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The purpose of this paper is to evaluate accuracy of macro fiscal forecasts done by Government of Zimbabwe and the spillover effects of forecasting errors over the period 2010-2015.

In line with the study objectives, the study employed the root mean square error methodology to measure the accuracy of macro fiscal forecasts, borrowing from the work of Calitz et al. (2013). The spillover effects were assessed through running simple regression in Eviews programme. The data used in the analysis are based on annual national budget forecasts presented to the Parliament by the Minister of Finance. Actual data come from the Ministry of Finance budget outturns and Zimbabwe Statistical Agency published national accounts.

The results of the root mean square error revealed relatively high levels of macro-fiscal forecasting errors, with revenue recording the highest. The forecasting errors display a tendency of under predicting the strength of economic recovery during boom and over predicting its strength during periods of weakness. The study although found significant evidence of GDP forecasting errors translating into revenue forecasting inaccuracies, the GDP forecasting errors fail to fully account for the revenue errors. Revenue errors were, however, found to be positive and significant in explaining the budget balance errors.

In other jurisdictions, particularly developed countries, they undertake regular evaluation of their forecasts in order to improve their forecasting procedures, which translate into quality public service delivery. The situation is lagging in Zimbabwe. Given the poor performance in public service delivery in Zimbabwe, this study contributes in dissecting the sources of the challenge by providing a comprehensive review of macro fiscal forecasts.

The purpose of this paper is to contribute to the literature on the determinant factors of government budget balance forecast errors for Eurozone countries based on four different database sources from 1998 to 2011.

Besides the analysis on quality and efficiency of government budget balance projections, panel data analysis is made from different methods taking into account economic, political, institutional and governance factors, and lagged forecast errors for estimations of budget balance forecast errors.

The results show that even with the concern and pressure due to the fiscal crisis in the Eurozone, the bias in fiscal forecasts remains.

One contribution of this paper, in comparison to other studies, is the use of longer time periods for the analysis of forecast errors as well as the employment of different data sources for detecting systematic patterns of errors, and the use of various estimation methods for the fiscal forecast error determinants, which gives insights into the reliability and robustness of results obtained in earlier studies. In particular, the introduction of variables such as fiscal council and fiscal rules allows one to check whether institutional behavior may change the effect from debt on fiscal forecast errors.

The purpose of this study is to integrate modern decision sciences and develop a dynamic risk management model for international alliance engineering design projects.

To apply the model to real-world risk assessment and managerial decision-making, a mega project case study was conducted. System dynamics and computer simulations were used for improving quantitative analyses and scenario planning.

Based on the consideration and analyses of different cooperation risk factors, ripple effects of design error is found to be the key factor of subcontract management in international alliance projects in this study.

This study provides a rationale for dynamic risk management decisions and enables international alliance companies to systematically control the cooperation risks in the execution of projects.

In the dynamic project management process, a significant increase in the design error rate does not unilaterally occur but is caused by subcontract and other management errors as a system problem. Integrative solutions with systems thinking would help the management.

This study proposed a framework of measuring project performance and dynamic risk management. The benchmarked case study demonstrates the capability of the proposed model for the feedback learning of business lessons and knowledge accumulations.

Mastering high‐density optical disks, like the Blu‐ray™ disk, requires new equipment design. Active magnetic bearing technology seem well suitable for this purpose, but challenges arise in obtaining the required extreme accuracy. Creating a very low mechanical coupling between the system and the external world is the potential solution to this challenge pursued in this paper. Design considerations on actuators, amplifiers, sensors and overall design are discussed and the system performance is predicted using an error‐budgeting estimation. This prediction indicates the feasibility of the concept, while the first prototype has been assembled and is being tested.

This study investigates the impact of federal income tax rates and budget deficits on the nominal interest rate yield on high-grade municipal tax-free bonds (municipals) in the US. The 58-year study period covers the years 1959 through 2016 and thus is very recent.

The study develops a loanable funds model that allows for various financial market factors. Once developed, the model is estimated by autoregressive two-stage least squares, with a Newey-West heteroskedasticity correction.

The nominal interest rate yield on municipals is a decreasing function of the maximum marginal federal personal income tax rate and an increasing function of the federal budget deficit (expressed as a per cent of GDP). This yield is also an increasing function of nominal interest rate yields on three- and ten-year treasury notes and expected inflation.

