Panel Vector Autoregressive Model Research Articles

The Effects of Factors of Production Shocks on Labor Productivity: New Evidence Using Panel VAR Analysis

Labor productivity has an essential role in creating a more sustainable labor market platform, leading to better economic sustainability. However, the sluggish growth in labor productivity in Malaysia could hinder the vision in realizing the status of a high-income nation in the future. Thus, understanding how production shocks affect labor productivity sustainability is crucial for firms in managing their inputs (resources). This paper aims to elucidate how shocks in wage, capital intensity, and human capital may affect the dynamic of labor productivity in the Malaysian manufacturing industry. The study further explains the magnitude of this impact on labor productivity. This study employs the panel vector autoregression (PVAR) model in analyzing the propagation of the shocks through the impulse response function and variance decomposition. The main findings reveal that shocks in production factors have a positive and significant transitional impact on productivity and the cumulative effects are positive over time. The economic impact of wage shock is material, whereas capital intensity shock is moderate and only exerts a minor effect on labor productivity emanating from human capital shock. These findings provide further insights into assisting policymakers in amplifying the current labor market policy for sustainable economic growth.

The path to renewable energy consumption in the European Union through drivers and barriers: A panel vector autoregressive approach

Renewable energy consumption brings sustainable economic growth and pollution reduction. Despite the worldwide increase in renewable energy consumption, global energy-related carbon dioxide emissions are rising and there are still considerable differences in the share of renewable energy consumption in national energy portfolios. These concerns require further effort at the policy level, especially by countries that make extensive use of energy imports. These countries could improve their lack of energy independence by using renewable energy sources and leveraging a few factors to facilitate their transition. This study aims to investigate renewable energy consumption drivers, focusing on the role of socio-technical (rather than economic) aspects such as policy stringency, lobbying, public awareness, and education. We employ a panel vector autoregressive model in first differences to test the complex dynamic relationships among renewable energy consumption, policy stringency, lobbying, public awareness, and education, controlling for variables such as per capita income and import levels, for 12 European Union net energy importing countries. Results show that the positive income effect prevails in the influence of the level of carbon dioxide emissions (negative) on renewable energy consumption, despite the latter being more significant in countries with higher levels of education. Increasing energy needs push traditional sources towards complementarity with renewable energy consumption, implying a positive lobbying effect. Public awareness is not enough to facilitate the transition to renewable energy consumption. By contrast, policy stringency has positive direct and indirect effects on renewable energy consumption, suggesting that the approach adopted by the European Commission in the recent Green Deal is a step in the right direction. Moreover, as shown, policymakers are able, through renewable energy consumption, to generate a decrease in carbon dioxide emissions and electricity production from oil, gas, coal, and nuclear sources in the first instance, but also in net energy imports, even if at a later stage.

ON THE RELATIONS AMONG CO2 EMISSIONS, GROSS DOMESTIC PRODUCT, ENERGY CONSUMPTION, ELECTRICITY USE, URBANIZATION, AND INCOME INEQUALITY FOR A SAMPLE OF 134 COUNTRIES

This paper is aimed at examining the relations among CO2 emissions, gross domestic product (GDP) growth, energy consumption, electricity use, urbanization, and income inequality for a sample of 134 countries by using principal components analysis, Granger causality, vector error correction (VEC) models, and panel vector autoregression (PVAR) models. Data was obtained from the World Bank with annual observations from 1990 to 2014. The chosen countries are those with ten years or more of concurrent data of the variables under study. The main empirical findings suggest a Kuznets curve between CO2 emissions per capita and GDP per capita. In addition, CO2 emissions have a long-term relationship with economic growth, energy use, electricity use, urbanization, and inequality. Finally, in the short run, CO2 emissions depend on economic growth, urbanization, and income inequality.

Enhancing women’s engagement in economic activities through information and communication technology deployment: evidence from Central–Eastern European countries

This study takes a macro perspective to examine the associations between the economic deployment of information and communication technology (ICT), women’s labor market participation, and economic growth in Central–Eastern European countries between 1990 and 2017. We use data extracted from World Bank Development Indicators, World Development Reports, and the World Telecommunication/ICT Indicators Database. Our methodological framework combines time trends, graphical non-parametric analysis, and panel vector-autoregressive models. The findings reveal significant relationships between ICT and women’s economic activity. Panel vector-auto-regression model estimates and Granger causality tests indicate causal relationships between ICT, economic growth, and female youth employment but not between the remaining pairs of variables.

