ESTUDIOS SOBRE LA ECONOMÍA ESPAÑOLA

Patterns of Investment in Spanish Manufacturing Firms

Omar Licandro, Reyes Maroto and Luis A. Puch

EEE 185

May 2004

FEDEA Fundación de Estudios de Economía Aplicada

http://www.fedea.es/hojas/publicado.html

ISSN 1696-6384

Las opiniones contenidas en los Documentos de la Serie EEE, reflejan exclusivamente las de los autores y no necesariamente las de FEDEA.

The opinions in the EEE Series are the responsibility of the authors an therefore, do not necessarily coincide with those of the FEDEA.

Patterns of Investment in Spanish Manufacturing Firms

Omar Licandro, Reyes Maroto and Luis A. Puch

February 2004

Abstract

In this article we describe the main patterns of investment observed in a panel of Spanish manufacturing firms from 1990 to 2001. We provide evidence on a number of dimensions of investment behavior, technological activities and employment composition that we consider useful to account for productivity gains. This evidence is based upon a sample that contains annual information extracted from the survey Encuesta sobre Estrategias Empresariales (ESEE).

Key words: physical capital investment, human capital investment, R&D investment JEL codes: E22, L60, O30

Licandro, European University Institute and FEDEA; Maroto, FEDEA and Universidad Carlos III; Puch, Universidad Complutense and ICAE. We thank DGCYT, project SEC2000-0260. Puch also thanks the financial assistance of FEDEA. Correspondence: Luis A. Puch, Departamento de Economía Cuantitativa, Universidad Complutense de Madrid, E-28223, Somosaguas- Madrid-Spain, e-mail: lpuch@ccee.ucm.es.

1. Introduction

The aim of this paper is to describe the main patterns of investment observed in a panel of Spanish manufacturing firms from 1990 to 2001. We do this to identify a number of preliminary stylized facts across manufacturing firms in the accumulation of physical capital, human capital and technological capital. This selected evidence should be useful as a reference when investigating the sources of productivity growth from disaggregated data.

We are interested in both time and firm heterogeneity. We look to cross-section distributions and time frequencies to organize a set of great ratios and stable characteristics that can be used as a starting point for empirical analysis on Spanish manufacturing investment and factor input composition.

One question is whether capital and labor evolution patterns are smooth or not. Another is the extent to which it is type, size, or sector what determines part of these adjustments, if any. Finally, the connection between R&D investment and innovative activity could help to see the link between the production and the adoption of new technologies. This is particularly important as far as the effort devoted to the adoption of new technologies is well above the size of resources devoted to the production of new technologies.

The way in which we organize the description of the data builds upon two hypotheses. First, under embodied technical progress new vintages of physical and human capital embody improved technology. Consequently, different investment strategies should have different effects on productivity and growth. Further, there might be a connection between investment activity and innovative activity so different innovative strategies should have different effects on productivity. Second, maintenance and repair seems too big to ignore so an important component of investment patterns may come just from age heterogeneity and physical depreciation.

2. Description of the Sample

The data set is a pooled cross-sectional time-series official survey, Encuesta sobre Estrategias Empresariales (ESEE), containing annual firm-level information on more than 3400 large and small firms in the Spanish manufacturing sector between 1990 and 2001. This survey is representative of Spanish manufacturing has thoroughly discussed in Fariñas and Jaumandreu (1999). In particular, Figure 1 depicts the number of firms per year included in the survey. In all of the years the number of firms surveyed is well above 1200, with 1457 (7.06% of the total number of observations) in the 2001 survey and 1858 (9.01%) in the 1997 one. The survey includes newborn, continuing and exiting firms, the later reflecting death and attrition.

