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Under the background of the overall increase of China's economic policy uncertainty and the urgent need for the transformation and upgrading of the substantial economy, this paper studies the time-varying causality between China's economic policy uncertainty and the growth of the substantial economy through bootstrap rolling window causality test, further refines economic policies and studies the causal differences between different types of economic policies and substantial economic growth, refining the conclusions of previous studies.

This paper first studies the causal relationship between China's economic policy uncertainty and substantial economic growth in the full sample period through bootstrap Granger causality test. Then, the paper tests the short-term and long-term stability of the parameters of the VAR model, and it is found that the model parameters are unstable in both the short and long term, so the results of the Granger causality test of the full sample are not credible. Finally, we conduct a dynamic test of the causal relationship between China's economic policy uncertainty and substantial economic growth by means of rolling window, so as to comprehensively analyze the dynamic characteristics and sudden changes of the relationship between them.

The research shows that economic policy uncertainty in China has a significant inhibiting effect on the growth of substantial economy. Growth in the substantial economy will drive up economic policy uncertainty before 2016 and restrain it after that. In addition, this paper further subdivides economic policy uncertainty to explore the causal differences between different types of economic policy uncertainty and substantial economic growth. The test results show that the relationship between them has obvious policy heterogeneity. The fiscal policy uncertainty and the monetary policy uncertainty, as the main policy means in China, has a significant impact on the growth rate of substantial economy in multiple ranges, but the effect time is short. Although trade policy uncertainty has a significant impact on the growth rate of substantial economy only during the financial crisis, the effect lasts for a long time. The impact of exchange rate and capital account policy uncertainty on the growth rate of substantial economy is mainly reflected after 2020.

The values of this paper are as follows: First, the economic policy uncertainty is combined with the growth of substantial economy, which makes up the gap of previous studies. Second, the economic policy uncertainty is further subdivided. The paper explores the causal differences between different types of economic policy uncertainties and the growth of substantial economy, so as to make the research more detailed. Finally, different from the previous static analysis, this paper uses dynamic model to examine the relationship between China's economic policy uncertainty and the growth of substantial economy from a dynamic perspective, with richer research conclusions.

This study is aimed at testing the validity of the BARS theory and determining the threshold level at which excessive government expenditure hampers growth. The data from 10 African emerging economies from 1988 to 2019 were used.

The methodology comprises several different stages. In the first stage, an Lagrange Multiplier (LM) type test was employed to find the appropriate transition variable among all the candidate variables to assess the linearity between government expenditure and economic growth and to find the sequence for selecting the order m of the transition function. The linearity test helped to identify the nature of the relationships between government expenditure and economic growth. In the second stage, the model evaluation was tested using the wild cluster bootstrap-Lagrange Multiplier (WCL-LM) test to assess appropriateness of the model. Thirdly, the Panel smooth transition regression (PSTR) model with one regime was estimated to test the validity of the BARS curve.

The results revealed evidence of nonlinear effects between government expenditure and economic growth, where the size of the government spending was found to be a 27.84% share of GDP, above which government expenditure caused growth to decline in African emerging economies. The findings combined into an inverted U-shape relationship, in line with the BARS theory.

This study proposes that policy-makers ought to formulate prudent fiscal policies that encourage expenditure, which would improve growth for selected countries as their current level of spending is below the threshold. This might be done through: (1) a suitable investment portfolio and (2) spending more on infrastructure.

The purpose of the paper is to examine the impact of infrastructure investment and development on economic growth in Brazil, Russia, India, China and South Africa (BRICS) countries. The effect is examined for each country separately and also collectively by combining each country.

Ordinary least square regression method is applied to examine the effects of infrastructure investment and development on economic growth for each country. Panel data techniques such as panel least square method, panel least square fixed-effect model and panel least square random effect model are used to examine the collective impact by combining all countries in BRICS. The dynamic panel model is also incorporated for analysis in the study.

