Autoregressive Distributed Lag Error Correction Model Research Articles

Time-series analysis of the health outcomes-financial development nexus: Evidence from South Africa

This study contributes to the literature by investigating the health and financial development nexus in South Africa. The ‘health is wealth’ debate was again exemplified by the outbreak of the COVID-19 pandemic, thereby raising awareness of the inescapable links between poor health and diverse threats to global socioeconomic prosperity. Thus, the influencing factors of health have continued to be studied. Accounting for structural breaks, the study estimates annual time series data sourced from the World Development Indicators within the autoregressive distributed lag error correction model (ARDL-ECM). The regression outcomes show that financial development has differential impacts on health outcomes. In particular, financial development proxied by domestic credit to the private sector has a negative effect on life expectancy at birth while reducing child mortality, thereby fostering better child health outcomes. This research engages health policy strategists on the right policy mix to achieve better health outcomes. While the financial development drive is ongoing, efforts should be intensified to improve socioeconomic determinants of health, and policy strategies aimed at solving national priority health challenges should be logically pursued.

The effects of green finance, environmental tax and industrial ecologicalization towards carbon neutrality targets in China: evidence from autoregressive distributed lag-error correction model

The effects of green finance, environmental tax and industrial ecologicalization towards carbon neutrality targets in China: evidence from autoregressive distributed lag-error correction model

Investigating the causal impacts relationship between economic flood damage and extreme precipitation indices based on ARDL-ECM framework: A case study of Chungcheong region in South Korea

The attribution of climate change to various natural disasters, including flood events, has continued to receive a considerable attention as it impacts the socioeconomic sustainability of society. However, the existing knowledge on the influential role of extreme precipitation on flood events and subsequent economic damage is limited. Thus, this study investigates the causal relationship between flood damage cost, flooded area, and extreme precipitation indices in the Chungcheong region of South Korea using the autoregressive distributed lag-error correction model (ARDL-ECM) framework and pairwise Granger causality analysis. Four extreme precipitation indices: consecutive wet days (CWD), number of very heavy precipitation days (R30mm), maximum 1-day precipitation amount (Rx1day), and simple daily precipitation intensity (SDII) that measure precipitation frequency, intensity, and duration were selected with time series data on the flooded areas and estimated flood damage cost from 1985 to 2020. The ARDL-ECM bound test indicates an existence of a long-run relationship among all the variables. The empirical results of pairwise Granger causality analysis further reveal that flooded area, R30mm, and Rx1day have significant positive causal impacts on the flood damage cost in both short and long-runs, in the current period. This implies that any increase in any of these variables will cause an increase in the flood damage cost. Unidirectional causality exists from the flooded area, R30mm, Rx1days, and SDII to flood damage cost, and from R30mm and SDII to flooded area. These extreme precipitation variables could serve as indicators of flood events and economic flood damage. This study advances the knowledge of the causal link between extreme precipitation indices and economic damage from flood events.

Foreign direct investment and tax revenue mobilization in South Africa: an ARDL bound testing approach

ABSTRACT In addition to performing their basic fiscal functions, governments in developing economies are constantly challenged by new and re-emerging socioeconomic issues such as insecurity, hunger, natural disaster, collapsing infrastructure and disease outbreaks which have made the competition for limited resources fierce and hence the need to mobilize funds. Revenue mobilization forms a critical crux of development plans in any economy and the public finance literature is replete with an investigation of factors that motivate revenue mobilization. In spite of the documented indisputable roles of foreign direct investment (FDI) in the economic performance of developing economies and the resultant aggression in mobilizing FDI, its implications for tax revenue have not been well investigated. This study, therefore, assessed the role of FDI in mobilizing tax revenue in South Africa. Accounting for the potential structural break, the study used time series data from 1994 to 2021 within the Autoregressive Distributed Lag–Error Correction Model (ARDL-ECM). The results showed that FDI has a statistically significant negative effect on tax revenue. Following the outcomes of this study, it is recommended that in addition to sound public finance policies, the government should prioritize efficient investment policies in its FDI mobilization drive.

