Coupled Dynamics in the Phillips Machine Model of the Macroeconomy

In this paper it is claimed that the Phillips machine is a nonlinear mechanism. Phillips (1950) presented his machine as being described with a linear differential equation. In this paper it is claimed that the machine is better described with a system of nonlinear difference.-differential equations. This system itself is approximated by a set of nonlinear differential equations. This differential equations are of the Hicks-Goodwin flexible multiplier accelerator type. Consistently with this conjecture and following Phillips’ suggestion we have presented a ‘digital’ simulation of two coupled would-be Phillips machines.computable economics; flexible-accelerator, coupled dynamical systems, Goodwin, Phillips machine, MONIAC

Online Ensemble Learning of Sensorimotor Contingencies

Forward models play a key role in cognitive agents by providing predictions of the sensory consequences of motor commands, also known as sensorimotor contingencies (SMCs). In continuously evolving environments, the ability to anticipate is fundamental in distinguishing cognitive from reactive agents, and it is particularly relevant for autonomous robots, that must be able to adapt their models in an online manner. Online learning skills, high accuracy of the forward models and multiple-step-ahead predictions are needed to enhance the robots’ anticipation capabilities. We propose an online heterogeneous ensemble learning method for building accurate forward models of SMCs relating motor commands to effects in robots’ sensorimotor system, in particular considering proprioception and vision. Our method achieves up to 98% higher accuracy both in short and long term predictions, compared to single predictors and other online and offline homogeneous ensembles. This method is validated on two different humanoid robots, namely the iCub and the Baxter

Technological Progress in Italian Regions: Some Comparisons

In this paper we study technological progress in a set of representative Italian regions. The analysis is conducted using input-output data. We construct the technological frontiers and calculate new indices of technological progress (see Fredholm and Zambelli 2009 and Zambelli and Fredholm 2010). The empirical results are robust and seem to be interesting. We find, for the years 2001 and 2004 that Trentino and Sicily are the regions, among those examined, with the largest number of technologically advanced productive methods, while Veneto and Lombardy are characterized by poor relative technological performance. Given the micro data about observed productivity this result is, at first, surprising, but we provide an interpretation. In the case of the Trentino region the technological progress is actually exploited so that the region is near to full employment and the income generated is relatively high. In the case of Sicily our results show that there is a great potential for growth which is not exploited. Veneto and Lombardy seem to be cases in which the embodied technological progress is not high, this indicates, ceteris paribus, a low potential for future growth or, alternatively, that the development has occurred in the past. Good performance is also indicated by Emilia Romagna.Technological Progress, Technological Frontier, Productivity, Regional Economy

An Algorithmic Measurement of Technical Progress

In this paper we propose a measure of technological progress which is based on the information embedded in standard input-output tables. Well known duality properties enables one to establish a connection between the quantities necessary as inputs and the associated output and some auxiliary prices (like the wage-profit curves). We claim that properly tailored wage-profit frontiers may provide a basis for the measurement of technological progress. But the computation of these wage-profit frontiers is not trivial. A brute force algorithm for the computation of the wage-profit frontiers has high combinatorial complexity that would make its precise computation intractable. But thanks to an efficient algorithm that we have been able to devise we can now compute it. We consider this to be an important and original contribution. Here we present and apply this algorithm. Due to this improvement we can now use these wage-profit frontiers as benchmarks against which to measure technological progress: two new indices have been defined. These new tools have have been applied to the OECD input-output data 1970-2005 and the reslts are presented here.Technological Change, Convergence, Input-output analysis, Technological Frontier, Computational Techniques