Propensity Score Matching-difference In Difference Research Articles

How does green credit guidelines affect environmentally friendly enterprises' ESG? A quasi-natural experiment from China.

Following decades of extensive economic development, promoting the transition to greening and decarbonization in economic development have become inevitable choices for controlling environmental pollution and achieving high-quality development in China. Green Credit Guidelines (NIGCG) is a major policy innovation to promote green credit and further improve sustainable economic development. The influence of these guidelines on environmentally friendly enterprises' sustainable development capacity, proxied by environmental, social, and corporate governance (ESG), has not yet been discussed. Therefore, this study takes the NIGCG issued in 2012 as a quasi-natural experiment, and adopts a propensity score matching-difference-in-differences (PSM-DID) model to test whether the NIGCG has affected ESG in environmentally friendly enterprises from 2009 to 2022. Our results indicate that the NIGCG significantly boosts environmentally friendly enterprises' ESG, and this finding remains robust to a series of tests. In addition, a mediating effect analysis reveals that the NIGCG affects enterprises' ESG through research and development (R&D) investment, verifying the Porter hypothesis in China. Finally, we determine that the role of NIGCG in promoting ESG is significantly reflected in the non-politically connected enterprises and enterprises in the eastern region. The empirical results suggest that the authorities should stimulate enterprises' R&D investments through supporting policies, such as tax reimbursement and government subsidies, and formulate differentiated policies according to the characteristics of enterprises and their regions, so as to improve the effect of NIGCG.

The Impact of Rural–Urban Student Mobility on the Efficiency of Resource Allocation in China’s Rural Households: Optimization or Distortion?

The impact of rural-urban student mobility on the efficiency of resource allocation in China’s rural households is crucial for refining policies related to rural migrant settlement and the balanced allocation of urban and rural educational resources. Drawing on theoretical insights, this study employs a mixed methods approach—primarily qualitative, with quantitative support—to empirically test the impact of rural-urban student mobility on the resource allocation efficiency of rural households in China. Utilizing micro-survey data from China Family Panel Studies (CFPS), this study applies ordinary least squares (OLS) models, propensity score matching difference-in-differences (PSM-DID) models, and endogenous switching regression (ESR) models to ascertain the direction of this impact. Furthermore, this study incorporates in-depth interview data gathered from field research in D County to explore the dynamic mechanisms of resource allocation adjustments within these households. The results show that rural-urban student mobility significantly reduces the efficiency of labor resource allocation and agricultural production in China’s rural households. The impact is heterogeneous across different groups, most negatively affecting households with limited labor resources, lower educational levels, lower incomes, more productive fixed assets, and less self-owned land. Mobility leads to suboptimal occupational choices, resulting in decreased labor resource efficiency. Additionally, it distorts agricultural production by leading to labor loss, reduced investments in agricultural productivity, and misaligned land allocation decisions.

Cross-regional integration of renewable energy and corporate carbon emissions: Evidence from China's cross-regional surplus renewable energy spot trading pilot

Using data from A-share listed renewable energy enterprises, this study constructs a quasi-natural experiment with China's Cross-regional Surplus Renewable Energy Spot Trading Pilot policies as the shock and explores its impact on corporate carbon emissions from 2014 to 2021 using the staggered difference-in-differences (DID) model. The results indicate that the Cross-regional Surplus Renewable Energy Spot Trading Pilot can significantly reduce the carbon emissions of renewable energy enterprises in pilot regions during the sample period, demonstrating heterogeneity in regional location, ownership, and corporate social responsibility. The positive effect of the pilot is more pronounced for enterprises in the central region, state-owned enterprises, and enterprises with a high sense of social responsibility. The results remained robust when we applied propensity score matching DID, difference-in-differences-in-differences (DDD), placebo tests, alternative measures and 2SLS instrumental variable tests to further eliminate the interference from other factors. Moreover, in terms of mechanisms, the Cross-regional Surplus Renewable Energy Spot Trading Pilot can reduce corporate carbon emissions by promoting renewable energy consumption and corporate energy efficiency. This study enhances understanding of cross-regional renewable energy integration, expanding discussions on selecting trajectories for energy efficiency and emissions reduction goals in the energy sector. Our findings offer practical examples of how different regions and countries promote the integration of renewable energy markets, thereby contributing to research on renewable energy integration.

