Quantile

international econometric journal
in Russian language

no. 4

march 2008

 

Econometric literacy: nonparametric analysis

 

Creel, Michael. Some possible pitfalls of parametric inference

This essay reviews some of the undesirable things that can occur when parametric models are used without proper concern for checking that they are at least approximately correctly specified. It shows that nonparametric methods can, to a certain extent, avoid these problems.

Racine, Jeffrey. Nonparametric econometrics: a primer

This article is a primer for those who wish to familiarize themselves with nonparametric econometrics. Though the underlying theory for many of these methods can be daunting for some practitioners, this article will demonstrate how a range of nonparametric methods can in fact be deployed in a fairly straightforward manner. Rather than aiming for encyclopedic coverage of the field, we shall restrict attention to a set of touchstone topics while making liberal use of examples for illustrative purposes. We will emphasize settings in which the user may wish to model a dataset comprised of continuous, discrete, or categorical data (nominal or ordinal), or any combination thereof. We shall also consider recent developments in which some of the variables involved may in fact be irrelevant, which alters the behavior of the estimators and optimal bandwidths in a manner that deviates substantially from conventional approaches.

Zinde-Walsh, Victoria. Consequences of lack of smoothness in nonparametric estimation

Nonparametric estimation is widely used in statistics and econometrics with many asymptotic results relying on smoothness of the underlying distribution, however, there are cases where such assumptions may not hold in practice. Lack of smoothness may have undesirable consequences such as an incorrect choice of window width, large estimation biases and incorrect inference. Optimal combinations of estimators based on different kernel/bandwidth can achieve automatically the best unknown rate of convergence. The combined estimator was successfully applied in density estimation, estimation of average derivatives and for smoothed maximum score in a binary choice model. In the extreme case when density does not exist the estimator estimates a non-existent function; nevertheless its limit process can be described in terms of generalized (in terms of generalized functions) Gaussian processes. Inference about existence of density and about its smoothness is not yet well developed; some preliminary results are discussed.

 

Advice to econometrics students

 

Anatolyev, Stanislav. Making econometric reports

This essay discusses the structure of an econometric report, format of tables and diagrams, as well as precision of numerical results.

 

History of econometrics

 

Prokhorov, Artem. Nonlinear dynamics and chaos theory in economics: a historical perspective

This essay focuses on the genesis of ideas of nonlinearity, stochastics, and dynamics in economic thought as a series of intellectual advances that connected the linear static (quasi-dynamic) determinism of the 18th19th centuries with the linear mechanistic systems with stochastic terms and the nonlinear deterministic and stochastic dynamic models of the late 20th century, specifically, the chaos theory. The emphasis is placed on the developments of the second half of the 20th century. Technicalities are avoided.

 

Articles: applied econometrics

 

Shilov, Andrey; Möller, Joachim. Wage curve: theory and empirics

We consider the concept of a wage curve describing a negative relationship between unemployment and wages. We suggest an explanation of the wage curve using a number of theoretical labor market models, and present an empirical result of its determination for Russia obtained from analysis of regional data.

 

 International econometric journal in Russian language Quantile, 20062013
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