Journal Issue

Chile: Selected Issues

International Monetary Fund
Published Date:
September 2009
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III. Investment-Specific Productivity Growth: Chile in a Global Comparative Perspective1

1. Chile’s productivity growth has been lackluster during the last decade. According to official estimates, total factor productivity (TFP) at end-2007 was lower than that at end-1997, by about 2 percent (Ministerio de Hacienda, 2008). This performance contrasts strongly with the performance during 1986–97, when productivity grew by a cumulative 30 percent. Most importantly, the decrease in TFP growth in the past decade has occurred in tandem with a decrease in average GDP growth.

2. In addition to the strong change in trend that occurred in 1998, the behavior of productivity has been especially puzzling since 2004. Given Chile’s strong integration with the world economy, some attributed the post-1997 slowdown in productivity growth to the effects of the Asian crisis and the September 11, 2001 aftermath. Indeed, beginning in 1998, investment rates in Chile decreased with respect to those observed earlier in the decade. However, since 2004 investment has picked up dramatically, but productivity growth has continued to be lackluster.

Chile. Total Factor Productivity

(Index 1986=1)

Chile. GDP Growth

(Annual average per period)

Chile. Investment Ratio

(In percent of real GDP)

3. This puzzle stems from the marked increase of investment in machinery and equipment since 2004. In this connection:

  • Investment in machinery and equipment (IM&E) has almost doubled (as percentage of GDP) since 2004, and by 2008 amounted to about half of total investment: The strong increase in IM&E observed since late 2004 is part of a longer trend initiated in the 1980s, and which has coincided with a secular decrease in the relative price of M&E in terms of consumption goods, as technological advances made M&E less expensive. This trend seems to be shared by a group of high income and emerging economies (Figure 1).
  • New M&E usually incorporates the latest technological advances. New M&E is embedded with investment-specific productivity (ISP) improvements that makes them more productive than the existing stock of M&E; this is especially true in Chile, where more than 80 percent of M&E purchases are imported. In addition, IM&E is also more productive than other types of investment, like housing.

Figure 1.Investment in Machinery and Equipment: Quantity and Price Trends

Source: Fund Staff calculations.

Chile. Investment in M&E: Quantity and Price Trends

4. This chapter looks at Chile’s productivity trends over the past 25 years, including from a global comparative perspective. Chile’s experience with investment and productivity is also compared with a group of OECD countries, including net commodity exporters (Australia, Canada, and Norway), as well as importers (Korea and Netherlands).2 A more accurate measure of total factor productivity, that explicitly accounts for the productivity embedded in Chile’s large share of IM&E, allows to decompose growth in output per (effective) hour into two sources: (i) Investment-specific productivity increases (linked with technological improvements in M&E); and, (ii) neutral factor productivity changes.

5. Productivity trends are analyzed in the context of a general equilibrium model. In this regard, the model used here slightly adapts that used by Greenwood, Hercowitz and Krusell (GHK,1997) to analyze similar developments for the U.S economy. The production function in GHK was modified to allow for (exogenous) increases in labor-specific productivity, as well as to incorporate an index of utilization of the capital stock (Annex I). Both modifications were introduced in order to better account for country-specific issues, and to make the results more comparable to those produced by the Chilean authorities (Ministerio de Hacienda, 2008).

6. Needless to say, an accurate assessment of factors contributing to growth is relevant for a number of issues. These include long-run fiscal policy, the solvency of entitlement programs, as well as potential GDP growth forecasting (Gordon, 2003).

