Global consequences of a loss of confidence in emerging economies

Global consequences of a loss of confidence in emerging economies

1 Introduction The two episodes of economic and financial crises over the past two decades have left an important message to regulators: a shift in risk perception can have large real consequences for the global economy. For example, one of the major drivers of the 1997 East Asian financial crisis was a shift in investor confidence which eventually led to a financial panic (Radelet & Sachs 1998). Further, the primary source of the 2008 global financial crisis (GFC) was the collapse of Lehman Brothers and the bursting of housing bubbles which slashed household and business confidence, leading to a sharp decline in private investment and consumer spending (McKibbin & Stoeckel 2009). There was an immediate reappraisal of risk in the aftermath of the GFC. The risk premia on interbank borrowing and corporate bonds which was close to zero rose sharply by more than 5 percent (McKibbin & Stoeckel 2009). Firms postponed investment in large projects and the demand for manufacturing durables collapsed. As a result, the economic growth of advanced economies fell sharply from 2.7 percent in 2007 to 0.1 percent and 3.4 percent in 2008 and 2009 respectively (IMF 2014). While the emerging market economies were initially thought to be insulated from the contagion, lower export demand, higher commodity prices and current account imbalances led to an economic slowdown with the growth of real GDP falling from 8.7 percent in 2007 to 5.9 percent in 2008 and 3.1 percent in 2009 (IMF 2014). Since then, policy responses and financial adjustments have reduced global risks, although remain elevated (World Bank 2014). Developing economies remain vulnerable to rapid growth of domestic credit fueled by locally issued debt and cheap credit from abroad. Further, a recent announcement of the US monetary policy normalization (tapering of quantitative easing) increases the risks of capital flow reversals and higher cost of capital for the emerging markets (IMF 2014). Growth slowdown in China increases the downside risks for Latin America and East Asia. For developed

1

economies, fiscal sustainability (US, Europe and Japan), sliding inflation (Europe), higher sales tax (Japan), political tensions, and low interest rates remain a concern. The anticipated policy adjustments such as fiscal and monetary tightening in the high income developed countries over the next few years put the emerging and developing markets into the risk of higher interest rates, capital outflows, and balance of payment imbalances (Shin 2013). This could have a significant negative impact on investor confidence, leading to another financial and economic turmoil (IMF 2014). Therefore, it is timely to examine what would happen if there is a permanent loss of confidence in emerging economies. Re-evaluation of risk can lead to severe economic disruption through outflow of financial capital (McKibbin 1998). Carriere-Swallow and Cespedes (2013) find that emerging economies are more vulnerable to uncertainty shocks than the developed economies. Policy prescriptions often advocate for capital controls, particularly for the emerging economies, to lessen the macroeconomic and financial instability risks arising from large capital inflows (IMF 2011). Stiglitz (2014) argues that excessive capital flows can only lead to volatility, not higher economic growth. He suggests that countries should have some form of capital controls to avoid large swings in the exchange rate. However, McKibbin (1998) argues that this would be a very expensive strategy to follow as limiting capital flows would be the same as raising risk premium in the imposing countries. McKibbin (1999) finds that free flow of trade and financial capital in fact stabilizes economic fluctuations when the shock originates from a loss of confidence. This paper simulates a permanent loss of confidence in emerging economies using a multi-country-multi-sector inter-temporal G-Cubed model. The study attempts to answer the question: what happens to the emerging economies and the rest of the world if there is a permanent increase in the country risk premia in emerging markets by 200 basis points relative to the baseline. The simulation results suggest that a permanent shift in risk perception has significant short and long term impacts on the global economy. As emerging markets are hit by higher risk premia, financial capital immediately flows out of these economies. This leads to a higher short and long term interest rate, and to a lower level of consumption, investment, stock value and desired stock of capital. As a 2

result, the output of emerging economies falls for several years. On the other hand, higher inflows of capital allow significant expansion of the non-emerging economies for more than two decades with a higher level of consumption, investment and capital stock. However, depreciation (appreciation) of the exchange rate improves (deteriorates) the trade and current account balance of emerging markets (developed economies), which partially offsets the negative (positive) financial flow-on effects. The study finds that open trade and capital markets act as important stabilizers to lessen the global impact of a higher risk premia in emerging markets. While emerging economies need a boost in exports to partially offset the negative financial flow-on effects, developed economies need additional capital to expand their productive capacity in the face of higher domestic demand. This paper therefore suggests that policymakers should not obstruct the mobility of financial capital, rather should focus on monitoring and managing risks with a transparent and accountable financial system. This would require greater coordination across countries as highlighted in various G20 summits (Claessens 2010). The remainder of this paper is structured as follows. Section 2 provides an overview of the G-Cubed model and explains how a loss of confidence is modeled in the G-Cubed. Section 3 summarizes and discusses the simulation results. Finally, Section 4 concludes.

