Core-tube morphology of multiwall carbon nanotubes

The present paper investigates the cross-sectional morphology of Multiwalled Carbon Nanotubes (MWNTs) restrained radially and circumferentially by an infinite surrounding elastic medium, subjected to uniform external hydrostatic pressure. In this study, a two-dimensional plane strain model is developed, assuming no variation of load and deformation along the tube axis. We find some characteristic cross-sectional shapes from the elastic buckling analysis. The effect of the surrounded elastic medium on the cross-sectional shape which occurs due to pressure buckling is focused on by the comparison with the shape for no elastic medium case in our discussion. It is suggested that in no embedded elastic medium cases, the cross-sectional shapes of inner tubes maintain circle or oval; on the other hand, an embedded medium may cause inner tube corrugation modes especially when the number of shells for MWNTs is small.Comment: 7 figures, 2 figure

On PPP, Unit Roots and Panels

This paper re-assesses the panel (unit root test) evidence for PPP on four monthly data sets. We discuss and illustrate that commonly-used first generation panel unit root tests are inappropriate for PPP analysis since they are constructed for cross-sectionally uncorrelated panels. Given that real exchange rate panel data sets are – almost by construction – highly cross-sectionally correlated, so called second generation panel unit root methods that allow for and model cross-sectional dependence should be applied. Using inappropriate first generation tests, quite strong evidence for PPP is found. However, this evidence vanishes entirely when resorting to an appropriate method (e.g. the one developed in Bai and Ng, 2004a) for nonstationary cross-sectionally correlated panels. We strongly believe that our findings are relevant beyond the data sets investigated here for illustration.PPP, Real exchange rate index, Unit root, Panel, Cross-sectional dependence, Factor model

Semiparametric Trending Panel Data Models with Cross-Sectional Dependence

A semiparametric fixed effects model is introduced to describe the nonlinear trending phenomenon in panel data analysis and it allows for the cross-sectional dependence in both the regressors and the residuals. A semiparametric profile likelihood approach based on the first-stage local linear fitting is developed to estimate both the parameter vector and the time trend function.cross-sectional dependence, nonlinear time trend, panel data, profile likelihood, semiparametric regression

The impact of trade liberalisation on South African agricultural productivity

This study attempts to examine the empirical relationship between trade and total factor productivity (TFP) in the agricultural sector using both cross -sectiona, (across nine agricultural commodities), and time -series analysis. The Error Correction Model of ordinary least square (OLS) results from the cross -sectional analysis confirm that export shares and capital formation were found to be positive and significant; whereas, import shares and real exchange rate were found to be related negatively. However, the net effect of export and import shares had a positive effect. This implies that trade liberalisation causes productivity gains. Moreover, the time -series analysis goes in the same direction as the cross -sectional results, showing that there is a robust relationship among TFP, degree of openness, and capital formation. Whereas, debt was found to be inversely related, this implies that agricultural industries / farmers lack debt management skills.TFP, OLS, Trade liberalization or degree of openness, capital formation, International Relations/Trade,

A quasi maximum likelihood approach for large approximate dynamic factor models

This paper considers quasi-maximum likelihood estimations of a dynamic approximate factor model when the panel of time series is large. Maximum likelihood is analyzed under different sources of misspecification: omitted serial correlation of the observations and cross-sectional correlation of the idiosyncratic components. It is shown that the effects of misspecification on the estimation of the common factors is negligible for large sample size (T) and the cross sectional dimension (n). The estimator is feasible when n is large and easily implementable using the Kalman smoother and the EM algorithm as in traditional factor analysis. Simulation results illustrate what are the empirical conditions in which we can expect improvement with respect to simple principle components considered by Bai (2003), Bai and Ng (2002), Forni, Hallin, Lippi, and Reichlin (2000, 2005b), Stock and Watson (2002a,b). JEL Classification: C51, C32, C33factor model, large cross-sections, Quasi Maximum Likelihood

