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The Statistical Analysis of Cointegration Vectors
Abstract
We consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors. We then derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimensions. Further we test linear hypotheses about the cointegration vectors.The asymptotic distribution of these test statistics are found and the first is described by a natural multivariate version of the usual test for unit root in an autoregressive process, and the other is a χ2 test.
... In its simplest form, the main idea is that if the price series (P t ) from two markets are integrated of the same order and there exists a linear combination β"'P t which is stationary (i.e., I(0)), then they are cointegrated with cointegrating vector β which describes their long-run equilibrium relationship (Engle & Granger 1987). The null hypothesis of interest under this simple framework is that there is no cointegration and it can be evaluated using two test statistics referred to as the Eigen value and Trace tests (Johansen, 1991;Johansen, 1988). Rejecting no cointegration implies that in the long run, the two prices move together. ...
... We exhaustively employed six conventionally used unit root test statistics (Dickey & Fuller 1981;Dickey & Fuller 1979;Elliott, Rothenberg & Stock, 1996;Kwiatkowski et al., 1992;Phillips & Perron 1988;Zivot & Andrews 1992), with constant and/or time trend where the option is applicable, to minimize the risk of assigning the wrong order of integration to each price series. For pairs integrated of the same order, the null hypothesis of no cointegration is tested against the alternative hypothesis of one cointegrating vector (Johansen, 1991;Johansen, 1988). If no cointegration is rejected, we test for threshold cointegration and the number of implied regimes using recommended test statistics (Hansen & Seo 2002). ...
This research explores the integration of regional markets for 21 food commodities in Ghana. Utilizing co-integration tests and autoregressive distributed lag models, it investigates price linkages and market responsiveness, also considering the impact of telecommunications and road infrastructure. The study reveals that markets generally adjust quicker to price increases than decreases, with disparities noted in specific regions and commodities. It emphasizes the importance of improving internet speeds and road quality to enhance market integration, suggesting policy measures to sustain and optimize agri-food networks amid global disruptions.
... The long-run equilibrium relationship among rice production, rice imports, and GDP was tested using the Johansen co-integration technique (Johansen, 1988;Johansen and Joselius, 1990) based on the Vector Autoregressive (VAR) model. The co-integration test procedure is valid only if all the variables in the series are non-stationary and have the same order of integration at first differencing, I(1). ...
... Based on the Vector Autoregressive (VAR) model, the Johansen co-integration technique (Johansen 1988;Johansen and Joselius, 1990) was used to investigate the long-run equilibrium relationship among rice output, rice imports, and GDP. Only when every variable in the series is non-stationary and has the same order of integration at initial differencing, or I(1), is the co-integration test procedure valid. ...
Rice is an important staple food in Nigeria, playing a critical role in the country’s food security, agricultural development, and economic growth. This research investigated how rice importation affected rice production and Nigeria's economic growth from 1990 to 2020 using time series data. The study aimed to understand the dynamics between rice importation, local production, and economic performance to inform policy decisions that promote agricultural sustainability. The data were analyzed with various econometrics models such as the trend model, Augmented Dickey-Fuller (ADF) test, Johansen Cointegration technique, Granger causality test, and simultaneous equation model. The results showed a significant gap between rice demand and supply in Nigeria and a long-run relationship between rice production, rice importation, and economic growth. While the gap indicated a high dependence on foreign rice to meet the rising domestic demand, the long-run relationship indicated that rice importation had a negative impact on the economy. The results also revealed causal relationships between rice production, rice importation, and GDP, and that rice importation had a negative and significant effect on Nigeria's economic growth and domestic rice production potential. Rice production in Nigeria was influenced by rice importation and population growth, while rice importation was affected by exchange rates and population growth. The study concluded that a sustained overdependence on rice importation has adverse consequences on Nigeria's economy and thereby suggested that the adoption of a multifaceted policy measure or strategy that emphasizes reducing rice importation, increasing domestic production of rice, and enhancing the standard of living for domestic rice producers is a key policy objective.
... The econometric model for in ation and its main determinants is based on two main approaches. The rst approach applies a cointegration process (Johansen, 1988 ...
... The CPI is integrated of order 2. Tables 2 and 3, the results of the cointegration test run with variables lagged only once can be observed. Taking into account the fact that the r statistic is greater than the critical values calculated as an asymptotically non-standard distribution according to the Johansen methodology (Johansen, 1988 and1991) in the case of at least 3 vectors (when r < = 3), the null hypothesis of 3 cointegrated long run relationships are not rejected (see Table 2). ...
This paper shows what the main inflation macroeconomics drivers in Spain are. Even if there has been a less than two-digit inflation in the last three decades, it can be emphasized the fact that the inflation rate has raised and declined rapidly in recent years because of its fundamental determinants. Main reasons behind the behaviour of the consumption price index are related to higher prices in the energy sector and a higher government expenditure, particularly after the post-pandemic economy re-opening. Proxy variables such as oil prices free on board in the European Brent market, the 12 months Euribor interest rate of the Economic and Monetary Union, the nominal gross domestic product, the government expenditure of the public administration, and fiscal deficits in terms of the gross domestic product are those variables in which the consumer price index depends on. Changes on interest rates have managed to stabilized inflation rates once again, thereby diminishing the percentage change in the consumer price index. JEL Classification: E31, E58, L71
... According to Pesaran, Shin and Smith (2001), different econometric analyses are utilized in determining economic relationships, and in particular, different Co-integration analyses like Engle & Granger (1987), Johansen (1988) and Johansen and Juselius (1990). This method allows us to investigate how variables interact with each other over both extended and shorter time periods. ...
... But according to Pesaran et al. (2001, p. 290), the independent variables should be stationary at I(0) and/or I(1), and the dependent variable should be stationary at I(1). Another benefit of the ARDL model is that it can be used in small sample studies and yields more accurate and efficient results than co-integration tests developed by Johansen (1988Johansen ( , 1995 and Engle and Granger (1987) (Narayan and Smyth, 2005, p. 103 ...
Defense expenditures are an item that exists cyclically throughout the world in every period and covers most of the public expenditures of countries. The effect of defense expenditures on inflation, employment, balance of trade balance, gross domestic product, geopolitical risk index, and political stability index within the scope of Türkiye has been examined. The findings, while the causality relationship from defense spending to balance of trade, geopolitical risk index, and political stability index is determined and there is a positive relationship from defense spending to foreign trade balance and a negative relationship to geopolitical risk index, there is a cointegration towards gross domestic product. Empirical findings support the military Keynesian approach in the long and short term, indicating that the increase in defense expenditures in Türkiye increases exports and the balance of trade. Increasing R&D activities and implementing policies that encourage investment in higher-density defense industry products will increase positive externalities in the balance of trade. Long-term, the rise in defense spending allows one to draw the conclusion that the country tends to lower geopolitical risks by boosting confidence in its political, economic, and security realities and lowering the threat of terrorism.
... These techniques predict the financial integration, i.e., the co-movements of equity markets that share mutual stochastic trends. The cointegration techniques were first introduced by Granger (1981) and further complemented by Engle and Granger (1987) and Johansen (1988). In this research, the Johansen cointegration test is applied, due to its ability to test one or more long-run cointegration vectors, thus relationships. ...
... In this research, the Johansen cointegration test is applied, due to its ability to test one or more long-run cointegration vectors, thus relationships. Johansen (1988Johansen ( , 1991 also developed the two methods of the Trace test and maximum-eigenvalue test to test the quantity of long-run cointegration vectors. The framework of Johansen cointegration is based on a VAR model: ...
This study investigates the co-movement and integration between conventional and Islamic indexes in Malaysia by analysing the volatility spillover and asymmetric effect over the period of 28/2/2007 to 28/2/2023. The sample is divided into five periods: full sample period, pre-, during- and post-Global Financial Crisis period including the during-COVID-19 period. Based on GARCH-M and EGARCH models, the findings indicate that the volatility of every index is more responsive to its lag values than it is to new shocks with the Islamic index consistently demonstrating higher volatility persistence than its conventional counterpart. The EGARCH results also observe asymmetric bidirectional volatility spillovers between Malaysia’s conventional and Islamic index in the during-GFC period. However, unidirectional volatility spillover is found in every sample period, except for the during-COVID-19. This indicates the absence of return and volatility spillover, which makes COVID-19 a special/unique event for Malaysia. The overall findings support the decoupling hypothesis for Malaysian conventional and Islamic indexes. Hence, it is important for policymakers in developing policies to deal with the co-movement and spillovers of the indexes for achieving financial stability. This study suggests that domestic investors in Malaysia have high diversification opportunities by combining both conventional and Islamic indexes in their portfolios in the long run.
... This means that cointegrated series do not drift apart over time, suggesting an existing connection between them [88]. In such cases, Johansen's cointegration test is applicable, allowing for the identification of multiple cointegration vectors and determining their number [33]. This test, which assesses the cointegration of multiple time series, is based on the vector error correction model (VECM). ...
... Eigenvalues are crucial as they measure the strength of the long-term equilibrium relationship. Larger eigenvalues indicate stronger cointegration relationships [33,96,97]. ...
