Central bank research hub - Papers by Wagner P. Gaglianone
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Research hub papers by author Wagner P. GaglianoneenExpectations Anchoring Indexes for Brazil using Kalman Filter: exploring signals of inflation anchoring in the long term
https://www.bcb.gov.br/pec/wps/ingl/wps497.pdf
Central Bank of Brazil Working Papers by Fernando Nascimento de Oliveira and Wagner Piazza GaglianoneExpectations Anchoring Indexes for Brazil using Kalman Filter: exploring signals of inflation anchoring in the long term2019-08-01T00:00:07ZOur objective in this paper is to build expectations anchoring indexes for inflation in Brazil that are fundamentally driven by the monetary authority's capacity to anchor long-term inflation expectations vis-à-vis short-run inflation expectations. The expectations anchoring indexes are generated from a Kalman filter, based on a state-space model that also takes into account fiscal policy dynamics. The model's signals are constructed using inflation expectations from the Focus survey of professional forecasters, conducted by the Central Bank of Brazil, and from the swap and federal government bond markets, which convey daily information of long-term inflation expectations. Although varying across specifications, the expectations anchoring indexes that we propose tend to display a downward trajectory, more clearly in 2009, and show a recovery starting in 2016 until the end of the sample (mid-2017).Expectations Anchoring Indexes for Brazil using Kalman Filter: exploring signals of inflation anchoring in the long termFull texthttps://www.bcb.gov.br/pec/wps/ingl/wps497.pdfWagner P. GaglianoneFernando Nascimento de OliveiraFernando Nascimento de Oliveira and Wagner Piazza Gaglianone2019-08Central Bank of Brazil Working PapersIncentive-driven Inattention
https://www.bcb.gov.br/pec/wps/ingl/wps485.pdf
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone, Raffaella Giacomini, João Victor Issler and Vasiliki SkretaIncentive-driven Inattention2018-10-01T00:08:05ZThis paper establishes a link between incentives and limited attention in economic decision-making. We explore how agents' attention reacts to incentives versus the arrival of information and how each factor affects the quality of decisions. We analyze a unique survey dataset where professional forecasters decide when to update a forecast and there is a formal incentive in the form of a contest rewarding forecast accuracy. There is also a major piece of information arriving right after the contest. We empirically establish that the contest is the primary driver of updating decisions and accuracy improvements. Then, we develop and structurally estimate a rational inattention model where agents choose how much attention to allocate to updating. The estimated model fits the data and allows us to perform counterfactuals to quantify the value of the contest and how it affects updates and accuracy, as well as to establish the optimal timing of the contest.Incentive-driven InattentionFull texthttps://www.bcb.gov.br/pec/wps/ingl/wps485.pdfVasiliki SkretaWagner P. GaglianoneRaffaella GiacominiJoão Victor IsslerWagner Piazza Gaglianone, Raffaella Giacomini, João Victor Issler and Vasiliki Skreta2018-10Central Bank of Brazil Working PapersD80D83E27E37Predicting Exchange Rate Volatility in Brazil: an approach using quantile autoregression
http://www.bcb.gov.br/pec/wps/ingl/wps466.pdf
Central Bank of Brazil Working Papers by Alessandra Pasqualina Viola, Marcelo Cabus Klotzle, Antonio Carlos Figueiredo Pinto and Wagner Piazza GaglianonePredicting Exchange Rate Volatility in Brazil: an approach using quantile autoregression2017-11-07T12:30:08ZWe apply quantile regression in some of its new formulations to analyze exchange rate volatility. We use the conditional autoregressive value at risk (CAViaR) model of Engle and Manganelli (2004), which applies autoregressive functions to quantile regression to estimate volatility. That model has proved effective when compared to others for various purposes. We not only compare the forecasting power of models based on quantile regression with some models of the GARCH family, but also examine the behavior of the exchange rate along its conditional distribution and its consequent volatility. When applying CAViaR in the whole distribution, our results show differentiation of the angular coefficients for each quantile interval of the distribution for the asymmetric CAViaR model. With respect to the exchange rate volatility, we build forecasts from 60 models and use two models as reference to apply the predictive ability test of Giacomini and White (2006). The