Difference In Difference Method Research Articles

How antitrust enforcement affects corporate ESG performance? Evidence from merger review cases in China

Chinese unique treatment of unreported merger cases (which should be reported according to antitrust law) in the context of merger review provides a distinctive and robust control group for the Difference-in-Differences (DID) research method. We employ the DID method to investigate the impact of China’s merger review antitrust enforcement on Environment, Social and Governance (ESG) performance. We find that the implementation of merger review antitrust enforcement suppresses corporate ESG performance, especially with significant effects observed on the Environment (E) and Governance (G) components. Mechanism analysis indicates that antitrust enforcement poses an impact on corporate profits by reducing market concentration and safeguarding fair market competition. This leads to the emergence of corporate financial performance protection behaviors, resulting in a decrease in corporate ESG performance. Heterogeneous analysis finds that the use of structural remedy in the enforcement process and stronger antitrust enforcement will further intensify the inhibitory effect of antitrust enforcement against business concentration on ESG.

The Impact of Double Reduction Policy on College Entrance Examination Performance: Empirical Evidence

In China, the College Entrance Examination weights great in both students' and parents' hearts, which is even recognized as the rare chance to change a people's fate. At this circumstances, heavy homework, countless tests, little break time, burning night oils and even extracurricular tutoring on the weekends have become the daily routine for Chinese high school students, which have hurt their health conditions and added great burden on their mental health. To curb this long-standing issue caused by this phenomenon, a new educational policy called Double Reduction was released by the Chinese government on 2021 and nine Chinese cities are selected as the national policy pilot areas to test the effect in advance. This paper aims to verify the impact of the Double Reduction Policy in some provinces in which lie the selected policy pilot areas. Through continuous difference-indifference method, this study found no significant correlation between the Double Reduction and the College Entrance Examination performance in these areas. Policy makers should make proper actions to implement this new policy, in order to lighten the physical and mental burden of students and the financial burden of parents while take students learning effectiveness into consideration meanwhile.

The Belt and Road Initiative: Industry Competition and Corporate Environmental Information Disclosure in China

The Belt and Road Initiative (BRI) is a significant Chinese strategic measure designed to construct a platform for multinational cooperation. The study investigates whether the BRI construction influences corporate environmental information disclosure (EID) and whether the industry competition moderates their relationship. Adopting the legitimacy theory, we assume that firms focus more on EID to differentiate themselves after the BRI construction, especially amongst fierce competition where firms apply the EID strategy more for higher legitimacy. Taking the BRI construction in 2014 as an exogenous shock, we use a difference-in-differences method (DID) and propensity score matching difference-in-differences method (PSM-DID) based on the panel data of 4099 A-share listed firms from 2008 to 2022 and take the parallel trend and placebo tests for the robustness. We reveal a significant improvement in the EID of firms within the BRI stock sector following its establishment, with the effect of the BRI construction being further strengthened by industry competition. Leveraging legitimacy theory, the paper sheds light on the motivations behind EID and how industry competition serves as a moderating factor of the EID-promoting effects brought by the BRI construction.

Does green transportation affect carbon emission efficiency? Evidence from a quasi-experimental study in China

The establishment of a low-carbon transportation system (LCTS) holds prominent importance in advancing modern transportation development and achieving green growth. Employing the LCTS pilot policy as a shock to green transportation construction in China, we investigate its influence on carbon emission efficiency (CEE) using urban panel data from 2006 to 2021. Results based on difference-in-differences (DID) show that LCTS contributes to increasing CEE following such a pilot policy. This finding still holds after we perform a propensity score matching DID method, double machine learning, instrumental variable method, heterogeneous treatment effect, and other robustness checks. Meanwhile, the mediation analysis shows that the increased CEE can be accounted for by spurring green innovation activities. Moreover, the moderation outcomes reveal that FinTech exerts a positive moderating influence on the increased impacts of LCTS on CEE. Heterogeneity analysis shows that LCTS's impact on CEE varies by region and development level. Overall, our research stresses the importance of green transportation construction in shaping CEE, which has significant practical and theoretical implications for scholars and policymakers.

