Nonlinear Cointegration Research Articles

Wheat Price Dynamics in Hungary: Resilience to Shocks

This study investigates the impact of recent global disruptions, focusing on the Covid-19 pandemic and the ongoing Ukraine-Russia war, on Hungary's wheat-flour supply chain, with a focus on price transmission and market integration. While much research has explored food supply chain disruptions and rising prices globally, there has been limited analysis of their effects on Central and Eastern European agricultural markets, particularly Hungary. This study fills that gap by using linear and non-linear cointegration approaches to examine price relationships along the wheat supply chain. Causality tests indicate a strong bidirectional relationship between producer and consumer prices, demonstrating a tightly integrated market. Cointegration analysis reveals a long-term equilibrium between these prices, with no significant structural breaks during either the pandemic or the Ukraine war. Despite short-term price asymmetries, the study finds that producer-level price changes are ultimately transmitted to consumer prices in the long run, offering insights into Hungary’s unique agricultural market dynamics.

Cement production and CO2 emission cycles in the USA: evidence from MS-ARDL and MS-VARDL causality methods with century-long data

The cement industry is among the top three polluters among all industries and the examination of the nonlinear and cointegration dynamics between cement production and CO2 emissions has not been explored. Focusing on this research gap, the study employs a novel Markov-switching autoregressive distributed lag (MS-ARDL) model and its generalization to vector error correction, the MS-VARDL model, for regime-dependent causality testing. The new method allows the determination of nonlinear long-run and short-run relations, regime duration, and cement-induced-CO2 emission cycles in the USA for a historically long dataset covering 1900–2021. Empirical findings point to nonlinearity in all series and nonlinear cointegration between cement production and cement-induced CO2 emissions. The phases of regimes coincide closely with NBER’s official economic cycles for the USA. The second regime, characterized by expansions, lasts twice as long relative to the first, the contractionary regime, which contains severe economic recessions, as well as economic crises, the 1929 Great Depression, the 1973 Oil Crisis, the 2009 Great Recession, and the COVID-19 Shutdown and Wars, including WWI and II. In both regimes, the adverse effects of cement production on CO2 emissions cannot be rejected with varying degrees both in the long and the short run. Markov regime-switching vector autoregressive distributed lag (MS-VARDL) causality tests confirm unidirectional causality from cement production to CO2 emissions in both regimes. The traditional Granger causality test produces an over-acceptance of causality in a discussed set of cases. Industry-level policy recommendations include investments to help with the shift to green kiln technologies and energy efficiency. National-level policies on renewable energy and carbon capture are also vital considering the energy consumption of cement production.Graphical

On the Long-run Sustainability of Current Account Deficits in India: Some Insights from Linear and Non-linear Cointegration Tests

On the Long-run Sustainability of Current Account Deficits in India: Some Insights from Linear and Non-linear Cointegration Tests

Asymmetric Effects of Uncertainty and Commodity Markets on Sustainable Stock in Seven Emerging Markets

The increase in global economic policy uncertainty (EPU), volatility or stock market uncertainty (VIX), and geopolitical risk (GPR) has affected gold prices (GD), crude oil prices (WTI), and stock markets, which present challenges for investors. Sustainable stock investments in emerging markets may minimize and diversify investor risk. We applied the non-linear autoregressive distributed lag (NARDL) model to examine the effects of EPU, VIX, GPR, GD, and WTI on sustainable stocks in seven emerging markets (Thailand, Malaysia, Indonesia, Brazil, South Africa, Taiwan, and South Korea) from January 2012 to June 2023. EPU, VIX, GPR, GD, and WTI showed non-linear cointegration with sustainable stocks in seven emerging markets and possessed different asymmetric effects in the short and long run. Change in EPU increases the return of Thailand’s sustainable stock in the long run. The long-run GPR only affects the return of Indonesian sustainable stock. All sustainable stocks are negatively affected by the VIX and positively affected by GD in the short and long run. Additionally, long-run WTI negatively affects the return of Indonesia’s sustainable stocks. Our findings contribute to rational investment decisions on sustainable stocks, including gold and crude oil prices, to hedge the asymmetric effect of uncertainty.

