Fixed Effects Panel Data Model Research Articles

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.

The impact of digital economy development on public health: evidence from Chinese cities.

The swift advancement of the digital economy not only plays a crucial role in stimulating a country's economic growth but also exerts a significant influence on national health and well-being. Adopts the data of 285 prefecture-level cities in China from 2010 to 2022, and employs the panel data fixed-effects model, spatial Durbin model, and mediated effects model to study the impact of digital economic development on the level of urban public health. It is found that digital economic development significantly improves the level of urban public health, and the effect has a spatial spillover effect. The impact of digital economic development on urban public health is mainly concentrated in cities with higher levels of economic development, higher levels of digital economic development, and lower levels of urban public health. Among them, technological innovation and information dissemination are the main dissemination channels through which digital economic development affects the level of urban public health. The advancement of the digital economy significantly impacts urban public health. It is advisable to bolster policies guiding digital economy development, enhance cross-sector collaboration between the digital economy and public health, reinforce public health education and awareness campaigns, improve the digital health literacy of the population, continue to enhance the fairness and accessibility of basic medical services, and address and bridge the "digital divide" between regions, as well as urban and rural areas.

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

The Long Run Impact of Exchange Rate and Inflation on GDP: A Panel Data Approach Consistent with Data from Brazil, Russia, India, China, And South Africa (BRICS)

The study seeks to address current discrepancies, providing valuable knowledge for decision-makers, fostering economic stability and expansion, informing global economic trends, assisting in business risk mitigation, and contributing to academic advancement through methodological innovation, with a focus on the changing nature of global economic dynamics. The purpose of this study is to assess how inflation and currency exchange rates affect the GDPs of the BRICS (Brazil, Russia, India, China, and South Africa) nations between 1998 and 2022 We employed a fixed-effect panel data model using EViews software to conduct a thorough regression analysis on the influence of exchange rates and inflation on the Gross Domestic Product (GDP) of the BRICS nations. The World Development Indicators website provides data that shows that, in contrast to predictions, exchange rates have no appreciable impact on GDP. Nonetheless, during the given time frame, inflation turns out to be a noteworthy and positively connected element impacting these countries' economic growth. This research contributes to the current understanding by uncovering the complex interconnections between exchange rates, inflation, and GDP in BRICS economies. Our findings highlight the necessity of customized economic strategies that recognise the distinct functions of inflation and currency rates in influencing the long-term growth patterns of individual countries.

Openness to international collaboration and tie strength in enhancing knowledge creation

This study aims to understand whether and under what condition openness to international collaboration enhances knowledge creation. How the configuration of openness, domestic ties, and foreign ties of an institution affects its knowledge creation is examined in egocentric networks. Using fixed-effects panel data models, we find that a positive association exists between openness and knowledge creation, which is catalyzed by domestic tie strength and diminished by foreign tie strength, and both domestic and foreign tie strength have an inverted U-shaped effect on knowledge creation. The findings contribute to international collaboration and knowledge-based view literature by proposing that maintaining strong domestic ties and a wide range of relatively weak foreign ties simultaneously is an efficient way to leverage international collaboration to integrate domestic and foreign knowledge. It also enriches the strong tie theory by suggesting the strength of strong domestic ties could be reinforced by openness.

Does basic medical insurance promote public health? Evidence from China family panel study.

To promote common prosperity, China government has devoted much financial resources to the basic medical insurance system, it is of great significance to improve the health level of the insured groups to prevent them from returning to poverty due to illness. Whether or not the basic medical insurance can improve health status is an important policy issue after China has win the absolute poverty alleviation movement. Based on the data of China Family Panel Studies this paper constructs a strong balanced panel data with two levels information, which including variables from family level and personal level. This paper uses the panel data fixed effect model and propensity score matching model to analysis. This paper finds that after controlling the family and personal confounding variables, the basic medical insurance has positive effect toward health status. With propensity score matching model, this paper finds that there is causality between basic medical insurance and public health. Basic medical insurance has a significant health effect, that is, basic medical insurance has a significant positive impact on individual self-rated health. Participating in basic medical insurance can significantly improve the ability of families to face risk shocks, promote the accumulation of health capital in families, promote the diversification of livelihood strategies, and effectively prevent the occurrence of returning to poverty due to illness.

Not the priciest, but the best quality: A new interpretation of high import food price in China

AbstractAgainst the background of rapid increases in food imports, high food import prices have become an important issue for China. This paper first establishes the theoretical relationship between per capita income and import price, then uses a panel data fixed effect model and an instrumental variable estimation based on highly disaggregated firm‐level import data from the General Administration of Customs to analyze food import prices. This paper studies the impact of China's per capita income on the food import price and the key role of imported food quality in price formation for imported food in China. The study finds that the increase in per capita income has a significant, positive influence on the price of imported food in China, but this positive impact on the price is due to quality upgrading. The results suggest that while the increase of per capita income in China has generally pushed up import food prices, it has been mainly due to imports of higher‐quality food. There is no evidence that Chinese consumers are being fleeced by foreign exporting country or are seeking expensive products to flaunt their wealth. Chinese consumers are upgrading their diet with higher‐quality food imports. [EconLit Citations: F13, F14, Q17, Q18].

