E XPERIENCIAS M UNDIALES DE P LANIFICACIÓN EN E COTURISMO

In this section, I return to the issue of whether size conditions the ability of a new firm to benefit from its local environment, this time by interacting establishment size with the

specific measures of external economies. I initially estimated models inclusive of interaction terms for each of the sources of external economies. This resulted in excessive

multicollinearity in nearly all industries. To check for inferential bias, I also estimated restricted models where each interaction is modeled separately, with only the SIZE*URB interaction repeated in each model.58 Most of the interaction effects changed little between

the full and restricted specification, but in cases where the two diverge, the restricted models produced more plausible estimates. I proceed by interpreting the interactions estimated independently, with the caveat that some of interactions may not fully control for other size- related interactions. Using the generic variable X to represent diversity, specialized input suppliers, intermediate goods markets, labor pooling or knowledge spillover, the estimating equation is:

58 _{I include the region size interactions in all models because it is not excessively correlated with the other} interactions and provides a theoretically necessary control.

(

)

[

]

(

)

(

i i

)

i i i i i i i i i i i i i i i it X SIZE b URB SIZE b KNOW b LABOR b MARKETS b INPUTS b DIV b URB b SOUTH b NEAST b MWEST b SIZE b QTR b QTR b QTR b t • + • + + + + + + + + + + + + + + = − − 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 1 2 3 ) ( 1 log log λ α . (7.2)

To economize on space I only report coefficient estimates for the particular interactions and related first order terms from each model (Appendix U). The signs and significance values of the interactions are summarized in Table 7.5. I also estimate the hazard ratios for the external economy variables with size evaluated at the 10th_{, 50}th _{and 90}th _{percentiles (see}

Table 7.6) following the approach outlined in the previous chapter.59

I interpret the establishment size-regional size (ie. SIZE*URB) interactions based on estimates from models controlling for the establishment size-diversity interaction

(SIZE*DIV). Since regional size and industrial diversity are the two specific dimensions of urbanization controlling for diversity interactions helps isolate pure regional size effects. I expect that the burden of higher costs in large cities bears greater on larger start-ups, who favor the cheaper land and labor costs of decentralized locations.

Consistent with my expectations, an increase in the size of a region typically increases the hazard for larger firms and has less influence on the survival of smaller plants. These results roughly coincide with the localization-urbanization models of the previous chapter and the localization-size interaction models. The interaction between size and urbanization is positive and significant in manufacturing, professional services, motor vehicles parts (≤ 80 km), computer and data processing and research and testing services (≤ 80 km). In

manufacturing and professional services, the hazard rate increases with urbanization for all three establishment sizes, with larger plants having the highest rate of increase. Larger firms

in larger regions also have relatively higher hazards in motor vehicle parts and research and testing services, while smaller

establishments in these industries experience no significant change in hazard rates. Smaller new firms in computer and data processing have significantly lower hazard rates in large areas while larger plants have higher hazard rates only at small spatial scales.

Table 7.5

Model Summary: Interactive Analysis Sources of External Economies

Man ufac turi ng Prof essi onal Ser vice s Drug s Farm & g arde n m achi nery Met alw orki ng m achi nery Ele ctro nic com pone nts Mot or v ehic le p arts Mea suri ng d evic es Adv ertis ing Com pute r & dat a pr oces sing Rese arch & te stin g Size*Urbanization 20 km + + + - - + + - - + + 40 km + + - - - - + - + + + 80 km + + - - - - + - + + + 160 km + + - - - + + - + + + Size*Diversity 20 km + + + + + + - + + + + 40 km - + + + + + - + - + + 80 km + + + + + + + + - + + 160 km + - + + + - - - - + + Size*Input Suppliers 20 km + - - - - - + + + + - 40 km - - + + + - + + + + - 80 km - - + - + - - + + + - 160 km + - + + + - - + + + + Size*Intermediate Markets 20 km + - - + + - + + + + + 40 km + - - + + - + + + + + 80 km + - - + + - - + + + + 160 km + - - + + - - + + + + Size*Labor Pooling 20 km + - + + - - - + + + - 40 km - - - + - - - + + + - 80 km - - - + + - - + + - - 160 km - - + + + - - + - - - Size*Knowledge Spillovers 20 km + - - - - - + 40 km + - - - - - + 80 km + - - + - - + 160 km + + + + - - +