7. The results suggest that ISP improvements have contributed significantly to long-term growth in Chile. In particular:

  • Like in all countries analyzed, ISP growth has been significant in Chile. It has averaged about 3.8 percent per year, which is similar to that of Norway (3.6 percent per year). ISP growth in rest of the countries analyzed averaged about 3 percent per year.
  • Neutral, factor productivity (TNP) growth has been, on average, lower than ISP growth in all countries considered. In the case of Chile, it has averaged 0.7 percent per year, similar to that in Norway. For the net commodity exporters (Australia, Canada, Chile and Norway) the lower average TNP growth masks differing behaviors in two periods, with TNP growth being positive until late 1990s or early 2000s and turning negative afterwards (Figure 2).
  • ISP growth contributed to 43 percent to the long-term growth in output per effective hour in Chile. ISP contribution to growth appears largest in Australia and Canada (exceeding 70 percent), and is lower in Netherlands and Korea.3
  • In turn, ISP growth contributed to 28 percent to the long-term growth of output per hour in Chile; TNP contributed to 37 percent, and growth in human capital (HK) to the remaining 35 percent. The contribution of HK to long-term output per hour in Chile appears similar to that in Australia and Canada, and higher than in Korea, Netherlands and Norway.
  • The contribution of ISP to output growth has increased significantly since the second half of the 1990s. This is especially the case in Chile and the net commodity exporters. (Figure 2). The contribution of TNP to growth has decreased during the last decade. In the case of Chile, the decrease in the contribution of total, or neutral, factor productivity to growth results in a productivity measure (depicted as z in the model presented in this chapter) that is lower than the official estimates (depicted as TFP).
  • There appears to be some simultaneity in the behavior of TNP of net commodity exporters during, especially during the last 5 years or so. Indeed, TNP (depicted as z in Figure 2) decreased in Australia, Canada, Chile and Norway since about 2004. The observed decreases are simultaneous, in all cases with significant increases in IM&E as percentage of GDP (Figure 1) and with large improvements in their terms of trade.

Figure 2.Investment-Specific Productivity and Total Factor Productivity

(Index 2003=100)

Source: Fund Staff calculations.

Output, ISP and TNP Growth(Average percent per year)
Ouput per effective hourOuput per hourISPTNP
Chile 1/
Source: Fund Staff calculations.


Source: Fund Staff calculations.


Long-Run Contribution to Growth(In percent)
Ouput per

effective hour
Ouput per hour
Chile 1/4357283735
Source: Fund Staff calculations.


Source: Fund Staff calculations.


Chile. Measures of Neutral Factor Productivity

(Index 1986=100)

Terms of Trade

(Index 2000=100)

8. In general, there are a number of possible explanations for a TNP slowdown. Poor TNP growth may reflect a combination of factors, most notably:

