This paper develops a consistent nonparametric test for Granger causality in the context of stron... more This paper develops a consistent nonparametric test for Granger causality in the context of strong-mixing process, which covers a large class of stationary processes including ARMA and ARCH models. The previously proposed tests require absolute regularity (-mixing) more stringent than the strong-mixing condition. We prove the consistency of the test under a high level assumption on the approximation error of U statistic by its projection. Due to the sample splitting, the test statistic we propose is asymptotically normally distributed under the null.
The nuclear power and radio-isotope based industriesin Korea have been major drivers in the natio... more The nuclear power and radio-isotope based industriesin Korea have been major drivers in the nation’s socio-economic development over the past decades. Theseindustries have also provided spin-offs to technologicalinnovation as well as environmental benefits in terms ofavoiding both greenhouse gas emissions and pollution inthe context of achieving sustainable development.Furthermore, the country has changed its position froman importer to an exporter of nuclear plants and nucleartechnologies. The history of nuclear energy development in Koreacommenced in earnest in 1978 when the first nuclearpower plant, Kori-1, was built on a turn-key basis andbegan commercial operation. Nuclear energy was chosento diversify the nation’s energy supply in response toeconomic development setbacks resulting from the oilcrises of the 1970s and 1980s. Twenty nuclear powerreactors have been since put into commercial operation,supplying approximately 40% of Korea’s electricity witha total generating capacit...
Although Computable General Equilibrium (CGE) models are now widely used in fields of energy, env... more Although Computable General Equilibrium (CGE) models are now widely used in fields of energy, environment and economy to assess policy impact, they are often criticized as most key parameters are not econometrically estimated. Since the models are often large in scale, however, econometric estimation of parameters is costly, particularly in constructing huge database. Identifying important parameters would be useful as resources and information could be efficiently concentrated on them. This paper employs a novel approach of Belgodere and Vellutini (2011) to the identification of important parameters of an economy-energy-environment CGE model for the Korean economy. In the approach, (i) after a CGE model is constructed, parameter values denoted as X are randomly drawn via a Monte Carlo simulation, (ii) outcomes of the CGE model, denoted as Y, are calculated given the parameter values, (iii) the procedures are repeated N times to yield sample data of X and Y with size N, and (iv) fin...
In Korea, a proton linear accelerator complex is being built as a part of the 21st Century Fronti... more In Korea, a proton linear accelerator complex is being built as a part of the 21st Century Frontier Projects. Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely. This study shows the method can be applied to the benefit assessment of the proton accelerator complex. Using the discrete choice CVM method, this study estimates the willingness-to-pay (WTP) of a would-be user for the proton accelerator complex as 20,133 won per month.
This paper considers the test of money and income causality. Jeong (1991, 2003) developed a nonpa... more This paper considers the test of money and income causality. Jeong (1991, 2003) developed a nonparametric causality test based on the kernel estimation method. We apply the nonparametric test to USA data of money and income. We also compare the test results with ones of the conventional parametric test.
Since the pioneering work by Granger (1969), many authors have proposed tests of causality betwee... more Since the pioneering work by Granger (1969), many authors have proposed tests of causality between economic time series. Most of them are concerned only with ”linear causality in mean”, or if a series linearly affects the (conditional) mean of the other series. It is no doubt of a primary interest, but dependence between series may be nonlinear, and/or not only through the conditional mean. Indeed conditional heteroskedastic models are widely studied recently. The purpose of this paper is to propose nonparametric tests for possibly nonlinear causality up to K-th conditional moment. A desirable property of the tests is that they have nontrivial power against T 1/2-local alternatives, where T is sample size. Their null asymptotic distributions are not normal, but we can easily calculate the critical regions by simulation. Monte Carlo experiments showed that the proposed tests have good power properties, and much better than the competitors.
Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which market... more Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely; an example is environmental good. A dichotomous choice approach, the most popular type of CVM in environmental economics, employs binary discrete choice models as statistical estimation models. In this paper, we propose a semiparametric dichotomous choice CVM method using local linear model of Fan and Gijbels (1996) in which probability distribution of error term is specified parametrically but latent structural function is specified nonparametrically. The computation procedures of the proposed method are illustrated with a simple design of simulations.
