Abstract
This paper establishes a reference chronology for the Russian economic cycle from the early 1980s to mid-2015. To detect peaks and troughs, we tested nine monthly indices as a reference series, three methods of seasonal adjustments (X-12-ARIMA, TRAMO/SEATS, and CAMPLET), and three methods for dating cyclical turning points (local min/max, Bry–Boschan method, and Markov-switching model). As these more or less formal methods led to different estimates, any sensible choice was only possible on the grounds of informal considerations. The final set of turning points looks plausible and separates expansions and contractions in an explicable manner, but further discussions are needed to establish a consensus between experts.
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Notes
A business cycle is formed from a sequence of expansions and contractions in general economic activity; growth cycle represents waves of positive and negative deviations from the long-run trend; and growth rate cycle (or acceleration cycle) is a sequence of accelerations and decelerations of economic dynamics. Sometimes the turning points of all these cycles coincide, sometimes not. For more details see Mazzi and Ozyildirim (2017), esp. pp. 51–56.
The NBER US Business Cycle Dating Committee; The CEPR Euro Area Business Cycle Dating Committee; the Brazilian Business Cycle Dating Committee (O Comitê de Datação de Ciclos Econômicos (CODACE); the Investigation Committee for Business Cycle Indicators ESRI (Japan), etc.
And more, there is even a certain skepticism concerning the cyclicity of the modern Russian economy. Some academics differ between system, structural, external, and cyclical crises and hesitate to declare if there have been any cyclical (in this narrow sense) crises in Russia. See Poletaev and Savelieva (2001), Bessonov (2005), Entov (2009), Belyanova and Nikolaenko (2012, 2013).
This does not mean that all of them are incorrect but at least one (the trough in January 1999) seems very strange.
In the past few decades, there have been several important works published concerning the economic dynamics of the USSR (see Nutter 1962; Moorsteen and Powell 1966; Greenslade 1976; Kurtzweg 1990; Noren and Kurtzweg 1993; Kholodilin 1997; Solntsev and Kholodilin 2000; Suhara 2007) or of the Russian Federation as a part of the USSR (see Alekseev 1994; Suhara 2000; Ponomarenko 2002; Smirnov 2015). Many of these were very significant in that they refuted the myth of the crisis-free planned Soviet economy. On the other hand, they always used annual time-series and hence did not allow for the monitoring of the economic activity in real time or for constructing a system of leading indicators.
See Gimpelson and Kapeliushnikov (2013) for details.
The only other paper devoted to dating cyclical turning points for Russia is Dubovskiy et al. (2015). Most of the peaks and troughs estimated by them are similar (while not identical in all cases) to the ones from our list of possible turning points (see below).
As this method is well known, there is no need to add anything except that we used its implementation in Grocer 1.5 in the Scilab 5.3.3 environment. The main concepts implemented in this procedure (see Bry and Boschan 1971, p. 21) are rather technical and may be applied not only to mature economies but also to emerging economies with a sequence of mid-term expansions and contractions in their dynamics as well. Besides the Bry–Boschan method we also tried the similar Harding and Pagan (2002) method in its monthly (modified) form, also from the same package. Usually, the results were alike to Bry–Boschan’s but there were several false turning points for the period of stagnation in 2012–2013. Hence, we did not use the turning points detected by the Harding–Pagan method in our further analysis.
For all series under consideration in this paper, HQ criterion indicated two autoregressive lags.
We have nevertheless estimated the model with switches both in mean and in variance. As expected, this specification does not improve the fit.
This implies the use of the Markov chain of order 6 with restrictions on the transition probability matrix.
Anywhere in this paper “industry” includes: mining and quarrying; manufacturing; and electricity, gas and water supply.
Only the indices adjusted with X-12-ARIMA are shown. The charts for TRAMO/SEATS and CAMPLET are available upon request. We did not perform the calendar adjustment since it requires (unavailable) time series at a much lower level of aggregation in order to generate reasonable results.
Dubovskiy et al. (2015) dated September 2012 and February 2014 as additional peaks and June 2013 as an additional trough. We think this result is owing to a short time perspective (their time series ended in the middle of 2014) and to non-critical belief in the estimates received with formal methods.
See Smirnov (2015) for details.
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The support from the Basic Research Program of the National Research University Higher School of Economics is gratefully acknowledged.
