Chapter

Chapter 1. Investment in the Euro Area: Why Has It Been Weak?

Author(s):
Petya Koeva Brooks, and Mahmood Pradhan
Published Date:
October 2015
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Author(s)
Bergljot Barkbu, S. Pelin Berkmen, Pavel Lukyantsau, Sergejs Saksonovs and Hanni Schoelermann 

Investment across the euro area—both in real terms and as a percentage of GDP—remains below its precrisis level. Investment performance has been weaker than in most previous recessions and financial crises. IMF staff analysis shows that much of this weakness can be explained by output dynamics, although a high cost of capital, financial constraints, high corporate leverage, and uncertainty have also inhibited investment in parts of the euro area. Investment is expected to pick up as the recovery strengthens and uncertainty declines. However, financial fragmentation and high corporate leverage in some countries will likely continue to weigh on investment.

Investment in the Euro Area: Postcrisis Trends

Investment has been hit hard since the onset of the global economic and financial crisis. It has not recovered since, including in many of the core economies. Total real investment remains below its precrisis level across the euro area.1 Part of this decline reflects reductions in public investment and in investment in housing in certain countries. For example, housing investment declined from about 12–13 percent of GDP before the crisis to 6 percent of GDP in Spain and to 2–3 percent of GDP in Greece and Ireland after the crisis. Similarly, following the sovereign debt crisis, both public investment and private nonresidential investment remain well below their precrisis levels in most of the euro area, particularly in stressed countries (Figures 1.1 and 1.2).2

Figure 1.1Investment Recovery to Date: 2013:Q4

(Percent; 2007 quarterly average = 100)

Sources: Eurostat; Haver Analytics; and IMF staff calculations.

Note: EA = Euro area. Data labels in the figure use International Organization for Standardization (ISO) country codes.

Figure 1.2Private Nonresidential Investment Recovery through 2013:Q4

(Percent; 2007 quarterly average = 100)

Sources: Eurostat; and IMF staff calculations.

Note: Last available data point is 2013:Q3 for PRT and 2012:Q4 for DEU. EA = Euro area. Data labels in the figure use International Organization for Standardization (ISO) country codes.

Overall, the behavior of investment and its determinants has varied widely across the euro area. Stressed countries have suffered more than core countries. Small and medium-sized enterprises have suffered more than larger corporations. And the services sector has suffered substantially.

Weak investment performance is associated with weak aggregate demand. Real GDP in the euro area remains below its precrisis level and is more sluggish than in typical recessions (panel 1 of Figure 1.3). Although the recovery is gaining momentum, domestic demand growth is still fragile, and the output gap for the euro area is still negative and large. Given subdued aggregate demand, it is not surprising that investment has also lagged behind the trends observed in most previous recessions (panel 2 of Figure 1.3). Indeed, investment growth is still lower than real GDP growth in the euro area, unlike in the recovery in the United States (Figure 1.4).

Figure 1.3GDP Growth and Investment around Recessions

Sources: Eurostat; Organisation for Economic Co-operation and Development; and IMF staff calculations.

Note: Quarterly data and year-over-year changes. t = 0 at 2008:Q1; the second line starts from 2011:Q3 (t = 15) to indicate the back-to-back recessions in the euro area; historical episodes are based on CEPR-dated recessions: 1974:Q3 to 1975:Q1, 1980:Q1 to 1982:Q3, and 1992:Q1 to 1993:Q3. CEPR = Centre for Economic Policy Research.

Figure 1.4GDP and Investment Growth in the Euro Area and the United States

Sources: Eurostat; and IMF staff calculations.

In addition, financial crises tend to have durable effects on investment, reflecting credit supply constraints, balance sheet problems, and other supply-side factors. Previous experience with financial crises shows that the decline in the investment-to-GDP ratio could be long lasting, with a peak impact of 3 to 3½ percentage points three years after the crisis (IMF 2014a). In the euro area, the observed decline in the investment-to-GDP ratio since the beginning of the crisis is more severe than the standard financial crisis but is in line with the decline observed in the most severe crises—with the ratio standing at 4¼ percentage points below the precrisis level (Figure 1.5).

Figure 1.5Euro Area versus Other Financial Crisis Episodes

Sources: IMF 2014b; and IMF staff calculations.

Note: Gross fixed capital formation in percent of GDP. The entire sample of advanced economy financial crises between 1970 and 2007 identified by Laeven and Valencia (2012). Big five financial crises are those in Spain, 1977; Norway, 1987; Finland, 1991; Sweden, 1991; and Japan, 1992. Dashed red lines denote 90 percent confidence bands; black line denotes the actual evolution of the investment-to-GDP ratio in the euro area from 2007 to 2013. Units on the x-axis are years; t = 0 denotes the year of the financial crisis.

