assessing the capacity of a country’s statistical system. It is based on a diagnostic framework assessing the following areas: methodology; data sources; and periodicity and timeliness. Countries are scored against 25 criteria in these areas, using publicly available information and/or country input. The SCI score is then calculated as the simple average of all three area scores on a scale of 0-100. The SCI only covers developing economies but has the advantage of going back historically to 2004/2005, allowing for tracking the evolution of data systems over time. See Table A2 in the annex for definitions of subcomponents.

The SPI, which is the successor to the SCI, measures the capacity and maturity of national statistical systems by assessing the use of data, the quality of services, the coverage of topics, the sources of information, and the infrastructure and availability of resources. The goal is to improve development outcomes and track progress toward the Sustainable Development Goals. The Statistical Performance

> 2 See Table A1 in the annex for a summary of all three indicators.

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