2 The G-Cubed model 2.1 Overview of the model Originally developed by McKibbin and Wilcoxen (1992), the G-Cubed model is a dynamic general equilibrium model of the world economy which imposes inter-temporal constraints on households, firms, governments and nations (McKibbin & Wilcoxen 1999). The G-Cubed model is a bridge between the static computable general equilibrium (CGE) models and macroeconomic models, which gives importance to time dimension and agents’ expectations and therefore have rich dynamic behavior. In this model, a mix of backward and forward looking economic agents (households and firms) optimize their behavior dynamically, subject to inter-temporal constraints (Cagliarini & McKibbin 2009). The model allows short run deviations in agents’ 3

behavior from an optimal path, due to factors such as myopia or agents’ inability to borrow at risk-free bond rate on government debt. However, short run deviations should follow a rule of thumb such that a unique inter-temporal equilibrium is achieved in the long run. Households maximize the present value of lifetime utility, subject to an intertemporal budget constraint that the present value of lifetime consumption should satisfy the present value of expected after-tax lifetime income. Similarly, price-taking firms make investment decisions to maximize the present value of future dividend streams, subject to production technology and capital adjustment costs. The G-Cubed model distinguishes between physical and financial capital by assuming that physical capital is immobile within sectors and across countries, but financial capital is perfectly mobile, immediately flowing to the country that offers the highest expected returns. Further, the model embodies ‘macroeconomic characteristics’ by giving financial assets (including money) explicit treatment and allowing nominal wage rigidity in the short run. Thus, depending on the labor market condition in each economy, unemployment can arise for significant periods in the short to medium term, but full employment should be achieved in the long run. Labor is assumed to be completely mobile between sectors but immobile across regions. 2.2 Modeling a permanent loss of confidence in the G-Cubed model The aim of this study is to quantify the global consequences of a permanent loss of confidence in emerging economies. For this, we need an inter-temporal general equilibrium model which allows both inter-linkages between the real and financial sectors of a country and interconnection across economies. The G-cubed model is well designed to capture such inter-linkages because it includes the international financial markets for bonds and equities, takes into account the trade and financial flow-on effects, and incorporates agents’ expectations and wealth effects (McKibbin & Stoeckel 2009). Incorporating changes in the risk perception is one way of identifying a loss of confidence in the G-Cubed model (McKibbin 1998). There are several areas where risks are reflected in an economy. First, an increase in the equity risk premia drives a wedge between the real interest rate (return on bonds) and the underlying rate of return on

4

equity (McKibbin & Stoeckel 2009). This implies that with a higher equity risk, investors need to be offered a higher return on capital to hold equities over bonds. Higher equity risk can be modeled in the G-Cubed as an increase in the discount rate in the Tobin’s q equation, which leads to a lower present value of stocks. Second, an increase in the household risk is modeled in G-Cubed as an increase in the real interest rate (adjusted by risk premium) that households use to discount their future income streams. A higher risk premia leads to a higher discount rate and therefore, to a lower present value of lifetime income. As households feel poorer than before, they respond by reducing consumption and increasing savings. Third, an increase in the country risk (which is of our interest) is modeled in the GCubed as an increase in the country risk premia (McKibbin 1998). This reflects the excess returns on a country’s bonds, relative to the US bonds that investors need to be offered to hold bonds of that country relative to the US bonds. The country risk premia appears in the uncovered interest parity equation: =

(

)+

(1)

The interest parity condition tells us that the interest rate differential between country-i and the US ( (

depends on the expected rate of change in exchange rate

) and the country risk premia

. If country-i becomes riskier than the US,

the interest rate on its bonds is expected to be higher. If investors expect depreciation of the domestic currency (a positive change in e), they need to be offered a higher return on the domestic assets because when the return is converted into the US dollar, it would not worth much. In the G-Cubed model, exchange rate is determined by the equation: (2) Equation (2) tells us that the value of exchange rate today ( ) is the sum of interest rate differentials and the risk premia up to period T,

plus the expected

exchange rate in period T+1. It is important to note that a permanent shift in risk is not discounted so that future risk premium is as important as today’s risk premium. 5

