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Some tests of specification for panel data: Monte Carlo evidence and an application to employ
Abstract
This paper presents specification tests that are applicable after estimating a dynamic model from panel data by the generalized
method of moments (GMM), and studies the practical performance of these procedures using both generated and real data. Our
GMM estimator optimally exploits all the linear moment restrictions that follow from the assumption of no serial correlation
in the errors, in an equation which contains individual effects, lagged dependent variables and no strictly exogenous variables.
We propose a test of serial correlation based on the GMM residuals and compare this with Sargan tests of over-identifying
restrictions and Hausman specification tests.
... This study examines impact of liquidity risk on banks' profitability by taking panel of 22 listed commercial banks of Pakistan from 2006 to 2022. For this, GMM (Generalized Methods of Moments) technique is applied as it accrues several advantages such as it removes endogeneity, reduces heteroscedasticity and corrects serial correlation problems and generates efficient and effective estimators as recommended by (Arellano & Bond, 1991). Two step system GMM has also been employed by (Ozili, 2017) and (Dietrich & Wanzenried, 2011). ...
... Where Y i,t denotes the return on average assets (proxy of profitability) dependent variable, α is constant; β 1 , β 2 , β 3 are coefficients while Y i,t−1 indicates lagged value of dependent variable; X is explanatory variables (liquidity risk; credit risk); Z denotes control variables (bank capital, bank size; bank efficiency, economic activities and consumer price index) and ε is error term. The system GMM estimator ignores Arellano and Bond (1991) weak instrument issues and provides a more flexible variance-covariance structure for momentary situations. Thus, we choose the two-step system GMM estimator over the usual OLS technique for handling data endogeneity, heteroskedasticity, and autocorrelation. ...
... To achieve our objectives, we employ a dynamic panel model over the period 2009-2019 and a system GMM approach (Arellano and Bover 1995;Arellano and Bond 1991) to tackle potential endogeneity issues of bank capitalization. The results indicate that ESG exerts a significant positive effect on the performance of both IBs and CBs. ...
... It is worth noting that the consistency of this estimator is based on two tests. The first is the test of Arellano and Bond (1991) for the presence of secondorder serial correlation in the residuals (AR2). The second is Hansen's (1982) test for the overall validity of the instruments used. ...
This research investigates the impact of environmental, social, and governance (ESG) factors on the performance of 67 banks across 13 countries, with a specific focus on comparing Islamic banks (IBs) and Conventional banks (CBs) from 2009 to 2019. By leveraging the two‐step process generalized method of moments (GMM) estimator presented by Blundell and Bond (1998), we address potential endogeneity concerns associated with bank capitalization. Our examination, while controlling for bank‐specific and macroeconomic factors, demonstrates a noteworthy positive effect of ESG on overall bank performance, particularly attributable to the governance element. Curiously, our analysis indicates that while the governance factor of ESG positively affects IBs, it does not produce a similar impact on the performance of CBs. This differential effect highlights the distinct operational structures inherent in these banking paradigms and enriches the literature by offering empirical insights into how ESG factors affect bank performance differently within dual banking systems. The implications of the research advocate for policymakers and bank executives, particularly in Islamic banking, to devise tailored governance approaches to bolster ESG integration and performance.
... In econometric estimation, to moderate our findings, we applied fixed effect, panel-corrected standard errors (PCSE), and Arellano-Bond dynamic systems with lag-dependent variable approaches to avoid biased and inconsistent results. These three models are anticipated to address AR (1) autocorrelation within panels, country-specific effects, cross-sectional dependency, endogeneity, and heteroskedasticity across panels (Green 2003;Beck and Katz 1995;Wooldridge 2010;Arellano and Bond 1991;Arellano and Olympia 1995). Initially, we begin our estimation based on fixed-effect regression. ...
... Lagged variables help reduce the impact of unobserved factors that could skew the genuine causal effect of internal displacement because previous performance predicts present outcomes (Shumway and Stoffer 2000). Therefore, to address this concern, we employed the Arellano-Bond system dynamic models with lagged variables and a year dummy as internal instrumental variables (Arellano and Bond 1991;Arellano and Olympia 1995). Nevertheless, the relationship between SDG indicators and internal displacement is frequently portrayed in standard analysis as unchanging. ...
This study investigates the links between conflict‐driven internal displacement and the United Nations Sustainable Development Goals (SDGs). Analyzing annual data from 50 nations and territories spanning 2009 to 2022, the findings demonstrate a negative association between conflict‐induced internal displacement and SDG 2 (zero hunger), SDG 3 (health and well‐being), SDG 4 (quality education), SDG 6 (clean water and sanitation), and SDG 8 (economic growth and employment). Specifically, the result indicates that an increase in conflict‐induced internal displacement correspond to an in increase in unemployment rate, food insecurity, and maternal and under‐five mortality rates. Additionally, conflict‐induced internal displacement contributes to a rise in the number of children out of school and hinders access to safely managed drinking water. A 1% increase in conflict‐induced internal displacement is associated with a 0.099% rise in unemployment, a 0.356% increase in food insecurity, a 2.251% increase in children out of primary school, a 0.756% higher maternal mortality rate, and a 0.271% increase in under‐five mortality. Furthermore, the availability of safe drinking water is reduced by 0.055%. These results underscore the detrimental impact of conflict‐induced internal displacement on the socio‐economic fabric of conflict‐affected countries, suggesting that internal displacement presents a substantial barrier to the achievement of SDG targets. Policy interventions in conflict‐affected regions must account for the specific challenges posed by internal displacement in order to mitigate these adverse effects and promote progress towards the SDGs.
... The associated lagged dependent variable ( , −1 − , −2 ) and the error term ( , − , −1 ) indicates that the explanatory factors are endogenous, which means that the estimate of equation (1) will be biassed and inconsistent (Hao, 2006). Arellano and Bond (1991) therefore suggest that the model satisfy the subsequent moment criteria. ...
... It is important to note that whereas first-order autocorrelation (AR (1)) is predicted to be substantial, AR (2) is not. When AR (2) is found, it suggests that the instruments could not be reliable, which could lead to biassed results (Arellano & Bond, 1991). Hence, verifying the lack of AR (2) suggests that the model is precisely defined and the outcomes are resilient. ...
This study explores the impact of financial innovation and energy poverty on the development of microfinance in 49 African nations, using yearly data from 2000 to 2022. The study deploys the panel system Generalised Method of Moments (GMM) to investigate the relationships between the phenomena, with robustness checks performed using the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) models. The GMM investigation revealed that financial innovation has a positive impact on microfinance development in Africa, but energy poverty has a significant negative impact. The FMOLS results confirm the positive benefits of financial innovation and the negative implications of energy poverty. In contrast, the DOLS findings show that financial innovation may have a significant negative impact on microfinance development, although the long-term implications of energy poverty are equivocal. The study emphasises the need of using contemporary financial technologies including ATMs, point-of-sale systems, mobile banking, and mobile money to improve microfinance in Africa. Additionally, it emphasises the importance of addressing energy poverty, since reliable energy is crucial to the sustainability of small businesses and industries. As a result, the research suggests authorities should draw attention to increasing energy production while ensuring equal and cheap distribution. Keywords: Financial Innovation, Energy Poverty, Microfinance DevelopmentJel Classification: N2, G53, F63, P28
... The difference GMM estimator (GMM-D) introduced by Arellano and Bond (1991) and Arellano and Bover (1995) is frequently used in the literature to correct endogeneity and heteroscedasticity problems. Thus, Blundell and Bond (1998) improved this estimator and developed the system GMM estimator (GMM-S), which is more appropriate to correct endogeneity problems of explanatory variables. ...
