The cyclicality of consumption,wages and employment of the public sector in the euro area

This study empirically examines the business cycle behaviour of public consumption and its main components, the public wage bill (including its breakdown into compensation per employee and public employment) and intermediate consumption, in the euro area aggregate, euro area countries and a group of selected non-euro area Organization for Economic Co-operation and Development (OECD) countries (Denmark, Sweden, the UK, Japan and the US). It looks across a large number of variables and methods, using annual data from 1960 to 2005. It finds robust evidence supporting that public consumption, wages and employment co-move with the business cycle in a pro-cyclical manner with 1–2 year lags, notably for the euro area aggregate and euro area countries. The findings reflect mainly the correlation between cyclical developments, but also point to an important role of pro-cyclical discretionary fiscal policies.     

面板数据分析中含两阶段自回归残差的单因素误差分量模型研究

在面板数据分析中残差自相关使得参数估计更加复杂。本文提出了含两阶段自回归残差的单因素误差分量模型,并推导了在这一模型中如何计算广义最小二乘估计量及其相关性质。     

Panel unit root tests under cross section dependence with recursive mean adjustment

Utilizing recursive mean adjustment (RMA) we provide two unit root tests: the covariate RMA unit root test and the panel feasible generalized RMA unit root test. The proposed panel unit root tests are precise and powerful, especially when T > N.     

Drivers of operational efficiency and its impact on market performance in the Indian Airline industry

India is considered to be one of the toughest aviation markets in the world, due to high fuel prices, overcapacity and intense price competition. It is therefore important to identify critical drivers of performance, which enable the airlines to survive and succeed in this emerging market with huge growth potential. In the current empirical study, we investigate the linkages between various performance drivers, operational efficiencies and market performance. An extensive data collection using primary and secondary sources enabled us to gather data on all the airlines operating in India, both private and public, for the period 2005–2012, on a variety of important parameters. We carried out a two-stage empirical analysis, which involved estimation of operational efficiencies during the first stage using Data Envelopment Analysis, and determination of performance drivers during the second stage using a two-way random effects GLS regression and also a Tobit model. Our findings suggest that while some of the structural and regulatory factors have an undesirable impact on airline performance, the low cost carriers in India have managed to achieve significant operational efficiencies. In addition, we find that, while cost efficiency is driven by a variety of factors, it is the technical efficiency which brings in better market performance through pricing power in the Indian airline industry.     

同期相关面板数据退势单位根检验的小样本性质

本文基于SUR回归将时间序列的两种单位根检验（ADF—GLS检验）推广到面板数据，得到了同期相关面板数据退势单位根检验，称为SUR—ADF—GLS检验。通过蒙特卡洛试验研究发现，SUR—ADF—GLS检验具有良好的小样本性质。并且，SUR—ADF—GLS检验关于面板数据的同期相关性结构存在着较强的“依存性”。     

多种单位根检验法的比较研究

本文基于单位根检验基本原理,比较了5种单位根检验的方法,说明在小样本情况下,为提高检验功效,应针对数据生成过程的特点联合多种检验法进行检验。如果检验变量为非平稳,则需要进行进一步的结构突变检验,本文主张选用结构突变点内生的Perron检验法与外生检验法相结合来判断变量的平稳性。     

Optimal versus orthogonal and equivalent-estimation design of blocked and split-plot experiments

This article provides an overview of the recent literature on the design of blocked and split-plot experiments with quantitative experimental variables. A detailed literature study introduces the ongoing debate between an optimal design approach to constructing blocked and split-plot designs and approaches where the equivalence of ordinary least squares and generalized least squares estimates are envisaged. Examples where the competing design strategies lead to totally different designs are given, as well as examples in which the optimal experimental designs are orthogonally blocked or equivalent-estimation split-plot designs.     

GLS detrending-based unit root tests in nonlinear STAR and SETAR models

We extend GLS detrending procedure to testing for unit roots against STAR and SETAR alternatives. Monte Carlo simulations and applications to DM/Yen real exchange rates demonstrate that GLS detrending-based nonlinear unit root tests are more powerful than OLS detrending-based counterparts.     

On the predictability of realized volatility using feasible GLS

This study deals with the out-of-sample predictability of realized volatility induced by implied volatility using FGLS. The original dataset was collected from Bloomberg and includes price and implied volatility indices from the US, Hong Kong, China, South Korea and India. Prices were then transformed into realized volatility indices. The relation between realized and implied volatility is important insofar as market expectations about future turbulence may affect the investor's behavior in advance. However, there are some features of the financial data which turn problematic the choice of the OLS estimator. These features include endogeneity and persistence of the predictor, and also conditional heteroskedasticity of the predicted innovations. Consequently, OLS becomes biased and inefficient. The FGLS estimator accounts for these characteristics and, therefore, performs better than OLS-based estimators, as indicated by many of our results.     

On testing for symmetry in business cycles

Business cycle forecasting has become an important part of short and medium term economic planning. Such forecasting, however, is often very intricate, as business cycles are not at all periodic, just recurrent. Furthermore, they often include irregular timing and varying amplitudes. When patterns and relationships are very irregular there are no simple reliable business cycle forecasting procedures. In practice there is, somewhere, a limit for business cycle predictability, and it is often worthwhile to examine empirically the various theoretical regularity assumptions. One important regularity issue concerns the business cycle symmetry assumption. The present paper empirically tests the hypothesis of symmetry around business cycle turning points in some economic time series. Two test procedures are applied. One is based on the analysis of transition probabilities between expansion and recession regimes. The second procedure tests symmetry versus asymmetry through skewness statistics. The analysis is based on detrending through the use of linear deterministic trends as well as by Beveridge-Nelson decompositions.