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This study focuses on the relationship between foreign direct investment (FDI) and economic growth of the formal sector comprising all foreign and domestic registered enterprises engaged in production of goods and services.

This study uses a balanced longitudinal data set for the period from 2006 to 2014 from secondary sources in 63 provinces/cities of Vietnam. The generalized method of moments (GMM) estimation for a dynamic panel data model is applied.

The greater the share of FDI in capital resource, the more favorable the output growth in the whole formal sector. The FDI enterprises are more productive than domestic formal firms, and the output growth of FDI firms creates a positive spillover effect on the output growth of domestic firms.

The effect of FDI on economic growth is investigated at subnational level for the whole formal economic sector as well as the formal domestic firms. The domestic and foreign industrial agglomerations and the business environment are also examined.

The paper underpins an advanced domestic manufacturing that comes with some advanced employment specialization status of individual industries as the key determinant of foreign direct investment (FDI) and considers how FDI in the food processing industry in India relates to this focal point.

This paper investigates how inward FDI inflows relate to domestic investment and revival in the industry using Auto Regressive Distributed lags (ARDL) model over the period 2000–2017. The model allows for different specifications to study whether FDI is responsible for the revival or the prior revival induces the FDI.

The results show the lack of proper advanced specialized employment status of the food processing industry. FDI in food processing is mainly guided by exports and imports opportunities and FDI plays no role in the revival of advanced growth in the industry. This finding explains why FDI in the industry is predominantly service sector oriented.

The paper underlines (1) the proper conceptualization of human capital as an important determinant of FDI; (2) reinterpretation of Kaldor's technical progress function that uncovers how employment dynamics embedded in intermediate goods specializations play a key role in supporting a higher pace of investment (and FDI); (3) labor costs' importance should involve not only the wage rate but also the advantages that a specialized employment base and (4) FDI in manufacturing demands a greater policy focus on developing domestic bases of intermediate goods specializations.

This paper aims to explore the impact of digital inclusive finance (DIF) on regional economic growth and innovation-driven development.

Based on the panel data of 31 provinces (autonomous regions and municipalities directly under the central government) in China from 2011 to 2018, this paper explores the impact of DIF on economic growth and innovative development.

(1) DIF has a direct positive effect on economic growth and innovative development; (2) there is significant regional heterogeneity in the impact of DIF on economic growth and innovative development. (3) DIF can indirectly affect economic growth and innovative development by increasing residents’ personal disposable income, increasing fiscal expenditure and improving educational level.

Exploring the relationship between them and digital inclusive financial development can provide a reference for national productivity construction and development.

Economic growth and innovation-driven development have been one of the main concerns of China’s policymakers. Exploring the relationship between them, digital inclusive financial development can provide a reference for national productivity construction and development.

This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method.

The study uses the DiD method.

Exploiting county-city mergers during 2010–2018, the key strategy to expand the city outward and promote urbanization on the urban fringe by local government, the authors find that county-city mergers led to the growth of primary industry decline by 4.23%. The result can be explained by the loss of essential production factors, including land and labor used for farming. In addition, the negative effect is more pronounced for counties with more substantial manufacturing. The results indicate that urbanization in China relocates land and labor; however, it does not improve the efficiency of agricultural output.

This paper contributes to the understanding of urbanization and rural development from the perspective of the primary industry by showing production factor redistribution. Second, this study complements the literature on local government mergers.

This paper aims to explore the extreme effect of crude oil price fluctuations and its volatility on the economic growth of Middle East and North Africa (MENA) countries. It also investigates the asymmetric and dynamic relationship between oil price and economic growth. Further, a separate analysis for each MENA oil-export and oil-import countries is conducted. Furthermore, it studies to what extent the quality of institutions will change the effect of oil price fluctuations on economic growth.

As the effect of oil price fluctuations is not the same over different business cycles or oil price levels, the paper uses a panel quantile regression approach with other linear models such as fixed effects, random effects and panel generalized method of moments. The panel quantile methodology is an extension of traditional linear models and it has the advantage of exploring the relationship over the different quantiles of the whole distribution.

The paper can summarize results as following: changes in oil price and its volatility have an opposite effect for each oil-export and oil-import countries; for the former, changes in oil prices have a positive impact but the volatility a negative effect. While for the latter, changes in oil prices have a negative effect but volatility a positive effect. Further, the impact of oil price changes and their uncertainty are different across different quantiles. Furthermore, there is evidence about the asymmetric effect of the oil price changes on economic growth. Finally, accounting for institutional quality led to a reduction in the impact of oil price changes on economic growth.

The study concludes more detailed results on the impact of oil prices on gross domestic product growth. Thus, it can be used as a decision-support tool for policymakers.

The study investigates the effectiveness of government policies to mitigate the impact of a pandemic. The study adopts the small open economy of Nigeria for the following reasons. First, Nigeria is the largest economy in SSA. Second, Nigeria was also significantly impacted by the COVID-19 pandemic.

