Dynamic Error Correction Model Research Articles

Short-term industrial load forecasting based on error correction and hybrid ensemble learning

Accurate industrial load forecasting is a prerequisite for ensuring the smooth operation of the power system. Due to the strong fluctuation and complex characteristics of industrial loads, it is difficult to accurately predict short-term power demand. To address this issue, this paper proposes a deep learning prediction model based on hybrid ensemble and error correction. The proposed model is divided into two phases: in the first phase, deep power features are extracted from multivariate data through a hybrid ensemble strategy consisting of Random Subspace, Boosting, Ensemble Pruning, and Multi-Objective Molecular Dynamics Theory Optimization Algorithm (MMDTOA). First, the strategy splits high-dimensional industrial data into multiple sub-datasets. Subsequently, for the features of each sub-dataset, the proposed MMDTOA is applied to perturb the parameters of GRU to generate base learning machines that balance accuracy and diversity. Finally, these base learning machines are integrated by kernel ridge regression stacking. Among them, the two-stage selection strategy and co-evolutionary strategy are embedded into the MMDTOA to enhance the optimization searching effect; in the second stage, a combined error correction strategy is proposed by utilizing the residual information in the prediction results. By combining the dynamic Gaussian error correction function and GRU error correction model, the prediction accuracy of the ensemble model is further improved; Experimental results on real Korean datasets show that the proposed method achieves a minimum value of 3.684% and 7.266% in NMAE and NRMSE, which outperforms eight comparative models, such as SVM, ELM, and CNN, with higher accuracy and robustness.

Monetary policy, threshold of profitability and dynamics of private investment in the West African Economic and Monetary Union

This study investigates the interactions between optimal monetary policy, investment profitability thresholds, and private sector investment dynamics within the West African Economic and Monetary Union. Analyzing data from 2000 to 2021, it employs advanced econometric models (linear, asymmetric, and threshold effect dynamic panel error correction models) to provide a nuanced understanding of the investment environment in the union. The findings reveal the confluence of low returns and high borrowing costs for private investment. Notably, this study suggests that simply pursuing an expansionary monetary policy does not offer a sufficient solution. Instead, it proposes a more accommodative stance by the Central Bank, featuring lower policy rates, to alleviate the negative impact of high credit costs on private investment and ultimately stimulate economic activity.

The Influence of Bank Health Level with RGEC on Bank Financial Performance

This study aims to analyze the effect of Bank RGEC's health indicators on bank financial performance at commercial banks listed on the Indonesia Stock Exchange (IDX). In this study, a sample of 43 banks was used. The sampling method in this study used a purposive sampling technique. The analysis technique used in this study uses dynamic panel data analysis Error Correction Model. The results of the analysis that has been carried out show that Non Performing Loans (NPL) have a negative and significant effect on bank financial performance (ROA), Good Corporate Governance does not have a significant effect on bank financial performance (ROA), Net Interest Margin (NIM) has a positive influence and significant to the bank's financial performance (ROA), and the Capital Adequacy Ratio (CAR) has no significant effect on the bank's financial performance (ROA).

A Novel Physics‐Aware Machine Learning‐Based Dynamic Error Correction Model for Improving Streamflow Forecast Accuracy

AbstractOccurrences of extreme events, especially floods, have become more frequent and severe in the recent past due to the global impacts of climate change. In this context, possibilities for generating a near‐accurate streamflow forecast at higher lead times, which could be utilized for developing a reliable flood warning system to minimize the effects of extreme events, are highly important. This paper aims to investigate the potential of a novel hybrid modeling framework that couples the random forest algorithm, particle filter, and the HBV model for improving the overall accuracy of forecasts at higher lead times through the dynamic error correction schematic. The new framework simulates an ensemble of streamflow for estimating uncertainty associated with the predictions and is applied across two snow‐fed Himalayan rivers: the Beas River in India and the Sunkoshi River in Nepal. Several statistical indices along with graphical performance indicators were used for assessing the accuracy of the model performance and associated uncertainty. The modeling framework achieved the Nash Sutcliffe Efficiency of 0.94 and 0.98 in calibration and 0.95 and 0.99 in validation for the Beas and Sunkoshi river basin respectively for a 7‐day ahead forecast. Thus, the proposed framework can be considered as a promising tool having reasonably good performance in forecasting streamflow at a higher lead time.

