Fixed Effects Estimation Research Articles

Does household’s food and nutrient acquisition capacity predict linear growth in children? Analysis of longitudinal data from rural and small towns in Ethiopia

Nutritious foods are unaffordable to the majority of households in lower-income countries. Hence, starchy staples tend to be the main source of diets for men, women, and children, implying poor diet quality and deficiency in key nutrients that are crucial for child’s physical growth and cognitive development. Much of existing studies on child linear growth or stunting examined the impact of current dietary consumption on physical growth even though the effect of diets and nutrition would only be observed with time lag. This study examined the associations between sustained consumption of animal sourced foods (ASFs) and adequate nutrient intakes (measured by the mean nutrient adequacy (MPA)) and linear growth differences among children in rural and small towns in Ethiopia. Using nationally representative longitudinal data, results of fixed effects estimations suggested that a standard deviation increase in the household MPA was associated with a 10–11% increase in the height-for-age z-score; and a 10% increase in the household MPA was associated with a 3.2 – 5.6% reduction in stunting rate in children 6–59 months of age. Results also indicated some associations between past ASFs consumption and current linear growth outcomes in younger children. The gap in the household MPA was over 41%, indicating the need for nutrient-dense ASFs in the household diets despite the sustainability concerns around ASFs. Key implication is that policies and interventions aimed at improving linear growth outcomes of children in rural and small towns in Ethiopia should improve household’s access to ASFs and nutrient acquisition capacity.

The Investment development path theory: Evidence from developing countries' agricultural sector.

We examined the investment development path (IDP) through the perspective of developing countries' agricultural sector. Our analytical approach indirectly accounts for interactions among countries regarding cross-border resource transfers. Aside from providing knowledge on testing the IDP by inferential statistics, the information would be relevant for policymaking. Identifying the stage(s) in the IDP not only highlights the global appeal of agriculture but also guides firms seeking to expand beyond borders. This information is essential for developing an effective economic strategy. We employed data from 1991 to 2021 for 55 countries from the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) and applied a fixed effects estimator corrected for serial correlation and non-constant variances. We found that agriculture in developing countries is currently in stages I and II of the IDP. Broadly, agricultural production requires policies that would increase outward foreign direct investment and inward foreign direct investment. Domestic agricultural businesses in developing countries must develop capacity by learning from foreign multinationals. This would enable agricultural businesses to invest abroad. Such a move would lead to an increase in outward FDI. As this would have resulted from increased GDP per capita, it will lead to movement from the existing stage to higher ones.

Measuring returns to experience using supervisor ratings of observed performance: The case of classroom teachers

AbstractWe study the returns to experience in teaching, estimated using supervisor ratings from classroom observations. We describe the assumptions required to interpret changes in observation ratings over time as the causal effect of experience on performance. We compare two difference‐in‐differences strategies: the two‐way fixed effects estimator common in the literature, and an alternative which avoids potential bias arising from effect heterogeneity. Using data from Tennessee and Washington, DC, we show empirical tests relevant to assessing the identifying assumptions and substantive threats—e.g., leniency bias, manipulation, changes in incentives or job assignments—and find our estimates are robust to several threats.

Empirical Evidence of ESG Disclosure's Impact on Corporate Investment Decision in Indonesia

The purpose of this study is to investigate the impact of environmental, social, and governance (ESG) disclosure on corporate investment decisions. Data were collected from annual reports of firms listed in Indonesia Stock Exchange between 2015 and 2020 (378 firm-year observations). Using Ordinary Least Square (OLS) and fixed effect estimation, this study found that the dimension of ESG practices positively affects corporate investment decisions. In addition, the presidential election periods increase the effectiveness of corporate investment decisions. The study results reveal that uncertainty in the economic and business environment over the impact of general elections increases the company's ability to generate higher investments. This study contributes to the company strategic alignment to justify management about investment prioritize in the stakeholder wealth through ESG disclosure.

Effectiveness, cost-effectiveness and return on investment of individual placement and support compared with traditional vocational rehabilitation for individuals with severe mental illness in the Netherlands: a nationwide implementation study

ObjectivesTo assess the effectiveness, cost-effectiveness and return on investment of individual placement and support (IPS) implemented through a reimbursement strategy on a nationwide scale compared with traditional vocational rehabilitation (TVR)...

