Search results

The purpose of this paper is to focus on modeling economy growth with indicators of knowledge-based economy (KBE) introduced by World Bank for a case study in Iran during 1993-2013.

First, for grouping and reducing the number of variables, Tukey method and the principal component analysis are used. Also for modeling, 67 per cent of data is used for training in the two approaches of ARDL bounds testing and gene expression programming (GEP) and 33 per cent of them for testing the models. Then, the result models are compared with fitness function and Akaike information criteria (AIC).

The GEP model with fitness 945.7461 for training data and 954.8403 for testing data from 1000 is better than ARDL bounds testing model with fitness 335.5479 from 1000. In addition, according to model comparison tools (AIC), the GEP model has an extremely larger weight in comparison with ARDL bounds model. Therefore, the GEP model is introduced for future use in academia.

Knowledge and information is one of the most basic sources of wealth in economists’ sight. Thus, using KBE indicators appears essential in economic growth regarding daily progress in knowledge processes and its different theories. It is also extremely important to determine an appropriate model for KBE indicators which play a highly important role in the allocation of the economic resources of the country in an optimal manner.

This paper introduced a novel expression for economy growth using KBE indicators. All the data and the indicators are extracted from Word Bank service between 1993 and 2013.

This study aims to empirically examine the relationship between energy consumption and agricultural economic growth in Pakistan over the period from 1984 to 2016.

This study used the autoregressive distributed lag (ARDL) bounds testing approach to cointegration to investigate the long-run and short-run determinants of agricultural economic growth in Pakistan.

The results of the ARDL bounds testing approach to cointegration revealed that long-run linkage exists among the study variables. The findings of this paper showed that agricultural economic growth is positively affected by gas consumption and electricity consumption both in the long-run and short run. The long-run and short-run coefficients of gas consumption and electricity consumption were estimated to be 0.906, 0.421, 0.595 and 0.276, respectively. The estimated equation remains stable during the period from 1984 to 2016 as analyzed by the stability tests.

This study considers the relationship between energy consumption and agricultural economic growth in Pakistan by using an ARDL bounds testing approach to cointegration. The study has three contributions to economic literature:this study used different unit root tests to test stationarity of the variables such as ADF unit root test by Dicky and Fuller and P-P unit root test by Philip and Perron; the ARDL bounds testing approach to cointegration is applied to test the existence of long-run analysis between energy consumption and agricultural economic growth; and to check the robustness, the authors used the Johansen cointegration test to examine the long-run relationship between dependent and independent variables.

The study aims to evaluate the long- vs short-run relationships between crops' production (output) and crops' significant inputs such as land use, agricultural water use (AWU) and gross irrigated area in India during the period 1981–2018.

The study applied the autoregressive distributed lag (ARDL) bounds testing approach to estimate the co-integration among the variables. The study uses the error correction model (ECM), which integrates the short-run dynamics with the long-run equilibrium.

The ARDL bounds test of co-integration confirms the strong evidence of the long-run relationship among the variables. Empirical results show the positive and significant relationship of crops' production with land use and gross irrigated area. The statistically significant error correction term (ECT) validates the speed of adjustment of the empirical models in the long-run.

The study suggests that the decision-makers must understand potential trade-offs between human needs and environmental impacts to ensure food for the growing population in India.

For a clear insight into the impact of climate change on crops' production, the current study incorporates the climate variables such as annual rainfall, maximum temperature and minimum temperature. Further, the study considered agro-chemicals, i.e. fertilizers and pesticides, concerning their negative impacts on increased agricultural production and the environment.

This paper aims to examine the relationship between trade and economic growth using data of UAE economy for the period of 1974-2011.

The bounds testing is applied for testing the cointegration relationship between the variables. The rolling window approach has been used to analyze the stability of long run coefficients.

The empirical analysis shows the presence of cointegration between trade and economic growth. Furthermore, exports have positive, but imports have negative effect on economic growth. The rolling window approach confirms the stability of long-run estimates.

This paper provides new insights for policymakers to use trade as economic tool for sustainable economic development.

This paper makes a unique contribution to the literature with reference to UAE, being a pioneering attempt to investigate the relationship between trade and economic growth by using long time series data and applying more rigorous techniques like time varying rolling window analysis.

The purpose of this paper is to examine the impact of base lending rate (BLR), consumer prices, gross domestic product, money supply (M₃), Karachi stock exchange composite index, KIBOR, and profit rate of Islamic banks on deposits of both conventional and Islamic banks in Pakistan.

Quarterly data of six years (2006-2011) are obtained from 30 banks, consisting of 25 conventional and five Islamic banks. The short-run as well as long-run relationships among these variables are examined by utilizing advanced time series approach. Bounds testing and autoregressive distributed lag have been used to examine cointegration and error correction framework for short-run dynamics.

The empirical results reveal that variables such as interest rate of conventional banks, profit of Islamic banks, consumer prices, M₃, and BLR have different impact on conventional and Islamic bank deposits. Depositors of conventional and Islamic banks are sensitive to the returns received on deposits. A boost in interest rate increases the deposits of conventional banks but decreases those of Islamic banks.

This study signifies that customers of Islamic banks are motivated by profit. This indicates the normal behavior of customers, hence endures the substitution effect in conventional system. The study has important implications for Islamic banks to offer more competitive rates of profit with respect to the interest rate of conventional banks in order to collect more deposits. It also identifies relevant policy implication for the central bank of the country.

