Panel Data Model Research Articles

Determination of the Number of Breaks in Heterogeneous Panel Data Models

Abstract This paper considers a heterogeneous panel data model with an unknown number of breaks. We propose a so-called two-stage procedure to determine the number of breaks and detect the location of break points. The consistency of the estimated number of breaks and the estimated break points are established under fairly general conditions. Monte Carlo simulations and two empirical applications are provided to demonstrate the finite sample performance of the proposed method.

Fast and order‐invariant inference in Bayesian VARs with nonparametric shocks

SummaryThe shocks that hit macroeconomic models such as Vector Autoregressions (VARs) have the potential to be non‐Gaussian, exhibiting asymmetries and fat tails. This consideration motivates the VAR developed in this paper that uses a Dirichlet process mixture (DPM) to model the reduced‐form shocks. However, we do not follow the obvious strategy of simply modeling the VAR errors with a DPM as this would lead to computationally infeasible Bayesian inference in larger VARs and potentially a sensitivity to the way the variables are ordered in the VAR. Instead, we develop a particular additive error structure inspired by Bayesian nonparametric treatments of random effects in panel data models. We show that this leads to a model that allows for computationally fast and order‐invariant inference in large VARs with nonparametric shocks. Our empirical results with nonparametric VARs of various dimensions show that nonparametric treatment of the VAR errors often improves forecast accuracy and can be used to analyze the changing transmission of US monetary policy.

The Impact of Research and Development Investment on the Performance of Portuguese Companies

This study investigates the impact of Research and Development (R&D) investment on the performance of Portuguese companies, specifically addressing the gap in understanding how R&D influences a company’s value and performance. We employ a dynamic panel data model estimated using the Generalized Method of Moments (GMM) to account for potential endogeneity issues. This approach allows us to analyze the influence of R&D investment on the Return on Operating Assets (ROA) for Portuguese companies with significant R&D investments between 2012 and 2019. The analysis reveals that while R&D investment itself may not have a statistically significant short-term impact on ROA, lagged financial performance, leverage, asset turnover ratio, and accounts payable turnover all demonstrate a statistically significant relationship with the dependent variable.

Panel Data Regression Analysis of the Determinants of Educated Unemployment in East Java

The primary goal of this research is to determine the relationship between the educated unemployment rate in East Java Province and several variables, including the minimum wage from 2018 to 2022, the labor force, and the human development index. This study included 190 secondary data samples in total, all of which came from the Central Bureau of Statistics' official website. For this investigation, the fixed effects panel data model (FEM) works well. This research demonstrates that: (1) the labor force and the educated unemployment rate do not correlate, or only partially correlate; (2) the educated unemployment rate is negatively impacted by the human development index; (3) there is a significant correlation between the educated unemployment rate and the minimum wage; and (4) in East Java, the minimum wage, the human development index, the labor force, and educated unemployment have a substantial correlation.

Dynamic cultures, dynamic responses: The impact on corporate cash holdings amid uncertainty

This study investigates the changes in national culture, economic uncertainty, and their joint effects on corporate cash holdings across 58 countries over the period 2004 to 2020. The study also delves into the importance of national culture in amplifying the impact of economic uncertainty in influencing corporate cash holdings. Drawing on three national cultural dimensions, trust-distrust, collectivism-individualism, and duty-joy orientation-based on the European Value Survey (EVS) and World Value Survey (WVS), we employ a panel data model with a fixed effect approach and incorporate the lag of the independent variable to mitigate potential endogeneity issues. Our findings show that transitions in national culture from collectivism to individualism do not significantly decrease corporate cash holdings. Moreover, a cultural shift from distrust to trust does not result in a decrease in corporate cash holdings. Conversely, a move towards a short-term orientation motivates firms to reduce their cash holdings. The interaction between economic uncertainty and collectivism and individualism tends to increase corporate cash holdings. However, there is no difference in the impacts of the three cultural dimensions for financially constrained and unconstrained firms on corporate cash holdings. This study offers significant practical implications, particularly for policymakers in countries where they have strong collectivistic national culture, which may amplify the effects of economic uncertainty.

Understanding the socioeconomic determinants of cooking fuel expenditure in Uttar Pradesh, India

Poor people in a developing country like India face energy poverty and are deprived of clean cooking fuel. Clean cooking fuels are costlier and require more willingness to pay (WTP) from the consumer. Therefore, this is a descriptive study aims to analyze factors associated with differences in cooking fuel expenses at the household level in Uttar Pradesh, India. For this purpose, panel data from the Consumer Pyramids Household Survey of CMIE from 2014 to 2019 has been considered. The study uses fixed-effect panel data model to control individual-specific effects. Cooking fuel expenses show positive elasticity concerning per capita income. However, this elasticity is lower for the higher-income group than the bottom-income group. Less educational attainments of households are associated with lower spending on cooking fuel. Moreover, households with better access to electricity are willing to spend more on cooking fuel expenditure. Hence, improved access to electricity nudges households towards more WTP for cooking fuel. It is further confirmed by finding a positive association between electricity-using household appliances and cooking fuel expenses. Therefore, improved access to electricity may increase the WTP for cooking fuel and adopt clean cooking fuel in different ways. This suggests positive spillover effects of modern energy services on clean cooking fuel.

