General diagnostic tests for cross-sectional dependence in panels

This paper studies the validity of Gibrat’s law for the growth of Slovenian farms between 2007 and 2015 using Farm Accountancy Data Network datasets. Cross-sectional dependence test and four different groups of panel unit root tests are applied to study the relationship between farm size and the farm size growth. It revealed evidence of cross-sectional dependence in farm sizes. Both input (land and labour) and output (economic) sizes of variables as proxy for the measures of farm size are applied. The results suggest that Gibrat’s law is valid for Slovenian farms independently from the measures of farm size and types of panel unit root tests. Slovenian smaller farms are not growing faster than larger ones and thus all farm sizes tend to contribute to an increase in average farm size in generally relatively small- to medium-size farm structures.

This study investigates an AR (autoregressive)-filtered version of several conventional diagnostic tests for cross-sectional dependence in large mixed panels when both N and T are large, including the adjusted Lagrangian Multiplier test (LM), the cross-section dependence test (CD), and the Schott test. We show that conventional tests of cross-sectional dependence based on Pearson correlation coefficients could diverge if the components are not all I(0) processes and the modified tests possess the asymptotical normality property. The distinctive feature of these new tests is their ease of implementation, even though the exact time series properties of each component of a mixed panel are unknown or unobservable in practice. Simulations show that the AR-filtered version of the CD test (CDAR ) performs well relative to the other testing procedures in the finite sample and computation time, especially for those cases with a large cross-sectional dimension. Given the good statistical properties of CDAR test, we also propose to use it as an early warning indicator for market risk or crisis.

In panel data analysis, the cross-sectional dependence (CD) test has been extensively used to test the cross-sectional dependence. However, this traditional CD test does not take serial correlation into consideration, which commonly occurs in many fields. To solve this problem, we propose an adjusted CD test which is able to effectively handle serial correlation. More specifically, the serial correlation can be of arbitrary form in our work. Furthermore, we establish the theoretical properties of the proposed adjusted CD test. Our extensive Monte Carlo experiments show that the traditional CD test cannot work well under serial correlation, while the proposed adjusted CD test does provide rather satisfactory performance.

This study empirically investigated financial development moderating task on the connection allying various types of financial inflows (foreign direct investment, foreign portfolio investment, foreign debt flows, and remittances) and economic growth in the West Africa sub-region, while accounting for cross sectional dependence existence. The analysis is motivated by the need to understand how financial development level influences financial inflow effectiveness in economic growth promotion, given the interconnectedness and potential spillover effects among countries in the region. Drawing from a panel dataset spanning 1990-2022 for five West African countries, a range of econometric techniques was employed to address cross-sectional dependence and slope heterogeneity, among which includes: slope homogeneity tests, cross-sectional dependence tests, second-generation panel unit root tests, and estimation methods robust to cross-sectional dependence, such as Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators. Using the CCEMG estimator, financial development exerted a positive and significant influence on economic growth, and its interaction with foreign portfolio investment was also positive and significant. The AMG estimator provided additional insights, showing remittances had a positive impact on growth, while foreign portfolio investment negatively affected growth. Notably, the interaction between financial development and remittances was negative and significant under the AMG model. These mixed results suggest that while financial development generally promotes growth, its interactions with different types of capital flows can have varying and even opposing effects depending on the specific combination and empirical approach used. The study concludes that financial development engages in a crucial moderating task in the connection allying financial inflows and economic growth in the West Africa sub-region, with varying effects across different types of financial inflows. The findings underscore the relevance of accounting for cross-sectional dependence and heterogeneity in panel data analysis and have policy implications for harnessing the potential gains of financial inflows while promoting sustainable growth in the West Africa sub-region.

This article provides an overview of the existing literature on panel data models with error cross-sectional dependence (CSD). We distinguish between weak and strong CSD and link these concepts to the spatial and factor structure approaches. We consider estimation under strong and weak exogeneity of the regressors for both T fixed and T large cases. Available tests for CSD and methods for determining the number of factors are discussed in detail. The finite-sample properties of some estimators and statistics are investigated using Monte Carlo experiments.

