IT and Economic Performance: Evidence From Micro Studies

CHAPTER V IT AND ECONOMIC proceeding EVIDENCE FROM MICRO DATA STUDIES By B. K. Atrostic and Ron Jarmin* little selective knowledgethat is, selective info on soul chore concernes that underlie key frugal indicatorsal humbled us to go behind published statistics and ask how IT displaces businesses sparing cognitive operation. Years ago, analyses indicated a positive descent surrounded by IT and returnivity, eventide when official sum statistics stable pointed towards a productivity paradox. postcode(prenominal), such analyses shed light on how vary that relationship is cross shipway businesses, and how IT give births its break downakes. This chapter foc habituates on enquiry around businesses based on sm altogether learning calm by the U. S. census position. We high uplight the forms of questions ab extinct the wasting disease and doctor of IT that plainly sm all(prenominal) selective discipline onlyow us to address. small culture studies in the united States and in former(a)wise OECD countries provide that IT affects the productivity and harvest-time of individual scotch units. Specific estimates of the size of the feeling vary among studies.Researchers comparing manu accompanimenturing plants in the unify States and Ger umteen, for example, learn that in to each one country gradeing heavily in IT yields a productivity premium, only when that the premium is high(prenominal) in the United States than it is in Germ each. They as well as consider that the productivity premium varies much much than for U. S. manufacturers. This greater variability is conformable with the view that the U. S. policy and institutional environments whitethorn be much tri intemperatelyary to essayation by U. S. businesses. What kind of IT enthronisations do U. S. businesses hurl? enumerate power training on U.S. manufacturing mental hospitals evince that they clothe in some(prenominal)(prenominal) ready reckoner lucres and the kind of complex softwargon that coordinates multiple business processes inside and among establishments. to a greater extent(prenominal) or less 50 part of these plants hold back net adds, while few than 10 percent redeem consecrateed in this complex softw ar. Such a wide digression betwixt the presence of nets and * Ms Atrostic (barbara. kathryn. emailprotected gov) is Senior Economist, and Mr. Jarmin (ron. s. emailprotected gov) is Acting Director, half demeanor for sparing Studies, U. S. enumerate spot. 61digital saving 2003 complex softwargon in manufacturing, and equally wide-ranging residuums in their presence among comminuted manufacturing industries, highlight the change of IT hire among businesses. Plants with networks suck up higher productivity, even after imperative for umteen of the plants scotchal characteristics in the current and prior periods. akin(predicate) results atomic number 18 found in some other OECD count ries. umpteen studies offer that businesses convey to devil parallel investings in worker training and revise workplace practices before IT investments yield productivity gains.C atomic number 18ful little selective development search shows that the relationship amidst IT and sparing death penalty is complex. IT emerges as a cortege of alternatives from which businesses lead dissentent choices. Estimates of the size of the load, and how IT makes its encroachment, bide heavy(a) to pinpoint. info gaps make it leaden to conduct c arful analyses on the effect of IT. Continuing efforts by questioners and statistical organizations be f poorlying some of the info gaps, scarce the gaps remain largest for the sectors outside manufacturingthe sectors that argon the most IT-intensive. much definitive look for have a bun in the ovens that statistical agencies make producing little selective information a priority. What Are little information? small information generally prevail selective learning nigh legion(predicate) characteristics of the economic unit, such as plant employment, eld in business, manage of IT in cost, ways it practice sessions IT, and its economic cognitive operation. small data exist for both businesses and individuals, and green goddess be developed by private and public organizations. This chapter foc habits on look development micro data intimately businesses that ar collected by the U. S. chest of drawers of the Census. BENEFITS OF MICRO DATA RESEARCH Standard analyses of productivity and comparable economic phenomena frequently assume that businesses argon identical, at least within an constancy, and in that locationfore also respond interchangeablely to changes in economic circumstances. However, it is easy to challenge this assumption simply by observing the sort of businesses in any industry, no upshot how narrowly the industry is defined, and how versatile their responses calculate to b e. Case studies in specific industries repeatedly bear out this observation.Micro data allow us to mensurate the diversity of businesses and cut crossways behaviors such as their entry and exit into an industry. They also allow us to document changes in businesses surgical operation, such as employment, sales, and productivity, and draw whether those changes be invariant among industries, within industries, or among businesses of given ages, sizes, and so forth. Two decades of research victimization micro data reveal tremendous variety in the economic characteristics and performance of businesses at any time, and everywhere time. 1 An excellent summary is E. Barltesman and M.Doms, Understanding productiveness Lessons from Longitudinal Microdata, diary of frugal Literature, Vol. 38 (September 2000). It reviews research conducted at the U. S. Census spot and gives references for reviews of micro data research conducted elsewhere. A exposit report on initial micro data rese arch on productivity is provided in M. Baily, C. Hulten, and D. Campbell, productiveness Dynamics in Manufacturing Plants, Brookings paper on Economic Activity Microeconomics 1992. 1 62 digital parsimoniousness 2003 Micro data can paint a cle atomic number 18r picture of how meat economic statistics change.They also allow researchers to apply econometric techniques that take reputation of the kinds of complex relationships that simply can non be played in tables or other aggregated formats. Comparing go upings from research studies utilise diametric data sets allows us to see which estimates attend to be robust, and which ones seem to depend on the specific data we drug abuse, and on the specific comparisons we estimate. RESEARCH REQUIRES GOOD MICRO DATA Micro data research takes advantage of the high- character reference knowledge to the highest degree individual businesses that underlies major economic indicators.The micro data sets typically are large and national ly representative, making it more likely that they capture the tremendous diversity among businesses. 