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This study aims to construct alternative models to establish the dynamic nexus between inflation and housing prices by estimating the short- and long-run relationship between housing prices and inflation for 15 OECD countries from 1980Q1 to 2022Q4. Furthermore, the authors examined this association using the core and headline inflation and price-income and price-rent ratios as proxies for inflation and housing prices, respectively.

The authors use the panel autoregressive distributed lag technique to examine the nexus between housing prices and inflation to capture the distinct characteristics of the sample countries, estimate various short-run and long-run dynamics cum separate analyses for turbulent and calm periods in the relationship between housing prices and inflation.

Changes in housing prices have a greater impact on core inflation than headline inflation. Overall, the authors establish a positive (negative) relationship between housing prices and core inflation in the long run (short run) based on alternative proxies of housing prices. However, this connection tends to be less significant for headline inflation and episodic over smaller samples, as it seems stronger during calm periods than turbulent ones.

To the best of the authors’ knowledge, the authors are the first to examine the association between housing prices and inflation by demonstrating how these variables behave during calm and turbulent periods.

The paper examines the asymmetric effects of fiscal deficits on selected macroeconomic variables in Nigeria, which include economic growth, exchange rates and inflation. The existing works of literature are premised on symmetry assumptions with dichotomous findings. In such situations, they suggest using a nonlinear approach as an alternative to checkmate the findings premised on linearity. This is critical, considering the perpetual fiscal deficit trends of Nigeria, which are considered a major economic problem in the country.

The study employs nonlinear autoregressive distributed lag (NARDL) estimator using secondary data collected from the statistical bulletin of the Central Bank of Nigeria (CBN).

The results show that in the short run, both positive and negative shocks to the fiscal deficit have no effect on Nigeria's economic growth. The same is found on the negative shocks in the long run. However, positive shocks to the fiscal deficit have a long-run positive impact on economic growth. It is further revealed that, in the short run, positive shocks as well as negative shocks to fiscal deficits are positively related to the inflation rate. More so, long-run estimates show that positive shocks to the fiscal deficit have negative impacts on inflation, while negative shocks to the fiscal deficit have positive impacts on inflation.

This study introduces novelties to the understanding of the relationship between fiscal deficits and macroeconomic stability in Nigeria. It accounts for asymmetric and nonlinear features that are more aligned with the socioeconomic realities of real-world phenomena. This study also offers more insightful policy perspectives to enhance the fiscal profile of the country.

The purpose of this study is to provide empirical evidence on the impact of deviations from the long-run sustainable real exchange rate (RER) equilibrium on real economic growth rate applying panel autoregressive distributed lag model (ARDL) (Pooled Mean Group, Mean Group and Dynamic Fixed Effects estimators) in a dynamic heterogeneous panel setting and panel NARDL for the largest database covering 104 countries during 1995–2022 period developed by Couharde et al. (2017).

The EQCHANGE database makes available not only the equilibrium RER but also misalignments according to the Behavioral Equilibrium Exchange Rate approach for each country. One of the main objectives is to examine whether undervaluation or overvaluation RER can imply different responses on economic performance trying to differentiate between short and long run effects. Additionally, the authors consider the World Bank (WB)’s income classifications to compare the asymmetries attending to high-income, upper-middle-income, lower-middle-income and low-income levels.

Applying the panel ARDL technique, the results suggest that the RER misalignments have a negative but not significant effect on the short-run, nevertheless a negative and highly significant impact on real economic growth rate is detected on the long-run. Considering the panel NARDL, the asymmetric relationship between RER misalignment and economic growth rate is supported considering all countries in the long-run (in the short-term is not significant). In the long run is detected that undervaluation can promote economic growth rate, rather than overvaluation which can harm the economic performance. Additionally, the WB and the International Monetary Fund (IMF) income’s classifications have been applied and the long-run symmetry test is strongly rejected regardless of income group.

To the best of the author knowledge, this is the first time the non-linear panel ARDL methodology has been applied for analyzing the impact of deviations from the long-run sustainable RER equilibrium on real economic growth. This allows us to see the asymmetric effect not seen before. The panel ARDL estimation can efficiently performed regardless of the integration level of the variables, additionally, it is consistent even in the presence of endogeneity. Besides, another advantage of this method is that it is possible to reflect not only the short but also the long-run dynamics. Moreover, this analysis offers a comparison between linear panel ARDL and non-linear to compare the advantages from the former. Additionally, this study covers the largest database, in particular, 104 countries during the 1995–2022 period implemented with the Couharde et al. (2017) EQCHANGE database. Finally, it is compared the asymmetries attending to different income classifications.

