Short-run Causality Research Articles

Do geopolitical uncertainty and inflation transmit opportunities or threats to green energy consumption?

Purpose This study aims to examine the impact of geopolitical uncertainty and inflation on green energy consumption. In addition, it aims to reveal the cause-and-effect relationship among these variables. Design/methodology/approach The authors exert the panel dynamic ordinary least squares (OLS) approach of Kao and Chiang (2000) and the Granger non-causality method of Dumitrescu and Hurlin (2011). On the other hand, current study relies on the annual time series data of 29 countries from 1985 to 2022. Findings The panel dynamic OLS results confirm a long-run relationship between geopolitical uncertainty, inflation and green energy consumption. On the other hand, inflation negatively impacts green energy consumption, with high inflation levels potentially halting the transition. Conversely, geopolitical uncertainty shows no significant effect on green energy use, indicating a reliance on traditional energy sources. Moreover, the current investigation reveals the unidirectional causality from green energy consumption to inflation, while no short-run causality exists from inflation as well as geopolitical uncertainty to green energy consumption in the selected countries. Research limitations/implications The authors drew conclusions about the potential impact of geopolitical uncertainty and inflation on green energy uses by considering the macro-level data. However, this investigation further be enhanced by looking at such issues through the micro perspective by understating the thought and perspective of public on the implication of geopolitical uncertainty and inflation on green energy uses. Such micro-level, country-specific study would definitely help us to generate more concrete ideas about such themes. Practical implications The empirical findings have important implications for policymakers. Results suggest that high inflation negatively impacts green energy use, so policymakers must consider implementing measures to control the inflation while promoting green energy uses for economic prosperity and environmental sustainability. In the short run, green energy use leads to inflation. Therefore, macroeconomic policymakers can implement various subsidy policies for the general public to mitigate the short-term inflationary impact of green energy use. Originality/value This investigation is novel in three ways. First, it explores the impact of geopolitical uncertainty and inflation on green energy use, using Caldara and Iacoviello’s (2022) geopolitical risk index as a proxy of geopolitical uncertainty. Second, it uses panel data econometric analysis, a method that most previous studies have not contemplated for this type of investigation. Finally, by including both advanced and emerging economies, it provides valuable insights for policymakers to develop effective strategies related to green energy consumption for achieving sustainable economic development.

Assessing the Environmental Sustainability Corridor for BRICS Nations by Integrating Three SDGs, ‘Biocapacity’ and ‘Ecological Footprint’

The present study makes an attempt to analyse the co-integrating relation between ‘ecological footprint’ on one hand and GDP, trade openness, forest area and biocapacity on the other for the period 1992–2015 for five BRICS economies with the objective of ascertaining whether the rapid growth achieved by the BRICS is along a ‘sustainable’ path. Further, the study also tries to lookout for signs of ‘convergence’ of ‘ecological footprint’ amongst all BRICS economies. The methodology employed includes ARDL Co-integration Model, TY Causality and Beta Convergence Models. The results showed existence of long run co-integration amongst four BRICS nations (except for India where no co-integration was proved) with fast speed of adjustment towards long run equilibrium. Further, short-run causality was seen moving from ‘GDP’ and ‘forest area’ towards ‘ecological footprint’ in three of the five BRICS nations, while variable ‘trade’ was not seen causing ‘ecological footprint’. ‘Beta convergence’ was also proved for ‘ecological footprint’ amongst all BRICS nations. These results thus provide a clear indication as to which variables need to be targeted to achieve a ‘sustainable’ growth. The results also reveal the pace of long-term adjustment as shown by ECM(1) term, which would enable policymakers to plan their action for fulfilment of the objective of tackling ‘environmental degradation’ in BRICS economies. Also, convergence of ‘ecological footprint’ across BRICS indicates that similar policies to tackle environmental degradation could be framed for BRICS at their group meetings.

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.

