Annual Time Series Research Articles

Probability ogives for trends in stock biomass and fishing mortality from landings time series

AbstractMost fisheries are conducted without any scientific knowledge about the size and productivity of the stocks that support them. This navigation in the dark in most fisheries is a major obstacle in making them sustainable sources of nutrition for people in general and income for fishers and other economic actors along supply chains. Fisheries that have not been assessed generally are data‐intermediate and data‐poor, the latter usually having annual time series of landings as the single piece of data available. A major effort in the last two decades has been directed toward developing ‘catch‐only’ stock assessment methods, although some of these methods have been tested and found deficient. Here we provide a novel approach to using annual landing time series as the single source of data to qualitatively judge the condition of un‐assessed stocks using frequentist cumulative probability ogives, both in terms of stock biomass and fishing mortality. A meta‐analysis of the FishSource database allowed us to infer statistical patterns from hundreds of assessed fisheries and thousands of annual landings, biomass, and fishing mortality observations. Four stock‐management types were considered separately in the analysis: short‐lived and others (mid‐ to long‐lived) stocks, controlled or not controlled by catch limits. Obtained cumulative probability ogives provide clear evaluations of stock biomass and fishing mortality trends in all four stock‐management types, leading to actionable information on probable current status and future trends. Using these probability ogives, we developed decision trees that lead to qualitative scores on the exploitation status of un‐assessed stocks.

Investigating the impact of credit channels, energy production and oil revenues on agricultural development in sub-Saharan Africa

Development of the agricultural sector can numerously gift the economy by ensuring food security and rural livelihoods, fostering economic growth, reducing poverty, promoting social stability, and achieving sustainable development goals. But agricultural activities especially in Sub-Saharan Africa are faced with numerous challenges like lack of required credits to the farmers, unavailability of needed energy for powering the farm machinery and transportation of farm produce, and fluctuation of crude oil prices which serve as the main source of energy in Sub-Saharan Africa. However, the sequel to these highlighted challenges that face agricultural activities, this study examines the impact of credit channels, energy production, and oil revenue on agricultural development in sub-Saharan Africa using an annual time series covering 21 years (2001–2021) drawn from selected sub-Saharan African countries under study. Using the panel autoregressive distributed lag model (ARDL) as the baseline model and the generalized method of moment (GMM) as the robustness check, we made the following findings. From the ARDL perspective, we found that credit channels have a negative impact on agricultural development. In contrast, energy production and oil revenue have positive and negative significant impacts on the agricultural development of sub-Saharan Africa. Further, results of the Generalized Method of Moment (GMM) revealed that while credit channels have both negative and positive long-run relationships with agricultural development, energy production, and oil revenues have positive and significant long-run relationships with agricultural development in sub-Saharan Africa. The study concludes that credit channels have both negative and positive long-run relationships with agricultural development. In contrast, energy production and oil revenue have negative and significant long-run relationships with agricultural development in sub-Saharan Africa. We recommended effective agricultural credit provision and a mechanized farming system to increase the quality and quantity of food supplies in sub-Saharan Africa.

Modelling the Relationship Between Public Expenditure, Tax Revenue and Economic Growth in Türkiye Using the AARDL Approach

This study aims to investigate the macroeconomic impact of fiscal policy in Türkiye, where fiscal policy faces several challenges. Using annual time series data from 1980 to 2021, we examine the impact of tax and public expenditure subcomponents on GDP using the augmented autoregressive distributed lag (A-ARDL) bound test approach proposed by Sam et al. (2019). The A-ARDL test results indicate that tax revenue has a positive impact on economic growth in the short run, while tax revenue has a negative impact on economic growth in the long run. Furthermore, we conclude that increases in current and investment expenditures have a positive impact on economic growth in the short and long run, while increases in transfer expenditures have a negative impact on economic growth in the short run.

Do Trade and Foreign Direct Investment Contribute to Environmental Degradation in Pakistan

This study aimed to examine the impact of trade and Foreign Direct Investment on environmental degradation in Pakistan. This study used annual time series data over the period of 1990 to 2022. Based on the nature of the data, ADF and PP tests are employed to test the stationarity of the data. Tests reported a mixed order of stationarity for different variables of the study. Therefore, the literature advised to use ARDL estimation Technique for estimation purpose of the parameters of the model. In the first step, Bound Test confirmed the existence of the long-run association between the variables of the model of the study. Some additional variables are also added to the model based on their importance these variables are national income /production and energy consumption. The impact of FDI and income is found positive and significant in the long run.