REGULATION OF DYNAMIC PROCESSES IN THE INDICATORS OF DISPROPORTIONS OF UKRAINIAN REGIONS: OPERATIONAL AND LOGISTIC APPROACH

Indicators of socio-economic development of the regions of Ukraine demonstrate a tendency to increase disproportions, which are significantly intensified in the conditions of military operations. In addition to the deterioration of performance indicators, this trend leads to the fragmentation of the country's economic space. Regulation of regional development does not contribute to the reduction of disparities, in particular, due to shortcomings in the assessment, interpretation of indicators of disparities and modeling of their dynamics, which leads to the definition of unrealistic goals of regulation. Taking into account the need to ensure the connection between short-term and long-term planning of regional development, the purpose of the article is to develop theoretical and empirical foundations aimed at regulating dynamic processes in the indicators of regional development disproportions. To achieve the goal, the following tasks were chosen: to analyze the models of convergent-divergent processes of regional development imbalances, to build models of long-term interaction of indicators of imbalances in the spheres of life, to determine the basis for assessing the crisis dynamics of regional indicators. Methodology. To regulate the development of regions, a model of long-term interaction of indicators of disproportions in various spheres has been developed. The process component of the study of dynamic processes in the indicators of regional disproportions and forecasting of crisis situations in the spheres of regional activity, which covers the tasks, tools and main results of the study, has been formed. The paper investigates the long-run interaction of inequality indicators in different areas using econometric dynamic vector autoregressive and error correction models (VAR&ECM). This makes it possible to identify and predict non-stationary impulse processes in general, to identify trends relevant to individual phases of activity, to identify the relationship and interdependence of the trajectory of imbalances. The research tools are designed to solve a set of tasks on the regulation of imbalances. The originality of the article lies in the application of the modeling results in the form of interrelationships of disproportions for different time intervals in the formation of a set of programs and preventive measures to manage regional development disproportions. This also enhances the practical significance of the study. Practical implication. The data obtained as a result of the study of the dynamic processes of disproportion indicators can be taken into account in solving a set of tasks to regulate the disproportions of regional development, developing a set of measures for the implementation of regional strategies, financial and budgetary regulation of regional development, determining budget expenditures for solving problems arising from disproportions.

Asymmetry in Gasoline Price Transmission: How do Fuel Pricing Strategy and the Ethanol Addition Mandate Affect Consumers?

This work aims at verifying the existence of asymmetries in gasoline price transmission between refining, distribution, and gas stations. The analysis covers two moments: before (2006-2016) and after (2016-2020) the new fuel pricing strategy adopted in the refining sector. Before 2016, gasoline prices in refineries were stable due to price intervention. After that, prices fluctuated in convergence with the international market. In this paper, we also consider ethanol prices. Due to an addition mandate, ethanol prices influence gasoline price' dynamics. Our hypothesis is that there are “rocket” and “feather” patterns. This means that positive changes in costs are rapidly and fully transmitted to prices, while negative cost changes tend to be transmitted gradually. As a consequence, there is a cost for consumers. We use Dynamic Ordinary Least Squares estimators and Error Correction Models to test the presence of asymmetries and Cumulative Response Functions to measure consumer cost. Results confirm an asymmetric price transmission and indicate that the new pricing strategy has changed the readjustment dynamic. Although we detect asymmetries in both periods, the new pricing strategy proved to be better for consumers, as social costs decreased after its adoption.

