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This paper aims to examine whether idiosyncratic volatility and other asset pricing factors predict growth rates of the ten Australian economic indicators.

The authors use the Liew and Vassalou (2000) model augmented with an idiosyncratic volatility factor to investigate the issue.

Using regression analysis, the authors find that the asset pricing factors can be used to predict the growth rates for eight out of the ten economic indicators. Moreover, using portfolio performance analysis, the authors find that high returns of size factor and a book-to-market factor portfolios precede periods of good macroeconomic states, whereas high returns of HIMLI portfolios precede periods of bad macroeconomic states.

To the authors’ knowledge, the relationship between idiosyncratic volatility and Australian economic growth has not been investigated explicitly in the literature.

Financial market holds superior information that can give insights into the future trajectory of economic growth. Further, identifying sectors that hold the key to future economic growth is important for all economies, but particularly relevant to emerging markets. However, unlike existing studies, the paper provides new insights into the forward-oriented nexus between financial markets and economic growth.

This paper takes a forward-looking approach of using financial market information to predict future economic growth. The authors use ARDL modeling approach to predict economic growth using the information from stock market sectoral returns.

The authors find that sectoral stock returns significantly improve economic growth forecasts. However, the forecasting superiority is not uniform across sectors and horizons. Auto, consumers' spending, materials and realty sectors provide the most forecasting gains. In contrast, banking, capital goods and industrial sectors provide superior forecasts, but only at horizons beyond one year. The authors also find that the forecast superiority of sectors at longer horizons is inversely related to volatility.

Research highlights the need for sector-focused policy actions in driving economic growth. Further, the findings of the paper identify sectors that drive short-, medium- and long-term economic growth.

There is a significant heterogeneity among different sectors and across horizons in predicting economic growth. Results suggest that targeted policy actions in sectors like materials, metals, oil and gas, and realty are key in driving economic growth. Further, policies geared toward the grassroots industries are at least as beneficial as the large-scale industries. Evidence also suggests the need for an active fiscal policy to address infrastructural bottlenecks in primary industries like basic materials and energy. Evidence nevertheless does not undermine the role of monetary policy actions.

Unlike any paper till date, the innovation of the paper is that it takes an ARDL modeling approach to measure stock market sectoral returns' ability to forecast economic growth several months ahead in the future. Though the paper considers the Indian case, the innovation and contribution extents to the entire field of economic studies.

The impact of financial inclusion on economic growth is a topic that is generating widespread interest among researchers and practitioners. In this paper, the authors review the existing literature to highlight the state of research in the literature and identify new opportunities for innovative research.

The authors used a thematic literature review methodology which involves dividing the review along relevant themes.

The authors find that significant research on the topic emerged in the post-2016 years. Most of the existing studies are from developing countries and from the Asian and African regions. Existing studies have not utilized relevant theories in explaining the impact of financial inclusion on economic growth. Most studies report a positive impact of financial inclusion on economic growth while very few studies show a negative impact. The most common channel through which financial inclusion affects economic growth is through greater access to financial products and services offered by financial institutions that increases financial intermediation and translates to positive economic growth. The common empirical methodology used in the literature are causality tests, cointegration and regression methods. Multiple proxies of financial inclusion and economic growth were used in the literature which partly explains the conflicting result among existing studies. The review paper concludes by identifying some directions for future research.

This paper presents the first rigorous thematic review of the existing literature on the impact of financial inclusion on economic growth. It highlights the main approach that researchers have taken on this topic and identifies some important research areas for future investigation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2022-0339.

This paper aims to attempt to compare the development strategies and achievements of India and China in the last 50 years and to analyse the challenges lying ahead if the trend continues.

The paper critically evaluates the growth strategies of the two economies. Changes in approaches, achievements and failures are analysed using materials from past research and secondary data. Impacts of economic reform process and economic management capabilities have been evaluated. Critical analysis is the main approach of the paper.

Based on the experiences of economic growth so far with reformed and open economies, India can learn several things from China. China has achieved better results based on investment‐driven export‐oriented policies that may not be sustainable in the long run. It has so far ignored the socio‐political issues, which can have very serious consequences in the future. Relatively slower economic growth in India is based on stronger socio‐economic foundations. Mutually beneficial economic cooperation between the two economies and rising interdependence with regional and global powers should provide a better future.

