Vector Autoregression Techniques Research Articles

Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Africa's gold exploration

South African gold mining is one of the main contributors to the country's economic growth and employment creation. Assessment of future gold production is pivotal for positioning the country's supply security and contribution to the projected global demand. In this study, we modelled and forecasted South African and global gold production trends (1990–2022) using the Autoregressive Integrated Moving Average (ARIMA), Vector Autoregressive (VAR), and Autoregressive Neural Network (ARNN) techniques. The study also evaluated the impact of annual productions on the collated reserves (2008–2021) and the contribution of resource–reserve conversion in sustaining gold reserves within the South African goldfields. The ARIMA (1,1,0) model, based on root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), outperformed both ARNN (1,1) and VAR (2) methods. The forecast of the ARIMA model showed an increase in South Africa's gold production, with a compounded annual growth rate (CAGR) of ∼0.6%. The model also predicted an increase in global gold production, with CAGR of ∼2.2%. The analyses of reserves–production trends showed that most South African mining companies have been depleting their gold reserves due to production and were minimally converting resources to reserves, averaging at ∼2%/year from 2017 till present. The minimal conversion may also reflect the challenging mining conditions (such as mining depths and underground flooding) and the mining industry's socio-political dynamics. We demonstrated that, if the resource–reserve conversion factor is maintained (at ∼2%/year and above), the forecasted production may sustain the current reserves (at > 2000 t Au excluding tailings) but deplete ∼27 % of the resources to reserves by 2040. However, if the conversion factor continues to decline (to <1 %), the forecasted gold production will reduce the reserves to < 500 t Au with ∼3% of the resources converted to reserves.

Short-term effects of productive credit, savings and money demand on Ecuador’s economic growth, 2006–2020

PurposeThis paper aims to determine causal relationships between the level of productive credit, real deposits and money demand – all of them in real terms – and Gross National Product between 2006 and 2020.Design/methodology/approachThe vector autoregressive technique (VAR) was used, where data from real macroeconomic aggregates published by the Central Bank of Ecuador (BCE) are correlated, such as productive credit, gross domestic product (GDP) per capita, deposits and money demand.FindingsThe results indicate that there is no causal relationship, in the Granger sense, between GDP and financial activity, but there is between the growth rate of real money demand per capita and the growth rate of total real deposits per capita.Originality/valueThe study shows that bank credit mainly finances the operations of current assets and/or liabilities. In addition, economic agents use the banking system mainly to carry out transactional and precautionary activities.

International emigration and economic complexity: Evidence from the dynamic GMM panel VAR approach

For over a decade, developing nations have used foreign direct investment and trade to access advanced economies’ technology and knowledge. However, the role of emigrants in promoting the productive capacity of their home countries through the diffusion of knowledge and novel technologies has been relatively overlooked. The present study investigated the relationship between emigration stock and productive knowledge embedded in their origin economy, as measured by the Economic Complexity Index (ECI). The study applied a GMM Panel Vector Autoregressive (PVAR) technique to 86 non-high-income countries between 1995 and 2020. In principle, the PVAR model findings indicated that international emigrants promoted the level of technology and knowledge in their home countries. Further causality analyses revealed that within all countries, there was unidirectional causality from emigration to the ECI. However, a bidirectional relationship existed between the two variables in countries with low education levels. Developing countries should consider the opportunities emigrants offer when planning their development strategies.

Foreign Exchange Market Pressure, Exchange Rate and Trade Balance in Nigeria: Is There Evidence of the J-Curve Effect?

