Internet Appendix for “Innovation Activities and the Incentives for Vertical Acquisitions and Integration” (Not for publication) Laurent Fr´esard, Gerard Hoberg, and Gordon Phillips August 31, 2015 This appendix contains additional material that we mention in the paper, but do not report to preserve space. Section I lists words from the BEA commodity vocabulary that we exclude because they are used in a large number of commodities. Section II lists the phrase exclusions from firms’ 10-Ks that we apply to construct vertical links between firms. Section III provides validation tests for our text-based measure of firm-level vertical integration. Finally, we report in Section IV additional tests that assess the robustness of our main results. I Excluded BEA words Becausetheyareusedinthelargestnumberofcommodities,weexcludethefollowing words from the BEA commodity vocabulary we use to compute vertical relatedness: Accessories, accessory, air, airs, attachment, attachments, commercial, commer- cials, component, components, consumer, consumers, development, developments, equipment, exempt, expense, expenses, ga, gas, industrial, industrials, net, part, parts, processing, product, products, purchased, purchase, receipt, receipts, re- search, researches, sale, sales, service, services, system, systems, unit, units, work, works, tax, taxes, oil, repair, repairs, aids, aid, air, apparatuses, apparatus, applica- 1 tions, application, assemblies, assembly, attachments, attachment, automatic, aux- iliary, bars, bar, bases, base, blocks, block, bodies, body, bulk, business, businesses, byproducts, byproduct, cares, care, centers, center, collections, collection, combi- nations, combination, commercials, commercial, completes, complete, components, component, consumers, consumer, consumption, contracts, contract, controls, con- trol, covers, cover, customs, custom, customers, customer, cuts, cut, developments, development, directly, distributions, distribution, domestic, dries, dry, equipments, equipment, establishments, establishment, exempt, expenses, expense, facilities, fa- cility, fees, fee, fields, field, finished, finish, finishings, finishing, gas, generals, gen- eral, greater, hands, hand, handling, high, hot, individuals, individual, industrials, industrial, industries, industry, installations, installation, lights, light, lines, line, maintenances, maintenance, managements, management, manmade, manufactured, manufacture, materials, material, naturals, natural, nets, net, offices, office, only, open, operated, operate, organizations, organization, others, other, pads, pad, paid, pay, parts, part, permanent, portable, powers, power, processing, products, product, productions, production, public, purchased, purchase, purposes, purpose, receipts, receipt, reclassified, reclassify, repairs, repair, researches, research, sales, sale, self, services, service, sets, set, shares, share, shipped, similar, singles, single, sizes, size, small, soft, specials, special, stocks, stock, storages, storage, supplies, supply, sup- ports, support, surfaces, surface, systems, system, taxes, tax, taxable, technical, this, trades, trade, transfers, transfer, types, type, units, unit, used, without, work, works. II 10-K Phrase Exclusions Because we use 10-K text only to identify a firm’s own-product market location (vertically related vocabulary is identified using BEA data), we exclude any part of a sentence that follows any of the following 81 phrases: Buy, buys, sells its, are sold, buying, products for, for sale, for their, used in, used by, used as, used for, used with, used primarily, used mainly, used commonly, 2 primarily used, mainly used, commonly used, for use, uses, utilized, serve, serving, serves, sold to, sold primarily, sold mainly, sold commonly, designed for, supply of, supply for, supplier to, supplied to, service to, purchase, purchaser, purchasers, cus- tomer, customers, user, users, for application, equipment for, equipment to, equip- ment by, product for, product to, product by, solution for, solution to, solution by, component for, component to, component by, application for, application to, application by, system for, system to, system by, equipments for, equipment for, equipment