Can Renewable Energy Be a Driving Factor for Economic Stability? An In-depth Study of Sector Expansion and Economic Dynamics

India has emerged as one of the world's most appealing locations for renewable energy development. It has set lofty renewable energy goals to reach 450 gigawatts (GW) capacity by 2030. These aims indicate India's determination to move to greener and more sustainable energy sources. India has been investing in R&D to promote technological innovation in renewable energy. This includes improvements to solar photovoltaic technology, wind energy, energy storage technologies, and smart grid systems. Innovation is critical for improving efficiency, lowering prices, and increasing the reliability of renewable energy sources. This paper aims to analyse the linkages between economic growth and renewable energy usage in India. For this, the Granger Causality technique is adopted, and it is found that no short-run causality exists among the economic growth and RE installed capacity. However, Industrial Production Granger Causes both GDP and Renewable Energy Capacity. When the stock price data of the last five years of top renewable energy companies was also collected, it was found that all the companies are showing an upward trend. While renewable energy is growing rapidly, especially solar and wind power, it is insufficient to meet the bulk of India's energy demands. Renewables contribute to reducing carbon emissions and diversifying the energy mix, but they still account for a smaller percentage compared to thermal power.

The Influence of Gold, Black Gold, and Digital Gold on Stock Market Portfolios

This research paper aims to study the influence of Bitcoin (BTC), Crude Palm Oil (CPO), Crude Oil (WTI), the Dollar Rate (USD), and Gold (XAU), on Stock Market Portfolios (KLSE). Time series data for this investigation was obtained from Yahoo Finance and Investing.com. Furthermore, the Unit Root Test conducted found that the variables are stationary after 1st differencing. Moreover, since there was no Cointegration discovered between the variables, VAR was performed to determine the long-run causality effect, while the Wald Test was conducted to examine the short-run causality effect. The findings revealed that none of the variables contained a long-run relationship, whereas Bitcoin (BTC), Crude Palm Oil (CPO), and Gold (XAU) contained a short-run relationship with the independent variable (KLSE).

Financial development, institutional quality and economic growth in countries in sub-Saharan Africa (SSA)

Over the years, there have been huge variations in the growth performances of the economies in SSA. Whilst these disparities can be attributed to a wide range of factors, it is generally understood that differences in their economic structures explain the capacity for generating growth and absorbing shocks during a recession. This study contributes to literature by examining the impact of institutional quality and financial development on economic growth in low- and middle-income countries. Data was obtained from the World Bank and covered the period from 1975 to 2020. The study employed an ARDL model to establish both short and long run dynamics in the two sub samples. The study confirmed both short and long run causality from financial and institutional quality to growth. Institutional quality enhances growth in both low- and middle-income countries in the long run. Whilst the direction of the impact is the same, the magnitude of the impact of institutional quality is different within the two categories. Institutional quality plays a more significant role in low-income countries compared to middle income economies. The study brings out potential financial fragility and systemic risks in financial institutions among countries in SSA. Policies that enhance the quality, consistency, and uniformity of legal reasoning in judicial decisions are ideal. Reducing the risk profile for investments may enhance the flow of credit to the private sector by financial institutions.

The nexus among CO2 emission, health expenditure and economic development in the OECD countries: New insights from a cross-sectional ARDL model.

To find a way to realize sustainable development, this paper applied a cross-sectional ARDL (CS-ARDL) method to explore the interaction between carbon emissions, economic development, and health care expenditure for OECD countries. Firstly, we conduct a cross-sectional test to check whether the data is confronted with this issue. Secondly, we conduct a panel unit root test and cointegration test to confirm whether the ARDL-based method is suitable for our data. Thirdly, we analyze the results and provide possible explanations. Lastly, we conduct a short-term causality test to detect the connection between different variables. The main conclusion of our study includes: 1) Health care is a necessity in OECD countries. 2) Environmental deterioration places a heavy burden on health care expenditure in OECD countries. 3) Health care expenditure of last year negatively affects health care expenditure. 4) There is a short-run causality relationship from CO2, economic development, and dependency rate of youth to health care expenditure in OECD countries. Related policy proposals are provided according to our analysis of the results.

