Fixed Effects Panel Data Model Research Articles

Cloud computing in the Polish public administration: current state and development prospects

The EU's goal of digital transformation of the economy and society requires increased participation of businesses and citizens. This cannot be achieved without a high level of digitalization in public administration. The paper aims to examine the scale and determinants of cloud computing (CC) adoption in Polish public administration units from 2018 to 2021. A comparison was conducted between the level of adoption of cloud services in the public administration sector and in the enterprise sector in Poland. Next, a synthetic taxonomic measure of technology development was determined so as to assess the differentiation of cloud computing usage in the country's voivodeships. Finally, a two-way fixed effects panel data model was estimated to identify the determinants of the level of CC implementation in public administration. The results showed a wide variation in the adoption of cloud solutions between voivodeships (Polish provinces). The study found a significant correlation between the CC use in public administration and the level of economic development of individual voivodeships, as well as IT training for employees, but no correlation with the level of CC use in enterprises.

Decadal analysis of measles epidemiological data in India (2011–2020)

BackgroundDespite India being one of the largest contributors to the measles burden, crucial epidemiological information is significantly lacking. We have analyzed the national-level representative data between 2011 and 2020 to estimate the national- and state-level incidence, first dose vaccine coverage, and mortality; and developed a prediction model to examine the trend of the disease.MethodsWe extracted the Health Management Information System (HMIS) for monthly aggregated measles cases, deaths, and child immunization (9–11 months) for first dose measles vaccine coverage across all states & Union Territories (UT). Population information & projections were extracted based on Census 2011. A multilevel fixed effect panel data model was used to predict measles incidence rate, assuming measles vaccination coverage as a predictor while accounting for time fixed effects.ResultsTotal 558,536 measles cases and 4209 measles deaths were reported in India between 2010 and 2020. The incidence rate was highest in 2013 (628.8/million population), followed by a significant decline to reach 52.0/million in 2020. Measles vaccination coverage for the first dose was 84.1% in 2011 to 91.3% in 2019. Higher vaccination coverage was significantly correlated (r = 0.7, p = 0.02) with decline of measles incidence rate. The case fatality rate (CFR) was least in 2014 (0.13%) but upsurged consistently reaching to 3.3% in 2020. The predictive model indicates that with a first-dose vaccine coverage of 93.5%, and keeping other factors constant, the national measles incidence is projected to reach zero by 2025.ConclusionMeasles incidence is declining in India due to higher vaccination coverage, yet the rise in death rates emphasizes the need for continued collaborative efforts to achieve a measles-free nation.

Environmental, social, and governance performance as an influencing factor of financial sustainability: Evidence from the global high‐tech sector

AbstractThe corporate sector strives to improve its environmental, social, and governance (ESG) performance to transition from short‐term to sustainable long‐term profit maximisation. This study thus explores the impact of ESG performance on the financial sustainability (FS) of a sample of the top 100 global high‐tech firms. Specifically, we employ the two‐step generalised method of moments to control for endogeneity bias and a panel data fixed effects model to control for unobserved heterogeneity. Empirical findings reveal that overall ESG performance has a statistically negative association with the FS of global high‐tech firms. Individual pillar‐wise analysis reveals that the environmental and social (governance) pillar has a negative (positive) association with the FS of the sampled firms. This result proves that each ESG pillar exerts varying effects on corporate performance indicators. Overall, the results provide empirical evidence that could help policymakers devise policies for investing optimally in ESG indicators to spur corporate FS.

Cash holding, economic uncertainty and investment: Evidence from ASEAN countries

This research observes the effect of uncertainty on corporate cash holding. Uncertainty drives up asymmetric information problems, increasing companies' external capital costs. As a result, companies prefer to accumulate cash to protect their investment capabilities in the future. The study uses a sample of non-financial public companies in six ASEAN countries, such as Malaysia, the Philippines, Thailand, Singapore, Indonesia, and Vietnam, from 2008 to 2021. The study uses a total of 34,359 firm-year observations. The research method employs a fixed-effect panel data model with Driscoll-Kraay standard errors. The findings of this study indicate that economic uncertainty can cause companies to accumulate their cash holdings. Furthermore, cash holding can reduce the impact of economic uncertainty on decreasing corporate investment decisions. This research contributes to the literature by showing the relationship between economic uncertainty, cash holdings, and corporate investment in the context of ASEAN countries.

