Applying a microfounded-forecasting approach to predict Brazilian inflation

We investigate whether combining forecasts from surveys of expectations is a helpful empirical strategy for forecasting inflation in Brazil. We employ the FGV–IBRE Economic Tendency Survey, which consists of monthly qualitative information from approximately 2000 consumers since 2006, and also the Focus Survey of the Central Bank of Brazil, with daily forecasts since 1999 from roughly 250 professional forecasters. Natural candidates to win a forecast competition in the literature of surveys of expectations are the (consensus) cross-sectional average forecasts (AF). We first show that these forecasts are a bias-ridden version of the conditional expectation of inflation using the no-bias tests proposed in Issler and Lima (J Econom 152(2):153–164, 2009) and Gaglianone and Issler (Microfounded forecasting, 2015). The results reveal interesting data features: Consumers systematically overestimate inflation (by 2.01 p.p., on average), whereas market agents underestimate it (by 0.68 p.p. over the same sample). Next, we employ a pseudo out-of-sample analysis to evaluate different forecasting methods: the AR(1) model, the Granger and Ramanathan (J Forecast 3:197–204, 1984) forecast combination (GR) technique, a Phillips-curve based method, the Capistrán and Timmermann (J Bus Econ Stat 27:428–440, 2009) combination method, the consensus forecast (AF), the bias-corrected average forecast (BCAF), and the extended BCAF. Results reveal that: (i) the MSE of the AR(1) model is higher compared to the GR (and usually lower compared to the AF); and (ii) the extended BCAF is more accurate than the BCAF, which, in turn, dominates the AF. This validates the view that the bias corrections are a useful device for forecasting using surveys. The Phillips-curve based method has a median performance in terms of MSE, and the Capistrán and Timmermann (2009) combination method fares slightly worse.     

About optimal harvesting policies for a multiple species forest without discounting

We study the optimal harvesting of a mixed forest composed of multiple species, each one having a different maturity age, where only mature trees can be harvested. We prove the existence of an optimal program and the equivalence of maximal, optimal and minimal value-loss programs. We characterize the unique golden rule stock and prove that it is sustainable, i.e., it is invariant along the optimal program. Furthermore, we also prove that along any good program from any initial condition there is convergence of the forest’s state to this sustainable state. Finally, we define a value function in the set of forest states and define a pre-order that provides an alternative way of characterizing the golden rule stock and may potentially have independent interest.     

The Cost of Living and Terror: Does Consumer Price Volatility Fuel Terrorism?

Do fluctuations of consumer prices prompt terrorist activity? A latent assumption among conflict scholars is that price volatilities for basic consumer goods produce hardships for people that increase popular grievances, damage government legitimacy, and raise the chances for terrorism. In this study, I use a series of regression estimations to test volatility in consumer price indices for energy, housing, and foods as predictors of domestic and transnational terrorism in a cross section of countries. I produce several findings. First, food price fluctuations are significant predictors of multiple measures of terrorism, while energy and housing prices are not. Second, rapid food price increases, not decreases, promote terrorist attacks. Third, the relationship between food price volatility and terrorism is most consistently present in nondemocratic and “hybrid” political regimes and in medium human development countries rather than in democracies or in countries characterized by very high or very low economic development.     

CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS

Decision makers often observe point forecasts of the same variable computed, for instance, by commercial banks, IMF and the World Bank, but the econometric models used by such institutions are frequently unknown. This paper shows how to use the information available on point forecasts to compute optimal density forecasts. Our idea builds upon the combination of point forecasts under general loss functions and unknown forecast error distributions. We use real‐time data to forecast the density of US inflation. The results indicate that the proposed method materially improves the real‐time accuracy of density forecasts vis‐à‐vis those from the (unknown) individual econometric models. Copyright © 2013 John Wiley & Sons, Ltd.     

