Эконометрика: учебно-методический комплекс
This paper examines two Markov chain Monte Carlo methods that have been widely used in econometrics. An introductory exposition of the Metropolis algorithm and the Gibbs sampler is provided. These methods are used to simulate multivariate distributions. Many problems in Bayesian statistics can be solved by simulating the posterior distribution. Invariance condition is of importance, the proofs are given for both methods. We use finite Markov chains to explore and substantiate the methods. Several examples are provided to illustrate the applicability and efficiency of the Markov chain Monte Carlo methods. They include bivariate normal distribution with high correlation, bivariate exponential distribution, mixture of bivariate normals.
The collection of materials held on 29 October 2013 scientific-practical conference "Econometric methods in the study of global economic processes", organized by the Department of econometrics and mathematical methods of economic analysis in partnership with the MGIMO development Fund and with the support of the International statistical Institute. The conference is held within the International year of statistics, was devoted to the accumulated experience and prospects of use of econometric models and numerical methods in solving of applied tasks of international macroeconomics.
This paper presents a preliminary analysis of hotel room prices in several European cities based on the data from Booking.com website. The main question raised in the study is whether early booking is advantageous indeed, and if so, how early should it be? First a script was developed to download more than 600 thousand hotel offers for reservations from 25 March 2013 to 17 March 2014. Then an attempt to discover more details concerning the early booking effect was made via basic statistics, graphical data representation and hedonic pricing analysis. It was revealed that making reservations in advance can be really gainful, although more data and research are needed to measure the exact numbers, as they depend on at least seasonality and city.