Information about Asia and the Pacific Asia y el Pacífico

Chapter 2. Investment in China: Too Much of a Good Thing?

Anoop Singh, Malhar Nabar, and Papa N'Diaye
Published Date:
November 2013
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Information about Asia and the Pacific Asia y el Pacífico
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Il Houng Lee, Murtaza Syed and Liu Xueyan 

As documented in Chapter 1, much of the decline in China’s current account surplus has been accomplished by boosting investment as a share of the national economy. This chapter assesses the appropriateness of China’s current investment levels. It finds that although China’s capital-to-output ratio is within the range of other emerging markets, its economic growth rate stands out, partly as the result of a surge in investment since 2000. Moreover, its investment is significantly higher than suggested by a cross-country panel estimation. This deviation has been accumulating since 2000, and at nearly 10 percent of GDP is now larger and more persistent than experienced by other Asian economies leading up to the Asian crisis of the late 1990s. However, because China’s investment is predominantly financed by domestic savings, a crisis appears unlikely when assessed against dependency on external funding. But this does not mean that the cost is nil. Rather, it is distributed to other sectors of the economy through a hidden transfer of resources, estimated to average 4 percent of GDP per year.


In non–resource rich countries, most economic takeoffs are strongly associated with high levels of investment. Asia, in particular, is a typical example of how high investment has facilitated rapid economic growth.1 Investment alone, of course, does not explain the growth story. Total factor productivity (TFP), labor supply, and savings in the neoclassical sense, and market access and efficient financial intermediation from the macro aspect, all play important roles. Moreover, in Asia’s case, economies have also benefited from exports. Even during periods when investment has been below its long-term trend, Asian economies have enjoyed rapid growth through access to expanding global markets, notably during most of the 1970s when the newly industrialized economies were taking off.

However, high investment has also proven to be costly. Although Asian countries usually have a high saving rate, several countries resorted to foreign financing to maintain even-higher investment ratios. Although this strategy enabled them to achieve a faster growth path for some time, typically it eventually led to a banking or foreign exchange crisis, from which it took several years to recover (Figure 2.1). These crises occurred because the cost of financing such high rates of investment was often mispriced, only to be corrected abruptly. In emerging economies, mispricing often involved currency and maturity mismatches, the risk of which was obscured by implicit guarantees or lack of information. In other words, an artifically low cost of financing supported excessive investment, including in property and manufacturing sectors, which eventually resulted in a crisis. This pattern was also observed in other emerging markets outside Asia, such as in Latin America during the 1980s.

Figure 2.1Gross Capital Formation

Source: IMF staff estimates.

Note: Year of take-off for each economy given in parentheses.

This chapter compares China’s current investment level with those of comparator economies.2 It finds that China’s capital-to-output ratio is within the range of other emerging markets, but its pace of growth stands out from the rest, partly as the result of a surge in investment since 2000. Moreover, when measured against a norm estimated from a cross-country panel, its investment is too high. Although a crisis appears unlikely when assessed against dependency on external funding, concerns arise about the underlying domestic strain associated with financing such a high level of investment, which appears to be implicitly borne by households. This chapter also contributes to the literature by harnessing the insights, sparse assumptions, and increased degrees of freedom that come from using an up-to-date panel of comparator economies, with both the countries and the time coverage carefully selected to match China’s economic features and phase of development.

The rest of the chapter is structured as follows: The next section motivates the analysis by comparing China’s investment with a group of other emerging market economies. A simple welfare maximization model is then introduced to illustrate that assessing the appropriateness of the level of investment requires a more comprehensive approach than the neoclassical indicators. The subsequent section uses a panel estimation to derive an investment “norm” based on fundamentals across countries and the implict cost of supporting China’s high investment level is estimated. The last section concludes.

