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CYCLICAL INDICATORS IN ARGENTINA A Tool for Monitoring Economic Activity 1. Introduction The profound structural change experienced by Argentina in the early 90s and subsequent macroeconomic stability has revived interest in the analysis and monitoring of the real economy. Analysis of the features associated with the so-called economic cycle has once again moved to the center of the economic scene after decades during which inflation had been the dominant subject. One of the methods for monitoring the economic cycle is the construction of composite indicators that are both coincident and leading. Thus the US leading economic indicators published monthly by the Conference Board1 is one of the most closely-watched economic statistics in that country, having been used for many years as a guide on the future direction of the economic activity. The purpose of the cyclical indicator approach is to gain several months’ advance warning of changes in the phases of an economic cycle (either switching from recovery to recession or vice-versa) or of the speeding up or deceleration of a stage in the growth cycle (when using the methodology for the analysis of the so-called growth cycles)2 . It should be made clear that this is not an infallible technique, as it can be appreciated from the empirical evidence of countries which have developed it for decades. According to them, it is normal to find changing cyclical patters leading to premature or incorrect signals, as well as making it necessary to carry out continuous reviews. Economic cycles are recurrent sequences of alternating phases of expansion and contraction that involve a large number of different economic processes and show the fluctuations that take place in wide series for production, employment, income, trade and all other aspects of aggregate economic activity. The US National Bureau of Economic Research (NBER) has developed a series of leading, coincident and lagging economic indicators with the aim of estimating the status of the business cycles in the US economy3 . Leading economic indicators are those series that tend to change direction in advance of the economic cycle, and therefore attract the greatest attention. Coincident indicators are those that measure aggregate economic activity and thus define the economic cycle. Lagging economic indicators tend to change after the business cycle has turned up or down, later than the coincident indicators. These series are used to confirm turning points and warn that structural imbalances are taking place within the economy. 2. The Reason for Combining Indicators into Indices The primary motivation for building composite indexes for economic activity is the belief that there is no single proven and accepted cause for all the cycles observed. If different recessions are caused by different factors, then it is probable that no indicator will perform any better than any other in all cycles. Nor is there any single chain of symptoms that invariably presages such developments. Instead there are a number of frequently-observed regularities that appear to persist and play important roles in the economic cycles, although they are certainly not immutable. Study of modern economic history suggests that there are systematic changes in short-term macro-dynamics that may be linked to long-term changes in the structure and institutions and in the role and policies of government. For these reasons, after analyzing the various series to determine which are sensitive to changes in the economic cycle, it is usual to define a business cycle chronology, on the basis of which to classify the ups and downs in the period it is intended to cover. The peaks and troughs in the cycle and the movement in the coincident index, as well as in the real gross domestic product, are then used to determine which indicators consistently lead the economic cycle. There are three main reasons supporting the advisability of combining selected indicators into an appropriately-constructed index, to then monitor on a regular basis the changes taking place in such an index, as well as those that are recorded by its components: 1. Some indicators, whether leaders, coincident or lagging, tend to be more operational and useful in a certain set of conditions, while others are more suitable in different conditions. To increase the chances of obtaining true signs and reduce the risk of obtaining false readings, it is advisable to trust to a reasonably diversified series with a proven predictive potential. 2. Measurement errors by individual indicators are often large, especially in the case of recent observations based on preliminary data. As long as the errors in data in the various indicators are unrelated, the risk of a bad signal can be reduced when the series are linked. 3. In general indicators tend to react not only to cyclical fluctuations but also to frequent disturbances of all kinds, as dissimilar as general strikes, wars or financial crises. This is particularly so in the case of leading indicators, which are more sensitive. As a result, monthly changes in these series usually reflect short-term erratic movements rather than prolonged cyclical changes. A well-designed composite index can eliminate some of these disturbances. As a corollary to these reasons, when indexes are built by using series selected on the basis of common temporal patterns the failure of an individual indicator does not disqualify the method. If the fault is repeated, it can if necessary lead to the exclusion of the indicator. Unless the underlying economic process is significantly disturbed, the problem is limited to obtaining a better representation of the economic process either by improving the series or replacing it with one that performs satisfactorily. 