Bootstrap Rolling Window Approach Research Articles

Exchange rate and inflation between China and the United States: A bootstrap rolling-window approach

This paper studies the relationship between the exchange rate and inflation within China and the United States using the bootstrap rolling-window approach. We provide robust evidence to show that the purchasing power parity (PPP) theory is invalid for the whole period. The impact of the China-US exchange rate on relative inflation is greater than the effect of relative inflation on the exchange rate. The negative effect of the China-US exchange rate on inflation is more evident from 2006 to 2014, and inflation is more affected by the exchange rate in the US than that in China. The positive effect of US inflation on the China-US exchange rate only exists from January to July 2019 and the negative effect of China’s inflation on the exchange rate merely exists from August 2008 to July 2010 and from September 2010 to May 2011. These findings have important implications for maintaining the stability of prices and currency values in the trade market.

Revisiting the Causality between Oil Prices and Stock Markets in Selected MENA Countries: A Bootstrap Rolling-window Approach

The main objective of this paper is to explore the dynamic causality between the fluctuations in oil prices and the trends observed in stock market indices of selected economies with oil-related characteristics. These countries include oil-importing nations such as Egypt and Tunisia, as well as one oil-exporting country, namely Oman. Our study uses monthly data spanning from January 2008 to February 2022. To investigate this causality, we adopt the rolling-window bootstrap causality test. The empirical results reveal that the causal relationship between stock market indices and oil prices is not stable, but rather fluctuates over time. Remarkably, these variations in causality coincide to important events, such as the sovereign debt crisis and the Covid-19 pandemic. This suggests that external shocks and exceptional events significantly influence the causal dynamics between oil prices and stock market in these countries. It is, therefore, crucial for policymakers and investors to take into account periods of economic uncertainty and major world events into their decision-making process. By adopting a proactive approach and carefully monitoring global economic indicators, they will be able to anticipate risks, adjust their strategies to meet economic challenges.

Renewable energy effect on economy and environment: The case of G7 countries through novel bootstrap rolling window approach

One mystifying outcome in the literature on renewable-economy-environmental causality is the inconsistency of outcomes specifically across various sample sizes, model specifications, and periods. Considering such difficulties, the study applies Bootstrap Rolling Window Granger Causality (BRWGC) test with fixed-size rolling sub-samples to evaluate connections. The data used incorporates REC, EG, and CO2 emissions for G-7 nations between 1970 and 2021. Using the full-sample, it is observed that there is predictive power from REC to EG only in the USA and UK while there is predictive power from REC to CO2 emissions in the USA and Italy. However, full-sample outcomes are unreliable because models do have not parameter constancy based on parameter instability tests. Similar to full-sample results, BRWGC estimation results do not present evidence of a consistent relationship from REC to EG and CO2 emissions. However, it is discovered that causal interrelationships exist between the series in a number of the sub-samples. Additional evidence that the results are not statistical artifacts but rather reflect actual economic shifts comes from the fact that these sub-sample times coincide with important economic events. The findings of this study complement earlier research and provide a rationale for divergent outcomes.

Analyzing the mechanism between nuclear energy consumption and carbon emissions: Fresh insights from novel bootstrap rolling-window approach

This research utilizes a bootstrap rolling-window (BRW) causality test to explore the causal interrelationship between nuclear energy consumption (NUC) and carbon dioxide emissions (CO2) in 6 developed countries from 1980 to 2020. When there are structural shifts in the full-sample time series, empirical research exploring causality between two-time series generates erroneous conclusions. On the other hand, the BRW method allows researchers to find potential time-varying causality between time series using sub-sample data. The outcomes of the BRW causality test disclosed the following results: (i) a unidirectional negative causality from NUC to CO2 without feedback was found for Japan; (ii) a negative causality at sup-sample periods from NUC to CO2 surfaced at the sub-sample period while a positive causality surfaced from NUC to CO2 in sub-sample period for the United States of America (USA) and France; (iii) a negative feedback causality between NUC and CO2 was found For Canada; (iv) a positive unidirectional causality surfaced from NUC to CO2 was found for Germany, which implies that consumption of NUC worsens the environment in the sub-sampled period. The results may have policy consequences for the selected developed countries regarding NUC and CO2 nexus.

