Strategies for increasing the use of statistical data

SSRN Electronic journal, 2020

This paper describes key aspects of the structural and functional transformation of the Russian state statistics system as a core element of the future National Data Management System. Issues such as establishing a dialogue between the statistics service and users, integrating data from various sources, and intelligent data processing in the context of the digitalization of the economy are considered. New approaches and mechanisms should integrate and advance all of the previously achieved best results in methodology, observation areas, metrics, and other domains. Improvement areas include providing higher-quality information for policy shaping, businesses, individuals, and external partners. National statistics is expected to present an interconnected, objectively measurable model of socioeconomic processes and phenomena based on relevant theoretical concepts. In addition to using various sources of data, a necessary feature of the new system will be its reliance on a consistent conceptual framework and approaches to interpreting data, which will make it possible to integrate various data sources in the first place. Users of intelligent statistics are becoming not only active participants in primary data collection, accumulation and application processes, but are turning into “smart” consumers who develop statistical thinking and are able to derive the greatest possible benefits from the use of statistical data. Such skills should become an inherent (and possibly mandatory) component of any.

Big Data & Society, 2014

The rise of Big Data changes the context in which organisations producing official statistics operate. Big Data provides opportunities, but in order to make optimal use of Big Data, a number of challenges have to be addressed. This stimulates increased collaboration between National Statistical Institutes, Big Data holders, businesses and universities. In time, this may lead to a shift in the role of statistical institutes in the provision of high-quality and impartial statistical information to society. In this paper, the changes in context, the opportunities, the challenges and the way to collaborate are addressed. The collaboration between the various stakeholders will involve each partner building on and contributing different strengths. For national statistical offices, traditional strengths include, on the one hand, the ability to collect data and combine data sources with statistical products and, on the other hand, their focus on quality, transparency and sound methodology. ...

IDS Bulletin, 1994

Nepal Public Policy Review, 2021

Globally, countries adopt either centralized or decentralized statistical management system. With over 60 years of history, Nepal has been practicing decentralized statistical management system where various government agencies alongside non-government and private agencies manage statistics based on their needs and requirements. Statistics Act 1958 set the foundation for statistical management system, that is in operational stage as of 2021. This paper sets an objective of reviewing the legal instruments associated with statistical management system and explores the opportunities and challenges of integrated statistical management system. Paper adopts systematic literature review method to search, sort and filter the relevant literature associated with opportunities and challenges of statistical management systems and/or practices. The adoption of statistical management system among countries were found to be varied (centralized/decentralized) based on the countries’ needs, interest...

2010

We argue that the development and expansion of direct, secure access to administrative micro-data should be a top priority for the NSF. Administrative data offer much larger sample sizes and have far fewer problems with attrition, non-response, and measurement error than traditional survey data sources. Administrative data are therefore critical for cutting-edge empirical research, and particularly for credible public policy evaluation. Although a number of agencies have successful programs to provide access to administrative data -most notably the Centers for Medicare and Medicaid Services -the United States generally lags far behind other countries in making data available to researchers. We discuss the value of administrative data using examples from recent research in the United States and abroad. We then outline a plan to develop incentives for agencies to broaden data access for scientific research based on competition, transparency, and rewards for producing socially valuable scientific output.

1999

Statistical journal of the IAOS, 2016

Good strategies start with diagnosis of the challenge. The paper presents indications that the High-Level Group for the Modernisation of Statistical production and Services took lightly on that task. The argument of the paper is that in order to detect the challenges that the industry is facing, the venues where it operates should be considered as markets. This is also a precondition for meeting the challenges with the tools for strategic management. Four venues are analysed: The Treasury, which serves as the industry's capital market, the product markets of sample surveys and administrative records statistics, and the public sphere or marketplace of ideas. The venues have different market characteristics. The capital market is a monopsony. The market for sample surveys statistics is subject to free competition. Administrative records are natural monopolies. In the public sphere statistics may be subject to monopolistic competition. Depending on the market the members of the official statistics industry can take four positions, as competitor, collaborator, coordinator and controller. Some are compatible, but impossible to reconcile are the positions as competitor and coordinator or controller. The development in the increasingly important market for administrative records statistics suggests that the industry should emphasize the controller option.

Journal of Privacy and Confidentiality

Government statisticians are intrigued by the possibility of accessing administrative data as a way to enhance survey and census data. Survey data are rich in attributes, but they exhibit sampling errors. More consequentially, they demonstrate non-sampling errors, often because of nonresponse, but also because of responses that are incomplete or inaccurate, frequently due to the respondent's inability to recall. Additionally, panel data are subject to attrition. Administrative data can help compensate for these problems importantly because administrative data, such as social security files, include almost everybody. Further, supplementing statistical data can be cost-effective, because an enormous amount of administrative data are already collected to support the functional operations of government agencies, and so are potentially available. In many instances, respondent burden in surveys can be lessened because certain attribute values may be available from administrative records. Some U.S. federal agencies, e.g., the Social Security Administration (McNabb et al., 2009) have linked administrative data with survey data to broaden its demographic and socioeconomic measures and also to improve the quality of the survey data. See National Research Council (2005), pp.45-48 for additional examples and discussion of benefits of such data linkage.

