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The purpose of this paper is to move beyond individual level characteristics of founders to explain the performance gap between white and black majority owned new ventures. It specifically investigates three potential mediators: demographic characteristics of venture’s location, financial size of the venture and its credit riskiness.

The Kauffman Firm Survey, a longitudinal data set of 4,928 new ventures started in the USA in 2004, has been utilized in this paper. Pooled OLS and Logit regression models were employed for direct effects. Mediation effects were tested using two different approaches: the Baron and Kenny approach and decomposition analysis.

The paper finds that the financial size and credit riskiness mediate the relationship between majority race ownership and the performance of a venture.

The data were collected for a single cohort (2004) of nascent firms; furthermore, the sample draws from firms based in the USA. Future studies could replicate this research utilizing samples of different cohorts and from other parts of the world.

The paper provides important guidance to policy makers. In general, to reduce the performance gap between black and white owned ventures, providing access to subsidized assets, capital and credit could be very helpful.

Past research suggests that the majority race ownership of a new venture impacts its performance and attributes these differences to heterogeneous endowments, usually of the primary owner. In this paper, analyses are conducted at multiple levels and new mechanisms through which the internal resources and capabilities of a new venture mediate the relation are discovered.

The purpose of this paper is to reveal the paradox between diversification and specialization from a dynamic perspective. More precisely, this paper will analyze the impact of diversification and specialization as well as their interaction on regional innovation in different development stages.

Based on the principles of new economic geography and innovation geography, data from 30 provinces from 2001 to 2017 was used to explore the relationship. Least squares regressions with fix effect were used to examine the hypotheses.

The results show that both diversification and specialization have a significant and positive impact on regional innovation. The interaction of diversification and specialization also significantly and positively impacts regional innovation. The effect of industrial agglomeration is heterogeneity under different development stages.

This paper verifies the positive role of diversification and specialization and their interaction in promoting regional innovation. The impact of industrial agglomeration on innovation is dynamic and changes with the regional development process. Emerging economies should make appropriate industrial agglomeration strategies according to their development stages.

This paper introduces diversification, specialization and their interaction into the research framework at the same time to analyze their impact on innovation performance which deepened the research of industrial agglomeration. Taking China as an example, this paper also examines the impact of industrial agglomeration on regional innovation in different development stages that expands the dynamic perspective of industrial agglomeration.

As an essential part of mainstream Western development economics, the trickle-down theory originates from the behavioral choices and iterations of thought on conflicts of interest in the evolution of remuneration structure in Western countries. The fundamental flaw of the logic of this theory is that it conceals the inherent implication of social systems and the essential characteristics of social structures.

This paper examines the relationships among economic growth, income distribution and poverty from the perspective of social relations of production – the nature of production relations determines the nature of distribution relations and further determines the essence of trickle-down development, and ownership is the core mechanism for realizing the trickle-down effect.

The stagnation or smoothness of the trickle-down effect in different economies is essentially subject to the logic of “development for whom”, which is determined by ownership relationship.

To be more specific, “development for capitalists” and “development for the people” indicate two distinctly different economic growth paths. The former starts with private ownership and follows a bottom-up negative trickle-down path that inevitably leads to polarization, while the latter starts with public ownership and follows a top-down positive trickle-down path that will lead to common prosperity in the end.

Whether by direct or indirect action (or by inaction), multinational enterprises (MNEs) can have both a positive and a negative effect on within-country social and economic inequality. This paper aims to comment on this multifaceted relationship between MNEs and within-country inequality.

Given the absence of either robust theory or evidence in the neglected realm of MNEs and within-countries inequalities, this paper offers some general observations, highlights some of the key issues and illustrates possible avenues for future research studies.

The capacity of MNEs to upgrade economic activity in the host country is a key policy objective. MNEs have arguably contributed to reducing income inequalities between countries. However, the limited evidence available suggests that the gains of FDI are rarely evenly distributed within recipient countries, and many of the underlying dynamics need further investigation.

