THE COMPLEX DYNAMICS OF THE SIMPLE RICARDIAN SYSTEM: A NOTE

In a recent note, Bhaduri and Harris (1987) showed that a discrete-time dynamic version of the ‘simple’Ricardian system (i.e. Blaug's (1978) popular version of Kaldor's (1955-6) representation of Ricardian distribution theory, which includes linear agricultural productivity) can be endowed with an unstable stationary state, and that the system can also exhibit “chaotic” orbits (cfr. Collet and Eckmann, 1980), even if these phenomena cannot appear when the adjustment process is continuous. This stationary state does not necessarily have to be unstable. A slightly generalized version of the ‘simple’Ricardian system (we dispense with the linearity assumption) is used in this paper to analyse a number of meaningful special cases in which the stationary state is stable.     

Occupational and Job Mobility in the US*

We propose a new methodology to measure worker mobility across occupations and jobs in the US, building on the limited longitudinal dimension of monthly CPS data. For the period 1979–2006, we find that about 3.5% of male workers employed in two consecutive months report different three‐digit occupations. This rate is procyclical, mildly rising in the 1980s and falling after 1995. We also revise upward current estimates of aggregate job‐to‐job mobility since 1994, from 2.7% to 3.2% of employment per month. Despite extreme similarity of average levels and time‐series behavior, occupational and job mobility are only weakly correlated.     

Real-time squared: A real-time data set for real-time GDP forecasting

This paper uses real-time data to mimic real-time GDP forecasting activity. Through automatic searches for the best indicators for predicting GDP one and four steps ahead, we compare the out-of-sample forecasting performance of adaptive models using different data vintages, and produce three main findings. First, despite data revisions, the forecasting performance of models with indicators is better, but this advantage tends to vanish over longer forecasting horizons. Second, the practice of using fully updated datasets at the time the forecast is made (i.e., taking the best available measures of today's economic situation) does not appear to bring any effective improvement in forecasting ability: the first GDP release is predicted equally well by models using real-time data as by models using the latest available data. Third, although the first release is a rational forecast of GDP data after all statistical revisions have taken place, the forecast based on the latest available GDP data (i.e. the “temporarily best” measures) may be improved by combining preliminary official releases with one-step-ahead forecasts.     

Home bias in divestment decisions of multinational corporations in the EU

We empirically investigate the claim that multinational corporations (MNCs) suffer from a “home bias” in divestment decisions: MNCs prefer to divest from foreign subsidiaries because the “emotional involvement” and the commitment in divesting from domestic subsidiaries is larger. This issue has not been yet empirically explored in the economic literature, although it is quite recurrent in the political debate on MNCs and FDI. Using detailed company‐level data on the EU corporate groups during the economic crisis (2008–2014), we show that, in spite of prima facie empirical evidence of a home bias, the bias disappears when firm‐, country‐, and sector‐specific factors are accounted for.     

Early stage SME bankruptcy: does the local banking market matter?

Small Business Economics - This paper investigates the role of local context, with regard to the effect of local financial development and banking concentration, on a firm’s probability of...     

Currency substitution and the stability of the Italian demand for money before the entry into the monetary union, 1972–1998

A money demand function for M2 is estimated for Italy for the period 1972–1998 within an error correction framework. This period has been characterized by major structural changes in the Italian financial system and by major changes in monetary policy. This study takes these changes into account. Moreover, currency substitution, especially between Italy and Germany is incorporated into the model. By accounting for structural breaks and currency substitution a stable money demand function can be found.Financial support from the Deutsche Forschungsgemeinschaft, SFB 373, is gratefully acknowledged. We thank Uwe Hassler, Goethe Universität, Frankfurt, and Carsten Trenkler, SFB 373, Humboldt-Universität zu Berlin, for helpful comments. An earlier version has been presented at the ESEM 2001, Lausanne.     

Anchoring the yield curve using survey expectations

The dynamic behavior of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have underperformed since the early 2000s. On the other hand, survey expectations can accurately predict yields, but they are typically not available for all maturities and/or forecast horizons. We show how survey expectations can be exploited to improve the accuracy of yield curve forecasts given by a base model. We do so by employing a flexible exponential tilting method that anchors the model forecasts to the survey expectations, and we develop a test to guide the choice of the anchoring points. The method implicitly incorporates into yield curve forecasts any information that survey participants have access to—such as information about the current state of the economy or forward‐looking information contained in monetary policy announcements—without the need to explicitly model it. We document that anchoring delivers large and significant gains in forecast accuracy relative to the class of models that are widely adopted by financial and policy institutions for forecasting the term structure of interest rates.