The Impact of Selected Financial Ratios on Economic Value Added: Evidence from Croatia

Traditional financial performance measures should be extended to provide additional information to stakeholders. One such extension is the economic value added (EVA). It shows residual profit above the cost of financing, both creditors and equity financing. This paper elaborates on the impact of selected financial ratios on EVA to total assets and EVA to capital employed using the 20-year aggregated data of non-financial business entities operating in Croatia. It answers the research question of which of the selected financial ratios impacts the above-mentioned EVA-based ratios. Applying dynamic panel data modeling using the generalized method of moments technique resulted in the derivation of two models. The human capital efficiency ratio was statistically significant in both models, positively affecting EVA/total assets and EVA/capital employed. In contrast, the debt ratio and net profit margin were significant only in the second model, where EVA/capital employed was a dependent variable. The research results indicate that the debt ratio affects EVA/capital employed negatively while the net profit margin has a positive effect, confirming the existing research. Total liabilities/earnings before interest, taxes, depreciation and amortization, and total asset turnover were not found to be significant in either of the two models.

Role of Social Demography Factors in Economic Growth and Sustainability Models: Evidence from selected emerging economies

A country’s social demography characteristics are described by population dynamics and technology-based lifestyle changes. Such unique elements may correlate with economic growth and sustainability. In this study, a static panel data model analysis for economic growth and sustainable development of ten emerging economies was presented. Estimation results revealed that social demography factors exhibited a negative significant impact in both economic models, relative to the technological influence. Therefore, effective macroeconomic policies should be meticulously designed against changing demographic trends. Conclusively, by delivering focused public services to the urban area, more liveable cities will emerge to empower human capital development.

GMM estimation for high-dimensional panel data models

In this paper, we study a class of high dimensional moment restriction panel data models with interactive effects, where the factors are unobserved and these factor loadings are nonparametrically unknown smooth functions of individual characteristic variables. We allow the dimension of the parameter vector and the number of moment conditions to diverge with the sample size. This is a very general framework and is closely related to many existing linear and nonlinear panel data models. In order to estimate the unknown parameters, factors and factor loadings, we propose a sieve-based generalized method of moments estimation method and we show that under a set of simple identification conditions, all those unknown quantities can be consistently estimated. Further we establish asymptotic distributions of the proposed estimators. In addition, we propose tests for over-identification, specification of factor loading functions, and establish their large sample properties. Moreover, a number of simulation studies are conducted to examine the performance of the proposed estimators and test statistics in finite samples. An empirical example on stock return prediction is studied to demonstrate both the empirical relevance and the applicability of the proposed framework and corresponding estimation and testing methods.

An Econometric Study Using Panel Data Model of Factors Affecting Women's Economic Empowerment for Some Countries During the Period (2000-2023)

Objectives: The study aimed to use the analytical and standard method in analyzing the results of the study based on the analysis of factors affecting the economic empowerment of women in some countries during the period (2000-2023). Methods: To investigate the relationships between variables, the Panel Data model has Been Described to express the relationship between the female employment rate as a Dependent variable and women's empowerment indicators as independent variables. The study sample consisted of five countries, including Saudi Arabia, Sudan, Egypt, India and South Africa. The data were estimated using three models: the aggregate regression model, the static effects, and the random effects model. Results: The results showed that the fixed effects model is the most appropriate model for this study. Using the statistical program E-views12. Conclusion: The study found the following: It is expected to have an inverse relationship between the female unemployment rate and the female employment rate (FE) - as a dependent variable - and a positive relationship between the female labor force rate and FE. Contrary to expectations, it was found that there is a positive relationship between the female mortality rate and the dependent variable, in addition to the dependent variable not affected by the age dependency ratio of males.

