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This study aims to examine the impact of housing construction on single-family housing values and the implications for urban development.

To achieve this objective, the author used the difference-in-difference methodology to examine the effect of multifamily and single-family housing construction on surrounding single-family homes in Stockholm, Sweden. The author analysed data from approximately 480 housing construction projects between 2009 and 2014 and 17,000 single-family detached house transactions between 2005 and 2018.

The research found that multifamily construction projects did not affect the value of surrounding single-family homes, while single-family home construction had a negative impact. The author attributes this result to single-family housing projects typically located in areas with initially positive externalities, while multifamily housing projects are often located on the edge of areas with negative externalities before construction.

The research is limited by its focus on a specific geographic area and time frame, and future research could expand the scope to include other cities and regions and different periods. Additionally, further research could examine the impact of housing construction on other economic factors beyond housing values.

The research has practical implications for urban planners and policymakers. They should consider the potential negative impact of new single-family home construction on existing single-family housing areas while balancing the need for new housing in urban areas. By carefully evaluating construction locations, policymakers can create more sustainable, livable and equitable urban environments that benefit all members of society.

This research paper contributes to the field of housing economics by examining the impact of housing construction on single-family housing values in the context of urban development and climate change mitigation. Using a difference-in-difference methodology, the study provides evidence of the price effect of multifamily and single-family housing construction on surrounding single-family homes, which has important policy implications for urban planners and policymakers. By identifying the negative impact of single-family home construction on surrounding areas and highlighting the need for careful evaluation of construction locations, the research provides valuable insights for creating sustainable, livable and equitable urban environments that benefit all members of society.

The spatiotemporal compression effect of China–Europe Railway Express (CR-Express) can reduce the flow costs of resources between China’s node cities. Additionally, it can break through the limitations of low-added-value marine products, significantly impacting the logistics industry efficiency. However, there are few literature verifying and analyzing its heterogeneity. This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.

First, this study uses panel data to measure the efficiency of node city logistics industry. Secondly, this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model. Finally, according to the node city difference, the sample city experimental group is grouped for heterogeneity analysis.

The results show that CR-Express can promote the urban logistics industry efficiency, with an average effect of 4.55%. According to the urban characteristics classification, the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious. The improvement effect of node cities and central cities in central and western China is stronger, especially in the sample of megacities and type I big cities. Compared with non-value chain industrial products, the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.

Under the background of double cycle development, this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

This thesis deeply studies the impact mechanism of digital service trade on the high-quality development of the manufacturing industry from the aspects of technological innovation and industrial structure.

In this thesis, 40 countries from 2010 to 2020 were selected as samples, and the panel fixed-effect model and intermediary effect model were used to empirically analyze the impact path of digital service trade on the high-quality development of global manufacturing.

Overall, digital service trade has a positive impact on the high-quality development of the global manufacturing industry. Through the analysis of the intermediary effect mechanism, it is found that digital service trade can further positively affect the high-quality development of the global manufacturing industry by promoting technological innovation and industrial structure upgrading.

Based on the empirical results, targeted countermeasures and suggestions are given in this paper.

Through the test of national heterogeneity, it is found that in developing countries, digital service trade mainly acts on the high-quality development of the manufacturing industry by promoting industrial structure upgrading.

In developed countries, digital service trade mainly promotes the high-quality development of manufacturing through technological innovation; from the perspective of industry heterogeneity, the three service industries of information and communication technology (ICT), other business services and property have the intermediary effect of technological innovation and industrial structure.

This manuscript suggests that trade in digital services should be promoted as a national trade priority.

The effects of integrated reporting quality (IRQ) have been debated in increasing empirical studies. Several IRQ measures, different theoretical approaches and multiple contexts have been adopted and investigated, leading to mixed results. By using the meta-analytic technique, this study aims to contribute to the accounting literature, reconciling the conflicting results on the effects of IRQ and providing objective conclusions to complement narrative literature reviews.

A sample of 45 empirical papers from 2013 to 2022, with 653 effect sizes, was used to assess the effects associated with IRQ. The papers were clustered into five groups (market reaction, financial performance, cost of capital, financial analysts’ properties and managerial decisions) based on the different consequences of IRQ investigated in the primary studies. A random-effects meta-regression model was used to explore all sources of heterogeneity together.

The meta-regression results confirm that IRQ positively influences firms’ market valuation and financial performance and hampers opportunistic managerial behaviour by improving corporate transparency, mitigating information asymmetry and encouraging accountability. Moreover, differences in the study characteristics affect the strength of the relationship object of interest.

