Fixed Effects Panel Data Model Research Articles

Does carbon efficiency improve financial performance? Evidence from Chinese firms

In response to the global climate change, the actions of Chinese government to cut down carbon emissions have brought great risks and opportunities to firms. Considering that the production process with energy consumption is inevitably accompanied by carbon emissions, this paper uses SBM-DEA model with undesirable output to evaluate firms' carbon efficiency from production perspective. Then we use the fixed-effect panel data model to study the relationship between carbon efficiency and financial performance of Chinese firms. Furthermore, we analyze whether the resource efficiency has a moderation effect on the relationship between carbon efficiency and financial performance. The results show that the carbon efficiency has a significantly positive effect on the total asset turnover (short-term operating capacity) and Tobin's Q (long-term market value) of Chinese firms, while impacts the total risk (the combination of systemic and non-systemic risks) negatively and significantly, especially for firms in carbon-intensive industries. With the improvement of resource efficiency, the impact of carbon efficiency on financial performance begins to weaken. The carbon efficiency and financial performance have monotonic effect, while resource efficiency and carbon efficiency have interactive effect. Overall, we prove that high carbon efficiency can improve the financial performance, as well as reduce the risks of firms. Based on the results, we make some suggestions for firms to improve both the carbon efficiency and the financial performance.

Identifying causal changes in landscape greenness with very high-resolution airborne multispectral imagery and a panel data model

To effectively manage urban environmental systems, interventions on private lands may sometimes be necessary. This is illustrated in many water districts where water agencies run programs that provide incentives to landholders to change their landscaping to meet the water agency’s management goals. It is difficult to monitor, track, and evaluate landscape change programs on private land, however. To most efficiently do so, very high-resolution, time-series measurements of urban landcover would be useful, but such data is often unavailable. This study evaluates how private urban landscape change is represented in the highest resolution, publicly available, multispectral data product distributed in the United States. The study focuses on residential parcels that participated in a lawn replacement rebate program run by the East Bay Municipal Utility District, a water agency in California. Each parcel has a known quantity of turfgrass converted to drought-tolerant landscaping. The study asks if Normalized Differential Vegetation Index (NDVI) values derived from National Agriculture Imagery Program (NAIP) data can be used to detect participation in a lawn replacement program at the parcel-level. While the NAIP data product has substantial error in a time-series and urban context, this study finds that approaching change detection using a fixed effect panel data model accommodates error, making it possible to identify NDVI change. With control groups defined by matching and weighing with Covariate Balancing Propensity Scores, results indicate that observed browning at the parcel-level can be causally attributed to participating in the lawn replacement program. This ability to detect small, causal changes in a heterogenous environment opens possibilities for monitoring and evaluating programs acting on private urban landscapes, contributing to more effective and efficient design, pricing and implementation.

Impact of Supply Chain Performance on Firms’ Export Capability: Development of a Statistical Model

The purposes of this article are to establish the crucial indicators of supply chain performance (SCPI) impacting firms’ export performance, revealing its unique characteristics, and assess the effects of these SCPIs on the export capability of the firms. This article develops a statistical model, involving how critical SCPIs can influence firms’ export performance. The developed model is then empirically validated using top 53 firm-level data, based on market share, from the Indian pharmaceutical industry, taken for 10 years. The randomized complete block design approach is employed to confirm the variation of export intensity across firms and time. A panel data fixed-effects model is developed, associating critical SCPIs with export intensity to understand their impact on export performance. Finally, bootstrap is applied as a cross-validation procedure to carry out model authentication. This article contributes to obtaining crucial SCPIs and their impact on firms’ export competitiveness. It has revealed that firms’ raw material import efficiency, working capital efficiency, asset management efficiency, research and development (R&D) capability, and the total cost to serve have a significant impact on the firms’ export capability. The proposed model can help firms make appropriate decisions about different influencing parameters of supply chain performance to improve their export competitiveness.

Pandemic Severity, Policy Stringency, and Tourism Performance: A Global Analysis

This paper investigates the impact of the COVID-19 pandemic and its associated policy effects on global tourism performance. Using daily data from 117 countries between January 23, 2020 and June 5, 2021, we applied a fixed-effects panel data model to investigate the impact and its moderators. Results show that COVID-19 cases had a significantly negative effect on tourism revenue and pricing. Specifically, a 10% increase in COVID-19 cases led to a 0.490%, 0.103%, and 0.388% decline in RevPAR, ADR, and occupancy change, respectively. Furthermore, degree of dependence on tourism, and economic support policies moderated this effect. Consequences related to revenue and demand were more remarkable for luxury tourism products than economic ones. Geographical and temporal heterogeneity were also noteworthy, and the impact of pandemic severity on revenue and demand was highly notable in certain periods, such as April and May 2020 and January to mid-March 2021. Lastly, implications are provided.

