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Tourism–economy relationship in India has been studied extensively in the past literature using a single equation approach. However, the present paper diverted from this trend and examined the tourism–economy relationship using the specific to general modelling approach over the 1990–2018 time period. The study also accounts for the influence of merchandise trade, capital formation, foreign investment inflows and inflation on economic growth to achieve the robustness of the coefficient estimates.

To achieve the objective, the study utilised a specific to general modelling strategy. First, the regression equation includes only three core variables: gross domestic product (GDP), international tourist receipts and international tourist expenditures. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegration among the variables. As for the estimation technique, the authors employed autoregressive distributed lag (ARDL) approach.

The paper's findings highlight that tourism receipts and expenditures exert a positively significant impact on economic growth. Moreover, including the additional independent variables does not substantially change the tourism and economic growth relationship. The existence of one-way causality from tourism expenditures to economic growth supports the tourism-led growth hypothesis. These findings highlight the rationale for intervention by the government and policymakers to promote tourism potential and facilities to accelerate the overall growth performance of the country. While the existence of one-way causal effect from economic growth to tourism revenues supports the growth-led tourism development hypothesis, implying that economic expansion is necessary for tourism development.

This research article tried to present a comprehensive picture of India's tourism–economy relationship. However, the present study is organised as an aggregate economy-level analysis. It assumed that the aggregate tourism sector is homogenous. However, different tourism sectors exert different levels of influence on the economy. The authors expect future research can take the disaggregated analysis of the tourism–economy relationship.

This study provides valuable insights into the tourism-led growth hypothesis in India. The study highlights comprehensive intervention by the government and policymakers for accelerating tourism development to invigorate the overall growth performance of the country over the long run. The principal recommendation emerging from the present research is that the tourism growth potential can be depended upon to stimulate the economic performance of the Indian economy.

The present study diverted from the previous empirical studies by following a specific to general modelling strategy. First, the regression model includes only three core variables such as economic growth, tourism receipts and tourism expenditure. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegrating relationship among the variables. GDP growth rate is used as a dependent variable in all five specifications. The idea is to expand the model to capture every feature of the data generating process.

Hazel Kyrk’s contribution is the most advanced formulation of the economics of consumption as a social phenomenon, an approach to the analysis of consumption that, originated from Veblen’s theory, was developed in the US in the early 20th century. This approach was part of a wider stream of empirical analyses of consumption expenditure that had begun more than a century earlier.

Along with elements that can be traced back to the neoclassical tradition, in Keynes’ analysis of consumption, we find original elements. The dependence of consumption expenditure on the level of income, which is essential for asserting the principle of effective demand, can also be found in a long tradition of empirical studies. In qualifying this relationship, Keynes uses theoretical elements echoing key insights of the economics of consumption as a social phenomenon. There is no documentary evidence that Kyrk or the economics of the social relevance of consumption came to Keynes’ attention. It is possible, however, to develop reasonable speculative considerations to argue a link between Keynes’ elaboration and both the empirical literature on the determinants of consumption and the economics of consumption as a social phenomenon.

Unlike other types of corporate disclosure, corporate political disclosure (CPD), which is the disclosure of corporate political contributions and the related governing policies and oversight mechanisms, does not provide completely new information to stakeholders. Some of the information disclosed in CPD is available from other public records (e.g. the Federal Election Committee website or OpenSecrets website). Given this unique feature of CPD, it is interesting to investigate the cost and benefit tradeoff for firms of altering their CPD practice in response to policy and political uncertainty.

This study employs recently developed indexes of aggregate economic policy uncertainty (EPU) and a novel dataset of CPD transparency to examine the impact of EPU on CPD transparency and how the proprietary cost of corporate political activities moderates this association. The sample consists of S&P 500 companies from the 2012 to 2019 period.