Aquaculture Production in the Midst of GHG Emissions in South Africa

The study ascertained the relationship between aquaculture production and greenhouse gas (GHG) emissions in South Africa. The study used the Autoregressive Distributed Lag—Error Correction Model (ARDL-VECM) with time series data between 1990 and 2020. The results showed that the mean annual aquaculture production, GHG emissions, and Gross Domestic Product (GDP) in the period were 5200 tonnes, 412 tonnes, and US$447 billion, respectively. There was a long-run relationship between GHG emissions and GDP. In the short run, GHG emissions had a positive relationship with GDP and a negative relationship with beef production. Furthermore, there was a bi-directional relationship between aquaculture production and GHG emissions. In addition, beef production and GDP had a bi-directional relationship. Beef production also had a positive relationship with aquaculture production. The study concludes that aquaculture production is affected and tends to affect GHG emissions. Aquaculture legislation should consider GHG emissions in South Africa and promote sustainable production techniques.

ANALISIS DEFISIT KEMBAR DAN FELDSTEIN-HORIOKA PUZZLE DI INDONESIA

This study aims to empirically examine the twin deficit and Feldstein-Horioka puzzle in the case of Indonesia period 1972-2017 and main factor that affect current account deficit in Indonesia for the last ten years. Granger’s causality is used to know the influence of budget deficit against current account balance. The Autoregressive Distributed Lag-Error-Correction Model (ARDL-ECM) approaches are applied to estimate the long run and short run relationships. The estimation results that the budget deficit is not have impact on the current account deficit in Indonesia. Meanwhile, does not occur long run cointegration based on THE ARDL. ECM results that budget deficit and investment have a short term influence the current account deficit. Based on the ARDL-ECM results, it can be concluded that the theory of Feldstein-Horioka Puzzle in the period 1972-2017 proved to occur in Indonesia. The main factor that influences the current account balance in Indonesia generally is the increase in primary income payments due to financial transactions that are always surplus and will appear forwards as payments. The condition of the current account is sustainable in a weak form means financed by financial transactions needs to be wary of negative risks in the future. The Foreign Direct Investment (FDI), Other Investments, and particularly the Portfolio Investments to prevent the occurrence of the risk of abrupt reversals which is crisis prone. So that the focus of the direction of government policy should be able to carry out stimulus to increase domestic direct investment, especially those are export oriented or substitute for domestic import needs and deepening the domestic financial market in portfolio sub-investments also other investments.

Assessing the long-run and short-run effect of monetary variables on stock market in the presence of structural breaks: evidence from liberalized India

PurposeThe present study examines the long-run and short-run effects of monetary factors (money supply, interest rate, inflation and foreign currency exchange rate) on the Indian stock market.Design/methodology/approachThe study used sophisticated econometric tools to analyse monthly observations from January 1993 to December 2019.FindingsThe augmented Dickey–Fuller (ADF) test indicates that the variables involved in the present study are either I(0) or I(1). The Bai–Perron test multiple break point test identifies four breakpoint dates in the Indian stock market index series. The breakpoint dates are incorporated as different dummy variables in the autoregressive distributed lag-error correction model (ARDL-ECM) regression. The F-bounds test reveals that the variables in the study are cointegrated within the time period under consideration. This study’s findings show that the interest rate, which is a proxy for monetary policy instrument, and the foreign currency exchange rate have a negative impact on the Indian stock market. Furthermore, the authors find that structural changes significantly affect the performance of Indian stock market.Practical implicationsThe study's outcomes indicate that economic factors should be taken into account by investors and portfolio managers when formulating long-term investment strategies. The government, through the Reserve Bank of India, should exercise caution in avoiding discretionary actions that could increase interest rates since the flow of funds to the stock market will be disrupted. To reduce risk, investors should keep a close eye on how interest rates and foreign exchange rates are rising.Originality/valueThe study covers a long period of time, which the majority of previous work did not consider. Furthermore, the study uses different dummy variables in the ARDL model to represent structural breaks (as determined by the Bai–Perron multiple break point test).

