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Did fiscal policymakers know what they were doing? Re-assessing fiscal policy with real time data. Kerstin Bernoth, De Nederlandsche Bank Andrew Hughes Hallett, De Nederlandsche Bank John Lewis, De Nederlandsche Bank CIRANO Workshop on Data Revision in Forecasting and Macroeconomic Policy

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did fiscal policymakers know what they were doing re assessing fiscal policy with real time data

Did fiscal policymakers know what they were doing?Re-assessing fiscal policy with real time data

Kerstin Bernoth, De Nederlandsche Bank

Andrew Hughes Hallett, De Nederlandsche Bank

John Lewis, De Nederlandsche Bank

CIRANO Workshop on Data Revision in Forecasting and Macroeconomic Policy

Montreal, 10 October 2008

introduction
Introduction

“But as is well known, the actual variables required for implementation of such a rule -potential output, nominal output, and real output-are not known with any accuracy until much later. That is, the rule does not describe a policy that the Federal Reserve could have actually followed” – Orphanides 2001

Growing literature on monetary policy rules which use real time data.

Much less attention to fiscal policy- although Orphanides’ point is just as valid

Any attempt to say what fiscal policymakers were “trying to do” needs to take account of the information they had at the time they made the decision

Monetary literature shows us that real time and ex post data can give quite different characterisations of policymakers’ behaviour

Literature on fiscal policy finds that discretionary policy is often a- (or even) procyclical. Is what policymakers intended?

Are fiscal policymakers misintentioned or malinformed?

If misintentioned that acyclicality should also show up in RT data

overview
Overview

Paper makes two key contributions

Compares fiscal policy reaction based on real time data with their ex post counterparts

Develops new technique using real time data to separate out automatic from discretionary fiscal policy

Overview of Presentation

How data problems affect fiscal policymaking in real time

A simple model of fiscal policymaking in real time

The econometric problem of ex post reaction functions

New methodology to split up automatic and discretionary policy

Dataset

Estimation results

Conclusions

the cyclicality of fiscal policy a simple example
The Cyclicality of Fiscal Policy: A simple example

Cyclically adjusted budget balance usually used to capture discretionary policy

Strip out cyclical effect of automatic stabilisers to leave discretionary component

Mismeasuring output gap not only the control variable but also the instrument (cyclically adjusted budget balance)

Simple example

Real time output gap +1%, ex post it turns out to be 2%

Automatic stabilisers are 0.5

Budget balance = 1% (both real time and ex post)

Real time: CAB=+0.5%, output gap=+1% countercyclical fiscal policy

Ex Post: CAB= 1%, output gap= 2% pro-cyclical fiscal policy

Errors reinforce each other

a first look at the data
A first look at the data

Output gap and cyclically adjusted primary balance are prone to quite large revisions

Mean revisions to output gap and capb are approximately mean zero

(Hughes Hallet et al, 2007)

a simple model of fiscal policymaking
A simple model of Fiscal Policymaking

Fiscal policy is set at time t+s (s=0 or -1)

First subscript is conventional one: year in question

Second subscript is the vintage of the data (f is ex post data)

Fiscal policymaker cannot directly set the cyclically adjusted balance

Instead they enact a set of spending and revenue plans, which under certain assumptions about the economy, yield a given (cyc adj) budget balance

Spending and revenue split up into three components

Plan:

Outturn

Discretionary expenditures which respond to the real time output gap

Do not change as estimates of output gap revised

Expenditures fixed in cash terms

(For convenience expressed as ratios to estimated pot. Output at time s)

Do not change as estimates of potential output change

Automatic expenditures which respond to the true (“ex post”) level of output

Do change in response to the true output level

a simple model of fiscal policymaking 2
A simple model of Fiscal Policymaking (2)

Output and output gap measured

incorrectly in real time

With some simple re-arrangement we can re-write the “final” primary balance as a function of ex post variables, measurement errors, and the policymakers desired parameters:

“error” in real time

potential output

ex post

output gap

“error” in real time

output gap

=zt|t+s

ex post

primary balance

econometric problem with ex post reaction functions
Econometric Problem with Ex Post Reaction Functions

Strip out cyclical component of previous equation i.e. subtract

Standard ex post reaction function is estimated as:

Mis-specified as a measure of policymakers intentions- omitted variables

Can test this formally: is either v or z significant?

If policymaker somehow has other information from which they can work out the “true” output gap, then coefficient on z should be zero

“error” in real time

output gap

“error” in real time

potential output

discretionary vs automatic
Discretionary vs Automatic

Estimate the equation:

Recall:

(-) denote purely discretionary policy

coefficient on output gap error captures discretionary policy

(β-φ) denote purely automatic policy

coefficient on ex post output gap captures sum of discretionary and automatic fiscal policy

taking the model to the data the dataset
Taking the model to the data: The dataset

Variables:

Cyclically Adjusted Balances

Actual Deficits

Primary Balances

Output Gap

GDP time series

Government debt

Source: Successive issues of OECD economic outlook (Dec 94 onwards)

14 Countries: EU15 – Luxembourg

estimation 1
Estimation (1)

We estimate the following fiscal reaction functions:

where xt|t-j = -- Debt/GDP

eyear: dummy for parliamentarian elections in year t.

“Maastricht variable” (Momigliano et al. (2004)) - captures effect of fiscal consolidation in the run-up to EMU: For countries prior 1998 with deficit of more than 3%:

Lagged dep. variable included remove (possible) serial correlation due to persistence in budgetary variables.

estimation 2
Estimation (2)

To increase number of observations: Regression (a)-(d) regressed with a panel estimation.

Necessary condition: Countries are ‘poolable’: countries follow similar fiscal reaction functions.

Poolability test: Testing whether estimated slope coefficient not significantly different between countries. H0 cannot be rejected.

Choice of vintage: Vintage t|t rather than t|t-1 data fits better for real time model: Adjustment to fiscal policy during the year (see e.g. Kalckreuth and Wolff, 2007).

Application of Blundell and Bond estimation approach: provides consistent estimates of dynamic panel models, when autoregressive parameter is large.

Output gap instrumented with its own lags to account for possible endogeneity.

results baseline case
Results: Baseline Case

(A) Ex post CAPB

gap is not significant: Discretionary policy is acyclical

(B) Ex-post data CAPB plus z and v

z and gap jointly significant: Discretionary policy is counter-cyclical

(C) Real time CAPB (a la Cimadomo)

gap is significant: Discretionary policy is counter-cyclical

(D) Real time PB (our model)

Discretionary policy is counter-cyclical

Automatic policy is counter cyclical: 0.8 - 0.56 = 0.24.

 Smaller compared to previous findings.

results extra control variables
Results: Extra Control Variables

Coefficients measuring discrectionary and automatic fiscal policy robust to specification of control variables.

Significant Maastricht-effect: governments made addit. effort to tighten fiscal policy in run-up to EMU, if deficit > 3%.

In an election years, fiscal policy is around 0.35 percentage points looser.

conclusions
Conclusions

Real time measurement error of output gap complicates fiscal policy

Ex post, fiscal policy looks acyclical, but in real time it looks countercyclical

Policymakers are misinformed rather than malintentioned

Remedies based on malintentioned diagnosis are unlikely to work

Problem doesn’t show up in real time, so watchdog may not spot it

New methodology suggests automatic stabilisers weaker than commonly thought (0.24 rather than 0.35-0.50)

Traditional methodology may wrongly attribute some counter-cyclical discretionary policy to automatic side