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1 – 10 of 782The purpose of this paper is to examine the determinants of average health expenditures for inpatients in China with national data for period 2002-2010 and regional data during…
Abstract
Purpose
The purpose of this paper is to examine the determinants of average health expenditures for inpatients in China with national data for period 2002-2010 and regional data during 2005-2010.
Design/methodology/approach
The semi-parametric framework is established to identify the determinants of health expenditures with local-constant least squares (LCLS) and local-linear least squares (LLLS) techniques. The LCLS technique aims to identify correlative determinants among all considered variables, and LLLS technique aims to further distinguish linear decisive and nonlinear control variables among all correlative determinants.
Findings
First, root mean square error tends to decrease with irrelative variables smoothed out in regression model, validating the modelling reasonability of the semi-parametric approach. Second, the determinants of average health expenditures for inpatients exhibit considerable variation among regions despite the fact that governmental health expenditure, GDP per-capita, and urbanization do impact average health expenditures for inpatients to a certain extent. Third, both linear decisive and nonlinear control variables vary greatly with national, provincial, and regional data.
Practical implications
First, the illiteracy rate should be further reduced nationally. Second, urbanization development and the average treatment number of inpatients for each physician per day should be strictly controlled in region A and C, respectively, in order to control average health expenditure for inpatients.
Originality/value
First, the semi-parametric framework with LCLS and LLLS techniques allows for data structure-oriented model in regions rather than a uniform and definite model for underlying structure. Second, the research undertakes for the first time a comprehensive data analysis of the determinants of average health expenditures for inpatients with national and regional data in China.
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Christian M. Hafner, Dick van Dijk and Philip Hans Franses
In this paper we develop a new semi-parametric model for conditional correlations, which combines parametric univariate Generalized Auto Regressive Conditional Heteroskedasticity…
Abstract
In this paper we develop a new semi-parametric model for conditional correlations, which combines parametric univariate Generalized Auto Regressive Conditional Heteroskedasticity specifications for the individual conditional volatilities with nonparametric kernel regression for the conditional correlations. This approach not only avoids the proliferation of parameters as the number of assets becomes large, which typically happens in conventional multivariate conditional volatility models, but also the rigid structure imposed by more parsimonious models, such as the dynamic conditional correlation model. An empirical application to the 30 Dow Jones stocks demonstrates that the model is able to capture interesting asymmetries in correlations and that it is competitive with standard parametric models in terms of constructing minimum variance portfolios and minimum tracking error portfolios.
Jinwei Zhu, Yangyang Wang and Changyu Wang
This paper aims to examine the different impacts of six variables on firm technological innovation performance in different high-tech industries in China. Through a comparative…
Abstract
Purpose
This paper aims to examine the different impacts of six variables on firm technological innovation performance in different high-tech industries in China. Through a comparative analysis of data about growth enterprises market board (GEM)-listed companies, this study attempts to get some conclusions, to help firms in different high-tech industries use resources more rationally and to improve technological innovation performance more effectively.
Design/methodology/approach
This paper constructs semi-parametric models based on the relevant data of GEM-listed companies during 2010 to 2015 for different high-tech industries. These models can ensure that the influencing factors of firm technological innovation performance are no longer restricted to a particular aspect but can provide a comprehensive comparative analysis of the effects of factors on firm technological innovation performance in different high-tech industries.
Findings
The empirical results show that R&D expenditures have a significant positive impact on firm technological innovation performance in most high-tech industries, but not in electronic and communication equipment manufacturing industry; R&D personnel investment and government subsidies have significant positive impacts on firm technological innovation performance in knowledge-oriented industries; technology diversity has a significant positive impact on firm technological innovation performance in technology-oriented industries; the proportion of exports shows an inverted U-shaped relationship with firm technological innovation performance in electronic and communication equipment manufacturing industry, while firm size shows an inverted U-shaped relationship with firm technological innovation performance in general equipment manufacturing industry; and the effect of semi-parametric model fit is superior to the general parameters model.
Originality/value
Drawing on the resource dependence perspective, this paper is the first to consider a comprehensive treatment of differential effects of internal resources (R&D personnel, R&D expenditure), external resources (government subsides) and firm characteristics (firm size, export ratio) on firm technological innovation performance in different high-tech industries in an emerging country, in particular in contrast to previous studies that have focused on a single industry or taken the type of industry as a control variable. In addition, most studies about the determinants of firm innovation performance are based on survey questionnaires, which may introduce large subjective errors. Setting the relationship between variables in advance may also introduce fit error when using a general-parameter model. Semi-parametric regression which is used in this paper is able to prevent this shortcoming effectively. When constructing a regression model, this can be exempted from the formal constraints, thus estimating data more accurately and ensuring superior fit.
