ONLINE APPENDIX APPENDIX A. DESCRIPTION OF U.S. NON-FARM PRIVATE SECTORS AND INDUSTRIES

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ONLINE APPENDIX APPENDIX A. DESCRIPTION OF U.S. NON-FARM PRIVATE SECTORS AND INDUSTRIES 1997 NAICS Code Sector and Industry Title IT Intensity 1 IT Intensity 2 11 Agriculture, forestry, fishing, and hunting - - 113 115 Forestry, fishing, and related activities L L 21 Mining - - 211 Oil and gas extraction H H 212 Mining, except oil and gas H H 213 Support activities for mining H H 22 Utilities H H 23 Construction L L 31 33 Manufacturing - - 311, 312 Food and beverage and tobacco products L L 313, 314 Textile mills and textile product mills L L 315, 316 Apparel and leather and allied products L L 321 Wood products L L 322 Paper products L L 323 Printing and related support activities L L 324 Petroleum and coal products L H 325 Chemical products H H 326 Plastics and rubber products L L 327 Nonmetallic mineral products L L 331 Primary metals L L 332 Fabricated metal products L L 333 Machinery H H 334 Computer and electronic products H H 335 Electrical equipment, appliances, and components L L 3361-3363 Motor vehicles, bodies and trailers, and parts L L 3364-3366, 3369 Other transportation equipment H H 337 Furniture and related products L L 339 Miscellaneous manufacturing L L 42 Wholesale trade H H 44, 45 Retail trade L L 48, 49 Transportation and warehousing - - 481 Air transportation H H 482 Rail transportation H H 483 Water transportation H H 484 Truck transportation L L 485 Transit and ground passenger transportation H H 486 Pipeline transportation H H 487, 488, 492 Other transportation and support activities H L 493 Warehousing and storage L L 51 Information - - 511 Publishing industries (includes software) H H 512 Motion picture and sound recording industries L H 513 Broadcasting and telecommunications H H 1

IT In- IT Intensity 1 tensity 2 1997 NAICS Code Sector and Industry Title 514 Information and data processing services H H 52, 53 Finance, insurance, real estate, rental, and leasing - - 521, 522 Federal Reserve banks, credit intermediation, and related activities H H 523 Securities, commodity contracts, and investments H H 524 Insurance carriers and related activities H H 525 Funds, trusts, and other financial vehicles L H 531 Real estate L L 532, 533 Rental and leasing services and lessors of intangible assets H H 54 56 Professional and business services - - 5411 Legal services L L 5415 Computer systems design and related services H H 5412-5414, 5416-5419 Miscellaneous professional, scientific, and technical services H H 55 Management of companies and enterprises H H 561 Administrative and support services H L 562 Waste management and remediation services H H 61, 62 Educational services, health care, and social assistance - - 61 Educational services H L 621 Ambulatory health care services H H 622, 623 Hospitals and nursing and residential care facilities H H 624 Social assistance L L 71, 72 Arts, entertainment, recreation, accommodation, and food services - - 711, 712 Performing arts, spectator sports, museums, and related activities L L 713 Amusements, gambling, and recreation industries L L 721 Accommodation L L 722 Food services and drinking places L L 81 Other services, except government L L 2

APPENDIX B. CORRELATIONS AND COLLINEARITY DIAGNOSTICS Table B1. Correlations among the Independent Variables Non-IT Capital IT Capital Labor Non-IT Capital 1.000 IT Capital 0.367 1.000 Labor 0.343 0.289 1.000 Non-IT Services Intermediate Inputs Non-IT Services Intermediate Inputs 0.398 0.416 0.544 1.000 IT Outsourcing IT Outsourcing 0.154 0.463 0.522 0.515 1.000 Table B2. Collinearity Diagnostics VIF SQRT(VIF) Tolerance R 2 Non-IT Capital 1.32 1.15 0.756 0.244 IT Capital 1.46 1.21 0.686 0.314 Labor 1.70 1.30 0.589 0.411 Non-IT Services 1.83 1.35 0.548 0.452 Intermediate Inputs IT Outsourcing 1.75 1.32 0.570 0.430 Note: Mean VIF = 1.61 APPENDIX C. COMPARISON OF OUR COEFFICIENT ESTIMATES WITH THOSE FROM PREVIOUS STUDIES STUDIES LEVEL OF ANALYSIS IT CAPITAL NON-IT CAPITAL LABOR INTERMEDIATE INPUTS Our Production Function Industry 0.043 0.059 0.227 0.631 Lichtenberg (1995) Firm 0.10 0.333 0.507 - Computerworld Lichtenberg (1995) Firm 0.122 0.390 0.489 - Informationweek Brynjolfsson and Hitt Firm 0.0522 0.242 0.472 - (1995) Brynjolfsson and Hitt Firm 0.0169 0.0608 0.883 - (1996) Dewan and Min (1997) Firm 0.104 0.281 0.601 - Dewan and Kraemer County 0.051 0.176 0.955 - (2000) Cheng and Nault (2007) Industry 0.076 0.059 0.257 0.653 Note: Adapted from Cheng and Nault (2007). 3

