Análisis y Pronósticos de Política Monetaria Basados en Modelos
Montevideo, Uruguay, del 26 al 30 de agosto de 2019
The course took place in the Central Bank of Uruguay. It was jointly organized by CEMLA, the IMF and the Central Bank of Uruguay. The main objectives of the course were the presentation, discussion, analysis and implementation of New Keynesian semi-structural models. Such models are part of the Forecasting and Policy Analysis System (FPAS) recommended by the IMF. It is worth mentioning that the FPAS is a scheme to think about economic policy within a central bank rather than a model itself. The FPAS uses a set of models.
The course was divided into several theoretical sessions, delivered by Santiago Acosta-Ormaechea and Jorge Restrepo, and five practical sessions, delivered by Juan Pablo Medina. Their implementation was mostly in IRIS, a package in Matlab. All instructors have worked at the IMF, albeit Juan Pablo Medina is nowadays in the Adolfo Ibañez University in Chile.
In the course, a team from each central bank delivered an economic juncture presentation, also explained the decision process for monetary policy and how they use the type of models presented in the course for policy decision purposes. If it was the case that their central banks did not use these models, they explained what steps they could take to implement them and commented on some of the possible challenges they could face.
Next, we describe some of the main points from the course. The various monetary regimes in several economies were presented. The regimes in emerging economies were underscored. The range of exchange rate regimes go from the fixed-exchange rate, dollarized economies to free floaters. While the types of regimes are balanced in terms of number of economies, when one considers the economic size of the countries that have floating exchange rates, they surpass those with a fixed-exchange rate.
The semi-structural model was presented. There was some emphasis made on the importance of a model having micro-foundations. The main rationale for doing so is to address the so-called Lucas Critique. In a nutshell, this means that models should be invariant to policy modifications. In other words, if one uses a reduced form model to make a policy recommendation, there is the possibility that the model would change as a consequence of the policy, making it useless to assess the policy itself and its full implications. In other words, structural models are invariant to policy changes. The semi-structural feature of the models, however, was given a pragmatical justification. The use of semi structural models requires much discipline.
The different monetary policy transmission channels were explained and how such channels are captured by the model. Of course, the analysis of policy transmission channels is at the heart monetary policy. Their correct identification is crucial for the formulation of a policy response. Their identification is challenging given that they can be simultaneously present and generally interact with each other.
The relevance on considering the different components of the consumer price index were underlined. In particular, the relative importance of such components depending on the economy being considered was explained. Thus, as typical question is how to respond to a commodity shock. The answer depends, among other factors, on the weight that such commodity has within the consumer basket and well as the relative importance of such a commodity as an input to the economy in question.
There were explanations on the preparation of data before using it to model, the estimation of gaps, and long-run trends for the model. The estimation of gaps and long-run trends requires judgment in particular in the case of emerging market data, given two considerations. First, the fact that there is a short history of time series in EMEs. Second, the statistical properties of such time series. Some are likely non-stationary.
The Kalman Filter was explained and how it can be used as a possible method to estimate the gap of a given variables. The Kalman Filter has been used in areas different such as in the implementation of the GPS, and it is nowadays widely used in macroeconomics, for example. The central idea is that one observes (more generally, measures) a variable with some noise. Thus, one is interested in accounting for such a measuring the variable accounting for the presence of the noise. It is important to underscore that the variable (without the noise) follows an equation of its own. Thus, the typical model in the Kalman Filter context entails an observation equation and a state-transition (hidden) model.
The calibration of models was briefly considered. In particular, the advantages and disadvantages of calibrating a model. This was done relative to other common approaches such as econometric estimation.
Much emphasis was made on the importance of examining and presenting alternative scenarios and their implications on the predictions of the model. For example, central banks provide their predictions on several variables. The well-known dot plot from the Fed is an example. It is important to underscore that such predictions might be conditioned on different assumptions. In the case of the dot plot from the Fed, such predictions are conditioned on the policy that the president providing the forecast judges as the adequate one. Similarly, there are some fan charts on macroeconomic variables that are conditioned on the expected policy rate judged optimal or on the policy rate expected by the market.
