* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Macroeconomic Fluctuations in the UK Economy
Survey
Document related concepts
Fiscal multiplier wikipedia , lookup
Economics of fascism wikipedia , lookup
Non-monetary economy wikipedia , lookup
Edmund Phelps wikipedia , lookup
Fear of floating wikipedia , lookup
Full employment wikipedia , lookup
Monetary policy wikipedia , lookup
Inflation targeting wikipedia , lookup
Transformation in economics wikipedia , lookup
Phillips curve wikipedia , lookup
Austrian business cycle theory wikipedia , lookup
Post–World War II economic expansion wikipedia , lookup
Transcript
Macroeconomic Fluctuations in the UK Economy1 Keshab Bhattarai Department of Economics University of Hull Cottingham Road, Hull, HU6 7RX and Basil Jones, Ph.D. (Hull). Abstract: We present a simple model that can be useful in analysing the impacts official, monetary and exchange rate policies over the years. This model can take account of backward and forward looking expectations on prices and shocks in the demand and supply side of the economy. We implement the model with a simple VAR model using quarterly macroeconomic time series data of the UK economy from 1975 to 1999 and find persistency in unemployment and inflation and that the shocks in demand and supply tend to prolong up to ten periods. JEL Classification: E12, E30 Key words: Business cycle, UK economy July 2002 1 Correspondence regarding this paper should be directed to [email protected]. Phone: 44-1482-466483; Fax: 44-1482-466216. We appreciate the Social Science Faculty of the Hull University for the research grant #500R054. We are also grateful to the University of Essex for providing us an access to the quarterly macro time series data set for the UK economy in the Essex data archive through Navidata and MIMAS. Earlier version of this paper has appeared as Hull Advances in 1 I. Introduction Economies tend to grow over time but in an uneven fashion. The aggregate output, employment, investment, consumption and net exports all grow in good times and economy is close to full utilisation of resources. Consumers, producers and government are optimistic about future course of the economy. Such confidence propels economy forward. However, such optimism suddenly dies out when pessimistic outlook predominates in bad times. Downward swing continues until some confidence is restored among investors and consumers. Business planners, economic forecasters and policy planners study the economic scene intensely to detect signals of future macroeconomic developments. They are especially concerned with turning points, those times when the economic cycle reaches a peak or a trough in the cycle of economic activity. To that end, they watch a number of variables that tend to move systematically with, or even anticipate the business cycle. Business cycles are usually studied using quarterly data, in order to reveal enough details within the time period. In theory these macro time series tend to fluctuate around their long-term trends. Popular discussions in the UK emphasise the short run fluctuations associated with business cycles, to the point that cycles can have significant economic and political repercussions including bringing the governments down at home and a set of chains of upward or downward movement in the global economy. II. Literature Review The classical methods of business cycle analysis pioneered by Burns and Michell (1946) were successful at uncovering a broad set of statistical regularities observed among hundreds of economic time series. This massive body of empirical work provides the dominant background to most academic and policy discussion of macroeconomic developments. The qualitative features of business cycle behaviour they described have become the empirical foundation for modern business theory and set the standards for measuring and defining the business cycle characteristics of economic data. Insights provided by their methods of business cycle analysis serve as the foundation for theoretical models of business cycle behaviour and provide a standard to evaluate those models. For example, early Keynesian models were judged to be quantitatively successful in part because of the Adelman (1959) finding that Economic Policy working paper no. 5. All errors and omissions are of our own. 2 these models produced artificial time series whose cyclical properties could not be distinguished from historical business cycle behaviour on the basis of results generated using Burns and Mitchell methods. In order to investigate and measure the characteristics of different series over the business cycle, it is necessary to define the business cycle and to determine when it occurs. Burns and Mitchell adopted the working definition proposed earlier by Mitchell: Business cycles are a type of fluctuations found in the aggregate economic activity of nations that organise their work mainly in business enterprises: A cycle consists of expansions occurring at about the same time in many economic activities, followed by similar general recessions, contractions, and revivals which merge into the expansion phase of the next cycle; this sequence of changes is recurrent but not periodic; in duration business cycles vary from more than one year to ten or twelve years; they are not divisible into shorter cycles of similar character with amplitudes approximating their own. Burns and Mitchell investigated the business cycle characteristics of economic time series by constructing reference cycle patterns of cyclical behaviour, which compactly summarise business cycle properties of the data. These reference cycle pattern are the major tool used to describe the cyclical behaviour of economic time series within the ir framework. The first step in constructing these reference cycle patterns is to delineate periods of economic expansion and contraction and determine the specific dates of business cycle peaks and troughs. This is complicated by the fact that business cycles are characterised by the co- movements of many economic time series which are not perfectly in phase. However, peaks and troughs in a majority of individual series tend to cluster together with some