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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.

The objective of this study is to explore the dynamic inter-linkage between foreign aid and economic growth in Sri Lanka over the period of 1960–2018.

Both exploratory and inferential data analysis tools have been employed to examine the objective of this study. The exploratory data analysis covered the scatter plots, confidence ellipse with kernel fit. The inferential data analysis included the augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) unit root tests, the autoregressive distributed lag (ARDL) Bounds co-integration technique and the Granger causality test.

The test result of exploratory data analysis indicates that there is a positive relationship between foreign aid and economic growth. The ADF and PP unit root tests results indicate that the variables used in this study are stationary at their 1st difference. The co-integration test result confirms the presence of long-run relationship between foreign aid and economic growth in Sri Lanka. The estimated coefficient of foreign aid in the long-run and the short-run shows that foreign aid has a positive relationship with economic growth in Sri Lanka. The estimated coefficient of error correction term indicates that approximately 26.6% of errors are adjusted each year and further shows that the response variable of economic growth moves towards the long-run equilibrium path. The Granger causality test result shows that foreign aid in short-run Granger causes economic growth in Sri Lanka which means that one-way causality from foreign aid to economic growth is confirmed. Further, the estimated coefficient of error correction term confirms that there is the long-run Granger causal relationship between foreign aid and economic growth in Sri Lanka.

The findings of this study have some important policy implications for the design of efficient policy related to foreign aid and economic growth, the knowledge of which will help follow sustainable foreign aid and growth nexus.

This study contributes to the existing literature by using the newly introduced ARDL Bounds cointegration technique to investigate the dynamic inter-linkage between foreign aid and economic growth in Sri Lanka.

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 purpose of this study aims to investigate the nature of the relationship between workers' remittances and financial development (FD) in Sri Lanka for the period from 1975 to 2017.

This study used both the exploratory data analysis and inferential data analysis (IDA) techniques to test the objective of this study. The IDA technique consisted of the augmented Dickey–Fuller (ADF) and Phillips–Perron unit root tests, the autoregressive distributed lag (ARDL) bounds cointegration technique, the Granger causality test and impulse response function analysis.

The unit root test results show that the variables are in mixed order. The empirical results of cointegration confirm that workers' remittances have a beneficial long-run relationship with FD in Sri Lanka. The Granger causality test result indicates that there is a bidirectional relationship between workers' remittances and FD. The impulse response analysis indicates that a positive shock to workers' remittance has an immediate significant positive impact on the FD of up to 10 years.

The analytical techniques used in this study explain how workers' remittances induce FD in Sri Lanka.

This study fills an important gap in the academic literature by using newly developed ARDL bounds cointegration techniques in Sri Lanka, by using impulse response function analysis, and by studying the dynamic relationship between workers' remittances and FD using time series data.

The objective of this study is to examine the inter-temporal relationship between workers' remittances and consumption expenditure in Sri Lanka over the period of 1975–2017 using the annual time series data.

To test the order of integration of the variables used in this study, the augmented Dickey–Fuller (ADF) and Phillips and Perron (PP) unit root tests were employed. The autoregressive distributed lag (ARDL) bounds cointegration technique was used to examine the long-run relationship between the variables. The Granger causality test was used to examine the causal relationship between the variables.

The unit root tests confirm that the variables are stationary at 1st difference I(1). Meanwhile, the ARDL test results show that workers' remittances have a positive long-run relationship with consumption expenditure in Sri Lanka. The coefficient of the error correction term indicates that 9.3% of disequilibrium error is adjusted each year and the response variable of the consumption expenditure moves towards the long-run equilibrium path. Further, the results of the Granger causality test indicate that workers' remittances Granger cause consumption expenditure in the short-run.

The findings have some important policy implications for the design of efficient policy related to workers' remittances and consumption expenditure pattern, the knowledge of which will help promote the macroeconomic stability and welfare of people in Sri Lanka.

This study contributes to the existing literature by using newly developed ARDL bounds cointegration techniques to investigate the inter-temporal relationship between workers' remittances and consumption expenditure in Sri Lanka. Furthermore, to our knowledge, this study is the first research in examining the inter-temporal relationship between workers' remittances and consumption expenditure in Sri Lanka.

This study aims to investigate the cointegration and causality relationships between Hong Kong’s residential property price and stock price, using quarterly data, from the 1st quarter of 1980 to the 3rd quarter of 2015.

In contrast to other studies, the cointegration test used is the autoregressive distributed lag (ARDL) cointegration (bounds testing) approach of Pesaran et al. (2001) that based on the estimation of an unrestricted error correction model and the causality test is based on non-causality test of Granger et al. (2000). Moreover, this research employs recursive least square procedures and Chow (1960) breakpoint test to detect unknown structural break and variation of relationships between residential property and stock price over the whole sample period.

The results of ARDL cointegration tests running from stock to residential property markets provide strong evidence to support the hypothesis that the stock and residential properties are cointegrated. The results of Granger et al. (2000) non-causality test support the view of wealth effect that stock price has an important causal effect on residential property price in Hong Kong but not vice versa. In addition, the results of recursive ordinary least squares coefficients estimates and Chow (1960) test (breakpoint test) for structural instability confirm the variation of the relationships between stock and residential property markets over the sample period.

The empirical results from cointegration and causality tests suggest that the residential asset returns are better predicted by including the lagged difference values of stock price.

