Multiple Structural Breaks Research Articles

Further evidence on Middle East and North Africa financial markets integration

This paper provides further evidence on financial integration among MENA and developed the US stock markets between 2000 and 2015. This paper employs Zivot and Andrews (1992) and Bai and Perron (2003) methods to test for single and multiple structural breaks in MENA markets, respectively, along with the autoregressive distributed lag (ARDL) and Granger causality techniques to examine the dynamic interaction among the aforementioned stock markets in both long and short-run. Results find that, in general, the Global Financial Crisis (GFC) to be the most significant event leading to structural change in almost all the MENA markets. Furthermore, MENA countries are cointegrated among each other, and with US stock market. Financial markets in the MENA region are not isolated from global events and global shocks such as the GFC and the European debt crisis are found to have at least the same impact as local and regional events on the financial systems in MENA countries.

Further evidence on Middle East and North Africa financial markets integration

This paper provides further evidence on financial integration among MENA and developed the US stock markets between 2000 and 2015. This paper employs Zivot and Andrews (1992) and Bai and Perron (2003) methods to test for single and multiple structural breaks in MENA markets, respectively, along with the autoregressive distributed lag (ARDL) and Granger causality techniques to examine the dynamic interaction among the aforementioned stock markets in both long and short-run. Results find that, in general, the Global Financial Crisis (GFC) to be the most significant event leading to structural change in almost all the MENA markets. Furthermore, MENA countries are cointegrated among each other, and with US stock market. Financial markets in the MENA region are not isolated from global events and global shocks such as the GFC and the European debt crisis are found to have at least the same impact as local and regional events on the financial systems in MENA countries.

The value of the US dollar and its impact on oil prices: Evidence from a non-linear asymmetric cointegration approach

The dynamic relationship between the real oil price and the US real effective exchange rate (REER) is one of the most important relationships for policy practitioners. But, the literature has largely disagreed on the direction of causation in cases when cointegration was found. This paper addresses this issue and provides new evidence by using an approach that accounts for the potential of asymmetric cointegration and multiple structural breaks. This was done using Threshold Autoregressive (TAR) and Momentum TAR (MTAR) models. Some key findings emerge: first, the variables are cointegrated with significant asymmetric error-correction adjustments, and the US REER is found to be weakly exogenous in this process. When exogenous shocks cause disequilibrium, then the adjustment is slower in the case of when a downward adjustment of real oil prices is needed to regain equilibrium, compared to the case of when an upward adjustment is needed. This asymmetry could be driven by downward rigidity in oil prices. Second, it follows that long-run causation is unidirectional, going from the US REER to real oil prices, however, there is bidirectional causation in the short run. The estimations accounted for four structural breaks found in the sample. Overall findings imply that countries exporting to the US may lose competitiveness in the long run not only because of an increased conversion price but also through the upward pressure on oil prices. From a US perspective, increased competitiveness leads to increased real oil prices, which may temper the gains of oil intensive exports in the long run.

Estimation of Environmental Kuznets Curve for CO2 emission: Role of renewable energy generation in India

Abstract The existing literature on environmental Kuznets curve (EKC) is mainly focused on finding out the optimal sustainable path for any economy. Looking at the present renewable energy generation scenario in India, this study has made an attempt to estimate the EKC for CO2 emission in India for the period of 1971–2015. Using unit root test with multiple structural breaks and autoregressive distributed lag (ARDL) approach to cointegration, this study has found the evidence of inverted U-shaped EKC for India, with the turnaround point at USD 2937.77. The renewable energy has found to have significant negative impact on CO2 emissions, whereas for overall energy consumption, the long run elasticity is found to be higher than short run elasticity. Moreover, trade is negatively linked with carbon emissions. Based on the results, this study concludes with suitable policy prescriptions.

Re-examination of the convergence hypothesis among OECD countries: Evidence from Fourier quantile unit root test

In this paper we revisit the convergence hypothesis among OECD countries. Unlike previous research which relied upon conventional unit root tests to determine if per capita real income in each country converge toward the real per capita income of a benchmark level, we employ recently introduced quantile unit root testing procedure which also accounts for multiple and unknown structural breaks via a Fourier expansion series. Our results indicate that the negative shocks due to World wars I and II and/or financial crises have transitory effects in countries such as Japan and Germany, while in other countries like Italy and France they have permanent effects.

