THE WORLD ECONOMY.
Naisbitt, Barry ; Hantzsche, Arno ; Lennard, Jason 等
Box A. The Great Synchronisation Economic growth has risen in a synchronised manner around the world in recent years (King, 2018; IMF, 2018; Naisbitt et al., 2018), but to what extent is synchronised growth unusual? In this box, I investigate the degree to which economic growth has been synchronised across twenty OECD countries from the first age of globalisation to the present. A simple measure of synchronicity is the standard deviation of the rate of economic growth across countries. Figure AI plots how this measure has evolved over time, where a lower (higher) standard deviation represents higher (lower) synchronisation. (1) Three distinct eras of synchronisation can be seen: an era of moderate synchronicity c. 1870-1913, an era of low synchronicity c. 1914-45, and an era of high synchronicity c. 1945 onwards. The first era is well known by economic historians. This was the first age of globalisation (Ferguson and Schularick, 2006), which was a period of high international trade underpinned by the classical gold standard--a fixed exchange rate system adopted by two-thirds of the world's economies (Reinhart and Rogoff, 2011). The second era spans the beginning of the Great War to the end of the Second World War. This was a time of rising protectionism and a breakdown of the international monetary system (Findlay and O'Rourke, 2007). The third era is the 'Great Synchronisation'. In the aftermath of the war, the Bretton Woods conference laid the foundations for new international economic institutions, such as the International Monetary Fund, World Bank and World Trade Organization. After a long, secular decline in the dispersion of world economic growth, 2017 was by this measure the most synchronous year on record. Of the twenty advanced economies in the sample, the minimum rate of growth was 0.7 per cent, while the highest was 3.2 per cent. The simple fact that growth was positive in all countries is rare, occurring in only sixteen years since the 1870s. One explanation could be that the financial crisis was a large global shock that reset the clocks on economies around the world, plunging each into recession and then recovery. As the shock fades over time, however, these countries might tend to move out of sync as growth runs at slightly slower and faster rates across countries, in line with the growth of the supply sides of the respective economies. Yet while this explanation might explain the high synchronicity since the crisis, it misses the long-run factors that set the Great Synchronisation in train in 1945. A central factor has been the development of international economic institutions that have lowered the barriers to the movement of capital and goods, tying the fortunes of distant economies together. NOTE (1) A similar pattern is seen in the cross-country standard deviation of the change in growth rates. REFERENCES Bolt, J., Inklaar, R., de Jong, H. and van Zanden, J.L. (2018), 'Rebasing "Maddison": new income comparisons and the shape of long-run economic development', GGDC Research Memorandum 174. Ferguson, N. and Schularick, M. (2006), 'The empire effect: the determinants of country risk in the first age of globalization, 1880-1913', Journal of Economic History, 66, pp. 283-312. Findlay, R. and O'Rourke, K.H. (2007), Power and Plenty: Trade, War, and the World Economy in the Second Millennium, Princeton University Press. IMF (2018), World Economic Outlook: Cyclical Upswing, Structural Change, International Monetary Fund, April. King, S. (2018), 'Why the global economy is due for a downswing', Financial Times. Naisbitt, B., Hantzsche, A., Lennard, J., Lenoel, C., Liadze, I., Lopresto, M., Piggott, R. and Thamotheram, C. (2018), 'The World Economy', National Institute Economic Review, 243, F43-80. Reinhart, C.M. and Rogoff, KS. (201 I), 'From financial crash to debt crisis', American Economic Review, 101, pp. 1676-706. This box was prepared by Jason Lennard. Caption: Figure Al. Standard deviation of real GDP per capita growth, 1871-2017
Box B. Predicting recessions in the United States with the yield curve There is a large literature on the relationship between the yield curve and recessions that started in the 1980s as a result of the inability of macroeconomic models to explain sudden downturns in economic activity. In this box, we review the literature on the predictive power of the yield curve, with a particular focus on the United States, and compute the current implied probability of a US recession using data ranging from 1953 to 2018. Recessions have often been associated with an inversion of the yield curve, moving from a positive slope to a negative one. A positive slope of the yield curve comes from the fact that investors require a premium for holding longer maturity bonds (the term premium) or expect the short-term rates to be higher in the future. A negative slope is a more unusual event--it has occurred less than 10 per cent of the time in the US in the past 65 years--reflecting the fact that the economy is probably in a transitory phase. In that situation, investors expect the future short-term rates to be lower than the current ones, according to the expectations hypothesis. Figure Bl displays the spread of the 10-year Treasury note yield minus the 3-month Treasury bill yield. The figure shows indeed that recessions have often been preceded by a negative value of the spread. Laurent (1988) and Estrella and Hardouvelis (1991) first showed that the spread in yield between longer-dated Treasury notes and short-dated T-bills could help predict future real GNP growth. Harvey (1988) and Estrella and Hardouvelis found that the yield spread can also be used to help forecast other economic variables such as consumption and investment growth. Comparing the role of the yield spread to other financial and economic indicators, Estrella and Mishkin (1998) concluded that while stock market and Stock-Watson indicators have good predictive power one quarter ahead, the yield spread dominates at longer time-horizons, in particular one year ahead, to forecast recessions. International evidence is however more mixed than for the United States; Chinn and Kucko (2015) found that the yield spread performed relatively well predicting recessions in Germany and Canada but it performed less well in Japan and Italy. We examine the probit methodology of Chinn and Kucko to estimate the probability of a recession in the US at any point within the next twelve