**4. Result**

### **4.1 Hodriсk-Preskott filtering application**

We applied the Hodriсk-Preskott filtering method to isolate the cyclic component of GDP. We took GDP data in US dollars at 2015 prices, in local currencies at constant prices, and in current prices in US dollars and local currencies. Thus, using different GDP data, we can not only identify the cyclical component but also analyze the contribution of local currency inflation and exchange rate to the result. In this case, it

is worth noting that the exchange rate of the Chinese currency is not floating, as well as the rate of the Russian ruble is significantly affected by methods of administrative regulation such as "budget rule" and central bank interventions. Both the Russian and Chinese currencies are far from the free-floating exchange rate model.

**Figure 1** shows the result of output gaps: Russia, India, and China calculated from GDP data in US dollars in 2015 prices. We believe that this calculation is cleared of the parameter of local currency inflation and the exchange rate and can be taken as a base. In addition, we logarithmized the original time series in order to bring it to an additive model. **Figure 1** shows that the cyclical component of economic growth looks different in all three countries.

For India, the constant random fluctuations around the GDP trend line are normal and reflect that the output gap is alternately positive and negative. It means that the economy works intensely and with a shortage of resources for a while, and then there is a period of recovery.

The output gap of all three countries in the base case is characterized by a period of positive values from 1999 to 2005. It is a period of rapid growth of emerging markets in the global economy. It means that economies have used their resources excessively and are now legitimately facing a slowdown in economic growth. The same situation was observed in Japan in the 1970s and 1980s, when rapid growth was replaced by the so-called lost decade. Today, we see a slowdown of the Chinese economy and almost zero economic growth in Russia.

However, in Russia, if we consider the basic version of the output gap calculation and the calculation in current prices in national currency, the picture is significantly different, and we see a huge negative effect associated with hyperinflation of the ruble and the instability of the national currency in the period from 1991 to 1999 (**Figure 2**) When analyzing economic cycles, we need to consider that emerging markets have no solid economic basis for market self-regulation. In addition, oftentimes in countries

*Hodrick-Prescott Filtering of Large Emerging Economies and Decoupling Hypothesis DOI: http://dx.doi.org/10.5772/intechopen.112176*

**Figure 2.**

*Russian output gap in constant USD in 2015 year prices and in local currency.*

such as China and Russia, economic regulation is performed by administrative methods, and the values of economic growth rates do not depend not only on the development of market mechanisms and the state of the economic environment but also on the level of government spending. This is why Russia has shown resistance to sanctions pressure, because after the 2008 crisis, Russia has been steadily replacing market mechanisms of regulation with administrative ones, which, when formally calculated, produce positive results, but the quality of such economic growth is left out of the picture.

However, we see an increase in the efficiency of the Russian economy in 2008, 2015, and 2020. In 2008, administrative regulation of the Russian economy was strengthened as a response to the global economic crisis, in 2015 as a response to the first wave of sanctions, and in 2020 in connection with the COVID pandemic. Such dynamics indicates the presence of a short-term effect from the replacement of market mechanisms of regulation with administrative ones. Then, when analyzing economic cycles and studying the degree of integration of countries, it is necessary to take into account the basis of this integration, whether integration is connected exclusively with administrative regulation.

Additionally, we calculated the impact of dollar inflation and inflation of the local currency, as shown in **Figures 3** and **4**, and found that the devaluation of the national currency gives a positive, but very short-term effect.

The third diagram shows the line reflecting the impact of inflation on economic growth for Russia in the period from 1991 to 1999, a period of sharp transition from administrative methods of regulation in Russia to the formation of a market economy. It is time when Russia faced huge negative effects associated with the devaluation of the ruble and hyperinflation. The excessive governmentalization of the Russian economy and the reliance on administrative methods of regulation today in the future may lead to the fact that the abrupt lifting of sanctions, for example, will be more disastrous than the sanctions themselves. Therefore, we can conclude that the dynamics of the output gap between countries is different, as well as the qualitative characteristics of economic growth, so we cannot confirm the synchronization of business cycles.

### **4.2 Spectral analysis**

Next, after excluding the trend, we conducted an additional study of the remaining time series. **Figure 5** shows correlograms of the remaining time series of LEE countries' GDP.

**Figure 3.** *Currency course effect.*

The highest dependence among the members of these series is: for India 8 and 9, and for Russia and China the diagram looks flat. Therefore, the graphs have different shape and nature, and there is not much correlation between them. As a result, the

*Hodrick-Prescott Filtering of Large Emerging Economies and Decoupling Hypothesis DOI: http://dx.doi.org/10.5772/intechopen.112176*

### **Figure 5.**

*Correlograms of the remaining time series of LEE countries' GDP.*

### **Figure 6.**

*Periodograms of the trend-less time series of lee countries' GDP.*

most intense fluctuations in these remaining GDP time series are likely to be in the years when the elements of the time series have the highest correlation. To confirm this, we have shown periodograms of these LEE countries' GDP in **Figure 6**.

The periodograms show that in Russia, fluctuations around the basic trend occur at intervals of 1.5–2 years. It correlates with fluctuations in economic activity that is associated with capital markets. India and China reaffirm the conclusions we made in the previous section.

In general, the results show that the synchronization in the economic cycles of the countries is minimal, and we can find no confirmation of the decoupling hypothesis.