Does economic self‐interest determine public attitudes toward immigrants? An econometric case study in Japan

AbstractWe examine two economic self‐interest hypotheses regarding the determinants of public attitudes toward immigrants: (1) the labor market hypothesis, which states that the employment and wage impacts of immigration determine the public attitudes, and (2) the welfare state hypothesis, which states that natives hold negative perceptions of immigrants due to concerns that they may strain the country's welfare budget. The first hypothesis predicts that natives' education will affect pro‐immigrant attitudes more positively when immigrants come from lower income countries. The second hypothesis predicts that natives' income affects the pro‐immigrant attitudes more negatively when immigrants come from lower income countries. We use the Japanese General Social Survey, which asks respondents' tolerance toward immigrants from different countries, allowing us to control for unobserved individual characteristics through a method akin to the fixed effect estimation. Our results indicate no difference in the effects of education and income on pro‐immigrant attitudes regardless of whether immigrants come from high‐ or low‐income countries. We conclude that economic self‐interest does not explain Japanese public attitudes toward immigrants. We discuss the policy implications about how to improve public attitudes toward immigrants.

Partner's contribution to housework and couple bonding activities among Korean working women: Heterogeneity by socioeconomic status

The present study investigates: (a) how a partner's contribution to housework is associated with couple bonding activities among Korean women in dual-earner couples and (b) whether this association varies by socioeconomic status. Using eight waves from the Korean Longitudinal Survey of Women & Families (N = 5758), we estimated fixed effects models to account for individual-level heterogeneity. Engagement in couple bonding activities was measured by the frequency of physical and cultural activities with a partner. Fixed effects estimates showed that a partner's contribution to housework is positively associated with engagement in physical and cultural activities with a partner. The association between a partner's contribution to housework and physical and cultural activities was more pronounced among women in dual-earner couples in which the woman was highly educated. The association for cultural activities, not physical activities, was amplified by household income. This study supports the notion that a more equal distribution of housework is important for improving the quality of life in a marriage.

DEVELOPMENT OF RETAIL BANKING SERVICES IN THE CONTEXT OF DIGITAL TRANSFORMATION

The article examines retail banking services, their importance and how they are improving in the context of digital transformation. In the article, using the data of 14 commercial banks in Uzbekistan, the number of observations is 280. The dependent variable is the deposit practice of commercial banks, the independent variables are the credit practice of commercial banks, the remote services of commercial banks and the practice of commercial banks with plastic cards, analyzed through several models.The research shows that when we analyze 3 models based on panel data, the Random effects estimator (REE) model econometric equation of the impact of retail banking services development practices in the national economy today is Y=0.59x1+0.08x2+0.22x3-1.66 is the most optimal model. Accordingly, regarding the choice between the Fixed effects estimator (FEE) model and the Random effects estimator (REE) model, the Hausman test is used to determine which model is more suitable. The test compares the estimates from two models and tests whether the difference between them is statistically significant. If the p-value of the test is greater than the significance level (usually 0.05), then the Random effects estimator (REE) model is preferred because it allows for unobserved heterogeneity not accounted for in the Fixed effects estimator (FEE) model.In this case, the p-value of the Hausman test is equal to 0.36, which is greater than 0.05. We use the Random effects estimator (REE) model to analyze the impact of the practice of developing retail banking services in the national economy today based on panel data. We came to the conclusion that it is suitable.

The Investment development path theory: Evidence from developing countries’ agricultural sector

Background We examined the investment development path (IDP) through the perspective of developing countries’ agricultural sector. Our analytical approach indirectly accounts for interactions among countries regarding cross-border resource transfers. Aside from providing knowledge on testing the IDP by inferential statistics, the information would be relevant for policymaking. Identifying the stage(s) in the IDP not only highlights the global appeal of agriculture but also guides firms seeking to expand beyond borders. This information is essential for developing an effective economic strategy. Methods We employed data from 1991 to 2021 for 55 countries from the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) and applied a fixed effects estimator corrected for serial correlation and non-constant variances. Results and conclusions We found that agriculture in developing countries is currently in stages I and II of the IDP. Broadly, agricultural production requires policies that would increase outward foreign direct investment and inward foreign direct investment. Domestic agricultural businesses in developing countries must develop capacity by learning from foreign multinationals. This would enable agricultural businesses to invest abroad. Such a move would lead to an increase in outward FDI. As this would have resulted from increased GDP per capita, it will lead to movement from the existing stage to higher ones.

