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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).

This study aims to examine the impact of some real variables such as real effective exchange rates, real mortgage rates, real money supply, real construction cost index and housing sales on the real housing prices.

This study uses a nonlinear autoregressive distributed lag (NARDL) model in the monthly period of 2010:1–2021:10.

The real effective exchange rate has a positive and symmetric effect. The decreasing effect of negative changes in real money supply on real housing prices is higher than the increasing effect of positive changes. Only positive changes in the real construction cost index have an increasing and statistically significant effect on real house prices, while only negative changes in housing sales have a small negative sign and a small increasing effect on housing prices. The fact that the positive and negative changes in real mortgage rates are negative and positive, respectively, indicates that both have a reducing effect on real housing prices.

This study suggests the first NARDL model that investigates the asymmetric effects on real housing prices instead of nominal housing prices for Turkey. In addition, the study is the first, to the best of the authors’ knowledge, to examine the effects of the five real variables on real housing prices.

This study aims to analyze the effect of cryptocurrency capitalization market development on bank deposits variability in the United Arab Emirates (UAE) spanning the period 2005M1–2020M4 using the novel nonlinear autoregressive distributive lag (NARDL).

The study employs the NARDL recently developed by Shin et al. (2014) to estimate the long and short-run relationships between the variables rather than the widely known ARDL (Pesaran et al., 2001), which suffers from a complex structure in the estimation equation that usually includes lags and differences in both short and long terms. The implementation of NARDL required several proceedings after plotting the descriptive data, commencing with unit root tests, selection of lag length, estimating the long-and-short variables coefficients, heteroscedasticity test and Wald test for symmetries.

The long-run estimations of the positive and negative asymmetric coefficients indicate that cryptocurrencies capitalization has a negative impact on bank deposits in the UAE. Further, the short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decrease bank deposits.

The study has applied to the UAE spanning the period 2005M1–2020M4 using the NARDL.

The short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decreases bank deposits, which means that the increase in the magnitude of cryptocurrencies capitalization stimulates depositors and speculators to adjust their portfolios towards contracting their deposits in banks to invest partially in cryptocurrencies, on the other hand, the decline in cryptocurrencies capitalization process spur depositors and speculators to reduce their deposits for purchasing cryptocurrencies at lower prices.

The study infers that individuals and businesses are cautious when investing in cryptocurrencies, and they need more certainty and trust to include these types of assets in their portfolios. The fluctuation in cryptocurrencies capitalization prompts speculators to change their deposits according to the cryptocurrencies' prices.

This study explores the short-and long-run asymmetric impacts of cryptocurrencies capitalization development on bank deposits volatility in the UAE, based on a NARDL, for providing a manifest depiction of whether the cryptocurrencies industry might be a threat to conventional banking system performance in the potential future.

The aim of this paper is to evaluate empirically the impact of oil price fluctuations on the relationship between banking sector development and economic growth in oil-importing MENA countries.

The study used the newly developed panel autoregressive distributed lagged (ARDL) approach in order to address any potential endogeneity between research variables.

The empirical results show a unidirectional causality in the long run from oil price to both economic growth and banking sector development for oil-importing countries. Also, banking sector development not only leads directly to economic growth but also can play a moderator role in the oil price—economic growth nexus.

The study has two principal limitations. On the one hand, this study was conducted in a relatively limited sample of countries. On the other hand, the study did not consider others indicators for banking sector development and others macroeconomic variables.

The results found have imperative implications for banks' managers, regulators and researchers. Bank managers should be more concerned with the negative repercussions of oil price fluctuations on the development of their banks. The regulatory authorities must emphasize policies and strategies to further strengthen their banking sector in order to alleviate the negative influence of oil price shocks on economic growth. Researchers focused on finance-growth nexus must take into account the potential influence of oil price shocks.

The developed conceptual model allows examining to what extent the oil price fluctuations might affect the relationship between economic growth and banking sector development. This effect is neither evaluated nor clarified in the relevant literature.

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.

Globalization occupies a central research activity and remains an increasingly controversial phenomenon in economics. This phenomenon corresponds to a subject that can be criticized through its impact on national economies. On the other hand, the world economy is evolving in a liberalized environment in which foreign direct investment plays a fundamental role in the economic development of each country. The advent of financial flows – foreign direct investment, remittances and official development assistance – can be a key factor in the development of the economy. The purpose of this study is to analyze the effect of financial flows on economic growth in developing countries. Empirically, different approaches have been used. As part of this study, an attempt was made to use a combined autoregressive distributed lag (ARDL) panel approach to study the short-term and long-run effects of financial flows on economic growth. The results indicate ambiguous effects. Economically, the effect of financial flows on economic growth depends on the investor’s expectations.

To study the short-run and long-run effects of financial flows on economic growth, this paper considers an empirical approach based on the panel ARDL. This model makes it possible to distinguish between the short-run effect and the long-run one. This type of model is based on three estimators, namely, mean group, pooled mean group (PMG) and dynamic fixed effect.