The investment grade and funds' portfolio allocation in Greek assets

The importance of investment funds for the global economy has increased in the aftermath of the global financial crisis. In the present paper, we focus on the case of Greece and the developments in investment funds’ portfolios, with a special emphasis on the period before the sovereign credit rating upgrade of Greece to investment grade. By means of a differences-in-differences estimator, we find that, in the aftermath of the change in Greece’s sovereign credit rating outlook to positive by the rating agency Standard and Poor’s (S&P), investment funds increased their holdings of Greek sovereign bonds in relation to other comparable euro area sovereign bonds. Next, in a dynamic panel data model setup we find that this increase in investment funds’ positions in Greek government bonds (GGBs) explains about 80% of the reduction in Greek sovereign bond spreads. Our results highlight the strong association between investment funds’ portfolio allocation and the underlying assets’ credit ratings, and provide incentives for continuing reforms that may lead to rating upgrades, as a means of increasing demand for Greek sovereign bonds and controlling the cost of debt. This is especially important when the monetary policy environment becomes tighter and interest rates, as well as the cost of funding, increase.

Sources of Endogenous Economic Growth in 83 Russian Regions

According to the theory of endogenous growth, technologies play a key role in economic development. Digital technologies, as innovations that create new innovations, change economic activity and create new opportunities for economic growth. Digitalization helps to reduce specific economic costs, changes the nature of work. It also causes the substitution of labor with capital. The study is devoted to characterizing the features of regional development and evaluate digital predictors of economic growth. We used a sample of data from 83 regions in the period 2009-2019, excluding from the sample years 2020 and 2021 because of changes in economic dynamics under the influence of pandemic shocks. Econometric estimates are obtained using least squares and a feasible generalized least squares method based on unidirectional panel data models. A statistically significant influence of the number of university students, innovation costs on the growth rate of gross regional product per capita was found. The impact of the number of granted patents and the number of Internet users of the organization on the regional development was not confirmed. The results of the study emphasize the necessity of state science and innovation policy to reduce technological inequality, strengthen macroeconomic stability, high level of qualifications and technologies. The direction of further research can be the creation of indicator system measuring the quality of political and economic institutions.

Micro Study on the Impact of the Digital Economy on Income from the Perspective of Labor Matching

As the digital economy continues to develop, the socio-economic structure and lifestyle have undergone significant changes, which have had a profound impact on the labor market. To explore the mechanism of the digital economys impact on income, this study builds a personal panel data model from a micro perspective and conducts an empirical analysis. The matching situation of individuals in terms of employment and income is assessed through the skill-job matching degree and skill-income matching degree. A bidirectional fixed-effects model is used for calculation and analysis, comprehensively considering individual characteristics, skill levels, job requirements, and other factors. This study examines the direct and indirect effects of the digital economy on income and explores its influencing mechanisms.

Financial distress and earnings management: evidence from non-financial companies listed on the Ho Chi Minh Stock Exchange

The study examines the impact of financial distress on earnings management for Vietnamese non-financial companies. The System Generalized Method of Moments was employed to estimate a dynamic panel data model. Data were collected from non-financial companies listed on the Ho Chi Minh Stock Exchange from 2011 to 2020. The results show that financial distress has a positive impact on earnings management. Specifically, enterprises with good financial health and low risk of bankruptcy tend to make upward profit adjustments, while financially distressed enterprises tend to make downward profit adjustments. This may be due to the supervisory pressure of auditors and creditors, which makes the most affected enterprises no longer have the opportunity to undertake profit manipulation. At the same time, a company with high operating performance tends to maintain profit growth to impress investors in the market. The study results warn policymakers, enterprises, and investors when even financially sound enterprises are incentivized to undertake earnings management. This paper provides additional evidence that financial distress is positively associated with earnings management, which contradicts the findings of some prior studies.

Does international trade promote economic growth? Europe, 19th and 20th centuries

In this paper, we analyse the relationship between international trade and economic growth in an unbalanced panel of 20 European countries in a long-term perspective, since the mid-19th century to present days, differentiating between the periods before and after the start of the Second World War. To this end, we perform Granger-causality tests between exports and GDP, and between imports and GDP, following the novel methodology of Juodis et al. (2021) for panel data models with large cross-sectional and time series dimensions. Our results support the existence of a bi-directional relationship between both trade variables and GDP, for the whole period and across subperiods.

Green Capital Dynamics: Investigating the Impact of Capital Structure on Profitability among IDX LQ45 Low Carbon Leaders in Indonesia

Research Aims: This study explores the nexus between capital structure and financial performance among firms listed in Indonesia's IDX LQ45 Low Carbon Leaders. The study focuses on capital structure, operationalized through leverage (Total Liabilities/Total Assets), and financial performance metrics, specifically Return on Assets (ROA) and Return on Equity (ROE). Design/methodology/approach: The research employs the Hausman test to select appropriate panel data models, subsequently validated by the Breusch-Pagan test. This rigorous approach ensures robust model selection between fixed-effect and random-effect specifications. Research Findings: Based on ROA and ROE measurements, leverage's influence on financial performance does not consistently show significant statistical importance. Theoretical Contribution/Originality: This study enriches financial literature by supporting the findings of Miller and Modigliani, which indicate that capital structure does not directly impact profitability, particularly in the context of companies listed in the IDX LQ45 Low Carbon Leaders in Indonesia.