Risk mitigation strategies in urban investment bonds: Insights from local government implicit debt governance

Growing concerns surrounding urban investment bond (UIB) defaults in China necessitate a thorough examination of risk mitigation strategies. This study investigates the impact of local government implicit debt governance on UIB credit risk using a propensity score matching difference-in-differences (PSM-DID) approach. Our findings reveal that effective debt governance significantly reduces UIB credit risk, particularly for bonds issued by local government financing vehicles (LGFVs) with “high bargaining power”. However, financial technology development may obscure credit risks and dampen the positive effects of governance. Further analysis, grounded in the “financial potential energy” framework, highlights the mediating roles of asset extension and risk warranty. Comparing the 2014 "Document No. 43" with the 2018 debt governance policy, we find the latter to be more effective in mitigating UIB credit risk. This study offers valuable insights into the micro-level effects of local government debt governance and provides guidance for policymakers in managing credit risks.

Impact of ISO 14000 on Energy Intensity of Manufacturing Plants in India

Using plant-level data for 2008-2017, we examine the impact of the adoption of ISO 14000 by Indian manufacturing plants on their energy intensity. The propensity-score-matching difference-in-difference (PSM-DID) estimator is used to assess the effect. Our results show that the adoption of ISO 14000 tends to reduce energy intensity in Indian manufacturing plants, especially among the low and low-medium technology industries. ISO 14000 lowers energy intensity in industrial plants in energy-intensive industries, and the effect is stronger for the group of such industries covered under the Perform–Achieve–Trade (PAT) scheme of the Indian government, a market-based compliance mechanism for energy efficiency improvement.

Enhancing children's nutrition: the influence of rural household technology under China's home appliances going to the countryside policy.

This study explores the influence of household technological advancements on children's nutritional intake, specifically within the context of the Chinese government's "Home Appliances Going to the Countryside" (HAGC) initiative. Utilizing data from the China Health and Nutrition Surveys of 2006, 2009, and 2011, we employed a Propensity Score Matching Difference-in-Differences (PSM-DID) framework to ascertain the repercussions of enhanced household technology on the dynamics of children's nutritional consumption patterns. Our analysis reveals that the HAGC-inspired integration of household appliances, including color televisions, washing machines, and refrigerators, has beneficially reshaped the nutritional consumption patterns of children, with a pronounced effect among female children. This finding remains consistent even when employing alternate methodological robustness tests. A deeper examination of the HAGC policy's mechanisms underscores the pivotal roles of parental time allocation, improved food storage capabilities, and augmented information accessibility as significant drivers bolstering children's nutritional intake. These insights bear considerable significance for strategizing interventions aimed at elevating the nutritional wellbeing of children in rural settings, offering valuable input for shaping public health policies tailored for such demographies.

How an emission trading system affects carbon emissions? Evidence from the urban agglomeration in the Middle Reaches of the Yangtze River, China

The emission trading system (ETS) is one of the important policy instruments that help to achieve the “double carbon” goals, however, how the ETS affects the carbon emissions for an urban agglomeration remains uncertain. This study aims to explore the ETS’s impacts to carbon emission intensity (CEI) in Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR) of China during 2006–2018. By using the Difference-in-Differences (DID) model, the positive effects of ETS to CEI reduction were confirmed, and the robustness of findings were proved via the parallel trend test, placebo test, and propensity score matching DID (PSM-DID) method. This study also recognized two mediation impacting paths, which were economic intensity improvement and green technology innovation, and provided the evidence that the ETS could further reduce the CEI through improving the economic intensity as well as the green technology innovation. Furthermore, the study investigated the heterogeneous impacts from ETS by dividing the cities within the agglomeration into different orientations. The ETS performed better in the edge cities, and the same phenomenon occurred when considering the mediation effect from economic intensity. Policy recommendations about ETS were also provided.

