chapter 12€¦ · chapter 12 monetary policy and data uncertainty. 2 learning outcomes monetary...

Chapter 12

Monetary Policy and data uncertainty

2

Learning Outcomes

➢Monetary policy & data uncertainty

➢ Data revisions Versus rationality

➢ Choice of Policy instruments

➢ Macro economic frameworks

➢ Poole’s Model

➢ Brainard’s Model

➢ Interest rate smoothing

3

12.1.1 Assumptions upto this point

Ch 12– Monetary policy and data uncertainties

▪ The central bank is assumed to know the true model of the economy,

▪ The central bank observes accurately all relevant variables timely and

accurately,

▪ The central bank knows sources and properties of economic disturbances.

4

12.1.2 Monetary policy in practice


▪ In reality there is a lot of uncertainty in the policy environment and on the

impact monetary policy actions would have

▪ Hence there is a need to be cautious when taking policy actions

▪ This calls for smooth and gradual adjustment of interest rates

5

12.2.1 Data uncertainty - Introduction


▪ Economic agents formulate their expectations based on information they

possess

▪ They use this information to formulate expectations and forecast in real time

▪ Most macroeconomic data is subject to continuous revisions.

Recent errors in fiscal estimation

5.0%

6.0%

4.4%

6.9%

5.6%

6.0%

2014E Interim Budget 2014 Treasury AR 2015F Interim Budget Finance Minister (16thNov)

FMR 2016 (New base) Budget 2016 (Newbase)

2014 2015

- Jan 2015 - May 2015 - Jan 2015 - 20th Nov - 20th Nov

7

12.2.2 Arouba (2008) - Characterizing

data revisions


▪ XP – Initial announcement

▪ Xf – Final value announced

▪ rf – Final revision which is unobserved

8

12.2.3 Reasons for revisions


Final revision = Latest observation – Initial announcement

▪ Short run revisions based on additional source data

▪ Benchmark revisions based on structural changes or updating base year.

▪ Measurement errors

Significant change in trend of GDP following the rebasing

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

2010 2011 2012 2013 2014

Old GDP (2002 Base) New GDP (2010 Base)

7.4%

6.3%

7.2%

4.5%

3.4%

9.1%

GDP estimate revisions

5.95

2.89

(1.88)

10.09

4.36

1.57

0.67

6.18

-3.0

-1.0

1.0

3.0

5.0

7.0

9.0

11.0

Total GDP Growth Agriculture Industry Services

Yo

Y G

ro

wth

, %

1Q2015 Provisional 1Q2015 Revised

Source: Deprt.. of Census and Statistics

2Q2015: 6.7%

11

12.2.4 Revisions Vs. rationality


▪ Data is said to be well behaved if revisions are done because of new data arrivals

that are not forecastable at the time of the forecast (news)

▪ If, however, future data revisions are forecast able at the time of the forecast

these are not well behaved revisions (noise).

▪ The former is consistent with rationality as agents cannot do anything about it

while the latter is inconsistent with rationality

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12.2.5 Properties of well behaved revisions


▪ Revisions should have a mean zero.

▪ Final revision should be unpredictable given the information set at the time of

the initial announcement

▪ The variance of the final revision should be small compared to the variance of

the final value of the data.

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12.2.6 Arouba (2008) Data revisions in reality


Arouba

▪ Revisions should have a mean zero. -

▪ Indicating that the initial announcements of statistical agencies are biased.

▪ Final revision should be unpredictable given the information set at the time of

the initial announcement

▪ forecast from a forecasting equation is significantly better than a naive

zero-forecast,

▪ The variance of the final revision should be small compared to the variance of

the final value of the data.

▪ Magnitudes of revisions are quite large compared to the original variables.

14Ch 12– Monetary policy and data uncertainties

12.2.6 Arouba (2008) Data revisions in reality

Findings▪ Even in advanced countries none of the conditions are satisfied

▪ The measurement problem is more important for output series than it isfor inflation or employment/unemployment series.

Reasons

▪ With technological progress it makes collecting data more harder due tothe difficulty in adjusting the quality of goods in the economy

▪ Revisions to durables consumption seem to be an important source of theproblem for the results we get regarding the revisions to real output.

15

https://www.youtube.com/watch?v=EryTjln7l2g


Video - What is GDP?

https://www.youtube.com/watch?v=EryTjln7l2g

16

12.2.6 Monetary Policy Instruments


In this context monetary authorities agree that there is broadly three policy

instruments available for the conduct of monetary policy

▪ Money Supply - Monetary policy should set the money stock while letting the

interest rate fluctuate as it will.

▪ Interest Rates - Authorities should push interest rates up in times of boom

and down in times of recession, while the money supply is allowed to fluctuate

as it will.

