Seasonal adjustment

Abstract: Analysis of the enterprise activities allows to determine the peculiarities of the activities of a particular economic entity in accordance with the external and internal factors of its activities. Therefore, knowledge of methods for determining and measuring seasonal fluctuations, methods for forecasting demand and ways to solve problems related to seasonal dependence are very important. It is found that the activities of manufacturing enterprises, namely, enterprises for the production of building materials, have certain features. A consideration of the activities of a private enterprise in the current economic conditions prompted to carry out a study in terms of assessing the influence of structural factors on exports of products. It is proved that enterprises engaged in export activities with ceramic tiles are exposed to the influence of seasonal factors. The presence of dynamic fluctuations in demand requires enterprises to have knowledge and skills to use scientific methods for analyzing seasonality. Different approaches to the selection of a system of statistical indicators for assessing structural changes in output in dynamics have been noted. The expediency of using the index method, in particular seasonality indices, in order to measure the influence of seasonal fluctuations on the volume of exports of ceramic tiles is justified. The algorithm for estimating seasonal components on the volume of exports of ceramic tiles is determined. The size of export-import operations in the ceramic tile market during 2016–2019 is presented graphically; also presented is the seasonal wave of exports of ceramic tiles by a manufacturing enterprise and a seasonality index. Seasonal fluctuations in exports of ceramic tiles by a manufacturing enterprise were estimated according to monthly data during 2018–2022. The system of indicators based on seasonality indices is computed as follows: amplitude of fluctuations; linear mean and standard deviation to measure the effect of seasonal fluctuations. Some effective methods for improving the analysis of enterprise activity are proposed. The necessity of using the identified tendencies in forecasting the production indicators of enterprise is determined.

Abstract: Economic time series can be impacted by seasonal factors. If present but not identified, seasonality may lead to incorrect conclusions derived from the analysis. Seasonality is not always easily identifiable as time series are shaped by other factors as well, such as one-off events or natural disasters. There is a variety of methods to deal with seasonality in data. An attempt was made to compare the outcome of two popular methods: X-12-ARIMA and TRAMO/SEATS. They were applied to analyse seasonality for the business climate index in the construction industry in Poland. Both procedures were used to produce a seasonally adjusted series for the business climate index. Comparison of model’s diagnostics proved that TRAMO/SEATS performed slightly better for the analysed series within a chosen time range, which is consistent with some more general results found in the literature.

Abstract: adjustments. Economists, policy makers, and consumers use time series we publish to make decisions. They try to identify important features of economic series such as direction, turning points, and consistency between other economic indicators. Sometimes seasonal movements can make these features difficult to see, so we publish economic series with the seasonal movements removed for those who prefer to view data without seasonal movements. In this paper we will explore seasonal movements, seasonal adjustment, and we'll take a look at some of the features of economic time series.