months. As is common in the literature, we define the yield spread as the difference in yield between the 10-year Treasury note and the 3-month Treasury bill and use the recession dates from the NBER. All data are of monthly frequency, between April 1953 and March 2018. Figure B2 shows the implied recession probabilities from the model and in the shaded areas the actual recessions. A reading above 50 per cent indicates that a recession is likely to be either ongoing or about to start in the next twelve months. Looking at the statistical power of this model, we can see that it has good 'precision'--when the model identifies that a recession month is likely during the following 12 months, it is correct in 69 per cent of the cases--but a rather low 'sensitivity'--when a recession month actually happens during any of the following 12 months, the model identifies it in only 35 per cent of the cases. So the model is far from perfect because it gives some false negatives. However, the model fares much better at predicting the onset of a recession period. For all the nine recession periods in our sample (we exclude the first one in 1953-4 because we don't have yield information one year in advance of the beginning of the recession), the indicator correctly rose above 50 per cent in the 12 months before the beginning of the recession. The signal came sometimes earlier and sometimes later. In the four recessions of 1970, 1980, 1990 and 2008, the indicator was already at 50 per cent or above more than 12 months before the first month of the recession and in the remaining five recessions the signal appeared between 5 and 10 months before the beginning of the recession. The latest data point for March 2018 is a yield spread of I. I per cent, which using the model translates into an estimated probability of recession within the next twelve months of 30.9 per cent. While this may appear quite high to forecasters, who look at a range of economic indicators, it is only marginally higher than the unconditional probability of 27.8 per cent, and well below the 50 per cent threshold. What is more interesting is that the indicator is on an upward trend, and in November 2017 it reached a 10-year high before levelling off. The main reason for the flattening of the yield curve in recent years is that the 3-month yield increased from 0 to 1.7 per cent while the 10-year yield stayed broadly flat. In short, the indicator does not indicate an imminent recession, but it would be wise to monitor if the yield curve flattens further. At this point, we should note that the New York Fed publishes on its website (1) a recession indicator with a different methodology: it computes the probability of recession in exactly twelve months, rather than at any point within the next twelve months. Because of its more narrow focus, the Fed indicator gives by construction a systematically lower probability of recession, with the latest reading for March at 10.8 per cent, also close to the unconditional probability of 13.0 per cent. The reason why we chose the cumulative indicator is that the average yield spread in the twelve months before the beginning of a recession has historically been lower than exactly twelve months before the beginning of a recession: 0.0 per cent versus 0.6 per cent. This suggests that, as the signal from the inversion of the yield curve sometimes arrives late, the Fed indicator may err on the optimistic side. Interpreting these results should be done with a degree of caution for several reasons. (2) First, the severity of the Great Financial Crisis has pushed the Fed into unprecedented monetary actions; Fed funds rates reached the Zero Lower Bound (ZLB) and the Fed bought a large quantity of long-dated government bonds as part of its Quantitative Easing (QE) programme. Both ZLB and QE have probably artificially reduced the yield spread by respectively pushing up the short rate and pushing down the long rate compared to what they would otherwise have been. As a result, the information content of the yield curve may have been temporarily blurred. Looking forward, the current tightening of monetary policy by the Fed is likely to have ambiguous effects on the slope of the yield curve; increasing Fed funds rates increases the short-term rates but reducing its balance sheet (composed mainly of long-term T-notes) also increases yield at the long end. In that regard, the current situation is different from what happened in previous business cycles. Secondly, the coefficients of the probit regression are not stable with regard to the estimation period sample, which means that out-of-sample forecasting performance is likely to be less good. As an example of such a structural break in the data, the average yield spread has nearly doubled since the mid-1980s as can be seen in figure B1: between 1953 and 1985, it averaged 1.1 per cent and since 1985 it has averaged 1.9 per cent. Indeed, the 'Great Moderation' led to short rates decreasing more than long rates on average. To conclude, using the yield curve to predict upcoming recessions is an easy and model-free way of extracting some of the information contained in the government bond market to forecast an event that is otherwise very difficult to predict. Our own research and that of the New York Fed and the San Francisco Fed (3) suggest that the possibility of a recession in the US has risen somewhat over the past year but it is still far from our central case outlook. NOTES (1) https://www.newyorkfed.org/research/capital_markets/ycfaq.html. (2) Chair Yellen's December 2017 press conference https://www.federalreserve.gov/mediacenter/files/ FOMCpresconf20171213.pdf. (3) Bauer M.D. and Mertens, T.M. (2018), FRBSF Economic Letter https://www.frbsf.org/economic-research/files/el2018-07.pdf. REFERENCES Chinn, M. and Kucko, K. (2015), 'The predictive power of the yield curve across countries and time', International Finance, 18(2), pp. 129-56. Estrella, A. and Mishkin, F. (1998), 'Predicting U.S. recessions: financial variables as leading indicators', The Review of Economics and Statistics, MIT Press, 80(1), February, pp. 45-61. Estrella, A. and Hardouvelis, G. (1991), 'The term structure as a predictor of real economic activity '.Journal of Finance, 1991, 46, 2, pp. 555-76. Harvey C. (1988), 'The real term structure and consumption growth', journal of Financial Economics, 22, 2, pp. 305-33. Laurent, R.D. (1988), 'An interest rate-based indicator of monetary policy,' Economic Perspectives, Federal Reserve Bank of