Lag Distribution Research Articles

R&D lags in economic models

ABSTRACT Quite different R&D lag structures predominate in studies of agricultural R&D compared with studies of R&D in other industries, and compared with studies of economic growth more broadly. Here we compare the main models and their implications using long-run data for U.S. agriculture. We reject the models predominantly used in studies of economic growth and industrial R&D both on prior grounds and using various statistical tests. The preferred model is a 50-year gamma lag distribution model. The estimated elasticity of agricultural MFP with respect to the knowledge stock is 0.21 and the implied marginal benefit–cost ratio is 18:1.

GOLD PRICE PREDICTION IN INDONESIA BASED ON INTEREST RATE USING DISTRIBUTED LAG ALMON TRANSFORMATION

Gold is valued for its safety and profitability, driven by steady price changes and influenced by interest rates. Accurately predicting gold prices is very important to make the right investment decisions. This study aims to build a gold price model in Indonesia using the Almon transformation lag distribution and see gold price predictions based on the model that has been built. We used the data on gold prices and interest rates from January 2016 to December 2023. Based on the results of the analysis, the best Almon transformation model used in this study is the Almon model with a maximum lag length of 16 and the second polynomial degree. The prediction results have a MAPE of 16.49%, which shows that the Almon model can predict gold prices well for one year. This study contributes to the understanding of gold price dynamics amid economic variations. However, limitations in the model assumptions should be considered.

Financial Development and Income Inequality: The Case of Ecuador

Financial development, characterized by the growth and sophistication of the financial system, is crucial for the global economy, since it facilitates investment, savings and the efficient allocation of resources, in addition to contributing to the reduction of poverty and inequality by allowing, broader access to financial services. Ecuador has experienced significant changes in its financial system during recent decades, such as dollarization, liberalization, digitalization, diversification of services, and strengthening of regulation and supervision. The research focuses on establishing the influence of financial development on income inequality. The autoregressive distribution of lags (ARDL) methodology was used with the purpose of identifying short- and long-term relationships. The variables included are the Gini index, financial development, financial instability, public social spending, and final consumption spending by resident households, trade openness and gross fixed capital formation. After applying the ARDL model, the main results show that credit allocation to the private sector plays a significant role in reducing income inequality, and its effect intensifies over time. Received: 22 October 2023 / Accepted: 9 April 2024 / Published: 5 May 2024

The symmetric and asymmetric effect of financial development on ecological footprint in South Africa: ARDL and NARDL approach

Introduction: The literature on the finance–emission nexus offers conflicting conclusions. This study resolves this inconsistency by investigating the symmetric and asymmetric effect of financial development on ecological footprint in South Africa, using the Environmental Kuznets Curve framework as a guide. Given the coexistence of ecological deficits and world-class financial development systems in South Africa, it is essential to explore and evaluate potential solutions to mitigating these deficits. Our empirical analysis contributes to the body of literature on the impact of financial development and ecological footprint by using a comprehensive measure of financial development and disaggregates it into its sub-indices to provide a nuanced analysis.Method: This study employs the linear auto regressive distribution lag and nonlinear auto regressive distribution lag techniques to explore the complex interactions of financial development and ecological footprint.Results and Discussion: The findings of this research indicate that financial markets and institutions seem to have varying effects on the ecological footprint. Financial market indices promote environmental quality, while financial institutions exacerbate environmental quality. These results call for policymakers to craft a watertight process that will encourage both financial markets and institutions to allocate capital to projects that are pro-environmental.

Hα Time Delays of Active Galactic Nuclei from the Zwicky Transient Facility Broadband Photometry