Examining the relationship between bitcoin and altcoins

Purpose- The purpose of this study is to examine the long and short-term relationship between Bitcoin and altcoins selected based on their market capitalization through an empirical analysis. For this purpose, the daily data of Bitcoin and nine altcoins consisting of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin for the period 07/08/2015-08/01/2020 were used. Methodology- The long-run relationship between Bitcoin and altcoins is first analyzed by Vector Autoregression (VAR) analysis. Granger causality test was utilized to determine the short-run causality relationship between the variables. The tests were conducted with the Eviews program. Findings- According to the results of the VAR analysis conducted to investigate the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. After determining the long-run relationship between the variables, the relationships between the variables were analyzed with the help of impulse response functions. Impulse response function shows the effect of a one-unit shock to one variable on the other variable. Accordingly, when the results of impulse response functions are analyzed; it is seen that a one-unit random shock in Bitcoin has a negative effect on Ripple, Nem, Litecoin, Dash, Litecoin, Dogecoin in the first two periods, the effect decreases in the second period, and this effect disappears in the third period. A random shock to Bitcoin causes a positive effect on Stellar that lasts for two periods. This positive effect ends in the third period. After analyzing the relationship between Bitcoin and altcoins with impulse response functions, the source of the changes in the variance of the variables is analyzed through variance decomposition. According to the variance decomposition results, the effect of Bitcoin on Dogecoin is 25% in the first period and 22% in the other periods. The variance decomposition of Dash shows that approximately 18% of the change in standard deviation was caused by Bitcoin in the first period and this percentage increased to 25.5% in the following periods. Litecoin's variance decomposition results show that 33% of the change in standard deviation from the first period to the last period was caused by Bitcoin. It is observed that approximately 8% of the change in Nem's standard deviation in the first period was caused by Bitcoin, while this rate increased to 21.5% in the last period. From the first period to the last period, 13.5% of the change in Stellar's standard deviation was caused by Bitcoin. When the variance decomposition of Ripple is analyzed, it is observed that 10% of the difference in the standard deviation is due to Bitcoin. This situation continued similarly from the first period to the last period. Following the VAR analysis, Granger causality test was conducted to explain the short-term relationship between the variables. According to the test results, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. When the Granger causality relationship between altcoins is analyzed, a causality relationship was observed from Tether to Stellar, while no causality was found from Stellar to Tether. Similarly, while Granger causality is observed from Tether to Ripple, there is no causality from Ripple to Tether. The variance decomposition of Stellar and Ripple shows that Tether does not contribute to the change in standard deviation. The variance decomposition test supports the Granger test results. All altcoin variables except these are Granger causes of each other. Conclusion- At the end of the study, according to the results of the VAR analysis to determine the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. There is no long-run relationship between Tether, Monero, Ether and Bitcoin. According to the Granger causality analysis test results conducted to observe the short-term relationship, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. As a result, it is observed that Bitcoin has a short-term relationship with all 9 altcoins subject to the study, and a long-term relationship with Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple. These results show that the price movements in Bitcoin have an impact on altcoins. Keywords: Bitcoin, altcoin, cryptocurrency, causality analysis, VAR analysis. JEL Codes: G17, G10, C58

The Impact of Foreign Direct Investment on Poverty Reduction: Evidence from Bangladesh

This study aims to identify the contribution of foreign direct investment on poverty reduction in Bangladesh with a data period of 32 years starting from FY 1991 to FY 2022 with annual observations in real term. Besides foreign direct investment, gross domestic product, government expenditure on education, employment, and trade openness are used as control variables. Per capita consumption is used as a proxy for poverty reduction. The study goes for Johansen Co-integration test and then Vector Error Correction Model rather than Ordinary Least Squares Regression to avoid any spurious result as indicated by Augmented Dickey-Fuller test. This study finds that FDI has significantly negative relationship while Employment has almost indifferent effect on poverty reduction in the long run. However, other control variables, i.e., GDP, Govt. Expenditure on education and Trade openness have long run positive relationship in this regard. The short run causality of FDI toward poverty reduction is also insignificant in Bangladesh.

Government and Business Funding of Sources of Funds for R&D at Universities: Complements or Substitutes?

AbstractThe paper examines the relationship between different sources of funding for research and development at universities. Following the European Commission methodology, we distinguished between government, business and abroad financing of research and development (R&D) in the higher education sector. The paper aims to test short-run and long-run relationships between different funding sources. We are focused on the relationship between government and business funding of R&D at universities. Based on panel data for EU countries, we applied the Granger causality tests and General methods of moments to examine short-run causality and cointegrating regression to search for potential long-run relationships. Our results suggest that government funding of R&D act as a complement to business funding. Hence, rising government financial support for research in higher education can, lead to higher funding from the business sector. Founding from abroad seems to have a similar effect on business funding in the long run.

