Volume 9, Issue 1, November 2007
The Research Agenda: Amir Yaron on Lifetime Inequality and Long Run Risks and Asset Pricing
My research is at the intersection of macroeconomics and finance. An
ongoing challenge in macroeconomics and finance is to identify the
important sources of risks that individuals and firms face and how
these in turn affect allocations and prices. These risks might
include, for example, aggregate productivity shocks, uninsurable
individual labor risk, and/or financial frictions faced by both
individuals and firms. My research identifies and measures a subset
of these risks, and analyzes how they map into observable quantities
such as consumption and prices.
Amir Yaron is Associate Professor of Finance at the Wharton School of Business, University of Pennsylvania and Faculty Research Associate at the NBER. He is interested in macrofinance, in particular studying aggregate and individual sources of risks.
Yaron's RePEc/IDEAS entry
I would like to describe two research programs which at first may appear
somewhat remote, but at least from my perspective, do ultimately
have a common intersection point. The first area departs from the
representative agent paradigm and analyzes issues such as
consumption behavior, portfolio choices, risk sharing, inequality
and equilibrium prices in environments where agents face uninsurable
idiosyncratic labor market risk. Most of this research has been with
Chris Telmer and Kjetil Storesletten. In this research line there
are two interrelated questions: (i) what are the properties of
idiosyncratic earnings shocks and (ii) what are their quantitative
ramifications for allocations, risk sharing, inequality, and
ultimately asset pricing? Since Kjetil described most of it in his
newsletter contribution, I will proceed to discuss some recent work with Mark
Huggett and Gustavo Ventura that tries to embed these risks within
models of human capital. The second area focuses on my recent work
with Ravi Bansal on aggregate models that feature Long Run Risks for
understanding the sources of fluctuations of asset prices.
Human Capital and Lifetime Inequality
Much of my current research in this area
is channeled to endogenize, to some degree, idiosyncratic earnings
risks. Currently, the common approach to modern versions of the life-cycle,
permanent-income hypothesis, is to specify earnings and wages as
exogenous random processes. This approach has dominated the
literature on consumption, savings, and wealth distribution as well
the literature on social security and income tax reform.
Our research program asks to what extent differences in individual
conditions at the start of economic life contribute to the dynamics
of earnings inequality over the life cycle. In this context, we
revisit issues regarding the quantitative importance of earnings
shocks during agents' working years for lifetime inequality and
welfare. That is, we ask to what degree is lifetime inequality due
to differences across people established early in life as opposed to
differences in luck experienced over the lifetime? Among initial
conditions, individual differences established early in life, which
ones are the most important?
Answers to these questions should shed light on several important
issues. This analysis can provide quantitative information on the
relative importance of the many policies directed at modifying or at
providing insurance for initial conditions (e.g. public education)
against those directed at shocks over the lifetime (e.g.,
unemployment insurance programs). A discussion of lifetime
inequality cannot proceed far without discussing which type of
initial condition is the most critical for determining how one fares
in life. Finally, a useful framework for answering these questions
should also be central in the analysis of a wide range of policies
considered in macroeconomics, public finance and labor economics. In
particular, many of the current policy analyses are done with an
exogenous earnings or wage processes. These policy experiments do
not change, by construction, the earnings process and thus changes
are mainly operative through various risk sharing channels. However,
when human capital is endogenous, such policy experiments can alter
the incentives to acquire human capital and therefore change the
earnings profiles themselves, and potentially result in large
In Huggett, Ventura and Yaron (2006), we first take an extreme view,
abstract from idiosyncratic risk altogether, and ask whether the
process for endogenous accumulation of human capital can induce
sufficient transition dynamics over the life-cycle to allow such a
model to match salient features of the earnings distribution.
We focus on the age profiles for the mean, Gini and skewness of earnings.
Surprisingly, the richness of these dynamics can accommodate many
features of the earnings distribution. We show that a benchmark
human capital model (the Ben-Porath (1967) model) in which agents are different in learning ability and initial human capital can replicate these earning properties.
The distributions for initial human capital and ability to learn
have the property that learning ability must substantively differ
across agents and that learning ability and initial human capital are positively correlated.
The model implies, however, that over time both individual earnings
levels and growth rates are strongly positively autocorrelated.