Decomposing supply shocks in the US electricity industry: evidence from a time-varying Bayesian panel vector autoregression model

This paper investigates spillovers between electricity supply shocks and US growth, using monthly data from forty-eight US states from January 2001 to September 2016, and employs a novel strategy for electricity supply shocks based on a time-varying Bayesian panel vector autoregression model. It accounts for the decomposition of the electricity supply by fuel type and links its possible interactions with the US macroeconomic conditions. In that sense, the methodology models the coefficients as a stochastic function of multiple structural characteristics. The findings document that gross domestic product growth increases after a positive electricity supply shock, regardless of the source of energy that generates it. The absence of a sluggish adjustment mechanism may reflect weak competition and significant market power by the incumbents in the electricity industry. Lastly, we argue that the rate of response of gross domestic product growth per capita to electricity supply.

Total factor productivity of urban land use in China

AbstractPrevious studies pay little attention to the role of technological progress in measuring urban land use efficiency, and ignore the interactions among total factor productivity, technological progress, pure technical efficiency and scale efficiency in the process of urban land use. To narrow the gaps, this research uses the Malmquist index approach to measure and decompose urban land use total factor productivity and a panel vector autoregressive model (PVAR) to investigate the interactions among urban land use total factor productivity, technological progress, pure technical efficiency, and scale efficiency in China from 2003 to 2016. This study shows that the overall urban land use efficiency increased at an annual growth rate of 0.7% in China from 2003 to 2016 while the growth rate of urban land use efficiency has generally decreased, which is reflected by the total factor productivity of urban land use. The total factor productivity fluctuates between 0.952 and 1.083 with a downward trend in 2003–2016. Technological progress, pure technical efficiency and scale efficiency all have positive effects on the improvement of urban land use efficiency, and there are differences in the order and degree of promotion. The improvement of scale efficiency is the most important measure to ensure the efficient use of urban land resources in the future.

The Interactive Effect of Science and Technology Finance Development and Regional Economic Growth in the Yangtze River Economic Belt: Analysis Based on Panel Vector Autoregressive (PVAR) Model of Interprovincial Data

The interaction effects between science and technology finance development and regional economic growth have received academic and governmental attention in recent years. Based on the data of 11 provinces and cities in the Yangtze River Economic Belt from 2008 to 2017, this paper constructs a panel vector autoregressive (PVAR) model, and analyzes the direct and indirect relationship between Sci-tech finance input, Sci-tech finance output and regional economic growth through Gaussian Mixed Model (GMM) estimation and impulse response function. The study finds that: (1) The regional economic development level has a fluctuant effect on the support of science and technology finance development. (2) The enhancement mechanism of Sci-tech finance output is autonomous. (3) Sci-tech finance output and economic development level have a positive impact on each other. (4) Sci-tech finance output contributes more to economic development than Sci-tech finance input, and its effect is sustainable in the long run. Some practical proposals are put forward on the basis of the conclusions above.

The Impact of Demographic Burden on Insurance Density

The article investigates the relationship between demographic burden and insurance market by employing panel vector autoregression models with six groups of endogenous variables to a dynamic panel data set of 25 economies for the period 1980–2016. Demographic burden is represented by dependency ratios measured in respect to the population younger than the age of 15 (young-age dependency ratio), population above the age of 64 (old-age dependency ratio) as well as males and females above the age of 64 being examined separately. As indicators of insurance market development, life insurance density, non-life insurance density, and total insurance density are used. The robustness of the results is verified across 10 subsamples of the main observation period. The conducted analyses show a heterogeneous impact of demographic burden on the insurance market. The impulse responses reveal that negative effects prevail in the long term, which may result from the negative impact of an increasing demographic burden on the economy. In the short term, growth in female and male old-age dependency ratios drives up life and non-life insurance density.

Investigating the dynamic relationships between credit supply, economic growth, and the environment: empirical evidence of sub-regional economies in Sub-Saharan Africa.