Asymmetries, outliers and structural stability in the US gasoline market

By using a recently developed nonlinear cointegration methodology, and a sample that encompasses more than thirty years of monthly data, we investigate whether the transmission of crude oil price variations to gasoline prices in the US market is asymmetric, i.e.,depends on the sign of the change in the explanatory variable, considering both the long- and the short-run. The model is further extended by taking separately into account the effects of extreme and mild changes in crude oil prices. This allows us to verify whether and to what extent the size and shape of any observed asymmetry in pricing is affected by the presence of outliers. Moreover, given the substantial length of the sample considered, we test for the possible presence of multiple structural breaks of unknown timing in the cointegrating vector. Our results indicate that the relationship between the prices of gasoline and crude oil has undergone a single structural break in the late 2008, and that after the break extreme observations have a non-negligible role in shaping asymmetry.

An efficient Bayesian approach to multiple structural change in multivariate time series

SummaryThis paper provides a feasible approach to estimation and forecasting of multiple structural breaks for vector autoregressions and other multivariate models. Owing to conjugate prior assumptions we obtain a very efficient sampler for the regime allocation variable. A new hierarchical prior is introduced to allow for learning over different structural breaks. The model is extended to independent breaks in regression coefficients and the volatility parameters. Two empirical applications show the improvements the model has over benchmarks. In a macro application with seven variables we empirically demonstrate the benefits from moving from a multivariate structural break model to a set of univariate structural break models to account for heterogeneous break patterns across data series.

The end of Brazilian big inflation: lessons to monetary policy from a standard New Keynesian model

The paper analyzes economic stabilization in Brazil in the context of a New Keynesian model estimated with Bayesian techniques. Dataset covers the period 1975–2012. Our methodology is based on tests for multiple structural breaks at unknown dates and counterfactual exercises. The results show that inflation and output volatility present an inverted U-shape pattern, peaking at the 1985–1994 sample. Changes in the monetary policy stance and milder shocks accounted for the reduced inflationary volatility (about 50% each, in some specifications). However, some assumptions indicated that a sharp decline in the Phillips curve slope was also important for controlling inflation. Concerning to output, the sole explanation for its volatility fall seemed to be smaller shocks. Therefore, we conclude that a mix of the “good luck” and “good policy” hypotheses mainly originated the current period of increased stability in the country.

Long memory or structural breaks: Some evidence for African stock markets

This study explores two main issues. One: How do the exchange rate and inflation rate impact long term dependency structure of weekly returns of seven African stock markets? Two: What is the long term dependency structure of stock returns and variance in the absence and in the presence of structural breaks? The sample period is 06-2002 through 02-2014. The returns are de-thinned to account for illiquidity of stock returns. The study implements sequential multiple structural breaks test to identify structural breaks. Three semi-parametric tests and three parametric methods are then implemented to test for the long memory behavior of raw returns and break-adjusted returns. The long memory estimates decline monotonically in magnitude or in statistical significance as returns are adjusted for exchange rate and then inflation rate. There is evidence of multiple structural shifts whose break dates correspond to major domestic or global events. Without structural breaks, the results indicate the existence of long memory components in returns and variance. Using the break-adjusted returns, the long memory evidence in returns and variance weakens in magnitude and/or statistical significance or just dissipates in some ASMs. The absence of long memory using break-adjusted returns suggests that long memory may be an artifact of short memory encountering breaks in some ASMs. Caution is therefore warranted when interpreting long memory inferences in the presence of structural breaks and making policy recommendations. Our evidence is useful to investors, fund managers and policy makers.

Unit Roots and Structural Breaks

This special issue deals with problems related to unit roots and structural change, and the interplay between the two.[...]

Are Dragons and Tigers Catching Up?

This paper studies the catching up process in per capita income of the so-called Asian Dragons and Tigers. It contributes to the literature in several ways. First, it tests the catching up hypothesis using the longest time span ever considered, from 1870 to 2014. Second, it documents the experiences of these two groups of countries and provides potential explanations for them. Third, by using the Kejriwal and Perron (2010) algorithm, we are able to endogenously estimate multiple structural breaks in the level and the trend of the series without prior knowledge of their integration level. This surpasses technical concerns of previous empirical studies. Fourth, it inquiries into how the Asian financial crisis affected the catching up process among the Dragons and Tigers economies.

