Autoregressive Lag Model Research Articles

P1203 Spatial mapping and geographic variation of inflammatory bowel disease in Canada: A population-based study using Statistics Canada data

Abstract Background Crohn’s Disease (CD) and Ulcerative Colitis (UC) pose significant challenges to patients and healthcare systems, with a rising incidence and prevalence globally1,2. To address the challenges of health resource allocation and understand the geographic distribution of these conditions in Canada, we conducted the spatial mapping of IBD across Canada using national population survey data available from Statistics Canada. Methods We utilized data from the 2009-2018 Canadian Community Health Survey (CCHS) to identify individuals with CD or UC. Prevalence rates, both crude and adjusted for age and sex, were calculated for each health region in Canada. Spatial dependencies between health regions were estimated using global Moran’s I and local indicators of spatial association (LISA) were used to identify clusters of health region (hot-spots) where the prevalence was significantly higher than in other areas. We further applied spatial simultaneous autoregressive lag models to explore the influence of region-level sociodemographic factors on identified spatial dependencies. Results A total of 492,560 individuals from 2010-2018 CCHS were included, representing 29,846,350 Canadians across 109 health regions. Survey data revealed that 0.38% of Canadians self-reported having CD and 0.47% reported having UC. The majority of respondents reported being urban-residing, middle-aged, and white. Across Canadian provinces, the age and sex-standardized prevalence of IBD ranged from 742 per 100,000 in Quebec to 1267 per 100,000 in Nova Scotia (Figure 1). Spatial analysis identified significant dependencies among health regions, but these spatial associations were explained by the differing distributions of sociodemographic characteristics in each health region (Table 1). Increased health region-level prevalence of CD and UC was associated with a larger proportion of individuals 30+ years, identifying as a female, immigrants, or as white (p<0.05 for each). Conclusion Data from this large, population-based Canadian national survey demonstrated significant geographic variation in the prevalence of CD and UC. However, after adjusting for patient demographic characteristics, the spatial dependency became non-significant. Key characteristics related to urbanization including the age distribution and proportion of immigrants in a health region were associated with increased prevalence rates. These results suggest that differences in CD and UC prevalence between geographic areas are primarily driven by individual demographics rather than differences in characteristics of local healthcare delivery systems and further support the notion that characteristics of urbanization increase the prevalence of IBD in an area1.

Is Redistribution Good for Our Health? Examining the Macrocorrelation between Welfare Generosity and Health across EU Nations over the Last 40 Years

Context: Social determinants of health are finally getting much-needed policy attention, but their political origins remain underexplored. In this article, the authors advance a theory of political determinants as accruing along three pathways of welfare state effects (redistribution, poverty reduction, and status preservation), and they test these assumptions by examining impacts of policy generosity on life expectancy (LE) over the last 40 years. Methods: The authors merge new and existing welfare policy generosity data from the Comparative Welfare Entitlement Project with data on LE spanning 1980–2018 across 21 countries in the Organization for Economic Cooperation and Development. They then examine relationships between five welfare policy generosity measures and LE using cross-sectional differencing and autoregressive lag models. Findings: The authors find consistent and positive effects for total generosity (an existing measure of social insurance generosity) on LE at birth across different model specifications in the magnitude of an increase in LE at birth of 0.10–0.15 years (p < 0.05) as well as for a measure of status preservation (0.11, p < 0.05). They find less consistent support for redistribution and poverty reduction measures. Conclusions: The authors conclude that in addition to generalized effects of policy generosity on health, status-preserving social insurance may be an important, and relatively overlooked, mechanism in increasing LE over time in advanced democracies.

Does agricultural trade respond asymmetrically to oil price shocks? Evidence from New Zealand

AbstractDo rising oil prices affect agricultural trade differently from falling oil prices? We answer this question using data on New Zealand, a net importer of oil and a net exporter of agricultural commodities. We consider a disaggregated approach, analysing exports and imports of five key commodity classes; nonlinear autoregressive lag models are employed to conduct the analysis. We find considerable evidence suggesting asymmetries in the effects of oil price shocks on agricultural trade in the long and the short run. Furthermore, in the long run, agricultural exports and imports appear to be largely insensitive to foreign and domestic real income, respectively; there is limited evidence for imports and exports being associated with the real effective exchange rate. In the short run, however, income and exchange rates are associated with imports and exports.

