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This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.

A dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).

The result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.

Researchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.

Digital financial innovation services if well managed increase the inherent benefits in financial system development.

To the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

This study aims to examine the effect of foreign direct investment (FDI) inflows on tax revenue in 34 developed and developing countries from 2006 to 2020.

Feasible generalised least squares (FGLS), a dynamic panel of a two-step system generalised method of moments (GMM) system and a pool mean group (PMG) panel autoregressive distributed lag (ARDL) approach were used to compare the developed and developing countries. Basic estimators were used as pre-estimators and diagnostic tests were used to increase robustness.

The FGLS, a two-step system of GMM, PMG–ARDL estimator’s results showed that there was a significant negative long and positive short-term in most countries relationship between FDI inflows and tax revenue in developed countries. This study concluded that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue. Meanwhile, there was a significant positive long and negative short-term relationship between FDI inflows and tax revenue in the developing countries. The developing countries sought to attract FDI that could be used to create job opportunities and transfer technology to simultaneously develop infrastructure and impose a tax policy that would achieve high tax revenue.

The present study sheds light on the effect of FDI on tax revenue and compares developed and developing countries through the design and implementation of policies to create jobs, transfer technology and attain economic growth in order to assure foreign investors that they would gain continuous high profits from their investments.

The discussion on international migration has become a significant part of globalization and a topical issue in international relations, especially in developing economies which mostly relies on migrant remittances. The purpose of the study is to examine whether financial market development (equity market development and banking sector development) really drives migrant remittance flow in Sub-Saharan Africa (SSA).

The study employs the dynamic heterogeneous panel data approach-the pool mean group (PMG) and the mean group (MG) techniques in analyzing the model based on data obtained from 27 SSA countries covering the period 2000–2020.

The findings of the study revealed that financial market development (equity market development and banking sector development) is a key driver of migrant remittances flows in the SSA region. In addition, the study revealed that the following macroeconomic variables such as real interest rate, unemployment rate, global growth, emigration, and economic growth are also determinants of migrant remittances flows in the SSA region.

The reviewed empirical literature revealed that several studies documents that the macroeconomic determinants of migrant remittances include inflation, GDP, interest rate, exchange rate, population growth, financial sector development and unemployment rate. Most of these studies fail to capture both equity market development and robust banking sector development (financial market development) as critical drivers of migrant remittances flow in SSA. Also, this study uses a robust measure of equity market development and banking sector development, unlike previous studies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0361

The purpose of this study is to examine two issues, namely the degree of current account deficit (CAD) sustainability and the degree of capital mobility.

The sample for this study comprises 24 Latin American and Caribbean countries, including three regional agreements: Andean Community, MERCOSUR (Mercado Común del Sur), and SICA (Central American Integration System). This study employs the dynamic common correlated effects mean group (DCCEMG) estimator in a panel data set to investigate the long-run relationship between savings and investment along with short-run dynamics.

The findings indicate that CAD is weakly sustainable in the Latin American and Caribbean region, MERCOSUR, and SICA, while CAD is strongly unsustainable in the Andean Community. The sub-period analysis reveals that CAD has been adversely affected by the 2008 crisis. However, in the post-crisis period, CAD has been slowly decreasing in the Latin American and Caribbean region and Andean Community, whereas CAD has continued increasing in MERCOSUR and SICA. Further, the estimates of error-correction terms and short-run coefficients indicate that the Andean Community and MERCOSUR observe a higher degree of long-run and short-run capital mobility than SICA.

The results carry fundamental implications for policy-making processes aimed at maintaining sustainable CADs.

This study gives an alternative interpretation of the “Feldstein-Horioka” coefficient in terms of CAD sustainability and analyses the saving–investment relationship in light of Chudik and Pesaran (2015).

The purpose of this study is to provide new insights into the relationship between fiscal policy and total factor productivity (TFP) while accounting for several economic and econometric issues of the phenomenon like non-stationarity, fiscal feedback effects, persistence in productivity, country heterogeneity and unobserved global shocks and local spillovers affecting heterogeneously the countries in the sample.

The paper is empirical. It builds an Error Correction Model (ECM) specification within a dynamic heterogeneous framework with common correlated effects and models both reverse causality and feedback effects.

The results of this study highlight some new findings relative to the existing related literature. The outcomes suggest some relevant evidence at both the academic and policy levels: (1) the causal effects going from fiscal deficit/surplus to TFP are heterogeneous across countries; (2) the effects depend on the time horizon considered; (3) the long-run dynamics of TFP are positively impacted by improvements in fiscal budget, but only if the austerity measures do not exert slowdowns in aggregate growth.

The main originality of this study is methodological, with possible extensions to related phenomena. Relative to the existing literature, the gains of this study rely on the way econometric techniques, recently proposed in the literature, are adapted to the economic relationship of interest. The endogeneity due to the existence of reverse causality is modelled without implying relevant performance losses of the models. Moreover, this is the first article that questions whether the effects of fiscal budget on productivity depend on the impact of the former on aggregate output growth, thus emphasising the importance of the quality of fiscal adjustments.