In the euro area, the high cost of capital and limited access to funding could pose additional impediments to investment in certain countries. Even though the European Central Bank’s (ECB’s) policy rate is close to zero, lending rates remain elevated in some countries as financial fragmentation persists (Figure 1.6). Debt financing in the euro area is mostly bank based (about 90 percent), which increases the cost of capital, particularly for smaller firms. In addition, many smaller companies have difficulty accessing credit (European Central Bank 2014) (Figure 1.7). Improvements in corporate bond and stock markets since 2012 are likely to benefit only larger corporations.

Figure 1.6Euro Area Corporate Lending Rates

(Percent)

Sources: European Central Bank (ECB); Haver Analytics; and IMF staff calculations.

Note: Unweighted average; MFI lending to corporations under €1 million, 1–5 years maturity. Core = Belgium, France, Germany, Netherlands. Stressed countries = Greece, Ireland, Italy, Portugal, Spain. In the sample, Ireland is excluded from May 2011 and Greece from September 2012.

Figure 1.7Outcome of Loan Application by Euro Area Firms, 2013:H2

(Weighted percentages of responses)

Sources: Survey on the access to finance of enterprises (SAFE), European Central Bank; and IMF staff calculations.

Note: SME = small and medium-sized enterprises. Among firms that applied within the past six months. Data labels in the figure use International Organization for Standardization (ISO) country codes.

Moreover, the corporate sector is highly leveraged in some countries, further depressing credit flows to the private sector.3 Corporate debt-to-equity ratios remain elevated in some stressed countries (Figure 1.8), and the deleveraging process is still at an early stage. As companies repair their balance sheets and reduce debt, the effects feed back into the banking sector through low demand for credit and higher nonperforming loans. As a result of both corporate and banking sector deleveraging, credit to the private sector continues to shrink (Figure 1.9).

Figure 1.8Euro Area: Nonfinancial Corporation Debt-to-Equity Ratio

(Percent)

Source: European Central Bank.

Note: Debt at euro area level is nonconsolidated. EA = Euro area. Data labels in the figure use International Organization for Standardization (ISO) country codes.

Figure 1.9Euro Area: Growth of Nominal Credit to Firms

(Year-over-year percent change)

Source: Haver Analytics.

Note: The stock of credit for Slovenia includes the December 2013 transfer of nonperforming loans to Bank Asset Management Company (BAMC).

Investment in the euro area could recover without credit, but creditless recoveries are associated with lower investment and GDP growth. Empirically, creditless recoveries are rare, especially in advanced economies, which suggests risks to recovery unless credit growth resumes (IMF 2014b). In addition, such recoveries are associated with lower investment and output growth than in recoveries with credit. A creditless recovery could, in turn, have long-term consequences through lower potential output.

Against this backdrop, this chapter explores to what extent output dynamics and other factors can explain private nonresidential investment across the euro area. First, to analyze the impact of the output dynamics, an accelerator model is estimated for the euro area and selected euro area countries.4 Although this model tracks investment closely, actual postcrisis investment has remained below its model-implied value for most countries. Second, to explore the impact of the cost of capital and financial constraints, the model is augmented with the real cost of capital and a proxy for financial constraints (European Commission 2014). These additional factors are significant for some of the countries; however, actual investment continues to remain below its estimated level for most countries. Finally, to explore the effects stemming from uncertainty, corporate leverage, and cash flow, a more eclectic (bond market) model is estimated. Controlling for these factors, changes in output are more representative of demand factors. Accordingly, uncertainty is associated with low investment in most countries. In addition, high corporate leverage is associated with subdued investment in Italy and Portugal, and to a lesser extent in Spain and France. Overall, this model seems to be a better fit for stressed countries, with the residuals substantially smaller than in the previous two models.

Drivers of Investment: Output Changes Versus Other Factors

Three types of investment models are used to explain the dynamics of private nonresidential investment, following Lee and Rabanal (2010): (1) an accelerator model (Clark 1917; Jorgenson 1971); (2) a neoclassical model (Jorgenson 1971; Caballero 1994); and (3) a bond market model (Philippon 2009; Bloom 2009; Lee and Rabanal 2010).5Annex 1.1 presents data sources and definitions.

Are Output Changes Sufficient to Explain the Decline in Investment (Accelerator Model)?

The first step is to explore whether changes in output are sufficient to explain investment dynamics in the euro area. The accelerator model relates real investment to past changes in real output, taken to be the primary determinants of the changes in the desired capital stock. A common approach is to run these regressions on the investment-to-capital stock ratio:

in which I is real private nonresidential investment, K is the total capital stock, and ΔY is the change in real GDP.6

The results indicate that changes in output can capture broad changes in investment but cannot fully account for the decline in investment after the crisis in most cases (Annex 1.2). Lags of changes in real GDP (up to 12) are correctly signed and significant. Although the model provides a good fit for overall trends, real nonresidential private investment, particularly during the second phase of the crisis, is lower than in-sample fitted values, with the exception of Spain (Figure 1.10). The model seems to track Spain’s investment closely, implying that output has played an important role in investment dynamics. For most countries, underinvestment becomes smaller toward the end of the sample. The model does not seem to explain the behavior of total investment in Greece and Ireland well. As a robustness check, the regressions are run for machinery and equipment investment in Ireland and Germany (with data up to 2013:Q4). For both cases, the results are broadly the same.