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.

The main purpose of this paper is to examine the role of population aging in determining the health care expenditure (HCE) in India over the period 1981 to 2018.

While establishing the linkage between population aging and HCE, the study has used economic growth, urbanization and CO2 emissions as control variables and used the autoregressive distributed lag (ARDL) approach to cointegration and VECM based Granger causality approach to estimate both the long-run and short-run relationships among the variables.

The results of the ARDL bounds test showed that there is a stable and long-run relationship among the variables. The long-run and short-run coefficients reveal that population aging and income per capita exert a statistically significant and positive effect on per capita HCE in India. The VECM causality evidence shows that there is a presence of short-run causality from economic growth and population aging to per capita HCE, urbanization to environmental degradation and further from aging to urbanization. However, the long-run causality evidence confirms unidirectional causality from population aging to the per capita HCE.

The research findings could be improved by considering the changes in mortality rate over time because of other environmental factors such as air pollution, among others as control variables. Various other variables affecting the health of an aged person could be considered for better research outcome which is not included in the present study because of the paucity of data. However, the present research findings would certainly serve effective policy instrument aiming at maximizing health gains that are highly associated with the elderly population and economic growth towards achieving sustainable development in India.

The uniqueness of the present study lies in its estimation where the relationship between population aging and HCE is looked at while considering the impact of other environmental factors separately. The causal relationship is shown among the variables using updated econometrics time-series techniques. The study tried to resolve the ambiguity associated with the relationship between aging and HCE at a macro level.

This paper aims to empirically examine the influence of macroeconomic and socioeconomic factors on improving financial inclusion in India, with a specific focus on two distinct indicators of financial inclusion.

This study has used a time-series data set covering the years 1996 to 2022, using a nonlinear autoregressive distributed lag methodology. This approach allows for the examination of both short- and long-run effects of key macroeconomic and socio-economic indicators, including GDP per capita growth, remittance inflows and the income share held by the lowest 20% of the population on the growth of two financial inclusion indicators: the number of commercial bank branches and ATMs per 100,000 adults.

Model-1 investigates how commercial bank branch growth affects financial inclusion. Positive remittance inflow growth and a rise in the income share of the bottom 20% both lead to increased financial inclusion in both the short and long term, with the effects being more pronounced in the long run. Conversely, negative effects of remittance inflow growth and a decline in GDP per capita growth lead to reduced financial inclusion, primarily affecting the long run. Focusing on ATM growth, Model-2 reveals that positive remittance inflow growth has the strongest impact on financial inclusion in the short term. While income share growth for the bottom 20% and GDP growth also positively influence financial inclusion, their effects become significant only in the long run. Conversely, a decline in GDP per capita growth hinders financial inclusion, primarily affecting the short run.

This study fills a gap in research on macroeconomic and socioeconomic factors influencing financial inclusion in India by examining the impact of GDP per capita growth, remittance inflows and the income share held by the lowest 20% of the population, an area relatively unexplored in the Indian context. Second, the study provides comprehensive distinct results for different financial inclusion indicators, offering valuable insights for policymakers. These findings are particularly relevant for policymakers working toward Sustainable Development Goal 8.10.1, as they can use the results to tailor policies that align with SDG objectives. Additionally, policymakers in other developing nations can benefit from this study’s findings to enhance financial inclusion in their respective countries.

This paper examines the impact of foreign direct investment (FDI) on the economic growth of Afghanistan over the period 1990 to 2019.

This study uses an autoregressive distributed lag (ARDL) to measure FDI’s impact on economic growth and determine the short- vs long-run relationship.

The results show that the F-bound cointegration test confirms the long-run relationship among the variables. The long-run and short-run results reveal that foreign direct investment has a significant negative impact on economic growth in the long run. However, domestic investment and labour force have a significant and positive impact on economic growth in the long run. Moreover, the impact of trade openness on economic growth is insignificant in the long run, while it has a significant negative impact in the short run.