China’s Investment From A Comparative Perspective

As a first proxy of whether a country’s investment is too high or low, it is instructive to compare the investment- and capital-to-output ratios of that economy with estimates of their long-term equilibrium (steady-state) levels.3 On this basis, China was underinvesting in the 1970s and to a lesser extent in the 1980s (Figure 2.2). China’s investment has since picked up, especially after 2000. By 2005, China’s capital-to-output ratio was close to its long-term level, so its investment-to-GDP ratio should theoretically have tended to fall back toward its steady-state value. However, during 2007–11, to counter the adverse effect of the global economic and financial crisis, China raised its investment further. Depending on the assumptions, China may have been overinvesting by between 12 and 20 percent of GDP relative to its steady-state desirable value during this period.

Figure 2.2Capital- and Investment-to-Output Ratios

(emerging market economies, relative to steady-state level in 2007–11)

Sources: Penn World Tables; IMF, World Economic Outlook database; and IMF staff calculations.

Of course, a number of limitations arise with this approach to assessing the appropriateness of the level of investment. In particular, the estimates do not capture structural changes such as a shift away from capital-intensive growth or in the efficiency of investment over time. Indeed, there is no a priori reason to presume that an economy growing faster so as to catch up with advanced economies should have a lower capital-to-output ratio, that is, below its long-term level, or that its investment rate should be above its long-term level. This will depend on several other factors, notably TFP.

On some simple metrics, China’s investment efficiency is still broadly in line with that of other emerging economies. As shown in Figure 2.3, China’s capital-to-output ratio has increased relative to those of other emerging markets since about 1990. However, it is still broadly within the average cross-country range. What stands out is China’s growth, showing that its achievement during this period has been unique.

Figure 2.3Growth and Capital-to-Output Ratios for Emerging Market Economies, 1990–95 and 2007–11

Sources: Penn World Tables; IMF, World Economic Outlook database; and IMF staff calculations.

Note: Small squares represent other emerging market economies.

However, China’s strong performance comes at a price. In the 1990s, China was within the bounds experienced by emerging markets worldwide for the relationship between investment rates and capital-to-output ratios (Figure 2.4), but it has since gravitated to an extreme outlier position that is suggestive of potential overinvestment. China now requires ever higher investment to generate the same amount of growth. Unless TFP surges, with export performance expected to remain subdued in the medium term (given both sluggish demand overseas and diminishing opportunities for dramatic gains in China’s market share), the contribution of investment to growth will need to reach 60–70 percent to support the same amount of growth (Figures 2.5). Under such a strategy, vulnerabilities will likely grow in the form of hidden deadweight that will have to be paid for in the future in one form or another.

Figure 2.4Capital- and Investment-to-Output Ratios for Emerging Market Economies, 1990–95 and 2007–11

Sources: Penn World Tables; IMF, World Economic Outlook database; and IMF staff calculations.

Note: Small squares represent other emerging market economies.

Figure 2.5Contributions to GDP Growth

Source: IMF staff estimates.

Note: ICOR—Incremental capital-to-output ratio.

Moreover, consumption has declined to about 40 percent of GDP, partly as the result of falling household income as a share of GDP. In fact, household income has risen very rapidly except relative to overall GDP growth. The latter, as discussed above, was pulled up by an increasing contribution from investment. To the extent that growth is to improve the quality of living standards by providing more value added to households, a falling consumption share raises questions about the very purpose of the current investment-based growth model.

What Can Aggregate Cross-Country Data Reveal?

Under a welfare-maximizing state, intertemporal consumption preferences will determine the level of consumption. However, the relative time preference for consumption is not directly observable. An indirect way of measuring intertemporal preference would be to assume that the average level of consumption, or investment, of a relatively large sample of countries approximates such a preference. Then, an optimal investment level, or a “norm,” could be defined as the level that would maximize social or household welfare. This level of investment will be determined by economic fundamentals, including the real interest rate and the depreciation rate (see Lee, Syed, and Xueyan, 2012, for details) and can be estimated from regressions linking cross-country investment rates over time to a set of fundamentals.

Dynamic panel data models were run for 36 economies for the period 1955–2009. The panel was unbalanced, with one innovation being that the starting period for each economy was calibrated to capture its economic takeoff (and associated elevated levels of investment). This county-specific starting period ensures that the investment norm is not biased downward and in fact represents a higher bar than usual for detecting any potential overinvestment. The sample consists of emerging market economies, as well as Japan and Taiwan Province of China. About one-third of the sample is made up of Asian economies. The empirical strategy allows for changes in preferences over time, but imposes a “normal” preference for intertemporal consumption across emerging markets relative to fundamentals. By carefully calibrating this around takeoff periods, and by including China’s Asian peers that have also tended to rely heavily on investment, this average is likely to be adequately representative.