Evidence from US data shows that earnings growth rates are
negatively correlated. This, in conjunction with related evidence on
consumption inequality as in
Storesletten, Telmer and Yaron (2004) and
Deaton and Paxson (1994), suggests an important role for
persistent idiosyncratic shocks. Moreover, based on the human
capital view, observed earnings fluctuations are a mixture of
exogenous shocks and investment in human capital--making inference
regarding earnings shocks difficult.
To address these issues in Huggett, Ventura and Yaron (2007),
we extend the human capital
model to include idiosyncratic shocks to human capital. In order to
identify the shocks empirically, we exploit the fact that toward the
end of (working) life agents no longer invest in human capital and
thus first differences in wages will reveal the shock process. Given
this process and observed initial conditions for wealth, we solve
for the best (joint log-normal) distribution for learning ability
and initial human capital that allows the model to fit various
earnings facts. The model suggests that most (around 60 to 70%) of
the variation in life time utility (or wealth) are attributable to
initial conditions as opposed to shocks. Among initial conditions,
variation in initial human capital is substantially more important
than variation in learning ability or initial wealth for determining
how an agent fares in life.
In the model there are two offsetting forces which together account
for the increase in earnings dispersion. One force is that agents
differ in learning ability. Agents with higher learning ability have
steeper mean earnings profiles than low ability agents, other things
equal. This mechanism is supported by the literature, see
Card (1999), on the shape of the mean age-earnings profiles
by years of education. It is also supported by the work of
Lillard and Weiss (1979), Baker (1997) and closely
related to the recent work of Guvenen (2007). These authors
estimate a statistical model of earnings and find important
permanent differences in individual earnings growth rates. The other
force is that agents differ in idiosyncratic human capital shocks
received over the lifetime.
Future work entails important analysis both in terms of data and
models. One important issue stems from the fact that some of the
known stylized facts have 'changed'. For example, the quantitative
magnitude of the rise in consumption inequality, found say in
Deaton and Paxson (1994) and which is so important for
interpreting the role of shocks and market insurance, seems to have
diminished with the recent samples. These results seem to also be
more sensitive to whether one treats the data using cohort or time
effects. There are several important efforts trying to address these
issues by contemplating various structural changes, data collection
issues, etc. (see Heathcote, Storesletten and Violante (2004)
and Attanasio, Battistin and Ichimura (2004)). These are
important measurement issues as they clearly affect our inference
and modeling choices.
We are currently working on several extensions and applications of
our framework. In particular, we are investigating issues related to
taxation and social insurance in the presence of human capital
acquisition and idiosyncratic risk. The analysis should reveal
whether the explicit consideration of human capital accumulation is
quantitatively important for some policy experiment and whether the
conclusions are different from those that arise using exogenous wage
or earnings framework. To get a better handle on the
shocks to human capital it would be interesting to link our
framework more directly to the literature on unemployment durations--the latter presumably affects the degree to which human
capital depreciates. This can be a fruitful ground for better
understanding the mapping from job loss duration and shocks to human
capital. Another potentially important area is distinguishing
between general human capital and schooling. We plan to extend our
framework to allow for discrete schooling choice early in life. This
extension can be important for differentiating the effects of
skilled and unskilled exposure to these human capital shocks.
Finally, in the background, many models assume agents (and their
employer) know their ability type. It can be potentially interesting
to extend our framework to allow for learning. Recent work by
Guvenen and Smith (2007) seems to indicate that this can be an
interesting channel for quantitatively interpreting the data.