Early human capital: the driving force to economic growth in island economies

PurposeThe paper investigates into the human capital–economic growth nexus by arguing that investment in early education and health helps in achieving higher economic growth. Early investment in human capital matters most for economic growth than the increase in human capital over the years.Design/methodology/approachA dynamic vector error correction model (VECM) together with the impulse response function and variance decomposition are used on data for Mauritius from 1983 to 2019. The paper distinguishes between the short-run and the long-run effects of human capital measured by the pupil–teacher ratio in pre-primary education and life expectancy at birth.FindingsThis study’s findings reveal that investment in early education and health has contributed positively to growth performance. There is evidence for long-run growth effects arising from a positive shock in the education and health indicators.Originality/valueThis paper contributes to both the theoretical and empirical literature on the human capital–growth nexus. Mauritius as a natural resource poor small economy is an important case study as it has started early in investing in its people to promote economic growth.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0674.

Rural credit and agricultural production: Empirical evidence from Brazil

AbstractThis article examines the long‐ and short‐run effects of rural credit on the gross value added of agricultural output in Brazil. We apply the dynamic vector error correction model (VECM) to the estimation and testing. The main finding is that there is a positive long‐run relationship between agricultural sector production and loans from financial institutions to the agricultural sector. The long‐run elasticity estimated was 0.44, implying that an increase of 1% in rural credit leads to a 0.44% increase in the agricultural sector's GDP. This result supports the policy of rural credit as a crucial institutional instrument to strengthen the agricultural sector and as an important factor to boost the country's economic growth.

The Effect of Natural Resources on Economic Growth in West Africa: The Mediating Role of Human Capital Disaggregation

The purpose of this paper is to examine the conditional impacts of natural resources on economic growth through human capital development. This study employs Dynamic Ordinary Least Squares (DOLS) and Vector Error Correction Model (VECM) methodologies in a panel dynamic analysis. The research demonstrates that natural resources and trade openness are the key contributors to lower economic growth. On the other hand, labour force, physical capital, and human capital development measures are effective in boosting growth. Furthermore, the estimates are much higher in the model of tertiary school enrolment (TSE) than in the model of secondary school enrolment (SSE). This means that TSE performs better than SSE in terms of augmenting natural resources to improve growth. From a policy aspect, governments in such nations should devise policies that will improve human capital. The emphasis must be on improving tertiary education quality.

Assessing the impact of technological progress on trade in COMESA: a PVECM approach

PurposeThe present study investigates the extent to which technological progress influences trade in the Common Market for Eastern and Southern Africa (COMESA) region over the period 1990–2017.Design/methodology/approachMethodologically, this study uses a rigorous dynamic analysis namely a dynamic vector error correction model (PVECM) to carry out the proposed investigation. Such a procedure ensures that the dynamic behaviour under consideration is properly captured, while simultaneously catering for causality issues.FindingsThe results show that technological progress has had a positive and significant effect on trade for the sample of countries in the COMESA region over the years of studies. Also, the long-run results show that local investment and economic growth have a positive impact on international trade. Furthermore, the short-run estimates allowed us to make further analysis of the results. For instance, it is observed that trade as well results in technological progress as per the study. Hence, there is reverse causation or bi-directional causality between trade and technological progress.Originality/valueVery few research studies have been conducted on the link between technological progress and trade in a macroeconomy. The analysis thus is believed to supplement the dwarf literature on the technological progress and trade nexus by bringing additional evidence from COMESA.

Does Democracy Reduce Corruption in Indonesia?