The G-Cubed model (version 108V) employed in this study includes 17 economies and 6 sectors of production (energy, mining, agriculture, durable manufacturing, non-durable manufacturing and services). Further, there is a household sector and a capital producing sector. The list of economies is presented in Table 1. The model is solved by a backward induction process to generate a baseline. The baseline is based on a range of assumptions, including the long-run productivity growth (1.8 percent), population growth (World Bank projections), policy rules, and tariff and tax rates (Cagliarini & McKibbin 2009). A permanent loss of confidence is modeled as an increase in the country risk premia by 200 basis points relative to the baseline (2013) from 2014 forever in six emerging economies- China, India, Indonesia, other Asia, Latin America and other developing countries. Table 1 Countries/regions Emerging economies China (CHI) India (IND) Indonesia (INO) Other Asia (OAS) Latin America (LAM) Other developing countries (ROW)

Non-emerging economies United States (USA) Japan (JPN) United Kingdom (GBR) Germany (DEU) Rest of Euro Zone (EUZ) Canada (CAN) Australia (AUS) Korea (KOR) Rest of OECD (ROECD) Eastern Europe and former Soviet Union (EEB) Oil Exporting and the Middle East (OPC)

Source: G-Cubed (v108V) model.

The monetary policy rule is defined as the Henderson-McKibbin-Taylor (HMT) rule (Henderson & McKibbin 1993; Taylor 1993), where the central bank of each economy targets the level of nominal income. In response to shocks, central banks adjust policy interest rates to bring the level of nominal income back to the target in the long run. The HMT rule for all economies (except for the Euro area) is defined as: (3a) (3b) Where, , π, Δy, ny and Δ denote the actual interest rate, inflation rate, output growth, nominal income, and the change in exchange rate respectively. Superscripts d and T

6

denote the desired and target level of the variables and x denote the exogenous component of interest rate. The actual policy interest rate, i adjusts gradually to the desired policy rate, id and can be shifted exogenously in the short term by changing the exogenous component, ix (interest rate target). The monetary rule for the European economies is defined as: the central bank of Germany is targeting inflation of the rest of the Euro Zone and the central bank of the rest of the Euro Zone is pegging its currency to the German exchange rate. As a result, these two economies are going to have the same interest rate and exchange rate. A summary of the parameters used in the HMT rule is reported in Table 2. Table 2 Coefficients in the Henderson-McKibbin-Taylor rule Developed (non-shocked economies) USA JPN GBR DEU EUZ CAN AUS KOR ROECD EEB OPC Emerging(shocked economies) CHI IND INO OAS LAM ROW

1

2

3

4

5

6

1 1 1 1 1 1 1 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0

2 2 2 2 2 2 2 2 2 2 2

0 0 0 0 -1000 0 0 -0.1 0 -1 -1

0.1 0.1 0.1 0.1 1 0.1 0.1 0.1 0.1 0.1 0.1

1 1 1 1 1 1

0 0 0 0 0 0

0 0 0 0 0 0

2 2 2 2 2 2

-1 0 -0.1 -0.1 -0.1 -0.1

0.1 0.1 0.1 0.1 0.1 0.1

Source: G-Cubed (v108V) model.

The US has a coefficient of 2 on nominal income and 0s on inflation, output growth and exchange rate (Table 2). This means that the Federal Reserve Bank (Fed) is targeting nominal income rather than inflation, output growth or exchange rate. The adjustment coefficient for interest rate (

) is 0.1 which indicates that the Fed is closing the gap by

10 percent each year. The rest of the Euro Zone has a very large coefficient on exchange rate (

), indicating that it is pegging to the German exchange rate. China has a high

7

weight on the exchange rate, relative to other emerging economies because the Chinese Yuan is pegged to the US dollar. Finally, the fiscal rule is defined as: when the government accumulates fiscal deficits and hence debt, a set of tax rates (including lump-sum tax) is imposed on households and firms to service that debt (McKibbin & Stoeckel 2012). This ensures that the present value of government debt does not explode over time. Fiscal deficit is exogenous and government spending is endogenous in the G-Cubed model.