External Debt and Economic Growth in Sierra Leone: A Threshold Analysis

The main focus of this study is to investigate the impact of external debt on economic growth and determine the threshold level of external debt that is favourable for economic growth in Sierra Leone, within the framework of a non-linear model (quadratic function). The study employs the Ordinary Least Squares estimation technique with annual time series data for the period 1980 to 2022. The empirical findings reveal that, lagged GDP, external debt, external debt squared and investment are the main drivers of economic growth in Sierra Leone. Specifically, the result reveals that external debt, investment and lagged GDP have a positive impact on growth whilst, external debt squared has a harmful impact on growth. Furthermore, the study establishes a nonlinear relationship between external debt and economic growth. The result indicates that the optimal threshold level of external debt (as a % of GDP) in Sierra Leone is 115%. The findings reveal that, external debt below the threshold level is growth enhancing. However, the accumulation of external debt beyond the threshold level of 115% is detrimental to growth. The diagnostic result confirms that about 76% of the variation in economic growth is explained by the regressors (independent variables). Also, the granger causality test result suggests a unidirectional causality from external debt to economic growth with no reverse causality, indicating that external debt granger caused economic growth at the 5% level. Based on the findings, the study recommends that, government should develop a robust debt management policy, to keep debt levels within sustainable limits and also cultivate an economic culture of transparency, on the issue of debt management and contract negotiations.

Controlling the money supply from macroeconomics perspective: Saving interest and exchange rate

<p>The M2 money supply over the last five years has tended to increase by 10-12%, which is allegedly due to macro factors, namely, low savings interest and increasing exchange rate requirements, causing rising inflation rates. This research aims to determine the influence of savings interest and the exchange rate on the money supply in Indonesia for the 2004-2023 period. The analysis technique used in this research is linear regression with annual time series data of 20 observation units. This simultaneous model has never been studied by previous researchers. The results of this research analysis provide information that every change in savings interest negatively affects the M2 Money supply by 78.60% and a significant, positive effect between the Exchange Rate and Money in circulation by 78.40%. Meanwhile, simultaneous changes in savings interest and exchange rates have a significant effect on changes in money supply in Indonesia and the influence is substantial at 91.20%. Therefore, the conclusion of this research is, that partially and simultaneously the proposed model exhibits a significant influence between savings interest and the exchange rate on the amount of money circulating in Indonesia. Therefore, it is crucial to pay attention to the current macroeconomic conditions concerning these two factors, especially the stability of the exchange rate, to ensure that it does not increase the money supply and inflation which may reduce people’s purchasing power in Indonesia.</p>

Investigating the Nexus between Inward Foreign Direct Investment and Capital Goods Imports: Empirical Evidence from Pakistan

This research found the empirical analysis between capital goods imports and inward foreign direct investment (FDI) of Pakistan by applying the annual time series data from 1975 to 2020. The importance of this area of research arises from its role in the balance of payments by incorporating foreign direct investment in the capital goods import demand model. The autoregressive distributed lag (ARDL) technique is used to estimate the long run relationship between dependent and independent variables. Furthermore, fully modified least square (FMOLS) and Dynamic ordinary least square (DOLS) techniques are also applied to check the robustness of the estimated long-run results. The findings indicate that capital goods import is positively influenced by foreign direction in the case of Pakistan. Moreover, domestic income, and relative price both have theoretically correct signs. On the other hand, the coefficient of export is negatively associated with import demand, which means that capital goods imports are not used in the promotion of export growth in Pakistan. We recommend that an import substitution policy should be encouraged to divert FDI toward the promotion of export growth and hence reduce the trade deficit in Pakistan.

Does corruption affect development outcomes differently in sub-Saharan Africa? Fresh evidence from Ghana

This study demonstrates that the effect of corruption on development might be dissimilar depending on how development is perceived. This study uses the linear and nonlinear ARDL bounds test estimation technique to cointegration with annual time series data (1980–2023 for WDI and 1995–2023 for Transparency International). Thus, the symmetric analysis reveals that corruption stimulates economic development in the long run; but in the short run, the effect is negative. However, the effect of corruption on sustainability is consistently negative in the short and long runs. The asymmetric analysis establishes a strong effect of corruption and corruption controls on economic development in the long run but with a weak effect in the short run. Yet, on sustainability, corruption has a weak consequence on genuine wealth per capita in the short run, but the long-run asymmetric effect is inconclusive. Governments in Africa, particularly Ghana must pay serious attention to the SDGs with recourse to the expedition of trial on environmental-related corruption cases. Strict adherence to environmental policies by MNEs must also be encouraged to stem the tide of the greenhouse effect (GHG).

