Vector Error Correction Model Research Articles

Changes in the Global Structure of Energy Consumption and the Energy Transition Process

The global energy transition represents a pivotal aspect of the pursuit of sustainable development and the reduction of greenhouse gas emissions. The objective of this study was to examine the dynamic relationships between global primary energy consumption and the consumption of individual energy sources (nuclear, oil, coal, natural gas, renewables) from 2011 to 2023. To examine both long-run and short-run relationships between variables, advanced econometric methods were employed, including the Johansen cointegration test and the Vector Error Correction Model (VECM). Furthermore, an Index of Sustainable Energy Transformation (ISTE) was devised to quantify the advancement of the transition to low-carbon energy sources. The analysis confirms the existence of long-term equilibrium relationships between global primary energy consumption and the consumption of individual energy sources. The analysis revealed that renewable energy consumption exerts a considerable influence on primary energy consumption, both in the short and long term. The ISTE index demonstrated a notable increase over the period of 2011 to 2023, indicative of advancement in the global energy transition. The results confirm the existence of a stable long-term equilibrium between global primary energy consumption and the consumption of individual energy sources. The observed increase in the ISTE index indicates progress towards low-carbon energy sources, which has important implications for energy policy and sustainable development. The results can support policymakers in monitoring the progress of the energy transition and shaping policies to accelerate the development of renewable energy sources.

A Cybernetic Delay Analysis of the Energy–Economy–Emission Nexus in India via a Bistage Operational Amplifier Network

In analyzing the decoupling of emissions from economic growth, current literature foregoes the nonlinear complexities of macroeconomic systems, leading to ineffective energy transition policies, specifically for developing countries. This study focuses on the Indian energy–economy–emission nexus to establish a control system that internalizes inflation, trade openness, and fossil fuel imports with economic growth and macro-emissions to visualize the complex pathways of decoupling. Through long-term cointegration and vector error correction modeling, it was found that GDP and energy affect capital, inflation and energy imports, which are locked in a long-run negative feedback loop that ultimately increases emissions. Capital growth enables decoupling at 0.7% CO2 emissions reduction for every 1% capital growth, while 1% inflation growth inhibits decoupling by increasing CO2 emissions by 0.8%. A cybernetic fractional circuit of R-C elements and operational amplifiers was utilized to examine the delay of pulses from GDP to the loop elements, which revealed that capital is periodic with GDP pulses. However, inflation, being aperiodic with the clock pulses of GDP, causes the pulse-width of capital to decrease and fossil fuel imports to increase. Through the circuital model, it was possible to determine the exact policy intervention schedule in business cycle growth and recession phases that could build clean energy capital and limit inflation-induced recoupling.

Evaluating Enteric Fermentation-Driven Environmental Kuznets Curve Dynamics: A Bayesian Vector Autoregression Comparative Study of the EU and Least Developed Countries

Global warming and climate change, primarily driven by human activities, with agriculture playing a significant role, have become central topics of scientific research. Livestock production, especially enteric fermentation, is a major source of greenhouse gas emissions, making it a focal point for both climate change adaptation and mitigation strategies. Both the European Union (EU) and Least Developed Countries (LDCs) are highly dependent on agriculture, particularly livestock, which plays a key role in their economic growth. In developing countries, livestock systems are evolving rapidly due to various factors, while in the EU, the livestock sector remains economically and socially significant, representing 36% of total agricultural activity. This study explores the environmental impact of enteric fermentation in livestock production, alongside the economic value it generates in both the EU and LDCs. The analysis utilizes a Bayesian Vector Autoregression (BVAR) methodology, which provides a more robust performance compared to traditional models like Vector Autoregression (VAR) and the Vector-error Correction Model (VECM). This research identifies significant relationships between the variables studied, with structural breaks quantified to reflect the impact of initiatives undertaken in both regions. Interestingly, the results challenge the environmental Kuznets curve, which hypothesizes an inverted U-shaped relationship between economic growth and environmental degradation, as proposed by Stern. This suggests that stronger economic incentives may be necessary to enhance policy effectiveness and promote eco-efficiency. The distinctive characteristics of livestock production in the EU and LDCs should be carefully considered when shaping agricultural policies, with a strong emphasis on farmer education as a critical factor for success. Additionally, corporate management practices must be tailored to address the unique needs, strengths, and challenges of livestock businesses in these two diverse regions.