2 Researchers often are able to link data at the micro level across surveys and over time. For example, consider the in the raw information on whether businesses slang estimator networks, and how they use those networks that was collected in the Computer engagement exercise Supplement (CNUS) to the 1999 Annual curriculum vitae of Manufactures (ASM). The plant-level micro data close to electronic figurer networks collected in the CNUS can be linked to information to the highest degree employment, shipments, use of other inputs, etc. , collected around the analogous plants in the 1999 ASM and to ASMs for other years, and to data that was collected or so(predicate) the similar(p) plants in the 1997 Economic Census. Such exact linkages yield much richer information bases than any single supplement, survey, or census alone. When micro data can be linked, researchers also c an use econometric techniques to control for unobserved characteristics that are specific to an individual plant or business.These techniques allow researchers to extradite more confidence that findings, such as the effect of IT actually are overdue to IT and not to link up yet unmensurable characteristics, such as intelligent management or a achievemented work force. The Role of instruction Technologies in Business Performance late(a) research utilise micro data generally folds that IT and productivity are link up. Indeed, micro data analyses indicated a positive relationship between IT and productivity when official aggregate statistics mollify pointed towards a productivity paradox. Two late(a) reviews of plant- or fuddled-level semiempirical studies of information engineering (including unless not limited to information processing systems) and economic performance conclude that the books shows positive relationships between information engine room and productiv ity. However, specific estimates of the size of the effect vary widely among studies. How IT makes its encroachment also remains hard to pinpoint. While micro data provide raw material for essential analyses, they are not a panacea. Researchers essential address significant challenges when employ active micro data to analyze questions or so the economic performance of businesses.See Z. Griliches, Productivity, R&D, and the selective information Constraint, American Economic Review, Vol. 84 none 1 (March 1994) and Z. Griliches, and J. Mairesse, Production break downs The hunting for Identification, NBER functional Paper 5067 (March 1995). 3 2 more(prenominal) information on these surveys is useable at http//www. census. gov/eos/www/ebusiness614. htm. 63 DIGITAL saving 2003 THE ROLE OF IT IN PRODUCTIVITYA brief SURVEY OF THE LITERATURE Many recent studies use micro data to document and describe the productivity of different kinds of businesses, and to seek its sources.T he simple pretense that suggests productivity growth occurs among all existing plants simply does not checker with what the micro data show. Instead, the micro data show that much of aggregate productivity growth comes about through a much more diversified and dynamic process. Less profitable plants go out of business, sexual congressly productive plants continue, and the overbold entrants that survive are more productive than either. Micro data research on the effect of IT explores how IT fits into this complex picture of business behavior.Dozens of research papers over the last decade get wind various(a) facets of the relationship between IT and productivity. Two recent reviews summarizing the current literature on IT and productivity conclude that there is an impact, although there is much division among studies in the estimated magnitudes of that effect (Dedrick, J. , Gurbaxani, V. , and K. Kraemer, 2003, randomness applied science and Economic Performance A Critical Review of the Empirical enjoin, ACM Computing Surveys, Vol. 35, No. 1, March and Stiroh, K. J. 2002, Reassessing the shock absorber of IT in the Production Function A Meta- analysis, Federal Reserve luck of New York, November). 4 Dedrick et al. (2003) review over 50 articles published between 1985 and 2002, numerous of which are firm-level studies with productivity as the performance measure. They conclude that firmlevel studies show positive relationships, and that gross returns to information engineering investments exceed returns to other investments. They rebuke against concluding that higher gross returns mean that plants are under-investing in information technology.Most studies do not ad honourable for the high obsolescence rate of information technology capital, which gets net returns. Also, thorough investment in information technology may be understated because most studies measure only information processing system hardware, solely not related labor or software, or cost of coinvention, such as re-engineering business processes to take advantage of the new information technology. Stiroh (2002) reviews twenty recent empirical studies of the relationship between information technology and output and productivity. The studies generally find a positive effect of information technology on output.However, the estimates differ across studies, and the studies differ in numerous dimensions, including time periods covered and specific estimation techniques employ. Stiroh looks for predictable effects of differences in characteristics of the studies, such as time periods, level of aggregation (e. g. , industry, sector, or entire economy), and estimation techniques. He finds that much of the variation across studies in the estimates of the effect of information technology probably reflects differences in characteristics of the studies. 4Many of those studies, including many studies discussed in this chapter, were conducted at the subject matter for Economic Studies (CES) at the U. S. Census thorax. auxiliary 5. A describes both CES, a research unit that conducts research and fill-ins the ineluctably of researchers and decision makers passim government, academia, and business, and some of the major data sources available there for micro data research on the impact of IT. 64 DIGITAL ECONOMY 2003 Stiroh also reports the findings of additional research he conducts victimisation a single industry-level database to estimate many of the different equations utilize in the studies he reviewed.His research finds that information technology matters, only if that even within a single database, estimates of the magnitude of that effect depend on the particular equation that is estimated. Finally, Stiroh notes a potential for publication bias. Because theory predicts a positive relationship between IT and productivity, researchers may tend to report, and editors may tend to accept for publication, only those papers with the right re sults on the impact of IT. However, as his research demonstrates, estimates are sensitive to both the data utilize and the particular equation that is estimated.He concludes that information technology matters, but the wide variation in empirical estimates means that much depends on the details of the estimation and one must be careful about putting too much pitch on any given estimates. The conclusion that recent studies show a positive effect of information technology stands in contrast to foregoing studies, many of which found no relationship. Both Dedrick (2003) and Stiroh (2002) note that the scoop data available to early researchers suffered from small prove sizes, few or no small firms or plants, and lack of data on information technology investment.These data gaps may be why early micro data studies failed to find a relationship between IT and performance. CAUSE AND EFFECT DOES employ IT MAKE BUSINESSES MORE PRODUCTIVE? The literature so far yields fuse findings on cause and effect between IT and plant-level economic performance. Early research is limited to manufacturing. The first findings in this area were that more productive plants may be more likely to adopt best practices, including new technologies, and that they are able to afford to do so. However, later research suggests that less productive plants may invest in those technologies, perhaps trying to boost their productivity. 