Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping

We examine the quantile serial dependence in crude oil prices based on the Linton and Whang’s quantile-based portmanteau test which we improved by means of quantile wild bootstrapping (QWB). Through Monte Carlo simulation, we find that the quantile wild bootstrap-based portmanteau test performs better than the bound testing procedure suggested by Linton and Whang. We apply the improved test to examine the efficiency of two crude oil markets – WTI and Brent. We also examine if the dependence is stable via rolling sample tests. Our results show that both WTI and Brent are serially dependent in all, except the median quantiles. These findings suggest that it may be misleading to examine the efficiency of crude oil markets in terms of mean (or median) returns only. These crude oil markets are relatively more serially dependent in non-median ranges.     

Examination of the impacts of the immediate interest rate of the United States and the VIX on the Dow Jones Islamic Market Index

This study examines the effects of the market volatility index of the Chicago Board Options Exchange (VIX) and the immediate interest rate of the United States on the Dow Jones Islamic Market Index (DJIMI) using quantile-based techniques and wavelet coherence (WTC) analysis with monthly data for the period January 2010to May 2021. A quantile cointegration model indicated that the relationship between the VIX and the DJIMI can be valid in the long term since the estimated coefficients are negative and statistically significant across the quantiles 0.05 and 0.50, while a quantile autoregressive model revealed that large negative and positive changes in the VIX and the immediate interest rate of the United States do not have a significant impact on the DJIMI in the short term. Allowing the role of regime changes, it was found by the quantile regression model that an increase in the VIX lowers the performance in the DJIMI, supported by the WTC. It was also underlined that the DJIMI may not benefit from the positive financial conditions. According to the quantile regression models, the immediate interest rate of the US has asymmetrical effects, and the stabilizing effect of the increase/decrease is valid during bearish/bullish market conditions in the DJIMI.     

Technology,Exports And Firm Efficiency In Taiwanese Manufacturing

Using firm-level data from the 1986 Census of Manufactures of Taiwan, we examine the links between technical efficiency and firm investments in technology and exports. Stochastic production frontier techniques are used to estimate the technical efficiency of firms by investments in technology as well as by export orientation. Our results indicate that accounting for firm investments in technology is critical in explaining the strong export-productivity link in the extant literature. For the group of large, high technology firms, the differences in the mean efficiencies between exporters and non-exporters are not significantly different than zero in all nine industries under study. However, for the large number of small firms that make no formal investments in technology. exporters are significantly closer to the production frontier than their counterparts that sell in the domestic market.     

Cost efficiency of the Chinese banking sector: A comparison of stochastic frontier analysis and data envelopment analysis

This paper investigates the consistency of efficiency scores obtained from the stochastic frontier analysis and data envelopment analysis methods. We estimate cost efficiency and economies of scale based on an unbalanced panel data set of Chinese banks over the period 1994 to 2007. The results suggest moderate consistency between parametric and non-parametric frontier methods in efficiency scores rankings, identification of best and worst practise banks, the stability of efficiency scores over time and correlation between frontier efficiency and accounting based performance measures. Based on the findings, we conclude that the use of multiple frontier techniques for efficiency analysis is to be strongly recommended and that this methodological cross-checking analysis will result in more robust and convincing assessments of bank performance.     

A quantile regression approach for estimating panel data models using instrumental variables

We introduce a quantile regression approach to panel data models with endogenous variables and individual effects correlated with the independent variables. We find newly developed quantile regression methods can be easily adapted to estimate this class of models efficiently.     

Quantile estimation of frontier production function

The purpose of the paper is to provide new information on the performance of frontier estimation methods, using data from Italian hotel industry. Quantile regression is also suggested as solution to frontier production function estimation. It is shown that, while the choice of estimation methods among conventional techniques significantly affects the economic analysis, quantile regression provides valuable new information by estimating the whole spectrum of production functions corresponding to different efficiency levels. In addition, the method makes available a coherent framework to analyze the performance of the conventional techiniques. Jel classification: C14, C16, D24We would like to thank the Co-Editor, the Associate Editor and an anonymous referee for comments and suggestions. The research was supported by the University Research Council and the National Research Council. The usual disclaimer applies.The estimates were computed using the Roger Koenker and StatLibS-Plus routine of quantile regression and the Tim Coelli and CEPA Web site FRONTIER 4.1 Program. The data set is provided by the Ho.Re.Ca. survey conducted by ISTAT in 1992.First version received: June 2001/Final version received: December 2002     

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.     

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.     

