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1
Kruiniger, Hugo. "GMM ESTIMATION AND INFERENCE IN DYNAMIC PANEL DATA MODELS WITH PERSISTENT DATA." Econometric Theory 25, no. 5 (October 2009): 1348–91. http://dx.doi.org/10.1017/s0266466608090531.
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In this paper we consider generalized method of moments–based (GMM-based) estimation and inference for the panel AR(1) model when the data are persistent and the time dimension of the panel is fixed. We find that the nature of the weak instruments problem of the Arellano–Bond (Arellano and Bond, 1991,Review of Economic Studies58, 277–297) estimator depends on the distributional properties of the initial observations. Subsequently, we derive local asymptotic approximations to the finite-sample distributions of the Arellano–Bond estimator and the System estimator, respectively, under a variety of distributional assumptions about the initial observations and discuss the implications of the results we obtain for doing inference. We also propose two Lagrange multiplier–type (LM-type) panel unit root tests.
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Shina, Arya Fendha Ibnu. "ESTIMASI PARAMETER PADA SISTEM MODEL PERSAMAAN SIMULTAN DATA PANEL DINAMIS DENGAN METODE 2 SLS GMM-AB." MEDIA STATISTIKA 11, no. 2 (December 30, 2018): 79–91. http://dx.doi.org/10.14710/medstat.11.2.79-91.
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Single equation models ignore interdependencies or two-way relationships between response variables. The simultaneous equation model accommodates this two-way relationship form. Two Stage Least Square Generalized Methods of Moment Arellano and Bond (2 SLS GMM-AB) is used to estimate the parameters in the simultaneous system model of dynamic panel data if each structural equation is exactly identified or over identified. In the simultaneous equation system model with dynamic panel data, each structural equation and reduced form is a dynamic panel data regression equation. Estimation of structural equations and reduced form using Ordinary Least Square (OLS) resulted biased and inconsistent estimators. Arellano and Bond GMM method (GMM AB) estimator produces unbiased, consistent, and efficient estimators.The purpose of this paper is to explain the steps of 2 SLS GMM-AB method to estimate parameter in simultaneous equation model with dynamic panel data. Keywords:2 SLS GMM-AB, Arellano and Bond estimator, Dynamic Panel Data, Simultaneous Equations
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Sebki, Wafa. "Education and Economic Growth in Developing Countries: Empirical Evidence from GMM Estimators for Dynamic Panel Data." Economics and Business 35, no. 1 (February 1, 2021): 14–29. http://dx.doi.org/10.2478/eb-2021-0002.
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Abstract The paper aims at studying the effect of education measured by enrolment ratios in secondary and higher education on economic growth measured by the rate of GDP growth in a sample of 40 developing countries during the period from 2002 to 2016 using the dynamic panel data estimators. The results of estimating the model of this study using the difference GMM estimator or what is known as the Arellano and Bond estimator showed that the proportions of those enrolled in tertiary education had a significant positive effect on economic growth, while the proportions of those enrolled in secondary education had a significant negative effect.
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Ehizuelen, Michael Mitchell Omoruyi. "China's Infrastructure Financing and the Role of Infrastructure in Awakening African Economies." Journal of Comparative Asian Development 18, no. 2 (July 2021): 1–25. http://dx.doi.org/10.4018/jcad.20210701.oa2.
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African economies, through Agenda 2063, recognize that developing infrastructure – transport, electricity, energy, water, and e-connectivity – will be critical for the region to assume a lasting place in the global economic system. As a result, this paper addresses the continent’s infrastructure gap and provides an important insight into the rapidly growing presence of China’s official infrastructure financing in Africa as well as the distinctive character of its involvement. In addition, the paper provides an empirical evaluation of the role of infrastructure in awakening African economies. The generalized-method-of-moments (GMM) estimator for dynamic models of panel data developed by Arellano and Bond (1991), and Arellano and Bover (1995) was employed to estimate an infrastructure-increased growth model.
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Mickiewicz, Tomasz, Kate Bishop, and Urmas Varblane. "Financial Constraints in Investment. Panel Data Results From Estonia, 1995-1999." Acta Oeconomica 54, no. 4 (December 1, 2004): 425–49. http://dx.doi.org/10.1556/aoecon.54.2004.4.2.
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To investigate investment behaviour the present study applies panel data techniques, in particular the Arellano-Bond (1991) GMM estimator, based on data on Estonian manufacturing firms from the period 1995-1999. We employ the model of optimal capital accumulation in the presence of convex adjustment costs. The main research findings are that domestic companies seem to be financially more constrained than those where foreign investors are present, and also, smaller firms are more constrained than their larger counterparts.
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Višić, Josipa, and Blanka Škrabić Perić. "The determinants of value of incoming cross-border mergers & acquisitions in European transition countries." Communist and Post-Communist Studies 44, no. 3 (August 10, 2011): 173–82. http://dx.doi.org/10.1016/j.postcomstud.2011.07.004.
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This research aims to determine variables that affect the aggregate value of incoming cross-border M&As in European transitional countries. Dynamic panel models have been estimated using Arellano and Bond GMM estimator for period between year 1994 and 2008. The ratio of the total value of cross-border M&A to GDP of the country is the dependent variable. Independent variables include following indicators: lagged value of cross-border M&A to GDP, lagged GDP per capita, lagged GDP growth, inflation, interest rate spread, lagged private credit to GDP ratio, market capitalization to GDP ratio, lagged rule of law and lagged control of corruption.
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Cheng, Ningning, and Youngsok Bang. "A Comment on the Practice of the Arellano-Bond/Blundell-Bond Generalized Method of Moments Estimator in IS Research." Communications of the Association for Information Systems 48, no. 1 (2021): 423–42. http://dx.doi.org/10.17705/1cais.04838.
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Mazhar, Ummad. "Does regulatory discretion increase the unofficial economy? Evidence from panel data." Acta Oeconomica 65, no. 1 (March 1, 2015): 129–41. http://dx.doi.org/10.1556/aoecon.65.2015.1.7.
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One factor that contributes in the size of the shadow economy is the regulation of business activities. This paper provides empirical analysis of the effects of regulatory discretion on the unofficial economy. It adds to the previous findings by gathering evidence from a large data set of 162 countries for the 1999 to 2007 period. Going beyond simple correlation, it uses the Arellano-Bond estimator to investigate the dynamics and causal effects of regulation on the shadow economy. We find that increase in regulation increases the size of the shadow economy.
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Miao, Ruiqing. "Impact of Ethanol Plants on Local Land Use Change." Agricultural and Resource Economics Review 42, no. 2 (August 2013): 291–309. http://dx.doi.org/10.1017/s106828050000438x.
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We investigate effects of corn-based ethanol plants on local land uses using county-level panel data for Iowa for 1997 through 2009 and an Arellano-Bond difference-generalized method-of-moments estimator. Our results show that ethanol plants have statistically significant effects on the proportion of acres planted to corn in the plants’ host counties. Furthermore, ceteris paribus, the land-use-change effect of locally owned plants (owned by local farmers or cooperatives) is about twice as large as the effect of plants with nonlocal owners. We also explore implications for the environment of ethanol plants and the changes in land use that they induce.
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BALIAMOUNE-LUTZ, MINA. "DO INSTITUTIONS AND SOCIAL COHESION ENHANCE THE EFFECTIVENESS OF AID? NEW EVIDENCE FROM AFRICA." Journal of International Commerce, Economics and Policy 03, no. 01 (February 2012): 1240003. http://dx.doi.org/10.1142/s1793993312400030.
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This paper explores the effects of aid, institutions, and social cohesion on per capita income growth in 34 African countries using the Arellano-Bond dynamic panel GMM estimator. The paper focuses on the interplay of aid and institutions and the interplay of aid and social cohesion. The empirical results indicate that social cohesion enhances the growth effects of aid but there is a threshold effect, suggesting that aid becomes effective in enhancing growth in countries with higher social cohesion. Surprisingly, the results show that beyond a certain level of improvements in institutional quality, institutions (political rights and civil liberties) reduce the effectiveness of aid.
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Gómez-Trueba Santamaría, Paula, Alfredo Arahuetes García, and Tomás Curto González. "A tale of five stories: Defence spending and economic growth in NATO´s countries." PLOS ONE 16, no. 1 (January 11, 2021): e0245260. http://dx.doi.org/10.1371/journal.pone.0245260.
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This article examines the relationship between defence expenditure and its impact on the growth of NATO’s countries between 2005 and 2018. The aim is to determine if this relation exists and to test if it is possible to discover different models across the countries. The results obtained using the Arellano–Bond estimator, suggest that there is more than one model, and confirm, through the poolability test, the existence of five different groups of countries within the Alliance, with different impacts of the defence expenditure on their gross domestic product. These findings are in line with the review of existing literature that reveals heterogeneity in the results due to different parameters used.