regularity. Reference business cycle peaks and troughs are selected at the dates of these clusters. As McCallum (1989) points out, the real business cycle approach to modelling business cycle behaviour has gained attention for both theoretical and quantitative reasons. Growing dissatisfaction with the theoretical monetary misperception models of Lucas (1972) and Barro (1976) led to greater emphasis being placed on alternative equilibrium type models which could account for business cycle fluctuations. Further, 3 the real business cycle approach was indirectly supported by the empirical results of Sims (1980) and Nelson and Plosser (1982) which implied that nominal (monetary) shocks are incapable of generating typical business cycle behaviour in economic time series. However the most influential and quantitative support for real business cycle models was presented by Kydland and Prescott (1982). Their work was the first to show explicitly that a real business cycle model, driven by exogenous shocks to technology, was capable of generating time series with statistical properties characteristic of post war U.S. business cycles. Variability in the model’s data as well as co-variability between output and other variables in the model appeared to “match-up” well with the corresponding summary measure for similar U.S. economic time series. Kydland and Prescott (1982) showed that one could account for two-thirds of the U.S. economic fluctuations with a dynamic stochastic general equilibrium model from which nominal variables were totally absent, (Kydland and Zarazaga (1997)). They obtained this result using a variation of the same basic theoretical model economists had been using time and time again to study economic growth issues. What many economists found attractive about the Real Business Cycle (RBC) theory proposed by Kydland and Prescott was that for the first time, a business-cycle theory pointed to the possibility that the same analytical tools used to address economic growth issues could be used to address business-cycle questions as well. Beginning with Kydland and Prescott (1982), RBC theory initially concentrated on the closed economy and tried to construct a dynamic general equilibrium model, which mimics the business cycle features of the real economy. These models generate artificial data, such as output, consumption, investment and employment, from a model economy whose fluctuations are driven solely by technological shocks. Researchers then compare the co- movements and volatility of these simulated series with those present in actual data. Many proponents of RBC models tend to judge the success or failure of a model on how close these two measures calculated from artificial data are to their real counterparts. The real business cycle model is an extraordinarily bold conjecture in that it describes each stage of the business cycle – the troughs as well as the peaks as an equilibrium, 4 Hartley et al. (1997). The real business cycle model does not present a descriptively realistic account of the economic process, but a highly stylised or idealised account. This is a common feature of many economic models, but real business cycle practitioners are bold in their conjecture that such models nevertheless provide useful quantification of the actual economy. In particular, the real business cycle programme is part of a larger new classical economics, which is argued to provide satisfactory microfoundations for macroeconomics in a way that Keynesian models conspicuously failed to do (e.g. Lucas and Sargeant. (1979)). The claims that new classical models in general, and real business cycle models in particular provide microfoundations that is largely based on their use of a representative agent who solve a single dynamic optimisation problem on behalf of all the consumers, workers, and firms in the economy. Economic agent s maximize their objective function (utility or profits) subject to the resource and technology constrains and supply and demand in all markets are equal. What are the facts about business cycles Before the real business cycle models can be tested, we must know precisely what they are meant to explain. Following Prescott (1986), advocates of real business cycle models have defined the explanandum of business cycles. Business cycle theory has traditionally tried to explain what causes output to fall and then rise again. To be sure when output declines one expects employment, income, and trade to decline as well. Nevertheless the central fact to be explained was believed to be the decline and the subsequent recovery and not the co- movements of the aggregate time series. Two important measures of business cycles are the co-movement of economic variables and their volatility. While volatility issues, such as the smoothness of consumption and the magnitude of investment fluctuations, have been continuously subject to examination within business cycle research, co- movement issues have not always been emphasised. For example, time series studies often concentrate on single variable, such as output, to characterise the business cycle – e.g Hamilton (1989) and Hess and Iwata (1997). An early definition by Burns and Mitchell (1946) highlighted that expansions occurred simultaneously across many economic activities, followed by similar general recessions, contractions and revivals, which then merge into the expansion phase of the next cycle. Fortunately, the early tradition of emphasising the co-movement of economic variables at business cycle frequencies has been revived in 5 real business cycle (RBC) theory. Interest in the long run effect of business cycles was revived recently as part of the interest in endogenous growth. While the long run growth was traditionally thought of as entirely driven by some unexplained trend of technical progress, endogenous growth theory explicitly takes into account the fact that technical progress itself has economic determinants and depends on the incentives to innovate, to acquire education and on the acquisition of knowledge as a by-product of economic activity. Since the basic claim is that the business cycle is potentially as much a product of the permanent as the transitory