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The objective of the study is to investigate the dynamic relationship between fiscal stress (FS) shocks and foreign direct investment (FDI) in moderate FS developing countries spanning from 2000 to 2021. The paper seeks to identify dual-regime effects, exploring how FS shocks impact FDI differently in low-stress and high-stress environments.

This study employs advanced econometric techniques to investigate the dynamic relationship between FS shocks and FDI in a sample of moderate FS developing countries spanning from 2000 to 2021. The analysis utilizes variance decomposition, impulse response functions, and a regime-switching vector autoregressive model to explore the nuanced interactions between FS and FDI attraction. These techniques allow for the identification of dual-regime effects, wherein FS shocks exhibit differing impacts on FDI depending on the prevailing stress environment.

The analysis reveals a dual-regime effect of FS shocks on FDI in the sample of moderate FS developing countries studied from 2000 to 2021. In low-stress regimes, FS shocks initially have a positive impact on FDI, suggesting potential investment opportunities. However, in high-stress regimes, the effect reverses, resulting in a negative impact on FDI attraction. Moreover, the study highlights the asymmetric nature of this relationship, with the adverse effects of FS on FDI intensifying over time in high-stress environments.

Previous studies focused mainly on a country's fiscal position and its impact on FDI or capital inflows. This is the first study to assess how FS or fiscal pressure affects FDI.

The purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO₂ emissions during the time span from 1980 to 2020.

The study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in the Indian economy.

The estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO₂ emissions. The authors found that economic growth positively impacts CO₂ emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO₂ emissions. Similarly, RE consumption positively affects CO₂ emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO₂ emissions.

The study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO₂ emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO₂ emissions on further economic growth.

To the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in India, using the STAR model.

Standard economic theory predicts that any increase in public spending is accompanied by a rise in inflation in an economy. This paper presents empirical proof that prices do not always rise with an increase in public expenditure but only up to a certain threshold level. The primary aim of this paper is to unearth the government size-inflation nexus in India for the period from 1971 to 2019.

The logistic STAR (smooth transition autoregression) model is employed to unravel the government size-inflation nexus for the Indian economy from a non-linear perspective.

The finding of our study confirm the non-linear relationship between the size of the government and inflation in India. The estimated threshold level for government size is precisely found to be 9.27%. The size of the government exerts a negative influence on inflation until it reaches the optimal or threshold level. Any further increase in the size of government beyond this threshold level would result in a rise in inflation.

The findings have implications for the conduct of fiscal policy. Policymakers can increase government spending in a regime of small government size without having any inflationary impacts by generating revenues from taxes and other sources instead of relying much on the central bank. In the regime of a large-sized government, adhering strictly to the discipline in the conduct of fiscal and monetary policies would help curb inflation and enhance growth synchronously, hence alleviating any loss of welfare.

To the best of the authors’ knowledge, this study is an attempt to revisit the government size-inflation nexus in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model for the first time.

This study examines the role of financial development (FD) in enhancing the growth effect of foreign direct investment (FDI) in emerging and developing Asia from 1996 to 2019.

The study exploits the new broad-based Financial Development Index of the International Monetary Fund (IMF) and adopts panel smooth transition regression (PSTR) to perform alternative empirical models for a multidimensional analysis of the FD threshold effect in the growth–FDI nexus.

The results show two thresholds of FD mediating the nonlinear effect of FDI on growth. FD beyond a certain level will enhance the growth effect of FDI, but very high levels of FD will not induce foreign investment to benefit economic growth in emerging and developing Asian economies. The impact of financial institutions on the FDI–growth link is stronger than that of financial markets. Besides, FDI’s effect on growth has an inverted-U shape conditional on financial depth, whereas it is positively associated with the accessibility and efficiency of the financial system.

These results suggest policy implications for emerging and developing Asian countries, emphasizing the other side of “too much finance” and the potential for improvement in the access to and efficiency of the financial system to boost the effects of FDI and FD in the growth of these economies.

The study is the first multifaceted investigation into the influence of FD on the growth effect of FDI. Beyond the previous empirical evidence showing only the impact of credit from banking sector, this study shows different mediating effects of different financial sectors and three dimensions of financing (depth, access and efficiency). The study suggests essential implications for the region in adjusting long-run policies to enhance the FDI–FD–growth link.

In this article, we assess the impact of inflation on the current account balance in the case of Tunisia, covering the period 1976–2022.