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Buhaerah, Pihri. "INFLUENCE OF FINANCIALIZATION OF INCOME INEQUALITY IN ASEAN: DATA PANEL ANALYSIS." Buletin Ekonomi Moneter dan Perbankan 19, no. 3 (March 30, 2017): 335–52. http://dx.doi.org/10.21098/bemp.v19i3.669.
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This paper examines the impact of financialization on income inequality in ASEAN-5 countries for the period of 1990-2013 by employing panel data analysis. The data was collected from various secondary sources by undertaking fixed effect model and generalized method moment. The result shows that there is a significant relationship between all financialization indicators and income distribution. Generalized method moment analysis using Arellano-Bond estimator also shows that all financialization indicators have a significant relationship with income distribution. There is no different sign estimator both in fixed model effect and generalized method moment analysis. This paper revealed that financialization indicators such as stock market capitalization and return on assets contribute positively to worsen income inequlality. Incontrast, domestic private debt securities have a negative effect on gini coefficient in ASEAN-5 countries indicating that increasing domestic private debt securities will improve income distribution in the region.
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Kim, Kyungho. "Revisiting The Relationship Between Financial And Environmental Performance: Does Granger Causality Matter?" Journal of Applied Business Research (JABR) 31, no. 5 (September 1, 2015): 1861. http://dx.doi.org/10.19030/jabr.v31i5.9396.
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This study rigorously investigates two ongoing issues about the relationship between environmental performance and financial performance: its sign (negative or positive) and direction of causation. The results from the longitudinal sample of US heavy-polluting industries between 1991 and 2005 support the positive relationship between EP and FP. We also test the Granger causal relationship by applying Arellano-Bond estimator. The results present that the causal direction is contingent on the selection of financial performance measures and on the characteristics of sub-groups classified by environmental performance. Namely, we find that the causality is valid only in high pollution-intensive industry group in terms of the one-year lagged accounting-based FP. A weak reverse direction was found only in the pollution-intensive industry group with Tobins q. The findings clearly suggest that it is necessary to use a consistent estimator when examining causality with longitudinal data in a dynamic setting.
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Huay, Chong Siew, and Yasmin Bani. "Remittances, poverty and human capital: evidence from developing countries." International Journal of Social Economics 45, no. 8 (August 13, 2018): 1227–35. http://dx.doi.org/10.1108/ijse-10-2017-0454.
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Purpose The purpose of this paper is to analyze the relationship between remittances and poverty through the human capital channel in developing countries, which has received less attention in the literature. Design/methodology/approach The paper applied the system GMM developed by Arellano and Bond (1991) and Arellano and Bover (1995) containing 54 developing countries. This estimator is appropriate compared to a cross-section technique because it controls for the endogeneity of all explanatory variables, includes unobserved country-specific effects and allows for the inclusion of lagged dependent variables. Findings The results suggest that, while remittances reduced poverty, the effect is moderated via education. A 1 percent increase in remittances reduces the poverty headcount by 0.47 percent, while the reduction is 0.33 percent via education. The marginal effect of remittances is negatively related to the level of education, indicating that education mitigates the effect of remittances on poverty. Practical implications This paper includes the implications for the policymakers to justify the need for more effective approaches. It is useful to identify whether and how remittances and human capital interact in their effect on poverty when deciding the most desirable allocation of available resources between these two priorities. Originality/value This paper takes a step forward filling the limited evidence on the role of human capital in remittances–poverty relationship in developing countries. Different from the existing studies which have used the traditional panel estimators, this study utilizes the dynamic panel estimators such as system GMM to tackle the specification issues of endogeneity, measurement errors and heterogeneity.
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Pošta, Vít, and Marta Nečadová. "Economic Performance and Competitiveness Indicators: The Case of African Economies." Periodica Polytechnica Social and Management Sciences 29, no. 2 (August 13, 2021): 145–58. http://dx.doi.org/10.3311/ppso.15184.
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This paper presents a statistical analysis of the relationship between economic performance and competitiveness indicators to address the question of the extent to which competitiveness indicators provideuseful information when assessing economic performance. The analysis was performed on various examples of African economies. The possible relationships between economic performance and competitiveness indicators were examined by extending a basic relationship between economic performance per capita and investment by competitiveness indicators. The models were estimated by means of an Arellano-Bond estimator. The authors detected many statistically significant relationships between economic performance and competitiveness indicators in the cases of both the whole sample and specifically middle-income economies. However, in the case of low-income economies there are no discernible relationships between economic performance and the information included in the competitiveness indicators. The paper contributes to the analysis of the economic performance of African economies, for which the empirical evaluation of possible links between economic performance and competitiveness indicators is altogether missing.
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Chávez, Carlos Cesar. "The Impact of Macroeconomics Factors on Real Exchange Rate in Latin America:." Latin American Journal of Trade Policy 3, no. 8 (December 31, 2020): 6. http://dx.doi.org/10.5354/0719-9368.2020.57342.
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This paper studies the determinants of the real exchange rate using macroeconomic variables, and whether they can predict it. A panel data is used, which estimator is system GMM that allows controlling the endogeneity of the variables. In turn, we transformed the variables with forward orthogonal deviations (FOD) and first difference (FD), which allows us to eliminate unobserved effects that are invariant in time. To check the robustness of the estimates, different periods were used, from 1980-2019, 2000-2019 and 2010-2019. For the period 1980-2019, it is found that the past values of the real exchange rate, the current values of inflation, economic growth, fiscal and monetary policy have positive effects on the current values of the real exchange rate, while the money supply and the terms of trade have negative impacts on the real exchange rate. For the period 2000-2019, we had similar results and for the period 2010-2019, we found that economic growth has negative impacts on the real exchange rate. It is also presented the Arellano-Bond test and the Sargan test to estimate model over-identification. Using the Pedroni test, we estimated the cointegration of the variables with respect to the real exchange rate, finding cointegration with inflation in the long run. The originality of this paper is that we focused on Latin American countries, analyzing short-term relationships with the System GMM estimator and long-term relationships with the Pedroni Test.
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Huay, Chong Siew, Jonathan Winterton, Yasmin Bani, and Bolaji Tunde Matemilola. "Do remittances promote human development? Empirical evidence from developing countries." International Journal of Social Economics 46, no. 10 (October 20, 2019): 1173–85. http://dx.doi.org/10.1108/ijse-12-2018-0673.
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Purpose The purpose of this paper is to analyse the impact of remittances on human development in developing countries using panel data from 1980 to 2014 and to address the critical question of whether the increasing trend of remittances has any impact on human development in a broad range of developing countries. Design/methodology/approach Usual panel estimates, such as pooled OLS, fixed or random effects model, possess specification issues such as endogeneity, heterogeneity and measurement errors. In this paper, we, therefore, apply dynamic panel estimates – System generalised method of moment (Sys-GMM) developed by Arellano and Bond (1991) and Arellano and Bover (1995). This estimator is able to control for the endogeneity of all the explanatory variables, account for unobserved country-specific effects that cannot be done using country dummies due to the dynamic structure of the model (Azman-Saini et al., 2010). Findings The effect of remittances is statistically significant with positive coefficients in developing countries. The significant coefficient of remittances means that, holding other variables constant, a rise in remittance inflows is associated with improvements in human development. A 10 per cent increase in remittances will lead to an increase of approximately 0.016 per cent in human development. These findings are consistent with Üstubuci and Irdam (2012) and Adenutsi (2010), who found evidence that remittances are positively correlated with human development. Practical implications The paper considers implications for policymakers to justify the need for more effective approaches. Policymakers need to consider indicators of human development and to devise public policies that promote income, health and education, to enhance human development. Originality/value The question of whether remittances affect human development has rarely been subject to systematic empirical study. Extant research does not resolve the endogeneity problem, whereas the present study provides empirical evidence by utilising dynamic panel estimators such as Sys-GMM to tackle the specification issues of endogeneity, measurement errors and heterogeneity. The present study provides a benchmark for future research on the effect of remittances on human development.
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Emir Tuncay, Ferhan, and Hulya Cengiz. "The Relationship between Corporate Profitability and Macroeconomic Indicators: Evidence from 500 Largest Industrial Organizations in Turkey." International Business Research 10, no. 9 (August 14, 2017): 87. http://dx.doi.org/10.5539/ibr.v10n9p87.
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The purpose of this study is to examine the impact of chosen macroeconomic indicators on industrial corporate performance. In the analysis, economic profitability ratios of Turkey’s top 500 industrial firms, which represent the Turkish economy, have been used to estimate performance. In order to determine the effects of macroeconomic indicators, panel data with a non-linear instrumental variables estimator, Arellano Bond generalized methodology of moments (GMM) was used between the period of 2002 and 2012. As a result of the analysis, gross domestic product, inflation rate, the rate of domestic debt interest payments to the net new borrowing and the rate of domestic debt interest payments to total income tax have a direct relationship with corporate performance. On the other hand, exchange rate, interest rate and the rate of short term foreign debts to central bank international reserves have an inverse relationship.