Sub-Saharan Africa (SSA) is considered the most vulnerable to challenges emanating from climate changes. A number of factors notably accelerated changes in growth influence SSA environment. Linking financial sector within growth and environmental outcomes has been the focus of policy makers and researchers. This study investigated the dynamic relationships between credit supply, economic growth, and the environment from the perspectives of the four sub-regional economies (Central, East, Southern, and West African regions) in SSA over the period 1990-2018. In addition, the study tested Environmental Kuznets Curve hypothesis across sub-regions. We employed panel vector autoregressive (panel VAR) model in a generalized method of moment framework to investigate the topic. The panel VAR results revealed that (i) economic growth negatively influence on carbon emissions of Central African countries but not in the East, Southern and West African sub-regions, (ii) credit supply had significantly positive influence on carbon emissions and economic growth of Central and East African sub-regions but negative influence on carbon emissions and economic growth West African sub-regions in SSA, and (iii) carbon emissions had significantly negatively influence on credit supply of East and West African sub-regions. The granger causality results revealed bidirectional causal links between credit supply and carbon emissions, economic growth, and credit supply in the Central and East African sub-regions, while most of the relationships were unidirectional. The impulse response function revealed that the impact of one variable on another vary throughout the periods and across sub-regions. Similarly, the elasticity of the variables to each other varies across sub-regions over the period studied. EKC hypothesis was validated in East African sub-region but was rejected in Central (u-shape relationship), Southern, and West African sub-regional economies indicating variations in growth and environmental outcomes among the sub-regional economies. Specific sub-regional policy recommendations are discussed.

Is a sustainable loop of economy and entrepreneurial ecosystem possible? a structural perspective

Is region-level entrepreneurial ecosystem valid in emerging markets? What is the mechanism between entrepreneurial ecosystem elements? Is region-level entrepreneurial ecosystem in emerging markets economic-promoting? An endogenous growth model with labor-preference technologic progress is introduced to interpret the interactions between entrepreneurial ecosystem layers and growth; besides, a panel vector auto-regression model based on Chinese provinces from 2002 to 2016 is used to test. Accordingly, we empirically prove the possibility of entrepreneurial ecosystem achieving sustainable development at the scope of Chinese provinces. However, several specific situations should be avoided, including (1) a too-low relative human capital return, (2) a too-low poor-conditions-led transaction efficiency, and (3) a too-low human-capital-stock-determined technology. Thus, short-term tolerance and continuous promoting efforts are necessary. By doing so, we contribute to the literature of region-level entrepreneurial ecosystem and economic growth, or to say the fields of institutional economics, regional economics, and development economics.

The evolution and heterogeneity of credit procyclicality in Central and Eastern Europe

AbstractThis article presents empirical estimates of bank credit procyclicality for a sample of 11 Central and Eastern European countries (CEECs) for the period 2000Q1–2016Q4. In the first step, we estimate a traditional‐type panel vector autoregressive (VAR) model and analyse the evolution of credit procyclicality in the CEECs by comparing the impulse response functions for different business cycle periods. The results confirm the existence of credit procyclicality in the CEECs and show that procyclicality is higher during boom periods. Furthermore, we observe the heterogeneity of credit procyclicality in the different countries in our sample. To explain the cross‐country heterogeneity in credit procyclicality we construct an interacted panel VAR model and analyse whether bank‐level competition, proxied by the aggregate Lerner index, constitutes a driving force of credit procyclicality. Our findings indicate that bank competition affects credit procyclicality and explains the differences in credit dynamics across the CEECs. Specifically, we show that the reaction of credit to a gross domestic product shock is on average higher in a less competitive banking market.

Competition, diversification and performance in dual banking: a panel VAR analysis

This article investigates the dynamic relationship among competition, diversification and bank performance using data for 18 countries with a dual banking system over the period 2000 to 2016. Analyses using panel vector autoregression (P.V.A.R.) model, impulse response function (I.R.F.) and variance decomposition (V.D.C.) methods confirm that market power increases the profitability and the stability of banks the dual banking system while revenue diversification reduces them. Market power increases revenue diversification of banks. Segregating the sample of banks into emerging and developing countries, we find that positive impact of market power on profitability is stronger for emerging countries. Even though we find that revenue diversification has a more damaging effect on the profitability of banks in the developing countries, it only dampens the stability of banks in emerging countries. In addition, we find that asset diversification dampens the stability of banks. However, it has a more positive impact on the profitability of banks in emerging economies.