results indicate that the prediction of the asymmetric CAViaR model with quantile interval of (1, 99) is better than (or equal to) 66% of the models and worse than 34%. In turn, the other benchmark model, the GARCH (1,1), is worse than 71% of the models, better than 13%, and equal in forecasting precision to 16% of the modelsPredicting Exchange Rate Volatility in Brazil: an approach using quantile autoregressionFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps466.pdfMarcelo Cabus KlotzleAntonio Carlos Figueiredo PintoAlessandra Pasqualina ViolaWagner P. GaglianoneAlessandra Pasqualina Viola, Marcelo Cabus Klotzle, Antonio Carlos Figueiredo Pinto and Wagner Piazza Gaglianone2017-11Central Bank of Brazil Working PapersC14C22C53F31G17Estimating the Credibility of Brazilian Monetary Policy using Forward Measures and a State-Space Model
http://www.bcb.gov.br/pec/wps/ingl/wps463.pdf
Central Bank of Brazil Working Papers by Flávio de Freitas Val, Wagner Piazza Gaglianone, Marcelo Cabus Klotzle and Antonio Carlos Figueiredo PintoEstimating the Credibility of Brazilian Monetary Policy using Forward Measures and a State-Space Model2017-09-30T17:36:59ZEstimating the Credibility of Brazilian Monetary Policy using Forward Measures and a State-Space ModelFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps463.pdfFlávio de Freitas ValMarcelo Cabus KlotzleAntonio Carlos Figueiredo PintoWagner P. GaglianoneFlávio de Freitas Val, Wagner Piazza Gaglianone, Marcelo Cabus Klotzle and Antonio Carlos Figueiredo Pinto2017-09Central Bank of Brazil Working PapersE4E5Empirical Findings on Inflation Expectations in Brazil: a survey
http://www.bcb.gov.br/pec/wps/ingl/wps464.pdf
Central Bank of Brazil Working Papers by Wagner Piazza GaglianoneEmpirical Findings on Inflation Expectations in Brazil: a survey2017-09-30T17:36:59ZEmpirical Findings on Inflation Expectations in Brazil: a surveyFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps464.pdfWagner P. GaglianoneWagner Piazza Gaglianone2017-09Central Bank of Brazil Working PapersE31E37E52Evaluation of Exchange Rate Point and Density Forecasts: an application to Brazil
http://www.bcb.gov.br/pec/wps/ingl/wps446.pdf
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone and Jaqueline Terra Moura MarinsEvaluation of Exchange Rate Point and Density Forecasts: an application to Brazil2016-11-29T06:23:00ZIn this paper, we construct multi-step-ahead point and density forecasts of the exchange rate, from statistical or economic-driven approaches, using financial or macroeconomic data and using parametric or nonparametric distributions. We employ a set of statistical tools, from different strands of the literature, to identify which models work in practice, in terms of forecast accuracy across different data frequencies and forecasting horizons. We propose a novel full-density/local analysis approach to collect the many test results, and deploy a simple risk based decision rule to rank models. An empirical exercise with Brazilian daily and monthly data reveals that macro fundamentals matter when modeling the risk of exchange rate appreciation, whereas models using survey information or financial data are the best way to account for the depreciation risk. These findings have relevance for econometricians, risk managers or policymakers interested in evaluating the accuracy of competing exchange rate models.Evaluation of Exchange Rate Point and Density Forecasts: an application to BrazilAbstracthttp://www.bcb.gov.br/pec/wps/port/wp446.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps446.pdfWagner P. GaglianoneJaqueline Terra Moura MarinsWagner Piazza Gaglianone and Jaqueline Terra Moura Marins2016-11Central Bank of Brazil Working PapersC14C15C33E37F31Applying a Microfounded-Forecasting Approach to Predict Brazilian Inflation
http://www.bcb.gov.br/pec/wps/port/wp436.asp?idiom=I
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone, Joo Victor Issler and Silvia Maria MatosApplying a Microfounded-Forecasting Approach to Predict Brazilian Inflation2016-05-20T06:21:59ZIn this paper, we investigate whether combining forecasts from surveys of expectations is a helpful strategy for forecasting inflation in Brazil. We employ the FGV-IBRE Economic Tendency Survey, which consists of monthly qualitative information from approximately 2,000 consumers since 2006, and the Focus Survey of the Central Bank of Brazil, with daily forecasts since 1999 from roughly 250 registered professional forecasters. Natural candidates to win a forecast competition in the literature of surveys of expectations are the (consensus) cross-sectional average forecasts (AF). In an exploratory investigation, we first show that these forecasts are a bias ridden version of the conditional expectation of inflation. The no-bias tests are conducted for the intercept and slope using the methods in Issler and Lima (2009) and Gaglianone and Issler (2015). The results reveal interesting data features: consumers systematically overpredict inflation (by 2.01 p.p., on average), whereas market agents underpredict 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 (1984) forecast combination (GR), 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.Applying a Microfounded-Forecasting Approach to Predict Brazilian InflationAbstracthttp://www.bcb.gov.br/pec/wps/port/wp436.