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Bon, Nguyen Van. "Does FDI inflow crowd in private investment? Empirical evidence for the Southeast region of Vietnam from the panel quantile regression approach." HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ECONOMICS AND BUSINESS ADMINISTRATION 11, no. 2 (August 14, 2021): 127–36. http://dx.doi.org/10.46223/hcmcoujs.econ.en.11.2.1802.2021.
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Well-known to be the most dynamic economic region in Vietnam with the establishment of more export processing zones, high technology parks, and industrial zones, the Southeast region is increasingly attracting more capital flows from all over the world. Does FDI inflow crowd in private investment in this region? To answer this research question, the study examines the effect of FDI inflow on private investment for a sample of 6 provinces/cities of the Southeast region between 2005 and 2019 using the panel quantile regression approach, the difference GMM Arellano-Bond, and the FE-IV estimator. The results show that FDI inflow crowds in private investment in this region. In addition, public expenditure, inflation, and population also promote private investment. These findings suggest some crucial policy implications for local governments in this region to receive more FDI inflows as well as promote private investment.
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Vlahinić Lenz, Nela, and Barbara Fajdetić. "Globalization and GHG Emissions in the EU: Do We Need a New Development Paradigm?" Sustainability 13, no. 17 (September 4, 2021): 9936. http://dx.doi.org/10.3390/su13179936.
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The European Union (EU) has adopted a new development strategy based on “green” growth and announced carbon neutrality by 2050. Still, the EU’s previous development path was mainly based on trade openness and globalization, with positive economic and negative climate impacts. The aim of this paper was to test the hypothesis of globalization-induced carbon emissions in order to evaluate a possible future development path. The Arellano–Bond estimator was employed for dynamic panel analysis in 26 EU countries over the period 2000–2018. A significant and positive relationship was found between economic globalization and passenger mobility and greenhouse gas (GHG) emissions, while environmental taxes can correct the negative climate effect. On the other hand, social and political dimensions of globalization reduce negative climate impacts. To achieve net zero emissions, the EU needs to continue its global climate leadership, extend the use of environmental taxes, and stimulate economic growth based on low-carbon technologies such as hydrogen, energy storage, and CCUS.
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Kryeziu, Nexhat, and Egzon Hoxha. "Factors affecting on bank’s profitability: the case of 19 Euro-Area countries." Jurnal Perspektif Pembiayaan dan Pembangunan Daerah 9, no. 1 (April 30, 2021): 1–8. http://dx.doi.org/10.22437/ppd.v9i1.12165.
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The paper has addressed as the main objective the assessment of productivity performance in euro-area nations, observing a combination of factors both in terms of the internal environment and external factors, or known as macroeconomic factors. The analysis includes 19 euro-area countries with 323 observations, including the period 2003-2019. The dynamic approach, the fixed-effect model, and the Arellano / Bond estimator were applied using the panel data to evaluate the study's factors. The analysis shows that the factors under the competence of their internal supervision impact the degree of profitability on the one hand. Macroeconomic factors also show an impact on the degree of profitability for euro-area countries. Five of the seven factors applied in the analysis turned out to significantly impact, while two turned out to be non-significant. For further studies, it would be beneficial to apply other dynamic models by using other specific factors, which will be considered a useful input to the financial industry and financial policy-making.
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Kunaedi, Agung, and Darwanto Darwanto. "Central Bank Independence and Inflation: The Matters of Financial Development and Institutional Quality." Signifikan: Jurnal Ilmu Ekonomi 9, no. 1 (February 8, 2020): 1–14. http://dx.doi.org/10.15408/sjie.v9i1.12899.
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The inverse relationship between the independence of the central bank (CBI) and inflation became a consensus that trusted throughout the world. However, there is no conclusive explanation of why and how central bank independence has succeeded in suppressing inflation. The purpose of this study is to examine the influence of financial development and institutional quality on the relationship between central bank independence and inflation. Using 20 Countries of Asia with institutional diversity, this study analyzed through a dynamic panel approach (GMM-Arellano and Bond Estimator). The result indicates that the inverse relationship between central bank independence and inflation depends on the development of the financial sector and also the institutional quality of each country. In other words, to make the central bank's independence work effectively in order to solve bias inflation, the improvement of the financial sector and also the institutional quality is needed.JEL Classification : E580, E310, E020 How to Cite:Kunaedi, A., & Darwanto. (2020). Central Bank Independence and Inflation: The Matters of Financial Development and Institutional Quality. Signifikan: Jurnal Ilmu Ekonomi, Vol. 9(1), 1-14. doi: http://dx.doi.org/10.15408/sjie.v9i1.12899.
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Mendoza, Rufo, and John Paolo R. Rivera. "The Effect of Credit Risk and Capital Adequacy on the Profitability of Rural Banks in the Philippines." Scientific Annals of Economics and Business 64, no. 1 (March 1, 2017): 83–96. http://dx.doi.org/10.1515/saeb-2017-0006.
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Abstract This paper examines the credit risk and capital adequacy of the 567 rural banks in the Philippines to investigate how both variables affect bank profitability. Using the Arellano-Bond estimator, we found out that credit risk has a negative and statistically significant relationship with profitability. However, empirical analysis showed that capital adequacy has no significant impact on the profitability of rural banks in the Philippines. It is therefore necessary for the rural banks to examine more deeply if capital infusion would result in higher profitability than increasing debts. The study also implies that it is imperative for the banks to understand which risk factors have greater impact on their financial performance and use better risk-adjusted performance measurement to support their strategies. Rural banks should establish credit risk management that defines the process from initiation to approval of loans, taking into consideration the sound credit risk management practices issued by regulatory bodies. Moreover, rural banks need to enhance internal control measures to ensure the strict implementation of internal processes on lending operations.
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Mendoza, Rufo, and John Paolo R. Rivera. "The Effect of Credit Risk and Capital Adequacy on the Profitability of Rural Banks in the Philippines." Annals of the Alexandru Ioan Cuza University - Economics 64, no. 1 (March 1, 2017): 83–96. http://dx.doi.org/10.1515/aicue-2017-0006.
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Abstract This paper examines the credit risk and capital adequacy of the 567 rural banks in the Philippines to investigate how both variables affect bank profitability. Using the Arellano-Bond estimator, we found out that credit risk has a negative and statistically significant relationship with profitability. However, empirical analysis showed that capital adequacy has no significant impact on the profitability of rural banks in the Philippines. It is therefore necessary for the rural banks to examine more deeply if capital infusion would result in higher profitability than increasing debts. The study also implies that it is imperative for the banks to understand which risk factors have greater impact on their financial performance and use better risk-adjusted performance measurement to support their strategies. Rural banks should establish credit risk management that defines the process from initiation to approval of loans, taking into consideration the sound credit risk management practices issued by regulatory bodies. Moreover, rural banks need to enhance internal control measures to ensure the strict implementation of internal processes on lending operations.
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Butkus, Mindaugas, Kristina Matuzeviciute, Dovile Rupliene, and Janina Seputiene. "Does Unemployment Responsiveness to Output Change Depend on Age, Gender, Education, and the Phase of the Business Cycle?" Economies 8, no. 4 (November 11, 2020): 98. http://dx.doi.org/10.3390/economies8040098.
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The impact of economic growth on unemployment is commonly agreed and extensively studied. However, how age and gender shape this relationship is not as well explored, while there is an absence of research on whether education plays a role. We apply Okun’s law, aiming to estimate age-, gender- and educational attainment level-specific unemployment rate sensitivity to cyclical output fluctuations. Since the empirical literature provides evidence in favour of the non-linear impact of output change on the unemployment rate, supporting higher effects of recessions than that of expansions, we aim to enrich this analysis by estimating how the impact of positive/negative output change on the specific unemployment rate varies with the level of the total unemployment. The analysis is based on 28 European Union (EU) countries and covers the period of 1995–2019. The equations are estimated by least-squares dummy variables (LSDV), using Prais–Winsten standard errors. For the robustness check, we alternatively used Newey–West standard errors to address serial-correlations and heteroscedasticity, and the Arellano–Bond estimator for some specifications that assume dynamics in the panel. The results support previous findings of male- and youth-specific Okun’s coefficients and reveal that they significantly stand out just over the periods of negative output change. Additionally, we find that educational attainment level is an important factor explaining the heterogeneity of unemployment reaction to output change.
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Jiang, Weiling, Igor Martek, M. Reza Hosseini, Jolanta Tamošaitienė, and Chuan Chen. "FOREIGN INFRASTRUCTURE INVESTMENT IN DEVELOPING COUNTRIES: A DYNAMIC PANEL DATA MODEL OF POLITICAL RISK IMPACTS." Technological and Economic Development of Economy 25, no. 2 (February 7, 2019): 134–67. http://dx.doi.org/10.3846/tede.2019.7632.