The paper examined the relationship between the pressure in the exchange market, exchange rate, and trade balance in Nigeria to ascertain whether or not the J-Curve effects exist. The investigation was anchored on the Marshal-Lerner and the J-Curve theories using annual time series data from 1986 to 2021. The Structural Vector Autoregressive (SVAR) technique was employed, and the findings revealed that the pressure in the exchange market exerts a strong contemporaneous positive effect on the exchange rate in the country. Also, the findings showed that the exchange rate has a strong contemporaneous negative effect on the trade balance. Furthermore, the long-run results indicated that the exchange rate has a positive but weak effect on the country’s trade balance. Based on these findings, it was concluded that the relationship that exists among foreign exchange market pressure, exchange rate, and balance of trade suggests the potentiality of the J-Curve effects in the economy. The study recommended that local production of goods and services in Nigeria should be strengthened so that the depreciation of the naira would improve the trade balance. In the event of naira depreciation, domestic consumers could redirect their demand to the consumption of locally produced goods and services. Also, local production, especially in manufacturing and agricultural processing, should be encouraged, and the quality of the products be enhanced for competitive exportation to improve the trade balance in the country. The policy implication is that policymakers can leverage naira depreciation as a policy tool to enhance Nigeria’s balance of trade.

Carbon conundrums: Geopolitical clashes and market mayhem in the race for sustainability

This research presents an in-depth investigation into the dynamic correlation between geopolitical conflicts and carbon markets utilizing the Time-Varying Parameter Vector Autoregression (TVP-VAR) technique. The analysis focuses on the interconnectedness between the Geopolitical Risk Index Daily (GPRD) and vital carbon pricing instruments, specifically the Intercontinental Exchange Endex European Union Allowance (ECEFDC), KraneShares California Carbon Allowance Strat ETF (KCCAK), Shanghai Environment and Energy Exchange China Emission Allowances Online Transactions (SAXCEA), and S&P Global Ex-Japan LargeMidCap Carbon Efficient Index (SPGJ). The daily fluctuations were traced from May 2021 to July 2023. The analysis is divided into short- and long-term connectedness, with particular emphasis on the impact of the Russia-Ukraine conflict on the GPRD's spillover on carbon markets. The short-term connectedness (1–5 days) between GPRD and ECEFDC shows variability, fluctuating between 10% and 40%. Conversely, long-term connectedness exhibited a significant increase during the conflict, peaking at approximately 34% by mid-2022. The analysis of the Total Dynamic Connectedness (TCI) between the GPRD and the KCCAK indicates comparable magnitudes, although with minor initial discrepancies. The short-term connectedness of GPRD and KCCAK decreases from its peak of approximately 10% to approximately 1%. Conversely, long-term connectedness varies between approximately 32% and 2% from May 2022 onwards. The long-term connectedness between GPRD and SAXCEA revealed variable patterns, peaking at around 18% at the beginning of the sample period and rapidly reducing to around 1% within two months. The analysis of the connectedness between GPRD and the SPG) identifies intense fluctuations in both TCI and long-term connectedness. After an initial increase and decrease, these patterns rebound and experience another increase. This research provides significant insights into the complex dynamics of geopolitical conflicts and carbon markets, particularly the impact of the Russia-Ukraine conflict on carbon market behavior.

The impact of COVID-19 on sovereign contagion

In the midst of the unprecedented COVID-19 pandemic crisis, the scope of the current study is to outline the channels of shock propagation across sovereigns under these unprecedent conditions. We use a sample of European countries for a period of twelve years that encompasses the COVID-19 as well as the turbulent period of the European debt crisis. We apply Bayesian Vector Autoregressive techniques to show a dramatic increase in sovereign contagion during the outbreak of the COVID-19 pandemic, even higher than the increase recorded during the European Debt crisis. The result works through government response and containment measures. Extensive and severe detachment from any financial fundamentals is evident. The announcements of fiscal and monetary easing measures have eliminated the tension in the markets. When focusing on the period of the pandemic the impact of the national culture emerges through the channel of collectivism.