This study aims to analyze the long and short-run impact of democracy on corruption in Indonesia. This study used the method of Autoregressive Distributed Lag (ARDL) and dynamic Error Correction Model (ECM) technique during the year of 1995-2020 with secondary data from The Economist Intelligence Unit (EIU), The Global Economy and World Bank’s World Development Indicators (WDI), and Transparency International. The results of the study indicated that democracy has significant effects on the level of corruption only in the long run. In the long run, the results show that the impact of democracy is significant at a 1% significance level and decreases the amount of corruption in Indonesia. A 1% change in democracy and other factors are considered equal, which will change the corruption level by approximately 0.2%. The results imply that political stability associated with democracy will result in the corruption index. In other words, the results suggest that democracy reduces corruption. From a policy point of view, this means that developing democratic institutions should be part of strategies to reduce corruption.

Nexus between export variety and carbon emissions in Pakistan: The role of FDI and technological development

Carbon emissions constitute a large portion of greenhouse gases that are responsible for global warming and climate change. This study examines the impact of export variety on carbon emissions along with foreign direct investment (FDI) and technological development as determinants of environmental degradation in Pakistan. Moreover, this study is conducted in the context of the environmental Kuznets curve hypothesis (EKC). This study applies dynamic ordinary least squares and error correction models for long-term and short-term estimates, respectively. The results indicate that the EKC hypothesis is valid in the long term. This implies that Pakistan’s economy reached the threshold level of income, after which an increase in income was not responsible for environmental degradation. Export variety restrains environmental degradation in the short term and is not a significant factor in the long term. Energy consumption has aggravated environmental degradation, while FDI and technological development are restraining environmental degradation. Policy measures are recommended to curb environmental degradation in Pakistan.

Value-added intellectual capital and financial performance: evidence from Mauritian companies

PurposeThe purpose of this paper is to empirically assess the impact of value-added intellectual capital (VAIC) on the financial performance (FP) of companies in Mauritius.Design/methodology/approachThe research uses a dynamic panel vector error correction model (PVECM) which simultaneously allows for endogeneity and causality issues among the variables used.FindingsThe results show that VAIC enhances corporate FP, with a reported lower effect in the short run as compared to the long run. Other important determinants of firm’s performance are asset turnover, capital turnover and firm’s size. Leverage, on the other hand, is observed to be performance reducing in nature. FP of the companies is also a significant determinant of VAIC, implying reverse causal effects exist between the two variables of interest, namely, VAIC and FP.Research limitations/implicationsThe study can be enhanced by doing an industry-specific comparison of the impact of VAIC on FP for more insights.Practical implicationsIt is recommended that managers pay more attention to the role of firms’ stock of tangible and intangible assets, as this has a positive impact on firms’ FP. Also, the results may help to increase awareness of the importance of effective intellectual capital (IC) management within an organization. More so, as demonstrated by Ståhle et al. (2011), VAIC indicates the efficiency of the company’s labor and capital investments within firms in Mauritius. This study may, therefore, enable Mauritian firms to measure their IC efficiency and develop policies to promote and improve upon their intellectual potential to enhance firm’s performance.Originality/valueThe main theoretical contribution of this paper relates to the assessment and conceptualization of the bi-directional relationship between VAIC and FP. It confirmed that there are self-reinforcing feedback effects between VAIC and FP. Methodologically speaking, this paper investigates the VAIC–FP nexus in a dynamic setting using a dynamic panel data framework, namely, a PVECM which also allows for additional insights into the short- and long-run effects.

Tax Revenue and Socio-economic Performance in Nigeria

The study examined the effect of tax revenue on socio-economic performance in Nigeria between 1981 and 2020, the primary purpose of this study was to examine the effect of tax revenues on the socio-economic performance of Nigeria. The expo-factor research design was adopted for this study and the analysis was carried out using descriptive and broad econometric techniques. The analysis started with exploring the trends in each variable using line graphs after which descriptive statistics were used. Both the Autoregressive Distributive Lag (ARDL) and Dynamic Error-Correction Model (ECM) econometric models were estimated. Other relevant pre-estimation diagnostic tests (normality, serial correction, heteroscedasticity and unit roots) were satisfactory. Succinctly, the study found that tax revenue from Customs and Excise Duties (CED) showed a positive and significant influence on basic school enrolment and life sustenance. Also, current period company income tax revealed a negative influence on basic school enrolment but positive on life sustenance. Whereas, petroleum profit tax exhibited a positive influence on life sustenance and basic school enrolment. The study also confirms the existence of long-run relationship among the variables. Therefore, we conclude that the selected tax revenue components examined have the potential to spur a considerable improvement in socio-economic indicators of Nigeria. Consequently, the study put forward that the government should improve on channeling tax revenue receipts towards improvement in livelihood and the overall socio-economic condition of the Nigeria economy.