Long Run Risks
A fundamental question both macro and finance academics seek to
understand is what causes asset prices to fluctuate and what risks
warrant significant risk premia? In general, fluctuations in asset
prices can be attributed either to changes in costs of capital or to
changes in expected cash flows. However, the conventional wisdom
about cash flows, be it consumption growth or dividends growth, is
that for all practical purposes they are i.i.d. This view
leaves fluctuations in expected cash flows no role in explaining
asset prices. As a result, much attention in this literature has
focused on changes in the costs of capital. In general equilibrium,
such changes are often accommodated by fluctuations in risk
In Bansal and Yaron (2004), we challenge this
view by refocusing attention to cash flows. We model consumption and
dividend growth rates as containing (i) a small persistent expected
growth rate component, and (ii) fluctuating volatility--which
captures time-varying economic uncertainty and in the presence of
the Epstein and Zin (1989) preferences leads to fluctuations in
costs of capital/expected returns. We show that this specification
for consumption and dividends is consistent with observed annual
consumption and dividend data. Our model captures the intuition that
financial markets dislike economic uncertainty, and fluctuating
growth prospects are important for asset valuations. Shocks to
expected growth alter expectations about future economic growth not
only for short horizons but also for the very long run. Agents
demand large equity risk premia as they fear that a reduction in
economic growth prospects or a rise in economic uncertainty will
lower equilibrium consumption, wealth and asset prices. This is
distinct from habits-based models in which almost all asset price
fluctuations are attributable to time variation in risk premium due
to altering risk aversion. Hence, in these models fluctuations in
corporate profits (or dividends) do not play a significant role in
determining asset prices.
The Long Run Risks model relies on generalized recursive preferences
(e.g., Kreps and Porteus (1978), Epstein and Zin (1989), Weil (1989)),
which provide a
separate role for relative risk aversion and the intertemporal
elasticity of substitution (IES). In this framework, a restriction
on preferences arises if agents are to explicitly fear (in the sense
of lowering prices) adverse movements in expected growth and
economic volatility. The restriction is that the IES be greater than
one and that agents prefer early resolution of uncertainty (the risk
aversion be larger than the reciprocal of the IES). Risk premia in
this model are determined by three distinct sources of risk:
transient, long-run, and volatility (economic uncertainty) risks,
whereas in the standard time separable CRRA preferences the latter
two risks simply have zero market prices of risk.
We use econometric techniques to show that the cash flow process,
which contains in addition to an i.i.d component a small
persistent component, is essentially indistinguishable in finite
samples from a pure i.i.d process. Nonetheless, this process
results in profoundly different asset pricing implications.
Although, the innovations in expected cash flows are relatively
small, it is their long-lasting feature that requires risk
compensation and leads to large reaction in the price-dividend ratio
and ex-post equity return and, consequently, the risk-premium on the
asset. We show that risks related to varying growth prospects and
fluctuating economic uncertainty can indeed quantitatively justify
the observed equity premium, the level of the risk free rate, and
the ex-post volatilities of the market return, risk free rate and
the price-dividend ratio. The model implies time varying risk premia
and, as in the data, that market return volatility is stochastic.
The Long Run Risks framework has already received quite a bit of
attention and has been a useful framework for thinking about asset
pricing. There is an extensive ongoing body of research examining
various extensions to other assets markets. For example, to further
evaluate the empirical implications of long-run risks model,
Bansal, Dittmar and Lundblad (2005) measure cash-flows of
different portfolios (value, growth, size, etc.) and show that
differences in magnitude of the long-run response of cash-flows to
consumption shocks can empirically account for differences in
expected returns across assets. They show how to use cointegration
to measure long-run consumption risks in cash flows, and document,
that this goes quite a long way in explaining differences in mean
returns. There is an ongoing discussion on understanding the
precision of various approaches to measuring the long-run cash flow
responses to consumption shocks, see for example
Hansen, Heaton and Li (2005).
In a more recent work, Bansal, Kiku and Yaron (2007),
directly on a relatively rich menu of asset returns and show how to
estimate the long-run risks model using the more standard Euler
equation-GMM based approach such as in
Hansen and Singleton (1982). The difficulty in applying the
standard GMM techniques is that the intertemporal marginal rate of
substitution contains the unobservable return on wealth. We
circumvent this by exploiting the dynamics of aggregate consumption
growth and the model's Euler restrictions to solve for the
unobserved return on the claim over the future consumption stream.
We show that quantitatively the long-run risks model can
successfully account for the market, value, and size sorted returns.
Although we initially find low estimates of the IES and large risk
aversion coefficients, we show via simulations that finite sample
and time-averaging effects (the latter emanating from averaged
annual data but monthly decision interval) lead to a downward bias
in the IES estimate and a upward bias of the risk aversion
coefficient--reconciling many of the previous findings in this
literature. After accounting for these effects, the model generates
many of the appropriate asset pricing results at reasonable values
of risk aversion and IES. The empirical evidence in this paper
highlights, again, the importance of low-frequency movements and
time-varying uncertainty in economic growth for understanding
risk-return trade-offs in financial markets.