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps436.pdfSilvia Maria MatosJoo Victor IsslerWagner P. GaglianoneWagner Piazza Gaglianone, Joo Victor Issler and Silvia Maria Matos2016-05Central Bank of Brazil Working PapersC14C33E37Financial Conditions Indicators for Brazil
http://www.bcb.gov.br/pec/wps/port/wp435.asp?idiom=I
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone and Waldyr Dutra AreosaFinancial Conditions Indicators for Brazil2016-05-20T06:21:59ZIn this paper, we propose a methodology to construct a Financial Conditions Indicator (FCI) based on Brave and Butters (2011) and Aramonte et al. (2013). The main idea is to use a selected set of economic and financial time series and aggregate their information content into a single index that summarizes the overall financial conditions of the economy. This approach can be further employed to forecast economic activity. An empirical exercise for Brazil is provided to illustrate the methodology, in which a modified IS-type equation (substituting the interest rate by the FCI) is employed to point forecast the output gap. In addition, a standard quantile regression technique (e.g. Koenker, 2005) is used to construct density forecasts and generate fan charts of future economic activity. A risk analysis is conducted within this setup in order to compute conditional probabilities of the output growth to be above/below a given scenario.Financial Conditions Indicators for BrazilAbstracthttp://www.bcb.gov.br/pec/wps/port/wp435.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps435.pdfWagner P. GaglianoneWaldyr D. AreosaWagner Piazza Gaglianone and Waldyr Dutra Areosa2016-05Central Bank of Brazil Working PapersC53E32G10G17Local Unit Root and Inflationary Inertia in Brazil
http://www.bcb.gov.br/pec/wps/port/wp406.asp?idiom=I
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone, Osmani Teixeira de Carvalho Guilln and Francisco Marcos Rodrigues FigueiredoLocal Unit Root and Inflationary Inertia in Brazil2015-11-27T17:32:59ZIn this paper, we study the persistence of Brazilian inflation using quantile regression techniques. To characterize the inflation dynamics we employ the Quantile Autoregression model (QAR) of Koenker and Xiao (2004, 2006), where the autoregressive coefficient may assume different values in distinct quantiles, allowing testing the asymmetry hypothesis for the inflation dynamics. Furthermore, the model allows investigating the existence of a local unit root behavior, with episodes of mean reversion sufficient to ensure stationarity. In other words, the model enables one to identify locally unsustainable dynamics, but still compatible with global stationarity; and it can be reformulated in a more conventional random coefficient notation to reveal the periods of local non-stationarity. Another advantage of this technique is the estimation method, which does not require knowledge of the innovation process distribution, making the approach robust against poorly specified models. An empirical exercise with Brazilian inflation data and its components illustrates the methodology. As expected, the behavior of inflation dynamics is not uniform across different conditional quantiles. In particular, the results can be summarized as follows: (i) the dynamics is stationary for most quantiles; (ii) the process is non-stationary in the upper tail of the conditional distribution; (iii) the periods associated with local unsustainable dynamics can be related to those of increased risk aversion and higher inflation expectations; and (iv) out-of-sample forecasting exercises show that the QAR model at the median quantile level can exhibit, in some cases, lower mean squared error (MSE) compared to the random walk and AR forecasts.Local Unit Root and Inflationary Inertia in BrazilAbstracthttp://www.bcb.gov.br/pec/wps/port/wp406.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps406.pdfWagner P. GaglianoneFrancisco Marcos Rodrigues FigueiredoOsmani Teixeira de Carvalho GuillénWagner Piazza Gaglianone, Osmani Teixeira de Carvalho Guilln and Francisco Marcos Rodrigues Figueiredo2015-11Central Bank of Brazil Working PapersC14C22E31Inattention in Individual Expectations
