Econometric models at the Department of the Treasury

STUDY VISIT ALBANIAN MINISTRY OF FINANCE Econometric models at the Department of the Treasury Alessandra Caretta, Enrico D Elia, Fabio Di Dio, Francesco Felici, Cecilia Frale, Libero Monteforte, Francesco Nucci, Daniele Pacifico, Cristian Tegami

Macroeconomic models and forecasting Bridge Models TRILL ITEM Econometric Model on Italy's Economy JBM OXFORD Global Economic Model Quest III - Quarterly European Simulation Tool IGEM 2

THE PROCESS Technical steps Fixing of exogenous variables Renormalization: taking into account the most recent data Run forecast with different models Set a starting baseline for the macroeconomic projections Iterate with Public finance forecasts and budget measures Include the recent developments in revenues and expenditures From the unchanged legislation to the budget measures Produce potential output estimates and structural balance indicators 3

THE PROCESS Institutional procedures A number of units are involved Main task for the unit in charge of the Planning documents Labour market unit, price unit and others contribute as well The common view of the Directorate: The Working group on modelling and forecasting The interaction with other Departments: General Accounting Department (Ragioneria Generale dello Stato) Finance Department (Dipartimento delle Politiche fiscali) Feedback from the Public Debt Management Directorate Interest expenditure model 4

TOOLS: BRIDGE MODELS Short term GDP forecast: Bridge models Short time forecast models are created for the needs of a continuous monitoring of Italian economy when the official statistics are not yet disposable. The forecasts are one/two periods ahead. The variable to predict is the Italian quarterly GDP and its components. Bridge models are a kind of models which link the high frequency indicators (monthly) to the aggregate of interest for the prediction (quarterly). The indicators are splitted in two categories: hard data (e.g.: industrial production) and soft data (e.g.: confidence indicator) 5

TOOLS: BRIDGE MODELS Short term GDP forecast: Bridge models The relationship between GDP and the monthly indicators is estimated at quarterly frequency. If the indicators are not available for all the three months of the quarter, they are projected at monthly frequency with satellite models (ARIMA). Let s the bridge equation Y=a + b1x1 + b2x2 + b3x3 with X1, X2, X3 the monthly indicators, we could have the following set of information (dashed lines indicate forecast): Quarterly Monthly Y X1 X2 X3 Q1 M1 M2 M3 M4 M5 M6 Q2 6

TOOLS: BRIDGE MODELS Bridge models: the indicators SUPPLY SIDE Value added of industry Industrial production Non industry VA Industrial production Car registrations World demand Real short term interest rate Total job positions in services DEMAND SIDE Private consumption Car registrations Industrial production of durable goods Italian stock market index Volumes of consumer expenditures in services and non-durable goods Gross fixed investment Industrial production of investment goods Car registrations Price index of raw materials Import and Export Monthly foreign trade statistics Real effective exchange rate PPI 7

TOOLS: TRILL Mixed Frequency Models After the recent financial and economic crisis there is an increasing demand for macroeconometric models able to predict the state of the economy and to capture early signals of turning points, especially with the aim of defining an effective economic policy. Classical models for short term forecast used by Institutions, such as bridge models and standard factor models, have shown some limitations, especially as regards the time aggregation and the ragged-edge data problem. 8

TOOLS: TRILL Treasury s mixed frequency model: TRILL 9

TOOLS: TRILL Treasury s mixed frequency model: TRILL 10

TOOLS: TRILL Treasury s mixed frequency model: TRILL 11

TOOLS: TRILL GDP FORECASTS: FAN CHARTS 3 2 1 Monthly GDP (yoy) 0-1 -2-3 -4-5 -6 2009 2009(4) 2009(7) 2009(10) 2010 2010(4) 2010(7) 12

TOOLS: ITEM The quarterly macroeconometric model:item 13

TOOLS: ITEM Model Utilization 14

TOOLS: ITEM The supply side in ITEM 15

TOOLS: ITEM Production factors demand 16

TOOLS: ITEM TFP and the cycle 17

TOOLS: ITEM TFP modelling 18

TOOLS: ITEM TFP modelling 19

TOOLS: ITEM Demand side 20

TOOLS: ITEM Prices and wages 21

TOOLS: ITEM The labour market 22

TOOLS: ITEM Model properties as a response to different shocks 23

TOOLS: ITEM Demand shock simulations 24

TOOLS: ITEM World trade shock: Demand side view 25

TOOLS: ITEM World trade shock: Supply side view... growth accounting approach? 26