One of the important channels of the Long-Run Risks model is the
role of time variation in cash flow volatility. There is ample
evidence of time variation in market returns at least at high
frequency and also to some extent over business cycles. A question
that naturally arises is whether there is a detectable component for
these effects in consumption, dividends and earnings, the data that
researchers in this area often use. In
Bansal, Khatchatrian and Yaron (2005),
we provide extensive empirical evidence supporting this
channel of fluctuating economic uncertainty. We use data from the
U.S. and several other countries to show that economic uncertainty
(measured by consumption and earnings volatility) sharply predicts
and is predicted by price-dividend and price-earnings ratios. Our
evidence shows that a rise in economic uncertainty leads to a fall
in asset prices, and that high valuation ratios predict low
subsequent economic uncertainty. This latter finding is consistent
with a long-lasting uncertainty channel, but is inconsistent with
the standard formulation in which consumption growth is i.i.d
Views regarding the sources of variation of asset markets are often
shaped via a decomposition of the variation of the price-dividend
ratio. Interpreting this decomposition is intimately related to
whether one views asset market fluctuations as driven by variation
in discount rates or by changes in expected cash flows. This view
turns out to depend on the type of cash flow one chooses to focus on.
For example, in Bansal, Khatchatrian and Yaron (2005) we show
that there is a strong positive relation between aggregate earnings
growth and asset prices. This evidence suggests that broadening the
notion of cash flows provides a different view about the sources of
asset price fluctuations, and that the focus on dividends (which are
somewhat less predictable) may have led researchers to dismiss the
cash flow channel prematurely. Furthermore, in
Bansal and Yaron (2006), we show that the price-dividend ratio
decomposition critically hinges on whether one analyzes price and
dividend per share or total dividend and total market capitalization.
Broadly, the difference between these two cash flow measures captures
equity investment from the non financial corporate sector to the
corporate sector via issuances, and payments by the non-financial
corporate sector to the private sector via repurchases. While there
is no theoretical reason to impose cointegration between dividend
per-share and consumption or output, macroeconomic restrictions
suggest that total payouts ought to be cointegrated with
consumption. This is indeed the case in the data, and estimation
which imposes this restriction for aggregate payouts seems to
support a view in which about 50% of the variation in valuation
ratios are attributable to expected growth and the remaining to
discount rates. Furthermore, a variant of the Long Run Risk model
that imposes this cointegration restriction generates comparable
results. These issues highlight the importance of examining and
modeling cash flow dynamics. For example, models focusing on
production, which typically impose cointegation, have the difficult
task of endogenously generating the joint dynamics of consumption
and dividends--features that are so critical for the purpose of
asset pricing evaluations. Related issues arise when thinking about
how cash flows of firms, sectors, portfolios and aggregate quantities
relate. Future research will clearly have to explore these
dimensions of the data and models will need to address them in a
more consistent manner.
Long Run Risks is an exciting area and there are now several
researchers and papers that use features of the Long Run Risks
framework or extend it to address various issues and markets. These
include research on foreign exchange markets, the term structure of
interest rates, credit spreads, derivative markets, the recent rise
in the stock market and the great moderation, cost of business
cycles, cointegration and portfolio choice, the value premium,
production economies with long run risks, heterogeneous agents,
robust control and learning, inflation risk premia, and housing. I
believe these lines of research will remain fruitful and contribute
toward our understanding of economic risks.
Attanasio, Orazio, Erich Battistin and Hidehiko Ichimura, 2004, What Really Happened To Consumption Inequality in the U.S.?
, Working paper, NBER 10038.
Baker, Michael, 1997, Growth-rate Heterogeneity and the Covariance Structure of
Life Cycle Earnings
, Journal of Labor Economics
Bansal, Ravi, Robert F. Dittmar and Christian Lundblad, 2005, Consumption, Dividends, and the Cross-section of Equity Returns
, Journal of Finance
Bansal, Ravi, Varoujan Khatchatrian and Amir Yaron, 2005, Interpretable Asset
, European Economic Review
Bansal, Ravi, Dana Kiku and Amir Yaron, 2007, Risks for the Long Run: Estimation
, Working paper, University of Pennsylvania.
