Testing a linear dynamic panel data model against nonlinear alternatives

The most popular econometric models in the panel data literature are the class of linear panel data models with unobserved individual- and/or time-specific effects. The consistency of parameter estimators and the validity of their economic interpretations as marginal effects depend crucially on the correct functional form specification of the linear panel data model. In this paper, a new class of residual-based tests is proposed for checking the validity of dynamic panel data models with both large cross-sectional units and time series dimensions. The individual and time effects can be fixed or random, and panel data can be balanced or unbalanced. The tests can detect a wide range of model misspecifications in the conditional mean of a dynamic panel data model, including functional form and lag misspecification. They check a large number of lags so that they can capture misspecification at any lag order asymptotically. No common alternative is assumed, thus allowing for heterogeneity in the degrees and directions of functional form misspecification across individuals. Thanks to the use of panel data with large $N$ and $T$, the proposed nonparametric tests have an asymptotic normal distribution under the null hypothesis without requiring the smoothing parameters to grow with the sample sizes. This suggests better nonparametric asymptotic approximation for the panel data than for time series or cross sectional data. This is confirmed in a simulation study. We apply the new tests to test linear specification of cross-country growth equations and found significant nonlinearities in mean for OECD countries’ growth equation for annual and quintannual panel data.     

Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative

This paper is concerned with inference about a function g that is identified by a conditional quantile restriction involving instrumental variables. The paper presents a test of the hypothesis that g belongs to a finite-dimensional parametric family against a nonparametric alternative. The test is not subject to the ill-posed inverse problem of nonparametric instrumental variable estimation. Under mild conditions, the test is consistent against any alternative model. In large samples, its power is arbitrarily close to 1 uniformly over a class of alternatives whose distance from the null hypothesis is proportional to n^−1/2, where n is the sample size. Monte Carlo simulations illustrate the finite-sample performance of the test.     

规范非正规金融发展

由于正规金融供给不足,而非正规金融以信息优势、成本优势、效率优势深受中小企业和农户偏好,在一定程度上缓解了资金缺口,促进了中小企业和农村经济的发展。但非正规金融也存在规模和范围狭小、道德风险、法制欠缺等问题;因此,要建立健全相关法律和制度,适度监管,规范非正规金融行为。     

A General Approach to Testing Volatility Models in Time Series

Volatility models have been playing important roles in economics and finance. Using a generalized spectral second order derivative approach, we propose a new class of generally applicable omnibus tests for the adequacy of linear and nonlinear volatility models. Our tests have a convenient asymptotic null N(0,1) distribution, and can detect a wide range of misspecifications for volatility dynamics, including both neglected linear and nonlinear volatility dynamics. Distinct from the existing diagnostic tests for volatility models, our tests are robust to time-varying higher order moments of unknown form (e.g., time-varying skewness and kurtosis). They check a large number of lags and are therefore expected to be powerful against neglected volatility dynamics that occurs at higher order lags or display long memory properties. Despite using a large number of lags, our tests do not suffer much from the loss of a large number of degrees of freedom, because our approach naturally discounts higher order lags, which is consistent with the stylized fact that economic or financial markets are affected more by the recent past events than by the remote past events. No specific estimation method is required, and parameter estimation uncertainty has no impact on the convenient limit N(0,1) distribution of the test statistics. Moreover, there is no need to formulate an alternative volatility model, and only estimated standardized residuals are needed to implement our tests. We do not have to calculate tedious and model-specific score functions or derivatives of volatility models with respect to estimated parameters, which are required in some existing popular diagnostic tests for volatility models. We examine the finite sample performance of the proposed tests. It is documented that the new tests are rather powerful in detecting neglected nonlinear volatility dynamics which the existing tests can easily miss. They are useful diagnostic tools for practitioners when modelling volatility dynamics.     

A Note on Intraday Event Studies

Abstract

We investigate the specification and power of intraday event study test statistics. Mean, market, and matched firm models generate well-specified return results for a range of intervals up to 60?min around the event. These models detect return shocks equivalent to one spread in one-minute interval data and three spreads in longer intervals. Researchers using intraday return event studies can, therefore, be confident in their robustness. Some volume event study approaches have reasonable power but they are not generally well specified, while a matched-firm approach gives the best combination of specification and power for spread event studies.     

Specifying and synchronising partner activities in the dispersed product development process

This study is concerned with the way firms identify, specify and temporally co-ordinate partner activities in a networked development context. It draws attention to activity specification and synchronisation. These constructs are explored through a case study of the multiple and dispersed activities carried out in the development of a radical sound-broadcasting device. The findings suggest that the ability to specify partner activities and assess partner capabilities can influence the timing and nature of partner involvement. They further indicate that timely two-way capability display, along with organisational flexibility and adaptation, can enhance partner activity specification over time. The study shows that attention to pacing and synchronisation of partner activities can add value to the development process.     

Distribution-free specification tests of conditional models

This article proposes a class of asymptotically distribution-free specification tests for parametric conditional distributions. These tests are based on a martingale transform of a proper sequential empirical process of conditionally transformed data. Standard continuous functionals of this martingale provide omnibus tests while linear combinations of the orthogonal components in its spectral representation form a basis for directional tests. Finally, Neyman-type smooth tests, a compromise between directional and omnibus tests, are discussed. As a special example we study in detail the construction of directional tests for the null hypothesis of conditional normality versus heteroskedastic contiguous alternatives. A small Monte Carlo study shows that our tests attain the nominal level already for small sample sizes.     

普及型卫生电视接收站技术要求的论证

当前卫星电视接收技术的发展进入了一个新的时期,需要生产一些低档的普及站以满足不同用户的要求,而原来的“图标”没有包含这类普及站的技术条件。因此本文的目的旨在试图论证普及型卫星电视接收站应达到的五项视频指标。     

开放经济下的经济增长模型:中国的经验

本文从三个方面,以8个分指标为基础构造了衡量对外开放程度的变量——对外开放度指数,该指数较传统的外贸依存度更好地刻画了1978~2003年间中国经济对外开放程度的变化过程。在此基础上,本文运用动态建模方法建立了开放经济下的经济增长模型,从短期和长期的角度动态地考察了对外开放对经济增长的影响,很好地模拟了开放经济下中国经济增长的变化规律。实证研究的结果证实了对外开放不仅在短期内有效地促进了经济增长,而且也显著地进入了长期均衡方程。     

On Optimal Instrumental Variables Generators, with an Application to Hedge Fund Returns

In this paper, we propose a new benchmarking procedure lying on cumulants for computing the factor loadings in financial models of returns. We apply this technique to the well-known augmented Fama and French (J Fin Econ 43(2):153–193, 1997) model and compare it with another technique of ours based on higher moments. Our new procedure confirms the fact that the alpha is supposed to decrease when we disaggregate HFR indices to the level of individual funds while correcting for specification errors. Our new technique is therefore useful for hedge funds selection or ranking based on the alpha of Jensen corrected for specification errors. This technique will also be useful for calibrating other financial models of returns like the simple market model or the conditional alpha and beta models.