Figure 1.10Accelerator Model: Euro Area and Spain

Source: IMF staff estimates.

Do Cost of Capital and Financial Constraints Matter for Investment (Neoclassical Model)?

Because output developments cannot fully explain the decline in investment after the crisis, whether the cost of capital and financial constraints are additional impediments is explored. In the neoclassical model, current investment is a function of the lags of changes in desired capital stock, which, in turn, is determined by the cost of capital. Under the additional assumption that the cost of capital is equal to its marginal product, investment can be related to past changes in output and changes in the real cost of capital (Oliner, Rudebusch, and Sichel 1995). This baseline specification is then augmented with a variable to capture credit rationing (based on a question on financial constraints from the European Commission consumer and business survey).

Both nominal and real costs of capital are elevated for the stressed countries. (See Annex 1.1 for definition of the cost of capital.) Although reduced policy rates have translated into lower costs of borrowing in the core countries, these rates have remained elevated in the stressed countries (Figures 1.11 and 1.12)—a sign of continued fragmentation.

Figure 1.11Euro Area: Nominal Cost of Capital

(Percentage points)

Sources: Eurostat; Haver Analytics; and IMF staff calculations.

Figure 1.12Euro Area: Real Cost of Capital

(Percentage points)

Sources: Eurostat; Haver Analytics; and IMF staff calculations.

While financial constraints are generally significant, the coefficients on a proxy for lagged desired changes in capital stock are generally not statistically significant, with the exception of Greece. The lack of significance of coefficients in the neoclassical model has been encountered in the literature before, for example, in Oliner, Rudebusch, and Sichel (1995). On the other hand, financial constraints, in line with expectations, have a significant negative effect on investment in the euro area, Germany, Spain, and Portugal. Overall, actual investment remains below the predicted level for other countries throughout the duration of the European debt crisis, with the exception of Spain.7 The gap between the actual and fitted investment in the euro area and Italy closes toward the end of the estimation period (Figure 1.13). The robustness checks using alternative lag selection strategies, and narrower measures of nonresidential investment in Germany and Ireland produce broadly similar results.8

Figure 1.13Neoclassical Model: Euro Area and Italy

Source: IMF staff estimates.

Out-of-sample projections also suggest underinvestment. For all countries, one-step-ahead forecasts from 2008:Q3 onward produce projected investment levels that are higher than realized investment levels, particularly during the second phase of the crisis. For Germany, during the first phase of the crisis, the decline in projected investment was deeper than the actual decline. This reversed during the second phase of the crisis. To test whether the crisis has changed investment dynamics, intercept and interaction dummies are added to the specification. Although the intercept terms are generally significant, the results are mixed for the interaction terms. (All results are available upon request.)

Do Other Factors (Uncertainty, Leverage, and Cash Flow) Play a Role in Investment Dynamics?

To account for other factors that could potentially weigh on investment, a more eclectic model is used. Philippon (2009) suggests using bond prices instead of equity prices to estimate the value of Tobin’s Q. The proposed measure, called “Bond Market’s Q,” is a function of the real risk-free rate, the spread between bond yields and government bonds, leverage, and uncertainty. The real lending rate for nonfinancial corporations (NFCs) is substituted for the real rate in the baseline model, and following Lee and Rabanal (2010), the model includes a measure of cash flow.

The model captures any additional impact on investment from uncertainty and corporate leverage. The ratio of private nonresidential investment to total capital stock is modeled as a function of overall real lending rates to NFCs, corporate bond spreads, uncertainty, corporate leverage, and the cash-flow-to-sales ratio. To account for demand effects, the baseline model is augmented with changes in real output over total capital stock. This augmentation also allows this model to be compared with the accelerator and neoclassical models. Finally, similar to the neoclassical model, financial constraints are controlled for to account for possible credit rationing (Annex 1.4):9

High uncertainty is associated with low investment, particularly for the stressed countries. In the baseline model (without controlling for output changes and financial constraints), uncertainty reduces investment in most countries and in the euro area as a whole, though the effects are fairly small. A one standard deviation increase in uncertainty reduces the investment-to-capital-stock ratio by about 0.03–0.1 percentage point. The results remain broadly unchanged when output changes and financial constraints are controlled for.

