INTRODUCTION

The severe financial and economic crisis that hit Mexico after the devaluation of the peso in December 1994, and the unprecedented ‘Tequila effect’ by which Mexico's financial woes ‘infected’ emerging markets world-wide were a harbinger of a period of intense turbulence in international capital markets. Seven years later, in December 2001, a major crisis broke out in Argentina with an explosive combination of sovereign default, massive currency devaluation and collapse of economic activity. In the seven years separating the Mexican and Argentine crises, similar crises engulfed nearly all of the so-called ‘emerging markets,’ including Hong Kong, Korea, Indonesia, Malaysia, Thailand, Russia, Chile, Colombia, Ecuador, Brazil and Turkey. Interestingly, devaluation itself proved not to be a prerequisite for these crises, as the experiences of Argentina in 1995 and Hong Kong in 1997 showed. ‘Contagion effects’ similar to the ‘Tequila effect’ were also typical, as crises spread quickly to countries with no apparent economic linkages to countries in crisis. A favourite example is the correction in US equity prices in the autumn of 1998 triggered by the Russian default. The systemic nature of this correction forced the US Federal Reserve to lower interest rates and coordinate the orderly collapse of hedge fund Long Term Capital Management.

Emerging markets crises are characterised by a set of striking empirical regularities that Calvo (1998) labelled the ‘Sudden Stop’ phenomenon. These empirical regularities include: (a) a sudden loss of access to international capital markets reflected in a collapse of capital inflows, (b) a large reversal of the current account deficit, (c) collapses of domestic production and aggregate demand, and (d) sharp corrections in asset prices and in the prices of non-traded goods relative to traded goods. Figures 7.1–7.3 illustrate some of these stylised facts for Argentina, Korea, Mexico, Russia and Turkey. Figure 7.1 shows recent time series data for each country's current account as a share of GDP. Sudden Stops are displayed in these plots as sudden, large swings of the current account that in most cases exceeded five percentage points of GDP. Figure 7.2 shows data on consumption growth as an indicator of real economic activity. These plots show that Sudden Stops are associated with a collapse in the real sector of the economy.

INTRODUCTION

In recent years, dynamic stochastic general equilibrium (DSGE) models of monetary economies have focused on the role of nominal rigidities in affecting the economy's adjustment to monetary policy and non-policy disturbances. While these rigidities appear important for understanding the impact nominal shocks have on such real variables as output and employment, models with only nominal rigidities have been unable to match the responses to monetary disturbances that have been estimated in the data. Typically, empirical studies have concluded that monetary shocks generate large and persistent real responses that display a hump shape. After a positive money shock, for example, output rises over several quarters and then declines. Christiano, Eichenbaum and Evans (1999) document this effect and provide an extensive discussion of the empirical evidence on the effects of monetary shocks. Sims (1992) finds large, hump-shaped responses of real output to monetary shocks in several OECD countries. Inflation also displays a hump-shaped response, although inflation is usually found to respond more slowly than output to monetary shocks.

The ‘stylised facts’ emphasised by Christiano, Eichenbaum and Evans, by Sims, and by others are illustrated in figure 9.1, which shows estimated impulse responses of output and inflation following a shock to the growth rate of money. These responses were obtained from a three-variable VAR (output, inflation, and money growth) estimated using US quarterly data for 1965–2001. Output is real GDP, inflation is measured by the Consumer Price Index, and M2 is the aggregate used to measure money. The real persistence and inflation inertia seen in figure 9.1 has been hard for models based on nominal rigidities to match. As Dotsey and King (2001) have expressed it, ‘modern optimizing sticky price models have displayed a chronic inability to generate large and persistent real responses to monetary shock’.

In order to capture at least some of the real persistence seen in empirical studies, models based on nominal rigidity generally must assume a high degree of price stickiness. For example, it is common to assume that individual prices remain fixed on average for as much as nine months. Micro data on individual prices, however, suggests that prices typically change more frequently than this. Consequently, a number of researchers have recently argued that simply adding nominal rigidities to an otherwise standard DSGE model is not sufficient to match the persistence observed in the data.