This paper aims to analyze the effect of fiscal decentralization on the structure of public spending in Cameroonian municipalities. The study covers 213 regional and local authorities for 11 years from 2010 to 2020. After briefly reviewing the literature, we used different estimation techniques to get our results. The results show that revenue decentralization positively and significantly affects overall municipal spending. We further disaggregate public spending into investment and operating spending. We find that expenditure decentralization positively and significantly affects operating and capital spending. However, the effect is more pronounced on capital spending. By changing the measure of decentralization, we also find that revenue decentralization positively and significantly affects local public spending. We therefore encourage policymakers to transfer more responsibilities and resources to local authorities.
... Because the ESGP score is time-varying, we incorporate the first-order lag terms of the dependent variable (Dependent (t−1) and assess the robustness of our results using both a fixed effects model and a two-step system generalized method of moments (GMM) estimator (Arellano & Bond 1991;Arellano & Bover 1995). Additionally, we use the dependent variable, lagged by two periods, as an instrumental variable (Chen & Xie 2022). ...
We examine the role of environmental, social and governance performance (ESGP), board gender diversity (BGD), and their interactive effect on stock price crash risk (SPCR). Using a dataset of Chinese companies listed in the A-share market between 2015 and 2022 and employing three-stage least squares statistics to address the endogeneity issue, we found that ESGP is negatively associated with SPCR. Notably, BGD exhibits a positive association with SPCR. However, the interaction between ESGP and BGD reveals a negative relationship with SPCR, suggesting that ESGP moderates the positive effect of BGD on crash-related risk. Our results still hold even after conducting a series of robustness checks, such as using a fixed effect model, a two-step GMM estimator, and alternative measures of ESGP and BGD. This study contributes to the governance and sustainability literature by highlighting the influence of ESGP and BGD on SPCR and their interactive role in mitigating crash risk through enhanced transparency, stronger stakeholder relations, and improved risk management. It offers valuable organisational and policy implications, suggesting that Chinese listed companies can leverage ESGP to effectively reduce SPCR and strengthen corporate governance practices.
... The diagnostic tests strongly support the validity of our empirical strategy. The significant AR(1) test statistics (p < 0.05) and insignificant AR(2) tests (p > 0.05) align with the requirements outlined by Arellano and Bond (1991), confirming the absence of second-order serial correlation in the differenced residuals. This pattern is consistent with the identifying assumptions of the GMM framework and supports the consistency of our estimates. ...
This study examines how monetary and fiscal policies differentially affect Islamic versus conventional banking performance during the COVID-19 pandemic. Employing dynamic panel methodology with System GMM estimation, we analyze 635 banks (143 Islamic, 492 conventional) across 32 OIC countries from 2002-2023. Results reveal asymmetric policy transmission channels between banking models. Conventional banks demonstrate strong responsiveness to inflation and interest rates during normal periods, but this sensitivity weakens during crises, with only interest rate effects maintaining significance. Islamic banks show inflation responsiveness while unexpectedly developing interest rate sensitivity during market turmoil, contradicting assumptions about Islamic finance’s immunity to conventional monetary mechanisms. These findings suggest standard policy tools lose effectiveness when most needed. Results show regulators must abandon uniform approaches in dual banking systems and develop model-specific intervention strategies. This research advances crisis management literature by illustrating how exogenous shocks alter policy transmission effectiveness, providing empirical guidance for future regulatory framework design.
Keywords: Islamic banking, COVID-19, pandemic, banking performance, resilience
... GMM is an appropriate approach for analyzing dynamic panel data because of its properties (Blundell and Bond, 1998). The dynamic panel data framework has two main types: Difference-GMM (Arellano and Bond, 1991) and System-GMM. These two models each have their own advantages. ...
This study investigates the determinants of energy consumption, with a primary focus on energy prices, and explores whether human capital moderates the relationship between energy prices and energy consumption across developed and developing countries. Using the generalized method of moments (GMM) for empirical analysis, the study examines data from 81 countries over a 33-year period from 1990 to 2023. The findings reveal that an increase in energy prices leads to reduced energy consumption in both developed and developing nations. Furthermore, the moderating role of human capital suggests that energy prices and human capital act as substitutes in influencing energy consumption. Specifically, the conditional analysis indicates that when human capital transitions from lower to higher levels, energy prices exert a more detrimental effect on energy consumption. These insights have practical implications, particularly highlighting the importance of investing in human capital to enhance energy efficiency. The study suggests that policymakers worldwide should prioritize investments in higher education, as this can lead to improved energy efficiency through the positive link between human capital and energy use. To the best of the authors' knowledge, this is the first comprehensive empirical study examining the role of human capital in the relationship between energy prices and energy consumption in both developed and developing countries.
... 3.3.1 Board gender diversity and leverage. To test H1, we used Arellano and Bond's generalized method of moments (GMM) approach (Arellano and Bover, 1995;Arellano and Bond, 1991). They proposed the use of GMM with lagged values of the original independent variables as instruments to resolve the problem of endogeneity. ...
Purpose
This study aims to investigate the relationship between board gender diversity (BGD) and credit ratings, using agency theory, resource dependence theory and critical mass theory as theoretical frameworks.
Design/methodology/approach
This paper analyses a sample of 1,037 North American companies from 2008 to 2017. The methodology includes the Arellano–Bond generalized method of moments (GMM), an ordinal extension of the binary logit model and robustness tests to address potential endogeneity and sample selection bias.
Findings
The results indicate that increasing female representation on boards significantly affects credit ratings. Specifically, each additional female board member increases the likelihood of obtaining a higher credit rating by up to 17.71. This effect is particularly pronounced for firms transitioning to investment-grade ratings, where the impact of female representation is amplified fourfold. These findings highlight the important role of board gender diversity in improving firms’ credit evaluations.
Originality/value
By examining a crucial period and employing rigorous analytical techniques, this study fills a significant gap in the literature; it offers valuable insights into how BGD affects credit ratings and emphasizes its strategic importance in corporate risk governance.
... Furthermore, the exogeneity of the instrument subsets was tested using the Difference-in-Hansen Test (DHT), which requires the null hypothesis to be maintained in order to support exclusion constraints . In addition, autocorrelation in the differenced residuals was found using the Arellano-Bond second-order serial correlation test (AR(2)), which was described by Arellano and Bond (1991). The specification of the model and the consistency of the estimators are supported by not rejecting the null hypothesis that there is no second-order autocorrelation. ...
