Kien C. Tran

Statistical modelling of asymmetric risk in asset returns

The purpose of this article is to provide a straightforward model for asset returns which captures the fundamental asymmetry in upward versus downward returns. We model this feature by using scale gamma distributions for the conditional distributions of positive and negative returns. By allowing the parameters for positive returns to differ from parameters for negative returns we can test the hypothesis of symmetry. Some applications of this process to expected utility and semi-variance calculations are considered. Finally we estimate the model using daily UK FT100 index and Futures data.

Efficiency, technological change and output growth in Greek olive growing farms: a Box-Cox approach

This paper captures the relative contributions of input growth, technological change and technical efficiency to olive oil production growth for a panel data set of 125 Greek olive-growing farms for the period 1987 to 1993. A flexible generalized quadratic Box-Cox functional form is proposed to represent the underlying production technology. This functional specification copes with the problem of zero inputs and nests all widely used production frontiers. Empirical results show that the observed production growth is mainly due to increased input use since it was not accompanied by rapid introduction of technological innovations and improvements in efficiency levels.

Assessing the impact of economic liberalization across countries: a comparison of dairy industry efficiency in Canada and the USA

This paper examines and compares the technical efficiency measures of Ontario and New York dairy producers for the period 1992 to 1998. A nonparametric stochastic frontier model is introduced to estimate technical efficiency. The backfitting algorithm of Breiman and Friedman is used to estimate the frontier. Empirical results indicate that during the period of study, New York dairy farmers produced milk more efficiently than Ontario dairy producers, but the magnitude of the difference was small. The estimated mean technical efficiency for the former group is 0.602 as compared to 0.532 for the latter. The results also indicated that over time, dairy farms in both regions improved their level of technical efficiency. Furthermore, no correlation was found between farm size and estimated technical efficiency.

Estimating mixtures of normal distributions via empirical characteristic function

This paper uses the empirical characteristic function (ECF) procedure to estimate the parameters of mixtures of normal distributions. Since the characteristic function is uniformly bounded, the procedure gives estimates that are numerically stable. It is shown that, using Monte Carlo simulation, the finite sample properties of th ECF estimator are very good, even in the case where the popular maximum likelihood estimator fails to exist. An empirical application is illustrated using the monthl excess return of the Nyse value-weighted index.

Local GMM Estimation of Semiparametric Panel Data with Smooth Coefficient Models

In this article, we consider the estimation of semiparametric panel data smooth coefficient models. We propose a class of local generalized method of moments (LGMM) estimators that are simple and easy to implement in practice. We show that the proposed LGMM estimators are consistent and asymptotically normal. Monte Carlo simulations suggest that our proposed estimator performs quite well in finite samples. An empirical application using a large panel of U.K. firms is also presented.

The determinants of Canadian provincial health expenditures: evidence from a dynamic panel

This article seeks to reveal the magnitude of the income elasticity of health expenditure and the impact of non income determinants of health expenditure across Canada. For this purpose, panel data on gross domestic product, the relative price of health care, the share of publicly funded health expenditure, the share of senior population and the life expectancy at birth have been used to investigate the determinants of Canadian provincial health expenditures over a 28 year period. Dynamic models of health expenditure are analysed via Generalized Instrumental Variables (GIV) and Generalized Method of Moments (GMM). Results indicate that the long run income elasticity of health expenditure is substantially lower than one. Thus, health care is far from being a luxury in Canada.

Long-Run Economic Performance and the Labor Market

This article uses a simple variation of the Solow model to study the interrelations between economic growth and the labor market. We show, both analytically and empirically, that income and capital per worker in the steady state depend positively on flexibility of the labor market; that the steady-state unemployment rate depends positively on the rate of population growth and the productivity growth rate and negatively on the savings rate and flexibility of the labor market; and, finally, that labor market flexibility affects convergence toward steady state.

Zero-inefficiency stochastic frontier models with varying mixing proportion: A semiparametric approach

In this paper, we propose a semiparametric version of the zero-inefficiency stochastic frontier model of Kumbhakar, Parmeter, and Tsionas (2013) by allowing for the proportion of firms that are fully efficient to depend on a set of covariates via unknown smooth function. We propose a (iterative) backfitting local maximum likelihood estimation procedure that achieves the optimal convergence rates of both frontier parameters and the nonparametric function of the probability of being efficient. We derive the asymptotic bias and variance of the proposed estimator and establish its asymptotic normality. In addition, we discuss how to test for parametric specification of the proportion of firms that are fully efficient as well as how to test for the presence of fully inefficient firms, based on the sieve likelihood ratio statistics. The finite sample behaviors of the proposed estimation procedure and tests are examined using Monte Carlo simulations. An empirical application is further presented to demonstrate the usefulness of the proposed methodology.

Predicting technical effciency in stochastic production frontier models in the presence of misspecification: a Monte-Carlo analysis

This paper provides a theoretical explanation for the sensitivity of technical efficiency measures to the choice of functional specification in stochastic production frontier models. It is shown that inappropriate functional specifications translate into a misspecification in the conditional mean of the stochastic frontier regression model. This misspecification, in turn, results in estimates of technical efficiency, confidence intervals and production elasticities being biased, even asymptotically. Monte-Carlo simulations reveal that the severity of the bias depends on the functional specification and the percentage contribution of the variance of technical inefficiency to the total variance of the composed errors.

Series estimation of functional-coefficient partially linear regression model

ABSTRACT This paper develops an alternative and complement estimation procedure for functional coefficient partially linear regression (FCPLR) model based on series method. We derive the convergence rates and asymptotic normality of the proposed estimator. We examine its finite sample performance and compare it with the two-step local linear estimator via a small scale Monte Carlo simulation.