GDP Growth Predictions Through the Yield Spread. Time-Variation and Structural Breaks

2011 ◽  
Author(s):  
Pierangelo De Pace
Keyword(s):  
Time Variation ◽  
Structural Breaks ◽  
Gdp Growth ◽  
Yield Spread

scholarly journals Examining GDP Growth and Its Volatility: An Episodic Approach

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 890
Author(s):  
Jakub Bartak ◽  
Łukasz Jabłoński ◽  
Agnieszka Jastrzębska
Keyword(s):  
Economic Growth ◽  
Genetic Algorithm ◽  
Time Series ◽  
Human Capital ◽  
Growth Rates ◽  
Structural Breaks ◽  
Negative Relationship ◽  
Gdp Per Capita ◽  
Gdp Growth ◽  
Per Capita

In this paper, we study economic growth and its volatility from an episodic perspective. We first demonstrate the ability of the genetic algorithm to detect shifts in the volatility and levels of a given time series. Having shown that it works well, we then use it to detect structural breaks that segment the GDP per capita time series into episodes characterized by different means and volatility of growth rates. We further investigate whether a volatile economy is likely to grow more slowly and analyze the determinants of high/low growth with high/low volatility patterns. The main results indicate a negative relationship between volatility and growth. Moreover, the results suggest that international trade simultaneously promotes growth and increases volatility, human capital promotes growth and stability, and financial development reduces volatility and negatively correlates with growth.

A revisit of the unemployment rate, interest rate, GDP growth and Inflation of Pakistan: Whether Structural break or unit root?

2021 ◽  
Vol 3 (2) ◽  
pp. 80-92
Author(s):  
Sara Muhammadullah ◽  
Amena Urooj ◽  
Faridoon Khan
Keyword(s):  
Interest Rate ◽  
Unemployment Rate ◽  
Unit Root ◽  
Structural Breaks ◽  
Inflation Rate ◽  
Structural Break ◽  
Unit Root Test ◽  
Unit Root Tests ◽  
Gdp Growth ◽  
Macroeconomic Indicators

The study investigates the query of structural break or unit root considering four macroeconomic indicators; unemployment rate, interest rate, GDP growth, and inflation rate of Pakistan. The previous studies create ambiguity regarding the stationarity and non-stationarity of these variables. We employ Zivot & Andrews (1992) unit root test and Step Indicator Saturation (SIS) method for multiple break detection in mean. GDP growth and inflation rate are stationary at level whereas unit root tests fail to reject the null hypothesis of the unemployment rate and interest rate at level. However, Zivot and Andrew unit root test with a single endogenous break indicates that the unemployment rate and interest rate are stationary at level with a single endogenous break. On the other hand, the SIS method reveals that the series are stationary with multiple structural breaks. It is inferred that it is inappropriate to take the first difference of the unemployment rate and interest rate to attain stationarity. The results of this study confirmed that there exist multiple breaks in the macroeconomic variables considered in the context of Pakistan.

QUANTILE-BASED ASYMMETRIC DYNAMICS OF REAL GDP GROWTH

2019 ◽  
Vol 24 (8) ◽  
pp. 1960-1988
Author(s):  
Xiaochun Liu
Keyword(s):  
Conditional Distribution ◽  
Structural Breaks ◽  
Gdp Growth ◽  
Developed Economies ◽  
Real Gdp ◽  
Economic Downturns ◽  
Economic Recessions ◽  
The Mean ◽  
Linear And Nonlinear ◽  
Different Parts

This paper studies asymmetric dynamics of real GDP growth by estimating linear and nonlinear quantile persistence over different parts of the conditional distribution for six major developed economies. Several novel quantile-based hypotheses are motivated in this paper and tested for the steepness asymmetry of real GDP growth that hypothesizes that contractions are steeper than expansions. The empirical results show that quantile persistence is generally high at far lower tails, thus requiring much longer half-lives to reverting negative deviations to the mean of real GDP growth and hence leading to gradual economic recoveries. By contrast, less persistence in far upper tails tends to generate sharp and short economic downturns that adjust positive deviations towards the mean of real GDP growth so as to cause abrupt economic recessions. In particular, this asymmetry in quantile persistence strongly supports the steepness asymmetry conjecture, robust to the presence of structural breaks and potential nonlinearities in real GDP growth.

Trade-Off Between Defense and Development

2018 ◽  
pp. 448-471
Author(s):  
Maniklal Adhikary ◽  
Anindya Bhattacharya
Keyword(s):  
Growth And Development ◽  
Spline Function ◽  
Structural Breaks ◽  
Single Equation ◽  
Gdp Growth ◽  
Trade Off ◽  
Defense Expenditure ◽  
Expenditure Data ◽  
Development Expenditure ◽  
Year 2000

This chapter looks into the existence and the nature of relationship between defense expenditure and GDP and development expenditure for Indian economy for last 30 years (1987-2016). Using Spline function regression technique and single equation regression approach, it concludes that defense expenditure is not significantly contributing in explanation for changes in GDP growth and development expenditure and its components. Further, defense expenditure shows significant structural breaks in the year 2000, which might be attributed to exorbitant hike in the defense expenditure data during Kargil War in 1998. Considering all these rises in defense expenditure, it is to an extent convenient to find the result that this has neither affected economic growth nor development expenditures in a significant manner.

APPARENT LONG MEMORY IN TIME SERIES AS AN ARTIFACT OF A TIME-VARYING MEAN: CONSIDERING ALTERNATIVES TO THE FRACTIONALLY INTEGRATED MODEL

2010 ◽  
Vol 14 (S1) ◽  
pp. 59-87 ◽  
Author(s):  
Richard A. Ashley ◽  
Douglas M. Patterson
Keyword(s):  
Time Series ◽  
Time Variation ◽  
Long Memory ◽  
Structural Breaks ◽  
Integrated Model ◽  
Time Varying ◽  
Penalized Spline ◽  
Spectral Estimates ◽  
The Mean ◽  
Modeling Strategy

Structural breaks and switching processes are known to induce apparent long memory in a time series. Here we show that any significant time variation in the mean renders the sample correlogram (and related spectral estimates) inconsistent. In particular, smooth time variation in the mean—i.e., even a weak trend, either stochastic or deterministic—induces apparent long memory. This apparent long memory can be eliminated by either high-pass filtering or by detrending. Here we demonstrate the effectiveness in this regard of nonlinear detrending via penalized-spline nonparametric regression. A time-varying mean can be of economic interest in its own right. This suggests that isolating out and separately examining both a local mean (i.e., a nonlinear trend or the realization of a stochastic trend) and deviations from it is preferable as a modeling strategy to simply estimating a fractionally integrated model. We illustrate the superiority of this strategy using stock return volatility data.

China: "A Bee Has a Stripy Back, but No One Can Call It a Tiger"

2003 ◽  
pp. 61-75
Author(s):  
V. Guelbras
Keyword(s):  
Energy Consumption ◽  
Gdp Growth ◽  
International Demand ◽  
Real Size ◽  
Rates Of Growth

The article is devoted to verification of the Chinese GDP data. The author compares the rates of GDP growth with the rates of growth of energy consumption, transport turnover of goods, and numbers of projected and constructed objects in 1980-2000. The former was significantly lower during that period. He also analyses the level of using productive capacities and the quality of production. About 25-30% of industrial productive capacities are not used because there is neither national nor international demand for their low quality goods. The main conclusion of the article is that the Chinese GDP real size is about 20-30% less than official releases.

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