Non-stationary Panel Data Research Articles

Driving low-carbon mechanisms through smart investments in renewable resources and green finance initiatives among G20 nations

In light of the escalating concerns regarding climate change and environmental decline, major nations are actively exploring strategies to mitigate environmental harm and achieve future sustainability. The surge in economic expansion in developed economies is linked to an increase in CO2 emissions. Consequently, in their pursuit of carbon-neutral policies, these countries are increasingly turning towards renewable energy as a means to enhance resource conservation and efficiency. This research investigates the varied impacts of renewable energy investment, green finance, geopolitical risk, GDP growth, foreign direct investment, and gross fixed capital formation on the carbon emissions of G20 countries. The study uses the CUP-FM (Continuously Updated Fully Modified) and CUP-BC (Continuously Updated Bias-Corrected) estimators, which are sophisticated econometric approaches designed to handle non-stationary panel data and cross-sectional dependency, to produce robust long-term parameter estimates. The CUP-FM estimator adjusts for potential endogeneity and serial correlation, improving the accuracy of long-run relationships in panel data. The CUP-BC estimator provides bias-corrected estimates to further enhance the precision of these long-run connections.The long-term parameter estimates reveal a negative correlation between renewable energy investment, green finance, and carbon emissions. In contrast, foreign direct investment, gross fixed capital formation, GDP growth, and geopolitical risk are positively associated with CO2 emissions. This suggests that financial stability often leads to investments in carbon-heavy economic ventures, thereby implicating economic growth as a contributing factor to environmental degradation in G20 countries.

Analysis of Finance--Growth Nexus in Developing Economies: Does the Quality of Leadership and Technology Matter?

This article investigates the effects of national leadership and telecommunication technology on the finance–growth nexus using balanced panel data from 50 developing countries for the 1997–2017. The study employs a set of nonstationary panel data approaches to investigate the long-run relationships between the variables of interest. The findings show that there is a long-term relationship between the variables wherein financial development, telecommunication technology, and quality of national leadership were found to have significant positive impact on economic growth in developing countries. This implies that financial development, telecommunication technology, and the quality of national leadership are important factors for promoting growth. Moreover, the results suggest that the effects of financial development on economic growth is contingent on the quality of national leadership and the sophistication of telecommunication technology in developing countries. The interaction term and marginal effects computed are positive and significant at all levels of telecommunication technology as well as on the quality of national leadership. This means that both the quality of national leadership and telecommunication technology have large direct and indirect positive impacts on economic growth in developing countries, and that financial development contributes more significantly and robustly to economic growth when telecommunication technology is sophisticated and national leadership is of high quality. Keywords: economic growth, financial development, ICT, panel data

The effectiveness of environmental protection policies on greenhouse gas emissions

In Canada, greenhouse gas (GHG) emissions continue to remain high despite the federal government's commitment to reduce GHG emissions. Environmental policy across Canadian provinces has largely lacked consistency with some provinces implementing targeted policy such as carbon taxes while others have strongly resisted the federal government's attempts to encourage such policy. This study examines the impact of environmental policy on GHG gas emissions across Canadian provinces with policy uniquely measured by public and business sector spending on environmental protection as well as notable province-specific policies. An extended STIRPAT model is specified with the inclusion of proxies for environmental policy using panel data from Canada's ten provinces from 1995 to 2019. The cointegration and the error correction modelling approaches are employed to estimate the non-stationary panel data. A pooled mean group estimation is applied to provide short run and long run coefficients. The findings indicate that although per capita GDP is the main driver of GHG emissions in Canada, environmental policy has a significant mitigating effect, as shown by the negative association between emissions and private and public sector spending on environmental protection in the long run. Furthermore, provinces with targeted policies, such as Ontario's coal phase-out and British Columbia's carbon tax, experienced significant emissions reductions. The theoretical implication is the successful addition of policy variables to the STIRPAT model, providing the model a new application for future research.

