Exchange Rate Regimes:
What Can We Learn from Hong
Kong and Philippines
Paul D. McNelis
Fordham University
April 2009
Relevance



Bangko Sentral ng Pilipinas is now rated in the
top ten of central banks world wide for
transparence
Since the Reform Act of 1994 BSP shifted from a
backward-looking monetary-targeting scheme to
a forward-looking inflation-targeting regime.
Hong Kong experienced acute deflation between
1998 and 2004. Yet it maintained its currency
board or hard bet to the dollar. Should HK have
changed after the onset of the Asian crisis?
The Data
Macro Time Series,
Philippines, 1995-2008
Hong Kong, 1984-2008
Interest Rates, Inflation and Terms of Trade in Philippines
GDP and Consumption
Exports and Imports in Philippines
Spending in Philippines
Financial Sector in Philippines
Hong Kong Inflation and Growth
Deposits and Loans in HK
HK: Index of Openness
HK Terms of Trade
Two Questions


When the BSP shifted policy toward
inflation targeting, did it make a big
difference, in terms of economic structural
change and welfare?
Would Hong Kong have done better if the
HKMA shifted to inflation targeting after
the Asian crisis in 1998?
Mythology: Bayesian DSGE Model

Dynamic: explains how the economy evolves over time;

Stochastic: embeds the random or unknown shocks

General Equilibrium framework: depicts the macro
(e.g., technological change, oil price volatility and
uncertainty in macroeconomic policy making) that hit the
economy.
economy as the sum of individual choices and decisions
made by firms, households, the government, and the
central bank, according to their own preferences and
views about the future.
Why?


Complements rather than replaces existing models
 ‘thick’ models because there is no one true model
The general equilibrium framework tends to reduce
inconsistencies and forces the modelers and
policymakers to think of economic linkages in a
disciplined manner.
 The micro-foundations of DSGE models make them
more suitable for policy evaluation because the
relationships embodied do not change with changes
in the policy environment.
 Key benefit: evaluation of welfare effects
Why Bayesian DSGE?







Since the late 1970’s we have shifted to Bayesian Macroeconometrics.
Equivalent to moving from the Wright Brothers to A380 fly
bye wire jets in 30 years.
There have been big structural shifts that weaken the
usefulness of historical time series. We have less data that
we think, even in developed countries like the USA.
In short, all of us have to work with limited data sets.
Using classical statistics, no scientific researcher would
claim any evidence based on tests with 40 or 100
observations.
Recognizes that we only have vague understanding of true
relationship among economic variables.
The only ‘truth’ is what we observe
 Makes use of our beliefs (“subjective priors”) and
allows the data to modify our priors (learning process)
More Reasons for Bayesian Methods








Truth is, Bayesian macro-econometrics is easier.
Easier to integrate a likelihood function numerically than it is to
maximize it—complexity, curse of dimensionality.
Bayesian inference is a way of thinking, not a basket of
methods (Sims): we go directly to the data, apply Bayes’
theorem and learn from it.
Frequentist statements are beautiful but inconsequential for
decision-makers: who cares about a 95% confidence interval
Not making use of prior information is an unforgivable sin of
omission.
Real life is full of bad or incomplete data—we have to make the
best out of bad situations.
Classical methods have a harder time jumping from point
estimates to whole distributions of policy-relevant objects.
We search for “pseudo-true parameter values”: how to use a
model as a language to express regular features of data, to tell
powerful economic histories and exert control over outcomes of
interest.
Flow Chart of Bayesian Method
Summary for Using Bayesian
Method
Structure of Model:
Conceptual Model (CM)
Agents and Decision Makers
Risks in the Conceptual Model
Actors: Household, Firms, Central
Bank, Banks, Fiscal Authority
Bayesian Macroeconometrics:
Philippines and HK
Adjusting Conceptual Model by
the Data
Philippines Structural Parameters and Volatilities
Philippines: Variance Decomposition of Inflation
Counterfactual Policy Simulation for Philippines
Hong Kong: Structural Parameters and Volatilities
Variance Decomposition for Hong
Kong
HK: Counterfactual Inflation
Targeting
Counterfactual Inflation Volatility in
HK
HK: Interest Volatility
Conclusions




Welfare improved by quite a bit when the BSP shifted
from a backward-looking money targeting regime to a
forward-looking inflation-targeting regime
Hong Kong would not have been better off if the HKMA
shifted from its currency board to inflation-targeting in
the wake of the Asian crisis or deflation.
Both countries have quite a bit of price flexibility.
For HK, foreign interest rates are very important, for
Philippines, exports and terms of trade more important.