3. Construction of Composite Indicators The technique for the building of composite indicators using leading, coincident and lagging indexes was pioneered by the National Bureau of Economic Research in the thirties. It involves studying a large number of monthly series to identify those that have a good cyclical performance (cyclical series), classifying them according to whether their peaks and troughs (in general their turning points) tend to lead, coincide or lag with regard to the dates of a reference cycle representing the evolution of economic activity levels. Selection is then made of the series that perform best according to various criteria: 1) Economic significance; 2) Statistical adequacy; 3) Timing at turning points; 4) Overall conformity to the historical business cycle; 5) Smoothness and 6) Timeliness of release date. The construction of composite indicators using leading, coincident and lagging indexes is made by using a technique that consists basically of averaging the rates of change in the component series. This method consists of: 1) calculating the symmetrical percentage variations of the component series compared to the previous month, 2) averaging the symmetrical changes using weighting factors that level out the extremes of the component series, and 3) symmetrically accumulating the average of the symmetrical changes to obtain the composite indicator. The purpose of step 1) is to make the positive and negative percentage variations comparable4 . Step 2) aims to ensure that the more volatile series do not prevail over the less volatile, providing more weighting to the former than to the latter. In international experience, leading indicators tend to show good leadership in the peaks but less leadership in the troughs, so they are more useful in predicting a recession than the end of a recession. In addition, in some exceptional circumstances they provide false warnings of recessions that do not then take place. Nevertheless, they have proven useful in predicting turning points, especially in the case of peaks, and for this reason their use is becoming widespread. 4. Use of the Composite Indicators in the Argentine Economy The application of this technique to the Argentine economy presents difficulties due to a: 1) the lack of lengthy monthly series with a good cyclical behavior, 2) the discontinuity of certain series that did perform well cyclically, 3) frequent changes of methodology in the case of many series. 4) the lag in the publication of many of the relevant series, 5) the irregularity of the evolution of the economy in recent decades (stagnation in the 80s and a sharp change in the system in the 90s). However, it has been possible to identify a small number of coincident and leading indicators that have performed well in meeting the selection criteria (see graphs on Cyclical Performance at the end of this Annex). There being no widely-recognized reference cycle such as there is in the USA, the coincident indicator has been built with special care to ensure it is representative of the level of business activity. Given the economic importance of GDP this series has been included in the coincident indicator, in spite of the fact that it is quarterly, projecting it on a linear basis as from the last month of the quarterly GDP to obtain monthly data. Where necessary monthly GDP data is obtained for the most recent months using the best available forecast for GDP for the quarter in progress. The remaining five series used for the coincident series are: • A manufacturing output index (the INDEC’s Industrial Monthly Estimator for the last segment of the series); • Total imports of goods in constant dollars; • A qualitative indicator of sales (FIEL’s Demand Trends); • Cement deliveries in tons; • Car sales in numbers of units. As can be seen from Graph 1, the coincident indicator for Argentina is closely synchronous with GDP. Six series are also used for the leading indicator: • The Buenos Aires Stock Exchange Index; • The market price of the GRA and Discount bonds (successively); • The number of new bankruptcy and creditor protection filings (inverted by means of a change in sign); • The difference between the sales series and a series on the level of inventories (also qualitative: FIEL’s Stock Levels); • The average working month for workers in manufacturing industry measured in man-hours (Total number of hours worked divided by the number of workers, both taken from the INDEC Industrial Survey); • Total VAT revenues (gross) in constant pesos. In those cases where the X-12-ARIMA program developed by the US Bureau of Census detects the presence of seasonally in the component series and considers that seasonally adjust would be advisable, the corresponding adjustment is made using the same program. Of the coincident series the only one not having identifiable seasonality is that of sales. On the other hand, in the case of the leading indicators only the indicator for bankruptcy and creditor protection filings requires seasonal adjustment. The dating of the peaks and troughs of the composite indicators is established by the application of an NBER program for the determination of turning points. This program was also used to evaluate and classify the series being analyzed. The dates of the peaks and troughs of the coincident indicator are used to determine precisely when recession and expansion begins. The leading indicator has a good overall performance, with an average lead of 7.8 months in the peaks and 3.5 months in the troughs (Table 1). In the case of only one of the six troughs in the period 1970-97 did the leading indicator not lead (coinciding with the trough of the coincident indicator). In addition the NBER program for the establishing of turning points detected two peaks in the leading indicator that were not followed by a recession: one in November 1971 and another in May 1992. In both cases there was a drop in GDP and in the coincident indicator, although of insufficient magnitude to be considered as a recession according to the program for determining turning points in the coincident indicator. In the case of the latest results being generated by these indicators5 , the coincident indicator rose by 2.7% in February 1998 compared to the previous month (Table 2), while the leading indicator fell by 1.1% in the same month (Table 3). The moving three-monthly average in the monthly rates of change for the coincident indicator was positive by 1.2%, reversing the negative percentages of the two previous months. For its part the moving four-month average in the monthly rate of change in the leading indicator was slightly negative, as in the month of January, although lesser in absolute terms (-0.9% and -0.7%, respectively) (Tables 2 and 3)6 . According to the recession signal system explained further on, in spite of the results of the leading indicator the economy is still not in any of the phases that would suggest the onset of a recession in the near future, so that it is considered that the period of expansion in economic activity is to continue. 