Modeling Multiple Regimes in the Business Cycle

1999 ◽  
Vol 3 (3) ◽  
pp. 311-340 ◽  
Author(s):  
Dick van Dijk ◽  
Philip Hans Franses
Keyword(s):  
Business Cycle ◽  
Growth Phase ◽  
High Growth ◽  
Smooth Transition ◽  
Star Model ◽  
Two Phase ◽  
Star Models ◽  
Moderate Growth ◽  
Multiple Regimes ◽  
The Business Cycle

The interest in business-cycle asymmetry has been steadily increasing over the past 15 years. Most research has focused on the different behavior of macroeconomic variables during expansions and contractions, which by now is well documented. Recent evidence suggests that such a two-phase characterization of the business cycle might be too restrictive. In particular, it might be worthwhile to decompose the recovery phase in a high-growth phase (immediately following the trough of a cycle) and a subsequent moderate-growth phase. The issue of multiple regimes in the business cycle is addressed using smooth-transition autoregressive (STAR) models. A possible limitation of STAR models as they currently are used is that essentially they deal with only two regimes. We propose a generalization of the STAR model such that more than two regimes can be accommodated. It is demonstrated that the class of multiple-regime STAR (MRSTAR) models can be obtained from the two-regime model in a simple way. The main properties of the MRSTAR model and several issues that are relevant for empirical specification are discussed in detail. In particular, a Lagrange multiplier-type test is derived that can be used to determine the appropriate number of regimes. A limited simulation study indicates its practical usefulness. Application of the new model class to U.S. real GNP provides evidence in favor of the existence of multiple business-cycle phases.

Forecasting Inflation Rate by Star Model: An Indian Experience

2002 ◽  
Vol 53 (3-4) ◽  
pp. 265-288
Author(s):  
G.P. Samanta
Keyword(s):  
Inflation Rate ◽  
Wholesale Price ◽  
Smooth Transition ◽  
Forecast Errors ◽  
Star Model ◽  
Star Models ◽  
Non Linear ◽  
Out Of Sample ◽  
Short Run ◽  
Forecasting Inflation

In this empirical study, an attempt has been made to model non-linear dynamics of inflation rate in India through Smooth Transition ⁄ Threshold Auto-Regression (STAR). Inflation is measured based on weekly data on Wholesale Price Index (WPI) fur a period of seven years from the week ended April 2, 1994 to the week ended March 31, 2001. The log(WPI) series is detected to be a Difference-Stationary process, indicating that the series is non-stationary but its first-order difference is stationary. The generating process of the transformed-stationary series is identified to be non-linear. Six variants of STAR model are estimated for transformed-stationary series and are used to forecast WPI and annual inflation rate. Empirical assessment of out-of-sample forecast errors eveals that estimated STAR models perform reasonably well in generating short-run forecasts of both the variables.

scholarly journals Genetic Algorithm Based Improved ESTAR Nonlinear Models for Modelling Sunspot Numbers and Global Temperatures

2021 ◽  
Author(s):  
Bishal Gurung ◽  
Achal Lama ◽  
Santosha Rathod ◽  
K N Singh
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Models ◽  
Forecast Error ◽  
Optimization Procedure ◽  
Smooth Transition ◽  
Star Model ◽  
Estimation Of Parameters ◽  
Sunspot Numbers ◽  
Star Models ◽  
One Step

Abstract Smooth Transition Autoregressive (STAR) models are employed to describe cyclical data. As estimation of parameters of STAR using nonlinear methods was time-consuming, Genetic algorithm (GA), a powerful optimization procedure was applied for the same. Further, optimal one step and two step ahead forecasts along with their forecast error variances are derived theoretically for fitted STAR model using conditional expectations. Given the importance of the issue of global warming, the current paper aims to model the sunspot numbers and global mean temperatures. Further, appropriate tests are carried out to see if the model employed is appropriate for the datasets.

scholarly journals The asymmetric effect of the business cycle on poverty in Argentina

