Short-run Dynamic Relationships Research Articles

Structural transformation, urbanization, and remittances in developing countries: A panel VAR analysis

Structural transformation and urbanization have increased greatly in developing countries over the last few decades. Migrant remittances—private external financial flows—have also grown phenomenally during this period. The literature reveals a significant causal relationship between urbanization and economic growth and considers urban cities to be the engines of growth. However, investigation into the link between structural transformation, urbanization, and remittances is missing in the literature. This study aims to fill that gap by investigating the relationship between structural transformation, urbanization, remittances, and GDP growth in developing countries. After finding no long-run relationship between the respective variables, this study applies vector autoregressive modelling to determine their short-run dynamic causal relationship, using panel data from 95 developing countries for the period 1980–2018. Its findings suggest that there is a two-way (bi-directional) causal relationship between structural transformation and urbanization, structural transformation and GDP growth, urbanization and GDP growth, and urbanization and remittances. Rapid urbanization can increase housing prices and overall urban living costs, which may increase remittance flows that support consumption. Likewise, increased urban infrastructure development may also attract remittances to real-estate investment, leading to further urbanization.

Effects of Health Factors on GDP Growth: Empirical Evidence from Saudi Arabia

The primary objectives of this study are to examine the presence of long-run equilibrium relationships and short-run dynamic relationships between health factors and GDP growth in Saudi Arabia over a specific time period. By utilizing an annual time series dataset from 1990 to 2019 obtained from the World Bank, the study focuses on four key health factors and employs the Johansen cointegration test and vector error correction model to estimate the relationship between these factors and GDP growth. The results indicate the existence of a long-run equilibrium relationship between the health factors and GDP growth; however, in the short term, the variables are found to be in a state of disequilibrium. Specifically, the study reveals that infant mortality, road traffic mortality, and healthcare expenditure exhibit a strong negative relationship with GDP growth, while the maternal mortality ratio displays a weak positive relationship. The findings of this research hold significant implications for policymakers who are striving to achieve sustainable GDP growth as outlined in Saudi Vision 2030. These findings suggest that policymakers can simultaneously promote higher GDP growth and reduce infant mortality, road traffic mortality, and healthcare expenditure. Although the maternal mortality ratio exhibits a relatively weak positive relationship with GDP, it is still crucial for policymakers to address this issue to enhance sustainable GDP growth, aligning with the objectives set forth in Saudi Vision 2030. Overall, this study bridges a research gap and provides valuable insights that can inform health and economic policies in Saudi Arabia.

Modelling Short-run Dynamics of Macroeconomic Variables on GDP in Ecowas Countries Using Panel Vector Autoregression Model

This study implemented Panel Vector Autoregression (PVAR) Model to examine short-run dynamic relationships between inflation rate, population and unemployment rate as function of Gross Domestic Product (GDP) for Economic Community of West Africa States (ECOWAS) counties. To achieve this, secondary data was sourced for Population, Inflation rate, Unemployment rate and GDP from National Bureau of Statistics, Nigeria and ECOWAS office Nigeria covering from 1991 to 2020. The study implemented PVAR (1) and PVAR (2) models but only PVAR (2) model fulfilled the stability condition. Results from the analysis PVAR (2) model for GDP shows that GDP, population, inflation rate and unemployment rate at lag 1 are all positively related to GDP but only GDP and population at lag 1 are significant (P<0.05). While at lag 2 for GDP model, inflation rate and unemployment rate are negatively related to GDP though only GDP and population were significant (P<0.05). This study therefore concluded and recommended that in the short run, previous GDP and population data are significant in determining current GDP in ECOWAS countries.

The dynamic relationship between trade openness, foreign direct investment, capital formation, and industrial economic growth in China: new evidence from ARDL bounds testing approach

The objective of this research is to use annual data from 1990 to 2021 to examine the long- and short-run dynamic relationships among China’s trade openness (TRO), foreign direct investment (FDI), capital formation (K), and industrial economic growth (IEG) using the Autoregressive Distribution Lag (ARDL) method. Firstly, the results of the ARDL co-integration tests show that there is a long-run co-integration relationship among TRO, FDI, K, and IEG. Secondly, from a path of influence perspective, both the long- and short-run relationships are almost the same. Specifically, TRO, FDI, and K all have positive effects on IEG and vice versa, which supports the feedback hypothesis. However, contrary to the short-run relationship, TRO and K have a small negative effect on IEG, but this is not statistically significant. Finally, K and TRO positively affect FDI, while FDI negatively affects K, although the effect is minimal and negligible at the 10% significance level. On the contrary, they are not statistically significant in the long run. These results support the theory that technological innovation in the trade, investment and capital system based on economic and market capital can stimulate the development of China’s industrial economy.

