Volume 4, Issue 2, April 2003
The Research Agenda: Tony Smith on Business Cycles and Inequality
How do business cycles affect inequality? What effects do business cycles
have on the distributions of income, wealth, consumption, and, especially,
welfare across different types of consumers? Are disadvantaged
consumers--for example, the poor and the unemployed--more exposed to
business cycle risk than the rich and the employed? These kinds of
questions lie at the heart of much of the public debate about the costs
and benefits of macroeconomic stabilization policy. Rather than focus on
the average cost or benefit across the entire population, this debate
instead typically centers on the question of who gains and who loses from
macroeconomic policy. The distribution of gains and losses across the
population also plays an important role in determining which macroeconomic
policies (especially fiscal policies) are adopted in a democratic society.
Because research on the interaction between inequality, business cycles,
and macroeconomic policy is still in its infancy, we do not yet have
satisfactory answers to many of the questions posed above. Nonetheless,
this text describes a set of partial answers that Per Krusell and I
provide in recent research to the question of how business cycles affect
different groups in the economy. This text then suggests some avenues for
Anthony A. Smith, Jr., is Associate Professor of Economics at Carnegie
Mellon University. His field of research is frictions and heterogeneity in
dynamic macroeconomic models. Smith's RePEc/IDEAS entry
In Krusell and Smith (2002), which is an extension of our earlier work in
Krusell and Smith (1999), Per Krusell and I study the distributional
implications of business cycle risk. Building on the work of Huggett
(1993) and Aiyagari (1994), we construct a model of economic inequality in
an environment featuring incomplete markets and business cycles. We then
use this model to study the effects of a hypothetical macroeconomic
stabilization policy that eliminates business cycles. The model is a
version of the stochastic growth model with a large number of
infinitely-lived consumers (dynasties). Consumers are ex ante identical,
but there is ex post heterogeneity due to shocks to labor productivity
which are only partially insurable. Consumers can accumulate capital (the
single asset available) in order to partially smooth consumption over
time. At each point in time, consumers may differ in the history of
productivities experienced, and hence in accumulated wealth. Consumers
also differ in their degree of patience: consumers' discount factors
evolve stochastically. The stochastic evolution of the discount factors
within a dynasty captures some elements of an explicit
overlapping-generations structure with altruism and less than perfect
correlation in genes between parents and children (see also Laitner 1992,
2001). With this interpretation in mind, the stochastic process governing
the evolution of the discount factors is calibrated so that the average
duration of any particular value of the discount factor is equal to the
lifetime of a generation. The purpose of the heterogeneity of the discount
factors is to allow the model to replicate the observed heterogeneity in
wealth, the key endogenous variable in the model.
A key equilibrium object in this class of models is the law of motion of
the distribution of wealth. In principle, computing this object is a
formidable task since the distribution of wealth is infinite-dimensional.
In earlier work (see Krusell and Smith 1997, 1998), Per Krusell and I
however, that this class of
when reasonably parameterized, exhibits "approximate aggregation": loosely
speaking, to predict prices consumers need to forecast only a small set of
statistics of the wealth distribution rather than the entire distribution
itself. This result makes it possible to use numerical methods to analyze
this class of models. More generally, this result opens the possibility
of using quantitative dynamic general equilibrium models to study how the
business cycle and inequality interact and to study the distributional
effects of macroeconomic policies designed to ameliorate the effects of
aggregate (macroeconomic) shocks.
