Miner´ıa de datos difusa

This section examines four additional issues. First, I examine whether spillovers de- pends on the firm operating on foreign or domestic markets. Second, I examine whether the spillover is heterogeneous with respect to the price of the machine or the size of the firm that is assumed as a peer influence. Third, I examine whether the results depend on the ownership of the firm. Fourth, I look into whether the results depend on the number of countries where a specific machine is available.

4.5.1 Does domestic competition matter?

The spatial clustering of machine imports can also occur because of the competitive pressure experienced by the second or third importer. This mechanism can be par- tially interpreted as demonstration effect but competition is not necessarily regarded as agglomeration effect. To control for the strength of competition I split the spillover variable by the export status of the peers. This will allow to examine whether spillover effect exist between exporter or non-trading firms. As exporters do not necessarily compete on the same product market, a detected spillover effect can be less likely to be due to competition pressure.

Table 4.12: Regressions on machine imports: the local competition

dep. Var: import dummy [1] [2] [3]

sample: all firms non-exporters exporters

num. of prior importers of the same machine in the same NUTS4

0.497*** 1.965*** 0.336*

who do not export [0.126] [0.221] [0.174]

0.993*** 0.222*** 1.198***

who export [0.0428] [0.0230] [0.0464]

controls yes yes yes

dummy: year yes yes yes

Observations 1278885 332577 946308

R-squared 0.009 0.002 0.007

*** p < 0.01, ** p < 0.05, * p < 0.1. Moulton corrected s.e. in parentheses

The table present result from three separate equation. The first column gives result for all firms, while others are estimated exporter dummy defined samples. Controls: size, foreign ownership, TFP, local agglomeration, number of firms and financial variables, all lagged. The NUTS3 spillover variables are also included, though not reported. The spillover variables are divided by 1000.

Table 4.12 reports regression results for machine import choice by the trading activity of firms. The first column shows results for all firms, while the second and the third columns show results for never exporters and exporters respectively. Results imply, that spillover originating from exporters has a higher effect on import probability. Also, results suggest that peer effects are the strongest across firms who trade (or not trade) similarly. As peer effects seem to exist across trading firms as well, one can conclude that the our spillover results are not entirely the consequence of competitive pressure.

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4.5.2 Does the size of the peer and the price of the machine matter?

So far it was implicitly assumed that all machine imports have or can have the same effect on subsequent imports. However, cheap widely available machinery might not generate the same spillover mechanisms as expensive or larger machinery. Also, a very sophisticated and expensive machinery imported by a manufacturing giant will not be suitable for a small firms. To investigate the heterogeneity of spillovers with respect to firm size and the price of machines I differentiate the spillover variable accordingly.

Table 4.13: Regressions on machine imports: by firm size

dep. Var: import dummy [1] [2] [3]

sample by firm size small medium large

# of prior importers of the

same machine in the same NUTS4 of

small firm 0.535*** 1.405*** 1.808***

[0.0863] [0.487] [0.456]

medium sized firm 1.188*** 0.71 3.754**

[0.208] [0.632] [1.835]

large firm 0.115 2.057*** 0.578

[0.101] [0.338] [0.745]

controls yes yes yes

dummy: year yes yes yes

Observations 842151 339375 97359

R-squared 0.005 0.006 0.01

*** p < 0.01, ** p < 0.05, * p < 0.1; Moulton corrected s.e. in parentheses

The table present result from three separate equation in each column, estimated for various firm sizes defined by average employment. The first column gives result for small firm (10-50), the second for middle-sized firm (50-250), the third for large firm (over 250). Spillover variables divided by size of the peer who imported the same machine. Controls: size, foreign ownership, TFP, local agglomeration, number of firms and financial variables. The NUTS3 spillover variables are also included, though not reported. The spillover variables are divided by 1000.

Table 4.13 divides the same machine, same micro-region spillover variable by the size category of the importer peer. The size is defined by the employment definition of

small and medium sized enterprises.22 _{The first column estimates equation 4.2 with}

this newly defined spillover variables for small firms. Results suggest that the import decision of small firms can mostly be influenced the imports of other small firms and of the medium sized firms. Column (2) collects results for middle-sized firms. It shows that middle sized firms benefit from imports by small firms and large firms only. The effect of an additional large firm is more than one and half times bigger than the effect induced by a small firm. Lastly, column (1) estimated spillovers for large firms only. Results suggest that large firms may benefit mostly from the presence of middle sized firms.

Table 4.14 divides the same machine, same micro-region spillover variable by the price category of the machine imported by the peer. The price category is defined by the within machine distribution of the real unit price. Cheap imports is the lowest, while

22_{Small firms are below 50 and above 10 employees. Middle sized firms have employment over 50 and below 250.}

Large firms have more than 250 employees. See http://ec.europa.eu/enterprise/policies/sme/facts-figures-analysis/sme- definition/