Determining the Twin Deficits Phenomenon in Kenya

Aims: This study examines whether the long-run relationship between fiscal and current deficits follows the tenets of twin-deficits, the Ricardian equivalence, the current account targeting, or the feedback linkages. It further reviews the effects of fiscal and current account deficits on economic growth. These have in recent years been debated both in developed and developing countries. In contributing to this ongoing debate, the authors applied unit root tests, cointegration analysis, a dynamic vector error correction model and Toda-Yamamoto Granger-causality representation using annual time series data from 1980 to 2016.
 Study Design: The study employs quantitative time-series research design by utilizing Stata econometrics software.
 Place and Duration of Study: Sample: Kenya, from 1980 to 2016.
 Methodology: The study employs unit root tests, Johansen (1995) co-integration analysis, a dynamic vector error correction model and a multivariate Toda-Yamamoto (1995) Granger-causality representation.
 Results: The paper provides evidence of unidirectional causality running from fiscal deficit to current account deficit in support of the twin-deficits phenomenon for Kenya. There is evidence that in the long-run fiscal deficits has significant negative effects while current account deficits had significant positive effects, on economic growth in Kenya. 
 Conclusion: Overall, the study concludes that the twin-deficits phenomenon fits for Kenya. The findings imply that the authorities need to pay more attention and promote policies that improve investment efficiency arising from these deficits. Importantly, some of the key policy implications include promotion of policies that upscale fiscal discipline and reduce the size of fiscal deficits for external stability and long-term economic growth, in Kenya.

The Effects of Current Account Deficits on Economic Growth: Evidence from Kenya

The study examines the effects of current account deficits on economic growth. It also evaluates the direction of causality between the current account deficits and economic growth. These have in the recent past been analyzed in developed and developing economies. In contributing to this ongoing debate, the study applied unit root tests, cointegration analysis, a dynamic vector error correction model and Toda-Yamamoto Granger-causality representation using annual time series data for Kenya from 1980 to 2016. There is evidence that in the long run, current account deficit has significant positive effect on economic growth in Kenya. The evidence suggests a bidirectional causality running from current account deficit to economic growth with feedback effects. The study underscores the need for the authorities to utilize current account deficits to strictly finance public investment to foster gross fixed capital formation, for shared prosperity in Kenya. The evidence underscores the need for more country specific studies in sub-Saharan Africa.

The Effects of Primary Budget Deficits on Economic Growth: Evidence from Kenya

Aims: The paper attempts to examine the effects of primary budget deficits on economic growth. It reviews the nature and direction of causality between primary budget deficit and economic growth. In the recent years, these have been debated both in developed and developing countries. In contributing to this ongoing debate, the study analyzes the case for Kenya from 1980 to 2016. The evidence is intended to provide policy insights for macroeconomic stability and sustained economic growth for shared prosperity in Kenya.
 Study Design: The study employs quantitative time-series research design by utilizing Stata econometrics software.
 Place and Duration of Study: Sample: Evidence from Kenya, from 1980 to 2016.
 Methodology: The study employs unit root tests, Johansen cointegration analysis, a dynamic vector error correction model and a multivariate Toda-Yamamoto Granger-causality representation.
 Results: The findings establish that the primary budget deficit, gross fixed capital formation, real interest rate, terms of trade, inflation growth and financial innovation have significant effects on GDP per capita growth in Kenya. Primary budget deficit has a strong and significant effect on GDP per capita growth both in short-run and long run. In the short-run, the results revealed that the primary budget deficit had a positive effect on economic growth which turned negative in the long-run. There was a unidirectional causality running from primary budget deficit to economic growth. 
 Conclusion: The study concludes that both in the short run and long run, primary budget deficit has strong and significant causal effects on economic growth in Kenya. The evidence underscores the need for the authorities to reduce high primary budget deficits, interest payments and domestic borrowings and strictly apply the golden rule of public finances to boost long term inclusive growth, in Kenya.