Valuable explanations were given on how to present alternative scenarios and, especially, how to present their implications. This is related to the type of scenarios used, in particular in terms of their conditionality.
The instructors shared their experience and knowledge on the implementation of some of these models and their implication on the economic policy of some of these central banks. Participants found this session particularly illustrative and the learned much about their colleagues’ experiences in a candid atmosphere.
From the coding perspective of the course, much of it was about having participants obtaining hands-on experience on executing codes in Matlab, with an emphasis on how changing some parameters made results different and, more importantly, why.
In addition, as one of the contributions of CEMLA, the paper “TIIE-28 Swaps as Risk-Adjusted Forecasts of Monetary Policy in Mexico”, was presented. It is in the spirit of the course. How introducing a model implication in a forecast can improve and provide economic content to it.
Sr. Santiago Acosta-Ormaechea, Economista, División del Hemisferio Occidental, Instituto de Capacitación (ICD)
Sr. Jorge Restrepo, Economista Principal, División del Hemisferio Occidental, ICD
Sr. Juan Pablo Medina, Experto, ICD
Sr. Santiago García-Verdú, CEMLA
Clase: Modernización de la Política Monetaria, Sistema de Análisis de Pronóstico y Política (FPAS) y Panorama General del Curso
- Marcos de Política Monetaria;
- Panorama General de los Canales de Transmisión;
- Componentes del FPAS: Bases de Datos, Monitoreo y Reporte, Proyecciones de Corto y Mediano Plazo, Comunicación y Toma de Decisiones
Clase: Introducción a un Modelo Nuevo-Keynesiano Pequeño para el Análisis de Política
- Estructura del Modelo;
- Tendencias de Largo Plazo y Estado Estacionario;
- Breve Panorama General de la Calibración
Taller: Software y Códigos del Modelo
- Paquete de Códigos;
- Funciones de Impulso-Respuesta
Clase: Componentes del IPC y sus Precios Relativos
Sr. Jorge Restrepo
- Subyacente, Alimentos y Energía: Inflación y Precios Relativos;
- Choques a los Componentes del IPC, Efectos de Primera y Segunda Ronda, Respuestas de Política;
- Choques Transitorios y Permanentes a los Precios Relativos
Clase: Regímenes Alternativos de Tipo de Cambio
- Gestión del Tipo de Cambio;
- El Tipo de Cambio como Meta Operativa;
- Intervenciones Cambiarias
Taller: Transformación e Interpretación de Datos, y Calibración del Modelo
- Preparación de Datos, Filtros Univariados;
- Condiciones Iniciales, Implicaciones para las Perspectivas de Inflación;
- Calibración Preliminar
Taller: Propiedades de los Modelos: Diferentes Regímenes de Política
- Transmisión de Choques en el Modelo
Clase: Estimación de Tendencias y Brechas a Largo Plazo
- PPP, y el Efecto Balassa-Samuelson; UIP;
- Identificación de Tendencias; Filtros Univariados: Hodrick-Prescott;
- Filtros Multivariados (Kalman)
Taller: Análisis de Tendencias y Calibración del Modelo
- Entendiendo los Filtros Univariados;
- Filtración del Modelo y Recalibración
Clase: Escenarios: Análisis de Riesgo bajo Incertidumbre
- Escenarios Macro para el Diálogo de Política;
- Proyecciones de los Escenarios Base y Alternativo
Taller: Formulación de Escenario y Análisis de Políticas
- Proyecciones Base;
- Diseño de Escenarios Alternativos;
- Contexto Externo
- Monitoreo y Reporte; Proyecciones de Corto y Mediano Plazo; Comunicación y Procesos de Decisión en los Países Participantes; Etapas para - Mejorar los Procesos
Presentación de los Proyectos Grupales
- Mensajes Principales del Curso;
- Extensiones: Calibraciones vs. Estimaciones