Multiple Indicators And Multiple Causes Research Articles

Preliminary development of a brief parent-report gender identity alignment/distress screener for children.

This research develops a brief, and preliminary, parent-report screener to assess gender identity alignment/distress in children. The increasing prevalence of children not identifying with their sex at birth, the length and outdated language of existing gender identity measures, and the need to assess gender identity among children (as opposed to adolescent/adult measures) motivate a screener. A survey containing 14 items from existing instruments was administered to a diverse set of 1110 parents of children ages 3-12. Exploratory and confirmatory factor analyses, followed by multiple indicators and multiple causes (MIMIC) modelling, were used to develop a 5-item, unidimensional screener that may assess gender identity alignment/distress. The screener may be suitable to identify children who experience misalignment between their gender and sex assigned at birth and parents or children for whom this misalignment causes distress. These families may benefit from additional resources and conversations between paediatric staff and children about their gender identity, including education for parents, and/or referrals for specialty care. Future research should further streamline and validate this preliminary screener, examine its convergence with gender identity and distress measures and explore including children's perspectives.

Polysubstance Use among Maryland High School Students: Variations across County-Level School Districts.

Polysubstance use is a highly prevalent public health issue, particularly among adolescents, and decisions on prevention programming and policies are often made at the local level. While there is a growing literature examining patterns of polysubstance use among adolescents, little is known about differences in those patterns across geographic regions. Using a large, representative sample of high school students from the state of Maryland (n = 41,091) from the 2018 Maryland Youth Risk Behavior Survey, we conducted a latent class analysis (LCA) of adolescent substance use along nine binary indicators, including past 30-day combustible tobacco, e-cigarette, alcohol, and cannabis use, as well as lifetime use of prescription opioids, cocaine, heroin, methamphetamine, and injection drug use. Measurement invariance across counties was examined using the Multiple Indicators and Multiple Causes (MIMIC) procedure. The results of the LCA show three classes of adolescent substance use for the total sample: (1) low substance use, (2) commonly used substances (i.e., e-cigarette, alcohol, and cannabis use), and (3) polysubstance use. The results from the MIMIC procedure demonstrated geographic differences in students' endorsement of specific indicators and their class membership. These differences demonstrate the need for an examination of local trends in adolescent polysubstance use to inform multi-tiered prevention programming and policy.

In the midst of the COVID-19 pandemic: Perceived risks, management strategies and emerging opportunities for small and medium agri-food enterprises in a developing country

The Covid-19 pandemic has posed unprecedented challenges to small- and medium-sized agrifood enterprises (SMAEs) in developing countries. However, research investigating what risks Covid-19 posed to these firms, how they responded, and what business opportunities emerged to SMAEs from the pandemic remains scanty. Drawing on a sample of 166 specialist SMAEs in Egypt, this study addressed these entwined questions by using multiple indicators and multiple causes (MIMIC) and mediation analysis. Our results point out that the Covid-19 pandemic exposed Egyptian SMAEs to complex and multidimensional risks, and caused profound effects on both upstream and downstream stages of their supply chains. In general, Egyptian SMAEs adopted a ‘wait-and-see’ approach to cope with such Covid-19 risks and impacts, which was attributed to their lack of sufficient financial resources to develop risk management strategies and formalize structures to deal with unexpected events. Interestingly, the results showed that several business opportunities emerged from pandemic; but SMAEs' resource disadvantages constrained their capacity to seize and exploit these opportunities. Moreover, we found that mitigation strategies adopted by SMAEs present a mediating factor between perceived Covid-19 risks and perceived business opportunities. Overall, our findings call for a paradigm shift in relation to enterprise risk management in developing countries' SMAEs toward more holistic frameworks to enhance their preparedness to future shocks, make mature operational and strategic management decisions, and exploit strategic opportunities.