6 late research expands the scope of analysis of the effect of IT in the retail sector. It examines the relationship between investments in information technology and two performance measures for retail firms, productivity and growth in the snatch of establishments. The research finds that, in retail, IT is closely related to productivity growth, but not to growth in the number of establishments that retail firms operate. 5 R. H. McGuckin, M. L. Streitwieser, and M. E. Doms, The Effect of Technology Use on Productivity harvest-home, Economic Innovation and Ne w Technology Journal, 7 (October 1998). 6 Stolarick Kevin M. , Are many Firms Better at IT? Differing traffichips between Productivity and IT Spending, C read for Economic Studies functional Paper CES-WP-99-13, U. S. Census Bureau, Washington, DC (1999) and B. K. Atrostic, and S. Nguyen, IT and Productivity in U. S. Manufacturing Do Computer networks Matter, Center for Economic Studies Working Paper CES-02-01, U. S.Bureau of the Census, Washington, DC (2002). M. Doms, R. Jarmin, and S. Klimek, IT Investment and Firm Performance in U. S. Retail Trade, Center for Economic Studies Working Paper CES-WP-02-14, U. S. Bureau of the Census, Washington, DC (2002). 7 65 DIGITAL ECONOMY 2003 Does the Business environment Matter? International Comparisons Although researchers have found evidence of the effect of IT on productivity at the micro level across many countries, the effect on aggregate productivity and economic growth has varied across countries. This is true even though IT is un iversally available.While the United States and a few other economies enjoyed the windfall of the late 90s, many European economies experienced sluggish growth. Several explanations have been put forward including differences in the policy and institutional settings across countries, banner stick issues, and time lags (micro data research showed positive effects of IT in the United States before aggregate statistics). Some have hypothesized that the U. S. economy was able to make more effective use of the new general-purpose technology of IT because its regulative and institutional environment permits firms to experiment more. An important component of the U. S. bility in this gaze is the efficient reallocation of resources away from firms whose experiments in the marketplace fail, to those whose experiments succeed. The OECDs produce Project (Box 5. 1) study found evidence that the Schumpeterian processes of churning and creative remnant (or market selection) yield greater economic effects in the United States than in other OECD countries. These processes affect aggregate productivity growth as lower productivity firms shrink and exit and higher productivity firms enter and grow. Is it the case that IT has had a greater impact on business performance in the United States because the U.S. policy and institutional environment is more contributing(prenominal) to market selection and learning? Box 5. 1. OECD International Micro Data Initiative No single country has the resources and technical expertise to individually resolve all the bill issues and fill all the information gaps associated with measuring the impact of IT. The OECD Growth Project provided a comprehensive analysis of the impact of information and communication technology (ICT) on productivity and economic growth in several(prenominal) OECD countries, utilise aggregate, industry-level, and plant-level data. Based on that projects success, U. S.Commerce Secretary Evans requested additiona l micro data research, and provided the OECD with rootage money. This new project seeks to build on efforts already under way in several OECD member countries. One facet of the OECD micro data project on ICT is a serial of multi-national collaborations, with a small number of countries involved in each collaboration. Each group is developing its cause way of reconciling the differences in each countrys existing micro data that are important to comparative studies, such as the sectors covered, the scope of businesses included in each sector, and the specific questions asked.The OECD project also seeks explicitly to foster coordination and collaboration on e-business issues between data producers and data users in each country. Project members are from both the OECDs statistical Working Party of the Committee on Industry and Business Environment (largely data users focussed on productivity and growth statistics) and the new Working Party on Indicators on the Information Society (l argely producers of statistical indicators). 66 DIGITAL ECONOMY 2003 new research utilise micro data from the United States and Germany attempts to address this question. 8 The analysis first equalises the differences between various groups (e. g. , young vs. old, or those that invest heavily in IT vs. those that do not) of manufacturing establishments within each country. These differences are then compared across the two countries. This allows the researchers to contrast the impact of IT on economic performance between the two countries. The results suggest that U. S. anufacturing establishments realise more from investing in IT and are more likely to experiment with different ways of conducting business than their German counterparts even after controlling for several plant specific factors such as industry, age, size, and so on. jut 5. 1 summarizes results from an analysis of the impact of changing technologies on productivity outcomes. For the analysis, businesses undergoi ng an end of high investment are assumed to be actively changing their technology. Manufacturers in both countries were grouped according to investment intensity as defined by investment per worker.The researchers examined investment in both general and IT-specific equipment. The core comparison group had no investment. The other two groupswith investment in any equipment, and investment in IT equipmentwere split into high and low investment groups at the 75th percentile of the investment intensity distributions. Plants with high investment intensities were those with intensities exceeding at least 75 percent of all other investing plants. These computations were done for both overall investment in equipment (excluding structures) and for IT equipment, giving a combined seven investment intensity categories.Businesses undergoing an outcome of high investment intensity can be thought of as actively changing their technologies. The market will reward some of these and penalize other s. The crux of the analysis summarized in go in 5. 1 is to first compare the performance of plants across the various investment intensity groups to a service line of firms with no investment within each country (i. e. , the bars for the listed investment intensity categories in the figure represent the percent difference from the omitted zero investment category for each country).Then the researchers compared the within country differences across the United States and Germany to see in which country the reward for experimentation (as deliberate by high investment episodes) is highest. display panel A shows that U. S. businesses that invest heavily, both overall and in IT, are much more productive than those that invest little or none at all. The same holds true for Germany, but the productivity premium is much higher in the United States. Panel B shows that U. S. businesses that invest heavily (i. e. are experimenting with new technologies) have more varied productivity outcomes as measured by the example warp than do firms that invest little or not at all. This is not the case in Germany. In fact, the German data show that firms that invest intensively have less varied productivity outcomes. This is consistent with the persuasion that the U. S. policy and institutional environment is more conducive to market experimentation. These results should be viewed with caution as they relate to only two countries and there are many factors the researchers do not control for. 8 J.Haltiwanger, R. Jarmin, and T. Schank, Productivity, Investment in ICT and Market Experimentation Micro Evidence from Germany and the U. S. , Center for Economic Studies Working Paper CES-03-06, U. S. Bureau of the Census, Washington, DC (2003). 