Forecasting government budgets : methods and applications
著者
書誌事項
Forecasting government budgets : methods and applications
Lexington Books, c2023
大学図書館所蔵 全2件
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  愛媛
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  佐賀
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注記
Content Type: text (rdacontent), Media Type: unmediated (rdamedia), Carrier Type: volume (rdacarrier)
Includes bibliographical references (p. 239-245) and index
Summary: "Written in a simple and easy to understand manner, Forecasting Government Budgets presents some of the frequently used methods, simple as well as advanced, in budget forecasting. Although written primarily for graduate students in public administration and management, students from other disciplines will also find it useful"-- Provided by publisher
内容説明・目次
内容説明
A budget is the nerve center of a government and forecasting is integral to budgeting. For a government to be able to carry out its everyday operations in a planned and organized manner, it has to have a sound knowledge of future revenues and expenditures, i.e., its budget. Forecasting provides that knowledge by producing estimates of revenues and expenditures, based on past and current information, to indicate whether the government will have sufficient revenue to effectively carry out its routine and non-routine operations. This notion of forecasting is more appropriate at the sub-national level, where the state and local governments are required by law to balance their budget, especially the operating budget. And without good and reliable forecasts, it will be difficult to determine the measures that will be necessary to balance the budget or ensure conformity between revenues and expenditures.
Written in a simple and easy to understand manner, the book presents a number of well-established methods, simple as well as advanced, including some recent developments in budget forecasting. Although written primarily for graduate students in public administration and government practitioners, students from other disciplines will also find it useful.
目次
Part I: Basic Time Series Models
Chapter 1: Basic Time Series Models I
Chapter 2: Basic Time Series Models II
Chapter 3: Time Series Regression
Part II: Advanced Time Series Models
Chapter 4: Box-Jenkins and ARIMA Models
Chapter 5: Seasonal ARIMA Models
Chapter 6: Advanced Time Series Models
Part III: Recent Advances in Forecasting Models
Chapter 7: Some Recent Advances in Forecasting Models
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