This is what the leading indicators lead

We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyse the CLI's accuracy at anticipating US output growth. We compare the predictive performance of linear, VAR extensions of smooth transition regression and switching regimes, probit, non‐parametric models and conclude that a combination of the switching regimes and non‐parametric forecasts is the best strategy at predicting both the NBER business cycle schedule and GDP growth. This confirms the usefulness of CLI, even in a real‐time analysis. Copyright © 2002 John Wiley & Sons, Ltd.     

Markov-switching dynamic factor models in real time

We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as mixed sampling frequencies and ragged-edge data. First, we evaluate the theoretical gains of using data that are available promptly for computing probabilities of recession in real time. Second, we show how to estimate the model that deals with unbalanced panels of data and mixed frequencies, and examine the benefits of this extension through several Monte Carlo simulations. Finally, we assess its empirical reliability for the computation of real-time inferences of the US business cycle, and compare it with the alternative method of forecasting the probabilities of recession from balanced panels.     

Extracting Nonlinear Signals from Several Economic Indicators

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one‐step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two‐step approach). Second, we examine the role of increasing the number of indicators. Our results suggest that one step is generally preferred to two steps, especially in the vicinity of turning points, although its gains diminish as the quality of the indicators increases. Additionally, we also obtain decreasing returns of adding more indicators with similar signal‐to‐noise ratios. Using the four constituent series of the Stock–Watson coincident index, we illustrate these results for US data. Copyright © 2014 John Wiley & Sons, Ltd.     

Markov-switching models and the unit root hypothesis in real US GDP

I find that real US GDP is better characterized as a trend stationary Markov-switching process than as having a (regime-dependent) unit root. I examine the effects of both assumptions on the analysis of business cycle features and their implications for the persistence of the dynamic response of output to a random disturbance.     

Patterns of care and burden of chronic idiopathic thrombocytopenic purpura in Brazil

Aims: Although several therapeutic options are available for chronic immune thrombocytopenic purpura (cITP), little is known about the treatment of cITP in Brazil.

Materials and methods: A multi-center, retrospective chart review, observational study was designed to describe the treatment patterns, clinical burden, resources use, and associated costs for adult patients diagnosed with cITP and treated in public and private institutions in Brazil. Patient charts were screened in reverse chronological order based on their last visit post January 1, 2012. (All costs were calculated using 1.00 USD?=?3.9571 BRL, from February 2016.)

Results: Of 340 patient charts screened, 50 patients were eligible for inclusion in the study. Single-drug therapy (prednisone, dexamethasone, or dapsone) was the most commonly used treatment, followed by combination therapies (azathioprine?+?prednisone, azathioprine?+?prednisone?+?danazol, and prednisone?+?dapsone). Splenectomy was performed in 22% of patients after at least first-line treatment. Platelet count and number of bleeding episodes at diagnosis were 31,561.1/mm³ (SD?=?±26,396.1) and 40 episodes, respectively; in first-line, 92,631.1/mm³ (SD?=?±79,955.3) and 19 episodes, respectively; in second-line, 96,950.0/mm³ (SD?=?±76,476.4) and 17 episodes, respectively. Private system patients had a higher median cost compared to public system patients (USD 17.49/month, range?=?0–2,020.77 vs USD 9.51/month, range?=?0–192.64, respectively).

Limitations: This study does not allow conclusions for causal explanations due to the cohort study design, and treatment patterns represent only the practices of physicians who have agreed to participate in the study.

Conclusions: The data indicate that available therapeutic strategies for second- and third-line therapies appear to be limited.     

A useful tool for forecasting the Euro-area business cycle phases

Based on a novel extension of existing multivariate Markov-switching models, we provide the reader with a useful tool for analyzing current business conditions and making predictions about the future state of the Euro-area economy in real time. Apart from the Industrial Production Index, we find that the European Commission Industrial Confidence Indicator, which is issued with no delay, is very useful for constructing the real-time predictions.     

Real-time forecasting US GDP from small-scale factor models

We show that the single-index dynamic factor model developed by Aruoba and Diebold (Am Econ Rev, 100:20–24, 2010) to construct an index of the US business cycle conditions is also very useful to forecast US GDP growth in real time. In addition, we adapt the model to include survey data and financial indicators. We find that our extension is unequivocally the preferred alternative to compute backcasts. In nowcasting and forecasting, our model is able to forecast growth as well as AD and better than several baseline alternatives. Finally, we show that our extension could also be used to infer the US business cycles very precisely.     

Commodity Prices and the Business Cycle in Latin America: Living and Dying by Commodities?

We analyze the dynamic interactions between commodity prices and output growth of the seven biggest Latin American exporters: Argentina, Brazil, Chile, Colombia, Mexico, Peru, and Venezuela. Using a novel definition of Markov-switching impulse response functions, we find that the response of each country's output growth to commodity price shocks is time dependent, size dependent, and sign dependent. The major evidence of asymmetries in output growth responses occurs when commodity price shocks lead to regime shifts. Thus, we conclude that the design of optimal countercyclical stabilization policies should consider that the reactions of economic activity vary considerably across business cycle regimes.     

High-growth recoveries, inventories and the Great Moderation

We present evidence about the disappearance of the high-growth recoveries from recessions with intense job creation typically observed until the eighties. This result matches the belief that recessions now have an L-shape as opposed to the old-time recessions that always had a V-shape. We also show how this change in business cycle dynamics can explain part of the Great Moderation. We postulate that these two phenomena may be due to changes in inventory management brought about by improvements in information and communications technologies.     

Mixed-frequency VAR models with Markov-switching dynamics

This paper extends the Markov-switching vector autoregressive models to accommodate both the typical lack of synchronicity that characterizes the real-time daily flow of macroeconomic information and economic indicators sampled at different frequencies. The results of the empirical application suggest that the model is able to capture the features of the NBER business cycle chronology very accurately.