Analysis of the Relationship between Privatization, Foreign Direct Investment, and Economic Growth in Azerbaijan

The solution of the main problems of the innovative development of the national economy directly depends on the attractiveness of foreign investments. In this study, the relationship between privatization, foreign direct investment, and economic growth is examined. In the analysis part, fully modified Least squares (fmols) and canonical cointegrating regress (CCR) tests, which show the cointegration rate, causal relationship, and correlation, were applied for statistical data reflecting the annual time series between 1996-2021. According to the results of the study, according to the FMOLS test results, it was concluded that a 1 percent increase in GDP led to 1.924,866 percent in privatization, and a 1 percent change in privatization led to a 0.906129 percent change in GDP. It also found that a 1 percent increase in privatization led to a 0.080900 percent (0.1811919 percent per CCR) increase in foreign direct investment. According to the CCR test, a 1 percent change in foreign direct investment also led to a 0.893101 percent change in privatization.

PUBLIC DEBT AND ECONOMIC GROWTH: EMPIRICAL EVIDENCE FROM NIGERIA

This study investigates the influence of public debt on economic growth in Nigeria, employing the autoregressive distributed lag (ARDL) model of cointegration and analysing annual time series data spanning from 1980 to 2022. The empirical findings reveal that in the long run, external debt exerts a positive and significant impact on economic growth. This suggests that external debt holds substantial economic potential to drive growth in Nigeria throughout the analysed period. However, debt service payments have a significant adverse effect on growth, both in the long run and the short run. Consequently, the study recommends that the government should ensure borrowed external funds are allocated to productive investments to achieve its desired objectives. Specifically, Projects financed through government borrowing should undergo thorough assessment, evaluating their technical feasibility, financial viability, and economic desirability before committing funds, borrowing should be allocated towards financing productive infrastructure projects and initiatives that enhance productivity, thereby potentially offsetting the costs associated with servicing the debt. Keywords: External debt; Economic Growth; ARDL cointegration; Nigeria

Deficit financing and consumption: a study of Indian private consumption expenditure

The study reinvestigates the 'Ricardian Equivalence hypothesis in India by taking private consumption as the dependent variable. The study aims to empirically study the impact of debt financing versus tax of fiscal deficit in the Indian context, as Indian policymakers primarily rely on fiscal policy as a tool for economic stability and growth. ARDL, FMOLS and DOLS approach was used by taking annual time series data from 1988 to 2023. The study reinvestigates the 'Ricardian Equivalence hypothesis in India by taking private consumption as the dependent variable. Government expenditure, public debt, tax, domestic income, and liquidity constrain as independent variables. The estimates confirm a significant symmetric as well as symmetric long-run and short-run relationship between the variables; the results reject the Ricardian Equivalence and propound the Keynesian approach that financing the fiscal deficit (debt vs tax) does matter to the private consumption expenditure. The positive and significant coefficient shows that the increase in liquidity will lead increase in private consumption expenditure. Over-reliance on debt financing strategies has a significant influence on domestic private consumption. The liquidity constraints, fiscal policies will be able to reallocate resources from the future to the present. Since debt financing of deficits and liquidity substantially influence India's consumer spending, expansionary fiscal policies should be carefully devised and supported. This study contributes to the existing literature on deficit financing and 'Ricardian Equivalence' by giving new evidence on designing sustainable fiscal policy by spending wisely without imperilling the country's consumption expenditure.

