A micro-econometric analysis of the role of R&D spillovers using a nonlinear translog specification

This paper assesses the impact of Research and Development (R&D) spillovers on production for a panel of 1,203 Italian manufacturing firms over the period 1998–2003.The estimations are based on a nonlinear translog production function augmented by a measure of R&D spillovers which combines the geographical distance between firms, the technological similarity within each pair of firms and the technical efficiency of each firm. The estimation method takes into account the endogeneity of regressors and the potential sample selection issue regarding the decision by firms to invest in R&D. Results show that the translog production function is more suitable than the Cobb-Douglas for modelling firm behaviour and that returns to scale are increasing. Moreover, the internal and external stocks of technology exert a significant impact on firms’ production. Finally, it emerges that, for Italian manufacturing firms, R&D capital and R&D spillovers are highly substitutes.     

Duality theory and pitfalls in the specification of technologies

Principles of duality enable the investigator to model the technology of a multiple-input-single- output firm either by means of a production function or a cost function. For empirical implementation, both alternatives employ the assumption of competitive market behaviour. Recently, functional forms have been developed which are sufficiently flexible to describe the substitution possibilities among factors when the technology consists of more than two factors. However, contrary to the strongly separable multi-factor Cobb-Douglas and CES forms, these functional forms are not self-dual. This poses the problem of choosing between two different maintained hypotheses. In this paper, we compare the inferences with respect to substitution possibilities obtained by imposing the two alternative specifications of a production function and a cost function on the same set of data. We find that they give very different inferences with respect to substitution possibilities between factors. Furthermore, these inferences continue to differ even when we explicitly adopt the position that both the production and cost functions are each approximations of the true technology.     

Testing the specification of multivariate models in the presence of alternative hypotheses

In this paper we propose a non-nested hypothesis test for testing the specification of a multivariate econometric model in the presence of an alternative model which purports to explain the same phenomenon. We demonstrate that the new test statistic tends to minus the same random variable as the CPD test statistic introduced by Pesaran and Deaton (1978), provided that the truth is ‘close’ to the null hypothesis. Since the new test is simpler to compute than the multivariate CPD test, it would seem to be the procedure of choice.     

Logit versus discriminant analysis: A specification test and application to corporate bankruptcies

Two of the most widely used statistical techniques for analyzing discrete economic phenomena are discriminant analysis (DA) and logit analysis. For purposes of parameter estimation, logit has been shown to be more robust than DA. However, under certain distributional assumptions both procedures yield consistent estimates and the DA estimator is asymptotically efficient. This suggests a natural Hausman specification test of these distributional assumptions by comparing the two estimators. In this paper, such a test is proposed and an empirical example involving corporate bankruptcies is provided. The finite-sample properties of the test statistic are also explored through some sampling experiments.     

Stochastic specification and the estimation of share equations

The standard stochastic specification for a system of share equations is obtained by assuming that the shares have a joint normal distribution with means depending upon exogenous variables and a constant covariance matrix. This specification ignores the requirement that shares be between zero and unity by giving positive probability to shares outside this range. An alternative stochastic specification involving the Dirichlet distribution, which automatically limits shares to the unit simplex, is suggested. A comparison of results obtained from the two specifications is made using sampling experiments and data from three different empirical studies. The sampling experiments and empirical applications show that the results are generally quite close, thus providing some justification for the continued use of the normal distribution specification in the estimation of share equations.     

Testing the exogeneity specification in the complete dynamic simultaneous equation model

It is shown that in the complete dynamic simultaneous equation model exogenous variables cause endogenous variables in the sense of Granger (1969) and satisfy the criterion of econometric exogeneity discussed by Sims (1977a), but that the stationarity assumptions invoked by Granger and Sims are not necessary for this implication. Inference procedures for testing each implication are presented and a new joint test of both implications isderived. Detailed attention is given to estimation and testing when the error vector of the final form of the complete dynamic simultaneous equation model is both singular and serially correlated. The theoretical points of the paper are illustrated by testing the exogeneity specification in a small macroeconometric model.     