Balancing Acts: Unveiling the Dynamics of Revitalization Policies in China’s Old Revolutionary Areas of Gannan

A series of revitalization policies (RPs) have been implemented in China’s Old Revolutionary Areas (ORAs). Evaluating the impact of these RPs is of paramount importance for refining policy design and achieving the goal of common prosperity. This study focuses on the ORAs in Gannan (ORAG) and employs the Propensity Score Matching Difference-in-Differences (PSM-DID) method to assess the effects of the RPs from two perspectives: stimulating economic growth and increasing farmers’ income, utilizing county-level data spanning from 2006 to 2019. The findings of this study reveal that while the RP restrains the growth of per capita GDP in ORAG, it significantly promotes the growth of farmers’ income. Moreover, it plays a crucial role in reducing the income gap between ORAG and Jiangxi Province, thus promoting the common prosperity of farmers in ORAG. A detailed examination using quantile regression shows that the RP has a significant and consistent negative impact on GDP per capita GDP at different quantile points. At the same time, it has a significant positive effect on increasing farmers’ income at the 25% quantile point, effectively reducing income inequality among farmers at all quantile levels. The mechanism analysis shows that the RP has stimulated increased government investment in ORAG, leading to an increase in farmers’ incomes and a reduction in income disparities. However, the study also highlights the existence of a “policy trap” that has hindered the RP’s effectiveness in ORAG. Drawing upon these findings, this paper offers policy recommendations to enhance the impact of RP in ORAs.

The Impact of Low-Carbon City Pilot Policies on Green Innovation Efficiency in Chinese Cities: An Empirical Analysis Based on the Multi-Period PSM-DID Model

On the basis of panel data taken from 226 Chinese cities in the period 2008 to 2019, this paper measures urban green innovation efficiency, with the help of the unexpected production output-stochastic block model (UPO-SBM), and applies the propensity score matching difference-in-differences (PSM-DID) model to analyze the impact of low-carbon city pilot policies (LCPP) on urban green innovation efficiency. This paper also applies a mediation effect model to analyze the mechanism of the LCPP that enhances urban green innovation efficiency, and also attempts to explore the impact of the LCPP on the green innovation efficiency of various types of cities by engaging with multiple dimensions. The results of the study shows that: (1) When all other conditions remain unchanged, the average promotion effect of the implementation of the LCPP on urban green innovation efficiency is 21.77%; (2) at 1% significance level, the mediating effect of financial technology R&D expenditure and environmental governance expenditure is 0.0664 and 0.0283, respectively, confirming that both are important to the role that LCPP plays; (3) at 5% significance level, the exogenous policy effect of the LCPP on urban green innovation efficiency is more obvious in cities with a larger population size and higher degree of development, whose pillar industry is heavy industry.

Analysing firm-level impacts of high-speed railways on reducing business costs: evidence from China

ABSTRACT Numerous studies have revealed that high-speed railways (HSRs) can efficiently reduce transportation costs for firms and therefore bring more business capacities to firms in regions with HSR services. This paper aims to adopt the difference-in-difference (DID) and PSM (propensity score matching) DID methods to examine the HSR’s causal effects on business costs. The author finds that business costs are significantly reduced due to the operation of HSR lines. Besides, private firms and firms in the secondary and tertiary sectors would experience more reductions of business costs encouraged by the HSR than state-owned and agricultural firms. The placebo test and parallel trend test have proved the feasibility of this study. Finally, this paper provides policy suggestions that the construction of HSR lines needs to be encouraged in order to promote the higher efficiency of business operations for firms and more-balanced spatial business developments in China.