Analysis of Price Transmission Chili at the Level from Producer to Consumer in Tapin Regency

The fluctuating prices of chili peppers can significantly impact farmers positively and negatively. Farmers cultivating bird’s eye chili can reap substantial profits with high prices. However, they earn less when bird’s eye chili prices are low. Currently, market integration refers to the evolution of costs across different market sectors and the extent to which market sectors in various geographical locations are informed about the supply and demand occurring in a market. This study aims to: 1) analyze the price developments of bird’s eye chili at the producer, wholesale, and consumer levels in Tapin Regency; 2) examine the price transmission of bird’s eye chili from the producer level to the consumer level through prices at the wholesale level and the production of bird’s eye chili in Tapin Regency. The data used in this research are secondary in the form of monthly time series data. The study utilized the documentation method, with data collected from January 2017 to December 2022, totaling 72 data points. The data analysis method employed is the Vector Error Correction Model (VECM), with tests including the Stationarity Test, Optimal Lag Length Test, Stability Test, Cointegration Test, VECM Estimation, Impulse Response Function (IRF), and Forecast Error Variance Decomposition (FEVD). The findings indicate that the prices of bird’s eye chili exhibit monthly fluctuations. The higher price fluctuations at the producer level indicate that farmers have weak bargaining power in setting the prices of bird’s eye chili. The stationarity test shows that the prices of bird’s eye chili at the consumer (HK), wholesale (HG), and producer (HP) levels, along with bird’s eye chili production (PC), are stationary at the first difference. The optimal lag test, with the smallest Akaike Information Criterion (AIC), is lag 2. The cointegration test shows that the trace statistic and max-eigen values are greater than the critical value, thus accepting H1, indicating a long-term relationship. In the short term, the increase in bird’s eye chili prices is influenced by the two previous periods. The analysis results demonstrate asymmetric price transmission from the producer level to the consumer price level.

Impact of COVID-19 trade suspension on price discovery in FPO-traded agri-derivatives

Purpose This study aims to examine whether agricultural commodities exhibited deviations in the lead-lag relationship between future and spot prices of farmer producer organizations (FPOs) traded commodities in the Indian derivative market after trade suspensions during Covid-19. The study may help buyers and sellers to get a fair price for their commodities after lockdown-trade disruptions. Design/methodology/approach The study applied the Granger causality (GC) test and the vector error correction model (VECM) to analyse short-run and long-run lead-lag relationships. Moreover, the study examined the pre-post-trade suspension effect on the lead-lag relationship of commodity prices. Findings The GC test results show that five out of the 13 agri-commodities have changed their lead-lag relationship from future to spot in the short run. Simultaneously, VECM captured changes in the lead-lag relationship for the same five commodities in the long run due to trade suspensions. Practical implications The findings indicate a reverse lead-lag relationship between future and spot prices for aforesaid commodities after trade suspension. The stakeholders may use the lead prices for these commodities to perform a fair trade. The study may be helpful in structuring price discovery strategy to achieve optimal price and efficient derivative trading. Originality/value To the best of the authors’ knowledge, this is the first study examining the effects of trade suspension on price discovery in FPO-traded agri-derivatives caused by the COVID-19 pandemic.

Foreign Portfolio Investment and Capital Market Development in Nigeria

This study investigates the impact of foreign portfolio investment (FPI) on the development of the Nigerian capital market from 1986 to 2023, addressing challenges such as exchange rate volatility and inadequate technological advancement. The research aims to explore the following questions: What is the relationship between foreign portfolio investments and capital market development in Nigeria? How do exchange rate volatility influence the capital market development in Nigeria? What role do technological advancements play in enhancing market performance and attracting foreign investors? Data were sourced from the Central Bank of Nigeria Statistical Bulletin and the National Bureau of Statistics. A quantitative methodology was employed, utilizing the Johansen co-integration test, Vector Error Correction Model (VECM), and Granger causality test to analyze secondary time-series data. The Johansen co-integration test revealed a long-run relationship among the variables, while the VECM indicated that FPI negatively impacts market capitalization. Additionally, the Granger causality test demonstrated unidirectional causality from capital market development to FPI. To address the identified challenges, the study recommends that policymakers create a more supportive environment that ensures foreign investors can repatriate capital and earnings. The government should prioritize exchange rate stability that reflects market realities to enhance investor confidence. Investments in advanced technology are crucial to improving efficiency and accountability in market transactions. By adopting these targeted recommendations, Nigeria can better leverage FPI to foster capital market growth and promote sustainable economic development. JEL Codes: G15, O16

Effect of Inflation Rate on government bond yields listed at the Nairobi Securities Exchange.