Appendix: “Longlist” of Russian Peaks and Troughs: 1981–2015
Appendix: “Longlist” of Russian Peaks and Troughs: 1981–2015
Short name of index | Time-span | TP | Local max/min | Bry–Boschan | Markov-switching | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
X-12 | T/S | C | X-12 | T/S | C | X-12 | T/S | C | |||
The end of the 1980s | |||||||||||
IO-SS | 01/81–12/92 | P | 02/88 | 01/89 | 01/89 | 12/88 | 01/89 | 01/89 | 01/90 | 08/90 | 08/90 |
Second half of the 1990s | |||||||||||
IO-RS_1 | 01/93–12/04 | T | 08/96 | 08/96 | 08/96 | 08/96 | 08/96 | 08/96 | 01/94 | 01/94 | 03/94 |
P | 11/97 | 11/97 | 11/97 | 11/97 | 11/97 | 11/97 | 03/98 | – | – | ||
T | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | – | – | ||
IO-B&B_1 | 01/90–02/07 | T | 11/96 | 11/96 | 02/97 | 11/96 | 11/96 | 02/97 | 09/94 | 05/94 | 08/94 |
P | 09/97 | 11/97 | 11/97 | 09/97 | 11/97 | 11/97 | – | – | – | ||
T | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | – | – | – | ||
IO-B&B_2 | 01/95–08/09 | T | 11/96 | 11/96 | 02/97 | 11/96 | 11/96 | 02/97 | – | – | 07/96 |
P | 10/97 | 11/97 | 11/97 | 11/97 | 11/97 | 11/97 | – | – | 03/98 | ||
T | 09/98 | 09/98 | 10/98 | 09/98 | 09/98 | 10/98 | – | – | 01/99 | ||
BAO-RS_1 | 01/95–06/07 | T | 06/97 | 11/96 | 08/96 | 08/96 | 11/96 | 08/96 | 08/96 | 08/96 | – |
P | 10/97 | 09/97 | 12/97 | 10/97 | 09/97 | 12/97 | 10/97 | 12/97 | 12/97 | ||
T | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | 09/98 | ||
2007–2009 and 2013–2015 | |||||||||||
IO-RS_2 | 01/99–10/14 | P | 02/08 | 02/08 | 02/08 | 02/08 | 02/08 | 02/08 | 07/08 | 07/08 | 07/08 |
T | 01/09 | 01/09/ | 08/09 | 01/09 | 01/09 | 08/09 | 01/09 | 01/09 | 01/09 | ||
P | 12/14 | 10/14 | 12/14 | 12/14 | 10/14 | 12/14 | – | – | 12/14 | ||
IO-B&B_3 | 01/00–10/14 | P | 05/08 | 06/08 | 06/08 | 02/08 | 06/08 | 06/08 | 07/08 | 07/08 | 08/08 |
T | 01/09 | 01/09 | 05/09 | 01/09 | 01/09 | 08/09 | 01/09 | 01/09 | 02/09 | ||
P | 05/14 | 04/14 | 05/14 | 05/14 | 04/14 | 05/14 | – | – | – | ||
BAO-RS_2 | 01/03–10/14 | P | 05/08 | 05/08 | 09/08 | 05/08 | 05/08 | 09/08 | 07/08 | 07/08 | 09/08 |
T | 05/09 | 05/09 | 05/09 | 05/09 | 01/09 | 05/09 | 01/09 | 01/09 | 05/09 | ||
P | 09/14 | 05/14 | 12/14 | 09/14 | 05/14 | 12/14 | 12/14 | – | 12/14 | ||
BAO-B&B | 01/00–10/14 | P | 05/08 | 05/08 | 09/08 | 05/08 | 05/08 | 09/08 | 07/08 | 07/08 | 09/08 |
T | 05/09 | 05/09 | 08/09 | 05/09 | 05/09 | 08/09 | 02/09 | 02/09 | 05/09 | ||
P | 09/14 | 10/13 | 10/13 | 10/13 | 10/13 | 10/13 | 09/14 | 09/14 | 01/15 | ||
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Smirnov, S.V., Kondrashov, N.V. & Petronevich, A.V. Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices. J Bus Cycle Res 13, 53–73 (2017). https://doi.org/10.1007/s41549-017-0014-9
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DOI: https://doi.org/10.1007/s41549-017-0014-9