• Economic Analysis
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• v.17 no.1
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• pp.103-130
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• 2011

This paper intends to provide applied economists which study the effects of research and development with valuable information on econometric model selection. It includes extensive discussion on econometric models which have been applied for the study on the relationship between research and development and productivity. In particular, it compares various stochastic production frontier models which have been developed recently. The discussion decomposes them into models with scaling property and the ones with nonscaling property as well as models with monotonic and nonmonotonic relationships between research and development and productivity. Finally, this paper applies the models to two different panel data sets (firm level data and country level data) and compare estimation results from competing econometric models.

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.194-201
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• 2017

This study investigates the factors that affect China's air pollution using city-level panel data and spatial econometric models. We address three air pollutants ($PM_{10}$, $SO_2$, and $NO_2$) present in 30 cities in China between 2004-2012 using global OLS and spatial models. To develop the spatial econometric analysis, we create a spatial weights matrix to define spatial patterns based on two neighborhood criteria - the queen contiguity and k nearest neighbors. The results show that the estimated coefficients are relatively consistent across different spatial weight criteria. The OLS models indicate that the effect of green spaces is statistically significant in decreasing the concentrations of all air pollutants. In the $PM_{10}$ and $SO_2$ analyses, the OLS models find that the number of buses and population density are also positively related to a reduction in the concentration of air pollutants. In addition, an increase in the temperature and the presence of secondary industries increase $SO_2$ and $NO_2$ concentrations, respectively. All spatial models capture a positive and significant effect of green spaces on reducing the concentration of each air pollutant. Our results suggest that green spaces in cities should receive priority consideration in local planning aimed at sustainable development. Furthermore, policymakers need to be able to discern the differences among pollutants when establishing environmental policies.

• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.373-391
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• 2022

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.

• Health Policy and Management
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• v.28 no.4
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• pp.339-351
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• 2018

Background: The purpose of this study is to estimate empirically whether there is a difference in medical use among income groups, and if so, how much. This study applies econometric model to the most recent year of Korean Medical Panel, 2015. The model consists of outpatient service and inpatient service models. Methods: The probit model is applied to the model which indicate whether or not the medical care has been used. Two step estimation method using maximum likelihood estimation is applied to the models of outpatient visits, hospital days, and outpatient and inpatient out-of-pocket cost models, with disconnected selection problems. Results: The results show that there was the inequality favorable to the low income group in medical care use. However, after controlling basic medical needs, there were no inequities among income groups in the outpatient visit model and the model of probability of inpatient service use. However, there were inequities favorable to the upper income groups in the models of probability of outpatient service use and outpatient out-of-pocket cost and the models of the number of length of stay and inpatient out-of-pocket cost. In particular, it shows clearly how the difference in outpatient service and inpatient service utilizations by income groups when basic medical needs are controlled. Conclusion: This means that the income contributes significantly to the degree of inequality in outpatient and inpatient care services. Therefore, the existence of medical care use difference under the same medical needs among income groups is a problem in terms of equity of medical care use, so great efforts should be made to establish policies to improve equity among income groups.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.139-147
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• 2020

This paper aims to explore the relationship between the quality of the audit and the level of stock return co-movement in the context of the Vietnamese emerging market. The empirical study is designed based on the quatitative method and deductive approach. The panel dataset includes 256 listed firms from different industries,with 1115 firm-year observations on Ho Chi Minh City Stock Exchange for the period from 2014 to 2018. In the research, we built the econometric regression model, using stock return synchronicity and audit quality as the dependent and independent variable, respectively. Some control variables are also added to the econometric regression models as they are well-documented in prior research to have an effect on stock price synchronicity. To improve the accuracy of the regression coefficients, beside the Ordinary Least Squares, we employ the Random Effects Model and the Fixed Effects Model for better statistical analysis of panel data set. The results show that the quality of the audit is positively correlated to stock price synchronicity. This finding suggests that stock returns of companies with higher quality of the audit are more synchronous with the market. Results for other control variables also support our reasoning for the main findings.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.77-88
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• 2021

