Suchergebnisse

Patterns for income tax forecasting are analysed and assessed in the article. Tax revenue is the main funding source to satisfy government needs, hence, a precise forecast is considered to be one of the most important constituents in budget making. Lithuania, as well as many EU countries, applies the software budget form, the system of planning, programming, and budgeting. Therefore, for this budget form, tax revenue forecasting becomes a valuable tool. By accurately forecasting the budget revenue and subsidies, the budget deficit (or surplus) can be provided, together with its cost of financing. Income tax is one of the main components in Lithuanian national budget receipts, and the forecast accuracy is an important condition to ensure the reliability of the revenue and deficit indicators. The research problem is to choose the most appropriate pattern for forecasting income from the income tax. The aim of the article is to assess the options of forecasting pattern application in predicting revenue from the income tax. To achieve the aim the following objectives have been set: 1) To carry out research on patterns offered by scientists and the ones applied in practice; to justify options of their application in predicting revenue from corporate taxation. 2) To put forward the most appropriate pattern of income tax forecast.

Patterns for income tax forecasting are analysed and assessed in the article. Tax revenue is the main funding source to satisfy government needs, hence, a precise forecast is considered to be one of the most important constituents in budget making. Lithuania, as well as many EU countries, applies the software budget form, the system of planning, programming, and budgeting. Therefore, for this budget form, tax revenue forecasting becomes a valuable tool. By accurately forecasting the budget revenue and subsidies, the budget deficit (or surplus) can be provided, together with its cost of financing. Income tax is one of the main components in Lithuanian national budget receipts, and the forecast accuracy is an important condition to ensure the reliability of the revenue and deficit indicators. The research problem is to choose the most appropriate pattern for forecasting income from the income tax. The aim of the article is to assess the options of forecasting pattern application in predicting revenue from the income tax. To achieve the aim the following objectives have been set: 1) To carry out research on patterns offered by scientists and the ones applied in practice; to justify options of their application in predicting revenue from corporate taxation. 2) To put forward the most appropriate pattern of income tax forecast.

Patterns for income tax forecasting are analysed and assessed in the article. Tax revenue is the main funding source to satisfy government needs, hence, a precise forecast is considered to be one of the most important constituents in budget making. Lithuania, as well as many EU countries, applies the software budget form, the system of planning, programming, and budgeting. Therefore, for this budget form, tax revenue forecasting becomes a valuable tool. By accurately forecasting the budget revenue and subsidies, the budget deficit (or surplus) can be provided, together with its cost of financing. Income tax is one of the main components in Lithuanian national budget receipts, and the forecast accuracy is an important condition to ensure the reliability of the revenue and deficit indicators. The research problem is to choose the most appropriate pattern for forecasting income from the income tax. The aim of the article is to assess the options of forecasting pattern application in predicting revenue from the income tax. To achieve the aim the following objectives have been set: 1) To carry out research on patterns offered by scientists and the ones applied in practice; to justify options of their application in predicting revenue from corporate taxation. 2) To put forward the most appropriate pattern of income tax forecast.

This thesis aims to test feasibility of the hybrid model for wood chips price in Lithuania's market forecasting. Conducting literature review such model was found as most accurate and promising amongst all other time series models. Analysis of wood chips market and prices resulted in conclusion that market is in developing state and the subject of energy production using renewable energy sources is getting more attention in Lithuania and European Union. Based on the approach presented by Zhang (2003) hybrid model –combination of ARIMA and feedback non linear autoregressive neural network, was designed. As a result of met performance targets: forecasting accuracy, general fit and outperform benchmark –naïve random walk, the model was determined as feasible for the step ahead wood chips price in Lithuania's market forecasting. The findings of this thesis supplements general body of knowledge on hybrid models outperforming traditional approaches.

This thesis aims to test feasibility of the hybrid model for wood chips price in Lithuania's market forecasting. Conducting literature review such model was found as most accurate and promising amongst all other time series models. Analysis of wood chips market and prices resulted in conclusion that market is in developing state and the subject of energy production using renewable energy sources is getting more attention in Lithuania and European Union. Based on the approach presented by Zhang (2003) hybrid model –combination of ARIMA and feedback non linear autoregressive neural network, was designed. As a result of met performance targets: forecasting accuracy, general fit and outperform benchmark –naïve random walk, the model was determined as feasible for the step ahead wood chips price in Lithuania's market forecasting. The findings of this thesis supplements general body of knowledge on hybrid models outperforming traditional approaches.