+ = Increased hazard rate = 90% significance (Pr χ2 <= .1) - = Reduced hazard rate = 95% significance (Pr χ2 <= .05) Large regions provide a

more suitable environment for larger new firms in the drugs (160 km), metalworking machinery (≤40 km) and measuring and controlling devices (≥ 80 km) industries. In the drugs and metalworking machinery industries, an

increase in regional employment increases the hazard rate for new firms at the 10th size percentile

but has no significant effect on 90th percentile establishments. An increase in regional

employment has a negligible influence on smaller establishments in measuring and controlling devices, but reduces the hazard rate of new firms with 47 employees (90th

percentile) from three to five percent.

Industrial diversity typically benefits smaller new firms relative to larger ones. The coefficient of the interaction term is positive and significant in the manufacturing sector (160 km), professional services (≤ 40 km) and for five study industries. In most of these industries an increase in regional size reduces the hazard for smaller firms with little effect on larger establishments. In metalworking machinery and computer and data processing diversity reduces the hazard rates of smaller plant hazards and increases hazard rates for larger ones. Only in the advertising (≥ 40 km) and professional services sector (160 km) do smaller plants have relatively higher hazard rates in areas of greater diversity.

The interaction between establishment size and specialized input suppliers is positive for most industries; specifically drugs (40 km and 80 km), metalworking machinery (≥ 80 km), motor vehicle parts (20 km), measuring devices (20 km and 80 km), advertising (20 km) and computer and data processing (≥ 40 km). In all but motor vehicle parts, smaller

establishments are more likely to survive in areas with a greater specialization of input suppliers. For motor vehicle parts, an increase in the density of input suppliers increases hazard rates of larger plants but has no significant impact on smaller ones. The interaction between size and input suppliers is negative and significant for new firms in electronic components (≤ 40 km) where an increase in the regional specialization of input suppliers reduces the hazard rates for establishments at the 90th percentile. In professional services,

hazard rates for all establishments decline with greater specialization of input suppliers, with larger establishments declining at a faster rate than smaller establishments.

Deeper markets for intermediate goods also typically reduce the hazard rates of smaller establishments relative to larger ones. There is a significant positive coefficient on the SIZE*MARKETS interaction in manufacturing (≤ 40 km), farm and garden machinery (≤ 40 km), metalworking machinery, motor vehicle parts (20 km), measuring devices (≥ 80 km) and advertising. Greater concentration of intermediate goods markets increases hazard rates of 90th percentile establishments in manufacturing, metalworking machinery, measuring

devices and computer and data processing, but has little influence on 10th and 50th percentile

establishments. In farm and garden machinery and advertising, 10th percentile establishments

have lower hazard rates and 90th percentile establishments have higher hazard rates in areas

of specialized product markets. The SIZE*MARKETS interaction is negative and significant in professional services, drugs (40 km), and electronic components (20 km and 160 km), favoring larger plants over smaller ones. In professional services, hazard rates for entrants of all three size classes decline with deepening local intermediate goods markets while the hazards for 90th _{percentile plants decline at a faster rate.}

Establishment size has a mixed effect on the relationship between labor pooling and new firm survival. The SIZE*LABOR interaction is negative and significant in professional services, electronic components (≤ 80 km), computer and data processing (160 km) and research and testing services (≥ 40 km). Of these, electronic components and research and testing services are characterized by increasing hazard rates for smaller plants and declining hazard rates for larger plants given an increase in the regional concentrations of specialized workers. The hazard rates for professional services and computer and data processing

increase for all establishments between the 10th and 90th percentiles, but larger establishments

are burdened less than smaller plants. The SIZE*LABOR interaction is positive and

significant in manufacturing (20 km), farm and garden machinery (160 km) and advertising (≤ 80 km). In these industries, the positive interaction is largely the product of significantly higher hazard rates for 90th percentile plants. The hazard rates for establishments between

the10th percentile and the median size are not significantly different from zero.

