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This paper attempts to investigate through empirical exercise how the chances of female employment opportunities rise in a developing country like India, against the backdrop of changes in institutions that are associated with globalization.

The paper develops a simultaneous equation model through a growth equation, gender equation and globalization equation to identify the factors impacting female labor market opportunities in India, based on annual time series data 1991–2019.

The major results of this study are as follows: (1) It is social globalization that positively impacts gender equality in employment opportunities apart from economic growth and trade diversification; (2) Evidence of “feminization of labor force” in the context of trade diversification is found; and (3) Equal gender opportunities reflect in equalizing outcomes in the labor market.

Growth strategies need to be constructed in such a way in India that it has redistributive implications and benefits women. The state agency needs to optimize the productive base of human resources and increase women's empowering capability through social and legal sanctions.

The uniqueness of the present paper lies in contributing to the existing literature on how gender inequality impacts trade diversification and how trade diversification impacts gender.

In the maritime industry, it is vital to have a reliable forecast of container shipping demand. Although indicators of economic conditions have been used in modeling container shipping demand on major routes such as those from East Asia to the USA, the duration of such indicators’ effects on container movement demand have not been systematically examined. To bridge this gap in research, this study aims to identify the important US economic indicators that significantly affect the volume of container movements and empirically reveal the duration of such impacts.

The durability of economic indicators on container movements is identified by a vector autoregression (VAR) model using monthly-based time-series data. In the VAR model, this paper can analyze the effect of economic indicators at t-k on container movement at time t. In the model, this paper considers nine US economic indicators as explanatory variables that are likely to affect container movements. Time-series data are used for 228 months from January 2001 to December 2019.

In the mainland China route, “building permission” receives high impact and has a duration of 14 months, reflecting the fact that China exports a high volume of housing-related goods to the USA. Regarding the South Korea and Japan routes, where high volumes of machinery goods are exported to the USA, the “index of industrial production” receives a high impact with 11 and 13 months’ duration, respectively. On the Taiwan route, as several types of goods are transported with significant shares, “building permits” and “index of industrial production” have important effects.

Freight demand forecasting for bulk cargo is a popular research field because of the public availability of several time-series data. However, no study to date has measured the impact and durability of economic indicators on container movement. To bridge the gap in the literature in terms of the impact of economic indicators and their durability, this paper developed a time-series model of the container movement from East Asia to the USA.

The purpose of this paper is to assess both short and long-term influences of public investment on economic growth and test the hypothesis that whether public investment promotes or demotes private investment in Vietnam.

The authors use the approach of autoregressive distributed lag model and Vietnam’s macro data in the period of 1990-2016, to evaluate the short and long-term effects of public investment on economic growth and private investment. The model evaluates the impact of public investment on economic growth and private investment based on the neoclassical theories. The public investment which strongly affects economic growth is also reflected by aggregate supply and demand. Public investment directly impacts aggregate demand as a government expenditure and aggregate supply as a production function (capital factor).

The results from this research indicate that public investment in Vietnam in the past period does affect economic growth in the pattern of an inverted-U shape as of Barro (1990), with positive effects mostly occurring from the second year and negative effects of constraining long-term growth. Meanwhile, investment from the private sector, state-owned enterprises, and FDI has positive effects on short-term economic growth and state-owned capital stock has positive impacts on economic growth in both the short and long run. The estimated influence of public investment on private investment also shows a similar inverted-U shape in which public investment have crowding-in private investment short-term but crowding-out in the long run.

The empirical findings in this study can be used for conducting a more efficient policy in restructuring the state sector investment in Vietnam.

The main contributions in this study are: to evaluate the impacts of public investment on economic growth and private investment, the authors extracted public investment in infrastructure from aggregate investment of state sector (as previous studies used); the authors also uses state-owned capital stock variable including cumulative public investment and state-owned enterprises investment suggesting that this could control for the different orders of integration between the stock and flow variable and improve the experimental characteristics of the equation to a higher degree.

This study provides empirical evidence on the impact of the Panama Canal expansion (PCE) on the economies of Latin American and Caribbean (LAC) countries, particularly in light of the emergence of larger container ships such as neo-Panamax and post-Panamax vessels.

This study uses the Bayesian structural time Series (BSTS) model to evaluate the economic effects of the PCE on 21 countries within the LAC region. It utilized the World Bank's gross domestic product (GDP) figures between 2000 and 2019 as the primary variable, alongside the human development index (HDI) (X1), container throughput (TEU) (X2) and unemployment rates (UNEMPL) (X3) covariates. This allowed a precise and robust approach to analyzing time series data while accounting for uncertainties and allowing the inclusion of various components and external factors.