An alternative quasi likelihood approach,Bayesian analysis and data-based inference for model specification

This paper studies an alternative quasi likelihood approach under possible model misspecification. We derive a filtered likelihood from a given quasi likelihood (QL), called a limited information quasi likelihood (LI-QL), that contains relevant but limited information on the data generation process. Our LI-QL approach, in one hand, extends robustness of the QL approach to inference problems for which the existing approach does not apply. Our study in this paper, on the other hand, builds a bridge between the classical and Bayesian approaches for statistical inference under possible model misspecification. We can establish a large sample correspondence between the classical QL approach and our LI-QL based Bayesian approach. An interesting finding is that the asymptotic distribution of an LI-QL based posterior and that of the corresponding quasi maximum likelihood estimator share the same “sandwich”-type second moment. Based on the LI-QL we can develop inference methods that are useful for practical applications under possible model misspecification. In particular, we can develop the Bayesian counterparts of classical QL methods that carry all the nice features of the latter studied in  White (1982). In addition, we can develop a Bayesian method for analyzing model specification based on an LI-QL.     

Generalized method of moments specification testing

This paper analyzes the asymptotic power properties of specification tests which are based on a finite set of moment conditions. It shows that any such test may fail against general misspecification that causes estimator inconsistency. The mutual asymptotic equivalence of maximal degree of freedom tests is shown and the form of optimal tests against specific forms of misspecification is derived. Applications to testing for exogeneity of a set of instrumental variables are presented.     

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.     

轻型汽车悬架侧倾角刚度分析

文章通过对某轻型汽车独立悬架和非独立悬架侧倾运动特性的分析,建立了侧倾角刚度的数学模型。     

谈产品标准中检验规范的制定

阐述了产品标准中检验规范的规定与实施，指出了检验标准是企业产品个有高质量、高效益、有竞争力的技术支持和保证。     

Optimal instruments when the disturbances are small

Single-equation instrumental variable estimators (e.g., the k-class) are frequently employed to estimate econometric equations. This paper employs Kadane's (1971) small-σ method and a squared-error matrix loss function to characterize a single-equation class of optimal instruments, $\text{A}$. $\text{A}$ is optimal (asymptotically for a small scalar multiple, σ, of the model's disturbance) in that all of its members are preferred to all non-members. From this characterization it is shown all k-class estimators and certain iterative estimators belong to $\text{A}$. However, non-iterative principal component estimators [e.g., Kloek and Mennes (1960)] are unlikely to belong to $\text{A}$. These latter instrumental variable estimators have been advocated [see Amemiya (1966) and Kloek and Mennes (1960)] for estimating ‘large’ econometric models.     

Modelling Currency Crises in Emerging Markets: A Dynamic Probit Model with Unobserved Heterogeneity and Autocorrelated Errors*

The paper investigates the causes of currency crises in emerging markets. We estimate the probability of a currency crisis by applying maximum smoothly simulated likelihood to a dynamic LDV model. This approach allows us to take explicit account of the existence of intertemporal links between crises. The results show that currency crises are influenced by real, monetary, debt and global variables. Past banking crises are significant determinants of the probability of currency crises. Moreover, countries that sharply devalued in the past are less prone to experience another currency crisis. We find evidence of unobserved heterogeneity, which may reflect differences in the countries’ institutional/historical background. Finally, the determinants of currency crises differ by type of exchange rate regime.     

The specification of least informative error distributions

Maximum likelihood estimation and most statistical tests require a full specification of the error distribution in a model. Under suitable parametric restrictions we can derive least informative specifications. The autoregressive processes prove to be least informative under a few simple variance and covariance restrictions. For the singular multivariate error distribution in a sum-constrained model, several least informative error distributions are obtained using different parametric assumptions on the covariance structure. A combined maximum entropy — maximum likelihood approach provides an alternative to other recent proposals for covariance estimation in small samples.     

Econometric specification of stochastic discount factor models

We consider the problem of derivative pricing when the stochastic discount factors are exponential-affine functions of underlying state variable. In particular we discuss the conditionally Gaussian framework and introduce semi-parametric pricing methods for models with path dependent drift and volatility. This approach is also applied to more complicated frameworks, such as pricing of a derivative written on an index, when the interest rate is stochastic.