Effect of Selected Macroeconomic Variables on Budget Deficit in Kenya

Macroeconomic stability has been a concern to many economies as it shows the economic health of a nation. Kenya has had unsustainable and persistent fiscal deficit which has been phenomenal in the recent past despite several economic reforms being established in an attempt to stabilizing the economy. The study was informed by the persistent increase in the budget deficit in Kenya amidst economic stagnation and macroeconomic instability. This therefore led to an attempt to establish the effect of selected macroeconomic variables on the budget deficit in Kenya. The specific objectives were to determine the effect of interest rates; exchange rate; inflation and money supply on budget deficit in Kenya. The study sought to evaluate the significant effect of the selected macroeconomic variables on budget deficit in order to formulate the policy consideration to the economic problem. The study was guided by the Keynesian which was the main theory of the study. The Mundell-Fleming and Ricardian Equivalence theories were also employed as addition theories to back up the study. The study methodology was based on an explanatory design for time series data covering 30 years from 1991 to 2020. Autoregressive distributed lag error correction model (ARDL) estimation was adopted to analyze and infer results of the study. The CUSUM model stability test indicated that the model was stable and the model coefficient was reliable. Diagnostic test results showed there was no autocorrelation (p=0.1510>2.062), no heteroscedasticity (p=0.0903>21.47), and there was no multicollinearity (vif=1.34). Shapiro wilk normality test indicated that the variables of the study were normally distributed. The ADF unit root test indicated that there was unit root and co-integration test confirmed that the variables had a long run relationship. The findings of the study were: interest rate had a positive significant effect on budget deficit in the long run ( β_1=0.0404, <0.05); exchange rate had a positive significant effect on budget deficit ( β_2=0.4189, <0.05); inflation had a negative insignificant effect on budget deficit ( β_3=-0.001, >0.05). Money supply had a positive insignificant effect on Budget deficit ( β_4=0.00004, >0.05). The ARDL long-run results showed that the explanatory variables had Adjusted R2=0.4666 impact on the budget deficit and an F-statistics of 135.5802. The study therefore concluded that interest rate had a positive effect on the budget deficit in the long run. Increasing interest rates in the economy ends up driving budget deficit upwards in the long run. The same was true when the variable of concern is exchange rate. The study findings recommend that there is need for the government to ensure there is stability in macroeconomic variables. This is because there was a significant link between the budget deficit and the selected macroeconomic variables. A strive by the government to reduce budget deficit would mean an adjustment in macroeconomic variables to suit the purpose. These adjustments may include reducing the interest rate in the economy. A reduction in the interest rates in the economy would end up reducing the budget deficit.

서울시 프라임 오피스 빌딩의 관리비 성격에 관한 연구

The purpose of this study is to identify characteristics and determinants for maintenance fees paid with rent from the complex perspective of costs and profits in domestic prime office rental markets. The analysis targeted prime office buildings in Seoul and dealt with 86 time-series data from 1Q 2000 to 2Q 2021 on a quarterly basis. In order to empirically testify, the methodology adopted both Autoregressive Distributed Lag (ARDL) and Autoregressive Distributed Lag Error- Correction Model (ARDL-ECM). The main findings of the study are briefly summarized as follows: First, long-term equilibrium relationship between maintenance fees and consumer prices remains, which suggests that actual maintenance fees account for a large portion of the fees paid by the tenant. Second, the results from ARDL-ECM model show that actual rental costs have a positive effect, while the vacancy rate have a negative one, which means that maintenance fees can fluctuate in light of office rental markets. Third, discount rates of rental costs by rent-free seem to be statistically verified as key factors than others because they have a positive effect on the increase in maintenance fees. In conclusion, the findings can be useful to figure out the nature of maintenance fees and anticipate earnings of domestic office rental markets in the future.