The paper provides a comprehensive picture of strategies, outcomes and possibilities. It links past development strategies to future challenges. It may be of value to researchers and policy makers in both economies while considering future directions.

The purpose of this paper is to consider the economic information content within several popular stock market factors and to the extent to which their movements are both explained by economic variables and can explain future output growth.

Using US stock portfolios from 1964 to 2019, the authors undertake three related exercises: whether a set of common factors contain independent predictive ability for stock returns, what economic and market variables explain movements in the factors and whether stock market factors have predictive power for future output growth.

The results show that several of the considered factors do not contain independent information for stock returns. Further, most of these factors are neither explained by economic conditions nor they provide any predictive power for future output growth. Thus, they appear to contain very little economic content. However, the results suggest that the impact of these factors is more prominent with higher macroeconomic risk (contractionary regime).

The stock market factors are more likely to reflect existing market conditions and exhibit a weaker relation with economic conditions and do not act as a window on future behavior.

Fama and French three-factor model still have better explanations for stock returns and economic information more than any other models.

This paper contributes to the literature by examining whether a selection of factors provides unique information when modelling stock returns data. It also investigates what variables can predict movements in the stock market factors. Third, it examines whether the factors exhibit a link with subsequent economic output. This should establish whether the stock market factors contain useful information for stock returns and the macroeconomy or whether the significance of the factor is a result of chance. The results in this paper should advance our understanding of asset price movement and the links between the macroeconomy and financial markets and, thus, be of interest to academics, investors and policy-makers.

I. Introduction For over forty years, a model for Third World development has gained widespread acceptance. Three key premises underpin the traditional development model: (1) the identification of “development” with the maximization of the rate of national economic growth; (2) the quest to achieve Western living standards and levels of industrialization which require the transfer of labor from the agricultural to the industrial sector as well as increased consumerism; and (3) the integration into the interdependence of Third World nations in the global economy and the global marketplace. Increasing the demand for a Third World nation's exports (in other words, export‐led growth) is viewed as leading to the maximization of a nation's Gross National Product (GNP).

This work proposes a methodology to project future freight demand for all commodity types that begin and end in each geographical region and the amount of freight that moves between all origin and destination pairs. Following the traditional four-step demand forecasting framework, the procedure corresponds to trip generation and trip distribution analysis for interregional freight demand. Using future economic growth factors from macroeconomic and input-output models, the amounts of freight production and attraction in each analysis zone are forecasted and taken as given. Subsequently, an iterative matrix balancing method is applied to determine the estimated freight shipment demand for all origin and destination zone pairs. The proposed algorithm is applied to generate predicted future freight demand within the United States from 2010-2050 in five-year increments based on the national freight demand data from 2007. Four different scenarios are proposed that consider variations in both global economic growth and environmental regulation. This study will assist transportation planners and decision makers in public and private sectors to assess how future freight delivery demand on the national scale considering various future global economic growth and environmental policy scenarios will affect various issues such as air quality and human health problems.

Authors investigate the key factors contributing to Poland's economic growth since 1989, including capital accumulation, technological progress, labour force and productivity and European integration.

Through the analysis of macroeconomic indicators, comparison with selected countries and review of relevant literature and policies, authors aim to offer a comprehensive understanding of Poland's growth story, providing valuable insights for informed policy recommendations and fostering sustainable economic development.

This study utilises a mixed-methods approach, combining quantitative analysis of macroeconomic indicators with qualitative examination of literature, policy documents and expert opinions. This comprehensive analysis allows us to assess Poland's economic growth, compare its performance with selected countries and identify underlying factors driving growth and potential future challenges.

Understanding the drivers of Poland's growth is essential for effective policy formulation and promoting sustainable development, while acknowledging the potential threats to maintaining its high growth rate such as modest innovation performance, population ageing, growing public debt and reliance on coal-based energy. The findings provide valuable insights into Poland's economic trajectory and form the basis for informed policy recommendations.