scholarly journals Tests for Structural Breaks in Time Series Analysis: A Review of Recent Development

2019 ◽  
Vol 7 (4) ◽  
pp. 66-79
Author(s):  
P Muthuramu ◽  
T Uma Maheswari
Keyword(s):  
Time Series ◽  
Dynamic Programming ◽  
Change Point ◽  
Structural Breaks ◽  
Structural Break ◽  
Econometric Models ◽  
Theoretical Development ◽  
Fundamental Change ◽  
Parameter Instability ◽  
The Past

The issue related to a structural break or change point in the econometric and statistics literature is relatively vast. In recent decades it was increasing, and it got recognized by various researchers. The debates are about a structural break or parameter instability in the econometric models. Over some time, there has been a different mechanism, and theoretical development stretching the fundamental change and strengthen the econometric literature. Estimation of structural break has undergone significant changes. Instead of exploring the presence of a known structural break, now the emphasis is on tracing multiple unknown cracks using dynamic programming. The paper an attempt has been made to review the different forms of the presence of structural break(s) over the past.

Testing Structural Break in the Relationship Between Exchange Rate and Macroeconomic Variables

2019 ◽  
Vol 23 (4) ◽  
pp. 442-453 ◽  
Author(s):  
Saidia Jeelani ◽  
Joity Tomar ◽  
Tapas Das ◽  
Seshanwita Das
Keyword(s):  
Exchange Rate ◽  
Structural Breaks ◽  
Time Series Data ◽  
Structural Break ◽  
Series Data ◽  
Ripple Effect ◽  
Macroeconomic Factors ◽  
Parameter Instability ◽  
Macroeconomic Variables ◽  
The Relationship

The article aims to study the relationship between those macroeconomic factors that the affect (INR/USD) exchange rate (ER). Time series data of 40 years on ER, GDP, inflation, interest rate (IR), FDI, money supply, trade balance (TB) and terms of trade (ToT) have been collected from the RBI website. The considered model has suggested that only inflation, TB and ToT have influenced the ER significantly during the study period. Other macroeconomic variables such as GDP, FDI and IR have not significantly influenced the ER during the study period. The model is robust and does not suffer from residual heteroscedasticity, autocorrelation and non-normality. Sometimes the relationship between ER and macroeconomic variables gets affected by major economic events. For example, the Southeast Asian crisis caused by currency depreciation in 1997 and sub-prime loan crisis of 2008 severely strained the national economies. Any global economic turmoil will affect different economic variables through ripple effect and this, in turn, will affect the ER of different economies differently. The article has also diagnosed whether there is any structural break or not in the model by applying Chow’s Breakpoint Test and have obtained multiple breaks between 2003 and 2009. The existence of structural breaks during 2003–2009 is explained by the fact that volume of crude oil imported by India is high and oil price rise led to a deficit in the TB alarmingly, which caused a structural break or parameter instability.

Studying Crisis through Structural Breaks: A Retrospective on Asian Currency Crisis

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
K. V. Bhanu Murthy ◽  
Anjala Kalsie
Keyword(s):  
East Asia ◽  
Financial Crises ◽  
Structural Breaks ◽  
Currency Crisis ◽  
Structural Break ◽  
International Comparisons ◽  
Dummy Variables ◽  
The Past ◽  
Asian Currency Crisis

The financial crises that have happened during the past few years give us an opportunity to think in retrospect about crisis. The objective of this paper is to identify and analyse various indicators which were affected by the East Asia crisis. The methodology employed is more scientific and systematic and studies structural breaks, before, during and after the crisis. Dummy variables have been used for both A5 countries and India which enabled inter-temporal and international comparisons of crisis variables. The variables do not show the same trend in case of all the crisis-hit countries. In India, none of the variables show structural break indicating that India was not hit by the crisis.

scholarly journals Testing of breakdates in agricultural prices of selected representatives of animal production

2012 ◽  
Vol 60 (7) ◽  
pp. 45-54
Author(s):  
Petra Bubáková
Keyword(s):  
Time Series ◽  
Structural Breaks ◽  
Structural Break ◽  
Animal Production ◽  
Economic Environment ◽  
Ar Model ◽  
Model Parameters ◽  
Agricultural Prices ◽  
Complex Models ◽  
Food Market

This paper deals with an investigation of breakdates in agricultural prices. A structural break has occurred if at least one of the model parameters has changed at some date. This date is a breakdate. Ignoring structural breaks in time series can lead to serious problems with economic models of time series. The aim is to determine the number and date of the breakdates in individual time series and connect them with changes in the market and economic environment. The time series of agricultural price relating to animal production, namely the prices of pork, beef, chicken, milk and eggs, are analyzed for the period from January 1996 to December 2011. The autoregressive model (AR) model of Box-Jenkins methodology and stability testing according to Quandt or Wald statistics are used for the purposes of this paper. Multiple breakdates are found in the case of eggs (September 1998, May 2004), milk (October 1999, December 2007) and chicken (October 2002, February 2005) prices. One breakdate was detected in the prices of beef (April 2002) and none in the case of pork prices. The results show the importance of multiple breakdate testing. The Quandt statistic provides one possible way of applying a multiple approach. All breakdates which were confirmed using these statistics can be associated with changes in the agri-food market and economic environment. Information about the date of changes in the time series can be used for other unbiased modelling in more complex models.

scholarly journals The Identification of Precursor Regulation Impact on the Methamphetamine Market and Public Health Indicators in the Czech Republic: Time Series Structural Break Analysis