Per Krusell and I use the model described above to provide a quantitative
answer to the following question: If the aggregate shocks driving the
business cycle are eliminated, how are different groups of consumers
affected? We answer this question in the spirit of the celebrated
calculation of Lucas (1987) in which Lucas finds that the welfare costs of
business cycles are very small. In particular, we assume that removing
business cycles does not change averages across cycles: both booms and
recessions are eliminated and replaced by their average in a sense to be
made precise below. In addition, we do not spell out an explicit
macroeconomic policy that the government could use to eliminate business
cycles. In this sense, our calculation, like Lucas's, can be viewed as an
upper bound on the welfare benefits (if any) of macroeconomic
stabilization policy, since any actual policy would presumably introduce
distortions that offset the positive effects of stabilization. Unlike
Lucas, however, we do not simply replace consumption with its average (or
trend) but instead replace the aggregate shocks by their averages and then
allow consumers to make optimal choices in the new environment without
cycles. By studying a general equilibrium environment, we also allow
consumers' new choices in response to the removal of aggregate shocks to
have equilibrium effects on wages and interest rates. These general
equilibrium effects on prices turn out to be quite important, as I
Replacing the aggregate technology shock and the unemployment rate (which
varies exogenously in the model with
cycles) with their averages is conceptually and technically
straightforward. It is less obvious, however, how the basic idea of
averaging across cycles should affect an individual consumer's stochastic
process for labor productivity. To accomplish the task of removing the
aggregate shock from a consumer's employment process, we adopt what we
call the "integration principle": fix an individual consumer's "luck" and
then average across realizations of the aggregate shock.
The key idea of this principle can be illustrated using a simple static
example in which the economy is in either good times or bad times and an
individual consumer is either employed or unemployed, where the
probability of employment depends in part on whether the economy is in
good or bad times. Let z denote the aggregate state, which takes on
value g (for "good") with probability p and the value
b (for "bad") with
probability 1-p, where 0<b<g<1. In good times
(z=g), the unemployment rate
is low and in bad times (z=b), the unemployment rate is high. Let
i be a
random variable uniformly distributed on the unit interval representing
the consumer's idiosyncratic "luck". By assumption, a consumer's luck is
statistically independent of both the aggregate state and any other
consumer's luck (and, in a more general dynamic setting, of the past
history of luck). Higher values of i mean worse luck: in
the world with cycles, the consumer is employed if i<g and
z=g or if i<b
and z=b. Applying a law of large numbers across the continuum of
consumers, this stochastic structure implies that the unemployment rate is
g in good times and b in bad times.
To apply the integration principle in this example, fix i for each
consumer and average over the good and bad realizations of the aggregate
state z to obtain an outcome for the consumer's labor productivity
Consumers with sufficiently good luck (i<b) are employed in both
bad times, so they are unaffected by averaging: e=1. Similarly,
with sufficiently bad luck (i>g) are unemployed in both good and
times, so they too are unaffected by averaging: e=0. The fate of
in the intermediate range [b,g], however, does depend on the
state. Averaging across realizations of the aggregate state, these
consumers are employed with probability p and unemployed with
1-p, so e=p. As this example illustrates, averaging across
state in accordance with the integration principle reduces idiosyncratic
risk: in the world with cycles, consumers receive only extreme outcomes
(e=1 or e=0) but in the world without cycles, a fraction
g-b of consumers
receive an intermediate outcome (e=p), thereby reducing the
cross-sectional variance of labor productivity.
Loosely speaking, using
the integration principle to eliminate the effects of business cycles
reduces idiosyncratic risk because some of this risk is correlated with
the business cycle: when business cycles are removed, the part of the
idiosyncratic risk that is correlated with the business cycle is removed
too. In our realistically calibrated economy, we find that the
cross-sectional standard deviation of labor productivity decreases by 16%.
Thus the integration principle differs from the principle advanced in
Atkeson and Phelan (1994) in which the removal of the business cycle
simply removes correlation across consumers, leaving their processes for
labor productivity unchanged.
I have explained the integration principle in detail because it lies at
the heart of the differential effects of eliminating business cycles on
different groups of consumers. The basic experiment that Per Krusell and I
perform is to "freeze" the economy with cycles at a point in time, remove
(via an unspecified and unanticipated macroeconomic policy) the business
cycle shocks using the integration principle, and then track the behavior
of the economy as it transits deterministically to a steady state. We then
compare, using a consumption-equivalent measure as in Lucas (1987), the
welfare of different consumers (as of the time of the removal of business
cycles) in the worlds with and without cycles.