The impact of digital economy development on carbon emissions-based on the perspective of carbon trading market

This study, grounded in panel data derived from A-share listed companies in Shanghai and Shenzhen spanning the years 2011–2019, employs a panel data fixed-effects model. It scrutinizes the ramifications of digital economic advancement on carbon emissions, adopting the perspective of the carbon trading market. The investigation delves into novel mechanisms and diverse studies about carbon reduction within the realm of the digital economy. Findings indicate that in carbon trading markets, a one-unit augmentation in the level of digital economic development corresponds to a reduction of 0.417 units in carbon emissions. Regions, whether economically advanced or less developed, witness favorable impetus in carbon reduction effects. However, the latter exhibits a relatively more substantial impact, averaging a reduction of 0.589 units in carbon emissions. Mechanistically, leveraging scale effects and green technological innovation, this research identifies the overarching factor of productivity of enterprises as a pivotal regulatory determinant. The digital economy, while augmenting overall factor productivity, manifests a heightened constraining influence on carbon reduction, particularly evident in companies immersed in carbon trading markets. This study not only introduces a novel analytical perspective for a comprehensive exploration of the carbon emissions impact of the digital economy but also furnishes valuable policy insights to actively propel the evolution of carbon trading markets and carbon finance. These insights contribute significantly to the dynamic progression of policies governing carbon trading.

Forms of fiscal governance in the Euro Area – An update

AbstractDespite the common Euro Area (EA) requirements, we find notable differences in the quality of fiscal governance among the 19 member states. Moreover, characteristics of the delegation approach, which have been largely ignored in the EA fiscal governance framework, remain important in various member states. Using a two‐way fixed effects panel data model for the EA countries during 2006–2018, we find that the delegation approach can be effective to improve the fiscal position. On the other hand, the imposition of centrally mandated common rules‐based reforms has not taken into account the national political, social and institutional setting, and this may have also affected their effectiveness to achieve fiscal discipline. Our findings thus suggest a reconsideration of the one‐size‐fits‐all, rules‐based approach to fiscal governance in the EA.

Can financial subsidy increase electric vehicle (EV) penetration---evidence from a quasi-natural experiment

Electric vehicles (EVs) are considered a promising solution for reducing emissions in urban transportation and addressing energy crises. Several countries, including China, have implemented direct financial subsidies to encourage the adoption of EVs. However, there is a lack of comprehensive evaluation regarding the effectiveness of these subsidies and their interaction with non-financial incentive policies. Additionally, the design of subsidy policies can be endogenous, potentially leading to biased estimations of their effects on EV penetration. To address these issues, this study utilizes a “quasi-natural experiment" approach, taking advantage of the gradual reduction of nationwide EV subsidies by the Chinese government due to financial constraints, rather than market conditions, thus mitigating the endogeneity problem. The study collects panel data from 224 prefecture-level cities in China and employs a modified panel data fixed effects model to quantify the impact of financial subsidies on EV sales and market shares. The analysis focuses on subsidy variations during six periods. The main empirical findings are as follows: (1) 1 % increase in purchase subsidies leads to a 1.36 % increase in EV sales and a 2.31 % increase in EV market share. (2) Non-financial policies, such as parking benefits, promotional goals, and restrictions on the number of vehicles, also contribute to boosting EV sales. (3) The effects of purchase subsidies vary across cities with different socio-economic conditions. (4) Some non-financial policies are found to enhance the positive effects of subsidy policies.

New Energy Technology Innovation and Industry Carbon Emission Reduction Based on the Perspective of Unbalanced Regional Economic Development

Innovation in new energy technologies is a key driver in China’s efforts to achieve its environmental goals. However, the ability of different regions to develop and utilize new energy technologies may depend on their level of economic development. Based on a two-way fixed-effects panel data model, this paper empirically analyses the industry carbon emission reduction effect of new energy technology innovation and its heterogeneous performance at different stages of economic development, using data from 30 provinces and cities in China from 2000 to 2019. The results show that new energy technology innovation generally promotes CO2 emissions in China. The specific effects are closely related to the characteristics of the industry and the stage of economic development. At the same time, the implementation of environmental regulations will inhibit this positive effect, while the adjustment of the industrial structure may promote this positive effect. This paper discovers the mechanism of heterogeneity in new energy technology innovation among different provinces with different levels of economic development. This finding helps to fully assess the carbon emission reduction capacity and potential of different provinces and facilitates the rational disaggregation and formulation of climate policy goals among regions.

Can Female Political Representation Impact Female Labour Force Participation Rate? A Study across Indian States using Fixed Effect Panel Data Model

Can Female Political Representation Impact Female Labour Force Participation Rate? A Study across Indian States using Fixed Effect Panel Data Model

Nonparametric Instrumental Regression with Two-Way Fixed Effects

Abstract This paper proposes a novel estimator for nonparametric instrumental regression while controlling for additive two-way fixed effects. In particular, the Landweber–Fridman regularization, to overcome the ill-posed inverse problem in the nonparametric instrumental regression procedure, is combined with the local-within two-ways fixed effect estimator presented by Lee, Y., D. Mukherjee, and A. Ullah. (2019. “Nonparametric Estimation of the Marginal Effect in Fixed-Effect Panel Data Models.” Journal of Multivariate Analysis 171: 53–67). Compared to other estimators in this context, an appealing feature is its flexible applicability with respect to different panel model specifications, i.e. models comprising either individual, temporal, or two-way fixed effects. The estimator’s performance is tested on simulated data, where a Monte Carlo study reveals good finite sample behaviour. Confidence intervals are provided by applying the wild bootstrap.