Investigating the impulse responses of renewable energy in the context of China: A Bayesian VAR Approach

This study applies a Bayesian Vector Auto Regression (VAR) technique to investigate the impulse responses (IR) of renewable energy (RE) on different macroeconomic variables, i.e., green finance (GF), investment in energy with private participation (IEPP), gross domestic product growth rate (GDPG), and foreign direct investment (FDI), in the context of China by using data from the years 2001–2020. Data normality and stationarity are validated before checking the VAR stability condition. The IR function captures the direct and reverse responses of RE with the shift of stipulated variables. Subsequently, it reveals the causal relationship between RE and the considered variables. The results are: (i) RE and GF are strongly endogenous, whereas IEPP and GDPG are weakly endogenous, and FDI is least endogenous; (ii) the response of RE is positive to GF and negative to FDI, IEPP, and GDPG. The reverse responses are quite similar except for IEPP, and (ⅲ) shocks from GF, GDPG, and FDI lead to more variability in RE than RE itself. Ultimately, it indicates RE's share in total energy output increases with the boost of GF and decreases with the amplification of FDI, IEPP, and GDPG. Inversely, RE's contribution boosts with the short-term increase in IEPP.

Does trade protection undercut the green efficiency of the marine economy? A case study

The development of the marine economy is closely related to trade openness. But does trade openness promote sustainable development of the marine economy? To understand the impact of trade openness on marine economy sustainable, this study examines the impact of trade openness on the green efficiency of marine economy. To this end, the green efficiency of the marine economy of 11 coastal provincial regions of China is measured by the undesired super-efficiency SBM technique, to examine the impact of trade openness on green efficiency of marine economy using a panel vector autoregressive technique from a perspective of North-South regional differences. The results show (i) the overall green efficiency of marine economy in China’s coastal areas needs to be improved, and a spatial distribution pattern is weak in the north and strong in the south; (ii) trade openness emerges as a positive factor contributing to the green efficiency of marine economy. It is evident that enhancing the level of trade openness is a pivotal pathway for promoting environmentally sustainable development in the maritime sector. Furthermore, it is noteworthy that the stimulatory effect of trade openness exhibits significant regional disparities, with its impact being notably stronger in the southern coastal areas compared to the northern ones; (iii) the development level of the marine economy and the structure of the marine industry exert negative influences on the green efficiency of marine economy; (iv) bidirectional causal relationships are observed between the green efficiency of marine economy and three crucial variables, namely, trade openness, marine economic development level, and marine industry structure. In light of the aforementioned results, this study adopts a regional disparity perspective to offer practical recommendations for advancing the green development of marine economies in emerging nations such as China.

Dynamic Effects of External Shocks on Current Account Imbalances in the MENA Countries: A Structural VAR (SVAR) Analysis

In this paper, we tried to contribute to the previous literature by analyzing the effect of external and domestic shocks on the current account balance. Using a Structural vector autoregression (SVAR) technique, we specifically examine the effect of external and domestic shocks on the current account balance considering the case of the MENA region during the period 1970 to 2019. Our results indicate that the oil shock leads to a deterioration of the current account and a depreciation of the terms of trade while its impact in terms of growth is significant but more attenuated. For oil-importing countries, the magnitude of current account responses to shocks is much smaller on average than for oil-exporting countries. Our findings have important policy implications, especially in light of discussions in recent years about whether current account surplus countries impede growth abroad. Thus, the most important policy implication of this paper is that different channels would be used by economic policymakers to control the current account deficit.

An Analysis of the Effect of Naira Devaluation on Nigerian Balance Of Trade

This study investigates the effect of naira devaluation on Nigerian balance of trade using time series data from 1986 to 2021. The study examined the long run and short-run equilibrium relationship between devaluation and trade balance over the study period. The study used unrestricted Vector Auto Regression (VAR), Co-integration and Vector Error Correction Mechanism (VECM) technique in the analysis of data. The variables currency devaluation (CDV), Export rate (EXPT), Import rate (IMPT) and Trade balance are found to be 1(1) variables, while Interest rate (INTR) is found to be 1(0) variables. Based on the VAR Co- integration test result, it indicates long-run equilibrium relationship among the variables. The error correction term was correctly signed and statistically significant. The estimates from the VAR model showed both positive and negative shocks running from naira devaluation to trade balance, export rate, import rate and currency devaluation based on the past and current values. The study concluded that, naira devaluation have positive and significant impact on trade balance of Nigeria. The study recommended that, Government should improve this indigenous innovation to meet up with international standard as a means to reduce dependence on import and encourage production of competitive goods and services, as export becomes cheaper after devaluation, it is expected that Nigeria as a country will immensely improve on its exported goods and increase the output of exportable goods which will leads to favorable balance of trade among others.