Our most striking finding is that the welfare effects of eliminating
business cycles are U-shaped across different wealth groups, regardless of
the state of the macroeconomy when the cycles are eliminated:in a
nutshell, the poor and the rich gain while the middle class loses. As
be expected, the poor benefit directly from the reduction in uninsurable
risk. The middle class and the rich care less about uninsurable risk
because they have sufficient wealth to buffer employment shocks. General
equilibrium effects on interest rates and wages, however, have important
welfare implications for the middle class and for the rich. In response to
the reduction in uninsurable risk, consumers in the aggregate accumulate
less capital. As a result, interest rates rise (benefiting the rich for
whom asset income is important) and wages fall (hurting the middle class
for whom labor income is important). Looking across all consumers, there
is a small average gain equivalent to 0.1% of consumption per period; this
number is an order of magnitude larger than the costs of business cycles
computed by Lucas (1987) in a representative-agent framework. This small
gain, however, masks substantial heterogeneity across different types of
consumers: the majority of consumers--the middle class--experience small
welfare losses from the elimination of cycles, whereas the welfare gains
of the poor and the rich are quite large: in the range of 4% for the
poorest unemployed consumers and 2% for the richest consumers. These
that aggregate stabilization policies can substitute for social insurance
policies: the poor benefit the most from the elimination of business cycle
risk. At the same time, eliminating business cycle risk has significant
distributional effects that an analysis based on a representative-agent
framework fails to capture.
Another striking finding is that wealth inequality increases dramatically
when business cycles are removed: for example, the Gini coefficient for
wealth increases from 0.8 to 0.9 and the fraction of consumers with
negative net worth increases from 11% to 31%. This spreading out of wealth
stems from the heterogeneity in the degree of patience of different
consumers. Although consumers' discount factors are not permanently
different, they are very persistent. If discount factors were in fact
permanently different, then the distribution of wealth would spread out
indefinitely, with the most patient consumers controlling all of the
economy's wealth, were it not for the uninsurable risk that provides an
incentive for the least patient consumers to hold assets for precautionary
reasons. When idiosyncratic risk is reduced, then, this precautionary
motive on the part of the least patient (and hence poorest) consumers is
mitigated to some extent, so that the heterogeneity in discount rates can
operate more strongly to push the economy apart. Although wealth
inequality increases, the integration principle implies that earnings
inequality (which is exogenous in this model) decreases. At the same time,
income inequality remains more or less unchanged while consumption
These findings also suggest an interesting policy experiment to be
undertaken in future research. Rather than provide social insurance to the
poor and unemployed indirectly by means of aggregate stabilization policy,
instead let poor/unemployed consumers receive subsidies financed by taxing
rich consumers. These subsidies are designed to mitigate the effects of
the idiosyncratic risk that is felt most strongly by the poor and
unemployed. These consumers will thus be made better off, as in the
experiment described above. The welfare of the rich is affected in two
ways. On the one hand, the taxes they face reduce their welfare. On the
other hand, the social insurance funded by these taxes, by redistributing
idiosyncratic risk from those who feel it the most strongly (the poor) to
those who feel it the least strongly (the rich whose wealth allows them to
absorb idiosyncratic shocks), reduces the effective amount of
idiosyncratic risk in the economy. This reduction in risk reduces
precautionary savings, so that the economy as a whole accumulates less
capital and interest rates rise. This increase in interest rates improves
the welfare of the rich and might be large enough to offset the
welfare-reducing effects of taxation. Finally, as in the experiment
described above, this set of policies might hurt the middle class by
reducing their wages, but if these welfare losses are small the middle
class could be compensated using only a small part of the tax revenue, the
bulk of which is directed to the poor. In sum, it seems possible that this
combination of fiscal policies--taxing the rich to provide insurance to
the poor and to provide a small income subsidy to the middle class--could
make everyone better off.