Purpose
This study examines the influences of remittances and governance in enhancing access to electricity in 40 sub-Saharan African (SSA) countries.
Design/methodology/approach
Using 5 years of non-overlapping from 1990 to 2022 using the system-generalised method of moment (System-GMM), with a particular focus on the rural-urban divide.
Findings
Evidence from the unconditional regression indicates that an additional migrant remittance received results in 8.7% and 23.4% increase in rural and urban access to electricity respectively. Second, the interactive regressions also indicate that corruption control, voice and accountability and government effectiveness exhibit negative synergies with remittances to influence rural access to electricity. In urban SSA, corruption control has positive synergies with remittances to enhance access to electricity. Voice and accountability interact with remittance, yielding a governance threshold of 1.76, for complementary policies.
Originality/value
The current empirical research bridges the research gap in the context of exploring the role that governance plays in influencing the effect of remittances on rural and urban access to electricity based on both conditional and unconditional analysis.
... Fourth, the system GMM can account for autocorrelation and heteroscedasticity within the panel data. The addition of the lagged dependent variable as one of the independent variables in a dynamic model as well as the unobserved effect (i.e., heterogeneity of units) could lead to persistence over time (Arellano and Bond 1991). It can address the potential persistence between climate change and the independent variables. ...
Climate change mitigation requires adequate insights into the underlying causes to ensure environmental sustainability. To attain macroeconomic goals, countries deploy economic policies such as fiscal policy tools (government expenditure and taxation), monetary policy tools (real interest rate and money supply), and external policy variables (foreign trade and foreign direct investment). Though these tools/variables have the capacity to enhance sustained economic growth, they could have ramifications for climate change. Hence, this study is motivated by the necessity to balance the demands of economic policies on the environment and the economy. It determines the impact of economic policies on climate change using the panel data of 38 Organization of Economic Cooperation and Development (OECD) and 78 non‐OECD countries during 1990–2020. Evidence from the system Generalized Method of Moments (GMM) estimation indicates that government consumption expenditure, real interest rate, and money supply play vital roles in climate change mitigation, while foreign trade aggravates climate change in OECD and non‐OECD nations. Though tax revenue has an insignificant impact on climate change in OECD nations, it intensifies climate change in non‐OECD nations. Besides, the pollution halo hypothesis was confirmed in OECD nations, while the pollution haven hypothesis was confirmed in non‐OECD nations. This study implies that efforts to mitigate climate change should integrate fiscal, monetary, and external policies.
... The second literature is that on the estimation of dynamic effects in panel data, where the presence of fixed effects (many regressors) produces a sizable bias in the coefficient on the lagged outcome variable (the weakly exogenous regressor) (Nickell (1981)). Unlike the solutions proposed in that literature (e.g., Arellano and Bond (1991)), our solution for the time-series context does not rely on the knowledge that only a single known regressor fails to be strictly exogenous, nor does it require that the many regressors in the model are fixed effects for mutually exclusive groups. Finally, the underlying algebraic source of the asymptotic bias issues, as well as some asymptotic statements related to Gaussianity of quadratic forms, are connected to the problems arising in linear models with many instruments and/or many regressors; see, for example, Hansen, Hausman, and Newey (2008), Chao, Swanson, Hausman, Newey, and Woutersen (2012), Kline, Saggio, and Sølvsten (2020). ...
This paper studies linear time‐series regressions with many regressors. Weak exogeneity is the most used identifying assumption in time series. Weak exogeneity requires the structural error to have zero conditional expectation given present and past regressor values, allowing errors to correlate with future regressor realizations. We show that weak exogeneity in time‐series regressions with many controls may produce substantial biases and render the least squares (OLS) estimator inconsistent. The bias arises in settings with many regressors because the normalized OLS design matrix remains asymptotically random and correlates with the regression error when only weak (but not strict) exogeneity holds. This bias' magnitude increases with the number of regressors and their average autocorrelation. We propose an innovative approach to bias correction that yields a new estimator with improved properties relative to OLS. We establish consistency and conditional asymptotic Gaussianity of this new estimator and provide a method for inference.
... Indeed, dynamic panel models face the issue of correlation between unobservable country-specific effects and the lagged dependent variable, which provides inconsistent estimators under ordinary least squares (OLS). Thus, using lagged first-difference values of the endogenous variable as instruments, Arellano and Bond (1991) developed a consistent estimator known as Difference GMM. However, due to the persistence of the dependent variable, this estimator results in very poor lagged instruments (Blundell and Bond 1998). ...
In regions where agriculture serves as a cornerstone for employment and export revenue, increased volatility of food prices, coupled with the rising occurrence of climate shocks (such as droughts, floods, and heat waves), has driven a notable increase in external debt. While previous research has investigated the relationships between climate, agriculture, and debt separately, limited attention has been given to the direct influence of agricul tural price volatility on external debt and the role of climate shocks as a transmission mechanism. Our study seeks to assess the direct effect of agricultural price volatility on external debt and to examine the mediating role of climate change in this relationship. From a panel of 45 countries in sub-Saharan Africa (SSA) over the period 1995–2020, we mobilize a country-time fixed effects model estimated by the Two-Way Fixed Effects (TWFE) method. Our results indicate that a 1% increase in food price volatility leads to an increase in external debt of 0.102 points. The mediation analysis confirms that climate change is exacerbating the effect of volatile agricultural prices on external debt. To limit the impact of agricultural price volatility and climate risks on debt, it is essential to stabi lize agricultural markets, integrate climate risks into economic planning, develop adaptive social safety nets, to diversify the economy and energy, mobilize innovative financing and develop technological innovations in the agricultural sector.
Keywords Agricultural food price volatility · External debt · Climate change · Sub Saharan Africa
Codes JEL Q13 · Q54 · F34 · O13 · O55
... First-differencing estimators are applied to eliminate these effects, and moment conditions are constructed with relevant instruments. The one-step GMM method, as advocated by Arellano and Bond (1991) and Holtz-Eakin et al. (1988), is utilized for the analysis of dynamic panel data. ...
This study examines the important but underexplored link between liquidity levels and profitability in commercial banks in Cambodia, a topic of great relevance for both bank managers and policymakers seeking to bolster financial stability. By analyzing data spanning 12 years (2011 to 2022) from 22 banks, the study applies a variety of panel data models, such as pooled ordinary least squares (OLS), fixed effects (FE), random effects (RE), and the one-step generalized method of moments (GMM). The findings reveal a statistically significant negative impact of liquidity on profitability across all static panel data models, with coefficients of –1.3005 (pooled OLS), –0.9786 (FE), and –0.9966 (RE), each statistically significant at varying levels. The dynamic panel data model (one-step GMM) further confirmed this negative relationship, showing a coefficient of –0.3588. It also highlighted a robust positive effect of lagged profitability, with a coefficient of 0.7491. Interestingly, the study found that only bank-specific factors, such as operating expenses and net interest margin, consistently influenced profitability across both static and dynamic panel models. On the other hand, macroeconomic factors like inflation were shown to negatively affect profitability, underscoring the need for sound bank management practices and well-designed regulatory policies. AcknowledgmentsWe sincerely appreciate the financial support from the management of CamEd Business School, which made it possible for us to submit this paper for publication.
