Online Appendix: Import Competition and Firm Refocusing

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1 Online Appendix: Import Competition and Firm Refocusing Runjuan Liu March 2009 Appendix A: Prevalence and Characteristics of Multi-product Firms Table A.1 summarizes the prevalence of multi-product firms. On average, multi-product firms produce 2.8 four-digit SIC products and 2.6 sector goods. The numbers are fairly close to an average of 3.1 industries and 2.5 sectors in which manufacturing firms are present (Bernard, Redding, and Schott, 2009). Although multi-product firms only represent 23% of all firms, they account for 57% of sales, 59% of assets, 53% of operating profits, 53% of employment, 51% of properties, plants, and equipments, 68% of intangibles (i.e., blue prints, copyrights, and trademarks), and 57% of R&D expenditure of all firms in the Compustat Segments data. Bernard, Redding, and Schott (2009) also document this economic dominance of multi-product firms. Table A.2 compares the mean differences between the characteristics of single-product and multiproduct firms and that of single-sector and multi-sector firms. Multi-product firms are significantly larger than single-product firms in terms of sales, assets, profits, and employment. On average, multi-product firms also hold more tangible assets (properties, plants, and equipments) and intangible assets (blue prints, copyrights, and trademarks) as well as invest more in R&D. These findings are consistent with those in Bernard, Redding, and Schott (2009), who find that multi-product firms exhibit higher output and employment than single-product firms. Based on the data availability, I also calculate three measures of firm performance: return on asset, profit margin, and sales per employee. 1 Table A.2 shows that these three measures are smaller for multi-product firms than for single-product firms. Particularly, multiproduct firms have a significantly lower return on asset and sales per employee than single-product firms, indicating the diversification discount documented in the finance literature (e.g., Lang and Stulz, 1994). 2 In Table A.3, I show that on average larger firms produce more products and that firms producing more products have larger sales per product. First, I decompose the firms total sales in Table A.3a by regressing log number of products on log firm sales. The coefficients are significantly positive across all specifications. Specifically, the extensive margin contributes to about 5% variation in firm sales. Second, I regress log average firm sales on log number of products in Table A.3b and show that the positive correlation between firms intensive and extensive margins holds for all specifications (especially among multi-product firms). Overall, Table A.3 indicates the same features of multi-product firms as those documented in Bernard, Redding, and Schott (2009). Appendix B: Pervasiveness and Importance of Product Mix Changes Product mix changes have been pervasive in the U.S. manufacturing sector (Bernard, Redding, and Schott, 2009). In Table B.1, I show that product switching is pervasive among U.S. public firms that produce multiple products as well. 73% of multi-product firms alter their product mix during each of the five-year periods, among which 31% drop products only, 7% add products only, and 35% both add and drop products. Table B.1 also reports the percentage of firms that switch sectors. As expected, fewer firms (61%) switch sectors (two-digit SIC categories) than switch industries (four-digit SIC categories). Given the various marketing, procurement, and production procedures that exist in different industries and 1 I define return on asset as the operating profit divided by total assets. I then define profit margin as the operating profit divided by sales. The variable sales per employee is sales divided by employment. 2 Bernard, Redding, and Schott (2009) find that multi-product firms exhibit higher productivity than single-product firms. Due to data availability, I am unable to calculate a comparable productivity measure for firms in my sample. 1

2 sectors, product mix changes could involve considerable changes in the nature and scope of multi-product firms. Product mix changes are also important to the changes in sales of continuing firms, as reported in Bernard, Redding, and Schott (2009). I decompose the total sales of the continuing firm into the share of continuing products and dropped products as well as decompose the total sales of the firm into the share of continuing products and added products. I report the results in Table B.2. On average, dropped products account for 22% and 18% of firm sales in 1984 and 1991, respectively, and added products account for 19% and 17% of firm sales in 1989 and 1996, respectively. These shares represent non-trivial product mix changes at the firm level. Appendix C: Trade and Shipment Data Annual import data comes from two sources. Data before 1989 come from the NBER Trade Database (Feenstra, 1996). I convert these data from SIC 1982 to SIC 1987 using the Bartelsman and Gray (1996) concordance (with weights) available from the NBER-CES Manufacturing Industry Database. Data after 1989 are from the U.S. Department of Commerce official data as described in Feenstra, Schott, and Romalis (2002). Tariff and freight data also come from two sources. For the period before 1989, tariff data are provided by Magee and available in the UC Davis Center for International Data, 3 while I calculate freight data as CIF value of imports minus the custom value of imports based on the NBER Trade Database (Feenstra, 1996). I convert them from SIC 1972 to SIC 1987 using the same concordance from Bartelsman and Gray (1996). For the period after 1989, the data are from Feenstra, Schott, and Romalis (2002). Industry shipment data is from the NBER Productivity Dataset (Bartelsman and Gray, 1996). Appendix D: Summary Statistics Table D presents the summary statistics of the baseline sample. Appendix E: Regression Results without Other Controls Table E.1-E.3 present the baseline regression results without other product, firm and industry controls. Appendix F: Robustness and Extensions Table F.1-F.6 present the robustness and extension results. References Bartelsman, Eric J., and Wayne B. Gray The NBER Manufacturing Productivity Database. NBER Technical Working Paper No Bernard, Andrew B., Stephen Redding, and Peter K. Schott Multi-product Firms and Product Switching. Forthcoming American Economic Review. Feenstra, Robert C U.S. Imports, : Data and Concordances. NBER Working Paper No Feenstra, Robert C., John Romalis, and Peter K. Schott U.S. Imports, Exports and Tariff Data, NBER Working Paper No Lang, Larry H. P., and Rene M. Stulz Tobin s q, Corporate Diversification, and Firm Performance. Journal of Political Economy. 102(6):