Effects of community water fluoridation on child dental caries in remote Northern Territory, Australia: a difference-in-difference analysis.

Community water fluoridation (CWF) is a cost-effective intervention to reduce dental caries at population level. This Australian study used a difference-in-difference (DiD) analysis to measure dental caries in children exposed to CWF in the Northern Territory (NT), Australia. Oral health data obtained from the NT Department of Health contained 64 399 person-year observations from 2008 to 2020, totalling 24 546 children aged 1-17 years. Drinking water quality data for fluoride levels, held by the Power and Water Corporation, were obtained for 50 remote communities and linked to the oral health dataset. The DiD analysis used a treatment group and two control groups to compare the effects of CWF on dental caries outcomes in children, measured using the decayed, missing and filled teeth (dmft/DMFT) index. The treatment group consisted of records from children residing in five remote NT communities that implemented CWF in 2014.The control 1 group included records of children residing in communities with naturally occurring fluoride in drinking water supplies at levels at or above the Department of Health policy threshold of 0.5 mg/L. The control 2 group included records of children residing in communities with naturally occurring fluoride in drinking water supplies below the level recommended by the Department of Health policy (<0.5 mg/L). The data were grouped into time periods prior to the inception of CWF in five remote communities in 2014 (pre-intervention) and after 2014 (post-intervention). Our results demonstrated that dental caries was significantly decreased for children in the treatment group following the implementation of CWF at a greater magnitude than both control groups for the same time period. Overall, children assigned to the treatment group exhibited a decline in the number of teeth affected by caries by an average of 0.28 (p=0.001). Notably, children of ages 7-10 years and 11-17 years experienced significantly greater post-intervention declines in average dmft/DMFT, by 0.32 (p=0.051) and 0.40 (p=0.012) fewer affected teeth respectively. While dental caries disproportionately impacts Aboriginal children in remote and very remote NT, it is clear that CWF produces population-level reductions in overall dental caries for these populations. Additionally, our study demonstrates the application of the DiD method in a public health policy evaluation. Our findings suggest that the longstanding policy position of the NT Department of Health on CWF has supported improvements in oral health among child populations that experience high levels of dental caries in remote NT communities.

Stopgap or sustainable strategy? The impact of China’s green credit guidelines policy on corporate ESG performance

Purpose This paper aims to investigate the impact of China’s Green Credit Guidelines (GCG) policy on the environmental, social and governance (ESG) scores of restricted enterprises and examine firm’s speculative behavior in response to the policy. Design/methodology/approach This paper views the GCG policy proposed in 2012 as a quasinatural experiment and uses difference-in-differences (DID) model to evaluate its influence on the ESG scores of Chinese nonfinancial A-share listed enterprises from 2007 to 2019. Robustness tests include the propensity score matching (PSM)–DID method and permutation tests. Findings The GCG policy significantly increases the ESG scores of restricted enterprises, particularly enhancing environmental (E) performance. However, it only improves the social (S) and governance (G) performance of firms heavily reliant on bank credit, indicating speculative behavior by enterprises. Increased Government attention, a higher proportion of female executives and more developed local green finance reduce speculative behavior, while executives with financial backgrounds promote it. Practical implications Governments should mandate standardized ESG reporting and monitor restricted enterprises, banks should monitor speculative behavior and firms should integrate ESG into their long-term strategies to support sustainable development. Social implications The results provide evidence of the effectiveness of implementing the GCG policy in China and offer guidance for better promoting green credit policy in developing countries, contributing to the transition toward a more sustainable future. Originality/value To the best of the authors’ knowledge, this paper is the first to explore if the GCG policy’s asymmetric effects on ESG components are due to enterprise speculative behavior and examines the factors influencing this behavior, providing insights for regulators to better implement the GCG policy to promote sustainable development.

