This study examines a recent change in voluntary disclosure by investigating the issuance of management cash flow forecasts for a sample of 690 UK non-financial firm-year observations which are drawn from the top 500 UK listed firms by total market capitalisation as listed by Financial Times on...

This paper tests for the importance of cash flow on investment in fixed capital and R&D using firm-level panel data in two countries between 1985 and 1994. For German firms, cash flow is not informative in simple econometric models of fixed investment or R&D. In identical specifications for...

Tens of thousands of young people leave school with no or very few qualifications in England. This paper seeks to build a fuller picture of Key Stage 4 low achievement and its correlates than available hitherto. We focus on three aspects. Firstly, the role of students’ personal...

This paper investigates the efficiency wage hypothesis and derives a tractable expression for the profit loss incurred by deviations from the efficiency wage. The extent of the wage deviation can be inferred from production function parameters. The resulting profit loss shown to depend upon the...

This paper shows that, with (partial) irreversibility, higher uncertainty reduces the impact effect of demand shocks on investment. Uncertainty increases real option values making firms more cautious when investing or disinvesting. This is confirmed both numerically for a model with a rich mix...

Disadvantaged groups tend also to constitute population minorities. One consequence of this is that the policies implemented by electorally accountable governments often fail to reflect minority interests. A policy solution is to enhance the political power of minority groups as a vehicle for...

In a panel data model with fixed effects, possible cross-sectional dependence is investigated in a spatial autoregressive setting. An Edgeworth expansion is developed for the maximum likelihood estimate of the spatial correlation coefficient. The expansion is used to develop more accurate...

Nonparametric regression is developed for data with both a temporal and a cross-sectional dimension. The model includes additive, unknown, individual-specific components and allows also for cross-sectional and temporal dependence and conditional heteroscedasticity. A simple nonparametric...