2019 ◽  
Vol 66 (3) ◽  
pp. 347-364
Author(s):  
Guido Zack ◽  
Daniel Sotelsek
Keyword(s):  
Income Distribution ◽  
Business Cycle ◽  
Social Indicators ◽  
High Growth ◽  
Present Situation ◽  
Asymmetric Effect ◽  
Extreme Poverty ◽  
Poverty Measures ◽  
The Social ◽  
The Business Cycle

After the crisis of 2002, Argentina started a process of strong recovery of the social indicators, which slowed from 2007 and has stagnated since 2012. The present situation is slightly better in relation to the 1990s, but worse if the comparison is made with the 1980s and the 1970s. Despite the high growth rates experienced until 2011, income distribution was the main cause of improvement in poverty and extreme poverty measures. This article examines the risk of reversing in the coming years part of the recovery achieved. This risk is based on the possible asymmetric effect of the business cycle on social indicators, analyzed through the income and income distribution elasticities of poverty and extreme poverty estimated for the 2003-2017 period.

scholarly journals The Cyclical Behaviour of the Small-Cap Premium: A Regime-Switching Approach

2020 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Lorne N. Switzer ◽  
Alan Picard
Keyword(s):  
Regime Switching ◽  
Factor Model ◽  
Smooth Transition ◽  
Star Model ◽  
Financial Variables ◽  
The Us ◽  
Model Star ◽  
Cyclical Behaviour ◽  
The Business Cycle ◽  
Smooth Transition Autoregressive

While the average annual small-cap premia for the US and Canada are substantial over long horizons, there is considerable time variation of this premium within and across these countries. For the US, during expansions, the average annualized premium is a sizable 5.44%, while during recessions, there is a small-cap discount of 6.23%. The differentials are less pronounced in Canada. This paper investigates the hypothesis that the variation of the small-cap premium is related to macroeconomic and financial variables that can be captured by a nonlinear time series econometric model, i.e., the smooth transition autoregressive model (STAR model), with different factor sets across regimes between and countries. The regimes reflect expansionary vs. contractionary phases of the business cycle. For the Canadian small-cap premium, an augmented factor model that includes US factors dominates a purely domestic factor model, which is consistent with integrated markets.

scholarly journals Testing Market Efficiency with Nonlinear Methods: Evidence from Borsa Istanbul

2019 ◽  
Vol 7 (2) ◽  
pp. 27
Author(s):  
Fuzuli Aliyev
Keyword(s):  
Random Walk ◽  
Market Efficiency ◽  
Financial Time Series ◽  
Weak Form ◽  
Ar Model ◽  
Smooth Transition ◽  
Star Model ◽  
Forecast Performance ◽  
Star Models ◽  
Out Of Sample

Market efficiency has been analyzed through many studies using different linear methods. However, studies on financial econometrics reveal that financial time series exhibit nonlinear patterns because of various reasons. This paper examines market efficiency at Borsa Istanbul using a smooth transition autoregressive (STAR) type nonlinear model. I develop nonlinear ARCH and STAR models, a linear AR model and random walk model for 10 years’ weekly data and then out-of-sample forecast next 12 weeks’ return. Comparing forecast performance powers, I find that the STAR model outperforms random walk, that is Borsa Istanbul returns are predictable at the given period. The results show that the shareholders may earn abnormal return and identify the direction of the return change for the next week with at least 66% accuracy. Contrary to the linear level studies, these findings show that the Borsa Istanbul is not weak form efficient at nonlinear level within the studied period.