The Potential of Human Capital Investment in Contributing to Economic Growth: ARDL Approach in the Context of Eastern and Southern Africa

Despite 25 years of exceptional progress in human development, there are still significant obstacles to overcome, particularly for underdeveloped nations. Numerous African countries devote substantial support to ensuring quality employment, a skilled workforce, and the building of an inclusive labour market. Hereby, the actual paper investigates the potential of human capital investment in contributing to the economic growth of Eastern and Southern Africa from the period 2001 to 2020. The study also attempts to determine the factors that promote skilled workforces in African countries. To carry on with the examination the study used an Autoregressive Distributed Lag (ARDL) model and the Granger causality tests. The rationale behind using these models is to capture the long-run and short-run dynamic relationship among the variables and to observe the direction of these relationships. Within this framework, the results exhibited that both during the long run and short run the educational level of individuals, government expenditure in education, and labour tax contribution affect the economic growth of the region. Whereas the Granger causality test establishes a one-way causal relationship between all educational levels and economic growth. The test presented no clear connection between government expenditure on education, labour tax, and GDP. Finally, the research provides evidence about the importance of investing in human capital to promote long-term economic growth. And how the government's efforts and educational system operate in Eastern and Southern Africa, which is a geographic region that is often overlooked.

The impact of foreign direct investment, renewable and non-renewable energy consumption, and natural resources on ecological footprint: an Indian perspective

PurposeGlobally, India ranks third in greenhouse gas (GHGs) emissions. Decarbonizing India's economy would necessitate significant changes in how the country generates energy, manufactures things, delivers services and manages natural resources. Recently, scholars from different parts of the world have used various indicators like carbon and methane emissions to investigate potential solutions to the global warming problem that has resulted in climate change. Therefore, this study aims to investigate the impact of foreign direct investment, renewable and non-renewable energy consumption, in addition to economic growth, trade openness, and natural resources on ecological footprint.Design/methodology/approachUsing India's yearly data from 1990 to 2016, this research investigates the impact of direct foreign investment (FDI), trade (TA) and natural resources (NR) on the ecological footprint (EF) within the framework of economic growth (GDP), renewable (RE) and non-renewable (NRE) energy consumption. The Zivot–Andrews unit root approach was used to examine the structural breaks in data series and the presence of stationary. An auto regressive distributive lag model was used to investigate the presence of long-run and short-run dynamic relationships among the variables.FindingsThe empirical findings demonstrate that FDI, RE and GDP have a negative and substantial impact on EF in the long term; in contrast, NRE and TA are significant and positive. The Granger causality test indicates that feedback transmission was observed between NR and EF and TA and EF. One-way causation passed from GDP to FDI and NR; TA to FDI and RE.Originality/valueIndian Government and authorities should push for an eco-friendly manufacturing process and technology adaptation to improve environmental quality.

Impact of Exchange Rate on Export in Nepal

This study examines the short-run and long-run co-integration of theexchange rate on export of Nepal. Data are extracted from the published source of World Bank from 1975 to 2020. ARDL Bounds test is applied to test the co-integration after the test of unit root. The dependent variable is export and the independent variables are exchange rate, import, money supply and GDP.Augmented Dickey- Fuller test shows the variables are in the order of I(1) where the error correction term is negative and significant. The results show there is long- run co-integrationand the study also supports the short-run dynamic relationship between the dependent and independent variables that show the long-run and short-run impact of exchange rate on export of Nepal.So, the policy makers should focus on increasing export and reducing import and its sound exchange rate policy.

Revisit of Tunisia’s Money Demand Function: What About Oil Price and Exchange Rate Effects?

This paper examines the long run and short run dynamic relationship between real broad money and macroeconomic factors in Tunisia for the period 2010M01 to 2019M07. We employ linear and NARDL bound testing approach for co-integration between the money demand measure and its determinants. Three real broader money demand variables (M2, M3, and M4) are considered to show that exchange rate have asymmetric significant effects once we introduce nonlinearity in the long run as well as in the short run association. Then, by using the (Shin et al., 2014) NARDL approach, we show that currency appreciation and depreciation could affect the demand for money in an asymmetric manner. However, in the long run, it is only the oil price and Tunisian Dinar (TD) depreciation and appreciation which have significant effect out of the five considered macroeconomic factors (real income, interest rates, inflation, oil price, and the exchange rate). Besides, the QSUMSQ stability tests results reveal that only real M3 money demand function which is clearly stable. In implementing monetary policy, the Tunisian central bank (TCB) should target the M3 monetary aggregate and take into account of the exchange rate changes stabilization.