Greening the finance for climate mitigation: An ARDL–ECM approach

Green finance is an effective policy instrument in mitigating climate change, but to date little is known about its impact on carbon dioxide (CO2) emissions. This study extends the literature on the relationship between green finance and CO2 emissions while taking trade openness and economic development into consideration to comprehensively explore the conservation/feedback hypothesis using the Autoregressive-Distributed Lag–Error Correction Model (ARDL–ECM) on data collected from 2000 to 2019. By constructing a green finance index comprising green credit, green securities, green insurance, and green investment, results include the following. (1) Support was found for the conservation hypothesis running from green finance, trade openness, and economic development to emissions per capita; the conservation hypothesis also was supported for the unidirectional relationship running from trade openness and economic development to green finance. (2) Green finance is found to be significantly and negatively related to emissions per capita in both the short and long term. (3) Trade openness shows a positive effect on emissions per capita. Robustness tests are provided. This study deepens policy implications of green finance in the post-pandemic era and highlights the moderating role of renewable energy in the green finance impact on carbon mitigation.

DRIVERS OF AGRICULTURAL FOREIGN DIRECT INVESTMENT AND ITS IMPACT ON FOOD PRODUCTION IN NIGERIA

Foreign Direct Investment is one of the growth promoters in many sectors of the economy including the agricultural sector. The study analysed the drivers of agricultural FDI and gauge its impact on food production in Nigeria. Annual time series data spanning from 1975 to 2017 were obtained from Central Bank of Nigeria, National Bureau of Statistics and World Bank’s Development Indicators Database. Descriptive analysis, stationarity analysis with Augmented Dickey Fuller and Philip Perrons’ unit root tests, co-integration test with Autoregressive Distributed Lag Bound test, Autoregressive Distributed Lag-Error Correction Model analysis were done to obtain results for the study. ARDL-ECM results showed that GDP at P≤0.1, government expenditure on agriculture at P≤0.1, inflation rate at P≤0.01 and real exchange rate at P≤0.01 levels of significance were the significant determinants of FDI inflow to agricultural sector in Nigeria in the long run model. In the short run, GDP at P≤0.1, government expenditure on agriculture at P≤0.1 and real exchange rate at P≤0.01 levels of significance were the significant drivers of Agricultural FDI in Nigeria. The speed of adjustment (ECM (-)) was 102.74%. Agricultural FDI also had significant long run and short run impact on food production in Nigeria at 1% and 1% levels of significance, respectively. The study concluded that FDI inflow had significant positive impact on agricultural sector in Nigeria. It was recommended that government should promote policies that are directed at employing all promotional resources to attract more FDI inflow to the agricultural sector so as to boost its productivity and contribution to the overall economy of Nigeria.

From FIT to FIP: assessing the impact of feed-in policies on renewable development in Germany

ABSTRACT By adopting the autoregressive-distributed lag error correction model, we examine both the short- and long-term impacts of feed-in policies on renewable energy deployment. The estimation results show that the feed-in premium scheme achieved its objective of encouraging the market integration of wind energy but discouraged and retarded investment in solar power technologies. Compared to the market mechanism, fixed price feed-in policy creates greater investment security for solar power projects.

An Empirical Evidence of Energy Consumption and Economic Development Dynamics in Nigeria: What is the Role of Population?

The place of population growth in the linkage between the consumption of energy and economic development in Nigeria was examined in this study. Annual data on total consumption of energy, the growth of population, and economic development were employed among other variables for the time 1995 to 2019. We used Autoregressive Distributed Lag -Error Correction Model (ARDL-ECM). Energy consumption had a feedback negative substantial relationship with economic development in the long run while in the short run, energy consumption had a negative significant impact on economic development. The population growth had a negative significant impact on economic development, and a positive substantial effect on energy consumption. However, energy consumption is not impacted on by oil price. Consequently, we advocate for the increase in the quality of energy, increasing government expenditure in the provision of energy supply, and the population maximization of energy for the achievement of economic development in Nigeria.

