Short-run Estimates Research Articles

Poverty Reduction and Economic Development in Nigeria

Extant literature shows that the incidence of poverty is one of the biggest threats to human development, however, not many studies have acknowledged the important role of financial development and access to internet services in reducing the incidence of poverty to enhance economic development. Therefore, this study examined the relationship between poverty reduction and economic development in Nigeria using data for the period of 2003Q1 to 2019Q4. The data for this study is collected from the United Nations Human Development Reports and the World Bank’s World Development Indicators Database. Using the Autoregressive Distributed Lag Model-Error Correction Modelling (ARDL-ECM) estimator, the results of the ARDL long-run estimates showed that poverty reduction, financial development, economic growth, trade openness, and the internet had positive and significant effects on human development. Furthermore, urbanisation had a negative but non-significant effect on human development, indicating a negative coefficient and exact p-value of 0.064735 and 0.8221. Meanwhile, the results of the ARDL short-run estimates except for urbanisation are consistent with the long-run results. Besides, the Error Correction Model (ECM), which indicates the speed of adjustment back to long-run equilibrium level after a short-run disturbance, showed a coefficient which is negative (-0.145327) and significant at 1% level of significance, implying that about 15% of any disequilibrium in the short-run is adjusted back to the long-run equilibrium in each quarter. Based on the long-run estimates, the study concludes that poverty reduction is important for economic development in Nigeria. It is, therefore, recommended that the poverty reduction strategies of the Nigerian government should not be pursued in isolation but rather in connection with access to financial and internet services, among other things.

PUBLIC EXPENDITURE FOR AGRICULTURAL DEVELOPMENT & THE ECONOMIC GROWTH OF BIHAR (1981- 2019)

This study explores the relationship between public expenditure on the agricultural sector and economic growth in the agriculturally underdeveloped states of Bihar over the period 1981-2019. In estimating the longrun model, first, the time series characteristic of the data is tested using ADF and the PhillipsPerron tests. Then, the Johansen cointegration test was conducted. Both The longrun and shortrun estimate result shows that public spending on the agricultural sector has a significant effect on the per capita real GDP. This study revealed that government spending on the agricultural sector has an insignificant effect both in the longrun and shortrun periods. While agriculture is the dominant sector and the majority of rural society is engaged in this sector, hence it needs to reduce unproductive government consumption expenditure and give attention to redirecting to productive activities. This will stimulate activities in the economic sectors and, perhaps, converse the insignificant effect on economic growth. The gross fixed capital formation has a positive and significant impact on per capita real GDP in Bihar during the period under review. This result seems to imply that the government should have to build up capital stock by the accumulation of capital formation regularly to improve the per capita real GDP. The labor force has an insignificant effect on the growth of per capita real GDP. Hence, improving the productivity of the labor force through technical and vocational training should have to be a prominent task.

Education and economic growth in a developing country

Quality education is one of the 17 United Nations Sustainable Development Goals (SDGs) for its 2030 vision to 'transform the world'. It is assumed that, investment in inclusive and equitable quality education opens economic opportunities for all and has a long-term positive impact on economic growth. This paper thus examines the impact of education on economic growth in Togo, a developing country, using the autoregressive distributed lag (ARDL) error correction model (ECM) estimation method on time series data from 1971 to 2018. Results of the short-run estimations show a significant positive relationship between education and GDP per capita. However, long-run estimations results show a negative relationship between education and GDP per capita growth. Thus, the study recommends governments to increase investment in education in the short term.