  • The size of the effective capital stock (both in structures and M&E) could be overestimated. Growth accounting exercises usually assume that current investment is incorporated immediately to the capital stock. However, the construction of some investment projects require more than one year. In such cases, the investment corresponding to those projects should not be incorporated to the economy’s capital stock until the project is finalized and ready to operate. Failure to do so would result in an overestimation of the contribution of capital to growth, and a simultaneous underestimation of TFP contribution. In the case of Chile, the Ministry of Finance reports that during the period 2006-08, there was an increase in the number and importance of projects whose maturity exceeds one year, in particular in the Energy and Mining Sectors (Ministerio de Hacienda, 2007). In this connection, and according to official estimates, the amount of current investment that should be added to the effective capital stock decreased from an average of about 75 percent during 2001-2005, to less than 60 percent in 2008. This could also be a factor that could explain decreasing TNP in other net commodity exporters as, following the large increase in their terms of trade, a substantial portion of their marginal investment has gone to commodity-related projects with maturity periods exceeding one year.
  • The size of output could be underestimated. Hornstein and Krusell (1996) underscore that in the case of certain economic activities (including construction, trade, finance, insurance, real estate, other services and government), output as well as quality improvements are more difficult to measure than those of others (including agriculture, mining, manufacturing, transportation and communications). Griliches (1994) refers to the former as part of the “unmeasurable sector” of the economy and the latter as the “measurable sector”. Thus, productivity slowdowns may reflect output mismeasurements, a problem that would be compounded if the unmeasurable sector in total output were to increase through time. The latter, however, does not appear to be the case for Chile, as the proportion of the unmesurable sector in total GDP (at factor cost) has remained relatively stable.
  • Labor and business management might be adapting to the introduction of new, more productive, technologies. Hornstein and Krusell (1996) and Greenwood and Yorukoglu (1997) point out that the adoption of new technologies involves a significant cost in terms of learning; only when labor has developed the necessary skills, technology could be successfully implemented. In other words, as the learning needed to fully take advantage of a new technology occurs, there is a transition period in which output and TFP growth could decrease. Such transition period is characterized by an increase in wage dispersion and an increase in the premium paid for skilled labor. Available wage data for Chile indicate that the premium paid to the most skilled workers (upper firm/public sector management and liberal professions) with respect to that of unskilled workers has increased by about 10 percent during the period 1997-2008, while the relative wage of technical workers (machine operators and artisans) to that of unskilled workers has remained fairly constant. Even though these results suggest some increase in wage dispersion, the stability of the relative wage of technical to unskilled workers seems to suggest that costly learning has not been the primary cause of the productivity slowdown.
  • Business regulations might be constraining growth: There is an abundant literature linking lackluster productivity performance with excessive and/or inadequate regulations affecting the investment climate (e.g., World Bank, 2004). The rationale is that heavy regulation makes it more difficult for business to operate smoothly, which results in poorer economic outcomes. The results of the 2009 World Bank’s Doing Business survey indicate that though Chile outranks the countries in the region, it ranks below the OECD average in the (general) “Ease of doing business” indicator. Moreover, Chile ranks below the OECD average in several areas. A closer look at the components of each of the specific categories in the case of Chile shows that there have been no substantial absolute changes in the results of the survey over the period 2004-2009. This has also been the case for Australia, Canada and Norway, which also experienced productivity slowdowns, but whose rankings exceed those of Chile for most indicators. Indeed, the experience of these countries shows that a better regulatory environment would not have necessarily prevented a productivity slowdown in Chile (i.e., productivity slowdowns may occur for reasons different than an inadequate regulatory environment). That said, the indicators for Chile also suggest that there is scope to improve existing regulations, so they would not affect the functioning of some markets, especially at times of economic stress. In this connection, the increase in the average rate of unemployment after 1998 appears to suggest that there still are some rigidities that might be affecting the economy’s capacity to absorb shocks, which could have a bearing in the productivity behavior.4
  • The growth of traditional sectors might have entered a “declining stage”. This could be significant for economies in which non-renewable resources constitute a large share of output. The exploitation of such resources usually implies that marginal costs eventually rise, with production and productivity eventually decreasing. In the case of Chile, mining GDP has fluctuated around a constant level since 2004 (in line with copper production), while a measure of “core” GDP (excluding mining, electricity gas and water and fishing), has increased at an annual average rate of 5.2 percent. However, it is important to note, that the productivity slowdown in Chile began in 1998, period in which mining GDP, and the physical production of copper, were expanding very strongly. Indeed, during 1998-2004, mining GDP increased at an average annual rate of 4.9 percent, while the physical copper production expanded at annual average rate of 6.9 percent. This seems to suggest that, though the deceleration observed in the mining sector may have had a bearing in the continuation, after 2004, of the productivity trend that began in 1998, there were other factors at play at the outset of such trend.
  • Market concentration might be stifling competition and growth: Acemoglu, Aghion and Zilibotti (2002) argue that limits on product market competition are important for middle-income countries trying to converge to the world technology frontier. In this connection, according to the World Economic Forum’s Global Competitiveness Report for 2008, Chile ranks 28 among 137 countries, better than any country in the region, but below the OECD average. As Engel and Navia (2006) indicate, corporate activity in Chile is dominated by a limited number of conglomerates, and it is frequently the case for key industries to be dominated by a small number of corporations (Chile ranks 57th in the “market dominance” indicator). In particular, they point to some lack in competition in the financial sector (banks and pension fund manager companies); this may be constraining the access to funds for middle and low-sized firms, perpetuating market concentration, and limiting the economy’s dynamism. However, market concentration does not preclude intense competition; indeed Chile has made important progress since the creation of an “Anti-monopoly Court” in 2004 (Chile ranks 19th in the “intensity of local competition” indicator).

Chile. Unmesurable GDP

(Percent of Total GDP)

Chile. Mining and Core GDP

(Index 1986=100)

9. To sum up, the productivity slowdown in Chile’s has likely been caused by a number of factors and seems to share some common trends with other net commodity exporters. Regulatory rigidities, that limited the capacity of the economy to absorb the external shocks of 1998 and 2001, were likely behind the initial phase the productivity slowdown. Beginning in 2004, a combination of causes were probably added up, including the growth deceleration in the mining sector, as well as some overestimation of the size of the effective capital stock (as the boom in commodity prices provided the incentives to invest in the energy and mining sectors, in projects that take more than one year to become operational). Other causes, including costly learning following the adoption of new technologies, as well as market concentration may have had a bearing too. The slowdown in Chile’s productivity seem to share some common trends, since 2003, with other net commodity exporters, such as Australia and Canada.

Annex I. The Economic Environment

1. The economy is deterministic and is populated by a representative household, a representative firm and a government. The representative household maximizes (discounted) utility over leisure and consumption:

where ct is consumption, lt is labor effort and 0<θ<1.

2. Final output is produced by a representative firm that maximizes profits operating a constant returns to scale Cobb-Douglas production function:

where, yt is output of final consumption goods, zt is a measure of total-factor, or neutral, productivity and 0<αe,αs,αe+αs<1. There are two types of capital: machinery and equipment, ke,t, and non-housing structures ks,t; the utilization of the capital stock is denoted by uk,t, which is assumed to be known, exogenous, and the same for both equipment and structures. Note that zt=γzt, where γz denotes the (gross) growth rate of neutral productivity.