INTRODUCTION

A New Neo-classical Synthesis (NNS) is merging three traditions that have dominated macroeconomic modelling for the last thirty years. In the 1970s, Sargent andWallace (1975) and others added rational expectations to the IS-LM models that were then being used to evaluate monetary policy; somewhat later, Calvo (1983) and Taylor (1980) introduced richer dynamic specifications for the nominal rigidities that were assumed in some of those models. In the 1980s, Kydland and Prescott (1982) and others introduced the Real Business Cycle (RBC) model, which sought to explain business cycle regularities in a framework with maximising agents, perfect competition, and complete wage/price flexibility.

The NNS reintroduces nominal rigidities and the demand determination of employment and output. Monopolistically competitive wageand price-setters replace the RBC model's perfectly competitive wage- and price-takers; monopoly markups provide the rationale for suppliers to expand in response to an increase in demand; and the Dixit and Stiglitz (1977) framework – when combined with complete sharing of consumption risks – allows the high degree of aggregation that has been a hallmark of macroeconomic modelling.

In this chapter, we present a simple model that can be used to illustrate elements of the NNS and recent developments in the macroeconomic stabilisation literature. We do not attempt to survey this rapidly growing literature. Instead, we focus on a set of papers that are key to a question that is currently being hotly debated: is price stability a good strategy for macroeconomic stabilisation? If so, some of the generally accepted tradeoffs in modern central banking would seem to evaporate. For example, inflation (or price-level) targeting need not be seen as a choice that excludes Keynesian stabilisation, and it would be unnecessary to give price stability such primacy in the statutes of the new central bank in Europe.

In section 2, we present our model and discuss some fundamental characteristics of the NNS. Our model is simpler than that which appears in much of the literature because we have replaced the dynamic Calvo and Taylor specifications of nominal rigidity with the assumption that some wages and/or prices are set one period in advance. This allows us to derive closed form equilibrium solutions for a class of utility functions and assumptions about the distribution of macroeconomic shocks.

The aim of this volume is simple: to demonstrate how quantitative general equilibrium theory can be fruitfully applied to a variety of specific macroeconomic and monetary issues. There is, by now, no shortage of high-quality advanced macroeconomic and monetary economics texts available – indeed two of the contributors to the present volume (Stephen Turnovsky and Carl Walsh) have recently written first-rate graduate texts in just these areas. However, there is often rarely space in a text book to develop models much past their basic setup, and there is similarly little scope for a detailed discussion of a model's policy implications. This volume, then, aims to bridge some of that gap.

To that end, we asked leading researchers in various areas to explain what they were up to, and where they thought the literature was headed. The result, we think, bears testimony to the richness of aggregate economic modelling that has grown out of the real business cycle (RBC) approach to growth and business cycle fluctuations. We treat this book as both a mark of the tremendous progress in this field and a staging post to even further progress subsequently.

We would like to thank colleagues who have taken the trouble to read parts of this book and provided useful comments: Anthony Garratt, Sean Holly, Campbell Leith, Paul Levine, David Miles, Ed Nelson, Sheilagh Ogilvie, Argia Sbordone, Frank Smets, Alan Sutherland, Peter Tinsley, Marcelo Veracierto, Simon Wren-Lewis, Mike Wickens. Ashwin Rattan and Chris Harrison at Cambridge University Press have provided constant support. Finally, we would like to thank Anne Mason and Gill Smith without whose efficiency this book would not have been so expertly completed.

INTRODUCTION

In this chapter we consider the interaction of monetary policy with aggregative fiscal policy. By ‘aggregative’ we mean that our focus is primarily on the effects of debts and deficits in the presence of lump-sum taxation. We shall, in particular, be concerned with the ways monetary and fiscal policies may need to be coordinated to ensure ‘good’ macroeconomic outcomes. To that end, we shall be largely occupied with two issues: (a) the fundamental linkages between the government's budget constraint and the setting of interest rates and (b) on the stabilisation issues thrown up by systematic fiscal and monetary policy over the economic cycle.

