Question

PROMPT:  The article describes how two prominent economists revisited their earlier work on the “gig economy” and determined that their estimates of its impact were too high, skewed by spotty data and the recession of a decade ago.

Comment on the idea of having researchers revisit their earlier work to comment on the outcome of their predictions based upon the availability of additional data.
Comment on the problems faced by a data-driven policy maker who does not have access to a complete understanding of the methods by which the data being used were compiled.

Answer 1

Introduction

A gig economy is one, in which people prefer to take short term contractual jobs to get the work done. For a company this means the lack of investment on a person to get the job done but rather short-term payments which allow for equal efficiency. For the person who takes up such jobs, even though job security is not present, yet the opportunity to earn more is an added incentive.

Over the years, numerous countries have seen the rise of gig economies primarily due to the Internet revolution which is allowing people to work from their homes itself.

In the case study, the Gig economy and its impact on the society was measured when there was a deep recession in the country. This creates a situation where the data favours the gig economy without accounting for the fact that these economies rise because of recession and companies prefer such contracts during that time period to save on costs.

Case Specifics: -

(A)

When new data is found to observe a change, it is important that the economists pay equal heed to the fact that these conditions exist today and therefore all other data points should also be analysed to know if the effects are present or not.

For example, when we evaluate the value of the total gig economy, previously we did not consider the recession and over estimated the value of the gig economy.

But we need to remember that now that the recession has gone away, we cannot estimate the gig economy on the basis of historical numbers. We need to find out the data as on date and consider additional variables and recalculate our data.

This allows for errors to be negligible and any new point which our research must cover should also analyse present values instead of historic ones so that errors do not take place.

(B)

If an analyst does not know, how the previous data was combined, it would lead to wrong interpretation. In the above example the estimation was done considering the fact that recession was not accounted for. If an analyst compared the present data with the historical data without considering the fact, then we would have incorrect results today as well.

An analyst needs to know, the sources and methodology of data collection and interpretation which were used previously so as to be able to derive meaningful results in the present.

Please feel free to ask your doubts in the comments section.