68 research outputs found
Wage Bargaining and Induced Technical Change in a Linear Economy: Model and Application to the US (1963-2003)
In a simple one-sector, two-class, fixed-proportions economy, wages are set through axiomatic bargaining a`la Nash (1950). As for choice of technology, firms choose the direction of factor augmentations to maximize the rate of unit cost reduction (Kennedy 1964, and more recently Funk 2002). The ag-gregate environment resulting by self-interested decisions made by economic agents is described by a two-dimensional dynamical system in the employment rate and output/capital ratio. The economy converges cyclically to a long-run equilibrium involving a Harrod-neutral profile of technical change, a constant rate of employment of labor, and constant input shares. The type of oscillations predicted by the model matches the available data on the United States (1963-2003). Finally, institutional change, as captured by variations in workersâ bargaining power, has a positive effect on the rate of output growth but a negative effect on employment.Bargaining, Induced Technical Change, Factor Shares, Employment.
Wage Bargaining and Induced Technical Change in a Linear Economy: Model and Application to the US (1963-2003)
In a simple one-sector, two-class, fixed-proportions economy, wages are set through axiomatic bargaining a la Nash [1950]. As for choice of technology, firms choose the direction of factor augmentations to maximize the rate of unit cost reduction (Kennedy [1964], and more recently Funk [2002]). The aggregate environment resulting by self-interested decisions made by economic agents is described by a two-dimensional dynamical system in the employment rate and output/capital ratio. The economy converges cyclically to a long-run equilibrium involving a Harrod-neutral prole of technical change, a constant rate of employment of labor, and constant input shares. The type of oscillations predicted by the model matches the available data on the United States (1963-2003). Finally, institutional change, as captured by variations in workers' bargaining power, has a positive effect on the rate of output growth but a negative effect on employment.Bargaining; Induced Technical Change; Factor Shares; Employment
Keeping up with the Joneses: Other-regarding Preferences and Endogenous Growth
We study a series of sustained growth models in which households' preferences are affected by the consumption of other households as summarized by average consumption. In endogenous growth models, the equilibrium paths involve lower savings and lower growth than the corresponding efficient paths. Both savings and growth are inversely related to the extent of social preferences. In semi-endogenous models, other-regarding preferences have no growth effects, but have positive level effects on the long-run research intensity, because they increase the market size for potential monopolists in the intermediate goods sector. To test the extent to which consumption is other-regarding, we use Consumer Expenditure Survey data: our identification strategy relies on a two-stage estimator that uses the Tax Reform Act of 1986 and the Omnibus Budget Reconciliation Act of 1993 as a positive and a negative consumption shocks to top incomes respectively. In the first stage, we use a difference-in-difference approach to exploit the exogenous variation in consumption caused by federal tax reform. We then use the predicted values for average within-cohort consumption by income deciles as an instrument to estimate the extent of social preferences. Our results point toward highly significant long-run `keeping up' effects on the order of 30%
A walk in the statistical mechanical formulation of neural networks
Neural networks are nowadays both powerful operational tools (e.g., for
pattern recognition, data mining, error correction codes) and complex
theoretical models on the focus of scientific investigation. As for the
research branch, neural networks are handled and studied by psychologists,
neurobiologists, engineers, mathematicians and theoretical physicists. In
particular, in theoretical physics, the key instrument for the quantitative
analysis of neural networks is statistical mechanics. From this perspective,
here, we first review attractor networks: starting from ferromagnets and
spin-glass models, we discuss the underlying philosophy and we recover the
strand paved by Hopfield, Amit-Gutfreund-Sompolinky. One step forward, we
highlight the structural equivalence between Hopfield networks (modeling
retrieval) and Boltzmann machines (modeling learning), hence realizing a deep
bridge linking two inseparable aspects of biological and robotic spontaneous
cognition. As a sideline, in this walk we derive two alternative (with respect
to the original Hebb proposal) ways to recover the Hebbian paradigm, stemming
from ferromagnets and from spin-glasses, respectively. Further, as these notes
are thought of for an Engineering audience, we highlight also the mappings
between ferromagnets and operational amplifiers and between antiferromagnets
and flip-flops (as neural networks -built by op-amp and flip-flops- are
particular spin-glasses and the latter are indeed combinations of ferromagnets
and antiferromagnets), hoping that such a bridge plays as a concrete
prescription to capture the beauty of robotics from the statistical mechanical
perspective.Comment: Contribute to the proceeding of the conference: NCTA 2014. Contains
12 pages,7 figure
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Path Dependence and Stagnation in a Classical Growth Model
This paper embeds a technical progress function in a classical growth model and studies the effects of permanent changes in parameters and temporary shocks such as pandemics. Technical change is driven by dynamic economies of scale and responds to distributional forces: the wage share regulates labor-saving technical change and employment regulates its capital- using bias. The model features path dependence in the employment-population rate and the output-capital ratio. Population growth and distribution can respond to the employment rate. Interpreted through the model, secular stagnation under neoliberal capitalism has been driven by a combination of diminished investment and reduced worker bargaining power more than by slower technical change and population growth. A temporary unfavorable shock to the output- capital ratio will permanently reduce the employment rate. In the fully endogenous model, this will increase the profit share and reduce the rates of technical change, capital accumulation, and population growth