... Indeed, the appeal of the bracketing property lies in its inherent promise to be an alternative to estimating the FE-LDV model, for which estimation will suffer from "Nickell bias" if the number of time periods is fixed (Nickell 1981). 4 Under these circumstances, a Generalized Method of Moments approach in the style of the Arellano and Bond (1991) estimator (AB estimator) is a common way to obtain a consistent estimate of the treatment effect, τ . 5 However, as the AB estimator instruments the lagged dependent variable, y i,t−1 , with deeper lags of y it , the method requires the availability of sufficient time periods. ...
We investigate a bracketing property that purports to yield upper- and lower bounds on the treatment effects obtained from a fixed effects (FE) and lagged dependent variable (LDV) model. Referencing both analytical results and a Monte Carlo simulation, we explore the conditions under which the bracketing property holds, confirming this to be the case when the data generating process (DGP) is characterized by either unobserved heterogeneity or feedback effects from a lagged dependent variable. However, when the DGP is characterized by both features simultaneously, we find that bracketing of the treatment effect only holds under certain conditions—but not in general. Practitioners can nevertheless obtain the lower bound estimate by referencing a model that includes both FE and an LDV. While the Nickell bias in the coefficient of the LDV is known to be of order 1/T , we show that the Nickell-type bias in the estimator of the treatment effect is of order .
... This section reviews theoretical and empirical literature relevant to the present study. Gibrat's Law of Proportionate Effect [2], a classical theory of firm growth, posits that a firm's growth rate is independent of its size. ...
Using econometric techniques, this paper investigates the determinants of growth in Micro, Small, and Medium Enterprises (MSMEs) in India. Using a balanced panel dataset of 560 fast-growing Indian MSMEs from 2014-2018, the study employs Fixed Effects (FE) estimation and the Generalized Method of Moments (GMM) to model the relationship between firm growth and various firm-specific and macroeconomic variables. According to the report, macroeconomic factors like inflation and the corporate tax rate, productivity metrics, business size, and internal financing all greatly impact MSME growth. On the other hand, there was little to no statistical relevance between leverage and GDP growth. The results provide policy implications for focused interventions in emerging economies and advance our understanding of the fundamental dynamics of MSME development.
... The Two-Step System GMM model was utilized to address potential endogeneity concerns and enhance the precision of estimations [147,148,164]. This approach effectively mitigates unobserved heterogeneity and inter-variable correlation, which could otherwise bias estimates in the baseline model. ...
This study examines the relationship between integrated reporting quality (IRQ) disclosures , corporate governance quality (CGQ), and the implied cost of equity capital (ICC) in developed markets, focusing on Australia and New Zealand. The increasing adoption of integrated reporting and its potential implications for firms' ICC motivates this research. Moreover, the study highlights the role of IRQ in mitigating information asymmetry between firms and investors, emphasizing the need for high-quality disclosures. sing a quantitative approach with panel data analysis, the research analyzes a sample of the top 174 companies by Standard and Poor's market capitalization in Australia and New Zealand from 2018 to 2022, encompassing 870 observations post-IRQ implementation. Statistical methods, including fixed-effects, IV2SLS, two-step system-GMM, pooled OLS, and medium quantile regression, were applied to ensure robust findings. The results reveal a significant negative relationship between IRQ disclosure and ICC, with CGQ playing a moderating role in strengthening this association. Consistent with agency theory, the findings suggest that to reduce information asymmetry, firms issue more information which allows to reduce the cost of capital. Therefore, a more comprehensive firms' reporting, including information about their strategy and risks, increases investors' confidence, hence it may reduce the cost of capital. This study provides valuable insights for regulators and policymakers by emphasizing the importance of integrated reporting frameworks and robust corporate governance practices to promote transparency, reduce information asymmetry, and optimize capital allocation efficiency in developed markets.
Purpose
This paper aims to investigate the relationship between relevant company determinants and corporate social performance as measured by the social pillar of the environmental, social and governance (ESG) score, exploring whether firm size matters.
Design/methodology/approach
The authors use the system generalized method of moment estimator for dynamic panel data to analyze an unbalanced panel of firms listed in the STOXX Europe 600 index from 2015 to 2021.
Findings
The results indicate that several board characteristics (size, independence, percentage of nonexecutive members, gender diversity and the presence of a corporate social responsibility sustainability committee) and fewer ESG controversies are associated with higher corporate social performance. However, the results show no relationship between corporate financial performance and the social pillar. Furthermore, the authors demonstrate that large companies and those external to the financial industry show higher social performance.
Practical implications
The findings provide important implications for several stakeholders, including regulators and policymakers. Increasing attention should be directed toward specific firm determinants to enhance corporate social performance.
Originality/value
The authors advance understanding of the existing literature by examining how corporate social performance is influenced by its main corporate determinants.
Organizational slack is associated with various positive effects on the organization. By focusing on slack’s cushioning property, which shields the firm from external adversities, this article discusses how slack can also mute important external stimuli for problemistic search and increase adverse self-enhancement effects when an organization performs below aspirations. We use panel data on publicly traded firms to test how shareholder voice affects problemistic search and how slack negatively moderates this relationship. We also show that problemistic search suffers more in self-enhancing firms as a firm’s slack increases. We contribute to the behavioral theory of the firm by unfolding the negative side of slack and demonstrating how differentiation between internal and external coalition perspectives unfolds new sides of this concept.
JEL Classification: L20, M10
Bu çalışma, Türkiye'de Ege Bölgesi'nde yer alan sekiz şehrin optimal kent büyüklüğünün ekonomik dinamiklerini incelemektedir. Araştırmada, optimal kent büyüklüğünün belirlenmesinde farklı ekonomik yaklaşımlar benimsenmiş ve şehirlerin nüfus yoğunluğu ile arazi büyüklüğü dikkate alınmıştır. Panel veri analizi yöntemi kullanılarak, 2007-2022 yılları arasındaki verilerle ortalama maliyet ve ortalama fayda fonksiyonları tahmin edilmiştir. Araştırma, optimal kent büyüklüğünün minimum maliyet, maksimum net fayda ve maksimum kar yaklaşımlarına göre değişiklik gösterdiğini ortaya koymaktadır. Özellikle, nüfus yoğunluğu kullanılarak yapılan hesaplamalar, Ege Bölgesi'ndeki şehirlerde optimal büyüklüğün önemli ölçüde farklılaştığını göstermiştir. Çalışmanın sonuçları, kent büyüklüğünün ekonomik optimizasyonunda nüfus yoğunluğunun kritik bir rol oynadığını ve bu faktörün kentleşme politikalarının belirlenmesinde göz önünde bulundurulması gerektiğini vurgulamaktadır. Ayrıca, araştırma bulguları, optimal kent büyüklüğünün hesaplanmasında kullanılan yöntemlerin, şehirlerin ekonomik ve sosyal gelişim stratejilerine yönelik önemli politika önerileri sunabileceğini ortaya koymaktadır. Bu bağlamda, Ege Bölgesi'ndeki şehirler için geliştirilecek politikaların, bölgesel kalkınma hedeflerine uygun şekilde tasarlanması gerektiği sonucuna varılmaktadır.