This study aimed to determine the effect of inflation rates on government bond yields listed on the Nairobi Securities Exchange (NSE). The primary objective was to assess how fluctuations in inflation impact the yields of 15-year government bonds over a 16-year period, from the first quarter of 2007 to the first quarter of 2023. The study applied liquidity premium theory, as posited by Brennan (1979), which suggests that investors require a liquidity premium, or higher yield, during inflationary periods to compensate for the erosion of purchasing power in fixed-income investments. Given this theoretical framework, the research sought to quantify the relationship between inflation rates and bond yields, considering how rising inflation prompts higher yields to maintain purchasing power.The study employed a causal-comparative research design, utilizing secondary data on bond yields and inflation rates sourced from NSE and Central Bank of Kenya records. Key diagnostic tests, such as the Jarque-Bera test for normality, Breusch-Pagan-Godfrey test for heteroscedasticity, and Augmented Dickey-Fuller test for stationarity, ensured data validity and reliability. The Vector Error Correction Model (VECM) was used to analyze both short- and long-term relationships between inflation and bond yields. Findings revealed a statistically significant positive correlation between inflation rates and government bond yields, with inflation accounting for 45% of the variance in bond yields. The standardized coefficient of 0.67 suggested a moderate-to-strong association, highlighting inflation’s critical role in bond pricing. Based on these results, it is recommended that investors and policymakers closely monitor inflation trends as they influence bond yields and market performance. Further research could explore other macroeconomic factors, such as interest rates, to offer a more comprehensive view of bond market dynamics in emerging economies.

Inklusi Keuangan dan Efektifitas Kebijakan Moneter : Studi Kasus Negara Indonesia dan Malaysia

Financial inclusion, defined as access and use of formal financial products and services by individuals and companies, has become a major focus in Indonesia and Malaysia in recent years. Authorities in both countries have implemented various policies and programs to increase financial inclusion, hoping to provide economic benefits, namely reducing inflation. The aim of this research is to analyze the influence of financial inclusion, exchange rates, interest rates, broad money, and GDP on inflation in Indonesia and Malaysia. The data used in this research is secondary data ranging from the period 2013Q1 to 2022Q4. The analytical method used in this research is the Vector Error Correction Model (VECM). The conclusion of this research states that the financial inclusion variable has a negative influence on inflation in Indonesia with a VD contribution at the end of the period of 29.37%, while in Malaysia Financial Inclusion has a positive influence on inflation with a VD contribution at the end of the period of 11.22% . The exchange rate negatively influences inflation in Indonesia and Malaysia with VD contributions at the end of the period of 1.28% and 3.87% respectively. Interest rates have a negative influence on inflation in Indonesia with a VD contribution at the end of the period of 1.71%, while in Malaysia interest rates have a positive influence on inflation with a VD contribution at the end of the period of 13.19%. Broad Money positively influences inflation in Indonesia and Malaysia with VD contributions at the end of the period of 2.27% and 2.57% respectively. GDP has a positive influence on inflation in Indonesia with a VD contribution at the end of the period of 22.01%, while in Malaysia GDP has a negative influence on inflation with a VD contribution at the end of the period of 45.39%.

Impact of urbanization and planting structure on water footprint of food, cash, and feed crops in China’s northern agro-pastoral ecotone

China, especially the northern agro-pastoral ecotone, is facing severe water scarcity, which presents a significant challenge for the agriculture sector, the largest consumer of water. This study selected Yanchi County as a typical area. First, the water footprint method is used to evaluate the water usage of food, cash, and feed crops in the region from 1990 to 2020. Then, the vector error correction model (VECM) is used to analyze the short-term effects and long-term effects of urbanization and planting structure on the water consumption of these three types of crops. The results show: 1) The total agricultural water footprint (WF) in Yanchi County, as well as the WFs of the predominantly grown food and feed crops, show an upward trend. Additionally, the proportion of blue WF is relatively high across all crop types. 2) Reducing the proportion of food crops will increase the WF of cash and feed crops, but it will not necessarily decrease the WF of food crops. 3) An increase in the level of urbanization may reduce the agricultural WF in the short term, but ultimately, it will lead to an increase in the WF. Overall, this study reveals the growing pressure on agricultural water use faced by the agro-pastoral ecotone during the processes of urbanization and planting structure transformation. It highlights the importance of developing rain-fed agriculture, seizing the technological development opportunities brought by urbanization, and reasonably adjusting the cropping structure for the sustainable use of water resources.

