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Predicting Recessions and Slowdowns: A Robust Approach Pami Dua Delhi School of Economics, University of Delhi and Economic Cycle Research Institute, New York Presentation to 15th Conference of Commonwealth Statisticians February 7, 2011 Objectives Can we Predict Recessions? Business Cycle Analysis: Background Indicator Analysis: A Robust Approach Can we Predict Recessions? The sheer severity of the Great Recession for many developed economies – most importantly the United States – motivates the vital question of whether the recession, or the crisis that triggered it, could have been foreseen. Can we Predict Recessions? A few years ago, the International Monetary Fund completed a 63country study of the ability of economists’ consensus forecasts to predict recessions. The IMF concluded: “The record of failure to predict recessions is virtually unblemished.” The real challenge is not to identify the best model to predict recessions ex post in a specific economy over a given time frame, but to identify approaches that are robust enough to perform well in real time under diverse structural conditions. Can we Predict Recessions? Key is to make timely recession calls in fast-changing emerging markets as well as in mature economies undergoing material structural changes. Thus it would do little good to develop models optimized on the basis of past performance if the future is likely to be quite different. Real time forecasting failure cannot therefore always be blamed on “parameter drift” or “this time it’s different” as an excuse for forecast error. Can we Predict Recessions? Econometric models are “falsifiable” since these can be tested against real data. On the other hand, the leading indicator approach relies on descriptive observations of sequences of events in the vicinity of cyclical turning points that are not ‘falsifiable’. The pioneers of business cycle research were Wesley C. Mitchell and Arthur F. Burns, who in 1938 identified the very first “leading indicators of cyclical revival” . They were later joined by Geoffrey H. Moore who developed the first ever list of “leading indicators of cyclical revival and recession.” Can we Predict Recessions? Steps in indicator analysis: Define a business cycle Define a recession Determine the reference chronology – benchmark for determining recession-forecasting performance Identify leading indicators on the basis of the reference chronology Business Cycle Analysis: Background The Classical Business Cycle “Business cycles are a type of fluctuation found in the aggregate economic activity of nations that organize their work mainly in business enterprises. A cycle consists of expansions occurring at about the same time in many economic activities, followed by similarly general recessions, contractions, and revivals which merge into the expansion phase of the next cycle. This sequence of changes is recurrent but not periodic. In duration business cycles vary from more than one year to ten or twelve years; they are not divisible into shorter cycles of similar character with amplitudes approximating their own.” -- Burns and Mitchell, 1946 Recessions and Expansions A recession is the phase of the business cycle marked by pronounced, pervasive and persistent declines in the key measures of aggregate economic activity, i.e., output, employment, income and sales. An expansion is the phase of the business cycle marked by pronounced, pervasive and persistent increases in the key measures of aggregate economic activity, i.e., output, employment, income and sales. Alternating expansions and recessions make up the business cycle. Business Cycles, Growth Cycles, Growth Rate Cycles The business cycle is a consensus of cycles in many activities, which have a tendency to peak and trough around the same time. A growth cycle traces the ups and downs through deviations of the actual growth rate of the economy from its long-run trend rate of growth. Growth rate cycles are the cyclical upswings and downswings in the growth rate of economic activity. Business Cycles and Growth Rate Cycles Indicator Approach to Monitoring Economic Activity A coincident indicator measures current economic activity. It turns down when the economy turns down and up when the economy turns up. A leading indicator predicts future economic activity. It turns down before the economy enters a recession and up before the expansion begins. Composite Indexes A composite index is constructed from a number of individual economic indicators. By construction, it has more information than any individual component of the index. A composite coincident index comprises variables that collectively represent the current state of the economy. It indicates whether the economy is currently expanding or is in a recession. A composite leading index includes variables that collectively anticipate turning points of the business cycle. This is used as a predictive tool to gauge if and approximately when a recession or an expansion might take place. Leading Indexes