Development of an individual index of social vulnerability that predicts negative healthcare events: a proposed tool to address healthcare equity in primary care research and practice

PurposeSocially disadvantaged patients may lack self-efficacy to navigate a complex health system making them vulnerable to healthcare inequity. We aimed to develop an Index of social vulnerability that predicts increased risk of negative healthcare events (e.g. emergency hospitalization), independent of chronic disease burden. The analysis illustrates the conceptual and practical steps leading to the development of a pragmatic Index of social vulnerability to limited healthcare self-efficacy.MethodsUsing data from a 3-year cohort of 2507 adult primary care patients in Québec (Canada), we applied two complementary structural equation modelling approaches—Partial Least Squares Path Modelling (PLS-PM) and Multiple indicators and Multiple Causes (MIMIC) modelling—to identify a minimal set of social characteristics that could be summed into an Index related to limited healthcare self-efficacy. We then used logistic regression to determine if the Index predicted: hospital emergency department use; hospital admissions; unmet need for care, and others. We privileged parsimony over explanatory capacity in our analytic decisions to make the Index pragmatic for epidemiologic and clinical use.ResultsThe Individual Social Vulnerability Index is the weighted sum of five indicators: two indicators of social support; educational achievement; financial status; limited language proficiency. The Index predicts increased likelihood of all negative healthcare outcomes except unmet need, with a clear threshold at Index ≥ 2. The effect is independent of chronic disease burden.ConclusionWhen social deficits outweigh social assets by two or more (Index ≥ 2), there is an increased risk of negative healthcare events beyond the risk attributable to poor health. The Index is a pragmatic tool to identify a minority of patients who will require additional support to receive equitable healthcare.

DIF Statistical Inference Without Knowing Anchoring Items

Establishing the invariance property of an instrument (e.g., a questionnaire or test) is a key step for establishing its measurement validity. Measurement invariance is typically assessed by differential item functioning (DIF) analysis, i.e., detecting DIF items whose response distribution depends not only on the latent trait measured by the instrument but also on the group membership. DIF analysis is confounded by the group difference in the latent trait distributions. Many DIF analyses require knowing several anchor items that are DIF-free in order to draw inferences on whether each of the rest is a DIF item, where the anchor items are used to identify the latent trait distributions. When no prior information on anchor items is available, or some anchor items are misspecified, item purification methods and regularized estimation methods can be used. The former iteratively purifies the anchor set by a stepwise model selection procedure, and the latter selects the DIF-free items by a LASSO-type regularization approach. Unfortunately, unlike the methods based on a correctly specified anchor set, these methods are not guaranteed to provide valid statistical inference (e.g., confidence intervals and p-values). In this paper, we propose a new method for DIF analysis under a multiple indicators and multiple causes (MIMIC) model for DIF. This method adopts a minimal L_1 norm condition for identifying the latent trait distributions. Without requiring prior knowledge about an anchor set, it can accurately estimate the DIF effects of individual items and further draw valid statistical inferences for quantifying the uncertainty. Specifically, the inference results allow us to control the type-I error for DIF detection, which may not be possible with item purification and regularized estimation methods. We conduct simulation studies to evaluate the performance of the proposed method and compare it with the anchor-set-based likelihood ratio test approach and the LASSO approach. The proposed method is applied to analysing the three personality scales of the Eysenck personality questionnaire-revised (EPQ-R).

Understanding the effect of sociodemographic and psychological latent characteristics on flex-route transit acceptance.

Flex-route transit (FRT) has significant advantages in low-demand areas. Existing studies have focused on practical experience, strategic planning, and operational planning. Few studies have addressed the effect of sociodemographic and psychological latent characteristics on the acceptance of FRT. This study aims at exploring the effect of sociodemographic and psychological latent characteristics on FRT acceptance. To finish the goal, a household survey is conducted from April to May 2020 in Nanjing, China. The survey includes sociodemographic characteristics and observed variables of individuals. Firstly, the study extracts six psychological latent characteristics to reflect individuals' attitudes based on previous and mature researches in the field of technology acceptance model (TAM) and theory of planned behavior (TPB). Then, a multiple indicators and multiple causes (MIMIC) is applied to calculate six psychological latent characteristics. Finally, an integrated model, consisting of the MIMIC and a binary logit model (BLM), is applied to match sociodemographic and psychological latent characteristics. The BLM with sociodemographic characteristics is developed as the reference model to compare the effects of psychological latent characteristics. Results show that psychological latent factors play a significant role in estimating the effect on FRT acceptance. Results of the integrated model show that the parameter of car is -0.325, displaying individuals with private cars are more reluctant to use FRT. Therefore, restricting private cars is an effective measure to facilitate FRT. Improving flexibility (0.241) is a significant measure to facilitate FRT. Findings are expected to facilitate decision-making of transport planners and engineers, and therefore enhance the service of the FRT system.