The observed increase in demand for transport leads to higher energy consumption, which still predominantly originates from fossil fuels. As a result, the transport sector remains one of the main sources of GHG emissions. At the same time, transport activities bring economic benefits by generating public income and contributing to GDP. This article analyzes the relationship between total final energy consumption in transport, CO2 emissions from transport, and government revenues, using Poland as a case study. The study applies Johansen’s cointegration method to identify long-term relationships between time series. Unlike many cross-country studies, this research addresses a gap by focusing specifically on Poland—a post-transition economy where the transport sector holds both fiscal and environmental significance. After cointegration test, the Impulse Response Function was used to examine dynamics and identify system shocks. Results indicate that energy consumption in transport significantly affects both CO2 emissions and government revenues. A rise in energy use leads to higher emissions and also correlates with increased public income. The study contributes to the understanding of how transport-related energy use impacts both fiscal outcomes and emissions in a national context. These findings offer a foundation for shaping future policies that promote economic growth and stable revenue while encouraging more efficient energy use and lower emissions.
... Therefore, Granger causality provides additional evidence as to whether and in which direction price transmission is occurring between two markets. In the realm of scholarly literature, pioneering contributions made by Granger (1981Granger ( , 1986, Engle and Granger (1987), Johansen (1988) and other esteemed researchers have laid the foundational framework for the application of cointegration analysis in the field of econometric modeling. Consequently, recent advancements in the study of agricultural market integration have embraced the utilization of increasingly sophisticated econometric tools, including cointegration tests, vector error correction models (VECM), and impulse response functions. ...
The book Time Series and Artificial Intelligence Models for Forecasting Agricultural Data serves as a comprehensive guide to analyzing and forecasting agricultural time series using both classical and AI-based methods. It covers fundamental time series concepts, trend and long memory analysis (ARIMA, ARFIMA), count and spatiotemporal models, and advanced techniques like Bayesian, fuzzy, VAR, ARCH/GARCH, and machine learning models such as ANN, SVR, RF, ELM, and LSTM. With practical R code and examples, it also explores hybrid and ensemble models, intervention analysis, and grey modeling, equipping readers with the tools to effectively analyze and forecast complex agricultural data.
... The null hypothesis (H0): ∂ =0 indicates the presence of a unit root, while the alternative hypothesis (H1): ∂ < 0 suggests stationarity (100). Secondly, we employed the Johansen Cointegration test, developed by Johansen (101), is used to determine the number of Cointegration relationships between multiple time series. It relies on maximum likelihood estimation to test for the presence of Cointegration and identify the number of Cointegrating vectors. ...
Health is directly linked to SDG 3, “Good Health and Well-being,” which aims to ensure healthy lives and promote well-being for all ages. Achieving this goal involves improving health outcomes, including increasing life expectancy (LEX) and reducing mortality rates. Therefore, the current study aims to examine the impact of Air pollution’s on LEX, and the role of education, and health expenditure in achieving the SDG 3 in China from 2000 to 2023. This study utilizes the Auto Regressive distributed lag (ARDL) model. We use the Fully modified ordinary least squares (FMOLS) and Dynamic ordinary least squares (FMOLS) methods for robustness analysis. The results show that CO2 emissions and inflation negatively impact LEX, while education, health expenditure, and GDP positively affect LEX. Policymakers should prioritize reducing CO2 emissions through stricter environmental regulations to improve public health. Increased investment in education and healthcare, alongside policies that boost GDP growth, should be emphasized to enhance life expectancy further. Additionally, controlling inflation through sound economic policies will mitigate its negative impact on life expectancy.
... − represent the VAR components in first differences and error correction components respectively in levels of equation (1) Based on Johansen (1988), the three equations (2), (3), and (4) in the VAR (p) system can have a minimum of one cointegrating equation and a maximum of three cointegrating equations (see Engle and Granger, 1987 ...
In practice, forecasting of multivariate time series variables cannot be achieved directly from the Vector Error Correction Model (VECM). As a result, it is achieved through the help of the Vector Error Correction Model-Vector Autoregressive (VECM-VAR) model, which is also a VAR model derived from the VECM model. To demonstrate this, the forecasting dynamics Correction Term (ECT) confirmed equilibrium adjustments in the lnEXR equation. The study's findings revealed a continuous depreciation trend for the Naira against the United States Dollar.
... The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) and Augmented Dickey-Fuller (ADF) tests were selected to assess stationarity [42,43]. We proceeded by performing the Johansen test to examine the presence of long-term relations among our examined time series [44]. To provide insights into the interconnectedness between stock traders' sentiment and the BDI, we conducted the standard Granger causality test. ...
Our research focuses on the maritime industry, specifically the dry bulk market, contributing to the emerging research agenda regarding the influence of financial markets on the real economy. Motivated by the documented relationship between the Baltic Dry Index (BDI) and financial markets, we study how different types of investors’ sentiment in the US stock market influence the BDI. Employing Granger causality tests and impulse response functions, we examine how investors’ confidence and ensuing liquidity in both the US maritime and the broader US stock markets impact corporate decisions related to freight rates and secondhand vessel investments. Our findings highlight the critical role of investor sentiment for stakeholders in the dry bulk market and the significance of the BDI in shaping traders’ investment in the US capital market. Additionally, by comparing our results with previous studies, we provide fresh evidence regarding the identity of traders in the maritime capital market. We also employ Long Short-Term Memory (LSTM) neural networks to establish the out-of-sample predictive power of our sentiment proxies, positioning themas novel BDI determinants. The results provided align with signal theory, challenge the efficient market hypothesis, and offer valuable insights for optimizing profitability and fostering economic sustainability in various industries.
... -Pedroni's test for Cointegration: The Pedroni test for cointegration is based on seven results of cointegration tests between Cross-section, within units, with a constant and a general trend, and it depends in the decision-making process on the majority of the results, where if the p-value is less than 0.05, then we can say that there is at least one cointegration relationship (Pedroni, 2004), and the results of this test are summarized in the following table: The decision-making in Johansson's cointegration test depends on the p-value and Fisher's value, the trace test and the maximum value test. If the p-value is less than 0.05, we say that there is at least one cointegration relationship (Johansen, 1988). We can show the results of Johansson test in the follow table: From the Results of Johansson test, we notice that we have one or at most two cointegrating relationships, which is determined by the P-value at the 5% significance level. ...
This research paper deals with the relationship between the consumer price index and the macroeconomic policy variables (LG, M2 and EXCH), in the North African countries (Algeria, Tunisia, Egypt and Morocco), in the period (2001-2020). The study relied on the Panel Vecm model in order to show this relationship in the long and short run. This study was found that there is at least one cointegration relationship, through tests of (Pedroni, Kao and Johanssen), the stability of the variables in the first differences, and the rate of return to equilibrium was determined, which was estimated at 3.5% per year, which showed the extent of the weakness of the economies of the selected countries in fixing the various imbalances that occurred.
... No entanto, é possível estimar um Modelo Vetorial de Correção de Erro (VECM) se houver uma relação de cointegração entre as variáveis, o que implicaria que elas compartilham um equilíbrio de longo prazo. Para testar a existência de cointegração, utiliza-se o procedimento tradicional proposto por Johansen (1988), que verifica a presença de vetores de cointegração entre as variáveis analisadas. ...
Resumo Este artigo investiga os determinantes macroeconômicos da inadimplência no crédito rural brasileiro, com ênfase no papel dos preços dos cereais e de outras variáveis macroeconômicas, como a taxa de câmbio, os preços dos fertilizantes e o custo do crédito. Utilizando dados mensais de janeiro de 2013 a julho de 2024, o estudo aplica um Modelo Vetorial de Correção de Erro (VECM) para captar as dinâmicas de curto e longo prazo entre a inadimplência e essas variáveis. Os resultados indicam que os preços dos cereais têm a maior influência na redução da inadimplência, tanto no curto quanto no longo prazo, refletindo a forte relação entre a lucratividade agrícola e a capacidade de pagamento dos produtores. A taxa de câmbio também exerce um efeito significativo, com a desvalorização do Real contribuindo para a redução da inadimplência ao aumentar as receitas de exportação. O impacto dos preços dos fertilizantes é mais pronunciado no longo prazo e o custo do crédito afeta a inadimplência no curto prazo, mas sem persistir no longo prazo. O artigo conclui que os ciclos de preços das commodities devem ser considerados no planejamento do crédito rural.
... The Cointegration test, which was established [24], used in this study to examine the long-term relationship between the variables. Johansen's test comprises two probability tests (the trace test and the maximum eigenvalue test) as illustrated in Equations (2): ...
Somalia's rainfall is crucial for water resources, agriculture, and ecosystem services. In this drought-prone environment, the rainfall significantly influences crop yields, animal survival, and water supply for rural and urban populations. Changes in seasonal rainfall patterns resulting from climate change led to droughts, hunger, vulnerable health issues, and economic disruption since Somalia's food and water security heavily relies on rainfall. To get empirical evidence for these phenomena, this study examines the impact of climate change on human health, measured explicitly in life expectancy from 1990 to 2020 using the VEC model. The VECM results show that average rainfall negatively affects life expectancy in both the short and long terms, while GDP and population growth positively influence life expectancy. DOLS and CCR long-run results confirm the negative impact of average rainfall, with its insignificance noted. A Granger causality test indicates unidirectional causality from life expectancy and population growth to GDP, with no causal links between average rainfall and life expectancy or GDP. Lastly, this study disclosed that there is bidirectional causality between population growth and life expectancy. The study recommends building resilience against climate change through investment in drought-resistant agriculture, effective water management, sustainable development, and managing population growth for health improvements.