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The existence of the regional Kuznets curve, i.e. an inverted U-shaped relationship between regional disparity and economic development is widely debated and discussed. The…
Abstract
Purpose
The existence of the regional Kuznets curve, i.e. an inverted U-shaped relationship between regional disparity and economic development is widely debated and discussed. The bell-shaped curve of the spatial growth process where during the initial phase inequality increases and then reduces is theoretically supported by Myrdal (1957), Hirschman (1958), and Williamson (1965). It becomes important to understand regional Kuznets curve globally. Understanding the relationship between regional disparity and economic development becomes essential for public policy for balanced regional growth.
Design/methodology/approach
Regional Kuznets Curve which is an inverted U-shaped relationship between regional disparity and economic development is not a new phenomenon. Theoretical framework by Myrdal (1957), Hirschman (1958), and Williamson (1965) support the an inverted U-shaped relationship. To understand the relationship between regional disparity and economic development, the authors investigate the regional Kuznets curve by using data for 184 countries and 1765 subnational regions. Using parametric, semi-parametric, and non-parametric, it is found that there exists an inverted U-shaped relationship between regional disparity and economic development. The presence of the regional Kuznets curve is observed. As the theoretical framework suggests, regional inequality increases with income initially and decreases after attaining a certain level of income. This study identifies two stages of divergence-convergence where in the first stage, divergence across regions in a country happens with increasing income and in the later stage, convergence across regions in a country occurs with increasing income.
Findings
Using the parametric approach (panel data analysis), semi-parametric and non-parametric approaches, it is found that there exists a regional Kuznets curve. It is found that there exists an inverted-U relationship between regional inequality and per capita GNI. This suggests that the divergence-convergence passes through two stages. In the first stage, divergence across regions in a country happens with increasing income while in the later stage convergence occurs.
Originality/value
This research work has done three important things which fill the research gap that exists in the literature: (1) constructing the Gini coefficient to measure the regional inequality for 184 countries using 1765 subnational regional data; (2) using a parametric approach (panel data analysis) to understand the regional Kuznets phenomenon and (3) using a semi-parametric approach and non-parametric approach to understand the regional Kuznets phenomenon.
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Stéphane Hamayon, Florence Legros and Yannick Pradat
The authors aim to demonstrate the importance of taking into account “mean reversion” in asset prices and show that this type of modeling leads to a high share of equities in…
Abstract
Purpose
The authors aim to demonstrate the importance of taking into account “mean reversion” in asset prices and show that this type of modeling leads to a high share of equities in pension funds’ asset allocations.
Design/methodology/approach
First, the authors will study the long-run statistical characteristics of selected financial assets during the 1895-2011 period. Such an analysis corroborates the fact that, for long holding periods, equities exhibit lower risk than other asset classes. Moreover, they will provide empirical evidence that stock market returns are negatively skewed in the short term and show that this negative skewness vanishes over longer time horizons. Both these characteristics favor the use of a semi-parametric methodology.
Findings
This empirical study led to two major findings. First, the authors noticed that the distribution of stock returns is negatively skewed over short time horizons. Second, they observed that the fat-tailed shape of the returns distribution disappears for time periods longer than five years. Finally, they demonstrated that stock returns exhibit “mean-reversion”. Consequently, the optimization program should not only take into account the non-Gaussian nature of returns in the short run but also incorporate the speed at which volatility “mean reverts” to its long-run mean.
Originality/value
To simulate portfolio allocation, the authors used a Cornish–Fisher Value-at-Risk criterion with the advantage of providing an allocation that is independent of the saver’s preferences parameters. A backtesting analysis including a calculation of replacement rates shows a clear dominance of the “non-Gaussian” strategy because the retirement outcomes under such a strategy would be positively affected.
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Pavel Ciaian, Jan Fałkowski and d'Artis Kancs
The purpose of this paper is to analyse how farm production and input use (land, variable inputs, labour, and capital) is related to farm access to credit in the Central and…
Abstract
Purpose
The purpose of this paper is to analyse how farm production and input use (land, variable inputs, labour, and capital) is related to farm access to credit in the Central and Eastern Europe (CEE) transition countries.
Design/methodology/approach
Drawing on a unique farm level panel data set with 37,409 observations and employing a matching estimator, this paper analyses how farm access to credit affects farm input allocation and farm efficiency in the CEE transition countries. The large size of the FADN data set has an additional advantage. It allows the authors to employ a semi‐parametric estimator based on the propensity score matching. Using more than 37,409 observations assures that the loss in efficiency of semi‐parametric estimates, as compared to parametric ones, is not a problem. This is important for at least two reasons. First, applying a semi‐parametric propensity score matching (PSM) estimator allows to control for any heterogeneity in the relationship between farm performance and their observable characteristics (in particular access to credit). Second, matching estimators are robust in situations where farms having access to credit systematically differ from those that do not.
Findings
It is found that farms are asymmetrically credit constrained between inputs. The use of variable inputs and capital investment increases up to 2.3 percent and 29 percent, respectively, per 1,000 EUR of additional credit. The authors' estimates suggest also that farm access to credit increases the total factor productivity up to 1.9 percent per 1,000 EUR of additional credit, indicating that an improved access to credit results in adjusting the relative input intensities on farms. This finding is further supported by a negative effect of better access to credit on labour, suggesting that these two are substitutes. Interestingly, farms are found not to be credit constrained with respect to land.