to, equipments to, equipments by, products for, products to, products by, solutions for, solutions to, solutions by, components for, components to, compo- nents by, applications for, applications to, applications by, systems for, systems to, systems by. III Validation of Text-Based Vertical Integration We perform two analyses to provide additional external validation for the text- based measure of vertical integration VI we introduce and use in the paper. First, we compare our measure to a direct but binary measure of vertical integration based on whether firms explicitly mention that they are vertically integrated in their 10- Ks. Second, we compare our measure of vertical integration to (industry) measures of related-party trade (RPT). A Detecting Explicit Integration We identify whether a firm explicitly indicates that it is vertically integrated by searching for the terms ‘vertical integration’ and ‘vertically integrated’ in each firm’s 10-K.Weexcludecaseswhereafirmindicatesitisnotintegratedorlacksintegration. We then create a dummy variable VI that is equal to one when a firm explicitly search states that it is vertically integrated in a given year, and zero otherwise. Because this measure is based on direct statements by firms and does not rely on firms’ product description or the input-output economic flows, it enables us to gauge the ability of our text-based measure to identify firms that mention being integrated, 3 and to compare it with the existing measure based on Compustat segments, that we label VI in the text. segment Table IA.III.1 presents results from probit regressions estimating the probabil- ity that a firm explicitly indicates that it is vertically integrated (VI = 1) as search a function of VI and VI . To provide more meaningful economic compar- segment isons, we standardize both independent variables so that they have unit standard deviation. The first column indicates that our text-based measure of vertical inte- gration has a much higher propensity to detect explicitly stated vertical integration compared to the Compustat segment-based measure. The estimated coefficient on VI is roughly four times larger than that on VI (0.213 versus 0.061). The segment statistical significance is also much larger on VI. The superior performance of VI continues to hold when we include VI and VI separately (columns (2) and segment (3)). In these columns, we also observe that the explanatory power of VI (measured by pseudo R2) is much larger than that of VI . Columns (4) to (6) reveal that segment the differences are robust to the inclusion of year and industry fixed effects. B Related-Party Trade As an alternative way of to provide external validation, we relate our text-based measure of vertical integration to industry measures of related-party trade (RPT) provided by the U.S. Census Bureau.1. The data measure the intensity of trade (both imports or exports) that occurs between related parties, where “related party trade” is defined as trade with an entity located outside the United States in which the importer (exporter) holds at least a 6% (10%) equity interest (as defined by the Census). The data thus captures the intensity of international transactions that occur within firms’ boundaries. Arguably, related party trade could capture both horizontalandverticalflowsofgoods. Yet,totheextentthatourtext-basedmeasure of vertical integration builds on vertical relations between products described in firms’ 10Ks, any correlation between our measure and RPT should be related to international transactions that are vertical in nature (see Antras (2013), or Antras 1http://sasweb.ssd.census.gov/relatedparty/ 4 and Chor (2013) for instance). The RPT data is available over the 2000-2010 period at the NAICS 6-digit level. We aggregate the data at the NAICS 4-digit and 5-digit levels to map it to our Compustat sample. For each industry, we compute the share of related-party im- ports to total imports to capture the propensity of firms to integrate foreign supplier activities (RPT(import)). Similarly, we compute the share of related-party exports in total exports to capture the propensity of firms to integrate foreign customers (RPT(export)). We also consider the average