In our previous work on broadband photometric reverberation mapping (PRM), we proposed the interpolated cross-correlation function (ICCF)-Cut process to obtain the time lags of the Hα emission line from two broadband lightcurves via subtracting the continuum emission from the line band. Extending the work, we enlarge our sample to the Zwicky Transient Facility (ZTF) database. We adopt two criteria to select 123 type 1 active galactic nuclei (AGNs) with sufficient variability and smooth light curves from 3537 AGNs at z < 0.09 with more than 100 epoch observations in the g and r bands from the ZTF database. We calculate the Hα time lags for 23 of them that have previous spectroscopic reverberation mapping (SRM) results using the ICCF-Cut, Just Another Vehicle for Estimating Lags In Nuclei (JAVELIN), and χ 2 methods. Our obtained Hα time lags are slightly larger than the Hβ time lags, which is consistent with the previous SRM results and the theoretical model of the AGN broad-line region. The comparisons between the SRM and PRM lag distributions and between the subtracted emission line light curves indicate that after selecting AGNs with the two criteria, combining the ICCF-Cut, JAVELIN, and χ 2 methods provides an efficient way to get the reliable Hα lags from the broadband PRM. Such techniques can be used to estimate the black hole masses of a large sample of AGNs in large multiepoch photometric sky surveys such as the Legacy Survey of Space and Time and the survey from the Wide Field Survey Telescope in the near future.

The Seoul National University AGN Monitoring Project. III. Hβ Lag Measurements of 32 Luminous Active Galactic Nuclei and the High-luminosity End of the Size–Luminosity Relation

We present the main results from a long-term reverberation mapping campaign carried out for the Seoul National University AGN Monitoring Project (SAMP). High-quality data were obtained during 2015–2021 for 32 luminous active galactic nuclei (AGNs; i.e., continuum luminosity in the range of 1044–46 erg s−1) at a regular cadence, of 20–30 days for spectroscopy and 3–5 days for photometry. We obtain time lag measurements between the variability in the Hβ emission and the continuum for 32 AGNs; 25 of those have the best lag measurements based on our quality assessment, examining correlation strength and the posterior lag distribution. Our study significantly increases the current sample of reverberation-mapped AGNs, particularly at the moderate-to-high-luminosity end. Combining our results with literature measurements, we derive an Hβ broadline region size–luminosity relation with a shallower slope than reported in the literature. For a given luminosity, most of our measured lags are shorter than the expectations, implying that single-epoch black hole mass estimators based on previous calibrations could suffer large systematic uncertainties.

Improved Breitung and Roling estimator for mixed-frequency models with application to forecasting inflation rates

Instead of applying the commonly used parametric Almon or Beta lag distribution of MIDAS, Breitung and Roling (J Forecast 34:588–603, 2015) suggested a nonparametric smoothed least-squares shrinkage estimator (henceforth SLS1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${SLS}_{1}$$\\end{document}) for estimating mixed-frequency models. This SLS1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${SLS}_{1}$$\\end{document} approach ensures a flexible smooth trending lag distribution. However, even if the biasing parameter in SLS1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${SLS}_{1}$$\\end{document} solves the overparameterization problem, the cost is a decreased goodness-of-fit. Therefore, we suggest a modification of this shrinkage regression into a two-parameter smoothed least-squares estimator (SLS2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${SLS}_{2}$$\\end{document}). This estimator solves the overparameterization problem, and it has superior properties since it ensures that the orthogonality assumption between residuals and the predicted dependent variable holds, which leads to an increased goodness-of-fit. Our theoretical comparisons, supported by simulations, demonstrate that the increase in goodness-of-fit of the proposed two-parameter estimator also leads to a decrease in the mean square error of SLS2,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${SLS}_{2},$$\\end{document} compared to that of SLS1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${SLS}_{1}$$\\end{document}. Empirical results, where the inflation rate is forecasted based on the oil returns, demonstrate that our proposed SLS2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${SLS}_{2}$$\\end{document} estimator for mixed-frequency models provides better estimates in terms of decreased MSE and improved R2, which in turn leads to better forecasts.

PEMODELAN JUMLAH KASUS DEMAM BERDARAH DENGUE DENGAN MENGGUNAKAN MODEL AUTOREGRESSIVE DISTRIBUTED LAG

This study aims to model dengue hemorrhagic fever (DHF) cases with an autoregressive distributed lag (ARDL) model to investigate significant predictor variables in Bojonegoro Regency. The selected predictor variables are the percentage of poverty, population, health facilities, and health workers. A research design with a quantitative approach was used to investigate the predictor variables in dengue cases with the ARDL model and the help of EViews. Stationarity, cointegration, classical assumptions, parameter significance, and model goodness assessment, namely R-square, MSE, AIC, and SBC, were tested. The research data source is secondary data, namely annual data from the reports of the Central Bureau of Statistics and the Health Office in Bojonegoro Regency from 2008 to 2022. The test results show only cointegration in the response variable, so the ARDL model is applied, but the lag distribution is only done on the response variable. In testing the significance of the parameters, it was found that an increase in the health workforce significantly affected the decrease in the number of DHF patients. At the same time, the other predictor variables were not significant

