Investigating the effects of monetary versus fiscal policies on GDP growth in Malaysia: Smooth transition autoregressive (STAR) approach

2021 ◽  
Author(s):  
Siti Fatimah Ismail ◽  
Siok Kun Sek
Keyword(s):  
Smooth Transition ◽  
Gdp Growth ◽  
Fiscal Policies ◽  
Smooth Transition Autoregressive

scholarly journals Dynamically Changing Cattle Market Linkages with Supply-Side-Controlled Transitions

2019 ◽  
Vol 51 (3) ◽  
pp. 472-484
Author(s):  
Wenying Li ◽  
Yunhan Li ◽  
Jeffrey H. Dorfman
Keyword(s):  
Simple Procedure ◽  
Economic Indicator ◽  
The United States ◽  
Transition Function ◽  
Smooth Transition ◽  
Supply Side ◽  
Star Model ◽  
Cattle Markets ◽  
Cattle Market ◽  
Smooth Transition Autoregressive

AbstractCattle are costly to transport, which could lead to segmented regional cattle markets. The cointegration of cattle prices over regions has been of research interest for decades. This article investigates price cointegration between regional cattle markets in the United States and proposes a simple procedure for incorporating a flexible transition function into an economic indicator–controlled smooth transition autoregressive (ECON-STAR) model to evaluate market dynamics. The empirical results show that these markets have been highly integrated when excess supply exists, but when cattle inventories decrease, the market pattern becomes very regionally segmented.

MULTIVARIATE STAR ANALYSIS OF MONEY–OUTPUT RELATIONSHIP

2001 ◽  
Vol 5 (4) ◽  
pp. 506-532 ◽  
Author(s):  
Philip Rothman ◽  
Dick van Dijk ◽  
Philip Hans
Keyword(s):  
Granger Causality ◽  
Predictive Accuracy ◽  
Information Criteria ◽  
Smooth Transition ◽  
Correction Model ◽  
Vector Error Correction ◽  
Accuracy Test ◽  
Vector Error ◽  
Out Of Sample ◽  
Smooth Transition Autoregressive

This paper investigates the potential for nonlinear Granger causality from money to output. Using a standard four-variable linear (subset) vector error-correction model (VECM), we first show that the null hypothesis of linearity can be rejected against the alternative of smooth-transition autoregressive nonlinearity. An interesting result from this stage of the analysis is that the yearly growth rate of money is identified as one of the variables that may govern the switching between regimes. Smooth-transition VECM's (STVECM's) are then used to examine whether there is nonlinear Granger causality in the money–output relationship in the sense that lagged values of money enter the model's output equation as regressors. We evaluate this type of nonlinear Granger causality with both in-sample and out-of-sample analyses. For the in-sample analysis, we compare alternative models using the Akaike information criteria, which can be interpreted as a predictive accuracy test. The results show that allowing for both nonlinearity and for money–output causality leads to considerable improvement in model's in-sample performance. By contrast, the out-of-sample forecasting results do not suggest that money is nonlinearly Granger causal for output. They also show that, according to several criteria, the linear VECM's dominate the STVECM's. However, these forecast improvements seldomly are statistically significant at conventional levels.

scholarly journals Testing for a unit root against ESTAR stationarity

2017 ◽  
Vol 22 (1) ◽  
Author(s):  
David I. Harvey ◽  
Stephen J. Leybourne ◽  
Emily J. Whitehouse
Keyword(s):  
Unit Root ◽  
Unit Root Tests ◽  
Smooth Transition ◽  
Local Power ◽  
Sources Of Uncertainty ◽  
Deterministic Trend ◽  
Smooth Transition Autoregressive

AbstractIn this paper we examine the local power of unit root tests against globally stationary exponential smooth transition autoregressive [ESTAR] alternatives under two sources of uncertainty: the degree of nonlinearity in the ESTAR model, and the presence of a linear deterministic trend. First, we show that the KSS test (Kapetanios, G., Y. Shin, and A. Snell. 2003. “Testing for a Unit Root in the Nonlinear STAR Framework.”

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