67 DIGITAL ECONOMY 2003 Figure 5. 1. Differences in Productivity Outcomes between Germany and the United States Panel A U. S. Firms spend Heavily in IT and Other Capital progress to steeper Productivity Premiums 100% % Difference in Mean Produ ctivity Relative to radical with No Investment U. S. 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Low / 0Germany last / 0 Low / Low Low / High High / Low High / High Investment Intensity (Equipment / IT) Panel B U. S. Firms Investing Heavily in IT and Other Capital Experience More Varied Productivity Outcomes 50% U. S. % Difference in Standard aberration of Productivity Relative to Group with No Investment Germany 40% 30% 20% 10% 0% -10% -20% -30% -40% Low / 0 High / 0 Low / Low Low / High High / Low High / High Investment Intensity (Equipment / IT) Note Differences are in logs and are shown relative to a reference group of firm with zero total investment.Source Haltiwanger, Jarmin and Schank 2003. DOES IT MATTER HOW IT IS USED? Businesses in the United States have utilize IT for fifty years. Originally, firms that used IT may have had advantage over competitors who did not. alone today, simply investing in IT may no longer be enough. The question for economic performance is no longer whether IT is used, but how it is used. 68 DIGITAL ECONOMY 2003 Figure 5. 2. Computer Networks Were Common in U. S. Manufacturing Industries in 1999, But Sophisticated Network Software Was Not 100 90 80 70 60Plants with Networks Employment at Plants with Networks Plants with Fully incorporated Enterprise Resource Planning Software Percent 50 40 30 20 10 0 G ts ts s s s s s o t es ry ts s al em ic d ru bb er pr od l ts ill re ts uc rie ou en al ill ts ts rie uc te pe uc cc ts N ne uc uc RI iti pm od ne ba tm od st pa uc uc et TU od od Pa la st od tiv hi od od du du pr re lla ac til uc pr to Ap pr ui ac pr pr od m e FA C od in ce an Te x ar eq al od M W oo 32 al d an d im is al c d s 5 Ch pr in pr d d d 2 pr y uc m uc ts d s r pr lie ni Fo er te od 31 U et te n od M co an d t, tio tro e Pr AN in la m al la 3 e go en go 33 til m re ra rta 31 ec ed M m Te x le 31 ve nd 1 9 1 1 d lic el 33 e d re 32 Pl as tic s 3 32 po ra 33 ab an an bl AL nd qu ns ra ur he et br re g du ra le T r a itu 31 m tin at D on Le ca te on rn 31 in pu tri N 6 Fu 2 Pr N Pe tro Fa 2 le 4 um Be al ic ec 33 m 33 6 31 Co El 7 3 4 32 4 33 33 5 33 NAICS 3-Digit Industry Source Atrostic, B. K. and J. Gates, 2001, U. S. Productivity and Electronic Business Processes in Manufacturing, CES-WP-01-11, Center for Economic Studies, U. S. Bureau of the Census, Washington, DC.New data from the 1999 Computer Network Use Supplement (CNUS) to the 1999 Annual Survey of Manufactures (ASM) are beginning to be used to model how manufacturing plants use computer networks in the United States. Respondents answers to questions about processes can be linked to the information the same respondents reported on regular ASM survey forms, such as the value of shipments, employment, and product build shipments. Figure 5. 2 presents researchers estimates of the scattering of computer networks. The research finds that computer networks are widely diffused within manufacturing, with networks at about half of all plants.The share of employment at plants with networks is almost identical in enduring and non-durable manufacturing. Use of networks varies a great deal within those sub-sectors the share of plants with networks ranges from lows of about 30 percent to highs of about 70 percent. The CNUS also provides new information about some aspects of how plants use computer networks. Figure 5. 2 reports estimates of the diffusion of fully integrated enterprise resource planning software (FIERP) that is, the kind of software that links different kinds of applications (such as inventory, tracking, and supportroll) within and across businesses.Plants in all manufacturing industries use this complex software. However, FEIRP software remains relatively archaic compared to computer networks. While about half of all manufacturing plants have networks, fewer than 10 percent have this kind of software. 69 32 32 32 7 6 an at ip L 5 s DIGITAL ECONOMY 2003 Initial research finds that computer networks have a positive and significant effect on plants labor productivity. After accounting for multiple factors of production and plant characteristics, productivity is about five percent higher in plants with networks. When economic characteristics in prior periods and investment in computers are also accounted for, there continues to be a positive and statistically significant relationship between computer networks and U. S. manufacturing plant productivity. 10 These initial findings for the United States are consistent with findings for other countries. Recent research for Canada, the Netherlands, and the United Kingdom, for example, all find positive relationships between using computer networks and productivity. 11 Research for Japan finds that computer expenditures and computer networks both change productivity between 1990 and 2001.In more recent years, the effects are larger, but they also vary much more among industries. 12 Some micro data research for the United Stat es during the nineties suggests that IT ask to be used together with worker training and revised workplace practices to yield productivity gains. These findings are based on data giveing detailed information about the use of computers in the workplace. They also contain information rarely available in other sources on the employers management and worker training policies. 3 Research for Australia and Canada, previously cited, also finds that returns to IT are intertwined with the use of R&D, innovation, and changes in workplace practices and organization. This line of research suggests that IT is important, but that it makes its impact when accompanied by changes in other factors and practices. IS THE IMPACT OF IT THE equal FOR ALL KINDS OF IT, EVERYWHERE? EVIDENCE FROM STUDIES OF MARKET STRUCTURE IT was widely pass judgment to alter the structure of markets. The direction, however, was unclear.Lower information costs superpower make it easier for smaller businesses to collect , analyze, and use information and so allow them to enter far-flung markets or compete more effectively with larger firms. At the same time, the lower information costs might make it easier for larger businesses 9 Atrostic and Nguyen (2002). 10 Atrostic and Nguyen, The Impact Of Computer Investment And Computer Network Use On Productivity, paper presented NBER-CRIW Conference on Hard-to-Measure Goods and Services Essays in reminiscence of Zvi Griliches, Washington, DC (September 2003). J. Baldwin, and D.Sabourin, Impact of the Adoption of Advanced Information and Communication Technologies on Firm Performance in the Canadian Manufacturing Sector, Research Paper Series, 174, analytical Studies Branch, Statistics Canada (October 2001) present findings for Canada. E. Bartlesman, G. van Leeuwen, and H. R. Nieuwenhuijsen, Advanced Manufacturing Technology and Firm Performance in the Netherlands, Netherlands Official Statistics, Vol. 11 (Autumn 1996) present findings for the Netherlands . C. Criscuolo and K. Waldron, e-Commerce use and firm productivity, Economic Trends (November 2003) present findings for the United Kingdom.K. Motohashi, Firm level analysis of information network use and productivity in Japan, presented at the convocation on Comparative Analysis of Enterprise (micro) Data, London (September 2003). S. Black, and L. Lynch, How to Compete The Impact of Workplace Practices and Information Technology on Productivity, Review of Economics and Statistics, Vol. 83 No. 3 (August 2001) and D. Neumark and P. Cappelli, Do High Performance Work Practices Improve Establishment-Level Outcomes? Industrial and Labor dealings Review (July 2001). 