Equality, freedom and democracy: how important are they for environmental performance?

The complexity of the relationship between society and the environment is recognized by researchers and practitioners as a major challenge. This article examines how the type of political regime, the degree of political freedom and civil rights, and the level of income concentration relates to environmental performance as measured by the Environmental Performance Index (EPI). The analysis is based on a sample of 161 countries and covers the period 2007-2016, using a fixed effects panel data model. Our findings suggest that democracy as a political regime does not necessarily induce greater commitment to environmental issues. Lower income inequality offers the same results. However, a positive association was found between the expansion of rights and freedoms and the EPI, suggesting that freer countries tend to have better environmental performance. Given the multiplicity of profiles in terms of the nature and depth of democracy and inequality, our study suggest parsimony with more generalist analyses.

Effects of Vertical Integration Reform on Primary Healthcare Institutions in China: Evidence From a Longitudinal Study.

Integrated care is a global trend in international healthcare reform, particularly for piloting vertical integration involving hospitals and primary healthcare institutions (PHIs). However, evidence regarding the impact of vertical integration on primary healthcare has been mixed and limited. Our study aims to evaluate the empirical effects of vertical integration reform on PHIs in China, and examines variations across integration intensity (tight integration vs. loose collaboration). This study used a longitudinal design. The time-varying difference-in-difference (DID) method with a fixed-effect model for panel data was adopted. A total of 370 PHIs in the eastern, central, and western areas of China from 2009 to 2018 were covered. Outcome measures included the indicators at three dimensions regarding inpatient and outpatient service volume, patient flow between PHIs and hospitals and quality of chronic disease care (hypertension and diabetes). Significant increases in absolute (the number) and relative (the ratio between PHIs and hospitals) volume of inpatient admissions have been found after reform under tight integration, peaking at 183% and 15.0% respectively, in the third reform year. The quality of hypertension and diabetes care (by indicators of control rate of blood pressure and blood glucose) showed significant improvements under both types of vertical integration after reform. It was much more distinct for the PHIs under tight integration, which had the most significant increase of 34.0% and 22.8% under tight integration for the control rate of hypertension and diabetes compared to the peak of 21.2% and 22.1% respectively under loose collaboration. Our findings suggest that vertical integration (especially tight integration) in China significantly contributed to strengthening primary healthcare in terms of inpatient services and quality of hypertension and diabetes care, providing empirical evidence to other countries on integrating primary healthcare-based health systems.

Effects of Economic Policy Uncertainty on Manufacturing Structural Upgrading: Evidence from China

Manufacturing is one of the drivers of China’s growth, realizing structural upgrading is vital to achieve high-quality economic development during periods of economic policy uncertainty. Based on firm-level and province-level panel data from 1997 to 2018, this paper used a fixed effect panel data model and panel quantile regression model to investigate the effect of economic policy uncertainty on structural upgrading in manufacturing. The findings indicate that the effect of economic policy uncertainty on structural upgrading in manufacturing is significantly positive and great in regions at advanced stages of manufacturing structure. The discussion about the results suggests that the mechanism of economic policy uncertainty affecting structural upgrading in manufacturing operates through pushing the manufacturing industry to implement service transformation strategies along with vertical integration.

Striking a Balance During Economic Crisis: An Empirical Application of Strategic Balance Theory

This paper examines the generalizability of the strategic balance theory in the context of economic crisis by empirically investigating the relationship between strategic similarity and firm performance during economic recessions. Analyzing the WRDS Compustat data for the U.S. manufacturing firms from 1984 to 2019 by using a firm-specified fixed effect panel data model, we show that the strategic balance mechanism is strengthened in the context of economic crisis. We also find that the strategic balance mechanism is weakened for technological leaders. This study contributes to the current literature by investigating the boundary conditions of the strategic balance theory and revealing how the strategic balance mechanism changes in different contexts.

Information and Communication Technologies in food and accommodation sector in EU countries: Sticker or challenge for tourism development?

The article discusses the use of Information and Communication Technologies (ICTs) in the food and accommodation sector in the context of tourism development in EU countries. The paper is of a review and research nature. The purpose is to define a measure of the level of ICTs use in food and accommodation enterprises in EU countries, to consider the relation between proposed measure and chosen macroeconomic indicators, and finally to identify the impact of ICTs use on the development of this sector.To attain the aim of this research, a critical analysis of literature as well as desktop research has been carried out, the latter drawing on the data of Eurostat referring to companies from accommodation and food service activities. For the analysis, data for 26 EU countries over two time periods 2012–2019 and 2012–2017 were used. To assess the diversification of the level of ICTs use in the analysed sector, Hellwig's linear ordering method was utilized. Then, a fixed effects panel data model was used in order to examine the impact of the level of ICTs use on sector development, where the financial situation of enterprises (gross operating surplus) was assumed as the measure of the sector's growth.The values of the constructed taxonomic measure of development indicate the different levels of ICTs use by food and accommodation enterprises between countries. The estimated two-way panel data model confirmed a significant positive impact of ICTs use on gross operating surplus with a time lag of two years.

