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Papers
Presented at
the State-Space
Models, Regime Switching,
and Identification Conference,
May 10-11, 2002
- Zero-Information-Limit
Models
and Spurious Inference: The Case of ARMA with Near Cancellation by
Charles
Nelson and Richard Startz - In this paper we introduce the idea of
Zero-Information-Limit
(ZIL) models and show how that property accounts for spurious inference
in the ARMA model when there is near cancellation between AR and MA
factors.
- Measuring
the Reaction of Monetary
Policy to the Stock Market by Robert Rigobon and Brian Sack - Movements
in the stock market can have a significant impact on the macroeconomy
and
are therefore likely to be an important factor in the determination of
monetary policy. However, little is known about the magnitude of the
Federal
Reserve's reaction to the stock market. One reason is that it is
difficult
to estimate the policy reaction because of the simultaneous response of
equity prices to interest rate changes. This paper uses an
identification
technique based on the heteroskedasticity of stock market returns to
identify
the reaction of monetary policy to the stock market. The results
indicate
that monetary policy reacts significantly to stock market movements,
with
a 5% rise (fall) in the S&P 500 index increasing the likelihood of
a 25 basis point tightening (easing) by about half. This reaction is
roughly
of the magnitude that would be expected from estimates of the impact of
stock market movements on aggregate demand. Thus, it appears that the
Federal
Reserve systematically responds to stock price movements only to the
extent
warranted by their impact on the macroeconomy.
- Why Were Changes in the
Federal
Funds Rate Smaller
in the 1990s? by Arabinda Basistha and Richard Startz - In this paper,
we identify two major changes in the dynamics of the federal funds rate
in the 1990s. We model the desired rate in a two-regime setting, on
when
the Fed makes no change and the other when the Fed is moving the
desired
rate to a new level. We find that the 1990s saw longer duration in the
no-change regime as well as smaller changes in the other regime. We
show
the smaller changes were neither due to a less aggressive Fed nor due
to
lower volatility of the fundamentals. In fact, the Fed responded more
aggressively
to changes in fundamentals in the 1990s. The results also suggest that
the Fed became more forward-looking in the last decade.
- Empirical
Assessment of an Intertemporal
Option Pricing Model with Latent Variables by Rene Garcia, Richard
Luger
and Eric Renault - This paper assesses the empirical performance of an
intertemporal option pricing model with latent variables which
generalizes
the Black-Scholes and the stochastic volatility formulas. We derive a
closed-form
formula for an equilibrium model with recursive preference where the
fundamentals
follow a Markov switching process. In a simulation experiment based on
the model, we show that option prices are more informative about
preference
parameters than stock returns. When we estimate the preference
parameters
implicit in S&P 500 call option prices given our model, we find
quite
reasonable values for the coefficient of relative risk aversion and the
intertemporal elasticity of substitution. Finally, when we calibrate
the
model to minimize out-of-sample pricing errors, we obtain a performance
which is in line with a practitioners' Black and Scholes approach based
on implied volatility.
- Strategic
Asset Allocation
Under Regime Switching by Massimo Guidolin and Allan Timmermann - This
paper studies optimal asset allocation to stocks, long-term bonds and
T-bills
in the presence of regime switching in returns. We find strong evidence
that four separate regimes - characterized as crash, slow growth, bull
and bull burst states - are required to capture the joint distribution
of stock and bond returns. Optimal asset allocations vary considerably
over these states - both across bonds and stocks and among large and
small
stocks - and consequently also change over time as investors update
their
perceptions of the current state probabilities. Furthermore, while in
the
crash state investors always allocate more of their portfolio to stocks
the longer their investment horizon, the optimal allocation to stocks
actually
declines as a function of the investment horizon in bull markets.
- A Nonlinear Model of the
Business
Cycle by Edward
E. Leamer and Simon M. Potter - The usual index of leading indicators
has
constant weights on its components and is therefore implicitly premised
on the assumption that the dynamical properties of the economy remain
the
same over time and across phases of the business cycle. We explore the
possibility that the business cycle has phases, for example,
recessions,
recoveries and normal growth, each with its unique dynamics. Based on
this
possibility we develop a nonlinear model of the business cycle that
combines
a number of previous approaches. We model the state of the economy as a
latent variable with a threshold autoregression structure. In addition
to dependence on its own lags the latent variable is also determined by
observed economic and financial variables. In turn these variables are
modeled as following a nonlinear vector autoregression with regimes
defined
by the latent business cycle variable. A Markov Chain Monte Carlo
algorithm
is developed to estimate the model. Special attention is paid to
specification
of prior distributions given the large dimension of the model. We also
investigate using the business cycle chronology of the NBER to aid in
the
classification of the latent variable. The two main empirical
objectives
of the model are to provide more accurate predictions of economic
variables
particularly at turning points and to describe how the dynamics differ
across business cycle phases.
- A Markov-Switching Model of
Business Cycle Dynamics
with a Post-Recession 'Bounce-Back' Effect by Chang-Jin Kim, James
Morley,
and Jeremy Piger - This paper presents a nonlinear model of U.S. GDP
growth
dynamics that allows for post-recession "bounce-back" effect in the
level
of GDP. While a number of studies have attempted to capture such an
effect
using ad hoc recession-based dummy variable methods, we
endogenously
estimate this business cycle asymmetry using an extended version of
Hamilton's
(1989) Markov-switching model. Like Hamilton, we find model regimes
that
correspond closely to NBER-dated recession and expansions. We also find
a large "bounce-back" effect that, according to our Monte Carlo
analysis,
is statistically significant and implies a relatively small permanent
effect
of recessions.
- Smooth but not Random: The
Behavior of Aggregate Consumption
According to Cointegration Analysis with Correlated Unobserved
Components
by James Morley - This paper investigates the relationship between
aggregate
consumption and income. It applies a new approach to cointigration
analysis
that builds on Stock and Watson's (1988a) common stochastic trends
representation.
The permanent and transitory components of the cointegrated time series
are estimated directly using the Kalman filter and are allowed to be
correlated.
This approach avoids any implicit restriction that permanent income be
as smooth as consumption. Instead, permanent income appears to be
reasonably
volatile, with consumption adjusting toward it slowly over time.
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