Our purpose is the examination of the effects of fiscal policy on private lending for the Eurozone countries. The emphasis is on the identification of the time path of government spending and bank lending.

Fiscal policy is a main factor of macroeconomic stability for the euro area economy. This paper, investigates the impact of government spending on bank lending. For this reason, we present a dynamic theoretical model with a perfectly competitive banking sector, estimated using panel cointegration for the Eurozone countries from 2000Q1 to 2022Q2.

Our findings highlight that, in the long run, consistent management of government spending can have a beneficial multiplicative impact on bank lending for housing and business reasons. This finding is stronger in magnitude for business versus housing lending. The high level of homogeneity of our results across Eurozone countries has positive implications for a common fiscal policy in the future. Finally, authorities should know that policy adjustments are quicker in housing lending when compared to business lending.

In this paper, we contribute to the existing literature, concentrating on the investigation of any existence of long-run and short-run relationships between government spending and bank lending. Additionally, our analysis allows one to investigate the contribution of each Eurozone member state in the short-run and long-run model’s dynamics, providing significant outcomes for the implementation of economic policy and the need for fiscal discipline in the Eurozone.

This paper assesses the environment of legitimacy by determining the role of institutional quality and policy uncertainty on the performance of five major South Asian stock markets (India, Pakistan, Bangladesh, Sri Lanka, and Nepal) using 21 years data from 2000 to 2020. The focus of this study is to approach the issue of the environment of legitimacy that leads to sustained market returns.

Panel cointegration tests of Kao and Pedroni are applied, and the Dynamic Panel Vector Autoregressive (PVAR) model is used to determine the estimates.

ADF P-Values of both Kao and Pedroni tests show that the panels are cointegrated; the statistical significance of the results of the Kao and Pedroni panel cointegration test confirms cointegration among the variables. After determining the most appropriate lag, the analysis is done using PVAR. The results indicate that institutional quality, policy uncertainty, and GDP positively affect stock market return. Meanwhile, government actions and inflation negatively affect stock market returns. On the other hand, stock market return positively affects institutional quality, government action, policy uncertainty, and GDP. While stock market return negatively affects inflation.

The sample is taken only from a limited number of South Asian countries, and the period is also limited to 21 years.

Based on our research findings, we have identified several policy implications recommended to enhance and sustain the performance of stock markets.

This paper uses a unique analytical tool, which gives a better insight into the problem. The value of this work lies in its findings, which also have practical implications and theoretical significance.

Economic literature highlights both positive and negative impact of FDI on economic growth. The purpose of this study is to confirm the relationship between various economic factors and FDI equity inflows and find out deviations, if any. This is investigated using standard time-series econometric models. The long and short run relationship is inquired with respect to market size, inflation rate, level of infrastructure, domestic investment and openness to trade. The choice of variables for Indian economy is purely based on empirical observations obtained from scientific literature review.

The study involves application of autoregressive distributive lag (ARDL) model to investigate the relationship. The long run co-integration between FDI and economic growth is tested by Pesaran ARDL model. The stationarity of data is tested by augmented Dickey Fuller test and Phillip–Perron unit root test. Error correction model is applied to study the short run relationship using Johansen’s vector error correction model method besides other tests.

The results show that the domestic investment, inflation rate, level of infrastructure and trade openness influence inward FDI flows. These factors have both long and short-term relationship with FDI inflows. However, market size is insignificant in influencing the foreign investments inflows. There lies an inverse relation between FDI and inflation rate.

To the best of the authors’ knowledge, the study is original. The methodology and interpretation of results are distinct and different from other similar studies.

Digitalisation, which involves the use of digital technologies in transforming an organisation’s activities, transcends just the acquiring of emerging digital tools. Having the right people to drive the implementation of these technologies and attaining strategic organisational goals is essential. While most studies have focused on the use of emerging technologies in the construction industry, less attention has been given to the ‘people’ dimension. Therefore, this study aims to assess the people-related features needed for construction digitalisation.

The study adopted pragmatic thinking using a mixed-method approach. A Delphi was used to achieve the qualitative aspect of the research, while a questionnaire survey conducted among 222 construction professionals was used to achieve the quantitative aspect. The data gathered were analysed using frequency, percentage, mean item score, Kruskal–Wallis H test, exploratory factor analysis and confirmatory factor analysis.

Based on acceptable reliability, validity and model fit indices, the study found that the people-related factors needed for construction digitalisation can be grouped into technical capability of personnel, attracting and retaining digital talent and organisation’s digital culture.

The findings offer valuable benefits to construction organisations as understanding these identified people features can help lead to better deployment of digital tools and the attainment of the digital transformation.

This study attempts to fill the gap in the shortage of literature exploring the people dimension of construction digitalisation. The study offers an excellent theoretical backdrop for future works on digital talent for construction digitalisation, which has gained less attention in the current construction digitalisation discourse.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.