How do financial institutions and markets impact the ecological footprint in Saudi Arabia? A nonlinear cointegration approach

How do financial institutions and markets impact the ecological footprint in Saudi Arabia? A nonlinear cointegration approach

Non-linear Cointegration Test, Based on Record Counting Statistic

Non-linear Cointegration Test, Based on Record Counting Statistic

Nonlinear cointegration analysis of China’s money demand function stability

ABSTRACT In this study, an analytical framework of non-linear co-integration theory is applied to empirically analyze the Chinese money demand function data from Q1 1994 to Q3 2017. The results show that it neglects non-linearities in all variables and that M1 and M2 have long-run nonlinear equilibrium relationships with real GDP, interest rate, inflation rate, the effective exchange rate of RMB, and trade dependence. Further, an enhanced BP neural network is applied to estimate the long-run equilibrium equation, and it is found that the marginal coefficients of M2 are more stable than those of M1. It is suggested that although China was much less dependent on foreign trade since the 2008 financial crisis, the RMB-USD exchange rate and financial variables outside China had a slight impact on China’s money demand because of its closed financial market so that the financial crisis had little effect on China’s financial system.

Comparison of the Asymmetric Relationship between Bitcoin and Gold, Crude Oil, and the U.S. Dollar before and after the COVID-19 Outbreak

This paper aims to reveal the asymmetric co-integration relationship and asymmetric causality between Bitcoin and global financial assets, namely gold, crude oil and the US dollar, and make a comparison for their asymmetric relationship before and after the COVID-19 outbreak. Empirical results show that there is no linear co-integration relationship between Bitcoin and global financial assets, but there are nonlinear co-integration relationships. There is an asymmetric co-integration relationship between the rise in Bitcoin prices and the decline in the US Dollar Index (USDX), and there is a nonlinear co-integration relationship between the decline of Bitcoin and the rise and decline in the prices of the three financial assets. To be specific, there is a Granger causality between Bitcoin and crude oil, but not between Bitcoin and gold/US dollar. Before the outbreak of the COVID-19 pandemic, there was an Asymmetric Granger causality between the decline in gold prices and the rise in Bitcoin prices. After the outbreak of the pandemic, there is an asymmetric Granger causality between the decline in crude oil prices and the decline in Bitcoin prices. The COVID-19 epidemic has led to changes in the causality between Bitcoin and global financial assets. However, there is not a linear Granger causality between the US dollar and Bitcoin. Last, the practical implications of the findings are discussed here.

THE INFLUENCE OF SHORT-TERM AND LONG-TERM FACTORS ON THE DEVELOPMENT OF KEY SECTORS OF THE SOCIO-ECONOMIC SPHERE OF THE ALTAI KRAI

A prerequisite for the stable progressive development of the economy at any level is the predictability of the behavior of its elements. In modern conditions, the economy of the region can be affected by both external factors and internal changes.
 The purpose of the study is to identify short-term and long-term factors affecting the development of key indicators of socio-economic development for the region. The article presents the results of modeling the influence of these factors on the indicators of the main economic sectors of the region and the social sphere.
 The obtained results are provided by the application of econometric methodology. In particular, the methods of checking for a unit root are used, taking into account possible nonlinearity, seasonality and the presence of structural breaks, Granger causality, nonlinear cointegration relationship.
 Thus, the hypothesis of a nonlinear long-term relationship between nominal accrued wages and the consumer price index has been confirmed, a long-term relationship between the coefficients of natural and migration growth, a causal relationship between the development of the main sectors of the economy of the region with the external price environment has been revealed.
 Further steps are proposed to develop the results obtained, in particular, in the development, modification and control of the implementation of strategic planning documents of the region.

The impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS index before and during COVID-19: a quantile regression and NARDL analysis