The authors document that firms mitigate the heightened information asymmetry associated with higher aggregate EPU by increasing CPD transparency. The positive association between EPU and CPD is less pronounced for firms that are more sensitive to EPU, for firms that more actively manage EPU through corporate political contributions or lobbying activities and for firms that are followed by more analysts. The authors also find that more transparent CPD helps to mitigate the information asymmetry caused by heightened EPU. This study’s results hold when the authors control for other types of voluntary corporate disclosure.

This study contributes to the emerging literature on the determinants of CPD transparency by identifying EPU's positive impact on CPD transparency. This study also provides empirical evidence that the proprietary costs arising from the controversial nature of corporate political activities dampen firms' incentives to provide transparent CPD in response to heightened EPU, and that information on corporate political activities gathered and processed by financial analysts seems to lower the marginal benefit to companies of publicizing CPD on their own website.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

This chapter examines the influence of external public borrowing resources on economic progress in Tunisia. The study focuses on two stages: First, the influence is studied in a direct sense and then in an indirect sense, i.e., through a transmission channel of this influence. By applying the autoregressive distributed technique with staggered lags (ARDL), over a period ranging from 1986 to 2019, the results showed that the influence of external borrowing resources on growth seems to be unfavorable in the short term but positive in the long term, hence the importance of the empirical technique chosen. Second, three interaction variables were tested, namely total government expenditure, government investment expenditure, and the real effective exchange rate. The results obtained call for better attention to the channels identified to maximize the positive influence of external public debt on the country's economic progress.

Government spending plays a crucial role in fiscal policy in any country, both as a tool for implementing individual government policies and as a possible instrument for mitigating uneven economic developments and economic shocks. This chapter provides direct empirical evidence on the development and structure of general government expenditure and its relationship with real economic growth in Czechia and the European Union countries. Compared to theoretical recommendations, general government expenditure has not been used as a stabiliser in Czechia and EU countries and has been observed to be pro-cyclical in the period under review. Granger causality analysis identified the direction of causality between the macroeconomic variables analysed and found that in most cases economic growth came first, followed by government spending.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

Considering that food security is a global responsibility, the purpose of this study is to examine the impact of agricultural industries on vulnerability to climate change and the moderating effects of gender-diverse parliaments, education expenditures, research and development (R&D) expenditures and foreign direct investment (FDI).

Using concepts in governance, innovation and knowledge theory, a large panel data set of 125 countries covering 1997–2018 (1,852 country-year observations) was analyzed. Data were sourced from the Notre Dame Global Adaptation Index, the World Bank, the Heritage Index and the International Monetary Fund. Moderated random effects regression was conducted in Stata.

The results reveal that agricultural industries are positively associated with vulnerability to climate change and provide support for our predictions that education expenditures and FDI both reduce the impact of agricultural industries on vulnerability to climate change. However, contrary to predictions, the percentage of women in parliament and R&D expenditures both increase this impact.

To the best of the authors’ knowledge, this is the first quantitative study that uses large, established data sets to explore the relationship between agricultural industries and country vulnerability to climate change. This study shows the significance of country-level factors that both decrease and increase the impact of agricultural industries on vulnerability to climate change.

As digital technologies expand access to new forms of legalized gambling, including sports betting and online gaming, it is important to assess the impact of macroeconomic and equity market outcomes on fund flows into gambling. The authors’ findings will be of interest to policymakers and the gambling industry, as various forms of gambling, including day trading, gain broad public acceptance.

The authors examine the impact of macroeconomic forces, business cycles, and financial market wealth on gambling. The authors propose a nonlinear model linking aggregate gambling expenditures to macroeconomic, stock market, and gambling industry variables. The authors estimate the proposed model using nonlinear estimation procedures.

The authors find that price of wagering, incomes, and supply of gambling opportunities are the primary determinants of wagering demand. Aggregate wagering is negatively impacted by realized stock returns and market volatility, but rises during recessions.

To the best of the authors’ knowledge, the questions posed and addressed in this manuscript have not been addressed in prior literature.