Cereal Prices and Child Undernutrition in Ethiopia

This paper looks at how changing cereal prices affect child undernutrition in Ethiopia. It derives height for age (stunting) and weight for height (wasting) as indicators of child undernutrition from the two most recent years of the Living Standards Measurement Survey and utilises market prices for key cereals, teff, wheat, and maize in enumeration areas across all regions of the country. Using a panel data fixed effects model, the analysis finds that, contrary to previous studies, rising cereal prices are positively associated with improved child stunting rates for children between ages 6 months and 5 years. There is no evidence to suggest that cereal prices have a significantly greater impact on height for age for children that come from households who are net sellers of these crops. Cereal prices do not appear to be associated with wasting, which is a short-term negative health outcome.

Orta Doğu ve Kuzey Afrika'da Kapsayıcı Büyüme: Küresel Finansal Krizden Öncesi ve Sonrası

In this study the macroeconomic fundamentals and structural factors which affect inclusive growth in 16 MENA countries before and after the Global Financial Crisis are investigated. A panel data fixed effects model is used in two time periods: 1996-2007 and 2008-2016. A measure of inclusive growth is defined by integrating economic growth and income inequality. In this way, the relative impacts of GDP per capita growth rate and change in Gini coefficient are accounted for. A wide range of factors such as environmental degradation, macroeconomic stability, fiscal discipline, globalization, human capital, life expectancy, and technological development appear to significantly affect inclusive growth performance in the MENA region.

Legislative budgetary power and fiscal discipline in the euro area

PurposeThe objective of this study is to understand the budgetary role of national legislatures in euro area (EA) countries and to analyse implications for fiscal discipline.Design/methodology/approachBuilding on the budget institutions literature, a legislative budgetary power index for all the 19 euro area (EA) countries is constructed using Organisation for Economic Co-operation and Development (OECD) and European Commission data as well as data generated from questionnaires to national authorities. A two-way fixed effects panel data model is then used to assess the effect of legislative budgetary power on the budget balance in the EA during 2006–2015.FindingsOverall, in the EA, formal legislative powers vis-à-vis the national budgetary process are weak, but there is more legislative involvement in Stability and Growth Pact (SGP) procedures, and legislative budgetary organisational capacity is generally quite good. In contrast to the traditional view in the budget institutions literature, this study’s empirical findings show that strong legislative budgetary power does not necessarily result in larger budget deficits.Research limitations/implicationsData on legislative budgeting were available from different sources, and time series data were very limited.Practical implicationsThere is scope to improve democratic legitimacy of the national budgetary process in the EA, without necessarily jeopardising fiscal discipline.Originality/valueThe constructed legislative budgetary power index covers all the 19 EA countries and has a broad scope covering various novel institutional characteristics. The empirical analysis contributes to the scarce literature on the impact of legislative budgeting on fiscal discipline.

Developing a tailored strategy for mobile applications’ adoption across diffusion levels: A panel data analysis

This paper proposes that there should be contextual strategy development of applications’ diffusion based on the stage of mobile applications (apps) adoption already reached in a country. This is because as apps diffusion grows, the demand and supply constraints challenging the adoption of apps will change accordingly. A total of 77 countries are categorized into three clusters, Initial, Fast-Adoption, and Maturity, grouped by their adoption rates and the speeds over four-years from 2014 to 2017. With pooled and fixed-effect panel data models, this paper examines which variables out of 22 independent variables are effective in enhancing apps adoption globally. Further, by interacting two dummy clusters, Initial and Maturity with determinant variables, the study identifies the differential policy effectiveness of each determinant factor on apps adoption. The paper concludes that the three stages of apps diffusion levels have their respective effective strategy choice sets: 11 for Initial stage, 12 for Fast-adoption stage, and 13 for Maturity stage, suggesting that countries should develop their mobile apps inclusiveness strategy tailored to their context of apps adoption.