A deployment model of EV charging piles and its impact on EV promotion

The construction of public-access electric vehicle charging piles is an important way for governments to promote electric vehicle adoption. The endogenous relationships among EVs, EV charging piles, and public attention are investigated via a panel vector autoregression model in this study to discover the current development rules and policy implications from the historical panel data in China. Five policies related to EV charging piles, EV purchase subsidies, commercial land prices, and retail gasoline prices are controlled as exogenous variables in the model. The results indicate that EV and charging piles diffusion do interact, and public attention plays a nexus role in EV and charging piles deployment. Reducing the electricity rate is the most effective policy approach to promote EV charging piles. Subsidising the construction cost has an insignificant impact on charging piles diffusion in this study, and several possible reasons have been discussed. The promotion effect of direct-current charging piles on EV sales is twice that of alternating-current charging piles in the one-year simulation of our model. Increasing the number of EV charging piles has a significant impact on battery electric vehicle sales but not on plug-in hybrid electric vehicle sales.

Receptiveness of effective tax rate to firm characteristics: an empirical analysis on Indian listed firms

PurposeThe purpose of this paper is to empirically investigate the factors deriving effective tax rate (ETR) for Indian manufacturing firms in different sectors. The study also tries to analyze the sensitiveness of ETR because of shocks on its key determinants.Design/methodology/approachThe study is using Arellano–Bond dynamic panel regression model to identify the key drivers of ETR, and impulse response functions of panel vector auto-regression model to analyze the response of ETR because of one standard deviation (SD) shock to its key determinants.FindingsThis study concludes that ETR is significantly explained by firm size, profitability, growth rate and non-debt tax shield in most of the sectors, and debt ratio, asset tangibility and age of the firms are impacting ETR differently across sectors. In case of entire manufacturing sector, firm size, profitability, growth and non-debt tax shield are driving ETR positively and asset tangibility is driving ETR negatively. Interest coverage ratio (ICR) and firm age are not significant drivers of ETR. ETR is positively related with firm size, but responses negatively when there is an immediate shock to firm size. Similarly, ETR is negatively related with asset tangibility, but responds positively following an immediate shock to it. Overall, ETR is more sensitive and responses significantly because of shocks in firm size, profitability, growth, asset tangibility and non-debt tax shield whereas, the response is very marginal following shocks to debt ratio, ICR and age of the firm.Research limitations/implicationsFirm managers may find the study useful to understand the receptiveness of ETRs at each sector level. The empirical findings are not only validating the theoretical developments but also providing a root cause analysis to the firm managers to understand the cause and consequence of ETRs for firms at different sectors.Originality/valueEmpirically investigating the factors driving ETR and analyzing its sensitiveness because of one SD shock on its key determinants for Indian manufacturing firms from different sectors is the originality of this study. Developing a strong theoretical background and empirically validating it through advanced methodology makes the study unique.

Sovereign default risk and credit supply: Evidence from the euro area

Did sovereign default risk affect macroeconomic activity through firms’ access to credit during the European sovereign debt crisis? We investigate this question by a estimating a structural panel vector autoregressive model for Italy, Spain, Portugal, and Ireland, where the sovereign risk shock is identified using sign restrictions. The results suggest that the decline in the creditworthiness of the sovereign contributed to a fall in private lending and economic activity in several euro-area countries by reducing the value of banks’ assets and crowding out private lending.

DO OIL PRICE SHOCKS GIVE IMPACT ON FINANCIAL PERFORMANCE OF MANUFACTURING SECTORS IN INDONESIA?