The Impact of Cryptocurrency and Electronic Money Use On The Circulating Money Supply and Monetary Stability in Indonesia

The purpose of this research is to analyze the long-term and short-term impacts of the use of cryptocurrency and electronic money on the money supply (M2) in Indonesia, as well as to analyze the long-term and short-term impacts of the use of cryptocurrency and electronic money on monetary stability (exchange rates) in Indonesia. The research method used is quantitative descriptive analysis with the Vector Error Correction Model (VECM) using the Eviews application and secondary data in the form of monthly data from 2011 to 2023 obtained from the official websites of Bank Indonesia and Finance. This study utilizes data on cryptocurrency transaction values and electronic money transaction values in Indonesia by analyzing the VECM model, which can observe the long-term and short-term impacts of the use of digital money on the money supply and monetary stability, in this case, viewed through the Indonesian exchange rate. The research results indicate that there is a one-way causality between electronic money and cryptocurrency, but not the other way around, and there is a one-way causality between the money supply and cryptocurrency, with the money supply as the dependent variable influencing cryptocurrency. The results of the VECM estimation indicate that in the long term, electronic money has a negative and sifnificant impact on the money supply. Meanwhile, the short-term estimation shows that both cryptocurrency and electronic money significantly influence the money supply, but their effects are dynamic and vary based on different lags. The long-term estimation with the exchange rate as the dependent variable shows that cryptocurrency does not have a significant impact on the exchange rate, while in the short term, both cryptocurrency and electronic money have a negative and significant effect on the exchange rate.

The Impact of Financial Development, Foreign Direct Investment, and Trade Openness on Carbon Dioxide Emissions in Jordan: An ARDL and VECM Analysis Approach

Jordan has made substantial strides in enhancing its economy by focusing on economic growth stimulants, which include financial development, foreign direct investment (FDI), and trade openness. However, these economic activities often lead to significant environmental risks. Despite their relevance, the existing literature has rarely examined the influence of these dynamics on environmental quality in the Middle East, particularly in Jordan. This study aims to investigate the influence of financial development, FDI, and trade openness on carbon dioxide (CO2) emissions in Jordan. To achieve this, the study employs the Autoregressive Distributed Lag (ARDL) technique and the Vector Error Correction Model (VECM) Granger causality approach, utilizing data sourced from the World Bank for the period from 1990 to 2022. The findings indicate that financial development, FDI, and trade openness positively impact CO2 emissions, thereby increasing environmental risks in both the short and long term. Additionally, there exists a bidirectional causal relationship between financial development and both FDI and trade openness, as well as between FDI and trade openness. It is imperative for Jordan to design strategies that balance economic growth with sustainable environmental practices.

The Interplay of Foreign Direct Investment in Unravelling the Nexus of Technological Innovation and Economic Dynamics: An Integrated Study Using Vector Error Correction Model

Most lower-middle income countries prioritise innovation, with foreign direct investment (FDI) as a key funding source for sustainable development. This article studies the interplay between FDI, technological innovation (measured by patent-granted residents), gross domestic product (GDP), research and development (R&D) expenditure (RDE) and inflation of the Indian economy from 2002–2003 to 2022–2023. It uses a vector error correction model, Johansen cointegration tests, Granger causality tests, the impulse response function and variance decomposition. The study finds two cointegration relationships between the variables. GDP and RDE have a significant positive effect on technological innovation in the long term. Neither FDI nor inflation shows such an impact. FDI policies should therefore consider factors such as a conducive regulatory framework, tax breaks and grants for R&D to enhance their impact on innovation. JEL Codes: O31, O32, F21, F23, E01, O47

The Impact of Crude Oil Price Shock: Evidence from Bangladesh

This study aims to estimate the impact of crude oil price on the DSEX broad index of the Dhaka stock exchange using the Vector Error Correction Model (VECM) for the study period 2013:01-2022:12. It has decomposed the oil price shock into supply side and demand side oil shock. The empirical result shows that the stock price decreases significantly with crude oil prices driven by the shock in oil production. In contrast, the improvement in global economic activity results in a shock in the oil price which has a significant positive impact on the stock price. Furthermore, the accumulated shock in oil prices has a significant positive impact on stock prices. The variance decomposition under the VEC model shows that the demand shock of oil price contributes more to the variation in stock price for the oil-importing country Bangladesh. Since different oil price shocks have different impacts, the policy maker and investors implement decisions based on the understating of the sources of the shocks.

