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1. Introduction -- 2. People and Techniques in Budgeting -- 2.1. The effectiveness of budget control systems -- 2.2. The wood and the trees -- 2.3. Potential psychological gains in using quantitative methods -- 2.4. Quantitative methods in assessing the social aspects of a control system -- 2.5. Conclusion -- 3. Balanced Transfer Values in Scheduling, Costing and Recompensing -- 3.1. Extended introduction and summary -- 3.2. Linear programming and accountancy -- 3.3. Models of the values as well as the measures of flows -- 3.4. Linking objects: transferrers of value -- 3.5. Balancing procedures: evaluation of intracompany trade -- 3.6. Degrees of freedom and channels of valuation -- 3.7. Ancillary interrelations in costing and recompensing -- 3.8. Recapitulation -- 4. Ratio Network Models and their Application in Budgeting -- 4.1. Ratio network models -- 4.2. Budgeting with the help of the ratio network method -- 5. The Development of a Budgeting Model -- 5.1. Introduction -- 5.2. The preliminary phase -- 5.3. The conceptual side -- 5.4. The general model -- 5.5. The first phase -- 5.6. The second phase -- 5.7. Conclusions with respect to the implementation -- Appendix 5.1. Mathematical description of the generalized model -- 6. Cost Accounting, Planning and Budgeting -- 6.1. Cost functions and product costing -- 6.2. The relations between production centres -- 6.3. Alternative production methods of economically homogeneous products -- 6.4. Planning, linear programming and unit costs -- 6.5. Planning, budgeting and costs -- 6.6. Example -- 7. Stochastic Budgeting -- 7.1. Introduction -- 7.2. Probability distributions -- 7.3. Some specific distributions -- 7.4. Relations between the variables -- 7.5. Computer program -- 7.6. Interval boundaries and policy -- 7.7. Concluding remarks -- Appendix 7.1. Flow-chart of computer program -- Appendix 7.2. Interval exploitation budget -- Appendix 7.3. A definition of subjective probability -- 8. Variance Analysis, Flexible Budgeting and Responsibility Accounting -- 8.1. Classical variance analysis -- 8.2. The flexible-budgeting approach to variance analysis -- 8.3. Multi-stage, multidimensional variance analysis -- Appendix 8.1. Two-stage, two-dimensional variance analysis with flexible budgeting -- Appendix 8.2. Algebra and numerical example of two-stage, three-dimensional variance analysis with flexible budgeting -- 9. Where Short-Term Budget Meets Long-Term Plan -- 9.1. Next year's budget in conflict with first year of long-term plan -- 9.2. Using budget pattern for disaggregation of long-term plan -- 9.3. The multiproportional RAS algorithm -- 9.4. Taking account of prior information.

Summary  A table and a nomogram are given to find the growth rate of a regression line drawn on so‐called semi‐logarithmic graph paper. The growth rate is determined by: a) the slope of the regression line, b) the length ratio between the logarithmic and the metric unit, in other words, the number of years on the time axis (if a year is the time unit) corresponding in length to one cycle on the logarithmic axis (say, 1 to 10, or 100 to 1000). With an example, the use of the table and nomogram is explained.

Summary  In business practice it happens that annual growth is measured by the ordinary (arithmetic) average of yearly growth percentages. It is argued that there are better methods in any case. A method requiring relatively much time is least squares. Methods requiring very little time are a) determining growth graphically, using semi‐logarithmic graph paper b) computing the geometrical average, which is nothing else than the n‐th root (if there are n+l observations) of the ratio between the last and first observation.In a table, a survey of bias and dispersion of three estimators is given for a few numerical cases.