Converting Data into Value with Economic Analytics

The ever-evolving economic theories and its research applications are getting modified in the age of big data. New avenues of economic research are opening up, which was not previously feasible. It has been observed that researchers are tilting more towards empirical efforts.

New data sources and a wide array of data is changing the scope of the economic theory, modelling, and research from every dimension. Previously, data was available mostly from public and government sources. But nowadays, the amount of private data created and generated is massive. This amount of data can help economists to study and verify theories that were not previously possible. So, economists are increasingly using newly-available large-scale data or private sector data that are often obtained through collaborations with private firms, giving rise to new opportunities and challenges of application.

Changing Landscape of Economics

This change from small-scale government data to administrative data is allowing economists to rigorously examine indicators, the study of which was not previously possible. The data can also help economists to create meaningful economic insights for the business of private firms. With variety and quantity, quality of data is also improving. Better quality data also allow for more accurate tests of existing models and tests of theories and hypothesis that had previously been difficult to evaluate.

Some Characteristics of the Data Collected

•  Data is now available in real-time that means there is no delay in the timeline of the information provided.

•  Data is now also available on a larger scale and on novel variables that were not possible to record before.

•  The form of the data collected is mostly unstructured, which might pose a challenge for the economists.

Advantages

•  With a wide variety of data, economic effects and outcomes can be measured with better accuracy and new research designs can be formulated across a range of topics.

•  These data will allow focussing more on population variation and a broader range of analysis of economic activities. As a consequence, it will allow economists to ask better questions. It will also facilitate and enable more empirical-based research, in explaining historical patterns, long-term trends and causal effects of different policies.

•  Development of new economic statistics and econometric methods may be enhanced. Predictive models can be widely used and applied. So practical application may increase the availability of data. Large data statistical methods that were previously difficult to implement will become easier.

•  Better government policies can be designed by accounting new variables in the model. Better policies for private firms can also be formulated.

Challenges

•  Today, the major issue is security and privacy in accessing data. The challenge is to develop methods for researchers to access and explore data in ways respecting privacy and security. This issue is important in working with government as well as private firms.

•  Development of appropriate data management and programming compatibilities is necessary without which it will become impossible to analyze or explore large-scale unstructured data. Learning the skills required for handling such data is also necessary.

•  It is easy to get lost in such vast types and quality of data. Having a lot of data does not automatically make for great research if not applied correctly. In fact, it might become difficult to focus on a single indicator or issue with data on many more indicators available.

Future

Economists and policymakers need better quality of data to base their forecasts. Some two-three decades ago, data on economic activities was relatively scarce. However, the situation has changed dramatically in the past few years. New sources of information on the economy have recently opened up with the vast collections of private data collected by search engines and other internet companies.  From 2014, there has been a 42% increase in the number of internet users in just three years only. With the advancement of the internet of things, these numbers are projected to increase even more out of proportion.

Every firm is trying to explore "data-network effect"— using data to attract more users. A similar transformation is seen in other sectors as well. The data revolution is bound to have a profound impact on the subject and its research applications. These newly available real-time data will reflect the behavior of economic agents, giving insights on previously undetectable shifts in the economy.

Conclusion

There is no doubt that over the next few years big data will change the landscape of economic policy and research. Big data will also revolutionize economic forecasts. It remains to be seen how the private firms and government agencies use these data for future policies and research.