Macroeconomic Forecasting During Crisis Period

Macroeconomic research and forecasting have become more important and difficult than ever before. Making precise forecasts requires some key considerations.

Market forecasting has always been challenging due to the unpredictability of human nature. During a crisis like COVID-19, macroeconomic research and forecasting became much more difficult for this precise reason. Since it is humans who run corporations, we can say there is an amount of uncertainty attached to business practices.

The pandemic has also catalysed a number of changes in a way unseen before. The work-from-home environment has helped to reveal several glaring gaps in corporations that otherwise would have gone unnoticed. Some of the important areas the pandemic has cast light on include:

Supply chain issuesProduct shortagesAn increase in e-commerce retail salesA larger portion of the employee population working from homeA tendency to overgeneralise

Many of these were swept under the rug, with overgeneralisation about macroeconomic features staying prominent. However, this proved a considerable hurdle when experts tried macroeconomic forecasting during the pandemic.

That said, with employment rates continuing to drop and fewer institutions wishing to let go of the work-from-home model, macroeconomic analysis has become crucial to economic development and recovery. Economic forecasting helps governments and other such institutions take preventive measures in case of economic dips.

How can we improve economic forecasting?

Understanding Consumer Sentiment

The first step to building a viable econometric model and forecasting is through analysing and understanding consumer behaviour and sentiment. The advent and growth of big data have made these real-time analyses much easier. Since consumer purchasing forms a large part of GDP, evaluating past and current spending habits can provide insights into possible future habits.

Several studies have already covered consumer habits amid the pandemic, and as we emerge from the lockdown, it is safe to assume that consumers will continue experimenting with digital commerce. Some habits are here to stay.

Examining Transaction Data

Macro Economic Research focused on credit and debit transactions can further enhance forecasting, especially with the advent of digital payments, which ACI Worldwide predicts will make up 71.7% of all transactions in India by 2025. No doubt, this number has only been spurred by the pandemic, pushing the public towards a completely digital era.

Using large, representative samples can further help gauge future spending, showcasing which industries can recover after the pandemic. Notably, both the travel and restaurant industries took a huge hit during COVID-19. However, analysing consumer behaviour and transaction data can improve macroeconomic forecasting and determine the likelihood of these sectors getting back on their feet.

Avoiding Overgeneralisations

The dynamic nature of economic development and consumer behaviour makes generalisations near-impossible. COVID-19 showcased this more than ever before, truly bringing to light the role of the individual in economic activities.

That said, macroeconomic theory thrives on generalisations, which makes some generalisations necessary for certain predictions. However, assuming that these predictions are final with no exceptions will yield poor results. Instead, researchers and analysts need to be prepared for the likelihood that their predictions will not be entirely accurate.

Expert builders of econometric models as well as efficient digital tools can help make forecasting more accurate. Reaching out to an organisation like Acuity Knowledge Partners can significantly enhance the authenticity and accuracy of your macroeconomic analyses and reports.