Abstract

Despite the existence of macroeconomic models and complex business cycle indicators, it would be beneficial to policymakers and market participants if they could look at one well-chosen indicator in predicting business cycle turning points. If one indicator accurately predicts business cycle turning points, it provides an easy way to confirm the predictions of macroeconomic models, or it can eliminate the need for a macroeconomic model if the interest is in the turning points and not in the levels of the business cycle. The objective of this paper is to investigate whether turning points of the South African business cycle can be predicted with only one economic indicator.

Highlights

  • The modern literature on business cycles dates back to the seminal work of Burns and Mitchell (1946)

  • Variables such as interest rates, international indicators, stock price indices and monetary aggregates are examined. The performance of these individual indicators will be compared with the performance of the composite index of leading indicators compiled by the South African Reserve Bank

  • The deteriorating performance of the composite index and the improving performance of the interest rate models might be the result of important structural change in the economy

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Summary

INTRODUCTION

The modern literature on business cycles dates back to the seminal work of Burns and Mitchell (1946) They defined the business cycle as follows: “a cycle consists of expansions occurring at about the same time in many economic activities, followed by general recessions, contractions and revivals that merge into the expansion phase of the cycle: this sequence of change is recurrent but not periodic” (Burns and Mitchell, 1946: 3). This definition remains the basis of business cycle analysis, and it is the foundation of several recent studies that model the characteristics that distinguish expansions from contractions.

LITERATURE REVIEW
The Probit model
Pseudo-R2 for models with dichotonomous dependent variables
INDICATORS EXAMINED AND DATA USED
Performance of individual leading indicators
Probit models
Findings
CONCLUSION
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