Figure 1: Number of firms per year

The ESEE samples small firms (10 to 200 employees), but contains the whole population of large firms (200 or more employees). The sample we consider excludes those observations for which either reported value added is negative and employment data or investment data are missing. Table 1 shows the frequency of observations in the data set by industry for the two extracts of the ESEE we consider after the aforementioned basic filtering. First, an unbalanced panel with 17916 observations on 2128 firms (653 large and 1475 small) observed at least four consecutive years during the entire sample period.¹ Indeed, when a firm presents more than a sequence we have retained the longer consecutive cut, and if several sequences of the same length the latest one. About 65% of firms without missing relevant information are observed four consecutive years according to this criterion. This unbalanced panel represents on average 35% of investment in Spanish manufacturing. Second, a balanced panel containing 401 small and 190 large firms continuously observed for the entire sample period, which represents roughly 40% of the total number of observations from the unbalanced panel.

By comparing columns we see that the distribution of continuing firms in the data set across two-digit SIC (NACE) industries is roughly comparable to the distribution for the unbalanced panel of the survey.

Table 1: Frequency of observations in the data set by industry.

¹ We follow this strategy in order to capture investment patterns representative of some form of replacement activity. See Licandro et al. (2003) for an analysis of the role of replacement and innovation activity in shaping investment behavior and labor productivity of firms in this extract of the Survey.

3. Investment behavior

In this section we describe physical capital investment by firms in the sample.

Figure 2 shows the distribution of investment by categories according to firm size. Equipment investment, defined as including all investment items other than structures, represents more than two thirds of total investment in manufacturing. More precisely, average equipment investment represents 70% of total investment among small firms and up to 86% for large firms. By industry, equipment investment is always above 60% both among small and large firms as it can be seen in Table 2. In particular, equipment investment represents 81% of investment in the Electrical and Electronic goods industry, whereas investment in structures reaches 38% of total investment in the Timber and Furniture industry.

Table 2 reports also investment intensity by sectors. On average, total investment over sales is 5.13% whereas for equipment investment it is 4.02%. The figures are similar for large and small firms and it is only very specific sectors that substantially deviate from these ratios, e.g. other transport equipment or non-metallic minerals.

Figure 3 depicts the distribution of investment intensity (over sales) for the total number of observations in the sample. Both total and equipment investment intensities exhibit a frequency of investment inaction, i.e. a situation where investment is strictly zero, of nearly 20%. Further, there are no substantial differences in the distribution of both types of investment at any investment intensities. As far as we are mostly interested in the technological content of investment decisions we focus on equipment investment in what follows. When looking to equipment investment intensity by firm size (right panel) we observe a slightly higher frequency of observations about intermediate levels of investment effort for large firms. On the other hand, inaction or small investment intensities are more frequently found among small firms. This might suggest that large firms exhibit a smoother investment pattern.

Table 2: Investment by type, considering sectors

* Proportion to the total investment

Figure 3: Investment intensity distribution, considering type and firm size

We report also a description of the distribution of equipment investment rates (over capital). In order to measure each firm real equipment assets we use the perpetual inventory method, the series being initialized by the book value of equipment the first period the firm is observed. Figure 4 depicts the corresponding equipment investment rate distribution in the unbalanced panel.

Figure 4: Investment rate distribution considering type

These figures imply that inaction represents roughly 17% of observations for equipment investment. There is also at the other extreme of the distribution a sizeable frequency of large investment episodes: more than 12% of observations have investment rates above 30%. It is worth saying that there are no substantial differences along this dimension when we consider the balanced panel instead. The fact that selection causes the less productive firms to exit, a feature not present in the balanced panel, does not affect the finding of investment rates distributions skewed to the left with a long-wide right-hand tail.

From Figure 5 we see that the frequency of observations showing inaction decreases with firm size. Something similar occurs for very large investment episodes (above 30%). This might suggest that episodic investment is more frequent in small than in large firms. In any case, there is a substantial difference in these patterns between firms with less than 50 workers and the rest of the size groups. Also, we do not find substantial differences between large and small firms at intermediate levels of investment rates, particularly at those levels (say, from 20% to 30%) that could be considered as representative of episodes of large investment.