Profitable agricultural activity provides a stable self-sufficiency with agricultural and food products. Positive structural production changes have been reached in the Lithuanian agrarian sector while implementing EU common agricultural policy measures. However, due to both external and internal factors influence differences, profitability of separate agricultural branches and products vary a lot and may have a negative impact on the rational agricultural production changes. The aim of the research is to provide the rational decisions of profitability increase in agrarian sector using mathematical model. The tasks of the research are: to perform comparative analysis of Lithuanian and EU member states agrarian sector; to prepare mathematical model for agrarian sector profit forecasting and formulate assumptions for the model application; to evaluate factors influencing agrarian sector profit and provide their forecast up to the year 2013. Results of the research: evaluation of Lithuanian and EU member states agrarian sector economic indicators show that Lithuanian agrarian sector, having unequal level of competitive abilities, stands behind. Therefore it is necessary to use efficiently available external (support, prices) and internal (costs) reserves. Mathematical model has been prepared for agrarian sector profit and its scenarios forecasting, in consideration with different assumptions (actual and normative production costs, different direct payments levels) up to the year 2013. Forecasting results and scenario analysis show that optimization of production costs leads to higher profit, prices and direct payments increase profitability of the agricultural production at different level. Recommendations for the sustainable development of agricultural sector and policy measures improvements are proposed.

Profitable agricultural activity provides a stable self-sufficiency with agricultural and food products. Positive structural production changes have been reached in the Lithuanian agrarian sector while implementing EU common agricultural policy measures. However, due to both external and internal factors influence differences, profitability of separate agricultural branches and products vary a lot and may have a negative impact on the rational agricultural production changes. The aim of the research is to provide the rational decisions of profitability increase in agrarian sector using mathematical model. The tasks of the research are: to perform comparative analysis of Lithuanian and EU member states agrarian sector; to prepare mathematical model for agrarian sector profit forecasting and formulate assumptions for the model application; to evaluate factors influencing agrarian sector profit and provide their forecast up to the year 2013. Results of the research: evaluation of Lithuanian and EU member states agrarian sector economic indicators show that Lithuanian agrarian sector, having unequal level of competitive abilities, stands behind. Therefore it is necessary to use efficiently available external (support, prices) and internal (costs) reserves. Mathematical model has been prepared for agrarian sector profit and its scenarios forecasting, in consideration with different assumptions (actual and normative production costs, different direct payments levels) up to the year 2013. Forecasting results and scenario analysis show that optimization of production costs leads to higher profit, prices and direct payments increase profitability of the agricultural production at different level. Recommendations for the sustainable development of agricultural sector and policy measures improvements are proposed.

Profitable agricultural activity provides a stable self-sufficiency with agricultural and food products. Positive structural production changes have been reached in the Lithuanian agrarian sector while implementing EU common agricultural policy measures. However, due to both external and internal factors influence differences, profitability of separate agricultural branches and products vary a lot and may have a negative impact on the rational agricultural production changes. The aim of the research is to provide the rational decisions of profitability increase in agrarian sector using mathematical model. The tasks of the research are: to perform comparative analysis of Lithuanian and EU member states agrarian sector; to prepare mathematical model for agrarian sector profit forecasting and formulate assumptions for the model application; to evaluate factors influencing agrarian sector profit and provide their forecast up to the year 2013. Results of the research: evaluation of Lithuanian and EU member states agrarian sector economic indicators show that Lithuanian agrarian sector, having unequal level of competitive abilities, stands behind. Therefore it is necessary to use efficiently available external (support, prices) and internal (costs) reserves. Mathematical model has been prepared for agrarian sector profit and its scenarios forecasting, in consideration with different assumptions (actual and normative production costs, different direct payments levels) up to the year 2013. Forecasting results and scenario analysis show that optimization of production costs leads to higher profit, prices and direct payments increase profitability of the agricultural production at different level. Recommendations for the sustainable development of agricultural sector and policy measures improvements are proposed.

Profitable agricultural activity provides a stable self-sufficiency with agricultural and food products. Positive structural production changes have been reached in the Lithuanian agrarian sector while implementing EU common agricultural policy measures. However, due to both external and internal factors influence differences, profitability of separate agricultural branches and products vary a lot and may have a negative impact on the rational agricultural production changes. The aim of the research is to provide the rational decisions of profitability increase in agrarian sector using mathematical model. The tasks of the research are: to perform comparative analysis of Lithuanian and EU member states agrarian sector; to prepare mathematical model for agrarian sector profit forecasting and formulate assumptions for the model application; to evaluate factors influencing agrarian sector profit and provide their forecast up to the year 2013. Results of the research: evaluation of Lithuanian and EU member states agrarian sector economic indicators show that Lithuanian agrarian sector, having unequal level of competitive abilities, stands behind. Therefore it is necessary to use efficiently available external (support, prices) and internal (costs) reserves. Mathematical model has been prepared for agrarian sector profit and its scenarios forecasting, in consideration with different assumptions (actual and normative production costs, different direct payments levels) up to the year 2013. Forecasting results and scenario analysis show that optimization of production costs leads to higher profit, prices and direct payments increase profitability of the agricultural production at different level. Recommendations for the sustainable development of agricultural sector and policy measures improvements are proposed.