Chicago, January, pp. 3-14. This box was prepared by Cyrille Lenoel. Caption: Figure B1. Yield spread between 10-year Treasury note and 3-month Treasury bill Caption: Figure B2. Probability of a recession in the US within the next 12 months, implied by the yield curve Box C. The re-emergence of concerns about debt One outcome of the financial crisis and Great Recession is that the monetary authorities in many countries now regularly publish reports on financial stability and discuss the main risks that they think could adversely affect economic and financial conditions. As would be expected, debt is one topic. In part this may just reflect back to the build-up of debt before the Great Recession. But it also reflects the relatively low levels of policy interest rates since then and concerns about what might happen to debt service burdens should policy rates rise. This note looks at some recent trends in debt internationally, noting the increase in debt, especially amongst emerging economies. The focus is on private sector debt, in particular trends in household sector and non-financial company sector borrowing. The point is not to be alarmist about recent trends but rather to highlight something that may become a risk issue should the world economy face a negative shock or should policy and market interest rates rise markedly faster than expected. In advanced economies (as defined by BIS statistics), private non-financial sector debt increased from 144 per cent of GDP at the end of 2001 to 163 per cent of GDP by the end of 2008. Of the credit at end 2008, households accounted for 47 per cent and non-financial companies 53 per cent. Private non-financial sector debt has since risen to 168 per cent of GDP, a notable slowing in the pace of debt accumulation, with the shares broadly constant (households 45 per cent) but with debt still rising. In contrast, in emerging economies private non-financial sector debt held steady in the run-up to 2009, from 70 per cent of GDP at the end of 2001 to 76 per cent of GDP at the end of 2008. It has since risen to 143 per cent of GDP. The key feature is that corporate credit has increased markedly. Corporate debt is now estimated at 104 per cent of GDP and 79 per cent of the total. Rapid growth in corporate debt in China has played a major role in the emerging markets story. According to BIS figures, since late 2008 the share of emerging market corporate sector credit that is due to China has risen from 46 per cent to 70 per cent That said, other emerging market economies have seen their corporate sector debt rise by 66 per cent in US dollar terms over the same period. The IMF (2015) has noted that at the same time as corporate debt of non-financial firms across major emerging market economies has risen, the composition of that corporate debt has been shifting toward bonds. While credit can be used to fund productive investment, thereby boosting growth, for companies there is also an added possible concern in that some bond finance will have been arranged in foreign currency terms and not based on domestic interest rates. This creates a potential added risk if, for example, credit is in US dollars and US interest rates rise relative to domestic rates and also if the value of the US dollar appreciates, especially if the primary source of cash for repayments is domestic currency based and does not keep pace. The IMF notes "tentative evidence that listed firms that have issued (bonds) in foreign currency do not appear to have raised their foreign exchange exposures". To date, with the dollar index depreciating, this has not been a realised concern, but, with debt having risen sharply, adverse shocks to the global economy run the possible risk of bringing the debt crises of previous decades back into focus. REFERENCES Dembiermont, C., Drehmann, M. and Muksatunratana, S. (2013), 'How much does the private sector really borrow?', BIS Quarterly Review, March. International Monetary Fund (2015), 'Corporate leverage in emerging markets--a concern?', IMF Global Outlook, October. Liadze, I. and Haache, G. (2017), 'US monetary policy and its impact on emerging market economies', National Institute Economic Review, 240, May. This box was prepared by Barry Naisbitt Caption: Figure C1. Total credit to private non-financial sector as percentage of GDP Caption: Figure C2. Non-financial private sector debt to GDP ratios
Box D. The war on trade: beggar thy neighbour--beggar thyself? A long-held and widespread consensus in economics is that free trade creates more benefits than costs. It allows countries to specialise in goods they are good at producing (Ricardo, 1817), opens markets for firms to exploit economies of scale and for consumers to enjoy a wider variety products (Krugman, 1979) and exposes producers to international competition, raising the overall level of productivity (Melitz, 2003). However, under certain circumstances delaying opening up to trade can be beneficial. For instance, the once emerging markets of Asia, Japan, South Korea and China, only entered the world stage of trade once internationally competitive industries had developed. Existing barriers to trade continue to be held up in the developed and developing world to protect workers in less productive industries from painfully rapid disruptions, such as those described in Foliano and Riley (2017), consumers from low-quality imports and innovators from a theft of ideas. The question we raise in this box is: Who wins and who loses from erecting new barriers to trade? We focus in particular on the effect of tariff and non-tariff trade barriers on the international price system. US President Trump's protectionist rhetoric and imposition of tariffs on some products from the country's trading partners together with the UK's decision to leave the world's most integrated trading block highlight the risk that international trade might become more costly in the future. Tariffs increase the cost of shipping goods across borders. This also holds for regulatory barriers that restrict, in particular, the trade in services. We use the National Institute's Global Econometric Model (NiGEM) to run a stylised scenario, that could be thought of as a supply side shock, illustrating the impact of a 10 per cent increase in import prices worldwide. (1) This could come as the result of the imposition of tariffs or a rise in trade costs due to regulatory barriers. (2) Our analysis demonstrates that the share of trade in world GDP would fall by about I percentage point over a 