Impact of Foreign Direct Investment, Productivity, and Growth on Indonesian Youth Unemployment

Unemployment is a consistent economic challenge faced by all countries. Indonesia, as a developing country, grapples with unemployment issues predominantly affecting young individuals. This research aims to examine the impact of Foreign Direct Investment (FDI), economic growth, and labor productivity on youth unemployment in Indonesia. Annual time series data from 1991 to 2022 were analyzed using Autoregressive Distributed Lag (ARDL) technique. The study reveals a significant negative relationship between economic growth and labor productivity with youth unemployment in the long term. Meanwhile, in the short term, FDI and labor productivity have a significant positive impact on youth unemployment. It is hoped that the Indonesia government will prioritize the creation of job opportunities for young domestic workers and provide training to enhance the quality of youth workforce in Indonesia

Temporal distributions of aerosols over the Horn of Africa–Ethiopia using MODIS satellite data: Part 01

There are large temporal variations in the optical properties and types of aerosols. These are due to the effects of environmental and meteorological conditions, industrial and agricultural influences, and other human influences and natural factors in each ecological functional area. Aerosol optical depth AOD and Ångström exponent AE parameters were extracted from the Moderate Resolution Imaging Spectroradiometer MODIS satellite with a 3 km resolution of MOD04_3K and MYD04_3K. The study covers sixteen selected stations in Horn Africa–Ethiopia with neighboring Eritrea, Djibouti, and South Sudan countries clustered into four regions for the periods of 2001–2022 to obtain detailed information on the temporal behaviors and classification of aerosols in each season. The results show that the temporal variability of AOD and AE values is large, with values ranging from 0.00 to 2.10 and 0.67 to 1.23, with minimum values most likely between December 16 and January 07, and maximum values between June 22 and July 24 for both Terra and Aqua in the southeast and northeast clusters, respectively. The lowest AOD and AE values were most common in the Belg (during September–November) and sometimes in Bega (during December–February), while the highest were in the Kiremt season (during June–August). The minimum values were observed at the Kebri Dahar site, and the maximum were at the Erta Ale site, which belongs to Ethiopia. Appropriate AOD and AE thresholds were used to classify the aerosol types into marine (MR), dust (DS), biomass burning (BB), desert dust (DD), urban (UR), and the residual cases were considered mixture (MX) types. The study concludes that marine aerosols were the most abundant at 47.71%, followed by urban aerosols at 28.29%, while desert dusts, enriched at 14.65%, accounted for the third place with free of dust particles. The Mann–Kendall (MK) statistical trend test was applied to the annual time series in all clustered regions and shows an almost positive increasing variability with a slight decrease in the forward series and vice–versa.

Estimating The Financial Repression Index for The Economy of Bangladesh: A Principal Component Analysis

Financial repression was a common practice in the past, but it became less common during the liberalization era of the 1980s and 1990s. With the rise in financial sector vulnerability following the Asian financial crisis, the Global Financial Crisis, and the COVID-19 pandemic, repressive policies have once again become popular. Bangladesh, for instance, has imposed administrative interest rate ceilings. This study aims to assess the extent of financial repression on the economy of Bangladesh, using annual time series data spanning from 1973 to 2022. An aggregate financial repression index was calculated using the principal component analytical method, including the major policy variables such as real deposit rates, interest rate restrictions, capital account restrictions, the share of state-owned commercial banks in total loans, and statutory liquidity ratio. The reliability and validity of the results were tested by comparing them with the index calculated using different policy variables. The index of financial repression indicates that Bangladesh’s financial sector has undergone considerable liberalization, yet it remains subject to some degree of repression. In recent times, financial repression has intensified, particularly following the imposition of lending rate ceilings in the wake of the outbreak of the COVID-19 pandemic. Policymakers are in a position to take proper measures to liberalize the financial sector and ensure financial stability.

Hydrological and climate intensification induces conservative behavior in the Hydrochorea corymbosa xylem production in a Central Amazon floodplain forest

