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This article provides evidence of a long-term structural relationship between demand for heated tobacco products (HTPs) and for combustible cigarettes in a Marshallian demand framework, using data from the Italian market.

A cointegration-based approach allows to capture the substitution effects between the two products arising for reasons (possibly) other than price.

The authors find that such a relationship exists and is sufficiently strong to constitute a cointegration.

Since a fully consolidated consensus on reduced harm from smokeless tobacco products is absent, symmetric policies on both markets are therefore necessary in terms of regulation and excise incidence to minimize the social cost of substitution and to maximize government revenues, which are a necessary counterpart to negative externalities that arise with smoking both products.

This paper focuses on the Italian market with product specific volume and price data, both for cigarettes and HTPs. Because of the detected relationship, a regulatory trade-off arises in case of a relatively mild regulation on heated-tobacco products: benefits from decreasing demand for combustible cigarettes may be offset by the social cost of increasing consumption of heated tobacco products. Moreover, a milder regulation makes price related policies to curb smoking less effective.

Managers engage in marketing efforts to boost sales and in setting marketing budgets based on current or historical sales. Past studies have overlooked the reciprocal relationship between marketing spending and sales. This study aims to examine the nature of the relationship between sales and marketing expenses in the B2B market.

Five hypotheses on the relationship between sales and marketing expenditures were framed. A total of 30 of India’s dyeing firms provided data on revenues, sales (in units) and marketing expenditures over time. The structural vector auto-regressive model and the vector error correction model were fitted to the data.

The results show that marketing expenses and sales are related bidirectionally in a sequential way. Furthermore, sales drive the long-term equilibrium relationship to a greater extent than marketing expenditures.

The findings of this study should assist managers in predicting sales and marketing budgets simultaneously and devising precise marketing strategies and tactics.

Using econometric models in data-driven research is not a frequent practice in marketing. This study adds value to the body of marketing literature by advancing the theory of the relationship between sales and marketing spending using real-world data and econometric models in the B2B sector.

Trade of environmentally sensitive goods (ESGs) is often exposed to countries with less stringent regulations suggesting that those countries have comparative advantage in the polluting sector. The Group of Twenty (G20) members are among the highest polluters, globally. Different stringency policies are enacted time to time in G20 to control environment pollution. However, the impact of policy stringency on export performance of ESGs is seldom examined. The paper aims to address some of the issues concerning this matter.

The present study aims to address the short run and long-run association between Revealed Comparative Advantage of ESGs and Environmental Policy Stringency Index for the period of 1990–2019 in G20. Periodic fluctuations and time adjustment mechanism are also studied. Second Generation Panel Cointegration, Vector Error Correction, Impulse Response Function and Variance Decomposition methods are employed to address the objectives.

Result is evident that more exposure to stringent environmental regulations reduces the comparative advantage of ESGs in the long run. But there is no evidence of the short-run relationship between the variables. The possible reason could be that new regulations enacted prove fruitful in the long run.

The novelty of the study is to focus on inter linkages between stringency and global export competitiveness in G20, almost nonexistent in the past studies. The study also provides a road map to policymakers to find out potential ways for sustainable development by balancing environmental stringency measures and international trade.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0560

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

This paper aims to examine Nigeria’s dynamic output and output volatility connectedness with USA, China and India using quarterly data from 1981Q1 to 2019Q4.

The study adopted the network approach of Diebold and Yilmaz (2014) and used the normalized generalized forecast error variance decomposition from an underlying vector error correction model to build connectedness measures.

The findings show that the global financial crisis (GFC) increased the connectedness index far more than the 2016 Nigeria economic recession. The moderate effect of the 2016 Nigeria economic recession on the connectedness index underscores the fact that Nigeria is a small, open economy with minimal capacity to spread output shock. For both real output and its volatility, the total connectedness index rose smoothly and systematically through time, thereby leaving the economies more connected in the long run.

To the best of the authors’ knowledge, this paper is among the first to examine Nigeria’s dynamic output and output volatility connectedness with the USA, China and India using new empirical insights from the GFC versus 2016 Nigerian recession. The study, therefore, concludes that the Nigerian economy should be diversified immediately as a hedge against future real output shocks, while the USA, China and India should maintain and sustain their current policy frameworks to remain less vulnerable to real output shocks.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

Paper aims to investigate the interdependencies and spillover effects that the Visegrad (V4 hereafter) Equity Markets hold on each other. The V4 group stands for the political alliance of four Central European countries: Poland, the Czech Republic, Hungary and Slovakia.