When introducing additional interest rates such as treasury bills as explanatory variables, multi-collinearity becomes a serious problem.

This study indicates that lower maximum federal personal income tax rates and larger federal budget deficits, both act to raise borrowing costs for cities (of all sizes), counties and states across the country. Given the study period of 58 years, these relationships appear to be enduring ones that responsible policy-makers should not overlook.

Tax reform and debt management need to be conducted in a very circumspect fashion.

No recent study investigating the impact of the two key policy variables in this study has been published.

Time-cost trade-off is normal conduct in construction projects when projects are expectedly late for delivery. Existing research on time-cost trade-off strategic management mostly focused on the technical calculation towards the optimal combination of activities to be accelerated, while the managerial aspects are mostly neglected. This paper aims to understand the managerial efforts necessary to prepare construction projects ready for an upcoming trade-off implementation.

A preliminary list of critical factors was first identified from the literature and verified by a Delphi survey. Quantitative data was then collected by a questionnaire survey to first shortlist the preliminary factors and quantify the predictive model with different machine learning algorithms, i.e. k-nearest neighbours (kNN), radial basis function (RBF), multiplayer perceptron (MLP), multinomial logistic regression (MLR), naïve Bayes classifier (NBC) and Bayesian belief networks (BBNs).

The model's independent variable importance ranking revealed that the top challenges faced were the realism of contractual obligation, contractor planning and control and client management and monitoring. Among the tested machine learning algorithms, multilayer perceptron was demonstrated to be the most suitable in this case. This model accuracy reached 96.5% with the training dataset and 95.6% with an independent test dataset and could be used as the contingency approach for time-cost trade-offs.

The identified factor list contributed to the theoretical explanation of the failed implementation in general and practical managerial improvement to better avoid such failure. In addition, the established predictive model provided an ad-hoc early warning and diagnostic tool to better ensure time-cost implementation success.

This paper tests public budgeting as a long-run and short-run process; political decision makers strive to head toward budgetary balance over the long run but are constrained in the short run and follow incremental decision-making. First, the budget equilibrium theory is stated and is used to explain the relationship between revenues and expenditures. Second, the interaction between expenditures and revenues is tested with a vector error correction model for Canada, UK and the US, using annual time series data between 1948 and 2000. The results show that, in the long-run, revenues are the driving force behind the budget in Canada; in the UK expenditures force the budget toward balance. In the short-run, incrementalism occurs in both of these countries. The most interesting finding is for the United States where on-budget revenues and expenditures both push the budget toward balance over the longrun but there is no incrementalism in the process in the short-run. This, of course, is contrary to much of the existing literature.

This study examines whether rules, particular participants, and executive politics in state tax revenue estimation exert measurable influences on forecast error. Fixed-effects estimation using data from states’ respective fiscal years 1994 to 2003 indicates that all impact state tax revenue forecast accuracy in varying ways, and results suggest that policy can be crafted to effectively mitigate forecast error. Further examination of the quality of participation in tax revenue forecasting as well as the mechanisms of political involvement in this arena is suggested.

This paper contributes to shed light on the quality and performance of US fiscal forecasts.

The first part inspects the causes of official fiscal forecasts revisions by Congressional Budget Office (CBO) between 1984 and 2016 that are due to technical, economic or policy reasons.

Both individual and cumulative means of forecast errors are relatively close to zero, particularly in the case of expenditures. CBO averages indicate net average downward revenue and expenditure revisions and net average upward deficit revisions. Focusing on the causes of the technical component, the authors uncover that its revisions are quite unpredictable, which cast doubts on inferences about fiscal policy sustainability that rely on point estimates. Comparing official with private-sector (consensus) forecasts, despite the informational advantages CBO might have, one cannot unequivocally say that one or the other is more accurate. Evidence also seems to suggest that CBO forecasts are consistently heavily biased toward optimism while this is less the case for consensus forecasts. Not only is the extent of information rigidity is more prevalent in CBO forecasts but also evidence seems to indicate that consensus forecasts dominate CBO in terms of information content.

The authors provide a detailed analysis on US fiscal forecasts both using revenue and expenditure and decomposing forecast errors into several explanatory components. Moreover, the authors compare official with private-sector (consensus) forecasts and assess which one is better or preferred.