Do Innovation and Institutional Quality Elevate Economic Growth? Empirical Evidence from Developing Countries

Research Highlights • An assessment of institutional quality, innovation, and economic growth in developing countries. • Long-run causality from innovation and institutional quality to economic growth is present. • Short-run directions of causality are varied among variables of interest. • Innovation and institutional quality generally positively impact economic growth. Continuous innovation is the lifeblood of a competitive economy. Furthermore, and arguably, the existence of institutions of governance of quality can be a catalyst for emerging economies to transition up the universal innovation value chain. In this context, we investigate temporal causal interactions among institutional quality, innovation, and economic growth for developing countries (DCs) spanning the period of 2005–2020. Employing a vector error-correction model (VECM), we find that for each case and specification (49 instances), there is evidence of the long-run causality from institutional quality and innovation to economic growth. Stated another way, in the long run, institutional quality and innovation Granger-cause economic growth. However, the short-run causality results differ depending on the specific measures of innovation and institutional quality. The strongest short-run conclusion is support for the feedback hypothesis for economic growth and innovation where there is a strong endogenous relationship between innovation, institutional governance, and economic growth. The empirical analysis shows over 70% of our observations support that economic growth and innovation jointly determine each other in the short run. The results suggest that DCs should develop and pursue long-term growth strategies that simultaneously develop innovation and improve institutional governance.

Economic digitalization and energy transition for green industrial development pathways

This study explores the novel aspect of how economic digitalization moderates the effect of energy transition on green industrial development in the presence of urban agglomeration, international investment inflows, and economic prosperity. We examine G7 countries from 2003 to 2019, employing advanced empirical techniques, which indicate that economic digitalization induces a short- and long-term green industrial development promotion effect. Furthermore, the energy transition had positive short- and long-term consequences on developing the green industrial sector. Most notably, economic digitalization positively moderated the impact of the energy transition on green industrial development, with the effect being more pronounced in the long run. The short-run causality revealed a unidirectional causality from economic digitalization and moderation term to green industrial development, while other variables established a bidirectional causality link with the same. Policies strengthening the integrated coordination of digital and energy transition technologies are recommended to achieve a green industrial structure for sustainable development.

Industrialization, globalization, ICT, and environmental degradation in Malaysia: A frequency domain analysis

This paper examines the causal relationship between industrialization, globalization, information communication technology (ICT) and environmental degradation in Malaysia during 1970–2019. It uses two indicators of environmental degradation (carbon emissions and ecological footprint), three dimensions of globalization (political, social, and economic) and three indicators of ICT (users of internet, mobile cellular, and fixed telephone subscriptions). It utilizes Granger causality technique in frequency domain which differentiates between permanent and temporary causality, Vector Error Correction approach as well as Variance Decompositions. The bound test shows that the variables have cointegration relationship. It reveals joint long-run and short-run causality from industrialization, globalization, and ICT to carbon emissions, albeit the causality to ecological footprint is tenuous. It indicates that industrialization, globalization, and ICT significantly predict carbon emissions at high frequency than at low frequency. A substantial percentage of the forecast error variance in environmental degradation are explained by industrialization, globalization, and ICT. The robustness of the empirical outcomes is confirmed by the alternative proxies of the variables. Our study implies that industrialization, globalization, and ICT are determinants of environmental degradation. Therefore, policies to mitigate environmental problem should prioritize these variables to attain green economy.