In this study, we contribute to this research area by analysing the function of FDI in economic growth from Afghanistan’s experience and perspectives. This is the first study empirically examining this relationship in Afghanistan while considering other selected macroeconomic indicators. This paper could greatly benefit policymakers in Afghanistan by guiding the formulation of FDI policies that would spur its economic growth and development.

This paper aims to identify the key drivers of US sustainable stock price movements in both the short and long term, deploying a rich collection of variables corresponding to green finance, investor attention and sentiment, market fear and uncertainty, macroeconomic variables, common market risk factors, commodity markets and the carbon emission market.

The empirical analysis is based on two main methodologies. First, the elastic net penalized regression is utilized to select the factors most influential on the price formation of sustainable stocks. Second, short- and long-run dynamics of the chosen factors are examined using the dynamic simulations of the autoregressive distributed lag (DYNARDL) model.

Of 32 candidate variables, the elastic net chooses US renewable energy, European sustainable stock market, EU ETS emission allowances, public attention to sustainable finance, gold and European renewable energy as the most contributing factors to the price behavior of sustainable stocks. The DYNARDL estimation results reveal that US renewable energy, European sustainable stock market and EU ETS emission allowances are important determinants in the short and long term, while public attention (European renewable energy) tends to affect sustainable stock prices only in the short (long) run.

The corresponding short- and long-run effects of US renewable energy, EU ETS emission allowances and European sustainable stocks on US sustainable stock prices should induce policymakers to keep the price behavior of these factors under systematic review. The formulation of policy measures could serve to safeguard the sustainable stock market from the price vagaries in these influential markets.

Relevant literature often focuses on the reaction of sustainable stocks to mainstream assets and risk proxies, limiting analysis to a few factors and providing an incomplete understanding of the drivers behind sustainable stock prices. More comprehensive research is needed due to the lack of studies on the determinants of sustainable stock prices and the growing global demand for these investments. This paper aims to address this gap by examining the potential explanatory power of 32 candidate factors representing key players in the global economic and financial landscape.

The purpose of this paper is to assess the possibility of asymmetric impact of monetary policy on housing permits issued in each state of the USA.

The methodology and approach are based on the linear ARDL and nonlinear ARDL approach to error-correction modeling and asymmetric cointegration.

The linear models predict that money supply impact housing permits in 28 states in the short run and only nine states in the long run. However, the asymmetric effects are far more pervasive, highlighting the restrictive nature of the linear model. The results from the nonlinear model show at least one lag of positive and/or negative changes in money supply significantly impacts housing permits in nearly all states. Even in the long run, housing permits in 32 states share a long-run relationship with positive and/or negative changes in money supply. The authors also find contractionary monetary policy has a greater influence on housing permits in most states compared to expansionary policy.

For the first time, the authors use state-level data and asymmetric approach to assess the impact of monetary policy on house permits issued in each state of the USA.

This study investigated the asymmetric effects of changes in policy uncertainty on real sector variables in Brazil, China, India and South Africa.

The study used the nonlinear autoregressive distributed lag (NARDL) modeling framework.

The results showed that both in the long run and short run, rising uncertainty not only increases consumer prices significantly in these economies, but also impedes aggregate and sectoral output growths, and deters investment, employment and private consumption. Contrary to economic expectation, the results also showed that in the long run, declining uncertainty impedes aggregate and sectoral output growths in these economies, and significantly hinders employment in South Africa and Brazil. This suggests that in the long run, economic agents in these economies somewhat behave as if uncertainty is rising. The authors also found significant asymmetric effects in the response of real sector variables to uncertainty both in the long run and short run, which justifies the choice of NARDL framework for this study.

The sample is limited to Brazil, India, China and South Africa. While Brazil, India and China are three of the most prominent large emerging market economies, South Africa is the largest emerging market economy in Africa.

To lessen the adverse effects of policy uncertainty observed in the results, there is need for sound institutions and policy regimes that can promote predictable policy responses in these economies so that policy neither serves as a source of uncertainty nor as a channel through which the effects of other shocks are transmitted.

Apart from using the NARDL framework to capture the asymmetric effects of policy uncertainty, this study also accounted for the sectoral effects of uncertainty in emerging markets.