Interconnected Stock Markets: Analysing Cointegration and Correlation among Global Stock Indices

This study examines the long-term and short-term relationships among five major global stock indices—NSE NIFTY (India), S&P 500 (USA), FTSE 100 (UK), Hang Seng (Hong Kong), and Nikkei 225 (Japan)—over the period from 2008 to 2023. Using advanced econometric techniques such as Johansen cointegration tests, Engle-Granger residual cointegration test and the Vector Error Correction Model (VECM), the research explores the degree of interconnectedness and cointegration among these indices. The results indicate strong positive correlations between NSE NIFTY, S&P 500, and Nikkei 225, suggesting a growing synchronization of these markets due to global economic integration. Johansen's test reveals the presence of multiple long-term equilibrium relationships, affirming that despite short-term deviations, these markets tend to move together in response to global macroeconomic factors. The analysis further highlights that the S&P 500 and FTSE 100 indices exhibit significant error correction mechanisms, underscoring their leadership role in global market dynamics. In contrast, NSE NIFTY shows a weaker adjustment toward long-term equilibrium, indicating its reactive nature to changes in other global indices, particularly the S&P 500. The study finds that while Hang Seng and Nikkei 225 are connected globally, their short-term linkages appear weaker, likely influenced by regional factors. Overall, the results emphasize the critical influence of the U.S. and Japanese markets on NSE NIFTY, with both long-term cointegration and short-term market dynamics shaping the Indian stock market’s movements. This research offers key insights for investors seeking to understand global stock market interdependencies and manage portfolio risk.

Impact of Energy Consumption from Renewable Energy Sources on Economic Growth: Evidence from Nigeria

This study examines the impact of renewable energy consumption and electricity tariff on the economy of Nigeria. The study considers the casual relationship and vector decomposition between various renewable energy sources (solar, hydro and biomass), electricity price and Gross domestic product (GDP) using an unrestricted vector error correction model (VECM). In addition, other robust econometric techniques were applied to the time series of GDP, electricity price and energy consumption from renewable energy sources from 1980 to 2021. The findings indicated a 1% increase in biomass consumption causes increase in GDP by 0.14% in the long-run. Mixed result in the short-run with the difference in the log value of the current lag of solar and bio electricity consumption having positive impact on GDP. The coefficient of the Error Correction Model (ECM) was negative (-0.49) and statistically significant indicating that short-run change from the long-run equilibrium is corrected by 49% annually. Unidirectional causality from GDP to solar electricity consumption. Solar, hydro, biomass and electricity price explain 1.4%, 0.4% 2.2% & 12% respectively of fluctuations in GDP in the long-run. The study results demonstrates that regulations need to be put in place to control the adverse effect of consuming biomass on the environment which could cause mixed impact on gross domestic product in the short run whereas, policies to foster development of solar projects could impact positively on GDP and alleviate the electricity supply deficiency in Nigeria.

Depreciation and Trade Balance: An Exploration of the J-Curve Phenomenon in Indonesia

Research Originality: Global economic uncertainty has increased in recent years, leading to an appreciation of the US dollar relative to most global currencies, including the Indonesian rupiah. The novelty of this study is the inclusion of natural resource commodity price index variables, given the importance of these commodities in Indonesia's balance of trade.Research Objectives: This study aims to examine the effect of rupiah exchange rate depreciation on Indonesia's trade balance.Research Methods: This study uses a Vector Error Correction Model (VECM) to analyze Indonesia's balance of trade from January 2015 to December 2023, examining the potential J-Curve phenomenon resulting from the depreciation of the Indonesian rupiah.Empirical Result: Findings from the impulse response analysis suggest that the J-Curve phenomenon is present in Indonesia's balance of trade as a result of the rupiah's depreciation. The results of this study also confirm the positive effect of increasing natural resource commodity prices on Indonesia's trade balance.Implications: The implication of these findings is that exchange rate depreciation can improve Indonesia's trade balance only when natural resource commodity prices are rising. Conversely, if commodity prices decline, maintaining the stability of the rupiah exchange rate becomes crucial.JEL Classification: F11, F14, F31, Q02