5. System of Signals and Retrospective Analysis of the Predictive Capacity of the Leading Indicator So that the leading indicator may be of use in predicting a coming recession it is necessary to interpret it in the light of a system of signals that will help to indicate when a recessive environment exists. Such a system has been designed specifically for data on Argentina, which tends to be more volatile than that of other countries. When a recession is nearing the sequence of events is usually as follows: 1) in the expansion phase the percentage variations with regard to the previous month for both the coincident and leading indicator are positive;2) in the first phase of recession signals (Alert -1) there begin to be negative variations in the leading indicator, sometimes interspersed with positive changes; 3) in the second phase of recession signals (Alert -2) there also begin to be negative variations in the coincident indicator, sometimes interspersed with positive variations, while the leading indicator will have already accumulated a substantial fall from its previous peak; 4) in a confirmation phase of a recession the coincident indicator will have already accumulated a substantial fall from its previous peak. The signs of alert can fade temporarily during several months, then repeating themselves in a confirmation stage. When an Alert-2 phase leads into a confirmation stage it is probable that a recession has already begun. To smooth the percentage variations and thus be able to discount the positive variations that may be interspersed with a predominance of negative variations, moving averages (MA) of percentage variations are calculated. As the leading indicator is more subject to noise than the coincident indicator it should be smoothed out using a moving average covering more months. Experience has indicated that a MA(3) for the coincident indicator and MA(4) for the leading indicator would be appropriate. Any greater smoothing out would excessively delay the moment at which the recession signal is perceived, and any lower smoothing out would not generate a clear signal as there would be positive percentage variations in the middle of the series. Using moving averages, the phases of 1) Expansion, 2) Alert-1, 3) Alert-2 and 4) Confirmation are structured as follows: 1) The moving average MA(3) for the percentage variations of the coincident indicator and the moving average MA(4) for the percentage variations in the leading indicator are both positive. 2) In month t0 the moving average MA(4) for percentage variations in the leading indicator turn negative and continue to reflect negative values in subsequent months. 3) In month t1 t0 the situation in point 2) continues in force and the moving average MA(3) for the percentage variations of the coincident indicator turns negative. In addition, in t1 the leading indicator records an accumulated decline of at least 5% from a recent peak. 4) In month t2 t1 the factors in 3) continue in force and the coincident indicator records an accumulated fall of at least 5% from a recent peak. With the reaching of Alert-1 the first sign has been given of a possible recession. Once Alert-2 is recorded, it is probable that the economy is experiencing a recessive process. The beginning of the Confirmation is a sign that the recession began some months earlier. Based on the experience of the last five recessions, confirmation took place between three and seven months after the peak in the coincident indicator. It is important to bear in mind that when a series that was rising begins to fall back it cannot be determined whether a peak had been reached or whether the fall is temporary. The system of signals is designed precisely so as to help determine when a peak is involved. The limited lead in troughs makes the design of a system to signal the end of a recession of limited practical use. On the basis of the experience in the period 1970-97, this system of signals works acceptable although not infallibly. The system failed in the case of the recession that began in December 1974, which was unusual in that after generating an Alert-1 signal it faded for three months before re-appearing. In addition the cumulative fall in the coincident indicator exceeded 5% one month before the same happened to the leading indicator. In the last five recessions this system of signals has worked very well. The recession that began in June 1987 was unusual in that after the Alert-2 stage was reached in November 1986 it disappeared, generating a complete sequence of signals as from July 1987. During the decline in economic activity levels in mid-1992, which did not qualify as a recession according to the turning point program, Alert-2 was reached (in September 1992) without first passing through Alert-1, and the warning then faded without Confirmation (the accumulated drop in the coincident indicator reached 3.6%). Table 4 shows the historical performance of the recession signal system. 1 This was one of the statistical responsibilities transferred to the Conference Board at the end of 1995 by the US Department of Commerce. 2 In countries where there are no time series available that are reliable going back several years it is very difficult to define long-term trends and thus patterns for long-term growth, for which reason efforts have to be centered on analysis of business cycle indicators rather than on growth cycles ones. 3 The popularity of the “leading indicators” in the USA has accelerated the development of similar indicators by other countries. Klein and Moore have described how a wide range of economic indicators that have become strong cyclical indicators in the US also perform very well as such in a large number of market-oriented economies. 4 In the case of ordinary percentage variations to rise from 50 to 100 is an increase of 100%, while to drop from 100 to 50 is a 50% reduction. 5 At the date of this Report only five of the six series making up each of the indicators were available: in the case of the coincident indicator there is no information on imports for February, and in the case of the leading indicator the information on the average monthly working month is still missing. 6 The use of moving averages and the optimum number of months to be averaged for each index is explained in the following section.