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Chapter 3. Tools of the Trade

Author(s):
Ayhan Kose, and Marco Terrones
Published Date:
December 2015
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Chapter Epigraphs

To determine the cyclical behavior… of different economic activities, we should have a method that yields comparable results when applied to a wide variety of time series. If possible, the results should be in quantitative form, that is, we should measure the cyclical behavior of economic activities… We need to know how the specific cycles of different activities are related to one another in direction of movement, in the timing of their peaks and troughs, and in the duration of their expansions and contractions… If there is [consensus among these movements], the dates of specific-cycle troughs of individual activities must be concentrated around certain points of time, and the like must be true of specific-cycle peaks. We can then proceed to identify business cycles… assign approximate dates to their troughs and peaks, and plunge into a study of behavior of different economic activities within the periods thus marked off.

Arthur F. Burns and Wesley C. Mitchell (1947)

What tools do we need to study the features of global recessions and recoveries? The answer is straightforward: we need to construct a comprehensive database and employ robust methodologies widely accepted by the economics profession. This chapter introduces our global database, which includes a wide range of macroeconomic and financial indicators for a large number of countries and describes the two complementary methods we use to identify the dates of global recessions and recoveries.

A Global Database

Our extensive database uses annual series of wide-ranging indicators of economic activity for a large number of countries.1 Some of these are the components of national income accounts, including gross domestic product (GDP), consumption, and investment. Others are used to track additional measures of activity and prices, such as industrial production, international trade, unemployment, inflation, and commodity prices. The database also includes various measures that capture fluctuations in financial markets: international capital flows, interest rates, credit, and equity and house prices.

What is a recession? How we can gauge when an economy has slipped into recession.

Over what period is it best to study global recessions and recoveries? It would be possible to construct a measure of the global business cycle using more than a century of annual data if we focused on a small set of countries and employed a narrow set of activity indicators. For example, using small data sets, the 2009 global recession has often been compared with the Great Depression of the early 1930s.2

Our objective here is to provide a systematic analysis of “modern” global recessions and recoveries using multiple measures of global activity and a sample that truly represents the world economy. Our database of annual series therefore covers 163 countries during 1960–2012. We rely mainly on well-known data sets, but we also use other sources. We study the ongoing recovery using the GDP forecasts of the IMF World Economic Outlook for 2013 (we provide additional information about the country coverage, variables in the database, and their sources in Appendix B).

We divide the countries in our sample into three functional groups: advanced economies (24), emerging market economies (30), and other developing economies (109). The main distinction between the emerging market and other developing economies is that the former have attained a much higher level of integration into global trade and finance.3 For instance, since the mid-1980s the average growth rate of total trade (exports plus imports) has been more than twice the growth rate of GDP for the emerging market economies; the corresponding figure for the other developing economies is much lower. Emerging market economies have also received the bulk of private capital flows going from advanced economies to the rest of the world over the past quarter century.

Our regional country samples closely follow the standard geographical groupings, but we also examine groups of emerging market and developing economies in different regions. In addition, we sometimes consider well-known country groups, such as the euro area (Appendices B.2 to B.4 list countries included in each group).

Depending on our objective and data availability, the coverage of our database differs in some chapters. For a smaller group of advanced and emerging market economies, for example, we use higher-frequency, quarterly macroeconomic and financial time series in a few chapters when we analyze the implications of recessions and recoveries accompanied by periods of financial disruptions and uncertainty. In Chapter 11, we use a smaller sample of countries because we include only those with sufficient data coverage to conduct our empirical exercise. We provide the details of these changes in the relevant chapters.

Methodology: Let’s Date

Our measure of the global business cycle is the annual growth rate of real world GDP per capita. This is the difference between the weighted real GDP growth of countries in our sample and world population growth.4 A per capita measure is useful because it accounts for the variation in population growth rates over time and across countries. It also partly dampens the impact on the global business cycle of the significant differential between trend growth rates of advanced economies and emerging market and developing economies. In addition, real world GDP per capita is a primary measure of the overall well-being and living standard of a typical world citizen.

Real world GDP growth per capita is a primary measure of the well-being of the typical world citizen.