2020 ◽  
Vol 17 (21) ◽  
pp. 7840
Author(s):  
Benjamin Petruželka ◽  
Miroslav Barták
Keyword(s):  
Public Health ◽  
Time Series ◽  
Czech Republic ◽  
Structural Breaks ◽  
Structural Changes ◽  
Structural Break ◽  
Health Indicators ◽  
Drug Market ◽  
Test Framework ◽  
The Impact

Background: This study provides insight into the impact of methamphetamine precursor regulation, which is considered to be one of the most important tools of supply reduction and a tool with potential public health impact. Methods: It is based on a longitudinal and quasi-experimental design and it investigates the changes of methamphetamine precursor regulation in Czech Republic, which is treated as a natural experiment. The statistical analysis uses features from the generalized fluctuation test framework as well as from the F test framework to estimate structural changes in the methamphetamine-related arrests and nonfatal intoxications time series. Results: The analysis identified structural breaks in the majority of the methamphetamine drug market-related time series in the period related to the tightening of regulation. The results of this study show that methamphetamine precursor regulation was associated with the proliferation of international and organized crime groups and with no change in the overall number of arrests and nonfatal intoxications. Conclusions: The precursor regulation ceteris paribus plausibly leads to the change in drug supply towards more organized groups and to an increasing involvement of foreign nationals at the drug market and is not effective in suppressing the methamphetamine market and in reducing the public health indicator of nonfatal methamphetamine intoxications.

Random order autoregressive time series model with structural break

2020 ◽  
Vol 15 (3) ◽  
pp. 225-237
Author(s):  
Saurabh Kumar ◽  
Jitendra Kumar ◽  
Vikas Kumar Sharma ◽  
Varun Agiwal
Keyword(s):  
Time Series ◽  
Structural Breaks ◽  
Time Series Data ◽  
Structural Break ◽  
Random Order ◽  
Real Data ◽  
Series Data ◽  
Model Parameters ◽  
Multiple Time ◽  
Multiple Time Points

This paper deals with the problem of modelling time series data with structural breaks occur at multiple time points that may result in varying order of the model at every structural break. A flexible and generalized class of Autoregressive (AR) models with multiple structural breaks is proposed for modelling in such situations. Estimation of model parameters are discussed in both classical and Bayesian frameworks. Since the joint posterior of the parameters is not analytically tractable, we employ a Markov Chain Monte Carlo method, Gibbs sampling to simulate posterior sample. To verify the order change, a hypotheses test is constructed using posterior probability and compared with that of without breaks. The methodologies proposed here are illustrated by means of simulation study and a real data analysis.

scholarly journals The New Econometrics of Structural Change: Dating Breaks in U.S. Labor Productivity

2001 ◽  
Vol 15 (4) ◽  
pp. 117-128 ◽  
Author(s):  
Bruce E Hansen
Keyword(s):  
Time Series ◽  
Structural Change ◽  
Labor Productivity ◽  
Time Trends ◽  
Structural Break ◽  
Unit Roots ◽  
Empirical Assessment ◽  
Time Series Econometrics ◽  
The Past ◽  
The Face

We have seen the emergence of three major innovations in the econometrics of structural change in the past fifteen years: (1) tests for a structural break of unknown timing; (2) estimation of the timing of a structural break; and (3) tests to distinguish unit roots from broken time trends. These three innovations have dramatically altered the face of applied time series econometrics. In this paper, we review these three innovations, and illustrate their application through an empirical assessment of U.S. labor productivity in the manufacturing/durables sector.

scholarly journals Structural Breaks in Mean Temperature over Agroclimatic Zones in India

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ranjit Kumar Paul ◽  
P. S. Birthal ◽  
Ankit Khokhar
Keyword(s):  
Structural Breaks ◽  
Arid Zone ◽  
Structural Break ◽  
Past Century ◽  
Asian Countries ◽  
The Past ◽  
Increasing Trend ◽  
Before And After ◽  
Agroclimatic Zones ◽  
July Temperature

Amongst Asian countries India is one of the most vulnerable countries to climate change. During the past century, surface temperature in India has shown a significant increasing trend. In this paper, we have investigated behavior of mean monthly temperature during the period 1901–2001 over four agroclimatic zones of India and also tried to detect structural change in the temperature series. A structural break in the series has been observed at the national as well regional levels between 1970 and 1980. An analysis of trends before and after the structural break shows a significant increase in July temperature in the arid zone since 1972.

The relationship between output growth and unemployment in the Philippines economy (1990-2014):

2017 ◽  
Vol 5 (1) ◽  
pp. 49
Author(s):  
Marlon A. Mojica ◽  
Virgilio M. Tatlonghari
Keyword(s):  
Labor Force ◽  
Structural Break ◽  
Empirical Relationship ◽  
Trade Openness ◽  
Negative Relationship ◽  
Participation Rate ◽  
The Philippines ◽  
Output Growth ◽  
Recursive Least Squares ◽  
Parameter Instability

This paper examines the empirical relationship between unemployment and real output in the Philippines utilizing quarterly data from the Labor Force Survey by the Philippine Statistics Authority for the period from 1990-2014. The study employed three variants of Okun’s Law – the “gap” approach, the “first difference” approach, and a dynamic approach.   Findings show that the Okun’s coefficients based on the gap approach are consistent with the theoretical expectation of a negative relationship.  In the ARDL model, labor force participation rate and trade openness were found to be significantly related to unemployment. The result of dummy variable test revealed the presence of structural break following the re-definition of unemployment in the Philippines in 2005. Recursive least squares and rolling regressions show evidence of parameter instability in several sub-periods.

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.

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