The employment effects of short selling: evidence from China

This study examines the impact of short selling on firm-level employment growth. Exploiting the staggered short-sale deregulation in China, we find that short selling has a significant negative effect on employment growth. We establish causality by applying a propensity score matching difference-in-differences (PSM-DiD) method and an instrumental variable (IV) approach. Exploring the underlying mechanisms, we find that financial constraints, information transparency, and agency costs are three plausible channels by which short selling affects employment growth. Furthermore, a series of cross-sectional tests suggest that the effect of short selling on employment growth is concentrated in non-state-owned enterprises (non-SOEs), firms with higher operating risk, firms with lower governance quality, firms in regions with weaker labor protection, and in periods prior to the Covid-19 pandemic. Overall, our study offers novel evidence on the consequences of short selling on employment growth in an emerging market, complementing the literature on short sales and labor market outcomes.

The link between Chinese belt and road initiative and foreign direct investment inflows in Southern Africa

This study investigates the association between infrastructure development in China's Belt and Road Initiative (BRI) and foreign direct investment (FDI) inflows to southern Africa, using a propensity score matching–difference-in-difference (PSM-DID) regression. The empirical examination is based on a sample of eight southern African countries selected based on data availability. We find that China's BRI has significantly positive effects on FDI inflows to southern Africa. Therefore, governments and development policy makers in southern African countries are recommended to devise supporting policies in order to ensure that the BRI leads to sustainable FDI inflows and sustainable economic growth. The study makes significant contributions to theory, policy, and practice. In policy and practice, our study is valuable for policy-making on driving FDI inflows. However, the context of the study is specifically southern Africa, hence, the results might not be generalizable to other African regions or Africa as a whole, so further research is needed to consider those areas.

How Does the National Big Data Comprehensive Pilot Zone Affect the Technical Complexity of Urban Exports?

Taking "the establishment of the national big data comprehensive pilot zone" as a quasi-experiment, this study uses propensity score matching-difference in difference (PSM-DID) to investigate how the national big data comprehensive pilot zone improves the technical complexity of urban exports and its mechanism, which is based on the data of 280 prefecture cities from 2007 to 2019. The results show that the establishment of national big data comprehensive pilot zone can improve the technical complexity of urban exports. Specifically, it drives regional trade upgrading by increasing technology investment. In addition, its establishment has inhibited the technical output to some degree, and the trade openness negatively regulates the impact of the big data comprehensive pilot zone on the technical complexity of urban exports. Besides, this study not only lays a foundation for empirical research on the national big data policy to promote the high-quality development of regional trade, but also provides a new perspective for studying the transformation of digital economy.

Evaluation of the effect of a low-carbon green city policy on carbon abatement in South Korea: A city-level analysis based on PSM-DID and LSA models

Climate change response is a long-term, stage-specific global challenge that necessitates ongoing research on its routes. Although previous research has examined policy planning and indicator development for a low-carbon transition based on a variety of macropolicies, more research is needed to determine whether such policies can help reduce carbon emissions and accelerate urban transitions. Based on 2015–2021 panel data covering 17 South Korean first-level administrative districts, we employ a propensity score matching-difference in difference (PSM-DID) model and a mediating effect model to address issues of interregional development faults and policy feasibility and to investigate the impacts of the low-carbon green city (LCGC) policy in different regions on urban carbon emissions. To address the development gap and policy feasibility across regions, this study investigates the mechanism and path of the effect of the LCGC policy on urban carbon dioxide emissions in various regions, ultimately incorporating local spatial autocorrelation (LSA) to investigate the characteristics of the differences at the spatial level. The findings demonstrate that (1) the present regulations effectively limit total urban carbon emissions but are characterized by strong rebound elasticity and a short period. (2) Energy use and renewable energy production have the greatest influence on reducing total urban carbon emissions. (3) The local spatial autocorrelation clustering characteristics present the clustering characteristics of being high in the east and low in the north. The HH agglomerations have the largest coverage and are mainly distributed in the southeast and southwest directions of the study area. The results of the study provide a decision-making basis and theoretical support for relevant decision-makers to formulate differentiated carbon emission reduction policies and to eliminate the current transition dilemma with a new research methodology.