A micro-based approach to evaluate the effect of water supply on health in Uganda

• We merge individual panel datasets with sub-county level administrative data on water supply projects. • We estimate fixed-effects panel regressions to account for spatial and temporal variation at the sub-county level. • Provision for improved water is found to have a significant effect on water usage and water collection times. • No statistically significant effects of improved water are found for reported diarrhoea incidence. • Our approach is a cost-effective means of evaluating development projects. This paper proposes a micro-based approach to investigate the impact of improved water provision on individual health outcomes in rural Uganda. We merge household and individual panel datasets with sub-county level administrative data on water supply projects. Our approach allows us to estimate fixed-effect panel data models which use temporal and spatial variation at the sub-county level as identifying variation. We find evidence that the installation of improved water sources leads to higher reported improved water usage, and shorter water collection times. However, increasing the sub-county rate of improved water sources per capita does not seem to be sufficient to lead to a statistically significant effect in the likelihood of individuals suffering from symptoms of illness associated with inadequate water supply. We argue that our micro-based approach provides a cost-effective means of evaluating development projects. The approach is scalable, i.e. it can be applied to other settings and countries.

Estimating the marginal cost of reducing power outage durations in China: A parametric distance function approach

The increasing penetration of intermittent renewables and the accelerated climate change are challenging the power system operation in China, and understanding the cost of reducing power outage durations is essential in supporting the equipment maintenance, infrastructure investments and regulation policies. Therefore, this study first uses production theory combined with a parametric distance function approach to estimate the marginal costs (MCs) of reducing power outage durations by 1 h. Then, we establish a fixed-effects panel data model to investigate the impacts of different environmental factors on the estimated MCs. Finally, the estimated MCs are applied to the evaluations and designs of interruption compensation prices in the demand response mechanism. The significant findings are that: (1) The national MC shows an increasing trend during the period from 2002 to 2017 in China, ranging from 1.27 billion yuan/hour to 11.63 billion yuan/hour. (2) The MCs vary substantially among different provinces, and provinces with better reliability levels will have higher MCs. (3) The current compensations for power outages are only about 6% to 61% of the estimated MCs, indicating that grid companies would like to pay for the compensations rather than to enhance the system reliability from the supply side.

Adversarial Inference Is Efficient

We study properties of the adversarial framework, introduced in Kaji, Manresa and Pouliot (2020). We show that the adversarial inference with an oracle classifier is statistically efficient. In addition, we study the finite sample properties of the adversarial estimation framework for the autoregressive parameter of a linear dynamic fixed effects panel data model with Gaussian errors. Unlike maximum likelihood, but similarly as other minimum distance estimators, the adversarial estimators do not suffer from the incidental parameter bias. In our simulations, using a one-hidden-layer neural network as discriminator delivers the estimates with smallest root mean squared error.

Health Disturbances of Negative Nutritional Shocks

The Fetal Origin Hypothesis show that the prenatal development period is a critical period for birth outcomes. Applying a panel data fixed effect model and using the universe of birth records in the US, I find that exposure to the holy month Ramadan, during which Muslim mothers fast for the whole day, during prenatal development has negative birth outcomes. Exposure to a full month of fasting is associated with 96 grams lower birth-weight. These results are robust across specifications and do not appear to be driven by mothers’ selective fertility.

Pengaruh Female Director, Institutional Ownership, Dan Profitability Terhadap Intellectual Capital Disclosure

This study has purpose to determine the influence of female directors, institutional ownership, and profitability on intellectual capital disclosure. This study uses manufacturing companies listed on the Indonesia Stock Exchange in 2016-2018. This study used a purposive method in sampling and 39 companies was obtained. This study uses a fixed effect panel data model after conducting a chow test and a hausmann test. This study uses E-views 10 in data processing. The results of this study is that female directors have a positive influence on intellectual capital disclosure, while institutional ownership and profitability do not have an influence on intellectual capital disclosure.

Pengaruh Female Director, Institutional Ownership, Dan Profitability Terhadap Intellectual Capital Disclosure

This study has purpose to determine the influence of female directors, institutional ownership, and profitability on intellectual capital disclosure. This study uses manufacturing companies listed on the Indonesia Stock Exchange in 2016-2018. This study used a purposive method in sampling and 39 companies was obtained. This study uses a fixed effect panel data model after conducting a chow test and a hausmann test. This study uses E-views 10 in data processing. The results of this study is that female directors have a positive influence on intellectual capital disclosure, while institutional ownership and profitability do not have an influence on intellectual capital disclosure.

Social Insurance, Welfare Codes, and the Spread of Covid-19

This paper explores disparities in the effect of pollution on confirmed cases of Covid-19 based on counties’ socioeconomic and demographic characteristics. Using data on all US counties on a daily basis over the year 2020 and applying a rich panel data fixed effect model, we document that: 1) there are discernible social and demographic disparities in the spread of Covid-19. Blacks, low educated, and poorer people are at higher risks of being infected by the new disease. 2) The criteria pollutants including Ozone, CO, PM10, and PM2.5 have the potential to accelerate the outbreak of the novel coronavirus. 3) The disadvantaged population is more vulnerable to the effects of pollution on the spread of coronavirus. Specifically, the effects of pollution on confirmed cases become larger for blacks, low educated, and counties with lower average wages in 2019.