The results are also mixed for industrial knowledge spillovers. When measured by the geographic concentration of related patents, the interaction between knowledge spillovers and establishment size is positive for manufacturing (≤ 40 km) and measuring devices and negative for electronic components (≤ 40 km) and motor vehicle parts (20 km, 40 km and 160 km). An increase in the relative specialization of related patents reduces the hazard rate for smaller new firms in manufacturing while increasing the hazard for 90th percentile plants

in measuring and controlling devices. In motor vehicle parts and electronic components 90th

percentile plants an increase in patent specialization reduces the hazard rates for 90th

P10 P50 P90 P10 P50 P90 P10 P50 P90 P10 P50 P90 Manufacturing 1.01 1.01 1.02 1.00 1.00 1.01 1.00 1.00 1.01 1.00 1.00 1.00

Drugs 1.02 1.02 1.05 1.02 1.02 1.02 1.03 1.02 0.99 1.02 1.02 0.98

Farm & garden machinery 1.05 1.04 0.99 1.04 1.04 1.04 1.03 1.02 1.00 1.01 1.01 0.98 Metalworking machinery 1.03 1.01 0.92 1.01 1.00 0.97 1.01 1.01 0.99 1.00 1.00 1.00 Electronic components 1.02 1.03 1.04 1.01 1.01 1.00 1.00 1.00 0.98 1.00 1.00 1.00 Motor vehicle parts 0.97 0.99 1.20 0.99 0.99 1.06 0.99 0.99 1.02 1.00 1.00 1.01 Measuring & controlling devices 1.02 1.02 0.98 1.00 1.00 0.97 1.00 1.00 0.98 1.00 1.00 0.98

Professional Services 1.00 1.00 1.01 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Advertising 1.01 1.00 1.00 1.00 1.00 1.01 1.00 1.00 1.00 1.00 1.00 1.00 Computer & data processing 0.99 1.00 1.01 0.99 0.99 1.00 0.99 1.00 1.00 1.00 1.00 1.00 Research & testing services 1.00 1.00 1.04 0.99 1.00 1.02 1.00 1.00 1.01 1.00 1.00 1.00

P10 P50 P90 P10 P50 P90 P10 P50 P90 P10 P50 P90 Manufacturing 1.00 1.01 1.05 0.99 0.99 0.99 0.95 0.95 0.98 0.95 0.96 0.98

Drugs 0.45 0.54 1.37 0.53 0.63 1.61 0.45 0.62 3.18 0.35 0.50 3.10

Farm & garden machinery 0.97 1.05 1.61 0.89 0.89 0.91 0.60 0.67 1.28 0.58 0.65 1.22 Metalworking machinery 0.79 1.05 2.87 0.74 0.91 1.88 0.71 0.82 1.33 0.82 0.88 1.13 Electronic components 0.91 0.92 1.06 0.91 0.97 1.43 1.06 1.08 1.22 1.34 1.20 0.57 Motor vehicle parts 1.18 1.11 0.45 1.20 1.16 0.75 1.19 1.20 1.39 1.11 1.10 0.92 Measuring & controlling devices 0.82 0.83 0.94 0.74 0.82 1.51 0.76 0.82 1.29 0.99 0.97 0.86

Professional Services 0.98 0.99 1.03 1.00 1.00 1.03 0.99 0.99 1.00 1.00 1.00 0.96 Advertising 0.98 0.99 1.02 1.02 0.98 0.81 0.95 0.91 0.74 0.97 0.93 0.75 Computer & data processing 0.96 0.97 1.01 0.93 0.95 1.15 0.88 0.90 1.17 0.90 0.91 1.12 Research & testing services 0.93 0.96 1.17 0.94 0.96 1.09 0.84 0.88 1.13 0.82 0.85 1.13

P10 P50 P90 P10 P50 P90 P10 P50 P90 P10 P50 P90 Manufacturing 1.01 1.01 1.02 1.01 1.01 0.99 1.01 1.01 0.97 1.02 1.02 1.02