Through meta-analysis, this study provides a broader overview of the effects of IRQ by enhancing the generalisability of the findings. The results also pave the way for additional evidence on the outcome variables affected by the quality of integrated disclosure.

In confronting the challenge of climate change and progressing towards dual carbon goals, China is actively implementing low-carbon city pilot policy. This paper aims to focus on the potential impact of this policy on enterprise green governance, aiming to promote the reduction and balance of carbon emissions.

Based on the panel data of China's large-scale industrial enterprises from 2007 to 2013, this paper uses the Difference-in-differences (DID) method to study the impact and path mechanism of the implementation of low-carbon city pilot policy on enterprise green governance. Heterogeneity analysis is used to compare the effects of low-carbon city pilot policy in different regions, different enterprises and different industries.

The low-carbon pilot can indeed effectively enhance corporate green governance, a conclusion that still holds after a series of robustness tests. The low-carbon city pilot policy mainly enhances enterprise green governance through two paths: an industrial structure upgrade and enterprise energy consumption, and it improves green governance by reducing enterprise energy consumption through industrial structure upgrade. The impact of low-carbon city pilot policy on enterprise green governance shows significant differences across different regions, different enterprises and different industries.

This paper examines the impact of low-carbon city pilot policy on enterprise green governance. However, due to availability of data, there are still some limitations to be further tackled. The parallel trend test in this paper shows that the pilot policy has a significant positive effect on the green governance of enterprises. However, due to serious lack of data in some years, the authors only selected the enterprise data of a shorter period as our experimental data, which leads the results to still have certain deficiencies. For the verification of the impact mechanism, the conclusions obtained in this paper are relatively limited. Although all the mechanism tests are passed, the reliability of the results still needs to be further tested through future data samples. In addition, as the pilot policy of low-carbon cities is still in progress, the policy can be tracked and analysed in the future as more data are disclosed, and further research can be carried out through dimensional expansion.

Low-carbon city pilot policy plays an important role in inducing the green governance of enterprises. Therefore, policy makers can continue to strengthen the construction of low-carbon city pilots by refining pilot experience, building typical cases, actively promoting pilot policy experience, expanding pilot scope and enhancing the implementation efficiency of pilot policy nationwide, which will contribute to the optimization and upgrading of the regional industrial structure at the urban level and will provide experience and reference for the synergistic implementation plan of pollution reduction and carbon reduction.

The impact of the low-carbon city pilot policy on enterprise green governance not only exists in two separate paths of urban industrial upgrading and enterprise energy consumption but also exists in a chain transmission path from macro to micro. The authors find that the effect value of each influence path is different, and there is an obvious leading influence path for the role of enterprise green governance. Therefore, in the process of implementing a low-carbon city pilot policy, policies should be designed specifically for different mechanisms. Moreover, complementing and coordinating several paths should be advocated to give full play to the green governance effect of enterprises brought by different paths and to further expand the scope of industries and enterprises where policies play a role.

To the best of the authors’ knowledge, for the first time, this paper connects macro mechanisms with micro mechanisms, discovering a macro-to-micro transmission mechanism in the process of low-carbon city pilot policy affecting enterprise green governance. That is, the low-carbon city pilot policy can facilitate industrial structure upgrading, resulting in reduced enterprise energy consumption, ultimately enhancing enterprise green governance.

We propose an economic model of housing markets. The model incorporates the macroeconomic relationships between prices, demand and supply. Since vacancy rates are not observable, the demand-supply mismatches are identified using a microeconomic model of search, matching and price formation. The model is applied to data on regional housing markets in England and Wales.

Economic theory combining macroeconomics and microeconomics together with new generation econometric methods for empirical analysis.

The empirical model, estimated for the ten government office regions of England and Wales, validates the economic model. We find that there is substantial heterogeneity across the regions, which is useful in informing housing and land-use policies. In addition to heterogeneity, the model enables us to better understand unrestricted inter-regional spatial relationships. The estimated spatial autocorrelations imply different drivers of spatial diffusion in different regions.

In the nature of other empirical work, the findings are subject to specificities of the data considered here. The understanding of spatial diffusion can also be further developed in future work.

This paper develops a nice way of closing macroeconomic models of housing markets when complete demand, supply and pricing data are not available. The model may also be useful when data are available but with large measurement errors. The model comes together with corresponding empirical methods.

Implications for the housing market and other regional policies are important. These are context-specific, but some implications for housing policy in the UK are provided in the paper as an example.