A cross-sectional study on the impact of the COVID-19 pandemic on psychological outcomes: Multiple indicators and multiple causes modeling.

Although the psychological impact of coronavirus disease 2019 (COVID-19) has been evaluated in the literature, further research is needed, particularly on post-traumatic stress disorder (PTSD) and psychological outcomes, is needed. This study aims to investigate the effect of the COVID-19 pandemic on psychological outcomes (depression, anxiety, and insomnia). A cross-sectional study using an online survey was conducted using the following instruments: Impact of Event Scale-Revised (IES-R), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Insomnia Severity Index (ISI). Confirmatory factor analysis (CFA), structural equation model (SEM), multiple indicators and multiple causes (MIMIC) modeling, and differential item functioning (DIF) were performed to analyze the collected data. According to the results, participants with PTSD (n = 360) showed a higher level of depression, anxiety, and insomnia than those without PTSD (n = 639). Among the participants, 36.5% experienced moderate to severe symptoms of depression, and 32.6% had mild depressive symptoms. Moreover, 23.7% of participants experienced moderate to severe anxiety symptoms, and 33.1% had mild anxiety symptoms. In addition, 51.5% of participants experienced symptoms of insomnia. In conclusion, the PTSD caused by COVID-19 is significantly associated with depression, anxiety, and insomnia at the level of latent constructs and observed variables.

Development and Validation of the Scale of Attitudes about Seeking Formal Help in the Context of Intimate Partner Violence.

Stigma plays a critical role in the decision-making process of intimate partner violence (IPV) survivors, particularly whether they disclose, initiate, and continue with care for the consequences of the violence. As such, this study developed and validated a scale to assess the manifestation of IPV stigma on survivors' attitudes toward accessing services, using a racially and ethnically diverse sample of women (N = 409). An exploratory factor analysis was conducted using a calibration subset (n = 206) to identify the factor structure of the newly developed scale. A confirmatory factor analysis was then performed using a validation subset (n = 203) to validate the hypothesized model. To assess language and Latina ethnic differences in the scale functioning, multiple indicators and multiple causes (MIMIC) modeling was applied. To test for construct validity, the scale's correlation with two conceptually relevant variables was estimated. The final exploratory factor analysis (EFA) model retained eight items across two factors, accounting for 58.63% of the variance. Factor 1 captures attitudes related to anticipated stigma, and factor 2 captures attitudes related to internalized stigma. Results from the CFA validated the hypothesized second-order, two-factor model of the scale of Attitudes About Seeking Formal Help. Overall, results from the MIMIC model indicated measurement invariance across English and Spanish-speaking and Latina and non-Latina survivors. Construct validity was supported. This scale provides a tool to help capture and understand IPV stigma in relation to accessing professional services. Specifically, practitioners will be able to identify survivors who endorse high negative attitudes about seeking formal help, potentially being at higher risk of service discontinuation. Such information could, in turn, help guide a targeted service plan. Practitioners may also use this tool with ongoing clients to inform their practices and determine whether specific IPV stigma should be the focus of intervention.

Psychometric validation of the Chinese Health Questionnaire among young people in Hong Kong across 2018 and 2019.

The Chinese Health Questionnaire (CHQ) is a 12-item assessment tool of psychological distress. The present study systematically evaluated the psychometric properties of the CHQ in a large sample of 1968 young people in Hong Kong. The participants completed the CHQ online in 2018 and 869 of them completed a follow-up survey on the CHQ, suicidal ideation, hikikomori, and help-seeking in 2019. Dimensionality of the CHQ was assessed via confirmatory factor analysis using the robust weighted least square estimator in 2018 and 2019. Measurement invariance was investigated across gender, age groups, and time between 2018 and 2019. Convergent validity of the CHQ factors were evaluated with respect to the mental health outcomes in the multiple indicators and multiple causes (MIMIC) approach. Confirmatory factor analyses shortened the CHQ into 10 items and revealed a superior fit for the bifactor model with a general factor and two specific factors on somatic and depressive symptoms in both 2018 and 2019. The general factor demonstrated substantial factor loadings (λ = 0.58-0.91), good reliability (ΩH = 0.85), and temporal stability (r = 0.62), and scalar measurement invariance across gender, age groups, and time. The general factor was significantly and positively associated with suicidal ideation, hikikomori, and help-seeking. The two specific factors displayed lower factor loadings, reliability, temporal stability, and weaker associations with the mental health outcomes. The present findings lend support to a valid and stable bifactor structure with a strong general factor for the CHQ-10 among young people in Hong Kong. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Illegal gambling: measuring the market using the MIMIC model

ABSTRACT Using a multiple indicators and multiple causes (MIMIC) model, this paper estimates the extent of illegal gambling in Italian regions over the period 2013–18. By treating illegal gambling as an unobserved latent variable directly related to its causes and effects, this model gives information about the relationship between cause and indicator variables and the latent variable from covariance structures. From the analysis, it emerges that the share of illegal gambling increases with the value of the winnings paid; it decreases when the number of authorized machines increases. We also find that individuals with low levels of education and low income show a greater propensity to gamble illegally.

Factorial validity and measurement invariance of the Psychosocial Uncertainty Scale

This study presents the development of the Psychosocial Uncertainty Scale (PS-US), which articulates the perception of uncertainty in the social context and its psychological experience. It was validated with a sample of 1596 students and active professionals (employed and unemployed). By randomly dividing this sample in three sub-samples, the following analyses were performed: exploratory factor analysis (sample one: N = 827); preliminary confirmatory factor analysis identifying the final version of the scale (sample two: N = 382); confirmatory factor analysis (sample three: N = 387). Multi-group analysis was used to assess measurement invariance, gender, sociocultural level, and group of origin invariance, by using samples two and three. Group differences were explored with the complete sample through Multiple Indicators and Multiple Causes (MIMIC) Models. Associations between this scale and the Uncertainty response Scale were explored through Structural Equation Modelling. Exploratory and confirmatory analyses’ results showed good internal consistency and overall good psychometric qualities. The scale reached full metric invariance across groups, gender, SCL level and group of origin. Results highlight the sensitivity of the scale towards social vulnerability, proving the existence of sociocultural levels’ effects on experiences of psychosocial uncertainty within working contexts, relationships and community living and self-defeating beliefs; and gender and students versus professionals’ effects on psychosocial uncertainty. Furthermore, the scale associated significantly with Uncertainty Response Scale’s dimensions, specifically with emotional uncertainty, which can be considered a self-defeating strategy. Results suggest that emotional coping strategies, are explained by psychosocial uncertainty by 57%, and so, may have social origins.

Private Parking Space Sharing Intention in China: An Empirical Study Based on the MIMIC Model

The shared parking scheme improves the utilization rate of existing parking resources and contributes to the sustainable development of cities, but many private parking spaces that are not included in the shared parking scheme have a low utilization rate in China. In order to better promote the shared parking scheme, it is necessary to study the intention of the owners of private parking spaces to share their parking spaces. Therefore, this paper used the Unified Theory of Acceptance and Use of Technology (UTAUT) and Benefit-Risk Analysis Model (BRA) as the combined theoretical framework (C-UTAUT-BRA). Hypothesis testing using the Multiple Indicators and Multiple Causes (MIMIC) model was performed using an empirical assessment of the shared parking scheme in China. The results show that (1) the sharing behavioral intention (BI) is directly affected by perceived benefit (PB), perceived risk (PR), social influence (SI), and facilitating condition (FC) and indirectly affected by effort expectancy (EE), of which the total effect of PB is the largest; (2) exogenous variables have an indirect effect on BI through other psychological latent variables; among them, different sociodemographic and economic characteristics have a significant influence on different latent variables, while the built environment has no significant effect on latent variables. This research contributes to theory building in shared parking participation intention and informs business and government leaders on how to promote the shared parking scheme through the action mechanism of influencing factors on BI.

Estimating Social Discount Rate Trend in Iran

The Discount rate is one of the important variables in the inter-temporal analysis which makes it possible to compare the current and the future values and enables economic agents and policymakers to make better decisions. In this context, the discount rate is a vital variable for the accurate evaluation of economic projects. Considering the different approaches that governmental and private sectors use to implement the investment projects, for evaluation of the governmental and public projects, a separate discount rate is used called social discount rate (SDR). In this article by using the structural equation modeling, we have estimated the SDR trend in the Iranian economy during the period 1996- 2016. To do that by extracting influencing & consequence factors of SDR (as a latent variable), we applied a Multiple Indicators and Multiple Causes (MIMIC) model. The SDR trend, as the main finding of this paper, seems to be robust enough due to its explanatory power for fluctuations of the Iranian economy in reality. The results imply that the SDR has had a mild decreasing trend in Iran's economy during the sample period and among influencing variables, the inflation rate has had the most impact on its trend. Accordingly, when the level of prices rocketed during the periods 2012-14, the SDR trend experienced a more than 60% increasing jump. However, the GDP has been the variable that mostly affected by the SDR fluctuations. It seems that controlling inflation and consequently social inflationary expectation can be proposed as a proper policy recommendation to manage SDR and its distorting impacts in Iran.