3. Final output can be used for consumption and investment in equipment and machinery, je,t, and structures, js,t:

4. The stock of structures evolves according to,

where, γH,N = γHγN denotes the combined growth (gross) rate of working age population, γN, and human capital, γH, both assumed to be exogenous and known, and δs is the depreciation rate.

5. The stock of machinery and equipment evolves according to,

where, qt is an index of investment-specific productivity (ISP), that measures the quality of new equipment, and δe, is depreciation rates of equipment and structures. There is also a government that levies taxes on labor income, τl, and on both forms of capital, τk. The government transfers back to the consumer, in the form of a lump-sum transfer, τ, the revenue raised in the form of taxes:

where, re represents the return for the services of equipment, rs represents the return for that of structures and w denotes wages paid to labor.

Balanced Growth Path Conditions and Calibration

6. The variables y,c,ie,is,ke,ks, in (1)-(7) are normalized in terms of effective available labor, e.g., in the case output, yt = yt/NtHt, where Yt is aggregate output, Nt denotes nonsleeping hours of the working age population and Ht represents a measure of human capital. Note that Nt=γNt and that H=γHt. As finding a balanced growth path (BGP) requires an adequate transformation of variables, note that (4) implies that, along a BGP, output, consumption, and investment all grow at the same rate, γy; note also that γy denotes the (gross) growth rate of output per available effective hour. From (5) the stock of structures should also grow at rate γy; however, (6) implies that the stock of equipment will grow faster, at (gross) rate γe. The production function (3) implies that γy=γzγeaeγyas; thus, as GHK point out, the following restrictions are imposed on a BGP:

where γq is the (gross) growth rate of qt. In turn, if one is interested in output per available hour, equation (8) should be modified to incorporate the rate of growth of human capital, as follows:

7. Using (8)-(9), the transformation of the problem into one in which all variables are stationary, requires first defining x˜t=xt/γyt, with x equal to output, consumption, investment and the stock of structures; then one should define k˜e,t=ke,t/γet,z˜t=zt/γzt and finally q˜t=qt/γqt. Assuming that the economy behaves competitively, the BGP conditions for the transformed problem are as follow:

8. The 18 unknowns associated with the balanced growth conditions are γy,γN,γH,γq,θ,β,τk,τL,δe,δs,αe,αs,1,c˜/y˜,i˜e/y˜,i˜s/y˜,k˜e/y˜,and k˜s/y˜; thus, the solution of the system (11)-(16) requires calibrating 12 parameters. Following GHK, the calibration procedure implies choosing the values of the unknowns in the BGP so they coincide with their average values observed during the period considered. The variables chosen for calibration are: and γy,γN,γH,γq,τk,τ1,δe,δs,(αe+αs),1,i˜e/y˜,and i˜/y˜. In particular, with respect to γq, note that ISP is proxied by the ratio of the implicit price deflator for personal consumption expenditures to the implicit price deflator for equipment and machinery.

9. Once the parameters are determined, total neutral productivity, z, can be calculated from equation (3), and the contributions to long-term growth can be calculated either from (8) or (10), depending on whether one is interested in output per effective hour worked, or output per hour worked. The calibration results are shown in Table 1.21

Table 1.Calibration Results
alfa e + alfa s0.400.330.400.400.350.40
tao L0.520.440.320.450.620.57
tao k0.300.460.150.290.330.28
delta e0.
delta s0.
gamma y1.
gamma H1.
gamma N1.
gamma q1.
gamma H, N1.
k s / y0.970.990.841.341.241.20
k e / y0.260.370.310.500.310.21
alfa e0.
alfa s0.
Source: Fund Staff calculations.
Source: Fund Staff calculations.

Datasets are available upon request. A more detailed version of this paper (including a thorough description of data definitions and related data issues) is forthcoming as IMF Working Paper.


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This chapter was prepared by Gabriel Di Bella (37483).


For countries other than Chile, the analysis extends from 1980 to 2008.


Output per effective hour is defined as output per hour deflated by an index of human capital, which is proxied by the average number of schooling years of the labor force, (Ministerio de Hacienda, 2008).


Regulatory rigidities may be behind the observed increase in the natural rate of unemployment after 1998 (See Restrepo, 2008).

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