Efficiency of public investment in education in Peru, 2016-2022: A comparative analysis by region

The study analyzes the level of technical efficiency of public investment in Education at the primary and secondary level in Peru, 2016 to 2022. Data envelopment analysis – DEA was used and for the association between the provision of resources and educational quality. the panel data fixed effects model. The results indicate that there are relative differences in efficiency between the regions, registering an average score of 49% for the primary level and 38% for the secondary level, with the most efficient being Moquegua, Tacna, Arequipa and Ica, and the least efficient being Loreto, Huánuco, Ucayali, and San Martín. From the input-output association, classroom size, infrastructure in good condition and public investment have a direct relationship, while students per teacher and per computer, the relationship is inverse with respect to educational achievement in communication and mathematics at the primary and secondary level. This suggests that inefficient regions should increase educational attainment at the primary and secondary levels by an average of 51% and 62%, respectively, while maintaining the same level of spending. Therefore, to improve their efficiency within the framework of public policies, they can adopt the management implemented by regions such as Moquegua and Tacna.

Can the Difference of the Transfer Trice of Industrial Land "Bidding, Auctions and Listings" Promote the Transformation and Upgrading of Regional Industries?

The purpose of this study is to explore the impact of the difference in the transfer price of industrial land on the regional industrial transformation and upgrading under the "bid and auction" system. Research methods: panel data fixed effect model. Research results: Improving the differentiation of industrial land transfer price is conducive to regional industrial transformation and upgrading, and this conclusion has passed a variety of robustness tests. Research conclusions: First, formulate and improve the promotion of industrial land transfer price differentiation strategy. The second is to establish and improve the enterprise entry and exit mechanism to improve the efficiency of industrial land resource allocation. The third is to further improve the secondary market trading system of industrial land, and actively explore the circulation mechanism of stock industrial land to ensure the reasonable flow and efficient use of industrial land resources.

Modelling the Effect of Police Motivating Factors on Effective Crime Management in Nigeria

This study investigates the relationship between police motivating factors' and the crime rate in Nigeria. The fixed effect panel data model with geopolitical zones and states as dummy variables results indicated the significance of motivating factors aside from logistics and insurance with multiple R-squared values of 76.65%. The random effect panel data model showed every motivating factor was significant with multiple R-squared values of 53.81%. Therefore, based on multiple R squared values, the fixed effect panel data model explained the variations in crime rate better—random effect study. Conclusively, police motivating factors have a significant impact on the crime rate in Nigeria.

Assessment of working capital management efficiency – a two-stage slack-based measure of data envelopment analysis

PurposeThis study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.Design/methodology/approachThe current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.FindingsThe results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.Originality/valueInstead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

Variable Selection for Panel Data Linear Regression Models with Fixed Effects

This paper introduces a robust variable selection mechanism for fixed effect panel data models by integrating compound quantile regression with the adjusted MIXED penalty method. Initially, forward orthogonal deviation transformation is employed to eliminate the influence of fixed effects. Subsequently, the MIXED penalty is utilized to construct a penalized compound quantile regression objective function, facilitating simultaneous estimation of regression coefficients and variable selection. This method not only effectively eliminates the interference of fixed effects but also demonstrates outstanding robustness. Its performance with limited sample sizes was validated through simulation studies, and its practical value was illustrated through application in real data analysis.