▪ Fence sitters – those who argue for a combination of the two

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12.2.6 Monetary Policy Instruments


Notation

- Fix real interest rate and change money supply

- Fix money supply and change real interest rate

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12.2.8 Instruments Versus outcomes


In the case where we have a deterministic macro model where there are is no

shocks and no parameter uncertainty, the choice of policy instruments does not

matter

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12.2.8 Instruments Versus outcomes


However in the presence of macro shocks (Shown by shifts in IS and LM curves)

the choice of policy instrument will matter

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12.3.1 Poole’s additive model -Introduction


Poole (1970) argued that data uncertainty can come from both the IS side as well as

the LM side

IS Side

▪ Changes in consumer tastes

▪ Government expenditures shocks

LM Side

▪ stock market crashes

▪ Financial crises

21

12.3.2 Poole’s additive model -Assumptions


▪ parameters and structure of the model are known with certainty – unrealistic

assumption

▪ IS and LM schedules are allowed to be subject to zero-mean random errors –

News errors

Model Setup

IS Curve =>

LM Curve =>

22

12.3.4 Poole’s additive model –Key Results


The objective of the Central bank is to choose a policy instrument (R or M) that

would minimize the variance of the Output.

The variance in output is caused by IS or LM shocks

▪ Setting Interest rate

▪ Setting money supply

23

12.3.5 Poole’s additive model –Policy

implications


Optimal policy responses

▪ No IS Shocks – Change money supply while keeping interest rates unchanged

▪ No LM Shocks – Change Interest rate keeping money supply fixed

24

12.3.6 Poole’s additive model –Graphs


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12.4.1 Brainard’s multiplicative model


Poole’sModel assumptions

▪ parameters of the model are known with certainty

▪ The response of target variables to policy instruments is known for certain

Brainard’s model corrects for this and takes into account the possibility that the

model may be misspecified or there may be measurement error

Model Setup

Policy Constraint =>

Monetary policy objective =>

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Key result

▪ Because of model uncertainty, the authorities will never push aggressively

enough to make average output equal to the target level y *

▪ Doing so would cause output variation to increase to an intolerable level

▪ The policy maker would rather have a stable level of output below the full

employment level than very volatile output – Brainerd Conservatism

27



Graph

28

12.5.1 Key definition – Certainty equivalence

Brainard 1967

▪ This is a situation where the response of target variables to policy instruments

are known for certain

▪ This however does not mean that there are no shocks in the system

▪ Even though the actual target variable may differ from what was expected, the

policy-maker should act on the basis of expected values as if he were certain

they would actually occur

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12.5.1 The New Keynesian Model & Parameter

uncertainty


Cold Turkey Vs. Gradualism

30


uncertainty


Key result to be proved

▪ Nomodel uncertainty-

▪ Economy behaving like Poole model

▪ set policy such that output = y* - Certainty equivalent

▪ Cold Turkey

▪ Model Uncertainty

▪ Economy behaves like Brainard model

▪ Conservative approach recommended y < y*

▪ Gradualism

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uncertainty


Model setup

▪ The economy is characterized by the 1st 2

Equations

▪ The economy is subject to non-stochastic shocks

Captured by et

▪ The objective of the Central Bank is to minimize

The loss function characterized by an inflation gap

▪ The policy instrument used is the short term

Interest rate

32


uncertainty


Additive uncertainty (Poole’smodel)

▪ The monetary authorities incorporate the fact that the E(e) = 0 into their

decision making process

Certainty equivalent result

▪ policy rate set by the policy maker is the same as the one that it would set if

there were no shocks hitting the economy.

33


uncertainty


Parameter uncertainty (Brainard’smodel)

▪ The monetary authorities are uncertain of the parameters that determine real

income

▪ The authorities can however still form expectations (albeit imperfect

expectations) about the value of the parameter b

▪ The shocks to the economy are still additive.

34


uncertainty


Key result

▪ The coefficient of variation of the parameter b captures the trade-off faced by

monetary authorities. It captures the tension between bringing inflation back

to target while the increasing uncertainty about inflation depends on the

variance of parameter b

▪ A large coefficient of variation means for a small reduction in the inflation bias

the central bank induces a large variance into future inflation.

35

12.6.1 Graphical representation


Scenario 1 – No uncertainty

36



Scenario 2 – Additive uncertainty

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Scenario 3 – Parameter uncertainty

38

12.7.1 Interest rate smoothing


▪ In light of the previous discussion, monetary authorities are more likely to

adopt a gradualist approach to monetary intervention

▪ Hence interest rates are likely to be altered in stages. There seems to exists a

positive correlation whereby changes in the funds rate to be followed by

additional changes in the same direction.

▪ Sack (2000) - The interest-rate smoothing that is observed may reflect the

cautious reaction of the Fed to uncertainty over the dynamic structure of the

economy. – Interest rate smoothing

39

12.7.2 Federal Funds rate


“The results indicate that the estimated dynamic structure of the economy can account for the

observed persistence of the directional movements in the funds rate”

40

12.7.2 Actual vs. optimal policy“The optimal policy responds more aggressively to changes in the state of the economy than

the observed policy. As a result, the funds rate path under the optimal policy is more

volatile than the actual funds rate.”


41

12.7.3 Loss functions with and without

uncertainty


42

Optimal Policy vs. Preferred action

43

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