TOOLS: JBM How to reconcile in a unique forecast: JBM 27

TOOLS: OTHER International model: Oxford Global Economic Model The core Oxford Global Model comprises forty-four country models together with headline indicators for another 33. There are also six trading blocs to complete the world coverage. The country models are fully interlinked via trade, prices, exchange rates and interest rates, with the blocs completing all the world coverage In addition, the model includes a bloc of world variables such as oil and commodity prices, world GDP and industrial production, OECD average inflation, aggregates covering the Eurozone group etc. The database is updated monthly with new historical data and a 10 years out of sample forecast section. 28

TOOLS: QUEST Quest III - Quarterly European Simulation Tool QUEST is a large-scale Dynamic Stochastic General Equilibrium (DSGE) model. It is one of the latest versions of the class of DSGE models developed by the European Commission. It is a simulation tool mainly employed to analyze the effects of structural reforms and the response of the economy to a variety of shocks. In our simulation exercises we use the version of the model calibrated for Italy, already employed by the Commission in multi-country analyses of structural reforms by the European Commission (e.g. D'Auria et al. 2009). This version of QUEST III is augmented with R&D. The endogenous mechanism of growth allows to study policies aimed at increasing the rate of knowledge creation 29

TOOLS: QUEST Quest III - Quarterly European Simulation Tool As DSGE models QUEST integrates typical Keynesian elements (such as imperfect competition and frictions in price and wage setting) into a dynamic general equilibrium framework Equilibrium conditions for the main aggregate variables are derived from the optimising behaviour of households and firms, and combined with the market clearing conditions. The calibrated (or estimated) parameters represent deep structural parameters and are thus independent of the conduct of monetary and fiscal policy (not subject to the Lucas (1976) critique) 30

TOOLS: QUEST Quest III - Quarterly European Simulation Tool By including several nominal and real frictions, modelling markets as imperfectly competitive, the model can be used to study the effects of competition-enhancing policy Distinction of employment in three skill categories (low, medium and high) allows to analyze the effects of specific labor market policies like increasing the social benefits for low-skilled workers, changing the skill composition of the labour force, promoting high skilled immigration policies and subsidizing employment of the high-skilled workers in the R&D sector Optimizing households (non liquidity constrained households) and hand-tomouth consumers (differentiation necessary to reproduce empirically relevant Keynesian effects of fiscal policy) 31

TOOLS: IGEM IGEM: A new DSGE for Italy A new DSGE for the Italian economy has now been developed to match some main features of Italy s economy (especially in the labor market) In this model we have heterogeneous workers with different contract types: two types of employees (skilled and unkilled, very high firing and hiring costs, trade unions), self-employed (high efficiency, low hiring and firing costs, no market power) and atypical (low efficiency, low hiring and firing costs, no market power, as consumers no access to financial markets) Employment and wage response to shocks will depend on the contract Except for the labor market, the model contains the main mechanisms of standard DSGE models (e.g., real and nominal frictions as in QUEST) 32

Microeconomic models for the labour market and long term dynamics EconLav Microsimulation Model T-DYMM 33

TOOLS: EconLav Static and behavioral Microsimulation model for the Italian households Microsimulation models are a powerful tools for the ex-ante evaluation of fiscal reforms and for the assessment of the distributive impact of the actual tax-benefit system. Static microsimulation models define a one-to-one mapping between gross and net individual earnings, through a precise parameterization of the Italian fiscal roles. Therefore, it is possible to evaluate a fiscal reform by studying how the individual net income changes after the implementation of a new policy. Specifically, the static model allows determining winners and losers of a given reform, something that is possible neither with macroeconomic models nor from simulation models based on the fiscal declarations held by the Ministry, which contain only few information about a given fiscal record. 34