지역화경제와 도시화경제가 지역 산업의 생산성에 미치는 영향

Purpose: Based on Japan’s regional-industries data from 1994 to 2018, we intend to analyze and present Japanese evidence on the productivity-enhancing effects of localization economies(MAR externality) and urbanization economies(Jacobs externality), and to accumulate research evidence for comparative analysis between Korea and Japan on the effect of agglomeration economies on productivity.
 Research design, data, and methodology: In order to empirically analyze the impact of localization economies and urbanization economies on the labor productivity, RIETI’s R-JIP database, which provides high-quality data on 31 industries in 47 prefectures from 1994 to 2018, was used. We implement a panel co-integration test for non-stationary panel data, and estimate panel co-integration vectors.
 Results: As a result of the panel cointegration test, labor productivity by region in Japan has a long-term equilibrium relationship with the industrial specialization index and industrial diversity index. In the estimation result of the panel cointegration vector, In the case of manufacturing, localization economy improves labor productivity, but urbanization economies does not affect labor productivity. On the other hand, in the case of IT manufacturing, both localization and urbanization economies have a significant impact on improving labor productivity.
 Implications: It is necessary to strengthen manufacturing specialization (localization economies) in order to improve the productivity of regional manufacturing. In addition, in order to improve the productivity of the IT manufacturing, a policy to strengthen the localization economies is important, and in addition, a policy to expand the diversity of related industries.

Economic growth and female labour force participation in an ageing society: evidence from Southeast Asia

ABSTRACT This study examines the impact of female labour participation and life expectancy on economic growth in Southeast Asia economies using non-stationary panel data techniques. The study utilizes balanced panel data spanning from 1992 to 2020, encompassing ten countries in Southeast Asia. The results reveal that economic growth, female labour participation, and other factors are cointegrated. The findings indicate that trade openness has a negative impact on economic growth. However, we find that female labour participation, female longevity, female education, domestic investment, and foreign direct investment have a positive long-term effect on economic growth. Our study also highlights that the effect of female labour participation on growth varies depending on female longevity. We find that female labour participation positively impacts economic growth but changes negatively when countries exhibit a high level of female life expectancy.

Smooth structural changes and common factors in nonstationary panel data: an analysis of healthcare expenditures†

This article suggests new panel unit root tests that allow for multiple structural breaks and control for cross-correlations in the panel. Breaks are modeled with a Fourier function, which allows for smooth or gradual change rather than abrupt breaks. Cross-correlations are corrected by using the PANIC procedure. The simulations show that our tests have good size and power properties and perform reasonably well when the nature of breaks or the factor structure is unknown. The new panel unit root tests support fresh evidence on the persistence of healthcare expenditures in OECD countries.

Statistical disclosure and economic growth: What is the nexus?

Although the benefits of information for the quality of economic decisions have been highlighted by numerous theoretical studies, only a few empirical studies have investigated the relevance of statistics for the economy. It is particularly surprising that no previous empirical study has researched the existence of a causal link running from statistical disclosure to long-run economic growth. Our research investigates the existence of this nexus in a panel of 105 countries. We applied methodologies for non-stationary panel data in order to assess the long-run causality. We found that data availability was causing long-run economic growth in all income level groups but in the high income one. However, the higher certainty about a positive causality was found in middle income nations. This is true because bidirectional causality was found in poor nations, where it is possible that statistical production demand more resources than it may generate by boosting economic growth. With regard to short-run causality, it was only found in middle income nations. Finally, we find that the publication of the indicators in the World Bank’s World Development Indicators database is in fact relevant for economic growth.

Backward mean transformation in unit root panel data models

The effectiveness of an orthogonal to backward mean transformation is investigated in the context of a non-stationary panel data model. It is shown that the corresponding estimator is as efficient as Transformed Maximum Likelihood when the autoregressive parameter is equal to unity. Furthermore, a recently introduced bias-corrected version is almost as efficient as the Pooled Least Squares estimator.

İkiz Açık Hipotezinin Geçerliliğinin Kırılgan Beşli Ülkeleri İçin Test Edilmesi

Bu çalışmada, ikiz açık hipotezinin geçerliliği Kırılgan Beşli (Brezilya, Endonezya, Güney Afrika, Hindistan ve Türkiye) ülkeleri için araştırılmıştır. 2000 – 2017 dönemi için ele alınan çalışmada, panel veri analizi yöntemleri kullanılmıştır. Yüksek cari açık ve bütçe açığına sahip kırılgan beşli ülkelerinin etkin ve sürdürülebilir bir maliye ve para politikası oluşturabilmelerinin önünde ikiz açık önemli bir sorun olabilmektedir. Çalışma kapsamında, yatay kesit bağımlılığını dikkate alan birim kök testlerinden CADF ve SURADF testleri kullanılmıştır. Tüm ülkelerde düzeyde ve seviyede durağanlık elde edilememiştir. Bu yüzden durağan olmayan panel veri modellerinden Westerlund Hata Düzeltme Modeli tercih edilmiştir. Kısa ve uzun dönemli parametrelerin tahminlenmesinde Havuzlanmış Ortalama Grup Tahmincisi ve Birimler İçin Havuzlanmış Ortalama Grup Tahmincisi kullanılmıştır. Ampirik sonuçlara göre uzun dönemde bütçe açığındaki % 1 artış cari açıkta % 0.34 oranında artışa yol açmaktadır. Bu bağlamda Geleneksel Keynesyen Yaklaşımı çerçevesinde ikiz açık hipotezinin geçerli olduğu sonucuna ulaşılmıştır. Anahtar Kelimeler: İkiz Açık, Bütçe açığı, Cari Açık, Durağan Olmayan Panel Veri Modelleri, Kırılgan BeşliJEL Sınıflandırması: C23, F30, H62

