Autoregressive Distributed Lag Regression Research Articles

Exploring the effects of energy consumption on millets and rice yields in Odisha, India

Energy is a crucial input in determining the agricultural growth of an economy. Thus, this study aims to investigate the impact of energy consumption (EC) on agricultural productivity growth (APG), specifically in relation to rice and millet yields in Odisha, India. The study uses data from the period spanning 1990–91 to 2019–20. The study uses an autoregressive distributed lag (ARDL) bound F-test to examine for a cointegration relationship amid the variables, and an ARDL regression framework to investigate the effect of EC on the yields of rice and millets in Odisha. The results advocate that there exists a long-run equilibrium relationship amid the variables in the study. Regarding the result for long- and short-run elasticities, it is evidenced that EC has a positive and statistically significant effect on rice yield and has no statistically significant impact on millet yield in the long-run. However, in the short-run, EC has a positive and statistically significant effect on both rice and millet yields. According to the findings of the current study, the state government of Odisha should place a greater emphasis on ensuring that farmers have access to power in order to encourage agricultural expansion and improve crop yields.

Estimating the Potential Effect of Climate Change on Rice Yield in India by Considering the Combined Effects of Temperature and Rainfall

Background: Rising seasonal temperatures are associated with losses in most areas. Climate change is predicted to have an influence on cold-climate locations as well. In both the short and long term, agricultural production suffers marginal losses. This research analyses the long-term association as well as the short-term dynamics between rice yields and climatic variables, namely maximum and lowest temperature as well as rainfall. Methods: This study used time-series data of India from 1991 to 2020 in India. By using the Autoregressive-Distributed Lag Regression or ARDL bounds testing technique for co-integration analysis. Result: The study demonstrates that the variables do have a long-term connection with one another. According to the data, rainfall significantly impacts the amount of rice produced. Rice yields and rainfall have been shown to have a particular connection that is unidirectional, positive and substantial; however, this relationship only goes one way. Rice yields grow by 1.58 per cent for every millimeter when the amount of rainfall increases. Because of the impact of temperature on rice harvests and the increasing vulnerability of the rice crop to climate change, agricultural experts need to concentrate their efforts on studying and creating temperature-tolerant rice varieties to increase rice yields.

Do capital inflows affect domestic bank credit? Empirical evidence from India

This paper studies multivariate dynamic analysis of capital inflows in relation with domestic bank’s credit which has not been investigated earlier adequately in the context of Indian economy. Using autoregressive distributed lag (ARDL) model, we find the existence of co-integration over the period 1991 Q3 to 2022 Q1. The long-run ARDL regression model results show net equity inflows, i.e. net foreign direct investment, and net non-equity inflows, i.e. foreign loan, are significant to influence domestic bank credit. Result also reveals that depreciation of exchange rate and current account (trade) deficit increase bank credit. Outcome of this research contributes significantly to frame effective monetary policy in the Indian context.

Determinants of Inflation in Ethiopia: Autoregressive Distributed Lag Model

Price stability is one of the major goals of monetary policy and the key indicators of macroeconomic stability. Pursuing of price stability is primary to long-run growth and development; it should be the concern of every economy. This study examine the factors in determining inflation in Ethiopia, using the autoregressive distributed lag (ARDL) model by employing the data series for the period ranging from 1974 to 2017. The ADF Unit root test confirmed that the variables in the model are integrated of order 0 I (0) and order one I (1)). The Bound F-test of co integration has confirmed the existence of long run relationships among the variables entered in the inflation model. ARDL regression result suggest that real gross domestic product, real effective exchange rate and budget deficit variables are important in determining inflation in the short run. In the long run inflation is determined by real effective exchange rate, budget deficit, gross national saving and lending interest rate. The error correction term coefficient is negative and significant at 1 percent level of significance suggesting that inflation adjusts to deviations from its long -term equilibrium. The estimated model passes diagnostic tests and the graphical evidence (CUSUM and CUSUMQ graphs) indicate that the model is stable during the sample period. Finally, investments in food and agricultural sectors could considerably support the process of ensuring price stability. Moreover, a credible and sustained fiscal adjustment, aiming to boost revenue generation can reduce fiscal deficit.

