The purpose of this study is to estimates the size of the shadow economy for 80 countries from nine regions spanning the period 1975-2012 based on Tanzi-type currency demand approach (CDA). This study contributes to the literature in three distinct ways. First, we augment CDA regression with a macroeconomic uncertainty index (MUI). Second, the construction of the uncertainty index is based on the dynamic factor model (DFM). Third, the pooled mean group (PMG) estimator allows in capturing the heterogeneity across countries in the short-run dynamics but imposing restrictions in the long-run parameters. The results confirm the existence of the longrun equilibrium relationship among the variables examined. All coefficients show expected signs along with statistical significance. More importantly, the macroeconomic uncertainty index variable show positive relationship, suggesting that public tend to hold more currency in an uncertain macroeconomic environment. In addition, we observe that developing regions (ranging from 19.9% to 37.3%) exhibit relatively large size of the shadow economy. On the contrary, developed regions have a considerable smaller estimate (ranging from 13.7% to 19.0%) of the size of shadow economy. On average, the world estimate of the shadow economy as a percentage of GDP is about 23.1%. Keywords: Shadow Economy; Currency Demand; Macroeconomic Uncertainty; Pooled Mean Group.
Purpose: The challenging economic climate and increasing inflationary pressures have made it necessary to re-evaluate inflation research and its impact on the stock market. The purpose of this study is to use bibliometric analysis to review scholarly writing on stock returns and inflation from 1975 to 2022. Design/methodology/approach: This study analyses bibliometric markers such as the number of citations, authors, journals, and institutions using the Web of Science database to discover publishing patterns and illustrate commonalities. Findings: The study indicates that the volatility domain has gained more attention, therefore there is a necessity for future research to model predictive accuracy to match the rising volatility and uncertainty environment. Due to the expanding energy theme from bibliographic coupling analysis and the oil-related macroeconomic factors cluster from author keyword co-occurrence analysis, the study revealed a research gap that underlines the need for a green and sustainable stock market. Research, Practical & Social implications: The study suggests a need for future research to increase academic collaboration and to contribute toward the development of theoretical and empirical literature. Originality/value: The results revealed that it is vital to revise the current theory to integrate theoretical implications in light of the volatile market conditions and rising inflation rate.
This study investigates whether oil prices have enough predictive information to predict the direction of the movement of exchange rate by examining the type of cointegration relationship between exchange rate and oil prices in India between 1991Q1 and 2013Q1. Our findings suggest the existence of cointegration relationship between exchange rate and oil prices using both Engle-Granger two-step cointegration test and Johansen cointegration test. Using a momentum threshold autoregressive consistent model, we find evidence in favour of asymmetric cointegration between the two variables. Nevertheless we find no evidence to support asymmetric cointegration relationship between the two variables when threshold autoregressive, threshold autoregressive consistent, and momentum threshold autoregressive models are used. Thus, the results suggest that for certain time period, the adjustment process between exchange rate and oil price is constant, which makes it conducive for predicting the direction of exchange rate movement. However, evidence of asymmetric cointegration suggests that the stable relationship is likely to be interrupted with intervals of structural change implying correction in the dynamics of influencing factors. ARTICLE HISTORY
Malaysia is recognized as one of the mega biodiversity countries of the world. However, Malaysia’s biodiversity hotspot experiencing a more pronounce biodiversity loss. Accordingly, the objective of this study is to explore the link between climate change, socio-economic factors and biodiversity loss in Malaysia from 1990 to 2016, with a special focus on different climate change indicators namely rainfall, temperature and carbon dioxide (CO[Formula: see text] emissions. Using the autoregressive distributed lag (ARDL) bounds testing approach, this study provides evidence on long-run relation between each of the indicators of climate change and biodiversity loss. The core threats to biodiversity are growing demand for agricultural land, rapid population, elevated temperature, higher CO2 emissions and rainfall reduction. Interestingly, the biodiversity loss-income nexus is also supportive of the environmental Kuznets curve (EKC) hypothesis; with biodiversity threats increasing with income, beyond a certain level of income, a rise in income reduces the loss of biodiversity. The findings are essential for future studies with a special consideration to reduce the losses of biodiversity.
The environmental Kuznets curve (EKC) is a widely tested hypothesis in the environmental economics literature. It explains the dynamics between economic growth and environmental degradation. This study conducts a bibliometric analysis for the past three decades (1994–2021) that contributes to the intellectual structure and knowledge progress of the EKC hypothesis using descriptive analysis and networking analysis. The descriptive analysis comprises publication trends, language, publishers, Web of Science category and research areas, and citation analysis. Meanwhile, networking analysis includes keyword co-occurrence analysis, co-authorship analysis and co-citation analysis. The findings of the descriptive analysis reveal that the number of publications in the EKC hypothesis has gradually increased over the years. The most productive publishers are Elsevier and Springer Nature. Researchers from China and Turkey tend to be the most prolific authors, with the highest number of citations, co-authorships and co-citations. According to the network analysis, the main keywords appearing in the EKC studies are economic growth, CO2 emissions, energy consumption, China, renewable energy and financial development, which is also supported by the most frequently used keyword plus and its clusters. Based on our findings, we have proposed several policy recommendations from the keyword analysis that could foster economic development and improve environmental quality simultaneously. From the emerging trends of EKC, new directions for future research are also proposed.
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