http://www.bcb.gov.br/pec/wps/port/wp395.asp?idiom=I
Central Bank of Brazil Working Papers by Yara de Almeida Campos Cordeiro, Wagner Piazza Gaglianone and Joo Victor IsslerInattention in Individual Expectations2015-08-26T16:53:00ZThis paper investigates the expectations formation process of economic agents about inflation rate. Using the Market Expectations System of Central Bank of Brazil, we perceive that agents do not update their forecasts every period and that even agents who update disagree in their predictions. We then focus on the two most popular types of inattention models that have been discussed in the recent literature: sticky-information and noisy-information models. Estimating a hybrid model we find that, although formally fitting the Brazilian data, it happens at the cost of a much higher degree of information rigidity than observed.Inattention in Individual ExpectationsAbstracthttp://www.bcb.gov.br/pec/wps/port/wp395.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps395.pdfWagner P. GaglianoneJoo Victor IsslerYara de Almeida Campos CordeiroYara de Almeida Campos Cordeiro, Wagner Piazza Gaglianone and Joo Victor Issler2015-08Central Bank of Brazil Working PapersC14C52D84E37Microfounded Forecasting
http://www.bcb.gov.br/pec/wps/port/wp372.asp?idiom=I
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone and Joo Victor IsslerMicrofounded Forecasting2014-12-13T17:53:00ZIn this paper, we propose a microfounded framework to investigate a panel of forecasts (e.g. model-driven or survey-based) and the possibility to improve their out-of-sample forecast performance by employing a bias-correction device. Following Patton and Timmermann (2007), we theoretically justify the modeling of forecasts as function of the conditional expectation, based on the optimization problem of individual forecasters. This approach allows us to relax the standard assumption of mean squared error (MSE) loss function and, thus, to obtain optimal forecasts under more general functions. However, different from these authors, we apply our results to a panel of forecasts, in order to construct an optimal (combined) forecast. In this sense, a feasible GMM estimator is proposed to aggregate the information content of each individual forecast and optimally recover the conditional expectation. Our setup can be viewed as a generalization of the three-way forecast error decomposition of Davies and Lahiri (1995); and as an extension of the bias-corrected average forecast of Issler and Lima (2009). A real-time forecasting exercise using the Brazilian Focus survey illustrates the proposed methodology.Microfounded ForecastingAbstracthttp://www.bcb.gov.br/pec/wps/port/wp372.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps372.pdfWagner P. GaglianoneJoo Victor IsslerWagner Piazza Gaglianone and Joo Victor Issler2014-12Central Bank of Brazil Working PapersC14C33E37Risk Assessment of the Brazilian FX Rate
http://www.bcb.gov.br/pec/wps/port/wp344.asp?idiom=I
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone and Jaqueline Terra Moura MarinsRisk Assessment of the Brazilian FX Rate2014-01-13T17:53:00ZIn this paper, we construct several multi-step-ahead density forecasts for the foreign exchange (FX) rate based on statistical, financial data and economic-driven approaches. The objective is to go beyond the standard conditional mean investigation of the FX rate and (for instance) allow for asymmetric responses of covariates (e.g. financial data or economic fundamentals) in respect to exchange rate movements. We also provide a toolkit to evaluate out-of-sample density forecasts and select models for risk analysis purposes. An empirical exercise for the Brazilian FX rate is provided. Overall, the results suggest that no single model properly accounts for the entire density in all considered forecast horizons. Nonetheless, the GARCH model as well as the option-implied approach seem to be more suitable for short-run purposes (until three months), whereas the survey-based and some economic-driven models appear to be more adequate for longer horizons (such as one year).Risk Assessment of the Brazilian FX RateAbstracthttp://www.bcb.gov.br/pec/wps/port/wp344.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps344.pdfWagner P. GaglianoneJaqueline Terra Moura MarinsWagner Piazza Gaglianone and Jaqueline Terra Moura Marins2014-01Central Bank of Brazil Working PapersC14C15C53E37F31Financial Stability in Brazil