Dynamic interrelations between environmental innovations, human capital, and energy security in Vietnam: new evidence from an extended TVP-VAR approach.

This study employs an extended joint connectedness approach, as well as a time-varying parameter vector autoregression technique (ETVP-VAR), to characterize the interrelationships among six factors, namely, renewable energy, environmental innovations (EI), gross domestic product (GDP), human capital, energy consumption, and energy productivity (EP), from 1995 to 2019 in Vietnam. Taking a holistic view, it appears that both energy consumption and GDP are net recipients of contagion shocks. In addition, renewable energy, as well as environmental innovations, is critical net transmitters during our studied period. From 1995 to 2003, human capital constantly acted as a crucial net shock absorber before switching to a crucial net transmitter after that year. With a significant exception around 1997, this variable is mostly a shock transmitter when it comes to energy production. Pairwise connectedness reveals that renewable energy consistently appears as a shock transmitter to GDP, human capital, energy consumption, and energy productivity. That being said, environmental innovations consistently contribute to renewable and green energy volatility by transmitting shocks from other markets.

An Exploration of Interlinkages between International Trades and Green Energy Volatility over Quantiles

In this paper, we employ the quantile vector autoregression (QVAR) technique to determine the degree of connectedness between seven variables from 1985 to 2019 for the purpose of examining the relationships between the Trade market and Green energy consumption. Based on our findings, dynamic connectedness, which is 24.18% in the short term and 9% in the long term, is influenced by both long-term and short-term periods. Based on the dynamic net total connectedness of a quantile, a quantile of 50% describes the period’s overall connectedness, which is associated both with highly positive changes (above the 80% quantile) and with highly volatile variables (below the 20% quantile) of export, import, and green energy consumption. In both durations, export and import values turn into a net shock transmitter, and green energy consumption acts like a net shock receiver since the last half of the period. In 2008, uncertain events were correlated with dynamic net pairwise directional connectedness over a quantile, such as the Global Financial crisis, have an influence on the trade market and green energy consumption’s volatility.

Do geopolitical risks and global market factors influence the dynamic dependence among regional sustainable investments and major commodities?

This paper uses the Quantile Vector-Autoregressive (Q-VAR) technique to examine the connectedness between three regional (North America, Europe and Asia-Pacific) sustainability indices and major natural resource commodities including energy commodities (crude oil and natural gas), precious metals (gold, silver, and platinum), and industrial metals (steel, aluminium, and copper). It also uses a linear regression model to investigate the macroeconomic and geopolitical factors that drive the connectedness among these investments. The QVAR results reveal asymmetric connectedness among these investment indices, with the levels of total connectedness during extreme downside and upside market conditions being significantly stronger than the level of connectedness during normal market condition. The results also show that, on average, the amount of shocks the regional sustainable investment indices each received from the studied energy and metal commodity markets are higher (lower) than what they transmit to the commodity market during the extreme upside (downside) market condition. During the normal market condition, however, only the Asian Pacific sustainable investment receives more shock than it transmits to the studied commodity market indices, making a net shock receiver. Finally, geopolitical risks, business environment conditions, gold and fixed income markets and economic policy uncertainty are important predictors of return connectedness, although the predictive strength and direction vary across market conditions. We discuss the implications of our findings.

The macroeconomic effects of oil price uncertainty

We study the impact of oil price uncertainty (OPU) on macroeconomic activity. We construct a new measure of OPU by extracting information on oil markets from 50 newspapers around the world using textual analysis techniques. Our index spikes around important historical events, such as the oil price shock of the 1970s and the supply glut of the 1980s. The effects of OPU on macroeconomic activity are captured using Bayesian vector autoregressive techniques. OPU is an important source of macroeconomic fluctuations in the US, with industrial production displaying a maximum estimated drop of 0.34% almost 10 months after impact. These negative effects are sharpened when monetary policy is constrained by the Zero-Lower Bound. OPU exerts an economically meaningful impact on global economic conditions and affects economic activity in other industrialized countries.

