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The degree of development and the way to identify a fiscal shock matter in evaluating the effects of the fiscal policy. This paper contributes to the debate on the effects of a fiscal expansion on private consumption and the real effective exchange rate.

This paper uses a sign-restriction method to identify a fiscal shock in the panel structural VAR analysis in the context of both developed and developing countries.

The authors’ find that (1) private consumption increases in response to a positive government spending shock in both groups, yet such consumption effect is greater in developing than industrial countries; (2) the response of real effective exchange rate to the government spending shock varies across groups: it depreciates in developed countries and appreciates in developing countries; (3) trade balance improves in both groups.

This study sheds light on the differential effects of fiscal shock on consumption and real exchange rate in both developed and developing economies.

Entrepreneurship policy is a vital component of any entrepreneurial ecosystem. However, the specific policy initiatives that have a greater impact on women's entrepreneurship remain unclear in many developing economies. Therefore, this study aims to evaluate the effectiveness of entrepreneurship policies targeted at women’s entrepreneurship in sub-Saharan Africa (SSA).

Employing fuzzy-set qualitative comparative analysis (fsQCA), this paper utilises and analyses secondary data collected by the World Bank's Women, Business, and the Law (WBL) from 1970 to 2020, encompassing 48 countries within SSA.

Through our analysis, we identified two configurations that sufficiently support women's entrepreneurship. First, a combination of gender-based policies focussing on enabling “access to credit” and “signing of contracts”; and second, a blend of policies supporting “signing of contracts”, “business registration”, and “opening a bank account”, represent significant antecedents to supporting women's entrepreneurship. These distinct pathways are crucial to fostering women’s entrepreneurship in the SSA region.

The study's findings indicate that the impact and effectiveness of entrepreneurship policies targeted at women entrepreneurs in developing economies depend on the effectiveness of other policies that are in place.

This study offers new insights into the intricate interrelationship between entrepreneurship policies and women’s entrepreneurship in developing countries by considering the interdependence and combinative value of gender-based policies that effectively support women’s entrepreneurship in sub-Saharan Africa.

The authors construct an index of economic policy uncertainty (EPU) for Greece using textual analysis and analyze its role in the 10-year Greek economic crisis.

To identify the causal relationship between various measures of economic activity and EPU in Greece, the authors use a sophisticated “shock-based” structural vector autoregressive identification scheme. Additionally, the authors use two additional models to ensure the robustness of the results.

EPU is negatively associated with domestic economic activity and economic sentiment, and positively with bond credit spreads. EPU is also estimated to have prolonged the crisis even in periods when macroeconomic imbalances were cured. The results are robust across various model specifications and different proxies of economic activity.

Brunnermeier (2017) observed that uncertainty may be central to understanding the evolution of the Greek crisis. Yet little attention has been paid to policy uncertainty in the existing long and growing literature on the Greek crisis. The authors attempt to fill this gap.

The monetary policy is an important driver of the real estate sector’s performance. The recent wave of monetary tightening in 2022 in response to the cost-of-living crisis has been associated with the decline in housing prices across the globe. There are two main channels through which the US monetary policy may affect the real estate market in the dollar-pegged countries: the cost of serving mortgages (financing cost) and the exchange rate channel (for example, the appreciation of the US dollar and consequently the local currency). The exchange rate channel, which involves the appreciation of the US dollar and the subsequent effect on the local currency, is particularly significant in the case of Dubai, given how international the housing market in Dubai and might be viewed as a tradable good. Using recent data, the purpose of this study to evaluate the spillover impact of the US monetary policy on the housing market performance in the dollar-pegged countries using Dubai as a case study.

For this purpose, this study collected unique longitudinal data on the volume of the monthly transactions of residential properties and performs a panel-data analysis using within-variation models. The changes in the interest rate policy in the USA are determined by the domestic inflation in the USA, thereby, representing an exogenous shock in the UAE.

The results are robust to different specifications and suggest that a strong negative correlation between the interest rate in the USA and the housing sector demand in Dubai. Fiscal policy measures can be taken to mitigate tighter financial conditions in case of policy misalignment.

Few studies have looked at the spillover impact of the global monetary conditions on the real estate market in the GCC region. This study fills this gap by exploring the impact of the US financial conditions on Dubai’s real estate, using panel data analysis.

This paper aims to examine the dynamic impacts of the COVID-19 pandemic and government policy on real house price indices in five emerging economies, namely, Brazil, China, Thailand, Turkey and South Africa.

The authors use the local projection method with a panel data set of these countries spanning from January 2020 to July 2021.

The number of COVID-19 confirmed positive cases raised housing prices, whereas government containment measures reduced them. Both conventional and unconventional monetary policy implemented by central banks to cope with the COVID-19 helped increase housing prices. These effects were strengthened by the US monetary policy via globalized financial markets.

First, while previous researches typically concentrated on developed countries, the authors investigate emerging economies where proportionally more people were badly affected by the pandemic. Second, a panel data set of five emerging economies enabled the authors to examine the dynamic effects of the COVID-19 crisis on housing prices. Third, to the best of the authors’ knowledge, this is the first study evaluating the influences of easing monetary policy on housing prices in emerging economies during the pandemic.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

Whether a human body has a healthy carrying capacity is calculated by body mass index (BMI). The BMI is found by dividing body weight in kilograms by the square of body length. If the person's body weight is more than the heaviness that the body can carry healthily, it is called obesity. Destinations have a specific area, just like a human body. Therefore, any destination whose carrying capacity is exceeded can be called an “obese destination”. This study's primary purpose is to reveal the importance of destination carrying capacity through the concept of obesity.