On the Mitra–Wan forestry model: A unified analysis

We present a substantive and far-reaching generalization of the principal results in the economics of forestry, as formalized by Mitra and Wan (1986). Rather than a polarized dichotomy of linear and strictly concave, differentiable benefit (felicity) functions, we develop the theory in the context of functions that are supported at the golden-rule consumption and are not necessarily concave. Through a non-interiority condition on the set of zeroes of a resulting “discrepancy function,” we show the equivalence of finitely-maximal, maximal, minimal value-loss and optimal programs, and thereby answer questions left open by Brock and Mitra. Our synthesizing criterion is new to the capital theory literature, and in the concave setting, proves to be necessary and sufficient for the asymptotic convergence of good programs.     

Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns

In this paper we propose an innovation diffusion framework based on well-known Bass models to analyze and forecast national adoption patterns of photovoltaic installed capacity. This allows for interesting comparisons among several countries and in many cases highlights the positive effect of incentive policies in stimulating the diffusion of such a technology. In this sense, the Generalized Bass Model proves to be essential for modelling and forecasting. On this basis, we observe important differences in the investments made by countries in the PV sector and we are able to identify whether and when these investments obtained the expected results. In particular, from our analysis it turns out that in some cases incentive measures have been certainly effective in facilitating adoption, while in some others these have not been able to produce real feed-back. Moreover, our cross-country approach is able to forecast different stages in PV evolution: whereas some countries have already entered the mature stage of diffusion, others have just begun. This result may suggest various considerations about the competitive advantage of those countries that invested in alternative energy provisions. In spite of a very diversified scenario in terms of historical patterns of diffusion, we may report, as a general result, the fragile role of innovators for this special market and the dominance of imitative behaviour in adoptions.     

Is transcatheter aortic valve implantation (TAVI) a cost-effective treatment in patients who are ineligible for surgical aortic valve replacement? A systematic review of economic evaluations

Objectives:

Health Technology Assessment (HTA) agencies often undertake a review of economic evaluations of an intervention during an appraisal in order to identify published estimates of cost-effectiveness, to elicit comparisons with the results of their own model, and to support local reimbursement decision-making. The aim of this research is to determine whether Transcatheter Aortic Valve Implantation (TAVI) compared to medical management (MM) is cost-effective in patients ineligible for surgical aortic valve replacement (SAVR), across different jurisdictions and country-specific evaluations.

Methods:

A systematic review of the literature from 2007–2012 was performed in the MEDLINE, MEDLINE in-process, EMBASE, and UK NHS EED databases according to standard methods, supplemented by a search of published HTA models. All identified publications were reviewed independently by two health economists. The British Medical Journal (BMJ) 35-point checklist for economic evaluations was used to assess study reporting. To compare results, incremental cost effectiveness ratios (ICERs) were converted to 2012 dollars using purchasing power parity (PPP) techniques.

Results:

Six studies were identified representing five reimbursement jurisdictions (England/Wales, Scotland, the US, Canada, and Belgium) and different modeling techniques. The identified economic evaluations represent different willingness-to-pay thresholds, discount rates, medical costs, and healthcare systems. In addition, the model structures, time horizons, and cycle lengths varied. When adjusting for differences in currencies, the ICERs ranged from $27K–$65K per QALY gained.

Conclusions:

Despite notable differences in modeling approach, under the thresholds defined by using either the local threshold value or that recommended by the World Health Organization (WHO) threshold value, each study showed that TAVI was likely to be a cost-effective intervention for patients ineligible for SAVR.     

Modelling a dynamic market potential: A class of automata networks for diffusion of innovations

Innovation diffusion processes are generally described at aggregate level with models like the Bass Model (BM) and the Generalized Bass Model (GBM). However, the recognized importance of communication channels between agents has recently suggested the use of agent-based models, like Cellular Automata. We argue that an adoption or purchase process is nested in a communication network that evolves dynamically and indirectly generates a latent non-constant market potential affecting the adoption phase.Using Cellular Automata we propose a two-stage model of an innovation diffusion process. First we describe a communication network, an Automata Network, necessary for the “awareness” of an innovation. Then, we model a nested process depicting the proper purchase dynamics. Through a mean field approximation we propose a continuous representation of the discrete time equations derived by our nested two-stage model. This constitutes a special non-autonomous Riccati equation, not yet described in well-known international catalogues. The main results refer to the closed form solution that includes a general dynamic market potential and to the corresponding statistical analysis for identification and inference. We discuss an application to the diffusion of a new pharmaceutical drug.