The effects of precipitation shocks on rural labour markets and migration

ABSTRACT The welfare of workers in rural areas is highly affected by agricultural output volatility, caused in part by weather shocks. A volatile source of income is an important factor in inducing migration. While the impact of rainfall shocks on migration is well studied, the channels through which these shocks affect migration are underexplored. In this paper we study the hypothesis that the labour market is an avenue that carries the effect of precipitation shocks on migration. This paper first establishes the effect of precipitation shocks on the labour market. We use individual-level data combined with station-based precipitation data of Iran at the rural-agglomeration level in a fixed-effects panel-data model to find that workers in agriculture and industry sectors decrease their hours of work in response to negative shocks. We then use a linear probability model to show that negative shocks almost double the probability of migration and labour-migration for young men in Iran. Estimations of this paper indicate that as unemployment rate in rural areas increases, migration out of those regions rises as well. Additionally, controlling for the local labour market conditions at origin captures the impact of shocks on migration, implying the labour market is a channel through which precipitation shocks affect migratory decisions.

Green finance, new infrastructure, and carbon emission performance in Chinese cities

Green finance (GF), new infrastructure (NI), and low-carbon green development play important roles in promoting high-quality economic development in China. To date, few studies have considered the relationships among GF, NI, and carbon emission performance (CEP) simultaneously. Using the panel data of 285 Chinese cities from 2011 to 2021, an improved vertical and horizontal pull-out gearing method was used to measure the GF and NI composite indices, and the CEP was measured using the slacks-based measure (SBM) non-expected output model. Using the panel data fixed-effects model and interactive effect model, it was found that both GF and NI can effectively enhance urban CEP and produce a superposition effect, promoting each other to deepen their ability to enhance the CEP. Heterogeneity analysis showed that the effects of GF and NI are more notable in eastern China, with a higher degree of marketization, policy support for the development of the digital economy, and resource-based cities. Green technological innovation, industrial structure upgrading, and resource allocation optimization are pathways for GF and NI to jointly enhance the CEP. Further analysis of the spatial system of the equation model using the generalized three-stage least squares (GS3SLS) methodology found that there were spatial interaction spillover effects among GF, NI, and CEP and that these effects were better for a local area than for the surrounding neighboring cities.

What are the main determinants of social expenditure? A panel data approach for EU and OECD countries

PurposeThe aim of this study is to analyze which socioeconomic factors (economic, demographic, and political) most commonly affect the social expenditure of the European Union (EU) and Organization for Economic Co-operation and Development (OECD) countries.Design/methodology/approachA panel data fixed-effects model is employed for 34 OECD and 23 EU countries between 2000 and 2020.FindingsResults indicate that, in all country groups, economic factors have the most significant influence on social expenditures, with income being the primary determinant, particularly in EU countries. The negative impacts of unemployment and inflation underscore the importance of counter-cyclical measures adopted by countries to maintain stability in their social expenditures. The most influential demographic factor is found as the old-age-dependency ratio. While the rule of law affects social expenditure positively, government effectiveness and female labor force participation affect it negatively. The positive effect of Konjunkturforschungsstelle (KOF) indexes shows the globalization effect, which can be attributable to the compensation hypothesis.Practical implicationsGovernments enforce inclusive and sustainable policies to boost economic activities and GDP, thus combating inflation and unemployment and regulating the labor market and socioeconomic problems about aging populations and women’s economic participation to control social expenditures. The rule of law and institutional quality will also boost economic growth.Originality/valueThis study focuses on the effects of social expenditures in a broader view within the framework of the three main factors (economic, demographic, political) and attempts to determine the key factors that account for the differences in social expenditure between the OECD and EU countries.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0384

Robust Hausman Pretest for Panel Data Model in the Presence of Heteroscedasticity and Influential Observations

The classical Hausman pretest (HT) is used to specified the right model between random and fixed effect panel data models. However, in the presence of heteroscedastic error variances and influential observations (IOs) in the data set, it may not correctly identify the right model. Therefore, this motivated us to proposed a new method termed Robust Hausman Test (RHTFIID) which employed residuals from weighted least square (WLS) instead of OLS in the construction of heteroscedasticity consistent covariance matrix (HCCM) estimator. The weighting method is based on an efficient High Leverage Points (HLPs) detection method called Fast Improvised Influential Distance (FIID) which down weight only vertical outliers and bad HLPs. The good HLPs were allowed in the estimation as they might contribute to the precision of the estimate. The result indicates that the new proposed RHTFIID outperformed the existing classical Hausman pretest by identifying the right model with and without heteroscedasticity and influential observations.