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Foreign direct investment (FDI) is inhibited by political risk. Developing countries tend to experience higher levels of such risk, yet need foreign capital to generate growth. Moreover, foreign direct investment in infrastructure (FDII) – fundamental to economic growth – is particularly sensitive to political risk; characterized by high capital investment, longer investment periods, while especially exposed to mercurial shifts in government policy. Yet, no comprehensive study has been undertaken that measures the impact of political risk on FDII in developing countries. This paper addresses this lack. Twelve political risk indicators, drawn from the International Country Risk Guide Index, are used to quantify the political risk inherent to 90 developing countries, over the period 2006 to 2015. An Arellano-Bond GMM estimator is developed which measures the dollar value impact of risk on both FDI and FDII. A comparison of results confirms that FDII is generally more sensitive to risk than is FDI, however the influence of risk categories is found to vary significantly. The findings can be expected to inform infrastructure policy-makers and foreign investors alike on the dollar-impact of determinable risk levels on foreign-funded projects, and in so doing better facilitate corrective risk mitigation strategies.
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Joshi, Prathibha, and Kris Aaron Beck. "Biological Oxygen Demand and Economic Growth: An Empirical Investigation." Water Economics and Policy 01, no. 02 (June 2015): 1550001. http://dx.doi.org/10.1142/s2382624x15500010.
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Economic development frequently contributes to a decline in water quality; industrial effluents entering the water cause an increase of bacteria that strip the water of its oxygen, often then leading to mass die-offs of other aquatic life. However, the environmental Kuznets curve (EKC) suggests that rising water pollution due to continuing economic growth ultimately stabilizes and then decreases, thus eventually resulting in more oxygenated water that can meet the biological oxygen demand (BOD) required by aquatic life. Yet previous studies have found mixed results for a BOD EKC, with some researchers confirming the inverted U scale of the EKC but others finding different patterns. We therefore re-evaluate the interaction between economic growth and water quality by using a balanced dataset from 1979–1995 and the more dynamic econometric technique of Arellano–Bover/Blundell–Bond generalized methods of moments (GMM) estimator. We compare different samples of OECD and non-OECD countries to determine the likelihood of an EKC. The results show that the OECD countries have an N-shaped curve and that the EKC only emerges with a general sample of non-OECD countries.
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Halili, Enver, Ali Salman Saleh, and Rami Zeitun. "Governance and long-term operating performance of family and non-family firms in Australia." Studies in Economics and Finance 32, no. 4 (October 5, 2015): 398–421. http://dx.doi.org/10.1108/sef-02-2014-0034.
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Purpose – The purpose of this study is to conduct a comparative analysis of the long-term operating performance of family and non-family firms from the agency theoretic perspective. The analysis is focused on investigating the impact of family ownership on principal–agent conflicts of interest. Design/methodology/approach – This paper examines the relationship between firm operating performance and family ownership for a large sample of 677 Australian-listed companies. The paper uses the Generalised Method of Moments (GMM) estimator model developed by Arellano and Bond (1991) and used by other studies in finance (Baltagi, 2012; Bond, 2002; Mohamed et al., 2008). Findings – The empirical results show that firms with ownership concentration has a better operating performance due to the alignment of owner-management interests. This study also finds that family-listed companies have higher survival rates and perform better than non-family companies. Findings support the hypothesis that agency costs arise as a result of privileged access of information and self-interest behaviour of managers (outsiders) in firms with dispersed ownership structures. Originality/value – Earlier studies have only focused on short-term perspectives, particularly investigating small and medium types of Australian family businesses from narrow aspects, such as productivity, business behaviour, capital structure and leverage. Therefore, this paper has conducted a comparative examination of family and non-family firms listed on the Australian Stock Exchange (ASX) to identify the impact of agency costs on their financial performance.
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Bougatef, Khemaies, and Fakhri Korbi. "The determinants of intermediation margins in Islamic and conventional banks." Managerial Finance 44, no. 6 (June 11, 2018): 704–21. http://dx.doi.org/10.1108/mf-11-2016-0327.
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Purpose The distinctive feature of Islamic financial intermediation is its foundation on profit-and-loss sharing which reinforces solidarity and fraternity between partners. Thus, the bank margin and its determinants may differ between Islamic and conventional banks (CBs). The purpose of this paper is to empirically assess the main factors that explain the bank margin in a panel of Islamic and CBs operating in the Middle East and North Africa (MENA) region. This study will permit to identify the common and the specific determinants of the intermediation margins in dual banking systems. Design/methodology/approach The authors use a dynamic panel approach. The empirical analysis is carried out for a sample of 50 Islamic banks (IBs) and 126 CBs from 14 MENA countries. Findings The results reveal that net profit margins of IBs may be explained for the most part by risk aversion, inefficiency, diversification and economic conditions. With regard to CBs, their margins depend positively on market concentration and risk aversion and negatively on specialization, diversification, inefficiency and liquidity. Practical implications The significant impact of the degree of diversification on margins suggests that any policy analysis of the pricing behavior of banks should rely on its whole output. The high levels of margins in Islamic and CBs based in the MENA region may represent an obstacle to these countries to pursue their development process. Thus, policy makers in these countries should consolidate the role of capital markets and nonbanking financial institutions to provide alternative sources of funding and stimulate more competition. Social implications The positive relationship between concentration and net interest margins requires that policy makers should create competitive conditions if they want to lower the social cost of financial intermediation. The creation of competitive conditions may be achieved through encouraging the establishment of new domestic banks or the penetration of foreign banks. Originality/value The present study aims to contribute to the existing literature on the determinants of bank margins in three ways. First, the authors identify the factors that most explain bank margins for both conventional and IBs. The majority of previous studies examine the determinants of the profitability or the overall performance of banks and in particular conventional ones. Second, this paper employs two generalized method of moments (GMM) approaches introduced by Arellano and Bover (1995) and Arellano and Bond (1991). It differs from Hutapea and Kasri (2010) who employed the co-integration technique to examine the long-run relationship between Islamic and CB margins and their determinants in Indonesia. Third, unlike previous studies focusing on MENA region that use a small number of countries and a short sample period, the period of study covers 16 years from 1999 to 2014 and a large sample of countries (14 countries). This paper differs from Lee and Isa (2017) who applied the dynamic two-step GMM estimator technique introduced by Arellano and Bond (1991) to study the determinants of intermediation margins of Islamic and CBs located in Malaysia.
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Gluszak, Michal, Agnieszka Malkowska, and Bartłomiej Marona. "Green Building Adoption on Office Markets in Europe: An Empirical Investigation into LEED Certification." Energies 14, no. 7 (April 2, 2021): 1971. http://dx.doi.org/10.3390/en14071971.
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The goal of the paper is to evaluate the impact of selected factors on the adoption of LEED (Leadership in Energy and Environmental Design) green building certification in Europe. In the empirical part of the paper we track the fraction of LEED-registered office space in selected European cities, and assess the impact of selected socioeconomic and environmental factors on the certification adoption rate. This research contributes to the ongoing debate about the adoption of green buildings in commercial property markets. In this paper, we investigate factors affecting the adoption of LEED certification using the Arellano and Bond generalized method-of-moments estimator. Compared to prior studies, which relied on cross-sectional data, our research uses a panel approach to investigate the changes in green building adoption rates in selected European cities. Among the cities that are quickly adopting LEED are Frankfurt, Warsaw, Stockholm, and Dublin. The adoption process was not equally fast in Brussels and Copenhagen. Using the dynamic panel model approach, we found that the adoption of green building certification is linked to overall innovativeness in the economy and the perceived greenness of the city. Contrary to some previous studies we did not observe links between the size of the office market and the LEED adoption rate.
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Ahmed, Shakeel, M. Ejaz Majeed, Eleftherios Thalassinos, and Yannis Thalassinos. "The Impact of Bank Specific and Macro-Economic Factors on Non-Performing Loans in the Banking Sector: Evidence from an Emerging Economy." Journal of Risk and Financial Management 14, no. 5 (May 11, 2021): 217. http://dx.doi.org/10.3390/jrfm14050217.
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The current study examines macro-economic and bank specific determinants of non-performing loans (NPLs) for commercial banks from 2008–2018. The Pakistani banking sector has observed a significant increase in NPLs. In addition, the current study is undertaken to fill this gap in the literature as most of the prior studies focus on the developed markets. In the current study, we prefer the system GMM estimator. Its reliability depends on the validity of the instruments. To testing the second-order serial correlation, we apply the J test for testing the validity of the instruments and the Arellano–Bond AR (2) test. Using dynamic-GMM estimations, we find that credit growth, net interest margin, loan loss provision, and bank diversification significantly increase NPLs, while operating efficiency, bank size, and ROA lower NPLs. In addition, higher interest rates, exchange rates, and political risk significantly increase NPLs, while GDP growth decreases NPLs. This paper provides a timely insight to management and policy makers about the determinants of NPLs. The findings help management to take corrective actions and policy makers may take into consideration the significance of macro-economic conditions while formulating policy regarding NPLs. Likewise, the study provides insight to potential investors to consider the findings while selecting better investment opportunity. The current study is the first of its kind focusing on the link among bank specific, macroeconomic variables, and non-performing loans within the specific context of an emerging economy, Pakistan.