COVID-19 Entwined the Dynamic Relationship between Stock Returns and Macroeconomic Variables

This study examines the dynamic relationship between macroeconomic variables and stock prices in Pakistan in the COVID-19 pandemic scenario. For this purpose, monthly data has been taken from Jan 2019 to June 2021 and divided into Pre-COVID, COVID and overall periods. Data have been retrieved from various sources including Statistical Reviews & Bulletins of State Bank of Pakistan, Karachi Stock Exchange and Pakistan Economic Survey. To assess the relationship between economic variables and stock prices, Cointegration, Granger-causality and Impulse Repose Function Tests have been applied on three data series. The results of the study reveal that there is a long-term equilibrium relationship between all economic variables and stock prices in the Pre-COVID period. However, most of the economic variables do not have such a relationship during the COVID period and the pattern of the relationship is almost the same in the overall period. Even the short-run dynamic relationship between economic variables and stock returns is affected by the pandemic. The results show that economic variables affect stock returns differently in the COVID situation than in the Pre-COVID scenario and it also affects the short-run relationship in the overall period. This research study provides imminent findings on the linkage between macroeconomic variables and stock prices in the Pakistani context. It helps investors and regulators in customizing their decisions and macroeconomic regulations respectively to improve the financial and economic stability of the country in the wake of the pandemic.

An Analysis of the Relationship between Inflation and Gold Prices: Evidence from Turkey

In this paper, we examine the short and long run dynamic relationship between inflation (consumer price index) and the price of gold in Turkey by using monthly data over the period of 2008m10-2021m04. The finding shows there is no long run and cointegration between consumer price index and the price of gold in Turkey. However, the results demonstrate that CPI does Granger cause of gold but gold dose not Granger cause of CPI. Those results are also confirmed by results of short-run of S-model and the long-run properties of the accumulated impulse responses of structural VAR (SVAR) model that there is not long run interaction between gold and inflation.

KEMAJUAN TEKNOLOGI DAN KECEPATAN PERPUTARAN UANG: STUDI KASUS INDONESIA

Technological developments and financial innovations, especially in the payment system, have encouraged banks around the world to carry out a number of innovations that have resulted in a new paperless based financial system. The finding that the payment system innovation affects the circulation of money and the stability of the monetary condition of a country, makes this risk possible in Indonesia. By using the error correction model, this study can provide information on the short run dynamic relationship and the impact of payment system innovation represented by non cash payment instruments such as credit cards, debit cards, e-money and payment transaction settlement processes (national clearing system and real time gross settlement) on the velocity of money in Indonesia in the period 2016M1 to 2020M6. The results of the research findings state that the impact generated by the rapid velocity of payment system innovation on the velocity of money circulation is not temporary, this is evidenced by the effect of payment system innovation on the velocity of money circulation which continues over a long period of time.

Kemajuan Teknologi dan Kecepatan Perputaran Uang: Studi Kasus Indonesia

Technological developments and financial innovations, especially in the payment system, have encouraged banks around the world to carry out a number of innovations that have resulted in a new paperless based financial system. The finding that the payment system innovation affects the circulation of money and the stability of the monetary condition of a country, makes this risk possible in Indonesia. By using the error correction model, this study can provide information on the short run dynamic relationship and the impact of payment system innovation represented by non cash payment instruments such as credit cards, debit cards, e-money and payment transaction settlement processes (national clearing system and real time gross settlement) on the velocity of money in Indonesia in the period 2016M1 to 2020M6. The results of the research findings state that the impact generated by the rapid velocity of payment system innovation on the velocity of money circulation is not temporary, this is evidenced by the effect of payment system innovation on the velocity of money circulation which continues over a long period of time.

The Tripartite Dynamic Relationship between Poverty, Unemployment and Construction Sector: Empirical Evidence from Nigeria