Relation Between Inflation and Capital Market in India

Capital market has significant influence on the inflationary situation in an economy both in the short run and in the long run. The general determinants which affect capital market are share indices, stock prices, prices of gold and silver, interest rate, exchange rate and even money supply can be treated as influencing variable when money is treated as capital. In this paper the author examined the impact of capital market on inflation in India during 1980-2022 taking CPI and WPI as the indicators of inflation and gold price, silver price, BSE index, BSE market capitalization, money supply and rupee dollar nominal exchange rate are considered as the indicators of capital market. Augmented Dickey-Fuller test was applied to verify unit root for all variables including break unit roots and the author calculated growth rates during 1980 – 2022 using the simple semi-log linear trend model. Author applied Johansen cointegration test and vector error correction models among the variables in both the cases of CPI and WPI and calculated short run causality through Wald test and long run causality through cointegrating equation. In VECM, the paper found one significant cointegrating equation in case of CPI and found three significant cointegrating equations in WPI. The paper found that CPI has long run causal relationships with BSE index, BSE market capitalisation, money supply and rupee dollar exchange rate and WPI has long run cointegrating relationships with BSE market capitalisation, money supply and rupee dollar exchange rate respectively. Rupee dollar exchange rate has short run causal relationships with CPI and again CPI and BSE index has bidirectional short run causality. According to impulse response functions, the responses of CPI to gold price, BSE market capitalization and money supply have been approaching towards equilibrium but finally diverged away from equilibrium. There are significant short run causalities from BSE index and money supply to WPI. The impulse response of WPI to gold price, silver price, BSE index, BSE market capitalisation and exchange rate of rupee have been converging towards equilibrium many times although diverged finally. The model can be modified by including interest rate, share prices, bond prices under monthly data analysis.

The effect of monetary policy shocks on industrial output in Afghanistan

Purpose- This study examines the impact of monetary policy shocks on industrial output in Afghanistan. Quarterly secondary data were collected for the period from 2003 to 2021 from various official sources such as the Statistical Bulletin of the Central Bank of Afghanistan, the International Monetary Fund, and the World Bank. Methodology- This study used a three-stage procedure. The first stage involved testing the stability of the variables to be included in the model. The second stage involves selecting the optimal lag length using various lag length criteria. Finally, the Vector Error Correction (VECM) model was used to determine if there were any short-run correlations or dynamics among the variables. The study also conducted some post-tests to confirm the validity and robustness of the regression model. Findings- The results of the long-run vector error correction model show that there is a long-run causality running from monetary policy rate, broad money supply, inflation, exchange rate, and a commercial bank loan to the industrial sector. So, there was a speed of adjustment from the short-run to the long-run equilibrium. However, the Wald test confirmed that the short-run causality runs from the explanatory variables to the dependent variable. Commercial bank credit to the industrial sector was found to cause a change in industrial production in all six lag periods. The results were further supported by the Granger causality test. Shocks in commercial bank lending to the industrial sector were found to have no significant effect on industrial output. However, the performance of the industrial sector was the main cause of the flow of commercial banks' credit to the industrial sector. Conclusion- The study recommends that monetary policy should proceed with extreme caution in managing the exchange rate. The study also recommends that the Central Bank of Afghanistan should encourage commercial banks to offer credit to the industrial sector at low-interest rates. Keywords: Monetary policy shocks, industrial output, Vector Error Correction Model (VECM), Granger Causality Test, Afghanistan. JEL Codes: E52, E32, L60

Long-Run and Short-Run Causality between Government Tax Revenue and Economic Growth in Ghana

Long-Run and Short-Run Causality between Government Tax Revenue and Economic Growth in Ghana

Connexion Between Cryptocurrencies Liquid and Futures Markets: Discernment from Static, Dynamic and Wavelet Approach

The knowledge of the interconnectedness between liquid and futures markets of cryptocurrencies amidst dynamic contemporary environment can be enriched through the full characterization of the direction, persistence and intensity of information flows between these markets. So, the present study attempts to investigate the static and dynamic connexions between liquid and futures markets of Bitcoin, Ethereum, Litecoin, Ripple XRP and Bitcoin Cash from June 2018 to June 2022. The connexion between their liquid and futures markets is first investigated using unconditional correlation, Johansen’s cointegration, vector error correction and Wald’s block exogeneity. Their estimates discern connexions encompassing significant long-run relationships between their liquid and futures markets; momentous unidirectional long-run causality from their futures market to liquid market; and momentous bidirectional short-run causality from their liquid market to futures market and from their futures market to liquid market. The present treatise encompasses methodological advancement in the investigation of interconnectedness between these markets by employing a dynamic conditional correlation model and a wavelet transform framework. Their discerned estimates indicate that the markets of Bitcoin, Litecoin, Ethereum and Bitcoin Cash have only momentous long-run perseverance, lingering and spillover effects of shocks’ sway on conditional correlations. However, there is momentous short- and long-run perseverance, lingering and spillover effects in the case of Ripple XRP. The wavelet coherence analysis also confirms these results by indicating a bidirectional short-run causal relation and a long-run positive comovement between liquid returns and futures returns of these cryptocurrencies. These discernments may help investors, portfolio managers and policymakers to enhance hedging effectiveness through optimal portfolio allocation and monitor financial contagion to attain and sustain financial stability in economies.