Does Financial Development Advanced Environmental Quality in Thailand: Evidenced from ARDL

This study investigates the long-term effects of financial-sector development, energy consumption, and economic growth on Thailand's carbon emission from 1970 to 2018. Firstly, use the conventional unit-root test, augmented Dickey-Fuller root (ADF), and (PP) Phillips-Perron unit root tests to confirm stationarity of variables. Later, Autoregressive Distributive lag (ARDL) test used to examine the cointegration level with long and short-run estimates. ARDL bound test verifies that there exists a long-run association among the model. Empirical results indicate that the financial sector improves the quality of the environment, while energy consumption inversely affects the environment. Furthermore, they indicate the presence of EKC hypothesis validation in Thailand by confirming the negative and positive effects of economic and square economic expansion towards carbon emission levels. Financial development is proxied by domestic credit to private divisions with a detrimental impact on a carbon production level. This study could pave the way for policymakers to capture the essential environmental pollutants better and develop efficient and effective energy in the presence of well-organized economic policies. That can significantly reduce carbon dioxide (CO2) emissions in the presence of economic development. It is the only research to examine the long-term influence of the financial sector on (CO2) carbon dioxide emission, using a cointegration-approach. Therefore, this research is a moderate demand to reduce the possibility of biased estimation of econometric variables and to close gaps in the existing literature.

Assymmetric effect exchange rate to Indonesian agriculture subsector

This study explores the asymmetric effect on the rupiah exchange rate on every subsector agriculture export in Indonesia during 2006-2020. The non-linear ARDL method is used in this study to analyze the asymmetric relationship between exchange rate and export. NARDL method includes short-run and long-run coefficient estimates and embraces the asymmetric effect. The previous studies generally used the linear models on the aggregated data and ignored the differences in each export of the agricultural sub-sector, then they offered ambiguous results. The latest studies have preferred to use the method of NARDL on the agricultural sector in general data. Instead of using agricultural export data for each subsector, this paper considers subsector export data of agriculture. The estimated NARDL results indicate an asymmetric effect of the rupiah exchange rate on exports of the agricultural sub-sector in the long run. In general, there is no asymmetric effect in the short run. Generally, depreciation and appreciation of the Rupiah have a negative effect on exports of the agricultural sub-sector in the long run. However, rupiah appreciation positively impacts lag 2, and depreciation caused a different effect on each sub-sector. The NARDL results suggest that positive movements have lesser impacts than those of negative movements in the exchange rate on the agriculture sector both in the short and long run

Relationship Between Money Market and Economic Growth in Nigeria

AbstractThis paper investigated the relationship between money market and economic growth in Nigeria. Secondary data for 38 years covering the period of 1981 to 2018 was used. Econometric methods of analysis of Lag Length Selection Criteria, ARDL Bound Test for Cointegration, Long Run and Short Run Estimations and Diagnostics Tests of Serial Correlation, Hetroskedascitity, Cusum Test and Ramsey Reset Test were carried out. The result found that there is long run relationship between money market and economic growth, as indicate by the F-statistics 4.48 which is higher than the upper bound values at all level of significance. This suggests that there exists a long run relation between money market and economic growth. The results of the error correction suggest the validity of long-run relationship between money market and economic growth. The study recommends that financial market regulatory body to increase the size of the money market through policy relaxation in order to achieve economic growth in the country.Keywords: Money Market, Economic Growth, Bound Test.JELClassification: C01, E05, G10

Does Technological Innovation Advance Environmental Sustainability in ASEAN Countries?

Environment degradation is a very important issue in developing nations and a lot of research had done to examine the factors of environmental degradation but these studies were missed some important factors which are covered by this study. By examining the effect of economic growth and energy in the presence of renewable energy consumption and technology innovation on environment degradation for ASEAN nations. Panel ARDL (which is PMG and MG) is used to estimate the model, and the advantage of this model is it gives both the long and short-run estimates of the model which helps to understand the situation in both short as well as long run. The results confirm that economic growth, Population, trade, and renewable energy increase the carbon emission level in ASEAN nations. While technology innovation decreased carbon emission levels which means technology innovation helps to keep the environment healthy and clean. Hence, economic growth helps the nations to improve their energy mode from non-renewable to renewable energy, which meets the energy demand by keeping the environment clean.

How climate change is impacting the major yield crops of Pakistan? an exploration from long- and short-run estimation.