Abstract The increasing rate of poverty and unemployment in Nigeria has necessitated further efforts towards alternative means of reducing the trend, outside the government’s microeconomic mechanisms. As a sector with multiplier effects on other sectors of economy through its numerous activities, the construction sector is expected to reduce both poverty and unemployment. This study, therefore, examined the relationships between construction sector variables, poverty and unemployment rates in Nigeria. Using socio-economic data published by the Central Bank of Nigeria, National Bureau of Statistics, United Nations Development Program and World Bank from 1981-2019, the study deployed an Autoregressive Distributed Lag (ARDL) approach to analyze the relationships between construction sector variables, poverty, and unemployment rates. It also used Granger causality test to determine the direction of causation between the variables under investigation. The results showed that there are both long-run and short-run dynamic relationships between poverty rate and construction sector variables (F-stat. (3.93) > upper (3.67) and lower (2.79)) bounds. It showed that no long-run balanced relationship exists between the unemployment rate and construction sector variables (F-stat. (2.01) < lower (2.79) and upper (3.67)) bounds. The result further revealed that there are significant and positive linear correlations between construction sector variables, poverty, and unemployment rates; except between construction output and poverty rate, where an insignificant linear relation was established. Nevertheless, the relationships could not result to direct causal effect, except a unidirectional Granger causal relationship that flows from government capital expenditure to construction service recurrent expenditure and construction output, and from construction service recurrent expenditure to construction output. Consequently, the study suggested that construction sector expenditure and output should be directed towards poverty and unemployment reduction. This could be done through the diversification and integration of all construction sub-sectors, particularly the private sector into the nation’s economic equation. Thus, this study would direct the paths of policy makers and construction planners towards the right construction policies and plans that would lead to reduction in unemployment and poverty rates with a long-term economic transformation in Nigeria.

Impacts of urbanization on carbon emissions: An empirical analysis from OECD countries

The impacts of urbanization on carbon emissions have attracted widespread attention for a long time. Quantitative research on the impacts is of great significance for formulating carbon reduction policy. Based on the dynamic panel autoregressive distribution lag (ARDL) model, we systematically study the general and heterogeneous long-run equilibrium relationships, short-run dynamic relationships, impact mechanism and lag effect between urbanization and three carbon emission dimensions in OECD high-income countries during long period. The main empirical results indicate that developed countries tend to have the same negative impacts of urbanization on carbon emissions, although there are differences in the endowments of different countries. The impact is relatively weak, for each percentage point increase in urbanization rate, CO 2 emissions per capita decrease by 0.015%, total CO 2 emissions decrease by 0.012%, and CO 2 emission intensity decrease by 0.009%. All member countries have achieved the decoupling of urbanization and carbon emissions. Urbanization affects carbon emissions by affecting economic growth, energy efficiency, and final energy consumption structure. This paper further reveals the multi-level impacts of urbanization on carbon emissions and provides policy implications of achieving carbon reduction through urbanization's agglomeration effect for government decision makers. • Estimate the impact of urbanization on carbon emissions based on panel ARDL model. • Analyze general & heterogeneous long-, short-run relationship and impact mechanism. • Urbanization decreases carbon emissions but the impact is weak in OECD countries. • Developed economies have achieved the decoupling of urbanization and CO 2 emissions. • Promote urbanization process and exert its scale effect to reduce carbon emissions.

Explain the Determinants of Credit Spreads in the US

This paper focuses on how economic variables affect Baa corporate bond spreads in the US from January 1990 to December 2018. Credit spreads in this paper are defined as the Baa corporate bond yield minus the Aaa corporate bond yield, and are explained by four variables which are interest rates, the slope of yield curve, the stock market volatility and the economic environment. Cointegration analysis and VAR model are used in this paper to estimate the effects of the determinants of the credit spreads in the long-run and in the short-run respectively. The impacts of the industrial production index and the slope of yield curve on the Baa credit spread are negative, and the impacts of 10 year Treasury bond rate and the stock market volatility on the credit spreads are positive in the long run. In the short-run dynamic relationship, the impact of the industrial production index and the 10 years Treasury bond interest rate are negative for the credit spreads, and the slope of yield curve and stock market volatility are positive for the Baa credit spreads.

A dynamic relationship between crude oil price and Indian equity market: an empirical study with special reference to Indian benchmark index Sensex

PurposeThe purpose of the study is to investigate the long-run and short-run dynamic relationship between crude oil prices and the movement of Sensex for the period of 2000–2018.Design/methodology/approachThe study uses the augmented Dickey–Fuller test for the presence of unit root, Johansen cointegration test for estimating the cointegration among the variables. Further, in the case of no cointegration found, the study employed the vector autoregression (VAR) model to estimate the long-run relationship and the Granger causality/Wald test for short-run relationship. The study also conducted tests for the prerequisites of the model: serial correlation, heteroskedasticity and normality of data.FindingsThe study found that both the variables, crude oil prices and Sensex are integrated of order 1, that is, I (1), and there is no cointegration between them. Further, the results proliferated from the VAR model unfold the marked effect of previous month crude oil prices (lag 1) on the movement of Indian stock market represented by Sensex considered as the benchmark index. Furthermore, VAR–Granger causality/block exogeneity Wald tests results indicated that there is a causal relationship between the crude oil prices and Sensex under the VAR environment. The model does not have any serial correlation and heteroskedasticity indicating toward the unbiased and robust estimates.Research limitations/implicationsThe study is conducted till the year 2018, and data for the present period (post-2018) is excluded due to ongoing trade issues between the USA and oil-exporting countries such as Iran. The current COVID-19 outbreak has also put serious issues. Due to limited time and availability of standardized data, researchers have considered Sensex as equity index only, but for more generalized research outcome few other equity indexes could have been taken for study.Originality/valueThe study is completely original in nature and is an extensive study of the relationship between the crude oil price and Indian stock market with reference to causality between the variables.