5-year period, relative to baseline, if import prices were to rise substantially (see figure DI). To show the impact of the shock on a wide range of countries, we have chosen economies with differing characteristics: developed and developing; with different levels of openness; as well as varying degrees of trade linkages with the US. As illustrated in figure D2, an increase in import prices raises inflation and depresses output in all countries, with the magnitude and persistence depending on the sensitivity of domestic prices to import prices, the stickiness of domestic prices as a result of labour market rigidities as well as differences in the reaction of monetary policy. The increase in trade costs leads to a fall in domestic demand in all economies, as both private consumption and investment suffer. Higher domestic prices depress real personal disposable income and hence private consumption, while increases in interest rates by central banks in response to rising inflation discourage investment. The effect on external current account balances varies across countries both in magnitude and sign--in the Euro Area and China the current account improves, while in the US and Brazil it deteriorates. The net effect in each economy will be determined, among other things, by the relative sensitivity of export and import volumes to changes in export and import prices as well as the relative share of exports and imports in total trade (see the article by Slopek in this Review). Our results show that a global war on trade has the potential to make everyone worse off through adjustments in relative prices. However, some countries would have potentially more to lose than others depending on each economy's reliance on imports and exports. The analysis builds on our earlier work (Carreras and Ramina, 2017; Liadze and Hacche, 2017), which shows that unilateral tariffs can have detrimental effects not just on others but also on the country that imposes them. In practice, a global wave of protectionism would likely affect economies through a range of additional channels, which have not been considered here, including risk premia in financial markets and productivity. The fact that we focus on aggregate outcomes further caveats our results, as we would expect substantial differences within countries across industries and along the income distribution. NOTES: (1) NiGEM version v1.18b was used for the simulation. (2) Shocks are applied to non-commodity export prices to deliver equivalent increases in non-commodity import prices. (3) The authors wish to thank Garry Young for helpful comments. REFERENCES: Carreras, O. and Ramina, M. (2017), 'The risk from increased trade protectionism', NiGEM Observations, Noll. Foliano, F. and Riley, R. (2017), 'International trade and UK de-Industrialisation', National Institute Economic Review, 242, November. Krugman, P.R. (1979), 'Increasing returns, monopolistic competition, and international trade', Journal of International Economics, 9(4), pp. 469-79. Liadze, I. and Hacche, G. (2017), 'The macroeconomic implications of increasing tariffs on US imports', NiGEM Observations, No 12. Melitz, M.J. (2003), 'The impact of trade on intra-industry reallocations and aggregate industry productivity', Econometrica, 71(6), pp. 1695-725. Ricardo, D. (1817), On the Principles of Political Economy and Taxation, London: John Murray. This box was prepared by Arno Hantzsche and Iana Liadze. (3) Caption: Figure D1. World trade-to-GDP ratio Caption: Figure D2. Average impact on GDP, inflation and the current account balance-to-GDP ratio over a 5-year period (relative to baseline)
Table A1. Interest rates Per cent per annum
Central bank intervention rates
US Canada Japan Euro Area UK
2014 0.25 1.00 0.10 0.16 0.50
2015 0.26 0.65 0.10 0.05 0.50
2016 0.51 0.50 -0.08 0.01 0.40
2017 1.10 0.70 -0.10 0.00 0.29
2018 1.89 1.42 -0.11 0.00 0.60
2019 2.64 2.08 -0.11 0.09 1.08
2020-24 3.61 3.41 0.30 1.24 2.35
2016 Q1 0.50 0.50 0.00 0.04 0.50
2016 Q2 0.50 0.50 -0.10 0.00 0.50
2016 Q3 0.50 0.50 -0.10 0.00 0.34
2016 Q4 0.55 0.50 -0.10 0.00 0.25
2017 Q1 0.80 0.50 -0.10 0.00 0.25
2017 Q2 1.05 0.50 -0.10 0.00 0.25
2017 Q3 1.25 0.79 -0.10 0.00 0.25
2017 Q4 1.30 1.00 -0.10 0.00 0.41
2018 Q1 1.53 1.20 -0.10 0.00 0.50
2018 Q2 1.83 1.25 -0.10 0.00 0.50
2018 Q3 2.01 1.50 -0.11 0.00 0.66
2018 Q4 2.19 1.75 -0.12 0.00 0.75
2019 Q1 2.37 1.88 -0.14 0.00 0.92
2019 Q2 2.55 2.01 -0.12 0.00 1.00
2019 Q3 2.74 2.14 -0.10 0.09 1.16
2019 Q4 2.92 2.27 -0.08 0.26 1.25
10-year government bond yields
US Canada Japan Euro Area UK
2014 2.5 2.2 0.6 1.9 2.5
2015 2.1 1.5 0.4 1.0 1.8
2016 1.8 1.3 0.0 0.7 1.3
2017 2.3 1.8 0.1 1.0 1.2
2018 2.9 2.3 0.1 1.1 1.6
2019 3.3 2.9 0.4 1.6 2.3
2020-24 3.9 3.8 1.2 3.0 3.5
2016 Q1 1.9 1.2 0.1 0.8 1.5
2016 Q2 1.7 1.3 -0.1 0.7 1.4
2016 Q3 1.6 1.1 -0.1 0.4 0.8
2016 Q4 2.1 1.5 0.0 0.8 1.3
2017 Q1 2.4 1.7 0.1 1.1 1.3
2017 Q2 2.3 1.5 0.0 1.0 1.0
2017 Q3 2.2 1.9 0.0 1.0 1.2
2017 Q4 2.4 2.0 0.0 0.9 1.3
2018 Q1 2.8 2.2 0.1 1.0 1.5
2018 Q2 2.8 2.1 0.0 0.9 1.4
2018 Q3 2.9 2.3 0.1 1.1 1.6
2018 Q4 3.1 2.5 0.2 1.3 1.8
2019 Q1 3.2 2.7 0.3 1.4 2.0
2019 Q2 3.3 2.8 0.4 1.6 2.2
2019 Q3 3.4 3.0 0.4 1.7 2.3
2019 Q4 3.5 3.1 0.5 1.9 2.5
Table A2. Nominal exchange rates
Percentage change
in effective rate
US Canada Japan Euro
Area
2014 3.8 -5.7 -5.5 3.1
2015 13.2 -11.2 -6.3 -6.0
2016 5.2 0.3 15.2 4.8
2017 0.6 2.0 -2.4 3.0
2018 -4.0 0.9 1.2 5.2
2019 -0.6 0.2 1.5 1.2
2016 Q1 1.6 4.2 6.5 2.5
2016 Q2 -1.7 2.1 5.7 1.1
2016 Q3 1.1 -1.2 5.9 0.3
2016 Q4 3.6 -0.6 -4.1 0.0
2017 Q1 1.1 -0.1 -2.9 -0.6
2017 Q2 -2.4 0.0 1.0 1.1
2017 Q3 -3.4 7.3 -1.5 4.3
2017 Q4 1.3 -3.7 -1.7 0.6
2018 Q1 -2.3 0.1 2.3 1.9
2018 Q2 -0.5 0.1 1.0 0.5
2018 Q3 0.0 0.1 0.0 0.0
2018 Q4 0.0 0.0 0.0 0.0
2019 Q1 -0.2 0.0 0.5 0.4
2019 Q2 -0.2 0.0 0.5 0.4
2019 Q3 -0.2 0.0 0.5 0.4
2019 Q4 -0.2 0.1 0.6 0.5
Percentage change in effective rate
Germany France Italy UK
2014 1.6 1.5 2.5 7.4
2015 -3.7 -3.8 -3.1 5.6
2016 2.4 2.5 2.9 -9.9
2017 1.3 2.0 2.0 -5.2
2018 2.6 3.0 3.5 4.1
2019 0.7 0.6 0.8 0.6
2016 Q1 1.3 1.2 1.5 -5.6
2016 Q2 0.5 0.8 0.7 -1.6
2016 Q3 0.0 0.4 0.0 -7.9
2016 Q4 -0.1 0.1 0.2 -2.6
2017 Q1 -0.4 -0.2 -0.2 0.8
2017 Q2 0.6 0.7 0.7 1.1
2017 Q3 2.3 2.3 2.6 -1.6
2017 Q4 0.3 0.4 0.5 1.7
2018 Q1 0.8 1.1 1.3 1.9
2018 Q2 0.3 0.3 0.4 1.7
2018 Q3 0.0 0.0 0.0 0.0
2018 Q4 0.0 0.0 0.0 0.0
2019 Q1 0.2 0.2 0.3 0.1
2019 Q2 0.2 0.2 0.3 0.0
2019 Q3 0.2 0.2 0.3 0.0
2019 Q4 0.3 0.2 0.3 0.0
Bilateral rate per US $
Canadian Yen Euro Sterling
$
2014 1.112 105.8 0.754 0.607
2015 1.299 121.1 0.902 0.654
2016 1.314 108.8 0.904 0.741