Machine learning-based causal inference for evaluating intervention in travel behaviour research: A difference-in-differences framework

Causal inference with the difference-in-differences (DID) framework is popular in identifying causal effects with observational data and has started to be applied in recent travel behaviour studies. Most relevant transportation research adopts the conventional linear parametric DID model, which is known to be inflexible and restrictive. This study applies non-parametric DID estimators facilitated by machine learning (ML) models for causal inference in a variety of data scenarios. Semi-parametric and doubly robust estimators are established and integrated with the ML-based cross-fitting pipeline. Simulation studies and empirical case studies are conducted to showcase the ability of ML-based DID to detect causal effects from both simulated and real-world datasets. Results suggest that the proposed methods outperform conventional DID models in all data scenarios. Light working models are generally preferred over hyperparameter-dependent ones for their comparable performance, lower computational burden, and higher levels of compatibility to real-world empirical analysis. Empirical case studies also demonstrate how the proposed DID method could be applied to evaluate the impacts of various interventions on travel behaviour in different contexts. The present study adds to the existing travel behaviour literature by leveraging machine learning algorithms and non-parametric estimators to the impact evaluation of external interventions on travel characteristics and expanding the application of causal inference approaches in transportation research.

Economic Impact Analysis of Value Chain Development Programme (VCDP) on Net Farm Income of Rice Farmers in Niger State, Nigeria

This study evaluated economic impact analysis of VCDP on net farm income (NFI) of rice farmers in Niger State, Nigeria. Primary data were used. A multi-stage sampling technique was used to select a total sample size of 292 rice farmers which comprised of 155 value chain development program beneficiaries and 137 non- beneficiaries. Data were analyzed using descriptive statistics, gross margin analysis, multiple regression analysis, difference-in-difference method (DD), propensity score matching (PSM), principal component analysis, F-Chow test, and t-test. The gross margin ratio for VCDP beneficiaries and non-beneficiaries was 88% and 71%. Rice production was profitable. The result of the difference-in-difference regression analysis showed that treatment (P&lt; 0.10), period (P&lt; 0.01), interaction (P&lt; 0.10), level of educational (P&lt; 0.10), and farm experience (P&lt; 0.10), were statistically significant variables influencing the net farm income of rice farmers in the study area. The results of PSM show that the coefficient of Average Treatment Effect for all matching algorithms for net farm income of rice farmers such as nearest neighbor, radius, kernel, and stratification were significant at (P&lt; 0.01). The F-Chow test conducted for difference between NFI of participant and non-participant of VCDP was statistical significant. This shows that VCDP impacted positively on NFI of rice farmers. The study recommends that low-interest loans should be made available to rice farmers to increase income.

The Association Between Medicaid Expansion and Disparities in Vestibular Schwannoma Incidence.

The effect of Medicaid expansion as a part of the Affordable Care Act on vestibular schwannoma (VS) incidence overall and in marginalized populations has not yet been elucidated. The goal of this study was to determine if Medicaid expansion was associated with increases in VS incidence overall, as well as in patients of non-white race or in counties of low socioeconomic status (SES). We performed a difference-in-difference (DiD) analysis from January 1st 2010-December 31st 2017 utilizing the Surveillance, Epidemiology, and End Results (SEER) database. Our DiD method compared the change in VS rate between counties that did and did not expand Medicaid among patients of white and non-white race, in low and high SES counties, before and after expansion. The study included 17,312 cases across 1020 counties. Medicaid expansion was associated with a 15% increase (incidence rate ratio 95% CI: [11%, 19]) in VS incidence. White populations saw a 10% increase (CI: [1.06, 1.19]), Black populations saw a 20% increase (CI: [1.10, 1.29]), and patients of other races saw a 44% increase in incidence associated with expansion (CI: [1.21, 1.70]). Low SES counties saw an increase in incidence 1.12 times higher than that of high SES counties (CI:[1.04, 1.20]). Medicaid expansion was associated with increases in VS incidence across populations. Furthermore, this increase was more evident in disadvantaged populations, such as patients of non-white race and those from low SES counties. These findings emphasize the impact of Medicaid expansion on healthcare utilization for VS diagnosis. 3-Retrospective Cohort Study Laryngoscope, 134:4383-4388, 2024.