Impact of agricultural credit disbursement on cereals yield in Odisha

AbstractRealizing the significance of agricultural credit and considering millets and rice are the major crops in Odisha, this study proposes to examine the impact of agricultural credit disbursement (crop loan and term loan) on the yield of total cereals, millets and rice for the period 2000–01 to 2019–20. To examine the cointegration relationship among the variables, an autoregressive distributed lag (ARDL) bound F‐test, and to investigate the impact of agricultural credit on yield of total cereals, millets and rice, an ARDL regression modelling framework is employed. The empirical result for the bounding F‐test provides a statistically significant relationship between agricultural credit and yield of total cereals, millets and rice at 1% level, confirming the long‐run equilibrium relationship in the models. The long‐run impact of crop loans positively affects the yield of total cereals and rice, whereas it has no statistically significant effect on the yield of millets. Moreover, the change in term loan negatively affects the yield of total cereals, millets and rice in the long‐run, where the magnitude is higher in the rice yield compared to the yield of millets. However, in the short‐run, both crop and term loans negatively affect the yield of total cereals, millets and rice. Based on the findings of this study, few policy implications have been suggested to reduce the negative consequences of agricultural credit on cereal yields in Odisha.

Macroeconomic influences on M&A deal outcomes: An analysis of domestic and cross-border M&As in developed and emerging economies

The abandonment of announced merger and acquisition (M&A) deals during negotiations has recently gained prominence in academia and practice. However, the effect of macroeconomic variations on announced deal outcome is uncertain. This study attempts to determine the impact of interest rate, inflation, real exchange rate, and gross domestic product on the abandonment of domestic and cross-border M&As through autoregressive distributed lag regression on BRICS and G7 countries. Domestic M&As from BRICS are very volatile, whereas outbound M&As from G7 are mostly stable to changing home country macroeconomy. The findings reveal divergences in firms’ financial abilities and strategic mindsets in developed (G7) and emerging (BRICS) countries. Macroeconomic changes have a varying impact on deal abandonments. The results provide a better understanding of higher abandonments in emerging economies. This study will help firms create differentiated strategies for M&A negotiation under changing macroeconomic scenarios and policymakers frame policies influencing M&A outcomes.

Pengaruh Nilai Tukar, Harga Saham, dan Harga Minyak Dunia terhadap Harga Emas di Indonesia

This research is intended to test and analyze the effect of exchange rates, stock prices, and world oil prices on gold prices in Indonesia. The data in this study are time series data from 2004 to 2019. This type of research is descriptive, data used is secondary data in the format of monthly data from 2004 to 2019 in Indonesia. In this study using ARDL (Autoregressive Distributed Lag) regression with Eviews 9. The test results (1) the gold price variable in the past from 2004 to 2019 had a positive and significant effect on gold prices in Indonesia; (2) the exchange rate variable from 2004 to 2019 showed positive and significant results; (3) on the other hand, stock prices and world oil prices indicates a negative but not significant relationship.

Harga Minyak Dunia Terhadap Harga Emas Di Indonesia

This study aims to examine and analyze the effect of exchange rates, stock prices, and world oil prices on gold prices in Indonesia. The data in this study are time series data from 2004 to 2019. This type of research is descriptive, the data used is secondary data in the form of monthly data from 2004 to 2019 in Indonesia. In this study using ARDL (Autoregressive Distributed Lag) regression with Eviews 9. The test results (1) the gold price variable in the past from 2004 to 2019 had a positive and significant effect on gold prices in Indonesia; (2) the exchange rate variable from 2004 to 2019 showed positive and significant results; (3) on the other hand, stock prices and world oil prices show a negative but not significant relationship.

Environmental Kuznets Curve for Carbon Dioxide Emissions and Economic Growth in Algeria

This article examines how economic growth affects the environment through the lens of carbon dioxide (CO2) emissions, by testing the validity of the environmental Kuznets curve (EKC) for the case of Algeria during the period 1973–2016. For this, the auto regressive distributed lag (ARDL) method is used. The results of the econometric analysis confirm the existence of a positive long-term relationship between CO2 emissions and real GDP and show that the direction of this relationship goes from economic growth to CO2 emissions according to Granger causality tests. Specifically, for a developing country like Algeria, economic growth determines the level of emissions. This implies that an energy policy in favour of the environment can be put in place without risking negative repercussions on economic growth. In addition, the results of the ARDL regression validate EKC’s hypothesis: in the first phase, economic growth leads to a higher level of CO2 emissions, however, when a given threshold (inflection point) is reached, these emissions decrease. JEL Codes: O10, O47, Q50, Q53

Determinants of Inflation in Ethiopia: An Autoregressive Distributed Lag Model.