Determinants of Rice Import Demand in Nigeria

Primarily, the study examined the determinants of rice import demand in Nigeria by assessing the short run and long run dynamic model relationships among the determinants, trends and extent of causality among per capita income, population, exchange rate and price of rice imports were equally examined, using data obtained from the Central Bank of Nigeria (CBN) and National Bureau of statistics (NBS) over the period 1961 to 2013. Data obtained showed the perceived determinants of imports demand for rice in Nigeria were local rice production, rice import price, rice consumption, per capita income, and exchange rate, price of local rice, domestic stock variation, maize price, meat price and demographic development. The short run dynamic model result showed that rice consumption, price of meat, price of maize, local rice quantity, demography development and stock variance are statistically significant at 5%. The significance of the coefficient of the error correction term confirmed theappropriateness of the error correction approach which also showed that ignoring the long run relationship is detrimental. The result however, revealed that rice import demand increases significantly with increasing rice consumption, increasing price of meat, increasing price of maize (keeping that for imported rice unchanged) and increasing demography development. Rice import price, per capita income, price of local rice and exchange rate had no significant effects on rice import demand. The study therefore recommends that locally-produced rice should be intensively improved.
 Keywords: demography, determinants, Error correction mechanism, rice import demand

INTERNATIONAL DEVELOPMENT ASSISTANCE AS PREDICTOR OF ECONOMIC GROWTH IN NIGERIA

The focus of this study was to test if International development assistance bring any change in the Nigerian economy. The data was based on the foreign aid inflow for the period of 1986 to 2016. Stationarity of data is established using the unit root test. For testing the direction of causality, short run and long run dynamic relationship between independent and dependent variables, Granger Causality Procedure, Johansen Co-Integration and Error Correction Model is utilized. Finding indicate that International development assistance bring improvement in the Nigerian economy. Furthermore, long run equilibrium relationship between official development assistance and economic growth is established in this study.

Does Profitability of a Corporation Depends on It’s Corporate Social Responsibility?

This study was to find the impact of corporate social responsibility practices on the firm financial performance of the oil and gas sector of Pakistan. For this study, fourteen companies of the oil and gas sector, listed on the Karachi stock exchange of Pakistan were selected as samples. Secondary data has been collected covering ten years from 2010-2019. The data was collected from the annual report and state bank site of Pakistan. E-views have been used to test the impact of CSR and firm profitability. For this study four tests were used to check the significance and stationarity of data. In which include Unit Root test, Co-integration, Vector Error Correction Estimation, and Granger Causality test. On the basis of the Unit Root test results, all variables show the stationarity. According to the results of Cointegration, there is no long-run relationship between variables. According to Granger Causality results shows all variables are move to another and impact on another if CSR take dependent variable excluded net profit after tax (0.0249), net profit margin (0.9989) and total assets are (0.4841) so, in which all three variables are move to one variable that is CSR. In vector error correction estimates take a137 observations these observations shows a results about short run dynamic relationship of variables. So In overall tests are used for analysis shows significant and stationarity results and these are good for study so it means these results create a positive impact on CSR and firm performance.

Exploring the Climate Change Impact on Major Food Crops of Bangladesh - A Time Series Analysis

This paper tries to explore the dynamic relationship between the yield of major crops in Bangladesh (aus, amas, boro, wheat and potato) and climate change (average rainfall, average maximum temperature and average minimum temperature). Graphical visualization shows that, there is increasing trend in average annual minimum temperature and average annual minimum rainfall, while there is decreasing trend of average annual maximum temperature. We applied autoregressive distributive lag (ARDL) cointegration method in order to study the dynamic relationship. The paper finds long run dynamic link between yield of aus rice and average rainfall and average minimum temperature. We have found short run dynamic relationship for yield of aman rice, boro rice and potato. However, we do not find any dynamic relationship has been found for yield of wheat with the variables of climate change. After estimation the dynamic relationship, we ensure there is no serial correlation among residuals using Breusch-Godfrey test and models are normally distributed using histogram and Jarque-Bera test. Finally, we ensure the stability of the models applying CUSUM test.