A monthly indicator of employment in the euro area: real time analysis of indirect estimates

The paper presents the results of an extensive real time analysis of alternative model-based approaches to derive a monthly indicator of employment for the euro area. In the experiment the Eurostat quarterly national accounts series of employment is temporally disaggregated using the information coming from the monthly series of unemployment. The strategy benefits of the contribution of the information set of the euro area and its 6 larger member states, as well as the split into the 6 sections of economic activity. The models under comparison include univariate regressions of the Chow and Lin' type where the euro area aggregate is directly and indirectly derived, as well as multivariate structural time series models of small and medium size. The specification in logarithms is also systematically assessed. The largest multivariate setups, up to 49 series, are estimated through the EM algorithm. Main conclusions are the following: mean revision errors of disaggregated estimates of employment are overall small; a gain is obtained when the model strategy takes into account the information by both sector and member state; the largest multivariate setups outperforms those of small size and the strategies based on classical disaggregation methods.temporal disaggregation methods, multivariate structural time series models, mixed-frequency models, EM algorithm, Kalman filter and smoother

Multitasking associative networks

We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzman machine and we show its thermodynamical equivalence to an associative working memory able to retrieve multiple patterns in parallel without falling into spurious states typical of classical neural networks. We focus on systems processing in parallel a finite (up to logarithmic growth in the volume) amount of patterns, mirroring the low-level storage of standard Amit-Gutfreund-Sompolinsky theory. Results obtained trough statistical mechanics, signal-to-noise technique and Monte Carlo simulations are overall in perfect agreement and carry interesting biological insights. Indeed, these associative networks pave new perspectives in the understanding of multitasking features expressed by complex systems, e.g. neural and immune networks.Comment: to appear on Phys.Rev.Let

A Critical Assessment of George Klosko’s Version of the Principle of Fair Play

The nature of our obligation to obey the law has consistently been an important object of philosophical dispute. Fair play based theories of obligation purport to show that it is unfair for us to benefit from anorganizational scheme (such as the state) without contributing our fair share to the provision of goods. George Klosko is a major proponent of this approach. I develop his particular version of the argument from fair play into a defensible theory of citizens’ obligation to obey the laws of their state

Covariance estimation for multivariate conditionally Gaussian dynamic linear models

In multivariate time series, the estimation of the covariance matrix of the observation innovations plays an important role in forecasting as it enables the computation of the standardized forecast error vectors as well as it enables the computation of confidence bounds of the forecasts. We develop an on-line, non-iterative Bayesian algorithm for estimation and forecasting. It is empirically found that, for a range of simulated time series, the proposed covariance estimator has good performance converging to the true values of the unknown observation covariance matrix. Over a simulated time series, the new method approximates the correct estimates, produced by a non-sequential Monte Carlo simulation procedure, which is used here as the gold standard. The special, but important, vector autoregressive (VAR) and time-varying VAR models are illustrated by considering London metal exchange data consisting of spot prices of aluminium, copper, lead and zinc.Comment: 21 pages, 2 figures, 6 table

A monthly indicator of employment in the euro area: real time analysis of indirect estimates

The paper presents the results of an extensive real time analysis of alternative model-based approaches to derive a monthly indicator of employment for the euro area. In the experiment the Eurostat quarterly national accounts series of employment is temporally disaggregated using the information coming from the monthly series of unemployment. The strategy benefits of the contribution of the information set of the euro area and its 6 larger member states, as well as the split into the 6 sections of economic activity. The models under comparison include univariate regressions of the Chow and Lin' type where the euro area aggregate is directly and indirectly derived, as well as multivariate structural time series models of small and medium size. The specification in logarithms is also systematically assessed. The largest multivariate setups, up to 49 series, are estimated through the EM algorithm. Main conclusions are the following: mean revision errors of disaggregated estimates of employment are overall small; a gain is obtained when the model strategy takes into account the information by both sector and member state; the largest multivariate setups outperforms those of small size and the strategies based on classical disaggregation methods