Nexus Between Pension Funds and Stock Market Sustainability Development in Nigeria

Objective: It has long been recognized that pension systems across the emerging markets including Nigeria have undergone dramatic reforms over the last twenty-eight years. This process has mainly been fueled by the demographic problem faced by modern financial systems. Hence, this study examines the short-run and long-run dynamic of pension funds on capital market development in Nigeria using ex-post facto research design. Method: Data were collected from the Central Bank of Nigeria (CBN) statistical bulletin and annual report of the pension fund commission from 1995 to 2022. Data collected were analyzed using descriptive statistics, unit root test and auto regressive lag model (ARDL) and Toda Yamamoto multivariate granger causality approach. The unit root test reveal that all the variables used in the study are non-stationary at first difference except inflation which is stationary at level. Results: The findings from the ARDL analysis reveal a short-run dynamic impact between pension funds and capital market development due to the coefficient of error correction mechanism (speed of adjustment) which is negative and significant at 5% level of significant. The result suggests that over 22% of the short run disequilibrium is corrected in the long run equilibrium. However, the results from the long-run dynamic impact reveal a positively significant impact between the proxies of pension funds (pension contributory fund, pension investment) and control variable - inflation to be positively significant with capital market development proxied by market capitalization as a ratio to GDP at 5% level of significant. The results of the Toda Yamamoto granger causality results suggest a bidirectional relationship between pension funds (pension contributory fund, pension investment) and market capitalization as a ratio of Gross Domestic Product (GDP) in Nigeria at aggregate level. This suggest that the relationship between pension funds (pension contributory fund, pension investment) and market capitalization as a ratio of Gross Domestic Product (GDP) in Nigeria was two-ways. Conclusion: The study concludes that pension fund administrators in Nigeria should understand that the rate of inflation is dynamic in Nigeria and the value of money is being lost as money is not worth it values in the next five years.

THE EFFECT OF INFLATION AND INTEREST RATE ON PROFITABILITY FOR SHARIA BANKING RESULTS

This study was conducted to examine the effect of the inflation variable on the profitability of Islamic banking profit sharing in Indonesia, as well as to test whether there is an asymmetric effect of inflation and interest rate variables on the profitability of Islamic banking profit sharing in Indonesia, the study was conducted using agency theory, portfolio selection and policy. monetary. This study uses a quantitative method, the regression tool used is the Non-linear Autoregressive Lag Model (NARDL) using the Eviews 10 data processing tool, the sample of this study is Islamic banking registered with the Financial Services Authority (OJK), with an observation period from 2014 -2020. The results of this study indicate that inflation and interest rate variables have an asymmetric relationship to the profitability of Islamic banking in Indonesia, namely when inflation and interest rates rise, the effect is smaller than when inflation and interest rates fallKeywords: Profitability, Asymmetric, Inflation, Interest Rate, NARDL

Race to achieving sustainable environment in China: Can financial globalization and renewable energy consumption help meet this stride?

Investigating the drivers of CO2 emissions is essential for limiting global warming, which has sparked widespread concern. This study evaluates the association between economic complexity and CO2 emissions in China, considering the effect of disintegrated energy and financial globalization on the environmental function between 1970 and 2018. This dataset was analyzed using the autoregressive lag model (ARDL) and frequency-domain causality approaches. The ARDL unveiled that urbanization, economic complexity, financial globalization, and economic growth deteriorate the environment while environmental sustainability is achieved through renewable energy utilization. The study also validates the Environmental Kuznets Curve hypothesis. Also, the frequency-domain causality disclosed that all regressors (economic growth, financial globalization, economic complexity, and urbanization) could forecast CO2 emissions in China at different frequencies. Based on these outcomes, policy recommendations are formulated.

The role of renewable energy consumption and financial development in environmental sustainability: implications for the Nordic Countries

ABSTRACT The Nordic nations have yet to significantly contribute to achieving Sustainable Development Goals (SDG) 7 and 13. This predicament might be attributed to fundamental financialization concerns in these nations and renewable energy generation implementation issues. The Nordic nations are fighting to reduce CO2 emissions as a result of these two situations. Dealing with this problem may necessitate a policy shift, which represents the focus of this research. Utilizing data from 1980 to 2020, we analyze the heterogeneous impacts of financial development and renewable energy on CO2 emissions using advanced panel and time-series methodologies. The advantage of the wavelet tools (wavelet coherence, partial wavelet and multiple wavelet techniques) is that they help to capture policy initiatives at different frequencies, i.e., short, medium and long-term. Our empirical outcomes from the CS-ARDL show that both financial development and renewable energy decrease CO2 emissions in the short and long term. Furthermore, the outcomes of the wavelet coherence show negative co-movement between CO2 and renewable energy in each Nordic nation except for Iceland with renewable energy driving CO2 in all frequencies. Additionally, financial development enhances the ‘CO2 emissions-renewable energy consumption’ association, but in the short term, it has no stimulating effect. These findings lead to the recommendation of an SDG-oriented policy framework. While this policy agenda is designed to achieve SDGs 7 and 13, it may also be applied to other nations. The study recommends that the Nordic countries implement measures to boost renewable energy supply through enhanced renewable energy technologies. Abbreviations: ASEAN: Association of Southeast Asian Nations; BRICS: Brazil, Russia, India, China and South Africa; CO2 : Carbon Emissions; CS-ARDL: Cross Sectional Autoregressive Distributed Lag Model; FD: Financial Development; PMG-ARDL: Pool Mean Group Autoregressive Lag Model; VAR: Vector Autoregressive; VECM: Vector Error Corrected Model; MINT: Mexico, Indonesia, Nigeria and Turkey; REC: Renewable Energy; SDG: Sustainable Development Goal; SD: Sustainable Development

