Iskandar, I and Willett, R and Xu, S, The development of a government cash forecasting model, Journal of Public Budgeting, Accounting & Financial Management, 30, (4) pp. 368-383. ISSN 1096-3367 (2018) [Refereed Article]
Purpose: Government cash forecasting is central to achieving effective government cash management but research in this area is scarce. The purpose of this paper is to address this shortcoming by developing a government cash forecasting model with an accuracy acceptable to the cash manager in emerging economies.
Design/methodology/approach: The paper follows "top-down" approach to develop a government cash forecasting model. It uses the Indonesian Government expenditure data from 2008 to 2015 as an illustration. The study utilises ARIMA, neural network and hybrid models to investigate the best procedure for predicting government expenditure.
Findings: The results show that the best method to build a government cash forecasting model is subject to forecasting performance measurement tool and the data used.
Research limitations/implications: The study uses the data from one government only as its sample, which may limit the ability to generalise the results to a wider population.
Originality/value: This paper is novel in developing a government cash forecasting model in the context of emerging economies.
|Item Type:||Refereed Article|
|Keywords:||neural networks, hybrid models, ARIMA model, government cash forecasting, public expenditure management|
|Research Division:||Information and Computing Sciences|
|Research Group:||Information Systems|
|Research Field:||Conceptual Modelling|
|Objective Division:||Information and Communication Services|
|Objective Group:||Information Services|
|Objective Field:||Electronic Information Storage and Retrieval Services|
|Author:||Iskandar, I (Mr Iskandar Iskandar)|
|Author:||Xu, S (Dr Shuxiang Xu)|
|Deposited By:||Information and Communication Technology|
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