E21 - Macroeconomics: Consumption; Saving; WealthReturn

The development of the standard of living of pensioners is an important issue that is very rarely analysed. The paper focuses on the development of households' consumption for both economically active and economically inactive households. Besides the impacts on individuals' consumption, it is the most important expenditure component of gross domestic product. The change in households' consumption is also caused by population aging. It means that the proportion of people in the retirement age and pensioners' households increases. Actually, this causes that the number of people needed to provide for retired people is decreasing. The paper deals with the analysis of future living conditions of pensioners, i.e., people, who are still part of the productive population nowadays. This text also deals with present and future consumption by different types of households based on a projection of the population in the retirement age. Finally, estimates of the structure of their consumer spending and comparison with the current spending are presented.

Statistics has been developing for almost 250 years - since the publication of an essay which included one theorem called Bayes' after the author. This whole period (since 1763 to this day) has been accompanied by a duel between the supporters of a subjective concept of probability and those who refuse everything but a purely objective concept of probability as well as statistics. While the 18th and 19th centuries accepted the importance of the subjective (let us say Bayesian) way of thinking for the development of probability and statistics without a problem, in the 20th century the classic (frequentist) way took over and has been dominant in teaching and textbooks to this day. Only in the second half of the 20th century did the situation begin to change slowly. Reasons for that are partly described in the present article, but arguments and simple examples supporting the Bayesian way in comparison with the classic one are clear and generally respected worldwide. Unsuspected new computing possibilities have caused an explosive development of Bayesian statistics, which has infiltrated almost all the areas of statistics and a number of other scientific fields. It is not possible to expect a retreat of the different philosophical or pedagogical positions of the fighting schools of thought (even though it is really needed), but the use of advantages of both the approaches is methodologically not only possible, but even expected. Part of the teaching of statistics must be prepared for these changes, but it has not been the case in the Czech Republic at all so far.

Statistics has been developing for almost 250 years - since the publication of an essay which included one theorem called Bayes' after the author. This whole period (since 1763 to this day) has been accompanied by a duel between the supporters of a subjective concept of probability and those who refuse everything but a purely objective concept of probability as well as statistics. While the 18th and 19th centuries accepted the importance of the subjective (let us say Bayesian) way of thinking for the development of probability and statistics without a problem, in the 20th century the classic (frequentist) way took over and has been dominant in teaching and textbooks to this day. Only in the second half of the 20th century did the situation begin to change slowly. Reasons for that are partly described in the present article, but arguments and simple examples supporting the Bayesian way in comparison with the classic one are clear and generally respected worldwide. Unsuspected new computing possibilities have caused an explosive development of Bayesian statistics, which has infiltrated almost all the areas of statistics and a number of other scientific fields. It is not possible to expect a retreat of the different philosophical or pedagogical positions of the fighting schools of thought (even though it is really needed), but the use of advantages of both the approaches is methodologically not only possible, but even expected. Part of the teaching of statistics must be prepared for these changes, but it has not been the case in the Czech Republic at all so far.

Statistics has been developing for almost 250 years - since the publication of an essay which included one theorem called Bayes' after the author. This whole period (since 1763 to this day) has been accompanied by a duel between the supporters of a subjective concept of probability and those who refuse everything but a purely objective concept of probability as well as statistics. While the 18th and 19th centuries accepted the importance of the subjective (let us say Bayesian) way of thinking for the development of probability and statistics without a problem, in the 20th century the classic (frequentist) way took over and has been dominant in teaching and textbooks to this day. Only in the second half of the 20th century did the situation begin to change slowly. Reasons for that are partly described in the present article, but arguments and simple examples supporting the Bayesian way in comparison with the classic one are clear and generally respected worldwide. Unsuspected new computing possibilities have caused an explosive development of Bayesian statistics, which has infiltrated almost all the areas of statistics and a number of other scientific fields. It is not possible to expect a retreat of the different philosophical or pedagogical positions of the fighting schools of thought (even though it is really needed), but the use of advantages of both the approaches is methodologically not only possible, but even expected. Part of the teaching of statistics must be prepared for these changes, but it has not been the case in the Czech Republic at all so far.

In this note, we consider in discrete time the Ramsey growth model without discounting under stochastic uncertainty modelled by Markov processes. To make the model computationally tractable we shall consider finite state approximations of the original model. Properties of policies maximizing mean value of the global utility of consumers over an infinite time horizon, along with algorithmic procedures finding optimal and suboptimal policies, are reported.