Development effects of industrialization, labor force participation and electrification on productive capacity in Africa: A panel data investigation

In our study spanning 2010–2022 across 50 African economies, we investigated the effects of industrialization, labor force participation, and electrification on Africa’s productive capacity. We also examined how electrification moderates the effect of industrialization and labor force participation on productive capacity. We adopted the pooled OLS, the fixed effect estimator, and the dynamic system GMM estimation technique for our analysis. Our findings indicate industrialization, labor force participation, and electrification as potent channels for enhancing Africa's productive capacity. In tandem with Africa’s reality, we find that electrification isn’t moderating the positive impact of industrialization and labor force participation on productivity. Our findings also revealed human capital development, government health expenditure, and institutional quality as pivotal drivers of productive capacity in Africa, while factors like global economic policy uncertainty and natural resource endowment exhibit predominantly negative roles. These results underscore the need for African policymakers and leaders to foster an enabling environment that facilitates industrialization, increased labor force participation, and improved electricity access to promote economic performance and productivity.

The clarity of monetary policy communication and financial market volatility in developing economies

This study investigates the effect of the clarity of monetary policy statements (MPSs) on financial market volatilities by employing linguistic analysis and a panel fixed effects estimator for a newly built dataset drawn from the MPSs of 21 developing countries. Our results show that MPS clarity, measured by complexity and readability indices, negatively affects foreign exchange rate volatility, a key policy variable in developing economies, suggesting that clear central bank communication can reduce financial market volatility. Given the low literacy levels in developing countries, their central banks should make an extra effort to write statements that are easy to comprehend.

Estimating Yield Response Functions to Nitrogen for Annual Crops in Iran

Nitrate is a crucial element for crop growth, and its optimal application is essential for maximizing agricultural yield. In Iranian agriculture, there is a substantial gap between recommended nitrate usage and what farmers actually apply. In this study, our primary objective is to determine the most effective utilization of nitrate for crop cultivation. Simultaneously, we aim to analyze the factors that contribute to the disparity between optimal and current nitrate application practices. Furthermore, our research explores the impact of these differences on regional variations in crop yields. This is achieved using a quadratic yield response function model based on unbalanced panel data spanning the years 2000 to 2016, which includes a total of 14 crop activities and encompasses 31 administrative regions. The results show that rice exhibits the highest nitrogen usage, while rain-fed wheat demonstrates the lowest utilization at the optimal point. Depending on whether random- or fixed-effects estimation is found to be the most suitable specification, average yields corresponding to the optimal level of nitrogen use are calculated by region, or the average across all regions. In Iran, the top-performing regions for cereals like rain-fed wheat and irrigated barley can achieve yields of 1.33 and 3 t/ha, respectively. These yields represent a 31% and a 9% increase from the levels observed in 2016. The outcomes derived from the estimated yield response function will be integrated into comprehensive agricultural, economic, and environmental optimization models. These integrated models will facilitate the assessment of various fertilizer policies on fertilizer use, land allocation, farm-household incomes, and environmental externalities, such as nitrate leaching and nitrate balance. This study holds substantial scientific promise, given its exploration of the policy implications surrounding fertilizer usage, making it crucial not only for Iran, but also for many developing nations grappling with inefficient and unsustainable agricultural practices. It represents the first of its kind in the literature, providing estimations of optimal nitrogen use and crop yield points across all regions in Iran. This is achieved through advanced visualization using GIS maps.

The multidimensional Mundlak estimator

Mundlak (1978) shows that the fixed effects estimator is equivalent to the random effects estimator in the one-way error component model once the random individual effects are modeled as a linear function of all the averaged regressors over time. In the spirit of Mundlak, this paper shows that this result also holds for the multidimensional error component model. This is a generalization of Baltagi (2023) from the two-way Mundlak model to higher order multidimensional error components model, see Balazsi et al. (2024a) for the multidimensional fixed effects model and Balazsi et al. (2024b) for the multidimensional random effects model. The F test suggested by Mundlak (1978) to test for this correlation between the random effects and the regressors generate Hausman (1978) type tests that are easily generalizable to the multi-dimensional Mundlak regression.