Results confirm the existence of a long-run relationship because the adjustment coefficient (error correction parameter) is negative and statistically significant. This paper finds that the PMG estimator is more consistent and more efficient. In the short-run, foreign direct investment do negatively affect economic growth, the effect is no significant in the long-run. On the other hand, the effect of remittances on economic growth is significant in the short-run. However, it is no significant in the long-run. Finally, the results suggest that the effect of official development assistance on economic growth is insignificant; both in the long-run and in the short-run.

To study the interaction between financial flows and economic growth, some empirical methodology are used such as the dynamic panel data and the autoregressive vector (VAR) model. In this study, we apply the panel ARDL model to analyze the short-run and the long-run effect for each financial flow on economic growth. The objective is to study the heterogeneity on dynamic adjustment in the short-term and long-term.

Tourism–economy relationship in India has been studied extensively in the past literature using a single equation approach. However, the present paper diverted from this trend and examined the tourism–economy relationship using the specific to general modelling approach over the 1990–2018 time period. The study also accounts for the influence of merchandise trade, capital formation, foreign investment inflows and inflation on economic growth to achieve the robustness of the coefficient estimates.

To achieve the objective, the study utilised a specific to general modelling strategy. First, the regression equation includes only three core variables: gross domestic product (GDP), international tourist receipts and international tourist expenditures. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegration among the variables. As for the estimation technique, the authors employed autoregressive distributed lag (ARDL) approach.

The paper's findings highlight that tourism receipts and expenditures exert a positively significant impact on economic growth. Moreover, including the additional independent variables does not substantially change the tourism and economic growth relationship. The existence of one-way causality from tourism expenditures to economic growth supports the tourism-led growth hypothesis. These findings highlight the rationale for intervention by the government and policymakers to promote tourism potential and facilities to accelerate the overall growth performance of the country. While the existence of one-way causal effect from economic growth to tourism revenues supports the growth-led tourism development hypothesis, implying that economic expansion is necessary for tourism development.

This research article tried to present a comprehensive picture of India's tourism–economy relationship. However, the present study is organised as an aggregate economy-level analysis. It assumed that the aggregate tourism sector is homogenous. However, different tourism sectors exert different levels of influence on the economy. The authors expect future research can take the disaggregated analysis of the tourism–economy relationship.

This study provides valuable insights into the tourism-led growth hypothesis in India. The study highlights comprehensive intervention by the government and policymakers for accelerating tourism development to invigorate the overall growth performance of the country over the long run. The principal recommendation emerging from the present research is that the tourism growth potential can be depended upon to stimulate the economic performance of the Indian economy.

The present study diverted from the previous empirical studies by following a specific to general modelling strategy. First, the regression model includes only three core variables such as economic growth, tourism receipts and tourism expenditure. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegrating relationship among the variables. GDP growth rate is used as a dependent variable in all five specifications. The idea is to expand the model to capture every feature of the data generating process.

This paper examines the short- and long-run effects of foreign direct investment (FDI) on tax revenue in Ghana.

The paper adopts the autoregressive distributed lag approach to estimate FDI’s long-run and short-run effects on tax revenue. The study uses time-series data from 1983 to 2019 for Ghana, mainly obtained from The Bank of Ghana, the World Bank and the IMF.

The results show that, in the short-run, FDI has no significant effect on direct tax revenue and total tax revenue but significantly hurts indirect tax revenue. In the long run, however, the results show that FDI has significant positive effects on indirect tax revenue and total tax revenue but no significant effect on direct tax revenue.

Empirical studies often fail to analyse the short-run and long-run effects of FDI on tax revenue. This study contributes to the mixed literature by analysing the short-run and long-run effects of FDI on tax revenue in an emerging market context. Additionally, this study employs three tax revenue measures in analysing the nexus.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

This study aims to investigate the main drivers of private saving in Egypt (2005–2020).

It employs an autoregressive distributed lag (ARDL) approach for quarterly data on private saving, lagged private saving, real gross domestic product (GDP) growth, public saving, inflation, real interest rate, money supply, current account deficit and unemployment.

Private saving in Egypt displays persistency and public saving depresses private saving in the short run and long run. Real interest rate, inflation and unemployment have negative and statistically significant impacts on private saving in the short run and long run. The current account deficit displays a negative effect on private saving but is significant only in the short run. Other incorporated variables, like real GDP and money supply, are not statistically significant. This could be attributed to the high consumption rather than saving motive of the Egyptian population and their tendency to rely more on other informal saving channels.

Findings are of policy relevance as unleashing the determinants of private saving guides policymakers in formulating the appropriate sustainable development policies. It also assists in identifying the main obstacles hindering the promotion of private saving and hence major areas for policy intervention, like financial inclusion, poverty eradication, employment generation and structural reforms.

This study contributes to the literature: (1) it tackles private saving figure rather than aggregate saving figure that is covered by similar studies due to lack of consistent data, (2) given the relatively low quality, unavailability and inconsistency of data on private saving in developing countries, investigating the determinants of private saving should be carried out on an individual country basis which is done by this study, (3) this study fulfills the gap in literature related to the lack of up-to-date studies on private saving in Egypt and (4) it relies on quarterly data that could produce more reliable results.