Statistical analysis of the regional air quality index of Yangtze River Delta based on complex network theory

Air pollution is an urgent global issue with significant implications for the environment and public health. This study focuses on the daily Air Quality Index (AQI) data from 27 major cities in the Yangtze River Delta (YRD) region of China spanning 2017-2022. Firstly, we establish an optimal threshold for constructing a stable AQI-weighted directed network, considering time lag coefficients and correlation coefficients. Quarterly analyses of correlation coefficients and time lag distribution among cities are conducted. Secondly, we apply complex network theory to examine the basic properties of the AQI-weighted directed network. Thirdly, integrating traditional methods and PageRank values, we identify crucial nodes, emphasizing key cities like Nantong, Nanjing, and Yangzhou in air quality management. Finally, utilizing the Louvain algorithm, three community structure divisions led by influential city nodes are dynamically identified. This study offers a valuable framework for collaborative air pollution management in the Yangtze River Delta, promoting improved air quality and sustainable urban development.

Research on the influence of an adhesive layer on the monitoring signal of piezoelectric sensors

Electromechanical impedance (EMI) technology, as one of the important methods for analyzing and studying the interaction between sensors and structures, has the characteristics of clear physical meaning and high computational efficiency. However, for complex structures, it is difficult to quantitatively combine the measured impedance signal with the physical parameters of the tested structure. Therefore, establishing an appropriate EMI model is crucial to facilitate the quantitative analysis of structural health monitoring. The impedance models developed so far assume perfect adhesion between PZT and the structure, with displacement compatibility, and ignore the shear lag effect of the adhesive layer. Therefore, this research focuses on analyzing how surface-bonded PZT couples with the structure through the adhesives and conducting a shear layer analysis on two-dimensional (2-D) circular PZT to derive a closed-form solution for shear lag distribution. The shear lag effect is integrated into the 2D impedance formula. The influence of the adhesive layer on bolt loosening monitoring is studied, and it is proven that the modified EMI model can effectively predict the shear lag effect of the adhesive layer. The result of relative error analysis proves that conventional adhesive PZT also exhibits the shear lag phenomenon. The influence of different thicknesses of adhesive layers on sensor sensitivity is studied. The experimental results show that as the thickness of the adhesive layer decreases, the monitoring sensitivity of the sensor increases. Moreover, for slight bolt loosening, the thickness of the adhesive layer can affect the monitoring frequency.

An effect that counts: Temporally contiguous action effect enhances motor performance.

An action-effect temporal contiguity holds essential information for motor control. Emerging accounts suggest that the temporally contiguous action effect is rewarding in and of itself, further promoting the development of motor representations and reinforcing the selection of the relevant motor program. The current study follows these theoretical and empirical indications to directly investigate the promoting impact of action effect temporal contiguity on motor performance. In two experiments, participants rapidly moved toward a target location on a computer monitor and clicked on the target with their mouse key as quickly and accurately as possible. Their click response triggered a perceptual effect (a brief flash) on the target. To examine the impact of action-effect delay and its temporal contiguity context, we manipulated action-effect delay in two temporal contiguity contexts-long versus short lag conditions. The findings demonstrate that the temporally contiguous perceptual effect enhances motor performance as indicated by end-point precision and movement speed. In addition, a substantial impact of the temporal contiguity context was observed. Namely, we found enhanced motor performance after an ambiguous (300 ms) action-effect delay sampled from short compared to long lag distributions (Experiment 1). This pattern was inconclusive for an immediate action effect (Experiment 2). We discuss the findings in the context of reinforcement from action effect and movement control.