Bansal, Ravi, and Amir Yaron, 2004, Risks for the Long Run: A potential Resolution
of Asset Pricing Puzzles
, Journal of Finance
Bansal, Ravi, and Amir Yaron, 2006, The Asset Pricing-Macro Nexus and Return-Cash
, Working paper, The Wharton School, University of Pennsylvania.
Ben-Porath, Yoram, 1967, The Production of Human Capital and the Life Cycle of
Earnings, Journal of Political Economy
Card, David, 1999, The Causal Effect of Education on Earnings
, In Orley Ashenfelter and David Card, editors, Handbook of Labor Economics
, Volume 3, (Elsevier,
Deaton, Angus, and Christina Paxson, 1994, Intertemporal Choice and Inequality
Journal of Political Economy
Epstein, Larry G., and Stanley E. Zin, 1989, Substitution, Risk Aversion, and the
Intertemporal Behavior of Consumption and Asset Returns: A Theoretical Framework
Guvenen, Fatih, 2007, Learning your Earning: Are Labor Income Shocks Really Very
, American Economic Review
Guvenen, Fatih, and Anthony Smith, 2007, Inferring Labor Income Risk from Economic Choices: An Indirect Inference Approach, Working paper, Yale University.
Hansen, Lars Peter, John Heaton and Nan Li, 2005, Consumption Strikes back?
paper, NBER, 11476.
Hansen, Lars Peter, and Kenneth Singleton, 1982, Generalized Instrumental Variables
Estimation of Nonlinear Rational Expectations Models
Heathcote, Jonathan, Kjetil Storesletten and Gianluca Violante, 2004, The Cross-Sectional Implications of Rising Wage Inequality in the United States
, Discussion paper, CEPR, 4296.
Huggett, Mark, Gustavo Ventura and Amir Yaron, 2006, Human Capital and Earnings Distribution Dynamics
, Journal of Monetary Economics
Huggett, Mark, Gustavo Ventura and Amir Yaron, 2007, Sources of Lifetime Inequality
, Working paper, NBER, 13224.
Kreps, David, and Evan Porteus, 1978, Temporal Resolution of Uncertainty and
Dynamic Choice Theory
Lillard, L., and Yoram Weiss, 1979, Components of Variation in Panel Earnings Data:
American Scientists 1960-70
Storesletten, Kjetil, 2003, The Research Agenda: Kjetil Storesletten on Inequality in Macroeconomics
Storesletten, Kjetil, Chris I. Telmer and Amir Yaron, 2004, Consumption and Risk
Sharing Over the Life Cycle
, Journal of Monetary Economics
Weil, Philippe, 1989, The Equity Premium Puzzle and the Risk-free Rate Puzzle
Journal of Monetary Economics
EconomicDynamics Interviews Timothy Kehoe and Edward Prescott on Great Depressions
Timothy Kehoe is the Distinguished McKnight University Professor at the University of Minnesota and Adviser of the Federal Reserve Bank of Minneapolis.
Edward Prescott is the W. P. Carey Chaired Professor of Economics at Arizona State University and Senior Monetary Adviser at the Federal Reserve Bank of Minneapolis. Both are interested in the theory and the application of general equilibrium models.
Kehoe's RePEc/IDEAS entry
Prescott's RePEc/IDEAS entry
EconomicDynamics: Depressions have recently received a lot of interest, witness the special issue of the Review of Economic Dynamics in 2002 and now the book you have edited. Why this sudden interest?
Timothy Kehoe, Edward Prescott: In 1999 Hal Cole and Lee Ohanian published a paper in the Quarterly Review of the Federal Reserve Bank of Minneapolis that broke a long standing taboo. They analyzed the U.S. Great Depression using the neoclassical growth model. What they found was fascinating. Productivity recovered by 1935, but labor supply remained depressed by 25 percent and did not begin to recover until 1939. An important question is why. Another important question, of course, is why productivity fell so sharply starting in 1929.
The Cole and Ohanian study motivated us to organize aa conference at Minneapolis Fed in 2000 at which people presented analyses of great depressions in other countries using the neoclassical growth model. Six of the studies were from the interwar period and the other three from the postwar period. We encouraged the authors to work more on their papers and to submit revised versions to RED. With the help of the graduate students in our workshop, we edited a special volume of RED with these studies. Just this past year, we have published a book with revised versions of Hal and Lee's original article and the articles in the RED volume, as well as six other studies.