Influence of the Revenues of the Co-Financed Universities of Ecuador on the Expenditure For Salaries of the Academic and Administrative Personnel

Objective: This study investigates the influence of income from co-financed universities on the salary expenses of teaching and administrative staff, aiming to understand how changes in employee salaries impact university revenues. Theoretical Framework: The research is grounded in labor economics and higher education finance theories, providing a robust context for analyzing the financial dynamics within universities. Method: Two econometric models were employed: a multiple linear regression model using ordinary least squares to measure individual effects and a panel data model with random effects to assess grouped effects. Data collection involved analyzing financial records from co-financed universities. Results and Discussion: The results indicate that increased salaries at Universidad Politécnica Salesiana and Universidad Católica Santiago de Guayaquil lead to higher income. A 1% increase in teachers' salaries results in a 0.49% income increase, while a 1% rise in administrative salaries leads to a 0.08% income decrease. These findings highlight significant implications and limitations. Research Implications: The study provides insights for budgeting strategies, salary policies, and financial planning in higher education. It emphasizes the practical and theoretical impacts of salary adjustments on university revenues. Originality/Value: This research contributes to the literature by exploring the novel relationship between employee salary increases and university revenues, offering valuable insights for financial decision-making in higher education institutions.

The impact of ESG performance on corporate sustainable growth from the perspective of carbon sentiment

With the increasing importance of environmental and economic sustainability concerns, the concept of Environmental, Social, and Governance (ESG) has gained significant attention. In the era of digitalization, a research approach called carbon sentiment analysis has emerged as an innovative method. This study aims to explore the connections between carbon sentiment, ESG, and corporate sustainable growth within the context of the green economy. By using Ordinary Least Squares (OLS) regression analysis and establishing a panel data model of ESG performance and sustainable growth for Chinese listed companies, a notable positive correlation between the two variables was observed. Endogeneity was addressed using the two-stage instrumental variable method (2SLS) and the dynamic panel Generalized Method of Moments (GMM) model, with the results remaining robust both before and after the COVID-19 pandemic. Carbon-related news and textual information were collected and analyzed using advanced deep learning methods in Natural Language Processing (NLP), specifically Bidirectional Encoder Representations from Transformers (BERT) and Long Short-Term Memory (LSTM) models. This analysis enabled sentiment analysis and identification of the sentiment orientation of carbon news. The obtained sentiment scores were then integrated with company data to establish a moderation effect model. The findings of the study reveal that carbon sentiment significantly and positively moderates ESG performance in relation to corporate sustainable growth. Furthermore, the construction of a mediation effect model showed that carbon sentiment can moderate ESG performance by reducing environmental uncertainty, enhancing social trust, and alleviating financing constraints, thereby influencing corporate sustainable growth. The results of the heterogeneity group regression analysis demonstrate that the impact of ESG performance driven by carbon sentiment on sustainable growth is more pronounced in carbon market pilot regions, non-heavily polluting industries, and labor-intensive industries. This research provides a fresh perspective for understanding the dynamics of ESG, online carbon sentiment, and their implications for corporate sustainable growth. Additionally, it contributes to the development of the green economy and the formulation of environmental management policies.

Robust estimation method for panel interval-valued data model with fixed effects

Panel data model with fixed effects is widely used in economic and administrative applications. However, the presence of factors: measurement errors, data variability and outliers may potentially decrease the accuracy of the model prediction. In this paper, we use panel interval-valued data to represent measurement errors and data volatility of observations. Further, we propose a corresponding panel interval-valued data model with fixed effects, in which both the response and explanatory variables are interval-valued data. To reduce the impact of outliers on our model, we propose a robust estimation method based on the iterative weighted least squares technique. Later, Monte Carlo simulation and empirical application demonstrate that our model is a suitable tool for analyzing the behaviour of panel interval-valued data.

Unraveling the spatial dynamics of regional economic disparities in East Java

The objective of this research was to analyze the determinants of regional disparities in East Java Province. This study utilized panel data, incorporating research locations across 38 regencies in East Java, with a data series spanning from 2016 to 2020. Spatial panel data models were employed to address the research objective, specifically examining the impact of spatial and non-spatial factors on disparities in East Java. The study's findings indicated that the Spatial Autoregressive (SAR) model was the most effective for estimating disparities in the region. The effects of each variable are as follows: the average duration of schooling and investment had positive and significant effects on disparities, while the variable of open unemployment rate did not exhibit any significant effect. Additionally, there is a spatial effect in the form of an endogenous interaction effect, signifying that the extent of disparities is influenced by the disparities in neighboring areas.