The role of intellectual and social capital in funding businesses: a cross-country analysis

ObjetivoEl estudio tiene como objetivo examinar el impacto del capital intelectual y social en la financiación de las empresas.Diseño/metodología/enfoqueUtilizamos modelos de datos de panel de efectos fijos con una muestra de 142 países de los cinco continentes durante el periodo 1998-2018.ResultadosEncontramos que el capital humano (CH), el capital relacional, el capital estructural y el capital social juegan un papel en las decisiones de los inversionistas para financiar un negocio. Encontramos que las decisiones de financiamiento de los inversionistas en los países con bajo índice de desarrollo humano se basan principalmente en la educación, mientras que las de los países con alto índice de desarrollo humano se basan principalmente en el componente de creatividad del CH y en el capital relacional, estructural y social.Limitaciones/implicaciones de la investigaciónSugerimos replicar el estudio utilizando datos a nivel de empresa dentro de cada país. Por otra parte, la búsqueda de nuevos indicadores de capital intelectual y social (aunque nuestra lista de variables es exhaustiva) tanto a nivel de país como de empresa, constituye una vía interesante para futuras investigaciones.Implicaciones prácticasLos países deben prestar atención al capital intelectual y social para fomentar la actividad empresarial. En particular, los países con bajo desarrollo humano deberían fortalecer el CH, como la tasa de matriculación escolar, con una formación empresarial temprana y aumentar las inversiones en investigación y desarrollo, mientras que los países con un alto nivel de desarrollo humano deberían seguir fomentando las alianzas estratégicas, proteger la propiedad intelectual y mantener o aumentar el nivel de confianza en el país.Originalidad/valorEl estudio contribuye a la literatura al ser el primero en explorar tal variedad de variables de capital intelectual y social desde una perspectiva a nivel de país.

The Impact of Government Subsidies and R&D Investment on the Operating Performance of New Energy Enterprises in China

This paper selects the data of listed companies of new energy enterprises in China from 2017 to 2021 for empirical analysis to explore the impact of government subsidies and R&D (research and development) investment on operating performance using the panel data fixed effects model. The results show that in new energy enterprises, R&D investment and government subsidies are positively correlated with operating performance. When R&D investment and government subsidies exist at the same time, the interaction effect triggered by the two will play a positive moderating effect on business performance, but the promotion effect of both on business performance is weakened; at this time, the government subsidies have a better promotion effect on business performance. Based on the above findings, this paper puts forward the following suggestions: the government and related departments should optimize the subsidy mode of new energy enterprises, reduce direct subsidies, and adopt indirect subsidy policies such as tax incentives, to avoid excessive dependence on direct subsidies.

Asymptotic Power of the Sphericity Test Under Weak and Strong Factors in a Fixed Effects Panel Data Model

Asymptotic Power of the Sphericity Test Under Weak and Strong Factors in a Fixed Effects Panel Data Model

Climate change and livestock production in Sub‐Saharan Africa: Effects and transmission channels

AbstractThis article assesses the effect of climate change on livestock production in Sub‐Saharan Africa, for a sample of 45 countries over the period 2000–2021. Using a two‐factor fixed effects panel data model, our results obtained by the two‐way fixed effects estimator show that (i) climate change negatively influences livestock production through high temperatures, while abundant rainfall is beneficial. (ii) Through transmission channels, we find that maize price volatility exacerbates the negative effect of rising temperatures on livestock production, while it reduces the beneficial effect of abundant rainfall. Furthermore, we find that water availability mitigates the adverse effect of rising temperatures on livestock, while enhancing the beneficial effect of rainfall on livestock. Finally, we concede that conflicts reduce the beneficial effect of rainfall on livestock production. To increase livestock production in Sub‐Saharan Africa, we recommend: the practice of pastoralism, based on the production of plants and fodder adapted to climate change, the improvement of animal nutrition, and the inclusion of breeders in the decision‐making process in the cattle industry.