On Bayesian analysis and unit root testing for autoregressive models in the presence of multiple structural breaks

Abstract A Bayesian approach is suggested for inferring stationary autoregressive models allowing for possible structural changes (known as breaks) in both the mean and the error variance of economic series occurring at unknown times. Efficient Bayesian inference for the unknown number and positions of the structural breaks is performed by using filtering recursions similar to those of the forward–backward algorithm. A Bayesian approach to unit root testing is also proposed, based on the comparison of stationary autoregressive models with multiple breaks to their counterpart unit root models. In the Bayesian setting, the unknown initial conditions are treated as random variables, which is particularly appropriate in unit root testing. Simulation experiments are conducted with the aim to assess the performance of the suggested inferential procedure, as well as to investigate if the Bayesian model comparison approach can distinguish unit root models from stationary autoregressive models with multiple structural breaks in the parameters. The proposed method is applied to key economic series with the aim to investigate whether they are subject to shifts in the mean and/or the error variance. The latter has recently received an economic policy interest as improved monetary policies have also as a target to reduce the volatility of economic series.

FDI Inflows Influence Merchandise Exports? Causality Analysis for India over 1991-2016

The deepening waves of globalization since late eighties and the growth in the international integrated production networks (IPN) over the past decade have significantly increased both Foreign Direct Investment (FDI) and merchandise trade flows. India, whose share in global FDI inward stock and global merchandise exports have increased from 0.08 percent to 1.13 percent and 0.51 percent to 1.60 percent over 1989–2015 respectively, is no exception to this trend. The current paper attempts to explain the influence of FDI inflows on India’s exports through a time series analysis with quarterly data over the period 1990–91 (Q1) to 2015–16 (Q4) in the presence of multiple structural breaks. The empirical analysis indicates that while exports influence FDI inflows, the reverse is not true in the Indian context. The result underlines the fact that FDI inflows in the country may primarily be targeting the growing domestic sectors, rather than utilizing the domestic resources for reaching the world market.

Hybrid multiple structural break model for stock price trend prediction

Because of the noises from the internal and external factors, the uncertainty increases in the financial market. The challenges of nonlinearities, volatility clusters, and multiple structural breaks which entail risk. Due to the risk, the prediction task becomes more complex. First, this work proposes a hybrid model to predict the one-day future price for the stocks; MSFT, Apple, Goldman Sachs and JP Morgan use the Markov switching model coupled with radial basis function network for prediction. Second, this paper forecasts the buy/sell trading strategy using the proposed hybrid method. Also, this paper explores the risk of investment decisions and the trading performance based on different value at risk (VaR) methods. Finally, by comparing the proposed model results with the pure linear and non-linear models, the prediction efficiency is evaluated. The experimental results indicate the investment risk, and the investment trading strategy provides a better accuracy with the best investment decision for the selected stocks.

Fourier methods for analyzing piecewise constant volatilities

We develop procedures for testing whether a sequence of independent random variables has constant variance. If this is fulfilled, the modulus of a Fourier-type transformation of the volatility process is identically equal to one. Our approach takes advantage of this property considering a canonical estimator for the modulus under the assumption of piecewise identically distributed zero mean observations. Using blockwise variance estimation, we introduce several test statistics resulting from different weight functions. All of them are given by simple explicit formulae. We prove the consistency of the corresponding tests and compare them to alternative procedures on extensive Monte Carlo experiments. According to the results, our proposals offer fairly high power, particularly in the case of multiple structural breaks. They also allow for an adequate estimation of the change point positions. We apply our procedure to gold mining data and also briefly discuss how it can be modified to test for the stationarity of other distributional parameters.

Financial development and poverty reduction in emerging market economies

Poverty reduction is one of the key challenges in the globalized world. This study investigates the relationship between financial development and poverty reduction in emerging market economies during the period 1993- 2012. The Carri?n-i-Silvestre, del Barrio-Castro, and L?pez-Bazo (2005) panel unit root test and the Basher and Westerlund (2009) cointegration test was applied considering the cross-sectional dependence and multiple structural breaks in the study period. The findings indicated that financial development, including banking sector development and stock market development, had a significant positive impact on poverty reduction in emerging market economies.