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Lee, Siew Peng, and Mansor Isa. "Determinants of bank margins in a dual banking system." Managerial Finance 43, no. 6 (June 12, 2017): 630–45. http://dx.doi.org/10.1108/mf-07-2016-0189.
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Purpose The purpose of this paper is to determine of bank margins for conventional and Islamic banks in the dual banking system in Malaysia. Design/methodology/approach The study uses unbalanced panel data for 20 conventional banks and 16 Islamic banks over the period 2008-2014. The dynamic two-step GMM estimator technique introduced by Arellano and Bond (1991) is applied. Findings The results suggest that there are significant similarities with minor differences in terms of factors determining bank margins between conventional and Islamic banks in Malaysia. The margins for conventional banks are influenced by operating costs, efficiency, credit risk, degree of risk aversion, market share, size of operation, implicit interest payments and funding costs. For Islamic banks, the margin determinants are found to be operating costs, efficiency, credit risk, market share and implicit interest payments. This means that more factors influence the margins in conventional banks compared to Islamic banks. Although bank diversification activities have increased in recent years, their impact on bank margins is minimal. Practical implications The results suggest that improving operational costs, operational efficiency and credit risk management, and minimising implicit interest payments would be the best strategy to enhance the bank margins for both conventional and Islamic banks. The results also have important policy implications on the necessity to expand the size of Islamic banking in Malaysia. Originality/value There are relatively few studies concerning determinants of bank margins in emerging markets. The present study adds to the literature by presenting evidence from Malaysia, an emerging market with a dual banking system. This allows us to explore the similarities and differences between conventional and Islamic banks in Malaysia in respect of determinants of the margins.
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Ghenimi, Ameni, Hasna Chaibi, and Mohamed Ali Brahim Omri. "Liquidity risk determinants: Islamic vs conventional banks." International Journal of Law and Management 63, no. 1 (November 18, 2020): 65–95. http://dx.doi.org/10.1108/ijlma-03-2018-0060.
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Purpose This paper aims to identify and analyze the similarities and differences of the liquidity risk determinants within conventional and Islamic banks. Design/methodology/approach This study uses a dynamic panel data approach to examine the relationship between liquidity risk and a set of bank-specific and macroeconomic factors during 2005–2015, by selecting 27 Islamic banks and 49 conventional ones operating in the MENA region. More specifically, the dynamic two-step generalized method of moment estimator technique introduced by Arellano and Bond (1991) is applied. Findings The results suggest that the set of bank-specific variables influences the liquidity risk of both banking systems, while macroeconomic factors determine the liquidity risk of conventional banks. Islamic banks are not affected by macroeconomic determinants. Practical implications The research facilitates to the academicians, practitioners and bankers to have an alluded picture about liquidity risk determinants and their management. The findings can be used by bankers’ policy decision-makers to improve and enhance their consideration for liquidity risk management in both banking systems. Indeed, the study makes them aware to manage liquidity risk differently between conventional and Islamic banks, as the results reveal different liquidity risk determinants. Originality/value Compared to the abundant studies on the determinants of credit risk, researchers have not sufficiently addressed the factors influencing liquidity risk. Moreover, none of these few research studies has discussed and compared liquidity risk determinants within both banking systems operating in the Middle East and North Africa (MENA) region. This leads us to identify the similarities and differences between conventional and Islamic banks in the MENA region in respect of systematic and unsystematic determinants of the liquidity risk. The value is attributed to the increasing differentiation between Islamic and conventional banks. Islamic banks are characterized with a different liquidity structure distinguishing them from their conventional counterparts.
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Charith, Krishnamoorthy, and Andrey Davydenko. "Informational Value of Dividend Initiations: Impact of Cash Dividends on Share Prices of Manufacturing Companies in Sri Lanka." International Journal of Economics and Finance 13, no. 3 (February 5, 2021): 13. http://dx.doi.org/10.5539/ijef.v13n3p13.
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The shareholder wealth consists of dividends and capital gains. The former is considered to be risk averse, whereas the latter is perceived to be risky. The risk return trade-off in these two returns drives the investor preference. The objective of a for-profit organization is to maximize shareholders’ wealth, however, disbursing dividends may not always be in the best interest of shareholders. Theoretically, retained earnings increase share prices as firms have more funds to be invested. The objective of the study is to measure the stimulus of cash dividends on share prices. We conduct empirical analysis based on data relating to companies listed on the Colombo Stock Exchange (CSE) under the manufacturing sector. As we show in our literature review, in order to reduce the risk of obtaining spurious results, this analysis requires the use of advanced modelling techniques allowing to model non-stationarity of time series, as well the presence of control variables and lagged variables. The novelty of our study is in the use of advanced modelling and data visualisation techniques (including the ‘xdPlot’ dataviz framework recently proposed by the authors), especially in application to CSE data. We conduct a thorough exploratory data analysis (EDA) aiming to spot data anomalies and initiate appropriate data transformations. Given the results of EDA and the nature of the data available, we select the Arellano-Bond estimator as the most adequate method for regression analysis. Market Price per share (MPS) termed as the dependent variable, whereas Dividend per Share (DPS) is viewed as the independent variable. The results validated theoretical literature such as signaling effect and bird in hand theory, but questioned some previous empirical studies. The study validated cash dividends as stimulus to investors given the positive relationship between DPS and MPS.
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Neves, Maria Elisabete, Zélia Serrasqueiro, António Dias, and Cristina Hermano. "Capital structure decisions in a period of economic intervention." International Journal of Accounting & Information Management 28, no. 3 (March 9, 2020): 465–95. http://dx.doi.org/10.1108/ijaim-08-2019-0094.
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Purpose This paper aims to analyse the Portuguese companies’ determinants of capital structure. To reach this objective, the authors used data from 37 non-financial Portuguese large enterprises and from 4,233 non-financial small and medium enterprises for the period 2010-2016. Additionally, the authors selected a sub-period from 2010 to 2014 for a deeper understanding of the impact of the sovereign debt crisis and the Economic Adjustment Programme of Troika on the capital structure of those companies. Design/methodology/approach Three dependent variables were tested according to debt maturity, and a dynamic panel data model, namely, the generalised method of moments system estimator, was used to test the formulated research hypotheses following Arellano and Bover (1995) and Blundell and Bond (1998) to capture the dynamic nature of the firm’s capital structure decisions. Findings In general, the results point out that the capital structure decisions depend on a set of firm-specific factors, and that the effects of the determinants of the debt maturity ratios differ according to the type of firm, i.e. large/small firms, and the economic cycle. Originality/value To the best of the authors’ knowledge, this is the first study that has been carried out in Portugal by using two samples of large and small companies for analysing the effects of the Economic Adjustment Programme of Troika on the capital structure of companies. The authors seek to understand which type of companies suffered more because of the effects of the Economic Adjustment Programme of Troika during this period, and which are the capital structure determinants that present greater change. Contrary to what might be expected, large companies are the firms that suffer most from the Economic Adjustment Programme. Probably, because these companies are the most immediate, most scrutinised and those that must show abroad that the bank did not fund them in the long term, because of the imposition and limits to grant credit faced by the banks themselves.
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Jouber, Habib. "Corporate social responsibility and earnings quality: do institutional features matter?" Journal of Global Responsibility 11, no. 1 (November 21, 2019): 54–92. http://dx.doi.org/10.1108/jgr-04-2019-0041.
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Purpose This paper aims to examine whether corporate social responsibility (CSR) is associated with firms’ earnings quality (EQ) and how this association is context-specific. The authors consider specific institutional differences in strength of corporate governance (CG) attributes, quality of law enforcement and level of investor protection found between Anglo-American, European and South-Eastern Asian CG models to test the impact of above country-level factors on this association. Design/methodology/approach To test the association between CSR and EQ, the authors consider EIRIS (Ethical Investment Research Service) (2018) CSR issues of sustainability indicators as proxy to capture CSR. Following Rezaee and Tuo’s (2019) study, the authors classify EQ into innate earnings quality (IEQ) and discretionary earnings quality (DEQ). The authors investigate the innate (discretionary) EQ as to refer to firm’s inherent operating uncertainty (earnings management). Several dependency models for panel data applying the generalized method of moment (GMM) estimator of Arellano and Bond (1991) are ruled based on archival data of 4,206 non-financial international listed firms over the period 2012-2017. Findings Univariate and GMM multivariate cross-country analyses show that CSR is positively associated with EQ and that this association is more pronounced for firms within countries where good CG tools and higher investor right protection are preserved. The authors interpret the findings as evidence that the CSR-EQ association is shaped by the degree of monitoring role played by institutional features at the country level. The results are robust to a battery of robustness tests. Originality/value The originality of this research is twice. On the one hand, it examines whether CSR is a reflection of manager’s ethical opportunistic behavior resultant on earnings quality derived from a firm’s innate traits. On the second hand, it tests whether CSR is a reflection of discretionary earnings quality manifested by earnings management behavior. This paper is the first to support that institutional features significantly matter when investigating the association between CSR and EQ.
