The hydroelectricity consumption and economic growth in Asian countries - evidence using an asymmetric cointegration approach

ABSTRACT

This study examines the four commonly tested hypotheses in hydroelectricity consumption – economic growth literature for 12 Asian countries. Our results from a recently developed hidden cointegration technique uncover rich and significant relationships between negative and positive components of the variables under consideration. In particular, we find evidence to support the neutrality hypothesis in five countries (Bangladesh, Indonesia, Pakistan, Philippines, and Thailand), the growth hypothesis in four countries (India, Japan, South Korea and Taiwan), and both growth and conservation hypotheses in three countries (China, Malaysia, and New Zealand). These findings suggest that appropriate economic policies should be elaborated on the basis of the country’s specific hydroelectricity consumption–growth nexus. Finally, our new evidence suggests that the lack of stable relationship between hydroelectricity consumption and economic growth documented in previous studies for some of these countries could be due to the failure to properly account for the nonlinearity property in the data.     

Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models

We examine and compare a large number of generalized autoregressive conditional heteroskedastic (GARCH) and stochastic volatility (SV) models using series of Bitcoin and Litecoin price returns to assess the model fit for dynamics of these cryptocurrency price returns series. The various models examined include the standard GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, t-distributed and moving average innovations. We report that the best model for Bitcoin is SV-t while it is GARCH-t for Litecoin. Overall, the t-class of models performs better than other classes for both cryptocurrencies. For Bitcoin, the SV models consistently outperform the GARCH models and the same holds true for Litecoin in most cases. Finally, the comparison of GARCH models with GARCH-GJR models reveals that the leverage effect is not significant for cryptocurrencies, suggesting that these do not behave like stock prices.     

Effective Rental Housing Demand in the Tokyo Metropolitan Region

This paper reports on the estimation of housing demand for tenants in Tokyo Metropolitan Region using household level data for 1993. The results indicate that the rental housing demand is inelastic with respect to permanent income and price, with coefficients as 0.31 and -0.093 respectively. Other important variables, which determine housing demand for tenants are length of stay and type of household. Larger households demand more housing. However, keeping the size of household constant, households with elderly members have higher demand for housing. The only exception to the rule is households formed with members not belonging to same nucleus family demand less housing.     

Binomial Option Pricing Biases and Inconsistent Implied Volatilities

We evaluate the binomial option pricing methodology (OPM) by examining simulated portfolio strategies. A key aspect of our study involves sampling from the empirical distribution of observed equity returns. Using a Monte Carlo simulation, we generate equity prices under known volatility and return parameters. We price American–style put options on the equity and evaluate the risk–adjusted performance of various strategies that require writing put options with different maturities and moneyness characteristics. The performance of these strategies is compared to an alternative strategy of investing in the underlying equity. The relative performance of the strategies allows us to identify biases in the binomial OPM leading to the well–known volatility smile . By adjusting option prices so as to rule out dominated option strategies in a mean–variance context, we are able to reduce the pricing errors of the OPM with respect to option prices obtained from the LIFFE. Our results suggest that a simple recalibration of inputs may improve binomial OPM performance.     

Bayes prediction density and regression estimation — A semiparametric approach

This paper is concerned with the Bayes estimation of an arbitrary multivariate density,f(x), x ? R ^k. Such anf(x) may be represented as a mixture of a given parametric family of densities {h (x¦θ)} with support inR ^k, whereθ (inR ^d) is chosen according to a mixing distributionG. We consider the semiparametric Bayes approach in whichG, in turn, is chosen according to a Dirichlet process prior with given parameterα. We then specialize these results whenf is expressed as a mixture of multivariate normal densitiesΦ (x¦Μ, λ) whereΜ is the mean vector and λ is the precision matrix. The results are finally applied to estimating a regression parameter.     

Financial Constraints and Other Obstacles: are they a Threat to Innovation Activity?

Summary  In this paper we examine the importance of financial and other obstacles to innovation in the Netherlands using statistical information from the CIS 3.5 innovation survey. We report results on the effect of these obstacles on the firms’ decision to abandon, prematurely stop, seriously slow down, or not to start an innovative project. These results are compared with those from other studies in the Netherlands and other countries. We end with a discussion of policy measures that have been taken to overcome, or at least attenuate these obstacles, such as R&D tax incentives, venture capital financing and policy mix packages.