Structural Breaks, the Export Enhancement Program and the Relationship between Canadian and US Hard Wheat Prices

2006 ◽  
Vol 57 (1) ◽  
pp. 101-116 ◽  
Author(s):  
P. J. Dawson ◽  
Ana I. Sanjuan
Keyword(s):  
Structural Breaks ◽  
Hard Wheat ◽  
The Relationship ◽  
Export Enhancement Program

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.

scholarly journals Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 93
Author(s):  
Pavel Kotyza ◽  
Katarzyna Czech ◽  
Michał Wielechowski ◽  
Luboš Smutka ◽  
Petr Procházka
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Financial Market ◽  
Structural Breaks ◽  
Structural Changes ◽  
Global Financial Crisis ◽  
Market Uncertainty ◽  
Volatility Index ◽  
The Global Financial Crisis ◽  
The Relationship

Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial market uncertainty in a crisis time. In more detail, using sequential Bai–Perron tests for structural breaks, we check whether the global financial crisis and the COVID-19 pandemic have induced structural breaks in that relationship. Sugar prices are represented by the S&P GSCI Sugar Index, while the S&P 500 option-implied volatility index (VIX) is used to show stock market uncertainty. To investigate the changes in the relationship between sugar prices and stock market uncertainty, a regression model with a sequential Bai–Perron test for structural breaks is applied for the daily data from 2000–2020. We reveal the existence of two structural breaks in the analysed relationship. The first breakpoint was linked to the global financial crisis outbreak, and the second occurred in December 2011. Surprisingly, the COVID-19 pandemic has not induced the statistically significant structural change. Based on the regression model with Bai–Perron structural changes, we show that from 2000 until the beginning of the global financial crisis, the relationship between the sugar prices and the financial market uncertainty was insignificant. The global financial crisis led to a structural change in the relationship. Since August 2008, we observe a significant and negative relationship between the S&P GSCI Sugar Index and the S&P 500 option-implied volatility index (VIX). Sensitivity analysis conducted for the different financial market uncertainty measures, i.e., the S&P 500 Realized Volatility Index confirms our findings.

Exploring the inflationary effect of oil price in the US

2019 ◽  
Vol 13 (1) ◽  
pp. 60-76 ◽  
Author(s):  
Amine Lahiani
Keyword(s):  
Growth Rate ◽  
Structural Breaks ◽  
Oil Prices ◽  
Oil Price ◽  
Inflation Expectations ◽  
Oil Price Shocks ◽  
Price Shocks ◽  
Content Type ◽  
The Us ◽  
The Relationship

PurposeThe purpose of this paper is to explore the effect of oil price shocks on the US Consumer Price Index over the monthly period from 1876:01 to 2014:04.Design/methodology/approachThe author uses the Bai and Perron (2003) structural break test to split the data sample into sub-periods delimited by the computed break dates. Afterwards, the author uses the quantile treatment effects over the full sample and then, by including sub-periods dummies to accommodate the selected structural breaks that drive the relationship between inflation and oil price growth.FindingsThe findings include a decreased transmission effect of oil price changes on inflation in recent years; a varied elasticity of inflation to the growth rate of oil prices across the distribution; and, finally, evidence of asymmetry in the relationship between the growth rate of oil prices and inflation, with a higher transmission mechanism for decreasing rather than increasing oil prices.Practical implicationsPolicymakers should remain alert to monitoring potential inflation increases and should take precautionary measures to anchor inflation expectations, because inflation reacts differently to positive and negative oil price shocks. Moreover, authorities should consider the asymmetric reaction of inflation to oil price shocks to adopt an appropriate monetary policy strategy to achieve the price stability target.Originality/valueThe paper used a quantile regression model with structural breaks, which has not yet been used in the literature.