3 Simulation results This paper models a permanent loss of confidence in emerging economies as an increase in the country risk premia

by 200 basis points relative to the baseline, from 2014

forever (see Appendix, Figure 1). This is equivalent to a permanent increase in the risk premia of households, firms, and international investors in the emerging markets. The base year is 2013 and all results are expressed as percentage deviation from the baseline. The results are reported for 20 years. Loss of confidence and the associated higher risk leads to a sharp contraction of the emerging economies (Figure 2) and an expansion of the developed (non-shocked) economies (Figure 3). Relative to the baseline, real GDP immediately falls by more than 1.5 percent in China and India and by more than 2 percent in Indonesia and Latin America. China and India recover relatively faster than the other emerging economies. For the next 20 years, the output of emerging markets remains below the baseline. Conversely, developed economies expand significantly in the short run and their level of GDP remains above the baseline for the next 20 years. The US and Korea expand the most in the short run (more than 1 percent) while the oil-exporting and Middle East countries enjoy a relatively higher level of GDP in the long run compared to other nonemerging economies. Contraction of the emerging markets and expansion of the developed economies can be explained by what happens to their exchange rate, interest rate, stock value, consumption, investment, savings, and other macroeconomic factors. The flow-on effects of financial capital and trade are important in this regard. When emerging

8

markets are shocked with risks, financial capital immediately flows out of these economies to the developed economies, affecting the exchange rate, interest rate, capital stock, and investment. When international investors perceive higher country risk, they shift away from all financial assets of the emerging markets, affecting bond price and real interest rates. Further, when households perceive higher risks, they postpone consumption and increase savings in the short run. These channels are important to analyze the global consequences of a loss of confidence in emerging economies, which are explained below. A permanent higher risk in the emerging economies leads to a massive capital outflow and hence to a depreciation of their currencies relative to the US dollar (Figure 4). India experiences the highest immediate depreciation in its real exchange rate (19.5 percent) followed by Latin America (18.7 percent), Indonesia (17.7 percent), and China (14.7 percent). It takes more than 20 years for the emerging markets to get their real exchange rate back to the baseline. The currencies of developed economies also depreciate relative to the US dollar but not as much as the emerging markets (Figure 5). This is because other developed economies are more exposed through trade with the emerging markets and therefore, their currencies strengthen relative to the currencies of emerging economies, but depreciate relative to the US dollar. As investors perceive higher risks, they shift away from all financial assets of the emerging markets, leading to a massive capital outflow and a sharp fall in bond price. In other words, the real interest rate, which is the inverse of bond price, goes up sharply in the emerging economies. Higher real interest rate, accompanied by higher risk premia, translates to a much higher risk-adjusted short term real interest rate (Figure 6). Relative to the baseline, the short term real interest rate immediately jumps by more than 2 percent in China, 1.2 percent in Indonesia and less than 1 percent in India and Latin America. Interest rate spikes for the first 5 years but eventually settle down to a permanently higher level (1.5 percent relative to the baseline) in the long run. Conversely, with massive capital inflow and a sharp fall in bond price, the short term real interest rate in non-emerging economies settles down to a permanently lower level in the long run (Figure 7).

9

The long term real interest rate in the emerging markets (reflected in the 10 year bond rate) rises immediately with the fall in bond price (Figure 8). The largest immediate increase is in China (1.13 percent) followed by Indonesia (1.11 percent), Latin America 0.83 percent) and India (0.71 percent). In the long run, the 10 year bond rate in these economies remains higher (at around 1.2 percent) relative to the baseline. Conversely, the higher level of investment in the financial markets of developed economies leads to a permanently lower long term bond rate (Figure 9). The equity risk premium in emerging markets goes up with higher country risks. Investors respond by liquidating all financial assets, including equities. As investors require extra returns to hold the equities of emerging markets, the discount rate goes up, leading to a sharp fall in the value of stocks (Figure 10). Latin America experiences the highest immediate decline in the value of its stock market (5.6 percent) followed by China (4.1 percent), India (3.8 percent) and Indonesia (2.9 percent). Over the next 20 years, the value of their stock markets remains below the baseline. On the other hand, with inflows of capital from the emerging markets, the value of stocks in developed markets jumps immediately in the range 0.8-2.1 percent (Figure 11). Except for the US, the stock market value of developed economies remains above the baseline in the long run. It can be noted that the fall in stock value of the emerging markets is sharper than the rise in stock values of the developed economies. This is due to the relative size of economies; an extra dollar flowing out of the emerging markets is worth less to the developed economies because of the size of their economies. Private investment falls steeply in the emerging markets due to the negative financial flow-on effects, and higher short and long term interest rates (Figure 12). As each extra unit of investment yields a lower rate of return due to higher risk premium, firms postpone investment in the short run. Investment in Latin America falls immediately by more than 20 percent relative to the baseline. China, India, and Indonesia experience a 7.7 percent, 8.8 percent and 10.1 percent immediate decline in investment respectively. Over the next 20 years, the level of investment in emerging markets remains below the baseline. In contrast, with inflows of financial capital, private investment in developed economies immediately goes up, expands sharply for the next 5 years and remains above