Business Cycle in Agriculture in Poland

2020 ◽  
Vol 69 (3) ◽  
pp. 219-230
Author(s):  
Andrzej Jędruchniewicz ◽  
Jan-Philipp Huchtemann ◽  
Philipp Welter ◽  
Eike Nordmeyer ◽  
Achim Spiller ◽  
...  
Keyword(s):  
Business Cycle ◽  
Growth Phase ◽  
Growth Phases ◽  
Agricultural Prices ◽  
Agricultural Income ◽  
Final Output ◽  
The Common ◽  
The Business Cycle ◽  
Analysis Of Dynamics ◽  
Almost All

The main objective of the study was to characterize the business cycle and its particular phases in Polish agriculture and compare with the features of the cycle occurring in theory. The research for the years 2001-2015 which was based on annual real changes in final output allowed to identify three full cycles in Polish agriculture: 1) 2001-2006; 2) 2007-2010; 3) 2011-2015. The analysis of fluctuations showed that all cycles lasted from 4 to 6 years. Growth phases took from 2 to 4 years, and all downward ones lasted 2 years. The amplitudes of these phases were similar. There were both turning points and turning zones in the cycles. The analysis of accumulated dynamics of production, income, prices and investments in particular phases of the business cycle in Polish agriculture shows that in each growth phase all categories have increased. In almost all cycles, the dynamics of these categories in the growth phase was greater than the changes during the downturn. According to the theory of the classical cycle, the value of production as well as agricultural prices changed the most. They had negative dynamics in almost every downward phase. On the other hand, the dynamics of agricultural incomes was positive in all downward phases. Therefore, changes in this category in most cases had the features of the modern cycle. Changes in investments in the downward phases were diversified. The analysis of dynamics indicates that agricultural income and investments in Poland was also affected by the Common Agricultural Policy.

scholarly journals The effects of government spending over the business cycle

2019 ◽  
Author(s):  
Ανδρομάχη Παρθενίου
Keyword(s):  
Business Cycle ◽  
Government Spending ◽  
Smooth Transition ◽  
Vector Autoregressive ◽  
The Business Cycle ◽  
Local Projections ◽  
Transition Vector

Η παρούσα διατριβή εξετάζει τις επιδράσεις των επιμέρους συνιστωσών των κυβερνητικών δαπανών κατά τη διάρκεια του οικονομικού κύκλου (δηλαδή, άνθηση και ύφεση). Χρησιμοποιούνται δύο διαφορετικές κατηγοριοποιήσεις κυβερνητικών δαπανών, όπως αυτές προτείνονται από το Διεθνές Νομισματικό Ταμείο (ΔΝΤ): η οικονομική και η λειτουργική κατηγοριοποίηση. Η οικονομική κατηγοριοποίηση διαχωρίζει τις δημόσιες δαπάνες με βάση τον τύπο ή τον οικονομικό χαρακτήρα της δαπάνης, ενώ η λειτουργική κατηγοριοποίηση οργανώνει τις δαπάνες σύμφωνα με το σκοπό για τον οποίο δαπανώνται. Στα κεφάλαια 3 και 4 επιστρατεύεται η οικονομική κατηγοριοποίηση, αλλά με τη χρήση εναλλακτικών μεθόδων εκτίμησης. Στο κεφάλαιο 3 χρησιμοποιείται ένα υπόδειγμα δομικής διανυσματικής αυτοπαλινδρόμησης ομαλής μετάβασης (Smooth Transition Vector Autoregressive (STVAR)) και δεδομένα από τις Ηνωμένες Πολιτείες, ενώ στο κεφάλαιο 4, οι δημοσιονομικοί πολλαπλασιαστές εκτιμώνται με τη χρήση των τοπικών προβολών (Local Projections) και δεδομένα πάνελ από χώρες μέλη του ΟΟΣΑ, αλλά και από χώρες μη-μέλη του ΟΟΣΑ. Τέλος, στο κεφάλαιο 5 χρησιμοποιούνται τοπικές προβολές (Local Projections) και δεδομένα πάνελ χωρών μελών του ΟΟΣΑ για να εκτιμηθούν δημοσιονομικοί πολλαπλασιαστές με βάση τη λειτουργική κατηγοριοποίηση. Τα αποτελέσματα επιβεβαιώνουν τους ισχυρισμούς για την ύπαρξη ετερογένειας μεταξύ των συνιστωσών των δημοσίων δαπανών, αλλά και μεταξύ των φάσεων του οικονομικού κύκλου.

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