study visit albanian ministry of finance econometric models … · 2015. 10. 13. · quest is a...

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

MINISTERO DELL‟ECONOMIA E DELLE FINANZE

Direzione I


Direzione I

Econometric models at the Department of the Treasury

2

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


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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

THE PROCESS


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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

THE PROCESS


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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)


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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):

Q1 Q2

M1 M2 M3 M4 M5 M6

Y

X1

X2

X3

Quarterly

Monthly


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Bridge models: the indicators

Value added of industry

Non industry VA

Industrial production

Industrial production

Car registrations

World demand

Real short term interest rate

Total job positions in services

SUPPLY SIDE 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


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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.


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Treasury’s mixed frequency model: TRILL

TOOLS: TRILL


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Treasury’s mixed frequency model: TRILL TOOLS: TRILL


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Treasury’s mixed frequency model: TRILL TOOLS: TRILL


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TOOLS: TRILL

GDP FORECASTS: FAN CHARTS

2009 2009(4) 2009(7) 2009(10) 2010 2010(4) 2010(7)

-6

-5

-4

-3

-2

-1

0

1

2

3

Monthly GDP (yoy)


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TOOLS: ITEM

The quarterly macroeconometric model:ITEM


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Model Utilization TOOLS: ITEM


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TOOLS: ITEM

The supply side in ITEM


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TOOLS: ITEM

Production factors demand


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TOOLS: ITEM

TFP and the cycle


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TOOLS: ITEM

TFP modelling


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TOOLS: ITEM

TFP modelling


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TOOLS: ITEM

Demand side


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TOOLS: ITEM

Prices and wages


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TOOLS: ITEM

The labour market


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TOOLS: ITEM

Model properties as a response to different shocks


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TOOLS: ITEM

Demand shock simulations


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TOOLS: ITEM

World trade shock: Demand side view


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TOOLS: ITEM

World trade shock: Supply side view...”growth accounting” approach?


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TOOLS: JBM

How to reconcile in a unique forecast: JBM


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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.


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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

TOOLS: QUEST



Direzione I 30


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)

TOOLS: QUEST



Direzione I 31


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-to-

mouth consumers (differentiation necessary to reproduce empirically relevant

Keynesian effects of fiscal policy)

TOOLS: QUEST



Direzione I 32

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)

TOOLS: IGEM



Direzione I 33


Microeconomic models for the labour market

and long term dynamics

EconLav Microsimulation Model

T-DYMM


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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.

TOOLS: EconLav

Static and behavioral Microsimulation model for the Italian

households


Direzione I 35


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


Direzione I 36


TOOLS: EconLav


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.)


Direzione I 37


TOOLS: EconLav


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.


Direzione I 38


TOOLS: EconLav


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)


Direzione I 39


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.


Direzione I 40


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

TOOLS: T-DYMM

T-DYMM: The Institutional context


Direzione I 41


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

TOOLS: T-DYMM

T-DYMM: Structure of the model


Direzione I 42


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

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study visit albanian ministry of finance econometric models … · 2015. 10. 13. · quest is a...

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