Meta-stable states in the hierarchical Dyson model drive parallel processing in the hierarchical Hopfield network
In this paper we introduce and investigate the statistical mechanics of
hierarchical neural networks: First, we approach these systems \`a la Mattis,
by thinking at the Dyson model as a single-pattern hierarchical neural network
and we discuss the stability of different retrievable states as predicted by
the related self-consistencies obtained from a mean-field bound and from a
bound that bypasses the mean-field limitation. The latter is worked out by
properly reabsorbing fluctuations of the magnetization related to higher levels
of the hierarchy into effective fields for the lower levels. Remarkably, mixing
Amit's ansatz technique (to select candidate retrievable states) with the
interpolation procedure (to solve for the free energy of these states) we prove
that (due to gauge symmetry) the Dyson model accomplishes both serial and
parallel processing. One step forward, we extend this scenario toward multiple
stored patterns by implementing the Hebb prescription for learning within the
couplings. This results in an Hopfield-like networks constrained on a
hierarchical topology, for which, restricting to the low storage regime (where
the number of patterns grows at most logarithmical with the amount of neurons),
we prove the existence of the thermodynamic limit for the free energy and we
give an explicit expression of its mean field bound and of the related improved
boun
Topological properties of hierarchical networks
Hierarchical networks are attracting a renewal interest for modelling the
organization of a number of biological systems and for tackling the complexity
of statistical mechanical models beyond mean-field limitations. Here we
consider the Dyson hierarchical construction for ferromagnets, neural networks
and spin-glasses, recently analyzed from a statistical-mechanics perspective,
and we focus on the topological properties of the underlying structures. In
particular, we find that such structures are weighted graphs that exhibit high
degree of clustering and of modularity, with small spectral gap; the robustness
of such features with respect to link removal is also studied. These outcomes
are then discussed and related to the statistical mechanics scenario in full
consistency. Lastly, we look at these weighted graphs as Markov chains and we
show that in the limit of infinite size, the emergence of ergodicity breakdown
for the stochastic process mirrors the emergence of meta-stabilities in the
corresponding statistical mechanical analysis
Optimal Induced Innovation and Growth with Congestion of a Limited Natural Resource
In a simple Neoclassical Growth Model with endogenous technical change, I expand
on the hypothesis of Induced Innovation including a production externality from a xed
input, called `land', which represents the carrying capacity of the earth's atmosphere.
Land is assumed to be congested by the use of labor and capital in production. A market
economy where land is free will fail to reach a steady state, and may end up in either
of three possible cases: (i) a catastrophe driven by overaccumulation; (ii) a state in
which Induced Innovation stops capital deepening but not environmental decline; (iii) a
path of perpetual decumulation of capital resembling an industrial counterrevolution. A
planned economy, instead, will assign a shadow-price to land, thus setting in motion the
Induced Innovation engine and fostering land-augmenting technological progress which
will reduce environmental stress. The unique equilibrium if this economy is found to
be locally asymptotically stable in the numerical analysis for substitution elasticities
smaller than 1. The corresponding direction of technical change is characterized by
constant shares of all inputs, a positive growth rate of labor- and land-augmenting
technologies, and by a rate of growth of capital-augmentation equal to zero
Wage Bargaining and Induced Technical Change in a Linear Economy: Model and Application to the US (1963-2003)
In a simple one-sector, two-class, fixed-proportions economy, wages are set through axiomatic bargaining a la Nash [1950]. As for choice of technology, firms choose the direction of factor augmentations to maximize the rate of
unit cost reduction (Kennedy [1964], and more recently Funk [2002]). The aggregate environment resulting by self-interested decisions made by economic
agents is described by a two-dimensional dynamical system in the employment rate and output/capital ratio. The economy converges cyclically to a long-run equilibrium involving a Harrod-neutral prole of technical change, a
constant rate of employment of labor, and constant input shares. The type of oscillations predicted by the model matches the available data on the United
States (1963-2003). Finally, institutional change, as captured by variations in workers' bargaining power, has a positive effect on the rate of output growth but a negative effect on employment
Wage Bargaining and Induced Technical Change in a Linear Economy: Model and Application to the US (1963-2003)
In a simple one-sector, two-class, fixed-proportions economy, wages are set through axiomatic bargaining a la Nash [1950]. As for choice of technology, firms choose the direction of factor augmentations to maximize the rate of
unit cost reduction (Kennedy [1964], and more recently Funk [2002]). The aggregate environment resulting by self-interested decisions made by economic
agents is described by a two-dimensional dynamical system in the employment rate and output/capital ratio. The economy converges cyclically to a long-run equilibrium involving a Harrod-neutral prole of technical change, a
constant rate of employment of labor, and constant input shares. The type of oscillations predicted by the model matches the available data on the United
States (1963-2003). Finally, institutional change, as captured by variations in workers' bargaining power, has a positive effect on the rate of output growth but a negative effect on employment
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