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Welch, Sarah B., Dinushi Amanda Kulasekere, P. V. Vara Prasad, Charles B. Moss, Robert Leo Murphy, Chad J. Achenbach, Michael G. Ison, et al. "The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data." JMIR Public Health and Surveillance 7, no. 6 (June 17, 2021): e24251. http://dx.doi.org/10.2196/24251.
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Background COVID-19 transmission rates in South Asia initially were under control when governments implemented health policies aimed at controlling the pandemic such as quarantines, travel bans, and border, business, and school closures. Governments have since relaxed public health restrictions, which resulted in significant outbreaks, shifting the global epicenter of COVID-19 to India. Ongoing systematic public health surveillance of the COVID-19 pandemic is needed to inform disease prevention policy to re-establish control over the pandemic within South Asia. Objective This study aimed to inform public health leaders about the state of the COVID-19 pandemic, how South Asia displays differences within and among countries and other global regions, and where immediate action is needed to control the outbreaks. Methods We extracted COVID-19 data spanning 62 days from public health registries and calculated traditional and enhanced surveillance metrics. We use an empirical difference equation to measure the daily number of cases in South Asia as a function of the prior number of cases, the level of testing, and weekly shifts in variables with a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano–Bond estimator in R. Results Traditional surveillance metrics indicate that South Asian countries have an alarming outbreak, with India leading the region with 310,310 new daily cases in accordance with the 7-day moving average. Enhanced surveillance indicates that while Pakistan and Bangladesh still have a high daily number of new COVID-19 cases (n=4819 and n=3878, respectively), their speed of new infections declined from April 12-25, 2021, from 2.28 to 2.18 and 3.15 to 2.35 daily new infections per 100,000 population, respectively, which suggests that their outbreaks are decreasing and that these countries are headed in the right direction. In contrast, India’s speed of new infections per 100,000 population increased by 52% during the same period from 14.79 to 22.49 new cases per day per 100,000 population, which constitutes an increased outbreak. Conclusions Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.
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Post, Lori, Kasen Culler, Charles B. Moss, Robert L. Murphy, Chad J. Achenbach, Michael G. Ison, Danielle Resnick, et al. "Surveillance of the Second Wave of COVID-19 in Europe: Longitudinal Trend Analyses." JMIR Public Health and Surveillance 7, no. 4 (April 28, 2021): e25695. http://dx.doi.org/10.2196/25695.
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Background The COVID-19 pandemic has severely impacted Europe, resulting in a high caseload and deaths that varied by country. The second wave of the COVID-19 pandemic has breached the borders of Europe. Public health surveillance is necessary to inform policy and guide leaders. Objective This study aimed to provide advanced surveillance metrics for COVID-19 transmission that account for weekly shifts in the pandemic, speed, acceleration, jerk, and persistence, to better understand countries at risk for explosive growth and those that are managing the pandemic effectively. Methods We performed a longitudinal trend analysis and extracted 62 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in Europe as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results New COVID-19 cases slightly decreased from 158,741 (week 1, January 4-10, 2021) to 152,064 (week 2, January 11-17, 2021), and cumulative cases increased from 22,507,271 (week 1) to 23,890,761 (week 2), with a weekly increase of 1,383,490 between January 10 and January 17. France, Germany, Italy, Spain, and the United Kingdom had the largest 7-day moving averages for new cases during week 1. During week 2, the 7-day moving average for France and Spain increased. From week 1 to week 2, the speed decreased (37.72 to 33.02 per 100,000), acceleration decreased (0.39 to –0.16 per 100,000), and jerk increased (–1.30 to 1.37 per 100,000). Conclusions The United Kingdom, Spain, and Portugal, in particular, are at risk for a rapid expansion in COVID-19 transmission. An examination of the European region suggests that there was a decrease in the COVID-19 caseload between January 4 and January 17, 2021. Unfortunately, the rates of jerk, which were negative for Europe at the beginning of the month, reversed course and became positive, despite decreases in speed and acceleration. Finally, the 7-day persistence rate was higher during week 2 than during week 1. These measures indicate that the second wave of the pandemic may be subsiding, but some countries remain at risk for new outbreaks and increased transmission in the absence of rapid policy responses.
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Oehmke, James Francis, Theresa B. Oehmke, Lauren Nadya Singh, and Lori Ann Post. "Dynamic Panel Estimate–Based Health Surveillance of SARS-CoV-2 Infection Rates to Inform Public Health Policy: Model Development and Validation." Journal of Medical Internet Research 22, no. 9 (September 22, 2020): e20924. http://dx.doi.org/10.2196/20924.
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Background SARS-CoV-2, the novel coronavirus that causes COVID-19, is a global pandemic with higher mortality and morbidity than any other virus in the last 100 years. Without public health surveillance, policy makers cannot know where and how the disease is accelerating, decelerating, and shifting. Unfortunately, existing models of COVID-19 contagion rely on parameters such as the basic reproduction number and use static statistical methods that do not capture all the relevant dynamics needed for surveillance. Existing surveillance methods use data that are subject to significant measurement error and other contaminants. Objective The aim of this study is to provide a proof of concept of the creation of surveillance metrics that correct for measurement error and data contamination to determine when it is safe to ease pandemic restrictions. We applied state-of-the-art statistical modeling to existing internet data to derive the best available estimates of the state-level dynamics of COVID-19 infection in the United States. Methods Dynamic panel data (DPD) models were estimated with the Arellano-Bond estimator using the generalized method of moments. This statistical technique enables control of various deficiencies in a data set. The validity of the model and statistical technique was tested. Results A Wald chi-square test of the explanatory power of the statistical approach indicated that it is valid (χ210=1489.84, P<.001), and a Sargan chi-square test indicated that the model identification is valid (χ2946=935.52, P=.59). The 7-day persistence rate for the week of June 27 to July 3 was 0.5188 (P<.001), meaning that every 10,000 new cases in the prior week were associated with 5188 cases 7 days later. For the week of July 4 to 10, the 7-day persistence rate increased by 0.2691 (P=.003), indicating that every 10,000 new cases in the prior week were associated with 7879 new cases 7 days later. Applied to the reported number of cases, these results indicate an increase of almost 100 additional new cases per day per state for the week of July 4-10. This signifies an increase in the reproduction parameter in the contagion models and corroborates the hypothesis that economic reopening without applying best public health practices is associated with a resurgence of the pandemic. Conclusions DPD models successfully correct for measurement error and data contamination and are useful to derive surveillance metrics. The opening of America involves two certainties: the country will be COVID-19–free only when there is an effective vaccine, and the “social” end of the pandemic will occur before the “medical” end. Therefore, improved surveillance metrics are needed to inform leaders of how to open sections of the United States more safely. DPD models can inform this reopening in combination with the extraction of COVID-19 data from existing websites.
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Post, Lori, Ramael O. Ohiomoba, Ashley Maras, Sean J. Watts, Charles B. Moss, Robert Leo Murphy, Michael G. Ison, et al. "Latin America and the Caribbean SARS-CoV-2 Surveillance: Longitudinal Trend Analysis." JMIR Public Health and Surveillance 7, no. 4 (April 27, 2021): e25728. http://dx.doi.org/10.2196/25728.
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Background The COVID-19 pandemic has placed unprecedented stress on economies, food systems, and health care resources in Latin America and the Caribbean (LAC). Existing surveillance provides a proxy of the COVID-19 caseload and mortalities; however, these measures make it difficult to identify the dynamics of the pandemic and places where outbreaks are likely to occur. Moreover, existing surveillance techniques have failed to measure the dynamics of the pandemic. Objective This study aimed to provide additional surveillance metrics for COVID-19 transmission to track changes in the speed, acceleration, jerk, and persistence in the transmission of the pandemic more accurately than existing metrics. Methods Through a longitudinal trend analysis, we extracted COVID-19 data over 45 days from public health registries. We used an empirical difference equation to monitor the daily number of cases in the LAC as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano–Bond estimator in R. COVID-19 transmission rates were tracked for the LAC between September 30 and October 6, 2020, and between October 7 and 13, 2020. Results The LAC saw a reduction in the speed, acceleration, and jerk for the week of October 13, 2020, compared to the week of October 6, 2020, accompanied by reductions in new cases and the 7-day moving average. For the week of October 6, 2020, Belize reported the highest acceleration and jerk, at 1.7 and 1.8, respectively, which is particularly concerning, given its high mortality rate. The Bahamas also had a high acceleration at 1.5. In total, 11 countries had a positive acceleration during the week of October 6, 2020, whereas only 6 countries had a positive acceleration for the week of October 13, 2020. The TAC displayed an overall positive trend, with a speed of 10.40, acceleration of 0.27, and jerk of –0.31, all of which decreased in the subsequent week to 9.04, –0.81, and –0.03, respectively. Conclusions Metrics such as new cases, cumulative cases, deaths, and 7-day moving averages provide a static view of the pandemic but fail to identify where and the speed at which SARS-CoV-2 infects new individuals, the rate of acceleration or deceleration of the pandemic, and weekly comparison of the rate of acceleration of the pandemic indicate impending explosive growth or control of the pandemic. Enhanced surveillance will inform policymakers and leaders in the LAC about COVID-19 outbreaks.