Unique housing market paper combining both macroeconomic and microeconomic theory as well as both theory and empirics. The rich framework so developed can be extended to much future work.

Microbusinesses are better able to assist many disadvantaged groups in finding employment and breaking the cycle of poverty because they require less initial capital and employ a large number of poor people in developing economies. Women run and own the majority of micro-businesses in urban Ethiopia. This study aims to investigate women’s microbusiness participation decisions and the effect on poverty in the Wolaita zone southern Ethiopia.

A cross-sectional study was carried out using a mixed-methods research approach. A total of 384 women who owned micro-businesses were chosen using a systematic random sampling technique, while 36 women were purposefully chosen for qualitative data analysis. Data were gathered through survey questionnaires, in-depth interviews and focus group discussions. The collected data were analyzed by using a propensity score matching technique as well as contextual analysis.

The study discovered that women’s participation in registered micro-businesses had a higher and more beneficial impact on their food, non-food and overall consumer spending than women’s participation in unregistered microbusinesses, which helped to reduce poverty. Besides, overall women’s participation in micro-business increased their decision-making power and enabled them to provide resources for their families food and non-food consumption, with registered micro-business participants reaping the greatest benefits.

This research focused on the effects of women’s micro-entrepreneurship on poverty in low-income communities. Rather than providing food, clothing and/or other aid to women in disadvantaged communities, the authors asserted that assisting women and their micro-businesses allows them to be self-sufficient in terms of food and clothing as a long-term solution to poverty reduction. As a result, policymakers can use our findings to gain a better understanding of how women’s micro-entrepreneurship affects poverty reduction, allowing them to develop more effective anti-poverty initiatives. This study’s findings are novel and add to the body of knowledge in Ethiopia and the sub-Saharan African region.

Exploring the intrinsic connection between the ecological environment and the digital economy and empirically testing how the level of digital economic development affects the ecological environment. Using the entropy weighting method to analyze the weights of the indicators in the digital economic development level and ecological environment system to explore the factors that have the greatest impact on the ecological environment in the indicator system of the digital economic development level so as to deepen the theoretical understanding of the relationship between the level of development of the digital economy and the ecological environment. Explore the regional heterogeneity of the level of development of the digital economy to promote the healthy development of China’s ecological environment proving the difference in the level of development of the digital economy in the east west and central regions of China and the difference in the effect on the ecological environment.

Based on the panel data of 30 provinces in China from 2013 to 2021 this paper fits the index system of digital economy development level with three factors. A digital infrastructure digital industry and digital application combines environmental pollution and energy consumption to construct ecological environment indicators and explored the impact of digital economy development level on the ecological environment by using the entropy weight method and the random effect model.

The findings indicate that the degree of digital economic development has a positive and significant impact on promoting the healthy development of the ecological environment, in which the digital industry has the greatest impact on the ecological environment. Meanwhile, the improvement of industrial structure also has a positive effect on the improvement of the ecological environment, whereas the level of human capital inhibits the healthy development of the ecological environment, and the governmental support fails to effectively and significantly promote the improvement of the ecological environment. Furthermore, the empirical research indicates that the level of digital economy development has obvious regional heterogeneity on the healthy development of the ecological environment: the eastern and central regions have a significant effect, while the western region has a less significant effect.

Although domestic and foreign scholars and experts have conducted sufficient studies on the ecological environment and the development level of digital economy respectively, there are few studies on the empirical analysis of the positive significance and regional heterogeneity of the impact of the development level of digital economy on the ecological environment, which can be supplemented and referred to in this study. At the same time, it also provides intellectual support for our country to achieve high-quality development of digital economy and efficient governance of ecological environment.

This paper aims to examine the effects of socio-emotional wealth importance (SEWi) in family firms and family firm-specific HR practices, namely professionalization and bifurcation bias, on their entrepreneurial orientation (EO).

The paper surveyed 133 small and medium-sized family firms in the USA. The respondents were recruited through Prolific Academic.

When SEWi is low, a family firm becomes more similar to a non-family firm, thereby enjoying the benefits associated with EO. When SEWi is high, a family firm leverages the unique resources and capabilities specific to family firms. Moderate SEWi levels are associated with lower EO levels. Additionally, the results support the argument that professionalization (involving non-family managers, formalization and decentralization) fosters EO, while bifurcation bias hinders its development.

Unlike previous studies, this paper posits a non-linear, U-shaped relationship between SEWi and EO. It contributes to the field by empirically investigating the effects of professionalization and bifurcation bias on EO in family firms.

This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys.

This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models.

The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations.

The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized.