Fixed Effects Estimation Research Articles

Comparing modelling approaches for the estimation of government intervention effects in COVID-19: Impact of voluntary behavior changes.

The efficacy of government interventions in epidemic has become a hot subject since the onset of COVID-19. There is however much variation in the results quantifying the effects of interventions, which is partly related to the varying modelling approaches employed by existing studies. Among the many factors affecting the modelling results, people's voluntary behavior change is less examined yet likely to be widespread. This paper therefore aims to analyze how the choice of modelling approach, in particular how voluntary behavior change is accounted for, would affect the intervention effect estimation. We conduct the analysis by experimenting different modelling methods on a same data set composed of the 500 most infected U.S. counties. We compare the most frequently used methods from the two classes of modelling approaches, which are Bayesian hierarchical model from the class of computational approach and difference-in-difference from the class of natural experimental approach. We find that computational methods that do not account for voluntary behavior changes are likely to produce larger estimates of intervention effects as assumed. In contrast, natural experimental methods are more likely to extract the true effect of interventions by ruling out simultaneous behavior change. Among different difference-in-difference estimators, the two-way fixed effect estimator seems to be an efficient one. Our work can inform the methodological choice of future research on this topic, as well as more robust re-interpretation of existing works, to facilitate both future epidemic response plans and the science of public health.

Examining the Role of Biomass Energy for Clean Environment in African Countries

This paper investigates the influences of biomass energy, fossil fuel, and some controlled variables on CO2 emission in African countries over the 1980–2014 period. The study employs pool mean group (PMG), mean group (MG), and dynamic fixed effect (DFE) estimators. In addition, it employs weighted fully modified ordinary least squares and weighted dynamic ordinary least squares to validate the robustness of estimates. The results reveal that the relation of fossil fuel with CO2 is positively significant. Conversely, biomass energy exerts a significant negative impact on CO2. In addition, the dampening effect of biomass energy utilization on CO2 emission helps to validate the Environmental Kuznets Curve hypothesis.

Effects of the vaccination against SARS-CoV-2 on infections and on hospitalizations in European countries

Since December 2020 vaccines against the SARS-CoV-2 virus have been available. However, little is known regarding their effects on infections and on hospitalizations. To gain insight into this topic we empirically analyze the effects of the vaccinations against SARS-CoV-2 for European countries beginning 2021 to February 2022 with weekly data. We perform panel fixed effects estimations, GMM estimations and nonlinear penalized spline estimations. We find a statistically significant and positive relationship between the share of infections with the SARS-CoV-2 virus and the share of vaccinated people in nine estimations while one estimation output was insignificant. Regarding hospitalizations, six out of ten estimations yielded a statistically insignificant relationship, and three estimation results were weakly statistically significant with a negative coefficient and one indicated a statistically significant negative relation. Hence, there is empirical evidence for a positive relationship between infections and the share of vaccinated people whereas we find weak empirical evidence for a negative relation between vaccinations and hospitalizations. The implication of our analysis is that vaccinations alone cannot end the pandemic. Rather developing effective medicines should be seen as an additional measure.

Is economic complexity an enabler of environmental innovation? Novel insightful lessons from European region

PurposeThis paper empirically examines the influences of economic complexity performance on environmental innovation implementation.Design/methodology/approachThe research is based on four measures designed to assess the effectiveness of environmental innovations in 24 European countries, including the percentage of enterprises implementing environmental innovation investment (% of surveyed firms), the percentage of enterprises implementing environmental innovation activities (e.g. implementation of resource efficiency actions, sustainable products or ISO 14001 certificates) measured, a number of enterprises having new ISO 14001 registration and a number of environmental innovation related patents. After conducting various tests for longitudinal correlations and asymmetry of the studied series, we examine the relationship between product proximity, economic complexity and environmental innovation (EI) implementation using the panel-corrected standard error model (PCSE) model in the following section. The feasible generalized least squares (FGLS) model is employed to further verify our findings by taking into account heteroscedasticity. An application of the two-step generalized mixed model (GMM) is considered to resolve an endogeneity issue. In addition, the dynamic fixed-effects estimate (DFE) estimator is applied to the autoregressive distributed lag (ARDL) method in order to calculate both the short-run and long-run effects. As indicated by Ha (2022a, b) and Ha and Thanh (2022), the DFE-ARDL method can be used to identify both time-fixed effects and country-fixed effects.FindingsThe authors provide empirical evidence to propose the mechanism through which economic complexity encourages the implementation of environmental innovation through favorable impacts of economic complexity on environmental innovation investments of firms and governments and the public's awareness regarding the importance of environmental innovations.Practical implicationsThis research provides important implications for policymakers in promoting environmental innovations.Originality/valueThe study is the first to empirically examine economic complexity performance's influences on environmental innovation implementation. It is also the first to investigate the importance of institutional quality in enhancing the influence of economic complexity on environmental performance.

Nexus between green finance, environmental degradation, and sustainable development: Evidence from developing countries

In this study, we aim to investigate the impact of green finance and environmental degradation on sustainable development in developing countries. We use a panel dataset for 42 developing countries for the 2000–2020 period employing the panel fixed effect estimation. Adjusted net savings are used to measure sustainable development, green credit, green securities, and green investments are applied as proxies for green finance, and carbon (CO2) emissions are used to indicate environmental degradation. The analysis reveals that green finance has a positive and significant impact, whereas environmental degradation exerts a negative and significant impact on sustainable development in developing countries. Further, we find the same outcomes by employing the system-generalized method of moments estimation, confirming the robustness of our results. Our study has implications for regulators and policymakers seeking to achieve sustainable development in developing countries. Our findings will be useful for designing policies related to green financing and investment in developing nations.

The impact of economic sanctions on foreign direct investment: empirical evidence from global data

PurposeThis study investigates the impact of global economic sanctions on foreign direct investment (FDI).Design/methodology/approachData were gathered from several sources, including the United Nations Conference on Trade and Development, the Global Sanction and the World Bank database, to build a dataset that consists of 172 countries during the period 2003–2019. The panel ordinary least square with a fixed-effects estimator was exploited to achieve the research objective.FindingsThe research findings reveal that sanction exerts a detrimental effect on the total inflows of FDI and its components. Regarding different types of sanctions, while military and trade sanctions have little or even no impact on greenfield investment, they have more adverse and sizable effects on cross-border mergers and acquisitions (M&As). The authors further show that sanctions exert devastating influences through the infrastructure and economic development channels.Practical implicationOverall, this study implies that a closer look at particular types of FDI is required when implementing policies as different types of FDI may be affected differently by changes in the economy, such as economic sanctions.Originality/valueThis paper is the first empirical study that critically investigates the impact of sanctions on the total inward FDI flows and its two components: greenfield investment and cross-border M&As. It then explores how the sanction–FDI nexus varies depending on several country-level economic factors to understand better how sanctions and different types of sanctions are related to international trade and relations.

Unleashing the Moderating Influence of Firms’ Life Cycle Stages and National Income on Capital Structure Targeting Behavior: A Roadmap towards Sustainable Development

Firms adjust their capital structures to avoid financial distress and bankruptcy to sustain in the market. Asian firms have significantly different financial patterns than their USA and European counterparts. The moderation model gains a better understanding of the relationship between the model variables. We tested the moderating roles of life cycle stages and macro-economic factor gross national income per capita to find their moderating impacts on the speed of adjustment towards target capital structures of Asian manufacturing firms from 2010 to 2018. Our sample of manufacturing industries comes from the eleven Asian economies. We used the dynamic GMM model to estimate moderating impacts and applied the pooled OLS and fixed effect estimations to test the validity of the coefficient of lagged leverage. We find that life cycle stages have positive moderating impacts, and different gross national incomes per capita have no significant effects in adjusting the capital structure. We test the combined moderating impacts of the life cycle and gross national income by applying the full model. The results reveal that moderator variables significantly impact adjusting the target capital structure. From the policy perspective, it is recommended that investors should consider the firms’ life cycle stages and per capita income of the economy in making their international investment portfolios. The government should ensure requisite finance for firms at subsidized interest rates to financially support them at critical stages like introduction and decline.

Happiness in the Daily Socio-Cultural Integration Process: A day Reconstruction Study among American Immigrants in Germany

Many immigrants struggle to integrate into host societies, despite the frequent long-term benefits of integration for immigrants and host societies. This article aims to increase understandings of immigrants’ experiences and obstacles in the daily socio-cultural integration process by examining the understudied impact of daily integration behaviors on momentary happiness. The daily experiences of 213 immigrants from the United States in Germany were captured, using a day reconstruction method. Our panel fixed-effects estimates show that immigrants who were not fluent in the host country's majority language generally felt happier when communicating in their mother tongue, as opposed to the majority language. Moreover, interacting with majority group members negatively affected the momentary happiness of less culturally integrated immigrants. By contrast, socio-cultural integration related positively to immigrants’ enduring happiness. Our results suggest that socio-cultural integration is an investment involving short-term costs to happiness, with important daily obstacles being the cost to momentary happiness of speaking the majority language and, to a lesser extent, interacting with majority group members. We argue that integration behaviors’ short-term costs also occur in many other migration contexts. The revealed short-term costs can increase understandings of immigrants’ integration struggles and related outcomes, including segregation and loneliness, and decreasing the costs may improve socio-cultural integration trajectories.

The China effect on the productivity in Nordic countries

Using a linear panel data model with a fixed-effect estimator, this article investigates the causal effect of the growing use of Chinese intermediates on the labour productivity growth in Nordic manufacturing production processes. The main result – based on changes within more than 70 global value chains during the period 2000–2014 – is that the effect is positive and economically relevant. This productivity effect exists before and after the financial crisis, in all Nordic countries, and is well-spread among the sub-sectors of the manufacturing industry. The effect is mainly caused by reduced employment, not increased value added. This employment effect appears both in the manufacturing sub-sectors themselves and along their domestic supply chains. Finally, China does not seem to be special: the productivity effect of the growing use of Eastern European intermediates is equally pronounced.

The two-way Mundlak estimator

Mundlak shows that the fixed effects estimator is equivalent to the random effects estimator in the one-way error component model once the random individual effects are modeled as a linear function of all the averaged regressors over time. In the spirit of Mundlak, this paper shows that this result also holds for the two-way error component model once the individual and time effects are modeled as linear functions of all the averaged regressors across time and across individuals. Wooldridge also shows that the two-way fixed effects estimator can be obtained as a pooled OLS with the regressors augmented by the time and individual averages and calls it the two-way Mundlak estimator. While Mundlak used GLS rather than OLS on this augmented regression, we show that both estimators are equivalent for this augmented regression. This extends Baltagi’s results from the one-way to the two-way error component model. The F test suggested by Mundlak to test for this correlation between the random effects and the regressors generate a Hausman type test that is easily generalizable to the two-way Mundlak regression. In fact, the resulting F-tests for the two-way error component regression are related to the Hausman type tests proposed by Kang for the two-way error component model.

Moderating Impacts of Education Levels in the Energy–Growth–Environment Nexus

The world’s environment has deteriorated significantly over the years. Pollution’s impact on the ecosystem is undeniably alarming. Many factors have been found in the literature to impact environmental pollution. However, there is a dearth of literature on the impacts of education levels on environmental pollution. This study, therefore, examines the effects of education levels and their moderating impacts on the energy–growth–environment nexus. Fundamentally, the study investigates the effects of economic growth, natural resources, and the marginal effects of energy consumption on environmental pollution at various levels of education in Africa from 1990 to 2017. The cross-sectional dependence test, unit root test, cointegration test, fixed effect estimation, Driscoll–Kraay standard errors, fully modified least ordinary least square estimator and dynamic ordinary least square estimator are employed for the analyses. The findings reveal that education increases environmental pollution and that the marginal impacts of energy consumption at various education levels adversely impact environmental pollution, implying that increased school enrollments exacerbate the adverse effects of energy consumption. The findings also show that economic growth, population, and trade openness degrade the environment, whereas natural resources promote environmental sustainability. We deduce several policy implications to improve environmental quality in Africa based on the findings.

Finding Integrated Schools? Latino Families Settle in Diverse Suburbs, 2000–2015

Diverse Latino families continue to settle in suburbs, hunting for better neighborhoods and educational opportunities. But do they discover more integrated schools relative to segregated city schools? We find that Latino children attending suburban elementary schools were exposed to a greater share of White peers nationwide between 2000 and 2015 than were Latinos attending urban schools. But exposure to White peers in suburbs declined on average during the period. Demographic forces within suburban districts, especially rising family poverty, contribute to worsening segregation of Latino children, as do institutional features. Districts enrolling fewer children and increasing spending per pupil remained more integrated during the period, as identified by two-level fixed-effect (Mundlak) estimation. Many heavily White districts served growing shares of Latino children without losing White families.

Exploration of parent-reported family meal dinner characteristics to inform a definition of family meals

ObjectiveTo examine parent-reported key family meal characteristics to advance the conceptualization of how parents perceive family meals to inform public health interventions and clinical practice. DesignCross-sectional study design using ecological momentary assessment (EMA) and online survey data from a racially and ethnically diverse population. ParticipantsParent/child dyads (N = 631) with children ages 5–9 years old from diverse, low-income households. AnalysisMulti-level logistic regression, conditional fixed effects estimators and multi-level logistic models with inverse probability weights. ResultsCharacteristics of meals that parents considered family meals (N = 3328) included: homemade, prepared by the caregivers, eaten at home (table/counter), most of the nuclear family gathered, having a conversation and an enjoyable atmosphere (p < 0.001). Characteristics of meals that parents deemed as non-family meals (N = 562) included: watching TV/tablets, non-family members joining, chaotic/rushed atmosphere (p < 0.001). Conclusions and implicationsParents consider family meals to be meals that take place at home around a table/counter, with homemade food prepared by the caregivers, and most family members gathered enjoying a conversation without other distractions. Study findings indicated that parents endorse specific characteristics as key for defining what "counts" as a family meal. These findings can be used by clinicians as recommendations for improving one's family meal experience and by future research as the basis for intervening on family meal characteristics and standardization of a definition of family meals.

Does Public Spending Trigger Agricultural Productivity Growth in Africa?

ABSTRACT Enhancing agricultural productivity growth is a key step to improving competitiveness and eradicating poverty in rural areas in developing countries. While the Comprehensive African Agricultural Development Program (CAADP) recommended increased public spending in agriculture to induce productivity growth, the extent to which expenditures affect food productivity remains an empirical question. To address this concern and provide policymakers with quantitative evidence, the authors assess the effect of two government-spending measures: agriculture budget share (BS) and research share (RS) of agricultural gross domestic product (GDP) on agriculture total factor productivity growth (TFPG) in Africa. They use a panel fixed-effect estimator to control for the country-specific characteristics in twenty-eight African economies from 1991 to 2012. They find marginal impact of approximately 6.77% of RS on TFPG after every seven years. However, the cumulative marginal impact of BS on TFPG is estimated at 7.21% over the seven years following budget allocation. These findings suggest that a BS of 14% and an RS of 15% are required for a country to double its TFPG in the following eight years. Therefore, an additional and continuous investment in research and development is required for significant productivity growth, especially in sub-Saharan Africa.

Which Decision Theory Describes Life Satisfaction Best? Evidence from Annual Panel Data

We use an annual household panel to conduct a comparative analysis of which decision theory explains life satisfaction better. We consider expected utility theory and prospect theory. We consider the effects of three domains on life satisfaction: income, health, and (un)employment. Using a fixed effects estimator we find that life satisfaction contains features of both expected utility theory and prospect theory. However, the elements of expected utility theory are stronger predictors of life satisfaction. Life satisfaction depends positively on income, good health, and employment. It also depends positively on income and employment improvements, however the reverse is true for health improvements. Life satisfaction is concave in income gains and convex in income losses, and it exhibits loss aversion in income and employment status, but not in health. The results suggest that life satisfaction is best described by expected utility theory, but also contains some aspects of prospect theory.

Short Guides to Static Panel Data Regression Model Estimator

This paper elaborates on the use of three regression model estimators under the classification of static panel data. In order to select the best regression model estimator for panel data analysis, the researcher should focus on conducting several tests to avoid bias in the estimation results. The Breusch Pagan Lagrangian Multiplier test (Breusch Pagan test) is a simple test carried out in the panel data analysis to check for heteroscedastic disturbances in the linear regression model in making the decision to choose whether Pooled Ordinary Least Square or Random Effects. If the Breusch Pagan test shows the rejection of the null hypothesis, it indicates that the Random Effect model is more appropriate than Pooled Ordinary Least Square because the data have a panel effect (unobserved heterogeneity). The panel effect should be checked using the Hausman test in order to identify whether the effects are correlated or uncorrelated with the regressors. In the case of rejection of the null hypothesis, the Fixed Effect estimator is a more appropriate or unbiased estimator to analyze the data.

Estimation of green bond premiums On the Chinese secondary market

Green bonds have gained prominence on China's capital market as tools that help to fuel the transition to a climate-resilient economy. Although the issuance volume on the Chinese green bond market has been growing rapidly in recent years, the impact of the green label on bond pricing has not been studied adequately. Therefore, this paper investigates whether this newly developed financial instrument offers investors in China an attractive yield compared to other equivalent conventional bonds. By matching green bonds with their conventional counterparts and subsequently applying a fixed-effects estimation, our empirical results reveal a significant green bond yield premium of 1.8 basis points (bps) on average on the Chinese secondary market. As compared to Climate Bond Initiative (CBI) certified green bonds, we find that investors are more willing to accept lower yields (pay higher prices) to include People's Bank of China (PBOC) certified green bonds into their portfolio management. Thus, we argue that Chinese green investors prefer PBOC certified green bond over CBI certified green bonds on the Chinese market. Driven by pro- environmental preference, investors are also found to be willing to pay a higher price for green bonds issued by environmental, social and governance (ESG) performance-rated issuers. Our results point to some practical implications for investors and policymakers.

The Impact of Digital Transformation on Corporate Sustainability: Evidence from Listed Companies in China

This study investigated whether digital transformation improves corporate sustainability. In particular, we focused on the mediating effects of operation efficiency and corporate innovation in the ability of digital transformation to enhance corporate sustainability. A novel analytical framework was constructed incorporating the resource-based view (RBV), institution-based view (IBV), enterprise efficiency theory and dynamic capability theory to explain the relationship between digital transformation and corporate sustainability. Fixed effects estimation and the 2SLS method were used to test our analytical framework based on Chinese A-share listed companies over the sample period, 2014–2020. We found that digital transformation is an important means to improve corporate sustainability, but this relationship is impacted by the heterogeneous factors of ownership, industry and location. At the end of the paper, implications, limitations and future research directions are discussed.

Does the demographic dividend with human capital development yield an economic dividend? Evidence from Central Asia

ABSTRACT Both fertility and mortality rates are declining in the five Central Asian countries, so far resulting in an increasingly working-age population. The main question is whether these countries can benefit from this demographic transition while having different economic structures and diverse ethnicities. Our article shows the importance of demographic, economic, and human capital indicators and the influential role of governance indicators such as the Political Corruption Index and Egalitarian Democracy Index for economic growth. Based on the data from 1991 to 2018, the analysis has been conducted by employing fixed effect estimation with Driscoll-Kraay standard errors. The findings indicate that human capital with proper education and an appropriately absorbed labour force does have a more powerful effect on the demographic benefit. In addition, improving the quality of governance has a significant impact on economic growth.

Handling multi-collinearity using principal component analysis with the panel data model

When designing a statistical model, applied researchers strive to make the model consistent, unbiased, and efficient. Labor productivity is an important economic indicator that is closely linked to economic growth, competitiveness, and living standards within an economy. This paper proposes the one-way error component panel data model for labor productivity. One of the problems that we can encounter in panel data is the problem of multi-collinearity. Therefore, multi-collinearity problem is considered. This problem has been detected. After that, the principal component technique is used to get new good unrelated estimators. For the purposes of our analysis, the multi-collinearity problem between the explanatory variables was examined, using principal component techniques with the application of the panel data model focused on the impact of public capital, private capital stock, labor, and state unemployment rate on gross state products. The analysis was based on three estimation methods: fixed effect, random effect, and pooling effect. The challenge is to get estimators with good properties under reasonable assumptions and to ensure that statistical inference is valid throughout robust standard errors. And after application, fixed effect estimation turned out to play a key role in the estimation of panel data models. Based on the results of hypothesis testing, the real data result showed that the fixed effect model was more accurate compared to the two models of random effect and pooling effect. In addition, robust estimation was used to get more efficient estimators since heteroscedasticity has been confirmed