... The common cointegration tests, such as Johansen [33] and Kao and Chiang [26], can be biased when there is crossdependence between variables. This study employs the Westerlund [34] cointegration test as recommended by Dauda et al. [35]. ...
This study aims to assess the long-term impact of institutional quality on economic growth in ASEAN countries over the period 2000-2022. The study uses panel data sourced from the World Development Indicators (WDI) for the years 2000 to 2022. It employs Fully Modified Ordinary Least Squares (FMOLS) and Canonical Cointegrating Regression (CCR) estimation techniques to evaluate the relationship between institutional quality and economic growth. Institutional quality is represented by six key indicators: voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption. Control variables include investment capital, human capital, trade openness, and the inflation rate. The empirical results indicate that voice and accountability, political stability, and the rule of law have a positive and statistically significant impact on long-run economic growth in ASEAN countries. In contrast, government effectiveness, regulatory quality, and control of corruption are found to have a negative impact on economic growth. Furthermore, investment capital, human capital, and the inflation rate contribute positively to growth, whereas trade openness exerts a negative influence. Based on the results, the study proposes several policy recommendations aimed at strengthening institutional quality to support long-term economic growth in ASEAN countries. Policymakers should prioritize improvements in the institutional components that show positive effects while critically reassessing and reforming the areas found to negatively influence growth.
... Similarly, Tan and Yan [24] unveiled a link between urban air pollution and corporate innovation. They vowed that increased air pollution diminished corporate innovation. ...
As emerging economies play a pivotal role in global growth, understanding the impact of environmental factors, especially air pollution, on innovation is crucial. This study empirically examines the relationship between air pollution and innovation performance in EAGLE (emerging and growth leading economies) using a 20-year dataset (2000–2019) and employing 2SLS (two-stage least square) and FMOLS (fully modified ordinary least square) estimation techniques. The key findings of the study reveal that air pollution hampers R&D activities and patent applications by weakening human capital, diverting resources, and creating an unfavorable research environment. The results remain robust across multiple control variables and alternative estimation techniques. These findings highlight the urgent need for pollution control policies to mitigate its adverse effects on innovation, offering valuable insights for policymakers striving to enhance innovation resilience amid environmental challenges. This study uniquely explores the causal impact of air pollution on the macro-level innovation performance of a country.
... La teoría económica sugiere que, en condiciones de libre mercado, existe una relación de equilibrio a largo plazo entre las exportaciones e importaciones de países socios comerciales (Johansen, 1988). No obstante, en el caso de Colombia y Venezuela esta relación puede verse alterada por factores como la inestabilidad política, las fluctuaciones en los tipos de cambio y las políticas proteccionistas (Bittencourt & Mosquera, 2021). ...
El presente estudio investiga la relación comercial de largo plazo en el sector agroalimentario entre Colombia y Venezuela durante el período 2004-2023, mediante un riguroso Modelo de Corrección de Errores (MCE). La investigación se sustenta en datos anuales de comercio bilateral, integrando variables macroeconómicas estratégicas como el Producto Interno Bruto (PIB) de ambos países y sus respectivos tipos de cambio. La metodología econométrica comprende una secuencia analítica sistemática. Inicialmente, se realizaron pruebas de raíz unitaria para establecer el orden de integración de las series temporales, seguidas de pruebas de cointegración destinadas a verificar la existencia de una relación de equilibrio estructural a largo plazo. La implementación del Modelo de Corrección de Errores permitió capturar simultáneamente la dinámica de corto plazo y los mecanismos de ajuste hacia el equilibrio económico. Los resultados revelan una cointegración estadísticamente significativa, evidenciando una profunda interdependencia comercial agroalimentaria entre Colombia y Venezuela. El coeficiente de ajuste del modelo indica una velocidad de reequilibrio ante desviaciones temporales, lo que sugiere una capacidad de adaptación relativamente rápida de los flujos comerciales. Adicionalmente, el estudio identificó hallazgos complementarios sobre el impacto de disrupciones económicas y políticas en los patrones comerciales bilaterales. La investigación aporta una perspectiva novedosa a la literatura especializada sobre comercio agroalimentario en América Latina, proporcionando conocimientos detallados sobre la dinámica comercial entre ambos países en un sector de crucial importancia económica y estratégica. Las conclusiones ofrecen implicaciones significativas para el diseño de políticas comerciales y agrícolas, especialmente en un contexto caracterizado por alta volatilidad económica y transformaciones en las relaciones bilaterales. El análisis constituye una herramienta valorable para formuladores de política, académicos e inversores interesados en la comprensión de las interconexiones económicas regionales.
... ARDL bounds testing approach as developed by [57] and extended by [58] provides advantages in ascertaining long-run relationship among variables as compared to techniques suggested by Engle and Granger, [18], Johansen and Juselius, [35] and Johansen, [34]. Some of these advantages offered by ARDL bounds testing include that, first, it does not impose restrictions that the variables under consideration have to be of the same order of integration. ...
This study aimed to establish the influence of economic growth (measured by GDP), industrialization (IND), mineral rents (MR) and population growth (PG) on CO2 emissions (CO2) in the context of one of the fastest growing economies in the world, i.e., India. The study employs the ARDL bounds test to analyze the information obtained from the World Bank records for the years 1990–2023. The outcomes of the empirical analysis revealed that GDP and PG clearly affect CO2 in the long run. Similarly, CO2 is negatively affected by its lagged value, whereas FDI is found to positively contribute to CO2 emissions in the short run. Our results also establish that IND negatively affects CO2, establishing the EKC hypothesis in the context of India. Finally, the short-term results indicate a negative impact of MR on CO2. The study produced relevant findings that make noteworthy input to the current knowledge in the area of emerging economies. Policy- and governance-related implications emerging from the analysis are provided by the study.
... To test the robustness of the estimates, the pooled mean group (PMG) estimator proposed by Pesaran et al. (1999) and Pesaran et al. (1999) is utilized. Johansen (1988) and Phillips and Hansen (1990) have noted that long-run associations exist only when variables are cointegrated with the same order of integration. However, Pesaran, 2004, p. 313) state that the ARDL model introduced by Pesaran et al. (1999) is applicable regardless of whether the regressors are purely I (0), purely I (1), or mutually cointegrated. ...
Abstractf
The 2030 United Nations Sustainable Development Goal (SDGs) is based on the principles of sustainable development; SDG 9 addresses the environment. Thus, this study applies the STIRPAT model to study how natural resources, technological innovation, and public policy (fiscal policy by government expenditure; as well as monetary policy by money supply affect carbon dioxide () emissions in 10 ASEAN countries (1980–2022). Panel Autoregressive Distributed Lag model and Pooled Mean Group (ARDL/PMG) are implemented to investigate long- and short-run relationships in the series. The Dumitrescu-Hurlin panel Granger causality approach is employed to explore the direction of causality in the series. Environmental degradation is negatively affected by emissions and positively affected by natural resources, economic growth, and the financial development index. Environmental sustainability requires economic, financial, and technical innovation. CO2's bidirectional correlation with fiscal policy, monetary policy, and technological innovation is revealed by the D-H Granger causality analysis. Based on these empirical findings, ASEAN countries are urged to consider the development of green technology and the promotion of a sustainable environment through research and development of energy-saving and ecologically friendly green technology. All this reduces pollution, waste, and the wastage of resources and results in the creation of a healthy environment.
Graphical abstract
... In this study, ADF single root test, PP single root test, cointegration test and causality test were used. Firstly, the data are examined to confirm the stability of the series, secondly, the cointegration analysis proposed by Johansen is utilized [9], and finally, the dynamics between the RMB exchange rate and the China-US interest rate differential are examined according to the Granger causality test to check whether there is a causal relationship between the variables [10]. The null hypotheses and opposing hypotheses in the research hypotheses are set as follows: ...
In recent years, China has been actively opening up and internationalizing its financial markets, so it is meaningful to study the relationship between the interest rate differential and exchange rate between China and the United States. This study uses the data from January 1996 to September 2015 to investigate the linkage between the interest rate differential and the exchange rate of the RMB between China and the United States using frequency causality test. Theoretically, interest rate differential and exchange rates should have Granger causality, but the empirical results show that there is no long-run relationship of cointegration between the China-U.S. interest rate differential and the RMB exchange rates in the cointegration test. In the frequency causality test, it is found that the RMB exchange rate has a long-run and medium-run unidirectional causality on the China-US interest rate differential, while the China-U.S. interest rate differential does not have long-run, medium-run and short-run frequency causality on the RMB exchange rate.
... If structural breaks go undetected, long-term relationships can still be analyzed using cointegration tests [35]. Prominent methods include the Engle and Yoo [36] approach, Johansen [37] methodology, and Pesaran et al. [38] framework. These tests help ascertain whether a long-term equilibrium exists among the series, including GDP and the aforementioned factors. ...