This research attempts to evaluate the linkage among climatic change factors such as average temperature and rainfall patterns and non-climatic factors such as the area under major yield crops, fertilizer consumption, and formal credit on major food crop yield from 1985 to 2016 in Pakistan. For the first step, we checked the stationarity of the series by utilizing the unit root tests. An autoregressive distributed lag (ARDL) model was employed to identify the linkages between variables after verifying the properties over a specific period of time. The consequences of this study confirmed the long-run association between climatic and non-climatic factors to the major food crop yield in Pakistan. Furthermore, the outcomes of the study revealed that temperature has a diverse impact on major food crop yields. Whereas, the area under major food crops, average rainfall, fertilizer consumption, and formal credit have a positive impact on major food crop yield in Pakistan. For the second step, we used the Granger causality test to verify the causal linkage for the variables. The outcomes reveal a significant effect of climatic and non-climatic factors on major food crop yield. The bidirectional causality causal associations are found to be significant among variables including average temperature, fertilizer consumption, and formal credit disbursement. The empirical results further indicated that major food crop yields are more affected by climatic factors such as average temperature as compared to non-climatic factors. Based on the study findings, few recommendations are made to cope with factors of climate change. Invent such agricultural-specific adaptation policies for farmers which possess the ability and resilience to tackle climate change. Research and development in agriculture should focus on major varieties of food crops that can endure high temperatures. The agriculture industry will be able to sustain long-term production and distribution efficiency attributable to these strategies.

A gateway towards a sustainable environment in emerging countries: the nexus between green energy and human Capital

The nexus between economic growth (EG) and carbon emission has been examined extensively, specifically in consumption-based CO2. However, the role of human capital, green energy, and sustainable economic growth in determining the carbon emission is yet to be explored specifically from emerging economies. This study aimed to examine the impact of human capital index, green energy, EG in terms of GDP, and square of GDP on carbon emission for long-short run with the help of CS-ARDL. The data for study variables was collected from 1995 to 2018. The study findings confirmed that there exists CSD, cointegration, and slope heterogeneity among the study variables. In contrast, the output through CS-ARDL indicated that the main reason for higher carbon emission in the targeted economies are economic growth under long-short run estimation. Additionally, the role of green energy and human capital index is also constructive in lowering the environmental degradation for both long-run and short-run estimation. Finally, some policy implications are also convassed at the end of the research.

Ageing Population's Impact on Economic Growth in Malaysia From 1981 to 2019: Evidence From an Autoregressive Distributed Lag Approach.

This study investigates the impact of the ageing population on the economic growth for short- and long-run estimations in Malaysia, by using time series data from 1981 to 2019. This study adopts the autoregressive distributed lag (ARDL) method with the Bound test approach for the long-run estimation and the vector error correction model for the short-run estimation. Several econometric diagnostic tests were applied for validation and the appropriate model specification basis. The estimated result of this work indicates that the age dependency ratio proxy for the ageing population variable has a significant negative impact on economic growth in Malaysia. A 1% increase in old age dependency will decline gross domestic product's (GDP's) growth by an average of 6.6043% at the 5% level of significance. Hence, an increase in the ageing population will impede economic growth. Although controlled variables (e.g., physical capital, labour participation, and human capital) have a significant positive impact on economic growth in Malaysia, there is evidence of a long- and short-run relationship between economic growth and the ageing population variable, and also the control variable.

The Energy Mix Dilemma and Environmental Sustainability: Interaction among Greenhouse Gas Emissions, Nuclear Energy, Urban Agglomeration, and Economic Growth

In this paper we examined the interaction between greenhouse gas emissions, nuclear energy, coal energy, urban agglomeration, and economic growth in Pakistan by utilizing time series data during 1972–2019. The stationarity of the variables was tested through unit root tests, while the ARDL (autoregressive distributed lag) method with long and short-run estimations was applied to reveal the linkages between variables. A unidirectional association between all variables was revealed by performing a Granger causality test under the vector error correction model (VECM) that was extracted during the short-run estimate. Furthermore, the stepwise least squares technique was also utilized to check the robustness of the variables. The findings of long-run estimations showed that GHG emissions, coal energy, and urban agglomeration have an adversative association with economic growth in Pakistan, while nuclear energy showed a dynamic association with the economic growth. The outcomes of short-run estimations also show that nuclear energy has a constructive association with economic growth, while the remaining variables exposed an adversative linkage to economic growth in Pakistan. Similarly, the Granger causality test under the vector error correction model (VECM) outcomes exposes that all variables have unidirectional association. Furthermore, the outcomes of the stepwise least squares technique reveals that GHG emissions and coal energy have an adverse association with economic growth, and variables nuclear energy and urban agglomeration have a productive linkage to the economic growth in Pakistan. GHG emissions are no doubt an emerging issue globally; therefore, conservative policies and financial support are needed to tackle this issue. Despite the fact that Pakistan contributes less to greenhouse gas emissions than industrialized countries, the government must implement new policies to address this problem in order to contribute to environmental sustainability while also enhancing economic development.