The study uses Wavelet coherence, dynamic conditional correlation GARCH (1, 1) and unrestricted vector autoregression (VAR) methodologies. Daily data series (covering the period from January 2, 2006, to February 2, 2023) are analyzed to assess coherence, time-varying conditional correlation and shock transmission among the V4 Equity Markets.

Wavelet analysis reveals that the Slovak equity market does not maintain coherence with three other equity markets. The time-varying conditional correlation documents for the high interdependence during the COVID-19 outbreak of the four indexes. The VAR estimates reveal that shocks in the Warsaw equity market are easily transmitted in Prague and Budapest exchanges but not in Bratislava. The results show that the Slovak equity market tends to be isolated from the influence of other three V4 exchanges. This isolation is attributed to its size, limited volume and adoption of the euro in 2009. The study emphasizes the Slovak financial system’s gravitation toward the Eurozone after euro adoption.

Notably, the findings provide important signals for local and international investors as the results cover four significant international shocks. The global meltdown of 2008/09, the Greek debt crisis of 2010/11, the COVID-19 pandemic and the Russia-Ukraine war.

This study seeks to build a financial uncertainty index for Saudi Arabia. This index serves as a leading indicator of Saudi economic activity and helps to describe economic fluctuations and forecast economic trends.

This study adopts an extension of the Jurado et al. (2015) procedure by combining financial uncertainty factors with their net spillover effects on GDP and inflation to construct an aggregate financial uncertainty index. The authors consider 13 monthly financial variables for Saudi Arabia from January 2010 to June 2021.

The empirical results show that the constructed financial uncertainty estimates are good leading indicators of economic activity. The robustness analysis suggests that the authors’ proposed financial uncertainty estimators outperform the alternative estimates used by other existing approaches to estimate the financial conditions index.

To the best of the authors’ knowledge, this is the first attempt at constructing a financial uncertainty index for Saudi Arabia. This study extends the empirical literature, from which the authors propose a novel conceptual framework for building a financial uncertainty index by combining the approach of Jurado et al. (2015) and the time-varying connectedness network approach proposed by Antonakakis et al. (2020)

Our study aims to evaluate the impact of infrastructure and public investment on private investment in machinery and equipment in Brazil from 1947 to 2017. The contribution of our article to the existing literature lies in providing a more comprehensive understanding of the presence or absence of the crowding effect in the Brazilian economy by leveraging an extensive historical database. Our central argument posits that the recent decline in private capital accumulation over the last few decades can be attributed to shifts in economic policies – moving from a developmentalist orientation to nondevelopmental guidance since the early 1990s, which is reflected in the diminished levels of public investment and infrastructure since the 1980s.

We conducted a series of econometric regressions utilizing the autoregressive distributed lag (ARDL) model as our chosen econometric methodology.

Employing two different variables to measure public investment and infrastructure, our results – robust across various specifications – have substantiated the existence of a crowding-in effect in Brazil over the examined period. Thus, we have empirical evidence indicating that the state has influenced private capital accumulation in the Brazilian economy over the past decades.

Our article contributes to the existing literature by offering a more comprehensive understanding of the crowding effect in the Brazilian economy, utilizing an extensive historical database.

The current study aims to ascertain the association between tourism development, economic growth and environmental quality by using the short-run and long-run autoregressive distributive lag model.

Tourism development has a major role to play in improving a nation’s economic growth. However, it is also blamed for exacerbating environmental pollution because of its massive use of energy (non-renewable energy).

The major findings of this research show that renewable energy (RE) use and gross domestic product (GDP) negatively impact carbon dioxide (CO₂) emissions in South Africa. Tourism arrivals and CO₂ emissions negatively impact GDP, while capital positively impacts GDP in the long run.

This research recommends the use of RE, since it reduces carbon emissions, and capital, as it remains the major driver of economic growth.

The originality of the current research is that it uses long-period annual time series data from 1971 to 2019 of South Africa, one of the largest tourist nations in Africa. To the best of the authors’ knowledge, no studies have examined South Africa in this context and minimal research has been conducted to ascertain the impact of the tourism industry on the environment, despite the accusations directed toward it.