Although some of these findings are provocative, at least some of them are
also quite sensitive to the manner in which Per Krusell and I have modeled
inequality and, in particular, to the mechanisms that we are using to
generate substantial wealth inequality as in U.S. data. Domeij and
Heathcote (2002) and Castaneda, Diaz-Gimenez, and Rios-Rull (2002), for
example, study models without heterogeneity in discount factors but with
exogenous processes for labor productivity that are chosen, in part, to
replicate facts about the distribution of wealth. In these models, a
reduction in idiosyncratic risk (thanks to the elimination of business
cycle risk) would, as in the model of Aiyagari (1994), reduce rather than
increase wealth inequality. Other researchers have focused on
entrepreneurship (see, for example, Quadrini 2000 and De Nardi and Cagetti
2002) and limited stock market participation (see, for example Guvenen
2002) as key mechanisms driving wealth inequality. Another set of
researchers emphasizes the importance of different kinds of uninsurable
shocks. Krebs (2002) studies the effects of business cycles in an
environment in which consumers face idiosyncratic human capital risk.
Storesletten, Telmer, and Yaron (2002a, 2002b) study the effects of
cycles in a life-cycle model with countercyclical variation in
idiosyncratic risk. Finally, Angeletos and Calvet (2002) study models with
idiosyncratic production rather than endowment risk and argue that in
these environments reductions in idiosyncratic risk can increase rather
than decrease aggregate savings.
In short, there currently exists a wide variety of research on inequality
which emphasizes different kinds of fundamental mechanisms and different
kinds of uninsurable shocks. As suggested above, these different
environments can generate different answers to the question of how
business cycles affect inequality and the distribution of welfare. In
provide convincing quantitative answers to this question, then, future
research will need to confront these various models to both macroeconomics
and cross-sectional data in more rigorous ways and to search for deeper
common elements linking the different models. Precisely because some of
answers provided by the framework that Per Krusell and I studied are
intriguing, it is important to investigate the robustness of these answers
to variations in the mechanisms and shocks underlying economic inequality
and to seek further empirical evidence that might sort out the
quantitative importance of the different approaches.
Another important item on the research agenda is to study the
effects on inequality of explicitly
specified macroeconomic stabilization policies, such as automatic
stabilizers, cyclical unemployment insurance (see, for example, Gomes
2002), and international macro markets along the lines suggested by
Shiller (1993, 2003).
Aiyagari, S. Rao (1994). "Uninsured
Idiosyncratic Risk and Aggregate Saving
", Quarterly Journal of
, 109, 659-684.
Angeletos, George-Marios, and Laurent Calvet (2002). "Idiosyncratic
Production Risk, Growth, and the Business Cycles", manuscript (MIT).
Atkeson, Anthony, and Christopher Phelan (1994). "Reconsidering the Cost
of Business Cycles with Incomplete Markets", NBER Macreconomics
Cagetti, Marco, and Cristina de Nardi (2002)' "Entrepreneurship,
Frictions and Wealth", Federal Reserve Bank of Minneapolis Working Paper
Castaneda, Ana, Javier Diaz-Gimenez, and Jose-Victor Rios-Rull
(2002). "Accounting for the U.S. Earnings and Wealth Inequality",
of Political Economy
Domeij, David, and Jonathan Heathcote (2002). "Factor Taxation with
", Stockholm School of Economics
Working Paper Series in Economics and Finance 372.
Gomes, Joao (2002). "The Right Stimulus: Extended Unemployment
Insurance Benefits or Tax Cuts?", manuscript (Wharton School, University
Guvenen, Fatih (2002). "Reconciling
Conflicting Evidence on the Elasticity of Intertemporal
Substitution: A Macroeconomic Perspective
of Rochester, Center for Economic Research (RCER) Working Paper 491.
Mark (1993). "The Risk-Free Rate in Heterogeneous-Agent
Incomplete-Insurance Economies", Journal of Economic Dynamics and
, 17, 953-969.