This study examines the influence of internal and external factors on Vietnam’s economic growth during a period shaped by digitalization, global integration via free trade agreements (FTAs), and climate change challenges. Utilizing a Vector Autoregression (VAR) model, the research analyzes key variables including skilled labor, internet access, patents, IT expenditure, climate costs, the KOF Globalization Index, balance of trade, and FTAs. The study covers a transformative phase of Vietnam’s economy, focusing on quantitative data to assess dynamic relationships. Skilled labor and internet access significantly boost economic growth, though the benefits of the internet exhibit a lag. Climate costs pose a substantial barrier to progress. Globalization drives short-term growth but introduces long-term risks, while FTAs show minimal direct impact on economic performance. The study underscores the importance of addressing internal strengths like education and digital infrastructure alongside external pressures like climate change and globalization. Limitations include reliance on estimated data for recent years, the VAR model’s linearity, and the omission of qualitative factors, suggesting future research directions. Policymakers should prioritize investments in education, digital infrastructure, innovation, and climate resilience while fostering balanced global integration to ensure sustainable economic growth for Vietnam.
... To determine the long-term equilibrium connection between the variables, the cointegration test is important. There is no longterm equilibrium between the variables when there is no cointegration, and they have a tendency to stray from one another at random (59). Instead of using OLS (Ordinary Least Square) estimation, the Johansen Method uses maximum likelihood estimation to construct the cointegrated variables. ...
The determinants of the global financial cycle are empirically investigated in this study report. The presence of concurrent changes in capital flows, asset prices, and global bank leverage is associated with the Global Financial Cycle (GFCy). According to the research now in publication, the Chicago Board of Exchange's VIX (Volatility Index), which gauges market uncertainty and risk aversion, indicates this cycle. The Federal Reserve's monetary policy decisions are the driving force behind this cycle, and the literature already in existence has examined the ramifications of these decisions. The GFCy and, thus, the financial circumstances of emerging market economies (EMEs) could be impacted by additional global shocks. Other global shocks have the potential to impact the global financial cycle and analysis of the same is required to make the existing literature more robust. Our analysis, which includes a study of identifying the potential global shocks for a period of 23 years data (quarterly), indicates that the global financial cycle is driven by global liquidity and global economic policy uncertainty. VECM, Granger Causality, Impulse Response functions were applied. There is a unidirectional causal relationship between the global financial cycle and global liquidity, as well as a unidirectional relationship between the global financial cycle and global economic policy uncertainty.
... Johansen's co-integration test was employed to examine the long-run relationship between wholesale and retail sugar prices (Johansen 1988;Johansen and Juselius 1990). The null hypothesis ( H 0 ) of utmost 'r' co-integrating vectorsi.e., rank of error-correction coefficient matrix-against a general alternative hypothesis ( H 1 ) of 'r + 1' co-integrating vectors was tested by trace and maximum eigenvalue statistics (Quandt 1958). ...
This paper examined the price dynamics and market integration in wholesale and retail sugar markets of India using monthly data from the Food and Agriculture Organization for four major markets from 2014-2015 to 2023-2024. Understanding these dynamics across spatially separated markets is crucial for developing policies that enhance market efficiency and promote sustainable growth. Various analytical tools were employed viz. compound annual growth rate, instability index, seasonal price index, correlation analysis, Johansen's co-integration test, and Granger causality test and impulse response function. The analysis demonstrated that the selected sugar markets exhibit suboptimal integration due to limited market intelligence, slow information flow and inadequate infrastructure. An upward trend was observed in sugar prices in all the markets over the study period. Seasonal price fluctuations were observed, linked to the crushing season and higher demand during summer months. Co-integration analysis confirmed a long-run equilibrium, Granger causality test revealed unidirectional, bidi-rectional and no causality price influence between the markets. Moreover, impulse response analysis concluded relatively well interconnected markets with potential inefficiencies, particularly in Patna market. This study uniquely highlights the interplay between market efficiency and seasonal fluctuations in the Indian sugar sector, providing a nuanced understanding of spatial integration and its policy implications. To enhance market integration and price convergence, policy recommendations include modernizing marketing systems, fostering public-private partnerships, improving infrastructure, strengthening supply chains and facilitating external trade.
... Co-integration tests are often applied in economic studies to analyze the long-term relationships between variables. For instance, Johansen (1988) used this method to explore the co-integration among multiple time series in econometric models. The Johansen test is based on the following VECM ...
Somalia, a country challenged by ongoing conflict and economic instability, faces significant environmental degradation, particularly deforestation. This study investigates the effects of key macroeconomic variables, economic growth, population growth, and inflation, on deforestation from 1993 to 2021. Using the Autoregressive Distributed Lag (ARDL) model, the analysis explores both short- and long-term relationships. Stationarity of variables was tested through ADF, PP, and Zivot-Andrews unit root tests, while diagnostic tests ensured the robustness of the model. The results confirm the Environmental Kuznets Curve (EKC) hypothesis, indicating that economic growth initially intensifies deforestation but later contributes to its decline after a critical GDP level. Population growth is found to significantly drive deforestation in the long run, whereas inflation shows no notable impact. These findings underscore the need for policies that foster sustainable economic growth, manage population pressures, and conserve natural resources. The study recommends integrated strategies, including community-based initiatives and regulatory reforms, to promote environmental sustainability in Somalia.
... Therefore, it is essential to introduce a cointegration test method to verify the series and determine whether there is a significant correlation between them. The most commonly used cointegration test methods include the Johansen method (Johansen, 1988), etc. Therefore, in this study, Johansen's method was adopted to conduct a cointegration test on the GDP, cargo throughput, and container throughput, to examine whether the variation exists in a long-term stable equilibrium relationship (Wei & Jasmine, 2006). ...
Interaction between ports and urban economies plays a crucial role in enhancing both port competitiveness and urban development. To deeply understand their relationship, this study explores the dynamic interaction between Shanghai Port and the urban economy by utilizing the time series data of Shanghai from 2000 to 2022 and incorporating exogenous variables such as international economic fluctuation, technological change and economic policy uncertainty. The Structural Vector Autoregressive (SVAR) model alongside cointegration tests, Granger causality tests and variance decomposition methods were also employed for empirical analysis. The main purpose of this study is to provide a theoretical framework for the benign interaction between Shanghai Port and the urban economy, specifically examining the interaction mechanism between Shanghai Port cargo throughput, container throughput and Shanghai GDP. The results of our study show that there is a stable dynamic equilibrium relationship between Shanghai Port and GDP, where the contribution of GDP to container throughput is much greater than that of cargo throughput, and the contribution of cargo throughput to GDP is higher than that of container throughput to GDP. Finally, recommendations are proposed for promoting the coordinated development of the Shanghai Port and the urban economy.
... Engel & Granger (1987) developed the cointegration method used in time series for the linear combinations between non-stationary variables to be in cointegration relationship in the long run. Upon some deficiencies in this method, Johansen (1988) introduced a different method based on the most similarity method. This method allows the estimation and testing of cointegrated vectors as well as testing some restrictions on the parameters. ...
Banks are among the most important actors in the economy due to their role as market makers. The banking sector stands out as one of the sectors with the highest liquidity. Borsa Istanbul (BIST) Bank Index represents the index of banks whose shares are traded on the stock exchange in Turkey. Money supply and policy interest rates are among the main monetary policy instruments most frequently used by the Central Bank (CB) to control liquidity. In this respect, analysing the effects of monetary policy instruments on bank index returns is deemed worthy of research. For this purpose, time series consisting of 225 monthly observations from 01/12/2005 to 01/08/2024, which is the earliest available date, are constructed for BIST Bank index, policy interest rate and M2 money supply. These three time series were subjected to Johansen Co-integration analysis and then the error correction model and the long-run equation of the variables were obtained. As a result of the analyses, it is decided that all three variables are cointegrated in the long run between 2005 and 2024, and it is observed that in case of a possible imbalance between the three variables, the variables converge to each other again in 52.4109 periods and move to a new equilibrium position. In addition, it is determined that a 1% increase in money supply in the long run causes a 0.9% increase in the bank index and a 1% increase in the interest rate causes a 0.7% increase in the bank index.
... From the eigenvalues of the matrix Π, we calculate the following to test the null hypothesis according to which there exist at most r co-integrating vectors. (Johansen, 1988) 1; ...
This paper studies the most important determinants of foreign direct investment in Algeria in a theoretical and practical framework (using the co-integration test and the causality test). Foreign direct investment has become very important, because it has become the object of competition between countries, whether developed or underdeveloped. Algeria, like the countries of the world, tries to take advantage of it as well, but this comes up against obstacles that this study has tried to identify, the most important of which are inflation (-0.0203) and administrative corruption (-1.2821), with the weakness of other determinants to attract it, such as market size (0.0113) or public spending (0.0527).Thus, according to the results of the study, Algeria still remains unattractive for foreign direct investment.