Oil Spillages and Captured Fish Production in the Niger Delta of Nigeria

The Niger Delta is the oil-producing region in Nigeria; it is the largest wetland in Nigeria and among the 10 most important wetland and marine ecosystems globally. The incidence of oil spillages raised serious concerns about seafood safety. Hence, this study empirically examined oil spillages and captured fish production in the Niger Delta of Nigeria. This study made used secondary data from 1986 to 2018, which was sourced from the Food and Agricultural Organisation (FAO), Central Bank of Nigeria (CBN), Federal Department of Fisheries (FDF) and Department of Petroleum Resources (DPR). The study engaged Auto-Regressive Distributed Lag (ARDL) Bounds estimation technique Findings revealed the existence of a 5% significant level of impact oil spillages on fish production negatively in Nigeria. The ARDL error correction model (ECM) for the first simulation showed a relatively low value of -0.28. This implies a relatively low speed of adjustment, which captures the rate of return to equilibrium. Therefore, this study concludes that oil spillage decreases the quantity of captured fish production in the Niger Delta region of Nigeria. It is essential that fishing activity remain viable because it is the main employer in the region. This can only be accomplished by sustainable exploitation, utilisation and management of oil resources in the Niger Delta region.

The impact of macroeconomic indicators on carbon emission in Indonesia

The advancement of the industrial sector in economic activities can negatively impact the environment. Inefficient use of natural resources causes environmental damage in almost all countries. Environmental damage caused by economic activities becomes a crucial issue. Hence, the main purpose of this research is to estimate the impacts of macroeconomic indicators on increasing CO2 emissions in Indonesia with time-series data from 1970 to 2016. The macroeconomic indicators used in this research were broad money, foreign direct investment, value-added manufacturing, and international trade. The analysis method was ARDL-ECM (Autoregressive Distributed Lag-Error Correction Model) for long-term and short-term analysis. The main findings in the long term value-added manufacturing and international trade have positive effects on the formation of CO2 emissions. In contrast, foreign direct investments have significant but negative effects at the 10% significance level of CO2 emissions. In the short term, only value-added manufacturing and international trade variables have significantly influenced the formation of CO2 emissions in Indonesia. In contrast, foreign direct investments have been proven to be insignificant. Broad money in both the long and short term is insignificant to CO2 emissions. Based on these findings and changing climatic conditions, it is necessary to have economic development policies that reduce emissions to preserve the environment and human civilization in the long term.

Monetary Policy, Exchange Rate Fluctuations and Trade Balance: The Sierra Leone Experience

This study investigates the effect of monetary policy and exchange rate fluctuations on trade balance in Sierra Leone using the autoregressive distributed lag (ARDL) bound testing framework with annual times series data covering the period 1980 to 2020. The results from the unit root test reveal a combination of I(0) and I(1) series, while the bound test result confirms there is cointegration, which validates the existence of a long-run relationship. The long run results reveal that, money supply, real effective exchange rate and real GDP are the main determinants of trade balance in Sierra Leone. The findings indicate that money supply and real effective exchange rate have negative impact on trade balance, whilst a positive relationship exists between real GDP and trade balance. Furthermore, results from the beta coefficients confirm that real GDP has the greatest effect on trade balance in the long run, followed by real effective exchange rate, whilst money supply has the least effect. Also, the short run ARDL error correction model results reveal that real GDP, government expenditure and foreign direct investment are the main determinants of trade balance in Sierra Leone. The diagnostic result posits that about 85% of the variation in trade balance is explained by the independent variables, as evident by the R-square value of 0.85. The CUSUM and CUSUMSQ tests indicate that the model is stable. A major policy recommendation is to maintain exchange rate stability consistent with its equilibrium path, and ensure that money supply growth is in tandem with domestic demand for non-tradeable goods and services.