APPENDIX D. ESTIMATION RESULTS WITH IT VENDOR INDUSTRY DUMMY VARIABLE PARAMETER FGLS OLS-PCSE WITH DUMMY WITHOUT DUMMY WITH DUMMY WITHOUT DUMMY Non-IT capital.076*** 0.059*** (0.011).075*** 0.058*** (0.012) Labor.234*** 0.227*** (0.012).219*** (.010) 0.212*** (0.010) IT capital.035*** (.009) 0.043*** (0.009).019* 0.029*** (0.011) 0.649*** (0.029) Non-IT services intermediate inputs.634*** (.015) 0.631***.659*** IT outsourcing.022** 0.034***.027** (0.010) IT vendor industry dummy.146**.160*** -- (.059) (.050) -- N 540 540 540 540 0.042*** (0.013) Notes: IT vendor industry dummy = 1 for three IT vendor industries (NAICS 334: Computer and electronic products, NAICS 514: Information and data processing services, and NAICS 5415: Computer systems design and related services). Signif.: *** = p < 0.01, ** = p < 0.05, * = p < 0.10. Standard errors are in parentheses. APPENDIX E. ESTIMATION RESULTS WITH INTERACTION EFFECTS BETWEEN IT INTENSITY AND IT OUTSOURCING PARAMETER IT INTENSITY MEASURE 1: IT CAPITAL / OUT- PUT Non-IT capital.065*** Labor.220*** IT capital.040*** (.009) Non-IT services intermediate inputs.632*** IT INTENSITY MEASURE 2: IT CAPITAL / LA- BOR.066***.218***.033*** (.009).648*** (.015) (.015) IT outsourcing.027**.012 IT outsourcing IT Intensity.023*.042*** N 540 540 Notes: IT Intensity is a dummy variable, which equals 1 for high IT intensity industries and 0 for low IT intensity industries. Signif.: *** = p < 0.01, ** = p < 0.05, * = p < 0.10. Standard errors are in parentheses. 4

APPENDIX F. ADDITIONAL FGLS AND OLS-PCSE ESTIMATION RESULTS Table F1. Production Function IT Intensity Split: FGLS PSAR1 Non-IT capital 0.001 (0.016) 0.116 *** 0.066 *** (0.024) 0.084 *** IT capital 0.166 *** (0.020) 0.087 *** 0.086 *** 0.079 *** Labor 0.248 *** 0.195 *** (0.021) 0.183 *** 0.183 *** Non-IT services intermediate inputs 0.471 *** (0.030) 0.525 *** 0.611 *** 0.509 *** (0.024) IT outsourcing 0.076 *** 0.034 * 0.040 *** (0.011) -0.022 Table F2. Production Function IT Intensity Split: PCSE AR1 Non-IT capital 0.051 *** 0.178 *** (0.043) 0.053 *** 0.014 (0.026) IT capital 0.112 *** 0.119 *** (0.046) 0.088 *** 0.106 *** (0.026) Labor 0.232 *** (0.013) 0.202 *** 0.158 *** 0.167 *** Non-IT services intermediate inputs 0.493 *** (0.040) 0.545 *** (0.027) 0.579 *** (0.038) 0.566 *** IT outsourcing 0.103 *** -0.0004 (0.028) 0.068 *** 0.022 Table F3. Production Function IT Intensity Split: PCSE PSAR1 Non-IT capital 0.042 (0.040) 0.107 *** (0.034) 0.123 *** (0.031) 0.095 *** IT capital 0.174 *** (0.034) 0.105 *** (0.031) 0.113 *** 0.091 *** Labor 0.200 *** 0.164 *** 0.161 *** (0.016) 0.187 *** (0.027) Non-IT services intermediate inputs 0.470 *** (0.047) 0.535 *** (0.034) 0.535 *** (0.038) 0.438 *** (0.035) IT outsourcing 0.067 *** (0.021) 0.040 *** (0.021) 0.041 *** 0.005 (0.035) 5