Justifying the incorporation of the materials balance principle into frontier-based eco-efficiency models

Frontier-based models are an alternative to traditional eco-efficiency ratio indicators. This paper considers two different types, environmentally adjusted production efficiency models and frontier eco-efficiency models, and tries to find justification for incorporating the materials balance principle (MBP) in them. Similar importance is attached to the economic and environmental outcomes of a production process. Like economic outcomes can be derived from inputs and outputs and respective prices, some cases allow for deriving environmental outcomes from the production function with the MBP. After an overview of attempts to incorporate environmental issues in production efficiency models and some reflections why MBP has been neglected in environmental economics and production efficiency analysis, the paper gives basic principles to incorporate the MBP in conventional production efficiency methods and shows how this adjustment leads to a more diversified diagnosis of eco-efficiency. Finally, potentialities and bottlenecks are discussed. Exploiting the MBP in production efficiency and eco-efficiency analysis will facilitate more pro-active eco-efficiency research.     

On the median regression for SURE models with applications to 3-generation immigrants data in Sweden

In this paper we generalize the median regression method to be applicable to system of regression equations, in particular SURE models. Giving the existence of proper system wise medians of the residuals from different equations, we apply the weighted median regression with the weights obtained from the covariance matrix of the equations obtained from ordinary SURE method. The benefit of this model in our case is that the SURE estimators utilise the information present in the cross regression (or equations) error correlation and hence more efficient than other estimation methods like the OLS method. The Seemingly Unrelated Median Regression Equations (SUMRE) models produce results that are more robust than the usual SURE or single equations OLS estimation when the distributions of the dependent variables are not normally distributed or the data are associated with outliers. Moreover, the results are also more efficient than is the cases of single equations median regressions when the residuals from the different equations are correlated. A theorem is derived and indicates that even if there is no statistically significant correlation between the equations, using SUMRE model instead of SURE models will not damage the estimation of parameters.     

Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks

In this paper, we use the local maximum likelihood (LML) method proposed by Kumbhakar et al. (J Econom, 2007) to estimate stochastic cost frontier models for a sample of 3,691 U.S. commercial banks. This method relaxes several deficiencies in the econometric estimation of frontier functions. In particular, we relax the assumption that all banks share the same production technology and provide bank-specific measures of returns to scale and cost inefficiency. The LML method is applied to estimate the cost frontiers in which a truncated normal distribution is used to model technical inefficiency. This formulation allows the cost frontier, inefficiency effects and heteroskedasticity in both noise and inefficiency components to be quite flexible.      

Impact of the adoption of information and communication technologies on firm efficiency in the Tunisian manufacturing sector

This paper aims at measuring the impact of information and communication technology use on the efficiency of the Tunisian manufacturing sector at the firm level within a simple theoretical framework. We are using a firm-level panel data for the manufacturing sector in Tunisia to investigate whether adoption of ICT influences efficiency in factor use. The analysis is conducted through the use of a parametric method to measure technical efficiency. We estimate a stochastic production frontier and the relationship aims to explain technical efficiency differentials in a single stage as suggested by Battese and Coelli [Battesse, G.E, Coelli, T.J. (1995). A model for technical inefficiency in a stochastic frontier production function for panel data. Empirical Economics, 20, 325–332].The results have confirmed the presence of positive returns to ICT capital. We have found that the impact of ICT on efficiency is strong. Our results also suggest that it is important to carefully control for human capital related characteristics of employment when studying the effect of ICT. The evidence shows that achieving benefits from investment in ICT requires complementary investments and changes in human capital. This means that the combined use of ICT and human capital in a firm would enhance its efficiency beyond the direct effects of these factors taken alone.     

The asymptotic efficiency of semiparametric estimators for censored linear regression models

This paper presents numerical comparisons of the asymptotic mean square estimation errors of semiparametric generalized least squares (SGLS), quantite, symmetrically censored least squares (SCLS), and tobit maximum likelihood estimators of the slope parameters of censored linear regression models with one explanatory variable. The results indicate that the SCLS estimator is less efficient than the other two semiparametric estimators. The SGLS estimator is more efficient than quantile estimators when the tails of the distribution of the random component of the model are not too thick and the probability of censoring is not too large. The most efficient semiparametric estimators usually have smaller mean square estimation errors than does the tobit estimator when the random component of the model is not normally distributed and the sample size is 500–1,000 or more.     

Do Listed Banks have Higher Operating Efficiency and Output Efficiency?

This paper investigates the efficiency and productivity of listed and non‐listed banks in China by using the meta‐frontier and GMMPI methods. We find that the improvement in productivity of listed and non‐listed banks is mainly due to changes in technological efficiency. The difference between them is that the improvement of productivity of listed banks presents a typical technology‐driven feature, and changes in scale efficiency negatively affect productivity. The productivity of non‐listed banks shows scale efficiency driving features. The meta‐frontier efficiency of listed banks is significantly higher than the others. After decomposing the technology gap ratio, we find that the current production technology of the listed banks is closer to the potential production technology frontiers, and there is space for the non‐listed banks to improve their efficiency. Besides, the gaps between the true extent and the potential technological frontiers of both listed banks and non‐listed banks have converged.     