Agricultural supply response and price risk of maize and sorghum in South Africa

The study used the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) approach to estimate the responsiveness of South African maize and sorghum producers to price risk, price incentives and non-price incentives. The price risk variable was incorporated in the supply models to examine its impact on maize and sorghum production decisions. The study used annual historical time series data of 49 observations for the period 1970 to 2018 was used in the analysis. The empirical results reveal that maize and sorghum producers' response to own price is reasonably low. The study further shows that both maize and sorghum crops demonstrate a high speed of adjustment to the long-run equilibrium, which means that in the event of a shock to the system, grain output will quickly re-establish itself at a faster rate. The findings underscore the relevance of price risk in determining production output in South Africa.

Did Financial Consumers Benefit from the Digital Transformation? An Empirical Investigation

This study aimed to test, through empirical investigation, how the rapid advancement of digital transformation (DT) has impacted the price of financial services. To this end, we compiled a set of macro-level indicators on the aggregate outcomes of the financial services sector in Korea over the last three decades and conducted an analysis to gauge the effects of DT on the country using those indicators. Using the ARDL-ECM (autoregressive distributed lag error-correction model), we show that, over time, the unit cost of financial intermediation in Korea has tended to move in tandem with the growth in economic output, although the profit portion of the unit cost has not exhibited a long-term relationship with the GDP trend. The long-term effect of the DT trend is negative (i.e., cost-saving) for labor input, capital expenditure, and the total unit cost of financial intermediation, which are all shown to be statistically significant. Consequently, we conclude that DT contributed to enhancing consumer benefit, mainly by achieving the operational efficiency of labor and capital, from 1990 to 2019 in Korea. From a policy perspective, our finding implies that DT-driven innovation in the sector can benefit financial customers if excessive levels of profit are restrained through market competition.

The impact of output volatility on CO2 emissions in Turkey: testing EKC hypothesis with Fourier stationarity test.

This study uses the output volatility–augmented environmental Kuznets curve (EKC) model to determine the dynamic short- and long-term impacts of the volatility of economic growth (VOL) on carbon dioxide (CO2) emissions in Turkey from 1980 to 2015. The results of the autoregressive distributed lag (ARDL) approach indicate that there is a long-run relationship between CO2, per capita real GDP, per capita energy use, and VOL. The coefficients obtained from the ARDL estimation indicate that economic growth and energy use increase CO2 emissions, while VOL decreases CO2 emissions in the long run. Moreover, the coefficients obtained from the ARDL error correction model show that VOL decreases CO2 emissions in the short run, as well. We also find that the EKC is valid in Turkey. This implies for the Turkish case that achieving macro-stability under a “just transition” is key for achieving both economic and environmental benefits from ratifying international agreements such as Paris Agreement and EU Green Deal.

What Explains the Trends of Wheat Imports in Kenya; A Cointegration Analysis Using ARDL-ECM Modelling

This study aims to determine the cointegration of wheat imports and its determinants in Kenya. To achieve this objective, annual time series secondary data from 2000 to 2019 was utilized. The time frame was considered because it was during this period that wheat imports in Kenya skyrocketed. Data was collected from national and international published sources. The findings of the Auto-Regressive Distributed Lag-Error Correction Model (ARDL-ECM) analysis shows that wheat imports in Kenya are determined by the tariff, relative prices and ending stock in the long run. In the short run relative price was the main determinant that influenced wheat imports in Kenya. It was also realized that wheat imports in Kenya are inelastic to its determinants. Therefore, the study recommends that policymakers should embrace policies that increase the competitiveness of domestic wheat production in Kenya to tap the multiplier benefits that can be realized from the wheat sector. This can be done by embracing modern and efficient production technologies. Keywords: ARDL model, Kenya, Time series, Wheat Import Demand, Error Correction Model. DOI: 10.7176/JESD/12-16-10 Publication date: August 31 st 2021