The Moderating Role of Leverage on Corporate Bonds Yield

This study aims to identify the effect of bond credit rating, firm size, profitability, and liquidity on the yield to maturity (YTM) of listed Indonesian corporate bonds, with leverage ratio as a moderating variable. A panel data multi-linear regression with the fixed effect estimator was used to investigate the YTM of 25 listed corporate bonds from 2019 to 2021. The sample data comprise complete financial reports published in the Indonesia Stock Exchange (IDX) market and operations in the non-financial sector to increase the accuracy of information obtained. The results show that profitability proxied to return-on-asset (ROA) and firm size positively affect the YTM, while the liquidity ratio proxied to the current ratio (CR) had a negative influence. As a moderating variable, leverage proxied to the debt-to-equity ratio (DER) positively moderates the effect of CR, DER negatively moderates the effect of ROA and DER cannot moderate the bond’s credit rating to influence the YTM. However, the bond’s credit rating does not affect the YTM. The analysis of corporate bonds is a relatively uncommon study in Indonesia, and significant implicating for policymakers, underscoring the importance of meticulous management of CR and DER, which can decrease the YTM.

Employee productivity spillovers generated by incentive schemes

Orientation: The introduction of various incentive schemes in the South African workplace creates incentive-induced employee productivity spillovers but could differ between industries and geographic areas.Research purpose: The aim of the study was to determine the industry and geographic nature of incentive-induced employee productivity spillovers to inform managerial decision-making on intrinsic and extrinsic motivators.Motivation for the study: The introduction of incentive schemes is an important motivator of employee productivity in the workplace. For this study, it was deemed important to indicate whether incentive-induced employee productivity spillovers differ between industries and geographic areas by taking into consideration firm-size, firm-profitability, different incentive schemes, trade union presence, employee age and skill levels.Research approach/design and method: Fixed-effect panel data estimations were computed to predict incentive-induced employee productivity spillover effects based on secondary firm-based data sets.Main findings: Incentive scheme-induced employee productivity spillover effects were generally similar for all the different industry and geographic areas. The spillovers increased with greater firm-sizes, higher profitability levels, introduction of greater levels of monetary-based incentive schemes (especially for unionised employee segments), and allocation of incentive schemes to the middle- age employee grouping (35 years–55 years) as well as higher skilled employees.Practical/managerial implications: The effective introduction of incentive schemes in the workplace is an important mechanism for creating positive employee productivity spillover effects and it is generally common for all firms irrespective of the industry or geographic area.Contribution/value-add: Improved understanding of incentive-induced employee productivity spillovers in the South African workplace will enable the effective alignment of incentive schemes with firm profitability.

Do corporate reputation concerns constrain real earnings management practices? A multidimensional analysis

Purpose: This study integrates Eisenegger and Imhof's (EI) reputation theory and the reputation-building hypothesis to explore how corporate reputation (CREP) concerns constrain real earnings management (REM). Motivation of the study: This study empirically tests the combined and individual effects of the dimensions of Eisenegger and Imhof's corporate reputation theory on real earnings management practices. Design/methodology/approach: The study used the least-square dummy variable (LSDV) two-way fixed effects estimator on a panel data constructed from 203 non-financial firms listed in 12 sub-Saharan African stock exchanges from 2014 to 2020. Main findings: The study provides empirical evidence that CREP, consistent with Eisenegger and Imhof’s reputation theory, curtails REM practices. Functional, social, and expressive reputation concerns reduce the managerial tendency to manipulate real activities, while considering other REM influencing factors. This result is consistent across REM components, country-level analysis, and endogeneity tests. Practical implications/Managerial impact: The results of this study are anticipated to motivate the use of corporate reputation building as a preventive strategy against REM, as it deters managers from manipulating business operations. The findings provide managers with a valuable approach to evaluating a firm's various reputations and how they can be leveraged to curb REM. Novelty/Contribution: The study offers new perspectives on assessing firm reputation from various stakeholder viewpoints and how CREP serves as a complement to existing CG mechanisms to mitigate managerial opportunism.