The driving effect of the Euro on inbound tourism: multiperiod DID method

The introduction of the euro has greatly increased the amount of inbound tourists. The paper employs a multiperiod difference-in-differences (DID) model aimed at investigating the impact of the introduction of the euro on inbound tourism in 19 member states of the European Monetary Union (EMU) during 2002–2018. The results show that the euro has a significantly positive impact on international tourist arrivals and international tourism receipts in euro area countries. Moreover, there are also quantile differences in this effect. With increasing quantile levels, the quantile regression coefficients of the euro on international tourist arrivals are increasing, and the quantile regression coefficients of the euro on international tourism receipts are decreasing. Furthermore, the impact of the euro on international arrivals and international tourism receipts has been on the rise as the increase in the number of years of Eurozone accession, but the rate of growth is slowing, and the impact of the euro on inbound tourism has fluctuated with the European debt crisis. These results highlight that although the euro has a positive and significant effect on both international tourist arrivals and international tourism receipts, they are found to have different patterns and trends through the decomposition of quantile regression and segmented regression.

CLIMATE-SMART CITY: CAN CHINA’S SMART CITY POLICY LEAD TO LOW-CARBON DEVELOPMENT OF CITIES?

As an intensive mode of urbanization, a smart city may be conducive to achieving a win–win situation of regulating the urban economy and the environment. Based on a quasi-natural experiment in three batches of smart pilot cities, we use the difference-in-differences (DID) method to examine the impact of the smart city policy on CO2 emissions by adopting city panel data in China during the period 2003–2017. This study also explores the influence mechanism and heterogeneous effects of smart city policy. The empirical results indicate that China’s smart city policy effectively lowered CO2 emissions by approximately 1.83%. This primary finding remains reliable using the propensity score matching (PSM)-DID method for robustness check. Moreover, the smart city policy not only directly inhibits CO2 emissions, but also indirectly influences CO2 emissions through scale, structure, and technology effects. Regarding city heterogeneity, the first-tier cities in the eastern area, which have larger population scale and more resource endowments, tend to have stronger negative impacts on CO2 emissions. Based on these conclusions, we highlight several specific policy measures for reducing CO2 emissions and achieving dual carbon targets in China.

Can innovative industrial clusters enhance urban economic resilience? A quasi-natural experiment based on an innovative pilot policy

Using data for 285 cities in China spanning the period from 2010 to 2019, we investigate the overall effect, heterogeneity, and mechanisms of industrial cluster development on urban economic resilience using the staggered difference-in-differences method (DID). Our study shows that innovative industrial clusters can improve local urban economic resilience and offer a cumulative learning effect, but increase economic vulnerability in neighboring cities. A heterogeneity analysis finds that piloting innovative industrial clusters has a more significant influence on economic resilience in more mature clusters, middle-labor-scale cities, areas with moderate economic development, and regions applying more artificial intelligence (AI) technology. An influencing mechanism analysis shows that piloting innovative industrial clusters mainly appears as a scale effect in the earlier stage of green finance development, while there is a network effect in the later stage, both of which promote economic resilience. This conclusion may serve as the foundation for more secure and sustainable growth in the global economy.

Can carbon emission trading improve regional eco-efficiency? Based on the environmental innovation perspective.