The models relate the investment-to-GDP ratio in country x at time t to a host of explanatory variables motivated by theory (Lee, Syed, and Xueyan, 2012). These variables include the lagged dependent variable; savings-to-GDP and credit-to-GDP measures to capture the availability of financing; real lending rates to capture the cost of capital; the exports-to-GDP ratio to capture the potential external contributions to investment; real growth rates as a proxy for the return to capital; the level of real GDP to capture the level of economic development; age-dependency ratios to capture the potential impact of demographics; and macroeconomic uncertainty captured by the standard deviation of three-year rolling windows of real GDP growth and the reserves-to-GDP ratio to measure the need for countries to save to counter volatile capital flows. These variables are grounded in the underlying model outlined in Lee, Syed, and Xueyan (2012) as well as others developed in the literature, such that the estimation is better thought of as being structural in nature, and not reduced form.

The models are estimated in first differences (to control for fixed effects) using generalized method of moments to account for the presence of the lagged dependent variable (which renders an ordinary least squares fixed-effects model inconsistent), measurement error, and potential endogeneity of the regressors (by using their lagged values as instruments).4 The estimation also includes time dummies, covering both the Asian crisis of the late 1990s and the 2008–09 global financial crisis. Provided no higher-order serial correlation is present in the residuals and the instruments are valid, this approach should yield unbiased and consistent parameter estimates. Both of these conditions are tested using standard tests.

The estimated investment equations fit the actual data well for most economies and suggest the following (with column 5 of Table 2.1 being the preferred specification):

Table 2.1Results of Investment Regressions
Lagged dependent0.652**0.628**0.630**0.615**0.652**0.664**
Real per capita GDP0.372**0.339**0.350**0.329**0.364**0.390**
Growth in credit0.033**0.030**0.023*0.032*0.031*
(annual percent of GDP)(0.01)(0.01)(0.01)(0.02)(0.02)
Real per capita GDP0.0002*0.0003*0.0002*0.0002*
(U.S. dollars)(0.00)(0.00)(0.00)(0.00)
Real interest rate−0.043**−0.041**
p-value of specification tests
m2 test (no second-order serial correlation in residuals)0.2010.2410.2390.2660.250.23
Hansen test (instrument validity)1.0001.0001.0001.0001.0001.000
Number of economies363636363636
Number of observations892892892892718718
Time period1955–20091955–20091955–20091955–20091955–20091955–2009
Sources: World Bank, World Development Indicators; IMF, World Economic Outlook; and IMF staff calculations.Note: Dependent variable is investment-to-GDP ratio. First-differenced general method of moments specifications, with year dummies. Instruments are lagged values of regressors. Robust t-statistics in parentheses. * and ** indicate significance at the 10 percent and 5 percent levels, respectively.

Ratio of population over age 65 to population ages 15–64.

Standard deviation of three-year rolling window of real GDP growth.

Sources: World Bank, World Development Indicators; IMF, World Economic Outlook; and IMF staff calculations.Note: Dependent variable is investment-to-GDP ratio. First-differenced general method of moments specifications, with year dummies. Instruments are lagged values of regressors. Robust t-statistics in parentheses. * and ** indicate significance at the 10 percent and 5 percent levels, respectively.

Ratio of population over age 65 to population ages 15–64.

Standard deviation of three-year rolling window of real GDP growth.