FINANCIAL INCLUSION IMPLICATIONS ON THE LIQUIDITY OF THE NIGERIAN CAPITAL MARKET

The objective of this study was to examine the implications of financial inclusion on capital market liquidity in Nigeria. Therefore, we applied Vector Autoregression (VAR) technique to the analysis of the quarterly time series data obtained from Central Bank of Nigeria’s statistical bulletin and World Development Indicators for the period, 2008Q1 to 2018Q4. Findings of this study reveal that deposit penetration, bank penetration and credit penetration have positive but non-significant impact on stock market turnover ratio in Nigeria. Furthermore, unlike deposit penetration which exerts negative and non-significant influence on the value of shares traded ratio; bank penetration and credit penetration have positive but non-significant impact on the value of shares traded ratio in Nigeria. The study posits that financial inclusion exerts no significant influence/implications on stock market liquidity in Nigeria with a very negligible variation in the latter (stock market liquidity) explained by the former (financial inclusion). It is therefore recommended that accounts and bank penetrations should be re-engineered towards their translations to high volume and value of capital market transactions rather than mere financial penetration without any capital market implications in Nigeria.

Productivity and Exports: An Industry-Level Analysis of the Service Sector in India

The large share of the service sector and its status as a net exporter raise concerns about the sustainability of such growth for a developing economy like India. Given the context, the present article attempts to examine the productivity dynamics of the service sector in India at the industry level. We use the India KLEMS dataset to identify the trends in total factor productivity (TFP) growth and the growth in factor inputs. By uniquely combining the India KLEMS dataset with the trade values in the Extended Balance of Payments Services classification, we examine the dynamics between TFP growth and exports of services using panel vector autoregression technique. The trends in factor inputs show that there is capital deepening within services and the growth in employment remained comparatively lower. The results indicate a feedback effect of exports and productivity growth within the service sector. Additionally, we note that the use of more skilled labour that is better equipped to handle new technology also contributes to growth in the service sector, both in terms of productivity and exports.

An Empirical Analysis of the Effects of Chinese Government Fiscal Policy on GDP Growth based on data frequency

This paper offers an empirical analysis of the effects of fiscal policy on economic growth. We use vector auto regression technique（VAR-SVAR）to distinguish stabilizing，discretionary and promoting effects of government fiscal variables in China on its GDP growth based on data frequency. The variables used here are government expenditure, tax revenue, and GDP, and the index for all these variables are monthly, quarterly and annually time series data, among them annually data covering the period of 1952 to 2022 and monthly, quarterly data covering from 1998-1 to 2022-4. The empirical results indicate that the effects of Chinese government fiscal policy do exist and the GDP growth systematically react to the changes of these fiscal variables. But the effects based on monthly, quarterly data and annually data are different especially on promoting effect, this is something should be studied further more.

Medium- and Long-Term Prediction of Polar Motion Using Weighted Least Squares Extrapolation and Vector Autoregressive Modeling

