Wages, Prices, Productivity, Inflation and Unemployment in Italy 1970-1994

The relationships between wages, prices, productivity, inflation and unemployment in Italy between 1970 and 1994, are modelled using a cointegrated vector autoregression. There is evidence of a change in the underlying equilibria and in the dynamic evolution of the variables, probably associated with the substantial changes in many sectors of the Italian economy after 1979. Alternative ways to model structural change in the Italian labour market are considered, including choice of lag length, the use of dummy variables, modelling conditionally on related macroeconomic variables, and modelling separate regimes. In adopting a split sample approach the results favour an hysteresis interpretation of unemployment.

Forecasting in the Presence of Structural Breaks and Policy Regime Shifts

The value of selecting the best forecasting model as the basis for empirical economic policy analysis is questioned. When no model coincides with the data generation process, non-causal statistical devices may provide the best available forecasts: examples from recent work include intercept corrections and differenced-data VARs. However, the resulting models need have no policy implications. A 'paradox' may result if their forecasts induce policy changes which can be used to improve the statistical forecast. This suggests correcting statistical forecasts by using the econometric model's estimate of the 'scenario' change, and doing so yields reduced biases.

Small system modelling of real wages, inflation, unemployment and output per capita in Italy 1970-1994

The relationships between real wages, output per capita, inflation and unemployment in Italy between 1970 and 1994, are modelled using a cointegrated vector autoregression. There is evidence of a change in the underlying equilibria and in the dynamic evolution of the variables, probably associated with the substantial changes in many sectors of the Italian economy after 1979. Alternative ways to model structural change in the Italian labour market are considered. In adopting a split sample approach the results favour an hysteresis interpretation of unemployment. <br><br> Keywords; regime shifts, forecasting, cointegration, real wages, infation, unemployment, output gap

Reformulating empirical macro-econometric modelling

The policy implications of estimated macro-econometric systems depend on the formulations of their equations, the methodology of empirical model selection and evaluation, the techniques of policy analysis, and their forecast performance. Drawing on recent results in the theory of forecasting, we question the role of `rational expectations'; criticize a common approach to testing economic theories; show that impulse-response methods of evaluating policy are seriously flawed; and question the mechanistic derivation of forecasts from econometric systems. In their place, we propose that expectations should be treated as instrumental to agents' decisions; discuss a powerful new approach to the empirical modelling of econometric relationships; offer viable alternatives to studying policy implications; and note modifications to forecasting devices that can enhance their robustness to unanticipated structural breaks. Keywords; economic policy analysis, macro-econometric systems, empirical model selection and evaluation, forecasting, rational expectations, impulse-response analysis, structural breaks

Model Identification and Non-unique Structure

Identification is an essential attribute of any model's parameters, so we consider its three aspects of 'uniqueness', 'correspondence to reality' and 'interpretability'. Observationally-equivalent over-identified models can co-exist, and are mutually encompassing in the population; correctly-identified models need not correspond to the underlying structure; and may be wrongly interpreted. That a given model is over-identified with all over-identifying restrictions valid (even asymptotically) is insufficient to demonstrate that it is a unique representation. Moreover, structre (as invariance under extended information) need not be identifiable. We consider the role of structural breaks to discriminate between such representations.

Progressive modelling of macroeconomic time series : the LSE methodology

Digitised version produced by the EUI Library and made available online in 2020

A retrospective on J.D. Sargan and his contribution to Econometrics

This retrospective provides a biographical history of Denis Sargan's career and reviews his contributions to econometrics, emphasizing the breadth of his work in both theoretical and applied econometrics. We include a complete bibliography for Denis and a list of PhD theses that he supervised - students were a substantive facet of his profesional life. Finally, two of Denis' previously unpublished manuscripts on model building now appear in print. Keywords; dynamic specification, econometrics, error correction model, finite sample distributions, identification, instrumental variables, model building, numerical computation, prices, production function, specification searches, wages

A Markov-switching vector equilibrium correction model of the UK labour market

There is a wide literature on the dynamic adjustment of employment and its relationship with the business cycle. Our aim is to propose a statistical model that offers a congruent representation of post-war UK labour market. We use a cointegrated vector autoregressive Markov-switching model where some parameters change according to the phase of the business cycle. Output, employment, labour supply and real earnings are found to have a common cyclical component. The long run dynamics are characterized by two cointegrating vectors: trend-adjusted labour productivity and the labour share. Despite there having been many changes affecting this sector of the UK economy, the Markov-switching vector-equilibrium-correction model with three regimes representing recession, growth and high growth provides a good characterization of the sample data over the period 1966(3)-1993(1) In an out-of-sample forecast experiment over the period 1991(2)-1993(1) it beats linear and non-linear model alternatives. The results of an impulse-response analysis highlight the dangers of using VARs when the constancy of the estimated coefficients has not been established. Keywords; business cycles, employment, impulse-response analysis, cointegration, regime shifts, markov switching