Do green innovation and financial globalization contribute to the ecological sustainability and energy transition in the United Kingdom? Policy insights from a bootstrap rolling window approach

AbstractEnvironmental sustainability and energy transition, especially the renewable energy transition, have become critical concerns of nations throughout the world in recent decades. The sustainable and eco‐friendly technologies have led to more sustainable methodologies, substantial stewardship of our natural resources, and the conversion to renewable energy sources, all of which have been demonstrated to benefit the environment significantly. However, prior studies have overlooked the ecological sustainability and energy transition effects of green technology innovation. Therefore, this study endeavored to investigate the role of green innovation (lnGRN) and financial globalization (lnFIG) on the sustainability of the environment (lnEFT) and energy transition (lnENT) in the United Kingdom using quarterly data for the period from 1995 to 2020. The study applied the time‐varying (bootstrapping) rolling window technique, which can retrieve casual associations among variables at different periods of sub‐samples. Besides this, the method is advantageous for addressing the non‐consistency of parameters and eliminating the pre‐test distortion. The novel Bootstrap Rolling‐Window full‐sample causality technique results demonstrate that lnGRN and lnFIG have unidirectional causality toward lnEFT and lnENT. Furthermore, the bootstrap rolling‐window subsamples in the final stage indicate that lnGRN and lnFIG mitigate lnEFT, whereas lnGRN and lnGDP enhance energy transition. On the other hand, lnGDP and lnETX contribute to environmental deterioration, while lnFIG hinders the energy transition. Several important policy implications are derived from the results to encourage financial globalization, green innovation technologies, renewable energy resources consumption, and environmental taxes.

Symmetric and Asymmetric Causal Relationship between Oil Prices and G7 Stock Markets: A Bootstrap Rolling-Window Granger Causality Test

This study examines the causal relationships between oil prices and the MSCI stock index of G7 countries between September 2004 and October 2020. This study is novel in implementing symmetric and asymmetric time-varying causality tests based on the bootstrap rolling-window approach. The results reveal that the causal link between oil prices and G7 stock markets is time-dependent. The periods of bidirectional causality roughly coincide with the global financial crisis and the ongoing COVID-19 pandemic. When asymmetry is accounted for, the results suggest an asymmetric causality between the two markets expressed by different patterns regarding positive and negative oil shocks. The results also indicate symmetric causality during the COVID-19 pandemic. These findings have implications for portfolio design and hedging strategies that are important to both policymakers and investors.

DOES THE CAUSAL RELATIONSHIP BETWEEN THE TWIN DEFICITS VARY OVER TIME? EVIDENCE FROM A BOOTSTRAP ROLLING WINDOW APPROACH

This paper uses the bootstrap rolling window approach to analyze the dynamic causal relationship between the fiscal deficit and the trade deficit in the US from 1901 to 2018. We find the origination and termination of each causality period by considering the structural breaks. The results show that the fiscal deficit had a positive impact on the trade deficit from 1946 to 1956, from 1982 to 1998, in 2000 and from 2002 to 2008, which is in accord with the results of the Mundell–Fleming model, while it had a negative impact from 1937 to 1945. The trade deficit had a positive impact on the fiscal deficit from 1940 to 1942, from 1959 to 1975 and from 1981 to 1994, mainly due to the World War II, oil crisis and trade friction with Japan. It means that the fiscal policy of American federal government can affect the external imbalance.

Time‐varying causal nexuses between economic growth and CO2 emissions in G‐7 countries: A bootstrap rolling window approach over 1820–2015

AbstractThis paper reinvestigates the causal nexuses between economic growth and CO2 emissions in G‐7 countries during 1820–2015 for all countries except Japan, for which the data spans from 1950 to 2015. The unit root test developed by Perron, Econometrica: Journal of the Econometric Society, 1989, 57, 1361–1401 and the cointegration test of Johansen et al., The Econometrics Journal, 2000, 3, 216–249 which accommodate structural breaks in trends are used to establish a long‐run equilibrium relationship between the variables. Our empirical analysis suggests a long‐run association between the variables. The bootstrap Granger causality test on the full sample and the sub‐samples with a fixed‐window size is used to resolve the issue of structural changes. The findings indicate that the causal relationships are country‐specific. Consistent with the short‐run stability tests, the rolling window analysis shows that causality between GDP and CO2 emissions is time‐varying. These findings offer important policy recommendations for sustainable growth and low‐carbon economy.

The Casual Relationship between China’s Financial Stress and Economic Policy Uncertainty: A Bootstrap Rolling-Window Approach

This study explores the causal relationship between China’s financial stress and economic policy uncertainty. Considering structural changes in two series, we find that long-run nexus using full-sample data are unstable, suggesting that causality tests cannot be relied upon. Then, we employ a time-varying rolling window estimation to re-examine the dynamic causalities. The empirical results show that financial stress has both positive and negative impacts on economic policy uncertainty in several sub-periods, meanwhile, economic policy uncertainty has the same effects on financial stress in China, which illustrates that the time-varying causality exists between two variables. These findings indicate that the government should make the formulation of macroeconomic policies stable and strengthen the supervision of financial markets, including the guidance of the public reasonable expectations, which are critical to the economic development in China.