Unemployment is one of the major challenges facing most countries, including Africa as a continent. Seeking how to reduce unemployment, debt, inflation and increase gross domestic product (GDP), foreign direct investment (FDI) and gross capital formation in the continent has been an agenda of governments, policy makers and economists to. This study examines the relationship between economic growth, inflation, debt, FDI, gross capital formation, labor force, population and unemployment in Africa.

An updated panel dataset of 29 African countries was selected from different regions from 1991 to 2019. These countries were selected based on their unemployment, population growth and inflation rates. The Pesaran cross-sectional dependence and panel unit root test (the Dickey–Fuller cross-sectional supplemented and the Im-Pesaran-Shin cross-sectional) were applied. Further, the panel Autoregressive Distributed Lag (ARDL) model (Bounds test) and pooled mean group (PMG) estimator were utilized in this work.

This shows that economic growth, debt, labor force and population have a positive relationship with unemployment in the long run. Therefore, an increase in these variables generates an increase in the selected African countries' unemployment growth. In contrast, inflation, FDI and gross capital formation have a negative relationship with unemployment in the long run, which implies that an increase in these variables reduces unemployment in the selected African countries.

This study has potential limitations because some data from the countries are not up to date and some years are missing from the data.

This study contributes to understanding unemployment and Okun's law in the African economy. This study shows that an increase in economic growth leads to a rise in unemployment, while an increase in inflation leads to a decrease in unemployment.

This paper provides an insight into the major factors that increase and reduces unemployment for government and policy marker to take the adequate measure.

This study attempts to examine the relationship between the banking sector and stock market development in India.

To analyze the relationship between banks and stock market development, the ratio of stock market capitalization to GDP is proxied by stock market development. The determinants of the stock market development are used for analysis namely domestic credit to the private sector as a ratio of GDP is used as a proxy for the development of banks, saving rate, per capita real GDP, and inflation. The autoregressive distributed lag (ARDL)-Bounds testing approach is used for the analysis. The paper also used the unrestricted error correction model and CUSUM and CUSUM square test to check the stability of the model.

The ARDL bounds test found that there is a long-run relationship between stock market development and bank-centered financial development. The results also revealed that the stock market is positively influenced by the development of banks, savings, and per capita real GDP in the short-run as well as long-run.

This paper suggests that improvement of banking sector plays an important role to increase liquidity of the capital market development in India. This paper also suggests that the economic growth and savings rate have positive impact to induce the capital market growth in both short run and long run.

The study has investigated the empirical relationship between the banking sector and the stock market development in a different methodological approach by using an ARDL model which is appropriate for a small sample size. There are few studies related to bank-centered financial development and stock market development in the context of India.

The purpose of this paper is to explore the long-run relationship and causality between economic activity and inbound tourism in the context of the Indonesian economy with a new quantitative methodology.

This research applies a new modified bounds testing approach of Pesaran et al. (2001) by Kripfganz and Schneider (2018) with the period of observation from 1974 to 2017.

The results suggest that there is a unidirectional causality from economic activity to inbound tourism.

This research applies the linear autoregressive distributed lag (ARDL) model and only uses bivariate variables to examine the existence of the tourism-led growth hypothesis. Further studies for the Indonesian case may apply a nonlinear ARDL model. Also, the addition of other socio-economic variables, especially those related to domestic tourism activity, can be applied to improve the model.

This work will provide an alternative quantitative methodology for scholars in studying the relationship between tourism and economic variables.

The findings in this research can complement touristic-public policy decision, and the methodology may be important for knowledge transfer.

This is the first quantitative study to measure tourism-led growth hypothesis in Indonesia by using the latest modified bounds testing approach.

This study aims to offer an up-to-date estimate of capital flight from selected emerging Asian economies and examine the anti-growth phenomenon of capital flight by using annual data for the period 1981–2019.

The study relies on residual methods to derive the estimate of capital flight with necessary adjustments. It then applies the autoregressive distributed lag Bounds testing approach in examining the impact of capital flight on the economic growth of Asian emerging economies.

The study identifies capital flight as the attributor to the slower economic growth of the selected emerging economies of Asia.

Apart from appropriate policies addressing the issues causing capital flight, unleashing the way of private sector-led growth of the emerging countries with necessary policy, infrastructural, institutional and regulatory support can rather help them retain and repatriate domestic capital.

The capital flight estimates in earlier studies are antithetical as they differ in terms of definition and estimation procedure. Again, the growth effect of capital flight in these economies has received meager attention in research and policy debates. Furthermore, being country-specific or region-specific, existing studies are unable to compare the growth effect of capital flight for different emerging economies in this region. Examining the growth effects for a large number of countries separately based on a common estimate of capital flight can resolve these issues that this study aims to do.

The purpose of this paper is to explore and investigate the electricity consumption and production and its linkage to economic growth in Pakistan.

The authors used an augmented Dickey–Fuller unit root test to check the stationarity of the variables, while an autoregressive distributed lag (ARDL) bounds testing approach and causality test were applied to investigate the variables long-term association with the economic growth.

The study results show that electricity consumption in the agriculture, commercial and industrial sector has significant association with economic growth, while electricity consumption in the household and street lights demonstrate a non-significant association with the economic growth. Furthermore, results also exposed that electricity production from coal, hydroelectric, natural gas, nuclear and oil sources have significant association with the economic growth of Pakistan.

This study made a contribution to the literature regarding electricity consumption and production with economic growth in Pakistan by using an ARDL bounds testing approach and causality test. This study provides a guideline to the government of Pakistan that possible steps are needed to improve the electricity production and supply to fulfill the country demand.