IMPACT OF CAPITAL STRUCTURE ON THE PERFORMANCE OF QUOTED INSURANCE FIRMS IN NIGERIA

Evidence from the past studies revealed that capital structure has an impact on the firm performance. This research appraises the impact of capital structure on the performance of quoted life insurance companies in Nigeria from 2010 to 2019. The researchers used the panel cointegration model, autoregressive dynamic lag error correction model and pair wise granger causality test to measure the relationship among the variables. The study revealed that capital structure and firm performance has a long-run relationshipand 81% long run disequilibrium is corrected within a year. It was also apparent that there is a significant short run relationship between liquidity of life insurance and return on asset. The Granger causality outcome also shows that bidirectional causality exists between firm size (SIZE) and profitability (ROA) in the short run. We conclude that a large size of life insurance firm has more scope to make more profit in Nigeria context within the study period. The study recommended that to maximize firm’s performance managers must endeavor to obtain and maintain an optimum capital structure level among others.

Banking Sector Intermediation Development and Economic Growth: Evidence from Nigeria

ABSTRACT In developing economies, banks act as a conduit for the efficient mobilization of financial resources from the surplus sectors for effective allocation to the deficit sectors for productive investment that will in turn lead to economic growth. Thus, the study is aimed at evaluating whether development in the banking sector intermediation process in the form of an increase in the number of branches, credit to private sectors, intermediation efficiency and total assets stimulated economic growth in Nigeria during the period 1987⎯2018. The study employed the Johansen cointegration test, dynamic ordinary least square regression and error correction model in determining the relationship between the variables. The results of the cointegration test confirmed the existence of a long-run relationship between banking sector development indicators and economic growth in Nigeria; whereas in the short-run only number of bank branches and bank’s total assets have a positive and significant impact on economic growth, signifying that much of Nigeria’s superior growth performance is attributed to an increase in the number of bank branches and growth in the bank’s total assets. Going by the above findings, the study recommends that the Central Bank of Nigeria should monitor the activities of Commercial Banks in terms of branch distribution to ensure a wider spread and even distribution and also review the asset base of banks from time to time so as to measure up to international standards in order to increase investment and economic growth.

Carbon Emissions in the SAARC Countries with Causal Effects of FDI, Economic Growth and Other Economic Factors: Evidence from Dynamic Simultaneous Equation Models.

South Asian Association for Regional Cooperation (SAARC) countries like other developing countries are the major destination for foreign investors. At the same time, these countries are facing different climate change challenges. This study aims to inspect the economic determinants of carbon emissions (CE) and dynamic causal interaction of CE with foreign direct investment (FDI), economic growth (EG), and other economic factors using panel cointegration test, dynamic ordinary least squares (DOLS) and vector error correction model (VECM) for the SAARC countries. To make the homogenous analysis, we examined the association among variables for the individual country and as a group for the period 1990 to 2016. The panel results of this study confirmed the presence of the unidirectional causal association of EG with CE. The panel results of other economic factors confirmed the causality of urban population (UP) and energy consumption (EC) with CE. Moreover, the panel results of domestic capital (DS) and inflation rate (INF) confirmed the causal association with EG. Finally, the panel results of DS revealed a causality with FDI. Based on the above results, some policy guidelines are proposed.