... Eşbütünleşme, ekonomik değişkenlerin uzun dönemde birlikte hareket etmesi olarak tanımlanabilir. Tüm seriler aynı düzeyde bütünleşik olduğunda, Johansen (1988) "tam bilgi en çok olabilirlik yöntemi" ile seriler arasında uzun dönemli bir ilişki olup olmadığını test eder (Özdemir ve Öksüzler, 2006). Johansen eşbütünleşme testinin sonuçları aşağıda, Tablo 5'te, yer almaktadır. ...
This study is to estimate the effect of traffic fines on traffic accidents in Türkiye by using annual data for the period 1990-2023 with the Johansen cointegration and Granger causality tests. The dependent variable employed is the number of traffic accidents while the independent variables are traffic fines, average years of education, per capita income and road/motor vehicle ratio. The analysis estimates a long-run relationship between traffic fines and traffic accidents. However, improvements in socio-economic status, such as education and per capita income, do not seem to impact traffic accidents. As a mandatory compliance instrument, traffic fines emerge as an important determinant in encouraging safer driving behavior. The amount of traffic fines should be regularly updated taking into account the inflation and economic conditions. Traffic fines should be set at a lower limit, which is a deterrent for everyone, but a progressive tariff based on the “vehicle insurance value” that takes into account the ability to pay can also be applied. Effective enforcement of fines is as vital as the fines themselves. Inconsistent or lax enforcement can weaken the impact of penalties. Policymakers should invest in speed cameras, automated ticketing systems, and new technologies to ensure consistent and fair enforcement. Traffic fines should be used as an effective tool in reducing traffic accidents and reducing the social and economic costs of these accidents
This paper explores the critical factors shaping coffee export decisions in Vietnam, one of the world’s largest coffee producers and exporters. Adopting a mixed-method approach that combines quantitative surveys with in-depth interviews involving coffee exporters and trade policymakers, the study identifies several key determinants including government trade policy, global coffee demand, production scale, supply chain infrastructure, and international pcoffee volatility. These variables collectively influence the strategic orientation of Vietnamese coffee exporters in the global marketplace. The findings offer valuable insights into how Vietnam can further enhance its export competitiveness and develop resilient, sustainable strategies for long-term growth in the coffee sector. Empirical evidence suggests that coffee production levels, yield per hectare, and global demand have a statistically significant and positive influence on export performance. Conversely, both domestic coffee pcoffees and international export pcoffees exhibit a negative relationship with export volume, indicating that elevated pcoffees may either constrain domestic supply or erode international pcoffee competitiveness. Interestingly, domestic consumption appears statistically insignificant in affecting export decisions, underscoring that Vietnamese coffee exports are predominantly shaped by supply-side capabilities and global market dynamics rather than internal demand pressures. To further analyze the short-run dynamics and the adjustment mechanism toward long-run export equilibrium, a Vector Error Correction Model (VECM) was estimated. The VECM results reveal that deviations from long-run equilibrium are corrected at a pace of approximately 0.62% per year, pointing to a slow but consistent realignment process in Vietnam’s coffee export system. In conclusion, the study recommends that Vietnamese policymakers prioritize increasing yield efficiency and expanding coffee production capacity, as these were found to be the most influential drivers of export growth. Moreover, strengthening access to global markets and implementing mechanisms to mitigate pcoffee fluctuations will be essential to reinforcing Vietnam’s competitive position in the international coffee trade.
Rekabetin koşullarının tam olarak oluşmadığı günümüz dünyasında, ülkeler çıkarları doğrultusunda dış ticarete müdahale ettiğinde herhangi bir reaksiyon ortaya koyamayan diğer ülkelerin aleyhine birtakım kazanımlar sağlayabilmektedir. Stratejik ticaret politikaları (STP), firmaların teşvik edilmesi ile küresel oligopolistik piyasa yapılarında oluşan rantların daha yüksek düzeyde ülkeye aktarılmasının mümkün olduğunu ileri sürmektedir. Bu çalışma, Türkiye’nin uyguladığı ihracat desteklerinin küresel ihracattan alınan pazar payını (KİPP) hangi seviyede etkilendiğini 2006-2020 arası verileri dikkate alarak incelemektedir. Oluşturulan model vasıtasıyla; KİPP ile ihracat teşvikleri, döviz kuru ve yabancı ülke geliri arasındaki ilişki incelenmiştir. Çalışmadaki verilerin birlikte kullanılmasının uygun olup olmadığının tespiti adına ADF birim kök testinden yararlanılmıştır. Uzun vadede oluşabilecek ilişkiyi tespit etmek için Johansen eşbütünleşme testi kullanılmıştır. Yapılan analizde uzun vadeli bir ilişkinin mevcut olduğu ortaya koyulmuştur. Bunun yanında, ihracat teşviklerinin istatistiksel olarak anlamlı bir şekilde ve STP teorisinde beklendiği gibi pozitif yönde KİPP’i etkilediği sonucuna ulaşılmıştır. Bununla birlikte ülkelerin çoğunluğunun faydasına olacak uzun vadeli makul politika, serbest ticaretle küresel rekabete uyum sağlayacak tedbirlerin geliştirilmesi şeklinde olmalıdır.
As already mentioned in Chap. 7, many raw economic time series are nonstationary and become stationary only after some transformation. The most common of these transformations is the formation of differences, perhaps after having taken logs. In most cases, first differences are sufficient to achieve stationarity. The so-transformed time series can then be analyzed in the context of VAR models as explained in previous chapters. However, many economic theories are formalized in terms of the original series so that we may want to use the VAR methodology to infer also the behavior of the original (untransformed) series. Yet by taking first differences, we lose probably important information on the levels. Thus, it seems worthwhile to develop an approach that allows us to take the information on the levels into account and at the same time take care of the nonstationary character of the variables. The concept of cointegration tries to achieve this double requirement.
Purpose
This study analyses the impact of climate change on price stability in South Africa by using quantitative analysis of annual data from 1990 to 2020.
Design/methodology/approach
The study runs unit root tests to test whether a time series variable is stationary. The auto-regressive distributive lag (ARDL) approach for cointegration is employed to evaluate the long-run impact of climate change on price stability.
Findings
The ARDL bound test analysis illustrates a cointegration relationship between the CPI and the three macroeconomic (interest rate, oil price and real effective exchange rate) and two climate change indicators (rainfall and temperature) variables. Results show that both temperature and rainfall have a significant negative relationship with inflation, hence climate change should be part of a macroeconomic policy framework. While some studies found a negative relationship between inflation and temperature in seasons other than summer, the current study found a negative relationship probably because it used annual data. Interest rate and oil price show a significant positive long-run relationship with inflation, while real effective exchange rate shows an insignificant negative long-run relationship with inflation.
Research limitations/implications
The study uses temperature as a proxy for climate change due difficulty in obtaining accurate data for CO 2 emissions. Future research should, therefore, test different other proxies and use a larger sample, to either agree with the findings or justify any deviation therefrom.
Practical implications
The findings of the study indicate the existence of a statistically significant long-run impact of climate change proxied by rainfall on inflation. Thus, this suggests that variations in seasonal rainfall and an escalation in weather changes diminish agricultural supply, including food products, leading to increased food prices and overall inflation. The substantial effect that climate change-related rainfall has had on South Africa’s inflation rate highlights the prerequisite for the Reserve Bank to take climate change into account when developing their monetary policy frameworks. This integration is crucial, as it serves as the initial phase for the Reserve Bank to adeptly implement their monetary policy objectives. This highlights that climate change effects are multidimensional and the fight against it should be collective. Based on this analysis, the immense pressing issue is not the lack of macro-level climate change programs or policies, but rather the establishment of effective policies that can successfully mitigate climate change in South Africa. Therefore, the Reserve Bank should take climate change into account when implementing its monetary policies. This may be attributed to the fact that, with their current macroeconomic forecasting models, it is becoming increasingly difficult for them to pinpoint the causes of inflationary pressures and create practical countermeasures as a result of climate change. They can then improve the processes by which they identify and evaluate risks associated with climate change and promptly adjust their strategies in response to alterations in the pace and severity of climate change.
Originality/value
The study uses recent data to clarify the relationship between inflation and climate change in the South African context using rainfall and temperatures as proxies for climate change.
This paper studies the role of central bank communication for the monetary policy transmission mechanism using text analysis techniques. In doing so, we derive sentiment measures from European Central Bank (ECB)’s press conferences indicating a dovish or hawkish tone referring to interest rates, inflation, and unemployment. We provide strong evidence for predictability of our sentiments on interbank interest rates, even after controlling for actual policy rate changes. We also find that our sentiment indicators offer predictive power for professionals’ expectations, the disagreement among them, and their uncertainty regarding future inflation as well as future interest rates. Policy communication shocks identified through sign restrictions based on our sentiment measure also have significant effects on real outcomes. Overall, our findings highlight the importance of the tone of central bank communication for the transmission mechanism of monetary policy, but also indicate the necessity of refinements of the communication policies implemented by the ECB to better anchor inflation expectations at the target level and to reduce uncertainty regarding the future path of monetary policy.