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Post, Lori, Michael J. Boctor, Tariq Z. Issa, Charles B. Moss, Robert Leo Murphy, Chad J. Achenbach, Michael G. Ison, et al. "SARS-CoV-2 Surveillance System in Canada: Longitudinal Trend Analysis." JMIR Public Health and Surveillance 7, no. 5 (May 10, 2021): e25753. http://dx.doi.org/10.2196/25753.
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Background The COVID-19 global pandemic has disrupted structures and communities across the globe. Numerous regions of the world have had varying responses in their attempts to contain the spread of the virus. Factors such as public health policies, governance, and sociopolitical climate have led to differential levels of success at controlling the spread of SARS-CoV-2. Ultimately, a more advanced surveillance metric for COVID-19 transmission is necessary to help government systems and national leaders understand which responses have been effective and gauge where outbreaks occur. Objective The goal of this study is to provide advanced COVID-19 surveillance metrics for Canada at the country, province, and territory level that account for shifts in the pandemic including speed, acceleration, jerk, and persistence. Enhanced surveillance identifies risks for explosive growth and regions that have controlled outbreaks successfully. Methods Using a longitudinal trend analysis study design, we extracted 62 days of COVID-19 data from Canadian public health registries for 13 provinces and territories. We used an empirical difference equation to measure the daily number of cases in Canada as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results We compare the week of February 7-13, 2021, with the week of February 14-20, 2021. Canada, as a whole, had a decrease in speed from 8.4 daily new cases per 100,000 population to 7.5 daily new cases per 100,000 population. The persistence of new cases during the week of February 14-20 reported 7.5 cases that are a result of COVID-19 transmissions 7 days earlier. The two most populous provinces of Ontario and Quebec both experienced decreases in speed from 7.9 and 11.5 daily new cases per 100,000 population for the week of February 7-13 to speeds of 6.9 and 9.3 for the week of February 14-20, respectively. Nunavut experienced a significant increase in speed during this time, from 3.3 daily new cases per 100,000 population to 10.9 daily new cases per 100,000 population. Conclusions Canada excelled at COVID-19 control early on in the pandemic, especially during the first COVID-19 shutdown. The second wave at the end of 2020 resulted in a resurgence of the outbreak, which has since been controlled. Enhanced surveillance identifies outbreaks and where there is the potential for explosive growth, which informs proactive health policy.
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Oehmke, James Francis, Charles B. Moss, Lauren Nadya Singh, Theresa Bristol Oehmke, and Lori Ann Post. "Dynamic Panel Surveillance of COVID-19 Transmission in the United States to Inform Health Policy: Observational Statistical Study." Journal of Medical Internet Research 22, no. 10 (October 5, 2020): e21955. http://dx.doi.org/10.2196/21955.
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Background The Great COVID-19 Shutdown aimed to eliminate or slow the spread of SARS-CoV-2, the virus that causes COVID-19. The United States has no national policy, leaving states to independently implement public health guidelines that are predicated on a sustained decline in COVID-19 cases. Operationalization of “sustained decline” varies by state and county. Existing models of COVID-19 transmission rely on parameters such as case estimates or R0 and are dependent on intensive data collection efforts. Static statistical models do not capture all of the relevant dynamics required to measure sustained declines. Moreover, existing COVID-19 models use data that are subject to significant measurement error and contamination. Objective This study will generate novel metrics of speed, acceleration, jerk, and 7-day lag in the speed of COVID-19 transmission using state government tallies of SARS-CoV-2 infections, including state-level dynamics of SARS-CoV-2 infections. This study provides the prototype for a global surveillance system to inform public health practice, including novel standardized metrics of COVID-19 transmission, for use in combination with traditional surveillance tools. Methods Dynamic panel data models were estimated with the Arellano-Bond estimator using the generalized method of moments. This statistical technique allows for the control of a variety of deficiencies in the existing data. Tests of the validity of the model and statistical techniques were applied. Results The statistical approach was validated based on the regression results, which determined recent changes in the pattern of infection. During the weeks of August 17-23 and August 24-30, 2020, there were substantial regional differences in the evolution of the US pandemic. Census regions 1 and 2 were relatively quiet with a small but significant persistence effect that remained relatively unchanged from the prior 2 weeks. Census region 3 was sensitive to the number of tests administered, with a high constant rate of cases. A weekly special analysis showed that these results were driven by states with a high number of positive test reports from universities. Census region 4 had a high constant number of cases and a significantly increased persistence effect during the week of August 24-30. This change represents an increase in the transmission model R value for that week and is consistent with a re-emergence of the pandemic. Conclusions Reopening the United States comes with three certainties: (1) the “social” end of the pandemic and reopening are going to occur before the “medical” end even while the pandemic is growing. We need improved standardized surveillance techniques to inform leaders when it is safe to open sections of the country; (2) varying public health policies and guidelines unnecessarily result in varying degrees of transmission and outbreaks; and (3) even those states most successful in containing the pandemic continue to see a small but constant stream of new cases daily.
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Oehmke, Theresa B., Lori A. Post, Charles B. Moss, Tariq Z. Issa, Michael J. Boctor, Sarah B. Welch, and James F. Oehmke. "Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis." Journal of Medical Internet Research 23, no. 2 (February 9, 2021): e26081. http://dx.doi.org/10.2196/26081.
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Background The COVID-19 pandemic has had profound and differential impacts on metropolitan areas across the United States and around the world. Within the United States, metropolitan areas that were hit earliest with the pandemic and reacted with scientifically based health policy were able to contain the virus by late spring. For other areas that kept businesses open, the first wave in the United States hit in mid-summer. As the weather turns colder, universities resume classes, and people tire of lockdowns, a second wave is ascending in both metropolitan and rural areas. It becomes more obvious that additional SARS-CoV-2 surveillance is needed at the local level to track recent shifts in the pandemic, rates of increase, and persistence. Objective The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk and persistence, and weekly shifts, to better understand and manage risk in metropolitan areas. Existing surveillance measures coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until, and after, an effective vaccine is developed. Here, we provide values for novel indicators to measure COVID-19 transmission at the metropolitan area level. Methods Using a longitudinal trend analysis study design, we extracted 260 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in the 25 largest US metropolitan areas as a function of the prior number of cases and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results Minneapolis and Chicago have the greatest average number of daily new positive results per standardized 100,000 population (which we refer to as speed). Extreme behavior in Minneapolis showed an increase in speed from 17 to 30 (67%) in 1 week. The jerk and acceleration calculated for these areas also showed extreme behavior. The dynamic panel data model shows that Minneapolis, Chicago, and Detroit have the largest persistence effects, meaning that new cases pertaining to a specific week are statistically attributable to new cases from the prior week. Conclusions Three of the metropolitan areas with historically early and harsh winters have the highest persistence effects out of the top 25 most populous metropolitan areas in the United States at the beginning of their cold weather season. With these persistence effects, and with indoor activities becoming more popular as the weather gets colder, stringent COVID-19 regulations will be more important than ever to flatten the second wave of the pandemic. As colder weather grips more of the nation, southern metropolitan areas may also see large spikes in the number of cases.
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Post, Lori Ann, Elana T. Benishay, Charles B. Moss, Robert Leo Murphy, Chad J. Achenbach, Michael G. Ison, Danielle Resnick, et al. "Surveillance Metrics of SARS-CoV-2 Transmission in Central Asia: Longitudinal Trend Analysis." Journal of Medical Internet Research 23, no. 2 (February 3, 2021): e25799. http://dx.doi.org/10.2196/25799.
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Background SARS-CoV-2, the virus that caused the global COVID-19 pandemic, has severely impacted Central Asia; in spring 2020, high numbers of cases and deaths were reported in this region. The second wave of the COVID-19 pandemic is currently breaching the borders of Central Asia. Public health surveillance is necessary to inform policy and guide leaders; however, existing surveillance explains past transmissions while obscuring shifts in the pandemic, increases in infection rates, and the persistence of the transmission of COVID-19. Objective The goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully. Methods Using a longitudinal trend analysis study design, we extracted 60 days of COVID-19–related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results COVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight. Conclusions The rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia.
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Chen, Shuowen, Victor Chernozhukov, and Iván Fernández-Val. "Mastering Panel Metrics: Causal Impact of Democracy on Growth." AEA Papers and Proceedings 109 (May 1, 2019): 77–82. http://dx.doi.org/10.1257/pandp.20191071.