share between the import and export shares (RPT). We then aggregate VI and VI at the industry-level (NAICS segment 4-digit and 5-digit levels) using equally-weighted averages. Table IA.III.2 presents the results of OLS regressions of industry-level VI (or VI ) on the three measures of related-party trade. Across all specifications, we segment observe a positive correlation between our text-based measure vertical integration and measures of RPT. Focusing on the average level of RPT in the first column, the correlation with VI is 0.580 at the NAICS 4-digit industry level, and 0.833 at the NAICS 5-digit industry level. Both coefficients are statistically significant at the 5% confidence level (t-statistics of 2.12 and 4.37 respectively). At both aggregation levels, our measure of vertical integration is also more strongly related to related- party import transactions compared to related-party export transactions (columns (2) and (3)). The coefficients on related-party import are 0.644 and 0.702, compared to 0.077 and 0.519 for related-party export. Moreover, columns (5) to (6) indicate thatrelated-partytradeisonlyweaklyrelatedtoverticalintegrationwhenmeasured using Compustat segments as an alternative. IV Additional Results This section contains additional tables that are mentioned and described in the paper but were not reported there to preserve space. Specifically, this appendix includes: 5 • Table IA.IV.1: Probit and OLS regressions whose dependent variables are the probability of being a target in a vertical or non-vertical transaction or vertical integration. We focus on own-firm independent variables instead of industry variables. • Table IA.IV.2: Probit and OLS regressions whose dependent variables are theprobabilityofbeingatargetinaverticalornon-verticaltransactionorver- tical integration. We focus on (one-year) lagged independent variables instead of contemporaneous variables. • Table IA.IV.3: Probit and OLS regressions whose dependent variables are the probability of being a target in a vertical or non-vertical transaction or vertical integration. We focus on sales-weighted industry average variables instead of equally-weighted average variables. • Table IA.IV.4: Probit and OLS regressions whose dependent variables are theprobabilityofbeingatargetinaverticalornon-verticaltransactionorver- tical integration. We only consider industry R&D/Sale and #Patents/assets asindependentvariables, andnotthebaselinefullsetofindependentvariables. • Table IA.IV.5: Probit and OLS regressions whose dependent variables are the probability of being a target in a vertical or non-vertical transaction or vertical integration. We include industry R&D/Sale and #Patents/assets in- dividually and not together. • Table IA.IV.6: Probit and OLS regressions whose dependent variables are the probability of being a target in a vertical or non-vertical transaction or vertical integration. Vertical and non-vertical targets are identified using the NAICS-10% vertical network instead of our text-based 10% vertical net- work. The measure of vertical integration is based in Compustat segments (VI(Segment)) instead of our text-based measure. • Table IA.IV.7: Probit regressions whose dependent variables are the proba- bility of being an acquirer in a vertical or non-vertical transaction. 6 • Table IA.IV.8: OLS regressions of firm-year R&D/sales on the user cost of R&D capital. We use the estimation presented in column (3) to predict R&D for each firm-year, and use these predicted values to construct our instrument. • Table IA.IV.9: Linear Probability Model (LPM) regressions whose depen- dent variables are the probability of being a target in a vertical or non-vertical transaction or vertical integration. • Table IA.IV.10: Difference in average R&D/sales before and after vertical transactions for targets that continue to exist post-transactions, and for com- bined entities that aggregate R&D and sales across acquirers and targets for each vertical deal. • Table IA.IV.11: List of the 30 most vertically integrated firms in 2008 based on our text-based measure of vertical integration (VI). • Table IA.IV.12: OLS regressions whose dependent variable is the logarithm of vertical integration instead of its level. 