Financing Economic Growth and Development in Sub-Saharan Africa (1981–2021)

The aim of this paper is to explore the relationship between financing growth and development using panel data, Auto regressive distributed lag model (ARDL) analysis in 31 selected high income sub-Saharan African countries for the period of 40 years from 1981 to 2021. The sampled countries were based on their average GDP growth rate over the years under study. The study used ex post-facto and analytical research design. The Gross Domestic Per Capita Growth (GDPPCG) served as the dependent variable while Domestic Credit to Private Sector by Banks (DCPSB), Bank Liquidity Reserve to Bank Assets Ratio (BLR) and Gross Domestic Savings (GDS) were used as the independent variables. The inflation rate served as the control variable. Using the bound test proposed by Pesaran, Shin, and Smith in 2001 (and long & short run causality approaches), the long-run association was estimated. The ARDL model's findings show that financial development has a favorable and considerable influence on economic growth in sub-Saharan African high-income nations. The study suggests implementing a financial inclusion approach to increase financial institution accessibility to households, particularly the unbanked in rural areas.

Strengthening TVET in Nigeria to meet the industry 4.0 needs in the changing world of works

The modern workplace had dramatically changed because the nature of work, workforce and work relations had changed; hence, the changes in the needs of industries. The aim of this study was to examine the relationship between Nigerian industries and the factor inputs that formed the needs of industries with keen aim on the Technical and Vocational Education and Training. Using the Central Bank of Nigeria Data, Vector Autoregression was used to test the relationship among the series of yearly output of all industries and the service sector in Nigeria from 1982 to 2021. The Technical and Professional Service subsector was used as one of the independent variables in the service sector. The Johansen Cointegration Test was used to test for convergence and long-term relations between industries and the service sector. The Wald Test was used to test for the significance of coefficients of Technical Services inputs on the Industrial Output. The VAR shows that more than 95% variation in the Industrial Output are explainable by variations in the factor inputs. The pairwise Granger Causality Test was used to test for the short run causality between the industrial output and the factor input. The study found that of Technical and Telecommunication services impacted on the changes in the Industrial Output in in the short run. The study recommended the need for the increase in the funding of TVET institutions, improvement in the quality of TVET training to include soft skills in order to meet the industrial requirements for the changing world of works and increased public – private partnership in order to transfer class training to the field.

Financialization and growth nexus in the EU new member states (NMS): an ARDL bounds testing approach and Granger causality analysis

PurposeThis study aims to explore the short-run and long-run relationships and causality between economic growth and financialization in the new member states (NMS-11) and to provide some policy implications drawn from the empirical findings.Design/methodology/approachThe autoregressive distributed lag (ARDL) bounds test approach to cointegration with the vector error correction model and the cumulative sum of squares (CUSUMQ) test for stability of functions is used between 1995q1 and 2021q4 to examine the existence of cointegration, relationships and causality between economic growth and financialization.FindingsThe findings of the ARDL bounds test demonstrate that the variables included in the models are bound together in the long run, as confirmed by the associated equilibrium correction. The estimated models indicate that the association between selected variables and economic growth is stronger and more statistically significant in the short run compared with the long run. Also, for NMS-11 understudied countries, short-run causality prevails over long-run causality. The changes in the level of financialization have a significant negative effect on the growth rates in the short run, which aligns with findings from previous empirical studies.Originality/valueThis study extends the existing very limited literature about short-run and long-run relationships and causality among economic growth and financialization, including inflation and unemployment variables, to determine their link in the NMS-11. Specifically, the present study reveals that the current level of financialization hampers economic growth and promoting such economic policies further can have adverse effects on the overall economic growth.