This paper investigates the entire distributional of causal effect by employing instrumental variables generalized quantile regression approach where multiple endogenous and instrument variables are applied in the estimator. Analysis of the dynamics of the sub-Saharan Africa (SSA) region income inequality provides a picture of disparate effects underlying the finance and digital development in the region on different tails of inequality. Results indicate that digitalization significantly impacts income inequality with financial developments in terms of access, efficiency, and depth of financial institutions and markets to different quantiles. Fixed telephone, mobile phone subscriptions, and internet adoption and use significantly reduce inequality in the region. The effectiveness and advancement of technology for financial institutions are mechanisms to lower inequality and the results imply heterogeneous impacts on income inequality and vary across different quantiles. Furthermore, the study highlights the potential of digital technology and financial progress in fostering inclusive growth, poverty reduction, and economic inclusion. We argued policymakers to intervene in the impact of digital and financial development in creating a more equitable economic landscape in SSA, ultimately contributing to sustainable development and reduced income disparities in the region.
This paper investigates the key factors influencing rice export decisions in Vietnam, one of the world's leading rice exporters. Using a mixed-method approach combining quantitative surveys and in-depth interviews with rice exporters and policymakers, the study identifies variables such as government policy, international market demand, production capacity, logistics infrastructure, and global price fluctuations as critical determinants. The findings provide insights into how Vietnam can enhance its export competitiveness and formulate sustainable export strategies. The empirical results indicate that rice production, yield, and global demand have a statistically significant and positive impact on rice exports. In contrast, both domestic prices and export prices are found to negatively affect rice export volumes, implying that higher price levels may reduce competitiveness or domestic availability. Meanwhile, domestic demand appears statistically insignificant, suggesting that export decisions are more closely tied to supply-side and global market dynamics. To assess the short-term dynamics and the adjustment mechanism toward long-run equilibrium, a Vector Error Correction Model (VECM) is estimated. The VECM results reveal that the system corrects deviations from the long-run path at a rate of approximately 0.62% per year, indicating a slow but steady convergence. In conclusion, the study recommends that Vietnamese policymakers prioritize improvements in rice yield per hectare and total production capacity. These are shown to be the most effective drivers of export growth. Additionally, measures to enhance global market access and reduce price volatility will further strengthen Vietnam’s position as a leading rice exporter in an increasingly competitive global market.
The existing body of literature accentuates both the positive and negative relationships between public investment and economic growth. As mentioned in Ghani and Din (2006), the absence of such a stable theoretical aspect indicates that the issue is empirical, and comprehensive evaluation is needed regarding the relationship with respect to the given context. This research adopts an econometric model to assess the impact of public investment on Sri Lanka's Gross Domestic Product (GDP), utilizing annual data from 1978 to 2022, after implementing the trade liberalizing policies. Following the framework used by Ghani and Din (2006), private investment and government consumption variables are introduced in this article for a more extensive analysis. Stationarity tests unveil non-stationary variables, prompting the employment of the Vector Error Correction (VEC) model, affirmed by the Johansen cointegration test. The cointegration equation implies that there is a long-term adverse relationship between public investment, private investment, government consumption, and GDP. Short-run coefficients emphasize favorable impacts on GDP from public and private investments, contrasting with an unfavorable influence from government consumption. Causality analyses uncover that public investment lacks Granger causality for GDP, while both private investment and government consumption individually Granger cause GDP. Moreover, their collective effect Granger causes GDP. Impulse response functions and variance decomposition enhance the depth of the findings in the latter part of the analysis. This study is directed to offer a refined understanding of the dynamics shaping Sri Lanka's economy through the interactions of public investment, private investment, and government consumption.
Enerji, ekonomik faaliyetler ve üretim süreçlerinde temel bir girdi olarak öne çıkmaktadır. Ülkelerin ekonomik büyüme performansı ve dış ticareti üzerinde kritik bir rol oynayan enerji, sanayileşmenin hızla artması, küresel ekonominin gelişimi ve ticaretin serbestleşmesi gibi faktörlere bağlı olarak talep artışıyla karşı karşıyadır. Bu talebin en belirgin bir şekilde ortaya çıktığı alanlardan biri, sanayi sektörünün temel alt dalını oluşturan ve üretim süreçlerinde enerjiyi önemli ölçüde kullanan imalat sanayi sektörüdür. İmalat sanayi, üretimin ve tüketimin gerçekleştiği geniş bir yelpazede faaliyet gösteren ve çeşitli alt sektörleri kapsayan bir endüstri dalıdır. Bu endüstri dalı, malların üretiminden tasarımına, işleme süreçlerinden geri dönüşümüne ve tüketiciye ulaşıncaya kadar tüm aşamalarında enerjiyi kullanmaktadır. Özellikle hammaddenin işlenmesinden başlayarak tüketildiği son noktaya kadar üretim ve imalatla ilgili tüm endüstriyel faaliyetlerde kullanılan yoğun enerji tüketimi, sera gazı emisyonlarının önemli bir kaynağıdır. Gelişmekte olan ülkelerin büyüme sürecinde rol oynayan imalat sanayi Türkiye için kritik bir role sahiptir. GSYH içindeki payı %20’lerde olmasının yanı sıra toplam ihracatının %87’si gibi büyük bir kısmını oluşturmaktadır. 1991-2021 yıllarını kapsayan bu çalışmada Türkiye imalat sanayi enerji tüketiminin karbon emisyonu ve ihracatı arasındaki ilişki Johansen eşbütünleşme yöntemi ve Toda-Yamamoto nedensellik analizi kullanılarak test edilmiştir. Analiz sonuçlarına göre imalat sanayi ihracatı, enerji tüketimi ve karbon emisyonu arasında uzun dönemli bir ilişkinin olduğu belirlenmiştir. Toda-Yamamoto nedensellik analizine göre ise imalat sanayi ihracatı ile karbon emisyonu arasında çift yönlü nedensellik ilişkisi olduğu bu değişkenlerin karşılıklı olarak birbirini etkilediği, imalat sanayi enerji tüketiminden ihracata doğru tek yönlü bir nedensellik ilişkisinin varlığı tespit edilmiştir.
This study examines the causal relationship between financial development and economic growth (i.e., the finance-growth nexus) in India from 1970 to 2020. It is motivated as understanding the relationship between financial development and economic growth is crucial for policy formulation, particularly in emerging economies like India. Assuming the potential non-linearity of India’s finance-growth nexus, we employ Autoregressive Distributed Lag (ARDL) and Vector Autoregression with Exogenous Variables (VARX) cointegration techniques. It is also investigated how key control variables—carbon emissions, globalization, and government expenditure—affect this nexus. Economic growth is measured by real per capita GDP, while financial development is proxied by two indicators: financial depth (the ratio of private credit to GDP) and financial efficiency (the ratio of private credit to total deposits), which is one invention of this study. Using both ARDL and VARX techniques, our findings reveal a bidirectional and non-linear relationship between financial development and economic growth, irrespective of the financial development proxy used. This bidirectional relationship highlights the intertwined nature of economic growth and financial development, suggesting that policies targeting either must consider the implications for the other, particularly within the current context of sustainable development and globalization.
This research explores the influence of rainfall on the yield of major crops in Tamil Nadu through the application of the Vector Error Correction Model (VECM). Given the state’s reliance on agriculture, climatic factors especially rainfall play a pivotal role in determining crop performance across seasons. The study focuses on examining both the short-term variations and long-term equilibrium relationships between rainfall and the yields of key crops such as Cholam, Cumbu, and Maize. Leveraging the VECM framework, the analysis captures the cointegration between these variables, providing a nuanced understanding of how rainfall patterns affect agricultural productivity. The results reveal that rainfall exerts a significant long-term impact on crop yields, although its effects are moderated by seasonal shifts and regional disparities. These findings underscore the importance of developing adaptive strategies to address the challenges posed by irregular rainfall. Ultimately, the study offers valuable guidance for policymakers and farmers in Tamil Nadu, enabling more informed decision-making in the face of climate variability and changing weather patterns.
The main objective of this research was to examine the impacts of private and public physical capital accumulations on economic growth in Ethiopia for the period ranging from 1974/75-2017/18 by using Auto Regressive Distributed Lag (ARDL) Approach to Co-integration and Vector Error Correction Model. The result showed that real private capital accumulation had statistically insignificant impact while public capital accumulation had negative and statistically significant impact on economic growth of Ethiopia in the long-run. The result also revealed that human capital and labor force had positive and statistically significant impact while trade openness, macroeconomic instability and foreign aid had negative and statistically significant impact in determining economic growth of Ethiopia in the long-run. In addition, in the short-run private and public capital stocks had negative and statistically significant impact on economic growth of Ethiopia at first lag while human capital, labor force, trade openness, macroeconomic instability and foreign aid had positive and significant impact on economic growth of Ethiopia with lag. Overall, the policy implication of this study is that, given the long-run insignificant impact of private capital and negative significant impact of public capital stocks on economic growth, it is recommendable to reduce public capital investment in different sector investments rather better to encourage private sector participation on economic activities in Ethiopia.
This study examines Rosenstein-Rodan's Big Push Theory in the Nigerian context from 1985 to 2023 as predicated on the CobbDouglas
production
function.
