This paper presents a single unified framework that integrates the theoretical literature on Schumpeterian endogenous growth and major strands of the empirical literatures on R&D, productivity growth, and productivity convergence. Starting from a structural model of endogenous growth following...

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...

This paper describes a method for estimating panels by imposing a factor structure on the residuals. The method allows SUR estimation of panel models by providing a full-rank estimator of the system covariance matrix when the usual estimate is rank-deficient. We charactersie completely the...