10

the baseline for the next two decades (Figure 13). In the short run, the US investment expands the most, followed by the UK, Japan, Germany, and Korea. The rate of return on capital needs to be higher for investors to hold relatively risky financial assets of the emerging markets. This implies that the capital stock must fall significantly (due to diminishing returns) to generate a higher rate of return (Figure 14). The capital stock in emerging economies begins to fall a year after the permanent shock and reaches minimum after 4 years. By the year 2018, capital stock falls by around 18 percent in Latin America, 10 percent in Indonesia, 8 percent in India, and 7 percent in China and remains below the baseline in the long run. The opposite happens to the developed economies. With higher level of investment, non-emerging economies build up capital stock over time, which remains above the baseline over the next 20 years (Figure 15). By the year 2020, the US, UK and Korea build up around 5.8 percent, 7.3 percent, and 5.1 percent higher capital stock relative to their baseline. As a lot of capital flows into the formation of physical capital (which has an adjustment cost), the desired capital stock in the steady state must be higher in developed economies (due to lower marginal product of capital). Loss of confidence in emerging markets leads households to discount their expected future income at a higher rate. As the present value of lifetime wealth falls, households cut back consumption (Figure 16) and increase savings (Figure 17). Relative to the baseline, private consumption in the emerging economies immediately falls by 4.2-5.6 percent with China and Indonesia experiencing a relatively steep decline over the next 10 years. Private savings immediately jumps in all emerging economies except for Latin America. In case of the developed economies, consumption jumps immediately (the Keynesian multiplier effect) and remains above the baseline for the next 20 years (Figure 18). In the long run, the level of consumption in Australia settles down to a 2 percent higher level relative to the baseline. Further, with lower uncertainty about the future, households of these economies reduce savings in the long run (Figure 19). Although emerging markets are hit by the negative financial flow-on effects, massive exchange rate depreciation makes their exports relatively cheaper and imports relatively more expensive. This leads to an improvement in their trade and current account balance over the next two decades (Figure 20 & Figure 21). Latin America enjoys the highest 11

immediate increase in its trade balance (4.1 percent of GDP) followed by Indonesia (3.5 percent), China (2.7 percent), and India (2.6 percent). In contrast, the trade and current account balance of developed economies deteriorates due to exchange rate appreciation (Figure 22 & Figure 23). The trade balance of Korea immediately falls by 1.6 percent of GDP relative to the baseline followed by the UK (1.4 percent), USA (1.2 percent) and Germany (1.2 percent). For the next two decades, emerging economies enjoy a positive trade and current account balance. It can be noted that real GDP of the emerging economies (Figure 2) contracts less than the decline in their investment (Figure 12) and consumption (Figure 16). This is due to the positive trade effects which partially offset the negative financial flow-on effects. As emerging economies shrink, we would expect a fall in their aggregate price level. However, higher import prices (due to exchange rate depreciation) cause inflation to immediately jump in all the emerging markets, except China (Figure 24). This is because the Chinese Yuan is pegged to the US dollar and the US inflation falls immediately (Figure 25). India experiences the highest immediate inflationary pressure (2.5 percent) followed by Latin America (2.1 percent) and Indonesia (0.3 percent). In contrast, inflation in the non-emerging economies immediately falls below the baseline; by 0.77 percent in Germany, 0.67 percent in the UK, and 0.63 percent in the US (Figure 25). Inflation in all economies spikes for the next 10 years but eventually settles back to the baseline level. Contraction of the real economy, accompanied by rising inflation, leaves the central banks of emerging economies in a major dilemma. The monetary rule is defined as the nominal income targeting rule. Therefore, with adjustment in the short term policy interest rates (not shown) the nominal income of these economies goes back to the baseline level in the long run (Figure 26). To summarize, households reduce consumption and investors postpone investment due to higher risks in the emerging markets. As financial capital flows out of these economies, short and long term interest rates go up and the desired stock of capital shrinks. All these negative impacts translate to a sharp fall in real GDP. On the other hand, capital inflow in the developed economies brings down the real interest rates,

12

stimulates consumption and investment, builds up capital stock and therefore, leads to a higher level of GDP in the short and long run. However, GDP only reflects the production side of the economy. A better measure of welfare is the gross national product (GNP) which reflects income earned by all domestic residents, irrespective of their location (McKibbin 1998). Although real GDP of emerging economies remains below the baseline for the next 20 years, the level of real GNP crosses over the baseline after 10-15 years (Figure 27). Conversely, real GNP of the developed economies falls below the baseline in the long run (Figure 28). Thus, the level of income of developed economies does not rise as much as their production. This is due to the fact that part of the financial capital owned by foreigners now earns a lower rate of return.