Table F4. Labor Productivity Equation IT Intensity Split: FGLS PSAR1 Non-IT capital 0.035 *** (0.013) 0.122 *** 0.065 *** 0.134 *** IT capital 0.125 *** (0.019) 0.131 *** 0.072 *** 0.054 *** (0.019) Non-IT services intermediate inputs 0.488 *** (0.027) 0.516 *** 0.632 *** 0.502 *** IT outsourcing 0.062 *** 0.009 0.037 *** (0.010) -0.016 (0.020) Table F5. Labor Productivity Equation IT Intensity Split: PCSE AR1 Non-IT capital 0.060 *** 0.156 *** (0.047) 0.065 *** 0.054 * (0.032) IT capital 0.117 *** (0.019) 0.112 ** (0.046) 0.080 *** (0.013) 0.109 *** (0.032) Non-IT services intermediate inputs 0.479 *** (0.041) 0.536 *** (0.026) 0.613 *** (0.033) 0.599 *** IT outsourcing 0.096 *** 0.015 0.058 *** -0.030 Table F6. Labor Productivity Equation IT Intensity Split: PCSE PSAR1 Non-IT capital 0.051 *** (0.019) 0.129 *** (0.041) 0.123 *** (0.030) 0.132 *** (0.040) IT capital 0.173 *** (0.044) 0.123 *** (0.030) 0.107 *** (0.026) 0.083 *** (0.031) Non-IT services intermediate inputs 0.491 *** (0.046) 0.521 *** (0.036) 0.560 *** (0.038) 0.418 *** (0.040) IT outsourcing 0.054 ** (0.024) 0.020 0.033 ** (0.016) 0.042 (0.032) 6

APPENDIX G. RESULTS OF QUANTILE REGRESSION PARAMETER QUANTILE.25.5.75 Non-IT capital.035* (.020).038* (.020).0001 (.036) Labor.182*** (.015).187***.147*** (.049) IT capital.031**.034* (.019).075*** Non-IT services intermediate inputs.697*** (.020).680*** (.043).692*** (.039) IT outsourcing.062** (.010).058*** (.016).060*** N 540 540 540 Pseudo R 2 0.87 0.86 0.84 APPENDIX H. RESULTS OF TIME SPLIT ANALYSIS PARAMETER TIME PERIOD Pre-2002 (1998 2001) Post-2002 (2003 2006) Non-IT capital 0.053 *** (0.009) 0.031 ** IT capital 0.022 *** (0.008) 0.055 *** (0.012) Labor 0.209 *** 0.171 *** (0.021) Intermediate inputs less IT outsourcing 0.694 *** (0.010) 0.657 *** IT outsourcing 0.034 *** (0.009) 0.053 *** (0.012) Notes: Sixty non-farm private industries. Signif: *** = p < 0.01, ** = p < 0.05. Standard errors are in parentheses. Estimates of the labor productivity equation are almost identical, so we do not report them. 7

APPENDIX I. TESTS FOR POTENTIAL ENDOGENEITY OF THE IT Capital AND IT Outsourcing VARIABLES Table I1. Results of Two-Stage Least Squares Estimation of Our Production Function and Durbin-Wu-Hausman Test POTENTIAL ENDOGENOUS VARIABLES TESTED PARAMETER IT Capital IT Outsourcing IT Capital and IT Outsourcing Non-IT capital.040***.039***.040*** Labor.182***.182***.182*** IT capital.052***.052***.051*** Non-IT services intermediate inputs.686*** (.017).685*** (.017).685*** (.017) IT outsourcing.069***.069***.070*** N 420 420 420 Durbin-Wu-Hausman Statistic 1.639 0.510 4.231 Note: We used the one- and two-year lagged values of IT capital and IT outsourcing as instruments. The null hypothesis is that the suspected variables are exogenous. Table I2. Results of Two-Stage GMM Estimation of Our Production Function and the C Statistic Test and Hansen s J Test POTENTIAL ENDOGENOUS VARIABLES TESTED PARAMETER IT Capital IT Outsourcing IT Capital and IT Outsourcing Non-IT capital.038 (.034).029 (.032).025 (.032) Labor.182*** (.029).189***.190*** IT capital.047 (.031).064** (.029).060** Non-IT services intermediate inputs.693*** (.052).658*** (.043).659*** (.043) IT outsourcing.065** (.025).070*** (.025).068*** (.025) N 420 420 420 Hansen s J Statistic 2.182 0.828 3.438 C Statistic 0.390 2.601 3.443 Note: We used the one- and two-year lagged values of IT capital and IT outsourcing as instruments. For both the C test and Hansen s J test, the null hypothesis is that the suspected variables are exogenous. We use the feasible efficient two-step GMM estimator implemented in Stata s ivreg2 procedure (Baum et al. 2003). 8