Working papers results

A central problem for the game theoretic analysis of voting is that voting games
have very many Nash equilibria. In this paper, we consider a new refinement
concept for voting games that combines two ideas that appear reasonable for voting
games: First, trembling hand perfection (voters sometimes make mistakes when
casting their vote) and second, coordination of voters with similar interests. We
apply this refinement to an analysis of multicandidate elections under plurality rule
and runoff rule.
For plurality rule, we show that our refinement implies Duverger's law: In all
equilibria, (at most) two candidates receive a positive number of votes. For the case
of 3 candidates, we can completely characterize the set of equilibria. Often, there
exists a unique equilibrium satisfying our refinement; surprisingly, this is even true,
if there is no Condorcet winner. We also consider the equilibria under a runoff rule
and analyze when plurality rule and runoff rule yield different outcomes.

Building on recent work on dynamic interactive epistemology, we
extend the analysis of extensive-form psychological games (Geneakoplos,
Pearce & Stacchetti, Games and Economic Behavior, 1989) to
include conditional higher-order beliefs and enlarged domains of pay-off
functions. The approach allows modeling dynamic psychological
effects (such as sequential reciprocity, psychological forward induction,
and regret) that are ruled out when epistemic types are identified with
hierarchies of initial beliefs. We define a notion of psycholigical sequential
equilibrium, which generalizes the sequential equilibrium notion for
traditional games, for which we prove existence under mild assumptions.
Our framework also allows us to directly formulate assumptions about
"dynamic" rationality and interactive beliefs in order to explore strategic
interaction without assuming that players' beliefs are coordinated on an
equilibrium. In particular, we provide an exploration of (extensive-form)
rationalizability in psychological games.

We provide a summary updated guide for the construction, use and evaluation of
leading indicators, and an assessment of the most relevant recent developments in this
field of economic forecasting. To begin with, we analyze the problem of selecting a
target coincident variable for the leading indicators, which requires coincident indicator
selection, construction of composite coincident indexes, choice of filtering methods,
and business cycle dating procedures to transform the continous target into a binary
expansion/recession indicator. Next, we deal with criteria for choosing good leading
indicators, and simple non-model based methods to combine them into composite indexes.
Then, we examine models and methods to transform the leading indicators into
forecasts of the target variable. Finally, we consider the evaluation of the resulting
leading indicator based forecasts, and review the recent literature on the forecasting
performance of leading indicators.

Abstract

Iterated multiperiod ahead time series forecasts are made using a one-period ahead model, iterated forward for the desired number of periods, whereas direct forecasts are made using a horizon-specific estimated model, where the dependent variable is the multi-period ahead value being forecasted. Which approach is better is an empirical matter: in theory, iterated forecasts are more efficient if correctly specified, but direct forecasts are more robust to model misspecification. This paper compares empirical iterated and direct forecasts from linear univariate and bivariate models by applying simulated out-of-sample methods to 171 U.S. monthly macroeconomic time series spanning 1959 - 2002. The iterated forecasts typically outperform the direct forecasts, particularly if the models can select long lag specifications. The relative performance of the iterated forecasts improves with the forecast horizon.

We analyse the panel of the Greenbook forecasts (sample 1970-1996) and a
large panel of monthly variables for the US (sample 1970-2003) and show that
the bulk of dynamics of both the variables and their forecasts is explained by two
shocks. Moreover, a two factor model which exploits, in real time, information
on many time series to extract a two dimensional signal, produces a degree of
forecasting accuracy of the federal funds rate similar to that of the markets, and,
for output and inflation, similar to that of the Greenbook forecasts. This leads us
to conclude that the stochastic dimension of the US economy is two. We also show
that dimension two is generated by a real and nominal shock, with output mainly
driven by the real shock and inflation by the nominal shock. The implication is
that, by tracking any forecastable measure of real activity and price dynamics, the
Central Bank can track all fundamental dynamics in the economy.

How does the relationship between an investor and entrepreneur depend on the legal
system? In a double moral hazard framework, we show how optimal contracts,
corporate governance, and investor actions depend on the legal system. With better
legal protection, investors give more non-contractible support, demand more downside
protection, and exercise more governance. Investors in better legal systems develop
stronger governance and support competencies. Therefore, when investing in a different
legal systems they behave differently than local investors. We test these predictions
using a hand-collected dataset of European venture capital deals. The empirical
results confirm the predictions of the model.

Abstract

We employ Markov-switching regression methods to estimate fiscal policy feedback rules
in the U.S. for the period 1960-2002. Our approach allows to capture policy regime changes
endogenously. We reach three main conclusions. First, fiscal policy may be characterized,
according to Leeper (1991) terminology, as active from the 1960s throughout the 1980s, switching
gradually to passive in the early 1990s and switching back to active in early 2001. Second,
regime-switching fiscal rules are capable of tracking the time-series behaviour of the U.S. primary
deficit better than rules based on a constant parameter specification. Third, regime-switches in
monetary and fiscal policy rules do not exhibit any degree of synchronization. Our results are
at odds with the view that the post-war U.S. fiscal policy regime may be classified as passive at
all times, and seem to pose a challenge for the specification of the correct monetary-fiscal mix
within recent optimizing macroeconomic models considered suitable for policy analysis.

We explore the determinants of yield differentials between sovereign bonds in the Euro
area. There is a common trend in yield differentials, which is correlated with a measure
of the international risk factor. In contrast, liquidity differentials display sizeable heterogeneity
and no common factor. We present a model that predicts that yield differentials
should increase in both liquidity and risk, with an interaction term whose magnitude and
sign depends on the size of the liquidity differential with respect to the reference country.
Testing these predictions on daily data, we find that the international risk factor is consistently
priced, while liquidity differentials are priced only for a subset of countries and
their interaction with the risk factor is crucial to detect their effect.

This paper brings together two strands of the empirical macro literature:
the reduced-form evidence that the yield spread helps in forecasting output
and the structural evidence on the difficulties of estimating the effect of monetary
policy on output in an intertemporal Euler equation. We show that
including a short-term interest rate and inflation in the forecasting equation
improves the forecasting performance of the spread for future output but the
coefficients on the short rate and inflation are difficult to interpret using a
standard macroeconomic framework. A decomposition of the yield spread
into an expectations-related component and a term premium allows a better
understanding of the forecasting model. In fact, the best forecasting model for
output is obtained by considering the term premium, the short-term interest
rate and inflation as predictors. We provide a possible structural interpretation
of these results by allowing for time-varying risk aversion, linearly related
to our estimate of the term premium, in an intertemporal Euler equation for
output.

We study optimal monetary policy in two prototype economies with sticky prices and credit
market frictions. In the first economy, credit frictions apply to the financing of the capital stock,
generate acceleration in response to shocks and the financial markup (i.e., the premium on
external funds) is countercyclical and negatively correlated with the asset price. In the second
economy, credit frictions apply to the flow of investment, generate persistence, and the financial
markup is procyclical and positively correlated with the asset price. We model monetary policy
in terms of welfare-maximizing interest rate rules. The main finding of our analysis is that strict
inflation stabilization is a robust optimal monetary policy prescription. The intuition is that, in
both models, credit frictions work in the direction of dampening the cyclical behavior of inflation
relative to its credit-frictionless level. Thus neither economy, despite yielding different inflation
and investment dynamics, generates a trade-off between price and financial markup stabilization.
A corollary of this result is that reacting to asset prices does not bear any independent welfare
role in the conduct of monetary policy.