The study utilizes a threshold regression approach proposed by Hansen (2001) in a bid to identify inflation threshold values.

The results show two inflation threshold values (3.87% and 8.41%), which determine three inflation regimes in the case of Tunisia. In lower inflation regimes, inflation has a positive and statistically significant impact on the current account balance. However, in higher inflation regimes, where inflation rates exceed 3.87%, there is a negative and statistically significant correlation with the current account balance, resulting in a deficit.

The research suggests the need for a new policy approach that considers these threshold levels to address high inflation rates, which currently stand at approximately 11%, and aims to restore them to the targeted rate of 4%. This necessitates coordinated monetary and fiscal measures.

India’s historical fiscal performance has featured elevated deficit levels. Driven by the imperative need for fiscal stimulus measures in response to the crisis, efforts toward fiscal consolidation from 2003 to 2008 were reversed in 2008–2009 due to the financial crisis. These stimulus actions are believed to have wielded a notable influence on inflation dynamics. Presumably, a high inflation rate hinders growth and inflicts severe welfare costs. Accordingly, the principal objective of this paper is to scrutinise the threshold effects of fiscal deficit on inflation within the context of the Indian economy.

We employed the Smooth Transition Autoregressive (STAR) Model, a robust tool for capturing non-linear relationships, to discern the specific threshold level of fiscal deficit. Our analysis encompasses annual data spanning from 1971 to 2020. Additionally, we have leveraged the Toda-Yamamoto causality test to establish the existence and direction of a causal connection between fiscal deficit and inflation in the Indian economy.

Our analysis pinpointed a critical threshold level of 3.40% for fiscal deficit, a value beyond which inflation dynamics in India undergo a marked transition, signifying the presence of significant non-linear effects. Moreover, the results derived from the Toda-Yamamoto causality test offer substantiating evidence of a causal relationship originating from the fiscal deficit and leading to inflation within the Indian economic framework.

The findings of our study carry significant implications, particularly for the formulation and execution of both fiscal and monetary policies. Understanding the threshold effects of fiscal deficit on inflation in India provides policymakers with valuable insights into achieving a harmonious balance between these two critical economic variables.

To the best of our knowledge, this study is the first of its kind to empirically investigate threshold effects of fiscal deficit on inflation in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model.

Start-ups are successful in receiving valuation in billions of US dollars prior to initial public offering (IPO). However, to sustain higher valuation, the stocks need to perform consistently after the IPO. Short-run stock performance of India-based start-ups during the first year of IPO listing from March 2021 to March 2022 is analysed.

The paper deals with the new generation start-ups' stock performance in emerging market in terms of total and abnormal return generated in comparison to the market (NIFTY-200). Further, the volatility of returns during bear and bull regimes is analysed through a family of Markov-switching GARCH models using both normal and skewed distributions.

The results suggest that start-up stocks are more volatile during bear regime than in the bull run in market-based economies where price limit policy does not apply. Besides, the cumulative abnormal return over the market return was lower for majority of start-up IPO stocks.

Though negative returns of the start-up stocks during the first year of IPO need not be surprising, higher volatility during bear regime is a matter of concern as it could severely impact retail investors and founders. The results hold implication for IPO regulation in emerging markets and for retail investors desirous of investing in start-up stocks.

Volatility of return is examined using a state-space model during the first year of the start-up IPO listing. The study contributes to the emerging market IPO literature by examining IPO performance in market-based economy. Previous IPO performance studies in emerging markets are predominantly based on ecosystems where start-ups are subjected to price limit policy, and it does not reflect the true nature of IPO performance across emerging markets.

In this paper, we provide new evidence to strengthen the stock market overreaction hypothesis by examining a new context that has not been explored before. Our research is inspired by the widely held belief that investor sentiment experiences abrupt changes from optimism to pessimism as the market switches between bull and bear states.

If the stock market overreaction hypothesis is correct, it implies that investors are inclined to become excessively optimistic during bull markets and overly pessimistic during bear markets, resulting in overreaction and subsequent market correction. Consequently, the study first develops two testable hypotheses that can be used to uncover the presence of stock market overreaction with subsequent correction. These hypotheses are then tested using long-term data from the US market.

The study's findings support the hypothesis while also revealing a significant asymmetry in investor overreaction between bull and bear markets. Specifically, our results indicate that investors tend to overreact towards the end of a bear market, and the subsequent bull market starts with a prompt and robust correction. Conversely, investors appear to overreact only towards the end of a prolonged bull market. The correction during a bear market is not confined to its initial phase but extends across its entire duration.