Access to Electricity and Economic Growth in the WAEMU: Causality Analysis

The objective of this paper is to determine the possible link between economic growth and electricity access rate. An autoregressive lag model (ARDL) on panel data from 1998 to 2019 for West African Economic and Monetary Union (WAEMU) member states was used. This model shows that in long term, the growth rate has a positive impact on access to electricity in WAEMU member states. In the short term, economic growth rate has a positive and significant impact on electricity access rate only in Benin. The results of Granger causality test show an unidirectional relationship from GDP growth rate, investment rate to access to electricity.

Wages of Workers Spatial Analysis in Indonesia Region 2019

The wage inequality of workers in Indonesia is one of the main problems and concerns that are important to be addressed by the government. The determination of the regional minimum wage by the local government has not been able to solve the problem of inequality. On a larger scale, the wage inequality of workers can affect the stability of the national economy. Research on the spatial analysis of workers' wages is very important to be carried out as a basis for making appropriate policies by the government. In this study, we have succeeded in analyzing the dependence and spatial relationship of a region with the wages of its workers and have identified the factors that affect the wages of workers in a region. The result reveals the spatial dependences are detected among districts, followed by the spatial clusters and spatial outliers through global and local spatial autocorrelation. Applying two spatial autoregressive models, spatial autoregressive lag model (SAL) and spatial autoregressive error model (SEM), SAL confirmed that there are 4 significant independent variables with a level of 10 percent and have a positive relationship, namely education, age, internet, and sex ratio variables. And SEM confirmed that there are significants 5 significant independent variables with a level of 10 percent and have a positive relationship, namely education, age, technology, internet, and sex ratio variables. As the policy implication, since regional inequality in term of wage is still a major issue, it will be a call for better coordination and cooperation within and between regions.

Growth Analysis and the Determinants of Entrepreneurial Orientation in the Small-Scale Poultry Subsector in Delta State, Nigeria

Entrepreneurial orientation is vital to growth and development, but lacking in many small-scale enterprises. This study investigated growth and entrepreneurial orientation in the small-scale poultry subsector of Delta State, Nigeria. It also ascertained the drivers of poultry entrepreneurial orientation in the study area. A multistage sampling procedure was used to collect primary data from 180 poultry farmers, through a questionnaire. A four-point Likert scale of five items was used to measure entrepreneurial orientation from innovativeness, proactiveness, and risk-taking. The data were analyzed using descriptive and inferential statistics, including gross margins, an autoregressive lag model, and logistic regression. The majority (57.7%) of the farmers are female. The small-scale poultry entrepreneurs had an orientation that was above average. The autoregressive lag model result indicated an increase in stock size and gross margins of poultry enterprises. It was forecast that the growth trend would increase up to 2022. Furthermore, the ANOVA result was statistically significant at 0.002*** and 0.001*** for stock size and gross margins, respectively. Years of experience and training in poultry farming and noninvolvement of entrepreneurs in other occupations influence their entrepreneurial orientation. Poultriy entrepreneurs must be trained while they adopt poultry farming as their principal occupation.