Figure 5: Investment rate distribution by type, considering firm size

An alternative way of analyzing the discontinuity of the investment process consists of ordering the observations of each firm according to its investment levels. Figure 6 depicts equipment investment data for firms in the balanced panel with at least one year of positive investment (591 firms). Rank 1 corresponds to the lowest investment while 12 to the higher investment observation. The year of maximum investment represents on average 30.42% of cumulative investment over the sample period, 1.6 times larger than investment in the next rank and 32 times larger than the average for the smallest investment rank. The frequency of zero investment is decreasing with investment rank, where the zero frequency is the year of maximum investment.

Figure 6: Contribution of ranked annual investment to 12-year equipment investment Notes: The rank 1 represents the sum of investment associated with each firm´s smallest annual investment episode divided by the sum of each firm´s total investment for the 12-year period. The rank 2 represents the highest annual investment episode.

Consequently, we find that there are no substantial differences among sectors with respect to the contribution of equipment investment to total investment. Also, according to the patterns of investment analyzed above equipment investment and investment in structures are alike. On the other hand, looking to either small or large firms does make a difference in terms of the discontinuity of the investment process but this is particularly so at the extremes of the investment rates distribution. Further, these differences are not that important much once we take into account that relatively higher rates are found more often in large firms.

4. Technological activities

In this section we describe technological activities by firms in the sample. To this purpose we focus on the number and the nature of innovations declared by firms.² Part of the innovative activity relates directly to the production of innovations by use of technological capital input built from R&D expenditures as well as purchases (or sales) of patent rights and royalties. Clearly though, the adoption of innovations might be more related to physical and human capital investment than to R&D investment as far as technological progress is embodied and/or technological capital is vintage specific.

In the ESEE, a firm declares being involved in process innovation whenever it acknowledges a significant modification in the production process associated to the introduction of new equipment, new methods of organization or both situations. Correspondingly, product innovation is defined in the survey as a signification modification in products resulting from either introducing new materials or new intermediate inputs, or incorporating new designs, exhibiting new appearance or displaying new functions.

Figure 7 illustrates the importance of product and process innovation as well as who are the innovative sectors. For each type of innovative activity the chart depicts the distribution among sectors of innovative firms, i.e. over the 1276 firms declaring process innovation and the 1575 firms declaring product innovation. The more innovative sectors are electric machinery and fabricated metals. The less innovative is office material. There seems to be substantial differences among sectors. Innovative sectors exhibit no remarkable differences in the frequency of product and process innovative activities declared.

Figure 7: Frequency of firms declaring innovative activity by sector and type

Table 3 looks to the aggregate distribution of innovative activity over all firms in the unbalanced panel and taking into account firm's size. In all the cases the less common pattern among firms is being engaged only in product innovation. On the other hand, it is roughly as frequent being engaged only in process innovation as not being engaged in any innovative activity at all. Large firms, which are represented in the unbalanced panel by one third of the whole population, declare being involved in both types of innovative activities nearly twice small firms do.

² See, for instance, Huergo (2004) for an assessment of the determinants of innovation in a related data

Table 3: Frequency of firms by innovative activity and size

The corresponding frequency of observations is presented in Table 4. Process innovations are more frequent than product innovations (34.54% vs. 26.78%). On the other hand, large firms declare both types of innovative activities in a frequency that roughly doubles the one observed among small firms (52.09% vs. 26.05% and 40.89% vs. 19.95%, respectively). Most process innovations, 42.28%, refer to incorporating both new machines and methods (52.72% for large and 32.23% for small), whereas only 14% of observations correspond to new methods without new machines (12.03% for large and 15.63% for small).

Table 4: Frequency of observations by R&D and innovative activities

A similar categorization can be done for R&D investment. R&D investment is clearly a more frequently observed activity among large firms. Notwithstanding, we do find on average a similar frequency of observations of engagement in process innovation than on R&D, and both of these activities above the frequency of engagement in product innovation. Also, within R&D activity, developing as well as both developing and contracting are the more common activities when compared with only contracting R&D services.

A summary description according to the different categories of process innovation is also included, together with the average statistics for the individual figures of product innovation. Correspondingly, process innovations associated to either the introduction of new equipment or both new equipment and new methods of organization are the more frequently observed activities, compared to only introducing new methods. Unfortunately we do not have information on the precise nature of the innovations introduced associated to new products.