This is the pioneering study to examine the cointegration and causality study of stock and residential property price in Hong Kong by employing Pesaran ARDL cointegration approach and Granger non-causality approach. Investors are able to perform an effective evaluation to assist in allocating investment funds, and the government bodies can implement supplement housing policy in response to the public needs.

Net energy importing countries (NEICs) pursue strategic policies to reduce the consumption of energy from conventional sources and increase that of renewable energy to attain energy security and sustainable development. However, net energy exporting countries (NEECs) rely substantially on the proceeds realised from oil and gas exports to mainly NEICs to finance government activities. This paper aims to investigate the effect of increased consumption of renewable energy in developed NEICs on the Nigeria’s oil and gas exports.

The study was undertaken by analysing macro-economic annual time-series data set (1980-2014) using autoregressive distributed lag (ARDL) bounds testing approach.

Both the short-run and the long-run results of the ARDL modelling reveal that renewable energy consumption in developed NEICs is affecting Nigeria’s oil and gas exports negatively, thereby causing significant decrease in the amounts of revenue being generated therefrom.

Like most empirical studies, the conduct of this research has encountered some challenges. Thus, the use of rather small sample in terms of period covered (1980-2014), annual frequency of data and focus on one NEEC (Nigeria) are the key limitations of this paper. While the first two challenges were dealt with by using ARDL, future research can focus on other NEECs to extend the study.

The findings have several policy implications, including the need for Nigeria to focus on developing internal market trajectories to increase domestic utilisation of its conventional energy rather than depending on external markets. The results also suggest the need for public policymakers to develop a strategic plan that will effectively address the external economic threat arising from the influence of global energy transition.

To the best of the authors’ knowledge, this paper represents the first effort to empirically examine the effect of renewable energy consumption by developed NEICs on the Nigeria’s oil and gas exports. The paper contributes to the literature by providing insight into and documenting evidence that the world is taking transitioning to cleaner energy sources very seriously.

This study investigates the short-run and long-run impacts of agricultural credit on Vietnam's agricultural GDP over the period 2004:Q4–2016:Q4, with the incorporation of agricultural labor, public investment and rainfall as important determinants of agricultural GDP.

This study applies the indicator saturation (IS) break tests and the autoregressive distributed lag (ARDL) bounds test with structural breaks to examine the credit–agricultural performance nexus. The causal relationships among variables are explored through the Toda–Yamamoto Granger causality test.

The results indicate that agricultural credit positively influences agricultural GDP in both the short-run and long-run. A unidirectional causal relationship running from credit to agricultural GDP is confirmed. The results also discover the positive and significant effects of labor and rainfall on agricultural GDP in the long-run.

The results imply that the government should focus on expanding agricultural credit as well as enhancing the efficiency of agricultural credit. Furthermore, formal credit institutions should be encouraged to work closely with farmers and agricultural enterprises to offer flexible lending periods and amounts to meet the real situation of agricultural production.

This study is the first to examine the credit–agricultural performance relationship at the macro-level in Vietnam. Based on the empirical results, the study provides crucial implications for policymakers to optimize the effectiveness of agricultural credit and enhance nationwide agricultural performance.

This paper investigates the relationship between domestic gold prices and inflation in Vietnam based on the monthly series of the gold price index and consumer price index over the period of December 2001–July 2020.

The co-integration between the domestic gold price and inflation is examined within the autoregressive distributed lag-error correction (ARDL bounds testing) framework. This paper also applies the vector error correction model (VECM) and impulse response function analysis to explore the causal relationship between these two variables. Moreover, since both gold and inflation series are likely to have structural changes over time, a unit root test controlling for significant breaks is employed in this paper.

Findings from the ARDL bounds testing model suggest the presence of a co-integration between the underlying variables. The VECM indicates that shocks in inflation lead to a negative response to gold prices in the long run. In the short term, only fluctuations in gold prices impact inflation, and this causality is unidirectional.

Gold is regarded as a critical financial asset to preserve wealth from inflation pressure in the case of Vietnam. These findings propose implications for both investors and policymakers.

Empirical results suggest that inflation has a long-term impact on gold prices in the Vietnamese market. In the existence of a permanent inflationary shock, domestic prices of gold respond negatively to this shock; hence, gold can act as a good hedge against inflation in Vietnam.

This study aims to explore the relationship among energy consumption, real income, financial development and oil prices in Italy over the period 1960-2014.

Different econometric techniques – such as the General Methods of Moment (GMM) or the AutoRegressive Distributed Lags (ARDL) bounds test – are usually used in the empirical analysis. Moreover, both the Toda and Yamamoto causality tests and the Granger causality tests are applied to the data.

The results of unit root and stationarity tests show that the variables are non-stationary at levels, but stationary in first-differences form, or I(1). The ARDL bounds F-test reveals an evidence of a long-run relationship among the four variables at 1% significance level. Moreover, an increase in real GDP and oil prices has a significant effect on energy consumption in the long run. The coefficients of estimated error correction term are also negative and statistically significant. In addition, the paper explores the causal relationship between the variables by using a VAR framework, with Toda and Yamamoto but also Granger causality tests, within both multivariate and bivariate systems. The findings indicate that energy consumption is affected by real GDP.

The study also filled the literature gap of applying ARDL technique to examine this relevant issue for Italy.