component, it will be apparent that the “policy” one needs to discuss is not just monetary and fiscal settings but also actions designed to influence the longer-term performance of the economy. From the perspective of this paper, there seem to be three things that policy might aim at in influencing the cycle – the long-term growth rate, the degree of persistence of shocks, and the standard deviation of growth rates. The long-term growth rate is generally regarded as a phenomenon associated with growth in output and technical change. While growth in capital and labour is predictable, arrival of technology is stochastic. While increased R&D may be important for it, creating an environment that is conducive to the adoption of innovations, such as various micro-economic reform measures, is possibly just as important. A study of the factors that lead to an improvement in long-run growth potential is therefore a study of how to mitigate the classical cycle, although it would do nothing for the growth cycle. A second dimension along which policy may modify the cycle is through the degree of persistence of shocks. Whether policy can influence this depends a great deal upon the source of the persistence and it is here that one needs to be able to flesh out the parametric statistical model with some economic structure. If the RBC is correct, the persistence derives from the fact that a TFP shock remains for a long time. One way of categorising the post war literature on models of business cycles is into deterministic approach and stochastic approach, Muellbauer (1997). In the former 6 category come simple multiplier/accelerator models of aggregate demand, typically ignoring the supply side, which generate second-order differencing equations. Less convincing are the aggregate demand models with floor and ceilings (Barnett et al., 1989 and Grandmont 1991, 1993). Real business cycle (RBC) models can be seen as the attempt to account for observed fluctuations without appeal to phenomena such as sticky wages or lagged responses, which characterise approaches emphasising the demand side. The process of verifying, sharpening or refuting the real-shock account of business cycles has generated a large body of theoretical and empirical research. This framework assumes that the macroeconomy usually obeys simple behavioural relationships but is occasionally disrupted by large “shocks,” which force it temporarily away from these relationships and into a recession. The behavioural relationships then guide the orderly recovery of the economy back to full employment, where the economy remains until another significant shock upsets it. There are controversies about the methods used in empirical research on business cycles Quah (1997), Gregory and Smith (1997). There are criticisms of business cycle research made by econometricians and criticisms of econometricians made by business cycle researchers who use calibration and the heavy use of simulations to derive operating characteristics of models. These researchers argue that such practice allow one to focus on the important economic issues and makes transparent the economic significance of particular failures of their models. III. UK Macroeconomic Series In this section, we look at certain key statistics of the UK economy over a period of time so as to gain some insights into the performance of the UK economy. It is useful to examine the performance of the UK economy against the background of the aims of government’s macroeconomic policy. They are full employment, stable prices, and economic growth and balance of payments equilibrium. Apart from these four objectives, we can also recognise that the government may also have additional objectives concerned with such factors as for example the distribution of income, the size of the government sector within the economy ect. 7 We commence by looking at the extent to which the four policy objectives noted above were achieved. Table 1 shows the growth of national income, the rate of inflation and the current account balance over the period 1975-1999. The measure of national income is the growth of real GDP at market prices. Inflation is the retail price index excluding mortgage interest payment (underlying rate of inflation). From Table 1, it can be seen that national income has increased and growth rates were positive throughout the period. There are however considerable variations in individuals years ranging from –2.2 percent in 1980 to 5.1 percent in 1988 and 2.1 percent in 1999. These growth rates provide one measure of the trade cycle (stop/go phenomenon) which existed during this period, (see figure 1). Fig.1 - Deviation of output from equilibrium 8 6 4 2 0 19 7 19 0Q2 7 19 1Q3 72 19 Q4 7 19 4Q1 75 19 Q2 7 19 6Q3 7 19 7Q4 79 19 Q1 8 19 0Q2 8 19 1Q3 82 19 Q4 8 19 4Q1 85 19 Q2 8 19 6Q3 8 19 7Q4 89 19 Q1 9 19 0Q2 91 19 Q3 9 19 2Q4 9 19 4Q1 95 19 Q2 9 19 6Q3 9 19 7Q4 99 Q1 -2 -4 -6 -8 Source: Navidata 3.1, ONS, 2000 8 Turning to the rate of inflation, this averaged to 4.70 percent per annum over the full period. In general rates of inflation tended to trend upwards throughout the period up to about 1980 although there were notable variations from this trend for individual years for example the rate of inflation rose and then dropped by approximately eight percentage points for the years 1977-1978. The highest figure recorded was 16.9 Fig. 2: RPI 30 25 20 15 10 5 19 98 Q4 19 97 Q2 19 95 Q4 19 94 Q2 19 92 Q4 19 91 Q2 19 89 Q4 19 88 Q2 19 86 Q4 19 85 Q2 19 83 Q4 19 82 Q2 19 80 Q4 19 79 Q2 19 77 Q4 19 76 Q2 19 74 Q4 19 73 Q2 19 71 Q4 19 70 Q2 0 Source: Navidata 3.1, ONS, 2000. percent for the years 1980 and the lowest figure 2.3 percent in 1999. The highest sequence of inflation was for the period 1975-1981 where inflation for each year exceeded 10 percent per annum. It is also notable that the swings in the rate of inflation did not precisely synchronise with cycles in the growth rate of national income, (see figure 2). The third key macroeconomic statistics refers to the terms of trade. For the whole period, the current account of the balance of payments showed a mean deficit of £…… million. The size of the deficits increased over time. One reason for the