Krebs, Tom (2002). "Growth
and Welfare Effects of Business Cycles
in Economies with Idiosyncratic Human Capital Risk
", Brown University
Working Paper 2002-31.
Krusell, Per, and Anthony A. Smith, Jr. (1997). "Income and Wealth
Heterogeneity, Portfolio Selectio, and Equilibrium Asset Returns",
, 1, 387-422.
Krusell, Per, and Anthony A. Smith, Jr. (1998). " Income
and Wealth Heterogeneity in the Macroeconomy
", Journal of Political
, 106, 867-896.
Krusell, Per, and Anthony A. Smith, Jr. (1999). "On the
Welfare Effects of Eliminating Business Cycles
", Review of Economic
, 2, 245-272.
Krusell, Per, and Anthony A. Smith, Jr. (2002). "Revisiting the Welfare
Effects of Eliminating Business Cycles
manuscript, Carnegie-Mellon University.
Laitner, John P. (1992). "Random Earnings Differences, Lifetime
Liquidity Constraints, and Altruistic Intergenerational Transfers",
Journal of Economic Theory
, 58, 135-170.
Laitner, John P. (2002). "Wealth Accumulation in the U.S.: Do Inheritances
and Bequests Play a Significant
Role?", manuscript (University of Michigan).
Lucas, Jr., Robert E. (1987). Models of Business Cycles
Blackwell, New York.
Quadrini, Vincenzo (2000). "Entrepreneurship,
Saving and Social Mobility
", Review of Economic Dynamics
Shiller, Robert (1993). Macro Markets: Creating Institutions for
Managing Society's Largest Economic Risks
, Oxford University Press.
Shiller, Robert (2003). The New Financial Order: Risk in the 21st
Princeton University Press.
Storesletten, Kjetil, Christopher Telmer, and Amir Yaron (2002a).
"Cyclical Dynamics in Idiosyncratic Labor-Market Risk", Journal of
Storesletten, Kjetil, Christopher Telmer, and Amir Yaron (2002b).
"The Welfare Costs of Business Cycles Revisited:
Finite Lives and Cyclical Variation in Idiosyncratic Risk",
European Economic Review
EconomicDynamics Interviews Narayana Kocherlakota
Narayana Kocherlakota is Professor of Economics at Stanford University
He works on optimal taxation, social insurance, and the micro-foundations
Kocherlakota's RePEc/IDEAS entry
EconomicDynamics Newsletter: Your recent research on optimal unemployment
insurance and optimal capital taxation shows that small differences in the
information structure can have dramatic impacts on the optimal design of
these institutions. Does this not make it an impossible task for a policy
maker to design a sensible policy?
Narayana Kocherlakota: My new paper on optimal unemployment insurance, and
my RESTUD (2001) paper with Harold Cole, both show that the nature of
optimal social insurance changes dramatically if people can save secretly.
But I don't view this change as being "small". Think about the
government's costs of monitoring savings. When savings are observable,
these costs are zero. When savings are unobservable, these costs are
infinite. In this sense, the change is big.
I think these kinds of results point to two important directions for
future research. The first is theoretical: to provide sharp
characterizations of optimal social insurance when the government can
monitor savings and income, but only by paying auditing costs. The second
is empirical: to obtain some kind of measure of how big these costs are.
ED: Would you argue the same would hold with your work on capital
taxation? You show that when individual skills are unobservable and evolve
stochastically, capital tax rates should be positive. The standard
result was that capital tax rates should be zero.
NK: The now standard results on capital tax rates were derived by
Chamley and Judd using the Ramsey approach to optimal taxation. This
approach assumes that lump-sum taxes are unavailable, and that the
government is forced to use distortionary linear taxes. Chamley and Judd
show that even though lump sum taxes are unavailable, it is generally
optimal for capital tax rates to be zero in the long run.