Visual conservation center is a facility for the preservation of visual materials such as film an... more Visual conservation center is a facility for the preservation of visual materials such as film and digital image data, and its construction project is currently being considered. This study evaluates the economic benefit of the project using CVM (Contingent Valuation Method), the main method of nonmarket evaluation in the both domestic and foreign literature. Survey data used in the analysis was collected in seven major metropolitan cities using person-to-person interviews and a logit model is used for the econometric estimation. The economic benefit measured by a household's average willing to pay (WTP) per year is shown to amount to 8,958 won.
A company's market value-added, which equals the excess of a company's market capitalizat... more A company's market value-added, which equals the excess of a company's market capitalization over it s book value, is used as one of the measures for intangible assets valuation in accounting literature. One problem with the approach is that the valuation results are affected by severe fluctuations in capital markets. In this paper, we propose an approach using the Kalman filter for intangible assets valuation. We apply this method to data of Korean electronic companies.
In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been... more In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving average (MA), a recurrent NN and a parametric GACH in terms of their ability to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange rates from July 2, 2003 to June 30, 2005 and New York Stock Exchange (NYSE) daily composite index from July 3, 2003 to June 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms the MA, the recurrent NN and the parametric GARCH based on the criteria of mean absolute error (MAE) and directional accuracy (DA). No structured way being available to choose the free parameters of SVR, the sensitivity of performance is also examined to the free parameters.
Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regres... more Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the recurrent SVR is compared with three competing methods, MLE, recurrent MLP and feedforward SVR. Theoretically, MLE and MLP only focus on fit in-sample, but SVR considers both fit and forecast out-of-sample which endows SVR with an excellent forecasting ability. This is confirmed by the evidence from the simulated and real data based on two forecasting accuracy evaluation metrics (NSME and sign). That is, for one-step-ahead forecasting, the recurrent SVR is consistently better than the MLE and the recurrent MLP in forecasting both the magnitude and turning points, and really improves the forecasting performance as opposed to the usual feedforward SVR.
Journal of the Korean Data and Information Science Society
This study uses a continuous autoregressive (CAR) model to analyze daily average temperature in s... more This study uses a continuous autoregressive (CAR) model to analyze daily average temperature in six Korean metropolitan cities. Data period is Jan. 1, 1954 to Dec. 31, 2010 covering 57 years. Using a relative long time series reveals that the linear time trend components are all statistically significant in the six cities, which was not shown in previous studies. Particularly the plus sign of its coefficient implies the effect on Korea of the global warming. Unit-root test results are that the temperature time series are stationary without unit-root. It turns out that CAR(3) is suitable for stochastic component of the daily temperature. Since developing suitable continuous stochastic model of the underlying weather related variables is crucial in pricing the weather derivatives, the results in this study will likely prove useful in further future studies on pricing weather derivatives.
Journal of the Korean Data and Information Science Society
This study uses a quantile regression analysis to investigate intergenerational economic mobility... more This study uses a quantile regression analysis to investigate intergenerational economic mobility in Korea. The analysis is based on data from the 1st through 11th waves of the Korean Labor and Income Panel Study (KLIPS) conducted from 1998-2008. The household nature of the data allows us to link parents' incomes to children's incomes at different points in time. Using a quantile regression analysis instead of mean one reveals that the effect of fathers' earnings are different across the conditional distribution of sons' earnings, particularly being larger on the upper quantile than on the lower quantile. After controlling effect of sons' college education by including a dummy variable for the degree, however, the pattern among quantile effects for fathers' earnings is no longer clear. Instead a new pattern emerges that education has a much larger effect on the upper quantiles than on the lower ones. Using nonparametric estimates of conditional density curves based on the quantile regression results, we derive some interesting features in graphical forms, which are not obvious in numerical analysis.