Nuclear energy consumption and CO2 emissions in India: Evidence from Fourier ARDL bounds test approach

This study uses data from 1970 to 2016 to analyze the effect of nuclear energy use on CO2 emissions and attempts to validate the EKC hypothesis using the Fourier Autoregressive Distributive Lag model in India for the first time. Because of India's rapidly rising population, the environment is being severely strained. However, with 22 operational nuclear reactors, India boasts tremendous nuclear energy potential to cut down on CO2 emissions. The EKC is validated in India as the significant coefficients of GDP and GDP.2 The short-run estimates also suggest that most environmental externalities are corrected within a year. Given the findings, some policy recommendations abound. The negative statistically significant coefficient of nuclear energy consumption is an indication that nuclear power expansion is essential to achieving clean and sustainable growth as a policy goal. Also, policymakers should enact new environmental laws that support the expansion and responsible use of nuclear energy as it is cleaner than fossil fuels and reduces the cost and over-dependence on oil, which ultimately leads to higher economic growth in the long run. Future research should consider studying the nonlinearities in the nuclear energy-CO2 emissions nexus as the current study is examined in the linear sense.

The impact of natural resource rent, financial development, and urbanization on carbon emission.

There is a shred of evidence of environmental degradation in the form of carbon emissions to behave differently when tested with different macroeconomic variables. This paper aims to examine the long-run and short-run association between natural resource rent, financial development, and urbanization on carbon emission from the context of the USA during 1995–2015 with the help of a contemporary and innovative approach named quantile autoregressive distributed lagged model (QARDL). The stated approach is applied due to the fact that non-linearity is observed for the study variables. The findings indicated that the higher financial development (0.304), natural resource rent (0.102), and urbanization (0.489) have a positive impact on the environmental degradation in the region of USA during long-run estimation in the stated quantiles of the study. This would indicate that higher financial development, urbanization, and natural resources are putting more environmental pressure on the economy of the USA. Similarly, the findings under short-run estimation confirm that past and lagged values of carbon emission, financial development, natural resource rent, and urbanization are significantly determining the current values of the carbon emission. For this reason, it is suggested that the government requires some immediate steps of the USA to control the harmful effect of such financial development, more urbanization, and higher natural resource rent as well. This would indicate the reflection of some green strategies in all three explanatory variables to generate some fruitful environmental outcomes.

Asymmetric Impact of International Trade on Consumption-Based Carbon Emissions in MINT Nations

The association between carbon emissions and international trade has been examined thoroughly; however, consumption-based carbon emissions, which is adjusted for international trade, have not been studied extensively. Therefore, the present study assesses the asymmetric impact of trade (import and export) and economic growth in consumption-based carbon emissions (CCO2) using the MINT nations (Mexico, Indonesia, Nigeria and Turkey) as a case study. We applied the Nonlinear ARDL to assess this connection using dataset between 1990 and 2018. The outcomes from the BDS test affirmed the use of nonlinear techniques. Furthermore, the NARDL bounds test confirmed long-run association between CCO2 and exports, imports and economic growth. The outcomes from the NARDL long and short-run estimates disclosed that positive (negative) shocks in imports increase (decrease) CCO2 emissions in all the MINT nations. Moreover, positive (negative) shocks in exports decrease (increase) CCO2 emissions in all the MINT nations. As expected, a positive shock in economic growth triggers CCO2 emissions while a negative shift does not have significant impact on CCO2 emissions in the MINT nations. Furthermore, we applied the Gradual shift causality test and the outcomes disclose that imports and economic growth can predict CCO2 emissions in the MINT nations. The study outcomes have significant policy recommendations for policymakers in the MINT nations.

