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"ECONOMIC DATA"
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Reinventing capitalism in the age of big data
Discusses how data is replacing money as the driver of market behavior and shares predictions for how data will revolutionize the market economy and make cash, banks, and big companies obsolete. --Publisher.
What Are We Weighting For?
When estimating population descriptive statistics, weighting is called for if needed to make the analysis sample representative of the target population. With regard to research directed instead at estimating causal effects, we discuss three distinct weighting motives: (1) to achieve precise estimates by correcting for heteroskedasticity; (2) to achieve consistent estimates by correcting for endogenous sampling; and (3) to identify average partial effects in the presence of unmodeled heterogeneity of effects. In each case, we find that the motive sometimes does not apply in situations where practitioners often assume it does.
Journal Article
The digital era. 2, Political economy revisited
For 200 years, industry mastered iron, fire, strength and energy. Today, electronics shape our everyday objects, integrating chips everywhere: computers, phones, keys, games, household appliances, etc. Data, software and calculation frame the conduct of men and the administration of things. Everything is translated into data: the figure is king. The second volume of this series describes how the digital economy transforms market relations and why this change puts political economy to the test.
Book
The MID4 dataset, 2002–2010
Understanding the causes of interstate conflict continues to be a primary goal of the field of international relations. To that end, scholars continue to rely on large datasets of conflict in the international system. This paper introduces the latest iteration in the most widely used dataset on interstate conflicts, the Militarized Interstate Dispute (MID) 4 data. In this paper we first outline the updated data-collection process for the MID4 data. Second, we present some minor changes and clarifications to the coding rules for the MID4 datasets, as well as pointing out how the MID coding procedures affect several notable \"close call\" cases. Third, we introduce updates to the existing MID datasets for the years 2002–2010 and provide descriptive statistics that allow comparisons of the newer MID data to prior versions. We also offer some best practices and point out several ways in which the new MID data can contribute to research in international conflict.
Journal Article
On information quality
We define the concept of information quality 'InfoQ' as the potential of a data set to achieve a specific (scientific or practical) goal by using a given empirical analysis method. InfoQ is different from data quality and analysis quality, but is dependent on these components and on the relationship between them. We survey statistical methods for increasing InfoQ at the study design and post-data-collection stages, and we consider them relatively to what we define as InfoQ. We propose eight dimensions that help to assess InfoQ: data resolution, data structure, data integration, temporal relevance, generalizability, chronology of data and goal, construct operationalization and communication. We demonstrate the concept of InfoQ, its components (what it is) and assessment (how it is achieved) through three case-studies in on-line auctions research. We suggest that formalizing the concept of InfoQ can help to increase the value of statistical analysis, and data mining both methodologically and practically, thus contributing to a general theory of applied statistics.
Journal Article
Web3 : charting the Internet's next economic and cultural frontier
\"A book about how Web3 will develop and change the economy\"-- Provided by publisher.
Book
Payroll Employment at the Weekly Frequency
Nontraditional data can provide critical economic insights in real time. We document the development of weekly employment indexes based on microdata from the payroll processor ADP. These data have provided insights into labor market developments in the fast-moving pandemic environment of recent years, as well as in more quiescent periods. We describe processes for weighting and benchmarking, seasonally adjusting weekly data, and ultimately combining the signals from ADP and official data. Finally, we show how the weekly employment indexes have fared during the pandemic jobs recovery, focusing on revisions to official data for the second half of 2021.
Journal Article
Optimising medication data collection in a large-scale clinical trial
Pharmaceuticals play an important role in clinical care. However, in community-based research, medication data are commonly collected as unstructured free-text, which is prohibitively expensive to code for large-scale studies. The ASPirin in Reducing Events in the Elderly (ASPREE) study developed a two-pronged framework to collect structured medication data for 19,114 individuals. ASPREE provides an opportunity to determine whether medication data can be cost-effectively collected and coded, en masse from the community using this framework.
The ASPREE framework of type-to-search box with automated coding and linked free text entry was compared to traditional method of free-text only collection and post hoc coding. Reported medications were classified according to their method of collection and analysed by Anatomical Therapeutic Chemical (ATC) group. Relative cost of collecting medications was determined by calculating the time required for database set up and medication coding.
Overall, 122,910 participant structured medication reports were entered using the type-to-search box and 5,983 were entered as free-text. Free-text data contributed 211 unique medications not present in the type-to-search box. Spelling errors and unnecessary provision of additional information were among the top reasons why medications were reported as free-text. The cost per medication using the ASPREE method was approximately USD $0.03 compared with USD $0.20 per medication for the traditional method.
Implementation of this two-pronged framework is a cost-effective alternative to free-text only data collection in community-based research. Higher initial set-up costs of this combined method are justified by long term cost effectiveness and the scientific potential for analysis and discovery gained through collection of detailed, structured medication data.
Journal Article