Business Cycles in BRICS
This volume focuses on the analysis and measurement of business cycles in Brazil, Russia, India, China and South Africa (BRICS). Divided into five parts, it begins with an overview of the main concepts and problems involved in monitoring and forecasting business cycles. Then it highlights the role of BRICS in the global economy and explores the interrelatedness of business cycles within BRICS. In turn, part two provides studies on the historical development of business cycles in the individual BRICS countries and describes the driving forces behind those cycles. Parts three and four present national business tendency surveys and composite cyclical indices for real-time monitoring and forecasting of various BRICS economies, while the final part discusses how the lessons learned in the BRICS countries can be used for the analysis of business cycles and their socio-political consequences in other emerging countries.
Available composite cyclical indicators for Russia are surveyed, their components are enumerated and analysed. The aims, guiding concepts, and approaches of the newly established Russian Economic Cycle Dating Committee are also described. All the currently available monthly Composite Leading Indices (CLIs) are tested against the most recent cyclical turning points for their capacity to provide a timely alarm signal, especially about an impending recession. It is shown that experts’ informal judgments about Russia’s future economic trajectory remain more informative than findings derived from formal empirical rules. This suggests that there is some room for improvement of the Russian CLIs and additional efforts should be made to construct better cyclical indicators for Russia.
In many respects, the historical trajectory of the Russian economy during the Twentieth century has been a terra incognita until now. As for the official statistics, there are at least three important reasons for this. First, many relevant indicators were either not measured, or were kept secret and never published. Second, Russia (as the RSFSR) was a part of the USSR, and statistics for the RSFSR was much less prevalent than for the USSR as a whole (historical changes of the Russian borders also require special consideration). Third, an ideological dogma existed about the absence of inflation in the planned Soviet economy; therefore, all deflators (if any) were underestimated, and all aggregates in constant and/or comparable prices were overestimated (as were the corresponding growth rates). As for the unofficial historical estimates, most of them were focused on the USSR, not on the RSFSR. It’s very risky to use them as a proxy for historical indicators of the Russian Federation.
Hence, our first aim was to construct a statistical time-series that might be useful to describe the long-run trajectory of the Russian (the RSFSR and/or the RF) economy. Using previously unpublished data stored in Russian archives, we tried to extend them back as far as possible; in fact, most of them began in the late 1920s.
Our second aim was to denote periods of growth and contraction in the Russian economy and to reveal the economic factors that caused changes in trajectory. Periods of contractions during the era of the planned economy were of special interest for us. We found that recessions had occurred, not only in the market, but in the planned Russian economy as well (of course, with a significant remark that contractions in the planned economy were much rarer, but evidently more destructive).
This chapter begins with a brief history of the BRICS – from a purely analytical concept to the real-world political group with its own financial infrastructure. It then considers the role of the member countries in the global economy in terms of macro-indicators (territory, population and GDP), the production of a variety of key goods, trade and capital markets. Particular emphasis is placed on the rapid growth of the Chinese economy and the importance of its position in international commodity markets, the production of industrial goods, as well as other economic spheres. As a result, BRICS countries contribute significantly to global GDP growth, and the contribution of China is particularly important.
The current best practices in measuring, monitoring, and forecasting economic cycles are drawn from the experience of mature economies such as the USA, Japan, and several Western European countries. Meanwhile, there are a lot of peculiarities in emerging economies that should be kept in mind when developing a system for tracking and forecasting their short-run dynamics. In the literature, there have been numerous attempts to apply the international best practices to emerging economies, but these attempts have usually been sporadic. The experience of the BRICS economies accumulated in this book allows for a fresh look on the problem of the development and use of cyclical indicators and is potentially useful for other emerging countries.
Background and motivation for a study of business cycles, business tendency surveys (BTSs), and cyclical indicators in the BRICS countries are specified. The main concepts and problems involved in monitoring and forecasting business cycles in emerging countries and countries in transition are overviewed; the importance of the experience of the BRICS in this context is demonstrated; different examples of the interaction between business cycles and social and political spheres are outlined. At last, the structure of the book is adduced.
In large countries, the development of national macroeconomic business cycles clearly involves regional nuances that, as a rule, fall outside scholars’ fields of vision, especially when monitoring the current economic situation. Regional statistics published by the Russian Federal State Statistics Service (Rosstat) are reviewed in terms of quality, and radical disagreement between “month-on-month” and “year-on-year” monthly statistics is identified. In view of this, an original method is proposed for estimating the level of regional economic activity (REA), based on monthly official regional statistics in five key sectors of the Russian economy: industry, construction, retail trade, wholesale trade, and paid services for the population. This method transforms current “year-on-year” growth rates into specially constructed dichotomous variables, which eliminate the excessive volatility and inaccuracy of the initial time series.
On these grounds, REA indices are estimated for all Russian constituent entities for the period from January 2005 to November 2017. Composite REA indices for all five economic sectors, eight federal districts, and Russia as a whole are then calculated. Methods for visualising multidimensional regional data are also proposed. They allow us to track the regional peculiarities of the Russian economy and to discern the current phase of the business cycle more accurately and without any additional lag. Several illustrative examples for the possible application of these indices in real-time monitoring and analyses are provided.
In this chapter we aim to consider the interdependence between total factor productivity, economic welfare, and political institutions using BRICS as an empirical example. While relationships between each pair of factors have already been subject to scientific inquiry, we attempt to look at the productivity-institutions nexus in conjunction with economic development. We utilize nonparametric methods (data envelopment analysis) to estimate productivity levels for a large sample of countries and investigate the mutual relationships between productivity, GDP, and institutions for every year in the sample, as well as look into possible connections between dynamics of the three factors. We also analyze productivity trajectories of the BRICS countries in order to gain further insight into how capital-labor ratios might affect further economic development given each country’s institutional context. We show that levels of institutional development are a significant predictor for per capita GDP levels, as well as TFP levels. However, our tests for differences in TFP and growth remain inconclusive.