The role of public-private partnership investment and eco-innovation in environmental abatement in USA: evidence from quantile ARDL approach.

The current research investigates the role of public-private partnership investment (PPPI) and ecological innovation (ECO) along with economic growth on the environmental abatement (i.e., carbon dioxide emission, particulate matters 2.5) in the USA. Quantile autoregressive lagged (QARDL) method was employed during the study period of 1990–2015. The study findings confirm that under long-run estimation, GDP and PPPI are causing more environmental abatement in the form of CO2 emission and haze pollution like PM2.5. The factors like ecological innovation and GDP2 are playing their role towards lowering the CO2 emission and PM2.5 under different quantiles. Furthermore, it is observed that under short-run estimation, past values of the carbon emissions and PM2.5 have their significant and positive relationship with their current values. Besides, the findings through Wald test estimation confirm that parameter constancy of the speed of adjustment parameter is rejected at 1% significance level for the CO2 emission and haze pollution like PM2.5 in USA. Besides, present study also provides some policy implications.

Influencing Factors of New Energy Development in China: Based on ARDL Cointegration and Granger Causality Analysis

The development and competition of the new energy industry will become an important battlefield of a new round of technological and industrial competition. This study use the annual data from 1990 to 2019 to understand the factors affecting the development of new energy development in China by examining the long-run and causal relationship among the proportion of new energy consumption, energy prices, carbon emissions, industrial structure, economic growth, and new energy power generation in a multivariate model for China. The findings indicate that in the long run, new energy generation is positively linked with new energy consumption, whereas energy prices and carbon emissions have a negative and significant impact on new energy consumption. In the short run, economic growth can promote the growth of new energy consumption. However, this positive effect is gradually formed and is unlikely to happen soon. However, whether the impact of industrial structure optimization on new energy consumption is a long- or short-run estimate is not significant. Causality results suggest that a one-way Granger causality exists between each factor and new energy consumption in different lag orders, except for industrial structure. Re-examining the energy price mechanism and carbon emission mechanism policy, maintaining stable GDP growth, increasing the installed capacity of new energy power generation, and improving power generation conversion efficiency are vital for ensuring new energy development.

Dynamics of inequality in child under-nutrition in Ethiopia

IntroductionAlthough Ethiopia has already achieved a remarkable progress in reducing under-five mortality in the last decades, undernutrition among children is still a common problem in this country. Socioeconomic inequalities in health outcomes in Ethiopia have been thus of focus in academia and policy spheres for a while now. This study provides new evidence on child undernutrition inequalities in Ethiopia using longitudinal perspective.MethodUsing three round of household panel survey (from 2012 to 2016), we use concentration index (associated curve), different mobility index approaches for measuring inequalities and its dynamics, and decomposition method to identify contributing factors.ResultsIn all concentration index computing approaches and socioeconomic status ranking variables, the concentration indices are significant with negative value. This implies that in either of short-run or long-run inequality estimates, the burden of unequal distribution of undernutrition remains on the poor with significant difference across regions. While employing different SES ranking variables, the difference in the concentration indices is only found significant in case of Height-for-age Z-score. It signifies that relatively higher inequality is measured using consumption as ranking variable. Significant difference in inequality is also shown across regions. With respect to dynamics of inequalities, results on mobility indices computed based on Allanson et al. (Longitudinal analysis of income-related health inequality. Dundee Discussion Working Paper No. 214, 2010) approach show that inequality remain stable (persistent) in Height-for- age Z-score, and reduction of inequality in Weight-for- age Z-score while in case of Weight-for- height Z-score, there is no clear trend over subsequent waves. Results on decomposition of inequalities show that the major contributors are wealth index, consumption and mother’s education.ConclusionThe argument of the choice of welfare indicator can have a large and significant impact on measured socioeconomic inequalities in a health variable which it depends on the variable examined. Employing longitudinal perspective rather than weighted average of cross-sectional data is justifiable to see the dynamic of inequality in child malnutrition. In both socioeconomic status ranking variables, the bulk of inequality in malnutrition is caused by inequality in socioeconomic status in which it disfavours the poor in both cases. This calls for enhancing the policy measures that narrow socioeconomic gaps between groups in the population and targeting on early childhood intervention and nutrition sensitive.