poor trade performance of the UK economy is the relatively higher rates of inflation experienced in the UK compared with other developed nations. The Pound sterling remained slightly overvalued which resulted in a loss of competitiveness of UK exports with the ROW. This is evidenced by the pattern of the sterling exchange rate compared with two other major currencies, i.e. the $ and Dmark. It is evident from Table 2 that the period 1970-1999 is characterised by a marked depreciation of the 9 pound against the two currencies. Table 1: Key Statistics of the UK Economy 1975-1999 Year 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Growth of Inflation national income % per annum % per annum 2.8 2.3 3.5 2.7 -2.2 -1.3 1.9 3.8 2.4 3.7 4.2 4.5 5.1 2.1 0.7 -1.5 0.1 2.3 4.4 2.8 2.6 3.5 2.6 2.1 16.7 15.9 8.6 12.6 16.9 12.2 8.5 5.2 4.5 5.2 3.6 3.7 4.6 5.9 8.1 6.7 4.7 3 2.3 2.9 3 2.8 2.6 2.3 Terms of Trade 2 -0.0029 0.0056 0.0165 0.0074 0.0174 -0.0004 -0.0015 -0.0004 -0.0026 0.0030 -0.0119 -0.0007 -0.0001 -0.0045 -0.0006 0.0030 0.0041 0.0016 -0.0065 -0.0074 0.0038 This is particularly evident against the Dmark, the rate of exchange for which declined from 5.45 Dmark per £1 in 1975 to 2.91 per £1 in 1998. The broad trend in the movement of the effective exchange rate since 1975 can be divided conveniently into four phases. The first phase from 1975 to 1977 was a period of steady decline and rapid depreciation. In the second phase between 1978 to 1981 the effective exchange rate generally appreciated in value. The third stage from 1982 to 1996 was one in which the effective exchange rate has once again trended downwards reaching a low 2 Terms of trade = (percentage change in export prices)*exports/GDP – (percentage change in import 10 in 1996. Although the trend since 1982 has been downwards, it is evident from Fig3. That there has been considerable movement about the trend, with spells of depreciation followed by partial appreciation and this cycle repeated, though not with any degree of regularity. The movement of sterling relative to individual currencies, particularly the dollar, has been more volatile although until 1981 the broad trends were very similar to that of the effective exchange rate. Fig. 3 - Deviation of real exchange rate from trend 4 3 2 1 0 19 70 Q 19 2 72 Q 19 1 73 Q 19 4 75 Q 19 3 77 Q 19 2 79 Q 19 1 80 Q 19 4 82 Q 19 3 84 Q 19 2 86 Q 19 1 87 Q 19 4 89 Q 19 3 91 Q 19 2 93 Q1 19 94 Q 19 4 96 Q 19 3 98 Q2 -1 -2 -3 Source: Navidata 3.1, ONS, 2000 After 1972, the UK balance of payments position underwent important changes, most of which can be traced back to three major factors. First, the floating of sterling in 1972 following the end of the Bretton Woods era to the general international move towards floating exchange rates by the major industrial countries. This in turn changed considerably the role and constraints associated with balance of payments management. The second factor was the UK’s accession to the EC in January 1973 which it is estimated, resulted in the UK running a large balance of payments deficit or a small surplus than would other wise have been the case. The third and probably the most immediate importance for the UK, was the discovery and subsequent exploitation of North Sea oil. Accompanying these developments were the dramatic changes in the world price of oil: sharp increases in 1973 and 1979, followed by a prices)*imports/GDP taken from the World Bank database. 11 precipitate slump in 1985-86. Table 2: Key Exchange Rates 1975-1999 Year $ per £1 Dmark per £1 1975 2.2198 5.447 1976 1.8046 4.551 1977 1.7455 4.051 1978 1.9197 3.85 1979 2.1225 3.888 1980 2.3281 4.227 1981 2.0254 4.556 1982 1.7489 4.243 1983 1.5158 3.87 1984 1.3364 3.79 1985 1.2976 3.784 1986 1.4672 3.183 1987 1.6392 2.941 1988 1.7796 3.124 1989 1.6383 3.079 1990 1.7864 2.876 1991 1.7685 2.925 1992 1.7665 2.751 1993 1.5015 2.483 1994 1.5329 2.481 1995 1.5783 2.26 1996 1.5617 2.35 1997 1.6382 2.84 1998 1.6574 2.914 1999 1.618 Source: Navidata, ONS 2000 3 £ Sterling effective exchange rate 3 129.6 112.3 106.8 107.2 113.1 124.4 127.8 123.3 115.6 111.4 111.3 101.4 99.3 105.3 102.3 100 100.7 96.9 88.9 89.2 84.8 86.3 100.6 103.9 103.8 Formula for the real exchange rate: cpi(local)/cpi(USA)*official ER 12 16 14 12 10 8 6 4 2 0 19 70 Q2 19 71 Q4 19 73 Q2 19 74 Q4 19 76 Q2 19 77 Q4 19 79 Q2 19 80 Q4 19 82 Q2 19 83 Q4 19 85 Q2 19 86 Q4 19 88 Q2 19 89 Q4 19 91 Q2 19 92 Q4 19 94 Q2 19 95 Q4 19 97 Q2 19 98 Q4 % Fig. 4: - URATE Year Source: Navidata 3.1, ONS, 2000. Following the floating of sterling, 1973-76 saw a worsening of the current account deficits of unprecedented magnitudes because the pound remained overvalued. Overall, however, the UK was able to absorb a sequence of large current account deficits without having to undertake a major adjustment program as would otherwise have been required in the absence of North Sea oil. The turnaround in the balance of payments was eve n more dramatic than its earlier deterioration. The oil price rise of 1979 coincided with the coming on stream of major North Sea oil fields. Oil exports doubled between 1979 and 1981, even as non-oil visible balance deteriorated further. The net result was a shrinking of the overall deficit on visible trade which together with the continued strengthening of the invisible balance, combined to produce a sequence of record current account surpluses from 1980-85. The fall in the price of oil in 1985-86 coincided with the levelling-off of output from the North Sea and resulted in a fall in the net oil contribution to the visible balance. From 1986 onwards, the UK returned to the situation of the mid-seventies in experiencing significant current account deficits despite having substantial reserves of North Sea oil. 13 The fourth major objective discussed above is the target for full employment. To do this we present a graph for quarterly unemployment rate for the period 1970-1999, Fig. 4. Unemployment has a high cost. Individuals who are unemployed feel a loss of self-esteem and dignity, which cannot be measured. They are more prone to illness and their families suffer from poverty. The output that the unemployed would have produced and the income they would have earned