Drugs 2.43 2.27 1.59 0.24 0.59 67.3 0.03 0.08 31.7 0.22 0.45 16.7

Farm & garden machinery 0.78 0.77 0.68 1.11 1.13 1.25 0.67 0.57 0.22 0.60 0.68 1.41 Metalworking machinery 0.93 0.88 0.74 0.53 0.58 0.80 0.44 0.55 1.26 0.30 0.47 2.27 Electronic components 1.06 1.01 0.72 1.06 0.98 0.57 0.90 0.86 0.62 0.98 0.87 0.41 Motor vehicle parts 0.89 0.93 1.68 0.98 1.02 1.70 0.72 0.70 0.50 0.91 0.85 0.38 Measuring & controlling devices 0.73 0.76 0.97 0.83 0.85 1.01 0.75 0.82 1.46 0.71 0.74 0.96

Professional Services 0.93 0.93 0.86 0.93 0.91 0.80 0.90 0.88 0.75 0.76 0.75 0.66 Advertising 0.67 0.74 1.21 0.62 0.68 1.06 0.74 0.79 1.07 0.52 0.59 1.13 Computer & data processing 0.88 0.90 1.07 0.82 0.83 1.00 0.86 0.88 1.11 0.74 0.76 1.03 Research & testing services 1.07 1.04 0.87 1.11 1.08 0.90 1.25 1.23 1.10 1.00 1.01 1.08 P10 = 10th percentile size = 90% significance (Pr t ≤ .1, two tailed)

P50 = 50th percentile size (median) = 95% significance (Pr t ≤ .05, two tailed)

P90 = 90th percentile size

Table 7.6

Interaction Analysis: Simple Slope Hazard Ratios and Statistical Significance Sources of External Economies

Establishment Size * Urbanization

20 km 40 km 80 km 160 km

Establishment Size * Diversity

20 km 40 km 80 km 160 km

Establishment Size * Input Suppliers

P10 P50 P90 P10 P50 P90 P10 P50 P90 P10 P50 P90 Manufacturing 1.00 1.00 1.02 1.00 1.00 1.02 1.01 1.01 1.01 1.01 1.02 1.03

Drugs 1.22 0.88 0.16 1.98 0.95 0.02 3.58 1.53 0.02 6.92 3.58 0.11 Farm & garden machinery 0.97 0.99 1.08 0.94 0.96 1.07 0.94 0.95 1.02 0.90 0.91 1.00 Metalworking machinery 1.03 1.05 1.14 1.04 1.08 1.23 0.95 1.05 1.45 0.95 1.10 1.81

Electronic components 1.09 1.07 0.94 1.18 1.15 0.97 1.17 1.14 1.01 1.23 1.16 0.77 Motor vehicle parts 0.93 0.93 1.00 0.88 0.88 0.89 0.86 0.85 0.74 0.83 0.81 0.58

Measuring & controlling devices 0.99 1.00 1.06 1.04 1.05 1.12 1.03 1.08 1.47 1.16 1.25 2.01

Professional Services 0.97 0.97 0.92 0.94 0.93 0.86 0.91 0.90 0.81 0.93 0.92 0.85

Advertising 0.84 0.95 1.69 0.77 0.94 2.56 0.69 0.97 5.39 0.92 1.22 5.02

Computer & data processing 1.06 1.07 1.16 1.06 1.06 1.11 1.04 1.04 1.14 1.16 1.19 1.55

Research & testing services 0.99 1.02 1.20 0.98 1.03 1.39 0.92 0.94 1.04 0.88 1.01 2.22

P10 P50 P90 P10 P50 P90 P10 P50 P90 P10 P50 P90 Manufacturing 1.00 1.00 1.02 1.01 1.01 1.01 1.01 1.01 0.98 0.99 0.99 0.96 Drugs 0.54 0.57 0.76 0.74 0.70 0.50 1.68 1.53 0.91 4.67 5.22 9.42 Farm & garden machinery 0.84 0.93 1.73 0.91 0.99 1.53 0.95 1.05 1.83 0.77 0.99 4.43

Metalworking machinery 0.89 0.84 0.67 1.05 1.03 0.98 0.97 1.00 1.10 0.90 0.92 0.99 Electronic components 1.09 1.00 0.57 1.12 0.97 0.39 1.02 0.90 0.39 1.01 0.92 0.51 Motor vehicle parts 1.01 1.01 0.97 1.06 1.03 0.75 1.42 1.33 0.55 1.56 1.45 0.58 Measuring & controlling devices 0.85 0.87 1.06 1.11 1.12 1.19 1.12 1.12 1.14 1.32 1.33 1.38

