A Calibration Algorithm for Microelectromechanical Systems Accelerometers in Inertial Navigation Sensors

In the present work we develop an algorithm for calibrating MEMS sensors, which accounts for the nonorthogonality of the accelerometers' axis, as well as for the constant bias and scaling errors. We derive an explicit formula for computing the calibrated acceleration, given data from the sensors. We also study the error, that is caused by the nonorthogonality of the axis

Robust Tuning Datasets for Statistical Machine Translation

We explore the idea of automatically crafting a tuning dataset for Statistical Machine Translation (SMT) that makes the hyper-parameters of the SMT system more robust with respect to some specific deficiencies of the parameter tuning algorithms. This is an under-explored research direction, which can allow better parameter tuning. In this paper, we achieve this goal by selecting a subset of the available sentence pairs, which are more suitable for specific combinations of optimizers, objective functions, and evaluation measures. We demonstrate the potential of the idea with the pairwise ranking optimization (PRO) optimizer, which is known to yield too short translations. We show that the learning problem can be alleviated by tuning on a subset of the development set, selected based on sentence length. In particular, using the longest 50% of the tuning sentences, we achieve two-fold tuning speedup, and improvements in BLEU score that rival those of alternatives, which fix BLEU+1's smoothing instead.Comment: RANLP-201

Oil and the Great Moderation

We assess the extent to which the period of great U.S. macroeconomic stability since the mid-1980s can be accounted for by changes in oil shocks and the oil share in GDP. To do this we estimate a DSGE model with an oil-producing sector before and after 1984 and perform counterfactual simulations. We nest two popular explanations for the Great Moderation: (1) smaller (non-oil) real shocks; and (2) better monetary policy. We find that the reduced oil share accounted for as much as one-third of the inflation moderation and 13% of the growth moderation, while smaller oil shocks accounted for 11% of the inflation moderation and 7% of the growth moderation. This notwithstanding, better monetary policy explains the bulk of the inflation moderation, while most of the growth moderation is explained by smaller TFP shocks.Monetary policy ; Petroleum products - Prices ; Business cycles

Precautionary price stickiness

This paper proposes two models in which price stickiness arises endogenously even though firms are free to change their prices at zero physical cost. Firms are subject to idiosyncratic and aggregate shocks, and they also face a risk of making errors when they set their prices. In our first specification, firms are assumed to play a dynamic logit equilibrium, which implies that big mistakes are less likely than small ones. The second specification derives logit behavior from an assumption that precision is costly. The empirical implications of the two versions of our model are very similar. Since firms making sufficiently large errors choose to adjust, both versions generate a strong "selection effect" in response to a nominal shock that eliminates most of the monetary nonneutrality found in the Calvo model. Thus the model implies that money shocks have little impact on the real economy, as in Golosov and Lucas (2007), but fits microdata better than their specification. JEL Classification: E31, D81, C72(S, information-constrained pricing, Logit equilibrium, near rationality, s) adjustment, state-dependent pricing

Do peers see more in a paper than its authors?

Recent years have shown a gradual shift in the content of biomedical publications that is freely accessible, from titles and abstracts to full text. This has enabled new forms of automatic text analysis and has given rise to some interesting questions: How informative is the abstract compared to the full-text? What important information in the full-text is not present in the abstract? What should a good summary contain that is not already in the abstract? Do authors and peers see an article differently? We answer these questions by comparing the information content of the abstract to that in citances-sentences containing citations to that article. We contrast the important points of an article as judged by its authors versus as seen by peers. Focusing on the area of molecular interactions, we perform manual and automatic analysis, and we find that the set of all citances to a target article not only covers most information (entities, functions, experimental methods, and other biological concepts) found in its abstract, but also contains 20% more concepts. We further present a detailed summary of the differences across information types, and we examine the effects other citations and time have on the content of citances

Optimal monetary policy with state-dependent pricing

We study optimal monetary policy in a flexible state-dependent pricing framework, in which monopolistic competition and stochastic menu costs are the only distortions. We show analytically that it is optimal to commit to zero inflation in the long run. Moreover, our numerical simulations indicate that the optimal stabilization policy is "price stability". These findings represent a generalization to a state-dependent framework of the same results found for the simple Calvo model with exogenous timing of price adjustment. JEL Classification: E31optimal monetary policy, price stability, state-dependent pricing, stochastic menu costs

Distributional dynamics under smoothly state-dependent pricing

Starting from the assumption that firms are more likely to adjust their prices when doing so is more valuable, this paper analyzes monetary policy shocks in a DSGE model with firm-level heterogeneity. The model is calibrated to retail price microdata, and inflation responses are decomposed into “intensive”, “extensive”, and “selection” margins. Money growth and Taylor rule shocks both have nontrivial real effects, because the low state dependence implied by the data rules out the strong selection effect associated with fixed menu costs. The response to firm-specific shocks is gradual, though inappropriate econometrics might make it appear immediate. JEL Classification: E31, E52, D81heterogeneity, menu costs, nominal rigidity, state-dependent pricing, Taylor rule

Saudi Aramco and the oil market

We present a general equilibrium model of the global oil market, in which the oil price, oil production, and consumption, are jointly determined as outcomes of the optimizing decisions of oil importers and oil exporters. On the supply side the oil market is modelled as a dominant firm – Saudi Aramco – with competitive fringe. We establish that a dominant firm may exist as long as it enjoys a cost advantage over the fringe. We provide an expression for the optimal markup and compute the spare capacity maintained by such a firm. The model produces plausible dynamic in response to oil supply and oil demand shocks. In particular, it reproduces successfully the jump in oil output of Saudi Aramco following the output collapse of Iraq and Kuwait during the first Gulf War, explaining it as the profit-maximizing response of the dominant firm. Oil taxes and subsidies affect the oil price and welfare through their effect on the trade-off between oil production efficiency and oil market competition. JEL Classification: E32, Q43dominant firm, Oil Price, oil production, oil tax, Saudi Aramco

Learning from experience in the stock market

We study the dynamics of a Lucas-tree model with finitely lived agents who "learn from experience." Individuals update expectations by Bayesian learning based on observations from their own lifetimes. In this model, the stock price exhibits stochastic boom-and-bust fluctuations around the rational expectations equilibrium. This heterogeneous-agents economy can be approximated by a representative-agent model with constant-gain learning, where the gain parameter is related to the survival rate. JEL Classification: G12, D83, D84assett pricing, bubbles, Heterogeneous Agents, Learning from experience, OLG