Earnings management using classification shifting of revenues: evidence from Chinese-listed firms

PurposeThis study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.Design/methodology/approachThe study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.FindingsOur findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.Originality/valueThe study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.

Effects of economic freedom and ease of doing business on trade in global value chains: Evidence from sub‐Saharan Africa

AbstractInspired by the recent drastic shift in international trade from traditional to global value chains, this study analyzed the effects of economic freedom and ease of doing business on participation and position of sub‐Saharan Africa in global value chains. Panel data from 41 sub‐Saharan African countries from 2000 to 2018 were used. The study utilized a tobit estimator along with a fixed effects estimator. The findings show that economic freedom—namely, better regulation and sound money—positively influence the countries' participation in global value chains. Moreover, improving ease of doing business, such as by decreasing customs duties and simplifying procedures to register new businesses, enhances the countries' level of participation and their efforts to move upstream along the global value chains. The results are robust to different specifications. Therefore, sub‐Saharan African countries should promote economic freedom and ease of doing business to participate in and reap benefits offered by the current wave of globalization. Specifically, sub‐Saharan African countries should further reduce the number of procedures required to register new businesses, decrease tariffs and non‐tariffs barriers to trade in global value chains to enhance their participation and position along global value chains.

Evaluation of management soundness of Takaful industry in selected countries

PurposeManagement soundness is essential for the effectiveness of any industry, most especially in any Islamic financial sector, whereby fairness and justice are the key factors to be observed. This paper aims to examine the management soundness of the takaful industry regarding their asset quality, re-takaful and actuarial and earning and profitability.Design/methodology/approachThis study obtained quarterly data from 2019Q1 to 2021Q4 from the Islamic Financial Services Board across Malaysia, Brunei, Saudi Arabia, Jordan and the United Arab Emirates. The panel data modelling with random-effect and fixed-effect estimators were used for the analysis.FindingsThe finding revealed a strong relationship between re-takaful and earnings with management soundness and a weak relationship between asset quality and management soundness. In addition, the result established a significant and strong association between management soundness and earnings and profitability. Therefore, re-takaful and profitability contributed more to the management soundness of the takaful industry than asset quality during the study. An increase in earnings and profitability to enable the takaful industry to pay the claims, especially in calamity, and more focus on the quality of the asset they invested in could enable the smooth running of their day-to-day business affairs.Practical implicationsMore attention is required on the quality of assets in their portfolio for the sustainability of the takaful industry to fulfil their underlying objectives. Management soundness in the takaful industry should address the challenges of managerial lathery, which some studies linked with operational inefficiency because of unskilled personnel in the takaful industry. This could benefit takaful clients, irrespective of religion, to attain their associated share of benefits from the Islamic insurance industry.Originality/valueTo the best of the authors’ knowledge, this is the first empirical study that examined the effectiveness of takaful management across Malaysia, Brunei, Saudi Arabia, Jordan, and the United Arab Emirates.

Understanding the Consequences of Collinearity for Multilevel Models: The Importance of Disaggregation Across Levels

In multilevel models, disaggregating predictors into level-specific parts (typically accomplished via centering) benefits parameter estimates and their interpretations. However, the importance of level-specificity has been sparsely addressed in multilevel literature concerning collinearity. In this study, we develop novel insights into the interactivity of centering and collinearity in multilevel models. After integrating the broad literatures on centering and collinearity, we review level-specific and conflated correlations in multilevel data. Next, by deriving formal relationships between predictor collinearity and multilevel model estimates, we demonstrate how the consequences of collinearity change across different centering specifications and identify data characteristics that may exacerbate or mitigate those consequences. We show that when all or some level-1 predictors are uncentered, slope estimates can be greatly biased by collinearity. Disaggregation of all predictors eliminates the possibility that fixed effect estimates will be biased due to collinearity alone; however, under some data conditions, collinearity is associated with biased standard errors and random effect (co)variance estimates. Finally, we illustrate the importance of disaggregation for diagnosing collinearity in multilevel data and provide recommendations for the use of level-specific collinearity diagnostics. Overall, the necessity of disaggregation for identifying and managing collinearity’s consequences in multilevel models is clarified in novel ways.