International Journal of Computational Economics and Econometrics http://www.inderscience.com/browse/index.php?journalID=311&year=2011&vol=2&issue=2 Inderscience Publishers Ltd en-uk International Journal of Computational Economics and Econometrics 1757-1170 1757-1189 © 2011 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijcee_scoverijcee.jpg http://www.inderscience.com/browse/index.php?journalID=311&year=2011&vol=2&issue=2 http://www.inderscience.com/link.php?id=43248 The debate about exploring the drivers of pollution, material consumption and energy use has centred on estimating environmental Kuznet curves for countries in a time series, cross-sectional or panel analysis. Very often, evidence is mixed since especially institutional frameworks, market conditions and environmental policies are different between countries. This paper analyses industrial branches mirrored in the National Accounting Matrix including Environmental Accounts system with specific emphasis on the connections between the industrial production and selected environmental indicators in several panel estimations. Linkages between value added (VA) and environmental indicators are significantly positive only for the direct material consumption. For SO<SUB align=right>2, we find decoupling of VA and emissions. For energy consumption, CO<SUB align=right>2 and NO<SUB align=right>x emissions, the empirical estimations do indicate a stable relationship, neither positive nor negative. The results show that these linkages have to be analysed rather at the level of industrial branches than in an economy-wide framework. Industry-specific determinants of environmental indicators
Michael Getzner
International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 75 - 94
The debate about exploring the drivers of pollution, material consumption and energy use has centred on estimating environmental Kuznet curves for countries in a time series, cross-sectional or panel analysis. Very often, evidence is mixed since especially institutional frameworks, market conditions and environmental policies are different between countries. This paper analyses industrial branches mirrored in the National Accounting Matrix including Environmental Accounts system with specific emphasis on the connections between the industrial production and selected environmental indicators in several panel estimations. Linkages between value added (VA) and environmental indicators are significantly positive only for the direct material consumption. For SO<SUB align=right>2, we find decoupling of VA and emissions. For energy consumption, CO<SUB align=right>2 and NO<SUB align=right>x emissions, the empirical estimations do indicate a stable relationship, neither positive nor negative. The results show that these linkages have to be analysed rather at the level of industrial branches than in an economy-wide framework.

]]> 10.1504/IJCEE.2011.043248 International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 75 - 94 Michael Getzner Center of Public Finance and Infrastruktur Policy, Vienna University of Technology, Resselgasse 5, Vienna 1040, Austria indicator determinants environmental indicators industrial branches environmental Kuznet curves decoupling value added industry specific. 2011-10-22T23:20:50-05:00 2 2 75 94 2011-10-22T23:20:50-05:00 http://www.inderscience.com/link.php?id=43249 A portfolio optimisation problem on an infinite time horizon is considered. Risky asset price obeys a logarithmic Brownian motion, and the interest rate varies according to a Markov diffusion process. This paper obtains an investment strategy considering one stock, one bond where the risk-free interest rate, the appreciation and the volatility of the stock depend on an external finite state Markov chain. We investigate the problem of maximising the expected utility from terminal wealth and solve it explicitly by stochastic control methods for a specific utility function U (x ) = logx. Choosing an investment strategy by stochastic control
Amaresh Das
International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 95 - 104
A portfolio optimisation problem on an infinite time horizon is considered. Risky asset price obeys a logarithmic Brownian motion, and the interest rate varies according to a Markov diffusion process. This paper obtains an investment strategy considering one stock, one bond where the risk-free interest rate, the appreciation and the volatility of the stock depend on an external finite state Markov chain. We investigate the problem of maximising the expected utility from terminal wealth and solve it explicitly by stochastic control methods for a specific utility function U (x ) = logx.

]]> 10.1504/IJCEE.2011.043249 International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 95 - 104 Amaresh Das College of Business, Southern University at New Orleans, New Orleans, LA 70126, USA; Department of Mathematics, University of New Orleans, New Orleans, LA 70148, USA Markov chain Brownian motion portfolio strategy investment strategy stochastic control portfolio optimisation infinite time horizon. 2011-10-22T23:20:50-05:00 2 2 95 104 2011-10-22T23:20:50-05:00 http://www.inderscience.com/link.php?id=43250 This paper tests whether the econometric model of Boswijk et al. (2007) (BHM07) adequately identifies strategy switching behaviour by using computational data from a different model, in particular the model Friedman and Abraham (2009) (FA09). The purpose of using computational data based on an endogenous behavioural mechanism distinct from switching behaviour is to examine whether we can recover the estimates found using S&P 500 data. The results indicate that the estimation results from BHM07 can be partly recovered from the computational data suggesting that BHM07 does adequately identify switching behaviour. However, results also suggest that factors not included BHM07 but included in FA09 may be as or more important in explaining fat tails and excessive volatility. Econometrics and computational economics: an exercise in compatibility
Todd Feldman; Yi Sun
International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 105 - 114
This paper tests whether the econometric model of Boswijk et al. (2007) (BHM07) adequately identifies strategy switching behaviour by using computational data from a different model, in particular the model Friedman and Abraham (2009) (FA09). The purpose of using computational data based on an endogenous behavioural mechanism distinct from switching behaviour is to examine whether we can recover the estimates found using S&P 500 data. The results indicate that the estimation results from BHM07 can be partly recovered from the computational data suggesting that BHM07 does adequately identify switching behaviour. However, results also suggest that factors not included BHM07 but included in FA09 may be as or more important in explaining fat tails and excessive volatility.