Price stability is one of the major goals of monetary policy and the key indicators of macroeconomic stability. Pursuing of price stability is primary to long-run growth and development; it should be the concern of every economy. This study examine the factors in determining inflation in Ethiopia, using the autoregressive distributed lag (ARDL) model by employing the data series for the period ranging from 1974 to 2017. The ADF Unit root test confirmed that the variables in the model are integrated of order 0 I(0) and order one I(1)). The Bound F-test of co integration has confirmed the existence of long run relationships among the variables entered in the inflation model. ARDL regression result suggest that real gross domestic product, real effective exchange rate and budget deficit variables are important in determining inflation in the short run. In the long run inflation is determined by real effective exchange rate, budget deficit, gross national saving and lending interest rate. The error correction term coefficient is negative and significant at 1 percent level of significance suggesting that inflation adjusts to deviations from its long term equilibrium. The estimated model passes diagnostic tests and the graphical evidence (CUSUM and CUSUMQ graphs) indicate that the model is stable during the sample period. Finally, investments in food and agricultural sectors could considerably support the process of ensuring price stability. Moreover, a credible and sustained fiscal adjustment, aiming to boost revenue generation can reduce fiscal deficit. Besides, it is better for the government to rely more on other methods (rather than seigniorage) to finance its deficits.

How does economic growth impact on income inequality across ethnic groups in Malaysia?

AbstractThis study aims to examine the impact of economic growth on income inequality in Malaysia with special attention to the distribution of income among different ethnic groups. Twofold methodologies have been used in this analysis. The primary methodology is descriptive in nature where tables, charts, and diagrams have been extracted from the specific sources for analysis. Second, this paper applies the Granger noncausality test to estimate the causality and also applies the ARDL (autoregressive distributed lag) regression model to see the shot‐run and long‐run dynamic relationship between economic growth and income inequality in the context of Malaysia using the data of 1970–2018 from the household income survey, World Development Indicators, and the Standardized World Income Inequality Database. Additionally, it deploys panel Granger noncausality and dynamic pool mean group regression for the robustness of the results. This study reveals that the income gap among ethnic groups has been narrowed; although, intra‐ethnic income inequality is still very high, especially among Indians. The study further advises that income inequality does not Granger‐cause economic growth; rather, economic growth does Granger‐cause income inequality, and economic growth affects income inequality negatively, regardless of ethnicity, suggesting that economic growth significantly contributes to the reduction of income inequality in Malaysia. The paper concludes with a few policies which could significantly contribute to reducing income inequalities and achieving greater economic development goals, such that Malaysia can become a developed country by 2030.

Economic performance of India amidst high CO2 emissions

Abstract In recent times, the Indian economy has enjoyed a positive economic trajectory. However, the economy remains vulnerable to domestic and geographical risk as it relates to environmental degradation. The Indian economy is reputed as one of the leading emitters of carbon dioxide ( C O 2 ) emissions globally.. In the literature, there is no consensus on the contradiction between decoupling economic growth from CO2 emission in India and other regions of the globe. By drawing on the Sustainable Development Goals (SDGs) agenda and its 2030 targets, this study examines the relationship between responsible energy consumption (SDGs 7, 12), climate issues (SDGs 13), and economic growth (SDGs 8) for the case of India. Thus, the present study seeks to investigate the implications of CO2 emissions on Indian economic growth (GDP) with a focus on the energy intensity in the country's economy. To explore the nexus between economic growth and environmental degradation in a carbon income function, openness to trade and energy use were added as additional variables to circumvent the problem of omitted variable bias. Autoregressive Distributed Lag (ARDL) with the modified Wald test of Toda Yamamoto (T-Y) were applied to annual time series data from 1975-2017. The study reveals a long-term equilibrium association among the described variables over the considered period. Furthermore, a statistically significant negative relationship is observed between C O 2 emissions and trade openness and economic growth. This study validates the energy-induced economic growth as reported by the ARDL regression. This is also corroborated by the causality analysis results, as a uni-directional relationship was observed running from energy utilization to income (GDP). Thus, the Indian government officials should not adopt conservative energy policies, as this will be detrimental for economic growth given that the economy is dependent on energy. However, based on the growing environmental consciousness around the world, there is a need to shift the energy mix in India to renewables to make uses of cleaner energy sources and create environmentally friendly ecosystems.

Interest rate pass‐through and exogenous factors: Evidence from Vietnam

AbstractThis article examines the efficiency of the monetary policy transmission mechanism in Vietnam by investigating a two‐stage linkage between policy rates and retail bank rates in consideration of exogenous drivers including the asymmetric pass‐through behaviour and the State Bank of Vietnam's significant change on the operational target. The month‐end dataset, and asymmetric error correction model, autoregressive distributed lag regression and vector autoregressive regression are utilized to measure the degree of ultimate pass‐through, adjustment speed, and short‐run pass‐through of the two‐stage interest rate pass‐through process. Our results indicate quick responses in market rates to changes in policy rates; and incomplete long‐run pass‐through coupled with delayed impact and slow adjustment from market rates to retail rates; while the responses appear to be symmetric with respect to the direction of change of rates. Moreover, the positive impact of the State Bank's regime shift on the effectiveness of the interest rate transmission is another important finding of this study. These findings eventually lead to some suggestions on the possible measures to enhance the effectiveness of monetary policy transmission.