are lost forever. By being unemployed the worker’s career development is damaged and their skills deteriorate. The civilian labour force has grown by over two million since 1971 and that this was almost entirely due to the increase in the number of fe males. The male labour force has remained virtually static throughout this period. In 1971 females accounted for 37.3 percent of the workforce, by 1999 this figure rose to 42.5 percent. Much of the increase in the female activity rate has been associated with an increase in part time employment particularly for married women. Between 1948 and 1968, the annual unemployment rate in the UK averaged 1.8 percent and never rose above 2.6 percent. The following two decades witnessed a remarkably different story, especially during the 1980s when a new dimension was added to the post war history of UK unemployment. The unemployment rose from 2 percent in 1974 to 4 percent in 1979. This was followed by a remarkably sustained increase to over 11 percent in 1986, when more than 3 million people were recorded as claiming unemployment benefit. During the 1980s all industrialised countries were experiencing high unemployment. The fact that there was an upward shift in unemployment was wide spread across the world’s major trading nations suggests the existence of a common cause. First the sharp and unprecedented increase in the price of oil in 1973/74 from three dollars to ten dollars a barrel had serious adverse effects on the balance of payments of the major industrial nations, all of which relied heavily on imported oil. This oil price increase also provided an unwelcome impetus to inflation. In order to rectify their balance of payments deficits on current account and to deal with the threat of inflation, these nations deflated their economies by operating more restrictive fiscal and monetary policies. Similar polices were introduced in the aftermath of the increase in oil prices in 1979/80, this time from 13 dollars to 29 dollars a barrel. The effect of these two world-wide recession on the UK unemployment rate was an increase from 2.2 percent in 1974 to 5.2 percent in 1977; and an increase from 4.5 14 percent in 1979 to 11.3 percent in 1983. The UK’s balance of payments and unemployment rate should have been helped by the oil price increase of 1979/80 at a time when it became a net exporter of oil. The answer is that the sudden increase in the value of the UK’s oil reserves coupled with the tight monetary policy during 1980/81 caused a substantial appreciation of the sterling exchange rate. The dollar sterling exchange rate rose from 1.74 dollars per pound in 1977 to 2.33 dollars per pound in 1980. This led to a sharp decline in the UK’s export competitiveness, which had particularly harmful effects on the manufacturing sector. Different components of GDP including consumption, investment, government expenditures and revenues, exports and imports account for its cyclical volatility. For virtually all countries and time periods, all components of GDP except consumption generally are more volatile than GDP. This finding is consistent with the presence of a consumption smoothing motive, that is the desire for consumers to maintain a relatively smooth stream of consumption over time in the face of volatility in their income and wealth. Table 3: Variability of Key Macro Variables over the Cyclea output consumption Investment Gov. Exports Imports spending Prices (GDP deflator) % standard deviation relative to standard deviation of output EU 1.12 0.87 2.23 0.47 2.35 3.26 1.00 Japan 1.66 0.73 2.80 3.76 6.99 11.67 1.98 USA 1.73 0.71 3.01 1.18 6.82 5.17 0.90 a Variability is measured as the standard deviation of seasonally adjusted and detrended values using the Hodrick- Prescott filter. Source: Burda and Wyplosz (1997) Ch. 14 2 pp. 361 Prices are less variable than output, which is consistent with the keynesian assumption. Consumption is smoother than output, output is smoother than investment expenditure and trade (exports and imports) represents the most unstable component of GDP. 15 IV. The Model Though the research on business cycle, either in the traditional sense or in the multiplier accelerator settings or in the real business cycle tradition has gone much further, a very simple model based on IS-LM or AS-AD analysis is still more popular among the business cycle practitioners. A very simple business cycle model should be able to show the effect of fiscal policy (budget deficit), movements in the real exchange rates and real interest rates on output. Beside these demand side effects it should also explain formation of prices and its effect on outputs in the supply side. Furthermore, some macroeconomists have advanced the idea that shocks to the supply side or “real” factors cause many, if not most of the ups and downs in the economy. This idea could be captured by shocks either on the demand or the supply sides in this simple model. Thus this simple models takes account of the traditional macroeconomic notion that changes in the aggregate demand causes most of the fluctuations on the one hand and effect of real disturbances through shocks on the other. While some shocks are amenable to policy corrections others are immediate and have no clear policy options before such shocks hit the economy. Our simple business cycle model consists of four equations that explain aggregate supply, aggregate demand, prices, and unemployment rate. We also incorporate four policy variables: budget deficit, real exchange rate, real interest rate and core inflation. Thus this model is a useful frame work to study the impacts of fiscal, monetary, exchange rate policies and effect of trade unions and labour market conditions in price setting process. A formal presentation of the model underlying the AD-AS framework with underlying IS and LM analysis is as following. We assume an autoregressive process for aggregate prices Pt = Pt −1 (1 + π t ) . This ∗ implies that the real exchange rate to be λt = ∗ Et Pt (1 + ε t )(1 + π t ) , λt = where ε is Pt 1+πt the (expected and actual) rate of change of the exchange rate and π * is the foreign rate of inflation assumed to be constant. Thus equilibrium value of the real