Higher corporate leverage is associated with weak investment in some countries. In the baseline model (without controlling for output changes), corporate leverage reduces investment in France, Italy, Portugal, and Spain by between 0.1 and 0.4 percentage point for every 10 percentage point increase in the debt-to-equity ratio. Controlling for output changes and financial constraints, leverage is still important for France, Italy, and Portugal. Cash flow is significant for a few countries in the baseline model, but only has the expected positive sign for Germany, Greece, and, after controlling for changes in output, Spain.

Corporate bond spreads and real lending rates are significant and correctly signed for only a few countries. The former are significant for Ireland, as well as for Germany and Spain once output changes and financial constraints are controlled for. A 100 basis point increase in the spread of corporate over government bond yields decreases investment by about 0.1–0.8 percentage point. Real lending rates (deflated by the GDP deflator) are correctly signed and significant for determining investment in Italy once output changes and financial constraints are controlled for.10 The financial constraints variable is significant for Italy and Portugal.

Overall, the model seems to work better for stressed countries, in particular for Italy and Spain, and to a lesser extent for Portugal and the euro area as a whole (Figure 1.14). It performs comparatively poorly for France and Germany.11 The robustness checks using the series for machinery and equipment investment in Ireland and Germany (with data up to 2013:Q4) produce broadly similar results.

Figure 1.14Bond Market Model

Source: IMF staff estimates.

The Magnitude of Missing Investment

Since the European debt crisis, investment has been systematically lower than its estimated level, except in Spain. To better gauge how much investment has been missing since the start of the European sovereign crisis, the cumulative underinvestment since then is examined. Overall, controlling only for output, the cumulative underinvestment is about 3–6 percent of GDP (excluding Spain) (Figure 1.15). Once other determinants are also controlled for, the cumulative underinvestment declines substantially to about ½–2 percent. In Spain, output changes alone are enough to explain much of the decline in investment. However, other factors such as cost of capital, financial constraints, and uncertainty are also important elements affecting investment in Spain, implying that these factors may affect investment through their impact on output.

Figure 1.15Cumulative Underinvestment

(Since 2010:Q2, percent of GDP)

Source: IMF staff estimates.

Note: Germany ends in 2012:Q4 and Portugal in 2013:Q3.

Conclusion

Investment has been weak across the euro area. Empirical evidence suggests that output dynamics can explain the broad trends in investment, including its collapse after the financial crisis. In particular, output accounts for the behavior of investment in Spain. In other countries (including France and Germany), private nonresidential investment has been lower than suggested by output developments only since the onset of the crisis.

In addition to output dynamics, financial constraints affect investment, particularly for Italy, Portugal, and Spain. The neoclassical model that seeks to proxy desired capital stock with a measure based on the real cost of capital generally does not produce significant results, except for Greece. Nevertheless, investment continues to remain below its model implied value for most of the countries.

High uncertainty and corporate sector leverage are additional impediments to investment, particularly in France, Italy, Portugal, and Spain. After controlling for these two factors, investment (in cumulative terms) is lower than its estimated level by up to about 2 percent of GDP since the beginning of the European debt crisis.

Investment is expected to pick up as the recovery strengthens and uncertainty declines. However, a sustained recovery in investment will require that the corporate debt overhang and financial fragmentation be dealt with. Corporate debt-to-equity ratios remain elevated in some stressed countries, and the deleveraging process is still at an early stage. At the same time, borrowing costs need to be substantially lower, particularly for smaller firms.

Future work will focus on firm-level investment, particularly for small and medium-sized enterprises. Firm-level analysis will supplement macro-level regressions. The use of microeconomic data will allow differentiation between the investment patterns of large and small corporations, as well as a determination of the impact of firm-specific variables, such as cash flow, leverage, and Tobin’s Q.

Annex 1.1. Data Sources and Definitions

Real investment. Investment data are downloaded from Eurostat. Private nonresidential investment is the sum of investment in transport and other machinery and equipment, cultivated assets, and intangible fixed assets.

Capital stock series are from the European Commission Annual Macroeconomic (AMECO) database—the annual series were linearly interpolated so that the stock of capital in the last quarter would match the corresponding annual figure. Alternative measures of capital stock are also calculated using the perpetual inventory method. The initial capital stock values from the AMECO capital stock were scaled by applying appropriate investment subcomponent ratios. Depreciation rates are assumed to be constant and equal to average rates implied by the AMECO series.

Real GDP on a quarterly basis was obtained from the IMF World Economic Outlook database.