To further promote rural revitalization strategies and achieve common prosperity, it is necessary to clarify the relationships among public expenditure for agriculture, agricultural green total factor productivity (AGTFP), and the urban–rural income gap (URIG). On the basis of panel data for 30 provincial regions in China from 2012 to 2022, this study constructs a panel vector autoregression (PVAR) model and explores their mutual interaction and influence from both dynamic and static perspectives through the Granger causality test, impulse response analysis, and variance decomposition methods. The research results show that public expenditure on agriculture, AGTFP, and URIG exhibit significant self-reinforcing trends. There is a significant two-way interaction effect between public expenditure on agriculture and URIG, indicating that these factors promote and complement each other. In addition, both improving AGTFP and increasing public expenditure on agriculture can help narrow URIG, but the positive impact of AGTFP exhibits greater magnitude and sustainability. In conclusion, from a long-term perspective, to develop the rural economy and promote rural revitalization, it is necessary not only to increase public expenditure on agriculture continuously, but also to focus on enhancing AGTFP.
This study examines the relationship between political stability and absence of violence (PSAV), control of corruption (COC), gross domestic product per capita, current account balance (CAB), general government gross debt (GGGD), unemployment, and the KOF Globalization Index within the South Asian Association for Regional Cooperation (SAARC) countries from 2000 to 2022. Through panel vector autoregression (PVAR) analysis, the study calculates the long-term correlation between variables using a vector error correction model (VECM). The PVAR approach addresses the endogeneity issue by including endogenous interactions between the variables in the model. Additionally, the impulse response functions and the influence of various variables on certain lags are evaluated. Cointegration between variables was assessed using dynamic ordinary least squares and fully modified ordinary least squares panel analysis to investigate the long-term link further. The results demonstrate a robust cointegration relationship, revealing a shared equilibrium across the SAARC countries’ economic variables. The VECM estimates results for a model with three lags. The coefficients of the cointegrating vector indicate the presence of at least one cointegrated vector between the series. Three of the velocity fit parameters show significance at least at the 5% level, specifically COC, CAB, and GGGD. These non-zero coefficients suggest a causal relationship among the variables in the long-run Granger causality. On the other hand, the matrix β denotes the cointegrate parameter matrix. It is observed that COC, CAB, and GGGD are significant at the 5% level. The equation reveals that COC, CAB, and GGGD variables have a positive, increasing effect on PSAV in the long-term cointegrated parameter values. This suggests that while these variables have a positive relationship with PSAV, their impact is not conclusively significant.
Cross-lagged analysis is a statistical method employed to examine directional relationships between variables over time, making it especially valuable for addressing causality challenges in clinical research. This method is essential for comprehending complex bidirectional relationships, such as stress and immunity, dietary habits and metabolic conditions, or medication adherence and health outcomes. By analyzing longitudinal data, cross-lagged analysis establishes temporal precedence, tests reciprocal influences, and controls for confounding variables, thereby enhancing causal inferences. In nephrology, this approach can be beneficial for studying the interaction between acute kidney injury (AKI) and chronic kidney disease (CKD), clarifying whether AKI episodes accelerate CKD progression or if pre-existing CKD increases susceptibility to AKI. It also illuminates the relationship between CKD and cardiovascular diseases, investigating whether CKD exacerbates heart failure or vice versa while considering shared risk factors like hypertension and diabetes. Furthermore, cross-lagged analysis can elucidate the kidney-brain connection by examining whether CKD leads to cognitive decline through mechanisms such as uremic toxin accumulation or if neurological dysfunction worsens kidney outcomes through sympathetic overactivation. Cross-lagged analysis accommodates latent variables and measurement errors, allowing researchers to explore how variables interact over time. This method provides a strong framework for understanding dynamic relationships in nephrology, offering critical insights to guide interventions and advance knowledge of disease progression mechanisms.
In this study, we shed light on the significant, yet often overlooked, influence of aggregate time-varying risk aversion on capital structure. Our research, using real consumption expenditures of the Spanish economy, options on the IBEX-35, and a panel data set of Spanish public firms over the period 2007-2020, reveals that market-wide risk aversion significantly slows the speed of adjustment towards target leverage. Our findings not only highlight the interdependence of the Spanish financial and real sectors, but also provide valuable insights about risk aversion as a crucial driver of corporate managers’ decision-making regarding dynamic capital structure. The paper also shows that risk aversion amplifies the effects of adverse uncertainty shocks on the equity cost of capital. By consolidating these findings, our research elucidates the mechanism through which risk aversion negatively impacts aggregate output and investments during recessions.
This study explores how digitalization, through resident and non‐resident innovation initiatives, along with government effectiveness, affects the transition to renewable energy generation in five Advanced (Australia, Hong Kong, Japan, New Zealand and Singapore) and seven Emerging (China, India, Indonesia, Malaysia, Philippines, Thailand and Vietnam) Asian economies. The research uses annual data from 1985 to 2022 and applies several econometric methods to analyse the impact of these factors on renewable energy generation in a panel setup while also considering economic growth and human capital as key control variables. The findings reveal that residential innovation negatively impacts renewable energy generation in Advanced Asia but has a positive effect in Emerging Asia. Additionally, government effectiveness and non‐residential innovation hinder renewable energy generation in Emerging Asia while contributing positively in Advanced Asia. Economic growth and human capital show a positive association with renewable energy generation in both Advanced and Emerging Asian economies. These findings are robust to an alternative method used. Besides, additional robust results further indicate that artificial intelligence patents used as an alternative measure of digitalization hinder renewable energy generation in Emerging Asia and promote it in Advanced Asia. These findings provide valuable guidance for policymakers and stakeholders, highlighting the need for tailored strategies to drive sustainable energy transition in different economic contexts.
This study investigates the relationship between leverage and corporate profitability in Chile, with a focus on the moderating effect of adopting International Financial Reporting Standards (IFRS) since 2013. We used a System-GMM approach to analyze 41 companies from the Selective Share Price Index (IPSA) over the period 2008-2023. We find that, prior to IFRS implementation, there was a negative relationship between leverage and profitability. However, following the adoption of these standards, the relationship became neutral. The findings suggest that the enhanced quality of financial information provided by IFRS can influence strategic decisions regarding corporate financing and management, underscoring the importance of transparency in an emerging economy. JEL Codes: G3, G32. Received: 15/08/2024. Accepted: 28/01/2025. Published: 03/05/2025.
