international econometric journal
in Russian language
This essay is an
introduction to survival models in the context of generalized linear models. We
introduce the hazard and survival functions and describe the most common
censoring mechanisms and the resulting likelihood function. We discuss the main
approaches to modeling waiting times, including accelerated life and
proportional hazard models, with extensions to time-varying covariates and
time-dependent effects. We then focus on the piece-wise exponential survival
model and note its equivalence with Poisson regression models. We illustrate
this approach with an application to the analysis of infant and child mortality
This essay surveys two areas of application of semiparametric econometrics: the analysis of censored employment duration data, and the analysis of data on stated willingness-to-pay for natural resources.
This part of the dictionary comments on English econometric terms kurtosis, skewness, critical region, significance level, confidence level, and some others. Emphasis is again placed on accurate definitions of their meaning to avoid possible confusion and incorrect interpretation.
This is a survey of most notable time series econometrics texts written in English. The essay reflects the author's opinion, as well as opinions of econometricians expressed in published book reviews.
Measurement of technological progress is one of core issues in the growth theory. Applied growth accounting based on the standard Solow residual approach to technology measurement assumes exogenous nature of productivity growth not explained by the dynamics of factor inputs. This exogenous unexplained residual is considered as a proxy for the technological change. The existing research in TFP measurement for Russian economy concentrates on the analysis of the transition process and considers the collapse in output as being caused by the fall in TFP, i.e. by technological “regress”. The declining TFP is sometimes explained by the fall in efficiency of production process or by the fall in capacity utilization. In this paper the TFP is estimated using Russian industry level data from the Federal State Statistics Service and Russian Economic Barometer from 1995 to 2004. TFP measurement based on observable estimates for capital and labor utilization accounting for the specifics of Russian industrial statistics reveals that the output growth after 1998 is accompanied by a slow technological improvement, and that a negative technology shock is observed before 1998.
paper considers different ways of computing indexes for forecasting economic