We consider two types of weights in computing the growth rate of global GDP: purchasing-power-parity weights and market weights. Purchasing power parity calculates the rate at which the currency of one country would have to be converted into another to buy the same assortment of goods and services. Market weights, in contrast, are based on the conversion of domestic currencies into the (U.S. dollar) exchange rate prevailing in the open market. Since purchasing power parity reflects the fact that goods and services that are not traded internationally tend to be cheaper in low-income countries than in high-income countries, the value of output in low-income countries tends to be higher using purchasing power parity than using market rates.5

A quick glance at the data clearly shows the benefits of employing a per capita measure (Table 3.1). The average growth of world GDP (using purchasing-power-parity weights) is 3.8 percent during 1960–2012, but it fluctuates over time (from 5 percent in the 1960s to 2.9 percent in the 1990s). Output and population growth rates differ substantially across country groups. For example, output growth is on average 3 percent in advanced economies and 5 percent in emerging market economies. Average population growth is 0.7 percent in advanced economies but much larger in other groups: 1.7 percent in emerging market economies and 2.4 percent in other developing economies. Average population growth has declined both globally and in different groups of economies over time. Nonetheless, average global GDP growth picked up during the early 2000s because growth in emerging market and other developing economies accelerated markedly after registering consecutive declines during the previous four decades.

Table 3.1Annual Growth Rates of Output and Population(in percent)
1960s1970s1980s1990s2000s1960–2012
Market-weighted output
World4.924.163.182.592.733.44
Advanced economies4.793.492.982.401.552.92
Emerging market economies5.775.664.243.655.635.01
Other developing economies5.525.171.811.714.903.85
Purchasing-power-parity-weighted output
World5.074.463.222.923.673.83
Advanced economies5.023.612.902.541.583.00
Emerging market economies5.155.884.243.806.115.10
Other developing economies5.246.331.962.195.144.21
Population
World1.981.921.711.501.241.64
Advanced economies1.060.820.580.680.620.74
Emerging market economies2.242.101.791.441.041.67
Other developing economies2.512.432.452.322.212.37
Market-weighted output(per capita)
World2.952.241.471.091.491.81
Advanced economies3.732.672.391.720.932.18
Emerging market economies3.533.562.452.214.593.34
Other developing economies3.012.74-0.64-0.602.701.48
Purchasing-power-parity-weighted output(per capita)
World3.092.541.511.422.422.19
Advanced economies3.962.792.311.850.962.26
Emerging market economies2.913.782.452.365.073.42
Other developing economies2.723.89-0.49-0.132.931.83
Note: Market-weighted (purchasing-power-parity [PPP]-weighted) output is the gross domestic product growth rate of the respective group using market (PPP) exchange rates. Per capita market-weighted (PPP-weighted) output growth rate is the difference between market-weighted (PPP-weighted) output growth and population growth. Each column corresponds to the country group average in the respective decade. The 2000s period includes 2000–12.
Note: Market-weighted (purchasing-power-parity [PPP]-weighted) output is the gross domestic product growth rate of the respective group using market (PPP) exchange rates. Per capita market-weighted (PPP-weighted) output growth rate is the difference between market-weighted (PPP-weighted) output growth and population growth. Each column corresponds to the country group average in the respective decade. The 2000s period includes 2000–12.

We use two methods to identify the turning points in global activity: a statistical method and a judgmental method. Both are widely used in the context of national business cycles. Although the two methods use different information sets, both rely on the “classical” definition of a business cycle: economic expansions, marked by increases in many measures of economic activity, followed by broad contractions in activity. These complementary methods help us arrive at our definitions of the global recession and recovery.

Statistical Method

In deciding when a particular country is in recession, economists often use statistical procedures to date the peaks and troughs of a key indicator of economic activity, such as the country’s real GDP. The specific dating method we use provides a simple but effective procedure to identify turning points.6 Moreover, it is convenient because the turning points identified are robust to the inclusion of newly available data.7

The algorithm requires a search for local maxima and minima over a given period. It then selects pairs of adjacent, locally absolute maxima and minima that meet certain censoring rules (Figure 3.1). Our methodology requires a minimum two-year duration of a cycle and a minimum one-year duration of each of the cyclical phases. A complete cycle goes from one peak to the next with its two phases: the recession phase (from peak to trough) and the expansion phase (from trough to the next peak).8

Figure 3.1Evolution of a National Business Cycle

Note: This schematic represents a complete national business cycle comprising of two phases: an expansion and a recession. The expansion is the phase of the cycle between a trough and the following peak whereas the recession is between a peak and the following trough. P is the “peak” and T the “trough” of the cycle. Q is the point where the level of output reaches its previous peak and a recovery phase is completed (as implied by some definitions in the literature).