A sustainable study of economic growth and development amidst ecological footprint: New insight from Nigerian Perspective

The current study presents the mitigation of Nigerian economic performance and ecological footprint with other selected variables in ascertainment of the contribution of the country in global fight to reduce global warming amidst competitive economic operations. The motivation behind this is due to the fact that the country's economy is majorly relying on two major sectors which are considered as emission-induced sectors. These sectors (petroleum and agricultural sector) are characterized by the excessive utilization of non-renewable sources of energy in operations. The findings from this study, both from the Autoregressive Distributed Lag (ARDL) and Granger Causality (GC) perspectives aligns with the first stage of the theory (scale effect). Hence, both the economic growth and ecological footprint are increasing in the same pace. Among the findings from the ARDL regression are: a positive relation among income (GDP per capita) and the selected independent variables (ecological footprint, agric, FDI, energy use). Also, a negative relationship is revealed amid income and population of the country The findings from the causality test are: A one-way (Uni-directional) transmission is passed from economic growth (GDP per capita) to ecological footprint, from energy use to ecological footprint, from population to ecological footprint, from economic growth to energy use and from population to economic growth. It is evident that almost all the variables are causing the ecological footprint which aligns with the findings on ARDL regression. This has paved way for a well-articulated policy framing from the authorities of Nigeria with focus on the operations of both petroleum and agriculture. From the findings of this study, a well-structured policy is expected to be framed to curtail the growth based emissions in the Nigeria.

Does an N-shaped association exist between pollution and ICT in Turkey? ARDL and quantile regression approaches.

It is a debated issue that the influence of information and communications technologies (ICTs) on the environment is positive or negative in the literature. For instance, usage and disposal of ICTs may lead to environmental degradation and it may also increase carbon emission arising from electricity generation. However, ICT applications may contribute to environmental quality creating great opportunities for smarter cities, transport systems, electrical grids, and industrial processes. These two effects reveal the possible relationship of an inverted U-shaped association also known as the environmental Kuznets curve (EKC) hypothesis relationship between ICT and CO2. The objective of this study is to determine the structure of the relationship between environmental degradation and ICTs in Turkey for 1980-2017. The findings of the autoregressive distributed lag (ARDL) analysis indicate the validity of inverted N-shaped EKC hypothesis. However, the results of the quantile regression test are inconsistent with those of ARDL. When the coefficients from 30th to 95th quantiles are examined, it is observed that there is an inverted N-shaped relationship between ICT and CO2, but these coefficients are not statistically significant. In addition, in the 95th quantile, coefficients of the square of ICT and ICT are statistically significant, contrary to the cube of ICT which is not. This reveals that the relationship between the variables is U-shaped.

Why Does Turkey Have a Chronic Current Account Deficit?

Turkey faces a significant current account deficit since beginning of the first half of 2000s. The main objective of this study is to investigate the factors which affects the current account balance of Turkey for the period from September 2005 to November 2017. The required monthly data have been collected from Republic of Turkey’s central bank, Turkey statistical instutute, U.S energy information administration websites and investing.com websites. Autoregressive distributed lag(ARDL) approach and Error correction model(ECM) was used for data analysis. The ARDL regression findings show that industrial production index(IPI) statistically and positively affects the current account balance; CDS and the real effective exchange rate statistically and negatively affects the current account balance of Turkey. When investigating the long run impact of these three factors, all of them have a negative and statistcally significant impact on current account. However, in the short run only industrial production index has a negative and statistically significant impact on the current account balance.

The effect of China's RMB exchange rate movement on its agricultural export

Purpose – The paper aims to examine the relationship between changes and volatility of China's Renminbi (RMB) exchange rates and its agricultural export.Design/methodology/approach – A GARCH(1, 1) model is specified to measure the exchange rate volatility and autoregressive distributed lag regression with structural break dummy variables is estimated based on the results of unit root test with structural break.Findings – The export supply model reveals that the net trade effect of RMB exchange rate movements relies on the comparison of exchange rate level change (appreciation or depreciation) effect and exchange rate risk effect. The empirical examination results, taking China's agricultural exports to Japan as a case, show RMB depreciation against yen will promote export growth while appreciation hinder export, and exchange rate volatility positively stimulates agricultural exports to Japan. However, the effect of exchange rate volatility on the export is much smaller than that of exchange rate level, wh...