Table 5 reports the number of years that firms declare to be involved in R & D activity and in any innovative activity. Process innovation seems relatively evenly distributed across time. In contrast R&D activities are not and seem to track more closely the pattern observed for the frequency of declared product innovation. This could be taken as an indicator of the quality of investments and might serve to qualify the information we have on innovative activities.

Table 5: Frequency of R&D and innovative activity by year

In any case, process innovation appears to be a rather stable activity and does not seem as infrequent as investment. Actually, innovative behavior is persistent: the higher the number of years a firm has declared innovative activity in the past, the higher is the probability to innovate.

On the other hand, whereas 55.55% of firms declare having been engaged in R&D activities at least once in our sample period, 82% declare having carried innovative activity of any kind. Table 6 shows the frequency of declared innovative activity a certain number of years, in process or in product, excluding those firms that never declare being engaged in R&D activity. On average, process innovation appears to be a more stable activity and substantially more stable now we consider firms declaring at least once being engaged in R&D. It is in this case that the frequency of product innovation seems more closely related with the frequency R&D spending.

Table 6: Innovative activity among firms engaged in R&D

Not only the frequency of R&D activity is well below the frequency of innovative activity but also the size of R&D spending is small. Average R&D investment intensity (over sales) is small, 0.67%, ranging from 0.44% in small firms to 1.17% in large firms). By sector, transport equipment, chemical products, and electrical and electronic goods are those that exhibit more technological intensity. In the later case we do not find substantial differences in R&D effort between small and large firms. Further, by looking only to firms engaged in R&D activity, R&D effort goes up to 1.2% over sales on average, and the differences between small and large firms disappear (it becomes 1.08% in small and 1.32% in large firms). Table 7 documents all this information together with that corresponding to those firms declaring process innovation and product innovation separately.

Table 7: R&D investment intensity by sector, considering size and innovative type

... and for those firms declaring R&D activity at least once

5. Employment composition

In this section we describe the technological content of the employment composition observed among firms in the sample.

According to occupational groups we find that the share of production workers have remained stable on average about 70%. Alternatively, according to educational attainment the share of employees with education above secondary school have evolved from 7% in 1990 to nearly 11% in 1998 (the last available figure for this variable).

Table 8 reports employment composition by industry. The contribution of production workers to total employment range from 46.1% in the Chemical Products sector to 79.3% in the Timber and Furniture sector. Differences between small and large firms are relatively minor along this dimension. Likewise, we find substantial variation across sectors in educational attainment of workers but not between large and small firms within a sector.

Table8. Employment by type and sector

On the other hand, the share of workers devoted to technological activities has remained stable about 2% on average. The educational attainment of these R&D workers is equally split among graduate, undergraduate and below.

Table 9 presents the evolution of employment composition according to declared innovative activity. The share of production workers in non innovative firms is on average 6% point above that for firms engaged in both process and product innovation but in line with the share in firms that declare having been engaged only in process innovation.

Table 9: Employment evolution by type, considering innovative activity

6. Concluding remarks

The patterns of equipment investment are representative of the discontinuity of the investment process and there are no substantial differences among sectors. There are some differences between small and large firms but only at the extremes of the investment rate distribution. Likewise, innovative activity is more concentrated in a number of sectors but we do find innovative and non innovative firms in every sector and we do not find substantial differences in innovative activity between small and large firms. Patterns of R&D investment seem more in conformity with patterns of product innovation. Process innovation is related with relevant patterns of equipment investment instead.

References:

1. Fariñas, Jose C., and Jordi Jaumandreu (1999), “Diez años de Encuesta sobre Estrategias Empresariales (ESEE),'' Economía Industrial, 0(5), 29-42.
2. Huergo, Elena (2004), “The Role of Technological Management as a Source of Innovation: Evidence from Spanish Manufacturing Firms,'' unpublished manuscript.
3. Licandro, Omar, Reyes Maroto and Luis A. Puch (2003), “Innovation, Investment and Productivity: Evidence from Spanish Firms,'' Fedea Working Paper 03-30.