PurposeThis study aims to explore the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19.Design/methodology/approachThis research analyzes the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19, using the quantile regression approach for the 2016–2020 period. In addition, to catch long- and short-run asymmetries of cryptocurrencies on aforementioned dependent variables, an asymmetric nonlinear co-integration (nonlinear autoregressive distributed lag [NARDL]) approach is applied.FindingsThe result of the quantile regression shows that in a high market, which corresponds to the 90th quantile, the FTSE MIB, CAC40, SSE, BSE 30, and BVSP stock market showed a statistically insignificant negative coefficient, on the Bitcoin price. In a middle and low markets, which correspond to the 0.2, 0.3 and 0.5th quantiles, the BVSP, FTSE MIB, S&P/TSX, SSE and Nikkei stock markets show statistically significant and positive on Bitcoin. Evidence from the NARDL shows a statistically significant positive impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS indices before and during COVID-19 pandemic.Originality/valueThese results can provide investors with valuable analysis and information and help them make the best decisions and adopt the best strategies. Therefore, future investigations may concentrate and examine the monetary and governmental policies to be adapted to face the COVID-19 pandemic’s dangerous effects on both the society and the economy. For this reason, investors should take this into account when making their asset allocation decisions. Moreover, the portfolio managers, such as index funds, may consider few eligible cryptocurrencies for their inclusion into the portfolio. However, the speculators present in both stock and crypto markets may opt for a spread strategy to improve their portfolio returns.

Sustainable Strategies for the Indian Coal Sector: An Econometric Analysis Approach

Thermal power generation based on coal has been identified as the second largest polluting industry due to the greenhouse gas emissions caused by coal combustion. The pollution caused by this industry is not limited to power generation, but it also manifests itself throughout the use of products. Although a huge emphasis has been placed on replacing coal-based power generation with renewable resources, we showed that Indian power generation will depend on coal for more than fifty percent of its demand in the near future. In our study, we utilized a combination of linear cointegration, non-linear cointegration, ARIMA, and the VECM to forecast the use of coal based on the Indian industrial index and the amount of electricity generated through coal combustion required to meet the demand. Given that pollution and carbon emissions are inherent in the coal usage cycle, we drafted policy implications and recommendations to mitigate the consequences, green the coal usage cycle, and improve the coal supply chain.

Asymmetric and nonlinear comovements of credit default swap and bond markets: evidence from an emerging market

ABSTRACT This study examines the equilibrium and price discovery relationships between credit default swap (CDS) and bond markets through the symmetric and non-symmetric cointegration approaches, focusing on Turkish sovereign markets. While the findings, obtained using the threshold autoregressive (TAR) and momentum threshold autoregressive (MTAR) models, confirm the asymmetric and nonlinear cointegration relationship between CDS and bond markets described in a limited number of studies in the relevant literature, they also, in contrast to other relevant studies, reveal the importance of data frequency and structural breaks in price discovery research. In this context, the results show that the CDS market is the leader in price discovery in high-frequency data and after the first sub-period, and the bond market is the leader in price discovery in low-frequency data and before the first sub-period.

Nonlinear nexus between infectious diseases and tourism

ABSTRACT This study investigates the nexus between infectious diseases and tourism. We study the nonlinear relationship between the number of tourists, pandemic index, and gross domestic product in eleven European countries from January 1996 to March 2021. We propose a nonlinear cointegration approach based on a panel-switching transition model; this allows the tourism variable to switch smoothly between regimes after incorporating an endogenous change in the pandemic variable. The findings reveal a nonlinear cointegration relationship between the variables. Furthermore, a nonlinear error-correction mechanism between tourism and infectious diseases is identified, provided that the pandemic index remains below a certain threshold. These results can help professionals and researchers construct strategies to restore tourism following an epidemic.

Enhancing environmental quality in Portugal: can CO2 intensity of GDP and renewable energy consumption be the solution?

Despite Portugal's effort to reduce carbon emissions, the country still emits about 1.6% of the European Union's CO2 emissions. Meanwhile, limited empirical studies have been undertaken in the context of Portugal. As a result, this study examines the asymmetric and long-term impact of CO2 intensity of GDP, energy consumption, renewable energy and economic growth on CO2 emissions in Portugal from 1990 to 2019. The nonlinear autoregressive distributed lag (NARDL) is employed to uncover the asymmetric connection. The findings show that there is nonlinear cointegration among the variables. The long-run estimation reveals a positive change in energy consumption positively affects CO2 emissions, while a negative shock in energy consumption has a neutral effect on CO2 emissions. Furthermore, positive shocks of economic growth and CO2 intensity of GDP enhance environmental deterioration by increasing CO2 emissions. Meanwhile, the negative shock of these regressors positively impacts CO2 emissions. In addition, positive shocks in renewable energy enhance environmental quality, while negative shocks in renewable energy increase environmental deterioration in Portugal. Policymakers should focus on reducing per-unit energy usage and CO2 efficiency gains, which would necessitate a significant reduction in CO2 intensity andenergy density of GDP.