]]> 10.1504/IJCEE.2011.043250 International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 105 - 114 Todd Feldman; Yi Sun Department of Finance, San Francisco State University, San Francisco, CA 94132, USA. ' HSBC Private Bank, 71 S Wacker Drive, Suite 2700, Chicago, IL 60606, USA financial markets agent-based modelling agent-based systems multi-agent systems experimental economics econometrics computational economics strategy switching behaviour fat tails excessive volatility. 2011-10-22T23:20:50-05:00 2 2 105 114 2011-10-22T23:20:50-05:00 http://www.inderscience.com/link.php?id=43251 This paper discusses the numerical solution of the coupled algebraic Riccati equations associated with the linear quadratic differential games. The Lyapunov iteration for solving the considered coupled equations is discussed by Li and Gajic (1994). We modify this iteration and derive the new algorithm with typically convergence properties for methods of such a type introduced in the literature. Finally, to demonstrate the efficiency of the proposed algorithms, computational examples are provided and numerical effectiveness of the considered algorithms is commented. Equilibrium in Nash differential games via Lyapunov-type iterations
Ivan Ganchev Ivanov; Boyan Mihailov Lomev
International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 115 - 122
This paper discusses the numerical solution of the coupled algebraic Riccati equations associated with the linear quadratic differential games. The Lyapunov iteration for solving the considered coupled equations is discussed by Li and Gajic (1994). We modify this iteration and derive the new algorithm with typically convergence properties for methods of such a type introduced in the literature. Finally, to demonstrate the efficiency of the proposed algorithms, computational examples are provided and numerical effectiveness of the considered algorithms is commented.

]]> 10.1504/IJCEE.2011.043251 International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 115 - 122 Ivan Ganchev Ivanov; Boyan Mihailov Lomev Department of Statistics and Econometrics, Faculty of Economics and Business Administration, Sofia University “St. Kliment Ohridski”, Sofia 1113, Bulgaria. ' Department of Statistics and Econometrics, Faculty of Economics and Business Administration, Sofia University “St. Kliment Ohridski”, Sofia 1113, Bulgaria linear quadratic differential games Nash strategies coupled algebraic Riccati equations Lyapunov iteration econometrics. 2011-10-22T23:20:50-05:00 2 2 115 122 2011-10-22T23:20:50-05:00 http://www.inderscience.com/link.php?id=43252 Latent variable modelling is used widely in applications to economics, social and behavioural sciences. Since the normality-based model fitting procedures are simple and broadly available, and since such procedures are often applied to non-normal data or non-random samples, it is important to investigate the appropriateness of such practice and to suggest simple remedies. This paper addresses these issues for the analysis of multiple populations. For a very general class of latent variable models, a particular parameterisation is used for meaningful and interpretable analysis of several populations. It turns out that under this parameterisation the large sample statistical inferences based on the assumption of normal and independent populations are valid for virtually any non-normal and dependent populations. This result is also valid when some latent variables are treated as fixed instead of random, or when a group of individuals is measured over several time points longitudinally. Inference for structural equation modelling on dependent populations
Savas Papadopoulos
International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 123 - 153
Latent variable modelling is used widely in applications to economics, social and behavioural sciences. Since the normality-based model fitting procedures are simple and broadly available, and since such procedures are often applied to non-normal data or non-random samples, it is important to investigate the appropriateness of such practice and to suggest simple remedies. This paper addresses these issues for the analysis of multiple populations. For a very general class of latent variable models, a particular parameterisation is used for meaningful and interpretable analysis of several populations. It turns out that under this parameterisation the large sample statistical inferences based on the assumption of normal and independent populations are valid for virtually any non-normal and dependent populations. This result is also valid when some latent variables are treated as fixed instead of random, or when a group of individuals is measured over several time points longitudinally.

]]> 10.1504/IJCEE.2011.043252 International Journal of Computational Economics and Econometrics, Vol. 2, No. 2 (2011) pp. 123 - 153 Savas Papadopoulos Democritus University of Thrace, University Campus, Komotini 69100, Greece; Department of Financial Stability, Bank of Greece, Amerikis 3, Athens 10250, Greece structural equation modelling latent variables LISREL fixed variables non-normal factors asymptotic robustness multi-sample methods dependent populations panel data longitudinal data inference. 2011-10-22T23:20:50-05:00 2 2 123 153 2011-10-22T23:20:50-05:00