2017 1.294 112.2 0.887 0.776
2018 1.262 107.5 0.811 0.709
2019 1.257 105.6 0.798 0.699
2016 Q1 1.323 115.2 0.908 0.699
2016 Q2 1.289 107.9 0.886 0.697
2016 Q3 1.310 102.4 0.896 0.762
2016 Q4 1.333 109.5 0.927 0.805
2017 Q1 1.339 113.6 0.939 0.807
2017 Q2 1.330 111.1 0.909 0.781
2017 Q3 1.229 111.0 0.852 0.764
2017 Q4 1.277 112.9 0.849 0.753
2018 Q1 1.265 108.4 0.814 0.719
2018 Q2 1.262 107.2 0.810 0.706
2018 Q3 1.260 107.2 0.809 0.706
2018 Q4 1.260 107.2 0.809 0.706
2019 Q1 1.259 106.6 0.805 0.703
2019 Q2 1.257 105.9 0.800 0.700
2019 Q3 1.256 105.2 0.795 0.698
2019 Q4 1.254 104.5 0.790 0.695
Table B1. Real GDP growth and inflation
Real GDP growth (per cent)
2015 2016 2017 2018 2019 2020-24
Argentina 2.7 -1.8 2.9 3.3 3.2 2.4
Australia 2.5 2.6 2.3 3.2 2.7 2.7
Austria (a) 1.1 1.5 3.1 2.0 1.7 1.4
Belgium (a) 1.4 1.5 1.7 1.9 1.9 1.2
Bulgaria (a) 3.6 3.9 3.7 3.8 3.7 2.0
Brazil -3.5 -3.5 1.0 1.8 2.3 2.3
Chile 2.3 1.2 1.6 3.3 2.7 2.6
China 6.9 6.7 6.9 6.6 6.3 5.7
Canada 1.0 1.4 3.0 2.6 2.3 1.7
Czech Republic 5.4 2.5 4.6 3.4 2.4 1.4
Denmark (a) 1.6 2.0 2.2 1.9 2.1 1.0
Estonia (a) 1.8 2.2 4.8 4.3 3.4 1.9
Finland (a) 0.1 2.1 3.0 2.4 1.9 1.2
France (a) 1.0 1.1 2.0 1.9 1.9 1.5
Germany (a) 1.5 1.9 2.5 2.4 1.9 1.2
Greece (a) -0.3 -0.3 1.3 2.2 2.3 1.4
Hong Kong 2.4 2.1 3.8 2.8 2.2 2.3
Hungary (a) 3.3 2.1 4.2 3.8 2.3 1.7
India 7.6 7.9 6.4 7.7 7.9 7.2
Indonesia 4.9 5.0 5.1 5.5 5.4 5.0
Ireland (a) 25.5 5.1 7.8 4.9 2.8 2.1
Italy (a) 0.8 1.0 1.5 1.4 1.3 1.2
Japan 1.4 0.9 1.7 1.2 0.9 0.9
Lithuania (a) 2.0 2.3 3.8 3.8 2.6 0.9
Latvia (a) 2.8 1.5 5.0 3.3 1.7 1.8
Mexico 3.3 2.7 2.3 2.1 2.5 2.5
Netherlands (a) 2.3 2.1 3.3 2.7 2.1 1.4
New Zealand 4.2 4.2 3.0 2.7 3.0 2.4
Norway 1.8 1.0 1.9 2.2 2.0 1.4
Poland 3.8 2.9 4.6 3.6 2.9 1.8
Portugal (a) 1.8 1.6 2.7 2.4 2.2 1.8
Romania (a) 4.0 4.8 6.8 4.8 3.1 2.1
Russia -2.8 -0.2 1.5 1.9 2.3 2.1
Singapore 2.2 2.4 3.6 2.9 2.7 3.9
South Africa 1.3 0.6 1.2 1.4 1.5 2.5
S. Korea 2.8 2.9 3.1 3.1 3.1 3.5
Slovakia (a) 3.9 3.3 3.4 4.1 3.4 1.7
Slovenia (a) 2.0 3.3 5.4 3.7 3.1 1.5
Spain (a) 3.4 3.3 3.1 2.5 2.0 1.7
Sweden (a) 4.3 3.0 2.7 2.8 2.8 1.8
Switzerland 1.2 1.4 1.1 2.0 1.8 1.9
Taiwan 0.8 1.4 2.9 3.3 2.3 3.0
Turkey 5.9 3.2 7.4 4.7 4.6 3.7
UK (a) 2.3 1.9 1.8 1.4 1.7 1.7
US 2.9 1.5 2.3 2.7 2.6 2.2
Vietnam 6.6 6.1 6.7 7.1 6.8 5.7
Euro Area (a) 2.0 1.8 2.5 2.3 1.9 1.4
EU-28 (a) 2.2 1.9 2.5 2.2 1.9 1.5
OECD 2.5 1.8 2.6 2.4 2.3 1.9
World 3.4 3.2 3.7 3.9 3.8 3.6
Annual inflation (a) (per cent)
2015 2016 2017 2018 2019 2020-24
Argentina 26.5 41.4 26.3 25.0 16.1 11.1
Australia 1.5 0.9 1.2 2.2 2.4 2.7
Austria (a) 0.8 1.0 2.2 2.1 1.7 1.6
Belgium (a) 0.6 1.8 2.2 1.9 1.7 1.6
Bulgaria (a) -1.1 -1.3 1.2 2.9 1.6 1.5
Brazil 9.0 8.7 3.4 4.1 5.6 6.0
Chile 4.3 3.8 2.2 2.4 2.7 2.8
China 1.5 2.0 1.6 2.4 2.4 2.7
Canada 1.1 0.9 1.1 2.3 2.3 2.1
Czech Republic 0.3 0.7 2.4 2.0 1.8 1.7
Denmark (a) 0.2 0.0 1.1 1.1 2.0 1.7
Estonia (a) 0.1 0.8 3.7 3.0 3.0 1.9
Finland (a) -0.2 0.4 0.8 1.0 1.2 1.7
France (a) 0.1 0.3 1.2 1.6 1.4 1.7
Germany (a) 0.1 0.4 1.7 1.7 1.7 1.6
Greece (a) -1.1 0.0 1.1 1.0 1.7 2.3
Hong Kong 1.2 1.5 2.6 2.9 2.9 3.3
Hungary (a) 0.1 0.4 2.4 3.1 3.9 3.5
India 4.9 4.9 3.3 4.1 4.3 4.8
Indonesia 6.4 3.5 3.8 4.0 4.0 3.8
Ireland (a) 0.0 -0.2 0.2 0.8 1.4 1.6
Italy (a) 0.1 -0.1 1.3 1.3 1.5 1.4
Japan 0.4 -0.5 0.2 0.8 1.3 1.3
Lithuania (a) -0.7 0.7 3.7 2.8 1.7 1.0
Latvia (a) 0.2 0.1 2.9 2.0 1.7 1.5
Mexico 2.7 2.8 6.0 4.9 3.5 3.2
Netherlands (a) 0.2 0.1 1.3 1.7 1.9 1.6
New Zealand 0.8 0.6 1.4 1.2 1.9 2.2
Norway 2.4 3.4 1.5 2.1 1.9 2.0
Poland -0.7 -0.2 1.6 1.7 2.1 2.0
Portugal (a) 0.5 0.6 1.6 1.1 1.8 1.4
Romania (a) -0.4 -1.1 1.1 4.0 2.2 2.2
Russia 15.5 7.0 3.7 3.1 3.9 4.0
Singapore -0.5 -0.5 0.5 1.3 1.9 2.8
South Africa 4.0 6.2 4.6 4.5 5.9 3.6
S. Korea 0.7 1.0 1.9 2.0 2.2 2.3
Slovakia (a) -0.3 -0.5 1.4 2.8 1.7 1.3
Slovenia (a) -0.8 -0.2 1.6 2.1 1.9 1.5
Spain (a) -0.6 -0.3 2.0 1.7 1.5 1.6
Sweden (a) 0.7 1.1 1.9 2.0 2.2 1.9
Switzerland -0.6 -0.2 0.2 0.7 1.1 1.8
Taiwan -0.7 0.8 0.0 1.3 0.8 1.7
Turkey 7.6 7.8 11.1 11.2 8.9 6.0
UK (a) 0.1 0.7 2.7 2.4 2.1 2.0
US 0.3 1.2 1.7 2.3 2.1 2.2
Vietnam 0.6 2.7 3.5 4.7 2.8 4.1
Euro Area (a) 0.0 0.2 1.5 1.6 1.6 1.6
EU-28 (a) 0.0 0.3 1.7 1.8 1.7 1.7
OECD 0.8 1.1 2.1 2.5 2.3 2.2
World 3.8 4.0 4.1 4.5 4.5 3.7
Table B2. Fiscal balance and government debt
Fiscal balance (per cent of GDP) (a)
2015 2016 2017 2018 2019 2024
Australia -1.5 -2.1 -1.7 -1.6 -1.0 -1.2
Austria -1.0 -1.6 -0.5 -0.6 -0.5 -1.3
Belgium -2.5 -2.5 -1.8 -1.1 -0.7 -2.4
Bulgaria -1.6 0.0 0.3 0.3 0.1 -0.7
Canada -0.1 -1.1 -1.0 -1.0 -1.0 -1.5
Czech Rep. -0.6 0.7 0.9 0.4 0.0 -1.4
Denmark -1.8 -0.6 -2.4 -1.5 -1.3 -1.4
Estonia 0.1 -0.3 -0.6 -0.7 -0.8 -1.3
Finland -2.7 -1.7 0.0 0.6 0.2 -1.6
France -3.6 -3.4 -2.6 -1.9 -1.7 -2.7
Germany 0.6 0.8 1.1 0.9 0.5 -1.2
Greece -5.7 0.4 -1.2 -1.3 -0.3 -0.1
Hungary -2.0 -1.9 -3.0 -3.0 -2.8 -2.4
Ireland -1.9 -0.7 0.8 0.6 -0.2 -1.2
Italy -2.6 -2.5 -1.6 -1.1 -1.0 -2.4
Japan -3.5 -4.6 -4.8 -4.2 -4.0 -4.2
Lithuania -0.2 0.3 0.4 0.1 -0.2 -1.2
Latvia -1.2 0.0 0.2 0.1 -0.1 -0.8
Netherlands -2.1 0.4 1.3 2.0 1.7 -1.2
Poland -2.6 -2.5 -2.0 -1.7 -1.6 -2.2
Portugal -4.4 -2.0 -1.6 -1.4 -1.1 -1.7
Romania -0.8 -3.0 -3.1 -3.1 -2.9 -1.9
Slovakia -2.7 -2.2 -1.6 -1.0 -0.6 -0.2
Slovenia -2.9 -1.9 -1.0 -1.0 -1.2 -1.8
Spain -5.3 -4.5 -3.3 -2.1 -1.8 -2.3
Sweden 0.2 1.1 0.9 1.4 1.0 -0.6
UK -4.2 -3.0 -1.9 -4.0 -3.8 -3.9
US -4.3 -5.0 -3.6 -5.4 -5.3 -3.2
Government debt (per cent of GDP, end year) (b)
2015 2016 2017 2018 2019 2024
Australia 43.9 44.9 45.5 45.2 44.1 38.2
Austria 84.3 83.5 80.3 77.9 74.9 67.4
Belgium 106.0 105.7 103.9 100.0 96.7 92.3
Bulgaria -- -- -- -- -- --
Canada 97.8 96.6 95.6 91.6 88.2 79.6
Czech Rep. 38.7 35.8 33.4 31.5 30.5 31.1
Denmark 39.5 37.7 36.4 36.8 36.8 39.0
Estonia -- -- -- -- -- --
Finland 63.6 63.1 61.0 58.5 56.6 53.8
France 95.8 96.6 96.7 95.2 93.7 88.3
Germany 71.0 68.2 64.1 59.6 56.2 47.1
Greece 176.8 180.8 179.5 176.3 165.5 132.5
Hungary 74.4 73.7 68.8 67.7 66.4 61.9
Ireland 77.0 72.9 70.2 67.3 64.6 58.6
Italy 131.6 131.9 132.1 128.2 124.7 116.0
Japan 213.9 216.8 218.2 220.9 219.6 211.0
Lithuania -- -- -- -- -- --
Latvia -- -- -- -- -- --
Netherlands 64.6 61.8 55.9 51.9 48.2 41.8
Poland 51.7 53.8 50.5 49.6 49.0 49.9
Portugal 128.8 130.1 127.4 124.9 121.8 111.0
Romania -- -- -- -- -- --
Slovakia -- -- -- -- -- --
Slovenia -- -- -- -- -- --
Spain 99.4 99.0 97.5 94.7 92.4 85.5
Sweden 44.2 42.3 39.1 35.6 32.8 27.4
UK 88.2 88.2 86.0 86.1 84.6 79.3
US 104.1 105.3 103.2 103.4 104.0 100.9
Notes: (a) General government financial balance; Maastricht
definition for EU countries, (b) Maastricht definition for
EU countries.