High-Order Consumption Moments and Asset Pricing

To assess the potential of incomplete consumption insurance for explaining the equity premium and the risk-free rate of return, we use a Taylor series expansion of the individual's marginal utility of consumption around the conditional expectation of consumption and derive an approximate equilibrium model for expected returns. In this model, the priced risk factors are the cross-moments of return with the moments of the cross-sectional distribution of individual consumption and the coefficients of the risk factors are determined by the derivatives of the utility function. Using this approach allows to avoid an ad hoc specification of preferences and to consider a general class of utility functions when addressing the question of the effect of a particular moment of the cross-sectional distribution of individual consumption on the expected equity premium and risk-free interest rate. We demonstrate that if consumers exhibit decreasing and convex absolute prudence, then the cross-sectional mean and skewness of individual consumption help explain the equity premium if their cross-moments with the excess market portfolio return are positive, while the cross-sectional variance and kurtosis always lower the equity premium explained by the model. The empirical investigation uses the data on the monthly household consumption of nondurables and services, reconstructed from the Consumer Expenditure Survey database. The Hansen-Jagannathan volatility bound analysis, calibration, and GMM analysis results show that under the CRRA preferences, the model can reproduce the observed equity premium and risk-free rate with economically plausible values of the relative risk aversion coefficient (between 0.6 and 1.6) and the time discount factor when the cross-sectional skewness of individual consumption, combined with the cross-sectional mean and variance, is taken into accountequity premium puzzle, heterogeneous consumers, incomplete consumption insurance, risk-free rate puzzle.

Exponent of Cross-sectional Dependence: Estimation and Inference

An important issue in the analysis of cross-sectional dependence which has received renewed interest in the past few years is the need for a better understanding of the extent and nature of such cross dependencies. In this paper we focus on measures of cross-sectional dependence and how such measures are related to the behaviour of the aggregates defined as cross-sectional averages. We endeavour to determine the rate at which the cross-sectional weighted average of a set of variables appropriately demeaned, tends to zero. One parameterisation sets the exponent of the cross-sectional dimension, N, being between 1/2 and 1. We refer to this as the exponent of cross-sectional dependence. We derive an estimator of this exponent from the estimated variance of the cross-sectional average of the variables under consideration. We propose bias corrected estimators, derive their asymptotic properties and consider a number of extensions. We include a detailed Monte Carlo study supporting the theoretical results. Finally, we undertake an empirical investigation of the exponent of cross-sectional dependence using the S&P 500 data-set, and a large number of macroeconomic variables across and within countries.cross correlations, cross-sectional dependence, cross-sectional averages, weak and strong factor models, Capital Asset Pricing Model

Inflation Dynamics and the Cross-Sectional Distribution of Prices in the E.U. Periphery

We explore the connection between inflation and its higher-order moments for three economies in the periphery of the European Union (E.U.), Greece, Portugal and Spain. Motivated by a micro-founded model of inflation determination, along the lines of the hybrid New Keynesian Phillips curve, we examine whether and how much does the cross-sectional skewness in producer prices affect the path of inflation. We develop our analysis with the perspective of economic integration/inflation harmonization (in the E.U.) and discuss the peculiarities of these three economies. We find evidence of a strong positive relation between aggregate inflation and the distribution of relative-price changes for all three countries. A potentially important implication of our results is that, if the cross-sectional skewness of prices is directly related to aggregate inflation, not only the direction but also the magnitude of a nominal shock would influence output and inflation dynamics. Moreover, the effect of such a shock could be received asymmetrically, even when countries share a common currency.Inflation; Cross-sectional distribution of prices; Greece, Portugal, Spain; European Union; Harmonization.

Is the risk-return paradox still alive?

To date, the validity of empirical Bowman's paradox papers that employ mean-variance approach for testing the risk/return relationship are inherently unverifiable and their results cannot be generalized. However, this problem can be overcome by developing an econometric model with two fundamental characteristics. The first one is the use of a time series model for each firm, avoiding the traditional cross-sectional analysis. The other one is to estimate a model with a single variable (the firm rate of return), but whose expectation and variance are mathematically related according to behavioral theories hypotheses, forming a heterocedastic model similar to "GARCH". Our results agree with behavioral theories and show that these theories can also be carry out with market measures