3 Table A.1: Prevalence of Multi-Product and Multi-Sector Firms Single-Product Firms Multi-Product Firms Multi-Sector Firms Number of products/sectors Percent of firms Percent of sales Percent of assets Percent of profits Percent of employment Percent of properties, plants and equipments Percent of intangibles Percent of R&D expenditure Notes: Calculation is based on 92,274 year-firm observations of all firms in the Compustat Segments data during

4 Table A.2: Mean Differences Between the Characteristics of Single-Product and Multi-Product Firms Single-Product Firms Multi-Product Firms Comparison Mean Std. Err. Mean Std. Err. Difference t-stat Sales (million$) Assets (million$) Profits (million$) Employment (actual) Properties, plants and equipments (million$) Intangibles (million$) R&D expenditure (million$) Return on asset Profit margin Sales per employee Single-Sector Firms Multi-Sector Firms Comparison Mean Std. Err. Mean Std. Err. Difference t-stat Sales (million$) Assets (million$) Profits (million$) Employment (actual) Properties, plants and equipments (million$) Intangibles (million$) R&D expenditure (million$) Return on asset Profit margin Sales per employee Notes: Calculation is based on 92,274 year-firm observations of all firms in the Compustat Segments data during

5 Table A.3a: Intensive and Extensive Decomposition of Firm Sales Sample All Firms MP Firms All Firms 1996 MP Firms 1996 (1) (2) (3) (4) Log firm sales (86.19) (43.94) (18.21) (7.84) industry fixed effects Yes Yes Yes Yes year fixed effects Yes Yes No No R N 89,939 21,503 8,388 1,469 Notes: Dependent variable is the log number of products. OLS coefficients are reported with t- statistics in parentheses. Table A.3b: Correlation between Intensive and Extensive Product Margins Sample All Firms MP Firms All Firms 1996 MP Firms 1996 (1) (2) (3) (4) Log number of products (26.06) (19.69) (3.61) (3.24) industry fixed effects Yes Yes Yes Yes year fixed effects Yes Yes No No R N 89,939 21,503 8,388 1,469 Notes: Dependent variable is the log average sales of the firm. OLS coefficients are reported with t-statistics in parentheses.

6 Table B.1: Industry and Sector Switching by U.S. Public Firms that produce Multiple Products Frequency Switching Industries Percent of Firms Percent of Firms (Sales Weighted) Frequency Switching Sectors Percent of Firms Percent of Firms (Sales Weighted) None , Drop products only Add products only Both add and drop products Total 2, , Notes: Calculation is based on a pooled sample of 2,648 surviving firms producing more than one product at the beginning of the periods or Switching industries and sectors are defined as adding and/or dropping of four-digit SIC categories and two-digit SIC categories respectively. Firms are divided into four muturally exclusive groups: firms with none switching activities, firms only dropping products, firms only adding products and firms both adding and dropping products.