In my paper with Mikhail Golosov and Aleh Tsyvinski, "Optimal
Indirect and Capital Taxation," we abandon the Ramsey approach to
optimal taxation. Instead, we consider a large class of model economies
that are dynamic extensions of James Mirrlees' original optimal taxation
setup. The main ingredients of these models are that skills are privately
observable and that they evolve stochastically. We show that if individual
capital holdings can be monitored, then it is optimal to tax those holdings.
Note that unemployment is one example of the kind of privately observable
skill shocks that we have in mind. People are unemployed either because
they can't find a job (formally, their "skills" are low in the given
period) or they can find a job (their skills are high) and they choose not
to work. If savings are observable, then optimal unemployment insurance
requires taxation of individual savings.
Of course, it is impossible to tax capital holdings (or equivalently
savings) if individuals can save secretly. In that case, the nature of
optimal social insurance against skill shocks changes dramatically. As I
suggested in my first answer, I think it would be very fruitful to study
intermediate cases in which savings can be monitored at a finite cost.
ED: In an influential JET paper, you argue that "Money is Memory." Does
this mean with should add a new role for money in the Economics Principles
NK: Actually, I would argue something far stronger: we should eliminate
all of the standard explanations (medium of exchange, unit of account, and
store of value) from the textbooks. Why do I say this? These
"explanations" do not capture why money is necessary to achieve good
outcomes in a society. Rather, they are merely descriptions of what money
Why is money necessary to achieve good outcomes in a society? Well,
imagine a world without money, but with a perfect record of all past
transactions. (One way to imagine this is a giant spreadsheet which lists
everyone's name, and every event that ever happened to them.) In this
world, we can accomplish anything that we could have with money (without
adding any additional penalties or punishments that we might typically
associate with credit). We do so using elaborate chains of gifts.
For example, suppose I go to the bookstore and ask for a book. The
bookseller checks my past transactions. If I've given sufficiently
more gifts than I've received in the past, then he gives me a textbook.
Why is he willing to do so? Because in the future, when he goes to the
grocery store, the grocer is willing to give the bookseller more bananas
than if the bookseller had not given me the book. Why is the grocer
willing to do so? Because he is rewarded by being able to receive more
gifts in the future, etc, etc.
This is the key insight in "Money is Memory": a monetary equilibrium is
merely an elaborate chain of gifts. After all, when I give the bookseller
a fifty dollar bill in exchange for a book, he receives nothing of
intrinsic value. All he receives is a token that indicates to others
that he gave up something worth $50 ... that he has made a gift and so has
kept up his part in the gift-giving chain that is a monetary economy.
Without money, we would need to have the giant spreadsheet - or the gifts
would never take place (because the only reason to make the gifts is to
let others know that you have!).
This is the role of the intrinsically useless object termed money: to
credibly record some aspects of past transactions and to make that record
accessible to others. It is for this reason that I write that money is
always and everywhere a mnemonic phenomenon.
Chamley, Christophe (1986). "Optimal
Taxation of Capital Income in General Equilibrium with Infinite
, 54, 607-622.
Golosov, Mikhail, Narayana Kocherlakota, and Aleh Tsyvinski
(2001). "Optimal Indirect and
", Federal Reserve Bank of Minneapolis Staff Report 293.
Judd, Kenneth (1985). "Redistributive Taxation in a Simple Perfect
Foresight Model", Journal of Public Economics
, 28, 59-83.
Kocherlakota, Narayana (1998). "Money is Memory", Journal of Economics
, 81, 232-251.
Kocherlakota, Narayana (2003). "Simplifying Optimal
Insurance: The Impact of Hidden Savings
", working paper, March.
Kocherlakota, Narayana, and Harold Cole (2001). "Efficient
with Hidden Income and Hidden Storage
", Review of Economic
Mirrlees, James (1971). "An
Exploration in the Theory of Optimum Income Taxation
", Review of
, 38, 175-208.
Mirrlees, James (1976). "Optimal Tax Theory: A Synthesis", Journal of
, 6, 327-358.
