The effect of the national setting on employment practice: the case of downsizing

Although there is now a sizeable body of academic literature that tries to explain cross-country differences in terms of corporate control, capital market development, investor protection and politics, there is as yet very little literature on the degrees of protection accorded to other corporate stakeholders such as employees, based on a systematic comparison of firm level evidence. We find that both theories of legal origin and the varieties of capitalism approach are poor predictors of the relative propensity of firms to make redundancies in different settings. However, the political orientation of the government in place and even more so the nature of the electoral system are relatively good explanators of this propensity. In other words, political structures and outcomes matter more than more rigid institutional features such as legal origin. We explore the reasons for this, drawing out the implications for both theory and practice.

Forecasting with difference and trend stationary models

Although difference-stationary (DS) and trend-stationary (TS) processes have been subject to considerable analysis, there are no direct comparisons for each being the data-generation process (DGP). We examine incorrect choice between these models for forecasting for both known and estimated parameters. Three sets of Monte Carlo simulations illustrate the analysis, to evaluate the biases in conventional standard errors when each model is mis-specified, compute the relative mean-square forecast errors of the two models for both DGPs, and investigate autocorrelated errors, so both models can better approximate the converse DGP. The outcomes are surprisingly different from established results.

Economic forecasting: some lessons from recent research

This paper describes some recent advances and contributions to our understanding of economic forecasting. The framework we develop helps explain the findings of forecasting competitions and the prevalence of forecast failure. It constitutes a general theoretical background against which recent results can be judged. We compare this framework to a previous formulation, which was silent on the very issues of most concern to the forecaster. We describe a number of aspects which it illuminates, and draw out the implications for model selection. Finally, we discuss the areas where research remains needed to clarify empirical findings which lack theoretical explanations.