More specifically, we study how monetary policy may be influenced by doubts over the wider fiscal solvency of the public sector. In an important contribution Sargent and Wallace (1981) argued that the money stock and taxes were substitutes in the backing of government debt. This discussion brings to the fore the fact that monetary and fiscal policies are linked via a budget constraint. However, many countries have recently delegated control of monetary policy to an independent monetary authority, partly in response to the kind of concerns raised by Sargent and Wallace. There now seems to be some concern that monetary and fiscal policy may actually not be well coordinated under such an institutional structure. The issue seems less to do with solvency, and more to do with aggregate demand management over the economic cycle: if monetary policy is too ‘rigid’, then fiscal policy may need to compensate by being more ‘flexible’. So the second issue we discuss is how monetary and fiscal policies might be set jointly in order to smooth the economic cycle.

In the next section we set out the contents of the chapter in some more detail.

Key themes

Following Sargent and Wallace (1975, 1981) macroeconomists generally argued that there were two key requirements for monetary policy to retain control over nominal magnitudes. First, monetary policy ought to be characterised by control over the money stock as opposed to an interest rate peg. However, since fiscal policy may hamper the effective control of the money supply by requiring excessive seigniorage revenue – the tax revenue generated from money creation – this is not, in general, a sufficient condition.

In Dynamic Macroeconomic Analysis: Theory and Policy in General Equilibrium, Altug, Chadha and Nolan, hereafter ‘ACN’, have undertaken the extremely difficult task of bringing the reader up to date on the vast literature that has developed in this key area of economics since such seminal books as Cooley's Frontiers Of Business Cycle Research (1995).

ACN tackle this formidable assignment by recruiting top scholars to write individual chapters. Each individual chapter is of exceptionally high quality because each scholar is a first-rate expert in the chapter's area.

The approach of the book is ‘quantitative theorising’, in the sense that each chapter presents not only recent developments in theory but also recent developments in compilation of the facts that confront the theory. Discrepancies between facts and theories are carefully discussed. Many of the chapters offer modifications to the baseline theory that make it do a better job of matching the facts.

I give the reader a quick overview of the contents of this book in a brief introduction to each of the chapters. Three chapters are discussed in more detail than the others in order to keep my foreword within standard space limits. But all of the chapters are equally exciting and have equal command on the reader's attention. I hope this somewhat unusual approach to writing a foreword will entice more readers to add this important book to their libraries. In addition to saying a few words about the chapters, I shall use the discussion of some of them to give some reflections about the field they cover as well as give some speculations and opinions about potentially fruitful future research.

Jim Pemberton (chapter 1) reviews dynamic life cycle consumption/savings models, the facts they are designed to explain, the struggles in attempting to modify the basic core model to fit these facts and other uses to which they are put. Particularly interesting is discussion of how minor modifications can lead to big and rather counterfactual predictions by some of the models. For example, adding a small safety net in one model caused the model's consumer to borrow too large an amount of money early on to be consistent with fact.

INTRODUCTION

Growth and fluctuations are sometimes referred to as the Twin Horns of Harrod because of two influential essays (see Harrod 1936, 1939). Both Hicks and Solow reacted to the ‘knife-edge path’ implied by these papers’ dynamics. Hicks emphasised the consequences of ‘falling off’ the edge. Solow gave a rationale, grounded in agents’ behaviour, that would keep the economy on this knife-edge path. Yet, the urge to study growth and fluctuations can be traced back, by way of Ricardo, Malthus and numerous other classical authors to the very birth of economics as a field. Given the vastness of the subject matter, one must set clear goals to what one hopes to achieve here.