This study examines the effects of health expenditure, energy consumption, CO2 emissions, population size, and income on health outcomes in 46 Asian nations between 1997 and 2019. Cross-sectional dependence (CSD) and slope heterogeneity (SH) tests are utilized due to the close linkages between Asian nations as a result of commerce, tourism, religion, and international agreements. The research uses unit root and cointegration tests of the second generation after validating CSD and SH issues. Due to the results of the CSD and SH tests, it is clear that conventional methods of estimation are inappropriate, so a new panel method, the inter autoregressive distributive lag (CS-ARDL) model, is used instead. In addition to CS-ARDL, the study's results were checked with a common correlated effects mean group (CCEMG) method and an augmented mean group (AMG) method. According to the CS-ARDL study, higher rates of energy use and healthcare spending lead to better health outcomes for Asian countries over the long run. CO2 emissions are shown to be harmful to human health, according to the study. The influence of a population's size on health outcomes is shown to be negative in the CS-ARDL and CCEMG, but favorable in the AMG. Only the AMG coefficient is significant. In most instances, the results of the AMG and CCEMG corroborate the results of the CS-ARDL. Among all the factors influencing life expectancy in Asian countries, healthcare spending is the most influential. Hence, to improve health outcomes, Asian countries need to take the required actions to boost health spending, energy consumption, and long-term economic growth. To achieve the best possible health outcomes, Asian countries should also reduce their CO2 emissions.

GDP Fluctuations and Long-Run Economic Growth: A Study of Selected South Asian Countries

GDP Fluctuations and Private Investment: A Study of Selected South Asian Countries

Determinants of GDP Fluctuations in Selected South Asian Countries

BackgroundThe COVID-19 pandemic has highlighted the need for the betterment of health status, while also considering health expenditure, energy, and environmental issues. This paper examines the nexus between health status and health expenditure (both public and private), energy consumption and environmental pollution in the SAARC-BIMSTEC region.MethodsWe utilized the panel autoregressive distributed lag (ARDL) model, the heterogeneous panel causality test, the cross sectional dependence test, the cointegration test and the Pesaran cross sectional dependent (CADF) unit root test for obtaining estimated results from data over 16 years (2002–2017).ResultsOur results authorize the cointegration among the variables used, where the coefficients of energy consumption, public and private health expenditures, and economic growth are 0.027, 0.014, 0.030, and 0.029, respectively, and indicating positive and statistically significant effects. The coefficient of environmental pollution is − 0.085, implying significant negative effect on the health status of these regions in the long-run. However, no panel wise significant impact is found in the short-run. Bidirectional and unidirectional causal links between the studied variables and the health status are also identified..ConclusionsThe improved health status in the SAARC-BIMSTEC region needs to be protected by articulating the effective policies. The attained results are theoretically and empirically consistent, and have important policy implications in the health sector.

The aspiration of study is to explore the financial development-carbon footprint nexus in One Belt and Road initiative (BRI) region utilizing the panel dataset from 1990-2017. The cross-sectional dependence tests and second-generation panel unit tests were applied to affirm the cross-section dependence and integration level. The panel regression estimators from the Driscoll-Kraay standard error method for robust estimators in the presence of cross-sectional dependence have been applied to compute the estimators concerning the financial development-carbon footprint nexus for One Belt and Road economies. The estimates infer that financial development, urban population, and FDI have an adverse effect on carbon footprint. Furthermore, economic growth and energy consumption pollute the environment by enhancing the carbon footprint. Based on findings, it infers that financial development is a potential instrument to keep the environment through financial reforms. The estimates signify that it is necessary to allocate resources for renewable energy, energy efficiency, and energy conservation projects in order to moderate environmental degradation.