The stock markets in the BRICS (Brazil, Russia, India, China and South Africa) countries are the leading emerging markets globally. Therefore, it is pertinent to ascertain the critical drivers of stock market development in these economies. The currrent study empirically investigates to identify the linkages between stock market development, key macro-economic factors and institutional factors in the BRICS economies. The study covers the time period from 2000 to 2017. The dependent variable is the country's stock market development and the independent variables consist of six macroeconomic variables and five institutional variables. The study employs a panel cointegration test, Fully Modified OLS (FMOLS), a Pooled Mean Group (PMG) approach and a heterogeneous panel non-causality test.The findings of the study indicate co-integration among the selected variables across the BRICS stock markets. Long-run estimations reveal that five macroeconomic variables and four variables related to institutional quality are positive and statistically significant. Further, short-run causalities between stock market capitalization and selected variables are detected through the test of non-causality in a heterogeneous panel setting. The findings suggest that policymakers in the BRICS countries should enhance robust macroeconomic conditions to support their financial markets and should strengthen the institutional quality drivers to stimulate the pace of stock market development in their countries.

• New & Renewable Energy
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• v.16 no.3
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• pp.13-26
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• 2020

This study analyzed whether the diffusion of new and renewable energy contributed to mitigating emissions of various air pollutants, including particulate matter, using panel econometric models. The theoretical foundation of such econometric models is based on the Environmental Kuznets Curve (EKC) hypothesis, which assumes an inverted U-shaped relation between national income and environmental pollution, as originally proposed by Grossman and Krueger. We examined whether there are inverted U-, U-shaped, or N-shaped relations between national income and air pollution. We demonstrate that increases in new and renewable energy significantly mitigated emissions of CO, NO_X, and PM2.5. Additionally, we included NO_X, SO_X, PM10, and VOCs as secondary emission sources of PM2.5 and found that emission of PM10 resulted in the highest PM2.5 emissions, followed by NO_X and SO_X emissions. The impact of new and renewable energy on air pollution varied across regions. Increase of new and renewable energy in the Honam region significantly mitigated CO, NO_X, and TSP emissions, while that in the Youngnam and metropolitan areas did not significantly mitigate air pollution overall. There was a U-shaped relationship between air pollution and national income for CO, NO_X, PM2.5, and SO_X, while an inverted N-shape was observed for PM10.

• East Asian Economic Review
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• v.25 no.1
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• pp.3-31
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• 2021

This paper estimates the effects of transport (road and rail) & energy and ICT infrastructure (telephone, mobile, and broadband) on GDP growths in neighboring countries as well as own countries. We confirm positive direct contributions of infrastructure, access to Internet, and human capital on economic growth. The spatial panel regression models indicate that there exist positive externalities of the broadband infrastructure and human capital, and these results are robust regardless of the choice of spatial weight matrices. Our findings on spillover effects of infrastructure suggest the key role of neighboring countries' infrastructure on own country's economic growth.

• Economic Analysis
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• v.25 no.3
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• pp.1-29
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• 2019

This paper examines the impact of a dual labor market structure on labor productivity using unbalanced panel data from 29 OECD member countries between 1990 and 2015. By applying a variety of regression models on the panel data (e.g., a pooled regression, a fixed effects model and a GMM), we explore how changes in worker-type composition among temporary, permanent and self-employed workers contribute to productivity growth. While it appears that our results differ slightly, depending on the econometric models, overall an increase in the share of permanent workers leads to a relatively higher increase in productivity growth. On the other hand, it is also seen that the effects of the share of temporary workers on labor productivity are considerably lower than that of permanent and self-employed workers. To sum it up, our findings indicate that an increase in temporary workers could have an adverse effect on labor productivity.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.141-154
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• 2018

In order to meet the ever-increasing demand for international air travel, several plans are underway to open new airports and expand existing provincial airports. However, existing air demand forecasts have been based on the total air demand in Korea or the air demand among major cities. There is not much forecast of regional air demand considering local characteristics. In this study, the outbound air travel demand in the southeastern region of Korea was analyzed and the fixed-effects model using panel data was proposed as an optimal model that can reflect the inherent characteristics of metropolitan areas which are difficult to observe in reality. The results of model validation show that panel data analysis effectively addresses the spurious regression and unobserved heterogeneity that are difficult to handle in a model using only a few macroeconomic indicators with time series characteristics. Various statistical validation and conformance tests suggest that the fixed-effects model proposed in this study is superior to other econometric models in predicting demand for international demand in the southeastern region.