The panel vector autoregression model is estimated using three main variables related to with profitability, financial liquidity, and financial leverage for 94 manufacturing companies from 2000 to 2017 in Indonesia. The aim is to examine the impact of oil price shocks on the ROA (profitability), CR (financial liquidity), and DER (financial leverage). The impulse reaction function of samples reveals some remarkable results. First, the response of ROA, DER, and CR appears to be consistent in many ways. Second, either Brent oil or WTI oil gives the same result for these variables. Third, financial liquidity for Indonesia manufacturing companies is not affected by the oil prices. The results obtained are robust following the GMM model in the estimation of the panel VAR.Keywords: Oil price shocks, Panel VAR, Impulse Reaction Function, GMM modelJEL Classifications: L6, Q4DOI: https://doi.org/10.32479/ijeep.9808

Revisiting the nexus among foreign direct investment, corruption and growth in developing and developed markets

This study examines the dynamic association among foreign direct investment (FDI), corruption and economic growth. The study applies a panel vector autoregressive (PVAR) model to the context of the generalized method of moments estimation technique to determine the relationships in 54 developed and developing countries over the period of 1996–2018. The findings suggest that the control of corruption negatively (positively) affects inward FDI and economic advancement in developing (developed) countries, suggesting that weak (strong) institutional quality and higher (lower) corruption boost investments and economic development. The study further finds that economic growth and corruption have a positive bidirectional relationship for developing countries and negative unidirectional association for developed countries. Besides, the bidirectional linkage of FDI with corruption and economic growth is observed in both developed and developing countries. The findings are elicited through a series of robustness tests, including two-step system generalized method of moments. The results provide policy implications to government and regulatory authorities.

Market structure and credit procyclicality: Lessons from loan markets in the European Union banking sectors

The aim of this paper is to investigate whether the market structure has an impact on procyclicality in the European Union bank loan markets. The cyclical responses of three types of bank loans (residential mortgage loans, consumer loans, and corporate loans) are quantified separately using the interacted panel vector autoregression model at the country level and the single-equation panel regression model at the bank level. Using a sample of 26 European Union countries, we find that the procyclical responses of residential mortgage loans and consumer loans are significantly stronger and prolonged when the banking sector is more concentrated or dominated by foreign banks. However, we find that there are nonlinear relationships between the market structure and credit procyclicality based on bank-level data. We also find some heterogeneities between advanced and transitioning European Union banking sectors. Finally, our findings confirm the leading role of residential mortgages in intensifying credit fluctuations.

An alternative method for analyzing dimensional interactions of urban carrying capacity: Case study of Guangdong-Hong Kong-Macao Greater Bay Area

Most previous studies on comprehensive urban carrying capacity (UCC) have estimated UCC levels and comparatively analyzed the heterogeneity of the sample cities. Very few researchers have focused on the interaction effects between different categories of UCC based on synergetic theory. To fill this gap, we constructed a panel vector autoregressive (PVAR) model to study 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2016. The ultimate goal of this study is to improve comprehensive UCC levels by forming a virtuous circle of mutual reinforcement between the four types of carrying capacity. To do so, the interaction mechanisms of the four subsystems are examined. Results show that (a) only transportation and social carrying capacity had causality between them as per the Granger causality test; (b) all four carrying capacities can support themselves (i.e., the development of economic conditions helps to improve social carrying capacity and the improvement of social carrying capacity helps to improve environmental carrying capacity); and (c) both the four carrying capacities are mostly affected by their own fluctuations. Overall transportation carrying capacity is the most important driving force among the four subsystems that interact with each other; followed by economic carrying capacity, which has promotion effect on the social and environmental aspects; social carrying capacity poses impact on the environmental dimension but not vice versa. Policy suggestions and future research directions are highlighted in the final section.

Study on Evolution and Interaction of Service Industry Agglomeration and Efficiency of Hebei Province China

Using data from 2008 to 2017 regarding the service sector in 11 cities of the Hebei Province, this study measures the degree of agglomeration and efficiency of service subsectors, analyzes their spatiotemporal evolution, and discusses the interactive relationship between them using panel vector autoregressive (PVAR) models and GMM dynamic panel model. The findings are summarized as follows: (1) from 2008 to 2017, service subsectors in Hebei’s cities have a high degree of agglomeration and benefit significantly from specialization; (2) the service in Hebei’s cities is severely inefficient (i.e., efficiency loss is grave). The empirical results of PVAR models reveal that service sector agglomeration is primarily reliant on its own development momentum and while that can improve technical efficiency and pure technical efficiency, it can also inhibit technical change efficiency. The variance decomposition results reveal that service sector efficiency is influenced more significantly by itself than by service sector agglomeration. With the passage of time, the self-influence of efficiency decreases and the influence of service sector agglomeration on efficiency increases.