Real cost of capital. The correct measure of the cost of capital depends on the structure of financing of the firm. The flow-of-funds data suggest that liabilities of NFCs consist primarily of loans and equity, with the share of bond financing being less than 10 percent in most periods and countries. The following formula is used for the real cost of capital:

in which Di,t, Bi,t, and Ei,t are the amounts of bank loans, bonds (securities other than shares), and equity in the liabilities of NFCs. For the nominal costs of different kinds of capital, we use monetary financial institution lending rates in a given country for new business at all maturities, li,t, for bank loan liabilities; yield on the euro area–wide corporate bond index, it, for bond liabilities; and the yield on 10-year government bonds, ci,t, to price equity liabilities.12 In line with the literature, from the nominal rate, we subtract the year-over-year change in the investment deflator πi,t; add the depreciation rate, which is assumed to be constant but different across countries δi; and multiply the result by the relative price of investment goods (investment deflator) and output Pi,tI/Pi,t. We also report the “nominal cost of capital,” which is simply the first three terms in equation (1.1.1). In addition, we also use a measure of the real cost of capital for debt financing, composed of bond and bank lending (available upon request).

In most countries the real cost of capital has been declining throughout the 2000s; however, after the crisis, southern European countries diverged from France and Germany. Annex Figure 1.1.1 shows the nominal and real costs of capital for the countries considered. As of June 2014 moment, the lowest real cost of capital is in Germany (5 percent), while Italy has the highest cost (12.1 percent). The volatility of the real cost of capital in Greece (for which only a shorter sample is available) is driven by the volatility of the investment deflator.

Annex Figure 1.1.1Cost of Capital Calculations

Sources: Haver Analytics; and IMF staff estimates.

Financial constraints. This variable is from the quarterly European Commission Business and Consumer Survey. Seasonally adjusted series are from the survey of the manufacturing industry: percentage of correspondents listing financial constraints as the factor limiting production.

Corporate bond prices. We use the average spread of corporate over government bonds with maturity of one to five years for the euro area as a whole for all countries in the sample, to proxy corporate bond market conditions. This measure inherently gives more weight to large euro area economies and applies to large firms. (These are Merrill-Lynch indices, from Bloomberg.) This variable is in basis points.

Uncertainty index. Bloom (2009). Natural log of uncertainty index × 100.

Corporate sector leverage. Debt-to-equity ratio from the European Central Bank (in percent).

Cash flow to sales. Worldscope and IMF Corporate Vulnerability Unit database (median).

Crisis dummy. Crisis = 1 from 2008:Q3 (used only for robustness checks).

Annex 1.2. Results of the Accelerator Model13
Annex Table 1.2.1.Accelerator Model—Total Investments (Newey-West HAC Standard Error Estimates)
Euro AreaGermanyFranceItalySpainGreeceIrelandPortugal
β10.32***0.21***0.26***0.47***0.41***0.38**0.75**0.29***
(0.06)(0.06)(0.06)(0.08)(0.09)(0.17)(0.28)(0.08)
β20.21**0.23***0.23***0.39***0.49***0.70***0.99**0.26**
(0.1)(0.07)(0.05)(0.09)(0.06)(0.15)(0.42)(0.1)
β30.25***0.25***0.23***0.37***0.23***1.10***0.92**0.26***
(0.06)(0.06)(0.05)(0.07)(0.07)(0.1)(0.38)(0.06)
β40.22***0.18***0.20***0.19**−0.050.71***0.76**0.24***
(0.07)(0.04)(0.05)(0.08)(0.08)(0.12)(0.29)(0.07)
β50.13*0.13***0.20***0.27***0.12*1.04***0.370.21**
(0.07)(0.04)(0.05)(0.09)(0.07)(0.12)(0.35)(0.08)
β60.16***0.10**0.17***0.18***0.39***1.12***0.300.19**
(0.05)(0.04)(0.06)(0.07)(0.06)(0.16)(0.39)(0.08)
β70.17**0.070.09*0.28***0.090.82***0.280.22***
(0.07)(0.05)(0.06)(0.07)(0.06)(0.18)(0.33)(0.07)
β80.060.09*0.12**0.24***0.000.57**0.10
(0.04)(0.05)(0.05)(0.07)(0.05)(0.25)(0.07)
β90.10**0.12**0.11**0.090.050.550.16**
(0.05)(0.06)(0.05)(0.07)(0.04)(0.34)(0.08)
β100.09*0.070.10**0.18***0.15***0.71*0.16*
(0.05)(0.05)(0.05)(0.06)(0.03)(0.39)(0.09)
β110.050.10*0.080.26***0.06*1.04***0.17*
(0.04)(0.05)(0.05)(0.07)(0.03)(0.35)(0.09)
β120.18***0.20***0.38***0.75**0.16*
(0.05)(0.06)(0.08)(0.3)(0.08)
δ3.43***5.99***3.98***4.29***2.76***10.65***8.92***3.81***
(0.38)(0.35)(0.16)(0.3)(0.05)(0.48)(2.75)(0.66)
Observations6076969276765462
R-squared0.840.820.870.750.950.390.750.86
Akaike info criterion0.50−0.880.330.350.990.690.500.80
Schwarz Bayesian criterion−1.31−0.48−1.57−0.05−2.211.334.400.11
Standard error of regression0.090.140.100.180.060.391.520.18
Notes: HAC = heteroscedasticity and autocorrelation consistent.*significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.
Notes: HAC = heteroscedasticity and autocorrelation consistent.*significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.

