The High-Tech Rural Renaissance?

Information Technology, Firm Size and Rural Employment Growth

By Jed Kolko

2000. [10] pages. Harvard University, Cambridge, MA

This Small Business Research Summary (ISSN 1076-8904) summarizes one of a series of research papers prepared under contracts

issued by the U.S. Small Business Administration’s Office of Advocacy. The opinions and recommendations of the authors of this study do

not necessarily reflect official policies of the SBA or other agencies of the U.S. government. For more information, write to the Office of

Advocacy at 409 Third Street S.W., Washington, DC 20416, or visit the office’s Internet site at www.sba.gov/advo.

Purpose

Advances in information technology (IT) have held

out the possibility of a rural renaissance. If firms can

communicate over the Internet with customers, suppliers, and others electronically, perhaps they can

locate anywhere. The author tested the hypothesis

that the spread of the Internet and inexpensive longdistance telecommunications have made it more likely that IT-intensive industries will locate and create

jobs in rural areas, away from high-cost cities.

The central finding is that, at least over the 1989-

1995 period, information-technology-intensive industries were less likely than low- and medium-IT

industries to locate and create jobs in rural areas.

Scope and Methodology

This study uses the new Business Information

Tracking Series (BITS) data base, created by the

U.S. Bureau of the Census with funding from the

Office of Advocacy, to test where firms of differing

IT intensity locate. BITS (referred to in the study by

its former name—LEEM, Longitudinal Establishment and Enterprise Microdata file) is a microdata

file containing annual records for nearly every nonfarm private-sector establishment with positive payroll. Each record contains information on an establishment’s employment, payroll, location, start year,

and four-digit Standard Industrial Classification

(SIC) code for each year that it had positive payroll, beginning in 1989. An establishment is a separate physical location at which business activity

occurs. For establishments that are part of a multiestablishment firm, each record also contains information on the firm’s employment, payroll, and primary SIC code and location. This linkage allows

establishments to be tracked even if they are part of

different enterprises over time. At the time of this

research the file extended through 1995; new years

are being added annually to the data base.

The firm size for each establishment was based on

the size of the firm that the establishment belonged

to in 1989. New establishments born during the period were assigned the size of the firm they belonged

to in 1995. Thus, every establishment that existed in

both 1989 and 1995 remained in the same firm size

category. Firms were placed in one of four categories: smallest (1-19 employees), smaller (20-

99), medium (100-499), or large (500 or more).

A second data set, the October 1989 Current

Population Survey (CPS), reports on individual

workers’ demographic and economic characteristics.

Questions include items on employee computer

usage at work; workers reporting computer usage

also describe the tasks they use computers to perform. By aggregating responses of workers in the

same industry, a measure of industry-level technology usage is obtained. This study uses the fraction of

an industry’s workers that use a computer for electronic mail or other communications as the measure

of IT intensity. This measure of IT intensity yields a

somewhat different mix of high-, medium-, and lowIT-intensive industries than do other definitions.

An industry is deemed high-IT if the fraction was

over 25 percent, medium-IT if the fraction was

between 5 percent and 25 percent, and low-IT if the

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September 2000
fraction was under 5 percent. Examples of high-IT

industries include computer manufacturing, software

and data processing, scientific research, and securities/investment companies. Low-IT industries

include, among others, apparel manufacturing, beauty shops, auto repair shops, furniture manufacturing,

and nursing homes.

The industry classification in the CPS fol lows

the Census three-digit coding, which differs from the

SIC coding used in the BITS. A “crosswalk” linking

the two codes was used to classify BITS industries

into IT categories, a procedure that allowed 99 percent of establishments to be assigned an IT category.

Highlights

• Rural employment growth in 1989-1995 was

strong and was driven by small business. It grew

2.4 percent per year, while urban employment grew

1.4 percent per year.

• In part, the higher growth rate in rural areas was

attributable to the smallest firms (under 20 employees), which accounted for 19 percent of rural

employment, although they make up only 15 percent

of employment overall. Employment in the smallest firms grew much faster than in the other size categories, almost 4 percent per year in both rural and

urban areas versus rates of 0.3 to 2.6 percent for

other sizes of firms.

• The other sizes of firms grew much faster in

rural areas (1.6 percent to 2.6 percent annually)

than in urban areas (0.3 percent to 1.0 percent).

• High-IT firms were overwhelmingly urban in

1989, unlike medium- and low-IT firms. Only 7 percent of high-IT employment was in rural areas versus

14 percent of medium- and 18 percent of low-IT

employment. The difference in rural employment

between high-IT firms (7 percent rural) and low-IT

(18 percent) constitutes the “rural technology gap,”

which stood at 11 percent in 1989. If high- and lowIT firms were equally likely to locate in rural areas,

the gap would be zero.

• This rural technology gap existed across all

firm sizes but was least pronounced for the smallest

firms (4 percent) and smaller firms (5 percent). The

view from 1989, then, suggested that if the rural

technology gap were closing, it would close first for

the smallest firms.

• The gap did not close; instead, it grew from 11

percent in 1989 to nearly 13 percent in 1995. The

share of high-IT employment in rural areas dipped

slightly, while the rural share of low-IT employment

rose a point to more than 19 percent. The gap

widened the most for the smallest and smaller

firms, from 4 and 5 percent, respectively, to 8 percent in each case.

• How could the gap have increased even though

rural employment grew faster than urban employment? The growth in rural employment was confined

almost exclusively to medium- and low-IT industries.

Whereas rural growth in all industries was 2.4 percent annually, rural high-IT growth was only 0.5

percent. In contrast, high-IT employment in urban

areas grew three times faster, at 1.5 percent.

Conclusions

Contrary to popular expectation, high-IT firms did

not create large numbers of jobs in nonmetropolitan

areas in 1989-1995. Unlike medium- and low-IT

industries, which grew roughly twice as fast in rural

as in urban areas, high-IT firms barely increased

their rural employment at all.

There are several possible explanations. High-IT

industries depend on skilled labor and good

telecommunications infrastructure, which are more

plentiful in urban areas. New industries generally

locate first in cities. High-IT businesses also benefit

from face-to-face interactions with customers and

other contacts, which are easier to achieve in an

urban setting.

High-IT industries, as they mature, might start to

move to smaler cities and rural areas. As the infrastructure gap continues to close, the disadvantages of

rural areas for high-IT firms may shrink.

Ordering Information

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other studies performed under contract to the U.S.

Small Business Administration’s Office of

Advocacy, is available on the Internet at

www.sba.gov/advo/research.

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