4 Conclusion This paper examined the global consequences of a permanent loss of confidence in emerging economies using an inter-temporal G-Cubed model. The loss of confidence was modeled as an increase in the country risk premia by 200 basis points relative to the baseline from 2014 forever. The simulation results suggest that a permanent upward revision of risk has large real consequences for both emerging and developed economies. Emerging economies contract and developed economies expand in the short run and it takes more than two decades for the emerging markets to get their consumption, investment and output level back to the baseline. This paper finds that a permanent shift in risk perception has large effects on the real economy. Capital outflow from the emerging markets raises the cost of capital, leading to disinvestment by firms. As households perceive higher risks, they cut back consumption and increase savings which further accelerates the disinvestment process. As a result, emerging economies contract for several years. However, higher net exports driven by exchange rate depreciation improve their trade and current account balance over time, which partially offsets the contraction of domestic demand. The developed economies experience exactly the opposite effects. While their economies expand with higher inflows of capital, the trade and current account position worsens with appreciation of the exchange rate, which partially offsets the output expansion.

13

It follows from the analyses that open trade and capital markets act as important stabilizers for the shocked and non-shocked economies. Emerging economies, which are hit by the negative financial flow-on effects, need a temporary boost in exports to avoid a recession. On the other hand, non-emerging economies, which are facing stronger domestic demand, need additional capital to expand their productive capacity. Without these adjustments, the effects on the real economy would be much larger. This paper therefore suggests that policies should focus on managing risks rather than controlling international capital flows because such controls would hinder important stabilizing channels. A better policy should allow free capital mobility across countries and should try to strengthen the domestic financial system with greater transparency and accountability, for accurate evaluation of risks. The governments should not act as the insurer of last resort for the exchange rate or investment risks rather should try to build a better functioning domestic financial system that minimizes the fluctuation in risks. Word count: 4,936

References Cagliarini, A & McKibbin, WJ 2009, ‘Global relative price shocks: the role of macroeconomic policies’, Research Discussion Paper 2009-10, Reserve Bank of Australia, Canberra, viewed 18 October 2014, < http://www.rba.gov.au/publications/confs/2009/pdf/conf-vol-2009.pdf#page=310>. Carriere-Swallow, Y & Cespedes, LF 2013, ‘The impact of uncertainty shocks in emerging economies’, Journal of International Economics, vol. 90, no. 2, pp. 316-325. Claessens, S 2010, ‘The financial crisis policy challenges for emerging markets and developing countries’, The Journal of Applied Economic Research, vol. 4, no. 2, pp. 177-196. International Monetary Fund 2011, Recent experiences in managing capital inflows— cross-cutting themes and possible policy framework, International Monetary Fund, viewed 4 November 2014, < http://www.imf.org/external/np/pp/eng/2011/031111.pdf>. International Monetary Fund 2014, World economic outlook: recovery strengthens, remains uneven, viewed 24 October 2014, < http://www.imf.org/external/pubs/ft/weo/2014/01/pdf/text.pdf >.