can Time Turns Lead Leading Index Target The Recession as a Vicious Cycle A recession occurs when a decline in some measure of aggregate economic activity sets off cascading declines in the other coincident measures of activity. Thus, when a dip in sales causes a drop in production, triggering declines in employment and income, which in turn feed back into a further fall in sales, a vicious cycle results and a recession ensues. This domino effect of the transmission of economic weakness from sales to output to employment to income, feeding back into further weakness in all of these measures in turn, is what marks a recessionary downturn. This effect spreads from industry to indutry, region to region, and indicator to indicator. The Expansion as a Virtuous Cycle At some point, the vicious cycle is broken and an analogous self-reinforcing virtuous cycle begins, with increases in output, employment, income and sales feeding into each other – the hallmark of a business cycle expansion. How the Virtuous Cycle Works Turning Points: Business Cycle Peaks and Troughs Because recessions can be characterized as vicious cycles and expansions as virtuous cycles, the transition points between the vicious and virtuous cycles, based on the consensus of the coincident indicators (output, employment, income and sales), properly mark the start and end dates of recessions (peaks and troughs). That is also why “two down quarters of GDP” is not an adequate definition, nor a proper criterion, for a recession. Business Cycle Chronologies The historical dates of business cycle peaks and troughs are thus based on the consensus of the dates of the peaks and troughs in the broad measures of output, employment, income and sales. For 20 economies, ECRI maintains business cycle peak and trough dates based on the same approach. The up-to-date list of business cycle dates for 20 countries including the U.S. is available here: http://www.businesscycle.com Growth Rate Cycle Chronologies Growth rate cycles are made up of alternating periods of rising and falling economic growth. They are based on the growth rates of the coincident indicators whose levels relate to business cycles, and do not rely on estimation of the current trend. Hence, growth rate cycles, along with business cycles, are useful for real-time monitoring of the economy. For this reason, ECRI maintains growth rate cycle chronologies for 20 countries: http://www.businesscycle.com Turning Points are Hard to Predict Forecast Error Target Consensus Forecast Taming the Cycle Effects of Higher Trend & Lower Volatility on Business Cycles 8 Reducing Recessions: Raise trend rate of growth Lower amplitude of cycles 4 0 Recessions -4 8 4 0 Higher Trend: No Recessions -4 88 4 00 -4 -4 Lower Volatility: No Recessions Hence the need to anticipate After Chrysler’s near-death experience in early 1980’s the then Chairman, Lee Iacocca told his Chief Economist: "All I want from you is that you let me know six months before the next downturn." Robustness of Indicator Analysis Based on an understanding of business cycle theory, Moore examined the empirical record of the behaviour of a list of indicators at business cycle peaks and troughs. This empirical testing – based on U.S. data from 1870 to 1938 – determined the final selection of Moore’s 1950 list of eight leading indicators of recession and recovery. This entire process was rooted in business cycle theory: not in falsifiable statistical models, to be sure, but in a theoretical, conceptual understanding of the drivers of the business cycle, nevertheless. Empirical testing played only a secondary role in this process. Robustness of Indicator Analysis Nearly half a century later, Moore asked the question: we know that the original leading indicators anticipated both recessions and recoveries in the late 19th and early 20th centuries, but what have they done for us lately? He tested their “out-of-sample” performance, so to say, in the second half of the 20th century (Moore and Cullity, 1994). All the leading indicators continued to lead at US business cycle turning points. Robustness of Indicator Analysis We recently completed a similar analysis for the US from the mid 20th century through the early 21st century, including the Great Recession. Results are similar. We also gathered data on the same indicators, or their closest equivalents, in all the Group of Seven (G7) economies other than the U.S. in the postwar period. Remarkably, when we compared their turning points with the respective business cycle chronologies established independently by ECRI on the same basis as in the U.S., their performance held up. Robustness of Indicator Analysis Next, we conducted a similar analysis, but on the basis of growth rate cycles (acceleration-deceleration cycles, consisting of alternating cyclical upswings and downswings in economic growth) rather than classical business cycles. We found that the growth rates of the same leading indicators continued to lead the respective growth rate cycle turning points, which had been determined