Analyzing the Asymmetric Effects of Green Finance, Financial Development and FDI on Environment Sustainability: New Insights from Pakistan Based Non-Linear ARDL Approach

This research examines the Asymmetric Effects of Green Finance, Financial Development, Financial technology, economic growth, foreign direct investment, and financial development on environmental sustainability. It accomplishes this by applying the Asymmetric Autoregressive Distribution of Lag (NARDL) approach on information obtained from Pakistan from 1997 to 2022. The Data is collected from the Economic Survey of Pakistan and WDI. By analyzing these factors' intricate dynamics within the context of Pakistan, the study seeks to ascertain the short- and long-term effects on environmental sustainability. Using the NARDL paradigm, we address the nonlinearities and asymmetric effects that may exist in this Model. Our findings demonstrate that Pakistan's attempts to protect the environment are aided or hindered by green finance initiatives, technology advancements, economic growth trends, FDI, and financial development. The study investigates how these linkages evolve over time, which aids in developing methodological and policy recommendations for promoting environmental sustainability across the country. This study adds to the body of previous research, Businesses, legislators, and other interested parties attempting to reconcile environmental protection with economic expansion in a world-changing world will find the results to be an invaluable resource. Policymakers should prioritize the development of green financial instruments, support sustainable economic growth, draw in foreign investments with an environmental focus, and use innovations to address the urgent problem of reducing carbon emissions and promoting a more sustainable future for Pakistan. The limitation of the study is that determining the validity of observed trends may be difficult because data for some variables may only be available for a brief period of time.

The Influence of Government Spending in Education, Health, and Economics on Indicators for Calculation of Human Development Index in Bangka Belitung Islands Province

A country can be said to be successful in carrying out human development if its people enjoy the results of development. One of the indicators used to measure the extent to which development has affected results in a country is using the Human Development Index. In the Human Development Index there are three dimensions that are used as standardization of a decent life including the dimensions of education, health, and a decent standard of living or spending. To increase the Human Development Index based on the dimensions of education, health, and a decent standard of living, government spending is needed from the education, health and economic sectors. This study aims to analyze and determine the effect of government spending on education, health, and the economy on the indicators for calculating the Human Development Index in the Bangka Belitung Islands Province. This research uses a quantitative approach with secondary data. The analysis technique used is panel data regression with lag distribution. The results showed that there was a positive and significant effect between government spending on education in the same year and the previous year on the average length of schooling and there was a negative and significant effect between government spending on education in the same year and the previous year on the expected length of schooling. positive and significant effect between government spending on health in the same year and the previous year on life expectancy, and there is a negative and significant effect between government spending on the economy on per capita spending in the same year and in the previous year government spending on the economy is not effect on per capita spending.

Do foreign direct investment, trade and their interactions affect economic growth in Indonesia?

This study examines the direct and indirect impacts of foreign direct investment, exports, and imports on Indonesia's long-term and short-term economic growth. To this end, we used quarterly data for 2005.1–2021.4 sourced from Statistics Indonesia, the Bank of Indonesia, and the Bank of St. Louis. The analytical tools employed were the autoregressive model of the lag distribution (ARDL) and the error correction model (ECM-ARDL). Findings showed that foreign direct investment, exports, and imports directly affected Indonesia's economic growth. However, while the two formers had an impact only in the short run, the latter also did so in the long run. In addition, foreign direct investment also indirectly influenced economic growth through exports in the short and long run, whereas this was not the case with imports. Based on these findings, we argue for policy recommendations. To begin with, the government should encourage foreign direct investment, which may gradually replace imported raw materials with local raw resources, thereby creating an upstream connection while slowing the rate of imports. Furthermore, the government needs to adopt a policy of downstream processing of primary commodities into industrial commodities to increase export value and expand employment opportunities.

Analysis of the phase images obtained during the collection of a holographic registration system based on the geometric phase effect and a polarization camera

The results of measuring the surface depth of the test object using digital holography are presented. The resulting image was compared to a model based on the calibration slide documentation. In the presented holographic microscope, instead of an eyepiece, a lens with a geometric phase effect is used, which converts a beam with linear polarization into a pair of beams with circular polarizations (diverging and converging). The parallel phase shift method was used to obtain phase distribution. Using a polarization camera, four interferograms corresponding to four different linear projections of interfering waves with right and left circular polarizations were recorded in one exposure. Holograms of a phase object-micrometer were obtained, according to which, by the method of parallel phase shift, the distribution of phase lag introduced by the object was restored. To correct the aberration, subtraction of the recorded phase raid of the illuminating wave — the experimentally obtained phase of the wavefront without an object is used. The developed digital holographic phase microscope based on a geometric phase lens and a polarization camera makes it possible to correctly visualize the surface relief profile. The microscope can be used as a tool for monitoring the state of biological objects exposed to external effects.