exchange rate λ, is influenced by the nominal as well as the domestic and foreign inflation. Given these relations between the past and current prices as well as the relation between domestic and foreign inflation in determining the competitiveness of the economy the 16 aggregate demand consistent with goods market equilibrium given by the regular IS curve, under the Mundell Flemming assumptions is: − − − − Yt − Y = βFPt + γ ( λt − λ t ) − ϕ ( i − π t ) + s1t (1) where a bar above a variable denotes its long run value, ie Y . These long run trends are given by Yt = β 0 + β1t t + ut , linearised around the long-run equilibrium. Here, − FPt is a fiscal policy variable (budget deficit), λt − λ t represents the exchange rate − − policy, and i − π t represents monetary policy. Finally the last term in (1) s1t represents shocks in aggregate demand. Thus fiscal, monetary and exchange rate policies can influence aggregate demand. Parameters β, γ, and ϕ explain the relation of fiscal, exchange rate and monetary policy on aggregate demand their expected signs are β >0, γ <0, and ϕ <0. Thus this model summarises the effects of internal and external balances on demand side of the economy in the short run. Analysis of supply side of the economy is different in the short and long run. Output is determined by the amount of capital and labour inputs as well as the level of technology in the long run. However, business cycle models emphasise short run factors in determining the supply side of the economy. The short run supply side factors are often represented by the deviation of general prices from the core underlying price structure. In this tradition a simple aggregate supply is given by the combination of inflation and output as explained by the following equation − − π t =π t +b1 (Yt − Y ) +s 2t (2) where π t = core inflation rate in t, Y = trend (equilibrium) level of output s 2,t = one-off supply shock (e.g. oil price increases, indirect tax increases). It is assumed that b1 > 0 and that s 2,t represents a random shock with expected value equal to zero. Core inflation depends on wage bargaining along with increase in productivity and mark-up practices among the monopolistic firms. In simple form it captures both past experience and future expectations. A simple price setting process that incorporates 17 both backward and forward looking expectations can be summarised by the following equation: − π t = απ t+1 + (1 − α )π t −1 (3) where π t = core inflation in t. The constant α is restricted between zero and one so that 0 < α < 1. Thus the core inflation is higher when the economy is overheating as given by (2) and lagged term π t −1 in equation (3) and the expectation of future by the economic agents (particularly the employers and employees) in the economy as captured by π t +1 . Our last equation relates to the relation of unemployment rate with the output gap on the one hand and difference between foreign and domestic inflation on the other. It can be presented as following. . − Ut = γ 1 (Yt − Y t ) − γ 2 (π t − π t∗ ) + s 3t Ut Here (4) U& t is the change in the unemployment rate which depends upon the output gap Ut Yt − Y (in line with the Okun’s (1962)) and differences between domestic and foreign prices (Phillips (1958)), π t − π t∗ and shocks in the labour market, s 3, t . We expect unemployment to be lower when the current output, Yt , is higher than the trend output, Y and vice-versa. Similarly, higher domestic prices relative to foreign prices due to an expansion in aggregate demand implies lower unemployment rate. Labour market shocks can either be positive or negative. V. Results This section discusses empirical findings on aggregate demand and aggregate supply and unemployment- inflation tradeoffs using simple macroeconomic model as outlined above. First we use unit root tests to assure stationarity of variables included in the model. Then we present empirical results on aggregate demand and aggregate supply using single equation estimation methods. Finally we study simultaneous relation between unemployment and inflation using impulse response anlaysis. 18 a) Unit root tests The first step in applying the cointgration techniques is to determine the order of integration of each variable. The standard practice is to use the Augmented Dickey Fuller (ADF) tests. For our analysis, we use quarterly data from the Office of National Statistics. Before the estimating the cointegration paramenters, ADF test statistic was calculated to indicate the order of integration in each univariate time series. Table 4. gives the results of the ADF test for non stationarity in the variables. The usual selection criteria based on the AIC or SBC determines the lag length used. The null hypothesis is that the series are non stationary against the alternative that they are stationary. An acceptance of the null hypothesis will imply that the corresponding series are non stationary and have unit roots, while a rejection of the hypothesis will imply that the series are stationary with a well-defined mean and variance. As the results indicate, the null hypothesis of non stationarity cannot be rejected in all the case for the level of deviation of the series from trend but can be rejected for the other variables with intercept and trend suggesting stationarity. Table 4: Unit Root Test Intercept only Level Intercept with trend Lag length Level Lag length YY -0.80 0 -0.90 0 DEF -3.67 6 -3.80 6 RR -3.12 4 -3.76 5 RIR -2.89 0 -3.49 0 INF -2.44 1 -3.96 1 URATE -4.09 0 -4.19 0 An asterisk denotes ADF with trend. CV = -2.88 without trend and –3.45 with trend. a) Aggregate Demand : The results for the aggregate demand is 19 YYt = −0.01 − 0.06 DEFt − 0.09 RRt + 0.03RIR + 1.00YYt −1 t-ratio -0.31 2.01** -1.22 39.65*** R2 = 0.94; F (4,113) = 463.1*** ; DW-stat. = 1.81 b) Aggregate Supply: The results for the aggregate supply is RPI t = −0.05 + 1.00CINFt + 0.07YYt t-ratio 82.43*** 2.97*** R2 = 0.98; F (2,116) = 3398.0*** ; DW-stat. = 1.06 c) Unemployment Equation The results for unemployment is URATEt = −7.98 − 0.87YYt − 0.15DINFt t-ratio -11.4*** -2.57*** R2 = 0.53; F (2,116) = 65.24*** ; DW-stat. = 1.05 The results obtained using a simple model of aggregate