Annex Figure 1.2.1Accelerator Model: Private Nonresidential Investment/Capital Ratio

Sources: Eurostat; IMF, World Economic Outlook database; OECD, Analytical database; European Commission, Annual Macroeconomic Database; and IMF staff calculations.

Note: Total investment for Greece and Ireland.

Annex 1.3. Results of the Neoclassical Model
Annex Table 1.3.1.Neoclassical Model Augmented with Financial Constraints: Estimates with Newey-West Standard Errors
Euro AreaGermanySpainFranceGreeceIrelandItalyPortugal
α−507,279***−450,609***9,7526,546−44,545**92,896***100,171*24,477***
(186,844)(65,147)(6,595)(18,503)(17,547)(17,731)(55,275)(5,235)
β1−0.0960−0.104−0.005780.02220.270***−0.04010.0314−0.141**
(0.0750)(0.0889)(0.00419)(0.0179)(0.0846)(0.0417)(0.0894)(0.0516)
β2−0.0820−0.0665−0.00884*0.004970.244*−0.0452−0.0220−0.205***
(0.0780)(0.0998)(0.00466)(0.0203)(0.125)(0.0524)(0.0836)(0.0724)
β30.0197−0.00688−0.006160.002210.482***−0.04510.0284−0.250**
(0.0503)(0.0809)(0.00468)(0.0174)(0.0934)(0.0497)(0.0862)(0.0913)
β40.00570−0.0400−0.00671−0.005850.591***−0.06190.00272−0.109
(0.0583)(0.0712)(0.00523)(0.0215)(0.104)(0.0408)(0.101)(0.0873)
β5−0.0628−0.007800.001590.729***−0.0814***0.0256−0.0608
(0.0772)(0.00566)(0.0271)(0.105)(0.0256)(0.106)(0.0449)
β60.0191−0.007280.007530.820***−0.0613***0.0352−0.127**
(0.0684)(0.00473)(0.0222)(0.125)(0.0209)(0.117)(0.0582)
β70.0610−0.004190.007220.866***−0.0426***0.0458−0.0978*
(0.0636)(0.00399)(0.0186)(0.169)(0.0147)(0.130)(0.0553)
β8−0.0186−0.001210.02350.714***−0.0319***0.08890.0551
(0.0844)(0.00472)(0.0169)(0.125)(0.00932)(0.141)(0.0922)
β90.06130.002130.01710.598***−0.0195**0.0224
(0.0807)(0.00589)(0.0169)(0.120)(0.00939)(0.105)
β100.1210.02350.441***−0.0180*0.0471
(0.0982)(0.0232)(0.102)(0.00972)(0.124)
β110.02090.235***−0.0129*0.0579
(0.0211)(0.0681)(0.00740)(0.120)
β120.03060.139*−0.006970.129
(0.0296)(0.0685)(0.00585)(0.152)
γ0−0.141***−0.0807***−0.0681***−0.00961−0.0579−0.0593−0.0889***
(0.0363)(0.0237)(0.0161)(0.00917)(0.0411)(0.0363)(0.0133)
γ1−0.0532**−0.0465−0.0936***
(0.0264)(0.0638)(0.0228)
δ5.394***9.977***2.273***2.395***12.94***−12.42***0.979−0.343
(0.900)(1.073)(0.265)(0.400)(2.215)(3.869)(1.304)(1.123)
Observations6164626029506042
R-squared0.6280.7020.7870.3300.9210.6900.6590.747
Adjusted R-squared0.5350.6650.7400.1220.8290.5780.5530.654
Root-mean-square error0.1310.1650.1410.1190.4811.7090.2420.193
Durbin-Watson statistic0.3800.3760.4880.1801.0170.1120.6020.767
Note: *significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.
Note: *significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.
Annex 1.4. Results of the Bond Market Model
Annex Table 1.4.1.Bond Market Model (Controlling for Output Changes and Financial Constraints)
Euro AreaGermanySpainFranceGreeceIrelandItalyPortugal
α3.554***2.014***1.956***2.674***10.102***15.715***4.692***7.379***
(0.577)(0.578)(0.226)(0.443)(1.205)(3.069)(0.382)(0.732)
β1−0.0004−0.001*−0.002***−0.00040.0002−0.008***0.0003−0.001
(0.0005)(0.0004)(0.0003)(0.0005)(0.001)(0.003)(0.0004)(0.001)
β20.089**0.067**0.038***0.013−0.0120.094−0.07***0.06
(0.036)(0.025)(0.013)(0.032)(0.031)(0.056)(0.015)(0.036)
β3−0.003***−0.0003−0.001*0.0004−0.012***−0.027***−0.003***0.0001
(0.001)(0.001)(0.0004)(0.0004)(0.002)(0.005)(0.0005)(0.001)
β40.005−0.0030.006***−0.007**0.01***0.033***−0.005*−0.043***
(0.004)(0.002)(0.002)(0.003)(0.003)(0.006)(0.003)(0.013)
β5−0.0190.077**0.01***−0.01−0.065−0.150.018−0.047*
(0.03)(0.036)(0.003)(0.06)(0.053)(0.189)(0.018)(0.025)
β60.203***0.109**0.293***−0.1150.72***0.0080.333***−0.215*
(0.065)(0.045)(0.094)(0.092)(0.216)(0.198)(0.065)(0.117)
β70.091**0.165**0.308**−0.0080.814***0.3620.194***−0.277*
(0.043)(0.073)(0.115)(0.071)(0.209)(0.225)(0.065)(0.159)
β80.182***0.385***0.209***0.205***1.012***0.502**0.26***−0.237
(0.064)(0.076)(0.076)(0.063)(0.206)(0.231)(0.073)(0.139)
β90.203***0.302***−0.0440.205**0.751***0.871***0.137**−0.145
(0.058)(0.063)(0.076)(0.082)(0.152)(0.228)(0.058)(0.092)
β100.118*0.184***0.327***1.171***0.608*0.138**−0.09
(0.061)(0.054)(0.096)(0.142)(0.327)(0.054)(0.074)
β110.0470.1480.345***0.965***0.4450.116*−0.147
(0.071)(0.091)(0.102)(0.225)(0.32)(0.059)(0.104)
β120.0410.1150.0930.549***0.4460.132**−0.206*
(0.051)(0.09)(0.065)(0.168)(0.315)(0.063)(0.116)
β130.0470.199**−0.0480.493*0.105−0.186*
(0.073)(0.077)(0.064)(0.263)(0.075)(0.102)
β140.165***0.215**0.153*0.1850.107*0.099
(0.056)(0.1)(0.087)(0.182)(0.058)(0.088)
β150.218***0.176***0.340.0920.184**
(0.07)(0.057)(0.389)(0.06)(0.065)
β160.1120.4080.1070.214***
(0.08)(0.339)(0.067)(0.065)
β170.1*0.131**
(0.058)(0.06)
β180.0290.137***−0.011−0.005−0.005−0.034***−0.07***
(0.017)(0.024)(0.012)(0.005)(0.022)(0.007)(0.015)
Observations5955595954465940
R-squared0.880.840.980.680.940.930.970.94
Durbin-Watson statistic0.711.261.550.51.571.091.711.19
Note: *significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.
Note: *significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.

