A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Environmental taxes with heterogeneous consumers: an application to energy consumption in France

This paper constructs a model with four groups of households who have preferences over labor supply, consumption of polluting (energy related) and non-polluting (non-energy) goods, and emissions. It quantifies the model for the French economy and computes its optimal tax equilibria under nine second-best tax regimes. We find that the redistributive role of environmental taxes requires the polluting goods to be taxed at a rate much below their marginal social damage. These goods may even require an outright subsidy if the society values equality ‘a lot’. Secondly, if environmental taxes that have an exclusively externality-correcting role, they benefit all types—although the gains are rather modest. The gains and losses become more substantial when environmental taxes have a redistributive role as well. Third, setting the environmental tax at its Pigouvian level, rather than its optimal externality-correcting-cum-redistributive level, benefits the high-income group at the expense of the low-income groups. Fourth, nonlinear taxation of polluting goods, and nonlinear commodity taxation in general, is a powerful redistributive mechanism. Fifth, introducing environmental taxes in the current French tax system, with its suboptimal income taxes, results in substantial welfare gains for the highest income group and a sizable loss for the least well-off persons.     

A Bayesian analysis of a variance decomposition for stock returns

We apply Bayesian methods to study a common vector autoregression (VAR)-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy, which involves expressing beliefs about the components of the variance decomposition. Previous Bayesian work elicited priors from the difficult-to-interpret parameters of the VAR. With a commonly used data set, we find that the posterior standard deviations for the variance decomposition based on these previously used priors, including “non-informative” limiting cases, are much larger than classical standard errors based on asymptotic approximations. Therefore, the non-informative researcher remains relatively uninformed about the variance decomposition after observing the data. We show the large posterior standard deviations arise because the “non-informative” prior is implicitly very informative in a highly undesirable way. However, reasonably informative priors using our elicitation method allow for much more precise inference about components of the variance decomposition.     

A dynamic approach to the analysis of strategic alliances

The increasing trend in strategic alliance formation between major firms around the world, has prompted researchers from various disciplines to look at this phenomenon in great detail. In this paper, we review alternate approaches in the literature in this area. We then propose a non-linear dynamic approach to study the formation of competitive strategic alliances and contrast it with the traditional game-theoretic approach. The pros and cons of these two approaches are discussed with reference to a competitive alliance scenario. Dynamic models have significant managerial implications as they enable us to investigate ‘if-then’ type scenarios and project the impact of different strategies.     

非线性时序模型LM检验的两类临界值检验统计功效比较

本文基于模拟方法比较了不同非线性时序模型的LM检验的功效和规模，同时也考虑一般化线性检验BDS检验参与比较，目的在于探讨蒙特一卡洛渐近法检验与自举法（bootstrap）检验的两类临界值的统计功效何者更为有效。通过实证与对比分析，结果表明，当样本小于200或自回归系数接近单位根，或者线性性检验是ARCHT或BDS时，就可以考虑应用自举法临界值而非渐近临界值。而且还发现，BDS检验仅在一般性上优于LM检验。     

货币政策和银行风险承担：一种非线性关系

宽松的货币政策会通过估值、收入和现金流机制,追逐收益机制以及中央银行沟通和反应机制等渠道增加银行风险承担,通过风险转移机制降低银行风险承担,从而导致货币政策与银行风险承担之间可能存在复杂的非线性关系。本文使用面板阈值模型,基于我国银行业数据研究了货币政策对银行风险承担的影响,发现我国货币政策对银行风险承担的影响存在门限效应,即货币政策对银行风险承担的影响取决于货币政策基准利率偏离泰勒规则利率的程度。当这种偏离小于门限值时,宽松货币政策会增加银行风险承担;当这种偏离大于门限值时,宽松货币政策会降低银行风险承担。本文研究对更好地理解我国货币政策对银行风险承担及金融稳定的影响有一定参考意义。     

Endogenous human capital accumulation, comparative advantage and direct vs. indirect redistribution

Recently, several papers have reexamined the so-called production efficiency theorem and the Atkinson and Stiglitz theorem on commodity taxes in the optimal taxation literature. Naito [J. Public Econ. 71 (1999) 65] showed that indirect redistribution through production distortion or consumption distortion can Pareto-improve welfare and that the two theorems do not necessarily hold when different factors are imperfect substitutes and factor prices are endogenous. On the other hand, Saez J. Public Econ. (2002) forthcoming argued that in the long run, where human capital accumulation is endogenous, the two theorems are still valid. This paper develops reasonable alternative models where individuals accumulate human capital based on their comparative advantage. The present paper shows that the production efficiency theorem is not necessarily valid and that indirect redistribution from the able to the less able such as tariffs and production subsidies can increase efficiency even when skill accumulation is endogenous.     

Nonlinear IV unit root tests in panels with cross-sectional dependency

We propose a unit root test for panels with cross-sectional dependency. We allow general dependency structure among the innovations that generate data for each of the cross-sectional units. Each unit may have different sample size, and therefore unbalanced panels are also permitted in our framework. Yet, the test is asymptotically normal, and does not require any tabulation of the critical values. Our test is based on nonlinear IV estimation of the usual augmented Dickey–Fuller type regression for each cross-sectional unit, using as instruments nonlinear transformations of the lagged levels. The actual test statistic is simply defined as a standardized sum of individual IV t-ratios. We show in the paper that such a standardized sum of individual IV t-ratios has limit normal distribution as long as the panels have large individual time series observations and are asymptotically balanced in a very weak sense. We may have the number of cross-sectional units arbitrarily small or large. In particular, the usual sequential asymptotics, upon which most of the available asymptotic theories for panel unit root models heavily rely, are not required. Finite sample performance of our test is examined via a set of simulations, and compared with those of other commonly used panel unit root tests. Our test generally performs better than the existing tests in terms of both finite sample sizes and powers. We apply our nonlinear IV method to test for the purchasing power parity hypothesis in panels.     

锈蚀钢筋混凝土薄壁箱梁非线形分析

薄壁箱梁结构由于其结构轻,刚度大,在结构工程中得到了广泛的应用.钢筋锈蚀是影响混凝土结构耐久性的重要因素,为了正确评估钢筋锈蚀后构件的裂缝发展情况,本文利用大型有限元软件ANSYS通过对锈蚀钢筋混凝土薄壁箱梁的非线性分析,得到了锈蚀构件的裂缝的变化规律.     

World Oil Depletion Models: Price effects compared with strategic or technological interventions

World oil depletion, including natural gas liquids, was modelled in the past by many authors. Recently, Guseo and Dalla Valle have introduced and Guidolin has applied a new approach following perturbed life-cycle diffusion models. Here we examine joint effects of economic and strategic or technological interventions using a Generalized Bass Model (GBM). Statistical analysis takes into account three different hierarchical levels: natural diffusion, long memory interventions and stochastic components. The main results confirm the statistical significance of historical 1970s shocks and highlight a strong long memory effect due to an increase in oil production after World War II. The estimated peak-date, 2007, and the 90% depletion time, 2019, are determined under an equilibrium intervention hypothesis.