The development of big data is set to be a significant disruptive innovation in the production of official statistics offering a range of opportunities, challenges and risks to the work of National Statistical Institutions (NSIs). This paper provides a synoptic overview of these issues in detail, mapping out the various pros and cons of big data for producing official statistics, examining the work to date by NSIs in formulating a strategic and operational response to big data, and plotting some suggestions with respect to ongoing change management needed to address the use of big data for official statistics.

Statistical journal of the United Nations economic commission for Europe, 1991

In the article, a typology of the use of official statistics is proposed. Following an introduction to the subject, three dimensions of the use of official statistics are distinguished analytically: user categories, objectives oj use, and methods oj use. Each of the three dimensions is subdivided into four categories. The dimension user categories is subdivided in government, science, business, and the public; the dimension objectives oj use consists of knowledge, preparation for choice and action, evaluation of choice and action, and routinization of choice and action; and, finally, the dimension methods oj use is subdivided into consultation, monitoring and comparison, formal analysis of aggregate data, and formal analysis of individual-level data. Some of the more frequently occurring combinations are illustrated with the aid of examples from the Netherlands, the United States, Canada, and the European Communities. After some introductory statements on priority setting (an evaluation of the significance and the cost of statistical projects), the relationship between type of use and priority setting is clarified. It is stated that, since a classification cannot automatically lead to a particular outcome in terms of priorities, the primary goals for a classification of types of use are relevancy and structure of information. The final paragraph discusses the likeliness of each of the 64 possible combinations; it is concluded that in the Dutch situation, for several reasons, almost half of these 64 combinations are more or less unlikely to occur.

More and more National Statistical Institutes (NSI's) use administrative data as a primary source of information for producing statistics. Because the collection and maintenance of administrative data is beyond the control of NSI's, it is essential that NSI's are able to determine the quality (i.e. the statistical usability) of these sources when they enter the office in a quick, straightforward, and standardised way. The quality of the metadata components of administrative sources can be easily determined with the checklist developed by Statistics Netherlands. However, for the determination of the quality of the data in administrative sources a standard procedure was not yet available. This was the focus of research performed in part of the seventh framework project BLUE-Enterprise and Trade Statistics (BLUE-ETS). To enable the structured evaluation of administrative data, first the quality dimensions of administrative input data were identified: Technical checks, Accur...

In a central bank statistical information sustains many institutional functions and is a strategic resource for research and decision-making. To serve this purpose, new statistics often have to be created. This complex and dynamic scenario demands a comprehensive and flexible IT solution which should support various kinds of processes and be promptly adapted to new requirements. The solution should be founded on a rigorous and general information model that can describe all the characteristics of the statistical data: the meaning, the properties and the transformation rules to produce other data. Compliance of this information model with international standards is important, in that statistical production requires a high level of co-operation among all the stakeholders (statistical agencies, users, etc.).

2003

Abstract Over 70 agencies at the federal level are charged with collecting data and producing and disseminating statistics. These statistics are used to inform government policy, shape health care initiatives, provide information on the state of the economy, and others. They also have significant impact on the lives of citizens who use the statistics, for example, to determine job opportunities, changes in social security benefits, and quality of life in particular areas.

Technology is shaping the ways that evidence is used to influence policy and public opinion. Developments include: the semantic web; the Big Data movement, new tools for data visualisation, and the rise of data-driven journalism. Such developments will have profound effects in terms of the nature of evidence that is gathered, the ways in which it is presented and used, and the skills that will be needed for its interpretation. As such they offer opportunities, but also pose threats to both National Statistics Offices (NSOs) and to statistics educators. A great deal is to be gained from collaborations between NSOs, statistics educators, and other groups. Here, we give examples of the ways that technology is influencing practice, and describe a UK collaboration between the Data Visualisation Centre within the Office for National Statistics and the SMART Centre at Durham University, which sets out to work with journalists and policy makers, and uses Big Data tools to explore success. T...

The product of a national statistical system is the official statistics which is the bedrock of any national transformation agenda. This study examined the evolution of the Nigerian Statistical System (NSS) from 1928 to date. The historical development was categorized into Findings showed an astronomical increase in demand for data in recent times due to the search for new opportunities and agitation for accountability by citizens. However, progress remains insufficient, suppliers/users are not statistically literate, funding support is largely donor-driven while coordination and governance are still very weak. The status of implementation of the NSDS was found to be limited by existing ICT infrastructure. This study should enable the orientation of evidence-based policy making in Nigeria.