Annex Figure 1.4.1Bond Market Model (Controlling For Output Changes and Financial Constraints)

Sources: Annual Macroeconomic Database; Eurostat; Haver Analytics; and IMF staff estimates.

References

    BloomNick.2009. “The Impact of Uncertainty Shocks.Econometrica77 (3): 62385.

    CaballeroRicardo.1994. “Small Sample Bias and Adjustment Costs.Review of Economics and Statistics76 (1): 5258.

    ClarkJ. M.1917. “Business Acceleration and the Law of Demand: A Technical Factor in Economic Cycles.Journal of Political Economy25 (3): 21735.

    • Search Google Scholar
    • Export Citation

    European Central Bank. 2014. “Data of Survey on the Access to Finance of Enterprises in the Euro Area (SAFE).” Available at: https://www.ecb.europa.eu/stats/money/surveys/sme/html/index.en.html. Accessed June2014.

    • Search Google Scholar
    • Export Citation

    European Commission. 2014. “EC Business and Consumer Survey.” Available via HAVER Analytics. Accessed June2014.

    HayashiFumio.1982. “Tobin’s Marginal q and Average q: A Neoclassical Interpretation.Econometrica50 (1): 21324.

    International Monetary Fund (IMF). 2014a. “Perspectives on Global Real Interest Rates.” In World Economic Outlook: Recovery Strengthens Remains Uneven. Washington, DC: International Monetary Fund.

    • Search Google Scholar
    • Export Citation

    International Monetary Fund (IMF). 2014b. “Baltic Cluster Report, 2014 Cluster Consultation.Country Report No. 14/117Washington, DC.

    • Search Google Scholar
    • Export Citation

    JorgensonD. W.1971. “Econometric Studies of Investment Behavior: A Survey.Journal of Economic Literature9 (4): 111147.

    LaevenLuc and FabianValencia.2012. “Systemic Banking Crises Database: An Update.Working Paper 12/63International Monetary FundWashington, DC.

    • Search Google Scholar
    • Export Citation

    LeeJaewoo and PauRabanal.2010. “Forecasting U.S. Investment.Working Paper 10/246International Monetary FundWashington, DC.