Table B3. Unemployment and current account balance
Standardised unemployment rate
2015 2016 2017 2018 2019 2020-24
Australia 6.1 5.7 5.6 5.5 5.2 5.1
Austria 5.7 6.0 5.5 5.2 5.2 4.6
Belgium 8.5 7.8 7.1 6.4 6.7 6.2
Bulgaria 9.1 7.5 6.2 5.2 5.3 5.9
Canada 6.9 7.0 6.3 5.8 5.8 6.0
China -- -- -- -- -- --
Czech Rep. 5.0 3.9 2.9 2.1 1.9 2.6
Denmark 6.2 6.2 5.7 4.7 4.7 4.8
Estonia 6.2 6.8 5.8 6.4 6.0 6.5
Finland 9.3 8.9 8.6 8.4 8.4 8.3
France 10.4 10.1 9.4 8.9 8.4 7.3
Germany 4.7 4.2 3.8 3.6 3.6 4.0
Greece 25.0 23.5 21.5 20.7 19.2 18.5
Hungary 6.8 5.1 4.2 3.9 3.9 4.0
Ireland 10.0 8.4 6.8 6.2 6.1 6.2
Italy 11.9 11.7 11.3 10.8 10.5 10.5
Japan 3.4 3.1 2.8 2.4 3.0 3.3
Lithuania 9.1 7.9 7.1 7.4 7.7 7.8
Latvia 9.9 9.6 8.7 8.1 7.5 6.6
Netherlands 6.9 6.0 4.8 4.5 4.4 4.5
Poland 7.5 6.2 4.9 4.4 4.5 4.2
Portugal 12.6 11.1 9.0 7.8 7.9 8.0
Romania 6.8 5.9 4.9 5.1 4.8 5.0
Slovakia 11.5 9.7 8.1 7.3 7.4 8.2
Slovenia 9.0 8.0 6.6 5.9 5.8 6.4
Spain 22.1 19.6 17.2 15.0 13.2 13.1
Sweden 7.4 6.9 6.7 6.1 6.2 6.7
UK 5.4 4.9 4.4 4.1 4.2 4.7
US 5.3 4.9 4.3 4.1 4.1 4.8
Current account balance (per cent of GDP)
2015 2016 2017 2018 2019 2020-24
Australia -4.7 -3.1 -2.3 -2.8 -2.4 -2.6
Austria 1.9 2.1 2.8 1.0 1.2 1.1
Belgium -0.2 0.1 -0.7 -1.6 -1.4 0.1
Bulgaria 0.0 2.3 4.6 4.4 5.4 2.9
Canada -3.6 -3.2 -3.0 -2.5 -1.8 -0.9
China 2.8 1.8 1.3 0.5 0.5 0.9
Czech Rep. 0.2 1.5 0.9 -0.5 -1.1 -1.3
Denmark 8.8 7.3 7.7 6.9 7.2 8.3
Estonia 1.9 1.9 3.2 1.7 1.1 0.3
Finland -0.7 -0.4 0.7 -0.2 -0.1 0.7
France -0.4 -0.9 -1.2 -0.8 -0.5 -1.0
Germany 9.0 8.5 8.1 7.9 7.5 7.4
Greece -0.2 -1.0 -0.7 -1.4 -0.3 -0.7
Hungary 3.5 6.1 2.9 4.6 5.0 3.1
Ireland 11.0 3.4 12.4 10.7 9.1 9.9
Italy 1.5 2.7 3.0 3.1 3.9 4.9
Japan 3.0 3.7 4.0 3.5 3.7 4.8
Lithuania -2.4 -1.1 1.0 0.1 -2.4 -3.3
Latvia -0.5 1.4 -0.8 0.7 0.5 -0.7
Netherlands 8.7 8.5 10.2 10.7 8.7 7.6
Poland -0.6 -0.3 0.2 0.8 1.0 0.1
Portugal 0.3 0.6 0.6 -0.4 -1.4 -1.4
Romania -1.2 -2.1 -3.4 -2.4 -2.0 -2.3
Slovakia -1.7 -1.5 -2.1 -0.9 0.2 -0.6
Slovenia 4.4 5.3 6.4 3.0 3.0 0.7
Spain 1.1 1.9 2.0 1.7 2.3 2.1
Sweden 4.5 4.2 3.2 3.9 4.4 5.5
UK -5.2 -5.8 -4.1 -4.0 -3.8 -3.5
US -2.4 -2.4 -2.4 -3.1 -3.4 -3.3
Table B4. United States
Percentage change
2014 2015 2016
GDP 2.6 2.9 1.5
Consumption 2.9 3.6 2.7
Investment : housing 3.5 10.2 5.5
: business 6.9 2.3 -0.6
Government : consumption -0.5 1.3 1.0
: investment -1.4 1.6 -0.2
Stockbuilding (a) -0.1 0.2 -0.4
Total domestic demand 2.7 3.5 1.6
Export volumes 4.3 0.4 -0.3
Import volumes 4.5 5.0 1.3
Average earnings 2.6 2.8 1.1
Private consumption deflator 1.5 0.3 1.2
RPDI 3.6 4.1 1.4
Unemployment, % 6.2 5.3 4.9
General Govt, balance as % of GDP -4.9 -4.3 -5.0
General Govt, debt as % of GDP (b) 103.0 104.1 105.3
Current account as % of GDP -2.1 -2.4 -2.4
Average
2017 2018 2019 2020-24
GDP 2.3 2.7 2.6 2.2
Consumption 2.8 2.7 2.7 1.7
Investment : housing 1.8 5.3 6.4 3.6
: business 4.7 5.5 5.2 3.1
Government : consumption 0.1 1.4 1.5 1.6
: investment 0.1 1.7 1.2 1.6
Stockbuilding (a) -0.1 0.0 0.0 0.0
Total domestic demand 2.4 3.0 2.9 1.9
Export volumes 3.4 4.9 4.2 3.8
Import volumes 4.0 6.3 5.8 2.1
Average earnings 1.6 2.9 3.0 3.1
Private consumption deflator 1.7 2.3 2.1 2.2
RPDI 1.1 2.3 2.5 1.4
Unemployment, % 4.3 4.1 4.1 4.8
General Govt, balance as % of GDP -3.6 -5.4 -5.3 -3.9
General Govt, debt as % of GDP (b) 103.2 103.4 104.0 102.7
Current account as % of GDP -2.4 -3.1 -3.4 -3.3
Note: (a) Change as a percentage of GDP. (b) End-of-year basis.
Table B5. Canada
Percentage change
2014 2015 2016 2017
GDP 2.9 1.0 1.4 3.0
Consumption 2.6 2.2 2.3 3.4
Investment : housing 2.2 3.8 3.3 3.1
: business 4.5 -11.0 -9.2 2.7
Government : consumption 0.5 1.6 2.2 2.2
: investment -3.4 0.3 5.1 3.8
Stockbuilding (a) -0.4 -0.2 -0.2 0.7
Total domestic demand 1.8 0.3 1.0 3.8
Export volumes 5.9 3.5 1.0 1.0
Import volumes 2.3 0.7 -1.0 3.6
Average earnings 3.2 1.9 1.0 2.2
Private consumption deflator 1.9 1.1 0.9 1.1
RPDI 1.3 3.4 1.5 3.6
Unemployment, % 6.9 6.9 7.0 6.3
General Govt, balance as % of GDP 0.2 -0.1 -1.1 -1.0
General Govt, debt as % of GDMP 91.1 97.8 96.6 95.6
Current account as % of GDP -2.4 -3.6 -3.2 -3.0
Average
2018 2019 2020-24
GDP 2.6 2.3 1.7
Consumption 2.8 1.7 1.2
Investment : housing 3.7 2.9 2.7
: business 4.8 2.2 0.8
Government : consumption 2.2 1.9 1.7
: investment 5.2 2.8 1.9
Stockbuilding (a) 0.0 0.0 0.0
Total domestic demand 3.0 1.9 1.4
Export volumes 3.7 6.3 3.1
Import volumes 4.8 4.8 2.2
Average earnings 3.0 3.1 3.5
Private consumption deflator 2.3 2.3 2.1
RPDI 2.4 1.6 1.2
Unemployment, % 5.8 5.8 6.0
General Govt, balance as % of GDP -1.0 -1.0 -1.4
General Govt, debt as % of GDMP 91.6 88.2 82.7
Current account as % of GDP -2.5 -1.8 -0.9
Note: (a) Change as a percentage of GDP.
(b) End-of-year basis; Maastricht definition.