The results of the study are mixed. The association between infrastructure investment and development and economic growth for countries within BRICS is not robust. There is an insignificant relationship between infrastructure investment and development and economic growth in Brazil and South Africa. Energy and transportation infrastructure investment and development lead to economic growth in Russia. Telecommunication infrastructure investment and development and economic growth have a negative relationship in India, whereas there is a negative association between transport infrastructure investment and development and economic growth in China. Panel data results conclude that energy infrastructure investment and development lead to economic growth, whereas telecommunication infrastructure investment and development are significant and negatively linked with economic growth.

The study is novel as time series analysis and panel data analysis are used, taking the time span for 38 years (1980–2017) to investigate the influence of infrastructure investment and development on economic growth in BRICS Countries. Time-series regression analysis is used to test the impact for individual countries separately, whereas panel data regression analysis is used to examine the impact collectively for all countries in BRICS.

Entrepreneurial firms contribute to economic growth, but the potential gendered nature of this contribution must be investigated as outcomes of male-owned and female-owned firms differ. The study investigates the female underperformance hypothesis in a cross-country analysis of Schumpeterian entrepreneurs. Next, it investigates if there is a gendered dimension of Schumpeterian firm contribution to economic growth.

The study utilizes both nonparametric and parametric methodologies. Through nonparametric methods, the success of female-owned and male-owned firms is compared. Next, a parametric ordinary least squares regression model tests if there is a gendered nature of an entrepreneurial firm's economic contribution.

In nonparametric analyses, female-owned entrepreneurial firms in developed countries perform similarly to male-owned firms, while in developing countries male-owned firms significantly outperform female-owned firms. The author also finds strong evidence that the gender of the Schumpeterian entrepreneur does not matter in the contribution in economic growth.

In all countries, the number of female-owned entrepreneurial firms was significantly lower than that of male-owned firms. The findings point to consistent cultural barriers for women in innovation-related fields and persistent gendered norms in entrepreneurship. Thus, removal of cultural barriers and continued support for Schumpeterian entrepreneurship will benefit women and contribute to a country's economic growth.

The data for this study is a unique utilization of the Enterprise World Survey to identify Schumpeterian entrepreneurial firms. Additionally, the study challenges the female underperformance hypothesis and contributes to the literature on the role of entrepreneurship in economic growth.

By taking conventionalist view of the evolution of biotechnology, we suggest that the process by which entrepreneurs determined what made biotechnology valuable and figured out how to organize around such an economic logic was contested. The shape that biotechnology has ultimately taken emerged from the resolution of these contests. Convention theory – as elaborated in Boltanski and Thévenot's (2006) On Justification ¹ – argues that our economy is shaped by participants affecting the rules of economic action. Whereas most economists would argue that the assignment of value underpins any system of exchange, conventionalists suggest that this value is not only given by the principles of optimization but instead can be derived from many possible spheres such as civic duty, attainment of fame, proof of technologic performance, and demonstration of creativity. More specifically, Boltanski and Thévenot (2006, p. 43) claim that the establishment of a particular logic “comes about as a part of a coordinated process that relies on two supports: a common identification of market goods, whose exchange defines the course of action, and a common evaluation of these objects in terms of prices that make it possible to adjust various actions.” Simply put, economic logics embody principles of economic coordination or conventions that guide interpretation of the technology and its value.

This paper aims to examine and compare the dividend ratios’ statistical and economic ability to predict the equity premium in the UK and US markets and two US sub-indices (S&P 500 Growth and S&P 500 Value).

In this paper, the authors use the linear regression models to examine the dividend ratios’ statistical ability to predict the equity premium. The in-sample and out-of-sample approaches, including Diebold and Mariano (1995) statistics, and Goyal and Welch’s (2003) graphical approach, are used. Also, the mean-variance analysis is used to test the economic significance.

The paper findings indicate that the dividend ratios have in-sample and out-of-sample predictive abilities in both UK and US markets and both US sub-indices. However, the results show that the dividend ratios have a less impressive predictive ability in the US market compared to the UK market and less in the US value index than the US growth index. This could indicate that there is no relation between the number of companies that distribute dividends in each index and the informativeness of dividends ratios. Furthermore, the tests show the dividend ratios’ predictive ability departure during particular periods and in some indices.

