Inconsistency of the MLE and inference based on weighted LS for LARCH models

This paper considers a class of finite-order autoregressive linear ARCH models. The model captures the leverage effect, allows the volatility to be arbitrarily close to zero and to reach its minimum for non-zero innovations, and is appropriate for long memory modeling when infinite orders are allowed. However, the (quasi-)maximum likelihood estimator is, in general, inconsistent. A self-weighted least-squares estimator is proposed and is shown to be asymptotically normal. A score test for conditional homoscedasticity and diagnostic portmanteau tests are developed. Their performance is illustrated via simulation experiments. It is also investigated whether stock market returns exhibit some of the characteristic features of the linear ARCH model.     

Dominating estimators for minimum-variance portfolios

In this paper, we derive two shrinkage estimators for minimum-variance portfolios that dominate the traditional estimator with respect to the out-of-sample variance of the portfolio return. The presented results hold for any number of assets d≥4$d\ge 4$ and number of observations n≥d+2$n\ge d+2$. The small-sample properties of the shrinkage estimators as well as their large-sample properties for fixed d$d$ but n→∞$n\to \infty$ and n,d→∞$n,d\to \infty$ but n/d→q≤∞$n/d\to q\le \infty$ are investigated. Furthermore, we present a small-sample test for the question of whether it is better to completely ignore time series information in favor of naive diversification.     

Threshold bipower variation and the impact of jumps on volatility forecasting

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and discontinuous components using estimators which are not only consistent, but also scarcely plagued by small sample bias. With the aim of achieving this, we introduce the concept of threshold bipower variation, which is based on the joint use of bipower variation and threshold estimation. We show that its generalization (threshold multipower variation) admits a feasible central limit theorem in the presence of jumps and provides less biased estimates, with respect to the standard multipower variation, of the continuous quadratic variation in finite samples. We further provide a new test for jump detection which has substantially more power than tests based on multipower variation. Empirical analysis (on the S&P500 index, individual stocks and US bond yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods following the occurrence of a jump.     

ON THE “PRO‐POORNESS” OF GROWTH IN A MULTIDIMENSIONAL CONTEXT

This paper represents a first attempt to bring together the issues of multidimensional poverty and growth “pro‐poorness” assessments. More specifically, we suggest the use of sequential dominance procedures to test the “pro‐poorness” of observed growth spells when poverty is measured on the basis of income and another discrete well‐being attribute. Sequential procedures are also used to obtain graphical tools that are consistent with the spirit of Ravallion and Chen's growth incidence curve and Son's poverty growth curve. Contrary to traditional unidimensional tests, our method makes it possible to take into account the importance of deprivation correlations at the individual level and thus may reverse results observed with the traditional tools used to check the “pro‐poorness” of growth. An illustration of our approach is given using Turkish data for the period 2003–05.     

Human capital accumulation in R&D-based growth models

This paper develops a model that reproduces the essential aspects of the recent ICT-based economy using the framework of endogenous growth theory in which a central role is played by human capital accumulation. In particular, it considers a multi-sectoral growth model in discrete time with infinite horizon, endogenous growth, embodied technological progress, horizontal differentiation and “lab-equipment” specification of R&D, and with human capital accumulation (represented by the fact that households devote a fraction of their time to schooling), in order to take into account the crucial role of the latter when new technologies are present. In this model it is possible to obtain some important results, both analytically and through simulations, either in the case of constant productivity of schooling and in the case in which this productivity is a function of technological progress. The first conclusion is that the productivity of schooling affects the long run growth of the economy, contrary to the productivities of the other sectors, hence in this model human capital accumulation is the true engine of growth. It is then possible to study the reaction of the economy to different types of shocks, and to compare the results with the empirical evidence. The conclusion is that the model is able to reproduce such evidence, suggesting that the interaction between ICT and human capital is one of the drivers of the recent economic performance.     

Explosive U.S. budget deficit

In this study, we present new evidence that the postwar U.S. federal budget deficit was explosive in nature. Because of the government's inevitable attempts to reduce high or rapidly growing budget deficits, the deficit may contain a substantial component that periodically collapses, which renders the standard unit root tests biased toward stationarity. We apply a newly proposed recursive unit root test for explosiveness, which is known to be powerful to the periodically collapsing component. Although the evidence for explosiveness we found herein is not overwhelming, this study should at the very least serve as a warning against a blind application of standard unit root tests to budget deficits, which may harbor components that periodically collapse.     

Transition probabilities in a problem of stochastic process switching

Extant solutions for state-contingent process switching use first-passage time densities or differential equations. We alternatively employ transition probabilities. These conditional likelihood functions also have obvious appeal for econometric analyses as well as derivative pricing and decision making under absorption and extinction.     

A note on the incompatibility of strategy-proofness and Pareto-optimality in quasi-linear settings with public budgets

We show that any deterministic mechanism, for allocating identical items that are complements to budget-constrained bidders, cannot simultaneously satisfy individual-rationality, strategy-proofness, Pareto-efficiency, and no-positive-transfers. This holds even for two bidders, two items, and commonly-known budgets, and generalizes to richer settings.     

An experimental investigation of wage taxation and unemployment in closed and open economies

We investigate experimentally the economic effects of wage taxation to finance unemployment benefits for a closed economy and an international economy. The main findings are the following. (i) There is clear evidence of a vicious circle in the dynamic interaction between the wage tax and unemployment. (ii) Employment is boosted by budget deficits but subsequent tax rate adjustments to balance the budget lead to employment levels substantially lower than theoretically predicted. (iii) A sales risk for producers due to price uncertainty on output markets appears to cause a downward pressure on factor employment. For labor the wage tax exacerbates this adverse effect.     

基于单片机远程I2C温度控制系统

采用P89LPC922单片机为主控MCU,使用模拟I^2C方式,利用远程控制芯片P82896实现了基于I^2C的远程I／O扩展,同时该系统采用LM75A采集终端温度并在前端显示,前端通过控制PCA9554的I／O口来实现对终端温度的控制。温度过高则控制风扇转动来降温,温度过低则控制加热设备加热。