This chapter is going to visit several schools that have attempted to blend the theory of economic fluctuations with the theory of growth. Both theories are interesting in their own right and are technically difficult. The early non-market approaches of the Hicksian accelerator and of the Goodwin predator–prey model are a good point of departure because of their intuitive nature. Hicks and Goodwin wrote at a time when an author could not rely on mathematical expertise to get published and in a style that borders, at times, on story telling. This chapter will start by reviewing their approaches, in section 2, as they have essentially disappeared from modern textbooks. Therein lies a deep vein of theory that, as we shall see, has influenced more modern approaches and still has the potential to enrich them further. Next, in section 3, we will review both real business cycle (RBC) theory and the deterministic dynamic system approach. RBC has established itself as the leading explanation for economic fluctuations and its paradigm when applied to growth is the model of King, Plosser and Rebelo (KPR) (1988a, 1988b). Anyone interested in working on the subject would be well advised to study that model. To help researchers, details of the rather intricate calculations in KPR are provided. Section 4 will evoke the problem of persistence in macroeconomic data. It will point to a convincing source for this phenomenon, namely aggregation. It will argue that persistence fogs our reading of economic relationships. It will call for the development of new tools to deal with the problem of persistence, in the absence of which no theory can be tested properly.

INTRODUCTION

The introduction of labour income into both deterministic, and more particularly stochastic, endogenous growth models has been somewhat problematical. The standard AK model of Barro (1990) and Rebelo (1991) assumes either explicitly or implicitly that labour income is introduced in the form of a return to human capital. Rebelo does so explicitly, by introducing human as well as physical capital in production. But Barro does so only implicitly, by assuming that capital in the AK technology is sufficiently broadly defined to be an amalgam of physical and human capital, which are assumed to be perfect substitutes in the production process. Neither of these procedures is entirely satisfactory. The assumption that the two forms of capital are perfectly interchangeable is obviously a polar one. Introducing current labour through human capital, which can be accumulated only gradually, ignores the short-run labour–leisure tradeoffs. As a consequence, taxes levied on labour income and consumption both operate as lump-sum taxes, thereby failing to capture the distortionary effects of these taxes on the growth rate of the economy; see Turnovsky (2000a).

The problem for stochastic growth models is even more acute. The solution procedure proposed by Merton's (1969, 1971) pioneering work involves explicitly solving the stochastic Bellman equation for the value function. This is a task that is tractable only under very restrictive assumptions, namely that output be generated as a linear function of current wealth (capital), thereby in effect, being represented by a stochastic AK technology. As a consequence, Merton's approach and the literature that it spawned basically restricted itself to income from assets and ignored labour income; see Eaton (1981), Gertler and Grinols (1982), Grinols and Turnovsky (1993, 1998), Obstfeld (1994), and Smith (1996). Indeed, presumably for this reason the most prominent area of application of these techniques has been to portfolio allocation problems in finance; see, e.g., Adler and Dumas (1983), Stulz (1981, 1983).

In this chapter we show how the equilibrium growth path can be easily obtained for both deterministic and stochastic economies in the case where the production function is of the Romer (1986) form, in which output is a linear homogeneous function of (i) private capital and (ii) labour supply expressed in efficiency units. The latter is measured as the product of labour with the average economy-wide stock of capital, which the individual agent takes as given, but which in equilibrium accumulates endogenously along with private capital.

INTRODUCTION

This chapter highlights some key topics in understanding the dynamic general equilibrium (DGE) behaviour of open economies. In line with the evolution of best practice in closed economy macroeconomic theory, DGE models are now the standard workhorse in the international macroeconomics literature. In addition, the incorporation of nominal rigidities and imperfect competition means that the current generation of open economy DGE models is also able to address the concerns of policy-makers regarding potential inefficiencies in adjusting to fundamental shocks. In this way, the ‘new open economy macroeconomics’ (NOEM) is a direct descendant of the traditional Mundell–Fleming–Dornbusch model (Rogoff 2001). While respecting this lineage, the microfounded nature of the new generation of models means that much more can be done in terms of providing a rigorous welfare evaluation of alternative policy regimes.