Can environmental protection tax drive manufacturing carbon unlocking? Empirical evidence from China

IntroductionChina’s environmental protection tax policy has emerged as a pivotal force in steering the country towards reduced pollution and carbon emissions. This study focuses on evaluating the impact of the environmental protection tax on carbon unlocking within the manufacturing industry, offering crucial insights to address the dual challenges of industry development and carbon emission reduction.MethodsUtilizing Chinese provincial panel data spanning from 2004 to 2020, we gauge the carbon unlocking efficiency of the manufacturing industry using the super-efficiency slacks-based measure (SBM) model with undesired outputs. Additionally, we empirically examine the impact of the environmental protection tax policy on manufacturing carbon unlocking through the propensity score matching difference-in-differences (PSM-DID) model.ResultsOur findings indicate a significant enhancement in the carbon unlocking efficiency of the manufacturing industry due to the implementation of the environmental protection tax policy. Compared with the provinces (municipalities) that did not raise the environmental protection tax rate standard, the carbon unlocking efficiency of manufacturing in the provinces (municipalities) that raised the environmental protection tax rate standard increased by 11.6%, and the dynamic effect shows that the policy effect increases gradually over time. Further mechanism tests reveal that an environmental protection tax improves manufacturing carbon unlocking efficiency mainly by stimulating manufacturing firms to increase environmental protection investment and green technology innovation. Moreover, there is heterogeneity in the policy effect of the environmental protection tax, and its impact on manufacturing carbon unlocking is more significant in the central and western regions and regions with higher levels of legalization.DiscussionTherefore, we should adhere to the policy orientation of low-carbon development in manufacturing, accelerate green technological innovation in manufacturing, and coordinate the special advantages of each region according to local conditions to bring into play the role of an environmental protection tax in reducing carbon and improving efficiency.

Does emission trading system improve the urban land green use efficiency? Empirical evidence from Chinese cities.

Maximizing socioeconomic and environmental benefits with minimal investment in urban land resources is a key concern for sustainable urban development. The emission trading system is an important strategy of the Chinese government to control environmental pollution and promote green development, but whether it improves urban land green use efficiency is still unclear. Combining the concept of green development with urban land use efficiency, this paper uses the super-efficiency slack-based measure (SBM) model with undesirable outputs to measure the land green use efficiency of 261 prefecture-level cities in China from 2003 to 2017. In addition, the propensity score matching difference-in-differences (PSM-DID) method and the mediating effect model were used to test the impact of the China's emission trading system on urban land green use efficiency and behind the mechanism. According to the findings, China's emission trading system has significantly improved urban land green use efficiency, compared with that in nonpilot cities, urban land green use efficiency in pilot cities has increased by 10.40%. Moreover, the policy effect of the emission trading system is more significant in resource-based cities and cities with a high intensity of environmental regulations. Further mechanism analysis reveals that green technology innovation and industrial structure upgrading are effective transmission mechanisms for China's emissions trading policy to improve urban land green use efficiency. The findings provide policy implications for promoting the sustainable use of urban land resources and advancing the coordinated development of urban socioeconomic and ecological environments.