The
study
employed
secondary
data
gotten
from
the
Central
Bank
of
Nigeria
Statistical
Bulletin
and
employed
the Autoregressive Distributed Lag (ARDL) model. By analyzing various factors, including government investment,
income inequality (GINI), labor utilization, and technology, the study aims to identify the key drivers of growth in the classified real
sector of the Nigerian economy and provide practical recommendations for policymakers. Through three econometric models focused
on the services, agriculture, and industry sectors. The findings reveal that government investment significantly drives growth across
all sectors, supporting the premise of a Big Push, with the services sector showing the strongest positive response. Additionally, the
results indicate that income inequality, as measured by the GINI coefficient, adversely affects sectoral growth, underscoring the
importance of addressing disparities. These insights emphasize the necessity for targeted investment strategies that not only increase
public expenditure but also promote equity. Based on these insights, the study recommends targeted government expenditure, policies
to reduce income inequality, investments in human capital, and fostering technological innovation to promote the development of
Nigeria's service sector. These measures are crucial for achieving sustainable economic growth and improving living standards in
the country.
Keywords: Big-Bush Theory, Cobb-Douglas Model, Real Sector, Investment, Nigeria.
This article aims to investigate the nature and characteristics of the correlation between inflation and Tunisia’s unemployment rate from 1970 to 2020. Tunisia has experienced one of the highest unemployment and inflation rates in the Mediterranean Area. The empirical study demonstrates a long-term equilibrium between inflation and unemployment using the autoregressive distributed lag model (ARDL) and the nonlinear autoregressive distributed lag model (NARDL). The ARDL model’s results indicate that the unemployment rate is significantly and negatively impacted by the inflation rate, with a value of -0.526. However, based on the NARDL model’s results, we observe a long-term asymmetric effect. More precisely, we observe a positive and significant impact of low unemployment, evaluated at 0.581, and a negative and significant effect of high unemployment, evaluated at -0.695. The rigidity of labor market regulations has led to distortions that hinder the Tunisian labor market’s smooth operation. It is recommended that these “dysfunctions” be eliminated to increase the efficiency of the labor market’s operation. The quest for greater labor flexibility will make Tunisia’s labor market mechanisms function usually and efficiently.
The development of the phenomenon of the foreign direct investment in Algeria from the independence until now is associated with two important factors, the first one is characterized in the developments and the circumstances which the system of the international economic relations has witnessed and witch it has a remarkable impact on the development of the FDI and the increase of its weight in the framework of the international finance. As for the second factor, it is associated with the orientation which Algeria has adopted in the economic level and the change which the economic way has seen as well as the shift from the planned economy to the economy of market and the openness to the international markets witch has resulted in the advent of new development strategies. This paper focuses on the determinants of foreign direct investment in Algeria, we use annual data covering 1970-2009 period, we use an empirical model (based on cointegration test and error correction model ECM) using some macroeconomic variables, which allows us to obtain a general characterisation in Algerian economy. The results of the study showed negative effect of taxes in the short and long term on FDI in Algeria, a positive effect of public investment (short and long term) and trade openness (long term only). The study concludes by demonstrating results and making recommendations that have been approached.
This study explores the usage of mobile financial services (MFS) in a developing country like Bangladesh, where many underprivileged people who lack proper financial literacy and have no bank accounts are getting formal financial services through MFS. It investigates whether or not the electronic modes of MFS usage impact cash-based MFS usage. Secondary data on MFS usage in Bangladesh have been studied. The autoregressive distributed lag (ARDL) model has been applied to analyze the time series data. The results show that electronic modes of MFS usage negatively and significantly impact cash-based MFS usage. This study fills the gap in the literature with an empirical study at a country level using historical data of category-wise MFS usage instead of relying on users’ opinions. The analysis of this study can serve as a basis for strategic decision-making for policymakers, regulatory authorities and industry players and allow MFS providers to explore innovative approaches in response to the changing dynamics of the market.
ZET Günümüz dünyasında nakit ile yapılan işlemlerden nakitsiz işlemlere hızla geçildiği görülmektedir. Nakitsiz toplum olarak da değerlendirilen bu durumda fiziki olarak para taşımadan plastik kartlar ile işlem yapma kolaylığı sunmakta, sonucunda ise maliyetlerin azalmasından dolaşımdaki para miktarının kayıt altına alınmasına kadar birçok faktöre etki etmektedir. Bu nedenle kademeli olarak nakitsiz bir ekonomiye geçiş sürecinin ekonomik büyüme üzerindeki etkisinin araştırılması, ekonomik aktörler açısında önem teşkil etmektedir. Dolayısıyla bu çalışmada, nakitsiz ödeme araçları kullanımının Türkiye' de ekonomik büyüme üzerindeki etkisi incelenmiştir. Çalışmanın çıkış noktası elektronik kart ödemelerinin dünya ekonomik büyümesi üzerinde anlamlı bir etkisinin olduğu üzerine yapılan tartışmalardır. Diğer yandan nakitsiz ödemenin benimsenmesinin bir ekonomiyi nasıl etkileyebileceğine dair kesin bir kanıt olmamakla beraber ülkenin söz konusu dijital sürece uyum sağlaması önem arz etmektedir. Yine çalışmada, Türkiye için nakitsiz ödemenin 2014Q1-2023Q4 dönemleri arasında artan kullanımının ekonomik büyüme üzerindeki avantaj ve dezavantajlarını tespit etmek amaçlanmaktadır. Bu bağlamda nakitsiz toplumu temsilen kullanılan değişkenler, kredi kartı-banka kartı, internetten yapılan kartlı ödemeler, mektup/telefon ile yapılan kartlı ödemeler ve ekonomik büyümeyi temsilen GSYİH verileri kullanılmıştır. Dönüşen nakitsiz toplumun büyümedeki payını ölçmek üzere verilerin durağanlık sonucuna bağlı olarak Johansen eş bütünleşme ve Granger nedensellik testleri uygulanmıştır. Çalışma sonucunda değişkenler arasında eş bütünleşme ilişkisi ve nedensellik ilişkisi saptanmış, Türkiye' de nakitsiz ödemelerin, ekonomik büyümeyi arttırıcı bir etki yarattığı bulunmuştur. ABSTRACT In today's world, there is a rapid transition from cash transactions to cashless transactions. In this situation, which is also considered a cashless society, it offers the convenience of making transactions with plastic cards without physically carrying money, and as a result, it affects many factors from reducing costs to recording the amount of money in circulation. Therefore, economic actors need to investigate the impact of a gradual transition to a cashless economy on economic growth. Thus, this study examines the impact of the use of cashless payment instruments on economic growth in Turkey. The study's starting point is the debate on the significant impact of electronic card payments on world economic growth. On the other hand, although there is no conclusive evidence on how adopting cashless payment can affect an economy, the country needs to adapt to this digital process. Again, the study aims to identify the advantages and disadvantages of the increasing use of cashless payment for Turkey between 2014Q1-2023Q4 on economic growth. In this context, the variables used to represent the cashless society are credit and debit cards, card payments made online, card payments made by letter/phone, and GDP data representing economic growth. In this context, Johansen cointegration and Granger causality tests are applied depending on the stationarity of the data to measure the share of the transforming cashless society in growth with credit card-debit card, card payments made via the internet, card payments made via letter/phone and GDP data. The study's starting point is the debate on the significant impact of electronic card payments on world economic growth. On the other hand, although there is no conclusive evidence on how adopting cashless payment can affect an economy, the country needs to adapt to this digital process. As a result of the study, it was found that cashless payments have a positive impact on economic growth in Turkey.
Official Development Assistance (ODA) provided by the OECD Development Assistance Committee (DAC) means financial support given to underdeveloped and developing countries within the framework of certain criteria. In this context, it appears as one of the tools used to finance economic development, especially in developing countries. The study aims to examine the impact of official development assistance on foreign trade in Chad, one of the developing countries. Using data on exports (EXPORT), imports (IMPORT), gross domestic product (GDP) and official development assistance (ODA) from the World Bank and OECD database for the years 1960-2022, we examine the contribution of these aid to Chad's foreign trade and economic sustainability. aimed to evaluate. In the analysis, Regression Analysis was performed with the Least Squares Method. Phillips-Perron and Augmented Dickey-Fuller unit root tests were applied to test the stationarity properties of time series. Long-term relationships between the series were examined with the Johansen Cointegration Test and Granger Causality Analysis was performed to determine the direction of the relationships between the variables. The findings show that there is a bidirectional relationship between GDP and ODA, and between ODA and exports. However, the effect of ODA on imports and GDP on exports is unidirectional. Additionally, a bidirectional relationship between GDP and imports has been observed. Research results show that development aid can positively strengthen Chad's economic growth and foreign trade performance. It fills an important gap in the literature as it provides important findings on how development aid and foreign trade strategies can be integrated for Chad's economic sustainability and growth. Limitations of the study include data limitations and the variability of foreign trade policies over time.