7 Table B.2: Decomposition of Multi-Product Firm Sales Period a Average Share of Continuing Products of Firm Sales in the beginning of the periods Average Share of Dropped Products of Firm Sales in the beginning of the periods Period b Average Share of Continuing Products of Firm Sales in the end of the periods Average Share of Added Products of Firm Sales in the end of the periods Notes: a. Calculation is based on a pooled sample of 2,648 surviving firms producing more than one product at the beginning of the periods or b. Calculation is based on a pooled sample of 2,535 surviving firms producing more than one product at the end of the periods or

8 Table D: Summary Statistics Variables Obs Mean Std. Dev. Min Max Product exit %ΔImports Scaled %Δimports ΔTrade costs Core indicator Sales rank Supply relatedness Demand relatedness Production relatedness Sector relatedness Product initial sales Product initial profitability Firm growth Firm profitability change Industry growth

9 Table E.1: Regression Results: Import Competition and Product Dropping Industry Imports %ΔImports ** -1.01** 0.48** 0.78** 0.40* 0.42* (-0.52) (2.68) (-5.07) (2.72) (3.23) (2.38) (2.38) Core indicator -1.24** (-7.00) Sales rank 0.48** (4.44) Supply relatedness -0.10** (-5.44) Demand relatedness -1.32** (-4.93) Production relatedness -1.10** (-5.86) Sector relatedness -0.85** (-4.98) N Log likelihood Joint significance test a Core product -0.82** -0.54** -0.42** -0.54** -0.70** -0.43** (-5.59) (-4.13) (-3.77) (-3.88) (-4.16) (-3.28) Peripheral product 0.43** 3.30** 0.48** 0.78** 0.40* 0.42* (2.68) (4.04) (2.72) (3.23) (2.38) (2.38) Notes: Dependent variable is an indicator for product dropping. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include four-digit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

10 Table E.2: Regression Results: Import Competition and Product Composition Industry Imports %ΔImports * 0.30** -0.16* -0.24** -0.13* -0.13* (0.55) (-2.27) (3.68) (-2.34) (-2.79) (-1.97) (-1.99) Core indicator 0.38** (6.10) Sales rank -0.14** (-3.42) Supply relatedness 0.32** (4.62) Demand relatedness 0.42** (4.34) Production relatedness 0.35** (5.20) Sector relatedness 0.27** (4.13) N R Joint significance test a Core product 0.24** 0.16** 0.17** 0.17** 0.23** 0.14** (4.49) (2.99) (3.11) (3.17) (3.58) (2.69) Peripheral product -0.13* -0.99** -0.16* -0.24** -0.17* -0.13* (-2.27) (-3.15) (-2.34) (-2.79) (-1.97) (-1.99) Notes: Dependent variable is the change of sales share in total production. OLS coefficient is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include four-digit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

11 Table E.3: Regression Results: Using Change of Trade Costs as A Measure of Import Competition Industry Trade Costs ΔTrade costs ** -9.43* * (0.42) (-1.79) (2.93) (-1.97) (-2.39) (-1.68) (-1.52) Core indicator 22.91** (4.00) Sales rank -6.66** (-2.88) Supply relatedness 18.60** (3.31) Demand relatedness 26.63** (3.64) Production relatedness 21.09** (3.78) Sector relatedness 13.37** (2.96) N Log likelihood Joint significance test a Core product 15.28** 7.82* 9.17* 12.05** 13.95** 6.79 (3.24) (2.22) (2.15) (2.93) (3.13) (1.71) Peripheral product ** -9.43* ** (-1.79) (-2.61) (-1.97) (-2.39) (-1.68) (-1.52) Notes: Dependent variable is an indicator for product exit. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include four-digit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

12 Table F.1: Robustness Results: Including Firms Who Exit During Each Five-year Period Industry Imports %Δimports * -0.66** 0.34* 0.53** (-0.53) (2.09) (-3.55) (2.11) (2.69) (1.78) (1.81) Core indicator -0.88** (-6.01) Sales rank 0.31** (3.53) Supply relatedness -0.72** (-4.28) Demand relatedness -0.94** (-4.54) Production relatedness -0.79** (-5.37) Sector relatedness -0.62** (-4.07) N Log likelihood Joint significance test a Core product -0.58** -0.35** -0.38** -0.40** -0.52** -0.33** (-4.34) (-2.68) (-2.86) (-3.22) (-3.77) (-2.59) Peripheral product 0.30* 2.09** 0.34* 0.53** (2.09) (3.23) (2.11) (2.69) (1.78) (1.81) Notes: Dependent variable is an indicator of product exit. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include fourdigit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

13 Table F.2: Robustness Results: Defining Core Product as the Product with Largest Relative Sales Industry Imports %Δimports * -1.00** 0.35* 0.55** 0.30* 0.31* (-0.11) (2.25) (-4.86) (2.21) (3.07) (2.12) (2.27) Core indicator -0.87** (-5.33) Sales rank 0.49** (4.45) Supply relatedness -0.93** (-4.53) Demand relatedness -0.94** (-4.34) Production relatedness -0.81** (-4.91) Sector relatedness -0.61** (-4.26) N Log likelihood Joint significance test a Core product -0.56** -0.51** -0.49** -0.39* -0.51** -0.30* (-3.48) (-3.85) (-3.24) (-2.54) (-3.17) (-2.06) Peripheral product 0.32* 3.39** 0.35* 0.55** 0.30* 0.31* (2.25) (4.10) (2.21) (3.07) (2.12) (2.27) Notes: Dependent variable is an indicator of product exit. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include fourdigit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