Series-wise attention network for wind power forecasting considering temporal lag of numerical weather prediction

Numerical Weather Prediction (NWP), which provides approximate weather information in the next few days, is an essential feature in wind power forecasting (WPF). However, the forecasted wind speed in NWP (NWPWS) shows temporal lag compared to the actual wind speed. And the time-varying nature of the temporal lag challenges the WPF methods on selecting the NWP temporal features within valid time windows. To this end, this paper first summarizes the characteristics of the temporal lag and finds the weak inertia property within a few hours. Consequently, a series-wise mechanism, temporal lag attention (TLA), is proposed to extract valid NWP information for the ultra-short-term WPF by considering the temporal lag’s interference. Three fundamental parts included in TLA, Block-Sparse Attention Range, Lag Recognition, and Feature Fusion, are conducted sequentially. Block-Sparse Attention Range firstly screens out the critical range from the wide distribution of the temporal lag to simplify the subsequent calculation; Lag Recognition real-timely compares the series-wise similarity between actual wind speed and NWPWS time series to determine the top-k most likely temporal lags with their probability; Feature Fusion finally generates the lag-fixed weighted NWPWS as the valid NWP information. TLA has good scalability and can be integrated into the matured WPF model as the feature processing module. Real-world cases verify the accuracy improvement by integrating TLA into a modified encoder–decoder model (MED). Compared to the common point-wise attention mechanism, TLA can mitigate the negative influence of NWPWS temporal lag on WPF more effectively. Meanwhile, the sparse attention range is also proven to benefit the higher WPF accuracy and lower training cost.

Spatiotemporal variability of the PM2.5 distribution and weather anomalies during severe pollution events: Observations from 462 air quality monitoring stations across South Korea

We investigated the nationwide spatiotemporal variability of PM2.5 during 49 severe PM2.5 pollution events based on observations from 462 air quality monitoring stations (AQMSs) across South Korea during 2015–2020. We calculated the coefficient of divergence (COD) and Pearson correlation coefficient (R) for the entire nationwide AQMS network with respect to the time series of average PM2.5 in the Seoul area. We identified three distinct spatial COD and R distribution patterns (Cases I–III) among 49 pollution events that can help to determine locations for additional AQMSs. We present the spatial distributions of time lag associated with PM2.5 pollution events at each monitoring station relative to the Seoul area, clarifying the inter-district transport of PM2.5. When the time lag was adjusted, the average R values at all AQMSs were greater than 0.74 for all cases (compared to 0.52–0.57 before adjustment), suggesting that characteristic weather patterns over East Asia drive nationwide severe PM2.5 pollution. Analyses of composite anomalies of meteorological variables (compared to climatology for 1991–2020) suggest that weakened surface winds accompanied by strong positive temperature anomalies in East Asia play an important role in the onset of severe PM2.5 pollution in Korea (for all classified cases). Our findings have elucidated the weather patterns that lead to severe PM2.5 pollution, variations of spatiotemporal PM2.5 pollution patterns over Korea on the regional scale with weather patterns, and pollution transport across air quality districts (inter-air-quality-district transport patterns).

Time-scale-dependent X-ray to UV time lags of NGC 4593 using high-intensity XMM–Newton observations with Swift and AstroSat

ABSTRACT We present a 140 ks observation of NGC 4593 with XMM–Newton providing simultaneous and continuous pn X-ray and OM UV (UVW1 2910 Å) light curves, which sample short-time-scale variations better than previous observations. These observations were simultaneous with 22 d of Swift X-ray and UV/optical monitoring reported previously, and 4 d of AstroSat Soft X-ray Telescope (SXT), far (FUV 1541 Å) and near (NUV 2632 Å) UV allowing lag measurements between them and the highly-sampled XMM. From the XMM, we find that UVW1 lags behind the X-rays by 29.5 ± 1.3 ks, ∼half the lag previously determined from the Swift monitoring. Re-examination of the Swift data reveals a bimodal lag distribution, with evidence for both the long and short lags. However, if we detrend the Swift light curves by LOWESS filtering with a 5 d width, only the shorter lag (23.8 ± 21.2 ks) remains. The NUV observations, compared to pn and SXT, confirm the ∼30 ks lag found by XMM, and after 4 d filtering is applied to remove the long-time-scale component, the FUV shows a lag of ∼23 ks. The resultant new UVW1, FUV, and NUV lag spectrum extends to the X-ray band without requiring additional X-ray to UV lag offset, which if the UV arises from reprocessing of X-rays implies direct illumination of the reprocessor. By referencing previous Swift and HST lag measurements, we obtain an X-ray to optical lag spectrum, which agrees with a model using the KYNreverb disc-reprocessing code, assuming the accepted mass of 7.63 × 106 M⊙ and a spin approaching maximum. Previously noted lag contribution from the BLR in the Balmer and Paschen continua are still prominent.