Asymmetrical effects of renewable energy consumption, financial development, and urbanization on the economic growth of China: does the role of technology matters.

Our paper investigates the association of renewable energy, financial development, urbanization, and growth in China along with technology. The newly developed econometric techniques (asymmetries) have been applied to explore short and long-run nonlinear relation among variables by utilizing annual data for the period of 1965-2021. In nonlinear cointegration, findings highlight the importance of renewable energy consumption for growth and development. Urbanization also confirms a positive association with growth and development where positive shocks were more dominant to support the growth process. The stock of technology brings a positive impact on growth and development whereas financial development results reveal to consider policy carefully. Asymmetric causality supports a uni-directional causal association between renewable energy, financial development, and growth. Policy recommendations are also highlighted according to the results.

Role of Natural resources rent on economic growth: Fresh empirical insight from selected developing economies

The connection between natural resource rents and economic development has recently been the subject of heated dispute. Therefore, in this study we have analysed the relationship among natural resources rent and economic growth in a sample of the selected developing economiesbetween 1990 and 2020. The empirical findings support the nonlinear cointegration of variables in the selected developing economies. The ‘resource curse’ phenomenon in these nations is supported by long-run asymmetric effect data showing that total natural resource rent negatively impacts economic development in Nepal, Sri Lanka, and Afghanistan. However, we discovered that natural resource rent had a favourable impact on economic growth in Pakistan and India, suggesting that natural resources benefit these nations' economies. Vietnam and Sri Lanka show a long-run asymmetric impact between the total natural resource rent and economic development, whereas Bhutan and the Maldives show a short-run asymmetric effect. These empirical findings have several practical policy implications.

Natural gas and crude: evidence of nonlinear co-integration from Indian commodities market

Natural gas and crude: evidence of nonlinear co-integration from Indian commodities market

A study of the nonlinear dynamic interrelationship between CO2 emissions and logistics sector output growth

Using provincial panel data spanning from 1995 to 2020, this paper examines the nonlinear interrelationship between logistics carbon dioxide emissions and output growth. For this purpose, we conduct a nonlinear co-integration test in heterogeneous panels; our results suggests a long-run relationship between these two variables. In contrast, adjustment to the equilibrium is inherently nonlinear. Furthermore, we estimate a panel smooth transition vector error correction model. Our major contributions, as we know, are the first study confirming the existence of a dynamic mechanism between logistics carbon dioxide emissions and regional output growth and the Environmental Kuznets Curve in China. Last, the interaction between logistics carbon dioxide emissions and regional output growth varies over the output growth in Chinese provinces and autonomous regions. Our results highlight the importance of considering possible nonlinearities in analyzing output-carbon dioxide emissions causality nexus and designing energy policies.

The dynamic interdependence structure and risk spillover effect between Sino-US stock markets

PurposeThe purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.Design/methodology/approachThis paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.FindingsThe empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.Originality/valueThis paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

Exploring the Asymmetrical Influence of Economic Growth, Oil Price, Consumer Price Index and Industrial Production on the Trade Deficit in China

The present study intends to scrutinize the asymmetrical influence of economic growth, industrial production, CPI (consumer price index) and oil price on the trade deficit for the People’s Republic of China’s economy. The Toda–Yamamoto causality, non-linear ARDL method, and quarterly data for 1995Q1 to 2021Q4 have been utilized to investigate the results. The estimated results confirm the uni-directional causality and presence of non-linear co-integration among variables under discussion. However, bound test analysis also reveals the long-run asymmetrical association among TD (trade deficit), IP (industrial production), oil price, and GDP growth, but not the CPI (consumer price index). Further, long-run asymmetrical outcomes highlight that a decrease (increase) in industrial production and an increase (decrease) in oil price and GDP growth rate increase (decrease) the trade deficit. Short-run asymmetrical outcomes reveal a similar trend to the long run, but the impact of all variables in the short run is insignificant, which means that linkages between the trade deficit and the explanatory variables are a long-run phenomenon in People’s Republic of China. Thus, in terms of policy, to reduce the trade deficit, it is necessary to focus on attaining standardized GDP growth, increasing industrial-sector production using advanced technology, and replacing oil-using energy sources with green technology (solar panels, wind farm energy).