Developing a Parametric Cash Flow Forecasting Model for Complex Infrastructure Projects: A Comparative Study

Forecasting the cash flow for infrastructure projects has not received much attention in the existing models. Moreover, disregarding the cost flow behaviour and proposing models that entail a relatively high dimensionality of inputs have been the main drawbacks of the existing models. This study proposes a heuristic cash flow forecasting (CFF) model for infrastructure projects, and it explores the underlying behaviour of the cost flow. The proposed model was validated by adopting a case study approach,the actual cost flow datasets were mined from a verified data system. The results invalidated the employment of a dominant heuristic rule with regard to a cost-flow-time relationship in infrastructure projects. On the other hand, a mathematical parameter-based comparison between the trends analysed from previous studies revealed that the cost flows of infrastructure projects procured through a design-bid-build (D-B-B) route behaved in a similar manner to building projects procured through a construction management route. This research contributes to the body of knowledge providing a method to enable infrastructure contractors to accurately forecast the required working capital through adding a new dimension for project classification by coining the term “the quaternary flow percentage”. In addition, this study indicates the importance of identifying the impact of root risks on the individual cost flow components rather than on the aggregated cost flow, which is a recommendation for future research.

CASH MANAGEMENT: HOW DO COUNTRIES PERFORM SOUND PRACTICES?

Cash management is simply defined as making the right amount of money available at the right time and the right place to meet the government's obligations in the most cost-effective way. The main features of modern cash management are centralized government bank accounts and establishment of a Treasury Single Account, ability to make accurate cash flow forecasts, use of short-term financing instruments, and capacity for the investment of excess cash reserves. Establishing a sound cash management framework with the mentioned features is beneficial not only to the governments and public entities, but also to other stakeholders including the beneficiaries of government payments, banks and lenders. Given the recent COVID-19 (coronavirus) pandemic and locked-down measures introduced in many countries, governments had to deal with unanticipated revenue decreases, and significantly increased public expenditures due to fiscal stimulus packages and pandemic related health expenditures. Therefore, existence of a well-structured government cash management is now even more important than before. This paper aims to explore cash flow forecasting and cash management practices in 24 countries in various regions, at different income levels and technical capacity, and alignment to good practices based on the information provided at the World Bank workshops on Cash Flow Forecasting and Cash Management held in 2018 and 2019. The paper also draws on experiences and practices from other emerging and advanced countries. Cases from different countries indicate that full implementation of modern cash management is still a challenge, even though the Treasury Single Account system is common in most countries and liquidity buffers were established or increased following the Global Financial Crisis. Cash flow forecasting is an area to improve given the accuracy, horizon and frequency of the projections are frequently limited. Fragmented institutional structure makes cash management even more challenging. Country cases also demonstrate that there is a significant room to strengthen coordination between debt and cash management and the use of short-term instruments to cover cash shortages. Investment of cash balances seems to be a bigger weakness as many countries keep their liquidity buffers in the Central Bank with no remuneration.

Tail-Heaviness, Asymmetry, and Profitability Forecasting by Quantile Regression

We show that quantile regression is better than ordinary-least-squares (OLS) regression in forecasting profitability for a range of profitability measures following the conventional setup of the accounting literature, including the mean absolute forecast error (MAFE) evaluation criterion. Moreover, we perform both a simulated-data and an archival-data analysis to examine how the forecasting performance of quantile regression against OLS changes with the shape of the profitability distribution. Considering the MAFE and mean squared forecast error (MSFE) criteria together, we see that the quantile regression is more accurate relative to OLS when the profitability to be forecast has a heavier-tailed distribution. In addition, the asymmetry of the profitability distribution has either a U-shape or an inverted-U-shape effect on the forecasting accuracy of quantile regression. An application of the distributional shape analysis framework to cash flow forecasting demonstrates the usefulness of the framework beyond profitability forecasting, providing additional empirical evidence on the positive effect of tail-heaviness and supporting the notion of an inverted-U-shape effect of asymmetry. This paper was accepted by Shiva Rajgopal, accounting.

Does Human Resource Investment for Internal Control System Enhance Future Cash Flow Predictability?

Generating positive long-term cash flow is vital for a firm’s sustainability. In this paper, we consider the earnings in the forecasting of future cash flow from a human resource investment of an internal control system. Using the firms listed in the Korea Stock Exchange market from 2014 to 2018, we find that the current earnings are the components of cash flow forecasting, and this relationship is genuine in a firm equipped with sufficient internal control personnel and their experiences. These findings indicate that earnings are reliable when forecasting future cash flow for a firm with a well-operated foundation.

Do Analysts’ Cash Flow Forecasts Improve Firm Value?

We examine whether analysts’ cash flow forecasts improve firm value. First, we analyze whether the joint issuance of financial analysts’ earnings and cash flow forecasts improve firm value. Second, we analyze whether the quality of analysts’ cash flow forecasts improve firm value. The empirical results of our study are as follows. First, the joint issuance of analysts’ earnings and cash flow forecasts has a significantly positive effect on firm value; providing cash flow forecasts reduces information asymmetry and increases earnings quality, thereby increasing corporate value. Second, the quality of analysts’ cash flow forecasts has a significantly positive effect on firm value; the more accurate cash flow forecasts are, the higher firm value is. Our study provides empirical evidence for that the conclusion that cash flow forecasting information produced by financial analysts provides useful information for capital market participants in economic decision making.

Literature Review of Treasury Cash Flow Forecast

In this paper, the related literatures of treasury cash flow forecasting in the early stage are reviewed. By reviewing the related literatures, it is found that the treasury cash flow forecasting in China has made great progress, and various forecasting methods have been used in practical work, but there is still room for optimization in treasury cash flow forecasting. Suggestions for optimization are put forward.