Shadow economies and tax evasion: The case of the Czech Republic, Poland and Hungary

AbstractThis paper examines the drivers and the size of the shadow economies of the Czech Republic, Hungary and Poland. It also investigates the tax losses associated with these shadow economic activities in all three countries. The Multiple Indicators and Multiple Causes (MIMIC) model is applied and uses time series data covering the period 1990–2019. The key findings show that the sizes of the shadow economies of the Czech Republic, Hungary and Poland are 10.44, 11.18 and 20.47% respectively. The results also show that the average size of the shadow economies between 1990–2019 was 14.92% in the Czech Republic, 18.72% in Hungary and 22.85% in Poland. The Czech Republic loses 3.13% of tax revenue from goods and services and 2.83% from incomes and profits as a result of the shadow economy, while Hungary loses 5.05% of tax revenue from goods and services and 1.68% from incomes and profits. Poland loses 5.25% of tax revenue from goods and services and 4.34% from incomes and profits.

Research on the Mode Choice Intention of the Elderly for Autonomous Vehicles Based on the Extended Ecological Model

Due to the elderly’s limited physical ability, their mode choice behavior with particular demand for the traffic system is significantly distinguished compared to young people. The emergence of Autonomous Vehicles (AVs) and Shared Autonomous Vehicles (SAVs) will allow the elderly to travel independently and offer more mode choices. However, emerging vehicles will continue to coexist with other traditional modes such as public transport. This paper aims to explore the internal mechanism of the elderly’s choice behavior among public transport, AVs, and SAVs. We integrated the relevant factors by expanding the ecological model and used the Multiple Indicators and Multiple Causes (MIMIC) model to analyze the constructs’ relationship. The results show that the elderly believe that public transport, AVs, and SAVs are useful and convenient travel modes for themselves, affecting intention significantly. In addition, the elderly’s well-being and social influence during travel are also significant constructs for their behavioral intention. The research could provide academic supports for the traffic management departments when making relevant policies and measures for the elderly.

Comparing loneliness in England and the United States, 2014-2016: Differential item functioning and risk factor prevalence and impact.

The purpose of this study is to compare mean levels of loneliness, and correlates of loneliness, among older adults in the U.S. and England. Comparisons are conducted after attending to comparability of the loneliness measure between countries based on tests for discriminatory capacity and differential item functioning of the 3-item UCLA Loneliness Scale. Cross-sectional data from the 2015–16 wave of the National Social Life, Health and Aging Project (NSHAP) and the 2014–2015 wave of the English Longitudinal Study on Ageing (ELSA) were analyzed using graded item response models and multiple indicators and multiple causes (MIMIC) models. Risk factors included demographic variables, health characteristics, and social characteristics that were harmonized across surveys. Because of differences in the racial-ethnic composition of the U.S. and England, analyses were limited to white respondents (N = 2624 in NSHAP; N = 6639 in ELSA). Only respondents born 1925–1965 were included in analyses. Discriminatory capacity was evident in each item being able to distinguish a lonely from a nonlonely individual. Differential item functioning (DIF) was evident in country differences in the likelihood of endorsing the “lack companionship” item at a given level of trait loneliness, and in DIF among marital status, education, and gender subgroups that were comparable across countries. Overall loneliness levels are equivalent in England and the U.S. Risk factor impact did not differ between countries, but differences in risk factor prevalence between countries combined to produce a net result of slightly lower mean levels of loneliness in older adults in England than in the U.S. after risk factor adjustment. The fact that the impact of risk factors were similar across countries suggests that evidence of successful interventions in one country could be leveraged to accelerate development of effective interventions in the other.

Analyzing drivers' perceived service quality of variable message signs (VMS).