Empirical analysis of the push factors of human capital flight in Nigeria

Purpose Human capital flight from Nigeria to developed countries has remained a topical issue. This paper aims to empirically analyze the push factors for the migrants who explore the various legal migrant schemes from a macro perspective. The authors examine human capital development and its role in contributing to human capital flight to more developed counties. Design/methodology/approach This paper is anchored on the push–pull model. Using secondary data from 1990 to 2019, the authors look at the relationship between human capital flight and variables such as life expectancy, infant mortality rate, population growth rate and Nigeria’s unemployment rate. The auto-regressive lag model (ARDL) was adopted to estimate the empirical relationship among these variables. Findings The results from the ARDL model suggest a positive relationship exists between population growth rate and migration rate. A negative relationship was, however, observed between life expectancy and migration rate. This study also found that an increase in the infant mortality rate negatively impacted migration significantly. Therefore, an increase in infant mortality rate lowered the migration rate. Finally, an increase in the unemployment rate increased migration; however, insignificantly. Research limitations/implications The findings from this study are limited to the push factors influencing migration out of Nigeria. These factors are also restricted to variables for which data can be derived under the study’s scope. The results of this study have far-reaching implications, especially for policymakers and citizens alike. Better human capital development through enhanced life expectancy and reduced population in Nigeria will reduce the migration rate. Therefore, this study calls for the doubling of developmental and infrastructural efforts at all levels of governance. Originality/value This paper’s importance lies in its ability to elucidate push factors that influenced migration out of Nigeria empirically. An empirical approach to the subject matter will explain these factors and the degree to which they influence migration. This will guide the policy-making process in curbing brain drain, which is a major challenge in Nigeria.

A new look at the tourism development and economic growth nexus: International evidence:

This article tests the relationship between tourism development and economic growth in major tourism destinations in the world. The study relies on the quantile autoregressive distributed lag model...

Long-run Relationship of Economic Growth with Consumption, Unemployment Rates and Saving Rates in Developing Countries: A Case Study of Vietnam

The Keynesian macroeconomic model implies that household expenditures and savings have significant long-run impacts on economic growth by affecting total expenditures. Therefore, policymakers should determine and apply appropriate policies to maintain these variables. For this purpose, the long-run relationship of economic growth with consumption, unemployment and saving rates in Vietnam is analyzed with the time data method using annual data for the period 1996-2017. Consumption appears to have the most impact on economic growth in accordance with the estimation results of a co-integration test from an autoregressive distributed lag model (ARDL model). In long run, an increase of 1% in consumption expenditures decreases economic growth by 0.41%. A 1% increase in saving rates increases economic growth by 0.0009%. While an increase of 1% in unemployment rates decreases economic growth by 0.043%. Our results demonstrate that there exists only long run relationship among economic growth, consumption, saving and unemployment rates for Vietnam, but not in short run.

Influence of Real GDP Growth Rate, Industrialization, Energy Consumption on Carbon Dioxide Emissions: An Evidence from Vietnam

The purpose of this paper is to investigate the effects of energy consumption, economic growth and industrialization on carbon dioxide emissions in Vietnam. Using an autoregressive distributed lag model (ARDL model) on the data during the period over 1985-2013, collected from World Development Indicators, Department of Statistics in Vietnam. Evidence from the study shows that carbon dioxide emissions, GDP growth, energy consumption and industrialization are co-integrated and have a long-run equilibrium relationship. Our results demonstrate that both industrialization and energy consumption have positively affected carbon dioxide emissions and significant while economic growth also has positively affected carbon dioxide emissions but insignificant. In addition to short run relationship, evidence from the long-run result has policy implications for Vietnam; a 1 percent increase in industry growth will increase carbon dioxide emissions by 276 kt, while a 1 kg of oil increase in energy consumption will increase carbon dioxide emissions by 168 kt in the long-run. Increasing industry growth in Vietnam will therefore increase environmental pollution in the long-run. Positive effect of energy consumption on carbon dioxide emissions raise a problem of using non-green energy in Vietnam. It is noteworthy that the Vietnamese Government promotes sustainable economics, which improves the use of clean and environmentally energy.

Human Development Dynamics across Districts of Indonesia: A Study of Regional Convergence and Spatial Approach

Indonesia is an archipelago country which comprises of two main parts, western and eastern regions and spread into over 500 districts. Each district has their own characteristics, especially in development aspect. Some districts have been growing faster on economic and social development, yet others still fall behind. Using Human Development Index and its components on education, health and economic variables over 2010- 2018 period, this study aims to examine convergence on the regional human growth process and investigate the speed of convergence across districts. The result reveals convergence occurred on human development process and its determinants across districts during 2010-2018. Education variables are assumed as the main contributor for boosting the speed of convergence of human development. Spatial dependences are detected among districts, followed by the spatial clusters and spatial outliers through global and local spatial autocorrelation. Applying two spatial autoregressive models, spatial autoregressive lag model (SAR) and spatial autoregressive error model (SEM), confirmed that there is significant spatial spill-overs.The speed of convergence for all variables are much declining after the inclusion of spatial lag and error model. As the policy implication, since regional inequality in term of human development is still a major issue, it will be a call for better coordination and cooperation within and between regions.