This paper uses green innovation and environmental pollution as the mediating variables to construct a mediating effect model to investigate whether China's carbon emission trading policy can improve regional eco-efficiency by reducing regional environmental pollution and stimulating green innovation. This study is based on panel data from 30 provinces and municipalities directly under China's central government and autonomous regions from 2003 to 2019. The eco-efficiency of these provinces is measured using the super-efficiency DEA model and the difference-in-difference method (DID). The results show that (1) China's emission trading policy significantly improves regional ecological efficiency and the per capita GDP. The improvement can effectively improve regional ecological efficiency. (2) The mediating effect of green innovation and environmental pollution is significant. That is, China's carbon emission trading policy further improves regional ecological efficiency by stimulating more green innovation and reducing the synergy brought by environmental pollution. (3) There are differences in the feedback of this impact mechanism between different regions: It shows the characteristics of the western region being more significant than the eastern region. The central region has no significant effect. The research conclusion can provide a policy reference for the subsequent unified promotion of the construction of a carbon emission trading market nationwide and a theoretical basis for helping to achieve the "dual carbon" goal.

How green finance boosts carbon efficiency in agriculture: a quasi-experiment from China

PurposeThe research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development.Design/methodology/approachIn this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China’s green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively.FindingsAfter the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas.Originality/valueWithin the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model.

Unleashing digital empowerment: Pioneering low-carbon development through the broadband China strategy

Low-carbon development has emerged as an imperative in the pursuit of carbon peak and neutrality. To this end, the intersection of digital empowerment and the quest for innovative solutions in developing countries has taken center stage, particularly in exploring the network infrastructure construction potential. This research delves into the intricate relationship between network infrastructure construction expansion and low-carbon development in developing countries, drawing insights from a comprehensive analysis of panel data collected from 282 Chinese cities. Leveraging the quasi-natural experiment presented by “Broadband China” and employing a rigorous multi-period difference-in-difference (DID) model, our study uncovers significant findings. First, it reveals that the expansion of the network infrastructure construction directly amplifies the prospects of low-carbon development, a result consistently upheld through meticulous assessments of the multi-period DID approach and validation through the robust synthetic control DID method. Second, the study elucidates how network infrastructure construction expansion fosters low-carbon development by optimizing industrial structure and promoting investments in cutting-edge technologies. Third, it unveils the impact of network infrastructure construction expansion on the efficiency of low-carbon technology, concurrently encouraging its enhancement while imposing specific inhibitory effects. Remarkably, the policy outcomes exhibit variations among cities of differing sizes and between cities with old and non-old industrial bases. Finally, the research underscores the spatially endogenous interaction effects within low-carbon development. In sum, this study not only enriches comprehension of innovative avenues for low-carbon development within the sphere of digital empowerment but also provides empirical evidence to refine policy recommendations specifically tailored to the unique context of developing countries.

Could Environmental Regulations Reduce Energy Consumption: Evidence From China’s Implementation of an Environmental Pollution Tax

This article investigates the impact of environmental regulations on energy consumption. As the main way for the government to protect the environment, the implementation of environmental pollution tax has played an important role in China’s energy consumption. This article uses data from the implementation of environmental pollution tax in Chinese cities to match with urban energy consumption data, and uses the difference-in-difference method (DID) to estimate the impact of environmental regulations on energy consumption. We find that the implementation of environmental pollution tax has reduced energy consumption, but this effect is mainly effective in the central and western regions and two-controlled areas. Further analysis shows that the reduction of energy consumption by environmental pollution tax is mainly attributed to improving technological innovation capabilities, optimizing industrial structure, and increasing tax collection intensity. The results in this study provide evidence for achieving an environmentally friendly society and sustainable development.

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.

Can CSR engagement improve firm’s resilience to the COVID-19 pandemic? Evidence from the Moroccan stock market.