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We revisit the panel data analysis of Acemoglu et al. (forthcoming) on the relationship between democracy and economic growth using state-of-the-art econometric methods. We argue that panel data settings are high-dimensional, resulting in estimators to be biased to a degree that invalidates statistical inference. We remove these biases by using simple analytical and sample-splitting methods, and thereby restore valid statistical inference. We find that debiased fixed effects and Arellano-Bond estimators produce higher estimates of the long-run effect of democracy on growth, providing even stronger support for the key hypothesis of Acemoglu et al.
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Hu, Yi, Dongmei Guo, Ying Deng, and Shouyang Wang. "Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/672610.
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This paper suggests a generalized method of moments (GMM) based estimation for dynamic panel data models with individual specific fixed effects and threshold effects simultaneously. We extend Hansen’s (Hansen, 1999) original setup to models including endogenous regressors, specifically, lagged dependent variables. To address the problem of endogeneity of these nonlinear dynamic panel data models, we prove that the orthogonality conditions proposed by Arellano and Bond (1991) are valid. The threshold and slope parameters are estimated by GMM, and asymptotic distribution of the slope parameters is derived. Finite sample performance of the estimation is investigated through Monte Carlo simulations. It shows that the threshold and slope parameter can be estimated accurately and also the finite sample distribution of slope parameters is well approximated by the asymptotic distribution.
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Post, Lori Ann, Jasmine S. Lin, Charles B. Moss, Robert Leo Murphy, Michael G. Ison, Chad J. Achenbach, Danielle Resnick, et al. "SARS-CoV-2 Wave Two Surveillance in East Asia and the Pacific: Longitudinal Trend Analysis." Journal of Medical Internet Research 23, no. 2 (February 1, 2021): e25454. http://dx.doi.org/10.2196/25454.
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Background The COVID-19 pandemic has had a profound global impact on governments, health care systems, economies, and populations around the world. Within the East Asia and Pacific region, some countries have mitigated the spread of the novel coronavirus effectively and largely avoided severe negative consequences, while others still struggle with containment. As the second wave reaches East Asia and the Pacific, it becomes more evident that additional SARS-CoV-2 surveillance is needed to track recent shifts, rates of increase, and persistence associated with the pandemic. Objective The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk, persistence, and weekly shifts, to better understand country risk for explosive growth and those countries who are managing the pandemic successfully. Existing surveillance coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until an effective vaccine is developed. We provide novel indicators to measure disease transmission. Methods Using a longitudinal trend analysis study design, we extracted 330 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in East Asia and the Pacific as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results The standard surveillance metrics for Indonesia, the Philippines, and Myanmar were concerning as they had the largest new caseloads at 4301, 2588, and 1387, respectively. When looking at the acceleration of new COVID-19 infections, we found that French Polynesia, Malaysia, and the Philippines had rates at 3.17, 0.22, and 0.06 per 100,000. These three countries also ranked highest in terms of jerk at 15.45, 0.10, and 0.04, respectively. Conclusions Two of the most populous countries in East Asia and the Pacific, Indonesia and the Philippines, have alarming surveillance metrics. These two countries rank highest in new infections in the region. The highest rates of speed, acceleration, and positive upwards jerk belong to French Polynesia, Malaysia, and the Philippines, and may result in explosive growth. While all countries in East Asia and the Pacific need to be cautious about reopening their countries since outbreaks are likely to occur in the second wave of COVID-19, the country of greatest concern is the Philippines. Based on standard and enhanced surveillance, the Philippines has not gained control of the COVID-19 epidemic, which is particularly troubling because the country ranks 4th in population in the region. Without extreme and rigid social distancing, quarantines, hygiene, and masking to reverse trends, the Philippines will remain on the global top 5 list of worst COVID-19 outbreaks resulting in high morbidity and mortality. The second wave will only exacerbate existing conditions and increase COVID-19 transmissions.
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Jolly Cyril, Edison, and Harish Kumar Singla. "Comparative analysis of profitability of real estate, industrial construction and infrastructure firms: evidence from India." Journal of Financial Management of Property and Construction 25, no. 2 (May 4, 2020): 273–91. http://dx.doi.org/10.1108/jfmpc-08-2019-0069.
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Purpose This study aims to identify the most profitable segment of construction firms amongst real estate, industrial construction and infrastructure. This paper also examines the determinants of profitability of real estate, industrial construction and infrastructure firms. Design/methodology/approach The data of 67 firms (20 real estate, 21 industrial construction and 26 infrastructure) is collected for a 15-year period (2003–2017). Two models are created using total return on assets (ROA) and return on invested capital (ROIC) as dependent variables.. Leverage, liquidity, age, growth, size and efficiency of the firm are identified as firm-specific independent variables. Two economic variables, i.e. growth in GDP and inflation, are also used as independent variables. Initially, the models are tested for stationarity, multicollinearity and heteroscedasticity, and finally, the coefficients are estimated using Arellano–Bond dynamic panel data estimation to account for heteroscedasticity and endogeneity. Findings The results suggest that industrial construction is the most profitable segment of construction, followed by real estate and infrastructure. Their profitability is positively driven by liquidity, efficiency and leverage. The real estate firms are somewhat less profitable compared to industrial construction firms, and their profitability is positively driven by liquidity. The infrastructure firms have low ROA and ROIC. Originality/value The real estate, infrastructure and industrial construction drastically differ from each other. The challenges involved in real estate, infrastructure and industrial construction are altogether different. Therefore, authors present a comparative analysis of the profitability of real estate, infrastructure and industrial construction segments of the construction and compare their determinants of profitability. The results provided in the study are robust and reliable because of the use of a superior econometric model, i.e. Arellano–Bond dynamic panel data estimation with robust estimates, which accounts for heteroscedasticity and endogeneity in the model.
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Ahmad, Sardar Shakeel, Atif Ali Jaffri, Faisal Rana, and Asadullah Khan. "IMPACT OF CURRENT ACCOUNT GAPS ON INFLATION IN SOUTH ASIAN COUNTRIES." Humanities & Social Sciences Reviews 9, no. 3 (June 21, 2021): 1056–62. http://dx.doi.org/10.18510/hssr.2021.93104.
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Purpose of the study: The current study estimated the impact of current account gaps (CAGAP) on inflation in South Asian countries, namely, Pakistan, Bangladesh, India, Nepal, and Sri Lanka.
Methodology: CAGAP is estimated through macroeconomic fundamentals by applying panel time series data methodology from 1990 to 2018. We adopted the bias-corrected least square dummy variable (LSDVC) estimation technique for the time series macro and dynamic panel to find the impact of CAGAP on inflation.
Principal findings: CAGAP negatively affected consumer price inflation rate while Lag of inflation, trade openness, age dependency, and oil prices positively affected inflation rate in the selected sample countries. In LSDVC, the Blundell and Bond (BB), Arellano-Bond (AB), Anderson and Hsiao (AH) estimates are determined while system and difference GMM estimates also confirmed the results. Therefore, LSDVC-AB is selected from the three versions of LSDVC as baseline regression based on higher significance and lower standard error.
Applications of the Study: CAGAP affects inflation, so it should be estimated annually in all these countries for macroeconomic stability as IMF annually estimates for developed countries in an external sector report. It is worthwhile to estimate CAN regularly and watch it for CAB evaluation and future Adjustment. Based on the results, the study recommends that tailored policies and interventions focus on the structural distortions and slow-changing factors to eradicate CAGAP.
Novelty/ Originality of the Study: A few empirical studies have scrutinized the role of CAB on macroeconomic variables. No empirical study on CAGAP and its consequences are available in the selected region's existing literature to the best of our knowledge.
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Zyphur, Michael J., Manuel C. Voelkle, Louis Tay, Paul D. Allison, Kristopher J. Preacher, Zhen Zhang, Ellen L. Hamaker, et al. "From Data to Causes II: Comparing Approaches to Panel Data Analysis." Organizational Research Methods 23, no. 4 (May 24, 2019): 688–716. http://dx.doi.org/10.1177/1094428119847280.
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This article compares a general cross-lagged model (GCLM) to other panel data methods based on their coherence with a causal logic and pragmatic concerns regarding modeled dynamics and hypothesis testing. We examine three “static” models that do not incorporate temporal dynamics: random- and fixed-effects models that estimate contemporaneous relationships; and latent curve models. We then describe “dynamic” models that incorporate temporal dynamics in the form of lagged effects: cross-lagged models estimated in a structural equation model (SEM) or multilevel model (MLM) framework; Arellano-Bond dynamic panel data methods; and autoregressive latent trajectory models. We describe the implications of overlooking temporal dynamics in static models and show how even popular cross-lagged models fail to control for stable factors over time. We also show that Arellano-Bond and autoregressive latent trajectory models have various shortcomings. By contrasting these approaches, we clarify the benefits and drawbacks of common methods for modeling panel data, including the GCLM approach we propose. We conclude with a discussion of issues regarding causal inference, including difficulties in separating different types of time-invariant and time-varying effects over time.