Maria Ponomareva

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This paper continues our research on the identification and estimation of statistical functionals when the sampling process produces incomplete data due to missing observations or interval measurement of variables. Incomplete data usually cause population parameters of interest in applications to be unidentified except under untestable and often(More)
We study inference on parameters in censored panel data models, where the censoring can depend on both observable and unobservable variables in arbitrary ways. Under some general conditions, we characterize the information the model and data contain about the parameters of interest by deriving the identified sets, meaning that every parameter which belongs(More)
The paper was prepared under the research program "Transforming Government in Economies in Transition" (GET) sponsored by the Ford Foundation (Grant No950-1503), project "Enterprise Financing and the Role of the Government". Earlier draft entitled: “Do Governors Protect Firms From Paying Federal Taxes?” We are very grateful to Ahmed Ahmedov, David Brown,(More)
Results of complex treatment of patients with combined form of class II malocclusion and the vertical incisal disocclusion caused violation of function of muscles and syndrome of complicated nasal breath are presented. The complex of orthodontic actions with an application myogymnastics and respiratory exercise machine was reasonable. A new date about using(More)
We propose the sharp identifiable bounds of the potential outcome distributions using panel data. We allow for the possibility that statistical randomization of treatment assignments is not achieved until unobserved heterogeneity is properly controlled for. We use certain stationarity assumptions to obtain the sharp bounds. Our approach allows for dynamic(More)
The aim of this study was to investigate functional and morphological mechanisms of craniofacial complex compensation during the treatment of patients with combined forms of distal occlusion and deep bite. The article covers the results of orthodontic treatment of 26 patients, who have a combined form of distal occlusion and deep bite in the period of a(More)
Parametric mixture models are commonly used in applied work, especially empirical economics, where these models are commonly used to learn for example about the proportions of various types in a given population. It is well known that likelihood inference in these mixture models is complicated due to 1) lack of point identification, and 2) parameters (like(More)
In this study we address the problem of automated word stress detection in Russian using character level models and no partspeech-taggers. We use a simple bidirectional RNN with LSTM nodes and achieve the accuracy of 90% or higher. We experiment with two training datasets and show that using the data from an annotated corpus is much more efficient than(More)
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