http://www.bcb.gov.br/pec/wps/ingl/wps289.pdf
Central Bank of Brazil Working Papers by Luiz A. Pereira da Silva, Adriana Soares Sales and Wagner Piazza GaglianoneFinancial Stability in Brazil2012-08-14T16:12:00ZThis paper proposes a working definition for "financial stability" related to systemic risk. Systemic risk is then measured as the probability of disruption of financial services taking into account its time and cross-sectional dimensions and several risk factors. The paper discusses the implications of this definition for Brazil in the aftermath of the recent global financial crisis. A comparison with the United States and the Euro zone is provided. In addition, systemic risk in the Brazilian credit market is investigated given its crucial role as main financial stability driver. Finally, synthetic indicators of systemic risk are used to monitor financial stability. The link between systemic risk and synthetic indicators and/or well-correlated proxies (e.g., a credit-to-GDP gap) allows the calculation of the probability of disruption of the financial system across its time dimension. Therefore, if a Financial Stability Committee and/or the prudential regulator define its tolerance level for "financial stability" as a threshold measured by this probability of disruption, it might have the capability of determining the precise moment when it should strengthen its set of adequate macroprudential responses and policies.Financial Stability in BrazilAbstracthttp://www.bcb.gov.br/pec/wps/port/wp289.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps289.pdfAdriana Soares SalesWagner P. GaglianoneLuiz A. Pereira da SilvaLuiz A. Pereira da Silva, Adriana Soares Sales and Wagner Piazza Gaglianone2012-08Central Bank of Brazil Working PapersC15E44E58G01G18G20G28Macro Stress Testing of Credit Risk Focused on the Tails
http://www.bcb.gov.br/pec/wps/ingl/wps241.pdf
Central Bank of Brazil Working Papers by Ricardo Schechtman and Wagner Piazza GaglianoneMacro Stress Testing of Credit Risk Focused on the Tails2011-05-18T17:36:59ZThis paper investigates macro stress testing of system-wide credit risk with special focus on the tails of the credit risk distributions conditional on bad macroeconomic scenarios. These tails determine the ex-post solvency probabilities derived from the scenarios. This paper estimates the macro-credit risk link by the traditional Wilson (1997) model as well as by an alternative proposed quantile regression (QR) method (Koenker and Xiao, 2002), in which the relative importance of the macro variables can vary along the credit risk distribution, conceptually incorporating uncertainty in default correlations. Stress-testing exercises on the Brazilian household sector at the one-quarter horizon indicate that unemployment rate distress produces the most harmful effect, whereas distressed inflation and distressed interest rate show higher impacts at longer periods. Determining which of the two stress-testing approaches perceives the scenarios more severely depends on the type of comparison employed. The QR approach is revealed more conservative based on a suggested comparison of vertical distances between the tails of the conditional and unconditional credit risk cumulative distributions.Macro Stress Testing of Credit Risk Focused on the TailsAbstracthttp://www.bcb.gov.br/pec/wps/port/wp241.asp?idiom=IFull texthttp://www.bcb.gov.br/pec/wps/ingl/wps241.pdfRicardo SchechtmanWagner P. GaglianoneRicardo Schechtman and Wagner Piazza Gaglianone2011-05Central Bank of Brazil Working PapersAn Econometric Contribution to the Intertemporal Approach of the Current Account
http://www.bcb.gov.br/pec/wps/port/wp178.asp?idiom=I
Central Bank of Brazil Working Papers by Wagner Piazza Gaglianone and João Victor IsslerAn Econometric Contribution to the Intertemporal Approach of the Current Account2010-06-15T17:38:00ZAn Econometric Contribution to the Intertemporal Approach of the Current AccountAbstracthttp://www.bcb.gov.br/pec/wps/port/wp178.asp?idiom=IJoão Victor IsslerWagner P. GaglianoneWagner Piazza Gaglianone and João Victor Issler2008-12Central Bank of Brazil Working PapersEvaluating Value-at-Risk Models via Quantile Regressions
http://www.bcb.gov.br/pec/wps/port/wp161.asp?idiom=I
Central Bank of Brazil Working Papers by Wagner P. Gaglianone, Luiz Renato Lima and Oliver LintonEvaluating Value-at-Risk Models via Quantile Regressions2008-04-05T17:32:59ZEvaluating Value-at-Risk Models via Quantile RegressionsAbstracthttp://www.bcb.gov.br/pec/wps/port/wp161.asp?idiom=IOliver LintonLuiz Renato LimaWagner P. GaglianoneWagner P. Gaglianone, Luiz Renato Lima and Oliver Linton2008-02Central Bank of Brazil Working Papers