We research synchronization and spillover effects in business cycles of 48 African economies (1970–2023), set into four structural clusters: fragile states, agricultural commodity exporters, oil exporters, and emerging market economies (EMEs). Utilizing Hodrick-Prescott and Hamilton filtered real GDP data; we measure synchronization via multilateral correlations and output growth differentials relative to group averages. Spillover dynamics are captured via the Diebold & Yilmaz spillover index, while BCS determinants are identified via System-GMM estimation. Structural composition, institutional quality, and governance capacity fundamentally govern BCS in Africa. While fragile and oil-exporting nations exhibit moderate synchronization from shared exposure to external shocks, internal synchronization is weak. EMEs stand as the most synchronized unit, reinforced by diversified production, deeper trade, and better economic management, positioning them as leaders for potential monetary integration. Vitally, spillovers alone are insufficient to sustain convergence without supportive institutional bases and coherent policy. We suggest a gradual, multi-speed approach to economic integration, with EMEs anchoring initial monetary cooperation, oil-exporters progressively integrating through fiscal discipline and trade diversification, and fragile/agricultural economies focusing on structural renovation and governance consolidation. Fiscal policy coordination, industrial policy alignment, and intra-African value chain development are essential to reduce asymmetries and foster durable synchronization.
Purpose
This study aims to examine the intricate relationship between integrated reporting quality (IRQ), report readability (READ) and firm value relevance (VR) in European manufacturing firms, exploring how linguistic accessibility mediates high-quality reporting’s impact on VR.
Design/methodology/approach
The study analyzes 153 manufacturing firms from the STOXX 600 Europe index over 2018–2023, yielding 913 firm-year observations. It uses dynamic panel models using the generalized method of moments and bootstrapping Hayes’ analyses and incorporating multiple readability metrics (Flesch–Kincaid Grade Level index, Gunning Fog index and simple measure of Gobbledygook) and VR measures (weighted average cost of capital and market value). The rigorous sample selection excluded financial institutions and firms with insufficient data.
Findings
The results reveal that readability plays a significant mediating role between integrated reporting quality (IRQ) and value relevance (VR) Contemporaneous readability measures are negatively associated with firm value, while lagged measures show a positive relationship, indicating a complex, time-dependent dynamic. Despite their linguistic complexity, high-quality integrated reports enhance VR, challenging conventional readability assumptions in financial communications.
Research limitations/implications
Our research underscores the imperative of developing visually strategic communication techniques that transform complex financial narratives into cognitively accessible representations. By integrating sophisticated infographics and conceptual visualizations, organizations can effectively bridge linguistic complexity and stakeholder comprehension, enhancing integrated reporting’s VR while maintaining informational rigor and strategic depth.
Originality/value
This study pioneers insights into the multifaceted, temporal nature of the IRQ–readability–VR relationship in European manufacturing. It demonstrates that linguistic complexity can coexist with value enhancement in high-quality reports, reshaping the understanding of effective financial communication. These findings guide corporate leaders in balancing informational depth with accessibility and offer regulators nuanced perspectives on reporting standards’ impact across diverse European industries.
Purpose
Despite the growing body of literature on climate change and finance, there remains a notable gap in research exploring how banks’ operational structures influence carbon dioxide emissions. This paper aims to address this gap by investigating the relationship between banks’ operational activities and CO 2 emissions across 110 countries.
Design/methodology/approach
This study uses a cross-country analysis to examine how various aspects of banks’ operations – such as loans to governments and corporate entities, corporate-based deposits, noninterest income and retail deposits from individual customers – impact emissions. The analysis also incorporates a robust control mechanism to account for potential confounding factors.
Findings
The findings indicate that loans extended by banks to governments and corporations, along with corporate-based deposits, tend to increase carbon emissions. In contrast, income derived from noninterest sources and retail deposits from individual customers exert a downward pressure on emissions. The coefficients associated with bank operations are found to be more significant than those linked to renewable energy initiatives.
Originality/value
This paper contributes to the literature by examining the influence of banks’ operational structures on carbon dioxide emissions, a topic that has been underexplored.
This study explores both the linear and nonlinear effects of corporate governance (CG) and enterprise risk management (ERM) on insurers’ risk-taking preferences. This paper was analysed using the generalised method of moments and the dynamic panel threshold estimation techniques based on a sample of 33 insurance companies in Ghana between 2015 and 2021. The results from the linear regression show that ERM significantly and positively influences insurers’ risk-taking, indicating that insurance companies with effective ERM programs are more inclined to assume higher risks. Additionally, the empirical findings indicate that risk-taking is negatively associated with gender diversity but positively influenced by board independence and size. The study further reveals nonlinearities between ERM, CG and risk-taking. The empirical evidence indicates that a strong ERM system enhances the risk-taking behaviour of insurers when it exceeds the threshold level and vice versa, implying a U-shaped relationship. Thus, an effective ERM program promotes better insurance risk-taking decisions. Also, the study presents a U-shaped relationship between board independence and insurers’ risk-taking. Contrarily, board size, and gender diversity reveal a relationship with an inverted U-shape, implying that the board makes less risky decisions when they are large, gender diversified and there are more females on the board. Policy implications are provided.
Local governments have become key agents in advancing regional digital transformation in China. Drawing on a panel dataset of 30 provinces from 2009 to 2022, this study adopts an innovation ecosystem perspective. It explores how public service delivery interacts with market development, higher education institutions, and social entrepreneurship to support sustainable digital development. The results show that local public services have a strong positive impact on digital transformation. This effect is even greater when supported by other ecosystem components. These findings highlight the value of system-level collaboration in promoting inclusive, resilient, and sustainable regional growth. Rather than introducing a new theory, this study provides practical, context-specific evidence on how local governments and innovation ecosystems work together to support China’s digital transformation and long-term sustainability goals.
This study explores the relationship between technological innovation and happiness (and subjective well-being) across 17 European countries by utilising data from the European Social Survey and other sources from 2002 to 2020. The results, based on fixed effects methods and one-step difference generalised method of moments, demonstrate a positive and robust correlation between technological innovation (measured by patents) and happiness. This suggests that innovation facilitates happiness. However, this relationship turns negative beyond a certain threshold of innovativeness, suggesting diminishing returns or potentially even negative effects of excessive innovation on happiness. We additionally find heterogeneous relationships between innovation and happiness based on the health status and educational attainment level of countries. The findings have significant policy implications, emphasising the need for a balanced approach that does not merely aim at maximising innovation output but also includes tools to mitigate the potential drawbacks of innovation on well-being.
This study examines the effects of the real effective exchange rate (REER) and its
volatility on economic growth from 1996 to 2020 in 36 OECD countries utilizing fixed
effects (FE) and random effects (RE) methodologies from panel data econometrics.
For empirical analysis, the Hausman test indicates that the fixed effect method is
superior to the random effect method; and there were presence of cross-sectional
dependencies, autocorrelation, and heteroskedasticity in the FE model. The robust
estimates derived by the FE estimation using DRK S.E. indicate that the impact of the
real effective exchange rate on economic growth is negative and statistically
significant whereas the REER volatility has an insignificant effect on economic growth
in the OECD throughout the examined period. The findings from the FE model with
robust S.E. further evidence a significantly negative impact of GCE and a significantly
positive impact of GCF on economic growth. While population growth and trade do
not result in any significant impact on economic activity, the influence of inflation on
GDP growth presents mixed findings on significance levels both of which point out to
negative impacts. This study presents crucial outcomes in that the impacts of REER
and REER volatility on economic growth present diversified outcomes over the past
decades in the OECD.