The success of this enterprise is leading to a shift from studying small business cycle fluctuations to the study of big movements in the output relative to trend. With this shift, we have learned a lot. The studies in the RED volume and in the new book have identified important puzzles. The central message is that there is an overwhelming need for a theory of how policy arrangements affect TFP.
ED: The neoclassical growth model has been used extensively to study business
cycles. Lucas described business cycles as being all alike, and thus the
quest was for a single model of the business cycle. Are all depressions
alike? If not, can we still use the same model for all?
TK, EP: The real business cycle model developed by Finn Kydland and Ed has been
successful in capturing the regularities in business cycle fluctuations,
not just in the United States, but in other countries. Business cycles
are small deviations from balanced growth, driven largely by small
persistent changes in TFP. In real business cycle theory, fluctuations in
TFP are modeled as a Markov process.
Great depressions are large deviations from balanced growth. If we look
at a graph of U.S. real GDP per working age person over the past century
or more, we see small fluctuations around a path with growth of two
percent per year. The Great Depression of the 1930s and the subsequent
build up during World War II jump out of the graph as being something
We have found that great depressions are like business cycle downturns
in that they are driven mostly by drops in TFP, but these drops are very
large and often prolonged. Great depressions are not alike, and they
are not like business cycles, but we have found that the general
equilibrium growth model is very useful for identifying regularities and
puzzles. In some depressions, TFP drives everything, and we need to
identify the factors the cause the large and prolonged drop in TFP. In
other depressions, such as the U.S. and German great depressions of the
1930s, labor inputs are depressed more or longer than the model
predicts, and we need to identify the factors that disrupted the labor
ED: Thus, depressions can be characterized by deeper and more prolonged
deviations from trend than usual business cycles. But the reasons for these
deviations vary, contrarily to business cycles. Each depression is then a
case study. How can the validity of such a case study be established? In
particular, to use statistical terms, how can the lack of degrees of freedom
and out of sample testing be overcome?
TK, EP: In fact, we think that it is the other way around: Our study of depressions
has been so fruitful that we think that it is useful for studying the
business cycle. We have found that we can use the methodology that we have
developed to study the factors that gave rise to the relatively small
movements that we call business cycles. Treating populations, tax rates,
productivity paths, and other factors as exogenous, we are determining which
of these factors give rise to particular small depressions and booms.
We are finding deviations from the theory and puzzles. One particularly
interesting deviation from theory was the behavior of the U.S. economy in
the 1990s. Another is the behavior of the Spanish economy from 1975 to
1985. Ed is studying the first with Ellen McGrattan, and Tim is studying
the second with Juan Carlos Conesa. Even though these episodes are not
great depressions, we are using the same methodology as in the great
Macro has progressed beyond accounting for the statistical properties called
business cycle fluctuations to predicting the time path of the economy given
the paths of the exogenous variables. The great depression methodology
points to what is causing the problems in a particular economy, whether it be productivity, labor
market distortions, credit market problems, and so on. This is progress.
ED: What is the specific contribution of the volume you edited in the study of
Great Depressions of the Twentieth Century has 15 studies that
involve the work of 26 researchers and use the same basic theoretical
framework to organize the data and interpret the behavior of the
different economies during depressions. The list of collaborators on
this project is an impressive list of economists from all over the
world. Having this set of great depression studies that use the same
theoretical framework in a single volume should be valuable for
researchers, especially graduate students, in deciding which
conjectures to explore. We hope and expect that this volume will
stimulate research on important problems in macroeconomics.
Great depressions are not things of the past. They have occurred
recently in Latin America and in New Zealand and Switzerland. Unless
we understand their causes, we cannot rule out great depressions
Cole, Harold L., and Lee E. Ohanian, 1999,
The Great Depression in the United States from a Neoclassical Perspective
Federal Reserve Bank of Minneapolis, issue Winter, 2-24.
Kehoe, Timothy J., and Edward C. Prescott, 2002,
Great Depressions of the Twentieth Century
Review of Economic Dynamics,
Kehoe, Timothy J., and Edward C. Prescott (editors), 2007, Great Depressions of the Twentieth Century
, Federal Reserve Bank of Minneapolis.