ANALYSIS OF FACTORS AFFECTING COMPANY VALUE IN THE PROPERTIES AND REAL ESTATE SECTOR IN ISSI

This research aims to determine the influence of Debt to Equity Ratio, Return On Equity, Earning Per Share, Company Size and Dividend Policy either partially or simultaneously on the Value of Companies in the Properties & Real Estate Sector listed on the Indonesian Sharia Stock Index. This research was conducted using annual data from 2019 to 2021. The data used in this research is secondary data using published financial reports and accessed through the relevant company websites. The model used in this research is panel data fixed effect model, classical assumption test and hypothesis test with a significance value of 5%. The data processing was carried out using the Eviews12 analysis tool. The results show that Debt to Equity Ratio, Return On Equity, Earning Per Share and Dividend Policy partially have a significant effect on Company Value. However, partial company size does not have a significant effect on company value. Simultaneously Debt to Equity Ratio, Return On Equity, Earning Per Share, Company Size and Dividend Policy together have a significant effect on the Value of Companies in the Properties & Real Estate Sector listed on the Indonesian Sharia Stock Index.

Assessing The Impact of Airlines' Strategic Decisions in Fleet Planning on Profitability by Implementing Panel Data Analysis

This study investigates the impact on airline profitability of different types of aircraft that airlines choose as a strategic decision for their flight operations. Dataset were gathered from MIT Airline Data Project for ten airlines operating in the USA for five-year period between 2015-2019. Three different panel data models- Pooled, Fixed Effects, and Random Effects- were employed to examine the effects of aircraft types (small narrow-body, large narrow-body, and wide-body) on profitability. Plm package of R language was used to create panel data models. As a conclusion, Fixed Effects Panel Data Model proved to be the most successful in explaining profit variation in all dataset. Variables determining airline profits change according to the airline specifications and are not time-dependent.

Economic Growth, Public Expenditure, and Infrastructure on Provincial Financial Development of Nepal

Purpose: Financial development is inevitable to finance the domestic resources in the development of Nepal at the provincial level. This paper intends to evaluate the nexus of financial development at the provincial level with economic growth, public expenditure, and infrastructure. Design/Methodology/Approach: The targeted variables––financial development is a proxy by branches of banks and financial institutions and other regressors––economic growth (a proxy by annual growth in gross domestic product), public expenditure (proxied by current and capital expenditure), infrastructure (proxied by road networks, number of schools, electricity production) are considered throughout 2019 to 2023 across the seven provinces of Nepal. A fixed effect panel data model (FEM) is taken to estimate the intended outcome. To check the heteroscedasticity, autocorrelation, and cross-sectional dependency (CD), the CD test and Panel-Corrected Standard Errors (PCSE) are regressions that are also performed. Findings: The stylised facts, as a whole, indicate that the growth nexus has had a negative impact. However, infrastructure exerts a more significant influence on the financial development of Nepal's provinces. Additionally, combined public spending that is neither capital nor current has helped advance financial development in the provinces. Value/Originality: The results of the study highlight the necessity of prioritising infrastructure improvements and effective combined public spending to support financial development in Nepal's provinces. It offers unique insights not previously explored in Nepalese academia. Updated and relevant data are collected and applied to the different channels to evaluate the nexus of financial development at the province level of Nepal. Recommendation: Policymakers should give due consideration to the effective mobilisation of fiscal resources with proper fiscal discipline in every aspect. Moreover, enhancing the allocation of development finance has the potential to stimulate financial development across all areas herein examined. Keywords: Economic growth, public expenditure, infrastructure, financial development, fixed effect model JEL classification: H54, H72, G21, O47, C33