supply/demand equation is plausible. For the aggregate demand YYt-1 term is included to account for serial correlation. The deviation of output is inversely related to the budget deficit (DEF) and the deviation of real exchange rate from equilibrium (RR) and positively related to the real interest rate. The aggregate supply equation shows that inflation is positively related to core inflation and deviation of output from its equilibrium level. In the unemployment equation, U.K. unemployment is negatively related to the deviation of output from its equilibrium level and negatively related to the inflation differential between the domestic and foreign inflation (DINF). High inflation will cause a reduction in output as in the stagflation period of the 1980s. In the 1990s the 20 U.K. economy has been growing steadily with the lowest levels of unemployment recorded. Impulse response to shocks in supply and demand. Above results show that output level is influenced by budget deficit and prices. We also expect a negative relation between output and inflation at least in the short run. However the hysterisis hypothesis in the labour market implies persistency of unemployment rates over period. Such hysteresis effect also spills over to the unemployment rate. We use a simple VAR model to trade out the impulse response to both a supply shock and a demand shock in unemployment an inflation in this model. The equations for these shocks can be represented as follows OLS Estimation of a single equation in the Unrestricted VAR Dependent variable is URATE Regressor Coefficient T-Ratio [Prob] RPI(-1) 0.37 2.19 [0.30] RPI(-2) -0.56 -2.09 [0.39] RPI(-3) 0.33 2.07 [0.04] URATE(-1) 0.42 4.39 [0.00] URATE(-2) 0.19 1.92 [0.06] URATE(-3) 0.18 1.92 [0.06] CONSTANT 0.14 0.17 [0.86] DEF -0.49E-4 -0.89 [0.37] DEF(-1) -0.49E-4 -0.59 [0.56] RIR 0.13 1.74 [0.08] R2 = 0.66 F-stat. DW-statistic = 2.05 F(9,106)=22.8 [0.0] Diagnostic Tests: LM Version Serial Correlation CHSQ (4) = 5.96 [0.202] Functional Form CHSQ (1) = 0.37 [5.43] Normality CHSQ (2) = 886.6 [0.00] Heteroskedasticity CHSQ (1) = 1.02 [0.313] 21 Supply Shock: uit =β11 Luit + β12 Lπ it + ε it Demand Shock: π it = β 21 Luit + β 22 Lπ it + ε2t Where π and u are inflation rate and unemployment rate respectively and L is the lag operator. We can estimate these two equations and make short term forecasts for changes in fiscal policy, deviation of real exchange rates and real interest rates for policy simulation. Using Microfit 4.0 we otain the following VAR estimates. OLS Estimation of a single equation in the Unrestricted VAR Dependent variable is RIP Regressor Coefficient T-Ratio [Prob] RPI(-1) 1.39 13.82 [0.00] RPI(-2) -0.58 -3.62 [0.00] RPI(-3) 0.06 0.64 [0.53] URATE(-1) -0.02 -0.28 [0.78] URATE(-2) -0.11 -1.79 [0.08] URATE(-3) 0.06 1.02 [0.31] CONSTANT 1.58 3.25 [0.00] DEF 0.68E-5 0.21 [0.84] DEF(-1) 0.12E-4 0.34 [0.73] RIR -0.08 -1.73 [0.09] R2 = 0.96 F-stat. DW-statistic= 1.96 F(9,106) = 252.3 [0.0] Diagnostic Tests: LM Version Serial Correlation CHSQ (4) = 19.81 [0.001] Functional Form CHSQ (1) = 4.74 [0.03] Normality CHSQ (2) = 76.69 [0.00] Heteroskedasticity CHSQ (1) = 19.56 [0.00] These results show the business cycle effect on both prices (inflation) and unemployment. There is evidence of the Phillips curve in the dataset. Past 22 unemployment is important in the determination of current inflation rate. When past unemployment is high, unions bargain for higher wages, as there is a slack in the labour market. Furthermore unemployment is persistent over a period and supports the unemployment hysterisis. The result is consistent across the two models. It takes time for inflation to adjust following government intervention to reduce the rate of inflation. In the result, positive inflation coefficient is followed by a negative inflation coefficient. Economic operators closely watch the inflation rate especially the Bank of England Monetary Policy Committee. A fall in inflation is felt throughout the financial market. Impulse Response These two impulse response diagrams show the short run fluctuation in the long run steady state. It displays the Philips curve phenomenon, showing the trade off between unemployment rate and inflation. A unit shock to the inflation rate in period one will cause expectations to build up in the next period. As adjustment happens, inflation and unemployment returns to their long run natural level after 20 quarters. Generalised Impulse Responses to one SE shock in the equation for RPI 2.0 1.5 1.0 RPI 0.5 0.0 -0.5 0 5 10 15 20 25 30 35 40 45 5050 Horizon Generalised Impulse Responses to one SE shock in the equation for URATE 2.5 2.0 1.5 URATE 1.0 0.5 0.0 -0.5 0 5 10 15 20 25 30 35 40 45 5050 Horizon 23 VI. Conclusion: We present a brief review of literature and some stylised facts about business cycle in the UK economy. We discuss a simple model to study the cyclical fluctuation of output, employment and prices. This model can take account of fiscal, exchange rate and monetary policy. We show a structure where the forward and backward looking expectations in prices influence aggregate demand and aggregate supply in the short run. Evidence suggests persistency of unemployment and inflation in line with the hysteresis hypothesis and trade off between unemployment and inflation during our study period (1st quarter of 1975 to the last quarter of 1999). We find shocks arising either in demand or supply side tends to prolong up to 10 quarters in the future. 