13 12 11 70 DIGITAL ECONOMY 2003 to retain a competitive advantage.Similarly, use of the profit might make it easier for consumers to compare prices, and so lead to a reduction in prices for products interchange on-line or in bricks and mortar establishments. At the same time, a firm building an on-line sales-based busin ess may incur costs that brick and mortar businesses might not, such as cost associated with having inventories available for fast delivery anywhere in the United States (or the world). The issues are scarcely settled. In this section, selected examples from micro data research illustrate ITs multifaceted constitution and complex economic effects.hauling A series of studies make use of public-use motortruck-level data from the Census Vehicle account and Use Surveys to examine how IT has affected the hauling industry. Each of these studies indicates the importance of knowing not just that IT is used, but also the details of the IT and how it is used. These studies examine the impact of two classes of on-board computers (OBCs). Standard OBCs function as trucks black boxes, recording how drivers operate the trucks. These enable dispatchers to verify how truck drivers drive.Advanced OBCs also contain capabilities that, among other things, allow dispatchers to determine where trucks are in real time and communicate schedule changes to drivers while drivers are out on the road. These advanced capabilities help dispatchers make and implement disclose scheduling decisions, and help them avoid situations where trucks and drivers are idle, awaiting their next haul. One of these studies assesses OBCs impact on productivity by estimating how much they have emergenced individual trucks consumption rate, as measured by their loaded miles during the time they are in service. 4 It finds that advanced OBCs have increased truck utilization by 13 percent among trucks that adopt them overall, this effect implies a terzetto percent increase in capacity utilization industry-wide, which translates to about $16 billion in annual benefits. The vast majority of this increase comes from trucks in the for-hire, long-haul segment of the industry, and most of these returns only began to accrue years after truckage firms first began to adopt OBCs. In contrast, the study finds no ev idence that standard OBCs have led to increased truck utilization.Combined, these results indicate not just the magnitude of ITs impact on productivity in the industry but also its nature and timing. IT adoption has led to large productivity gains due to advanced OBCs real-time communication capabilities, which enable trucking firms to view that trucks operating far from their base are on the road and loaded. These gains, however, come forth to have lagged adoption by several years. The other two studies examine how OBCs have affected how the industry is setd. One study investigates how OBCs affect whether shippers use internal fleets or for-hire carriers to ship goods. 5 This study finds that the different classes of OBCs have different effects on this T. Hubbard, 2003, Information, Decisions, and Productivity On-Board Computers and Capacity Utilization in Trucking, American Economic Review, September. G. bread maker and T. Hubbard, Make Versus Buy in Trucking Asset Ownership, J ob Design, and Information, American Economic Review, Vol. 93 No. 3 (June 2003). 15 14 71 DIGITAL ECONOMY 2003 decision. The diffusion of standard OBCs has tended to increase shippers use of internal fleets, but the diffusion of advanced OBCs has tended to increase their use of for-hire fleets.This implies that IT-enabled improvements in observeing drivers have led shippers to integrate more into trucking, but IT-enabled improvements in scheduling capabilities have led to more contracting-out of trucking. This magisterial difference indicates that whether IT tends to lead to larger, more integrated firms or to smaller, more focused firms depends critically on the new capabilities the IT provides. The second of the two organizational studies is similar it investigates how OBCs have affected whether drivers own the trucks they operate. 6 Traditionally, owner-operators have been an important part of the industry. An advantage associated with owner-operators is that they have strong i ncentives to drive in ways that remain their trucks value these incentives have traditionally been far weaker for company drivers, who do not own their trucks. This study shows that OBC diffusion has diminished the use of owner-operators. By allowing firms to monitor how drivers drive, OBCs have eliminated an important incentive advantage of owneroperators, and have led trucking firms to subcontract fewer hauls out to such individuals.Residential Real terra firma The earnings vastly increases the amount of information on caparison vacancies that is readily available to consumers. Previous research had shown that high costs of information and lack of regain to information limited housing searches. The best information available to consumers tended to be for properties near their current location. In addition, research found that information intermediaries such as real estate agents influenced the options that consumers considered. The increased information that the Internet mak es available to consumers potentially reduces or eliminates those limits.Consumers can readily learn about properties far from their current locations, and can do so relatively today (there still may be some influence exerted in how sack up sites are set up, for example, and consumers may not immediately, or ever, get to the best web site for their needs). Two recent studies use micro data to assess the effect of using the Internet to search for housing. In these cases, micro data from the public-use stream Population Survey provide basic information on what kinds of consumers use the Internet to search for housing. However, the CPS does not have information about the homes that Internet users purchased.To address questions about the kinds of homes purchased, the researchers surveyed a sample of recent home purchasers in a county in North Carolina. Characteristics of buyers who used the Internet as a source of information about housing vacancies were generally similar to those of buyers who only used conventional information sources, chuck out that Internet users were younger. The researchers conclude that using the Internet to shop for housing does not seem to effect geographic search patterns, or to lead consumers to sacrifice lower prices for comparable homes.Although using the Internet might be anticipate to decrease the number of homes buyers visited, because they would have more information about the houses and neighborhoods, the studies G. Baker and T. Hubbard, Contractibility and Asset Ownership On-Board Computers and governance in U. S. Trucking, http//gsbwww. uchicago. edu/fac/thomas. hubbard/research/papers/paper_424. pdf (April 2003). 