The Effect of Corporate Income Tax on FDI Inflow in the Mining Sector in Tanzania

Purpose: Tanzania is one of the mineral-rich countries giving corporate income tax (CIT) concessions to encourage foreign direct investment (FDI). Tanzania's mining industry remains enticing to investors, owing to its expanding diversity. This paper assesses the impact of corporate income tax in the mining sector for the period of 1990 – 2020. The paper also sought to analyse the impact of other determinants of FDI namely, Political stability, Human capital and infrastructure on FDI inflow in the mining sector.&#x0D; Methodology: The study utilized secondary annual time series data collected from the World Bank (WB), Bank of Tanzania (BOT), and Foundation for Studies and Research on International Development (FERDI). The Autoregressive Distribution of Lags (Ardl) estimating approach was used to analyse the short-run and long-run relationship between FDI and corporate income tax as well as the aforementioned variables.&#x0D; Findings: A negative relationship between corporate income Tax and FDI inflow in the mining sector was confirmed. Thus, portraying both short-run and long-run effects of corporate income tax on FDI inflow in the mining sector.&#x0D; Unique Contribution to Theory, Practice and Policy: To encourage and increase FDI inflow in the mining sector, the government of Tanzania requires concerted efforts with relevant authorities that will ensure a fair moderation of corporate income Tax which will in turn increase tax compliance. The concerted efforts carter for factors linked with FDI inflow such as corporate income tax, political stability, human capital quality, and infrastructure. These factors align concurrently with the eclectic paradigm which is the anchoring theory of the study.&#x0D; &#x0D;

Lake Chad vegetation cover and surface water variations in response to rainfall fluctuations under recent climate conditions (2000−2020)

Monitoring the evolution of the Sahelian environment is a major challenge because the great Sahelian droughts, marked by significant environmental consequences and social impacts, contributed, for example, to the drying up of Lake Chad. We combined remote sensing images with a water level database from the Hydroweb project to determine the response of Lake Chad vegetation cover and surface water variations to rainfall fluctuations in the Lake Chad watershed under recent climate conditions. The variance in lake surface water levels was determined by computing the monthly anomaly time series of surface water height and area from the Hydroweb datasets. The spatiotemporal variability of watershed rainfall and vegetation cover of Lake Chad was highlighted through multivariate statistical analysis. The spatial distribution of correlations between watershed rainfall and Lake Chad vegetation cover was investigated. The results show an increase in watershed rainfall, vegetation cover, and surface water area and height, as their slopes were all positive i.e., 5.1 10−4 (mm/day); 4.26 10−6 (ndvi unit/day); 1.2 10−3 (km2/day) and 6 10−5 (m/day), respectively. The rainfall variations in the watershed drive those of Lake Chad vegetation cover and surface water, as the rainfall trend was strongly and positively correlated with those of vegetation cover (0.79), surface water height (0.57), and area (0.53). The time lag between the watershed rainfall fluctuations and lake surface water variations corresponded to approximately ∼112 days. Between rainfall variations and vegetation cover changes, the spatial distribution of the time lag showed a response time of <16 days in the western shores of the lake and on both sides of the great barrier, about 16 days in the bare soils of the northern basin and the eastern part of the south basin, and >64 days in the marshlands of the southern basin. For the analysis of lakes around the world, this research provides a robust method that computes the spatiotemporal variances of their trends and seasonality and correlates these with the spatiotemporal variances of climate changes. The correlations obtained have strong potential for predicting future changes in lake surface water worldwide.