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This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

The purpose of this paper is to understand the post-COVID-19 fluctuations in the building construction demand from various angles at the national, regional, and sectoral levels. Despite the significant impact of COVID-19 on the building construction industry, a detailed quantitative analysis of the COVID-19 impact on the building construction demand is still lacking. The current study aims to (1) establish a statistical approach to quantify the COVID-19 impact on the building construction demand; (2) investigate the post-COVID-19 fluctuations in the construction demand of different building services, regional markets, and building sectors using the historical time series of the architecture billings index (ABI); and (3) identify vulnerable market and sector and discuss the post-COVID-19 recovery strategies.

The research methodology follows four steps: (1) collecting national, regional, and sectoral ABIs; (2) creating seasonal autoregressive integrated moving average models; (3) illustrating cumulative sum control charts to identify significant ABI deviations; and (4) quantifying the post-COVID-19 ABI fluctuations.

The results show that all the ABIs experienced a statistically significant decrease after COVID-19. The project inquiries index reduced more but recovered faster than billings and design contracts indices. The midwest billings index decreased the most among the regional ABIs and the commercial/industrial billing index dropped the most among the sectoral ABIs.

This study is unique in the way that it utilized the ABI data and the approach using SARIMA models and CUSUM control charts to assess the post-COVID-19 building construction demand represented by ABI fluctuations.

This study examines the possibility of asymmetric impact of inflation on the financial development (FD) in the case of Indian economy from 1980 to 2020. Moreover, the finance–growth hypothesis is also tested.

The authors incorporated the “Nonlinear Autoregressive Distributed Lag” (NARDL) model due to Shin et al. (2014) to investigate the asymmetric impact of inflation on financial development. Asymmetric cumulative dynamic multipliers are also used to track the traverse of any short-run distortion towards the long-run cointegration.

The results revealed that inflation impacts the financial development negatively whereas the economic growth (EG) and trade openness have a positive effect. However, the effect of inflation on financial development is not symmetric. Moreover, the findings support the demand-led growth hypothesis.

To the best of the authors' knowledge, this is the first study examining the asymmetric effects of inflation on financial development in the Indian context. In addition, instead of using a single proxy to measure financial development, an index for financial development encompassing different aspects of the financial system has been incorporated.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0094

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.

The purpose of this paper is to understand the effect of basin water depth towards the cumulative distillate yield of the traditional and developed single basin double slope solar still (DSSS).

Modified single basin DSSS integrated with solar operated vacuum fan and external water cooled condenser was fabricated using aluminium material. During sunny season, experimental investigations have been performed in both conventional and modified DSSS at a basin water depth of 3, 6, 9 and 12 cm. Production rate and cumulative distillate yield obtained in traditional and developed DSSS at different water depths were compared and best water depth to attain the maximum productivity and cumulative distillate yield was found out.

Results indicated that both traditional and modified double SS produced maximum yield at the minimum water depth of 3 cm. Cumulative distillate yield of the developed SS was 16.39%, 18.86%, 15.22% and 17.07% higher than traditional at water depths of 3, 6, 9 and 12 cm, respectively. Cumulative distillate yield of the developed SS at 3 cm water depth was 73.17% higher than that of the traditional SS at 12 cm depth.

Performance evaluation of DSSS at various water depths by integrating the combined solar operated Vacuum fan and external Condenser.

The purpose of this paper is to empirically analyze the impact of remittance inflows on sustained economic growth in India.

This study has taken a time series dataset for the period of 1976–2021, and a nonlinear autoregressive distributed lag model technique (NARDL) has been applied to check the impact of remittance inflows along with other control variables, including broad money and service sector performance, on the sustained economic growth of India.

The results of the study indicated that in both the short and long runs, any positive shock in remittance inflows has a positive impact on the economic growth of India, while negative shocks do not affect economic growth.

The economic policymakers of India can use the findings of the study by implementing remittance-friendly policies. Moreover, NITI Aayog, the body working toward achieving sustainable development goals (SDGs) in India, can also use this study as a reference while making strategies to achieve SDG.

Economic growth has always been an area of interest among economists, researchers and policymakers. However, achieving sustained economic growth requires an analysis of those factors that themselves have sustained performance over a long period of time and have the potential to sustain it over the upcoming years. This study has taken remittance inflows as one such factor and investigated its impact on the sustained economic growth of India. At present, there is an evident gap in the literature that very little attention has been given to sustained Indian economic growth. Moreover, there is no study available in which the nonlinear impact of different variables has been tested on the economic growth of India.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

In this paper we examine the validity of the J-curve hypothesis in four Southeast Asian economies (Indonesia, Malaysia, the Philippines and Thailand) over the 1980–2017 period.

We employ the linear autoregressive distributed lags (ARDL) model that captures the dynamic relationships between the variables and additionally use the nonlinear ARDL model that considers the asymmetric effects of the real exchange rate changes.

The estimated models were diagnostically sound, and the variables were found to be cointegrated. However, with the exception of Malaysia, the short- and long-run relationships did not attest to the presence of the J-curve effect. The trade flows were affected asymmetrically in Malaysia and the Philippines, suggesting the appropriateness of nonlinear ARDL in these countries.

The previous research tended to examine the effects of the real exchange rate changes on the agricultural trade balance and specifically the J-curve effect (deterioration of the trade balance followed by its improvement) in the developed economies and rarely in the developing ones. In this paper, we address this omission.

This study aims to investigate the effect of oil prices, economic growth and information communication technology (ICT) on investment into renewable energy transition (RET).

Based on six selected African countries (i.e. Algeria, Egypt, Angola, Ethiopia, South Africa and Nigeria), the study uses a nonlinear autoregressive distributed lag model over the period from 1995 to 2020.

The results show that increasing oil prices, by substitution effect, leads to increasing RET investment, while declining oil prices lead to decreasing RET investment in the short and long run. Furthermore, the results reveal that increasing real gross domestic product leads to increased RET investment, while declining real gross domestic product (GDP) leads to decreasing RET investment both in the short and long run. Simultaneously, the study shows that increasing ICT has a significant and positive impact on RET investment, while declining ICT has a significant negative impact on RET investment in the short and long run.

The findings of this study have advanced the understanding of which factors significantly influence RET investment and the need to concentrate efforts on strategically addressing those factors. The findings indicate that these countries are at the progressive stage in terms of renewable energy; though increasing oil prices contribute to rising RET investment, the countries can be more proactive by improving the full potential of ICT as well as facilitating the growth of their economies.

This study reinvestigates the validity of the Phillips curve in Nigeria for the period 1980–2020 by considering the asymmetric nexus between unemployment and inflation.

The nonlinear autoregressive distributed lag (NARDL) technique was used to decompose the unemployment variable into two components: tight and loosened labour markets.

The empirical outcome shows that unemployment has a significant negative effect on inflation when the labour market is tight and a weakly negative and significant effect on inflation when the labour market is loose. The study confirms an asymmetric Phillips curve in Nigeria since the positive (tight) unemployment rate exerts a greater effect on inflation than the negative (loosened) unemployment rate.

The findings of this study have important implications for implementing monetary policy in Nigeria.

To the best of the authors’ knowledge, this is the first study to investigate the existence of a nonlinear Phillip curve in Nigeria.