This paper develops a consistent nonparametric test for Granger causality in the context of stron... more This paper develops a consistent nonparametric test for Granger causality in the context of strong-mixing process, which covers a large class of stationary processes including ARMA and ARCH models. The previously proposed tests require absolute regularity (-mixing) more stringent than the strong-mixing condition. We prove the consistency of the test under a high level assumption on the approximation error of U statistic by its projection. Due to the sample splitting, the test statistic we propose is asymptotically normally distributed under the null.
The nuclear power and radio-isotope based industriesin Korea have been major drivers in the natio... more The nuclear power and radio-isotope based industriesin Korea have been major drivers in the nation’s socio-economic development over the past decades. Theseindustries have also provided spin-offs to technologicalinnovation as well as environmental benefits in terms ofavoiding both greenhouse gas emissions and pollution inthe context of achieving sustainable development.Furthermore, the country has changed its position froman importer to an exporter of nuclear plants and nucleartechnologies. The history of nuclear energy development in Koreacommenced in earnest in 1978 when the first nuclearpower plant, Kori-1, was built on a turn-key basis andbegan commercial operation. Nuclear energy was chosento diversify the nation’s energy supply in response toeconomic development setbacks resulting from the oilcrises of the 1970s and 1980s. Twenty nuclear powerreactors have been since put into commercial operation,supplying approximately 40% of Korea’s electricity witha total generating capacit...
Although Computable General Equilibrium (CGE) models are now widely used in fields of energy, env... more Although Computable General Equilibrium (CGE) models are now widely used in fields of energy, environment and economy to assess policy impact, they are often criticized as most key parameters are not econometrically estimated. Since the models are often large in scale, however, econometric estimation of parameters is costly, particularly in constructing huge database. Identifying important parameters would be useful as resources and information could be efficiently concentrated on them. This paper employs a novel approach of Belgodere and Vellutini (2011) to the identification of important parameters of an economy-energy-environment CGE model for the Korean economy. In the approach, (i) after a CGE model is constructed, parameter values denoted as X are randomly drawn via a Monte Carlo simulation, (ii) outcomes of the CGE model, denoted as Y, are calculated given the parameter values, (iii) the procedures are repeated N times to yield sample data of X and Y with size N, and (iv) fin...
In Korea, a proton linear accelerator complex is being built as a part of the 21st Century Fronti... more In Korea, a proton linear accelerator complex is being built as a part of the 21st Century Frontier Projects. Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely. This study shows the method can be applied to the benefit assessment of the proton accelerator complex. Using the discrete choice CVM method, this study estimates the willingness-to-pay (WTP) of a would-be user for the proton accelerator complex as 20,133 won per month.
This paper considers the test of money and income causality. Jeong (1991, 2003) developed a nonpa... more This paper considers the test of money and income causality. Jeong (1991, 2003) developed a nonparametric causality test based on the kernel estimation method. We apply the nonparametric test to USA data of money and income. We also compare the test results with ones of the conventional parametric test.
Since the pioneering work by Granger (1969), many authors have proposed tests of causality betwee... more Since the pioneering work by Granger (1969), many authors have proposed tests of causality between economic time series. Most of them are concerned only with ”linear causality in mean”, or if a series linearly affects the (conditional) mean of the other series. It is no doubt of a primary interest, but dependence between series may be nonlinear, and/or not only through the conditional mean. Indeed conditional heteroskedastic models are widely studied recently. The purpose of this paper is to propose nonparametric tests for possibly nonlinear causality up to K-th conditional moment. A desirable property of the tests is that they have nontrivial power against T 1/2-local alternatives, where T is sample size. Their null asymptotic distributions are not normal, but we can easily calculate the critical regions by simulation. Monte Carlo experiments showed that the proposed tests have good power properties, and much better than the competitors.
Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which market... more Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely; an example is environmental good. A dichotomous choice approach, the most popular type of CVM in environmental economics, employs binary discrete choice models as statistical estimation models. In this paper, we propose a semiparametric dichotomous choice CVM method using local linear model of Fan and Gijbels (1996) in which probability distribution of error term is specified parametrically but latent structural function is specified nonparametrically. The computation procedures of the proposed method are illustrated with a simple design of simulations.