Analogue neural networks on correlated random graphs

We consider a generalization of the Hopfield model, where the entries of patterns are Gaussian and diluted. We focus on the high-storage regime and we investigate analytically the topological properties of the emergent network, as well as the thermodynamic properties of the model. We find that, by properly tuning the dilution in the pattern entries, the network can recover different topological regimes characterized by peculiar scalings of the average coordination number with respect to the system size. The structure is also shown to exhibit a large degree of cliquishness, even when very sparse. Moreover, we obtain explicitly the replica symmetric free energy and the self-consistency equations for the overlaps (order parameters of the theory), which turn out to be classical weighted sums of 'sub-overlaps' defined on all possible sub-graphs. Finally, a study of criticality is performed through a small-overlap expansion of the self-consistencies and through a whole fluctuation theory developed for their rescaled correlations: Both approaches show that the net effect of dilution in pattern entries is to rescale the critical noise level at which ergodicity breaks down.Comment: 34 pages, 3 figure

Desire in Spinoza's Value Epistemology

Spinoza claims that the good is what leads us to perfection. Yet he also affirms that whether we judge something to be good depends on whether or not we desire it. It is thus unclear whether Spinoza ultimately analyzes value in terms of perfection or in terms of desire. This is a well-known debate in the literature, but its dialectical complexity is underappreciated. Defenders of the first interpretation must explain not only why Spinoza might analyze the good in terms of perfection, but also why he claims that our judgments of value depend on our desires. They standardly argue that, for Spinoza, our desires offer epistemic justification for these judgments. In this paper, however, I argue that this reading fails. My argument supports the views on which desire plays a role in Spinoza’s account of the nature of value itself, and not merely in his value epistemology

Spinoza on Freedom, Feeling Free, and Acting for the Good

In the Ethics, Spinoza famously rejects freedom of the will. He also offers an error theory for why many believe, falsely, that the will is free. Standard accounts of his arguments for these claims focus on their efficacy against incompatibilist views of free will. For Spinoza, the will cannot be free since it is determined by an infinite chain of external causes. And the pervasive belief in free will arises from a structural limitation of our self-knowledge: because we are aware of our actions but unaware of their causes, we suppose that we alone must be responsible for them. Yet I argue that the standard accounts miss a further element of Spinoza’s arguments that also targets compatibilist views on which free will is consistent with a specific kind of determination—namely, self-determination in accordance with our value judgments. For Spinoza, we are misled not only in supposing that our actions lack external determination but also in thinking that they are determined by our representations of value. In fact, our actions are determined by our appetites, which are blind to our value judgments. And the pervasive belief that our actions are determined by such judgments arises from the projection of value onto the objects we seek. As he denies us free will, then, Spinoza also denies us a capacity central to agency—the capacity to determine our actions in accordance with our ideas of the good. This makes his arguments against free will more consequential, and more radical, than commonly assumed

A monthly indicator of employment in the euro area: real time analysis of indirect estimates

The paper presents the results of an extensive real time analysis of alternative model-based approaches to derive a monthly indicator of employment for the euro area. In the experiment the Eurostat quarterly national accounts series of employment is temporally disaggregated using the information coming from the monthly series of unemployment. The strategy benefits of the contribution of the information set of the euro area and its 6 larger member states, as well as the split into the 6 sections of economic activity. The models under comparison include univariate regressions of the Chow and Lin' type where the euro area aggregate is directly and indirectly derived, as well as multivariate structural time series models of small and medium size. The specification in logarithms is also systematically assessed. The largest multivariate setups, up to 49 series, are estimated through the EM algorithm. Main conclusions are the following: mean revision errors of disaggregated estimates of employment are overall small; a gain is obtained when the model strategy takes into account the information by both sector and member state; the largest multivariate setups outperforms those of small size and the strategies based on classical disaggregation methods