Trade policies are important factors in ensuring the welfare and economic stability of countries. It is seen that the power of foreign trade in determining macro and micro plans forces countries to act together and establish integrations based on economic cooperation. Although Turkey wants to become a member of the European Union (EU) to take advantage of the advantages provided by economic integrations, it has not been able to realise this desire until today and has decided to gradually diversify its integration policy as of 2024. At the beginning of these decisions, the desire to apply for membership by improving its relations with BRICS can be shown. The aim of this study is to determine the contribution of foreign trade between Turkey and the EU and BRICS to Turkey's economic growth by using the Generalised Method of Moments (GMM) for the period between 1985 and 2023. As a result of the analysis, it is found that Turkey's foreign trade with both integrations has a positive and significant effect on Turkey's economic growth, but foreign trade with BRICS member countries has a stronger effect on Turkey than EU countries
Let n observations Y 1, Y 2, ···, Y n be generated by the model Y t = pY t−1 + e t , where Y 0 is a fixed constant and {e t } t-1 n is a sequence of independent normal random variables with mean 0 and variance σ2. Properties of the regression estimator of p are obtained under the assumption that p = ±1. Representations for the limit distributions of the estimator of p and of the regression t test are derived. The estimator of p and the regression t test furnish methods of testing the hypothesis that p = 1.
This paper develops a multivariate regression theory for integrated processes which simplifies and extends much earlier work. Our framework allows for both stochastic and certain deterministic regressors, vector autoregressions and regressors with drift. The main focus of the paper is statistical inference. The presence of nuisance parameters in the asymptotic distributions of regression F-tests is explored and new transformations are introduced to deal with these dependencies. Some specializations of our theory are considered in detail. In models with strictly exogenous regressors we demonstrate the validity of conventional asymptotic theory for appropriately constructed Wald tests. These tests provide a simple and convenient basis for specification robust inferences in this context. Single equation regression tests are also studied in detail. Here it is shown that the asymptotic distribution of the Wald test is a mixture of the chi square of conventional regression theory and the standard unit root theory. The new result accommodates both extremes and intermediate cases.
This paper continues the theoretical investigation of Park and Phillips [7]. We develop an asymptotic theory of regression for multivariate linear models that accommodates integrated processes of different orders, nonzero means, drifts, time trends and cointegrated regressors. The framework of analysis is general but has a common architecture that helps to simplify and codify what would otherwise be a myriad of isolated results. A good deal of earlier research by the authors and by others comes within the new framework. Special models of some importance are considered in detail, such as VAR systems with multiple lags and cointegrated variants.
Ten invariant multivariate testing problems involving the real, complex, or quaternion structure of covariance matrices are considered. In each problem the maximal invariant statistic and its distribution are described, as well as the maximum likelihood estimators and likelihood ratio test statistics. These results are obtained by means of a new, unified method based on invariance arguments.
Recent work on the theory of regression with integrated process is reviewed. This work is particularly relevant in economics where many financial series and macroeconomic time series exhibit nonstationary characteristics and are often well modeled individually as simple ARIMA processes. The theory makes extensive use of weak convergence methods and allows for integrated processes that are driven by quite general weakly dependent and possibly heterogeneously distributed innovations. The theory also includes near integrated time series, which have roots near unity, and cointegrated series, which move together over time but are individually nonstationary. A general framework for asymptotic analysis is given which involves limiting Gaussian functionals and extends the LAN and LAMN families of conventional asymptotic theory. An application to the Gaussian AR(1) is reported.
This paper develops a general asymptotic theory of regression for processes which are integrated of order one. The theory
includes vector autoregressions and multivariate regressions amongst integrated processes that are driven by innovation sequences
which allow for a wide class of weak dependence and heterogeneity. The models studied cover cointegrated systems such as those
advanced recently by Granger and Engle and quite general linear simultaneous equations systems with contemporaneous regressor
error correlation and serially correlated errors. Problems of statistical testing in vector autoregressions and multivariate
regressions with integrated processes are also studied. It is shown that the asympotic theory for conventional tests involves
major departures from classical theory and raises new and important issues of the presence of nuisance parameters in the limiting
distribution theory.
This paper is concerned with the investigation of reduced rank coefficient models for multiple time series. In particular, autoregressive processes which have a structure to their coefficient matrices similar to that of classical multivariate reduced rank regression are studied in detail. The estimation of parameters and associated asymptotic theory are derived. The exact correspondence between the reduced rank regression procedure for multiple autoregressive processes and the canonical analysis of Box & Tiao (1977) is briefly indicated. To illustrate the methods, U.S. hog data are considered.
For an m-variate (“partially”) nonstationary vector autoregressive process {Yt}, we consider the autoregressive model Φ(L)Yt = εt, where Φ(L) = I − Φ1L − … − ΦpL and det{Φ(z)} = 0 has d < m roots equal to unity and all other roots are outside the unit circle. It is also assumed that rank {Φ(1)} = r, r = m − d, so that each component of the first differences Wt = Yt − Yt − 1 is stationary. The relation of the model to error correction models and co-integration (Engle and Granger 1987) is discussed. The process {Yt} has the error correction representation Φ(L)(1 − L)Yt = −P2(Ir − Λr)Q2Yt-1 + εt, where Q(Im − Φ(1))P = J = diag(Id, Λr) is in Jordan canonical form and Q' = [Q1, Q2]. It follows that the transformation Zt = QYt = [Z 1t, Z 2t] is such that the d × 1 process Z1t is nonstationary with Z1t − Z1t-1 stationary while Z2t is stationary. Asymptotic distribution theory for least squares parameter estimators of the model is first considered. A Gaussian partial reduced rank estimation procedure that explicitly incorporates the unit root structure in the model is then presented, and an asymptotically equivalent two-step reduced rank estimation procedure is also considered. A numerical example is presented to illustrate the methods and concepts. The finite sample properties of the estimators are also briefly examined through a small Monte Carlo sampling experiment.
Cointegrated multiple time series share at least one common trend. Two tests are developed for the number of common stochastic trends (i.e., for the order of cointegration) in a multiple time series with and without drift. Both tests involve the roots of the ordinary least squares coefficient matrix obtained by regressing the series onto its first lag. Critical values for the tests are tabulated, and their power is examined in a Monte Carlo study. Economic time series are often modeled as having a unit root in their autoregressive representation, or (equivalently) as containing a stochastic trend. But both casual observation and economic theory suggest that many series might contain the same stochastic trends so that they are cointegrated. If each of n series is integrated of order 1 but can be jointly characterized by k > n stochastic trends, then the vector representation of these series has k unit roots and n — k distinct stationary linear combinations. Our proposed tests can be viewed alternatively as tests of the number of common trends, linearly independent cointegrating vectors, or autoregressive unit roots of the vector process. Both of the proposed tests are asymptotically similar. The first test (qf) is developed under the assumption that certain components of the process have a finite-order vector autoregressive (VAR) representation, and the nuisance parameters are handled by estimating this VAR. The second test (qc) entails computing the eigenvalues of a corrected sample first-order autocorrelation matrix, where the correction is essentially a sum of the autocovariance matrices. Previous researchers have found that U.S. postwar interest rates, taken individually, appear to be integrated of order 1. In addition, the theory of the term structure implies that yields on similar assets of different maturities will be cointegrated. Applying these tests to postwar U.S. data on the federal funds rate and the three- and twelve-month treasury bill rates provides support for this prediction: The three interest rates appear to be cointegrated.
This paper provides an analytical study of linear regressions involving the levels of economic time series. An asymptotic theory is developed for regressions that relate quite general integrated random processes. This includes the spurious regressions of Granger and Newbold (1974) and the recent cointegrating regressions of Granger and Engle (1985). An asymptotic theory is developed for the regression coefficients and for conventional significance tests. It is shown that the usual t- and F-ratio test statistics do not possess limiting distributions in this context but actually diverge as the sample size T ↑ ∞. The limiting behavior of regression diagnostics such as the Durbin–Watson statistic, the coefficient of determination and the Box–Pierce statistic is also analyzed. The theoretical results that we present explain many of the earlier simulation findings of
[6] and [7].
The relationship between cointegration and error correction models, first suggested by Granger, is here extended and used to develop estimation procedures, tests, and empirical examples. A vector of time series is said to be cointegrated with cointegrating vector a if each element is stationary only after differencing while linear combinations a8xt are themselves stationary. A representation theorem connects the moving average , autoregressive, and error correction representations for cointegrated systems. A simple but asymptotically efficient two-step estimator is proposed and applied. Tests for cointegration are suggested and examined by Monte Carlo simulation. A series of examples are presented. Copyright 1987 by The Econometric Society.
The asymptotic distributions of cointegration tests are approximated using the Gamma distribution. The tests considered are for the I(1), the conditional I(1), as well as the I(2) model. Formulae for the parameters of the Gamma distributions are derived from response surfaces. The resulting approximation is flexible, easy to implement and more accurate than the standard tables previously published.
Time series variables that stochastically trend together form a cointegrated system. OLS and NLS estimators of the parameters of a cointegrating vector are shown to converge in probability to the true parameter value at the rate T11d for any positive d. These estim mators can be written asymptotically in terms of relatively simple nonnormal random matrices which do not depend on the parameters of th e system. These asymptotic representations form the basis for simple and fast Monte Carlo calculations of the limiting distributions of th ese estimators. Asymptotic distributions thus computed are tabulated for several cointegrated processes. Copyright 1987 by The Econometric Society.
Functional relations, random coefficients, and non-linear regression with application to kinetic data
- Johansen
Testing for cointegration
- Phillips