An open economy DGE model must contain a number of essential elements. Household preferences must be specified: this is more complex than in a closed economy model since the elasticity of substitution between home- and foreign-produced goods must be specified. This also applies to the specification of production functions since imported intermediate goods represent a potentially important linkage across economies. The international dimension of asset trade must also be specified, detailing whether home and foreign households share risks via state-contingent assets or just engage in bond trade or face even more restricted opportunities for international financial transactions. Of course, the form of nominal rigidities must also be determined (sluggishness in goods prices versus wages; the duration of rigidities): in an open economy, the researcher faces the problem of deciding the currency denomination of these sticky goods or factor prices. Finally, the nature of monetary and fiscal policies must be incorporated. Again, policy formation in an open economy involves extra dimensions in fixing the domestic policy response to foreign disturbances and evaluating whether there are gains to international policy coordination.

Lane (2001a) and Sarno (2001) provide broad surveys of this recent literature on ‘sticky’ DGE (NOEM) models that was initiated by the seminal ‘Redux’ model of Obstfeld and Rogoff (1995). Our strategy in this chapter is to focus on some key issues that are at the core of current research on open economy DGE modelling.

INTRODUCTION

During recent years economists have again been devoting attention to the issue of economic growth. In contrast to the neoclassical growth models derived in the Solow (1956)–Swan (1956) tradition, in which the steadystate rate of growth is given exogenously by technological and demographic factors, in the more recent literature the long-run growth rate is endogenously determined as the equilibrium outcome of the system; see, e.g., Barro (1990), Ireland (1994), Jones and Manuelli (1990), Lucas (1988), Rebelo (1991), Romer (1986) and Turnovsky (1996, 2000b). This is important, since it assigns a potentially significant role to fiscal policy as a determinant of long-run growth performance, something that is infeasible in the Solow–Swan framework. While the endogenous growth framework is not without its limitations, it provides an attractive and tractable approach to addressing issues pertaining to fiscal policy in an intertemporal context.

Most of the endogenous growth literature is based on perfect certainty. However, the endogenous growth framework can be easily extended to a stochastic context and thereby analyse issues relating to risk-taking and economic growth. The objective of this chapter is to construct such a stochastic growth model and to use it to analyse aspects of fiscal policy in the context of a stochastically growing economy. The formulation and solution of the problem employs continuous-time intertemporal optimising methods, rather than adopting the more familiar discrete-time approach. The main reason for this choice is that although continuous-time problems are tractable only under restrictive conditions, when these conditions are met, the solutions they yield are highly transparent, providing substantial insights into the characteristics of the equilibrium and the role of risk in its determination.

We should emphasise that our focus is on characterising the macroeconomic equilibrium, and to deriving its implications for macroeconomic policy-making – particularly fiscal policy – rather than on dwelling on the technical details of the solution procedures. At the same time, we should stress that the solutions themselves do involve substantial technical details and that the solutions to these stochastic growth models can be quite challenging.

A key assumption necessary to sustain a steady stochastic growth equilibrium is that all random disturbances are proportional to the current state of the economy, as represented by the capital stock or wealth.

I have written this book mainly for students who will need to apply maths in science or engineering courses. It is particularly designed to help the foundation or first year of such a course to run smoothly but it could also be useful to specialist maths students whose particular choice of A-level or pre-university course has meant that there are some gaps in the knowledge required as a basis for their University course. Because it starts by laying the basic groundwork of algebra it will also provide a bridge for students who have not studied maths for some time.

The book is written in such a way that students can use it to sort out any individual difficulties for themselves without needing help from their lecturers.

A message to students

I have made this book as much as possible as though I were talking directly to you about the topics which are in it, sorting out possible difficulties and encouraging your thoughts in return. I want to build up your knowledge and your courage at the same time so that you are able to go forward with confidence in your own ability to handle the techniques which you will need. For this reason, I don't just tell you things, but ask you questions as we go along to give you a chance to think for yourself how the next stage should go.