Keywords: Economic Growth, Exchange Rate, Fixed Effect, REER, Volatility,
OECD
This study delves into the acreage response of chickpea (gram) by examining price and non-price factors from 1997-98 to 2022-23. Employing the Nerlovian expectation and adjustment approach along with the system GMM (generalized method of moments) estimator, the study unveils that lagged area, relative price, and yield compared to wheat significantly impact land allocation for the subsequent year. Conversely, lagged gross irrigation, technological advancements, and government policies negatively influence chickpea (gram) acreage expansion over wheat. The study highlights the importance of enhancing sustainable agricultural practices and carefully balancing government programs with market solutions to bolster the agricultural supply responsiveness of Indian farmers.
This paper investigates the relationship between economic freedom and economic growth in Latin America and the Caribbean over the period 1997–2023, using data from 14 countries. To capture the multidimensional nature of economic freedom, two widely recognized indices—Heritage and Fraser—are incorporated into an extended Solow-type growth model. The empirical strategy relies on a dynamic panel data approach using the Arellano–Bond estimator, which allows for the control of unobserved heterogeneity, autocorrelation, and potential reverse causality. Robustness is assessed through alternative model specifications and in-sample forecasting using rolling-window techniques and Theil’s U-statistic. The results reveal a negative and statistically significant relationship between economic growth and the Heritage Index, while the Fraser Index shows a positive but generally non-significant effect. These findings highlight the methodological sensitivity of the economic freedom–growth nexus and suggest that context-specific institutional factors may shape how liberalization policies translate into development outcomes. The study contributes to the literature by jointly evaluating the impact of both indices in a unified dynamic framework, providing new evidence for a region marked by institutional heterogeneity and growth volatility.
which the relationships are not exact, so that a set of ideal economic variables is assumed to be generated by a set of dynamic stochastic relationships, as in Koopmans [12], and the actual economic time series are assumed to differ from the ideal economic variables because of random disturbances or measurement errors. The asymptotic error variance matrix for the coefficients of one of the relationships is obtained in the case in which these relationships are estimated using instrumental variables. With this variance matrix we are able to discuss the problem of choice that arises when there are more instrumental variables available than the minimum number required to enable the method to be used. A method of estimation is derived which involves a characteristic equation already considered by Hotelling in defining the canonical correlation [10]. This method was previously suggested by Durbin [7]. The same estimates would be obtained by the maximum-likelihood limited
This paper presents a statistical analysis of time series regression models for longitudinal data with and without lagged dependent variables under a variety of assumptions about the initial conditions of the processes being analyzed. The analysis demonstrates how the asymptotic properties of estimators of longitudinal models are critically dependent on the manner in which samples become large: by expanding the number of observations per person, holding the number of people fixed, or by expanding the number of persons, holding the number of observations per person fixed. The paper demonstrates which parameters can and cannot be identified from data produced by different sampling plans.
Panel data based studies in econometrics use the analysis of covariance approach to control for various ‘individual effects’ by estimating coefficients from the ‘within’ dimension of the data. Often, however, the results are unsatisfactory, with ‘too low’ and insignificant coefficients. Errors of measurement in the independent variables whose relative importance gets magnified in the within dimension are then blamed for this outcome.Errors-in-variables models have not been used widely, in part because they seem to require extraneous information to be identified. We show how a variety of errors-in-variables models may be identifiable and estimable in panel data without the use of external instruments and apply it to a relatively simple but not uninteresting case: the estimation of ‘labor demand’ relationships, also known as the ‘short-run increasing returns to scale’ puzzle.
The asymptotic variances of the IV estimators for dynamic panel data proposed by Anderson and Hsiao (1982) are obtained for some simple models. With an autoregressive exogenous variable, the estimator that uses differenced instruments has a singularity point and very large variances over a significant range of parameter values. On the contrary, the estimator that uses instruments in levels has no singularities and much smaller variances.
This paper derives, and then estimates, a model of employment where unions and firms bargain over wages and possibly employment, and efficiency wage considerations may be important. It illustrates the difficulties associated in interpreting many existing attempts to discriminate between alternative models. The results (based on over 200 U.K. firms) suggest that employment is negatively related to the firm's own wage and the change in the own wage relative to outside opportunities. The latter may be an efficiency wage effect. Various financial factors are also seen to have a significant effect on employment. Copyright 1991 by The Review of Economic Studies Limited.
This paper proposes efficient instrumental-variable estimators for an error-components model considering alternative assumptions about the sources of endogeneity and the variance-covariance properties of disturbances. The analysis develops a general result that provides for the construction of asymptotically efficient estimators when there exist variables that are predetermined for only a subset of the equations making up a structural model.
I assess the role of wealth and systemic risk in explaining future asset returns. I show that the residuals of the trend relationship among asset wealth and human wealth predict both stock returns and government bond yields. Using data for a set of industrialized countries, I find that when the wealth-to-income ratio falls, investors demand a higher risk premium for stocks. As for government bond returns: (i) when they are seen as a component of asset wealth, investors react in the same manner; (ii) if, however, investors perceive the increase in government bond returns as signalling a future rise in taxes or a deterioration of public finances, then investors interpret the fall in the wealth-to-income ratio as a fall in future bond premia. Finally, I show that the occurrence of crises episodes (in particular, systemic crises) amplifies the transmission of housing market shocks to financial markets and the banking sector.
This paper studies estimators that make sample analogues of population orthogonality conditions close to zero. Strong consistency and asymptotic normality of such estimators is established under the assumption that the observable variables are stationary and ergodic. Since many linear and nonlinear econometric estimators reside within the class of estimators studied in this paper, a convenient summary of the large sample properties of these estimators, including some whose large sample properties have not heretofore been discussed, is provided.
Recent studies argue that the spread-adjusted Taylor rule (STR), which includes a response to the credit spread, replicates monetary policy in the United State. We show (1) STR is a theoretically optimal monetary policy under heterogeneous loan interest rate contracts in both discretionay and commitment monetary policies, (2) however, the optimal response to the credit spread is ambiguous given the financial market structure in theoretically derived STR, and (3) there, a commitment policy is effective in narrowing the credit spread when the central bank hits the zero lower bound constraint of the policy rate.
This paper investigates the impact of international migration on technical efficiency, resource allocation and income from agricultural production of family farming in Albania. The results suggest that migration is used by rural households as a pathway out of agriculture: migration is negatively associated with both labour and non-labour input allocation in agriculture, while no significant differences can be detected in terms of farm technical efficiency or agricultural income. Whether the rapid demographic changes in rural areas triggered by massive migration, possibly combined with propitious land and rural development policies, will ultimately produce the conditions for a more viable, high-return agriculture attracting larger investments remains to be seen.