Econometric Analysis of Panel Data Models with Multifactor Error Structures

Economic panel data often exhibit cross-sectional dependence, even after conditioning on appropriate explanatory variables. Two approaches to modeling cross-sectional dependence in economic panel data are often used: the spatial dependence approach, which explains cross-sectional dependence in terms of distance among units, and the residual multifactor approach, which explains cross-sectional dependence by common factors that affect individuals to a different extent. This article reviews the theory on estimation and statistical inference for stationary and nonstationary panel data with cross-sectional dependence, particularly for models with a multifactor error structure. Tests and diagnostics for testing for unit roots, slope homogeneity, cointegration, and the number of factors are provided. We discuss issues such as estimating common factors, dealing with parameter plethora in practice, testing for structural stability and nonlinearity, and dealing with model and parameter uncertainty. Finally, we address issues related to the use of these economic panel models.

Estimating factor shares from nonstationary panel data

The measurement of the sources of economic growth, essential for understanding the long-term perspective of any economy, depends on both the functional form that summarizes technology and factor share values. We estimate the share of physical capital in output, implied by a Cobb–Douglas production function, using fully modified and dynamic ordinary least squares estimators within a panel cointegration framework for 109 countries over the period 1960–2014. For several measures of labor, our estimates range between 0.46 and 0.56 for the worldwide set and vary significantly across regions. The panel estimates are: (i) similar when human capital is taken as a separate factor of production; and (ii) more robust than both the average of the individual cross-country estimates and those obtained in the model in differences. We also find that the CES production function estimates favor the Cobb–Douglas specification. Finally, we provide some evidence of a decline in the share of labor, in line with recent empirical studies.

The nexus of electricity consumption and economic growth in Gulf Cooperation Council economies: evidence from non-stationary panel data methods

ABSTRACTThis paper investigates the electricity-growth nexus of Gulf Cooperation Council (GCC) member countries from 1980 to 2014. To achieve the goal of this research, both panel cointegration and causality approaches are utilised to examine the long-term and causal relationships between variables. Empirical results confirm the presence of cointegration between variables. Moreover, this study finds that electricity consumption affects the long-term economic growth. Given that GCC member countries are energy-dependent economies, policies that aim to conserve energy consumption may jeopardise economic growth.

Long run effect of public grants and tax credits on R&D investment: A non-stationary panel data approach

R&D investment is a key factor in long run economic growth. This paper analyzes the effectiveness of public grants and tax credits used to promote long-run R&D investment. Cointegration techniques have been used to deal with the existence of common trends, which might lead to spurious correlation. In this context, we propose a new empirical strategy applying DOLS and FMOLS estimators to the cointegrated firms and the LSDV estimator to non-cointegrated firms. Cointegrated firms are those that invest persistently in R&D while non-cointegrated firms invest in a non-continuous or occasional way. A panel of 237 Spanish manufacturing firms for the 1990–2009 period is used. We find evidence that public grants are more effective for firms where R&D investment is persistent and the quality of projects matters. In addition, our results suggest that a tax credit is suitable for boosting long-run R&D investment as a whole, especially if the base amount of tax credit is incremental. Surprisingly, incremental tax credit is only in force in a few countries such as Italy, Korea, Mexico, Portugal, United States and Spain.