IntroductionTrees from flooded forests have to adjust their xylem hydraulic structure to face the annual flooding and the climatic conditions of the atmosphere. Usually, this adjustment of anatomical tissues in the tropics is driven by drought events inducing conservative behavior and can be recorded annually in tree rings. However, how the flood pulse and the climatic conditions influence the xylem hydraulic structure in floodplain trees is unknown.MethodsTo fill this gap, we explore if flooded periods and monthly climate variation affect the annual tree growth and xylem anatomy structure for the tree species Hydrochorea corymbosa (Fabaceae) from the várzea flooded forest in the Central Amazon. We developed a 41-year ring width chronology (1971–2018) and a 30-year time series of xylem anatomy parameters (1988–2018) as mean hydraulic vessel diameter (Dh), vessel frequency (VF), and parenchyma quantity (PQ). We correlated the series with monthly hydrological and climatic data.ResultsThe hydrological regime did not correlate with annual tree growth in that species as we previously expected but showed correlations with the xylem anatomical structure. High flood levels during the end of the flooding period induced conservative patterns of the anatomical structure, with a negative correlation with Dh (rho June = −0.40, p < 0.05) and a positive correlation with the PQ (rho September/October = 0.42, p < 0.05). These responses show that these trees are responding to flooding similar to the tree responses to drought. Regarding the climatic variation, the annual tree growth showed a negative correlation with the vapor pressure deficit (VPD), after the second half of the flooded period with the strongest correlation happening during the non-flooded period (rho December = −0.66, p < 0. 01). These conservative patterns in tree behavior also happened when the maximum temperature negatively affected the vessel diameter (rho September = −0.42, p < 0.05).DiscussionIn that case, we recognized two different moments that the environment is inducing conservative patterns in the xylem structure of those trees: 1) increasing the flood levels and 2) the high evaporative demand during the non-flooded period. In this way, the intensification of the hydrological regime, as well as the strong drought conditions during the non-flooded periods, can be a risk for H. corymbosa in the Central Amazonian floodplains.

Effect of Renewable Energy Consumption on Economic Growth in Kenya

One of the significant economic growth problems in Kenya is the income inequality and poverty rate which has made it impossible for among the households to afford clean energy. While the country has experienced some economic growth over the years, it is not yet clear whether the adoption of renewable energy has been the cause of this growth. There have been mixed results on the studies done on renewable energy use and their effect on economic growth and therefore calls for further research. The general objective of the study was to determine the effect of renewable energy consumption on economic growth in the Kenyan economy. Specifically, the study specific objectives were to determine the effect of solar energy consumption, geothermal energy consumption, and hydroelectric energy consumption and wind power energy consumption on economic growth in Kenya. This was made possible through an analysis of 37 years’ data from 1986 to 2022 on an annual time series basis. This study employed the endogenous growth theory as the main theory of the study and triple bottom line theory as the supplementary theory. The study employed an explanatory research design and analyzed data using the Autoregressive Distributed Lag model to establish whether renewable energy consumption had any effect on economic growth of the Kenyan economy. Findings of diagnostic test demonstrated that there was no multicollinearity among the independent variables, residuals were homoscedastic, and there was no autocorrelation among the residuals. The results of the Jarque bera normality test showed that the study's variables were normally distributed. The Augmented dickey fuller unit root test both showed that there was no unit root and that the variables had a short run relationship. Additionally, the model's stability over time was confirmed by the CUSUM test. Findings of the study were: the relationship between hydroelectric energy consumption and economic growth was positive and significant, wind power energy consumption and economic growth was positive and significant and between geo-thermal energy consumption and economic growth was positive and significant. The study concluded that geo-thermal energy consumption, hydroelectric energy consumption and wind power energy consumption significantly affect economic growth positively. The study therefore recommends that the Kenyan government should set ambitious targets for renewable energy consumption such as a specific percentage of electricity generation or overall energy consumption. The Kenyan government should enhance and enforce regulatory frameworks specific to renewable energy in order to provide a stable and predictable investment environment. Finally, the Kenyan government should focus on expanding access to renewable energy solutions in rural areas, where energy access is limited. Implementing off-grid renewable energy systems, such as solar home systems and mini-grids, can provide clean and reliable electricity to rural communities.

Research on a global periodic climate prediction method based on improved BP neural network

Climate prediction has a wide social demand, but due to the complexity of climate system formation and the uniqueness of Chinas terrain, accurate prediction is extremely complex and difficult. Therefore, this article proposes a global periodic climate prediction method based on an improved BP neural network. Firstly, based on historical meteorological data, establish a climate model and summarize and analyze the characteristics of the patterns; Then, based on the BP neural network, considering the relationship between adjacent days, rolling sampling of historical data is carried out according to seasonal and meteorological factors in the sampling interval, establishing a multi-state transition probability matrix, and constructing an annual time series forecasting model; Finally, taking precipitation prediction as an example, an example was used to simulate the annual precipitation situation. The calculation results have verified the effectiveness of the proposed method, indicating that it can simulate climate conditions well and provide guidance for climate governance and engineering construction.