The impact of China’s bilateral currency swap agreements on bilateral direct investments

ABSTRACT This paper investigates the impact of China’s bilateral currency swap agreements (BSAs) on bilateral direct investments (BDIs). We treat signing China’s BSAs as a quasi-natural experiment and employ the gravity model with a staggered difference-in-differences (DID) method to explore the relationship between signing China’s BSAs and BDIs. Our empirical results suggest that signing China’s BSAs and increasing their value can effectively boost BDIs. The findings remain robust after utilizing the propensity score matching DID (PSM-DID) method, the instrumental variable method, adding additional explanatory variables, and eliminating interference from critical events. In addition, we find that the impact of China’s BSAs on BDIs varies significantly depending on partner country features, such as level of development, whether to sign the Belt and Road Initiative (BRI), trade relations with China, and the degree of capital account openness. Moreover, the governance quality in the host country has a positive moderating effect on the impact of China’s BSAs on the country’s FDI. Our study has vital policy implications for governments worldwide that have signed China’s BSAs and those that want to promote BDIs by signing China’s BSAs.

Going Green: Evidence from Product-Level Exports and Firms’ Environmental Performance in China

The environmental impact of exporting is a topic of significant concern to both scholars and policymakers. Analyzing how exporting influences firms’ environmental performance concerning the product level is vital for better understanding its implications. Drawing on the data obtained from Chinese industrial firms, this study employs the PSM-DID (Propensity Score Matching-Difference in differences) model to establish a causal relationship between exporting intermediate goods or final goods and firms’ emissions. The findings indicate that, on the one hand, exporting intermediate goods leads to a rise in firms’ production scale and total factor productivity, ultimately significantly increasing total pollution emissions and reducing pollution emission intensity. On the other hand, exporting final goods decreases total pollution emissions and emission intensity through the technical effect. In general, this study provides important micro-level evidence of how exports affect pollution emissions at the product level in China. This evidence is valuable for policymakers in shaping environmental regulations and export policies.

Impact of new energy demonstration city policy on energy efficiency: Evidence from China

This study extended the causal inference regarding the impact of the New Energy Demonstration City (NEDC) policy on energy efficiency. The effect of the NEDC policy on energy efficiency was assessed by integrating the Super Efficiency Epsilon-Based Measure (SE-EBM) model and the Propensity Score Matching Difference-in-Differences (PSM-DID) method, using panel data from 271 cities in China between 2006 and 2020. Initially, the SE-EBM model was utilized to measure energy efficiency. Subsequently, the PSM-DID model was employed to evaluate the effect of the NEDC policy on energy efficiency. The findings revealed that the NEDC policy had significantly enhanced energy efficiency in demonstration cities by approximately 4.8% compared to non-demonstration cities. To ensure the reliability of the results, we conducted five tests and confirmed that the policy effect was significant only after a lag of two periods. It was found that green technology innovation was a key channel for the NEDC policy to improve energy efficiency. This study offers valuable insights into the impact of energy transition policy on energy efficiency and lays a theoretical foundation for designing effective urban energy transition policies.

Can the green credit policy reduce carbon emission intensity of “high-polluting and high-energy-consuming” enterprises? Insight from a quasi-natural experiment in China

Previous studies have examined the effect of green credit policy (GCP) on innovation, the environment, and corporate performance. However, few studies have focused on GCP's impact on carbon reduction of high-polluting and high-energy-consuming (“two high”) enterprises. Based on millions of unbalanced panel data from the China Taxation Survey database from 2009 to 2016, this study considers the most acclaimed GCP (“Green Credit Guideline” in 2012) as a quasi-natural experiment and adopts a difference-in-difference (DID) method along with interactive fixed effects to study the impact of GCP on the carbon emission intensity of “two high” enterprises. In general, we find that GCP significantly reduces the carbon emission intensity of “two high” enterprises. This effect is achieved by optimizing the energy structure, promoting technology transformation, and increasing the intensity of innovation input. A heterogeneous analysis shows that the GCP has a significant suppression effect on “two high” enterprises in eastern and western regions, although its impact is less evident in central areas. Moreover, it shows that non-state-owned, unsubsidized, medium-scale, and large-scale “two high” enterprises are more significantly negatively impacted by the GCP. Finally, to further address the endogeneity problem, the propensity score matching–difference-in-difference (PSM-DID) estimation is conducted and pragmatic policy implications are proposed to improve the development and effectiveness of the GCP.