14 Table F.3: Robustness Results: Scaling Change of Imports by Industry Shipment Industry Imports Δimports/Shipment ** -6.03** 1.90* 4.25** 2.08** 2.23** (-0.04) (2.88) (-4.73) (2.46) (3.17) (2.83) (2.83) Core indicator -5.31** (-3.91) Sales rank 3.06** (5.21) Supply relatedness -4.22** (-3.38) Demand relatedness -6.55** (-3.27) Production relatedness -5.12** (-3.93) Sector relatedness -4.06** (-3.39) N Log likelihood Joint significance test a Core product -3.17** -2.98** -2.32* -2.29* -3.03** -1.82* (-2.94) (-3.51) (-2.41) (-2.28) (-2.91) (-2.09) Peripheral product 2.14** 21.47** 1.90* 4.25** 2.08** 2.23** (2.88) (5.03) (2.46) (3.17) (2.83) (2.83) Notes: Dependent variable is an indicator of product exit. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include fourdigit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

15 Table F.4: Robustness Results: Using One-Year Panel Industry Imports %Δimports * -0.08** 0.05** 0.06** 0.03* 0.04* (-0.43) (2.19) (-4.36) (3.07) (3.20) (2.17) (2.35) Core indicator -0.10** (-4.97) Sales rank 0.04** (3.65) Supply relatedness -0.11** (-5.62) Demand relatedness -0.12** (-4.64) Production relatedness -0.16** (-7.90) Sector relatedness -0.08** (-4.31) N 18,966 18,966 18,966 18,966 18,966 18,966 18,966 Log likelihood Joint significance test a Core product -0.07** -0.05** -0.06** -0.05** -0.13** -0.04** (-5.61) (-4.36) (-5.53) (-4.86) (-10.02) (-4.24) Peripheral product 0.03* 0.26** 0.05* 0.06* 0.03* 0.04* (2.19) (3.37) (3.07) (3.20) (2.17) (2.35) Notes: Dependent variable is an indicator of product exit. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include fourdigit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

16 Table F.5: Robustness Results: Including Service Firms Industry Imports %Δimports ** -0.97** 0.51** 0.84** 0.45** 0.46** (0.13) (3.11) (-4.91) (3.19) (3.61) (3.03) (2.87) Core indicator -1.20** (-6.45) Sales rank 0.48** (4.50) Supply relatedness -0.94** (-5.11) Demand relatedness -1.33** (-4.95) Production relatedness -1.09** (-5.67) Sector relatedness -0.82** (-4.90) N Log likelihood Joint significance test a Core product -0.74** -0.49** -0.43** -0.49** -0.63** -0.36** (-5.36) (-4.04) (-3.49) (-3.88) (-4.13) (-3.07) Peripheral product 0.46** 3.34** 0.51** 0.84** 0.45** 0.46** (3.11) (4.19) (3.19) (3.61) (3.03) (2.87) Notes: Dependent variable is an indicator of product exit. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include fourdigit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.

17 Table F.6: Extension Results: Core Import Competition and Firm Refocusing Core Imports %ΔImports ** -1.15** 0.64** 1.15** 0.53** 0.51** (0.16) (3.49) (-6.79) (3.76) (4.94) (3.54) (3.14) Core indicator -1.29** (-8.16) Sales rank 0.60** (7.22) Supply relatedness -1.12** (-6.47) Demand relatedness -1.64** (-6.27) Production relatedness -1.19** (-7.25) Sector relatedness -0.75** (-4.24) N Log likelihood Joint significance test a Core product -0.75** -0.54** -0.49** -0.48** -0.66** (-4.87) (-4.42) (-3.78) (-3.73) (-4.45) (-1.74) Peripheral product 0.54** 4.26** 0.64** 1.15** 0.53** 0.51** (3.49) (6.68) (3.76) (4.94) (3.54) (3.14) Notes: Dependent variable is an indicator for product exit. Marginal probability of probit regression is reported with robust t-statistics adjusted for clustering at the four-digit SIC level in parentheses. All the regressions also include fourdigit SIC industry and time fixed effects. a. Wald χ 2 test statistic for the joint significance of trade variables is reported. b. Point estimation of the effects of import competition are reported for the core product and the peripheral product. ** and * indicate statistical significance at 1% and 5% respectively.