The findings revealed that the PCE has a positive and statistically significant impact on most countries within the Caribbean Transshipment Triangle, ranging from 9.2% in Belize to 46% in Cuba. This suggests that the causal effect of the PCE on regional economies was not confined to any specific type of economy or geographical location within the LAC region. Where the growth rates were statistically insignificant, primarily in some Latin American countries, it coincided with countries that are primarily driven by exports and service industries, where bulk and oil tanker vessels are likely to be the main carriers for exports rather than container vessels.

The practical implications of this research are crucial for various stakeholders in the maritime industry and economic planning. The factors influencing economic growth resulting from investing in maritime activities are vital for decision-makers to create policies that lead to positive outcomes and sustainable development in regions and countries with flourishing maritime industries. The methodology and findings have significant implications for governments, managers, professionals, policy-makers and investors.

The purpose of this study is to investigate the impact of climate change on economic development in Bangladesh. More specifically, the research aims to figure out the influence of climate change on gross domestic product (GDP) growth rate related to different sectors such as agriculture, forest, water, health and infrastructure. It also attempts to explore the effect of climate change on the coastal economy of Bangladesh.

A set of statistical and econometric techniques, including descriptive and correlation analysis and time series regression model, was applied to address the objective of the research. Sector-wise time series economic data were collected from the World Bank for the period between 1971 and 2013. Climate data were received from the Bangladesh Agricultural Research Council online database for the period between 1948 and 2013.

The results from the statistical analysis show that climate variables such as temperature and rainfall have changed between 1948 and 2013 in the context of Bangladesh. The econometric regression analysis demonstrates that an increase by 1°C of annual mean temperature leads to a decrease in the GDP growth rate by 0.44 per cent on average, which is statistically significant at the 5 per cent level. On the other hand, the estimated coefficients of agriculture, industry, services, urbanization and export are positively associated with GDP growth rate, and these are statistically significant at the 1 per cent level. Sector-wise correlation analysis provides statistical evidence that climate change is negatively associated with various sectors, such as agriculture, forest, human health and arable land. In contrast, it has a positive relation to water access and electricity consumption. Analysis of coastal regions shows that climate change negatively affects the local economic sectors of the coastal zone of the country.

Although this study has received significant insight from the world-renowned research publication “The Economics of Climate Change: The Stern Review”, there is a dearth of research on the economic impact of climate change in the context of Bangladesh. The findings of the paper provide deep insight into and comprehensive views of policy makers on the impact of climate change on economic growth and various sectors in Bangladesh.

The purpose of this study was to create a more balanced, comprehensive and valid illustration of the relationships between casino gaming volume and employment during economic downturns in urban and rural locations in nondestination gaming states.

This study analyzes gaming volumes and employment prior, during and after the recession of 2007–2009, using a time series with intervention analysis on a monthly coin in, table drop and regression analysis on employment impacts of casinos.

Findings indicate that while there was a slight drop in gaming revenue and employment figures during the economic downturn, nondestination gaming locations such as Indiana proved relatively resilient to an economic downturn.

The Great Recession had no significant impact on gaming volume because gamblers chose to spend their more limited entertainment dollars on less expensive gaming options; in other words, casinos closer to home requiring the expenditure of fewer dollars on travel and/or hotel rooms. The current pandemic and pressures of the macro-environment again threaten the US gaming and casino market with an economic downturn and the results of this study are as timely as ever for hospitality professionals and social scientists to understand the behavior of casinos in recessionary environments.

The purpose of this study is to analyze how sentiment affects economic activity in Brazil.

Based on a nonlinear autoregressive distributed lag (NARDL) model, this study examines in detail the short-term and long-term asymmetric impacts between the variables during the period from January 2007 to December 2020.

There are three main results of this study. First, sentiment is an important factor for economic activity in Brazil, and its effect possibly occurs through the channels of consumption and investment, which are the two main components of economic growth. Second, sentiment affects economic activity in different ways in the short and the long term: in Brazil, although in the short-term, immediate shocks of sentiment may be confusing, the negative shocks from previous periods have a negative impact on economic activity. Third, the effect of shocks of optimism and pessimism on economic activity is asymmetric, and in the long run, only shocks of optimism have a significant and positive impact.

The relationship between sentiment and economic activity is still a controversial issue in the literature and this study seeks to advance its understanding in Brazil.

This study investigated the impact of economic growth on carbon emissions on selected West African countries between 1980 and 2019. Simon-Steinmann's economic growth model provides the relevant theoretical foundation. The main objective of this study was to ascertain whether economic growth will impact carbon emissions.

The study selected six-sample countries in West Africa and used secondary data obtained through the World Bank Group online database covering the period 1980–2019, employing panel econometric methods of statistical analysis.