TOOLS: EconLav EconLav: A Microsimulation model on workers EconLav is based on a representative survey of microdata, which collects detailed information on individual net incomes and wealth. The static part of the model recovers the gross earnings of each individual of the sample via an iterative procedure. The primary outcomes of the static part are: 1. A (single) gross income for each individual; 2. Net tax liabilities and their sub-components (i.e. tax deductions and tax credits), Social contributions and benefit entitlements. Secondary outcomes are: 1. Fiscal households; 2. Tax evasion; 3. Distributive and poverty indices 35

TOOLS: EconLav EconLav: A Microsimulation model on workers EconLav simulates the most important Italian taxes (and all their components): 1. Personal income tax (IRPEF) 2. Value added tax (IVA) 3. Local property tax (ICI) 4. Other minor direct and indirect taxes EconLav simulates the most important benefits: 1. Family-related benefits (ANF) 2. Additional allowance for families with more than 3 children 3. Other minor benefits (Social card, etc.) 36

TOOLS: EconLav EconLav: A Microsimulation model on workers The behavioral part of EconLav is based on a structural micro-econometric model of labor supply and allows evaluating the effect of fiscal reforms in terms of work incentives (either inner and outer margins). The econometric model is based on the assumptions of optimizing agents and a (flexible) specification of a random utility function. The model uses a discrete approach, meaning that the household chooses among a finite set of working hours in order to maximize its utility. A discrete approach implies estimating the probabilities of choosing each hours point by recovering the structural parameters of the utility function. Therefore, it is possible to compute individual labor supply elasticities numerically for each household after the estimation. 37

TOOLS: EconLav EconLav: A Microsimulation model on workers The econometric model allows for important innovation: errors in wage predictions for non workers, unobserved preference heterogeneity in the marginal utilities, fixed unobserved costs of working, joint work decisions for married couples. Both modules of EconLav are written in Stata 11 The Static and behavioral modules together give an overall assessment of the reform from the household point of view: the static part allows analyzing the distributive effects of the reform (winning and losing households), whilst the behavioral part allows studying its efficiency effects (i.e. the work incentives of each household) 38

TOOLS: T-DYMM T-DYMM: Tresury s Dynamic Microsimulation model The Model is developed inside a European project that aims at: Developing a unique and innovative dataset by matching, through individual fiscal codes, administrative longitudinal data coming from INPS (National Institute of Social Security) with survey data produced by ISTAT (National InstituteofStatistics). Developing a dynamic micro simulation model for Italy. Endowing the Ministry with a policy evaluation tool for the analysis of adequacy and sustainability of the Pension System. 39

TOOLS: T-DYMM T-DYMM: The Institutional context Italian pension system main reforms: Amato ( 92) - increase the retirement age and link the benefit to the average of the overall working life remuneration Dini ( 95): relevant change to a system based on total social contribution along the working life Tremonti - Maroni ( 04): cut the transition period for the full application of Dini ( 95), relevant change of the role of the Tfr (leaving indemnity) Budget Law 2007 - smoother transition; introduction of a score system for eligibility to retirement (combination of age and contributions years) Budget Law 2010 - Increase the age of retirement for female in the public sector so as that for male The introduction of the system based on total social contributions requires to track the career path in order to evaluate the expected benefit from the retirement 40

TOOLS: T-DYMM T-DYMM: Structure of the model The Model is bases on sequential modules that reproduce the main characteristics of the Italian society about: Demographic Labour market Pension System Taxation Demographic and social relationships are supposed to evolve over time according to ISTAT ( AWG) projections in the long run up to 2050 Dynamics is achieved essentially by updating attributes of each micro-unit for each time interval 41

New features Main features TOOLS: T-DYMM T-DYMM: The Pension Module Classification of individuals in the different pension schemes (retributivo, misto, contributivo) and funds (Fondo pensione lavoratori dipendenti, Autonomi, Gestione separata, etc.) Specification of requirements for eligibility to retirement benefits according to the reform process Computing different kinds of retirement benefits (IVS) Better prediction of future incomes/pensions thanks to the availability of occupational history (INPS) at micro level linked to socio demographic characteristics (IT SILC) Within group distributional analysis Adequacy analysis Allows to introduce migration and behavioral responses 42