Originality/value
To the best of the authors' knowledge, the present paper is the first to investigate the importance of access to credit for farm performance in the CEE region as a whole.
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Ahmed Hassanein, Jamal Ali Al-Khasawneh and Hany Elzahar
Corporate managers spend on research and development (R&D) for reasons of growth and survival. However, they may be less willing to invest in R&D because of its long-term horizon…
Abstract
Purpose
Corporate managers spend on research and development (R&D) for reasons of growth and survival. However, they may be less willing to invest in R&D because of its long-term horizon, high failure rate and uncertain outcomes. This study aims to explore the extent to which managerial ownership influences R&D expenditure decisions.
Design/methodology/approach
Apart from the linear regression models, this study uses a semi-parametric quantile regression analysis for a sample of German non-financial firms throughout 2009–2018.
Findings
This study finds a nonmonotonic sensitivity of R&D spending to the level of managerial ownership over various quantiles of R&D distribution. That is, managerial ownership increases the expenditure on R&D at low R&D intensity firms. However, it decreases the expenditure on R&D at high R&D intensity firms. These results suggest the presence of a maximum level of R&D expenditure, after which owner-managers would be unwilling to spend on R&D.
Practical implications
The results confirm the importance of corporate ownership structure for firm R&D and innovation activities. It provides an implication for corporate policymakers to reform the corporate ownership structures to encourage corporate managers and owners to invest in R&D projects.
Originality/value
This study offers two distinct contributions study. First, it provides the first German shred of evidence on the nonlinear relationship between managerial ownership and R&D expenditure decisions by distinguishing between high and low R&D intensity firms. Second, unlike prior research, it uses a semi-parametric quantile regression analysis. This method is more efficient than least-squares estimators and produces robust estimators to heteroscedasticity of the residuals.
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Arfat Ahmad Sofi and Raja Sethu Durai S.
The purpose of this paper is to investigate convergence hypothesis in a balanced panel of 22 Indian states for the time period of 1980-81 to 2010-11 by applying nonparametric…
Abstract
Purpose
The purpose of this paper is to investigate convergence hypothesis in a balanced panel of 22 Indian states for the time period of 1980-81 to 2010-11 by applying nonparametric model setting in a panel framework.
Design/methodology/approach
The present study uses nonparametric and semi-parametric panel data methods to test the absolute and conditional convergence, respectively, and examines the income convergence using nonparametric panel data methods with state specific effects taken into consideration. These models are being estimated by the iterative process for a balanced panel of state wise per capita income and other conditioning variables for the time period of 1980-81 to 2010-11. For removing the fixed effects, the authors follow within transformation procedure according to the feasibility of the problem. Since convergence is estimated by regressing dependent variable on initial level of independent variable (as growth rate of income and per capita income in this case). So using usual transformation for removing the fixed effects is not feasible because by doing so the authors may end up with singular matrices on both sides of the regression model.
Findings
The results reject the null of parametric specification for both absolute as well as conditional convergence model. As to the outcome of the empirical analysis, the findings reveal that the Indian states are diverging in absolute sense and converging on conditional basis. Convergence happens to be consistent and conditional upon public expenditure, power generation share of primary and tertiary sector to Gross State Domestic Product.
Originality/value
The originality of the study is in its application of advanced methodology to highlight the model misspecifications while testing the convergence hypothesis in earlier literature.
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Manthos D. Delis and Nikolaos I. Papanikolaou
This paper aims to analyze bank efficiency into a number of bank‐specific, industry‐specific and macroeconomic determinants.
Abstract
Purpose
This paper aims to analyze bank efficiency into a number of bank‐specific, industry‐specific and macroeconomic determinants.
Design/methodology/approach
The authors follow a semi‐parametric two‐stage methodology, where productive efficiency is derived via a non‐parametric technique in the first stage and then the scores obtained are linked to a series of determinants of bank efficiency, using a double bootstrapping procedure.
Findings
Overall, it is found that the banking sectors of almost all the sample countries show a gradual improvement in their efficiency levels. The model used shows that a number of determinants like bank size, industry concentration and the investment environment have a positive impact on bank efficiency, which is not the case when standard Tobit models are employed.
Research limitations/implications
The findings have important implications for the relevance of well‐known hypotheses that refer to the performance of the banking sectors, like the structure‐conduct‐performance and the efficient structure hypotheses. These implications are not necessarily verified when past conventional econometric methodologies are used.
Practical implications
The paper offers new insights to policy makers, bank managers and practitioners on the relevance of a number of driving factors of bank efficiency that might help them to improve the performance of the banking system and enhance the quality of services provided.
Originality/value
This is the first paper in the bank efficiency literature that employs a semi‐parametric two‐stage model, which relaxes several deficiencies of previous two‐stage empirical approaches thus, offering a solution to the many problematic features of standard censored regressions.
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