    OlinerStephenGlennRudebusch and DanielSichel.1995. “New and Old Models of Business Investment: A Comparison of Forecasting Performance.Journal of Money Credit and Banking27 (3): 80626.

    • Search Google Scholar
    • Export Citation

    Pérez RuizEsther.2014. “France, Selected Issues—The Drivers of Business Investment in France: Reasons for Recent Weakness.Country Report No. 14/183International Monetary FundWashington, DC.

    • Search Google Scholar
    • Export Citation

    PhilipponThomas.2009. “The Bond Market’s Q.Quarterly Journal of Economics124 (3): 101156.

    PinaAlvaro and IldebertaAbreu.2012. “Portugal: Rebalancing the Economy and Returning to Growth through Job Creation and Better Capital Allocation.Economics Department Working Paper 994Organisation for Economic Co-operation and DevelopmentParis.

    • Search Google Scholar
    • Export Citation

    TobinJames.1969. “A General Equilibrium Approach to Monetary Theory.Journal of Money Credit and Banking1 (1): 1529.

This chapter is based on Euro Area Policies: Article IV 2014 Consultation—Selected Issues, “Investment in the Euro Area: Why Has It Been Weak?” IMF Country Report 14/199, 2014, and the IMF Working Paper 15/32 of the same title, 2015. The authors are grateful for the comments provided by Philip Vermeulen and other participants at the European Central Bank seminar, as well as the European Commission staff.

1

Investment as a percentage of GDP remains below its precrisis long-term (1995–2007) level, particularly for stressed countries.

2

For the figures and regressions in this chapter, private nonresidential investment data are obtained from Eurostat to ensure consistency and comparability across countries. Other data sources also show weak investment dynamics. For example, real fixed investment in equipment in Germany and real investment by nonfinancial corporations (NFCs) in France, and equipment and transportation machinery investment in the euro area are also weaker than their precrisis levels. Stressed countries refer to debtor countries who have experienced high funding costs (public and private) and suffered from financial fragmentation during the period covered.

3

In addition to these standard factors, investment in many smaller European countries has been affected by availability of the EU Structural Funds. For instance, there are indications that investment in Portugal was too high before the crisis (Pina and Abreu 2012).

4

Selected countries are Germany, France, Greece, Ireland, Italy, Portugal, and Spain. Quarterly data between 1990 and 2013 are used (depending on data availability).

5

A model based on Tobin’s Q was also estimated. This model relates the real-investment-to-capital ratio to the ratio of firm value to the replacement cost of the existing capital stock (Tobin 1969; Hayashi 1982). Alternative definitions of Tobin’s Q (for NFCs) are used: (1) interpolated from annual Tobin’s Q (CVU, Worldscope); (2) price-to-book ratio; and (3) stock prices deflated by GDP deflator. The model also controls for firms’ leverage (debt-to-asset ratio) and cash flow (CVU, Worldscope). Among the Tobin’s Q proxies used, only price-to-book ratio appears to be significant in a few specifications for France, Germany, and Portugal. Controlling for endogeneity (by two-stage least squares) and running the regressions for the precrisis period, the significance of the results increases: price-to-book ratio and leverage are significant and correctly signed for Germany, Greece, Portugal, and the euro area. Overall, however, model performance remains weak.

6

For Ireland and Greece, total real investment is used. Because the residuals are highly correlated—a common result in the literature—Newey-West standard errors are reported. Note that the constant δ can be interpreted as an indirect estimate of the depreciation rate.

7

Similar to the accelerator model, the residuals are serially correlated. Annex 1.3 presents the results for the extended model; the results for the baseline model without financial constraints are available upon request.

8

We have also modeled the short- and long-term investment dynamics using a vector error correction model (VECM), controlling for cost of capital, output, and labor costs. We did not obtain consistently significant coefficients for the cost of capital measure, but output and labor costs were significant, showing that higher labor costs dampen investment growth. Augmenting the VECM with indicators of capacity utilization and uncertainty generally failed to establish significant results.

9

Annex 1.4 presents the results for the extended model. The results for the baseline and other steps are available upon request.

10

The coefficients for the euro area, Germany, and Spain have the reverse sign, which is a common finding in the literature, possibly reflecting difficulties in identifying credit demand and supply.

11

Pérez Ruiz (2014) uses a broader set of determinants to explain the level of business investment in France. That model provides a good fit for France.

12

We have experimented with alternative approaches to pricing equity capital, such as variations on the dividend growth model; however, they tend to produce counterintuitive implications for the ranking of the cost of capital across different countries. Using a 10-year government bond establishes a sensible lower bound for the cost of equity and, assuming that the risk premium is constant, is not expected to affect the results. For the euro area, we use the simple average of the 10-year bond yields in France, Germany, Italy, and Spain.

13

Results are in percentage terms. Total investment is used for Greece and Ireland.

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