Causality change between Korea and other major equity markets

The world financial markets are inter-linked in ways that varies according to market and time. We examine the causality of change focusing on the Korean market as related to the U.S. (S&P 500), Japan (Nikkei 225), Hong-Kong (HSI), and European (DAX) markets. In order to capture time-varying causality running from and to the Korea stock market, we apply the Granger causality test under a VAR model with a wild bootstrap rolling-window approach. We also propose a new concept of a significant causality ratio to measure the intensity of the Granger causality in each time unit. There are many asymmetric strengths in mutual Granger causal relationships. Moreover, there are cases with significant Granger causal relations only in one direction. The period with the most severe Granger causality both running from and to the KOSPI market is the GFC. The market that formed the two-way Granger causal relationship with the KOSPI market for the longest period is the S&P 500. The HSI and DAX markets have the strongest two-way Granger causal relationship with the KOSPI shortly after 2000, and the Nikkei market had the strongest two-way Granger causal relationship with the KOSPI market before the Asian financial crisis.

Is there a Causal Relationship between Financial Development and Economic Growth in China? Evidence from the Bootstrap Rolling-Window Approach

This study tests the causal relationship between financial development and economic growth in China applying the bootstrap rolling-window approach. The results show that economic growth has positive effects on financial development and that financial development exerts negative effects on economic growth. Economic growth promotes financial development, indicating the existence of a “demand-following” link. For a developing and repressed economy, it is critical to establish well-developed financial systems, particularly with sound financial intermediation and a liberalised interest rate, all of which promote financial innovation and improvement. It should be noted that a rational and steady relationship between financial development and economic growth is essential for China’s economic prosperity.

The dynamic causality between commodity prices, inflation and output in China: a bootstrap rolling window approach

ABSTRACTIn this article, we empirically study the time-varying bilateral causality between commodity prices, inflation and output in China. We first perform a series of parameter stability tests and find strong evidence of instability in the parameters estimated for Granger causality tests. We then use the bootstrap rolling window approach to test the causality and find that the causality from commodity prices to both inflation and output is time-varying in the entire sample period and asymmetric in different phases of the business cycle. We also find evidence of the causality from both inflation and output to commodity prices in certain sub-periods. Further discussion on the cost-price mechanism through which the economy fluctuates cyclically suggests that the dynamic causality between commodity prices and inflation contributes to understanding the nature of economic fluctuations and to forecasting economic crises. Overall, our results provide a new perspective to disentangle economic fluctuations.

Causal Relationship between Monetary Policy and the Stock Market: a Bootstrap Rolling Window Approach

Causal Relationship between Monetary Policy and the Stock Market: a Bootstrap Rolling Window Approach

Relationship between energy consumption and economic growth in South Africa: Evidence from the bootstrap rolling-window approach

ABSTRACTThis article examines the relationship between energy consumption (EC) and economic growth for South Africa for the period 1971–2009. Most studies examining this relationship do assume that it remains constant through the years; however, the reality might be different since many factors can affect the existence and direction of this causality. This article looks at a bivariate vector autoregressive process and takes into consideration any instability in the model using bootstrap rolling Granger non-causality tests. Full-sample Granger causality tests report no causal relationship between the two variables. Moreover, parameter stability tests detect instability in the model which means that the full-sample Granger causality results are not valid. We therefore allow for the possibility of structural breaks by using bootstrap rolling-window Granger causality tests. Although our results are not very strong, we do however find a sub-period from 1987 to 1989 where EC has a causal effect on gross domestic product growth. Except for this brief sub-period, the results show no linkage between economic growth and EC.

International stock return predictability: Is the role of U.S. time-varying?

This study investigates the predictability of 11 industrialized stock returns with emphasis on the role of U.S. returns. Using monthly data spanning 1980:2–2014:12, we show that there exist multiple structural breaks and nonlinearities in the data. Therefore, we employ methods that are capable of accounting for these and at the same time date stamping the periods of causal relationship between the U.S. returns and those of the other countries. First we implement a subsample analysis which relies on the set of models, data set and sample range as in Rapach et al. (J Finance LXVIII(4):1633–1662, 2013). Our results show that while the U.S. returns played a strong predictive role based on the OLS pairwise Granger causality predictive regression and news-diffusion models, its role based on the adaptive elastic net model is weak. Second, we implement our preferred model: a bootstrap rolling window approach using our newly updated data on stock returns for each countries, and find that U.S. stock return has significant predictive ability for all the countries at certain sub-periods. Given these results, it would be misleading to rely on results based on constant-parameter linear models that assume that the relationship between the U.S. returns and those of other industrialized countries are permanent, since the relationship is, in fact, time-varying, and holds only at specific periods.