  • Investment tends to be persistent. The lagged dependent variable is large and significant, indicating inertia in aggregate levels of investment.
  • Stronger output growth leads to higher investment. Including exports in this specification does not lead to a significant coefficient (column 6), suggesting that the primary route through which globalization affects investment is by leading to stronger overall economic growth and hence raising the returns to capital.
  • An increase in the cost of capital lowers investment. Higher real interest rates reduce investment, as expected.
  • Increased availability of credit is associated with higher investment. The analysis used both change in credit and the saving-to-GDP ratio as the relevant measure, and found the former to render the latter insignificant.
  • As economies develop, they typically need higher investment. To capture potential nonlinearities and thresholds beyond which this positive relationship no longer holds, the analysis also included a squared per capita GDP term. However, this term was not significant, suggesting that the economies in the sample are on average still “taking-off.” This is not surprising given that the majority remain in the middle-income category.
  • Macroeconomic uncertainty leads to lower investment. Conditioning for the standard deviation of three-year rolling windows of GDP growth, the alternative proxy variable of changes in reserves was not significant. This outcome suggests that higher uncertainty does lead to lower investment but that this effect is better captured by the volatility of growth rather than the accumulation of reserves (which, after all, may be driven by considerations other than precautionary motives).
  • Aging of the population reduces investment, possibly because it leads to slower growth and thus reduces the returns to investment. Investment will consequently fall in the absence of technological progress and other structural changes that raise labor productivity. The results suggest that this effect dominates any short-term increase in investment as firms invest more to substitute capital for labor as a means of coping with a growing shortage of workers.5

Using these parameter estimates, investment in China may currently be about 10 percent of GDP higher than suggested by fundamentals (Figure 2.6). Even allowing for elevated investment levels associated with most economic takeoffs, the econometric evidence suggests that China is overinvesting. China’s predicted investment norm since 1985 has ranged between 33 and 43 percent of GDP. In reality, it has fluctuated in a much broader band of 35–49 percent of GDP. The model consistently predicts a lower norm for China, but until 2000, the deviations were usually not that significant and typically closed over a five-year time horizon.

Figure 2.6Actual and Predicted Investment-to-GDP Ratio, China

Source: IMF staff calculations.

A probit model suggests that the error term is positively associated with the probability of a crisis (Table 2.2). The analysis uses the error terms of the above regression, as well as a number of other variables previously considered to have explanatory power for predicting economic crises, as a measure of overinvestment. Crises are dated in the sample according to the year in which they occurred, based on the dating of banking crises in Reinhart and Rogoff (2008). On average, other things being equal, overinvestment by 1 percent of GDP as measured in the cross-country regression leads to a 0.03 percentage point increase in the probability of an economy encountering a crisis.

Table 2.2Probit: Probability of Crisis
Real interest rate−0.016**−0.016**
Real per capita GDP growth−0.015**−0.015**
Growth in credit (annual percent of GDP)−0.001−0.002
Current account (percent of GDP)−0.022**−0.026**
Overinvestment (percent of GDP)0.031**
Number of economies3636
Number of observations752752
Time period1955–20091955–2009
Sources: World Bank, World Development Indicators; IMF, World Economic Outlook; and IMF staff calculations.
Sources: World Bank, World Development Indicators; IMF, World Economic Outlook; and IMF staff calculations.

The current deviation between predicted and actual investment for China is the largest ever and has been accumulating since 2000. Although the further widening of the deviation since 2009 could be regarded as a temporary result of the 2009 stimulus package, the divergence started before then, and is also larger than the implied overinvestment in other Asian economies leading up to the Asian crisis of the late 1990s or in Japan in 1980 before the onset of its lost decade (Table 2.3). Both of these episodes were followed by protracted declines in growth and investment. Credit growth (particularly postcrisis) and the cost of capital in China in recent years also appear to be in dangerous territory compared with experiences in other countries. Mechanically applying the coefficient estimates from the probit model to China’s estimated overinvestment shows that the probability of a crisis would rise from 8 percent in 2005 to about 20 percent in 2013. These numbers are only indicative, however. Not only does the usual uncertainty surround these parameter estimates, but as discussed below, the nature of China’s investment model is very different from that of other emerging markets and tends to reduce the probability of a crisis relative to the average country in the sample.

Table 2.3Evolution of Variables in the Five Years before a Crisis
Overinvestment (percent of GDP, average)Overinvestment (percent of GDP, cumulative)Overinvestment (number of years)Credit/GDP (annual percent change)Real cost of capital (annual average)Real GDP per capita (annual percent change)
Memo item:

Source: IMF staff estimates.
Source: IMF staff estimates.