Visual conservation center is a facility for the preservation of visual materials such as film an... more Visual conservation center is a facility for the preservation of visual materials such as film and digital image data, and its construction project is currently being considered. This study evaluates the economic benefit of the project using CVM (Contingent Valuation Method), the main method of nonmarket evaluation in the both domestic and foreign literature. Survey data used in the analysis was collected in seven major metropolitan cities using person-to-person interviews and a logit model is used for the econometric estimation. The economic benefit measured by a household's average willing to pay (WTP) per year is shown to amount to 8,958 won.
A company's market value-added, which equals the excess of a company's market capitalizat... more A company's market value-added, which equals the excess of a company's market capitalization over it s book value, is used as one of the measures for intangible assets valuation in accounting literature. One problem with the approach is that the valuation results are affected by severe fluctuations in capital markets. In this paper, we propose an approach using the Kalman filter for intangible assets valuation. We apply this method to data of Korean electronic companies.
In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been... more In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving average (MA), a recurrent NN and a parametric GACH in terms of their ability to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange rates from July 2, 2003 to June 30, 2005 and New York Stock Exchange (NYSE) daily composite index from July 3, 2003 to June 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms the MA, the recurrent NN and the parametric GARCH based on the criteria of mean absolute error (MAE) and directional accuracy (DA). No structured way being available to choose the free parameters of SVR, the sensitivity of performance is also examined to the free parameters.
Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regres... more Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the recurrent SVR is compared with three competing methods, MLE, recurrent MLP and feedforward SVR. Theoretically, MLE and MLP only focus on fit in-sample, but SVR considers both fit and forecast out-of-sample which endows SVR with an excellent forecasting ability. This is confirmed by the evidence from the simulated and real data based on two forecasting accuracy evaluation metrics (NSME and sign). That is, for one-step-ahead forecasting, the recurrent SVR is consistently better than the MLE and the recurrent MLP in forecasting both the magnitude and turning points, and really improves the forecasting performance as opposed to the usual feedforward SVR.
Journal of the Korean Data and Information Science Society
This study uses a continuous autoregressive (CAR) model to analyze daily average temperature in s... more This study uses a continuous autoregressive (CAR) model to analyze daily average temperature in six Korean metropolitan cities. Data period is Jan. 1, 1954 to Dec. 31, 2010 covering 57 years. Using a relative long time series reveals that the linear time trend components are all statistically significant in the six cities, which was not shown in previous studies. Particularly the plus sign of its coefficient implies the effect on Korea of the global warming. Unit-root test results are that the temperature time series are stationary without unit-root. It turns out that CAR(3) is suitable for stochastic component of the daily temperature. Since developing suitable continuous stochastic model of the underlying weather related variables is crucial in pricing the weather derivatives, the results in this study will likely prove useful in further future studies on pricing weather derivatives.
Journal of the Korean Data and Information Science Society
This study uses a quantile regression analysis to investigate intergenerational economic mobility... more This study uses a quantile regression analysis to investigate intergenerational economic mobility in Korea. The analysis is based on data from the 1st through 11th waves of the Korean Labor and Income Panel Study (KLIPS) conducted from 1998-2008. The household nature of the data allows us to link parents' incomes to children's incomes at different points in time. Using a quantile regression analysis instead of mean one reveals that the effect of fathers' earnings are different across the conditional distribution of sons' earnings, particularly being larger on the upper quantile than on the lower quantile. After controlling effect of sons' college education by including a dummy variable for the degree, however, the pattern among quantile effects for fathers' earnings is no longer clear. Instead a new pattern emerges that education has a much larger effect on the upper quantiles than on the lower ones. Using nonparametric estimates of conditional density curves based on the quantile regression results, we derive some interesting features in graphical forms, which are not obvious in numerical analysis.
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Papers by Kiho Jeong