The authors broaden the engagement with inequality beyond income levels, as this is just one aspect of inequality that shapes or impedes human development. They believe it is necessary – for both MNEs and policymakers – to have a more nuanced understanding of how, and under what circumstances, the presence of MNEs affects inequality in host economies.

This paper relates the large literature on inequality (going beyond the mainstream focus on income inequality) to the mainstream understanding of MNE-assisted development.

This study aims to analyse the consumption inequality between farm and non-farm households in rural Vietnam, using the data from the 2016 Vietnam household living standards survey.

The present paper applies the “recentered influence functions (RIF)” in “Oaxaca-Blinder (OB)” type decomposition as proposed by Firpo et al. (2018) to allow for the flexible distribution of the outcome variables and the non-randomness of non-farm employment that violates the classical linearity assumption.

Non-farm households have significantly higher per capita consumption expenditure than farm households for the entire distribution. The gap in expenditure is large at low percentiles and narrowing with higher percentiles. At 10th percentile, the gap is estimated at 27.1%, but it is decreasing to 11.1% at 90th percentile. Most of the gaps are explained by the differences in the observed characteristics between farm and non-farm households such as ethnicity, education, income, internal transmittances and household composition. Non-farm households are endowed with more productive factors that result in higher per capita consumption expenditure.

Gaps in ethnicity and education are found to be key predictors of the inequality in consumption expenditures between farm and non-farm households, then, government policies that are aimed at increasing access to non-farm employment and education for ethnic minorities and for rural poor households are pathways to improve rural household welfare and hence reduce inequality.

This paper aims to explore the drivers behind the accuracy of self-reported home valuations in the Warsaw (Poland) housing market.

In order to achieve the research goal, firstly, unique data on subjective residential property values estimated by their owners were compared with market-justified ones. The latter was calculated using geographically weighted regression, which allowed for taking into account spatially heterogeneous buyers' housing preferences. An ordered logit model was then used to identify the factors influencing the probability of the occurrence of bias towards over or undervaluation.

The results of the study revealed that, on average, homeowners overvalued their properties by only 1.94%, and the fraction of interviewees estimating their properties accurately ranges from 20% to 68%, depending on the size of the margin of error adopted. The drivers of the valuation bias variation were the physical, locational and neighbourhood attributes of the property as well as the personal characteristics of the respondents, for which their age and employment situation played a key role.

In contrast to previous studies, this is the first to examine drivers behind the accuracy of self-reported home valuations in a Central and Eastern Europe country. In addition, this work is the first to consider heterogeneous housing preferences when calculating objective property values.

Comprehensive studies examining how Korean e-commerce trade works are currently limited. This study seeks to explore whether Korea’s e-commerce trade is more applicable to traditional trade theory or to modern theories. According to our analysis, the share of intra-industry trade (IIT) in modern trade theory is less than that of general trade for Korean e-commerce. Therefore, trade based on comparative advantage can be more valid in explaining e-commerce trade. From results in analyzing the gravity model, it was found that Korea’s e-commerce exports are higher as IIT with its FTA partners. In contrast, it is found that the lower the proportion of e-commerce trade, the higher chance for the import growth. Lastly, this study looked at what kind of comparative advantage is realized through imports. While Korea has been mostly exporting goods of high quality, its major trading partners import products based on price and selection of goods. In order for Korea’s e-commerce to grow, a more strategic approach is necessary. A strategy of high price based on superior quality is not effective, and as e-commerce has radically reduced sales and marketing costs, so a price reduction needs to be reflected in the price of goods for consumers.

The purpose of this paper is to analyse the relation between occupational segregation and the gender wage differences using data on three-digit occupational level of classification. The authors examine whether a statistically significant relation between the share of men in employment and the size of the unexplained part of the gender wage gap exists.

Traditional Oaxaca (1973) – Blinder (1973) decomposition is performed to examine the differences in the gender wage gaps among minor occupational groups. Two types of reweighted decomposition – based on the parametric estimate of the propensity score and non-parametric proposition presented by Barsky et al. (2002) – are used as the robustness check. The analysis is based on individual data available from Poland.