Professional Services 1.06 1.05 0.95 1.09 1.09 1.02 1.10 1.10 1.06 1.18 1.17 1.07

Advertising 0.99 1.02 1.20 1.05 1.06 1.16 1.03 1.06 1.23 1.15 1.13 1.06 Computer & data processing 1.02 1.02 1.02 1.10 1.11 1.12 1.06 1.06 1.06 1.09 1.09 1.08 Research & testing services 1.07 1.04 0.88 1.11 1.05 0.73 1.11 1.01 0.57 1.29 1.12 0.48

P10 P50 P90 P10 P50 P90 P10 P50 P90 P10 P50 P90 Manufacturing 0.99 0.99 1.00 0.99 0.99 1.01 0.98 0.98 1.00 0.99 0.99 1.02 Drugs 1.07 1.01 0.78 1.06 1.02 0.82 0.88 0.88 0.85 0.50 0.52 0.66 Farm & garden machinery 0.97 0.97 0.94 1.00 0.93 0.59 0.97 0.93 0.73 0.87 0.89 0.98 Metalworking machinery 0.97 0.92 0.77 0.99 0.93 0.75 0.91 0.91 0.91 0.80 0.87 1.19 Electronic components 1.01 0.99 0.88 0.99 0.98 0.90 1.01 0.99 0.89 1.01 0.99 0.85 Motor vehicle parts 1.01 0.93 0.34 0.96 0.88 0.30 0.97 0.92 0.44 1.02 0.96 0.45

Measuring & controlling devices 1.08 1.09 1.17 0.98 0.99 1.05 0.94 0.96 1.15 0.90 0.94 1.24 P10 = 10th percentile size = 90% significance (Pr t ≤ .1, two tailed)

P50 = 50th percentile size (median) = 95% significance (Pr t ≤ .05, two tailed)

P90 = 90th percentile size

Table 7.6 (continued)

Interaction Analysis: Simple Slope Hazard Ratios and Statistical Significance Establishment Size * Intermediate Goods

Sources of External Economies

20 km 40 km 80 km 160 km

Establishment Size * Labor Pools

20 km 40 km 80 km 160 km

Establishment Size * Knowledge Spillovers

7.5 Discussion

In this chapter I examine how the sources of external economies influence the duration of new firms. I classify urbanization economies into those derived from the size of the region and industrial diversity, and model four specific sources of localization economies:

specialized input suppliers, intermediate goods markets, labor pooling and knowledge spillovers. In general, I found the specific measures of localization tend to be less

significant, but otherwise stronger, predictors of new firm hazard rates than the aggregate own-industry specialization indicator used in the previous chapter. Their low statistical significance may be due to limited spatial variation. The specific sources of external economies commonly have moderate to high correlations with one another, and require considerable spatial variation to effectively parse their individual effects. Analysis based on a larger sample of new firms may be necessary.

After controlling for other influences, regional size has a largely indeterminate effect on the duration of new firms, the result of offsetting forces of positive urbanization economies and negative congestion diseconomies. Diversity was found to reduce the hazard rates of new firms in manufacturing, drugs, advertising, computer and data processing services, and research and testing services. The recent literature emphasizes diversity as a source of dynamic knowledge spillovers but diversity may also benefit new firms in other ways. Access to a potentially diverse client base may buffer local serving businesses from industry specific shocks. Industrial diversity may also represent inherent advantages of a

competitively organized regional economy (Evans 1986). Of these potential benefits,

diversity spillovers may be more relevant in the drugs industry, where new firms compete on the basis of innovation. New firms in the professional services industries predominantly

serve other local businesses and are more likely to benefit from the diversity of clientele found in urban areas.

