BANCA NAŢIONALĂ A ROMÂNIEI

Outline: The forecasting process The model Further developments

BANCA NAŢIONALĂ A ROMÂNIEI The forecasting process Stages: Near term forecasts of key variables Assessment of current position of the economy over the business cycle Medium-term projections using the MAMTF (Model for Analysis and Medium-Term Forecasting)

BANCA NAŢIONALĂ A ROMÂNIEI Flow of information in the forecasting process at the National Bank of Romania Near-term models and expert forecast NTF Inflation, GDP, ex. rate etc. Assessment of initial conditions and medium-term trends Exogenous variables forecasts Trends & Gaps Medium-term (core) model Expert judgment Final medium-term forecast and risk scenarios Anticipated shocks, fiscal impulse, etc. Near-term forecast Tunes Uncertainty

BANCA NAŢIONALĂ A ROMÂNIEI Quarterly Forecasting & Decisions Schedule TimeEventDetails T-45Task Force meetingModel meeting (recalibration and other developments) - biannually T-35Task Force meetingNear-Term Forecasts – NTF (inflation, GDP, interest rates, exchange rate) and exogenous scenarios T-28Task Force meetingInitial conditions (GDP, interest rates, exchange rate gaps), medium run equilibrium conditions and exogenous variables T-22MPC meetingInitial conditions, equilibrium conditions, exogenous variables T-16Task Force meetingFinal projection meeting T-10MPC meetingForecasts and risk scenarios TInflation ReportForecasts and ‘Inflation Report’ sent to MPC T+1MPC meetingDiscussion of ‘Inflation Report’ T+7Bank Board meetingDiscussion of ‘Inflation Report’ and monetary policy decision Task Force set up to implement IT framework consists of experts from Monetary Policy and Macroeconomic Modelling Department and Research and Publications Department

BANCA NAŢIONALĂ A ROMÂNIEI The forecasting process Characteristics Based on formalized models and expert judgment Two types of modeling approaches – Estimation approach at the short-run horizon – Calibration approach at the medium-term horizon Final forecast integrates information from short-term models, medium-term model and expert judgment

BANCA NAŢIONALĂ A ROMÂNIEI The forecasting process Role of near-term forecasting –Cover short end of forecast horizon –Input for the initial conditions of the forecast Role of expert judgment –Flexibility of the NBR medium-run forecasting model allows direct incorporation of expert input –Forecasts of effects of anticipated exogenous events (e.g. change in excise duties) –Forecasts of variables not explicitly modeled (e.g. fiscal impulse) –Model forecasts can be “tuned” if unrealistic, using idiosyncratic judgments for each projection round

BANCA NAŢIONALĂ A ROMÂNIEI The forecasting process Role of medium-term model –Shapes the initial conditions of the forecast rounds –Integrates all information in a consistent way –Generates an interest rate path which can serve as policy guideline, together with projections for all relevant macroeconomic variables –Can be used to implement risk scenarios

BANCA NAŢIONALĂ A ROMÂNIEI Near-Term Forecasting Two-quarter horizon forecasts for key variables ARMAX model for core inflation and ECM for GDP components; expert judgment incorporated Economic theory as a basis of analysis, but emphasis on forecasting accuracy Used for analysis and for establishing the initial conditions for the QPM

BANCA NAŢIONALĂ A ROMÂNIEI M edium-Term Forecasting Framework 1. History of the Model Work on the NBR’s model (MAMTF) started in mid-2004 Significant progress achieved, with technical assistance support from several IMF missions and bilateral exchanges/expert visits with the Czech National Bank (MAMTF conceived in similar fashion to the CNB’s QPM)

BANCA NAŢIONALĂ A ROMÂNIEI 2. General characteristics of MAMTF Small semi-structural calibrated model with a New-Keynesian core (ST and MT non-neutrality) Consistent with achieving multi-period inflation targets Economy assumed to converge to well-defined and stable long-run equilibrium Deviations from trends reflect cyclical behavior of the economy, paramount for this type of model Model open to continuous improvement, while maintaining the core structure; in the near future, expected to be gradually replaced by a dynamic general equilibrium model Medium-Term Forecasting Framework

BANCA NAŢIONALĂ A ROMÂNIEI 2. General characteristics of MAMTF Use of satellite models for: - GDP components forecasting; the forecasts for other relevant variables (inflation, exchange rate, economic growth and so on) are exogenously imposed from the output of the MAMTF - fiscal impulse decompositions into cyclical and structural components Medium-Term Forecasting Framework

BANCA NAŢIONALĂ A ROMÂNIEI Deposit interest rates Lending interest rates Foreign interest rate Fiscal and income policies Balassa-Samuelson effect CORE2 inflation Import prices Administered and volatile prices CPI inflation Exchange rate pass-through Net exports channel Wealth and balance sheet effect Expectations Consumption/ saving decisions Consumption and investment borrowing Excess demand Exchange rate (UIP) NBR’s monetary policy rate 3. Transmission mechanism

BANCA NAŢIONALĂ A ROMÂNIEI 3. Transmission mechanism Interest rate channel - relatively slow impact and limited efficiency - monetary policy decisions transmitted through commercial banks’ deposit and lending interest rates Exchange rate channel - relatively quick through direct impact on import prices (including fuel prices and excise tax); indirect impact on aggregate demand through net export channel Expectations channel - quite significant; reflects second round effects of inflationary shocks Wealth and balance sheet channel - important due to high share of foreign currency loans

BANCA NAŢIONALĂ A ROMÂNIEI Inflation components –Core inflation determined by its structural persistence, inflation expectations, output gap, import price inflation and Balassa- Samuelson effect –Administered price inflation given by an exogenous scenario (discussions with the regulatory institutions on energy and natural gas prices) –Fuel price inflation determined by its structural persistence, international oil price, exchange rate and inflation expectations –Volatile prices inflation given by an exogenous scenario (seasonally pattern, exchange rate) 4. Model structure

BANCA NAŢIONALĂ A ROMÂNIEI Output gap determined by its own persistence, real deposit and lending interest rates gaps, real exchange rate gap and a proxy for the wealth and balance sheet effect induced by the dynamics of the exchange rate Exchange rate determined according to uncovered interest parity relationship including a risk premium; mixed backward and forward looking exchange rate expectations Monetary policy behavior described by a forward-looking policy interest rate rule that penalizes future deviations of inflation from the target, the output gap and excessive interest rate volatility Inflation expectations modeled as hybrids of backward-looking (inertial) and forward-looking (“model-consistent”) expectations 4. Model structure

BANCA NAŢIONALĂ A ROMÂNIEI Further developments Implementing a DSGE model: –Advantages over the current model: Fully structural Non linear Non-stationary steady state –Theoretical structure derived – specific features included: Exchange rate appreciation in steady state Trends in relative prices across different sectors Administered prices are included as a component of the CPI index

BANCA NAŢIONALĂ A ROMÂNIEI Further developments Draft evaluation of the model including: –Calibration –Filtering –Forecasting Short term objective: work with the current structure and provide shadow forecasts Medium term objective: further development of the model, including: –Liquidity constrained agents –Greater role for fiscal policy –Adding a financial sector block

BANCA NAŢIONALĂ A ROMÂNIEI Thank you for your attention!