However, the trigger of a crisis, if ever, in China will likely be different from the triggers in other countries. What distinguishes China from the rest is its relative lack of reliance on external funding for domestic investment. In large part, this is due to its high saving rate. However, various studies indicate that saving is arbitrarily high because of controls in the financial sector that de facto result in a subsidy transfer from households and small and medium enterprises to large corporations, estimated to be close to 4 percent of GDP per year.6 Whereas in other countries the high cost of excess investment has been exposed in the form of bank stress or a foreign exchange market crisis, in China, it will likely be captured in, or triggered by, any one of the weak links in this implicit subsidy system.


China’s extraordinary economic performance since 1980 undoubtedly is in large part attributable to investment. Despite the prolonged period of heavy investment, China’s capital-to-output ratio is still in the range of those of other emerging market economies while its growth rate has far outpaced others since 1990. Nevertheless, the marginal contribution of an extra unit of investment to growth has been declining, requiring ever larger increases in investment to generate an equal amount of growth. Now, with the ratio of investment to GDP already close to 50 percent, the current growth model may have run its course.

Measured against a norm estimated from panel data for a large number of countries, China is overinvesting. Moreover, the deviation that has been accumulating since 2000 is larger and more persistent than the estimated overinvestment in other Asian economies leading up to the Asian crisis of the late 1990s. The latest divergence was understandably the result of the 2009 measures used to contain the spillover from the global financial crisis. The government is well aware of the challenge posed by excessive reliance on investment and is thus accelerating its effort to reorient the economy, by moderating investment growth while promoting consumption.

Although a crisis appears unlikely when assessed against dependency on external funding, potential strains from financing overinvestment still exist and could be quite large. Assuming the conditions that prevailed in other emerging market economies during their pre- and postcrisis periods also apply to China, the probability of a crisis in China would mechanically be about one in five. However, because of the differences in the modality of financing investment, an external crisis of the kind experienced by many other emerging market economies appears very unlikely to occur in China. However, this does not mean that there is no cost. Rather, the cost is distributed to other sectors of the economy in the form of a hidden, implicit transfer of resources, estimated to average 4 percent of GDP every year.

The challenge will be to engineer a gradual reduction in investment to a path that would maximize social welfare. Because that path is not identifiable, the norm estimated using a large sample of emerging market economies could provide some guidance. Based on cross-country regressions, lowering China’s investment by 10 percentage points of GDP over time would bring it to levels consistent with fundamentals. Otherwise, vulnerabilities will continue to build. To the extent that elevated levels of investment during the postcrisis period in China were somehow abnormal and necessitated by the sharp external slowdown, the challenge now is how to return to a more “normal” level of investment without compromising growth and macroeconomic stability. Obviously, reaching the level itself should not be the only goal, but should be accompanied by reforms that would raise productivity and efficiency while ensuring that the fruits of China’s remarkable growth are shared more equitably across different economic agents, in particular, ordinary Chinese households. International experience shows that these are prerequisites for sustainable growth in any country.

Annex 2A. Implementing the Neoclassical Approach
  • Neoclassical model: Steady-state level of investment (i*) is given by i* = k*(g +d)/(1 + g), based on estimates of a steady-state capital-to-output ratio (k*), the depreciation rate (d), and the rate of potential output growth (g).
  • Capital stock: Derived from the standard perpetual inventory method. Data on gross fixed real investment during 1950–80 are obtained from Penn World Tables, and from 1980 onward from the IMF World Economic Outlook (WEO) database. The initial estimate of capital stock is obtained assuming that the country is at a steady-state capital-to-output ratio in 1950. To obtain this ratio, the averages of k, g, and d for 1950–60 are used (Easterly and Levine, 2001, adopt a similar methodology). Alternative assumptions are used (e.g., setting it equal to 10 times the initial level of investment), and the results show that the guess at the initial capital stock becomes relatively unimportant decades later.
  • k*: For a given depreciation rate, k* is found to be the maximum value of the capital-to-output ratio on average over long periods (15 and 20 years) between 1950 and 2011. This helps ensure robustness, particularly vis-à-vis boom and bust periods. The average capital-to-output ratio for the countries in the sample is about 2½ during 1950–2011 and for industrial countries it was similar during 1970–2011.
  • d: A number of depreciation rates were used5, 7, and 10 percent. Results shown in the text are for a 7 percent depreciation rate, but results are robust to alternatives.
  • g: Two sets of assumptions are used for potential growth—the maximum growth rate (capped at five) over long periods between 1950 and 2011 for each country, and medium-term projections for growth from the latest WEO database (which, at about 8 percent, are higher for China). Results shown in the text are based on the latter, but are generally robust. Because these growth rates are higher for China, they present a stricter test of over-investment because i* is larger.