A markov chain based photovoltaic power simulation method

Photovoltaic power generation has volatility and randomness, which affects the safety and reliability of the power system. In order to achieve accurate simulation of photovoltaic output, this paper proposes a photovoltaic power timing simulation method based on rolling sampled Markov chain model. Firstly, establish a photovoltaic output model and analyze the actual output characteristics; Then, based on the first-order Markov chain model, the relationship between adjacent days is considered, and a multistate transition probability matrix is established to construct an annual time series output model; Finally, based on the annual output data of a photovoltaic power station and historical meteorological monitoring data, an example is simulated to verify the effectiveness of the proposed method.

Monetary policy transmission tools and private sector performance – the Nigerian experience

Credit to private sector is considered vital for the stimulation of domestic investment, job creation, economic growth, and general improvement in the standard of living of the people. This is because the economic activity in the private sector significantly complements governments’ efforts in attaining macroeconomic objectives, globally. However, as laudable as the benefits of credit to private sector has been in catalyzing private sector performance in developed economies, the situation in most transitioning economies, particularly, Nigeria has been far from satisfying. Several studies in academic literature have identified political instability, poor institutional framework, absence of fiscal transparency, macroeconomic factors and frequent policy changes as having significant constraining influences on credit availability in Nigeria with plausible recommendations to private sector performance. However, the absence of noticeable improvement over the years, and its accompanying growth-retarding multiplier effects on domestic investment and productivity in Nigeria has instigated more concentrated studies on the direct impact of monetary policy framework in the determination of the performance of private sector through credit availability. Therefore, this study empirically evaluates the impact of key monetary policy toolkits on the availability of private sector credits and performance in Nigeria. To this end, annual time series secondary data from 1993 to 2023 were sourced from National Bureau of Statistics and Central Bank of Nigeria Statistical Bulletins for various years within the study period. The study adopts Autoregressive Distributed Lag (ARDL) estimation technique after carrying out pre-diagnostic tests such as ADF unit root test and Bound Cointegration test. Our result reveals that money aggregates (MAG) is positive and significant in explaining variations in private sector credit and performance. Further results reveal that monetary policy rate (MPR), open market operations (OMO) and inflation rate (INR) impacted negatively on the performance of private sector in Nigeria within the study period. Therefore, the study concludes that the performance of the private sector in Nigeria will improve with increased credit availability, which is positively influenced by systematic increase in money aggregates and efficiently expanded monetary policy framework. The study recommends adoption of a harmonious blend of a more relaxed monetary policy framework with purposeful compliant-based regulation that will free up liquidity for increased private sector credits and performance. Keywords: Credit to Private Sector, Monetary Policy Rate, Open Market Operations and Money Aggregates.

FISCAL POLICY ON ECOLOGICAL FOOTPRINT IN NIGERIA: AN EMPIRICAL INVESTIGATION

In recent times, the challenges of government policy formulation to achieve desired objectives and maintaining a sustainable environment without inhibiting human well-being is still an issue of debate among scholars in the literature. Many factors have been identified as culpable of environmental humiliation, but the government policy as a factor is more often than not ignored. However, the government formulates policies most especially fiscal policy that involve the collection of revenue through taxation and expenditure on infrastructural facilities, industrialization, mechanization, urbanization, etc to achieve sustained economic growth without recur to the effect of the policy on ecological footprint and its effects on human well-being in the society. Thus, this study uses the ARDL econometric approach on annual time series data extending from 1981 to 2022 to investigate the effect of fiscal policy on the ecological footprint in Nigeria. The variables used in the study include ecological footprint proxied by comprehensive measures of environmental degradation (dependent variable), government tax revenue and expenditure (independent variable), population, and technological changes proxied by industrial activities are the control variables. The study's findings indicate that fiscal policy variables are both positively and negatively related to ecological footprint and are statically significant. Specifically, government tax revenue reduces ecological footprint while government expenditure escalates the environmental degradation in Nigeria during the period under review and they are all significant statistically at 1% and 5% respectively. Considering these results, the research concludes that fiscal policy formulation has a noteworthy effect in determining changes in the ecological footprint in Nigeria. Given the effect of tax and government spending policy on infrastructure and industrialization, the government should formulate policies that are environmentally friendly and increase budgetary allocation to control and manage environmental challenges that inhabit the well-being of the citizens. By implication, the economic growth policy which invariably leads to ecological footprint challenges should be properly looked at to reduce ecological footprint in Nigeria.