Investigating the Nexus Between FDI and Institutional Quality: Evidence from Morocco

2021 ◽  
pp. 097491012110530
Author(s):  
Hamza Belfqih ◽  
Ahlam Qafas ◽  
Mounir Jerry
Keyword(s):  
Structural Breaks ◽  
Institutional Quality ◽  
Large Set ◽  
Policy Recommendations ◽  
Bounds Testing ◽  
Bounds Testing Approach ◽  
Testing Approach ◽  
The Relationship ◽  
Quality Evidence ◽  
Ardl Bounds Testing Approach

This article investigates the relationship between institutional quality and foreign direct investment (FDI) in Morocco using a large set of institutional quality variables over the period 1970–2016. The study uses ARDL bounds testing approach with structural breaks and Granger causality. The analysis is then extended to the disaggregated sub-components to discern the inherent dynamics of institutional quality. The study finds several relationships between FDI and various aspects of institutional quality. Results from both models conclude with policy recommendations.

scholarly journals Stock returns, inflation, and real activity in developing countries: A Markov-switching approach

2015 ◽  
Vol 62 (1) ◽  
pp. 55-76 ◽  
Author(s):  
Atilla Cifter
Keyword(s):  
Developing Countries ◽  
Stock Returns ◽  
Structural Breaks ◽  
Markov Switching ◽  
Negative Relationship ◽  
Real Activity ◽  
Effect Hypothesis ◽  
Arfima Model ◽  
The Relationship ◽  
Unexpected Inflation

This paper empirically investigates the relationship between real stock returns, inflation, and real activity using the Markov-switching dynamic regression (MS-DR) approach. The MS-DR allows multiple structural breaks in the estimation, and we can check regression coefficients separately in the recession and expansion periods. We selected two major developing countries (Mexico and South Africa) in order to reduce location bias. We use real stock returns, expected inflation, unexpected inflation, and real GDP growth in the estimations, and the ARFIMA model is used for unexpected inflation. The empirical results show that the relationship between real stock returns and inflation is negative only in the recession period. This regime-dependency is also tested with Eugene F. Fama?s (1981) proxy effect hypothesis, and it is found that the stock returns respond differently to inflation in a regime according to the regime-dependent proxy effect hypothesis. These findings suggest that the negative relationship puzzle in the empirical finance literature can be explained with the regime-dependency effect.

scholarly journals Franchise extension and fiscal structure in the UK 1820–1913: a new test of the Redistribution Hypothesis

Cliometrica ◽  
2021 ◽  
Author(s):  
Toke S. Aidt ◽  
Stanley L. Winer ◽  
Peng Zhang
Keyword(s):  
Experimental Data ◽  
Narrative Analysis ◽  
Structural Breaks ◽  
A Priori ◽  
Historical Narrative ◽  
Compelling Evidence ◽  
Novel Method ◽  
The Uk ◽  
The Relationship ◽  
Do So

AbstractThe Redistribution Hypothesis predicts that franchise extension causes an increase in state-sponsored redistribution. We test this hypothesis by considering the relationship between franchise extension and selected aspects of fiscal structure at both central and local government levels in the UK from 1820 to 1913. We do so without imposing a priori restrictions on the direction of causality using a novel method for causal investigation of non-experimental data proposed by Hoover (2001). This method is based on tests for structural breaks in the conditional and marginal distributions of the franchise and fiscal structure time series preceded by a detailed historical narrative analysis. We do not find compelling evidence supporting the Redistribution Hypothesis.

scholarly journals A Quantitative Study of the Interactions between Oil Price and Renewable Energy Sources Stock Prices

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1693 ◽  
Author(s):  
Goran Dominioni ◽  
Alessandro Romano ◽  
Chiara Sotis
Keyword(s):  
Renewable Energy ◽  
Stock Prices ◽  
Structural Breaks ◽  
Renewable Energy Sources ◽  
Structural Break ◽  
Oil Price ◽  
Policy Implications ◽  
Volterra Model ◽  
Predator Prey ◽  
The Relationship

In this article, we apply an integrable nonautonomous Lotka–Volterra model to study the relationship between oil and renewable energy stock prices between 2006 and 2016. The advantage of this innovative approach is that it allows us to study the simultaneous interaction among n stock indices at any point in time. In line with previous studies, we find that the relationship between oil and renewables is characterized by major structural breaks taking place in 2008 and around 2013. The first structural break might be caused by the financial crisis, whereas more studies are required to advance a hypothesis on the causes behind the second structural break. Our main finding is that oil is always in a predator–prey relationship with wind, whereas it proceeds in mutualism with solar after 2012. Moreover, we find that solar and wind proceed in mutualism between 2008 and 2013 but have a rivalrous interaction before (competition) and after (predator–prey) that period. We explore the possible reasons behind these patterns and their policy implications.

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