independently by ECRI for all the G7 economies Average Leads, in Months, of Eight Leading Indicators Selected in 1950 9 8 7 6 5 4 3 2 1 G7 excl. U.S. 0 Before 1938: Business cycles U.S. 1948-2008: Business cycles 1948-2008: Growth rate cycles Robustness of Indicator Analysis We also constructed a composite leading index out of Moore’s original list of U.S. leading indicators. That leading index covers 107 years and 21 recessions, including the 1907-08 and 1920-21 depressions, the entire period of the Great Depression, and the more recent Great Moderation. Again, no data fitting was involved in creating the index. So how did the Index of Original Leading Indicators (IOLI) perform during the Great Recession, which caught so many by surprise? As a matter of record, it peaked in July 2007, five months before the official December 2007 U.S. business cycle peak. It subsequently troughed in March 2009, three months before the June 2009 U.S. business cycle trough. Robustness of Indicator Analysis Over its 107-year span, the IOLI exhibits a median lead of 4.5 months at US business cycle peaks and three months at business cycle troughs, leading at 93% of business cycle turning points. In the out-of-sample post-war period, the statistics are similar: the IOLI has a median lead of six months at business cycle peaks and three months at business cycle troughs, leading at 91% of business cycle turning points. Robustness of Indicator Analysis What we have shown is that, when evaluated against those objective cyclical benchmarks, the original leading indicators of recession and recovery – selected primarily on a conceptual basis – continue to exhibit remarkably robust performance under a wide range of conditions. Whether we are faced with the specific likelihood of more frequent U.S. recessions, as ECRI’s research suggests, or with unforeseeable changes in structural conditions that may shape the next cycle, it is our belief that it would surely be prudent to rely on a time-tested, robust approach to business cycle forecasting. Way Forward The field of economic forecasting faces formidable challenges in the years ahead. Robust leading indicators can provide only a partial answer. Unlike econometric models, leading indicators are designed to predict only the timing of cyclical turning points, not forecasts of the magnitude of economic variables. Nor can they answer “what if” questions which are central to policy decisions. This approach should therefore be seen as a complementary tool but one that is capable of providing invaluable guidance in the lead-up to recessions and recoveries, preventing decision makers from being blindsided by the inevitable turning points in years to come. Thank You! Annualized Growth in U.S. Coincident Indicators in Postwar U.S. Expansions (%) 12 10 8 6 4 2 Industrial Production Mfg &Trade Sales 0 49-53 54-57 Personal Income 58-60 61-69 70-73 GDP 75-80 80-81 82-90 Employment 91-01 01-07 Three Key Aspects of the Economy Economic Growth Employment Inflation The State of the Art Inflation Imports Manufacturing Trade Balance Construction Economic Growth Non-Mfg Non-Financial Employment Exports Services Financial Mfg Domestic Long Leading, Weekly Leading, Short Leading & Coincident Foreign Trade Employment Future Inflation Gauge Home Prices Crack of the Bullwhip Around the globe, recession is being transmitted in amplified form to the more export-oriented economies Ruth Mack, a colleague of ECRI founder Dr. Geoffrey H. Moore, uncovered this link in a study of shoe, leather and hides When Mack did her study, shoes were not impulse buys but expensive products that consumers would buy in good times In not so good times, consumers would get their shoes repaired and postpone the purchase, implying that shoe demand was moderately cyclical Crack of the Bullwhip An increase in inventories of shoes and shoe leather due to a drop in demand resulted in shoemakers reducing production and orders for leather Thus slowdown in shoe demand would result in an actual decline in the demand for leather, which is made from cattle hides This would trigger a sharp plunge in the demand for hides Thus small shifts in demand growth at the consumer level are amplified through the supply chain into big swings in demand as we move up the supply chain away from the consumer This is the BULLWHIP EFFECT because a little flick of the wrist produces a big arc at the end of the whip Shoe-Leather-Hide Sequence: The Bullwhip Effect Frontline demand is cyclical Midline demand is more cyclical Demand early in the supply-chain is most cyclical but supply is relatively insensitive, so prices are highly cyclical Shoe Demand: Growth Slows Leather Demand: Level Falls Hides Demand: Level Plunges Bullwhip Effect Bottom Line Contractions in the global economy are concentrated in the developed countries Economies that are heavily involved in the exports of manufactured goods will be lashed by the Bullwhip Effect and their suppliers – especially the producers of industrial commodities, including oil – will be in even worse predicaments