Kydland, Finn E., and Edward C. Prescott, 1982,
Time to Build and Aggregate Fluctuations
, 50(6), 1345-1370.
McGrattan, Ellen R., and Edward C. Prescott, 2007,
Unmeasured Investment and the Puzzling U.S. Boom in the 1990s
369, Federal Reserve Bank of Minneapolis.
Conesa, Juan Carlos, Timothy J. Kehoe and Kim J. Ruhl, 2007.
Modeling Great Depressions: The Depression in Finland in the 1990s
NBER Working Paper
Society for Economic Dynamics: Letter from the President
Dear SED Members and Friends:
We had a terrific meeting in Prague. The program chairs Ricardo Lagos and
Noah Williams put together an outstanding intellectual program, including
great plenary talks by Dilip Abreu, Robert Shimer and Ken Wolpin. The local
organizers Radim Bohacek and Michal Kejak created a great environment,
culminating in an absolutely marvelous dinner the final night of the
Our upcoming meetings will take place in Cambridge, MA July 10-12, 2008,
hosted by MIT. Our co-chairs George-Marios Angeletos, Ariel Burstein, Mikail
Golosov, and Christian Hellwig are hard at work putting things together, and
we already have lined up a great set of plenary speakers: James Poterba,
José Scheinkman and Per Krusell. Details as they are available, including
the submission deadline, will be found at
http://www.economicdynamics.org/sed2008.htm. I look forward to seeing all of
you in Cambridge.
For 2009, we plan to hold the meetings in Istanbul. Istanbul is a great
city, and I expect we will put together our usual strong scientific program.
I would also like to highlight the contributions of our officers. Our
Treasurer is Ellen McGrattan - and as a consequence of her efforts our
finances remain in very good shape. Our newly installed Secretary is
Christian Zimmermann - who among his many other efforts on our behalf, edits
Finally the Review of Economic Dynamics continues its strong upward path
under the leadership of Narayana Kocherlakota, and we are hopeful that
Elsevier will increase their contribution towards the journal. One issue of
some importance is the credentialing of the journal. If you know about
institutions that maintain lists or ranking of journals to whom we might
usefully provide information about why the Review is a first rate journal,
drop me an email.
David Levine, President
Society for Economic Dynamics
Society for Economic Dynamics: 2008 Meetings Call for Papers
The 19th annual meetings of the Society for Economic Dynamics will be held
July 10-12, 2008 in Cambridge, MA. The plenary speakers are Jim
Poterba (MIT), José
Scheinkman (Princeton), and Per Krusell (Princeton). The program co-chairs
are George-Marios Angeletos (MIT), Ariel Burstein (UCLA), Mike Golosov
(MIT), and Christian Hellwig (UCLA).
The program will be made up from a selection of invited and submitted
papers. The Society now welcomes submissions for the Cambridge program.
Submissions may be from any area in economics. A program committee will
select the papers for the conference. The deadline for submissions is
February 15, 2008. Further details and instructions on how to submit a
paper are available at
Review: Money, Interest, and Policy
Money, Interest, and Policy
by Jean-Pascal Bénassy
In his latest book, Bénassy argues that while dynamic stochastic general equilibrium theory has been successful in explaining many aggregate phenomena, several stylized facts regarding money are still puzzling. For example, DSGE models find it difficult to replicate the liquidity effect found in the data (nominal interest rates decrease in response to a positive money shock). These models also typically advocate the Friedman rule, zero nominal interest rates, which leads to price indeterminacies.
The author suggests that one important reason for these deficiencies of the theory is that it relies on the Ricardian models, where Ricardian equivalence holds, and notably money and government bonds do not constitute real wealth. One way to make the model economy non-Ricardian is to assume newborns, and Bénassy shows that this assumption alone can solve many of the existing puzzles. This is first done in a model with population growth and infinitely lived agents, which allows for analytical ease, then within an overlapping generation framework.
This book builds a lot on existing research, but is not a collection of works. It seeks to demonstrate that current research should be looking at some classics and learn from them again. Unavoidably, the discussion is technical, but short and to the point. An essential read for anybody interested in monetary theory.
"Money, Interest, and Policy" is published by MIT Press.
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