Table B6. Japan
Percentage change
2014 2015 2016
GDP 0.3 1.4 0.9
Consumption -0.9 0.0 0.1
Investment : housing -4.0 -1.2 5.6
: business 5.2 3.4 0.6
Government : consumption 0.5 1.5 1.3
: investment 0.6 -1.3 0.1
Stockbuilding (a) 0.1 0.3 -0.2
Total domestic demand 0.3 1.0 0.4
Export volumes 9.3 3.0 1.3
Import volumes 8.2 0.7 -1.9
Average earnings 0.9 0.9 1.7
Private consumption deflator 2.0 0.4 -0.5
RPDI -1.7 0.8 2.3
Unemployment, % 3.6 3.4 3.1
Govt, balance as % of GDP -5.4 -3.5 -4.6
Govt, debt as % of GDP (b) 213.0 213.9 216.8
Current account as % of GDP 0.8 3.0 3.7
Average
2017 2018 2019 2020-24
GDP 1.7 1.2 0.9 0.9
Consumption 1.0 0.5 0.4 1.1
Investment : housing 2.7 -0.7 1.4 3.6
: business 3.0 3.3 1.3 1.6
Government : consumption 0.1 0.0 0.0 0.3
: investment 1.3 -0.1 0.2 0.3
Stockbuilding (a) -0.1 0.3 0.0 0.0
Total domestic demand 1.2 1.0 0.5 1.1
Export volumes 6.8 5.9 4.4 3.4
Import volumes 3.6 5.0 2.2 4.0
Average earnings 0.9 1.3 2.3 2.0
Private consumption deflator 0.2 0.8 1.3 1.3
RPDI 1.6 0.1 0.6 1.3
Unemployment, % 2.8 2.4 3.0 3.3
Govt, balance as % of GDP -4.8 -4.2 -4.0 -3.9
Govt, debt as % of GDP (b) 218.2 220.9 219.6 214.1
Current account as % of GDP 4.0 3.5 3.7 4.8
Note: (a) Change as a percentage of GDP. (b) End-of-year basis.
Table B7. Euro Area
Percentage change
2014 2015 2016
GDP 1.4 2.0 1.8
Consumption 0.9 1.8 1.9
Private investment 2.3 3.2 3.4
Government : consumption 0.7 1.3 1.8
: investment -0.7 2.9 1.1
Stockbuilding (a) 0.3 0.0 -0.1
Total domestic demand 1.3 2.0 2.0
Export volumes 4.6 6.1 3.4
Import volumes 4.9 6.5 4.8
Average earnings 1.3 1.4 1.5
Harmonised consumer prices 0.4 0.0 0.2
RPDI 0.8 1.3 1.9
Unemployment, % 11.6 10.9 10.0
Govt, balance as % of GDP -2.6 -2.1 -1.5
Govt, debt as % of GDP (b) 92.5 90.6 89.6
Current account as % of GDP 2.4 3.2 3.4
Average
2017 2018 2019 2020-24
GDP 2.5 2.3 1.9 1.4
Consumption 1.7 1.8 1.7 1.2
Private investment 4.7 4.6 3.5 2.0
Government : consumption 1.2 1.5 1.4 1.3
: investment 1.7 2.6 2.6 1.1
Stockbuilding (a) 0.0 0.0 0.0 0.0
Total domestic demand 2.1 2.2 2.0 1.4
Export volumes 5.3 4.8 3.5 2.5
Import volumes 4.3 4.9 4.0 2.7
Average earnings 1.4 2.1 2.3 2.7
Harmonised consumer prices 1.5 1.6 1.6 1.6
RPDI 2.1 1.7 2.1 1.6
Unemployment, % 9.1 8.4 8.0 7.9
Govt, balance as % of GDP -0.7 -0.5 -0.5 -1.4
Govt, debt as % of GDP (b) 86.9 83.6 80.8 75.4
Current account as % of GDP 3.5 3.5 3.4 3.4
Note: (a) Change as a percentage of GDP.
(b) End-of-year basis; Maastricht definition.
Table B8. Germany
Percentage change
2014 2015 2016 2017
GDP 1.9 1.5 1.9 2.5
Consumption 1.0 1.6 1.9 2.1
Investment : housing 3.1 -1.2 3.8 3.6
: business 4.8 1.4 2.5 4.0
Government : consumption 1.5 2.9 3.7 1.6
: investment -1.2 4.5 2.6 4.6
Stockbuilding (a) -0.3 -0.3 -0.1 0.0
Total domestic demand 1.3 1.5 2.4 2.4
Export volumes 4.5 4.7 2.4 5.3
Import volumes 3.5 5.2 3.8 5.6
Average earnings 2.5 3.0 2.9 2.5
Harmonised consumer prices 0.8 0.1 0.4 1.7
RPDI 1.5 1.9 2.1 2.4
Unemployment, % 5.0 4.7 4.2 3.8
Govt, balance as % of GDP 0.3 0.6 0.8 I.I
Govt, debt as % of GDP (b) 74.7 71.0 68.2 64.1
Current account as % of GDP 7.5 9.0 8.5 8.1
Average
2018 2019 2020-24
GDP 2.4 1.9 1.2
Consumption 2.4 2.1 0.6
Investment : housing 1.6 2.0 1.7
: business 4.3 3.2 1.4
Government : consumption 1.8 1.4 0.8
: investment 5.0 6.5 0.1
Stockbuilding (a) 0.2 0.0 0.0
Total domestic demand 2.8 2.2 0.8
Export volumes 5.3 4.2 2.7
Import volumes 6.6 5.3 2.2
Average earnings 3.0 2.5 2.6
Harmonised consumer prices 1.7 1.7 1.6
RPDI 1.3 1.7 0.8
Unemployment, % 3.6 3.6 4.0
Govt, balance as % of GDP 0.9 0.5 -0.6
Govt, debt as % of GDP (b) 59.6 56.2 49.9
Current account as % of GDP 7.9 7.5 7.4
Note: (a) Change as a percentage of GDP.
(b) End-of-year basis; Maastricht definition.
Table B9. France
Percentage change
2014 2015 2016 2017
GDP 1.0 1.0 1.1 2.0
Consumption 0.7 1.3 2.1 1.3
Investment : housing -3.0 -2.1 2.4 5.3
: business 2.9 3.1 3.6 4.4
Government : consumption 1.3 1.1 1.2 1.6
: investment -5.4 -3.0 -0.1 -1.0
Stockbuilding (a) 0.7 0.3 -0.1 0.4
Total domestic demand 1.5 1.5 1.9 2.3
Export volumes 3.4 4.0 1.9 3.3
Import volumes 4.8 5.5 4.2 4.1
Average earnings 1.5 0.3 1.6 2.1
Harmonised consumer prices 0.6 0.1 0.3 1.2
RPDI 0.7 1.2 2.0 1.6
Unemployment, % 10.3 10.4 10.1 9.4
Govt, balance as % of GDP -3.9 -3.6 -3.4 -2.6
Govt, debt as % of GDP (b) 94.9 95.8 96.6 96.7
Current account as % of GDP -1.3 -0.4 -0.9 -1.2
Average
2018 2019 2020-24
GDP 1.9 1.9 1.5
Consumption 1.4 1.8 1.5
Investment : housing 3.4 5.2 6.5
: business 4.5 3.6 2.0
Government : consumption 1.4 1.2 1.7
: investment 1.8 1.6 1.8
Stockbuilding (a) -0.3 0.0 0.0
Total domestic demand 1.6 2.0 1.9
Export volumes 5.2 4.1 2.4
Import volumes 3.7 4.3 3.3
Average earnings 1.9 1.8 3.1
Harmonised consumer prices 1.6 1.4 1.7
RPDI 1.6 1.9 2.0
Unemployment, % 8.9 8.4 7.3
Govt, balance as % of GDP -1.9 -1.7 -2.2
Govt, debt as % of GDP (b) 95.2 93.7 89.7
Current account as % of GDP -0.8 -0.5 -1.0
Note: (a) Change as a percentage of GDP.
(b) End-of-year basis; Maastricht definition.