14

McKibbin, WJ 1998, East Asia in crisis: from being a miracle to needing one?, Routledge Press, London. McKibbin, WJ 1999, ‘International capital flows, financial reform and consequences of changing risk perception in APEC economies. Brookings Institution, Washington DC, viewed 14 October 2014, < http://msgpl.com.au/download/apec993.pdf>. McKibbin, WJ & Wilcoxen, PJ 1999, ‘The theoretical and empirical structure of the GCubed model’, Economic Modelling, vol. 16, pp. 123-148. McKibbin, WJ & Stoeckel, A 2009, ‘Modelling the global financial crisis’, Oxford Review of Economic Policy, vol. 25, no. 4, pp. 581-607. McKibbin, WJ & Stoeckel, AB 2012, ‘Global fiscal consolidation’, Asian Economic Papers, vol. 11, no. 1, pp. 124-146. Radelet, S & Sachs, J 1998, ‘The onset of the East Asian financial crisis’, NBER Working Papers, no. 6680, National Bureau of Economic Research, Cambridge, Massachusetts, viewed 28 October 2014, < http://www.nber.org/papers/w6680.pdf>. Shin, HS 2013, ‘The second phase of global liquidity and its impact on emerging economies’, Keynote address at the Federal Reserve Bank of San Francisco Asia Economic Policy Conference, vol. 7, viewed 2 November 2014, . Stiglitz, J 2014, ‘Tapping the brakes: are less active markets safer and better for the economy?’, Conference on Tuning Financial Regulation for Stability and Efficiency, Atlanta, Georgia, vol. 15, viewed 3 November 2014, . Taylor, JB 1993, ‘Discretion versus policy rules in practice’, Carnegie-Rochester Conference Series on Public Policy, no. 39, North Holland, viewed 15 October 2014, < http://www.sciencedirect.com/science/article/pii/016722319390009L>. World Bank 2014, Global economic prospects: shifting priorities, building for the future, World Bank, viewed 22 October 2014, < http://www.worldbank.org/content/dam/Worldbank/GEP/GEP2014b/GEP2014b.pdf >.

15

USA

JPN

GBR

16

DEU

AUS

-3.0

-3.5 LAM

Figure 3 Non-emerging economies: Real GDP (GDPR)

1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

KOR

2032 2033

2032

2033

2031

-2.5

2031

-2.0 2030

-1.5

2030

-1.0 2029

2028

LAM

2029

2028

INO 2027

2026

2025

2024

OAS

2027

2026

2025

IND

2024

2023

2022

2021

INO

2023

2022

CHI

2021

2020

2019

2018

IND

2020

2019

2018

2017

2016

2015

2014

2013 CHI

2017

2016

2015

2014

% Deviation -0.5

2013

% Deviation

2053

2051

2049

2047

2045

2043

2041

2039

2037

2035

2033

2031

2029

2027

2025

2023

2021

2019

2017

2015

2013

% Deviation

Appendix

Figure 1 Emerging economies: Risk premia (EXCR) 2.5

2.0

1.5

1.0

0.5

0.0

ROW

Figure 2 Emerging economies: Real GDP (GDPR)

0.0

OPC

Figure 4 Emerging economies: Real exchange rate, REXC (US$ per unit of local currency)

% Deviation

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

-5

2013

0

-10 -15 -20 -25 CHI

IND

INO

LAM

% Deviation

JPN

GBR

DEU

AUS

KOR

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

0.0 -0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -5.0

2013

Figure 5 Non-emerging economies: Real exchange rate, REXC (US$ per unit of local currency)

OPC

Figure 6 Emerging economies: Risk adjusted short term real interest rates (INTR) 2.5

1.5 1.0 0.5

CHI

IND

INO

17

LAM

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

0.0 2013

% Deviation

2.0

Figure 7 Non-emerging economies: Short term real interest rate (INTR) 0.2 0.1 2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

-0.1

2013

% Deviation

0 -0.2 -0.3 -0.4 -0.5 -0.6

USA

JPN

GBR

DEU

AUS

KOR

OPC

2032

2033

2032

2033

2030

2029

2028

2031

INO

2027

2026

2025

2024

2023

2022

IND

2031

CHI

2021

2020

2019

2018

2017

2016

2015

2014

1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 2013

% Deviation

Figure 8 Emerging economies: Long term real interest rate (RB10)

LAM

% Deviation

USA

JPN

GBR

DEU

18

AUS

KOR

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

0.00 -0.05 -0.10 -0.15 -0.20 -0.25 -0.30 -0.35 -0.40 -0.45 -0.50

2013

Figure 9 Non-emerging economies: Long term real interest rate (RB10)

OPC

% Deviation

-5

CHI

IND

19

INO

-10

-15

-20

-25

-30

-35

LAM

2033

KOR

2032

2031

2030

AUS

2029

2028

2027

DEU

2033

2032

2031

2030

2029

2028

2027

2026

2025

INO

2026

2025

2024

2023

2022

IND

2024

2023

GBR

2022

2021

2020

2019

2018

2017

2016

2015

2014

CHI

2021

2020

JPN

2019

2018

2017

USA

2016

2015

2014

-0.5 2013

% Deviation

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

-1

2013

% Deviation

Figure 10 Emerging economies: Total stock market value (STMT) 0

-2

-3

-4

-5

-6 LAM

Figure 11 Non-emerging economies: Total stock market value (STMT) 2.5

2.0

1.5

1.0

0.5

0.0

-1.0

-1.5

OPC

Figure 12 Emerging economies: Investment (INVT)