The outcome indicates that the independent variable showed a positively significant impact on the dependent variable for the pooled samples in the short-run, with significant cointegration.

The study concluded that economic growth significantly impacts the emissions of carbon, and a 1% rise in economic growth will result to 3.11121% unit rise in carbon emissions.

Policy implementation should encourage the use of energy efficient facilities by firms and government and the establishment of carbon trading hubs.

Failure by governments to heed the recommendations of this research will result to serious climate change issues on economic activities with attendant consequences on human health within the region and globally.

This is one of the comprehensive works on subject covering the West African region within the continent.

This paper aims to study the relationship between employment and tourism activities as well as economic variables for the 32 states of Mexico for the period 1999-2014.

To study the case of Mexico, the authors use panel data and cointegration panel data. They also use geographic information systems to observe changes over time between the variables, which is useful in the empirical evidence.

The main results obtained by the models are as following: domestic tourism is the variable with the greatest impact on the generation of direct employment in the tourism sector, a finding supported by both methodologies; economic growth (measured by state gross domestic product) also directly impacts the generation of employment; and the cointegration of the panels causes a long-term equilibrium among the states and some variables.

The model used leaves out other variables that may influence the performance of the tourist activity. In addition, given the availability of official and homogeneous information, it only covers what has been documented up to 2014.

The aim is to measure the impact of tourism on the variables at the state level, where the economic activities could be based on public policies, as well as the importance of tourism activities in generating employment. In this sense, the impact would be in channeling efforts to support the main economic activities and could serve as a starting point for the evaluation of programs to promote domestic tourism.

This paper reviews the relationship that exists between tourism activity and its effect on other variables, especially employment. It is the first time that these topics are studied for the Mexican economy.

The purpose of this paper is to explore the concept of pensionomics as a prospective tool for pension evaluation. This paper suggests a paradigm shift – a multi-disciplinary synthesis of differing perspectives in evaluating pension’s overall performance based on past work on pension evaluation – incorporating non-economic variables with significant impact on economic growth and social development.

This paper suggests a new analytical tool called “Pensions Consistency (PC) Index” that identifies the level of consistency and the strengths and weaknesses within any pension system. The new conceptual framework focusses on building inter-sectoral and holistic policies able to respond to the new multi-dimensional dynamic environment.

The consideration of pensionomics concept as an evaluation tool for pension schemes provides insights that are helpful in explaining performance differentials. Taking definition, classification and evaluation as a guiding principle, the new conceptual framework can be a useful point of reference for the overall evaluation of pension schemes, revealing deficiencies that traditional evaluation methods cannot detect. The multi-disciplinary approach focusses on building inter-sectoral and holistic policies that are able to respond to the multi-dimensional uncertainties of the new dynamic environment.

The heterogeneity and complexity in event dynamics are systemic in the sense that the impact is far from linear. The idiosyncratic nature of unexpected and unpredictable events is rather a result of multi-dimensionality based, among others, on magnitude, frequency, timing, intensity and impact. It is plausible to argue that crisis episodes can destabilize critical systems of economic activity, producing economic spillovers that can directly or indirectly affect the sustainability of pension schemes. If the calculation of direct economic impact is readily traceable, the estimation of indirect economic impact can be an onerous task.

Pensionomics places the concept of retirement in a multi-disciplinary context. Pensionomics overcomes theoretical and empirical limitations encountered by the path-dependency perspective, developing a new research agenda to study pension schemes under historical, cultural, social, political, economic, political and environmental prism. Integrating diversified data, techniques, perspectives and concepts, pensionomics’ objective is to connect natural and man-made events with social protection mechanisms for the development of a dynamic social protection framework where individual, community and society needs are met effectively and efficiently by implementing tailored policies, closely related to their specific context.

The concept of retirement has evolved constantly, transforming societies and shaping both income and non-income dimensions of well-being. Pension entitlement turned gradually from a political discourse to a human right discourse. Pension schemes have extended the scope of insurance coverage beyond labour markets and the lifecycle, supporting the broader needs of entire population. Furthermore, pension schemes are widely acknowledged as drivers of economic growth: they enhance labour productivity; foster smooth consumption; and create a stable economic environment for investment and innovation. Current expectations require pension schemes to adopt proactive and reactive policies to examine options for mitigation or for modification of potential consequences in anticipation of exceptional events.

This paper suggests a paradigm shift, a multi-disciplinary approach called pensionomics, and this “multi-disciplinary” focus builds a new analytical framework to evaluate pension’s overall performance based on past work on pension evaluation, incorporating non-economic variables with significant impact on economic growth and social development. PC-Index introduces a comprehensive evaluation tool to study the coverage, performance, efficiency, effectiveness, current trends and future possibilities of pension schemes.