Introduction

This book aims to provide an overview of the issues that arise when measuring modern economies, at a time when the way that they operate is changing rapidly. It is aimed in particular at readers who might be in the last year of an undergraduate economics course, or perhaps the first year of a further degree, and who want to put the theoretical concepts they have studied into a real-world context. But it is also intended for a wider readership who might be interested in the challenges that are implicit in the measurement of today’s economies.

Indeed, the challenges in measuring and monitoring economies today are considerable. If ever it was the case that economic activity was largely about consumers buying goods and services from factories down the road or from local service providers, those days are long gone. Technological developments and other advances have changed and extended the range of goods and services that people are able to enjoy. The internet, for example, has allowed a variety of new products and services—which are not captured in the traditional market economy—to flourish. These same developments have also altered and improved the nature of goods and services that are already within the market economy. A car, for example, is now a much more sophisticated entity than those that were available thirty, or even five or ten, years ago. The nature of services and the way they are provided have also changed: for example, services provided by estate agents, lawyers or banks. Accurate measurement of the economy needs to take these developments into account.

It is not just the nature of the value generated by modern economies that has evolved; the business models by which the value is generated have also changed. Globalisation is a key theme here. The goods and services ultimately enjoyed by consumers are increasingly produced by virtue of a “global value chain”. The ultimate value may be generated by a series of production stages that may involve export and import of intermediate goods and services involving a number of countries. A further manifestation of globalisation is the ability of individual consumers and producers to trade directly with almost any part of the world. The rise of platforms such as Amazon, eBay and Alibaba means that a UK consumer can identify and pay for a product on the opposite side of the world and have it arrive a few days later, perhaps via a third country as a staging point. Similarly, he or she can consume services provided in a completely different country: Netflix, WhatsApp and YouTube are cases in point. Having regard to these new business models and trading patterns is an essential part of measuring modern economies reliably and accurately.

These same developments have also blurred the boundary between the domestic and overseas economies in other ways. Intellectual property—ownership of the rights accruing from the design, research and development of a product—has become increasingly important relative to the manufacturing of that product. What is the more important, for example, in the value given by owning an iPhone? Is it the manufacture of the device, or the research and development that led to the design? The two may involve completely different parts of the world and accurate measurement needs to reflect that. This issue is not entirely new; it has always been the case for the pharmaceutical and other high-tech industries. But it has become much more widespread. All this adds to the challenges of measurement.

But while it is true that technological advances have made economic measurement more complex, this has been offset by the fact that the same technological advances have also opened up exciting new ways of better measurement. Any economic statistics need to be underpinned by a data source—data that can be converted by means of an appropriate methodology into useful statistical outputs. Traditionally, compilation of economic statistics has relied upon data from large-scale economic surveys. These might be direct questionnaires sent out to producers to record various aspects of their operations including their outputs. Or they might be direct collection of prices from supermarket shelves or from other pricing sources. Such information is supplemented by administrative information, that is the use of data generated not primarily for statistical purposes but for the purposes of running an organisation. Traditionally, such use of administrative data has usually been at fairly aggregate level, and mainly from public bodies: concerning, for example, central or local government activities in the economy or on the activity of the National Health Service.

Data sources of this kind have been an indispensable part of compiling economic statistics since the Second World War. But their value is diminished by the fact that, particularly in the short term, they are often only samples, and that they are not as timely as might ideally be desirable. Increasing availability of “big data” and of administrative data at disaggregated levels opens up possibilities for more timely and accurate estimation than has hitherto been possible. These new data sources may never fully replace the traditional ones; but they will become more and more important. To take an example, prices scraped from internet sites or the data generated from supermarket checkouts can in principle yield much more timely and detailed data than could direct collection alone. Satellite and other “Earth observation” data is capable of illuminating many aspects of economic activity and is available near instantaneously. Income tax data or Value Added Tax returns, similarly, can give more timely and detailed information than has traditionally been possible.

These new potential data sources involve challenges of their own if they are to be fully exploited. Until quite recently, one constraint was the computational capacity needed to manipulate and organise what are often vast data sets. But with continuing advances in data science, computational issues are no longer major obstacles to progress. More significant issues are likely to be how best to exploit the new data for genuine statistical purposes while maintaining personal and corporate confidentiality. Similarly, commercial issues need to be considered thoroughly. Big and administrative data sets are often of considerable commercial value. How best the public good can be served needs careful working though. Of course, the existence of such problems and issues only adds to the interest in measuring the economy.