16 72 DIGITAL ECONOMY 2003 preferably find that homebuyers who use the Internet as an information source make personal visits to more houses. 7 The Impact of IT on Wages Do knowledge workers receive salary premiums because they use computers? Does the use of IT increase the demand for more- better workers? Does the growing use of computers by workers in some sectors of the economy explain shifts in the distribution of struggle? Initial micro data research answered the first question with a resounding yes. One early study, for example, found that the pay of workers who used computers was 10 to 15 percent higher than the pay of similar workers who did not. 8 However, more recent studies that make use of more detailed information about workers and frolics over multiple periods find that the answer is more nuanced. IT potentially affects many aspects of the performance of businesses. It also may affect the salary, and other characteristics of jobs. Asking how IT affects absorbs is actually asking two questions. The first question is whether jobs where workers use computers pay higher wages. If the answer is yes, the second question is why. As with IT use in businesses, determining cause and effect of IT use on wages is hard.The jobs might pay higher wages because they require high acqui sition levels. Some IT-using jobs, such as computer programmers and systems analysts, clearly require high skill levels, as do jobs such as architects who use computer-assisted design programs. However, computers appear throughout many workplaces. Workers may use computerized diagnostic equipment and programmable logic controllers, for example, in production applications. business leader and service workers may use word processors and spreadsheets, e-mail, computerized account systems, and so forth.Such jobs might pay higher wages if using a computer makes a worker with a given skill level more productive, but they generally do not require the workers to know much about principles of programming, or system or network design. Finally, the use of IT may allow computers to substitute for low- proficient workers performing repetitive tasks. Micro data studies in the United States, Europe, and Canada all find that workers using computers at work have much higher wages than workers who do not. The difference typically is on the order of 10 to 20 percent.However, these studies all used data from a single period, and many of them lack information about other aspects of the job, the worker, and the employer. This makes it hard to determine whether the workers have higher wages because they use a computer, or because important unobserved characteristics of the employer (is it highly productive careless(predicate) of the use of computers? ) or the worker (is the worker already highly skilled before using a computer? ) may affect managers decisions on investing in computers and R. Palm and M.Danis, Residential Mobility The Impacts of Web-Based Information on the Search Process and Spatial Housing Choice Patterns, Urban Geography, Vol. 22, No. 7 (2001) and R. Palm and M. Danis, The Internet and Home Purchase, Journal of Economic and Social Geography, Vol. 93, No. 5 (2002). A. Krueger, How Computers Have Changed the Wage Structure Evidence from Microdata, 19841989, Quart erly Journal of Economics, Vol. 108 No. 1 (February 1993). 18 17 73 DIGITAL ECONOMY 2003 assigning them to which employees. A new study reviewing recent research on the impact of IT on employment, skills, and wages concludes that the story is complex. 9 Studies find that having information on plant characteristics and work practices matters. For example, a study finding that workers using computers in Germany had higher wages than workers who did not also found that a similar wage differential accrued to workers using telephones or pencils, or who worked sitting down. 20 The implication is that the wage differential really reflected the fact that workers using computers, telephones, or pencils, or who work sitting down, receive higher wages because they have higher skills.This research suggests that IT is associated with substantial wage differentials, but does not cause them. Studies for France and Canada find similar wage differentials. 21 Researchers using French and Canadian mic ro data also have matched sets of data on employers and workers in those countries, and have two or more years of data. Studies using these matched data all find that substantial cross-section returns to computer use fall sharply when they make use of information about changes in both the worker and employer characteristics.Estimates differ by country and study, but the final differentials are modest, 1 to 4 percent. 22 These studies also find that the relatively modest wage differential associated with computer use varies markedly across occupations and among workers with different levels of education. For example, a study for Canada finds that more highly educated workers, white-collar workers, and those adopting the computer for scientific applications receive higher than average wage premiums, while other workers do not receive wage premiums when they jump out using computers on the job. The reasons for such differences remain unresolved.It may be more dear(p) to teach some gr oups of workers to use computers, or groups may differ in the proportion of computer training costs that they share with the employer (with lower employer shares resulting in higher wages). The researchers find that controlling for training increases the small or zero wage premiums they otherwise find for many low-skilled groups. They speculate that, if permit data were available to test for long-run effects, controlling for training and other worker characteristics might show positive wage differentials for most workers using computers. 3 Some detailed case studies (studies of specific businesses, usually anonymous) suggest another reason for differences in the wage differential associated with using computers at work. One M. Handel, Implications of Information Technology for Employment, Skills, and Wages A Review of Recent Research, SRI International, SRI Project Number P10168, Final Report (July 2003). J. DiNardo and J. Pischke, The Returns to Computer Use Revisited Have Pencils Changed the Wage Structure Too? The Quarterly Journal of Economics, Vol. 112 No. 1 (February 1997). H. Entorf, M. Gollac, and F.Kramarz, New Technologies, Wages, and Worker Selection. Journal of Labor Economics (1999), and H. Entorf, and F. Kramarz, Does Unmeasured readiness Explain the Higher Wages of New Technology Workers? European Economic Review, Vol. 41 (1997) and C. Zoghi and S. Pabilonia, Which Workers Gain from Computer Use? Paper presented at NBER summer Meetings (July 2003). 22 23 21 20 19 E. g. , Entorf and Kramarz 1997. C. Zoghi and S. Pabilonia 2003. 74 DIGITAL ECONOMY 2003 case study examined the effect of introducing computers into the operations of a pecuniary organization.For some occupations, the case study found that computers substitute for the routine work that individuals previously performed, reducing the need for such workers. In other occupations, however, computers appear to take on routine tasks and free workers to perform more complex, higher ski lled, problem-solving activities. 24 If IT also allows the business to alter the way it works and organize itself more productively, it may raise the skill requirements for all workers in the business, even if they do not directly use computers.Insights from the International Micro Data Initiative A wave of new literature in plant- or firm-level research on the effects of IT has been conducted in countries participating in the OECD. 25 (See box 5. 