PurposeThe growth of both the informal sector and illicit financial outflows necessitated this study, in order to investigate how countries in Africa respond to these realities in terms of mobilization of domestic resources. These are the main motivation for the current study to the extant literature in conjunction with the adoption of employing second-generation econometric techniques which take into account cross-sectional dependence and country-specific heterogeneity.Design/methodology/approachThis study therefore examined the capacity of Africa to mobilize domestic resources amidst rising illicit financial outflows and informal sector size in selected African countries between 2000 and 2018. Second-generation econometric techniques such as cross-sectional dependence tests, slope homogeneity tests, Westerlund (2007) long-run co-integration tests, Eberhardt and Teal (2010) augmented mean group estimations and Kónya (2006) panel causality testing were employed.FindingsFindings revealed the existence of cross-sectional dependence and slope homogeneity in the data series. Findings also supported the existence of depressing long-run impacts of IFOs and ISS on domestic savings. Causality test results were not uniform across variables among countries. Policy recommendations favour formalizing the largely informal African economies through budgetary policy adjustments and commitment to building stronger institutions.Practical implicationsThe fragility of the African countries economy and its macroeconomic indicators is suggestive for more policy construction.Originality/valueThis economic reality about the nature of the informal sector is one that has negated the traditional view which holds that economic reforms would make the informal sector shrink as it transits to formal sector. Experiences from Latin America and Africa in fact indicate that the informal sector is actually on an expansionary path in the wake of adjustment and policy reforms. It is often called the unobserved, unorganized or unprotected economy. With this sector growing in size, the possibility of a reverse may not be in sight, owing to the increasing poverty levels and unemployment prevalent in most African countries. Uncertain foreign investment and aid inflows coupled with lower export revenues and high levels of indebtedness have created new impetus to examine the capacity of Africa's fiscal policy regime to mobilise domestic resources for the development of the region. Surprisingly, the last decade witnessed continued rise in Africa's illicit financial outflows amidst large informal sector size (ISS).

Purpose- The most important tool in economic development is investments. Funds are needed for investments. Funds are obtained through domestic savings or foreign sources. Resources are known to be limited. For this reason, strong financial systems are needed. The banking sector is an important element in the financial system. The banking sector provides the collection and use of savings. In other words, the banking sector is closely related to economic development. The aim of this study is to examine the relationship between economic development and the banking sector. Methodology- BRICS-T countries are discussed in the study. Panel data for the 2001-2019 period were used. Human Development Index and domestic credit to private sector by banks (% of GDP) were used as variables. First, cross-section dependence tests were performed. Then unit root tests were applied. Heterogeneity was determined by delta test. In the last stage, causality test was applied. Causality was examined by the panel causality test developed by Dumitrescu and Hurlin (2012). Findings- Cross-sectional dependence tests showed that there is crossal-section dependence in the variables and the model. The stationarity of the series was obtained by the CADF test, which is one of the second generation panel unit root tests that takes into account the cross-sectional dependence. Delta test results showed that the slope coefficients were heterogeneous. It has been determined that the cross-sectional dependence and slope coefficients of the model are heterogeneous. The results of the Dumitrescu-Hurlin panel causality test applied showed that there is causality between the banking sector and economic development. Conclusion- The results of the research show that the banking sector contributes to the development of individuals. The increase in human development shows that there are educated, healthy and high-income people in a country. If the banking sector affects human development, human development activities will increase. High-quality human development will increase the level of technological knowledge, productivity in production, and therefore economic growth. Keywords: Banking sector, causality, economic development, human development index, panel data analysis JEL Codes: B26, G20, G21

Natural resources’ impact on capital flow and conflict relationship in Africa: A novel insight from GMM and quantile regression

This study attempts to find new evidence of causality between foreign direct investment, trade openness, and economic growth for BRICS and MINT countries between 1990-2021 using the Dumitrescu-Hurlin panel causality test. We first check whether there is a cross-sectional dependence between the countries using different cross-sectional dependence tests. After we find out there is cross-sectional dependence, we perform the CIPS unit root test. All variables are stationary at their first differences, so we applied the Dumitrescu-Hurlin panel causality test. There is bi-directional causality between trade openness and economic growth only for MINT countries. For BRICS, we found unidirectional relationships between economic growth and foreign direct investment and trade openness to economic growth. There is a unidirectional relationship from trade openness to foreign direct investment for both country groups.