It is important to bear in mind that economic statistics, like all official statistics, are not compiled for their own sake. The importance of good and accurate measurement is that it assists well-based decision making. One such set of decisions relates to economic policy. The Bank of England needs to know the true state of the UK economy for it to set interest rates. The same is the case for the Treasury when making fiscal policy decisions, or again for decision makers setting regional or local policies. But it is not just public authorities who demand and are entitled to accurate economic statistics. Commercial firms need such information to make well-informed business decisions. So do households—people—to plan their budgeting and spending.

This, in turn, places further responsibilities on official statisticians. It is not enough to say, “Here are some statistics compiled according to good practice: now make of them what you will.” Good communication of those statistics is no less important than their compilation. One aspect is that the statistics need to be presented in an accessible way so that they can easily be placed in context and understood. But good communication goes beyond that. Helping decision makers and more generally supporting public debate implies the need to “tell the story” of the statistics. What are the implications of the new statistics—or, for that matter, what they do not imply? How do they add to the evidence base and what are the key points that decision makers might want to bear in mind? The importance of communication in the statistical process has always been evident. But as modern economies become increasingly complex, good communication and telling the story of the statistics have become all the more important.

There is, in fact, an important loop back from communication to the prior compilation of the statistics. If the new statistics make it difficult to tell a coherent story—they do not fit well with other evidence and it is not easy to corroborate them—this is an important warning bell. It would usually be sensible in such circumstances to re-examine the compilation of those statistics. Such scrutiny may well confirm their validity and indeed the economy often does produce surprises. But it is also possible it might reveal issues in the compilation that can then be addressed. In this way, telling the story forms an important part of a thorough quality assurance mechanism.

Given these major new challenges and opportunities in the field of economic measurement, it is perhaps unfortunate that a gap has opened between measurement and other aspects of economic studies over the last few decades . Forty years ago, the major journals characteristically included articles, not only on economic theory and application, but also on the methodologies for the measurement of economic phenomena, to which the theory was to be applied. This became much less the case in subsequent years. Fortunately, however, the last few years have seen a revival of interest in the measurement field, with growing appreciation, not only of its importance, but also of the range and depth of issues where research would be both stimulating and pay dividends.

This book is intended to help promote this re-convergence of measurement with the rest of economics. The original idea for such an undertaking came out of discussions in the Office for National Statistics Economic Experts Working Group, from senior members of the UK economics profession. Subsequent consultation, in particular though the good offices of the Economic Learning Network—to whom the editors would like to record their gratitude—confirmed that this would be widely welcomed, as well as helping sharpen up what would be of most value. We also benefited from discussions with Wendy Carlin and other leaders of the Curriculum Open-access Resources Economics Group (CORE), who assisted with formulating an approach that might be of most value.

Initially, the book will be an online product with a set of chapters devoted to key areas of economic measurement. The first chapters deal with measurement of prices and with the national accounts. The following chapters will be added progressively in the course of 2019. In future editions, each chapter will be accompanied by teaching and learning material to help exploration and discussion of the issues concerned. At the same time, we will actively invite feedback as to what works well and what less so, where the material might be expanded or, for that matter, reduced. This information will enable iteration towards an improving resource. Of course, the economy never stands still and the material will be regularly updated to take account of the latest statistics and developments.

In due course, perhaps a couple of years after first publication, a hard copy will also be produced.

The chapters are sequenced in a broadly logical order:

However, teachers and students will not need to follow the sequence rigidly and “mixing and matching” is possible, according to the needs of particular courses.

The chapters are written by different specialist authors. However, the extent appropriate, the material is organised around a common framework. Generally, while avoiding an excessively rigid approach, each chapter sets out:

In future editions, the chapters will include case studies and exercises for students where these might help to illuminate the issues discussed and to stimulate thinking. The aim is partly to show what statistics are available and the issues that surround them, but at least as importantly to give a basis for critical appraisal of what the statistics mean and of their implications.

Jonathan Athow
Guiliana Battisti
Joe Grice
Ed Palmer