Trade, technology transfer and national efficiency in developing countries

This paper simultaneously explores the determinants of the developing countries’ production frontier and these countries’ ‘efficiency’ in using the available resources and technology. In doing so it allows for the transfer of (industrial country) technology in determining the frontier and for international trade's influence on absorptive capacity and national efficiency levels. Stochastic frontier analysis is used to model the production frontier for 57 developing countries for the period 1970-1998, to measure cross-country and temporal differences in efficiency levels and to explain the differences in efficiency levels. The results indicate significant differences in efficiency levels across countries and regions and movement over time, and an important influence of trade and trade policy in raising output both through technology improvements embodied in imported capital goods and by inducing efficiency improvements.     

Surface mining of coal: efficiency of US interior mines

In this paper the relative efficiency in surface mining of US interior coal is investigated. A nonparmetric, non-stochasitic method is applied to 186 observations and esch firm's efficiency is calculated relative to the piecewise llinesr frontier technology. In adition, three sources of inefficiency are identified, namely: Scale, congestion and purely technical inefficiency. The outcome of the study shows among other things that on the average, captive mines are more efficient than non-captive mines, and that unionized mines are more efficient than non-unionized mines.     

Estimating a mixture of stochastic frontier regression models via the em algorithm: A multiproduct cost function application

Researchers have become increasingly interested in estimating mixtures of stochastic frontiers. Mester (1993), Caudill (1993), and Polachek and Yoon (1987), for example, estimate stochastic frontier models for different regimes, assuming sample separation information is given. Building on earlier work by Lee and Porter (1984), Douglas, Conway, and Ferrier (1995) estimate a stochastic frontier switching regression model in the presence of noisy sample separation information. The purpose of this paper is to extend earlier work by estimating a mixture of stochastic frontiers assuming no sample separation information. This case is more likely to occur in practice than even noisy sample separation information. In order to estimate a mixture of stochastic frontiers with no sample separation information, an EM algorithm to obtain maximum likelihood estimates is developed. The algorithm is used to estimate a mixture of stochastic (cost) frontiers using data on U.S. savings and loans for the years 1986, 1987, and 1988. Statistical evidence is found supporting the existence of a mixture of stochastic frontiers. First version received: 3/13/01/Final version received: 6/17/02 RID="*" ID="*"  I am grateful to Ram Acharya, Janice Caudill, and especially James R. Barth for several helpful comments on an earlier version of the paper. During the revision process I benefitted greatly from the suggestions of the Associate Editor and three anonymous referees.     

The efficiency of the Scandinavian banking sector – a wavelet quantile regression analysis

In this article, the Scandinavian housing financing market is analysed in order to determine whether the interest rate price-discovery processes of Denmark, Norway and Sweden are efficient. Based on wavelet quantile regression analysis, we find systematic positive asymmetric price transmission (APT) inefficiencies. We conclude that there is a very high propensity for mortgage lenders to directly increase its customers’ mortgage interest rates subsequently to an increase in its borrowing costs. However, after a corresponding borrowing cost decrease, the same mortgage lenders are very slow to decrease its customers’ mortgage rates. These positive coefficients for so-called APT effects are found in all Scandinavian countries, even if the coefficients for Norway were not statistically significant. Wavelet quantile regression analysis, with a focus on the relevant higher percentiles, is easily motivated since the mortgage rates are adjusted very infrequently. Moreover, wavelet decomposition allows a robust analysis at different time frequency scales, while simultaneously controlling for nonstationary trends, autocorrelation and structural breaks. Except for the still positive but yet insignificant and inconclusive coefficients for Norway, the result is very clear-cut. Regardless of which wavelet scaling decomposition or quantile coefficient that is studied – positive APT effects are clearly identified and confirmed on the Scandinavian mortgage market.     

An analysis of the impact of unionization on efficiency: evidence from a meta-frontier analysis

This article examines the impact of unions on the efficiency of establishments in the manufacturing industry by comparing the results from two different empirical strategies: stochastic frontier analysis (SFA) and meta-frontier analysis (MFA). While SFA concludes that union establishments show higher technological efficiency, the results are the opposite when estimating production functions with MFA. In SFA, unionized establishments appear to be more efficient because they remain closer to their own production frontier; however, in MFA – where groups with heterogeneous technology can be compared – we find that nonunionized establishments are more efficient because they are closer to the meta-frontier than their unionized counterparts.     

Growth and value hybrid valuation model based on mean reversion

This article proposes a novel valuation model, growth and value hybrid model, to estimate the stock price. This proposed model combines the essence of the asset-based approach, the income-based approach, and the principle of mean reversion to develop the theoretical closed-form formula consisting of three coefficients: value coefficient, value support coefficient and growth coefficient. Regression analysis is employed to fit market data to determine these coefficients. Moreover, this study proposes the double sorting method to build the quantile regression models of the formula to estimate the stock price at a specific quantile. The results show that the predictive capability of the hybrid valuation model is superior to the model without using value support coefficient, which supports the assumption that the PBR is not associated with the ROE when the ROE is less than a threshold. In different time periods of the stock market, no significant difference exists on the value support coefficient. However, the variations of the value coefficient and the growth coefficient are significant.