Proximity to deeper pools of specialized input suppliers is the most consistently

significant source of localization economies. Predominantly small new firms are unlikely to have the requisite internal demand to efficiently produce their own auxiliary goods and services and may rely heavily on other local businesses to fill those needs. Although not directly comparable, my findings of significant benefits to specialized input suppliers coincide with previous studies. Feser (2002) includes separate measures for producer

services and input product suppliers, and finds that producer services increase productivity in measuring and controlling devices industry and the input product suppliers increase

productivity in the farm and garden machinery industry. My combined measure of specialized input suppliers is weakly significant in both of these industries. Rigby and Essletzbichler (2002) use a supply-chain measure that combines input suppliers with intermediate goods markets. This measure is found to increases productivity for plants in numerous two-digit manufacturing industries. In my models, proximity to intermediate goods markets has little influence on new firm survival.

Net of other sources of localization, proximity to specialized labor pools has little

influence on the survival of new firms in manufacturing industries and increases hazard rates for new firms in several business and producer services industries. These results are contrary to past studies where labor pooling is linked with higher productivity in manufacturing (Feser 2002; Rigby and Essletzbichler 2002). Both these studies are based on analysis of the

Longitudinal Research Database micro-files and systematically exclude the small

pooling was only significant for larger establishments. Regional specialization in labor markets may be complementary to internal scale economies, contrary to the traditional perspective of external and internal economies as partial substitutes. Larger plants are more likely to face labor supply constraints since they have a more refined internal division of labor that requires greater occupational specialization. New firms, by contrast, are very small and may have little need for deep reserves of specialized workers, or at least not to the extent that deficient regional labor pools pose a major barrier to survival in the early years. As successful new firms move along the life cycle, expand production and incorporate more specialized machinery, their reliance on specialized labor pools may also grow. The environmental isolation of large branch plants suggests there may be limits to the need for specialized labor with greater capitalization and adoption of large batch modes of production (Feser 2001a; Henderson 2003).

My measure of industrial knowledge spillovers is also insignificant in most industries. My results may say more about the value of patents as a measure of knowledge spillovers in particular industries than whether knowledge spillovers are, or are not, a relevant influence on the post-entry behavior of new firms. The propensity to patent and the economic value associated with patenting are known to vary greatly by industry, and the many patents can only be loosely matched to industry classes (Griliches 1979; Griliches 1990; Acs et al. 2002). Drugs manufacturing is one area where patents may provide a decent metric of knowledge and innovation. I find some evidence that new firms in the drugs industry were more likely to survive in areas where there is a higher concentration of patenting.

Establishment size plays an important role in determining the relationship between a business and its external environment and deserves greater consideration in future empirical

work. Failing to adequately account for the differential effects of establishment size may lead one to falsely conclude that external economies are insignificant. In this chapter and the last, I found many instances where external economies were insignificant when estimated on the entire population of establishments, but were significant when interacted with the

establishment size. In several cases the same external conditions had opposite influences on smaller and larger plants. In others, a change in the external economies only had significant influences on either larger or smaller plants.

The weight of my evidence suggests that smaller plants are the most common beneficiaries of external economies, particularly those stemming from specialized input suppliers, intermediate goods markets, and diversity. Small new firms are unlikely to have the requisite internal demand to efficiently produce their own auxiliary goods and services, and may rely heavily on other local businesses to fill these needs. They are also less likely to export their goods and services and are more reliant on local markets. However, there are several industries where an increase in external economies produces a relative reduction in hazard rates for medium sized plants (i.e. the new firms at the 90th percentile) over smaller

plants. Thus my results only partially refute the existence of an inverted U relationship between size and external economies (Sweeney and Feser 1998; Feser 2001a). Instead they stress the importance of industry-specific conditions in regulating the relationship between a business and its environment.

My estimates of the influence of plant size contrast with Feser’s (2001a) specific results for the measuring and controlling devices and the farm and garden machinery industries. In measuring and controlling devices, he finds no influence of external economies on small plants (< 31 employees), but producer services and specialized labor pools become

significant after raising the size limit to 88 employees. I find that specialized input suppliers favor smaller measuring and controlling devices plants (at 20 km) and have no significant influence on hazard rates of plants of 47 employees (the 90th percentile). There is no

significant relationship between labor pools and new firms in measuring and controlling devices of any size. In the farm and garden machinery industry, Feser finds significantly higher productivity resulting from labor pools, patent rates, and producer services for plants

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