ANALISIS INTEGRASI PASAR SPASIAL HARGA TELUR AYAM RAS MENGGUNAKAN METODE VECTOR ERROR CORRECTION MODEL

Purebred chicken eggs are one of the staple commodities whose price development continues to be monitored by the government. To maintain price stability of purebred chicken eggs, an understanding of spatial market integration is needed. Spatial market integration can show the level of closeness between markets in a region. The spatial market integration in this study was modeled using the Vector Error Correction Model (VECM) method. The VECM method was chosen with the aim of seeing the relationship between the price movement of purebred chicken eggs both in the short and long term, seeing the interaction of relationships that occur in each region and forecasting the price of purebred chicken eggs. The research objects used include the price of purebred chicken eggs in Semarang City, Salatiga City, Demak Regency, and Pati Regency in the period January 2021 to December 2022. The data used is weekly time series data that has met the stationary test at the first differential level. Based on the Johansen cointegration test on the four regions, 3 cointegrations were obtained, indicating that in each short-term period all variables adjust to each other to achieve long-term equilibrium. Granger's causality test in this study showed that not all variables have a two-way relationship. The resulting MAPE value is less than 10%, so the resulting model is very feasible to use.

Nexus between Gross Fixed Capital Formation, Household Loans and Savings in Bulgaria

The goal of this article is to analyze the impact of household savings and household loans on gross fixed capital formation in Bulgaria. The research is carried out on the basis of quarterly data for the 2010-2023 period. The sources of the data are the National Statistical Institute (NSI) and the Bulgarian National Bank (BNB). The algorithm of the empirical research includes: checking for stationarity by means of the extended Dickey-Fuller test; determining the optimal lag of the model; Johansen cointegration test; specification of vector error correction model (VECM). As a result of the research, it has been established that there is a long-term relationship between the variables gross fixed capital formation, household savings and household loans. At the same time, about 39.2% of the disequilibrium between the studied variables in a certain quarter is compensated in the next one.

The effects of financial development on crop productivity: ARDL evidence from Indian agriculture

Purpose This work aims to empirically investigate the effects of financial development on crop productivity of India. Design/methodology/approach Time series data such as crop production index, International Monetary Fund’s (IMF) financial development index, gross domestic product (GDP) per capita, arable land, rural population, trade openness and physical capital from 1980 to 2020 was used. The autoregressive distributed lag (ARDL) bounds testing approach of cointegration was used to determine the long-run equilibrium relationship between the selected time series. Also, ARDL long- and short-run coefficients were estimated to examine the effects of selected variables on crop productivity. Furthermore, to establish the robustness of results, long-run estimators such as fully modified least squares and the dynamic least squares were also used. Finally, using the vector error-correction model, causality between the selected time series was examined. Findings The ARDL cointegration test confirmed the existence of long-run equilibrium relationship among agricultural productivity, financial development, capital formation, GDP per capita, arable land, rural population and trade openness. The estimated long-run elasticities from all the three techniques and the short-run elasticities of ARDL have consistently suggested that the elasticity of financial development is higher (1.55% and 1.40%, respectively) in explaining the crop productivity of India. The short-run causality estimates indicated the presence of positive bidirectional causality between crop productivity and financial development and seven positive unidirectional causal relationships between the selected variables. Practical implications Agricultural credit being an important non-land input and essential for overall growth and sustenance of agricultural sector, the policymakers should ensure the overall development of its financial sector which will reduce the intermediation, informational and other transactional costs associated with agricultural credit. This will possibly result in timely availability and access to adequate and low-cost credit from institutional sources. Originality/value Though extensive research is available on the effects of financial development on economic growth, limited research is available concerning the impact of financial development on crop productivity, especially for an emerging economy like India. For India, predominantly studies have investigated the impact of farm credit on crop productivity but have not exclusively examined the effects of financial development on agricultural productivity. Therefore, this study not only adds to the empirical literature but also provides new evidence on the nexus between financial development and crop productivity by examining the effects of financial development on crop productivity using the composite financial development index developed by the IMF using the ARDL bounds test for cointegration and other econometric estimators.

Agricultural raw materials, information and communications technology and service exports on economic growth in twenty Sub-Saharan countries: A panel vector error correction model approach

Agricultural raw materials, information and communications technology and service exports on economic growth in twenty Sub-Saharan countries: A panel vector error correction model approach