These censoring rules imply that a global recession takes place when the growth rate of our measure of global economic activity is negative. However, this is a purely mechanical rule for identifying a global recession. In reality, many other factors affect the evolution of global economic activity in real time. It is precisely because of this reason that institutions such as the National Bureau of Economic Research (NBER) in the United States and the Centre for Economic Policy Research (CEPR) in the United Kingdom use a comprehensive set of indicators of activity and employ a judgmental approach to identifying the turning points of national and regional cycles.9

Judgmental Method

An alternate method for identifying business cycles also has a long history and finds its roots in the pioneering work of Arthur Burns and Wesley Mitchell (1947), who laid the methodological foundations of the analysis of business cycles in the United States. They define a national business cycle to “consist[s] of expansions occurring at about the same time in many economic activities, followed by similar general recessions, contractions, and revivals which merge into the expansion phase of the next cycle.”

In 1978, the NBER established its Business Cycle Dating Committee to determine the dates of recessions in the United States. The CEPR has performed a similar task for the euro area since 2002. In contrast to a purely statistical approach, the NBER and CEPR date business cycle peaks and troughs by looking at a broad set of economic indicators and reaching a judgment on whether a preponderance of the evidence points to a recession.10

The NBER uses GDP, industrial production, retail sales, employment, disposable income, and initial claims for unemployment insurance. Because these indicators can present conflicting signals about the direction of an economy, the judgmental approach can sometimes be difficult to employ in real time. The CEPR’s task is even more complex because, in addition to looking at multiple national indicators, it has to make a determination of whether the euro area as a whole is in recession.

We apply the judgmental method at the global level by looking at several indicators of global activity—real GDP per capita, industrial production, unemployment, trade and capital flows, and energy consumption. We focus on these indicators since the global analogs of some of the variables used by the NBER and CEPR are not available for a large number of countries over a long period. However, the measures we employ capture the essential information at the global level provided by the main variables used by these institutions. Moreover, our measures provide a broad perspective on the evolution of global business cycles. In addition to the standard activity measures, such as GDP, industrial production, and unemployment, the other variables we use capture changes in global trade and financial (capital) flows and global energy (oil) consumption.

Defining Global Recession and Global Recovery

Armed with these two approaches, we can now define the concepts of global recession and global recovery. A global recession is a contraction in world real GDP per capita accompanied by a broad decline in various other measures of global economic activity. A global recession begins just after the world economy reaches a peak of activity and ends when it reaches its trough. Since we use annual data, a global recession lasts at least one year.11

The recovery phase from a recession has been widely studied for national business cycles.12 Recovery is often defined as the early part of the expansion phase that follows a recession. In parallel, a global recovery is a broad rebound in worldwide activity during one to three years following a global recession. It simply refers to the period of increasing economic activity after a global recession. We consider the recovery phase to be associated with the first year following the trough of the global business cycle. We also examine the recovery in the first three years following a global recession, considering the possibility that a global recovery can take longer than a year.

A global recession is a contraction in world real GDP per capita accompanied by a broad decline in various other measures of global economic activity. A global recession begins just after the world economy reaches a peak of activity and ends when it reaches its trough.

Building on an Earlier Contribution

We are not the first ones to define a global recession. Kenneth Rogoff, former IMF chief economist, and his coauthors defined the concept of global recession in a short piece they wrote for the IMF’s World Economic Outlook in 2002. Their objective was to figure out whether the 2001 worldwide downturn was a global recession.13

As we do here, they also considered a measure of GDP per capita to identify episodes that could be labeled as global recessions. They also noted that the GDP per capita measure is an important metric, but it was at the same time a rather conservative one to pin down global recessions. They emphasized the relevance of the judgmental method and showed how it could be used in the context of the global economy. However, they focused on only two measures of global activity (output and industrial production), whereas we use a more comprehensive set of activity indicators. Moreover, their brief analysis did not cover global recoveries as we do here.

Our book on global recessions and recoveries was motivated by the events that have transformed the global economy since 2006. However, our approach to these concepts was certainly inspired by the work of Rogoff and his colleagues.14 As we explain in the next chapter, the dates of global recessions they identify correspond with ours. We also reach the same conclusion about the classification of the 2001 episode, as we discuss in Chapter 4.

Time to Get to Work

This chapter provides a disciplined framework for identifying global recessions and recoveries. It is time to put this framework into practice and get to the real work of determining the dates of global recessions and recoveries and documenting the events around these turning points.

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