0

% Deviation

9 8 7 6 5 4 3 2 1 0 -1

USA

JPN

GBR

20

DEU

AUS

Figure 15 Non-emerging economies: capital stock (CAPY)

KOR

2032

2033

2033

KOR

2032

2031

LAM

2031

-20 2030

-15

2030

-10 2029

2028

2027

AUS

2029

2028

INO

2027

2026

2025

2024

DEU

2026

2025

IND

2024

2023

2022

2021

GBR

2023

2022

CHI

2021

2020

2019

2018

JPN

2020

2019

2018

2017

2016

2015

2014

USA

2017

2016

2015

2014

-5 2013

% Deviation

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

18 16 14 12 10 8 6 4 2 0 -2

2013

% Deviation

Figure 13 Non-emerging economies: Investment (INVT)

OPC

Figure 14 Emerging economies: capital stock (CAPY)

5

0

OPC

USA

JPN

GBR

21

DEU

AUS

1.5

1.0

0.5

0.0 2028

KOR 2032 2033

2032

2033

2031

2.0

2031

2.5 2030

3.0

2030

Figure 18 Non-emerging economies: Consumption (CONP) 2029

LAM

2029

2028

2027

2026

2025

INO

2027

INO

2026

2025

IND 2024

2023

2022

IND

2024

2023

2022

CHI

2021

2020

2019

2018

2017

2016

2015

CHI

2021

2020

2019

2018

2017

2016

2015

2014

2013

10 8 6 4 2 0 -2 -4 -6 -8 -10

2014

% Deviation % Deviation

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

-1

2013

% Deviation

Figure 16 Emerging economies: Consumption (CONP) 0

-2

-3

-4

-5

-6

-7

-8

-9 LAM

Figure 17 Emerging economies: Domestic non-government savings (SAVT)

OPC

Figure 19 Non-emerging economies: Domestic non-government savings (SAVT) 6 2 2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

-2

2014

0 2013

% Deviation

4

-4 -6 -8 -10

USA

JPN

GBR

DEU

AUS

KOR

OPC

CHI

IND

INO

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2013

% Deviation

Figure 20 Emerging economies: Trade balance (TBAL)

LAM

CHI

IND

INO

22

LAM

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2013

% Deviation

Figure 21 Emerging economies: Current account balance (CURR)

% Deviation

USA

JPN

GBR

DEU

AUS

KOR

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

0.0 -0.2 -0.4 -0.6 -0.8 -1.0 -1.2 -1.4 -1.6 -1.8 -2.0

2013

Figure 22 Non-emerging economies: Trade balance (TBAL)

OPC

Figure 23 Non-emerging economies: Current account balance (CURR)

% Deviation

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

-0.5

2013

0.0

-1.0 -1.5 -2.0 -2.5

USA

JPN

GBR

DEU

AUS

KOR

OPC

Figure 24 Emerging economies: Inflation (INFL) 3.0 2.5 1.5 1.0 0.5

-1.0 -1.5 CHI

IND

INO

23

LAM

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

-0.5

2014

0.0 2013

% Deviation

2.0

% Deviation

1.0 0.5 0.0 -0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5 -4.0

CHI

IND

24

INO

LAM 2032 2033

2031

2032

2033

Figure 27 Emerging economies: Real GNP (GNPR) 2031

LAM 2030

-3

2030

-2 2029

2028

2027

AUS

2029

2028

2027

INO 2026

2025

2024

DEU

2026

2025

2024

IND 2023

2022

2021

GBR

2023

2022

CHI

2021

2020

2019

2018

JPN

2020

2019

2018

2017

2016

2015

USA

2017

2016

2015

2014

% Deviation

KOR

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

-0.2

2014

2013

-1

2013

% Deviation

Figure 25 Non-emerging economies: Inflation (INFL) 0.4

0.2

0.0

-0.4

-0.6

-0.8

-1.0 OPC

Figure 26 Emerging economies: Nominal income (LOGY+PRID) 3

2

1

0

Figure 28 Non-emerging economies: Real GNP (GNPR) 1.5

0.5

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

-0.5

2014

0.0 2013

% Deviation

1.0

-1.0

USA

JPN

GBR

DEU

Source: G-Cubed (v108V) model.

25

AUS

KOR

OPC