Recent advance in VMS technology has made it viable to ease traffic congestion and improve road traffic efficiency. However, the drivers’ low compliance with the posted information may limit its performance to ease traffic congestion and improve traffic safety. This paper explores drivers’ attitude to the service quality of VMS system resulted from the identified predominant influencing factors. A questionnaire is developed and used for surveying 9,600 drivers in Beijing, China. The collected data are analyzed with a multiple indicators and multiple causes (MIMIC) model considering different driver categories (e.g., private car driver, office car driver, taxi driver). The results show that the causal relationships between latent variables and socio-demographic characteristic is significant. Driving frequency, attitude towards contents of VMS, drivers’ decision-making and the effectiveness of VMS message can directly and indirectly affect driver’s perceived quality of service. The attitude towards formats of VMS indirectly affect their QoS resulting from the effectiveness of VMS message, while there is no indirect impact for taxi drivers. Besides, the drivers’ decision-making directly affects the perceived quality of service for private car drivers and office car drivers, but there is no impact for taxi drivers. The findings of this study can provide guidance and reference for urban authorities to perform the relevant actions required to meet user expectations.

Understanding the Linkages Between Parental Monitoring, School Academic Engagement, Substance Use, and Suicide Among Adolescents in U.S.

Suicide is the second leading cause of death among youth and young adults. Improving the understanding of social-ecological factors associated with youth suicide behaviors may highlight important ideas for prevention. From a social-ecological theoretical framework of suicide, this study aims to test whether parental monitoring and school academic engagement predict suicidal behavior and substance use in youth, and by gender. Data comes from a large cross-sectional U.S. study—the 2017 National Survey on Drug Use and Health (NSDUH)—which includes U.S. adolescents (N = 12,884) aged 12–17 years old. A structural equation model (SEM) and the MIMIC (Multiple Indicators and Multiple Causes) model of SEM were used to test the proposed conceptual model using AMOS Version 25. The final structural model had an adequate goodness of fit [χ2(df = 84, N = 12,884) was 2352.58, p < 0.001]. The other fit statistics indicated good fit with RMSEA = 0.044 and CFI = 0.94. Fifty-eight percent of the variance in suicide behaviors was accounted for by the model. These findings underscore critical associations between suicidal behavior and relational (parental monitoring), community (school academic engagement) and individual (substance use) social ecological factors. Gender paths in the model did not differ significantly. These factors suggest important prevention targets for reducing suicide risk among adolescents.

Income or Assets—What Determines the Approach to the Environment among Farmers in A Region in Poland?

The theory about the impact of farm size, income and assets on the environmental approach of farmers is ambiguous. We contribute to the existing discussion in two ways. Firstly, we look for the determinants of the environmental approach. Secondly, we treat farm size as a heterogeneous factor, affected not only by the value of assets but also flows of incomes. The main objective of the article is, therefore, to recognize the impact of assets and income on the environmental approach of agricultural producers. We analyze the results of surveys carried out in 2020 on a group of 120 farms from the Wielkopolska region (Poland), using structural equation modelling (generalized structural equation modelling (GSEM)-multiple indicators and multiple causes (MIMIC) model). Our results indicate that both the income and assets of the agricultural producers have a positive impact on their approach to the environment. However, to a greater extent, the farmer’s approach to the environment is influenced more by income than by assets. This may be influenced by the capitalization of subsidies in the price of agricultural land, which makes this element of farm assets detached from real processes. It is easier for farms with a higher income and assets to realize the orientation towards sustainability.

Environmental regulation, hidden economy, and China's outward foreign direct investment

The need to balance economic growth and its environmental impact continues to be a serious issue in China. As environmental regulation in China increases in importance, it is critical to understand how it impacts economic growth drivers such as outward foreign direct investment (OFDI) to formulate effective policies. One consideration should be the hidden economy, which can weaken the effects of environmental regulation on OFDI. This study investigates the scale of the hidden economy in 30 provinces and province-level municipalities in China in the period 2004 to 2015. The study uses the multiple indicators and multiple causes (MIMIC) model and the systematic generalized method of moments (GMM) test to analyze the impact of environmental regulation and the hidden economy on China's OFDI. The results show that stronger environmental regulation promotes OFDI. However, the hidden economy inhibits China's OFDI, as the positive effects of environmental regulation that drive OFDI are distorted. From a regional perspective, stronger environmental regulation promotes OFDI as well, while the hidden economy inhibits it. The interaction between environmental regulation and the hidden economy also inhibits it significantly.