Our study has some limitations related to its focus on investigating stock market overreaction in the US market and analyzing the pattern of mean returns during bull and bear market states. Expanding our study to different global markets would be necessary to understand whether the same stock market overreaction effect exists universally. Furthermore, exploring the relationship between volatility and overreaction during different market phases would be an exciting direction for future research, as it could provide a more complete picture of market dynamics.

Our study confirms the presence of the stock market overreaction effect, which contradicts the efficient market hypothesis. We have observed specific price patterns during bull and bear markets that investors can potentially exploit. However, successfully capitalizing on these patterns depends on accurately predicting the turning points between bull and bear market states.

The results of our study have significant implications for market regulators. Stock market overreactions resulting in market corrections can severely disrupt the market, leading to significant financial losses for investors and undermining investor confidence in the overall market. Further, the existence of overreactions suggests that the stock market may not always be efficient, raising regulatory concerns. Policymakers and regulators may need to implement policies and regulations to mitigate the effects of overreactions and subsequent market corrections.

This paper aims to provide additional support for the stock market overreaction hypothesis using a new setting in which this hypothesis has not been previously investigated.

This study addresses the empirical results of the spillover effect with export as the primary economic activity that enhances local businesses' total factor productivity (TFP). A learning mechanism is expected to be generated and used as the basis for the policy implication.

This study adopted the Cobb–Douglas function and multiple estimation approaches, including the generalized method of moments, the Olley–Pakes and the Levinsohn–Petrin estimation techniques. The findings were estimated based on the panel data of a Vietnamese local businesses survey conducted by the General Statistics Office of Vietnam (GSO) from 2010 to 2019.

The results showed that the highest TFP belongs to the businesses in the Southeast region, the Mekong Delta region, the mining industry and the foreign-invested enterprises. The lowest impacted TFP are businesses in the Northwest region and agricultural, forestry and fishery sectors. In addition, the estimated results also show that the positive spillover effect on TFP is shown through forward and backward linkage. The negative spillover effect is expressed through the backward and horizontal channels.

This study offers original empirical evidence on the learning mechanisms via which exports contribute to productivity improvement in a developing Asian economy, so making a valuable contribution to the existing academic literature in this domain. The findings of this research make a valuable contribution to the advancement of understanding on the many ways via which spillover effects manifest such as horizontal, forward, backward and supplied-backward linkage.

The study's findings indicate that it is advisable for governments to give priority to the development and improvement of forward and supply chain linkages between exporters and local suppliers. This approach is recommended in order to optimize the advantages derived from export spillovers. At the organizational level, it is imperative for enterprises to strengthen their technological and managerial skills in order to efficiently incorporate knowledge spillovers that originate from overseas partners and trade counterparts.

This study sheds new evidence on the export spillover effect on productivity in emerging economies, with Vietnam as the case study. The paper contributes to the research's originality by adopting novel methodological aspects to estimate local businesses' impact on total factor productivity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0373

This paper aims to analyze the volatility transmission between an energy stock index and a financial stock index in emerging markets during recent high instability periods. The study considers the impact of both the period under analysis and the data frequency on the direction and intensity of the contagion, as well as the effect of the potential spillovers on the risk measures. These questions still lack definitive answers and have become more relevant in a context of financially unsettling events such as COVID-19 crises.

This study employs an extension of the dynamic conditional correlation (DCC) model that allows for the time-varying dependence relationship between the variables. This dependence is analyzed at daily, weekly and monthly basis using data from the Bloomberg platform on energy and stock market indices for emerging markets between 2001 and 2021.

The results for a sample spanning from 2001 to mid-2021 show bidirectional volatility transmission on a daily basis, whereas only evidence of volatility transmission from the financial to the energy exists for weekly and monthly frequencies. However, considering different subsamples of daily data, the authors only find volatility transmission from financial (energy) index to the energy (financial) during the Great Recession (COVID-19) as a consequence of the different source of the shock and transmission channels.

This study reveals that volatility transmission between energy and stocks in emerging markets has changed and presents a unidirectional pattern from energy to financial markets during the COVID-19 period in contrast to calm and the sub-prime crisis intervals. These results differ from previous studies, focused on global markets, that show bidirectional spillovers during this period.