Table B10. Italy
Percentage change
2014 2015 2016
GDP 0.2 0.8 1.0
Consumption 0.2 1.9 1.4
Investment : housing -6.8 -1.7 2.9
: business 0.6 4.0 4.3
Government : consumption -0.7 -0.6 0.6
: investment -5.4 -1.2 -1.0
Stockbuilding (a) 0.7 0.0 -0.3
Total domestic demand 0.3 1.4 1.3
Export volumes 2.4 4.2 2.6
Import volumes 3.0 6.6 3.8
Average earnings 0.4 0.6 0.2
Harmonised consumer prices 0.2 0.1 -0.1
RPDI 0.5 0.5 1.4
Unemployment, % 12.6 1 1.9 11.7
Govt, balance as % of GDP -3.0 -2.6 -2.5
Govt, debt as % of GDP (b) 131.7 131.6 131.9
Current account as % of GDP 1.9 1.5 2.7
Average
2017 2018 2019 2020-24
GDP 1.5 1.4 1.3 1.2
Consumption 1.3 0.9 0.6 0.7
Investment : housing 2.2 2.9 2.0 1.7
: business 5.6 7.2 2.1 1.7
Government : consumption 0.1 0.9 1.1 0.9
: investment -2.5 2.9 2.8 1.0
Stockbuilding (a) -0.2 -0.4 0.0 0.0
Total domestic demand 1.3 1.3 1.0 0.9
Export volumes 6.0 3.9 2.7 2.4
Import volumes 5.7 4.2 1.7 1.7
Average earnings -0.4 1.4 2.5 1.9
Harmonised consumer prices 1.3 1.3 1.5 1.4
RPDI 1.2 1.8 2.3 1.0
Unemployment, % 11.3 10.8 10.5 10.5
Govt, balance as % of GDP -1.6 -1.1 -1.0 -1.9
Govt, debt as % of GDP (b) 132.1 128.2 124.7 118.7
Current account as % of GDP 3.0 3.1 3.9 4.9
Note: (a) Change as a percentage of GDP.
(b) End-of-year basis; Maastricht definition.
Table B11. Spain
Percentage change
2014 2015 2016
GDP 1.4 3.4 3.3
Consumption 1.5 3.0 3.0
Investment : housing 11.3 -1.0 4.4
: business -2.5 7.7 3.2
Government : consumption -0.3 2.1 0.8
: investment 8.8 16.5 2.2
Stockbuilding (a) 0.2 0.4 0.0
Total domestic demand 2.0 4.0 2.6
Export volumes 4.3 4.2 4.8
Import volumes 6.6 5.9 2.7
Average earnings -0.1 1.9 0.4
Harmonised consumer prices -0.2 -0.6 -0.3
RPDI 1.2 2.3 1.9
Unemployment, % 24.5 22.1 19.6
Govt, balance as % of GDP -6.0 -5.3 -4.5
Govt, debt as % of GDP (b) 100.4 99.4 99.0
Current account as % of GDP 1.0 1.1 1.9
Average
2017 2018 2019 2020-24
GDP 3.1 2.5 2.0 1.7
Consumption 2.4 2.3 1.8 1.4
Investment : housing 8.3 4.6 3.0 3.8
: business 3.8 4.5 2.8 2.8
Government : consumption 1.6 1.4 1.8 1.9
: investment 2.5 -0.1 1.8 1.9
Stockbuilding (a) 0.1 0.1 0.0 0.0
Total domestic demand 2.9 2.4 2.0 1.9
Export volumes 5.0 3.3 3.8 2.6
Import volumes 4.7 3.1 3.9 3.3
Average earnings 0.7 1.1 2.0 2.9
Harmonised consumer prices 2.0 1.7 1.5 1.6
RPDI 1.5 2.1 2.4 1.7
Unemployment, % 17.2 15.0 13.2 13.1
Govt, balance as % of GDP -3.3 -2.1 -1.8 -2.2
Govt, debt as % of GDP (b) 97.5 94.7 92.4 87.9
Current account as % of GDP 2.0 1.7 2.3 2.1
Note: (a) Change as a percentage of GDP.
(b) End-of-year basis; Maastricht definition.
Table 1. Forecast summary
Percentage change
Real GDP (a)
World OECD China
2008-13 3.3 0.8 9.1
2014 3.6 2.2 7.3
2015 3.4 2.5 6.9
2016 3.2 1.8 6.7
2017 3.7 2.6 6.9
2018 3.9 2.4 6.6
2019 3.8 2.3 6.3
2020-24 3.6 1.9 5.7
Private consumption
deflator
OECD Euro USA
Area
2008-13 1.8 1.5 1.7
2014 1.6 0.5 1.5
2015 0.8 0.3 0.3
2016 1.1 0.4 1.2
2017 2.1 1.4 1.7
2018 2.5 1.6 2.3
2019 2.3 1.6 2.1
2020-24 2.2 1.6 2.2
Real GDP (a)
EU-28 Euro USA
Area
2008-13 0.0 -0.3 0.8
2014 1.8 1.4 2.6
2015 2.2 2.0 2.9
2016 1.9 1.8 1.5
2017 2.5 2.5 2.3
2018 2.2 2.3 2.7
2019 1.9 1.9 2.6
2020-24 1.5 1.4 2.2
Private consumption
deflator
Japan Germany France
2008-13 -0.7 1.3 1.1
2014 2.0 0.9 0.1
2015 0.4 0.6 0.3
2016 -0.5 0.6 -0.1
2017 0.2 1.7 0.9
2018 0.8 1.7 1.5
2019 1.3 1.7 1.4
2020-24 1.3 1.6 1.7
Real GDP (a)
Japan Germany France
2008-13 0.2 0.7 0.3
2014 0.3 1.9 1.0
2015 1.4 1.5 1.0
2016 0.9 1.9 1.1
2017 1.7 2.5 2.0
2018 1.2 2.4 1.9
2019 0.9 1.9 1.9
2020-24 0.9 1.2 1.5
Private consumption
deflator
Italy UK Canada
2008-13 1.9 2.5 1.3
2014 0.3 1.9 1.9
2015 0.2 0.6 1.1
2016 0.1 1.4 0.9
2017 1.2 2.0 1.1
2018 1.3 2.2 2.3
2019 1.5 2.4 2.3
2020-24 1.4 2.3 2.1
Real GDP (a) World
trade (b)
Italy UK Canada
2008-13 -1.5 0.3 1.4 3.2
2014 0.2 3.1 2.9 3.9
2015 0.8 2.3 1.0 2.7
2016 1.0 1.9 1.4 2.6
2017 1.5 1.8 3.0 4.8
2018 1.4 1.4 2.6 5.3
2019 1.3 1.7 2.3 5.1
2020-24 1.2 1.7 1.7 4.0
Interest rates (c) Oil
($ per
USA Japan Euro barrel)
Area (d)
2008-13 0.6 0.2 1.5 95.5
2014 0.3 0.1 0.2 99.6
2015 0.3 0.1 0.1 52.8
2016 0.5 -0.1 0.0 43.4
2017 1.1 -0.1 0.0 53.5
20/8 1.9 -0.1 0.0 64.8
20/9 2.6 -0.1 0.1 67.6
2020-24 3.6 0.3 1.2 71.0
Notes: Forecast produced using the NiGEM model, (a) GDP
growth at market prices. Regional aggregates are based
on PPP shares, 201 I reference year, (b) Trade in goods
and services, (c) Central bank intervention rate, period
average, (d) Average of Dubai and Brent spot prices.
* All questions and comments related to the forecast
and its underlying assumptions should be addressed to
Iana Liadze (i.liadze@niesr.ac.uk). We would like to thank
Jagjit Chadha and Garry Young for helpful comments and
Yanitsa Kazalova for compiling the database underlying
the forecast. The forecast was completed on 27 April, 2018.
Exchange rate, interest rates and equity price assumptions
are based on information available to 11 April 2018.
Unless otherwise specified, the source of all data reported
in tables and figures is the NiGEM database and NIESR
forecast baseline.