7 Table IA.III.1: VI Detection Dep. Variable: Prob(VI =1) search (1) (2) (3) (4) (5) (6) VI 0.213a 0.224a 0.123a 0.130a (0.007) (0.007) (0.010) (0.010) VIsegment 0.061a 0.096a 0.052a 0.062a (0.007) (0.006) (0.008) (0.008) YearFE No No No Yes Yes Yes IndustryFE No No No Yes Yes Yes #.Obs. 45,198 45,198 45,198 45,198 45,198 45,198 PseudoR2 0.037 0.034 0.007 0.127 0.125 0.122 Note: ThistablereportsProbitestimationswherethedependentvariableisVI ,adummythatequalsoneif search afirmmentionsbeingverticallyintegratedinitsannual10-Kreport,andzerootherwise. Theindependent variablesarestandardizedforconvenience. Standarderrorsareclusteredbyindustryandyearandarereportedin parentheses. Symbolsa,b,andc indicatestatisticalsignificanceatthe1%,5%,and10%confidencelevels. 8 Table IA.III.2: VI and Related-Party Trade Dep. Variable: VI VIsegment (1) (2) (3) (4) (5) (6) Panel A: NAICS 4-digit industries RPT 0.580b 0.361 (0.272) (0.273) RPT(import) 0.644a 0.706a (0.208) (0.208) RPT(export) 0.077 -0.554c (0.295) (0.294) Obs. 636 636 636 636 636 636 PseudoR2 0.005 0.013 0.001 0.001 0.016 0.004 Panel B: NAICS 5-digit industries RPT 0.833a -0.510a (0.190) (0.191) RPT(import) 0.702a -0.122 (0.146) (0.147) RPT(export) 0.519a -0.876a (0.198) (0.197) #.Obs. 1,122 1,122 1,122 1,122 1,122 1,122 PseudoR2 0.015 0.019 0.005 0.005 0.001 0.016 Note: Columns(1)to(3)reportOLSestimationswherethedependentvariableisournewtext-basedmeasureof verticalintegrationVI. Columns(4)to(6)reportOLSestimationswherethedependentvariableisameasureof verticalintegrationbasedonCompustatsegmentsVIsegment. InPanelA,allvariablesareaggregatedatthe NAICS4-digitindustrylevel(averages). InPanelB,allvariablesareaggregatedattheNAICS5-digitindustry level(averages). Theindependentvariablesarestandardizedforconvenience. Standarderrorsareclusteredby industryandyearandarereportedinparentheses. Symbolsa,b,andc indicatestatisticalsignificanceatthe1%, 5%,and10%confidencelevels. 9 Table IA.IV.1: Vertical Acquisitions and Integration: Own-Firm Variables Dep. Variables: Prob(Target) (Probit) VI (OLS) Vert. Non-Vert. Vert. Non-Vert. Baseline Interaction (1) (2) (3) (4) (5) (6) (7) (8) R&D/sales 0.017 0.091a 0.035 0.113a -0.027a -0.004 -0.025a -0.007 (0.019) (0.013) (0.021) (0.013) (0.005) (0.004) (0.005) (0.004) #Patents/assets 0.101a -0.027b 0.118a 0.021 0.017a 0.006 0.020a 0.003 (0.013) (0.013) (0.015) (0.017) (0.004) (0.004) (0.006) (0.005) R&D/sales×#Patents/assets -0.013 -0.028a -0.002 0.003 (0.009) (0.007) (0.002) (0.002) PPE/assets -0.028c -0.077a -0.025c -0.072a 0.030a 0.037a 0.031a 0.037a (0.015) (0.018) (0.015) (0.018) (0.010) (0.009) (0.010) (0.009) HHI -0.028b -0.078a -0.028c -0.077a -0.105a -0.056a -0.105a -0.056a (0.015) (0.014) (0.015) (0.014) (0.006) (0.005) (0.006) (0.005) EndUser -0.166a 0.095a -0.165a 0.098a -0.241a -0.142a -0.241a -0.142a 1 (0.015) (0.012) (0.015) (0.012) (0.008) (0.007) (0.008) (0.007) 0 #Segment(NAICS) 0.088a -0.011 0.089a -0.022 0.132a 0.041a 0.132a 0.041a (0.010) (0.011) (0.010) (0.011) (0.006) (0.006) (0.006) (0.006) log(Assets) 0.285a 0.195a 0.285a 0.196a 0.049a 0.127a 0.049a 0.127a (0.016) (0.013) (0.016) (0.013) (0.005) (0.011) (0.005) (0.011) log(Age) 0.086a -0.025b 0.085a -0.026b 0.024a 0.012 0.024a 0.012 (0.015) (0.011) (0.015) (0.011) (0.005) (0.010) (0.005) (0.010) MB -0.145a -0.012 -0.146a -0.014 -0.019a 0.005b -0.019a 0.005b (0.021) (0.012) (0.021) (0.012) (0.003) (0.003) (0.003) (0.003) IndustryFixedEffects No No No No Yes No No Yes FirmFixedEffects No No No No No Yes No Yes #obs. 45,198 45,198 45,198 45,198 45,198 45,198 45,198 45,198 PseudoR2 /Adj. R2 0.113 0.037 0.114 0.038 0.525 0.855 0.525 0.855 Note: Columns(1)to(4)reportprobitestimationswherethedependentvariableisadummyindicatingwhetherthegivenfirmisatargetinaverticalornon-verticaltransaction inagivenyear. VerticaltransactionsareidentifiedusingtheVerticalText-10%network. Columns(5)to(8)reportOLSestimationwherethedependentvariableisvertical integrationVI. Allestimationsincludeyearfixedeffects. AllvariablesaredefinedinAppendix2ofthepaper. Theindependentvariablesarestandardizedforconvenience. Standarderrorsareclusteredbyindustryandyearandarereportedinparentheses. Symbolsa,b,andc indicatestatisticalsignificanceatthe1%,5%,and10%confidencelevels.