The nexus between insurance activity and economic growth: A bootstrap rolling window approach

This paper investigates the long-run linkage and short-run time-lagged causality between insurance activity and economic growth for G-7 countries. To overcome the problem of structural change, we adopt the bootstrap Granger causality test to full samples and subsamples with a fixed window size. We find that there exists a long-run relation between the series, and the results of the bootstrap Granger causality test in the full sample show that the short-run causal relationships are country-specific. Differing from the full sample results, the evidence of rolling VAR models demonstrates that the short-run causal nexus between the series is time-varying across various subsamples.

The Causal Relationship Between Economic Policy Uncertainty and Stock Returns in China and India: Evidence from a Bootstrap Rolling Window Approach

This article applies a bootstrap rolling-window causality test to assess the causal relationship between economic policy uncertainty (EPU) and stock returns in China and India. Empirical literature examining causality between two time series may suffer from inaccurate results when the underlying full-sample time series have structural changes. However, the bootstrap rolling-window approach enables us to identify possible time-varying causalities between time series based on sub-sample data. Using a twenty-four-months rolling window over the period 1995:02 to 2013:02 in China and 2003:02–2013:02 in India, we do find that there are bidirectional causal relationships between EPU and stock returns in several sub-periods rather than in the whole sample period. However, the association between EPU and stock returns is, in general, weak for these two emerging countries. Our findings have important implications for policy makers and investors.

Temporal causality between house prices and output in the US: A bootstrap rolling-window approach

This paper examines the causal relationships between the real house price index and real GDP per capita in the US, using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use quarterly time-series data on the real house price index and real GDP per capita, covering the period 1963:Q1 to 2012:Q2. The full-sample bootstrap non-Granger causality test result suggests the existence of a unidirectional causality running from the real house price index to real GDP per capita. A wide variety of tests of parameter constancy used to examine the stability of the estimated vector autoregressive models indicate short- and long-run instability. This suggests that we cannot rely on the full-sample causality tests and, hence, this warrants a time-varying (bootstrap) rolling-window approach to examine the causal relationship between these two variables. Using a rolling window size of 28 quarters, we find that while causality from the real house price to real GDP per capita occurs frequently, significant, but less frequent, evidence of real GDP per capita causing the real house price also occurs. These results imply that while the real house price leads real GDP per capita, in general (both during expansions and recessions), significant feedbacks also exist from real GDP per capita to the real house price.

Causality between Financial Deepening and Economic Growth in Nigeria: Evidence from a Bootstrap Rolling Window Approach

been implemented in an attempt to integrate financial services into growth objectives in Nigeria. Further, the global financial crisis has illustrated the potentially disastrous consequences of weak financial sector policies for financial development and their impact on the economic outcomes. The crisis has challenged conventional thinking in financial sector policies and has led to much debate on how best to achieve sustainable development. Nigerian financial market has been noted to be one of the largest in Sub-Saharan Africa with regard to diversity of institutions and instruments (3). The Nigerian financial system can be broadly divided into two sub-sectors, namely: the informal and the formal sectors. The informal sector comprises the local money lenders, the thrifts, savings associations, etc. This component is poorly developed, limited in reach, and not integrated into the formal financial system. The formal financial system on the other hand can be further sub-divided into capital and money market institutions. It is made up of the banks and non-bank financial institutions. The system became liberalized in the 1980s when the structural adjustment program me was introduced. The system has undergone significant changes in terms of the policy environment, number of institutions, ownership structure, depth and breadth of markets, as well as in the regulatory framework. The financial system comprises of the central bank, commercial banks, mutual funds, brokerage firms, discount houses, and stock exchange, to mention just few. These institutions trade in financial instruments such as domestic currency, foreign currency,

Revisiting the causality between electricity consumption and economic growth in South Africa: a bootstrap rolling-window approach

The study revisits the causality relationship between electricity consumption per capita and economic growth per capita in South Africa for the period 1971-2009 using annual data and takes into consideration different time/sample periods in causal relationships using bootstrapping techniques in conjunction with rolling Granger non-causality tests. Full-sample Granger causality tests find no evidence of causal link between electricity consumption and economic growth. However, parameter stability tests indicate that there is instability in our VAR model and therefore findings from our full-sample Granger causality test cannot be relied upon. This motivates the use of bootstrap rolling-window estimation to investigate the electricity consumption-growth nexus which accounts for the time varying causal link between the two variables. The results indicate two sub-periods, 2002-2003 and 2005-2006, whereby electricity consumption had a causal effect on GDP. Apart for these brief sub periods, the results indicate no causality between the two series. However, these sub-sample periods go hand in hand with significant economic events that occurred in the South African electricity market during these sub-sample periods and the economy in general, indicating that the results can be attributed to real life events and not solely on data provided.