Analysing the Efficiency of the Turkish Stock Market with Multiple Structural Breaks

Analysing the structural changes in the economy is important. Cruical financial, economic and social events may cause structural breaks. Not taking into account the existing structural breaks causes reduction in the ability to reject the null hypothesis of unit root equal to zero. In the previous studies, usually structural breaks are either not taken into account or in more recent studies one or two structural breaks are included. This study investigates the informational efficiency of the Turkish market in weak form considering multiple structural breaks and taking into account the effect of financial structural changes for the period of 1988-2011. The results indicated that BIST 100 National Index is informationally efficient in the weak form. With Clemao2 and Clemio2 analyses, the structural breaks in 1988:01-2011:11 period are 2007:11 and 2009:1; 2007:12 and 2009:2 respectively. When 1988:01-2011:11 period is separated into two subperiods as 1988-1996 and 1997-2011, in 1988-1996 period with clemao2 analysis 1995:9 and 1996:5, with clemio2 analysis 1995:10 and 1996:6 are the structural break dates. In 1997-2011 period, with clemao2 2007:11 and 2008:12, with clemio2 2007:12 and 2008:9 are the structural break dates. These structural breaks reflect the effects of 1994 national crisis and 2008 global crisis.

The Impact of Public Investment on Private Investment: Evidence from India

Executive Summary This paper estimates the impact of public investment on private investment in India during 1970-2013 using ARDL procedure developed by Pesaran and Shin (1999) and Pesaran, Shin, and Smith (2001) by incorporating endogenously determined structural break in the model. The base line result implies that a 1 per cent increase in public investment as a ratio to GDP leads to 0.81 per cent and 0.53 per cent decrease in private investment as a ratio to GDP in the long run (about 4 to 5 years) and short run (about 2 to 3 years), respectively, after controlling for economic conditions. To address the concern that the results may be driven by government consumption expenditure, fiscal deficit, or inadequate infrastructure, the analysis was repeated by estimating the investment function after including these variables and similar results were obtained. The investment regression was also estimated for a shorter sample period (1978–2013) to get the same result. It is observed that the crowding out effect of public investment on private investment has dampened during the post-liberalization period. The results also reveal that a “market friendly” incumbent and an increase in foreign direct investment dampen the magnitude of the crowding out effect of public investment. Formal tests were conducted to examine whether the crowding out effect was driven by political uncertainty and political business cycle channels but no evidence for the same is found. The results also reveal that public infrastructure (represented by kms of roads per capita) has a positive effect on private investment in the short run. This is similar to the findings by Blejer and Khan (1984) that while public infrastructure investment is complementary to private investment, other kinds of public investment lead to crowding out of private investment. This suggests that public investment should be more focused on goods and services which are enjoyed or consumed by many consumers simultaneously and non-excludable in nature with significant positive externalities. In this model, a single endogenously determined structural break was included and the possibility of multiple breaks was excluded. There is a scope to increase multiple structural breaks and re-investigate the impact of public investment on private investment in India in future studies.

Oil Price Versus Oil Output: Is Opec's Strategy Right?

The goal of this paper is to analyze the impact of OPEC’s oil price level versus oil supply strategy on the country’s gross domestic product (GDP) growth rate. Our motivation comes from a fundamental dilemma facing OPEC nations. Its members need to choose between the traditional OPEC cartel policy of setting quotas to target a certain oil price level versus that of choosing the oil output level that maximizes profits of oil producing firms. The main objective of this research is to investigate the relative efficiency of these two policies in promoting long-run economic growth in oil exporting countries. For that purpose, it uses time-varying parameter models in order to account for multiple structural breaks that characterize the crude oil market. This paper contributes to the oil and macroeconomics literature by showing that the impact of crude oil output on oil exporters’ GDP growth is much stronger than that of oil price fluctuations.

Structural Distress Index: Structural Break Analysis of the Czech and Polish Stock Markets

The estimation of multiple structural break models is usually associated with identification of spurious break points, which are identified by universal algorithms. This leads to overvaluation of structural distress in financial markets represented by data series. The paper is focused on an estimation of the new index, which incorporates results of Student, Bartlett, GLR, Mann-Whitney, Mood, Lepage, Kolmogorov-Smirnov and finally Cramer-von-Mises tests statistics together. The new measure is named Structural Distress Index and evaluates a probability of structural break occurrence based on estimations of proposed models. SDI values show that Czech and Polish stock markets went through more instable period in 1990s than at the beginning of the global financial crisis in 2007. SDI measure is straightforward and can be easily explained, the highest values of SDI can identify the most important break points of the research period, which starts in year 1993 and ends in year 2014. Universality of SDI offers its further extension and application to further research of financial markets.