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Table 4.14: Regressions on machine imports: by the price of machinery

dep. Var: import dummy [1] [2] [3]

sample by firm size small medium large

# of prior importers of the

same machine in the same NUTS4 of

low price 0.827*** 0.776* 0.941** [0.155] [0.422] [0.368] mid price 0.651*** 1.326*** 2.476*** [0.0573] [0.181] [0.436] high price 0.457*** 1.798*** 1.611*** [0.139] [0.335] [0.475]

controls yes yes yes

dummy: year yes yes yes

Observations 842151 339375 97359

R-squared 0.005 0.006 0.01

*** p < 0.01, ** p < 0.05, * p < 0.1; Moulton corrected s.e. in parentheses

The table present result from three separate equation in each column, estimated for various firm sizes defined by average employment. The first column gives result for small firm (10-50), the second for middle-sized firm (50-250), the third for large firm (over 250). Spillover variable is divided according to the price of the machine the peer has imported. Low price is lowest 20%, while high price is the most expensive 20%. Controls: size, foreign ownership, TFP, local agglomeration, number of firms and financial variables. The NUTS3 spillover variables are also included, though not reported. The spillover variables are divided by 1000.

the expensive machine is the highest 20 percent of the real price over the sample period. The first column of Table 4.14 collects results from estimates equation 4.2 with price divided spillover variables for small firms. Results suggests that small firms might benefit from same machine spillovers of all prices. However, the highest benefit can be expected from the cheap price imports of peers. The coefficient on cheap spillover is about twice as high as the coefficient on high price spillover variable. Column (2) holds estimates for medium sized firms. Results imply that medium sized firms might primarily benefit from medium and high priced imports of their peers. Similarly, large sized firms, column (3), seem to benefit also from medium and high priced imports. All in all, investigating heterogeneity of spillovers by size and price reveals plausible results. Firms seem to be benefiting mostly from peers that are of similar size and import a machine in the expected price-range. That is, small firms are mostly influenced by relatively cheaper machines and less from the most expensive ones. Similarly, I find that larger or middle sized firms would be influenced by the import activity of small firms only to a smaller extent and irrespective of the price of the machine they import. In line with this, I find that the strongest spillovers could be generated by the middle sized and large firms. This could be consistent with the notion that spillovers are propagated more efficiently through more employees.

4.5.3 Do domestic learn from foreign firms?

Foreign owned firms are overrepresented across machine importers. While 25 percent of the firms are foreign owned, about they have an about 40 percent share in the capital importing group. Assuming that foreign firms have ex-ante advantage in the knowledge

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about foreign technology, in this section I look into whether this knowledge spills over to domestic firms. I do this by, on the one hand, by separating spillover variable by the ownership of the peers and running regressions by subsamples of domestic and foreign firms of different size categories, on the other. Estimates of the spillover variables for machine choice are collected in Table 4.15.

Table 4.15 has two blocks. The upper contains results from regressions on domestic firms. The column (1) estimates equation 4.2 for machine choice for small firms. Results suggest that both foreign and domestic firms generate spillovers. Though the spillovers by domestic firms is twice as that of generated by the machine imports of foreign firms. The second column shows estimated spillover effects on middle sized domestic firms only. Here, the magnitude is twice as large as with small firms and spillovers from domestic firms still matter relatively more. The third column collects results for large firms and it shows that the estimated coefficients are three to four times are high as the estimate for middle sized firms.

The lower block contains results from regressions on foreign firms. Results indicate that foreign firms benefit from domestic firms about the same, irrespective of their sizes. At the same time except for small firms, there is no peer effect detected across foreign owned firms.

Results indicate that while domestic firms are more probable to import machinery when foreign machine importers are present in the same location, the effect does not exceed the benefit enjoyed from domestic firms.

Table 4.15: Regressions on machine imports by ownership

dep. Var: import dummy [1] [2] [3]

small middle large

for sample of domestic firms

# prior importers of the same machine in same NUTS4

domestic 0.790*** 1.526*** 4.111***

[0.0384] [0.157] [0.469]

foreign 0.268*** 0.663*** 3.157***

[0.0419] [0.118] [1.075]

for sample of foreign firms

# prior importers of the same machine in same NUTS4

domestic 0.953*** 1.441*** 1.392*

[0.105] [0.401] [0.785]

foreign 0.572** 0.799 -1.48

[0.238] [1.094] [1.151]

*** p < 0.01, ** p < 0.05, * p < 0.1. Moulton corrected s.e. in parentheses

The table present result from six equations in two blocks. The upper block are results from 3 equations on domestic sample by the firm size categories:Small firm (10-50), middle-sized firm (50-250) large firm (over 250). The lower block shows results for domestic firms. Controls: size, foreign ownership, TFP, local agglomeration, number of firms and financial variables, all lagged. The NUTS3 spillover variables are also included, though not reported. The spillover variables are divided by 1000.

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4.5.4 Is the machine available from many countries?

In order to ensure that firms indeed have the choice to pick machines from different countries, only those machines were considered that are available in at least three

countries. Naturally, if some machines in the choiceset were available in only one

country, machine imports from that country was clustered in space. Technically, there was no choiceset. Still, the number of countries where the machine is available might influence our results. Observed clustering may be the result of few seller countries rather than spillovers. In order to see how this affects the results, I estimate equation 4.2 on subsamples defined by number of source countries.

Table D.6 (in the Appendix) investigates the influence of the number of source countries. Column (1) estimates country choice on all firms and include a variable expressing the

number of countries where the given machine is available.23 Columns (2) to (4) collects

results from estimations on subsamples defined by the number of countries. The second column uses only machines that are available in 3 to 5 countries, third includes machines imported from 6 to 10 countries and the last columns includes those imported from more than 10 countries. The results on the spillover coefficients are not statistically different from each other, which indicates that the extent of global availability does not change the baseline results.