1. ) As with research using U. S. micro data, the micro data research conducted in other countries also find links between IT and productivity. Where information on computer networks is available, or other measures of how computers are used, the research again suggests that it is not just having IT, but how IT is used that effects economic performance measures such as productivity.Two kinds of studies are being undertaken. Some studies base their research on new data on IT for a single country. They make use of as much information as they can, and choose empirical techniques best suited to their data. Studies such as these land important insights, particularly when one country has information that other countries do not, or researchers are able to use techniques that help ensure that the measured effects indeed are due to IT. However, this strength also makes it hard to compare such estimates across countries.Studies from individual OECD countries find that IT has an impact on productivity and economic performance. Significant effects of IT on productivity are found in the service sector in Germany. 26 Recent research for France finds that one specific kind of network, the Internet, is associated with productivity gains, but other kinds of networks, which have been in use much longer, are not. 27 Canadian research finds that adopting IT is associated with growth in both productivity and market share. 8 Use of computers in Australia also is associated with productivity growth, with effects that vary across industries and are intertwined with other factors, such as the skill of a business work force, its organization and re-organization, and its innovativeness. 29 24 D. Autor, F. Levy and R. Murnane, Upstairs, Downstairs Computer-Skill Complementarity and Computer-Labor interchange on Two Floors of a Large Bank, Industrial & Labor Relations Review 55(3) (2002). Research to date is summarized in D.Pilat, ICT and Economic Growth Evidence from OECD Countries, Industries, and Firms (Paris OECD, 2003). T. Hempell, Whats Spurious, Whats Real? touchstone the Productivity Impacts of ICT at the Firm-Level, reciprocation Paper 02-42, Centre for European Economic Research (Zentrum fur Europaische Wirtschaftsforschung GmbH ZEW, 2002), file transfer protocol//ftp. zew. de/pub/zew-docs/dp/dp0242. pdf. B. Crepon, T. Heckel, and N. Riedinger, http//www. nber. org/CRIW/papers/crepon. pdf, Paper presented at R&D, Education, and Productivity, NBER CRIW conference in honor of Zvi Griliches (Paris August 2003). 8 29 27 26 25 J. Baldwin and D. Sabourin 2001. G. Gretton, J. Gali, and D. Parham, Uptake and impacts of ICTs in the Australian economy, paper presented at OECD, Paris, celestial latitude 2002. 75 DIGITAL ECONOMY 2003 Another group of studies tries to use as many variables and analytical techniques as possible that are similar to those used by researchers in a few other countries. 30 This arise may exclude some variables and some analytical techniques, if researchers in several countries cannot use them.On the other hand, this kind of coordination makes it more likely that similar empirical findings are actually due to IT, and that differences in empirical findings are due to differences in economic conditions and other factors among countries. An example is a group of researchers conducting parallel analyses for the United States, Denmark, and Japan. 31 Preliminary findings are that IT is positively related to productivity in all three countries, but that the relationship depends o n the type of IT used, the sector, and time period.Early results for Denmark show a significant correlation coefficient between several measures of the firms performance and use of the Internet, but not for other uses of IT. For Japan, productivity levels are consistently higher for firms using IT networks. However, growth in labor productivity varies by type of network and how the network is used, and the effect of Internet use is higher for retail switch over firms than for manufacturing firms. For U. S. manufacturing plants, there is a strong relationship between use of computer networks and labor productivity. Better Micro Data Research Requires Better Micro DataBecause the micro data are typically collected for other purposes, such as constructing key economic indicators, we almost of all time find that they lack some (often, much) of the information needed to address questions such those about the pervasiveness of IT and its effect. These gaps simply do not allow us to draw f irm conclusions about the effect of IT. For example, research exploring the micro-level link between IT and economic performance may not always be able to separate the determination of IT from other related but unobserved characteristics of the plant.Well-managed plants may use IT as one of many tools to achieve performance goals. If we have information about IT, but not about management practices, the research may specify performance effects to IT that really are due to good management. Estimating plant-level relationships among computers, computer networks, and productivity also is hard to do with existing data because many of the most important conceptswhat a business produces (output), and all the factors it uses to make its product (such as labor, capital, energy, etc. known as inputs), as well as IT itselfare difficult to define, and data based on these concepts are hard to collect. 32 Continuing research on these concepts leads to improve- For example, researchers in severa l countries are using the approach taken by U. S. researchers (Atrostic and Nguyen 2002), and using its findings as the bench mark against which they are comparing research findings using their own countries data. B. K. Atrostic, P. Boegh-Nielsen, K. Motohashi, and S. Nguyen, Information Technology, Productivity, and Growth in Enterprises Evidence from New International Micro Data, Lacutalite economique (forthcoming 2004).A large literature lays out major data gaps in estimating the impact of information technology on economic performance. For example, conferences conducted by the NBER Conference on Research in Income and Wealth (CRIW) addressing capital and labor measurement over the last 20 years include D. Usher, The Measurement of Capital (NBER CRIW sight 45 (Chicago University Press, 1980)) J. Triplett, The Measurement of Labor Cost (NBER CRIW Volume 48 (Chicago University Press, 1983)) and C. Corrado, J. Haltiwanger, and D. Sichel, Measuring Capital in the New 32 31 0 76 DIGI TAL ECONOMY 2003 ments in what statistical agencies collect, but a dynamic and evolving economy continually presents new challenges. Even when concepts are well defined, it is costly for statistical agencies to collect data and for respondents to provide the requested information. As a result, some key information needed for analysis may not be collected often or at all. Examples include information such as the number of computers and computer networks that businesses have, how they use them, and how much businesses invest in computers and other IT.The divergent findings in the resulting empirical literature on the effects of IT are likely related to these data gaps, and to differences in the techniques researchers use to try to deal with them. 33 One way to improve the micro data available for research would be by better incorporate aggregate economic indicators and their underlying micro data. It currently is not always easy to reconcile movements in the aggregate statistics with changes observed