Co-integration Analysis of the Central and Eastern European Tourism Demand in Tunisia using Non-stationary Panel Data

Co-integration Analysis of the Central and Eastern European Tourism Demand in Tunisia using Non-stationary Panel Data

Capital market integration in ASEAN: A non-stationary panel data analysis

Motivated by the establishment of ASEAN Economic Community (AEC) at the end of 2015, we examine saving-investment relationship in various subgroups of ASEAN to assess their capital market integration. The results from second generation panel unit-root and cointegration tests that account for cross-sectional dependence as well as estimates of long-run saving-retention rate provide some evidence of market integration in ASEAN. The analysis of short-run dynamics suggests that capital mobility in ASEAN during 1980–2014 appears similar to that in OECD countries during 1970–1999. More importantly, across different panel estimators and subgroups of membership, there is considerable heterogeneity among the member countries. The saving-investment association is very weak, thereby implying very high capital mobility, in more developed members such as Singapore, Malaysia, and Brunei; the association is very strong, implying very low capital mobility, for much less developed members such as Laos, Myanmar, and Cambodia. The results call for renewed effort to develop capital markets in less developed nations and integrate them with the rest of the membership in ASEAN. In this paper, we also address several major shortcomings of the original Feldstein-Horioka framework.

The Role of Property Rights in the Relationship between Capital Flows and Economic Growth in SSA: Do Natural Resources Endowment and Country Income Level Matter?

AbstractThis paper studies the role played by the quality of property rights in the linkages of international capital flows into sub‐Saharan African (SSA) economies. Using panel data of 36 SSA countries over the period 1996–2015 and the ARDL procedure with the Pooled Mean Group regression method appropriate for non‐stationary panel data estimation, we account for the joint effects of property rights quality and openness to foreign capital flows on economic growth. We uncover the existence of a property rights quality threshold beyond which property rights either amplifies the spillovers effects or attenuates the negative effect of capital flows on economic growth. For instance, it takes a level of property rights of at least 60 to have a positive long‐term impact of capital flows on economic growth in natural resource‐poor African countries. The quality of property rights matters more to obtain spillover effects of capital flows on growth in natural resource‐poor countries than in their peer natural resource‐rich countries. Finally, with regard to the countries' income levels, capital flows have significant long‐term spillovers effects on economic growth in advanced African economies than in their low‐income peers.

Fundamentals of the Real Exchange Rate of the CFA Franc in WAEMU: An Application of Non-Stationary Panel Data Econometrics

Identifying the fundamentals of the real exchange rate of the CFA franc in WAEMU is the main objective of this paper. To achieve this, we used panel data over a period from 1984 to 2014. The results obtained using the Pooled Mean Group (PMG) method show that investment, government spending, trade openness and balance significantly influence the real exchange rate of the long-term CFA franc in WAEMU. With regard to the short-term relationship, the results show that only productivity and the trade balance are the fundamentals that significantly influence the real exchange rate of the CFA franc.

The Economic Significance of Laws Relating to Employment Protection and Different Forms of Employment: Analysis of a Panel of 117 Countries, 1990-2013

This paper presents findings from analysis of a dataset of labour laws, based on the Centre for Business Research Labour Regulation Index (CBR-LRI), which has recently been extended to cover 117 countries and the period from 1970 to 2013. The dataset shows that laws regulating different forms of employment (DFE), including part-time work, fixed-term employment and agency work, have become significantly more protective over time, in particular since the late 1990s. Employment protection laws (EPL), covering individual dismissal, collective consultation and codetermination rights, have become steadily more protective since the 1970s. Europe has seen a decline in the level of EPL since the onset of the sovereign debt crisis in 2008, but this trend is small, on average, by comparison to earlier increases in protection beginning in the 1970s, and has not been replicated in other regions. Time-series econometric analysis using non-stationary panel data methods suggests that strengthening worker protection in relation to DFE and EPL is associated with an increase in labour’s share of national income, rising labour force participation, rising employment, and falling unemployment, although the observed magnitudes are small when set against wider economic trends.

Spatial econometric analysis of spatial general equilibrium

ABSTRACTA structural spatial econometric model for nine regions of Israel is estimated using non-stationary spatial panel data during 1987–2015. The model focuses on the relation between regional markets in labour, housing and capital when there is imperfect internal migration between regions, when capital is imperfectly mobile between regions, and when building contractors operate across regions. Since the regional panel data are non-stationary, the econometric methodology is based on spatial panel cointegration. The estimated model is used to simulate the temporal and spatial propagation of regional shocks induced, for example, by regional policy (land for housing, regional investment grants). Impulse responses are temporally and spatially state dependent. They are also highly persistent because of longevity in housing and capital.

Does Government Size Affect Economic Growth in Developing Countries? Evidence from Non-stationary Panel Data

Does Government Size Affect Economic Growth in Developing Countries? Evidence from Non-stationary Panel Data