Content analysis, one of the qualitative research methods, was employed, and graffiti reflecting the feelings of the local people toward tourists were used as data. Graffiti was considered as a social carrying capacity indicator to identify obese destination symptoms. Fifty graffiti obtained from search engines about destinations with obesity problems were analyzed.

The study's findings reveal that anti-tourist graffiti indicates obese destination symptoms. Furthermore, when the content analysis of graffiti is examined, it is seen that the obese destination's local people have intense anger toward tourists. This is a clear manifestation of the destination's health deterioration.

This study, in which the concept of obese destination is used for the first time, suggests that destinations' health may worsen just like people. If destinations with over-tourism are called obese, a more expansive awareness will be created about the destinations' problems. The study suggests that nonecolabel can be used as a mandatory diet tool for obese destinations. Anti-tourist graffiti has been addressed as an obese destination symptom.

The impact of COVID-19 on tourism destinations has been severe, but a future crisis is never far away. How communities can better prepare for disasters to come in the near future continues to be researched. This research aims to understand the tourism community’s responses to the COVID-19 pandemic and present the Tourism Community Resilience Model as a useful instrument to help communities better respond to disasters in the future.

This research uses a qualitative research approach which seeks to understand phenomena, events, social activities, attitudes, beliefs, perceptions and individual and group opinions that are dynamic in character in accordance with the situation in the field. Research primary data is in the form of Kuta Traditional Village local community responses in enduring the COVID-19 pandemic conducted between January and May 2022. These data were obtained through in-depth observations and interviews involving informants based on purposive sampling, including traditional community leaders, village officials, tourism actors (i.e. street vendors, tourist local guides, taxi drivers and art workers) and tourism community members. We selected the informants who are not only directly impacted by the pandemic, but also some of them have to survive during the pandemic because they do not have other job options. The results of previous research and government data concerning the pandemic and community resilience were needed as secondary data, which were obtained through a study of the literature. The data which had been obtained were further analysed based on the Interpretative Phenomenological Analysis (IPA) technique, which seeks to make meaning of something from the participants’ perspective and the researchers’ perspective as a result there occurs a cognition of a central position.

Based on findings from Bali, Indonesia, this resilience model for the tourism community was created in response to the difficulties and fortitude shown by the community during the COVID-19 pandemic. It comprises four key elements, namely the Local Wisdom Foundation, Resource Management, Government Contributions and External Community Support. These elements are all rooted in the concepts of niskala (spirituality) and sekala (real response); it is these elements that give the tourism community in the Kuta Traditional Village a unique approach, which can inspire other tourism destinations in other countries around the world.

A tourism community resilience model based on local community responses has implications for the process of enriching academic research and community management practices in facing future crisis, particularly by involving local wisdom foundation.

A tourism community resilience model based on local community responses has implications for the process of enriching academic research and community management practices in facing future crisis, particularly by involving local wisdom foundation.

The existence of the resilience model strengthens local community social cohesion, which has been made stronger by the bonds of culture and shared faith in facing disaster. This social cohesion then stimulates the strength of sustainable and long-term community collaboration in the post-pandemic period. For tourism businesses, having strong connections with the local communities is an important condition to thrive.

The value of this research is the Tourism Resilience Community Model, which is a helpful tool to optimise and improve future strategies for dealing with disasters. Illustrated by this Balinese example, this paper emphasises the importance of adding social factors such as niskala and sekala to existing community resilience models. Addressing these local characteristics is the innovative aspect of this paper and will help inspire communities around the world to prepare for future disasters better and build more sustainable and resilient tourism destinations elsewhere.

Based on the research of free trade agreements on alleviating service trade policy heterogeneity and its impact on manufacturing exports, this article aims to not only provide a basis for China's strategy of promoting regional economic integration, but also provide a policy reference for the manufacturing industry to expand the export market space.

This study uses the two principles of “answering” and “scoring” to quantify the indicators of service trade policy heterogeneity to test the relationship between heterogeneity of service trade policy, free trade agreement and manufacturing export.

According to empirical study, the export of Chinese manufacturing firms is severely hampered by the variety of service trade regulations, and the bigger the enterprise, the more hampered it is. In comparison to communications, transport and commerce, the financial industry's policy heterogeneity has a greater negative impact on certain industries. The major methods used to reduce the impact of service trade policy heterogeneity on manufacturing exports are product price increases and product quantity reductions. Also, by reducing the heterogeneity of service trade regulations and fostering industrial exports, the free trade agreement that China has signed can be quite successful. The open commitment in the area of national treatment, however, can reduce policy heterogeneity and advance manufacturing.

In the area of market access, the effect of export is superior to the open promise. Thus, in order to effectively support the stabilization of international trade, China should actively encourage the negotiation and signing of higher-quality and mutually beneficial free trade agreements.

The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations.

Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present.

This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated.

This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.