Society for Economic
Dynamics: Letter from the President
Dear SED Members and Friends,
This is a reminder to register for our Annual Meeting to be held June
26-28 in Paris, France. This year we had a record number of submissions
for the conference program. In spite of an increase in the number of
sessions, we still had to turn down many worthy submissions. The program
organizers, Lee Ohanian and
Franck Portier have put
together a stunning
program including Plenary addresses by Jeremy Greenwood of the
of Rochester, George
Mailath of the University of Pennsylvania, and Jean
Tirole of Institut d'Economie Industrielle, Toulouse.
The local organizers are Jean-Olivier
Hairault and Hubert Kempf of EUREQua
Universite de Paris I, and Francois
Langot, CEPREMAP and GAINS Universite
du Maine. They have planned a terrific Social Program that includes a
cocktail party at the Hotel de Ville de Paris on Friday June 27th. And a
conference dinner at the famous Musée des Arts forains on Saturday
28th. To register for
the conference online visit:
I look forward to seeing you in Paris.
Thomas F. Cooley,
Society for Economic Dynamics
Society for Economic
Dynamics: 2003 Meetings
The next meeting will be held in Paris, June 26-28. It will be hosted by
the Université Paris-1 Panthéon-Sorbonne and will take place
historical Sorbonne building, right in the centre of the Quartier Latin,
on the left bank.
More than 600 papers have been submitted to the program committee, chaired
by Lee Ohanian and Frank Portier and more than
have been selected and
will be presented during the meeting. Plenary sessions will be presented
by Jeremy Greenwood
(University of Rochester), George Mailath (University
of Pennsylvania), Jean Tirole (Institut d'Économie Industrielle,
Social events during the meeting include a cocktail party at the Paris
City Hall, and a conference dinner at the Musée des Arts forains
for antique fairs) which should be quite entertaining. It will of course
be followed by a life show by the Contractions.
Details on the meeting are available at
You can also go to the local website for the meeting at
You should plan to attend the meeting, even if you do not present a paper.
The program will be stunning and a must for any dedicated researcher,
interested in what is going on in economic dynamics. There is a discount
for those who register before May 15. To register and book for
accommodation, please contact Corporate Planners unlimited at the
following web address:
Do not delay the booking for your accommodation. Paris is a crowded
tourist spot at this period of the year, and hotels could be fully booked
Review: De la Croix and Michel's A Theory of Economic Growth
A Theory of Economic Growth
Dynamics and Policy in Overlapping Generations
by David de la Croix and
Just published by Cambridge University Press, this book covers most of
everything you would ever want to know about growth and fiscal policy in
overlapping generations models. For those interested in growth theory, it
is an important complement to the existing textbooks that focus more on
the Solow growth model and its infinite-lived derivatives. For those
interested in overlapping generations models per se, it complements the
book by McCandless and Wallace that focuses on monetary equilibria.
The book has six main parts. The first studies equilibria in the basic
overlapping generations model and its main extensions, the second
considers their optimality and the properties of optimal paths. Chapter 3
is devoted to fiscal issues: transfers, pensions, public spending and
second-bests. Chapter 4 introduces public debt. The last chapter deals
with other extensions, such as altruism, education, inter-generational
externalities and full Arrow-Debreu markets. Finally, a technical appendix
shows various tools and functions some students may need.
Note that the book focuses entirely on theory. The theory is not motivated
by some analysis of the data, an aspect that other growth textbooks have
clearly emphasized. The predictions of the theory are not compared to some
stylized facts or tested in some other ways. In that sense, "A Theory of
Economy Growth" should really be understood as a manual on the inner
workings of overlapping generation models, a toolbox that a researcher can
keep handy, or as a guide on how to prove properties of models related to
the ones presented. Many will come to appreciate this book for its
analytic depth and its attempt to provide a systematic and
precise presentation of overlapping generations.
"A Theory of Economic Growth" has been published by Cambridge University
Press in October 2002.
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