Results and implications of this research are exclusively applied to the US and UK markets. These results can also be applied with caution to other markets, taking into consideration the distinctive characteristics of these markets.

Results revealed in this paper imply that the investors in any of the indices may experience economic gain by adopting a dynamic trading strategy using the information content of the dividend ratios prediction models instead of the benchmark model, which is the prevailing simple moving average model.

This paper adds value through testing the prediction models’ economic significance in two well-developed markets, in addition to exploring the relationship between the number of companies distributing cash dividends and the dividends ratio prediction ability. Unlike most of the previous studies in which dividend ratios’ prediction ability is attributed to the number of companies that distribute dividends in the market, this paper denied this interpretation by studying two S&P 500 sub-indices. To the best of the authors’ knowledge, this is the first study to test the prediction models’ ability for these sub-indices.

The authors investigate the growth–inequality relationship, using panel data from 13 Southern African Development Community (SADC) countries over the period 1990–2015, to test the validity of the Kuznets and Tribble theories. Furthermore, the authors seek to determine the threshold level at which excessive growth hampers inequality.

The panel smooth transition regression (PSTR) model has several stages. The authors applied the Lagrange multiplier (LM) test to find the appropriate transition variable amongst all candidate variables, to assess the linearity between economic growth and income inequality and to find the sequence for selecting the order m of the transition function. The authors then estimated the PSTR model, but before facilitating the results, the authors first used the wild cluster bootstrap (WCB)–LM-type test to assess the appropriateness of the selected transition.

The authors found that at lower growth, income inequality tends to be lower, while if growth increases above US$8,969, inequality tends to increase in the SADC region. The findings combine into a U-shaped relationship, contradicting the Kuznets and Tribble theories.

The contribution of this paper is that it becomes the first to provide the threshold level at which excessive growth increases inequality in the selected countries. This study proposes that policymakers should focus on activities aimed at stimulating growth, in other words, activities such as spending more on infrastructure, drawing up a suitable investment portfolio and spending on technological investment for countries that are below US$8,969. An improvement in these activities will create job opportunities, which in turn will add to economic growth and thus lead to lower income inequality and better social cohesion.

The purpose of this study is to empirically weigh the evidence for financial depth, liquidity and efficiency role to economic growth, and test for the existence of cointegration between financial development variables and economic growth in Tanzania.

The study used the autoregressive distributed lag model with bound testing procedures. The sample covered yearly time-series data from 1980 to 2017, i.e. 38 years.

The results suggest that financial system depth is positively related to economic growth in the short run and that financial system liquidity and efficiency is strongly negatively associated with economic growth both in the short and long run. Further, it is found that financial development is cointegrated with economic growth. Thus, financial reforms and liberalisation have not fully brought the desired positive effects on economic growth yet.

The study uses principal component analysis to capture specific dimensions within the financial system as an intuitive way to aggregate financial development effects. Unlike studies that included several countries with heterogeneous characteristics, which are sometimes difficulty to homogenise, in recognition of countries’ unique experiences, this study uses data from Tanzania as a specific case. It documents pertinent pieces of evidence for a developing economy necessary for financial policy adjustments post the financial and economic liberalisation and reforms period. It nevertheless sheds light on financial policies for other comparable developing economies during and after both financial and economic liberalisation settings.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

The purpose of this paper is to explore the matching relationship between factor endowment and industrial structure, and its impact on economic growth.

The assortative matching method is developed to quantitatively measure the matching between factor endowment and industrial structure. A series of empirical tests are then carried out to evaluate the impact on the economic development of the matching.

1) The matching between factor endowment and industrial structure has a significantly positive impact on economic growth. (2) Economic growth reaches its maximum when the gap between the two sectors narrows to zero. (3) This effect is particularly significant for countries with higher GDP per capita and GNI per capita. (4) The results remain robust after employing a series of tests.

Aggressive industrial policies are not desirable. The optimal industrial structure is the one that complied with the comparative advantage of the given factor endowment in the economy.

So far, there has been a significant lack of an applicable quantitative indicator for measuring the matching between factor endowment and industrial structure, which is essential for conducting empirical tests and providing evidence for related economic theories.