The study employed the time-varying structural autoregressive (TVSVAR) model to control for the potential asymmetry in fiscal variables and to control for the shift in the structural shift, following a macroeconomic shock. As a form of robustness, the study also implements the time-varying Granger causality to formally assess the temporal instability of the variable of interest.

The results show that an oil price shock is an important source of macroeconomic instability in Nigeria. Importantly, the results indicate that the effects of fiscal policy are strongly time varying. Specifically, the results show that fiscal policy helps to stabilize the economy, (i.e. they help to reduce inflation and spur output growth) following macroeconomic shock. Further, the Granger test shows that fiscal policy helped to spur growth in Nigeria. The research and policy implications are discussed.

The study accounts for the time-varying effects of fiscal policy.

This paper aims to enhance the Global Projection Model (GPM) developed by the International Monetary Fund by constructing a GPM4 model that includes the United States of America, the Eurozone, Japan and China.

This article introduces the United States of America, the Eurozone, Japan and China into a comprehensive global forecasting model, analyzing the impact of liquidity management in G3 economies on nine key macroeconomic variables in China.

The findings reveal that the liquidity management strategies employed by major economies do exert a certain influence on China's major macroeconomic variables. Different types of liquidity shocks elicit varying effects. Monetary shocks exhibit the strongest instantaneous impact, while credit conditions and policy rate shocks contribute more significantly to China's long-term macroeconomic fluctuations. However, no single shock stands out as the dominant factor.

This paper attempts to expand the GPM model developed by the International Monetary Fund and build a GPM4 model including China, the United States of America, the Eurozone and Japan. For the first time, the GPM model was used to analyze the spillover effects of liquidity management in major economies on China's macroeconomy and revealed the impact of non-price factors such as credit conditions on China's macroeconomic variables.

The purpose of this paper is to investigate the impact of changes in credit stock on real and financial indicators in Turkey with a focus on conditional and time-varying dynamics.

In addition to lag-augmented vector autoregression (LA-VAR) based time-varying Granger causality tests, threshold models and a research setting that identifies high/low states of credit growth based on 24-month moving averages are used to explore regime-dependent behavior. For investigating the asymmetric dynamics, the authors use a methodology that identifies good/bad news in credit growth based on 24-month moving averages and standard deviations.

Results strongly suggest that the impact of changes in credit stock induces conditional responses. Moreover, we find evidence for asymmetric responses. In the case of Turkey, efforts to spur growth through credit produce a strong negative byproduct, a depreciation in the exchange rate. The authors also find that changes in credit stock have become more relevant for uncertainties in inflation and exchange rate expectations, particularly in the era after mid-2018 in which credit growth volatility has increased noticeably.

This study provides a comprehensive analysis of time-varying and conditional responses to a change in credit stock in a major emerging economy. Using a moving threshold based only on the available information in the analysis of state-dependency represents a new approach.

The purpose of this research is to examine the impact of alterations in the path of monetary policy rates on inflation via the supply side of an emerging economy.

The study employed semi-annual data covering the period 2007S1 to 2020S2 on the inflation rate, the combined outputs of industry and agriculture, the lending rate, and the monetary policy rate. The vector autoregression model was estimated and counterfactual simulation exercises were conducted.

The study revealed that a move from a higher to a lower monetary policy rate regime resulted in a shift in inflation from a higher to a lower regime. In particular, a 200-basis point reduction in the monetary policy rate over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

The study has a limitation due to the unavailability of a long-span dataset on all relevant variables. As a result, it is important to exercise caution when interpreting the study's findings. A potential area for further research is to explore how changes in interest rates impact inflation in the real economy by utilising other multiple-variable time series techniques.

It is the opinion of the authors that for inflation in Ghana to move to a lower regime, conscious efforts should be made by the monetary authorities to gradually move from a regime of a high monetary policy rate to a lower one.

In particular, a 200-basis point reduction in the MPR over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

This study enhances the authors' knowledge of how monetary policy can affect inflation in developing countries through the supply-side channel.

The paper analyses the prevalence of extreme and multidimensional poverty in line with the sustainable development agenda. In addition, the paper examines the drivers of extreme poverty while accounting for the potential spillover effect of poverty in the region.

The study adopts the pooled OLS with Discroll-Kraay robust standard errors to control for cross-sectional dependence. In addition, given the strong potential for endogeneity of poverty index, the authors also employ the generalized method of moments (GMM), which accounts for simultaneity and endogeneity problems, and the spatial error and lag models to control for all forms of spatial and temporal dependence since the factors that affect poverty disperse across borders.

The study finds that in addition to the traditional drivers of poverty (unemployment, low per capita GDP growth and public debt), poverty in Sub-Saharan Africa is a symptom of a deeper structural problem (lack of access to water and sanitation, high level of corruption and low level of financial development, and frequent economic busts). Likewise, the results from the spatial econometric specification show, consistently across all the specifications, that there is a substantial spillover effect of poverty across the region.

The main novelty of the paper is that the authors investigate the “economic shrinkage hypothesis,” and examined the potential negative spillover effect of poverty in the region.