The Dimensions of Agricultural Diversification: A Spatial Analysis of Italian Municipalities

AbstractDiversification in agriculture could ensure the survival of farming by broadening the income base of farms and encouraging agricultural sustainability. The diversification of on‐farm activities may depend on socioeconomic and environmental characteristics. Although multifunctionality is a hotly debated topic, few papers have focused on the farm characteristics that influence diversification and none have focused on the influence of the spatial pattern. This paper examines the relationship between farm characteristics and the adoption of a specific type of diversification. An econometric model is presented that uses a spatial autoregressive lag model at the municipal scale. The results demonstrate that the activation of each diversification dimension is influenced by both internal and external factors, encompassing farmers’ characteristics, the farm structure, and territorial features, including regional and spatial patterns. Deepening is mainly influenced by the farmer’s age, education, and the presence of small and labor‐intensive farms. The key factors for broadening diversification are the presence of small farms and farms with mixed production (breeding and crop cultivation). Regrounding is most affected by the labor‐intensive farms in the area and the farms with mixed production.

Monetary Policy and Financial Performance of Nigerian Deposit Money Banks

This paper aims to ascertain the monetary policy instruments of the Central Bank of Nigeria (CBN) during and after the bank consolidation exercise (2000 – 2016) and determine the effects of these policies on the financial performance of deposit money banks (DMBs) in Nigeria. An Autoregressive Lag Model (ADL) analysis of secondary data obtained from the CBN Statistical Bulletin, 2016 shows that monetary policies of the CBN had a significant effect on the performance of DMBs in the short-run but an insignificant effect in the long-run.

Urban Population Growth and Environmental Sustainability in Nigeria

It is believed that the increasing urban population has led to rapid forest decline and degradation of the environment. This paper examines the impact of urban population growth on environmental sustainability using Nigeria data from 1981-2017. The variables used are urban population growth, fossil fuel consumption, carbon emissions, food production index, arable land, and agricultural raw material exports with renewable energy consumption and forest reserves as explanatory variables. Autoregressive lag model was used to determine the impact of urban population on renewable energy consumption and forest reserves, which are proxies for sustainable environment. From the findings, urban population growth had significant impact on environmental sustainability while real gross domestic product does not have significant impact on renewable energy consumption and forestry. Findings also show that urban population growth increase renewable energy consumption but decrease forest reserves. A basic policy in this direction is effective curtailing in the rate of population growth and depletion of forest reserves.

Introducing bootstrap methods to investigate coefficient non-stationarity in spatial regression models

In this simulation study, parametric bootstrap methods are introduced to test for spatial non-stationarity in the coefficients of regression models. Such a test can be rather simply conducted by comparing a model such as geographically weighted regression (GWR) as an alternative to a standard linear regression, the null hypothesis. In this study however, three spatially autocorrelated regressions are also used as null hypotheses: (i) a simultaneous autoregressive error model; (ii) a moving average error model; and (iii) a simultaneous autoregressive lag model. This expansion of null hypotheses, allows an investigation as to whether the spatial variation in the coefficients obtained using GWR could be attributed to some other spatial process, rather than one depicting non-stationary relationships. The new test is objectively assessed via a simulation experiment that generates data and coefficients with known multivariate spatial properties, all within the spatial setting of the oft-studied Georgia educational attainment data set. By applying the bootstrap test and associated contextual diagnostics to pre-specified, area-based, geographical processes, our study provides a valuable steer to choosing a suitable regression model for a given spatial process.

Determination of the physical drivers of Zostera seagrass distribution using a spatial autoregressive lag model

Seagrass mapping has become a key tool in understanding the causes of change in seagrass habitats. The present study demonstrates a method for examining relationships between seagrass habitat polygons and environmental data generated by hydrodynamic, wave, catchment and dispersion models. Seagrass abundance data are highly spatially autocorrelated and this effect was corrected using a spatially simultaneous autoregressive lag model (SSARLM). The physical processes that determine the spatial distribution of seagrass in Port Phillip Bay, Australia, were investigated by examining the links between seagrass distribution and abundance and broadscale hydrodynamic (waves, currents), physical (light, depth, salinity and temperature) and catchment (nutrient and suspended sediment concentrations) processes. The SSARLM indicated that the distribution of Zostera spp. meadows is principally constrained by two physical thresholds, namely, wave height or exposure and light. The former excludes seagrasses from colonising wave-exposed coastlines, whereas the latter directly determines the depth profile of seagrasses through its influence on light availability. In total, 95% of all seagrass occurred within grid cells with a mean significant wave height of &lt;0.38m and a mean percentage irradiance of &gt;33% surface levels. By comparison, variation in water quality, represented by variables such as modelled total nitrogen, suspended solids or salinity, had little influence on seagrass distribution.