Cross-country investment regressions

Aggregate-level panel data are used to estimate the following investment model:

in which I/GDP is the investment-to-GDP ratio (from the WEO database) and Z is a vector of additional variables, including the lagged dependent variable, real per capita GDP growth, uncertainty (measured as the standard deviation of three-year rolling windows of real GDP) (all from the WEO); growth in credit as a percentage of GDP, real GDP per capita in U.S. dollar terms, the age-dependency ratio (defined as the ratio of the population over age 65 to the working-age population), and the real interest rate (all from the World Bank World Development Indicators database).

The sample was unbalanced, covering the period 1955–2009, and included the following emerging market economies (starting year in parentheses): Albania (1993); Algeria (1994); Argentina (1970); Armenia (1995); Belarus (1995); Bolivia (1979); Brazil (1970); Bulgaria (1991); Chile (1970); China (1982); Colombia (1970); Croatia (1994); Czech Republic (1997); Egypt (1970); Hungary (1989); India (1970); Indonesia (1971); Iran (2004); Israel (1980); Japan (1955); the Republic of Korea (1963); Malaysia (1970); Mexico (1971); Morocco (1978); Pakistan (2004); Peru (1986); Philippines (1970); Poland (1991); Romania (1994); South Africa (1964); Sri Lanka (1978); Taiwan Province of China (1965); Thailand (1970); Turkey (1973); Venezuela (1984); and Vietnam (1993).


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1During 1970–2010, the correlation between a five-year moving average investment-to-GDP ratio and economic growth was about 0.83 in developing Asia. The correlation is somewhat weaker at 0.74 for advanced economies, the G7, for example.
2Results of recent studies at the macro level on the question of whether China overinvests have been largely inconclusive, with Bai, Hsieh, and Qian (2006) and Lu and others (2008) suggesting not, while Rawski (2002); Dong, Zhang, and Shek (2006); Barnett and Brooks (2006); and Qin and Song (2009) argue otherwise. Microeconomic studies have tended to find greater support for misallocation of investment, including Liu and Siu (2009); Dollar and Wei (2007); Hsieh and Klenow (2009); Ding, Guariglia, and Knight (2010); and Geng and N’Diaye (2012). However, much of the literature imposes a number of strong assumptions, and few papers compare China’s investment with that in the rest of the world.
3According to the neoclassical model’s golden rule, such a level of investment is defined as i* = k*(g +d)/(1 + g), where (i*) is the steady-state level of investment based on estimates of a steady-state capital-to-output ratio (k*), the depreciation rate (d), and the rate of potential output growth (g). Relative to the golden rule equilibrium, China is currently overinvesting. See Annex 2A to this chapter for details.
4See Annex 2A to this chapter for details.
5The relative magnitude of the impact is, of course, smaller than the size of the estimated coefficients because of the different scales of the explanatory variables. With estimation in first differences, the annual change in the demographic variable is very small. As a result, the actual impact of the other variables on investment is significantly larger. For example, excluding the demographic variable from the specification increases the predicted level of investment in China by only 1 percent of GDP in 2009.
6See Lee, Syed, and Xueyan (2012) for details on this estimate. A large portion of the burden of financing overinvestment is borne by households, while small and medium enterprises are paying a higher price for capital because of the funding priority given to larger corporations.

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