An important purpose in pooling time-series and cross-section data is to control for individual-specific unobservable effects which may be correlated with other explanatory variables, e.g. latent ability in measuring returns to schooling in earnings equations or managerial ability in measuring returns to scale in firm cost functions. Using instrumental variables and the time-invariant characteristics of the latent variable, we derive: 1. (1) a test for the presence of this effect and for the over-identifying restriction we use;2. (2) necessary and sufficient conditions for identification of all the parameters in the model; and3. (3) the asymptotically efficient instrumental variables estimator and conditions under which it differs from the within-groups estimator.
We calculate efficient estimates of a wage equation from the Michigan income dynamics data which indicate substantial differences from within-groups and Balestra-Nerlove estimates — particularly a significantly higher estimate of the returns to schooling.
Observations on N cross-section units at T time points are used to estimate a simple statistical model involving an autoregressive process with an additive term specific to the unit. Different assumptions about the initial conditions are (a) initial state fixed, (b) initial state random, (c) the unobserved individual effect independent of the unobserved dynamic process with the initial value fixed, and (d) the unobserved individual effect independent of the unobserved dynamic process with initial value random. Asymptotic properties of the maximum likelihood and “covariance” estimators are obtained when T → ∞ and when N → ∞. The relationship between the pseudo and conditional maximum likelihood estimators is clarified. A simple consistent estimator that is independent of the initial conditions and the way in which T or N → ∞ is also suggested.
This paper considers estimation and testing of vector autoregressio n coefficients in panel data, and applies the techniques to analyze the dynamic relationships between wages an d hours worked in two samples of American males. The model allows for nonstationary individual effects and is estimated by applying instrumental variables to the quasi-differenced autoregressive equations. The empirical results suggest the absence of lagged hours in the wage forecasting equation. The results also show that lagged hours is important in the hours equation. Copyright 1988 by The Econometric Society.
The primary aim of the paper is to place current methodological discussions in macroeconometric modeling contrasting the ‘theory first’ versus the ‘data first’ perspectives in the context of a broader methodological framework with a view to constructively appraise them. In particular, the paper focuses on Colander’s argument in his paper “Economists, Incentives, Judgement, and the European CVAR Approach to Macroeconometrics” contrasting two different perspectives in Europe and the US that are currently dominating empirical macroeconometric modeling and delves deeper into their methodological/philosophical underpinnings. It is argued that the key to establishing a constructive dialogue between them is provided by a better understanding of the role of data in modern statistical inference, and how that relates to the centuries old issue of the realisticness of economic theories.
This article develops, tests of covariance restrictions after estimating by three-stage least squares a dynamic random effects
model from panel data. The asymptotic distribution of covariance matrix estimates under non-normality is obtained. It is shown
how minimum chi-square tests for interesting covariance restrictions can be calculated from a generalised linear regression
involving the sample autocovariances and dummy variables. Asymptotic efficiency exploiting covariance restrictions can also
be attained using a GLS estimator.
In this paper we present and estimate an adjustment cost model of industry employment which takes explicit account of both
expectations and aggregation over different labour types. The resulting model is subject to a large number of tests and is
a highly robust representation of the data. Finally forecasts are produced for manufacturing employment up to 1990.
Dynamic Panel Data Estimation Using DPD-A Guide for Users" (Institute for Fiscal Studies, Working Paper 88
- M Arellano
- S R Bond
ARELLANO, M. and BOND, S. R. (1988a), "Dynamic Panel Data Estimation Using DPD-A Guide for Users" (Institute for Fiscal Studies, Working Paper 88/15, London).
Panel Data Handbook of EconometricsIntertemporal Employment and Pricing Decision Rules in UK Manufacturing
- G Chamberlain
CHAMBERLAIN, G. (1984), "Panel Data", in Griliches, Z. and Intriligator, M. D. (eds.), Handbook of Econometrics, Volume IL (Amsterdam: Elsevier Science Publishers.) DOLADO, J. J. (1987), "Intertemporal Employment and Pricing Decision Rules in UK Manufacturing" (University of Oxford, Applied Economics Discussion Paper 18).
Analysis of Panel Data
- C Hsiao
HSIAO, C. (1986) Analysis of Panel Data (Cambridge: Cambridge University Press).
The reference numbering from the original has been maintained in this citation list. Specification Tests in
NOTE: The reference numbering from the original has been maintained in this citation list.
Specification Tests in Econometrics
J. A. Hausman
Econometrica, Vol. 46, No. 6. (Nov., 1978), pp. 1251-1271.
org/sici?sici=0162-1459%28198109%2976%3A375%3C598%3AEODMWE%3E2.0.CO%3B2-Q Testing for Autocorrelation in Dynamic Random Effects Models Manuel Arellano The Review of Economic Studies
- Url Stable
Stable URL:
http://links.jstor.org/sici?sici=0162-1459%28198109%2976%3A375%3C598%3AEODMWE%3E2.0.CO%3B2-Q
Testing for Autocorrelation in Dynamic Random Effects Models
Manuel Arellano
The Review of Economic Studies, Vol. 57, No. 1. (Jan., 1990), pp. 127-134.
- T W Anderson
Estimation of Dynamic Models with Error Components
T. W. Anderson; Cheng Hsiao
Journal of the American Statistical Association, Vol. 76, No. 375. (Sep., 1981), pp. 598-606.
org/sici?sici=0012-9682%28198203%2950%3A2%3C483%3AIVRWIO%3E2.0.CO%3B2-L 4 Panel Data and Unobservable Individual Effects Jerry A. Hausman; William E
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4 Panel Data and Unobservable Individual Effects
Jerry A. Hausman; William E. Taylor
Econometrica, Vol. 49, No. 6. (Nov., 1981), pp. 1377-1398.
org/sici?sici=0012-9682%28198311%2951%3A6%3C1635%3AEDREMF%3E2.0.CO%3B2-X 4 Instrumental-Variable Estimation of an Error-Components Model Takeshi Amemiya; Thomas E
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4 Instrumental-Variable Estimation of an Error-Components Model
Takeshi Amemiya; Thomas E. MaCurdy
Econometrica, Vol. 54, No. 4. (Jul., 1986), pp. 869-880.
Intertemporal Employment and Pricing Decision Rules in UK Manufacturing
DOLADO, J. J. (1987), "Intertemporal Employment and Pricing Decision Rules in UK Manufacturing"
(University of Oxford, Applied Economics Discussion Paper 18).
jstor.org/sici?sici=0012-9682%28198311%2951%3A6%3C1635%3AEDREMF%3E2.0.CO%3B2-X Large Sample Properties of Generalized Method of Moments Estimators Lars Peter Hansen Econometrica
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Large Sample Properties of Generalized Method of Moments Estimators
Lars Peter Hansen
Econometrica, Vol. 50, No. 4. (Jul., 1982), pp. 1029-1054.
Estimating Vector Autoregressions with Panel Data Douglas Holtz-Eakin
- S Rosen Harvey
- Econometrica
Estimating Vector Autoregressions with Panel Data
Douglas Holtz-Eakin; Whitney Newey; Harvey S. Rosen
Econometrica, Vol. 56, No. 6. (Nov., 1988), pp. 1371-1395.