Business Cycles and Turning Points: A Survey of Statistical Techniques

2003 ◽  
Vol 183 ◽  
pp. 90-106 ◽  
Author(s):  
Michael Massmann ◽  
James Mitchell ◽  
Martin Weale
Keyword(s):  
Business Cycles ◽  
Business Cycle ◽  
Turning Points ◽  
Statistical Techniques ◽  
The Business Cycle ◽  
The Uk

The business cycle has an importance in the popular debate which can tend to run ahead of the problems in measuring it. This paper provides a survey of the main statistical techniques that are used to measure the cycle. An application to the UK illustrates that the choice of what measure, or measures, to use is more than a dry academic issue. Inference about the business cycle is potentially sensitive to measurement. Fortunately, however, there is an element of consensus.

An Assessment of OECD and UK Leading Indicators

1996 ◽  
Vol 156 ◽  
pp. 63-71 ◽  
Author(s):  
Martin Weale
Keyword(s):  
Business Cycle ◽  
Standard Error ◽  
Turning Points ◽  
Leading Indicators ◽  
Var Models ◽  
National Statistics ◽  
Good Ability ◽  
The Business Cycle ◽  
The Uk

Leading indicators are produced by both the OECD and the UK Office of National Statistics as tools for predicting turning points of the business cycle. An assessment on the basis of performance at turning points is frustrated by their scarcity. It is found that the indicators generally have significant (but not good) ability to predict changes in the direction of the variable they are intended to lead. When they are included in VAR models the standard error of quarter on quarter changes is generally lower than when pure autoregressions are used. However, the forecasting power of such equations is poor, and the general conclusion is that such indicators are not good forecasting tools.

Dating business cycles in India

2017 ◽  
Vol 10 (1) ◽  
pp. 32-61 ◽  
Author(s):  
Radhika Pandey ◽  
Ila Patnaik ◽  
Ajay Shah
Keyword(s):  
Business Cycles ◽  
Business Cycle ◽  
Turning Points ◽  
Growth Cycle ◽  
Macroeconomic Shocks ◽  
Content Type ◽  
Reform Period ◽  
Cyclical Component ◽  
Policy Work ◽  
The Business Cycle

Purpose This paper aims to present a chronology of Indian business cycles in the post-reform period. In India, earlier, macroeconomic shocks were about droughts and oil prices. Economic reforms have led to an interplay of a market economy, financial globalisation and decisions of private firms to undertake investment and hold inventory. This has changed the working of the business cycle and has raised concerns about business-cycle stabilisation. In the backdrop of these developments, the macroeconomics research agenda requires foundations of measurement about business-cycle phenomena. One element of this is the identification of dates of business-cycle turning points. Design/methodology/approach This paper uses the growth-cycle approach to present the chronology of business cycles. The paper uses the Christiano–Fitzgerald (CF) filter to extract the cyclical component and shows the robustness of the findings to the contemporary methods of cycle extraction. It then applies the Bry–Boschan algorithm to identify the dates of peaks and troughs. Findings The paper finds three periods of recession. The first recession was from 1999-Q4 to 2003-Q1; the second recession was from 2007-Q2 to 2009-Q3; and the third recession ran from 2011-Q2 till 2012-Q4. These results are robust to the choice of filter and to the choice of the business-cycle indicator. These dates suggest that, on average, expansions in India are 12 quarters in length and recessions run for 9 quarters. The paper offers evidence of change in the nature of cycles. Originality/value Dates of business-cycle turning points are a critical input for academic and policy work in macroeconomics. The paper offers robust estimation of the business-cycle turning points in the post-reform period using contemporary techniques of cycle extraction. This work helps lay the foundations for downstream macroeconomics research by academicians and policymakers.

Have UK and Eurozone Business Cycles Become More Correlated?

2002 ◽  
Vol 182 ◽  
pp. 58-71 ◽  
Author(s):  
Michael Massmann ◽  
James Mitchell
Keyword(s):  
Business Cycles ◽  
Business Cycle ◽  
Industrial Production ◽  
Production Data ◽  
Alternative Measures ◽  
The Business Cycle ◽  
The Uk ◽  
The Relationship ◽  
Historical Levels ◽  
Sustained Increase

Recent estimates suggest that the UK business cycle is closer to the Eurozone business cycle than it was in the early 1990s. This paper investigates whether this phenomenon has been accompanied by increased correlation between UK and Eurozone business cycles. Considering a range of alternative measures of the business cycle we find, using 40 years of monthly industrial production data, no clear evidence for a sustained increase in correlation between UK and Eurozone business cycles. Instead, in the 1990s, the correlation between UK and Eurozone business cycles has been volatile relative to historical levels. It is only recently, i.e. since 1997, that the UK has become more correlated with the Eurozone, although the level of correlation is lower than against non-Eurozone countries. Importantly, the strength of these relationships is sensitive to how the business cycle is measured. Care should therefore be exercised when using business cycles estimates to test the relationship between UK and Eurozone business cycles.