The results indicate no strong relation between occupational segregation and the size of unexplained differences in wages. The unexplained wage differences are the smallest in strongly female-dominated and mixed occupations; the highest are observed in male-dominated occupations. However, they are probably to a large extent the result of other, difficult to include in the econometric model, factors rather than the effects of wage discrimination: differences in the psychophysical conditions of men and women, cultural background, tradition or habits. The failure to take them into account may result in over-interpreting the unexplained parts as gender discrimination.

The highest accuracy of the estimated gender wage gap is obtained for the occupational groups with a similar proportion of men and women in employment. In other male- or female-dominated groups, the size of the estimated gender wage gaps depends on the estimation method used.

The results suggest that decreasing the degree of segregation of men and women in different occupations could reduce the wage differences between them, as the wage discrimination in gender balanced occupations is the smallest.

To the best of the authors’ knowledge, this study is one of the few conducted at such a disaggregated level of occupations, and one of few studies focused on Central and Eastern European countries and the first one for Poland.

To cope with the severe situation of the global climate, China proposed the “30 60” dual-carbon strategic goal. Based on this background, the purpose of this paper is to investigate scientifically and reasonably the interprovincial pattern of China’s power carbon emission intensity and further explore the causes of differences on this basis.

Considering the principle of “shared but differentiated responsibilities,” this study measures the carbon emissions within the power industry from 1997 to 2019 scientifically, via the panel data of 30 provinces in China. The power carbon emission intensity is chosen as the indicator. Using the Dagum Gini coefficient to explore regional differences and their causes.

The results of this paper show that, first, China’s carbon emission intensity from the power industry overall is significantly different. From the perspective of geospatial distribution, the three regions have unbalanced characteristics. Second, according to the decomposition results of the Gini coefficient, the overall difference in power carbon emission intensity is generally expanding. The geospatial and economic development levels are examined separately. The gaps between the eastern and economically developed regions are the smallest, and the regional differences are the source of the overall disparity.

Further exploring the causes of differences on this basis is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies. This study provides direction for analyzing the green and low carbon development of China’s power industry.

As an economic indicator of green and low-carbon development, CO₂ intensity of power industry can directly reflect the dependence of economic growth on the high emission of electricity and energy. and further exploring the causes of differences on this basis is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies.

For a long time, with the rapid economic development, resulting in the unresolved contradiction between low energy efficiency and high carbon emissions. To this end, scientifically and reasonably investigating the interprovincial pattern of China’s power carbon emission intensity, and further exploring the causes of differences on this basis, is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies.

Third, considering the influence of spatial factors on the convergence of power carbon emission intensity, a variety of different spatial weight matrices are selected. Based on the β-convergence theory from both absolute and conditional perspectives, we dig deeper into the spatial convergence of electricity carbon emission intensity across the country and the three regions.

Striving to achieve the goal of carbon neutrality before 2060 indicates that China, as the most extensive power system in the world and a country based on coal power, is imperative to improve the technical level of electric power utilization. This paper aims to explore the nonlinear evolution mechanism of power technology progress under the constraints of net-zero carbon dioxide emissions in China.

This paper, first, based on China’s provincial panel data from 2000 to 2019, uses global direction distance function to measure power technological progress. Second, the threshold regression model is used to explore the nonlinear relationship between carbon emission reduction constraints on electric power technological progress.

There is a significant inverted U-shaped relationship between China’s provincial carbon emission reduction constraints and electric power technological progress. Meanwhile, the scale of regional economic development has a significant moderating effect on the relationship between carbon emission reduction constraints and power technological progress.

This paper puts forward targeted suggestions for perfecting regional carbon emission reduction policy and improving electric power technological progress.

Based on the global directional distance function, this paper extracts power as a production factor in total factor productivity and calculates the total factor electric power technological progress. This paper objectively reveals the influence mechanism of carbon emission reduction constraints on electric power technology progress based on the threshold regression model.