ABSTRACT This article presents the application of weighted least squares (WLS) extrapolation and vector autoregressive (VAR) modeling in polar motion prediction. A piecewise weighting function is developed for the least squares (LS) adjustment in consideration of the effect of intervals between observation and prediction epochs on WLS extrapolation. Furthermore, the VAR technique is used to simultaneously model and predict the residuals of x p, y p pole coordinates for WLS misfit. The simultaneous predictions of x p, y p pole coordinates are subsequently computed by the combination of WLS extrapolation of harmonic models for the linear trend, Chandler and annual wobbles, and VAR stochastic prediction of the residuals (WLS+VAR). The 365-day-ahead x p, y p predictions are compared with those generated by LS extrapolation+univariate AR prediction and LS extrapolation+VAR modeling. It is shown that the x p, y p predictions based on WLS+VAR taking into consideration both the interval effect and correlation between x p and y p outperform those generated by two others. The accuracies of the x p predictions are 13.97 mas, 18.47 mas, and 20.52 mas, respectively for the 150-, 270-, and 365-day horizon in terms of the mean absolute error statistics, 36%, 24.8%, and 33.5% higher than LS+AR, respectively. For the y p predictions, the 150-, 270-, and 365-day accuracies are 15.41 mas, 21.17 mas, and 21.82 mas respectively, 27.4%, 11.9%, and 21.8% higher than LS+AR respectively. Moreover, the absolute differences of the WLS+VAR predictions and observations are smaller than the differences from LS+VAR and LS+AR, which is practically important to practical and scientific users, although the improvement in accuracies is no more than 10% relative to LS+VAR. The further comparison with the predictions submitted to the 1st Earth Orientation Parameters Prediction Comparison Campaign (1st EOP PCC) shows that while the accuracy of the predictions within 30 days is comparable with that by the most accurate prediction techniques including neural networks and LS+AR participating in the campaign for x p, y p pole coordinates, the accuracy of the predictions up to 365 days into the future are better than accuracies by the other techniques except best LS+AR used in the EOP PCC. It is therefore concluded that the medium- and long-term prediction accuracy of polar motion can be improved by modeling x p, y p pole coordinates together.

Anaysis of Interest Rate Spread, Financial Development and Foreign Capital Inflow Nexus in Nigeria

ABSTRACT: The world has gone through various economic crises in the past century, and their effects have had varying implications on the economies of countries all over the world. In a bid to help stabilise economies all over the world, various measures have been put in place. Some of these measures include regulations and policies by the Bretton Woods institutions (World Bank and International Monetary Fund) and their agencies. The idea behind these measures is to ensure sustainable growth and development among member states and other countries of the world. Some of these policies include the privatization and liberalization policies of the Bretton Woods institutions as well as other policies bordering on such economic and social benefits for people all over the world. The Nigerian economy in our contemporary time can be described as passing through a rather 'volatile' phase with respect to interest rate, financial development and foreign capital inflow. Thus, this study investigated the impact of interest rate spread and financial development on foreign capital inflow in Nigeria. Several studies have been carried out using different methodologies, such as; co-integration equation, multivariate vector auto regressive (VAR) model and vector error correction technique. Each methodology used was in line with the objective of the research in question. However, to achieve its objective, this paper adopted the Classical Linear Regression Model. The results of the study showed that financial development has a positive impact on foreign capital inflow, while interest rate spread on the other hand, was also found to have a positive impact on foreign capital inflow. Other control variables such as market capitalization and treasury bills rate were also found to positively affect foreign capital inflow, while the all share index had a negative impact on foreign capital inflow. Some economists have opined that the Nigerian economy is currently going through a phase of recession. In order for large scale investments to be made within the country, there is a need for foreign participants to be attracted to the Nigerian economy and pull their resources, both financial and non-financial into the country (but, not without regulation). However, for these investors to have confidence to make investments in the Nigerian economy, there has to be a high degree of economic stability in the country. This can be supported by enacting and implementing policies that can enhance the quality of interest rates spread and financial development within the country. The policy implication here involves enhancing financial development through sound policies and adopting competitive interest rates, could increase the rate of foreign inflow into the economy. In view of this, it is also recommended that government policies should target interest rate competitiveness, financial and economic development as well as sustainability.

Did raising doing business scores boost GDP?

We use the time series variation in the World Bank’s “distance to frontier” estimates of the ease of doing business to assess the effects of changes in this variable on real GDP per capita. The use of Vector Autoregression techniques allows us to identify shocks to the Doing Business scores that are initially uncorrelated with GDP, thus addressing an important endogeneity problem that affects the cross-sectional literature on this topic. We report a robust finding that improvements in Doing Business scores have at least a temporary negative impact on GDP and find little evidence for a positive effect in the years following these improvements.