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Chapter Highlights

This chapter focuses on the data needs and measurement challenges associated with the

emerging digital economy. The authors view the emergence of e-commerce, however, as

part of a broad spectrum of changes in the structure of the economy related to the

developments extending over several decades in information technology (IT).

A good example of the problems confronting statistical agencies trying to measure the

impact of IT is found in the banking community. Here, the IT revolution has led to the

introduction of new services such as electronic banking and ATMs. How do you

associate a value (and hence measure the increased productivity) of an ATM machine

that provides you with the ability to service your bank accounts 24 hours a day, seven

days a week? Clearly, that is a hard concept to accurately measure.

The 1997 Department of Commerce report on “The Emerging Economy” provides

examples of aspects of the digital economy that we should be measuring:

1. The shape and size of the key components of the evolving digital economy, such as e-

commerce and, more generally, the introduction of computers and related technology

in the workplace.

2. The process by which firms develop and apply advances in IT and e-commerce.

3. Changes in the structure and functioning of markets, including changes in the

distribution of goods and services and changes in the nature of international and

domestic competition.

4. The social and economic implications of the IT revolution, such as the effects of IT

investments on productivity.

5. Demographic characteristics of user population.

Further, it is obvious that there is a dire need to improve the data collection activities

(which are inadequate) to accurately estimate the impact that IT has in the areas listed

above.

Given the pace of change in IT and the myriad new ways in which businesses,

households, and others exploit IT, it is understandable that the institutions that collect

economic and demographic data are behind in measuring the magnitude and scope of

IT’s impact on the economy.

Three broad areas of research and policy interest related to the digital economy require

high-quality data:

1. The investigation of the impact of IT on key indicators of aggregate activity, such as

productivity and living standards. Aggregate productivity growth slowed over much

of the period in which large investments in IT occurred, especially in service

industries, such as banking, that had particularly large IT investments. A number of

studies failed to find a link between IT investments and productivity, leading to the

identification of the “productivity paradox” [Solow, 1997]. There are several reasons

this paradox exists: (a) the official statistics do not capture all the changes in output,

quality, and cost savings associated with IT and therefore understate its impact, and

(b) as with previous technological innovations – such as electricity, railroads, etc... -

IT’s impact has yet to become manifest and hence there is a considerable lag between

investment in such innovations and related productivity increases.

With the growth of e-commerce, particularly in business-to-business transactions, we

are no longer interested only in measuring the impact of computers and IT on

productivity within organizations, but rather in organizations that do business

between themselves electronically. In this way, we can determine the size and scope

of measurable productivity gains in sectors and firms that rely on e-commerce.

2. The second area of research and policy interest that requires high-quality data is the

impact of IT on labor markets and income distribution. Of particular interest is

whether IT is increasing wage and income dispersion by creating groups of haves and

have-nots based on whether people have the skills and/or are employed in the

appropriate sectors to take advantage of IT advances.