The Role of Trade Policy in the Performance of Nigerian Agricultural Sector: A Time Series Analysis

There has been an increasing interest in understanding the role of trade policy in agricultural performance over the years. This time-series study investigates the impact of trade openness and domestic currency rate on agricultural performance in Nigeria within the period, 1981-2019. Using the autoregressive distributed lag (ARDL) approach, the study confirmed that there exists a long-run relationship between trade policy and agricultural performance in Nigeria. The result showed that trade openness has a significant and positive effect on agricultural performance in Nigeria. Further, the study confirmed that trade openness contributes more to agricultural performance in the long-run than in the short-run. However, exchange rate impacted negatively and significantly on agricultural performance in the long-run. Meanwhile, the short-run estimates showed that exchange rate has a significant and positive effect on agricultural performance. More so, it was gathered that interest rate affects agricultural performance negatively in Nigeria. There is need for government to embark on outward looking trade policy that supports the agricultural industry in terms of its exportation of indigenous commodities and stimulation of output growth. Keywords: Agricultural output, trade openness, exchange rate, interest rates, ARDL. JEL Classification: Q19, F13, E52. DOI: 10.7176/JESD/12-16-08 Publication date: August 31 st 2021

Home Alone: Implications of COVID-19 for Mental Health

RationaleThe outbreak of the 2019 novel coronavirus disease (COVID-19) has induced a considerable degree of fear, emotional stress and anxiety among individuals around the world. ObjectiveThe objective of this study is to evaluate the relationship between COVID-19 virus cases per 1000 residents and mental health outcomes of individuals across the globe. MethodsUsing plausibly exogenous variation in daily country-level reports of new COVID-19 cases across the world, this study employs an individual-by-day global data set to assess the association between virus outbreak intensity and short-term measures of mental health outcomes. ResultsResults indicate that females are 20.02% (95 % CI [6.65 %, 33.39 %]) more likely than males to find life depressing, suggesting that they may bear a much larger mental health burden than males during the COVID-19 pandemic. The association between the pandemic and mental health is more pronounced among individuals staying at home for the past week, who are 14.81 % (95 % CI [3.46 %, 26.16 %]) more likely to feel anxious and 11.17 % (95 % CI [2.13 %, 20.21 %]) more likely to experience emotional instability than their counterparts. The association between virus outbreak intensity and the likelihood of anxiety among individuals staying at home increases with household size, ranging from 11.73 % (95 % CI [-4.65 %, 28.11 %]) among individuals with 0–1 members in the household to 21.02 % (95 % CI [5.73 %, 36.31 %]) among those with 4–8 members in the household. ConclusionThese short-run estimates of mental health damages associated with COVID-19 imply that welfare losses from pandemics among individuals are enormous across the globe.

Financial development and CO2 discharge in Nigeria

This study examined the effect of financial development, fossil energy use, economic progress, and FDI on environmental pollution in Nigeria from 1981 – 2014 using the ARDL technique. The outcome of the bond test reveals the presence of a long-run association on the variables of the model. The short-run estimate shows that all the variables positively influence CO2. The result of the long-run analysis further indicates that financial progress, fossil fuel, and GDP accelerates the level of CO2 discharge. However, FDI does not explain environmental pollution in Nigeria. Hence, the study suggests that government and policymakers should formulate policies to improve financial development designed to mitigate CO2 discharge by giving directives to financial institutions that all credits allocation should be toward the purchase of low emission technologies and domestic appliances. In addition, environmentalists should enlighten citizens on the danger of environmental pollution and ways to reduce it through public lectures and seminars.