The purpose of this paper is to investigate empirically the role of corporate social responsibility engagement on stock returns during the COVID-19 crisis in the case of a sample of Moroccan-listed companies. The authors use a difference-in-difference (DiD) regression estimated on a panel dataset of a sample of 23 Moroccan listed companies for the period spanning from March 2019 to March 2021. We identified the connection between CSR activities and financial returns by comparing the monthly stock returns of the treatment and the control groups. Empirical results reveal that the pandemic-induced decrease in stock returns is stronger for firms with CSR activities. It means that engaging in CSR activities does not immunize Moroccan firms during the pandemic. Our findings show that Moroccan’s stock market is unable to positively value CSR activities. The results indicate that agency problems lead Moroccan investors to overinvest in costly CSR activities, which reduce the value of the firms in times of the COVID crisis and delay their recovery from it. To the best of our knowledge, this study is the first to investigate the relationship between CSR activities and the resilience of Moroccan companies. Also, this study is distinguished by using the DiD method and by exploiting data from the Eikon Refinitiv database.

The impact of the COVID-19 pandemic on regional inflation in Indonesia

PurposeThis paper aims to examine the impact of COVID-19 on inflation in Indonesia. There are two questions in this study: (1) Is there an impact of COVID-19 on inflation in Indonesia? and (2) whether there are differences in the impact of COVID-19 on regional inflation in Indonesia, considering the different intensities associated with COVID-19.Design/methodology/approachThe estimation technique showing the impact of the COVID-19 pandemic on inflation uses the difference-in-differences (DID) method described by Pischke (2008). The core idea of the estimation above is continuous DID using panel data. No province was affected by COVID-19 before 2020:Q1. Once COVID-19 hits the economy, the effects vary from one district to the other.FindingsThe authors find that the severity of the COVID-19 pandemic negatively affects inflation – the more severe the pandemic, the lower the inflation. This finding conforms with several studies suggesting higher demand pressures than supply during the pandemic. Compared with supply-side indicators such as production index, demand-side indicators – such as consumer confidence index and real sales index – fell more sharply.Research limitations/implicationsIn the Introduction section, the authors have added a discussion that indeed the COVID-19 pandemic affects inflation through both the demand- and supply-side shocks. While factors driving regional differences in inflation rate are important research and policy questions, the analysis of these factors is outside the scope of this study. The study focuses on the COVID-19 impact on inflation and whether the pandemic disproportionately affects some regions than the others.Practical implicationsThis research is important to provide an understanding of the nature of the pandemic on inflation in the context of the Indonesian economy, which is essential to policy formulation, especially for the Central Bank in carrying out the mandate to maintain rupiah stability. This issue is due to the implications of different policy responses between demand- and supply-side shocks.Originality/valueAs a novelty in this study and research gap, the authors use a continuous DID method to account for the varying intensity of COVID-19 across the provinces. In particular, the authors use the number of positive cases of COVID-19 per 1,000 population as opposed to just a binary indicator of before-and-during COVID-19 across provinces.

The Impact of Natural Disaster on US Stock Market Index: Using DID, ARMAX-GARCH, and Random Forest

The stock market might be impacted by natural disasters, which can cause significant market disruptions and financial uncertainty, as already shown in several existing studies. This study investigates the role of natural disasters in stock market movements in the US specifically, hypothesizing that incorporating natural disasters leads to more accurate stock market predictions. Various models, including Difference-in-Differences (DID), ARMA-GARCH/ARMAX-GARCH, and Random Forest, are employed to analyze the S&amp;P 500 index's daily returns and the impact of natural disasters. The study reveals that the ARMA-GARCH model effectively captures market volatility but does not account for all influencing factors such as interest rate, inflation rate, and natural disasters. The DID method isolates natural disaster effects, showing significant but inconsistent impacts. The Random Forest model, incorporating a disaster severity index, yields more accurate predictions than the one without, reinforcing the hypothesis and supporting previous studies. Although the study highlights the importance of considering natural disasters in stock market predictions, it also underscores the market's complexity, indicating that more features and factors should be considered in future research.