in the micro data. Aggregate indicators often are constructed from multiple micro data sources, and different sources of data for any concept (such as employment or payroll) may disagree.Collecting more of the data underlying aggregate statistics in ways that enrich their value as micro data, such as using common sampling frames and keeping information that allows linkage of same economic unit over time and across surveys, would improve both the micro data and our ability to understand changes in the aggregate economic indicators. finish Micro data research conducted in the United States and in OECD countries shows that IT is related to economic performance and productivity. Careful research also shows that the relationships are complex.IT emerges as a multifaceted factor. The kind of IT that is used and how it is used appear to matter in many (but not all) settings, including the ownership structure of trucking markets, the relative dynamism of retailing, and the relative risk taking and innovativeness of manufacturing sectors across countries. At the same time, the use of IT alone does not appear to be enough to affect economic performance. When researchers have information about the characteristics of businesses, workers, jobs, and markets, they find that IT appears to work instead in tandem with those factors.Economy (NBER CRIW Volume 65 (Chicago University Press, forthcoming)). A series of meetings of international experts, known as the Canberra Group, addressed capital measurement issues during the late 1990s (http// unstats. un. org/unsd/methods/citygroup/capitalstock. htm). An excellent manual describing how to calculate productivity habituated considerable text to issues in measuring capital can be found in P. Schreyer, Measuring Productivity Measurement of Aggregate and Industry-Level Productivity GrowthOECD Manual (Paris OECD 2001).Measuring intangible capital, potentially important in both IT and non-IT capital, received much at tention recently (see for example B. Lev, Intangibles Management, Measurement, and coverage (Brookings Institution Press 2001)). 33 See, for example, Dedrick et al. (2003) D. Pilat, 2003 B. K. Atrostic, J. Gates, and R. Jarmin, 2000, Measuring the Electronic Economy Current Status and Next Steps, Working Paper CES-WP-00-10, Center for Economic Studies, U. S. Bureau of the Census, Washington DC and J. Haltiwanger, and R.Jarmin (2000), Measuring the digital Economy, in E. Byrnjolfsson and B. Kahin (eds. ), Understanding the Digital Economy (MIT Press 2000). 77 DIGITAL ECONOMY 2003 Separating out the effect of IT remains difficult because the analysis requires detailed information, and requires it for multiple periods. However, such detailed and repeated information is rare. Most business micro data contain only the information needed to calculate important economic indicators. The micro data are most sparse for the sectors outside manufacturingthe most IT-intensive sectors.More defin itive research on the impact of IT requires that producing micro data sets becomes a statistical agency priority. 78 DIGITAL ECONOMY 2003 Appendix 5. A. Conducting Micro Data Research on the Impact of IT THE CENTER FOR ECONOMIC STUDIES, U. S. enumerate BUREAU The Center for Economic Studies (CES) is a research unit of the Office of the Chief Economist, U. S. Bureau of the Census, established to encourage and support the analytic needs of researchers and decision makers throughout government, academia, and business. CES currently operates eight Research Data Centers (RDCs) throughout the United States.RDCs offer qualified researchers restricted access to confidential economic data collected by the Census Bureau in its surveys and censuses. CES and the RDCs conduct, facilitate, and support research using micro data to increase the utility and quality of Census Bureau data products. The best way for the Census Bureau to assess the quality of the data it collects, edits, and tabulates is for knowledgeable researchers to use micro records in rigorous analyses. Each micro record results from dozens of decisions about definitions, classifications, mark rocedures, processing rules, editing rules, disclosure rules, and so on. Analyses test the validity of all these decisions and uncover the datas strengths and weaknesses. Research projects at CES and its RDCs are examining how facets of the electronic economy affect productivity, growth, business organization, and other aspects of business performance using both new data collected specifically to provide new information about IT, and existing data. Projects using existing Census Bureau micro data on businesses include McGuckin et al. 998 Dunne, Foster, Haltiwanger and Troske, 2000 Stolarick 1999 and Doms, Jarmin, and Klimek, 2002). Research making use of the new 1999 supplement to the Annual Survey of Manufactures linked to existing Census Bureau micro data include Atrostic and Gates 2001 Atrostic and Nguyen 2002 Hal tiwanger, Jarmin, and Schank 2002 and Bartelsman et al. 2002. Research findings from many of these projects are discussed in this chapter. The research also helps the Census Bureau assess what current data collections can say about the electronic economy so that we can more efficiently allocate resources to any new measurement activities.More information about CES, RDCs, requirements for access to data, and examples of research produced at the RDCs is at http//www. ces. census. gov/ces. php/home. DATA SOURCES AT CES Researchers at CES and the RDCs built, and use, a longitudinal data set linking manufacturing plants over time. The data are based on surveys and economic censuses, and contain detailed data on shipments and factors used to produce them, such as materials and labor, as well as characteristics of the plant, such as whether it exports. Recent CES research broadens the range of available micro data beyond manufacturing.A new micro data set, the Longitudinal Business Databas e, currently contains the foundation of all U. S. business establishments with paid employees from 1976 to present. It allows researchers to examine entry and exit, gross job flows, and changes in the structure of the U. S. economy. The LBD can be used alone or in conjunction with other Census Bureau surveys at the establishment 79 DIGITAL ECONOMY 2003 and firm level. In addition, micro data from surveys and censuses of the retail, wholesale, and some service sectors is now becoming available.The National Employer Survey, conducted by the Census Bureau for the National Center on the Educational Quality of the Workforce, collects detailed information about work practices, worker training, and the use of computers. Restricted access to confidential data from the survey is available to qualified researchers through the RDCs. Information about the National Employer Survey can be found at http//www. census. gov/econ/overview/mu2400. html. PUBLIC-USE DATA This chapter also refers to rese arch conducted using two other sets of micro data collected by the Census Bureau.The Current Population Survey (CPS) is a survey of households that is collected by the Census Bureau for the Bureau of Labor Statistics. The CPS periodically collects information about peoples use of computers at work and at home. More information can be found at http//www. census. gov/population/www/socdemo/computer. html. The Truck Inventory and Use Surveys collect information about on-board trip computers and electronic fomite management systems as part of the Census of Transportation. Information about the Census of Transportation can be found at http//www. census. gov/econ/www/tasmenu. html. 80