24 References: Adelman. I, and F. Adelman, (1959), “The Dynamic Properties of the KlienGoldberger Model” Econometrica, 27: 596-625. Artis et al.; (1995), “Turning Point Prediction for the UK Using CSO Leading Indicators,” Oxford Economic Papers, 47, 397-417. Artis, M.J. (1996), “The UK Economy: A Manual of Applied Economics,” Fourteen Edition. Oxford and New York: Oxford University Press. Backus, D.K., Kehoe, P.J. and Kydland, F.E., (1992), “International Real Business Cycles,” Journal of Political Economy, 101, 745-75. Backus, D.K., Kehoe, P.J. and Kydland, F.E., (1993), “International Business Cycles: Theory and Evidence,” Federal Reserve Bank of Minneapolis, Quarterly Review, 17, 14-29. Barnett, W.A., Geweke, J., And Shell, K. (eds) (1989), “Economic Complexitity: Chaos, Sunspots, Bubbles and Nonlinearity”, Proceedings of the Fourth International Symposium in Economic Theory and Econometrics, Cambridge University Press Bean, C. (1998), “The New UK Monetary Arrangements: A View from the Literature,” Economic Journal; 108(451). Blanchard, O.J. and L. Summers (1986) “Hysterisis and the European Unemployment Problem,” NBER Macroeconomic Annual 1986 (ed. S. Fischer), Cambridge: MIT Press. Burda, M.C. and C. Wyp losz, (1997), “ Macroeconomics, a European Text” OUP Burns, A and W. Michell, (1946), “Measuring Business Cycles” NBER, New York. Barro, R. J. (1976), “Rational Expectations and the Role of Monetary Policy” Journal of Monetary Economics, 2 (January): 1-32 Chauvet, M,.; (1998), “An econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching,” International Economic Review, Vol 39, No. 4 969-995. Church, K.B. (1996), “ Targeting Inflation: Comparative Control Exercises on Models of the UK Economy,” Economic Modelling; 13(2). Church, K.B. (1997), “ Comparative Porperties of Models of the UK Economy,” National Institute of Economic Review; 0(161). Church, K.B. (1999), “Properties of the Fundamental Equilibrium Exchange Rate in the Treasury Model,” National Institute of Economic Review; 0(161). Cromb, R. (1993), “Survey of Recent Econometric Work on the NAIRU,” Journal of 25 Economic Studies; 20(1-2). Evans, G.W. (1993), “Sectoral Imbalance and Unemployment in the United Kingdom:1963-84,” Oxford Economic Papers; 43(3). Grandmont, J.M., (1991), “Expectations Driven Business Cycles,” Eurpoean Economic Review, 32(2-3) 293-9. Grandmont, J.M., (1993), “On Endogenous Competitive Business Cycles,” in M.Jarsulic (ed.) NonLinear Dynamics in Economic Theory, Aldershot, Edward Elgar, 315-65. Gregory, A.W and Smith, G.W. ((1995), “Business Cycle Theory and Econometrics,” Economic Journal; 105, 1597-608. Haldane, A. and Quah, D. (1999), “UK Philips Curves and Monetary Policy,” Journal of Monetary Economics; 44(2). Hamilton, J., (1989), “A new Approach to the Econometric Analysis of Nonstationary Time Series and the Business Cycle,” Econometrica 57 357-384. Hartley, J., Hoover, K and Salyer, K. (1997) “The Limits of Business Cycle Research: Assessing the Real Business Cycle Model,” Oxford Review of Economic Policy; 13(3). Hasan, M.S. (1999), “New Evidence on Causal relationships between the Money Supply, Prices and Wages in the UK,” Economic Issues; 4(2). Hess, G.D. and S. Iwata., (1997), “Measuring and Comparing Business Cycle Features,” Journal of Business and Economic Statistics, 15, 432-44 Holden, K. and Peel, D.A. (1988), “Comparison of Some Inflation Growth and Unemployment Forecasts,” Journal of Economic Studies; 15(5) Holland, A. and Scott, A. (1997), “The Determinants of UK Business Cycles,” Bank of England Working Paper No. 58. Holly, Sean and Martin Weal (2000), (eds), “Econometric Modelling: Techniques and Applications, “ Cambridge University Press. Jaeger, A and Parkinson, M. (1994), “Some Evidence of Hysterisis in Unemployment Rates,” European Economic Review; 38(2) Jenkinson, T. (1996), “Readings in Macroeconomics,” Oxford and New York: Oxford University Press King, R.G. and Plosser, C.I. (1994), “Real Business Cycles and the test of the Adelmans,” Journal of Monetary Economics, 33, 405-38. Kydland, Finn. E. and E. Prescott, (1982), “Time to Build and Aggregate 26 Fluctuations”, Econometrica 50 (November) 1345-70 Kydland, Finn. E. and C. E. Zarazaga, (1997), “Is the Business Cycle in Argentina Different,”Federal Reserve Bank, Economic Review, Fourth Quarter, 21-36. Lucas, Robert. J (1972), “ Expectation and the Neutrality of Money, “ Journal of Economic Theory 4:103-124 Lucas, Robert. J and T.J. Sargent (1981), eds. “Rational Expectation and Econometric Practice,” Minneapolis, Minn: University of Minnesota Press. McCallum, B.T. (1989), “Real Business Cycle Models” in Robert J Barro ed., Modern Business Cycle Theory, 16-50. Cambridge: Harvard University Press McCormick, B. (1997), “Regional Unemployment and Labour Mobility in the UK,” European Economic Review; 41(3-5). Millard, S Scott, A and Sensier, M. (1997), “The Labour Market over the Business Cycle: Can Theory Fit the facts?,” Oxford Review of Economic Policy; 13(3). Muellbauer, J. (1997), “The Assessment: Business Cycles,” Oxford Review of Economic Policy; 13(3). Muellbauer, J. and K. Mayhew (1997), (eds) “ Business Cycles,” Oxford Review of Economic Policy; 13(3). Nelson , C.R. and C. I. Plosser (1982) “Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications.” Journal of Monetary Economics 10 (September): 139-162 Nickell, S. (1990), “Inflation and the UK Labor Market,” Oxford Review of Economic Policy; 6(4) Winter. Nickell, S.J and Wadhwani, S. (1990), “Insider Forces and Wage Determination,” Economic Journal; 100(401). Okun, A. (1962), “Potential GNP: Its Measurement and Sigtnificance: Proceedings of the Business and Economic Statistics. American Statistical Associatio n 98-103. Washington D.C. Pagan, A. (1997), “Policy, Theory and the Cycle,” Oxford Review of Economic Policy; 13(3). Pelloni, A. (1997), “Nominal Shocks, Endogenous Growth and the Business Cycle Characteristics,” Economic Journal; 107 474-76. Phillips, A.W. (1958), “The Relationship Between Unemployment and the Rate of Change of Money Wages in the United Kingdom, 1986-1957. Economica 25 (November) 283-299. 27 Prescott, E.C. (1986), “Theory Ahead of Business Cycle Measurement,” Federal Reserve Bank of Minne apolis, Quarterly Review; Fall. Quah, D.T., (1995), “Business Cycle Empirics: Calibration and Estimation,” The Economic Journal 105 (November) 1594-1596 Ravn, M.O. (1997), “Permanent and transitory Shocks and the UK Business Cycles,” Journal of Applied Econometrics; 12, 27-48. Robinson, B, (1994), “Structural Adjustment in the UK Economy: The Effects of North Sea Oil,” in Holly.S., ed. Money, Inflation and Employment: Essays in honour of James Ball. Aldershot UK: Elgar. Saunders, P.J. (1994), “Empirical Evidence on Causal Relationships between Money Supply, Prices and Wages in the UK,” British Review of Economic Issues; 16(39). Sims, C. (1980), “Macroeconomic and Reality,” Econometrica, 48, 1-49 28