Predicting returns over several decades

2021 ◽  
pp. 292-312
Author(s):  
Jesper Rangvid
Keyword(s):  
Business Cycles ◽  
Business Cycle ◽  
Interest Rates ◽  
Stock Price ◽  
Turning Points ◽  
Long Run ◽  
The Business Cycle

This chapter looks at expectations of returns several decades out. This is obviously a difficult task, as fundamental economic structures might change over such long periods. But we need multi-decade forecasts in certain situations. One conclusion of this chapter is that we must look beyond variables that predict turning points in the business cycle and stock-price multiples when dealing with the very long run. Over multiple decades, we will live through multiple business cycles. Variables that predict the next business cycle will not be particularly informative about the returns we expect over many decades. The chapter focuses on the deep underlying drivers of long-run returns, primarily expectations to long-run economic activity.The chapter also looks at expected long-run interest rates.

Development blocks, malinvestment and structural tensions – the Åkerman–Dahmén theory of the business cycle

2010 ◽  
Vol 7 (1) ◽  
pp. 105-129 ◽  
Author(s):  
LENNART ERIXON
Keyword(s):  
Business Cycles ◽  
Business Cycle ◽  
Institutional Theory ◽  
Financial Market ◽  
Turning Points ◽  
Optimization Models ◽  
Market Conditions ◽  
Modern Business ◽  
The Business Cycle

Abstract:Johan Åkerman and Erik Dahmén's institutional theory of economic fluctuations is a constructive alternative to traditional macroeconomic approaches and also to modern business-cycle analysis based on microeconomic optimization models. By its integration of a business-cycle and growth perspective, Åkerman and Dahmén's analysis was similar to that of Schumpeter in Business Cycles. But their notions of malinvestment, structural tensions, and development blocks provided an original explanation of the turning points in the business cycle. The Åkerman–Dahmén approach is more valid for innovation-driven cycles such as the ICT boom in the late 1990s and the subsequent crisis than for cycles with an independent role of financial-market conditions.

EXPANSIONS AND RECESSIONS IN THE MEXICAN STATES: A CLASSICAL BUSINESS CYCLES APPROACH

2017 ◽  
Vol 3 (5) ◽  
pp. 32
Author(s):  
Pablo Mejía-Reyes
Keyword(s):  
Business Cycles ◽  
Business Cycle ◽  
Monthly Basis ◽  
Production Index ◽  
Clear Cut ◽  
Output Measure ◽  
Central Regions ◽  
The Business Cycle ◽  
National Business ◽  
Cycle Indicator

This paper aims to document expansions and recessions characteristics for 17 states of Mexico over the period 1993-2006 by using a classical business cycle approach. We use the manufacturing production index for each state as the business cycle indicator since it is the only output measure available on a monthly basis. According to this approach, we analyse asymmetries in mean, volatility and duration as well as synchronisation over the business cycle regimes (expansions and recessions) for each case. Our results indicate that recessions are less persistent and more volatile (in general) than expansions in most Mexican states; yet, there is no clear cut evidence on mean asymmetries. In turn, there seems to be strong links between the business cycle regimes within the Northern and Central regions of the country and between states with similar industrialisation patterns, although it is difficult to claim that a national business cycle exists.

scholarly journals Forecasting Macedonian Business Cycle Turning Points Using Qual Var Model

2016 ◽  
Vol 5 (3) ◽  
pp. 61-78
Author(s):  
Magdalena Petrovska ◽  
Aneta Krstevska ◽  
Nikola Naumovski
Keyword(s):  
Business Cycle ◽  
Predictive Power ◽  
Turning Points ◽  
Probit Model ◽  
Economic Conditions ◽  
Var Model ◽  
Leading Indicators ◽  
Out Of Sample ◽  
The Business Cycle

Abstract This paper aims at assessing the usefulness of leading indicators in business cycle research and forecast. Initially we test the predictive power of the economic sentiment indicator (ESI) within a static probit model as a leading indicator, commonly perceived to be able to provide a reliable summary of the current economic conditions. We further proceed analyzing how well an extended set of indicators performs in forecasting turning points of the Macedonian business cycle by employing the Qual VAR approach of Dueker (2005). In continuation, we evaluate the quality of the selected indicators in pseudo-out-of-sample context. The results show that the use of survey-based indicators as a complement to macroeconomic data work satisfactory well in capturing the business cycle developments in Macedonia.

Judging the stance of the business cycle

2021 ◽  
pp. 222-240
Author(s):  
Jesper Rangvid
Keyword(s):  
Business Cycle ◽  
Turning Point ◽  
Turning Points ◽  
Leading Indicators ◽  
Economic Variables ◽  
Near Term ◽  
The Business Cycle

This chapter describes if and how we can detect business-cycle turning points. What variables should we study if we want to say something about the likelihood that the business cycle will change? The chapter discusses business-cycle ‘indicators’. It distinguishes between lagging, coincident, and leading indicators. Lagging indicators refer to economic variables that react to a change in the business cycle, i.e. variables that react after a business-cycle turning point. Coincident indicators tell us something about where we are right now in the business cycle. Leading indicators, which are probably the most important ones, tell us about the near-term outlook for the business cycle, i.e. forecast the business cycle. The chapter emphasizes that business-cycle turning points are hard to predict, but also that some indicators are more informative than others.

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