This article aims to draw the attention to a field that has been widely acknowledged worldwide but can be considered as rather new in Lithuania -- to the methods of foresighting & future studies. Foresighting can serve as a supplement to analytic research & can be applied as a significant methodological instrument in numerous fields of political science. Authors state that foresighting is particularly relevant to the research of international relations. As actors of the international system are competing for power & attempting to formulate strategies to expand their power, foresighting & construction of future scenarios becomes an inherent part of the strategic processes. A scenario constructing process & examples are presented in the article. Adapted from the source document.

Lithuania became European and World market share, arose the problem to evaluate not only internal but also external factors, when forecasting agricultural production, consumption and foreign trade. This can be done using econometric models, which allow consider the European Union (EU) and World balance sheets components forecasts and project developments of the Lithuanian agriculture. Objective of the study - to prepare forecast for the agricultural and food sector up to the year 2020. Tasks of the study: 1. To analyze the models used for the agricultural and food sector projections and select the most suitable in respect to the conditions of the country; 2. To identify indicators that affect the Lithuanian agriculture and food sector development; 3. To analyze and project the EU and national support influence for the developments of different agricultural and food sector branches; 4. To propose and assess forecasts of the main crop and livestock production balance sheets. Statistical data analysis, experts' interview and econometric sectoral modeline are used in the research study. The analysis is performed for main agricultural sectors using economic and manufacturing indicators for 2000‐2008. The first section consists of review of agricultural and food sectors forecasting models and research study methodology preparation. Lithuanian and EU macroeconomic assumptions, which have influence on agricultural and food sector development, are proposed in the second chapter. The third chapter consists of analysis and evaluation of current EU and national support influence on agricultural and food sector development. There are prognoses of crop (grains, rapes, sugar beet, potatoes) and animal (meat milk) sectors balance sheets up to the year 2020 in the fourth and fifth chapters.

Lithuania became European and World market share, arose the problem to evaluate not only internal but also external factors, when forecasting agricultural production, consumption and foreign trade. This can be done using econometric models, which allow consider the European Union (EU) and World balance sheets components forecasts and project developments of the Lithuanian agriculture. Objective of the study - to prepare forecast for the agricultural and food sector up to the year 2020. Tasks of the study: 1. To analyze the models used for the agricultural and food sector projections and select the most suitable in respect to the conditions of the country; 2. To identify indicators that affect the Lithuanian agriculture and food sector development; 3. To analyze and project the EU and national support influence for the developments of different agricultural and food sector branches; 4. To propose and assess forecasts of the main crop and livestock production balance sheets. Statistical data analysis, experts' interview and econometric sectoral modeline are used in the research study. The analysis is performed for main agricultural sectors using economic and manufacturing indicators for 2000‐2008. The first section consists of review of agricultural and food sectors forecasting models and research study methodology preparation. Lithuanian and EU macroeconomic assumptions, which have influence on agricultural and food sector development, are proposed in the second chapter. The third chapter consists of analysis and evaluation of current EU and national support influence on agricultural and food sector development. There are prognoses of crop (grains, rapes, sugar beet, potatoes) and animal (meat milk) sectors balance sheets up to the year 2020 in the fourth and fifth chapters.

Lithuania became European and World market share, arose the problem to evaluate not only internal but also external factors, when forecasting agricultural production, consumption and foreign trade. This can be done using econometric models, which allow consider the European Union (EU) and World balance sheets components forecasts and project developments of the Lithuanian agriculture. Objective of the study - to prepare forecast for the agricultural and food sector up to the year 2020. Tasks of the study: 1. To analyze the models used for the agricultural and food sector projections and select the most suitable in respect to the conditions of the country; 2. To identify indicators that affect the Lithuanian agriculture and food sector development; 3. To analyze and project the EU and national support influence for the developments of different agricultural and food sector branches; 4. To propose and assess forecasts of the main crop and livestock production balance sheets. Statistical data analysis, experts' interview and econometric sectoral modeline are used in the research study. The analysis is performed for main agricultural sectors using economic and manufacturing indicators for 2000‐2008. The first section consists of review of agricultural and food sectors forecasting models and research study methodology preparation. Lithuanian and EU macroeconomic assumptions, which have influence on agricultural and food sector development, are proposed in the second chapter. The third chapter consists of analysis and evaluation of current EU and national support influence on agricultural and food sector development. There are prognoses of crop (grains, rapes, sugar beet, potatoes) and animal (meat milk) sectors balance sheets up to the year 2020 in the fourth and fifth chapters.